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  • 101
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Collectively, the studies presented in this reprint have used various validated biomechanical models or proposed novel methods of motion analysis to gain new insights into health-related problems and sports performance.
    Keywords: human ankle model ; product of exponentials formula ; anthropometry ; biomechanics ; coordinate measuring machines ; kinematics ; pose estimation ; position measurement ; biomedical informatics ; adolescent idiopathic scoliosis (AIS) ; surface electromyography (sEMG) ; paraspinal muscle ; Schroth exercise ; paraspinal muscle symmetry index (PMSI) ; negative heel shoes ; positive heel shoes ; gait ; pregnant women ; OpenSim ; IDEEA ; dentistry ; dental unit chair systems ; muscle fatigue ; muscle activation ; in vivo study ; femoral neck fracture ; internal fixation ; intramedullary fixation ; finite element analysis ; finite element ; proximal junctional failure ; spinal reconstruction ; thoracolumbar ; rollback ; ligament strain ; kinematic alignment ; mechanical alignment ; total knee arthroplasty ; markerless motion capture system ; gait analysis ; joint moment ; joint power ; running economy ; running style ; duty factor ; vertical oscillation ; stride frequency ; freezing of gait ; gait initiation ; Parkinson’s disease ; posture ; segmental centers of mass ; anthropometric measurement ; base of support ; hand exoskeleton design ; motion simulation ; rehabilitation ; intention recognition ; machine learning ; deep learning ; two-dimensional (2D) image ; marker-free video ; walking speed ; walking speed classification ; bi-LSTM ; redundant feature ; ratio-based body measurement ; optimal feature ; surface topography ; rasterstereographic back shape analysis ; normative data ; healthy adults ; posture analysis ; spine ; intelligent system ; classroom behavior ; motion identification ; shoulder activity ; sensor ; rehabilitation protocol ; proximal humerus fracture ; ground reaction force ; knee and hip ; lower limb ; normal walking ; musculoskeletal multibody dynamics ; spinal biomechanics ; spinal alignment ; spinal loading ; muscle force computation ; thoracolumbar spine ; biomechanical model ; electromyography ; inertial measurement units ; gait-phase prediction ; spinal cord injury (SCI) ; muscle fiber conduction velocity (MFCV) ; surface electromyography (EMG) ; EMG–force relation ; composite index ; characteristic points ; multivariable linear regression ; anterior cruciate ligament deficiency ; competitive swimming ; performance ; velocity fluctuations ; multibody simulation ; finite element method ; co-simulation ; sports ; degeneration ; intervertebral disc ; coupled ; embryo implantation ; human choriocarcinoma cell ; extracellular matrix ; stiffness ; durotaxis ; n/a ; thema EDItEUR::M Medicine and Nursing
    Language: English
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  • 102
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-10-25
    Description: Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations.
    Keywords: physical human-robot interaction ; game theory ; adaptive optimal control ; robot control ; tandem force sensor ; traction force sensor ; human–robot interaction ; contact task ; imitation learning ; safe physical human–robot collaboration ; collision detection ; human action recognition ; artificial intelligence ; industrial automation ; reinforcement learning ; social robotics ; human-robot interaction ; reward design ; physical embodiment ; human robot collaboration ; human robot interaction ; path planning ; bidirectional awareness ; haptic feedback device ; human machine interface ; collision identification ; collaborative robot ; deep learning ; uncertainty estimation ; knowledge distillation ; human–robot collaboration ; speed and separation monitoring ; human–machine differentiation ; thermal cameras ; protective separation distance ; collaborative robots ; motion planning ; human motion prediction ; human-following robots ; teleoperation ; high-speed image processing ; machine learning ; finger position recognition ; grasp type estimation ; human-robot collaboration ; human-centered robotics ; task planning ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Language: English
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  • 103
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-12-06
    Description: This reprintshows recent advances in dam safety related to overtopping and the prevention, detection, and risk assessment of geostructural risks. Related to overtopping, the issues treated are: the throughflow and failure process of rockfill dams; the protection of embankment dams against overtopping by means of a rockfill toe or wedge-shaped blocks; and the protection of concrete dams with highly convergent chutes. In the area of geostructural threats, the detection of anomalies in dam behavior from monitoring data using a combination of machine learning techniques, the numerical modeling of seismic behavior of concrete dams, and the determination of the impact area downstream of ski-jump spillways are also studied and discussed. In relation to risk assessment, three chapters deal with the development of fragility curves for dikes and dams in relation to various failure mechanisms.
    Keywords: hydraulic structure ; sky-jump ; spillway ; flip bucket ; chute ; basin ; erosion ; flow rate ; jet flow ; wave overtopping ; levee ; cover ; probabilistic framework ; slope stability ; piping ; overtopping ; fragility curves ; Monte Carlo simulation ; dam ; stilling basin ; bucket ; flood ; weir ; safety ; protection ; dam protection ; wedge-shaped block ; WSB ; dam spillway ; dam safety ; ACUÑA ; rockfill dams ; throughflow ; numerical modeling ; non-Darcy flow ; porous media ; Forchheimer equation ; high velocity ; crushed rock ; rounded materials ; hydraulic mean radius ; intrinsic permeability ; shape of particles ; angularity of particles ; surface roughness of particles ; river levees ; geogrid reinforcement ; First Order Reliability Method (FORM) ; Surface Response Method (SRM) ; high gravity dams ; dam-foundation-reservoir dynamic interaction ; earthquake input mechanisms ; hydrodynamic pressure ; foundation size ; reservoir length ; stacking ; blending ; combination ; meta-learner ; experts ; machine learning ; Cross Validation ; radial displacement ; rockfill dam ; dam failure ; overflow ; floods ; dam breach ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 104
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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
    Language: English
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  • 105
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: The Special Issue presents almost 40 papers on recent research in modeling of pyrometallurgical systems, including physical models, first-principles models, detailed CFD and DEM models as well as statistical models or models based on machine learning. The models cover the whole production chain from raw materials processing through the reduction and conversion unit processes to ladle treatment, casting, and rolling. The papers illustrate how models can be used for shedding light on complex and inaccessible processes characterized by high temperatures and hostile environment, in order to improve process performance, product quality, or yield and to reduce the requirements of virgin raw materials and to suppress harