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  • machine learning  (126)
  • MDPI - Multidisciplinary Digital Publishing Institute  (126)
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  • 2020-2024  (126)
  • 1935-1939
  • 2021  (126)
  • 1
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; swarm-robotics ; drag-based system ; PID algorithm ; human–robot interaction ; behaviour dynamics ; state constraints ; fair optimisation ; micro mobile robot ; robot ; actuators ; high-gain observer ; turning model LIP ; space robot ; manipulation action sequences ; subgoal graphs ; remotely operated vehicle ; constrained motion ; joint limit avoidance ; curvilinear obstacle ; rehabilitation system ; stability criterion ; system design ; quad-tilt rotor ; iterative learning ; spiral curve ; cable detection ; SEA ; douglas–peuker polygonal approximation ; predictable trajectory planning ; ATEX ; obstacle avoidance system ; kinematic singularity ; collision avoidance ; biologically-inspired ; jumping robot ; differential wheeled robot ; design and modeling ; control efficacy ; robotics ; extremum-seeking ; object-oriented ; non-holonomic mobile robot ; magneto-rheological fluids ; rendezvous consensus ; altitude controller ; master-slave ; switching control ; deep reinforcement learning ; mechanism ; expansion logic strategy ; negative buoyancy ; action generation ; radial basis function neural networks ; unmanned aerial vehicles ; extend procedure ; glass façade cleaning robot ; convolutional neural network ; climbing robot ; micro air vehicle ; car-like kinematics ; variable speed ; machine learning ; dynamical model ; transportation ; geodesic ; unmanned surface vessel ; medical devices ; stopper ; extended state observer (ESO) ; high efficiency ; object mapping ; multi-objective optimization ; hybrid robot ; robot learning ; auto-tuning ; cable disturbance modeling ; manipulation planning ; pesticide application ; high-speed target ; sparse pose adjustment (SPA) ; service robot ; lumped parameter method ; Geometric Algebra ; dynamic coupling analysis ; Thau observer ; tri-tilt-rotor ; industrial robotic manipulator ; hardware-in-the-loop simulation ; robotic drilling ; muscle activities ; small size ; chameleon ; continuous hopping ; wall climbing robot ; hover mode ; 3D-SLAM ; curvature constraints ; PSO ; drilling end-effector ; Rodrigues parameters ; gait adaptation ; static environments ; position/force cooperative control ; snake-like robot ; shape-fitting ; powered exoskeleton ; input saturation ; kinematic identification ; methane ; human–machine interactive navigation ; q-learning ; path following ; hopping robot ; mobile manipulation ; high step-up ratio ; actuatorless ; monocular vision ; stability analysis ; compact driving unit ; snake robot ; non-holonomic robot ; curvature constraint ; phase-shifting ; dialytic elimination ; gesture recognition ; snake robots ; series elastic actuator ; flapping ; servo valve ; motion camouflage control ; biomimetic robot ; minimally invasive surgery robot ; centralized architecture ; trajectory planning ; computing time ; adaptive control law ; kinematics ; facial and gender recognition ; single actuator ; victim-detection ; shape memory alloys ; undiscovered sensor values ; discomfort ; Differential Evolution ; numerical evaluation ; quadruped robot ; coverage path planning ; localization ; MPC ; n/a ; fault diagnosis ; neural networks ; disturbance-rejection control ; sample gathering problem ; cart ; bio-inspired robot ; opposite angle-based exact cell decomposition ; optimization ; safety ; goal exchange ; hierarchical planning ; ocean current ; robot motion ; nonlinear differentiator ; mapping ; finite-time currents observer ; Newton iteration ; inverse kinematics ; deposition uniformity ; spatial pyramid pooling ; hierarchical path planning ; end effector ; head-raising ; fault recovery ; LOS ; path tracking ; non-inertial reference frame ; step climbing ; obstacle avoidance ; sliding mode control ; symmetrical adaptive variable impedance ; lane change ; quadcopter UAV ; singularity analysis ; biped mechanism ; fault-tolerant control ; dynamic neural networks ; mobile robots ; data association ; UAV ; enemy avoidance ; reinforcement learning ; grip optimization ; safety recovery mechanism ; exoskeleton ; dynamic environment ; uncertain environments ; hybrid bionic robot ; potential field ; robot navigation ; cleaning robot ; unmanned aerial vehicle ; non-singular fast-terminal sliding-mode control ; contact planning ; Lyapunov-like function ; piezoelectric actuator ; transition mode ; non-prehensile manipulation ; multiple mobile robots ; Tetris-inspired ; real-time action recognition ; integral line-of-sight ; topological map ; alpine ski ; target tracking ; closed-loop detection ; working efficiency ; mathematical modeling ; curve fitting ; force control ; biped robots ; NSGA-II ; mobile robot ; load carriage ; prescription map translation ; artificial fish swarm algorithm ; Q-networks ; self-reconfigurable robot ; G3-continuity ; autonomous vehicle ; loop closure detection ; excellent driver model ; robots ; graph representation ; regional growth ; target assignment ; evolutionary operators ; intelligent mobile robot ; motion sensor ; exploration ; droplets penetrability ; dynamic uncertainty ; simultaneous localization and mapping (SLAM) ; area decomposition ; multi-criteria decision making ; 4WS4WD vehicle ; biped climbing robots ; skiing robot ; ROS ; decision making ; smart materials ; centrifugal force ; missile control system ; formation of robots ; electro-rheological fluids ; pneumatics ; variable spray ; inertial measurement unit (IMU) ; Robot Operating System ; trajectory interpolation ; formation control ; immersion and invariance ; dragonfly ; parallel navigation ; harmonic potential field ; pallet transportation ; mobile robot navigation ; negative-buoyancy ; grip planning ; manipulator ; position control ; external disturbance ; legged robot ; passive skiing turn ; autonomous underwater vehicle (AUV) ; gait cycle ; path planning ; sliding mode observer ; dynamic gait ; self-learning ; polyomino tiling theory ; coalmine ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.
    Keywords: data envelopment analysis ; Kohonen self-organizing maps ; factor analysis ; multiple regression ; energy efficiency ; social media ; energy-consuming activities ; energy consumption ; machine learning ; ontology ; energy performance certificate ; heating energy demand ; buildings ; data mining ; classification ; regression ; decision tree ; support vector machine ; random forest ; artificial neural network ; open data ; electrification modelling ; Malawi ; OnSSET ; MESSAGEix ; reproducibility ; collaborative work ; open modelling and data ; data-handling ; integrated assessment modelling ; data pre- and post-processing ; space heating ; domestic hot water ; market assessment ; EU28 ; district heating ; data analytics ; big data ; forecasting ; energy ; polygeneration ; clustering ; kNN ; pattern recognition ; heating ; building stock ; heat map ; spatial analysis ; heat density map ; building performance simulation ; parametric modelling ; energy management ; model calibration ; Passive House ; energy planning ; energy potential mapping ; urban energy atlas ; urban energy transition ; energy data ; data-aware planning ; spatial planning ; open data analytics ; smart cities ; open energy governance ; urban database ; energy mapping ; building dataset ; energy modelling ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Robotics and control are both research and application domains that have been frequently engineered through the use of interdisciplinary approaches like cybernetics. Cognition is a particular concept of this approach, abstracted from the context of living organisms to that of artificial devices, and is concerned with knowledge acquisition and understanding through thought, experience, and the senses. Cognitive robotics and control refer to knowledge processing as much as knowledge generation from problem understanding, leading to special forms of architectures that enable systems to behave in an autonomous way. The main aim of this book is to highlight emerging applications and address recent breakthroughs in the domain of cognitive robotics and control and related areas. Procedures, algorithms, architectures, and implementations for reasoning, problem solving, or decision making are considered in the domain of robotics and control.
    Keywords: initial trajectory ; trajectory optimization ; Bézier surface ; robotics ; open FPGAs ; robot control ; surgical robotics ; human–machine interaction ; autonomous guidance ; low-cost platform ; FPGA ; S-curve ; motion control ; SoC ; telemanipulation ; haptics ; machine learning ; gesture recognition ; upper limb rehabilitation robot ; particle swam optimization (PSO) ; artificial bee colony (ABC) ; Ziegler Nichols ; Maximum sensitivity ; ontology ; robot task planning ; knowledge base ; knowledge representation ; industrial collaborative robots ; shared robotic tasks ; physical human–robot interaction ; human intention recognition ; time series classification ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book is a collection of recent publications from researchers all over the globe in the broad area of high-voltage engineering. The presented research papers cover both experimental and simulation studies, with a focus on topics related to insulation monitoring using state-of-the-art sensors and advanced machine learning algorithms. Special attention was given in the Special Issue to partial discharge monitoring as one of the most important techniques in insulation condition assessment. Moreover, this Special Issue contains several articles which focus on different modeling techniques that help researchers to better evaluate the condition of insulation systems. Different power system assets are addressed in this book, including transformers, outdoor insulators, underground cables, and gas-insulated substations.
    Keywords: TA1-2040 ; T1-995 ; artificial neural network ; simulation ; high-frequency ; artificial flashover tests ; wide bandgap power modules ; tracking ; electrical field strength ; fast-rise square wave voltages ; FDTD simulation ; cable joint ; corona discharge ; feature selection ; post insulator ; earthing systems ; wind speed ; surface discharge ; oil/paper insulation ; oil-paper insulation ; high-magnitude currents and impulse polarity ; UFVM ; Tettex 9520 ; electrical tree ; flashover characteristics ; composite insulator ; partial discharge ; numerical modeling ; saline mechanism ; thermal parameters ; space charge density ; seasonal ; ion flow field ; denoising ; DDX 9121b ; temperature ; transformer asset management ; cavity discharge ; space/interface charge ; insulation health index ; heat transfer model ; leakage current ; machine learning ; partial discharges (PD) ; RF signal ; flashover ; high impulse conditions ; grounding electrodes ; generalized finite difference time domain ; curve fitting ; grounding ; plasma discharge ; outdoor insulators ; flashover dynamic model ; wavelet transform ; degradation ; thermal properties ; bipolar charge transport model ; UHF sensor ; cable ; random walk theory ; tracking test setup ; GIL ; pressure ; modelling ; non-uniform pollution between windward and leeward sides ; calibrator ; secondary arc ; polymeric insulation ; optical-UHF integrated detection ; shoreline ; dry band arcing ; photoelectric fusion pattern ; DDX 8003 ; XLPE ; silicone gel ; partial discharge modeling ; electric field analysis ; NSCT ; electrode’s geometry ; gas ; Comsol Multiphysics ; fast-impulses ; laying modes ; ageing ; cable ampacity ; residual resistance formulation ; finite element analysis ; thermal effect ; hydrophobicity ; soil resistivity ; charge simulation method ; short-circuit discharge ; dry band formation ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-21
    Description: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe chronic health condition that is often misunderstood or ignored by health establishments. The lack of definitive diagnostic markers to separate ME/CFS patients from the healthy population as well as from other chronic disorders is problematic for both health professionals and researchers. A consortium of Australian researchers gathered to systematically understand ME/CFS, ranging from a deep analysis of clinical and pathology data to metabolomic profiles and the investigation of mitochondrial function. From this broad collaboration, a number of compelling insights have arisen that may form the basis of specific serum, blood, and/or urinary biomarkers of ME/CFS. This Special Edition reports on a conference centred on these biomedical discoveries, with other contributions, with a translation focus for predictive markers for ME/CFS diagnosis. By supporting health professionals with developments in diagnostics for this condition, the patients and their families will hopefully benefit from an improved recognition of the biomedical underpinnings of the condition and will be better able to access the care that is urgently required. This Special Edition contains a mix of speaker submissions and other accepted manuscripts that contributed to our objective of advancing biomedical insights to enable the accurate diagnosis of ME/CFS.
    Keywords: R5-920 ; RM1-950 ; fatigue syndrome ; n/a ; work rehabilitation ; tryptophan metabolism ; substrate inhibition ; myalgic encephalomyelitis ; 3-dioxygenase ; ME (Myalgic Encephalomyelitis) ; assessment ; myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) ; muscles ; hypoacetylation ; circadian rhythm ; immune system ; chronic ; CFS (Chronic Fatigue Syndrome) ; energy metabolism ; ME/CFS ; immunological ; cytokine ; bistability ; diagnosis ; biomarker ; symptoms ; kynurenine pathway ; inflammation and immunity ; metabolism ; neuro-inflammation ; pathology ; signaling ; exercise ; Epstein Barr virus ; methylhistidine ; hypothalamic–pituitary–adrenal axis ; potential biomarkers ; critical point ; inflammation ; histone deacetylation ; participatory research ; neurology ; neuroimmune ; activin ; mitochondria ; patient-driven questionnaire ; medical retirement ; machine learning ; prognosis ; gut microbiota ; post-exertional malaise ; chronic fatigue syndrome ; mathematical model ; reference intervals ; diagnostic biomarker ; indoleamine-2 ; bic Book Industry Communication::M Medicine
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Global health, conceived as a discipline, aims to train, research and respond to problems of a transboundary nature, in order to improve health and health equity at the global level. The current worldwide situation is ruled by globalization, and therefore the concept of global health involves not only health-related issues, but also those related to the environment and climate change. Therefore, in this Special Issue, the problems related to global health have been addressed from a bibliometric approach in four main areas: environmental issues, diseases, health, education and society.
    Keywords: social networks ; health ; young people ; bibliometric study ; scientometrics ; obesity ; interventions ; children ; youths ; pediatrics ; reclaimed water ; advanced oxidation process ; microorganisms ; concern emergent contaminant ; worldwide ; content analysis ; text mining ; diabetes ; QOL ; artificial intelligence ; machine learning ; bibliometric ; LDA ; HIV/AIDS ; quality of life ; global health ; public health ; scientometric study ; knowledge map ; visualization analysis ; CiteSpace ; COPD ; QoL ; medicinal plants ; drugs ; worldwide research ; bibliometrics ; traditional medicine ; asthma ; HRQoL ; Scival ; patents ; Spain ; Research and Development (R&amp ; D) ; social returns ; COVID-19 ; biomechanics ; musculoskeletal disorders ; RULA ; ergonomics ; applications ; climate change ; infectious diseases ; bibliometric analysis ; co-word analysis ; biclustering ; strategic diagram ; academic performance ; citation network ; motivation ; microplastics ; network analysis ; VOSviewer software ; research hotspots ; pulmonary disease ; musculoskeletal risks ; wastewater treatment ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.
    Keywords: TA1-2040 ; T1-995 ; optical sensor ; spectral analysis ; response surface sampling ; sensor evaluation ; electromagnetic induction ; multivariate water quality parameters ; mandarin orange ; crop inspection platform ; SPA-MLR ; object tracking ; feature selection ; simultaneous measurement ; diseases ; genetic algorithms ; processing of sensed data ; electrochemical sensors ; thermal image ; ECa-directed soil sampling ; handheld ; recognition patterns ; salt concentration ; clover-grass ; bovine embedded hardware ; weed control ; soil ; field crops ; vineyard ; connected dominating set ; water depth sensors ; SS-OCT ; wheat ; striped stem-borer ; silage ; geostatistics ; detection ; NIR hyperspectral imaging ; electronic nose ; machine learning ; virtual organizations of agents ; packing density ; data validation and calibration ; dataset ; Wi-SUN ; temperature sensors ; geoinformatics ; gas sensor ; X-ray fluorescence spectroscopy ; vegetable oil ; photograph-grid method ; Vitis vinifera ; WSN distribution algorithms ; laser-induced breakdown spectroscopy ; irrigation ; quality assessment ; energy efficiency ; wireless sensor network (WSN) ; geo-information ; Fusarium ; texture features ; weeds ; discrimination ; big data ; soil moisture sensors ; meat spoilage ; land cover ; stereo imaging ; near infrared sensors ; biological sensing ; compound sensor ; pest management ; moisture ; plant localization ; heavy metal contamination ; artificial neural networks ; spectral pre-processing ; moisture content ; apparent soil electrical conductivity ; data fusion ; semi-arid regions ; smart irrigation ; back propagation model ; wireless sensor network ; energy balance ; light-beam ; fluorescent measurement ; agriculture ; precision agriculture ; deep learning ; spectroscopy ; hulled barely ; dielectric probe ; RPAS ; water supply network ; rice leaves ; mobile app ; gradient boosted machines ; hyperspectral camera ; one-class ; nitrogen ; LiDAR ; total carbon ; chemometrics analysis ; rice ; agricultural land ; on-line vis-NIR measurement ; CARS ; obstacle detection ; stratification ; neural networks ; regression estimator ; Kinect ; proximity sensing ; distributed systems ; pest ; noninvasive detection ; texture feature ; soil mapping ; classification ; soil salinity ; visible and near-infrared reflectance spectroscopy ; germination ; computer vision ; hyperspectral imaging ; diffusion ; dielectric dispersion ; UAS ; random forests ; case studies ; total nitrogen ; thermal imaging ; cameras ; dry matter composition ; near-infrared ; salt tolerance ; deep convolutional neural networks ; soil type classification ; water management ; preprocessing methods ; wireless sensor networks (WSN) ; remote sensing image classification ; precision plant protection ; radar ; spatial variability ; GF-1 satellite ; plant disease ; naked barley ; leaf area index ; CIE-Lab ; change of support ; radiative transfer model ; 3D reconstruction ; plant phenotyping ; vine ; near infrared ; vegetation indices ; remote sensing ; greenhouse ; time-series data ; scattering ; sensor ; crop area ; speckle ; spatial data ; grapevine breeding ; wide field view ; partial least squares-discriminant analysis ; spiking ; area frame sampling ; chromium content ; machine-learning ; RGB-D sensor ; pest scouting ; PLS ; Capsicum annuum ; spatial-temporal model ; drying temperature ; boron tolerance ; ambient intelligence ; laser wavelength ; fuzzy logic ; dynamic weight ; landslide ; management zones ; real-time processing ; event detection ; crop monitoring ; apple shelf-life ; rice field monitoring ; wireless sensor ; birth sensor ; proximal sensor ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 8
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The book Green, Energy-Efficient and Sustainable Networks provides insights and solutions for a range of problems in the field of obtaining greener, energy-efficient, and sustainable networks. The book contains the outcomes of the Special Issue on “Green, Energy-Efficient and Sustainable Networks” of the Sensors journal. Seventeen high-quality papers published in the Special Issue have been collected and reproduced in this book, demonstrating significant achievements in the field. Among the published papers, one paper is an editorial and one is a review, while the remaining 15 works are research articles. The published papers are self-contained peer-reviewed scientific works that are authored by more than 75 different contributors with both academic and industry backgrounds. The editorial paper gives an introduction to the problem of information and communication technology (ICT) energy consumption and greenhouse gas emissions, presenting the state of the art and future trends in terms of improving the energy-efficiency of wireless networks and data centers, as the major energy consumers in the ICT sector. In addition, the published articles aim to improve energy efficiency in the fields of software-defined networking, Internet of things, machine learning, authentication, energy harvesting, wireless relay systems, routing metrics, wireless sensor networks, device-to-device communications, heterogeneous wireless networks, and image sensing. The last paper is a review that gives a detailed overview of energy-efficiency improvements and methods for the implementation of fifth-generation networks and beyond. This book can serve as a source of information in industrial, teaching, and/or research and development activities. The book is a valuable source of information, since it presents recent advances in different fields related to greening and improving the energy-efficiency and sustainability of those ICTs particularly addressed in this book
    Keywords: TA1-2040 ; T1-995 ; node speed ; linear recovery ; resource block allocation ; social awareness ; internet-of-things ; scheduling algorithm ; renewables ; neural network ; battery capacity ; energy awareness ; measurement structure ; optimization ; energy efficiency ; charging efficiency ; random structural matrices ; SDN ; water filling algorithm ; ONOS ; energy harvesting ; malware detection ; node density ; HetNets ; sustainability ; cooperative smart community ; adversarial samples ; spatial modulation ; NOMA ; 5G ; light-weight authentication ; green networking ; Device-to-Device (D2D) ; lightweight cipher ; mobile edge computing ; wireless power transfer ; adaptive link rate ; successive interference cancellation (SIC) ; directional charging vehicle ; self-interference cancellation ; proportional rate constraint ; inter-meeting time ; sustainable ; RWSN ; channel state information ; stochastic geometry ; networks ; green internet of things (IoT) ; PHY-layer ; IoT ; Markov chain ; traffic engineering ; QoS ; energy-efficient Ethernet ; power ; lightweight authentication ; energy aware routing ; authentication ; wired access ; amplify-and-forward ; software defined networking (SDN) ; image compressive sensing (CS) ; green ; edge computing ; LTE-A ; opportunistic networks ; RF Fingerprinting ; data centre ; multiple-input multiple-output ; Internet of Things ; machine learning ; peer discovery ; full-duplex ; industrial ; carbon footprint ; WSN ; imperfect CSI ; data center ; symbol error probability ; physical-layer authentication ; interference coordination ; clustering ; control and data plane ; wireless ; ICT ; bisection based optimal power allocation ; energy-efficiency ; consumer preferences ; real-time traffic ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-05
    Description: Beer is a beverage with more than 8000 years of history, and the process of brewing has not changed much over the centuries. However, important technical advances have allowed us to produce beer in a more sophisticated and efficient way. The proliferation of specialty hop varieties has been behind the popularity of craft beers seen in the past few years around the world. Craft brewers interpret historic beer with unique styles. Craft beers are undergoing an unprecedented period of growth, and more than 150 beer styles are currently recognized. This Special Issue, Brewing and Craft Beer, comprises nine different works by researchers from five continents (North America, South America, Europe, Africa, and Oceania). This Special Issue reflects thus a broad perspective on the most important questions that concern the researchers in different parts of the world.
    Keywords: QH301-705.5 ; QD415-436 ; Q1-390 ; polyphenols ; n/a ; nutrient ; audible sound ; wet milling ; brewing technology ; robotics ; fast-screening ; lactose ; image analysis ; bottle refermentation ; beer aging ; sensory attributes ; brewing ; automation ; bitterness ; stout beer ; beer ; craft beer ; foamability ; Safrari ; adjuncts ; fermentation rate ; barley milling ; preference ; germ ; beer wort ; machine learning ; carbonation ; quality ; FAN ; granulometry ; sensory evaluation ; coffee ; beer acceptability ; computer vision ; fermentation ; economic contribution analysis ; short-chain fatty acids ; local value chain ; AEDA ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering.
    Keywords: SVM ; budding rate ; UAV ; geometric consistency ; radiometric consistency ; point clouds ; ICP ; reflectance maps ; vegetation indices ; Parrot Sequoia ; artificial intelligence ; precision agriculture ; agricultural robot ; optimization algorithm ; online operation ; segmentation ; coffee leaf rust ; machine learning ; deep learning ; remote sensing ; Fourth Industrial Revolution ; Agriculture 4.0 ; failure strain ; sandstone ; digital image correlation ; Hill–Tsai failure criterion ; finite element method ; reference evapotranspiration ; moisture sensors ; machine learning regression ; frequency-domain reflectometry ; randomizable filtered classifier ; convolutional neural network ; U-Net ; land use ; banana plantation ; Panama TR4 ; aerial photography ; remote images ; systematic mapping study ; agriculture ; applications ; total leaf area ; mixed pixels ; Cabernet Sauvignon ; NDVI ; Normalized Difference Vegetation Index ; precision viticulture ; 3D model ; spatial vision ; fertirrigation ; teaching–learning ; spectrometry ; Sentinel-2 ; pasture quality index ; normalized difference vegetation index ; normalized difference water index ; supplementation ; decision making ; digital agriculture ; grape yield estimate ; berries counting ; Dilated CNN ; machine learning algorithms ; classification performance ; winter wheat mapping ; large-scale ; water stress ; Prunus avium L. ; stem water potential ; low-cost thermography ; thermal indexes ; canopy temperature ; non-water-stressed baselines ; non-transpiration baseline ; soil moisture ; andosols ; image processing ; greenhouse ; automatic tomato harvesting ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 11
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-02
    Description: Higher education has been considered both an ‘engine’ for innovation and a ‘catalyst’ for sustainability development; the integration of both the innovation engine and sustainability catalyst roles are discussed in a recently published Special Issue on the theme of Higher Education in Innovation Ecosystems in the journal Sustainability. Based on 16 articles contributing to the Special Issue from various perspectives, the Special Issue editors have developed an overarching framework about the relationships between higher education and innovation ecosystems. In the framework, we re-define the concept of innovation ecosystem and identify emerging roles of universities in developing sustainable innovation ecosystems. Re-conceptualization of innovation ecosystems In the editorial of the Special Issue, innovation ecosystem is defined as: co-innovation networks in which actors from organizations concerned with the functions of knowledge production, wealth creation, and norm control interact with each other in forming co-evolution and interdependent relations (both direct or indirect) in cross-geographical contexts and through which new ideas and approaches from various internal and external sources are integrated into a platform to generate shared values for the sustainable transformation of society. Compared with most commonly cited definitions of innovation ecosystem, our definition highlights three new aspects of interactions in co-innovation networks: cross-sectoral, transnational, and indirect, drawing insights from the literature including innovation, geography, and biology studies. The roles of universities in innovation ecosystems The emerging roles of universities in innovation ecosystems are as follows: (1) The role of universities is changing from being a central player in technology transfer to being an anchor in knowledge exchange; (2) universities are assuming a new role in trust-building between actors in innovation ecosystems; and (3) universities are not merely an entrepreneurial universities but are also institutional entrepreneur in the innovation ecosystem. The three emerging roles all indicate that universities are becoming the catalysts for sustainable development in innovation ecosystems. Knowledge exchange is crucial for sustainability; trust is the foundation of the sustainable networks; social entrepreneurship is indispensable for sustainable social change. Evidence in wider contexts A total of 44 authors from 10 countries contributed to the discussions on the changing roles of higher education in innovation ecosystems from varying perspectives. They also report transformations within higher education and universities’ responses to both external and internal transformations. When addressing these issues, the studies provide both theoretical and methodological contributions to the research on higher education in innovation ecosystems. The 16 articles can be generally placed into four categories: (1) new demands for universities arising from the transformation in society toward innovation ecosystems, (2) transformations within higher education responding to emerging societal demands, (3) dynamics of the interaction of university with other innovation actors in a transnational context, and (4) academic and student mobility for higher education innovation. Calling for a new research agenda While societal changes demand broader roles of universities, they also call for and leads to substantial changes within the internal fabric of the university. The innovations in both society and the universities necessitate a renewed understanding of higher education in society, which has become a new research agenda in studies on innovation in higher education. We hope our Special Issue will inspire and encourage more scholars to join the research field.
    Keywords: transnational industry cooperation ; transnational university cooperation ; transnational innovation ecosystem ; EU–China ; science, technology and innovation cooperation ; transdisciplinary approach ; artificial intelligence ; machine learning ; Higher Education ; University ; Entrepreneurial competences ; Employability ; Theory of Planned Behaviour (TPB) ; Open Innovation ; business creation ; technology transfer ; innovation ; innovation ecosystem ; entrepreneurship education ; science and technology ; sustainability ; higher education ; educational innovation ; Mexico ; academic mobility ; knowledge transfer ; higher education innovation ; institutional environment ; postgraduate education ; education level ; discipline background ; graduation institution ; R&amp ; D investment ; triple helix ; synergy mechanism ; national system of innovation ; China ; Belt and Road Initiative ; developmental model of intercultural sensitivity ; general model of instructional communication ; instructional beliefs model ; intercultural communication competence model ; green GDP ; environment ; sustainable development ; global innovation systems ; Chinese research university ; faculty income ; academic labor market ; ordinary labor market ; joint R&amp ; D institute ; institutional logics ; China’s innovation system ; China’s transnational Triple Helix linkages ; problem-solving ; critical reflection ; knowledge integration ; social learning ; systemic thinking ; entrepreneurial university ; entrepreneurship ; influencing factors ; sustainable universities ; corporate sustainability ; tensions ; integrative framework ; Finnish universities ; higher education system ; social entrepreneurship ; entrepreneurial universities ; business model innovation ; socialist economies ; Cuba ; knowledge brokers ; knowledge intensive policies ; smart specialisation ; innovation ecosystems ; global talent ; social integration ; economic integration ; Chinese student ; Finland ; university ; third mission ; knowledge-based society ; global innovation networks ; thema EDItEUR::N History and Archaeology::NH History ; thema EDItEUR::J Society and Social Sciences::JN Education
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  • 12
    Publication Date: 2024-04-11
    Description: heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.
    Keywords: TA1-2040 ; T1-995 ; TA170-171 ; geophysical monitoring ; data scarcity ; missing data ; climate extreme indices (CEIs) ; rule extraction ; Dataset Licensedatabase ; data assimilation ; data imputation ; support vector machines ; environmental observations ; multi-class classification ; earth-science data ; remote sensing ; magnetotelluric monitoring ; soil texture calculator ; machine learning ; ClimPACT ; invasive species ; species distribution modeling ; 3D-Var ; ensemble learning ; data quality ; water quality ; microhabitat ; k-Nearest Neighbors ; Expert Team on Climate Change Detection and Indices (ETCCDI) ; decision trees ; processing ; attribute reduction ; Expert Team on Sector-specific Climate Indices (ET-SCI) ; core attribute ; rough set theory ; GLDAS ; arthropod vector ; environmental modeling ; statistical methods ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 13
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: As we move further into the 21st century, despite the fact that new technologies have emerged, machining remains the key operation to achieve high productivity and precision for high-added value parts in several sectors, but recent advances in computer applications should close the gap between simulations and industrial practices. This book, “Machining Dynamics and Parameters Process Optimization”, is oriented toward the different strategies and paths when it comes to increasing productivity and reliability in metal removal processes. The topics include the dynamic characterization of machine tools, experimental dampening techniques, and optimization algorithms combined with signal monitoring.
    Keywords: CNC parameters ; machining mode ; high speed ; high accuracy ; high surface quality ; five-axis linear-segment toolpath ; path smoothing ; B-spline curve-fitting ; path synchronization ; feedrate scheduling ; flute-grinding ; evolution algorithms ; wheel location and orientation ; thin-floor machining ; chatter ; magnetorheological damper ; bull-nose end mill ; tool wear monitoring ; milling ; complex part ; deep learning ; autoencoder ; deep multi-layer perceptron ; tool condition monitoring ; tool change policy ; Industry 4.0 ; machine learning ; CNN ; AI ; additive manufacturing ; thin walled machining ; dynamics ; machining cycle optimization ; multivariable tool ; stable peninsula ; homotopy perturbation method ; machining robot ; natural frequency prediction ; model optimization ; dynamic performance ; stability ; machining ; grinding ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 14
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Smart textiles are the textiles that are sensitive to any environmental conditions and can respond accordingly. Using passive and active coatings to generate high sensitivity to textiles is among the most recent research trends by engineers around the World. This has resulted in expansion in the application of smart textiles in various industrial fields including medicals, electronics and protective clothing. The aim of this special issue is to introduce the most state-of-the-art research and review articles by distinguished researchers in the field of smart coatings on textiles. The guest editor hopes that content will be useful for researchers, students and companies for continuation of research and development with the concept of smart textiles.
    Keywords: TA1-2040 ; T1-995 ; TA401-492 ; chitosan ; pilling ; cyclodextrin ; polypropylene ; actuator ; UHMWPE ; hydrophobic ; separation ; reactive vapor deposition ; e-textiles ; image processing ; fiber ; conducting polymers ; conductive coatings ; dip coating technique ; textile ; triboelectricity ; smart textiles ; hernia meshes ; microgel ; optical fiber sensors ; polymer ; nanoparticle-laden elastomer ; touch sensor ; textile electronics ; structural color ; PLA fiber ; wearable technology ; carbon nanotubes ; electrospinning ; assembly ; photonic crystal ; electrospun nanofibers ; plasma treatment ; coating ; nanoparticle assemblies ; sodium alginate ; flexible electronics ; Janus material ; machine learning ; polymer actuators ; oxygen-plasma treatment ; polydopamine ; plain weave ; absorbant ; surface functionalization ; penetration resistance ; lab-on-fiber technology ; layer-by-layer method ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 15
    Publication Date: 2024-04-11
    Description: Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.
    Keywords: TA1-2040 ; T55.4-60.8 ; T1-995 ; localization ; smart system ; n/a ; connected enterprise ; digital manufacturing ; AHP ; YOLOv3 ; decision support ; neural network ; vertex distance ; depthwise separable convolution ; cutting insert selection ; smart service ; contour detection ; convolutional neural networks ; platform-based ecosystem ; in-line dimensional inspection ; dilated convolutions ; fabric defect detection ; classification ; FCM ; LGM ; digital information flow ; turning ; computer vision ; control service ; blister defect ; RMTs ; feature pyramid ; research and development indicators ; maintenance expert ; polymer lithium-ion battery ; IT concept ; Industry 4.0 ; matching ; data reduction ; competence ; fibre of preserved Szechuan pickle ; elliptical paraboloid array ; relative angle ; geometric relationship ; optical system ; configure-to-order ; aircraft structure crack detection ; digital twins ; smart factory ; D-VGG16 ; optical slope sensor ; smart manufacturing ; self-calibration method ; convolutional neural network ; industry 4.0 ; skyline queries ; machine learning ; scalability test ; cyber-physical production systems ; Cyber-Physical Systems (CPS) ; demand-side response ; cutting parameter optimization ; image smoothing ; marketing innovations ; genetic algorithm ; automation system ; defect detection ; scheduling ; job shop systems ; big data ; operator theory ; micro-armature ; train wheel ; industrial knowledge graph ; industrial load management ; bilinear model ; artificial neural networks ; 4th industrial revolution ; INDUSTRY 4.0 ; construction equipment ; lean assembly ; capacity control ; Grad-CAM ; revolution workpiece ; chatter ; anomaly detection ; QFD ; social network ; deep learning ; control as a service ; warm forming ; automated surface inspection ; cloud-based control system ; innovative marketing tools ; Internet of Things (IoT) ; flower pollination algorithm ; HED ; edge computing ; predictive analytics ; BIM ; digital platforms ; industrial big data ; energy flexibility ; impacts marketing innovations ; intellectualization of industrial information ; economic recession ; 3D mesh reconstruction ; demand-side management ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 16
    Publication Date: 2024-04-11
    Description: This Special Issue contains a series of excellent research works on telecommunications and signal processing, selected from the 2018 41st International Conference on Telecommunications and Signal Processing (TSP) which was held on July 4–6, 2018, in Athens, Greece. The conference was organized in cooperation with the IEEE Region 8 (Europe, Middle East, and Africa), IEEE Greece Section, IEEE Czechoslovakia Section, and IEEE Czechoslovakia Section SP/CAS/COM Joint Chapter by seventeen universities from the Czech Republic, Hungary, Turkey, Taiwan, Japan, Slovak Republic, Spain, Bulgaria, France, Slovenia, Croatia, and Poland, for academics, researchers, and developers, and serves as a premier international forum for the annual exchange and promotion of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors worldwide. This collection of 10 papers is highly recommended for researchers, and believed to be interesting, inspiring, and motivating for readers in their further research.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; dynamic time warping ; n/a ; Least Absolute Shrinkage and Selection Operator (LASSO) ; multispectral information ; transmission convergence layer ; 3D segmentation ; micrographia ; MATLAB ; neural network ; wireless communication ; identification ; interference alignment ; Parkinson’s disease dysgraphia ; NG-PON2 ; timing ; GPON ; semantic segmentation ; fractional-order filters ; maximum likelihood criterion ; kinematic analysis ; multitemporal data ; fractional calculus ; multi-hop relay network ; u-net ; interference leakage ; Richardson iteration ; activation process ; acoustic analysis ; follow-up study ; fractional-order derivative ; electrocardiogram (ECG) ; deep learning ; security ; modulo M quasi-stationary ; cognitive radio ; low-pass filters ; time-interleaved analog-to-digital converter (TIADC) ; sample-and-hold (S/H) mismatch ; authentication ; pattern recognition ; online handwriting ; sparse inference ; Taylor series ; EPON ; open-source ; spine ; machine learning ; brain ; signal representation ; magnitude responses ; Chebyshev filters ; XG-PON ; phonation ; hypokinetic dysarthria ; Parkinson’s disease ; overcomplete multi-scale dictionary construction ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 17
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.
    Keywords: TA1-2040 ; T1-995 ; supervised machine learning ; proper orthogonal decomposition (POD) ; PGD compression ; stabilization ; nonlinear reduced order model ; gappy POD ; symplectic model order reduction ; neural network ; snapshot proper orthogonal decomposition ; 3D reconstruction ; microstructure property linkage ; nonlinear material behaviour ; proper orthogonal decomposition ; reduced basis ; ECSW ; geometric nonlinearity ; POD ; model order reduction ; elasto-viscoplasticity ; sampling ; surrogate modeling ; model reduction ; enhanced POD ; archive ; modal analysis ; low-rank approximation ; computational homogenization ; artificial neural networks ; unsupervised machine learning ; large strain ; reduced-order model ; proper generalised decomposition (PGD) ; a priori enrichment ; elastoviscoplastic behavior ; error indicator ; computational homogenisation ; empirical cubature method ; nonlinear structural mechanics ; reduced integration domain ; model order reduction (MOR) ; structure preservation of symplecticity ; heterogeneous data ; reduced order modeling (ROM) ; parameter-dependent model ; data science ; Hencky strain ; dynamic extrapolation ; tensor-train decomposition ; hyper-reduction ; empirical cubature ; randomised SVD ; machine learning ; inverse problem plasticity ; proper symplectic decomposition (PSD) ; finite deformation ; Hamiltonian system ; DEIM ; GNAT ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 18
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields.
    Keywords: light emitting diode ; nonlinearity estimation and compensation ; probabilistic Bayesian learning ; visible light communication ; digital signal processing ; support vector machines ; BCSVM ; nonlinear equalization ; coherent detection ; k-nearest neighbor algorithm ; modulation format identification ; OSNR monitoring ; neural networks ; optical communications ; optimization ; equalizer ; tap estimation ; optical Fast-OFDM ; nonlinearity compensation ; optical fiber communications ; chromatic dispersion ; short-reach communication ; neural network ; hybrid signal processing ; fiber optics communications ; coherent communications ; machine learning ; clustering ; nonlinearity cancellation ; entanglement ; charge qubit ; position-based semiconductor qubits ; cryogenic technologies ; semiconductor photon communication ; Jaynes–Cummings–Hubbard formalism ; deep neural networks ; volterra equalization ; nonlinear systems ; coherent optical communication ; passive optical networks ; nonlinear compensation ; optical transmission ; optical networks ; artificial intelligence ; quality of transmission ; optical performance monitoring ; failure management ; artificial neural networks ; deep neural network ; image classification ; photonic integrated circuits ; semiconductor optical amplifiers ; photonic neural network ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 19
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue was created to collect the most recent and novel research on seismic performance evaluation of building structures. This issue includes three important topics on seismic engineering for building structures: (1) seismic design and performance evaluation, (2) structural dynamics, and (3) seismic hazard and risk analysis. To protect building structures from earthquakes, it is necessary to conduct seismic performance evaluations on structures with reliable methods and to retrofit these structures appropriately using the results of the seismic performance evaluation.
    Keywords: strength ; yielding capping and ultimate deformation ; RC column ; cyclic test database ; artificial neural network ; bi-linear and tri-linear lumped plasticity model ; columns ; cyclic behavior ; low height-to-depth ratio ; modeling parameters ; calibration ; SPSW ; axial compression ratio ; hole size ; thickness of stiffening plate ; hole position ; hysteretic performance ; FEM (Finite Element Method) ; DYNA6 ; soil-structure interaction ; soil-pile dynamic stiffness ; retrofitting ; viscous dampers ; optimum design ; collapse-resistant capacity ; economic benefit ; sustainability ; steel reinforced concrete ; joint ; post critical ; moment-curvature ; nonlinear ; frame model ; multi-story steel frames ; self-centering bracing elements ; buckling-restrained brace (BRB) ; seismic analysis ; earthquake/seismic forces ; seismic damage ; mold transformer ; shaking table test ; non-structural elements ; dynamic characteristics ; ground motion ; earthquake ; response history analysis ; station ; seismicity ; machine learning ; structural types ; decision forest ; self-training procedures ; city-scale seismic damage simulation ; numerical models ; model parameter ; analysis algorithm ; seismic performance evaluation ; seismic risk ; seismic hazard ; seismic force resisting system ; energy dissipater ; seismic design ; nonlinear response ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 20
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Electromagnetic (EM) waves carry energy through propagation in space. This radiation associates with entangled electric and magnetic fields which must exist simultaneously. Although all EM waves travel at the speed of light in vacuum, they cover a wide range of frequencies called the EM spectrum. The various portions of the EM spectrum are referred to by various names based on their different attributes in the emission, transmission, and absorption of the corresponding waves and also based on their different practical applications. There are no certain boundaries separating these various portions, and the ranges tend to overlap. Overall, the EM spectrum, from the lowest to the highest frequency (longest to shortest wavelength) contains the following waves: radio frequency (RF), microwaves, millimeter waves, terahertz, infrared, visible light, ultraviolet, X-rays, and gamma rays. This Special Issue consists of sixteen papers covering a broad range of topics related to the applications of EM waves, from the design of filters and antennas for wireless communications to biomedical imaging and sensing and beyond.
    Keywords: bonding wire ; S parameters ; electromagnetic simulation ; port embedding ; balanced bandpass filter ; common mode suppression ; spurline ; source–load coupling ; stepped impedance resonator (SIR) ; open-ended waveguide ; slow-wave ; endfire ; radiation ; dispersion ; gain ; energy verification ; Hall probe ; dipole ; movable slit ; Goubau line ; non-invasive blood glucose measurement ; Acu-check ; lancet ; leaky waves ; surface waves ; ultra-wideband ; THz absorber ; high absorption ; polarization independent ; holography ; microwave imaging ; microwave measurement system ; nondestructive testing ; electromagnetic compatibility ; protection of information ; electromagnetic emissions ; computers and information processing ; data acquisition ; image recognition ; pattern recognition ; image processing ; graphic information ; LED array ; laser printer ; compromising emanations ; electromagnetic infiltration ; reconstruction ; non-invasive data acquisition ; Fourier series expansion ; nanorod ; multimode ; propagation characteristics ; guided wave ; bandpass filter ; half-wavelength resonator ; insertion loss ; phantom measurement system ; bone lesion detection ; ground penetrating radar ; reverse time migration ; Tibetan Plateau ; permafrost active layer ; internal structure ; Chebyshev filter ; cavity ; metamaterial ; waveguide ; X-band ; meta-resonator ; machine learning ; material identification ; microwave sensor array ; microwave waveguide ; dipole and horn antennas ; carbon-composite material ; graphene ; antenna mesurements ; electromagnetic waves ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 21
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In recent years, the industrial environment has been changing radically due to the introduction of concepts and technologies based on the fourth industrial revolution, also known as Industry 4.0. After the introduction of Industry 4.0 in large enterprises, SMEs have moved into the focus, as they are the backbone of many economies. Small organizations are increasingly proactive in improving their operational processes, which is a good starting point for introducing the new concepts of Industry 4.0. The readiness of SME-adapted Industry 4.0 concepts and the organizational capability of SMEs to meet this challenge exist only in some areas. This reveals the need for further research and action plans for preparing SMEs in a technical and organizational direction. Therefore, special research and investigations are needed for the implementation of Industry 4.0 technologies and concepts in SMEs. SMEs will only achieve Industry 4.0 by following SME-customized implementation strategies and approaches and realizing SME-adapted concepts and technological solutions. Thus, this Special Issue represents a collection of theoretical models as well as practical case studies related to the introduction of Industry 4.0 concepts in small- and medium-sized enterprises.
    Keywords: latent semantic analysis ; virtual quality management ; concept investigation ; concept disambiguation ; knowledge discovery ; sustainable methodologies ; small and medium sized enterprises ; material handling systems ; simulation ; ARENA®, time study ; overall equipment effectiveness ; manufacturing performance ; Industry 4.0 ; manufacturing sustainability ; manufacturing process model ; business process management ; hierarchical clustering ; similarity ; BPMN ; human factors ; cyber-physical systems ; cyber-physical production systems ; anthropocentric design ; Operator 4.0 ; human–machine interaction ; energy efficient operation ; manufacturing system ; stochastic event ; digital twin ; Max-plus Algebra ; MATLAB-Simulink ; advanced manufacturing ; industry 4.0 ; SME ; technology adoption model ; assembly supply chain ; sustainability ; complexity indicators ; testing criteria ; SMEs ; e-business modelling ; LSP Lifecycle Model ; Quality Function Deployment ; Best-Worst Method ; Internet of Things ; India ; awareness ; small and medium-sized enterprises ; assessment model ; collaborative robotics ; physical ergonomics ; human-robot collaboration ; human-centered design ; assembly ; small and medium sized enterprise ; positive complexity ; negative complexity ; infeasible configurations ; product platform ; customer’s perception ; assessment ; field study ; smart manufacturing ; cloud platform ; artificial intelligence ; machine learning ; deep learning ; smart logistics ; logistics 4.0 ; smart technologies ; sustainable agriculture ; plant factory ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 22
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The depletion of natural energy resources provides evidential adverse impacts on world economy functionality. The strong requirement of a sustainable energy supply has escalated intensive research and the discovery of cleaner energy sources, as well as efficient energy management practices. In the context of a circular economy, this research not only targets the optimisation of resources utilisation at different stages but also emphasises the eco-design of products to extend production life spans. Based on this concept, this book discusses the roles of process integration approaches, renewable energy sources utilisation and design modifications in addressing the process energy and exergy efficiency improvement. The primary focus is to enhance the economic and environmental performance through process analysis, modelling and optimisation. The articles mainly show the contribution of each aspect: (a) design and numerical study for innovative energy-efficient technologies, (b) process integration—heat and power, (c) process energy efficiency or emission analysis, and (d) optimisation of renewable energy resources’ supply chain. The articles are based on the latest contribution of this journal’s Special Issues in the 21st conference entitled “Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction (PRES)”. This book is complemented with an editorial review to highlight the broader state-of-the-art development.
    Keywords: particulate matter ; fine particles ; combustion particles ; nucleation ; particle growth ; data envelopment analysis ; energy efficiency ; food loss and waste ; life-cycle assessment ; welding residual stress ; welding deflection ; T-joint fillet weld ; preheat temperature ; interpass time ; finite element analysis ; water desalination ; water supply ; water shortage ; energy demand ; environmental impacts ; specific energy consumption ; cryogenic energy storage ; air liquefaction ; exergy analysis ; economic analysis ; exergoeconomic analysis ; heat exchanger network ; structural controllability ; structural observability ; operability ; network science ; sensor and actuator placement ; simplified methods ; design procedure ; convection section ; radiant section ; flow distribution ; heat flux distribution ; boiler ; solar collector network ; minimum number of solar collectors ; maximum operating time ; flexible operation ; district heating ; heat accumulation ; pipe ; numerical model ; Modelica language ; Julia language ; performance ; off-grid polygeneration ; micro-hydropower plant ; fuzzy optimization ; mixed-integer linear programming ; dual-turbine ; multi-objective ; heat exchanger network (HEN) ; synthesis ; optimization ; direct heat integration ; indirect heat integration ; piping ; pumping ; impinging jet ; dimple ; Nusselt number ; heat transfer ; heat exchanger ; flow boiling ; surface-enhanced tube ; heat transfer coefficient ; flow pattern ; total site heat integration ; heat recovery loop (HRL) ; heat storage ; Monte Carlo (MC) simulation ; data farming ; gasification ; biomass ; total solid particle ; trigeneration system ; process integration ; pinch analysis ; co-generation ; storage system ; trigeneration system cascade analysis ; energy conservation ; latent heat thermal energy storage ; phase change materials ; passive cooling ; bio-adsorbents ; chitosan microbeads ; nanoparticles ; anaerobic digestion ; biowaste ; life cycle assessment ; smart city ; waste collection ; P-Graph framework ; process network synthesis ; multi-periodic model ; sustainability ; co-firing ; wheat straw ; softwood ; bog peat ; pellets ; thermal decomposition ; combustion ; DC electric field ; computational fluid dynamics ; temperature contour ; cooling system ; mathematical optimization ; machine learning ; flexible control technology ; biomass co-firing ; biomass quality ; network optimization ; goal programming ; mixed integer nonlinear programming ; renewable energy sources ; energy-saving technologies ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 23
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.
    Keywords: water resources management ; landslide ; dammed lake ; flood risk ; time-varying parameter ; GR4J model ; changing environments ; temporal transferability ; western China ; cascade hydropower reservoirs ; multi-objective optimization ; TOPSIS ; gravitational search algorithm ; opposition learning ; partial mutation ; elastic-ball modification ; Snowmelt Runoff Model ; parameter uncertainty ; data-scarce deglaciating river basin ; climate change impacts ; generalized likelihood uncertainty estimation ; Yangtze River ; cascade reservoirs ; impoundment operation ; GloFAS-Seasonal ; forecast evaluation ; small and medium-scale rivers ; highly urbanized area ; flood control ; whole region perspective ; coupled models ; flood-risk map ; hydrodynamic modelling ; Sequential Gaussian Simulation ; urban stormwater ; probabilistic forecast ; Unscented Kalman Filter ; artificial neural networks ; Three Gorges Reservoir ; Mahalanobis-Taguchi System ; grey entropy method ; signal-to-noise ratio ; degree of balance and approach ; interval number ; multi-objective optimal operation model ; feasible search space ; Pareto-front optimal solution set ; loss–benefit ratio of ecology and power generation ; elasticity coefficient ; empirical mode decomposition ; Hushan reservoir ; data synthesis ; urban hydrological model ; Generalized Likelihood Uncertainty Estimation (GLUE) ; Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) ; uncertainty analysis ; NDVI ; Yarlung Zangbo River ; machine learning model ; random forest ; Internet of Things (IoT) ; regional flood inundation depth ; recurrent nonlinear autoregressive with exogenous inputs (RNARX) ; artificial intelligence ; machine learning ; multi-objective reservoir operation ; hydrologic forecasting ; uncertainty ; risk ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 24
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.
    Keywords: cluster analysis ; equity index networks ; machine learning ; copulas ; dependence structures ; quotient of random variables ; density functions ; distribution functions ; multi-factor model ; risk factors ; OLS and ridge regression model ; python ; chi-square test ; quantile ; VaR ; quadrangle ; CVaR ; conditional value-at-risk ; expected shortfall ; ES ; superquantile ; deviation ; risk ; error ; regret ; minimization ; CVaR estimation ; regression ; linear regression ; linear programming ; portfolio safeguard ; PSG ; equity option pricing ; factor models ; stochastic volatility ; jumps ; mathematics ; probability ; statistics ; finance ; applications ; investment home bias (IHB) ; bivariate first-degree stochastic dominance (BFSD) ; keeping up with the Joneses (KUJ) ; correlation loving (CL) ; return spillover ; volatility spillover ; optimal weights ; hedge ratios ; US financial crisis ; Chinese stock market crash ; stock price prediction ; auto-regressive integrated moving average ; artificial neural network ; stochastic process-geometric Brownian motion ; financial models ; firm performance ; causality tests ; leverage ; long-term debt ; capital structure ; shock spillover ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
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  • 25
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The electric power sector is poised for transformative changes. Improvements in the cost and performance of a range of distributed energy generation (DG) technologies and the potential for breakthroughs in distributed energy storage (DS) are creating new options for onsite power generation and storage, driving increasing adoption and impacting utility distribution system operations. In addition, changing uses and use patterns for electricity—from plug-in electric vehicles (EVs) to demand response (DR)—are altering demands placed on the electric power system. Finally, the infusion of new information and communications technology (ICT) into the electric system and its markets is enabling the collection of immense volumes of data on power sector operations and use; unprecedented control of generation, networks, and loads; and new opportunities for the delivery of energy services. In this Special Issue of Energies, research papers on topics related to the integration of distributed energy resources (DG, DS, EV, and DR) are included. From technologies to software tools to system-wide evaluations, the impacts of all aforementioned distributed resources on both operation and planning are examined.
    Keywords: machine learning ; microgrids ; optimisation methods ; power systems ; reinforcement learning ; high penetration ; renewable energy ; adaptability planning ; source-grid coordination ; renewable electricity distribution for public space ; sustainability assessment model ; integrated assessment for public space ; tripartite altruism ; urban renewable energy ; ecological infrastructures ; Micro-grids ; continuity of supply ; power distribution ; power system planning ; decentralized control ; small hydropower plants ; microgrid ; emergency control ; recloser ; synchronous coupler ; power systems stability ; power system operation ; power system security ; renewable energy integration ; load flow analysis ; congestion management ; distributed generation curtailment ; demand side management ; demand response ; cyber-physical systems ; dynamic pricing ; load forecasting ; attack detection ; photovoltaics ; distributed energy resources (DERs) ; grid impact ; power quality ; low-voltage distribution network ; inverter regulation ; electric vehicles ; uncontrolled charging ; delayed charging ; controlled charging ; V2G ; V2B ; V2H ; peak shaving ; valley filling ; renewable energy sources ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR
    Keywords: TA1-2040 ; T1-995 ; n/a ; FPGA ; recurrence plot (RP) ; residual learning ; neural networks ; driver monitoring ; navigation ; depthwise separable convolution ; optimization ; dynamic path-planning algorithms ; object tracking ; sub-region ; cooperative systems ; convolutional neural networks ; DSRC ; VANET ; joystick ; road scene ; convolutional neural network (CNN) ; multi-sensor ; p-norm ; occlusion ; crash injury severity prediction ; deep leaning ; squeeze-and-excitation ; electric vehicles ; perception in challenging conditions ; T-S fuzzy neural network ; total vehicle mass of the front vehicle ; electrocardiogram (ECG) ; communications ; generative adversarial nets ; camera ; adaptive classifier updating ; Vehicle-to-X communications ; convolutional neural network ; predictive ; Geobroadcast ; infinity norm ; urban object detector ; machine learning ; automated-manual transition ; red light-running behaviors ; photoplethysmogram (PPG) ; panoramic image dataset ; parallel architectures ; visual tracking ; autopilot ; ADAS ; kinematic control ; GPU ; road lane detection ; obstacle detection and classification ; Gabor convolution kernel ; autonomous vehicle ; Intelligent Transport Systems ; driving decision-making model ; Gaussian kernel ; autonomous vehicles ; enhanced learning ; ethical and legal factors ; kernel based MIL algorithm ; image inpainting ; fusion ; terrestrial vehicle ; driverless ; drowsiness detection ; map generation ; object detection ; interface ; machine vision ; driving assistance ; blind spot detection ; deep learning ; relative speed ; autonomous driving assistance system ; discriminative correlation filter bank ; recurrent neural network ; emergency decisions ; LiDAR ; real-time object detection ; vehicle dynamics ; path planning ; actuation systems ; maneuver algorithm ; autonomous driving ; smart band ; the emergency situations ; two-wheeled ; support vector machine model ; global region ; biological vision ; automated driving ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.
    Keywords: TA1-2040 ; T1-995 ; programmable appliances ; energy management system ; MILP ; sensitivity analysis ; simulation ; development demand ; meta heuristic techniques ; feedback ; patent analysis ; optimization ; scenario planning ; micro grids ; solar generation ; IEC 61499 ; distributed energy management algorithm ; technology adoption ; ToU tariff ; photovoltaic power ; seawater pumped storage ; peak reduction ; planning ; K-modes clustering ; Gaussian process regression ; multilayer perceptron neural network ; economic feasibility analysis ; EnergyPlus ; intruder detection system ; occupant behavior ; HOMER ; smart grid security ; D strategy ; smart energy ; IEC 61850 ; cyberattacks ; semantic web technologies ; renewable energy sources ; optimal power flows ; forecasting ; heuristic ; households ; machine learning ; micro grid ; support vector machine ; comprehensive evaluation ; electricity charge discount program ; model driven architecture ; sustainable smart grid technology ; rules ; daily consumption curve ; genetic algorithm ; renewable energy ; combined dispatch (CD) strategy ; scheduling ; technology acceptance ; electric vehicle charging technology ; energy consumption ; ontology ; theories of social practice ; R&amp ; unbalanced three-phase distribution networks ; game theory ; sustainability ; distributed generation ; energy storage system ; energy and water consumption ; active distribution networks ; policy effectiveness evaluation ; peak/off-peak ; differentiation ; graph theory ; D planning ; data mining ; values ; optimal power flow ; Smart Grid Station ; Korean Time Use Survey ; smart grid architecture model ; single-person household ; holomorphic embedding load flow method ; storage device ; smart grid ; smart metering ; engineering support ; two-stage ; net present cost (NPC) ; nash equilibrium ; STEEP analysis ; electrical distribution system ; solar power generation prediction ; storage capacity ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things.
    Keywords: atmospheric ; on-line monitoring ; LoRa ; embedded system ; smart environments ; Internet of Things ; indoor occupancy ; machine learning ; data analysis ; landslide susceptibility ; China-Nepal Highway ; LSTM ; remote sensing images ; IoT ; network traffic ; monitoring ; DDoS ; packet classification ; indoor localization ; channel state information ; device-free passive ; WiFi fingerprint ; naive Bayes classification ; feature fusion ; posture recognition ; indoor positioning ; wireless body area network ; Kalman filtering ; multi-sensor combination ; prognostic and health management ; integrative framework ; internet of things ; convolutional neural network ; conditioned-based maintenance ; IoT platform ; intelligent monitoring robot ; active CCTV ; learning model ; electrical devices ; classification ; energy management ; smart environment ; architecture ; blockchain ; communication constraints ; decentralized application ; Ethereum ; Internet of things ; sensing and control ; computational efficiency ; robotic manipulators ; hysteresis ; adaptive control ; wireless sensor network (WSN) ; energy ; ant colony optimization (ACO) ; routing algorithm ; quantum-inspired evolutionary algorithms ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.
    Keywords: vacuum tank degasser ; rule extraction ; extreme learning machine ; classification and regression trees ; wind power: wind speed: T–S fuzzy model: forecasting ; linearization ; machine learning ; photovoltaic output power forecasting ; hybrid interval forecasting ; relevance vector machine ; sample entropy ; ensemble empirical mode decomposition ; high permeability renewable energy ; blockchain technology ; energy router ; QoS index of energy flow ; MOPSO algorithm ; scheduling optimization ; Adaptive Neuro-Fuzzy Inference System ; insulator fault forecast ; wavelet packets ; time series forecasting ; power quality ; harmonic parameter ; harmonic responsibility ; monitoring data without phase angle ; parameter estimation ; blockchain ; energy internet ; information security ; forecasting ; clustering ; energy systems ; classification ; integrated energy system ; risk assessment ; component accident set ; vulnerability ; hybrid AC/DC power system ; stochastic optimization ; renewable energy source ; Volterra models ; wind turbine ; maintenance ; fatigue ; power control ; offshore wind farm ; Interfacial tension ; transformer oil parameters ; harmonic impedance ; traction network ; harmonic impedance identification ; linear regression model ; data evolution mechanism ; cast-resin transformers ; abnormal defects ; partial discharge ; pattern recognition ; hierarchical clustering ; decision tree ; industrial mathematics ; inverse problems ; intelligent control ; artificial intelligence ; energy management system ; smart microgrid ; optimization ; Volterra equations ; energy storage ; load leveling ; cyber-physical systems ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This Special Issue (SI) deals with different end-users’ perspectives on newly developed energy policy and technology. Although the importance of end-users’ preferences is not totally new to the energy sector, this issue needs to be urgently and consistently addressed if new policies, projects, and technologies are to be introduced successfully. The eight papers included in this SI are focused on various issues such as modeling the future energy demand, household energy consumption behavior, public perceptions of new energy technologies and projects, and ICT–energy efficiency interrelationship. Some papers also analyze end-users’ experiences with recently introduced energy technologies. Based on these eight articles with various topics, this SI will provide fruitful insights in assessing and forecasting the evolution of the future energy sector. I hope this SI can contribute to the increase in communication and cooperation among academic researchers as well as practitioners in energy fields.
    Keywords: energy demand ; CO2 emissions ; Indonesia ; households ; energy consumption ; pro-environmental behavior ; conceptual framework ; energy technology ; energy security ; public opinion ; cost-benefit analysis ; energy strategy ; improved cook stoves ; Honduras ; occupant behaviour ; socio-economic profile ; survey ; energy efficiency ; persuasion ; intervention ; pro-environmental behaviour change ; workplace ; choice experiment ; renewable energy ; willingness to accept ; multinomial logit models ; LCOE ; stochastic ; solar PV ; South Korea ; data center ; thermal characteristics analysis ; machine learning ; clustering ; unsupervised learning ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders.
    Keywords: inertial measurement units ; gait analysis ; biomedical signal processing ; pattern recognition ; step detection ; physiological signals ; Parkinson’s disease ; pathological gait ; turning analysis ; wearable sensors ; mobile gait analysis ; wearables ; inertial sensors ; traumatic brain injury ; dynamic balance ; gait disorders ; gait patterns ; head injury ; gait symmetry ; gait smoothness ; acceleration ; machine learning ; classification ; accelerometer ; GAITRite ; multi-regression normalization ; SVM ; random forest classifier ; balance ; gait ; transcranial direct current stimulation ; wearable electronics ; IMUs ; cueing ; posture ; rehabilitation ; cerebellar ataxia ; movement analysis ; personalized medicine ; stroke ; asymmetry ; trunk ; reliability ; validity ; aging ; reactive postural responses ; yaw perturbation ; kinematics ; postural stability ; dynamic posturography ; multiple sclerosis ; gait metrics ; test-retest reliability ; sampling frequency ; accelerometry ; autocorrelation ; harmonic ratio ; six-minute walk ; back school ; inertial sensor ; lower back pain ; stability ; timed up and go test ; gait assessment ; tri-axial accelerometer ; CV ; healthy subjects ; test-retest ; trajectory reconstruction ; stride segmentation ; dynamic time warping ; pedestrian dead-reckoning ; near falls ; loss of balance ; pre-impact fall detection ; activities of daily life ; bio-signals ; EEG ; EMG ; wireless sensors ; posturography ; Alzheimer’s disease ; vestibular syndrome ; diagnosis ; symptoms monitoring ; wearable ; home-monitoring ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.
    Keywords: TA1-2040 ; T1-995 ; online community ; bibliometric analysis ; KDE ; big data analytic methods ; TP organics ; skills ; topic analysis ; systematic and replicable patent analysis method ; SDE ; Guangzhou ; filtering ; point of interests (POI) ; framing ; innovation in sustainable agriculture ; researchers ; sentiment polarity classification ; illegal accommodation ; dynamic topic model ; network data analysis ; decision-making ; learning analytics ; research frontier ; prediction grades ; framings ; opinion mining ; association rule ; big data research ; Hong Kong ; place sustainability ; spatial accessibility of residential public services ; maturity model ; data science ; educational data mining ; spatiotemporal analysis ; information systems ; information diffusion ; smart citizens ; policy ; back-propagation neural network ; innovation ; social media big data ; lbsn ; GWR ; context–problem network ; Social network ; machine learning ; web science ; social good ; social sciences ; online data ; resource optimisation ; data commons ; sustainable agri-food systems ; social and humanistic computing ; product attributes ; analytics ; car review ; technology platforms ; big data ; community detection ; technopolitics ; transaction costs ; problem-solved concept ; sales prediction ; sentiment analysis ; Barcelona ; TripAdvisor ; innovation networks ; sustainability ; sustainable development ; experimental cities ; online travel review ; check-in density ; decision making ; smart cities ; GDPR ; hype cycle ; advanced business analytics ; institutional innovation ; temporal analytics ; data mining ; decision-makers ; online word-of-mouth ; knowledge management ; semantic network analysis ; sustainable wireless energy transmission technology ; housing problem ; social impact ; paradox ; early career ; Greek Attica ; text mining ; user-generated content ; social media ; big data analytics ; social networks ; sustainability development ; building stock management ; data analyst ; NodeXL ; review voting ; promising technology ; social inclusive economic growth ; destination image ; Xiamen City ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This collection of articles addresses the most modern forms of loss reserving methodology: granular models and machine learning models. New methodologies come with questions about their applicability. These questions are discussed in one article, which focuses on the relative merits of granular and machine learning models. Others illustrate applications with real-world data. The examples include neural networks, which, though well known in some disciplines, have previously been limited in the actuarial literature. This volume expands on that literature, with specific attention to their application to loss reserving. For example, one of the articles introduces the application of neural networks of the gated recurrent unit form to the actuarial literature, whereas another uses a penalized neural network. Neural networks are not the only form of machine learning, and two other papers outline applications of gradient boosting and regression trees respectively. Both articles construct loss reserves at the individual claim level so that these models resemble granular models. One of these articles provides a practical application of the model to claim watching, the action of monitoring claim development and anticipating major features. Such watching can be used as an early warning system or for other administrative purposes. Overall, this volume is an extremely useful addition to the libraries of those working at the loss reserving frontier.
    Keywords: TJ1-1570 ; TA1-2040 ; T1-995 ; n/a ; granular models ; neural networks ; actuarial ; payments per claim incurred ; risk pricing ; machine learning ; claim watching ; loss reserving ; gradient boosting ; predictive modeling ; classification and regression trees ; individual models ; individual claims reserving ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering::TDCW Pharmaceutical chemistry and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-21
    Description: A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.
    Keywords: R5-920 ; RM1-950 ; precision medicine informatics ; n/a ; drug sensitivity ; chromatin modification ; cell lines ; biocuration ; neurodegeneration ; multivariate analysis ; artificial intelligence ; epigenetics ; missing data ; sequencing ; clinical data ; class imbalance ; integrative analytics ; algorithm development for network integration ; deep phenotype ; non-omics data ; feature selection ; Gene Ontology ; miRNA–gene expression networks ; omics data ; plot visualization ; Alzheimer’s disease ; tissue classification ; epidemiological data ; proteomic analysis ; genotype ; RNA expression ; indirect effect ; multi-omics ; dementia ; multiomics integration ; data integration ; phenomics ; network topology analysis ; challenges ; transcriptome ; enrichment analysis ; regulatory genomics ; scalability ; heterogeneous data ; systemic lupus erythematosus ; database ; microtubule-associated protein tau ; disease variants ; genomics ; joint modeling ; distance correlation ; annotation ; phenotype ; direct effect ; curse of dimensionality ; gene–environment interactions ; logic forest ; machine learning ; KEGG pathways ; multivariate causal mediation ; amyloid-beta ; bioinformatics pipelines ; support vector machine ; pharmacogenomics ; candidate genes ; tissue-specific expressed genes ; cognitive impairment ; causal inference ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.
    Keywords: TA1-2040 ; T1-995 ; opinion mining ; affect computing ; health insurance ; Twitter ; hybrid vectorization ; violence against women ; word association ; collaborative schemes of sentiment analysis and sentiment systems ; random forest ; cyber-aggression ; deep learning ; online review ; emotion analysis ; lexicon construction ; provider networks ; text mining ; sentiment lexicon ; social media ; sentiment-aware word embedding ; psychographic segmentation ; medical web forum ; gender classification ; racism ; sentiment analysis ; sentiment classification ; sentiment word analysis ; social networks ; convolutional neural network ; review data mining ; machine learning ; emotion classification ; big data-driven marketing ; text feature representation ; recommender system ; user preference prediction ; violence based on sexual orientation ; semantic networks ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones.
    Keywords: wildfire ; satellite vegetation indices ; live fuel moisture ; empirical model function ; Southern California ; chaparral ecosystem ; forest fire ; forest recovery ; satellite remote sensing ; vegetation index ; burn index ; gross primary production ; South Korea ; land subsidence ; PS-InSAR ; uneven settlement ; building construction ; Beijing urban area ; floodplain delineation ; inaccessible region ; machine learning ; flash flood ; risk ; LSSVM ; China ; Himawari-8 ; threshold-based algorithm ; remote sensing ; dryness monitoring ; soil moisture ; NIR–Red spectral space ; Landsat-8 ; MODIS ; Xinjiang province of China ; SDE ; PE ; groundwater level ; compressible sediment layer ; tropical cyclone formation ; WindSat ; disaster monitoring ; wireless sensor network ; debris flow ; anomaly detection ; deep learning ; accelerometer sensor ; total precipitable water ; Himawari-8 AHI ; random forest ; deep neural network ; XGBoost ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Conventional thermal power generating plants reject a large amount of energy every year. If this rejected heat were to be used through district heating networks, given prior energy valorisation, there would be a noticeable decrease in the amount of fossil fuels imported for heating. As a consequence, benefits would be experienced in the form of an increase in energy efficiency, an improvement in energy security, and a minimisation of emitted greenhouse gases. Given that heat demand is not expected to decrease significantly in the medium term, district heating networks show the greatest potential for the development of cogeneration. Due to their cost competitiveness, flexibility in terms of the ability to use renewable energy resources (such as geothermal or solar thermal) and fossil fuels (more specifically the residual heat from combustion), and the fact that, in some cases, losses to a country/region’s energy balance can be easily integrated into district heating networks (which would not be the case in a “fully electric” future), district heating (and cooling) networks and cogeneration could become a key element for a future with greater energy security, while being more sustainable, if appropriate measures were implemented. This book therefore seeks to propose an energy strategy for a number of cities/regions/countries by proposing appropriate measures supported by detailed case studies.
    Keywords: TA1-2040 ; T1-995 ; district heating ; 4th generation district heating ; data mining algorithms ; energy system modeling ; neural networks ; baseline model ; hydronic pavement system ; biomass district heating for rural locations ; CO2 emissions abatement ; low temperature networks ; ultralow-temperature district heating ; domestic ; optimization ; energy efficiency ; sustainable energy ; big data frameworks ; verification ; energy prediction ; parameter analysis ; greenhouse gas emissions ; time delay ; heat pumps ; primary energy use ; retrofit ; energy consumption forecast ; district heating (DH) network ; low-temperature district heating ; thermal inertia ; variable-temperature district heating ; data streams analysis ; Computational Fluid Dynamics ; energy management in renovated building ; Scotland ; heat reuse ; thermally activated cooling ; district cooling ; space cooling ; Gulf Cooperation Council ; biomass ; TRNSYS ; hot climate ; optimal control ; air-conditioning ; machine learning ; low temperature district heating system ; data center ; twin-pipe ; residential ; prediction algorithm ; CFD model ; nZEB ; thermal-hydraulic performance ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling,
    Keywords: G1-922 ; Q1-390 ; nitrogen nutrition index ; n/a ; soil organic carbon ; yield estimation ; hyperspectral sensor ; crop modeling ; crop residue management ; land use change ; flat-fan atomizer ; vegetation index ; septoria tritici blotch ; crop simulation model ; temporal variability ; spectral-weight variations in fused images ; plant ; EPIC model ; large cardamom ; crop inventory ; proximal sensing ; sorghum biomass ; soil ; UAV ; Integrated Administration and Control System ; canopy temperature depression ; fractional cover ; Cropsim-CERES Wheat ; hyperspectral data ; yield ; wheat ; precision farming ; SPAD ; AquaCrop ; prediction modeling ; spectral simulation ; leaf nitrogen concentration ; machine learning ; crop production ; protein content ; Á Trous algorithm ; spatial variability ; variable rate technology ; crop type mapping ; Tarim Basin ; leaf area index ; management zone ; irrigation ; multi-spectral ; agricultural land-cover ; crop modelling ; dynamic model ; satellite images ; climate change ; control variables ; generalized model ; Sentinel-2 satellite imagery ; vegetation indices ; vegetable monitoring ; Sentinel-2 ; remote sensing ; cultivars ; crop growth model ; yield monitoring ; big data technology ; conservation agriculture ; GIS ; fAPAR ; droplet drift ; simulation analysis ; durum wheat ; hydroponic ; grain yield ; Leaf Area Index ; NDVI ; precision agriculture ; relative frequencies ; soil stoichiometry ; habitat assessment ; data assimilation ; satellite ; species modelling ; ?13C ; disease ; nitrogen ; yield mapping ; UAV chemical application ; RGB images ; decision support system for agrotechnology transfer (DSSAT) ; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.
    Keywords: TP248.13-248.65 ; T1-995 ; cancer treatment ; extreme learning ; independent prognostic power ; AID/APOBEC ; HP ; gene inactivation biomarkers ; biomarker discovery ; chemotherapy ; artificial intelligence ; epigenetics ; comorbidity score ; denoising autoencoders ; protein ; single-biomarkers ; gene signature extraction ; high-throughput analysis ; concatenated deep feature ; feature selection ; differential gene expression analysis ; colorectal cancer ; ovarian cancer ; multiple-biomarkers ; gefitinib ; cancer biomarkers ; classification ; cancer biomarker ; mutation ; hierarchical clustering analysis ; HNSCC ; cell-free DNA ; network analysis ; drug resistance ; hTERT ; variable selection ; KRAS mutation ; single-cell sequencing ; network target ; skin cutaneous melanoma ; telomeres ; Neoantigen Prediction ; datasets ; clinical/environmental factors ; StAR ; PD-L1 ; miRNA ; circulating tumor DNA (ctDNA) ; false discovery rate ; predictive model ; Computational Immunology ; brain metastases ; observed survival interval ; next generation sequencing ; brain ; machine learning ; cancer prognosis ; copy number aberration ; mutable motif ; steroidogenic enzymes ; tumor ; mortality ; tumor microenvironment ; somatic mutation ; transcriptional signatures ; omics profiles ; mitochondrial metabolism ; Bufadienolide-like chemicals ; cancer-related pathways ; intratumor heterogeneity ; estrogen ; locoregionally advanced ; RNA ; feature extraction and interpretation ; treatment de-escalation ; activation induced deaminase ; knockoffs ; R package ; copy number variation ; gene loss biomarkers ; cancer CRISPR ; overall survival ; histopathological imaging ; self-organizing map ; Network Analysis ; oral cancer ; biostatistics ; firehose ; Bioinformatics tool ; alternative splicing ; biomarkers ; diseases genes ; histopathological imaging features ; imaging ; TCGA ; decision support systems ; The Cancer Genome Atlas ; molecular subtypes ; molecular mechanism ; omics ; curative surgery ; network pharmacology ; methylation ; bioinformatics ; neurological disorders ; precision medicine ; cancer modeling ; miRNAs ; breast cancer detection ; functional analysis ; biomarker signature ; anti-cancer ; hormone sensitive cancers ; deep learning ; DNA sequence profile ; pancreatic cancer ; telomerase ; Monte Carlo ; mixture of normal distributions ; survival analysis ; tumor infiltrating lymphocytes ; curation ; pathophysiology ; GEO DataSets ; head and neck cancer ; gene expression analysis ; erlotinib ; meta-analysis ; traditional Chinese medicine ; breast cancer ; TCGA mining ; breast cancer prognosis ; microarray ; DNA ; interaction ; health strengthening herb ; cancer ; genomic instability ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
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  • 40
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue presents the latest state-of-the-art research on solid fuels technology with dedicated, focused research papers. There are a variety of topics to choose from among the seven published re-search works to bring you up to date with the current trends in academia and industry.
    Keywords: peak shaving ; battery storage ; peak demand pricing ; lithium-ion ; tariff structure ; receiving-end system ; multi-infeed HVDCs ; security assessment ; emergency control strategy ; electromagnetic transient (EMT)-transient stability (TS) hybrid simulation ; impedance determination ; lossy compression algorithms ; singular value decomposition ; wavelet transformation ; voltage control ; deep deterministic policy gradient ; deep reinforcement learning ; model uncertainties ; energy communities ; machine learning ; forecasting ; abnormal data ; wind power ; outliers ; electricity consumption representative profiles ; self-consumption ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 41
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-01
    Description: This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal.
    Keywords: eHealth ; wearable ; monitoring ; services ; integration ; IoT ; Telemedicine ; wearable sensors ; multivariate analysis ; longitudinal study ; functional decline ; exercise intervention ; accidental falls ; fall detection ; real-world ; signal analysis ; performance measures ; non-wearable sensors ; accelerometers ; cameras ; machine learning ; smart textiles ; healthcare ; talking detection ; activity recognition and monitoring ; patient health and state monitoring ; wearable sensing ; orientation-invariant sensing ; motion sensors ; accelerometer ; gyroscope ; magnetometer ; pattern classification ; artificial intelligence ; supervised machine learning ; predictive analytics ; hemodialysis ; non-contact sensor ; heart rate ; respiration rate ; heart rate variability ; time-domain features ; frequency-domain features ; principal component analysis ; behaviour analysis ; classifier efficiency ; personal risk detection ; one-class classification ; actigraphy ; encoding ; data compression ; denoising ; edge computing ; signal processing ; wearables ; activity monitoring ; citizen science ; cluster analysis ; physical activity ; sedentary behavior ; walking ; energy expenditure ; wearable device ; impedance pneumography ; neural network ; mechanocardiogram (MCG) ; smart clothes ; heart failure (HF) ; left ventricular ejection fraction (LVEF) ; technology acceptance model (TAM) ; physical activity classification ; free-living ; GENEactiv accelerometer ; Gaussian mixture model ; hidden Markov model ; wavelets ; skill assessment ; deep learning ; LSTM ; state space model ; probabilistic inference ; latent features ; human activity recognition ; MIMU ; genetic algorithm ; feature selection ; classifier optimization ; bispectrum ; entropy ; feature extraction ; heat stroke ; filtering algorithm ; physiological parameters ; exercise experiment ; biomedical signal processing ; wearable biomedical sensors ; wireless sensor network ; respiratory monitoring ; optoelectronic plethysmography ; biofeedback ; biomedical technology ; exercise therapy ; orthopedics ; mobile health ; qualitative ; human factors ; inertial measurement unit ; disease prevention ; occupational healthcare ; P-Ergonomics ; precision ergonomics ; musculoskeletal disorders ; wellbeing at work ; electrocardiogram ; conductive gels ; noncontact electrode ; myocardial ischemia ; pacemaker ; ventricular premature contraction ; upper extremity ; motion ; action research arm test ; activities of daily living ; IoT wearable monitor ; health ; posture analysis ; spinal posture ; wearable sensor ; embedded system ; recurrent neural networks ; physical workload ; wearable systems for healthcare ; machine learning for real-time applications ; actigraph ; body worn sensors ; clothing sensors ; cross correlation analysis ; healthcare movement sensing ; wearable devices ; calibration ; inertial measurement units ; human movement ; physical activity type ; real-life ; GPS ; GIS ; n/a ; thema EDItEUR::N History and Archaeology::NH History ; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues
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  • 42
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Sensors are the eyes or/and ears of an intelligent system, such as UAV, AGV and robots. With the development of material, signal processing, and multidisciplinary interactions, more and more smart sensors are proposed and fabricated under increasing demands for homes, the industry, and military fields. Networks of sensors will be able to enhance the ability to obtain huge amounts of information (big data) and improve precision, which also mirrors the developmental tendency of modern sensors. Moreover, artificial intelligence is a novel impetus for sensors and networks, which gets sensors to learn and think and feed more efficient results back. This book includes new research results from academia and industry, on the subject of “Smart Sensors and Networks”, especially sensing technologies utilizing Artificial Intelligence. The topics include: smart sensors biosensors sensor network sensor data fusion artificial intelligence deep learning mechatronics devices for sensors applications of sensors for robotics and mechatronics devices
    Keywords: microelectromechanical systems ; inertial measurement unit ; long short term memory recurrent neural networks ; artificial intelligence ; deep learning ; CNN ; LSTM ; CO2 welding ; molten pool ; online monitoring ; mechanical sensor ; self-adaptiveness ; ankle-foot exoskeleton ; walking assistance ; visual tracking ; correlation filter ; color histogram ; adaptive hedge algorithm ; scenario generation ; autonomous vehicle ; smart sensor and device ; wireless sensor networks ; task assignment ; distributed ; reliable ; energy-efficient ; audification ; sensor ; visualization ; speech to text ; text to speech ; HF-OTH radar ; AIS ; radar tracking ; data fusion ; fuzzy functional dependencies ; maritime surveillance ; surgical robot end-effector ; clamping force estimation ; joint torque disturbance observer ; PSO-BPNN ; cable tension measurement ; queue length ; roadside sensor ; vehicle detection ; adverse weather ; roadside LiDAR ; data processing ; air pollution ; atmospheric data ; IoT ; machine learning ; RNN ; Sensors ; smart cities ; traffic flow ; traffic forecasting ; wireless sensor network ; fruit condition monitoring ; artificial neural network ; ethylene gas ; banana ripening ; unidimensional ACGAN ; signal recognition ; data augmentation ; link establishment behaviors ; DenseNet ; short-wave radio station ; landing gear ; adaptive landing ; vehicle classification ; FBG ; smart sensors ; outlier detection ; local outlier factor ; data streams ; air quality monitoring ; n/a ; evacuation path ; multi-story multi-exit building ; temperature sensors ; multi-time-slots planning ; optimization ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 43
    Publication Date: 2024-03-30
    Description: Advances in Peptide and Peptidomimetic Design Inspiring Basic Science and Drug Discovery is a book dedicated to Prof. Victor J. Hruby on the occasion of his 80th birthday. This book includes twenty contributions from authors representing diverse multidisciplinary fields of scientific expertise, and is focused on the extraordinary potential of peptides and peptidomimetics as a surging therapeutic modality and as tools for basic research and technology development.
    Keywords: R5-920 ; RM1-950 ; fusogenic ; small molecule ; cancer vaccine ; peptide-drug conjugate ; protein–protein interaction ; anticancer peptide ; tetrapeptides ; drug discovery ; ginkgo nuts ; prostaglandin F2? ; macrocyclic peptide ; melanocortins ; Toll-like receptor ; polo-box domain ; endosomolytic ; structure-activity ; free energy calculation ; peptide ; autophagy ; synthetic vaccine ; small antimicrobial peptides ; azapeptides ; classification ; multifunctional ligands ; cytoprotective ; polycationic -amino acids ; N-acetylated Pam2Cys ; Pam2Cys ; disulfide-rich scaffold ; d-amino acid scan ; VEGF165 ; antibiotics ; hyperdisulfide ; peptides ; random forest ; pseudosubstrate ; influenza hemagglutinin ; Ranalexin ; ?-ginkgotide ; LIR motif ; bioconjugation ; peptide agonist ; GnRH ; molecular rotor dye ; sensor chip ; helix-breaker ; Plk1 ; antimicrobial activity ; molecular dynamics ; machine learning ; melanocortin-4 receptor ; kinase inhibitor ; support vector machine ; D-amino acid ; drug screen ; receptor desensitization ; diabetes ; opioids ; selectivity ; IP20 ; aza-amino acids ; bis-benzamide scaffold ; G?S signaling ; chemical linker ; MC4R ; LHRH ; ?-hairpin ; androgen receptor ; adjuvant ; high throughput screening ; receptor internalization ; peptide design ; ?-helix mimetics ; adaptogenic ; obesity ; cardiovascular profile ; hypoxia ; programmed cell death ligand protein 1 ; PKA ; neuropilin-1 ; preterm labor ; ?-sheet ; PKI ; MC3R ; myometrium contractions ; amphiphilic ; structure–activity relationship ; peptidomimetics ; combinatorial chemistry ; sepsis ; coactivator PELP1 ; OBOC ; mixed-mode pharmacology ; configuration ; peptide permeability ; triazole ; stapled peptide ; cysteine-rich peptides ; GLP-1 ; RBC lysis ; mixed pharmacology ; therapeutic peptides ; opioid ; peptidomimetic ; prostate cancer ; alanine scan ; lipidation ; peptide therapeutics ; cancer ; pharmacophore
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  • 44
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Rheology, defined as the science of deformation and flow of matter, is a multidisciplinary scientific field, covering both fundamental and applied approaches. The study of rheology includes both experimental and computational methods, which are not mutually exclusive. Its practical importance embraces many processes, from daily life, like preparing mayonnaise or spreading an ointment or shampooing, to industrial processes like polymer processing and oil extraction, among several others. Practical applications include also formulations and product development. Following a successful first volume, we are now launching this second volume to continue to present the latest advances in the fields of experimental and computational rheology applied to the most diverse classes of materials (foods, cosmetics, pharmaceuticals, polymers and biopolymers, multiphasic systems, and composites) and processes.
    Keywords: graphene oxide ; polyethylene glycol ; rheological characterization ; human milk ; tube feeding ; breastfeeding ; viscosity ; complex modulus ; density ; rheological measurements ; non-viscometric geometries ; Couette analogy ; shear thinning fluids ; suspensions ; bread ; whey ; complex fluids ; experimental rheology ; breadmaking ; yield stress ; grout ; polypropylene fiber ; masonry ; consolidation ; rheology ; drop impact ; elasto-viscoplastic material ; free surface ; gravitational effects ; MRSA ; S. aureus ; antibiotics ; oxacillin ; bactericidal ; injection molding ; filling stage ; Cross-WLF model ; Tait model ; finite volume method ; openInjMoldSim ; OpenFOAM® ; Boger fluids ; circular contraction flow ; lip vortex ; pressure-drops ; vortex-enhancement ; first normal-stress difference ; swIM model ; reactive extrusion ; data-driven ; machine learning ; artificial engineering ; polymer processing ; digital twin ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 45
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: We are immersed in the so-called digital energy network, continuously introducing new technological advances for a better way of life. Numerous emerging words are in the spotlight, namely: Internet of Things (IoT), Big Data, Smart Cities, Smart Grid, Industry 4.0, etc. To achieve this formidable goal, systems should work more efficiently, and this fact inevitably leads to power quality (PQ) assurance. Apart from its economic losses, a bad PQ implies serious risks for machines, and consequently for people. Many researchers are endeavoring to develop new analysis techniques, instruments, measurement methods, and new indices and norms that match and fulfil the requirements regarding the current operation of the electrical network. This book offers a compilation of the some recent advances in this field. The chapters range from computing issues to technological implementations, going through event detection strategies and new indices and measurement methods that contribute significantly to the advancement of PQ analysis. Experiments have been developed within the frames of research units and projects, and deal with real data from industry and public buildings. Human beings have an unavoidable commitment with sustainability, which implies adapting PQ monitoring techniques to our dynamic world, defining a digital and smart concept of quality for electricity.
    Keywords: TA1-2040 ; T1-995 ; modulation ; FPGA ; flicker ; DC power quality indices ; limited resources hardware ; low cost monitor ; dynamic phasor estimation ; harmonics ; RMS voltage estimation ; islanding operation ; embedded system ; signal waveform compression ; big data ; digital signal processing ; data scalability ; data compression ; wind-grid distribution ; voltage fluctuations ; smart grid (SG) applications ; power event detection ; modelling ; voltage ripple ; power quality monitoring ; higher-order statistics (HOS) ; power distribution systems ; power quality disturbances ; reconfigurable computing ; operation analysis ; sensor node ; power quality (PQ) ; distribution networks ; wireless sensor network ; reliability ; power system measurements ; embedded microcontroller ; phasor measurement units ; IoT ; soft computing ; smart grids ; power quality monitor ; induction machines ; sensors and instruments for PQ ; Kalman filters ; low-voltage DC networks ; convolution neural network ; spectral kurtosis ; municipal distribution network ; statistical signal processing ; detection ; power quality disturbance ; smart grid ; energizing warning ; dense-mesh topology ; low computational cost ; fourth-order statistics ; PQ indices and thresholds ; machine learning ; voltage sags ; power quality ; computational solutions for advanced metering infrastructure (AMI) ; constant amplitude trend ; phasor measurement ; improved principal component analysis ; long-term ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 46
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-20
    Description: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
    Keywords: QA75.5-76.95 ; T58.5-58.64 ; metadata ; image classification ; sensitivity analysis ; ROI detection ; residual learning ; image alignment ; adaptive convolutional kernels ; Hough transform ; class imbalance ; land surface temperature ; inundation mapping ; multiscale representation ; object-based ; convolutional neural networks ; scene classification ; morphological profiles ; hyperedge weight estimation ; hyperparameter sparse representation ; semantic segmentation ; vehicle classification ; flood ; Landsat imagery ; target detection ; multi-sensor ; building damage detection ; optimized kernel minimum noise fraction (OKMNF) ; sea-land segmentation ; nonlinear classification ; land use ; SAR imagery ; anti-noise transfer network ; sub-pixel change detection ; Radon transform ; segmentation ; remote sensing image retrieval ; TensorFlow ; convolutional neural network ; particle swarm optimization ; optical sensors ; machine learning ; mixed pixel ; optical remotely sensed images ; object-based image analysis ; very high resolution images ; single stream optimization ; ship detection ; ice concentration ; online learning ; manifold ranking ; dictionary learning ; urban surface water extraction ; saliency detection ; spatial attraction model (SAM) ; quality assessment ; Fuzzy-GA decision making system ; land cover change ; multi-view canonical correlation analysis ensemble ; land cover ; semantic labeling ; sparse representation ; dimensionality expansion ; speckle filters ; hyperspectral imagery ; fully convolutional network ; infrared image ; Siamese neural network ; Random Forests (RF) ; feature matching ; color matching ; geostationary satellite remote sensing image ; change feature analysis ; road detection ; deep learning ; aerial images ; image segmentation ; aerial image ; multi-sensor image matching ; HJ-1A/B CCD ; endmember extraction ; high resolution ; multi-scale clustering ; heterogeneous domain adaptation ; hard classification ; regional land cover ; hypergraph learning ; automatic cluster number determination ; dilated convolution ; MSER ; semi-supervised learning ; gate ; Synthetic Aperture Radar (SAR) ; downscaling ; conditional random fields ; urban heat island ; hyperspectral image ; remote sensing image correction ; skip connection ; ISPRS ; spatial distribution ; geo-referencing ; Support Vector Machine (SVM) ; very high resolution (VHR) satellite image ; classification ; ensemble learning ; synthetic aperture radar ; conservation ; convolutional neural network (CNN) ; THEOS ; visible light and infrared integrated camera ; vehicle localization ; structured sparsity ; texture analysis ; DSFATN ; CNN ; image registration ; UAV ; unsupervised classification ; SVMs ; SAR image ; fuzzy neural network ; dimensionality reduction ; GeoEye-1 ; feature extraction ; sub-pixel ; energy distribution optimizing ; saliency analysis ; deep convolutional neural networks ; sparse and low-rank graph ; hyperspectral remote sensing ; tensor low-rank approximation ; optimal transport ; SELF ; spatiotemporal context learning ; Modest AdaBoost ; topic modelling ; multi-seasonal ; Segment-Tree Filtering ; locality information ; GF-4 PMS ; image fusion ; wavelet transform ; hashing ; machine learning techniques ; satellite images ; climate change ; road segmentation ; remote sensing ; tensor sparse decomposition ; Convolutional Neural Network (CNN) ; multi-task learning ; deep salient feature ; speckle ; canonical correlation weighted voting ; fully convolutional network (FCN) ; despeckling ; multispectral imagery ; ratio images ; linear spectral unmixing ; hyperspectral image classification ; multispectral images ; high resolution image ; multi-objective ; convolution neural network ; transfer learning ; 1-dimensional (1-D) ; threshold stability ; Landsat ; kernel method ; phase congruency ; subpixel mapping (SPM) ; tensor ; MODIS ; GSHHG database ; compressive sensing ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-05
    Keywords: QD1-999 ; Q1-390 ; QD450-801 ; information theoretic analysis ; multiplexing system ; HSI for biology ; point target detection ; digital elevation model ; neural networks ; oxygen saturation ; black polymers ; PZT ; blood detection ; multivariate analysis ; integral imaging ; hemispherical conical reflectance factor (HCRF) ; sprouting ; fluorescence ; multitemporal hyperspectral images ; plant phenotyping ; hyperspectral data mining and compression ; Raman ; medical imaging by HSI ; compressive detection ; stereo imaging ; image processing ; wound healing ; quality control ; lossless compression ; infrared hyperspectral imaging ; spectral tracking ; time series ; remote sensing ; diabetic foot ulcer ; classification ; Raman spectroscopy ; imaging ; fingerprints ; fusion ; wavelength selection ; Cramer–Rao lower bound ; three-dimensional imaging ; chemical imaging ; CS-MUSI ; total variation ; coastal dynamics ; forward observation model ; hyperspectral imaging ; fluorescence hyperspectral imaging ; age determination ; potatoes ; painting samples ; predictive coding ; hyperspectral ; video ; bi-directional reflectance distribution function (BRDF) ; optimal binary filters ; watercolours ; deep learning ; spectroscopy ; moving vehicle imaging ; sorting ; maximum likelihood ; multivariate data analysis ; interval partial least squares ; disease detection ; Raman hyperspectral imaging ; primordial leaf count ; machine learning ; spatial light modulators (SLM) ; Virginia Coast Reserve Long Term Ecological Research (VCR LTER) ; digital micromirror device (DMD) ; hyperspectral microscopy ; alternating direction method of multipliers ; statistical methods for HSI ; multiband image fusion ; digital light processor (DLP) ; linear mixture model ; retouching pigments ; liquid crystal ; principal component analysis ; Chemometrics ; compressive sensing ; PLSR ; Hyperspectral imaging ; thema EDItEUR::P Mathematics and Science::PN Chemistry
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  • 48
    Publication Date: 2024-04-11
    Description: The content of this Special Issue will highlight papers exploring non-commutative Fourier harmonic analysis, spectral properties of aperiodic order, the hypoelliptic heat equation, and the relativistic heat equation in the context of Information Theory and Geometric Science of Information.
    Keywords: TA1-2040 ; T1-995 ; glucose-dependent dielectric properties ; bioradar ; dielectric measurements ; dielectric spectroscopy ; snare ; RF sensing ; microwave breast imaging ; stress detection ; microwave resonators ; dielectric properties ; equipment-related confounders ; EMR ; monitoring ; phantom ; tissue-related confounders ; microwave imaging ; automated breast diagnosis ; breast cancer detection ; dielectric characterization ; blood glucose levels ; breast cancer diagnosis ; numerical calculation ; breast phantoms ; tomography ; image-guided ; on-site validation ; microwave tomography ; microwave ; non-invasive measurement ; on-body antennas ; psychophysiological state monitoring ; thermal ablation ; microwave ablation ; biological tissues ; breast cancer ; open-ended coaxial probe ; brain stroke monitoring ; machine learning ; patient study ; UWB diagnostics ; reconstruction ; medical radar ; unobtrusive monitoring ; medical imaging ; microwave spectroscopy ; UWB breast and head phantoms ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book focuses on the intelligent processing of images and optical information acquired by various imaging methods. Intelligent image and optical information processing have paved the way for the recent epoch of new intelligence and information era. Certainly, information acquired by various imaging techniques is of tremendous value; thus, an intelligent analysis of them is necessary to make the best use of it. A broad range of research fields is included in this book. Many studies focus on object classification and detection. Registration, segmentation, and fusion are performed between a series of images. Many valuable and up-to-most recent technologies are provided to solve the real problems in selected papers.
    Keywords: change detection ; NSCT ; variogram function ; structure similarity ; Dongting Lake ; ego-motion estimation ; hand-eye calibration ; IMU ; lidar odometry ; sensor fusion ; texture classification ; Gabor filter ; parameter optimization ; feature selection ; hybrid ant lion optimizer ; wireless multimedia sensor networks ; wildlife monitoring image ; extraction ; Hermite ; adaptive mean-shift ; biomedical imaging ; bone fracture ; calcaneus ; CT image ; segmentation ; zebrafish egg ; microscopy image processing ; convolutional neural network ; digital image correlation ; high-temperature measurement ; heat waves ; thermal disturbance ; background-oriented schlieren ; fermentation monitoring ; quality inspection ; process automation ; deep learning ; superellipsoid model fitting ; optical sensor ; multi-sensor ; face registration ; inner-distance ; Student’s-t Mixtures Model ; image fusion ; continuous casting slabs ; surface defect classification ; discrete non-separable shearlet transform ; gray-level co-occurrence matrix ; kernel spectral regression ; block compressed sensing ; error resilience ; reconstruction ; image completion ; tensor decomposition models ; image interpolation ; image up-scaling ; numerical optimization ; ADAM ; machine learning ; stochastic gradient methods ; healthy and infected lemons ; Hyperspectral image ; Penicillium digitatum pathogen ; lemon skin ; dominant spectral wavelength ; spectral intensity ratio ; zebrafish larva ; microscopy image analysis ; deep neural network ; clustering evaluation ; clustering algorithm ; cluster validity index ; boundary point ; interior point ; radiographic image ; image processing ; feature extraction ; classifier ; defect detection ; generative models ; GAN (Generative adversarial networks) ; facial image ; generation ; database augmentation ; synthesis ; autofocus ; night vision goggles ; sparse and low-rank matrix decomposition ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 50
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-23
    Description: The book is addressed to architects and civil engineers. Design and research are areas connecting their activities. The contents of the book confirm the fact that the interface between architecture and engineering is multidimensional. The ways of finding points of contact between the two industries are highlighted. This is favored by the dynamically changing reality, supported by new design paradigms and new research techniques. The multithreaded subject matter of the articles is reduced to six sections: Research Scopes, Methods, Design Aspects, Context, Nature of Research, and Economy and Cost Calculation. Each of the articles in these six blocks has its weight. And so, in the Nature of Research section, the following areas have been underscored: laboratory tests, in situ research, field investigations, and street perception experiments. The section Design Aspects includes design-oriented thinking, geometrical forms, location of buildings, cost prediction, attractor and distractor elements, and shaping spatial structures. The new design and research tools are an inspiration and a keystone bonding architects and engineers.
    Keywords: high-rise buildings ; development ; geometrical forms ; structural system ; advanced materials ; damping systems ; sustainability ; sustainable smart city ; architect ; image of the city ; participatory design ; body of the building ; facades ; roofs ; built environment ; design thinking method ; multi-criteria decision-making ; multi-criteria decision analysis ; fuzzy AHP ; sustainable development ; design solutions ; concrete performance ; concrete durability ; EIPI method ; waste copper slag ; natural radioactivity ; cost estimates ; construction costs ; bridge construction projects ; machine learning ; support vector machines ; regression ; technical condition ; performance characteristics ; prediction ; degree of wear ; building information modeling ; BIM ; construction management ; SWOT ; eye tracking ; visual perception ; the architecture of Cologne ; case study ; application in architecture and management ; assembly works ; computer planning ; Monte Carlo method ; selection ; construction ; application ; a curvilinear structure ; a hyperbolic paraboloid ; shaping structures ; structural optimization ; parametric design ; genetic algorithms ; multi-objective optimization ; topology ; Grasshopper ; FEM ; steel trusses ; semi-rigid joints ; RHS braces ; H-section chords ; overlapped joints ; resistance of welds ; Kraków Zabłocie ; Podolski Boulevard ; development of riverside embankment ; downtown riverside areas ; urban local centre ; community ; historical context ; multifunctional complex ; living environment quality ; spatial location conditions ; air pollution ; urban ventilation ; EU subsidies targeting environmental quality improvement ; masonry structures ; stiffening walls ; wall joints ; connectors ; bed joint reinforcement ; design for circularity ; design support tools ; circular construction ; circular economy ; architecture ; architectural design ; photovoltaic modules in architecture ; green building ; benefits of BIM ; public construction clients ; project outcomes ; engineering ; design paradigms ; research methods ; circular building ; spatial structures ; design-oriented thinking ; MCDM ; SVM ; thema EDItEUR::A The Arts ; thema EDItEUR::A The Arts::AM Architecture
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  • 51
    Publication Date: 2024-04-11
    Description: This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.
    Keywords: TA1-2040 ; T1-995 ; faster region-based CNN ; visual tracking ; intelligent tire manufacturing ; eye-tracking device ; neural networks ; A* ; information measure ; oral evaluation ; GSA-BP ; tire quality assessment ; humidity sensor ; rigid body kinematics ; intelligent surveillance ; residual networks ; imaging confocal microscope ; update mechanism ; multiple linear regression ; geometric errors correction ; data partition ; Imaging Confocal Microscope ; image inpainting ; lateral stage errors ; dot grid target ; K-means clustering ; unsupervised learning ; recommender system ; underground mines ; digital shearography ; optimization techniques ; saliency information ; gated recurrent unit ; multivariate time series forecasting ; multivariate temporal convolutional network ; foreign object ; data fusion ; update occasion ; generative adversarial network ; CNN ; compressed sensing ; background model ; image compression ; supervised learning ; geometric errors ; UAV ; nonlinear optimization ; reinforcement learning ; convolutional network ; neuro-fuzzy systems ; deep learning ; image restoration ; neural audio caption ; hyperspectral image classification ; neighborhood noise reduction ; GA ; MCM uncertainty evaluation ; binary classification ; content reconstruction ; kinematic modelling ; long short-term memory ; transfer learning ; network layer contribution ; instance segmentation ; smart grid ; unmanned aerial vehicle ; forecasting ; trajectory planning ; discrete wavelet transform ; machine learning ; computational intelligence ; tire bubble defects ; offshore wind ; multiple constraints ; human computer interaction ; Least Squares method ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 52
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The Special Issue entitled “Remote Sensing in Vessel Detection and Navigation” comprises 15 articles on many topics related to remote sensing with navigational sensors. The sequence of articles included in this Special Issue is in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used. It can be said that navigation and vessel detection remain important and hot topics, and a lot of work will continue to be done worldwide. New techniques and methods for analyzing and extracting information from navigational sensors and data have been proposed and verified. Some of these will spark further research, and some are already mature and can be considered for industrial implementation and development.
    Keywords: autonomous navigation ; automatic radar plotting aid ; safe objects control ; game theory ; computer simulation ; Sentinel-2 ; multispectral ; temporal offsets ; ship ; aircraft ; velocity ; altitude ; parallax ; jet stream ; Unmanned Surface Vessel (USV) ; multi-Global Navigation Satellite System (GNSS) receiver ; bathymetric measurements ; cross track error (XTE) ; SSL ; six-degrees-of-freedom motion ; motion attitude model ; edge detection ; straight-line fitting ; visual saliency ; vessel detection ; video monitoring ; inland waterway ; real-time detection ; neural network ; target recognition ; HRRP ; residual structure ; loss function ; trajectory tracking ; unmanned surface vehicle ; navigation ; bathymetry ; hydrographic survey ; real-time communication ; maritime situational awareness ; ship detection ; Iridium ; on-board ; image processing ; flight campaign ; position estimation ; ranging mode ; single shore station ; AIS ; bag-of-words mechanism ; machine learning ; image analysis ; ship classification ; marine system ; river monitoring system ; feature extraction ; synthetic aperture radar (SAR) ship detection ; multi-stage rotational region based network (MSR2N) ; rotated anchor generation ; multi-stage rotational detection network (MSRDN) ; convolutional neural network (CNN) ; synthetic aperture radar (SAR) ; multiscale and small ship detection ; complex background ; false alarm ; farbon dioxide peaks ; midwave infrared ; FTIR ; adaptive stochastic resonance (ASR) ; matched intrawell response ; nonlinear filter ; line enhancer ; autonomous underwater vehicles (AUVs) ; target tracking ; group targets ; GLMB ; structure ; formation ; remote sensing ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; swarm-robotics ; drag-based system ; PID algorithm ; human–robot interaction ; behaviour dynamics ; state constraints ; fair optimisation ; micro mobile robot ; robot ; actuators ; high-gain observer ; turning model LIP ; space robot ; manipulation action sequences ; subgoal graphs ; remotely operated vehicle ; constrained motion ; joint limit avoidance ; curvilinear obstacle ; rehabilitation system ; stability criterion ; system design ; quad-tilt rotor ; iterative learning ; spiral curve ; cable detection ; SEA ; douglas–peuker polygonal approximation ; predictable trajectory planning ; ATEX ; obstacle avoidance system ; kinematic singularity ; collision avoidance ; biologically-inspired ; jumping robot ; differential wheeled robot ; design and modeling ; control efficacy ; robotics ; extremum-seeking ; object-oriented ; non-holonomic mobile robot ; magneto-rheological fluids ; rendezvous consensus ; altitude controller ; master-slave ; switching control ; deep reinforcement learning ; mechanism ; expansion logic strategy ; negative buoyancy ; action generation ; radial basis function neural networks ; unmanned aerial vehicles ; extend procedure ; glass façade cleaning robot ; convolutional neural network ; climbing robot ; micro air vehicle ; car-like kinematics ; variable speed ; machine learning ; dynamical model ; transportation ; geodesic ; unmanned surface vessel ; medical devices ; stopper ; extended state observer (ESO) ; high efficiency ; object mapping ; multi-objective optimization ; hybrid robot ; robot learning ; auto-tuning ; cable disturbance modeling ; manipulation planning ; pesticide application ; high-speed target ; sparse pose adjustment (SPA) ; service robot ; lumped parameter method ; Geometric Algebra ; dynamic coupling analysis ; Thau observer ; tri-tilt-rotor ; industrial robotic manipulator ; hardware-in-the-loop simulation ; robotic drilling ; muscle activities ; small size ; chameleon ; continuous hopping ; wall climbing robot ; hover mode ; 3D-SLAM ; curvature constraints ; PSO ; drilling end-effector ; Rodrigues parameters ; gait adaptation ; static environments ; position/force cooperative control ; snake-like robot ; shape-fitting ; powered exoskeleton ; input saturation ; kinematic identification ; methane ; human–machine interactive navigation ; q-learning ; path following ; hopping robot ; mobile manipulation ; high step-up ratio ; actuatorless ; monocular vision ; stability analysis ; compact driving unit ; snake robot ; non-holonomic robot ; curvature constraint ; phase-shifting ; dialytic elimination ; gesture recognition ; snake robots ; series elastic actuator ; flapping ; servo valve ; motion camouflage control ; biomimetic robot ; minimally invasive surgery robot ; centralized architecture ; trajectory planning ; computing time ; adaptive control law ; kinematics ; facial and gender recognition ; single actuator ; victim-detection ; shape memory alloys ; undiscovered sensor values ; discomfort ; Differential Evolution ; numerical evaluation ; quadruped robot ; coverage path planning ; localization ; MPC ; n/a ; fault diagnosis ; neural networks ; disturbance-rejection control ; sample gathering problem ; cart ; bio-inspired robot ; opposite angle-based exact cell decomposition ; optimization ; safety ; goal exchange ; hierarchical planning ; ocean current ; robot motion ; nonlinear differentiator ; mapping ; finite-time currents observer ; Newton iteration ; inverse kinematics ; deposition uniformity ; spatial pyramid pooling ; hierarchical path planning ; end effector ; head-raising ; fault recovery ; LOS ; path tracking ; non-inertial reference frame ; step climbing ; obstacle avoidance ; sliding mode control ; symmetrical adaptive variable impedance ; lane change ; quadcopter UAV ; singularity analysis ; biped mechanism ; fault-tolerant control ; dynamic neural networks ; mobile robots ; data association ; UAV ; enemy avoidance ; reinforcement learning ; grip optimization ; safety recovery mechanism ; exoskeleton ; dynamic environment ; uncertain environments ; hybrid bionic robot ; potential field ; robot navigation ; cleaning robot ; unmanned aerial vehicle ; non-singular fast-terminal sliding-mode control ; contact planning ; Lyapunov-like function ; piezoelectric actuator ; transition mode ; non-prehensile manipulation ; multiple mobile robots ; Tetris-inspired ; real-time action recognition ; integral line-of-sight ; topological map ; alpine ski ; target tracking ; closed-loop detection ; working efficiency ; mathematical modeling ; curve fitting ; force control ; biped robots ; NSGA-II ; mobile robot ; load carriage ; prescription map translation ; artificial fish swarm algorithm ; Q-networks ; self-reconfigurable robot ; G3-continuity ; autonomous vehicle ; loop closure detection ; excellent driver model ; robots ; graph representation ; regional growth ; target assignment ; evolutionary operators ; intelligent mobile robot ; motion sensor ; exploration ; droplets penetrability ; dynamic uncertainty ; simultaneous localization and mapping (SLAM) ; area decomposition ; multi-criteria decision making ; 4WS4WD vehicle ; biped climbing robots ; skiing robot ; ROS ; decision making ; smart materials ; centrifugal force ; missile control system ; formation of robots ; electro-rheological fluids ; pneumatics ; variable spray ; inertial measurement unit (IMU) ; Robot Operating System ; trajectory interpolation ; formation control ; immersion and invariance ; dragonfly ; parallel navigation ; harmonic potential field ; pallet transportation ; mobile robot navigation ; negative-buoyancy ; grip planning ; manipulator ; position control ; external disturbance ; legged robot ; passive skiing turn ; autonomous underwater vehicle (AUV) ; gait cycle ; path planning ; sliding mode observer ; dynamic gait ; self-learning ; polyomino tiling theory ; coalmine ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 54
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; swarm-robotics ; drag-based system ; PID algorithm ; human–robot interaction ; behaviour dynamics ; state constraints ; fair optimisation ; micro mobile robot ; robot ; actuators ; high-gain observer ; turning model LIP ; space robot ; manipulation action sequences ; subgoal graphs ; remotely operated vehicle ; constrained motion ; joint limit avoidance ; curvilinear obstacle ; rehabilitation system ; stability criterion ; system design ; quad-tilt rotor ; iterative learning ; spiral curve ; cable detection ; SEA ; douglas–peuker polygonal approximation ; predictable trajectory planning ; ATEX ; obstacle avoidance system ; kinematic singularity ; collision avoidance ; biologically-inspired ; jumping robot ; differential wheeled robot ; design and modeling ; control efficacy ; robotics ; extremum-seeking ; object-oriented ; non-holonomic mobile robot ; magneto-rheological fluids ; rendezvous consensus ; altitude controller ; master-slave ; switching control ; deep reinforcement learning ; mechanism ; expansion logic strategy ; negative buoyancy ; action generation ; radial basis function neural networks ; unmanned aerial vehicles ; extend procedure ; glass façade cleaning robot ; convolutional neural network ; climbing robot ; micro air vehicle ; car-like kinematics ; variable speed ; machine learning ; dynamical model ; transportation ; geodesic ; unmanned surface vessel ; medical devices ; stopper ; extended state observer (ESO) ; high efficiency ; object mapping ; multi-objective optimization ; hybrid robot ; robot learning ; auto-tuning ; cable disturbance modeling ; manipulation planning ; pesticide application ; high-speed target ; sparse pose adjustment (SPA) ; service robot ; lumped parameter method ; Geometric Algebra ; dynamic coupling analysis ; Thau observer ; tri-tilt-rotor ; industrial robotic manipulator ; hardware-in-the-loop simulation ; robotic drilling ; muscle activities ; small size ; chameleon ; continuous hopping ; wall climbing robot ; hover mode ; 3D-SLAM ; curvature constraints ; PSO ; drilling end-effector ; Rodrigues parameters ; gait adaptation ; static environments ; position/force cooperative control ; snake-like robot ; shape-fitting ; powered exoskeleton ; input saturation ; kinematic identification ; methane ; human–machine interactive navigation ; q-learning ; path following ; hopping robot ; mobile manipulation ; high step-up ratio ; actuatorless ; monocular vision ; stability analysis ; compact driving unit ; snake robot ; non-holonomic robot ; curvature constraint ; phase-shifting ; dialytic elimination ; gesture recognition ; snake robots ; series elastic actuator ; flapping ; servo valve ; motion camouflage control ; biomimetic robot ; minimally invasive surgery robot ; centralized architecture ; trajectory planning ; computing time ; adaptive control law ; kinematics ; facial and gender recognition ; single actuator ; victim-detection ; shape memory alloys ; undiscovered sensor values ; discomfort ; Differential Evolution ; numerical evaluation ; quadruped robot ; coverage path planning ; localization ; MPC ; n/a ; fault diagnosis ; neural networks ; disturbance-rejection control ; sample gathering problem ; cart ; bio-inspired robot ; opposite angle-based exact cell decomposition ; optimization ; safety ; goal exchange ; hierarchical planning ; ocean current ; robot motion ; nonlinear differentiator ; mapping ; finite-time currents observer ; Newton iteration ; inverse kinematics ; deposition uniformity ; spatial pyramid pooling ; hierarchical path planning ; end effector ; head-raising ; fault recovery ; LOS ; path tracking ; non-inertial reference frame ; step climbing ; obstacle avoidance ; sliding mode control ; symmetrical adaptive variable impedance ; lane change ; quadcopter UAV ; singularity analysis ; biped mechanism ; fault-tolerant control ; dynamic neural networks ; mobile robots ; data association ; UAV ; enemy avoidance ; reinforcement learning ; grip optimization ; safety recovery mechanism ; exoskeleton ; dynamic environment ; uncertain environments ; hybrid bionic robot ; potential field ; robot navigation ; cleaning robot ; unmanned aerial vehicle ; non-singular fast-terminal sliding-mode control ; contact planning ; Lyapunov-like function ; piezoelectric actuator ; transition mode ; non-prehensile manipulation ; multiple mobile robots ; Tetris-inspired ; real-time action recognition ; integral line-of-sight ; topological map ; alpine ski ; target tracking ; closed-loop detection ; working efficiency ; mathematical modeling ; curve fitting ; force control ; biped robots ; NSGA-II ; mobile robot ; load carriage ; prescription map translation ; artificial fish swarm algorithm ; Q-networks ; self-reconfigurable robot ; G3-continuity ; autonomous vehicle ; loop closure detection ; excellent driver model ; robots ; graph representation ; regional growth ; target assignment ; evolutionary operators ; intelligent mobile robot ; motion sensor ; exploration ; droplets penetrability ; dynamic uncertainty ; simultaneous localization and mapping (SLAM) ; area decomposition ; multi-criteria decision making ; 4WS4WD vehicle ; biped climbing robots ; skiing robot ; ROS ; decision making ; smart materials ; centrifugal force ; missile control system ; formation of robots ; electro-rheological fluids ; pneumatics ; variable spray ; inertial measurement unit (IMU) ; Robot Operating System ; trajectory interpolation ; formation control ; immersion and invariance ; dragonfly ; parallel navigation ; harmonic potential field ; pallet transportation ; mobile robot navigation ; negative-buoyancy ; grip planning ; manipulator ; position control ; external disturbance ; legged robot ; passive skiing turn ; autonomous underwater vehicle (AUV) ; gait cycle ; path planning ; sliding mode observer ; dynamic gait ; self-learning ; polyomino tiling theory ; coalmine ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Attention in the AI safety community has increasingly started to include strategic considerations of coordination between relevant actors in the field of AI and AI safety, in addition to the steadily growing work on the technical considerations of building safe AI systems. This shift has several reasons: Multiplier effects, pragmatism, and urgency. Given the benefits of coordination between those working towards safe superintelligence, this book surveys promising research in this emerging field regarding AI safety. On a meta-level, the hope is that this book can serve as a map to inform those working in the field of AI coordination about other promising efforts. While this book focuses on AI safety coordination, coordination is important to most other known existential risks (e.g., biotechnology risks), and future, human-made existential risks. Thus, while most coordination strategies in this book are specific to superintelligence, we hope that some insights yield “collateral benefits” for the reduction of other existential risks, by creating an overall civilizational framework that increases robustness, resiliency, and antifragility.
    Keywords: TA1-2040 ; T1-995 ; strategic oversight ; multi-agent systems ; autonomous distributed system ; artificial superintelligence ; safe for design ; adaptive learning systems ; explainable AI ; ethics ; scenario mapping ; typologies of AI policy ; artificial intelligence ; design for values ; distributed goals management ; scenario analysis ; Goodhart’s Law ; specification gaming ; AI Thinking ; VSD ; AI ; human-in-the-loop ; value sensitive design ; future-ready ; forecasting AI behavior ; AI arms race ; AI alignment ; blockchain ; artilects ; policy making on AI ; distributed ledger ; AI risk ; Bayesian networks ; artificial intelligence safety ; conflict ; AI welfare science ; moral and ethical behavior ; scenario network mapping ; policymaking process ; human-centric reasoning ; antispeciesism ; AI forecasting ; transformative AI ; ASILOMAR ; judgmental distillation mapping ; terraforming ; pedagogical motif ; AI welfare policies ; superintelligence ; artificial general intelligence ; supermorality ; AI value alignment ; AGI ; predictive optimization ; AI safety ; technological singularity ; machine learning ; holistic forecasting framework ; simulations ; existential risk ; technology forecasting ; AI governance ; sentiocentrism ; AI containment ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.
    Keywords: TJ1-1570 ; TA1-2040 ; T1-995 ; artificial neural network ; n/a ; model switching ; sensitivity analysis ; neural networks ; logit boost ; Qaidam Basin ; land subsidence ; land use/land cover (LULC) ; naïve Bayes ; multilayer perceptron ; convolutional neural networks ; single-class data descriptors ; logistic regression ; feature selection ; mapping ; particulate matter 10 (PM10) ; Bayes net ; gray-level co-occurrence matrix ; multi-scale ; Logistic Model Trees ; classification ; Panax notoginseng ; large scene ; coarse particle ; grayscale aerial image ; Gaofen-2 ; environmental variables ; variable selection ; spatial predictive models ; weights of evidence ; landslide prediction ; random forest ; boosted regression tree ; convolutional network ; Vietnam ; model validation ; colorization ; data mining techniques ; spatial predictions ; SCAI ; unmanned aerial vehicle ; high-resolution ; texture ; spatial sparse recovery ; landslide susceptibility map ; machine learning ; reproducible research ; constrained spatial smoothing ; support vector machine ; random forest regression ; model assessment ; information gain ; ALS point cloud ; bagging ensemble ; one-class classifiers ; leaf area index (LAI) ; landslide susceptibility ; landsat image ; ionospheric delay constraints ; spatial spline regression ; remote sensing image segmentation ; panchromatic ; Sentinel-2 ; remote sensing ; optical remote sensing ; materia medica resource ; GIS ; precise weighting ; change detection ; TRMM ; traffic CO ; crop ; training sample size ; convergence time ; object detection ; gully erosion ; deep learning ; classification-based learning ; transfer learning ; landslide ; traffic CO prediction ; hybrid model ; winter wheat spatial distribution ; logistic ; alternating direction method of multipliers ; hybrid structure convolutional neural networks ; geoherb ; predictive accuracy ; real-time precise point positioning ; spectral bands ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering::TDCW Pharmaceutical chemistry and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The book “Building Energy Audits-Diagnosis and Retrofitting” is a collection of twelve papers that focus on the built environment in order to systematically collect and analyze relevant data for the energy use profile of buildings and extended for the sustainability assessment of the built environment. The contributions address historic buildings, baselines for non-residential buildings from energy performance audits, and from in-situ measurements, monitoring, and analysis of data, and verification of energy saving and model calibration for various building types. The works report on how to diagnose existing problems and identify priorities, assess, and quantify the opportunities and measures that improve the overall building performance and the environmental quality and well-being of occupants in non-residential buildings and houses. Several case studies and lessons learned from the field are presented to help the readers identify, quantify, and prioritize effective energy conservation and efficiency measures. Finally, a new urban sustainability audit and rating method of the built environment addresses the complexities of the various issues involved, providing practical tools that can be adapted to match local priorities in order to diagnose and evaluate the current state and future scenarios towards meeting specific sustainable development goals and local priorities.
    Keywords: feature selection ; prediction of energy consumption ; electricity consumption ; machine learning ; non-residential buildings ; sustainability ; buildings ; neighbourhoods ; decision-making process ; key performance indicators ; KPIs ; built environment ; audit ; assessment tools ; brick 1 ; moisture 2 ; heat flow 3 ; energetic rehabilitation 4 ; non-destructive test 5 ; energy community (EC) ; renewable energy sources (RESs) ; citizen involvement ; co-ownership in renewable energies ; nonresidential buildings ; baselines ; EUI ; energy use intensities ; carbon emission intensities ; EPCs ; energy performance certificates ; building energy simulation ; school building ; field measurements ; validation ; airing ; windows and door opening ; occupancy behaviour ; energy efficiency measures ; retrofitting ; thermo-modernization ; final energy ; primary energy ; energy consumption ; home energy management system ; human comfort factor ; thermal comfort ; visual comfort ; demand response ; energy performance ; energy audits ; school buildings ; indoor climate ; HeLLo ; energy retrofit ; non-destructive test ; in situ ; hygrothermal measurement ; dynamic conditions ; hygrothermal simulation ; historic wall ; daylight ; lighting control ; lighting ; occupant preferences ; occupant satisfaction ; photosensor ; post-occupancy evaluation ; survey ; single-family houses ; embodied energy ; operational energy ; benchmarks ; renovations ; energy use intensity (EUI) ; embodied energy intensity (EEI) ; energy recovery time ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    Publication Date: 2024-04-05
    Description: The idea of preparing an Energies Special Issue on “Structural Prognostics and Health Management in Power & Energy Systems” is to compile information on the recent advances in structural prognostics and health management (SPHM). Continued improvements on SPHM have been made possible through advanced signature analysis, performance degradation assessment, as well as accurate modeling of failure mechanisms by introducing advanced mathematical approaches/tools. Through combining deterministic and probabilistic modeling techniques, research on SPHM can provide assurance for new structures at a design stage and ensure construction integrity at a fabrication phase. Specifically, power and energy system failures occur under multiple sources of uncertainty/variability resulting from load variations in usage, material properties, geometry variations within tolerances, and other uncontrolled variations. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on SPHM are desired and expected, which attempt to prevent overdesign and unnecessary inspection and provide tools to enable a balance between safety and economy to be achieved. This Special Issue has attracted submissions from China, USA, Portugal, and Italy. A total of 26 submissions were received and 11 articles finally published.
    Keywords: B1-5802 ; empirical mode decomposition ; underground powerhouse ; sensitivity analysis ; DNN ; fault detection ; neural networks ; structural health monitoring ; analysis mode decomposition ; dynamic analysis of the structure ; residual useful life ; renewable energy ; remaining useful life ; retrofitting activities ; wind turbine blade ; optimized deep belief networks ; strain prediction ; offshore wind turbines ; low frequency tail fluctuation ; oil and gas platforms ; supporting vector machine (SVM) ; wave–structure interaction (WSI) ; sifting stop criterion ; probabilistic analyses of stochastic processes and frequency ; mode mixing ; non-probabilistic reliability index ; data-driven ; prognostics ; turbine blisk ; wind turbines ; supervisory control and data acquisition system ; fuzzy safety criterion ; analysis-empirical mode decomposition ; rotation of hydraulic generator ; life cycle cost ; health monitoring ; reliability ; wavelet decomposition ; weighted regression ; similarity-based approach ; vibration transmission mechanism ; wind and wave analysis ; full-scale static test ; deep learning ; multioperation condition ; extremum surface response method ; lithium-ion battery ; vibration test ; lateral-river vibration ; operational modal analysis ; dynamic analysis ; regeneration phenomenon ; machine learning ; prognostic and Health Management ; offshore structures ; NAR neural network ; techno-economic assessments ; stochastic subspace identification ; vertical axis wind turbine ; dynamic fuzzy reliability analysis ; thema EDItEUR::Q Philosophy and Religion::QD Philosophy
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Mineral processing deals with complex particle systems with two-, three- and more phases. The modeling and understanding of these systems are a challenge for research groups and a need for the industrial sector. This Special Issue aims to present new advances, methodologies, applications, and case studies of computer-aided analysis applied to multiphase systems in mineral processing. This includes aspects such as modeling, design, operation, optimization, uncertainty analysis, among other topics. The special issue contains a review article and eleven articles that cover different methodologies of modeling, design, optimization, and analysis in problems of adsorption, leaching, flotation, and magnetic separation, among others. Consequently, the topics covered are of interest to readers from academia and industry.
    Keywords: TA1-2040 ; T1-995 ; hydrothermal reaction ; n/a ; froth flotation ; modes of operation ; hydrocyclone ; computational fluid dynamic ; K-feldspar ; discrete event simulation ; endoscopic laser PIV ; magnetic separation ; adsorption ; silver leaching ; mining residues ; hydroxylation ; phase analysis ; multispecies ; turbulence models ; cyclonic flow field ; Boycott effect ; heap leaching ; flotation column ; artificial neural networks ; tailings ; lead chemistry ; thiosulfate ; flotation ; local regression ; CFD ; grinding ; fluorapatite ; settling velocity ; response surface methodology ; cassiterite ; thickening ; discrete element simulation ; DFT calculation ; flotation circuits ; recovery arrangement ; design ; smoothed particle hydrodynamics ; MLA (Mineral Liberation Analyzer) ; circuit configuration ; Pb(II)–BHA ; SEM-based image analysis ; uncertainty analysis ; partition curve ; tobermorite ; kinetic analysis ; water recovery ; process design ; metal–organic collectors ; natural convection ; quartz ; molecular dynamics ; machine learning ; flotation mechanism ; surface activation ; frontier molecular orbital ; support vector machine ; process optimization process ; hydrogarnet ; density functional theory ; Tabu-search algorithm ; global sensitivity analysis ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 60
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.
    Keywords: TD1-1066 ; T1-995 ; global monitoring service ; suspended sediment concentration ; image classification ; empirical ; Soil Moisture Active Passive ; data archival ; water resources ; GlobCover ; dNBR ; satellite imagery ; SDG ; cloud-based geo-processing ; spatial resolution ; land use change ; MTBS ; global scale ; landsat collection ; Geo Big Data ; trends ; FAPAR ; vegetation index ; pseudo-invariant features ; emergency response ; RBR ; BULC-U ; Africa ; Brazilian pasturelands dynamics ; Enhanced Vegetation Index ; geo-big data ; multitemporal analysis ; flood ; early warning systems ; low cost in situ ; web portal ; composite burn index (CBI) ; small-scale mining ; snow hydrology ; RdNBR ; seasonal vegetation ; burn severity ; random forests ; land-use cover change ; random forest ; Support Vector Machines ; lower mekong basin ; CWC ; Random Forest ; crop yield ; Landsat-8 ; sun glint correction ; protected area ; cropland areas ; disaster prevention ; gross primary productivity (GPP) ; segmentation ; high spatial resolution ; satellite-derived bathymetry ; Aegean ; Brazilian Amazon ; image composition ; pasture mapping ; carbon cycle ; machine learning ; earth observation ; ecosystem assessment ; Mato Grosso ; FVC ; image time series ; LAI ; semi-arid ; google engine ; spatial error ; Ionian ; forest and land use mapping ; snow cover ; long term monitoring ; RHSeg ; online application ; land cover ; PROSAIL ; support vector machines ; seagrass ; wetland ; Sentinel-1 ; Sentinel-2 ; surface reflectance ; user assessment ; remote sensing ; multi-classifier ; time series ; machine learning classification ; deforestation ; Google Earth Engine ; decision making ; cropland mapping ; change detection ; google earth engine ; industrial mining ; data fusion ; cloud masking ; Google Earth Engine (GEE) ; NDVI ; Bayesian statistics ; China ; cloud computing ; plant traits ; Soil Moisture Ocean Salinity ; soil moisture ; big data analytics ; Landsat ; phenology ; 30-m ; MODIS ; habitat mapping ; Mediterranean ; temporal compositing ; drought ; surface urban heat island ; BACI ; crop classification ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The Special Issue on Advances in Modeling and Management of Urban Water Networks (UWNs) explores four important topics of research in the context of UWNs: asset management, modeling of demand and hydraulics, energy recovery, and pipe burst identification and leakage reduction. In the first topic, the multi-objective optimization of interventions on the network is presented to find trade-off solutions between costs and efficiency. In the second topic, methodologies are presented to simulate and predict demand and to simulate network behavior in emergency scenarios. In the third topic, a methodology is presented for the multi-objective optimization of pump-as-turbine (PAT) installation sites in transmission mains. In the fourth topic, methodologies for pipe burst identification and leakage reduction are presented. As for the urban drainage systems (UDSs), the two explored topics are asset management, with a system upgrade to reduce flooding, and modeling of flow and water quality, with analyses on the transition from surface to pressurized flow, impact of water use reduction on the operation of UDSs, and sediment transport in pressurized pipes. The Special Issue also includes one paper dealing with the hydraulic modeling of an urban river with a complex cross-section.
    Keywords: drainage network ; climate change ; rehabilitation ; optimization ; SWMM ; drainage networks ; flooding ; multi-objective optimization ; water network partition ; genetic algorithm ; hydraulic ; water quality ; actions ; asset management ; ANN ; prediction ; performance ; water utility ; water system ; NSGA-II ; GIS modeling ; leakage management ; urban water network management ; valve closing algorithm ; web 2.0 ; total suspended solids ; in-situ ; erosion ; sedimentation ; pressure pipe ; sewage ; water distribution systems ; pipe bursts ; hydraulic transients ; real-time control ; machine learning ; sediment transport model ; numerical simulation ; advection-dispersion equation ; water distribution networks ; transmission mains ; pump as turbine ; energy recovery ; hydropower ; multi-objective ; water consumption ; chaos theory ; local approximation ; Kelowna ; gene expression programming ; trapezoidal stretch ; transition stretch ; culvert ; open channel ; hydraulic factors ; sewer design ; stochastic sewer modelling ; wastewater quality ; household discharge ; reduced water consumption ; flow regime transition ; finite volume methods ; numerical oscillations ; numerical viscosity ; Preissmann slot model ; hydraulic simulation ; water demand ; emergency scenario ; intermittent water supply ; water management ; WaterGEMS software ; pressure control ; leakage reduction strategies ; water distribution system modeling ; urban drainage system modeling ; emergency scenarios ; leakage ; demand ; energy ; sediment transport ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 62
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-29
    Description: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
    Keywords: algorithmic trading ; Stop Loss ; Turtle ; ATR ; community finances ; fiscal flexibility ; individualized financial arrangements ; sustainable financial services ; price momentum ; hidden markov model ; asset allocation ; blockchain ; BlockCloud ; Artificial Intelligence ; consensus algorithms ; exchange rates ; fundamentals ; prediction ; random forest ; support vector machine ; neural network ; deep reinforcement learning ; financial market simulation ; agent based simulation ; artificial market ; simulation ; CAR regulation ; portfolio ; contract for difference ; CfD ; reinforcement learning ; RL ; neural networks ; long short-term memory ; LSTM ; Q-learning ; deep learning ; uncertainty ; economic policy ; text mining ; topic model ; yield curve ; term structure of interest rates ; machine learning ; autoencoder ; interpretability ; thema EDItEUR::K Economics, Finance, Business and Management
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-21
    Description: Statistical relationships among the variables of a complex system reveal a lot about its physical behavior. Therefore, identification of the relevant variables and characterization of their interactions are crucial for a better understanding of a complex system. Linear methods, such as correlation, are widely used to identify these relationships. However, information-theoretic quantities, such as mutual information and transfer entropy, have been proven to be superior in the case of nonlinear dependencies. Mutual information quantifies the amount of information obtained about one random variable through the other random variable, and it is symmetric. As an asymmetrical measure, transfer entropy quantifies the amount of directed (time-asymmetric) transfer of information between random processes and, thus, it is related to concepts, such as the Granger causality. This Special Issue includes 16 papers elucidating the state of the art of data-based transfer entropy estimation techniques and applications, in areas such as finance, biomedicine, fluid dynamics and cellular automata. Analytical derivations in special cases, improvements on the estimation methods and comparisons between certain techniques are some of the other contributions of this Special Issue. The diversity of approaches and applications makes this book unique as a single source of invaluable contributions from experts in the field.
    Keywords: T58.5-58.64 ; statistical signal processing ; entropy estimation ; nonlinear interactions ; data mining ; machine learning ; information-theoretic quantities ; causality ; information flow ; entropy ; correlation ; statistical dependency ; information-theory ; transfer entropy ; causal relationships ; mutual information ; Granger causality ; interacting subsystems ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-01-31
    Description: It is time consuming and costly to detect new molecules of some special proteins. These special proteins include cytokines, enzymes, cell-penetrating peptides, anticancer peptides, cancer lectins, G-protein-coupled receptors, etc. Researchers often employ computer programs to list some candidates, and to validate the candidates with molecular experiments. These computer programs are key to possible savings on wet experiment costs. Software results with high false positive will lead to high costs in the validation process. In this Special Issue, we focus on these computer program approaches and algorithms. Some "golden features" from protein primary sequences have been proposed for these problems, such as Chou’s PseAAC (pseudo amino acid composition). PseAAC has been tried on nearly all kinds of protein identification, together with SVM (support vector machines, a type of classifier). However, I prefer special features, and classification methods should be proposed for special protein molecules. "Golden features" cannot work well on all kinds of proteins. I hope that submissions will focus on a type of special protein molecule, collect related data sets, obtain better prediction performance (especially low false positives), and develop user-friendly software tools or web servers.
    Keywords: R858-859.7 ; MHC binding peptide ; type III secreted proteins ; machine learning ; oncogene ; anticancer peptides ; bioinformatics ; Proteomics ; DNA/RNA binding proteins ; prediction ; PseAAC features ; Cell-Penetrating Peptides ; protein classification ; feature selection
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-21
    Description: The contribution of genomic variants to the aetiopathogenesis of both paediatric and adult neurological disease is being increasingly recognized. The use of next-generation sequencing has led to the discovery of novel neurodevelopmental disorders, as exemplified by the deciphering developmental disorders (DDD) study, and provided insight into the aetiopathogenesis of common adult neurological diseases. Despite these advances, many challenges remain. Correctly classifying the pathogenicity of genomic variants from amongst the large number of variants identified by next-generation sequencing is recognized as perhaps the major challenge facing the field. Deep phenotyping (e.g., imaging, movement analysis) techniques can aid variant interpretation by correctly classifying individuals as affected or unaffected for segregation studies. The lack of information on the clinical phenotype of novel genetic subtypes of neurological disease creates limitations for genetic counselling. Both deep phenotyping and qualitative studies can capture the clinical and patient’s perspective on a disease and provide valuable information. This Special Issue aims to highlight how next-generation sequencing techniques have revolutionised our understanding of the aetiology of brain disease and describe the contribution of deep phenotyping studies to a variant interpretation and understanding of natural history.
    Keywords: R5-920 ; RC346-429 ; polymicrogyria ; n/a ; neurodegenerative disease ; next generation sequencing (NGS) ; inborn error of metabolism ; genetic biomarker ; deep learning ; TUBA1A ; Alzheimer’s disease (AD) ; ataxia ; risk prediction ; p.(Arg2His) ; movement science ; tubulin ; R2H ; diagnosis ; machine learning ; metal storage disorders ; amyotrophic lateral sclerosis (ALS) ; glucocerebrosidase ; Parkinsonism ; cerebellar hypoplasia ; Gaucher disease ; disease phenotyping ; tubulinopathy ; Parkinson’s disease (PD) ; dementia ; Parkinson’s disease ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-01
    Description: In recent years, many technologies for gait and posture assessments have emerged. Wearable sensors, active and passive in-house monitors, and many combinations thereof all promise to provide accurate measures of physical activity, gait, and posture parameters. Motivated by market projections for wearable technologies and driven by recent technological innovations in wearable sensors (MEMs, electronic textiles, wireless communications, etc.), wearable health/performance research is growing rapidly and has the potential to transform future healthcare from disease treatment to disease prevention. The objective of this Special Issue is to address and disseminate the latest gait, posture, and activity monitoring systems as well as various mathematical models/methods that characterize mobility functions. This Special Issue focuses on wearable monitoring systems and physical sensors, and its mathematical models can be utilized in varied environments under varied conditions to monitor health and performance
    Keywords: step detection ; machine learning ; outlier detection ; transition matrices ; autoencoders ; ground reaction force (GRF) ; micro electro mechanical systems (MEMS) ; gait ; walk ; bipedal locomotion ; 3-axis force sensor ; shoe ; force distribution ; multi-sensor gait classification ; distributed compressed sensing ; joint sparse representation classification ; telemonitoring of gait ; operating range ; accelerometer ; stride length ; peak tibial acceleration ; running velocity ; wearable sensors ; feedback technology ; rehabilitation ; motor control ; cerebral palsy ; inertial sensors ; gait events ; spatiotemporal parameters ; postural control ; falls in the elderly ; fall risk assessment ; low-cost instrumented insoles ; foot plantar center of pressure ; flexible sensor ; gait recognition ; piezoelectric material ; wearable ; adaptability ; force sensitive resistors ; self-tuning triple threshold algorithm ; sweat sensor ; sweat rate ; dehydration ; IoT ; PDMS ; surface electromyography ; handgrip force ; force-varying muscle contraction ; nonlinear analysis ; wavelet scale selection ; inertial measurement unit ; gyroscope ; asymmetry ; feature extraction ; gait analysis ; lower limb prosthesis ; trans-femoral amputee ; MR damper ; knee damping control ; inertial measurement units ; motion analysis ; kinematics ; functional activity ; repeatability ; reliability ; biomechanics ; cognitive frailty ; cognitive–motor impairment ; Alzheimer’s disease ; motor planning error ; instrumented trail-making task ; ankle reaching task ; dual task walking ; nondestructive ; joint moment ; partial weight loading ; muscle contributions ; sit-to-stand training ; motion parameters ; step length ; self-adaptation ; Parkinson’s disease (PD) ; tremor dominant (TD) ; postural instability and gait difficulty (PIGD) ; center of pressure (COP) ; fast Fourier transform (FFT) ; wavelet transform (WT) ; fall detection system ; smartphones ; accelerometers ; machine learning algorithms ; supervised learning ; ANOVA analysis ; Step-detection ; ActiGraph ; Pedometer ; acceleration ; physical activity ; physical function ; physical performance test ; chair stand ; sit to stand transfer ; wearables ; gyroscopes ; e-Health application ; physical rehabilitation ; shear and plantar pressure sensor ; biaxial optical fiber sensor ; multiplexed fiber Bragg gratings ; frailty ; pre-frail ; wearable sensor ; sedentary behavior ; moderate-to-vigorous activity ; steps ; fall detection ; elderly people monitoring ; telerehabilitation ; virtual therapy ; Kinect ; eHealth ; telemedicine ; insole ; injury prevention ; biomechanical gait variable estimation ; inertial gait variable ; total knee arthroplasty ; falls in healthy elderly ; fall prevention ; biometrics ; human gait recognition ; ground reaction forces ; Microsoft Kinect ; high heels ; fusion data ; ensemble classifiers ; accidental falls ; older adults ; neural networks ; convolutional neural network ; long short-term memory ; accelerometry ; obesity ; nonlinear ; electrostatic field sensing ; gait measurement ; temporal parameters ; artificial neural network ; propulsion ; aging ; walking ; smart footwear ; frailty prediction ; fall risk ; smartphone based assessments ; adverse post-operative outcome ; intelligent surveillance systems ; human fall detection ; health and well-being ; safety and security ; n/a ; movement control ; anterior cruciate ligament ; kinetics ; real-time feedback ; biomechanical gait features ; impaired gait classification ; pattern recognition ; sensors ; clinical ; knee ; osteoarthritis ; shear stress ; callus ; woman ; TUG ; IMU ; geriatric assessment ; semi-unsupervised ; self-assessment ; domestic environment ; functional decline ; symmetry ; trunk movement ; autocorrelation ; gait rehabilitation ; wearable device ; IMU sensors ; gait classification ; stroke patients ; neurological disorders ; scanning laser rangefinders (SLR), GAITRite ; cadence ; velocity and stride-length ; power ; angular velocity ; human motion measurement ; sensor fusion ; complementary filter ; fuzzy logic ; inertial and magnetic sensors ; ESOQ-2 ; Parkinson’s disease ; UPDRS ; movement disorders ; human computer interface ; RGB-Depth ; hand tracking ; automated assessment ; at-home monitoring ; Parkinson’s Diseases ; motorized walker ; haptic cue ; gait pattern ; statistics study ; walk detection ; step counting ; signal processing ; plantar pressure ; flat foot ; insoles ; force sensors ; arch index ; sports analytics ; deep learning ; classification ; inertial sensor ; cross-country skiing ; classical style ; skating style ; batteryless strain sensor ; wireless strain sensor ; resonant frequency modulation ; Ecoflex ; human activity recognition ; smartphone ; human daily activity ; ensemble method ; running ; velocity ; smart shoe ; concussion ; inertial motion units (IMUs) ; vestibular exercises ; validation ; motion capture ; user intent recognition ; transfemoral prosthesis ; multi-objective optimization ; biogeography-based optimization ; smart cane ; weight-bearing ; health monitoring ; wearable/inertial sensors ; regularity ; variability ; human ; motion ; locomotion ; UPDRS tasks ; posture ; postural stability ; center of mass ; RGB-depth ; neurorehabilitation ; hallux abductus valgus ; high heel ; proximal phalanx of the hallux ; abduction ; valgus ; ultrasonography ; Achilles tendon ; diagnostic ; imaging ; tendinopathy ; foot insoles ; electromyography ; joint instability ; muscle contractions ; motorcycling ; wearable electronic devices ; validity ; relative movement ; lower limb prosthetics ; biomechanic measurement tasks ; quantifying socket fit ; rehabilitation exercise ; dynamic time warping ; automatic coaching ; exergame ; fine-wire intramuscular EMG electrode ; non-human primate model ; traumatic spinal cord injury ; wavelet transform ; relative power ; linear mixed model ; VO2 ; calibration ; MET ; VO2net ; speed ; equivalent speed ; free-living ; children ; adolescents ; adults ; gait event detection ; hemiplegic gait ; appropriate mother wavelet ; acceleration signal ; wavelet-selection criteria ; conductive textile ; stroke ; hemiparetic ; real-time monitoring ; lower limb locomotion activity ; triplet Markov model ; semi-Markov model ; on-line EM algorithm ; human kinematics ; phase difference angle ; thema EDItEUR::N History and Archaeology::NH History ; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.
    Keywords: TA1-2040 ; T1-995 ; optical sensor ; spectral analysis ; response surface sampling ; sensor evaluation ; electromagnetic induction ; multivariate water quality parameters ; mandarin orange ; crop inspection platform ; SPA-MLR ; object tracking ; feature selection ; simultaneous measurement ; diseases ; genetic algorithms ; processing of sensed data ; electrochemical sensors ; thermal image ; ECa-directed soil sampling ; handheld ; recognition patterns ; salt concentration ; clover-grass ; bovine embedded hardware ; weed control ; soil ; field crops ; vineyard ; connected dominating set ; water depth sensors ; SS-OCT ; wheat ; striped stem-borer ; silage ; geostatistics ; detection ; NIR hyperspectral imaging ; electronic nose ; machine learning ; virtual organizations of agents ; packing density ; data validation and calibration ; dataset ; Wi-SUN ; temperature sensors ; geoinformatics ; gas sensor ; X-ray fluorescence spectroscopy ; vegetable oil ; photograph-grid method ; Vitis vinifera ; WSN distribution algorithms ; laser-induced breakdown spectroscopy ; irrigation ; quality assessment ; energy efficiency ; wireless sensor network (WSN) ; geo-information ; Fusarium ; texture features ; weeds ; discrimination ; big data ; soil moisture sensors ; meat spoilage ; land cover ; stereo imaging ; near infrared sensors ; biological sensing ; compound sensor ; pest management ; moisture ; plant localization ; heavy metal contamination ; artificial neural networks ; spectral pre-processing ; moisture content ; apparent soil electrical conductivity ; data fusion ; semi-arid regions ; smart irrigation ; back propagation model ; wireless sensor network ; energy balance ; light-beam ; fluorescent measurement ; agriculture ; precision agriculture ; deep learning ; spectroscopy ; hulled barely ; dielectric probe ; RPAS ; water supply network ; rice leaves ; mobile app ; gradient boosted machines ; hyperspectral camera ; one-class ; nitrogen ; LiDAR ; total carbon ; chemometrics analysis ; rice ; agricultural land ; on-line vis-NIR measurement ; CARS ; obstacle detection ; stratification ; neural networks ; regression estimator ; Kinect ; proximity sensing ; distributed systems ; pest ; noninvasive detection ; texture feature ; soil mapping ; classification ; soil salinity ; visible and near-infrared reflectance spectroscopy ; germination ; computer vision ; hyperspectral imaging ; diffusion ; dielectric dispersion ; UAS ; random forests ; case studies ; total nitrogen ; thermal imaging ; cameras ; dry matter composition ; near-infrared ; salt tolerance ; deep convolutional neural networks ; soil type classification ; water management ; preprocessing methods ; wireless sensor networks (WSN) ; remote sensing image classification ; precision plant protection ; radar ; spatial variability ; GF-1 satellite ; plant disease ; naked barley ; leaf area index ; CIE-Lab ; change of support ; radiative transfer model ; 3D reconstruction ; plant phenotyping ; vine ; near infrared ; vegetation indices ; remote sensing ; greenhouse ; time-series data ; scattering ; sensor ; crop area ; speckle ; spatial data ; grapevine breeding ; wide field view ; partial least squares-discriminant analysis ; spiking ; area frame sampling ; chromium content ; machine-learning ; RGB-D sensor ; pest scouting ; PLS ; Capsicum annuum ; spatial-temporal model ; drying temperature ; boron tolerance ; ambient intelligence ; laser wavelength ; fuzzy logic ; dynamic weight ; landslide ; management zones ; real-time processing ; event detection ; crop monitoring ; apple shelf-life ; rice field monitoring ; wireless sensor ; birth sensor ; proximal sensor ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In geodesy and geoinformation science, as well as in many other technical disciplines, it is often not possible to directly determine the desired target quantities. Therefore, the unknown parameters must be linked with the measured values by a mathematical model which consists of the functional and the stochastic models. The functional model describes the geometrical–physical relationship between the measurements and the unknown parameters. This relationship is sufficiently well known for most applications. With regard to the stochastic model, two problem domains of fundamental importance arise: 1. How can stochastic models be set up as realistically as possible for the various geodetic observation methods and sensor systems? 2. How can the stochastic information be adequately considered in appropriate least squares adjustment models? Further questions include the interpretation of the stochastic properties of the computed target values with regard to precision and reliability and the use of the results for the detection of outliers in the input data (measurements). In this Special Issue, current research results on these general questions are presented in ten peer-reviewed articles. The basic findings can be applied to all technical scientific fields where measurements are used for the determination of parameters to describe geometric or physical phenomena.
    Keywords: EM-algorithm ; multi-GNSS ; PPP ; process noise ; observation covariance matrix ; extended Kalman filter ; machine learning ; GNSS phase bias ; sequential quasi-Monte Carlo ; variance reduction ; autoregressive processes ; ARMA-process ; colored noise ; continuous process ; covariance function ; stochastic modeling ; time series ; elementary error model ; terrestrial laser scanning ; variance-covariance matrix ; terrestrial laser scanner ; stochastic model ; B-spline approximation ; Hurst exponent ; fractional Gaussian noise ; generalized Hurst estimator ; very long baseline interferometry ; sensitivity ; internal reliability ; robustness ; CONT14 ; Errors-In-Variables Model ; Total Least-Squares ; prior information ; collocation vs. adjustment ; mean shift model ; variance inflation model ; outlierdetection ; likelihood ratio test ; Monte Carlo integration ; data snooping ; GUM analysis ; geodetic network adjustment ; stochastic properties ; random number generator ; Monte Carlo simulation ; 3D straight line fitting ; total least squares (TLS) ; weighted total least squares (WTLS) ; nonlinear least squares adjustment ; direct solution ; singular dispersion matrix ; laser scanning data ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Power quality (PQ) is receiving more and more attention from consumers, distribution system operators, transmission system operators, and other entities related to electrical power systems. As PQ problems have direct implications for business productivity, causing high economic losses, the research and development monitoring technologies and power electronics solutions that ensure the PQ of the power systems are matters of utmost importance. This book is a collection of high quality papers published in the “Power Electronics and Power Quality” Special Issue of the journal Energies. It reflects on the latest investigations and the new trends in this field.
    Keywords: TA1-2040 ; T1-995 ; p-q theory ; Pulse Width Modulation (PWM) ; power system protection ; modeling ; comtrade ; space vector modulation (SVM) ; propulsion inverter control system position estimator ; frequency adaption ; wavelet transform ; Simulink ; SGDFT ; indirect matrix converter (IMC) ; hysteresis current control ; switching transients ; input power factor ; high speed maglev ; harmonics ; optimization ; robust control ; protection relay ; variation in voltage ; FBMMC ; MMC ; microinverter ; digital control ; state-space model ; four-leg inverter ; phase-leading capacitor ; histogram ; pulse width modulation ; energy shaping passivity (ESP)-based control ; time multiplier setting (TMS) ; reactive power ; continuous particle swarm optimization (CPSO) ; power control ; microgrid (MG) ; passive method ; Matlab ; voltage control ; switching frequency ; Field Programmable Gate Array (FPGA) ; Omicron CMC 256plus ; distance protection ; low voltage direct-current residential microgrid ; Full-bridge ; series active filter ; static var compensator ; photovoltaic systems ; Total Harmonic Distortion (THD) ; long-stator synchronous motor ; SC ; constant power load ; CSC ; superconducting magnetic energy storage (SMES) ; hybrid power filter ; renewable power generation ; Lagrange-interpolation method ; multilevel converter ; multi-grounded neutral (MGN) system ; temperature ; computer simulation ; thyristor-controlled reactor ; hybrid static var compensator ; static synchronous compensator ; power semiconductor device ; DC short-circuit handling ; cost-effectiveness ; current control ; half-bridge inverters ; Hybrid HVDC ; power inverter ; input filter ; machine learning ; enerlyzer ; matrix converter (MC) ; DC-DC converter ; Shunt Active Power Filter ; neutral integrity detection ; overcurrent relay coordination (OCR) ; power quality ; event detection ; voltage source inverter ; Multiterminal HVDC ; distorted grid conditions ; hybrid active filter ; primary neutral integrity ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue “Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) Technologies” was in session from 1 May 2019 to 31 May 2020. For this Special issue, we invited articles on current state-of-the-art technologies and solutions in G2V and V2G, including but not limited to the operation and control of gridable vehicles, energy storage and management systems, charging infrastructure and chargers, EV demand and load forecasting, V2G interfaces and applications, V2G and energy reliability and security, environmental impacts, and economic benefits as well as demonstration projects and case studies in the aforementioned areas. Articles that deal with the latest hot topics in V2G are of particular interest, such as V2G and demand-side response control technique, smart charging infrastructure and grid planning, advanced power electronics for V2G systems, adaptation of V2G systems in the smart grid, adaptation of smart cities for a large number of EVs, integration, and the optimization of V2G systems, utilities and transportation assets for advanced V2G systems, wireless power transfer systems for advanced V2G systems, fault detection, maintenance and diagnostics in V2G processes, communications protocols for V2G systems, energy management system (EMS) in V2G systems, IoT for V2G systems, distributed energy and storage systems for V2G, transportation networks and V2G, energy management for V2G, smart charging/discharging stations for efficient V2G, environmental and socio-economic benefits and challenges of V2G systems, and building integrated V2G systems (BIV2G). Five manuscripts are published in this Special Issue, including “An Ensemble Stochastic Forecasting Framework for Variable Distributed Demand Loads” by Agyeman et al., “Where Will You Park? Predicting Vehicle Locations for Vehicle-to-Grid, An MPC Scheme with Enhanced Active Voltage Vector Region for V2G Inverter” by Shipman et al., “Electric Vehicles Energy Management with V2G/G2V Multifactor Optimization of Smart Grids” by Xia et al., and “A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies” by Savitti et al.
    Keywords: vehicle-to-grid (V2G) ; vehicle-to-home (V2H) ; bi-directional charging topologies ; communication standards ; battery cycle ; smart grid ; optimization ; energy management ; electric vehicles ; distributed generation ; MPC ; AV2R ; V2G ; inverter ; vehicle-to-grid ; vehicle location prediction ; automated machine learning ; machine learning ; Bayesian ; deep neural network ; demand load forecast ; distributed load ; ensemble algorithm stochastic ; K-means ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-05
    Description: This Special Issue Book, “Marine Bioactive Peptides: Structure, Function, andTherapeutic Potential"" includes up-to-date information regarding bioactivepeptides isolated from marine organisms. Marine peptides have been found invarious phyla, and their numbers have grown in recent years. These peptidesare diverse in structure and possess broad-spectrum activities that have greatpotential for medical applications. Various marine peptides are evolutionaryancient molecular factors of innate immunity that play a key role in host defense.A plethora of biological activities, including antibacterial, antifungal, antiviral,anticancer, anticoagulant, endotoxin-binding, immune-modulating, etc., makemarine peptides an attractive molecular basis for drug design. This Special IssueBook presents new results in the isolation, structural elucidation, functionalcharacterization, and therapeutic potential evaluation of peptides found inmarine organisms. Chemical synthesis and biotechnological production of marinepeptides and their mimetics is also a focus of this Special Issue Book.
    Keywords: QH301-705.5 ; Q1-390 ; cone snail ; tilapia ; n/a ; animal models ; BRICHOS domain ; recombinant peptide ; calcium absorption ; plastein reaction ; antioxidant activity ; endothelial dysfunction ; C3a ; lung cancer ; invertebrate immunity ; identification ; zinc bioavailability ; NA-inhibitory peptide ; nuclear magnetic resonance (NMR) ; review ; ACE-inhibitory activity ; intestinal absorption ; hairtail (Trichiurus japonicas) ; DU-145 cells ; peptide ; crustacean ; venom duct ; Kalloconus ; drug design ; molecular symmetry ; arenicin ; ?-helix ; APETx2 ; conotoxins ; functional diversity ; docking ; conotoxin ; neuraminidase ; angiotensin II ; polychaeta ; influenza virus ; phylogeny ; gene expression ; host defense peptide ; Perinereis aibuhitensis ; anti-diabetic activity ; conopeptides ; SHRs ; Chlorella pyrenoidosa protein hydrolysate (CPPH) ; metastasis ; Caco-2 cell monolayer ; Nrf2 ; caco-2 cells ; HUVEC ; PYP15 ; sea cucumber ; decapeptide ; cytotoxic ; arenicin-1 ; marine peptides ; cell proliferation ; Conus ; Conus ateralbus ; self-production of hydrogen peroxide ; antimicrobial activity ; molecular dynamics ; machine learning ; tachyplesins ; ion channels ; gut microbiota ; Anthopleura anjunae oligopeptide ; signaling pathways ; half-fin anchovy hydrolysates ; NF-?B ; Chlorella pyrenoidosa protein hydrolysate-calcium chelate (CPPH-Ca) ; antihypertensive effect ; QAGLSPVR ; antimicrobial peptides ; vasculogenic mimicry ; antibacterial ; ?-hairpin ; innate immunity ; transcriptome sequencing ; HIF-1? ; Gracilariopsis lemaneiformis ; function ; ACE-inhibitory peptide ; complement ; peptide-zinc complex ; structure-activity relationship ; multi-functional peptides ; cod skin ; adsorption ; Maillard reaction products ; molecular docking ; antibacterial peptide ; PI3K/AKT/mTOR signaling pathway ; Arenicola marina ; structure–activity relationship ; antimicrobial peptide ; Rana-box ; acid-sensing ion channel ; Neptunea arthritica cumingii ; apoptosis ; membrane damage ; proteolytic system ; toxin ; polyphemusins ; computational studies ; muscle ; oyster zinc-binding peptide ; abalone ; pain relief ; transport routes ; cytotoxicity ; dexamethasone ; cell death ; host?microbe relationship ; anti-LPS factor ; MMPs ; protein synthesis ; structure ; Pyropia yezoensis peptide ; cone snails ; chemical synthesis ; prostate cancer ; Ugr 9-1 ; myotube atrophy ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Nowadays, more and more people realize the importance of global sustainability. Also, there has been an increasing number of quantitative studies investigating the connection between climate change and human societies in academia. Given this background, the Atmosphere Special Issue “Climate Change, Climatic Extremes, and Human Societies in the Past” aimed to highlight the major aspects of the climate-society nexus in ancient and recent human history. There are eight papers based on quantitative approaches to illustrate different forms of climate-society nexus in ancient, historical, and contemporary periods. Regarding ancient periods, the interconnection among climate, agriculture, and human societies is focused. Regarding historical periods, the non-linear and complex relationship between climate change and the positive checks (wars, famines, and epidemics) in historical China and pre-industrial Europe is revealed. Regarding contemporary periods, the papers focus on weather-related phenomena that significantly affect human societies. The complexity of those phenomena is also highlighted. The associated findings can help human societies to mitigate the adverse impacts of weather extremes better. This special issue contributes to the field of quantitative analysis of the climate-society nexus, both theoretically and methodologically, which could facilitate a more fruitful discussion about the climate-society nexus.
    Keywords: soil moisture–temperature coupling ; heatwaves ; multiple time scales ; correlation dimension method ; Geogdetector method ; interaction effect ; multi-scale ; climate change ; war ; imperial China ; Global Moran’s I ; Emerging Hot Spot Analysis ; plague ; direct and indirect effects ; Structural Equation Modelling ; drought ; regional interaction ; North China Famine of 1876–1879 ; human diet ; hierarchy ; bronze age ; carbon and nitrogen stable isotope ratios ; decision tree ; random forest ; precipitation prediction ; machine learning ; Yangtze River valley ; Yellow River valley ; rice cultivation ; millet cultivation ; precipitation ; Neolithic China ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: During the past five decades, we have witnessed a tremendous evolution in water resource system management. Three characteristics of this evolution are of particular note: First, the application of the systems approach to complex water management problems has been established as one of the most important advances in the field of water resource management. Second, the past five decades have brought a remarkable transformation of attitude in the water resource management community towards environmental concerns and action to address these concerns. Third, applying the principles of sustainability to water resource decision-making requires major changes in the objectives on which decisions are based, and an understanding of the complicated inter-relationships between existing ecological, economic, and social factors. The Special Issue includes 15 contributions that offer insights into contemporary problems, approaches, and issues related to the management of complex water resources systems. It will be presumptuous to say that these 15 contributions characterize the success or failure of the systems approach to support water resources decision-making. However, these contributions offer interesting lessons from current experiences and highlight possible future work.
    Keywords: system dynamics ; system analysis ; complex water system ; uncertainty assessment ; climate change ; regional climate models ; averaging procedures ; HEC-HMS ; Lim river ; Lim water systems ; n/a ; artificial recharge ; groundwater ; treated wastewater ; freshwater resources ; water footprint ; water management ; wine production ; winemaking sector ; Italy ; SuDS ; decision-making ; Soft Systems ; ANP ; modelling ; stakeholder ; systems analyses ; water resources ; planning ; management ; implementation ; political processes ; innovation ; impact ; multi-purpose dam ; water resources systems ; performance-based engineering ; simulation ; resilience ; disaster ; risk ; perception ; community ; Canada ; integrated urban watershed management ; group decision-support system ; risk analysis ; group consensus ; Kashafroud watershed ; water policy ; water portfolio planning ; water resources management ; systems assessment ; adaptive capacity ; coupled human–natural systems ; integrated water resources management ; sociohydrology ; modeling perspectives ; agent-based modeling ; differential equations ; uncertainty ; artificial intelligence ; machine learning ; water resource modelling ; multiobjective optimisation ; river abstraction ; reservoir operation ; stochastic dynamic programming ; fuzzy optimization ; reservoir-river system ; water quantity-quality management ; socio-hydrology ; hydro-sociology ; human-water systems ; human-nature systems ; social-ecological systems ; CHANS ; SES ; socio-hydrologic modeling ; IWRM ; hydrology ; multireservoir operations ; optimization ; multi-agent reinforcement learning ; aggregation–decomposition ; neural networks ; systems ; complexity ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Beyond its identification with the second law of thermodynamics, entropy is a formidable tool for describing systems in their relationship with their environment. This book proposes to go through some of these situations where the formulation of entropy, and more precisely, the production of entropy in out-of-equilibrium processes, makes it possible to forge an approach to the behavior of very different systems. Whether for dimensioning structures; influencing parameter variability; or optimizing power, efficiency, or waste heat reduction, simulations based on entropy production offer a tool that is both compact and reliable. In the case of systems marked by complexity, it appears to be the only way. In that sense, realistic optimization can be carried out, integrating within the same framework both the system and all the constraints and boundary conditions that define it. Simulations based on entropy give the researcher a powerful analytical framework that crosses the disciplines of physics and links them together.
    Keywords: segmented thermoelectric generator ; pulsed heat ; transient ; non-equilibrium quantum field theory ; quantum brain dynamics ; Kadanoff–Baym equation ; entropy ; super-radiance ; complex systems thermodynamics ; machine learning ; quantum phase transition ; Ising model ; variational autoencoder ; out of equilibrium thermodynamics ; finite time thermodynamics ; living systems ; polyelectrolytes ; Ohm law ; colloids ; Debye plasmas ; thermodynamics ; pressure-ionization ; electrical conductivity ; electronic entropy ; Seebeck coefficient ; transport ; LaFeSi ; FeRh ; CuNi ; thermoelectrics ; power conversion ; efficiency ; voltage-electrical current curve ; working point ; entropy pump mode ; generator mode ; power factor ; figure of merit ; Altenkirch-Ioffe model ; entropy production ; optimization ; reactor modelling ; irreversible thermodynamics ; TEG performance ; device modeling ; temperature profile ; constant properties model ; Fourier heat ; Thomson heat ; Joule heat ; thermoelectric materials ; energy harvesting ; thermoelectric generator ; working points ; maximum electrical power point ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Over the last two decades, satellite gravimetry has become a new remote sensing technique that provides a detailed global picture of the physical structure of the Earth. With the CHAMP, GRACE, GOCE and GRACE Follow-On missions, mass distribution and mass transport in the Earth system can be systematically observed and monitored from space. A wide range of Earth science disciplines benefit from these data, enabling improvements in applied models, providing new insights into Earth system processes (e.g., monitoring the global water cycle, ice sheet and glacier melting or sea-level rise) or establishing new operational services. Long time series of mass transport data are needed to disentangle anthropogenic and natural sources of climate change impacts on the Earth system. In order to secure sustained observations on a long-term basis, space agencies and the Earth science community are currently planning future satellite gravimetry mission concepts to enable higher accuracy and better spatial and temporal resolution. This Special Issue provides examples of recent improvements in gravity observation techniques and data processing and analysis, applications in the fields of hydrology, glaciology and solid Earth based on satellite gravimetry data, as well as concepts of future satellite constellations for monitoring mass transport in the Earth system.
    Keywords: terrestrial water storage (TWS) ; GRACE ; GLDAS ; TRMM ; drought ; ENSO ; NAO ; Turkey ; Mass balance ; Ice Sheets ; Sea-level Rise ; Antarctica ; CryoSat-2 ; GRACE-Follow On ; GRACE-FO ; downward continuation ; spectral methods ; gravity field recovery ; GRACE Follow-On ; orbit configuration ; synergistic observation ; mass transport in the Earth system ; GRACE and GRACE follow-on mission ; current and future observation concepts and instruments ; GRACE TWSA ; groundwater level anomaly ; downscaling ; machine learning ; boosted regression trees ; glacial sediment ; ice mass ; satellite gravimetry ; Patagonia ; ice mass change ; SLR ; swarm ; normal equation combination ; coseismic gravity gradient changes ; gravity field model ; GOCE ; Earth’s gravity field ; kinematic orbit ; kinematic baseline ; time-variable gravity ; geocenter ; reference frames ; self-attraction and loading ; Level-2 processing ; time-variable gravity field ; mass change monitoring ; next-generation gravity mission ; temporal gravity field ; numerical closed-loop simulation ; satellite mission constellations ; mass transport ; gravity field satellite missions ; GOCE High-Level Processing Facility (HPF), earth gravity field ; geoid ; spectral enhancement method (SEM), GPS/leveling ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: The concept of a circular economy relies on waste reduction, valorization, and recycling. Global trends for “green” synthesis of chemicals have positioned the field of enzyme technology and biocatalysis (multi-enzymes and whole-cells) as an alternative for the synthesis of more social- and environmentally-responsible bio-based chemicals. Recent advances in synthetic biology, computational tools, and metabolic engineering have supported the discovery of new enzymes and the rational design of whole-cell biocatalysts. In this book, we highlight these current advances in the field of biocatalysis, with special emphasis on novel enzymes and whole-cell biocatalysts for applications in several industrial biotechnological applications.
    Keywords: 2G ethanol ; hemicellulose usage ; S. cerevisiae ; enzyme immobilization ; cell immobilization ; SHIF ; mannonate dehydratase ; mannose metabolism ; Thermoplasma acidophilum ; mannono-1,4-lactone ; 2-keto-3-deoxygluconate ; aldohexose dehydrogenase ; cyclodextrin glucanotransferases ; large-ring cyclodextrins ; semi rational mutagenesis ; carbohydrate active enzymes ; archaea ; glycosidase ; Sulfolobus solfataricus ; Saccharolobus solfataricus ; Lactobacillus ; β-galactosidase ; immobilization ; cell surface display ; LysM domains ; biocatalysis ; extremophile ; 5-hydroxymethylfurfural ; 5-hydroxymethylfuroic acid ; platform chemicals ; whole cells ; New Delhi metallo-β-lactamase ; NDM-24 ; kinetic profile ; secondary structure ; glycoside hydrolase ; thioglycosides ; Fervidobacterium ; endo-β-1,3-glucanase ; laminarinase ; thermostable ; gene duplication ; cofactor F420 ; deazaflavin ; oxidoreductase ; hydride transfer ; hydrogenation ; asymmetric synthesis ; cofactor biosynthesis ; ω-transaminase ; α-methylbenzylamine ; chiral amine ; biotransformation ; biodiesel ; waste cooking oil ; lipase immobilization ; interfacial activation ; functionalized magnetic nanoparticles ; DNase ; kinetic profiles ; RNase ; semi-rational mutagenesis ; substrate specificity ; engineered Escherichia coli ; flavonoid glucuronides ; multienzyme whole-cell biocatalyst ; organic solvents ; psychrophilic yeast ; hormone-sensitive lipase ; Glaciozyma antarctica ; Antarctica and homology modelling ; keratinase ; serine protease ; metalloprotease ; peptidase ; keratin hydrolysis ; keratin waste ; valorisation ; bioactive peptides ; ene reductase ; enzyme sourcing ; old yellow enzyme ; solvent stability ; machine learning ; flux optimization ; artificial neural network ; synthetic biology ; glycolysis ; metabolic pathways optimization ; cell-free systems ; hydrolase ; lipase ; esterase ; Bacillus subtilis lipase A ; transesterification ; organic solvent ; water activity ; immobilized lipase ; RSM ; fuel properties ; chemo-enzymatic synthesis ; glycosyl transferases ; protein engineering ; carbohydrates ; industrial enzymes ; thermostable enzymes ; glycoside hydrolases ; cell-free biocatalysis ; natural and non-natural multi-enzyme pathways ; bio-based chemicals ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Artificial intelligence techniques, such as expert systems, fuzzy logic, and artificial neural network techniques have become efficient tools in modeling and control applications. For example, there are several benefits in optimizing cost-effectiveness, because fuzzy logic is a methodology for the handling of inexact, imprecise, qualitative, fuzzy, and verbal information systematically and rigorously. A neuro-fuzzy controller generates or tunes the rules or membership functions of a fuzzy controller with an artificial neural network approach. There are new instantaneous power theories that may address several challenges in power quality. So, this book presents different applications of artificial intelligence techniques in advanced high-tech electronics, such as applications in power electronics, motor drives, renewable energy systems and smart grids.
    Keywords: droop curve ; frequency regulation ; fuzzy logic ; the rate of change of frequency ; reserve power ; smart grid ; energy Internet ; convolutional neural network ; decision optimization ; deep reinforcement learning ; electric load forecasting ; non-dominated sorting genetic algorithm II ; multi-layer perceptron ; adaptive neuro-fuzzy inference system ; meta-heuristic algorithms ; automatic generation control ; fuzzy neural network control ; thermostatically controlled loads ; back propagation algorithm ; particle swarm optimization ; load disaggregation ; artificial intelligence ; cognitive meters ; machine learning ; state machine ; NILM ; non-technical losses ; semi-supervised learning ; knowledge embed ; deep learning ; distribution network equipment ; condition assessment ; multi information source ; fuzzy iteration ; current balancing algorithm ; level-shifted SPWM ; medium-voltage applications ; multilevel current source inverter ; motor drives ; phase-shifted carrier SPWM ; STATCOM ; electricity forecasting ; CNN–LSTM ; very short-term forecasting (VSTF) ; short-term forecasting (STF) ; medium-term forecasting (MTF) ; long-term forecasting (LTF) ; asynchronous motor ; linear active disturbance rejection control ; error differentiation ; vector control ; renewable energy ; solar power plant ; Data Envelopment Analysis (DEA) ; Fuzzy Analytical Network Process (FANP) ; Fuzzy Theory ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 78
    Publication Date: 2023-12-21
    Description: The prefrontal cortex (PFC) plays a pivotal role in regulating our emotions. The importance of ventromedial regions in emotion regulation, including the ventral sector of the medial PFC, the medial sector of the orbital cortex and subgenual cingulate cortex, have been recognized for a long time. However, it is increasingly apparent that lateral and dorsal regions of the PFC, as well as neighbouring dorsal anterior cingulate cortex, also play a role. Defining the underlying psychological mechanisms by which these functionally distinct regions modulate emotions and the nature and extent of their interactions is a critical step towards better stratification of the symptoms of mood and anxiety disorders. It is also important to extend our understanding of these prefrontal circuits in development. Specifically, it is important to determine whether they exhibit differential sensitivity to perturbations by known risk factors such as stress and inflammation at distinct developmental epochs. This Special Issue brings together the most recent research in humans and other animals that addresses these important issues, and in doing so, highlights the value of the translational approach.
    Keywords: R5-920 ; RC321-571 ; norepinephrine ; medial prefrontal cortex ; fear extinction ; emotion regulation ; emotion processing ; connectivity ; anticipatory arousal ; Pavlovian ; triadic neural systems model ; prelimbic ; development ; positive and negative ; rat ; Williams Syndrome ; psychological treatment ; glia density ; anxiety ; fMRI ; area 25 ; anhedonia ; adolescence ; adolescent ; autonomic ; amygdala ; neuron density ; neural ; prefrontal cortex ; reliability ; functional magnetic resonance imaging (fMRI) ; networks ; cAMP ; cognitive control ; extinction ; infralimbic ; NMDA ; reward ; calcium ; stress adolescence ; BDNF ; machine learning ; negative affect ; hierarchical control ; emotion ; occasion setting ; serotonin transporter ; ventromedial prefrontal cortex ; psychophysiology ; depression ; aging ; dopamine ; age ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This text will provide the most recent knowledge and advances in the area of molecular computing and bioinformatics. Molecular computing and bioinformatics have a close relationship, paying attention to the same object but working towards different orientations. The articles will range from topics such as DNA computing and membrane computing to specific biomedical applications, including drug R&D and disease analysis.
    Keywords: TP248.13-248.65 ; T1-995 ; systems biology ; join graph ; hierarchical support vector regression ; transcription factor ; brain storm optimization ; heterogeneous information network embedding ; structural patterns ; gene fusion data ; Panax ginseng ; flowering plant ; geometric arithmetic index ; interspecies transmission ; iron-depleted ; drug discovery ; protein ; protein targeting ; recursively enumerable function ; Mycoplasma hominis ; environmental factor ; Alzheimer’s disease ; absorption ; angiogenesis ; classification ; self-organizing systems ; enzymatic numerical P system ; excretion ; atom-bond connectivity index ; molecular learning ; DNA coding ; phylogeny ; bone formation ; DCL1 ; line graph ; pseudo dinucleotide composition ; load balancing ; K2 ; efflux ratio ; osteogenesis ; distribution ; NanoString Technologies ; RAST server ; 8-bit adder/subtractor ; gene networks ; dihydrouridine ; structure information ; Cartesian product graph ; domain label ; stacking denoising auto-encoder ; DNA computing ; Stenotrophomonas maltophilia ; pattern classification ; stress ; causal direction learning ; machine learning ; adverse drug reaction prediction ; membrane computing ; support vector machine ; Brassica napus ; miRNA biogenesis ; identification of Chinese herbal medicines ; bio-inspired ; toxicity ; protein transduction domain ; RNA ; sequence information ; multiple interaction networks ; in silico ; protein complex ; drug ; low-dimensional representation ; gene coding protein ; amino acid mutation ; Bayesian causal model ; edge detection ; big data ; function prediction ; parallel computing ; resolution free ; Hamming distance ; cascade ; oligopeptide transporter ; DNA barcoding technology ; DNA strand displacement ; protein–protein interaction (PPI) ; biomedical text mining ; bioinformatics ; metabolism ; hypoxia-inducible factor-1? ; nucleotide physicochemical property ; Turing universality ; diabetes mellitus ; chaotic map ; multinetwork integration ; bacterial computing ; lignification ; penalized matrix decomposition ; ensemble classifier ; bacteria and plasmid system ; similarity network ; RNA secondary structure ; avian influenza virus ; evaluating driver partner ; image encryption ; siderophores ; meta-path-based proximity ; P-glycoprotein ; Tianhe-2 ; prostate cancer ; iron acquisition systems ; biochip technology ; gene susceptibility prioritization ; laccase ; DNA ; molecular computing ; microRNA ; clustering ; drug-target interaction prediction ; endoplasmic reticulum ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-29
    Description: This book comprises research articles contributed to the Special Issue on “ERP and EEG Markers of Brain Visual Attentional Processing” of the Brain Sciences journal by a panel of authoritative international cognitive neuroscientists and electrophysiologists. All articles present state-of-the-art knowledge on the relationships between visuospatial attentional processing and the brain in humans as investigated by means of EEG and ERPs from the perspective of cognitive neuroscience. All the articles compare overt behavioral data obtained in universally renowned visual selective attention protocols with the electrophysiological data obtained in these same protocols aimed at investigating different facets of visuospatial attentional processing. The research presented is interdisciplinary, ranging across visual selective processing mechanisms in health, the effects of psychological attentional dysfunctions and brain damage, and functional imaging of the human brain. The Preface of the book provides an overall theoretical introduction to the field and to the contents of each of the remaining articles. In this introductory Editorial, a framework is presented in which to consider EEG and ERPs as research tools able to contribute to both cognitive and brain sciences, putting together new knowledge about humans as integrated sociobiological individuals. This book may provide a useful starting point and reference for researchers and students of cognitive neuroscience, psychology, philosophy, or cognitive science who have an interest in mind and brain visual attentional processing.
    Keywords: selective attention ; mental ability ; P3 latency ; continuous performance test ; mental speed ; EEG ; alpha ; xi ; Posner ; covert attention ; object-based attention ; hemispheric asymmetry ; ERP ; selection negativity ; swLORETA ; anterior cingulate cortex ; visual recognition ; mTBI ; event-related potentials ; visual–attentional processing ; brain connectivity ; neuropsychological measures ; postconcussion symptoms ; rsvp ; lure stimuli ; priming ; ERPs ; N2pc ; perception ; video ; visual motion ; speed ; cortex ; rhythm ; entrainment ; working-memory training ; cognitive remediation ; P1 ; P3b ; N500 ; late posterior negative slow wave ; late parietal negativity ; ADHD ; performance monitoring ; error processing ; visual sustained selective attention ; voluntary control ; self-regulation ; executive functions ; preschool children ; ACT–R ; Dipole analysis ; spiking simulation ; FFT ; alpha desynchronization ; attention orienting ; alerting ; attention inhibition ; neurocognitive perceptual and motor workload ; hypoxia ; overt motor responses ; hemispheric lateralization ; category learning ; eeg ; machine learning ; erp ; memory ; learning ; multiple memory systems ; p300 ; brain visual attentional processing ; neural markers ; intracerebral single and distributed electric source localization analyses ; hemodynamic imaging ; psychological sciences ; cognitive neurosciences ; bic Book Industry Communication::J Society & social sciences::JM Psychology ; thema EDItEUR::J Society and Social Sciences::JM Psychology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue addresses the important issue of the energy efficiency of both manufacturing processes and systems. Manufacturing is responsible for one-third of global energy consumption and CO2 emissions. Thus, improving the energy efficiency of production has been the focus of research in recent years. Energy efficiency has begun to be considered as one of the key decision-making attributes for manufacturing. This book includes recent studies on methods for the measurement of energy efficiency, tools and techniques for the analysis and development of improvements with regards to energy consumption, modeling and simulation of energy efficiency, and the integration of green and lean manufacturing. This book presents a breadth of relevant information, material, and knowledge to support research, policy-making, practices, and experience transferability to address the issues of energy efficiency.
    Keywords: energy consumption ; scheduling approach ; mixed-flow shop ; multi-objective optimisation ; tardiness fine ; energy efficiency ; sustainable machining ; multi-objective optimization ; multi-criteria decision making method ; small quantity cooling lubrication SQCL ; cu nanofluid ; remote laser welding ; energy-efficient process ; machine learning ; welding process ; neural network ; knowledge representation ; fuzzy reasoning Petri net ; energy efficient operation ; manufacturing system ; Manufacturing ; life-cycle assessment ; aluminum ; cast iron ; pulp ; paper ; structural change ; compressed air systems ; energy data analysis ; energy measures ; performance control ; operations ; maintenance ; energy accounting ; laser drilling ; percussion ; trepanning ; productivity ; cost ; material removal rate (MRR) ; specific energy consumption (SEC) ; Taguchi ; hole taper ; IN 718 ; electric discharge machining ; response surface methodology ; sustainability ; surface quality ; microstructure ; multi-criteria decision making ; process planning ; manufacturing energy efficiency ; clean manufacturing ; sustainable manufacturing ; digital manufacturing ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In this Special Issue on human health engineering, we invited submissions exploring recent contributions to the field of human health engineering, which is the technology used for monitoring the physical or mental health status of individuals in a variety of applications. Contributions focused on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main aspects of the monitoring and control engineering scheme applied to human health applications, including papers focusing on measuring/sensing physiological variables, contributions describing research on the modelling of biological signals, papers highlighting health monitoring applications, and finally examples of control applications for human health. In comparison to biomedical engineering, the field of human health engineering also covers applications on healthy humans (e.g., sports, sleep, and stress) and thus not only contributes to develop technology for curing patients or supporting chronically ill people, but also more generally for disease prevention and optimizing human well-being.
    Keywords: TA1-2040 ; T1-995 ; n/a ; smartphone ; information technology ; stoop ; pain minimum compressive pressure ; pulse wave ; knee joint ; health information ; gait characteristics ; stance assistance ; air-trapping ; youth ; harmonization ; missing data ; wearable device ; decision tree ; usability ; children ; shoulder ; walking speed ; body-plethysmography ; lifting technique ; bicycle helmet ; smart wearables ; personalized model ; finite element simulation ; streaming algorithm ; thermoregulation ; soft walking assistive robot ; machine leaning ; simultaneous EEG–fMRI ; magnetorheological brake ; gradient artefact ; cohort studies ; long-term effect ; mortality prediction ; distal skin temperature ; model predictive control ; support-vector-machine ; ADHD ; sliding mode control ; reliability ; orthosis control ; SVM ; interface formats ; emphysema ; ligament ; Van der Pol ; quality function deployment ; FitzHugh–Nagumo ; insole foot area ; arm ; alveolar pressure ; contour of shoe insole ; emotional reaction ; oxygen uptake ; machine learning ; elderly person ; thermal comfort ; homeostasis ; hard-margin support vector machines ; ankle torque ; dystonia ; airflow limitation ; feature engineering ; zonal performance characteristics ; validity ; novel ; COPD ; forced expiration ; remoteness ; screening ; mobility scale ; mHealth ; work-related musculoskeletal disorders ; musculoskeletal modeling ; control parameter reference ; freestyle skiing aerials ; VO2 ; cyberaddiction ; pulse oximeter ; intensive care unit ; control system ; muscle modeling ; dynamic model ; airway resistance ; relaxation oscillator ; wearable devices ; four-wheeled rollator ; adaptive model ; body mass index ; electrocardiographic signal ; weight loss ; calcaneal spur ; Hill muscle ; anxiety ; spirometry ; cold-induced-vasoconstriction ; bicycle helmets ; spherical phantom ; antagonistic actuator ; kinetics ; internet ; choreoathetosis ; thermal manikin ; fractional calculus ; squat ; rehabilitation robotics ; cold-induced-vasodilation ; exercise testing ; artefact correction ; swarm optimization ; multiple imputations ; photoplethysmogram ; powered mobility ; head-shaped phantom ; specific airway conductance ; computed tomography ; streaming data ; back loading ; dynamic modelling ; meta-analysis ; pneumatic artificial muscle ; adaptive control ; convective and evaporative heat loss ; spine ; thermal sensation ; driver drowsiness ; movement disorder ; ankle angular velocity ; heart model ; older adults ; new technologies ; blood pressure estimation ; Kano-TRIZ design theory ; dyskinetic cerebral palsy ; nomophobia ; chronic obstructive pulmonary disease ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 83
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: River discharge is a fundamental hydrologic quantity that summarizes how a watershed transforms the input of precipitation into output as channelized streamflow. Accurate discharge measurements are critical for a range of applications including water supply, navigation, recreation, management of in-stream habitat, and the prediction and monitoring of floods and droughts. However, the traditional stream gage networks that provide such data are sparse and declining. Remote sensing represents an appealing alternative for obtaining streamflow information. Potential advantages include greater efficiency, expanded coverage, increased measurement frequency, lower cost and reduced risk to field personnel. In addition, remote sensing provides opportunities to examine long river segments with continuous coverage and high spatial resolution. To realize these benefits, research must focus on the remote measurement of flow velocity, channel geometry and their product: river discharge. This Special Issue fostered the development of novel methods for retrieving discharge and its components, and thus stimulated progress toward an operational capacity for streamflow monitoring. The papers herein address all aspects of the remote measurement of streamflow—estimation of flow velocity, bathymetry (water depth), and discharge—from various types of remotely sensed data acquired from a range of platforms: manned and unmanned aircraft, satellites, and ground-based non-contact sensors.
    Keywords: estuary ; morphology ; rapid assessment ; bathymetry ; flow velocity ; salinity ; tool ; remotely-sensed imagery ; small unmanned aerial system (sUAS) ; river flow ; thermal infrared imagery ; particle image velocimetry ; lidar bathymetry ; fluvial ; geomorphology ; change detection ; remotely piloted aircraft system ; refraction correction ; structure-from-motion photogrammetry ; water surface elevation ; topographic error ; machine learning ; UAV LiDAR ; airborne laser bathymetry ; full waveform processing ; performance assessment ; high resolution hydro-mapping ; remote sensing ; rivers ; discharge ; hydrology ; modelling ; ungauged basins ; Alaska ; river ; PIV ; large-scale particle image velocimetry ; LSPIV ; surface velocity ; river discharge ; Doppler radar ; pulsed radar ; probability concept ; water temperature ; salmonids ; Pend Oreille River ; thermal infrared (TIR) ; acoustic Doppler current profiler (ADCP) ; channel bathymetry ; cold-water refuge ; dam ; flooding ; high-water marks (HWMs) ; small unmanned aircraft systems (sUAS) ; drone ; photogrammetry ; hydraulic modeling ; aerial photography ; surveying ; inundation ; Landsat ; streamflow ; flow frequency ; satellite revisit time ; flow regime ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 84
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.
    Keywords: deposit insurance ; implied volatility ; static arbitrage ; parameterization ; machine learning ; calibration ; dichotomous response ; predictive model ; tree boosting ; GLM ; validation ; generalised linear modelling ; zero-inflated poisson model ; telematics ; benchmark ; cross-validation ; prediction ; stock return volatility ; long-term forecasts ; overlapping returns ; autocorrelation ; chain ladder ; Bornhuetter–Ferguson ; maximum likelihood ; exponential families ; canonical parameters ; prior knowledge ; accelerated failure time model ; chain-ladder method ; local linear kernel estimation ; non-life reserving ; operational time ; zero-inflation ; overdispersion ; automobile insurance ; risk classification ; risk selection ; least-squares monte carlo method ; proxy modeling ; life insurance ; Solvency II ; claims prediction ; export credit insurance ; semiparametric modeling ; VaR estimation ; analyzing financial data ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 85
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-20
    Description: There are many different theories of intelligence. Although these theories differ in their nuances, nearly all agree that there are multiple cognitive abilities and that they differ in the breadth of content they are typically associated with. There is much less agreement about the relative importance of cognitive abilities of differing generality for predicting important real-world outcomes, such as educational achievement, career success, job performance, and health. Some investigators believe that narrower abilities hold little predictive power once general abilities have been accounted for. Other investigators contend that specific abilities are often as—or even more—effective in forecasting many practical variables as general abilities. These disagreements often turn on differences of theory and methodology that are both subtle and complex. The five cutting-edge contributions in this volume, both empirical and theoretical, advance the conversation in this vigorous, and highly important, scientific debate.
    Keywords: BF1-990 ; general cognitive ability ; second stratum abilities ; narrow abilities ; cognitive abilities ; ability tilt ; identification ; occupational attainment ; scholastic performance ; longevity ; non-g residuals ; specific abilities ; higher-order factor model ; bifactor model ; intelligence ; general intelligence (g) ; specific factors ; academic achievement ; hierarchical factor model ; educational attainment ; nested-factor models ; ability differentiation ; general abilities ; relative importance ; relative importance analysis ; bifactor(S-1) model ; subscores ; g-factor ; school grades ; non-g factors ; nested-factors model ; general mental ability ; cognitive tests ; specific cognitive abilities ; curvilinear relations ; specific ability ; situational specificity ; predictor-criterion bandwidth alignment ; job performance ; health ; machine learning ; academic performance ; general factor ; bic Book Industry Communication::J Society & social sciences::JM Psychology
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  • 86
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem-solving. These algorithms have the capacity to generalize and discover knowledge for themselves and to learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves the mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topics range from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspired filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensor signal processing.
    Keywords: geometric calibration ; long- and short-period errors ; equivalent bias angles ; sparse recovery ; linear array push-broom sensor ; deep learning ; signal detection ; modulation classification ; the single shot multibox detector networks ; the multi-inputs convolutional neural networks ; medical image registration ; similarity measure ; non-rigid transformation ; computational efficiency ; registration accuracy ; signal denoising ; singular value decomposition ; Akaike information criterion ; reaction wheel ; micro-vibration ; permutation entropy (PE) ; weighted-permutation entropy (W-PE) ; reverse permutation entropy (RPE) ; reverse dispersion entropy (RDE) ; time series analysis ; complexity ; sensor signal ; tensor principal component pursuit ; stable recovery ; tensor SVD ; ADMM ; kalman filter ; nonlinear autoregressive ; neural network ; noise filtering ; multiple-input multiple-output (MIMO) ; frequency-hopping code ; dual-function radar-communications ; information embedding ; mutual information (mi) ; waveform optimization ; spectroscopy ; compressed sensing ; inverse problems ; dictionary learning ; image registration ; large deformation ; weakly supervised ; high-order cumulant ; cyclic spectrum ; decision tree–support vector machine ; wind turbine ; gearbox fault ; cosine loss ; long short-term memory network ; indoor localization ; CSI ; fingerprinting ; Bayesian tracking ; image reconstruction ; computed tomography ; nonlocal total variation ; sparse-view CT ; low-dose CT ; proximal splitting ; row-action ; brain CT image ; audio signal processing ; sound event classification ; nonnegative matric factorization ; blind signal separation ; support vector machines ; brain-computer interface ; motor imagery ; machine learning ; internet of things ; pianists ; surface inspection ; aluminum ingot ; mask gradient response ; Difference of Gaussian ; inception-v3 ; EEG ; sleep stage ; wavelet packet ; state space model ; image captioning ; three-dimensional (3D) vision ; human-robot interaction ; Laplacian scores ; data reduction ; sensors ; Internet of Things (IoT) ; LoRaWAN ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 87
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book presents collective works published in the recent Special Issue (SI) entitled " Digital Signal, Image and Video Processing for Emerging Multimedia Technology". These works address the emerging technology in signal processing and its new aspects, as well as the related applications. Recent developments in image/video-based deep learning technology have enabled new services in the field of multimedia and recognition technology. The applications vary and range from digital signal processing to image, video and multimedia signal processing, also including object classification, learning mechanism design and data security. Recent advances in numerical, theoretical and experimental methodologies are presented within the scope of the current book, along with the finding of new learning methods and new methodological developments and their limitations. This book brings together a collection of inter-/multidisciplinary works applied to many classification and data security applications in a coherent manner.
    Keywords: closed circuit television (CCTV) ; character order preserving ; cloud system ; privacy risk ; security ; video surveillance ; 3D ; depth map ; inter-component prediction ; MVD ; reversible data hiding ; texture ; wavelet analysis ; deep learning ; super-resolution ; deep neural architecture ; pattern mining ; multi-scale analysis ; reversible data hiding (RDH) ; image processing ; cloud computing ; public key cryptography (PKC) ; classification ; content–based image retrieval ; genetic algorithms ; image retrieval ; image classification ; Wiener-Granger causality ; block-compressive sensing (BCS) ; saliency ; error analysis ; flexible partitioning ; step-less adaptive sampling ; non-linear filters ; MCV and MLV filters ; de-noising ; noise removal ; edge preserving ; video coding ; motion estimation ; motion compensation ; affine motion model ; perspective motion model ; VVC ; quantization (signal) ; channel allocation ; scalable video coding ; convolution neural network ; scene recognition ; vector of locally aggregated descriptor ; weakly supervised attention map ; fire and smoke detection ; spatial and temporal ; wavelet transform ; coefficient of variation ; image steganalysis ; WOW ; UNIWARD ; ternary classification ; convolutional neural network (CNN) ; bayesian optimization ; gaussian process ; learning rate ; acauisition function ; machine learning ; moving object ; image stabilization ; object detection ; optical flow ; surveillance ; UAVs ; multiview high efficiency video coding ; ρ model ; bit allocation ; rate control ; image similarity ; frame complexity ; image deblurring ; generative adversarial network ; Wasserstein distance ; adversarial loss ; perceptual loss ; sentiment analysis ; social media ; lexicon ; image fusion ; multi-focus ; trimaps ; focus maps ; VisDrone2019 ; aerial imagery ; Faster R-CNN ; SSD ; RFCN ; YOLOv3 ; RetinaNet ; SNIPER ; CenterNet ; wrist-mounted DiverPAD ; electrical insulator ; capacitive touchscreen ; marine leisure activities ; convolutional neural networks ; pattern recognition ; low light ; image restoration ; denoise ; noise reduction ; deep leaning ; multiple feature ; dependency detection ; surveillance system ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 88
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The Special Issue “Non-Destructive Testing of Structures” has been proposed to present the recent developments in the field of the diagnostics of structural materials and components in civil and mechanical engineering. The papers highlighted in this editorial concern various aspects of non-invasive diagnostics, including such topics as the condition assessments of civil and mechanical structures and the connections of structural elements, the inspection of cultural heritage monuments, the testing of structural materials, structural health monitoring systems, the integration of non-destructive testing methods, advanced signal processing for the non-destructive testing of structures (NDT), damage detection and damage imaging, as well as modeling and numerical analyses for supporting structural health monitoring (SHM) systems.
    Keywords: capillary-based structural health monitoring ; fatigue crack growth ; fatigue crack initiation ; XFEM ; straight lug ; cast-in-place concrete ; temperature ; boundary conditions ; on-line monitoring ; numerical simulations ; strength ; extradosed bridge ; SHM system ; delamination ; width-to-depth ratio (WTDR) ; concrete bridge deck ; handheld IR camera (H-IRC) ; UAV IR camera (UAV-IRC) ; passive IRT ; non-destructive technique ; concrete structure ; non-destructive evaluation ; crack effect ; metal magnetic memory ; magnetic intensity gradient ; stress ; non-destructive testing ; ultrasonic tomography ; graph theory ; concrete ; damage mechanics ; elastic degradation ; damage parameter ; internal length ; experimental research ; methodology ; floors ; cement-based materials ; casting ; forming ; non-destructive and semi-destructive tests ; laser scanning ; photogrammetry ; tachymetry ; bridge deflection ; non-contact measurement ; wave propagation ; damage detection ; numerical modelling ; hardness ; Barkhausen noise ; number of events ; non-destructive testing inverse problem ; adhesive joint ; concrete beam ; guided waves ; debonding ; damage imaging ; root mean square ; cracking pattern ; cracks ; cement composites ; image analysis ; historical floor ; integrated diagnostics ; ground penetrating radar ; ultrasonic testing ; in situ surveys ; finite-difference time-domain modeling ; masonry structures ; autoclaved aerated concrete masonry units (AAC) ; compressive strength ; minor-destructive (MDT) techniques ; non-destructive techniques (NDT) ; acoustoelastic effect (AE) ; quasi-brittle cement composites ; acoustic emission ; acoustic spectrum ; micro events ; acoustic nondestructive methods ; large format tiles ; real-life application ; mechanical load ; failure ; vibration signal analysis ; nondestructive testing ; Kalman filtering ; parameter identification ; magnetic Barkhausen noise ; magnetic anisotropy ; grain oriented steel ; time-frequency representation ; signal processing ; data mining methods ; digital image correlation ; region-based convolutional neural network ; machine learning ; crack monitoring ; crack detection and localization ; elastic waves ; neural networks ; force prediction ; flange connection ; static test ; soil-steel bridge ; terrestrial laser scanning ; finite element method (FEM) ; modelling and simulations ; material parameters identification ; vibration measurements ; testing ; operational modal analysis ; lighthouse ; historic tower ; steel structures ; stressed-skin effect ; diaphragm design ; trapezoidal sheeting ; condition assessment of steel structure ; structural health monitoring ; civil engineering structures ; mechanical structures ; damage detection and visualization ; modeling and simulations ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 89
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-20
    Description: There is no denying the role of empirical research in finance and the remarkable progress of empirical techniques in this research field. This Special Issue focuses on the broad topic of “Empirical Finance” and includes novel empirical research associated with financial data. One example includes the application of novel empirical techniques, such as machine learning, data mining, wavelet transform, copula analysis, and TV-VAR, to financial data. The Special Issue includes contributions on empirical finance, such as algorithmic trading, market efficiency, market microstructure, portfolio theory and asset allocation, asset pricing models, liquidity risk premium, currency crisis, return predictability, and volatility modeling.
    Keywords: HC10-1085 ; n/a ; short-term forecasting ; wavelet transform ; IPO ; volatility ; US dollar ; institutional investors’ shareholdings ; neural network ; financial market stress ; market microstructure ; text similarity ; TVP-VAR model ; Japanese yen ; convolutional neural networks ; global financial crisis ; deep neural network ; cross-correlation function ; boosting ; causality-in-variance ; flight to quality ; bagging ; earnings quality ; algorithmic trading ; stop loss ; statistical arbitrage ; ensemble learning ; liquidity risk premium ; gold return ; futures market ; take profit ; currency crisis ; spark spread ; city banks ; piecewise regression model ; financial and non-financial variables ; exports ; data mining ; latency ; crude oil futures prices forecasting ; random forests ; wholesale electricity ; SVM ; random forest ; bank credit ; deep learning ; Vietnam ; inertia ; MACD ; initial public offering ; text mining ; bankruptcy prediction ; exchange rate ; asset pricing model ; LSTM ; panel data model ; structural break ; credit risk ; housing and stock markets ; copula ; ARDL ; earnings manipulation ; machine learning ; natural gas ; housing price ; asymmetric dependence ; real estate development loans ; earnings management ; cointegration ; predictive accuracy ; robust regression ; quantile regression ; dependence structure ; housing loans ; price discovery ; utility of international currency ; ATR ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCZ Economic history
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  • 90
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-01-31
    Description: Ocean optics is a branch of oceanography which is firmly embedded in studies of a great variety of ocean science and engineering questions. The interactive nature between radiative transfer of light and various dissolved and particulate constituents of seawater is at the core of ocean optics science and applications. The transfer of radiant solar energy has vital implications to life and climate on Earth, and the large variety of subjects of ocean optics ranges from the subtle problems of physical optics to optical remote sensing towards a better understanding of ocean biology, biogeochemistry and ecosystems and their roles in the Earth's system processes. The intention of this book is to present a collection of papers that generally share a common denominator of frontier topics in ocean optics which are unique, uncommon or outstanding in the literature, and to provide a balanced view of the extraordinary breadth of research in this field. Topics as diverse as measurements and modeling of radiative transfer, light fields, light scattering and polarization, ocean color, benthic optical properties, and the use of optics for characterizing seawater constituents are addressed in this book. The book is expected to be of interest and useful to a broad audience of professional ocean scientists, engineers and advanced students with an interest in ocean optics and applications of optical methods in oceanography.
    Keywords: GC1-1581 ; Q1-390 ; atmosphere ; radiative transfer ; ocean colour ; phytoplankton pigments ; satellite radiometry ; light scattering by pure water ; upward radiance ; CDOM and ENSO ; chromophoric dissolved organic matter ; irradiance quartet ; PFT ; FerryBox ; marine sensors ; Kallemeter ; DOM ; retrieval uncertainty ; particle dynamics ; suspended sediment ; downward irradiance ; sea ice heterogeneity ; optical properties ; inelastic processes ; MERIS ; bottom mapping ; FDOM ; NASA PACE mission ; volume scattering function ; ocean color algorithm validation ; Gelbstoff ; hyperspectral ; ocean euphotic zone ; light scattering ; ocean color database ; upwelling radiance distribution ; degree of linear polarization ; light scattering measurements ; polarization ; 3D Monte Carlo numerical simulations ; apparent optical properties ; EEMS ; machine learning ; bulk refractive index ; sensor noise ; remote-sensing reflectance ; coated-sphere model ; PARAFAC ; forward modeling ; coral reef ; oceanic carbon ; chlorophyll-a ; fractal structure ; shallow water ; melt ponds ; canopy ; coral ; phytoplankton ; backscattering ratio ; CDOM climatology ; remote sensing ; algorithm development ; ocean ; LISST-VSF instrument ; bathymetry ; suspended matter ; anomalous properties of water ; optical modelling ; marine optics ; derivative ; coupled systems ; ocean color ; light scattering by pure seawater ; CDOM spectral slope ; Gershun equation ; inverse problems ; ocean optics ; vertical attenuation coefficient ; organic carbon ; marine particles ; CDOM ; seawater component ; global oceans ; vector radiative transfer ; radiative transfer approximation ; oceanic light field ; Mueller matrix ; Trondheimsfjord ; Norway ; volume and surface integral methods ; ocean color remote sensing ; natural organic matter ; inherent optical properties ; dissolved organic carbon
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  • 91
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The book “Assessment of Renewable Energy Resources with Remote Sensing" focuses on disseminating scientific knowledge and technological developments for the assessment and forecasting of renewable energy resources using remote sensing techniques. The eleven papers inside the book provide an overview of remote sensing applications on hydro, solar, wind and geothermal energy resources and their major goal is to provide state of art knowledge to contribute with the renewable energy resource deployment, especially in regions where energy demand is rapidly expanding. Renewable energy resources have an intrinsic relationship with local environmental features and the regional climate. Even small and fast environment and/or climate changes can cause significant variability in power generation at different time and space scales. Methodologies based on remote sensing are the primary source of information for the development of numerical models that aim to support the planning and operation of an electric system with a substantial contribution of intermittent energy sources. In addition, reliable data and knowledge on renewable energy resource assessment are fundamental to ensure sustainable expansion considering environmental, financial and energetic security.
    Keywords: metaheuristic ; parameter extraction ; solar photovoltaic ; whale optimization algorithm ; cloud detection ; digitized image processing ; artificial neural networks ; solar irradiance estimation ; solar irradiance forecasting ; solar energy ; sky camera ; remote sensing ; CSP plants ; coastal wind measurements ; scanning LiDAR ; plan position indicator ; velocity volume processing ; Hazaki Oceanographical Research Station ; cloud coverage ; image processing ; total sky imagery ; geothermal energy ; geophysical prospecting ; time domain electromagnetic method ; electrical resistivity tomography ; potential well field location ; GES-CAL software ; smart island ; solar radiation forecasting ; light gradient boosting machine ; multistep-ahead prediction ; feature importance ; voxel-design approach ; shading envelopes ; point cloud data ; computational design method ; passive design strategy ; lake breeze influence ; hydropower reservoir ; solar irradiance enhancement ; solar energy resource ; wind speed ; extreme value analysis ; scatterometer ; feature engineering ; forecasting ; graphical user interface software ; machine learning ; photovoltaic power plant ; surface solar radiation ; global radiation ; satellite ; Baltic area ; coastline ; cloud ; convection ; climate ; renewable energy resource assessment and forecasting ; remote sensing data acquisition ; data processing ; statistical analysis ; machine learning techniques ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 92
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-24
    Description: In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included.
    Keywords: smart homes ; Internet of Things (IoT) ; Wi-Fi ; human monitoring ; behavioral analysis ; ambient assisted living ; intelligent luminaires ; wireless sensor network ; indoor localisation ; indoor monitoring ; Graphics Processing Units (GPUs) ; CUDA ; OpenMP ; OpenCL ; K-means ; brain cancer detection ; hyperspectral imaging ; unsupervised clustering ; impaired sensor ; Structural Health Monitoring ; Time of Flight ; subharmonics ; Cascaded-Integrator-Comb (CIC) filter ; FPGA ; fixed point math ; data adaptive demodulator ; motion estimation ; inertial sensors ; simulation ; spline function ; Kalman filter ; eHealth ; software engineering ; gesture recognition ; Dynamic Time Warping ; Hidden Markov Model ; usability ; Cramér–Rao lower bound (CRLB) ; human motion ; Inertial Measurement Unit (IMU) ; Time of Arrival (TOA) ; wearable sensors ; endothelial dysfunction ; photoplethysmography ; machine learning ; computer-assisted screening ; sleep pose recognition ; keypoints feature matching ; Bayesian inference ; near-infrared images ; scale invariant feature transform ; heartbeat classification ; arrhythmia ; denoising autoencoder ; autoencoder ; deep learning ; auditory perception ; biometrics ; computer vision ; web control access ; web security ; human–computer interaction ; n/a ; thema EDItEUR::C Language and Linguistics ; thema EDItEUR::C Language and Linguistics::CJ Language teaching and learning ; thema EDItEUR::2 Language qualifiers::2A Indo-European languages::2AC Germanic and Scandinavian languages::2ACB English ; thema EDItEUR::4 Educational purpose qualifiers::4L For language learning courses and examinations::4LE For ELT / ESL learning, courses, examinations and certificates
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  • 93
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-20
    Description: Alternative assets such as fine art, wine, or diamonds have become popular investment vehicles in the aftermath of the global financial crisis. Correlation with classical financial markets is typically low, such that diversification benefits arise for portfolio allocation and risk management. Cryptocurrencies share many alternative asset features, but are hampered by high volatility, sluggish commercial acceptance, and regulatory uncertainties. This collection of papers addresses alternative assets and cryptocurrencies from economic, financial, statistical, and technical points of view. It gives an overview of their current state and explores their properties and prospects using innovative approaches and methodologies.
    Keywords: HG1-9999 ; inflation propensity ; realized volatility ; portfolio modelling ; diamond stocks ; systemic risk ; cryptocurrencies ; initial coin offering ; smooth transition ; investment asset ; GARCH ; risk management ; transaction costs ; liquidity costs ; time series ; Baltic dry index ; statistical arbitrage ; volume ; cryptocurrency ; Hashrate ; blockchain ; diamond prices ; pro-cyclical volatility ; capital asset pricing model ; Bitcoin volatility ; trend prediction ; collatz conjecture ; high-frequency finance ; sentiment ; geometric distribution ; speculative bubbles ; gold ; classification framework ; limit order book ; venture capital ; proof-of-work ; high frequency ; Bitcoin ; machine learning ; metric learning ; stylized fact ; digital currency ; crowdfunding ; HAR ; GARCH-MIDAS ; bitcoin ; bic Book Industry Communication::W Lifestyle, sport & leisure::WC Antiques & collectables::WCF Coins, banknotes, medals, seals (numismatics)
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  • 94
    Publication Date: 2024-04-11
    Description: Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.
    Keywords: TD1-1066 ; T1-995 ; spectral ; Cameroon ; quantitative structural model ; digital hemispherical photograph (DHP) ; environment effects ; human activity ; reference level ; terrestrial laser scanning ; topographic effects ; Guyana ; predictive mapping ; aboveground biomass estimation ; geographic information system ; Pinus massoniana ; 3D tree modelling ; ensemble model ; destructive sampling ; model comparison ; topography ; remote sensing ; forest growing stock volume (GSV) ; local tree allometry ; tree mapping ; gray level co-occurrence matrix (GLCM) ; deforestation ; REDD+ ; sentinel imagery ; geographically weighted regression ; aboveground biomass ; random forest ; random forest (RF) ; silviculture ; agriculture ; crown density ; hazard mapping ; model evaluation ; old-growth forest ; full polarimetric SAR ; subtropical forest ; forest canopy ; forest classification ; low-accuracy estimation ; texture ; LiDAR ; Landsat ; phenology ; airborne laser scanning ; tall trees ; machine learning ; forest baseline ; overstory trees ; support vector machine ; above-ground biomass ; multispectral satellite imagery ; crown delineation ; specific leaf area ; forest inventory ; canopy cover (CC) ; voxelization ; forestry ; leaf area ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 95
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water
    Keywords: TA1-2040 ; T1-995 ; TA170-171 ; natural hazards & ; artificial neural network ; flood routing ; the Three Gorges Dam ; backtracking search optimization algorithm (BSA) ; lag analysis ; artificial intelligence ; classification and regression trees (CART) ; decision tree ; real-time ; optimization ; ensemble empirical mode decomposition (EEMD) ; improved bat algorithm ; convolutional neural networks ; ANFIS ; method of tracking energy differences (MTED) ; adaptive neuro-fuzzy inference system (ANFIS) ; recurrent nonlinear autoregressive with exogenous inputs (RNARX) ; disasters ; flood prediction ; ANN-based models ; flood inundation map ; ensemble machine learning ; flood forecast ; sensitivity ; hydrologic models ; phase space reconstruction ; water level forecast ; data forward prediction ; early flood warning systems ; bees algorithm ; random forest ; uncertainty ; soft computing ; data science ; hydrometeorology ; LSTM ; rating curve method ; forecasting ; superpixel ; particle swarm optimization ; high-resolution remote-sensing images ; machine learning ; support vector machine ; Lower Yellow River ; extreme event management ; runoff series ; empirical wavelet transform ; Muskingum model ; hydrograph predictions ; bat algorithm ; data scarce basins ; Wilson flood ; self-organizing map ; big data ; extreme learning machine (ELM) ; hydroinformatics ; nonlinear Muskingum model ; invasive weed optimization ; rainfall–runoff ; flood forecasting ; artificial neural networks ; flash-flood ; streamflow predictions ; precipitation-runoff ; the upper Yangtze River ; survey ; parameters ; Haraz watershed ; ANN ; time series prediction ; postprocessing ; flood susceptibility modeling ; rainfall-runoff ; deep learning ; database ; LSTM network ; ensemble technique ; hybrid neural network ; self-organizing map (SOM) ; data assimilation ; particle filter algorithm ; monthly streamflow forecasting ; Dongting Lake ; machine learning methods ; micro-model ; stopping criteria ; Google Maps ; cultural algorithm ; wolf pack algorithm ; flood events ; urban water bodies ; Karahan flood ; St. Venant equations ; hybrid & ; hydrologic model ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 96
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
    Keywords: QA75.5-76.95 ; T58.5-58.64 ; metadata ; image classification ; sensitivity analysis ; ROI detection ; residual learning ; image alignment ; adaptive convolutional kernels ; Hough transform ; class imbalance ; land surface temperature ; inundation mapping ; multiscale representation ; object-based ; convolutional neural networks ; scene classification ; morphological profiles ; hyperedge weight estimation ; hyperparameter sparse representation ; semantic segmentation ; vehicle classification ; flood ; Landsat imagery ; target detection ; multi-sensor ; building damage detection ; optimized kernel minimum noise fraction (OKMNF) ; sea-land segmentation ; nonlinear classification ; land use ; SAR imagery ; anti-noise transfer network ; sub-pixel change detection ; Radon transform ; segmentation ; remote sensing image retrieval ; TensorFlow ; convolutional neural network ; particle swarm optimization ; optical sensors ; machine learning ; mixed pixel ; optical remotely sensed images ; object-based image analysis ; very high resolution images ; single stream optimization ; ship detection ; ice concentration ; online learning ; manifold ranking ; dictionary learning ; urban surface water extraction ; saliency detection ; spatial attraction model (SAM) ; quality assessment ; Fuzzy-GA decision making system ; land cover change ; multi-view canonical correlation analysis ensemble ; land cover ; semantic labeling ; sparse representation ; dimensionality expansion ; speckle filters ; hyperspectral imagery ; fully convolutional network ; infrared image ; Siamese neural network ; Random Forests (RF) ; feature matching ; color matching ; geostationary satellite remote sensing image ; change feature analysis ; road detection ; deep learning ; aerial images ; image segmentation ; aerial image ; multi-sensor image matching ; HJ-1A/B CCD ; endmember extraction ; high resolution ; multi-scale clustering ; heterogeneous domain adaptation ; hard classification ; regional land cover ; hypergraph learning ; automatic cluster number determination ; dilated convolution ; MSER ; semi-supervised learning ; gate ; Synthetic Aperture Radar (SAR) ; downscaling ; conditional random fields ; urban heat island ; hyperspectral image ; remote sensing image correction ; skip connection ; ISPRS ; spatial distribution ; geo-referencing ; Support Vector Machine (SVM) ; very high resolution (VHR) satellite image ; classification ; ensemble learning ; synthetic aperture radar ; conservation ; convolutional neural network (CNN) ; THEOS ; visible light and infrared integrated camera ; vehicle localization ; structured sparsity ; texture analysis ; DSFATN ; CNN ; image registration ; UAV ; unsupervised classification ; SVMs ; SAR image ; fuzzy neural network ; dimensionality reduction ; GeoEye-1 ; feature extraction ; sub-pixel ; energy distribution optimizing ; saliency analysis ; deep convolutional neural networks ; sparse and low-rank graph ; hyperspectral remote sensing ; tensor low-rank approximation ; optimal transport ; SELF ; spatiotemporal context learning ; Modest AdaBoost ; topic modelling ; multi-seasonal ; Segment-Tree Filtering ; locality information ; GF-4 PMS ; image fusion ; wavelet transform ; hashing ; machine learning techniques ; satellite images ; climate change ; road segmentation ; remote sensing ; tensor sparse decomposition ; Convolutional Neural Network (CNN) ; multi-task learning ; deep salient feature ; speckle ; canonical correlation weighted voting ; fully convolutional network (FCN) ; despeckling ; multispectral imagery ; ratio images ; linear spectral unmixing ; hyperspectral image classification ; multispectral images ; high resolution image ; multi-objective ; convolution neural network ; transfer learning ; 1-dimensional (1-D) ; threshold stability ; Landsat ; kernel method ; phase congruency ; subpixel mapping (SPM) ; tensor ; MODIS ; GSHHG database ; compressive sensing ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 97
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.
    Keywords: TA1-2040 ; T1-995 ; polyacrylonitrile-based carbon fiber ; n/a ; coagulation bath ; binder dissolution ; sensitivity analysis ; simulation ; neural networks ; kernel development ; thermodynamics ; phytochemicals ; wave resonance ; natural extracts ; population balance model ; optimization ; vane ; parameter estimation ; grey-box model ; observability ; optimal clustering ; energy ; idling test ; data-mining ; extents ; computational fluid dynamics ; scrap dissolution ; Combined Heat and Power ; dynamic optimization ; scrap melting ; swelling ; engineering ; dry-jet wet spinning process ; fluid bed granulation ; point estimation method ; algebraic modeling language ; Design of Experiments ; costing stopping ; materials ; hydration ; SOS programming ; kinetics ; moisture content ; CHP legislation ; model predictive control ; graph theory ; robust optimization ; dynamic converter modelling ; partial least square regression ; uncertainty ; state decoupling ; utility management ; fluidized bed drying ; reactor coolant pump ; condensation ; wheat germ ; cooking ; maximum wave amplitude ; moving horizon estimation ; gray-box model ; chemistry ; barley ; machine learning ; heat and mass balance ; equality constraints ; porridge ; process model validation ; Pharmaceutical Processes ; mathematical model ; model identification ; Mammalian Cell Culture ; process modeling ; parameter correlation ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 98
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Despite being one of the most popular sports worldwide, basketball has received limited research attention compared to other team sports. Establishing a strong evidence base with high-quality and impactful research is essential in enhancing decision-making processes to optimize player performance for basketball professionals. Consequently, the book entitled Improving Performance and Practice in Basketball provides a collection of novel research studies to increase the available evidence on various topics with strong translation to practice in basketball. The book includes work by 40 researchers from 16 institutions or professional organizations from 9 countries. In keeping with notable topics in basketball research, the book contains 2 reviews focused on monitoring strategies to detect player fatigue and considerations for travel in National Basketball Association players. In addition, 8 applied studies are also included in the book, focused on workload monitoring, game-related statistics, and the measurement of physical and skill attributes in basketball players. This book also has a strong focus on increasing the evidence available for female basketball players, who have traditionally been under-represented in the literature. The outcomes generated from this book should provide new insights to inform practice in many areas for professionals working in various roles with basketball teams.
    Keywords: GV557-1198.995 ; n/a ; talent selection ; classification tree ; Movement Assessment Battery for Children-2 ; NBA ; basketball ; maturation ; body composition ; fatigue ; countermovement jump ; athletic performance ; circadian rhythm ; injury ; basketball tactics ; female ; athlete ; non-linear analysis ; monitoring ; basketball performance ; performance analysis ; training load ; variability ; game-related statistics ; sleep ; youth athletes ; accelerometer ; women athletes ; fat free mass ; collegiate athletes ; workloads ; team sports ; machine learning ; microtechnology ; motor manual sequences ; elite sport ; attention ; visuo-spatial working memory ; playing position ; smallest worthwhile change ; body fat ; thema EDItEUR::V Health, Relationships and Personal development::VX Mind, body, spirit::VXH Complementary therapies, healing and health::VXHT Traditional medicine and herbal remedies
    Language: English
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  • 99
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.
    Keywords: semi-supervised learning ; transfer learning ; radar emitter ; decision support systems ; population health management ; big data ; machine learning ; deep learning ; personalized patient care ; Nonlinear regression ; interactive platform ; component-based approach ; software architecture ; Eclipse-RCP (Rich Client Platform) ; spatial prediction ; rule-based expert systems ; tennis hitting technique ; computer algebra systems ; Groebner bases ; Boolean logic ; data envelopment analysis ; dimensionality reduction ; ensembles ; exhaustive state space search ; entropy ; associative classification ; class association rule ; vertical data representation ; classification ; algorithm evaluation ; parallel algorithms ; multi-objective optimization ; train rescheduling ; very large-scale decision support systems ; very large-scale data and program cores of information systems ; meta-database ; teleological meta-database ; thematic list ; indicators list ; computational methods list ; geographically dispersed systems ; external sources ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 100
    facet.materialart.
    Unknown
    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-05
    Description: Within the idea and objective of bringing together original studies dealing with the continuum aspects of meat, i.e., from farm to fork, this book grouped papers on the study of the nutritional, sensory, and technological aspects of carcass, muscle, meat, and meat-product qualities. This nook highlights a great part of the research activities in the field of meat science. A total of 14 original studies and one comprehensive review were edited within five main topics: (i) production systems and rearing practices, (ii) prediction of meat quality, (iii) statistical approaches for meat quality prediction/management, (iv) muscle biochemistry and proteomics techniques, and (v) consumer acceptability, development, and characterization of meat products.
    Keywords: QH301-705.5 ; Q1-390 ; TX341-641 ; meat quality ; sensory and technological quality ; serratus ventralis muscle ; modeling ; suckling cattle ; immunohistology ; pig ; carcass ; LC-MS/MS ; calpain ; sensorial and technological quality ; on-line ; infraspinatus muscle ; statistical tools for meat quality prediction ; malondialdehyde ; skeletal muscle ; chuck sale section ; male and female turkeys ; rearing managements ; dry-cured belly ; meat science ; breeders ; carcass characteristics ; production systems ; castration ; muscle biochemistry ; biomarker ; monitoring ; sample preparation ; quality ; bovine proteomics ; h2afx ; prediction ; broilers ; nutritional ; phenol ; shear force ; beef performances ; fetus ; complexus muscle ; near-infrared spectroscopy ; phenotypic model ; sensory acceptability ; cull cow ; trade-off ; meat sensory properties ; one-dimensional electrophoresis ; rhomboideus muscle ; boar taint ; OMICs tools ; pancetta ; longissimus muscle ; spectroscopy ; carcass and meat qualities ; finishing practices ; pre-weaning period ; grass-fed ; nutritional quality ; pasture ; consumer ; tenderness ; predictive model ; intramuscular fat ; fattening period ; rearing surveys ; rearing practices ; cows ; young bulls ; machine learning ; breed ; farm survey ; beef quality ; biological marker ; Folin-Ciocalteu ; decision trees ; natural antioxidant ; meat ; color attributes ; bovine ; processed meat ; meat rheological properties ; growth period ; muscle proteins ; extracellular matrix ; beef tenderness ; farm-to-fork ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
    Language: English
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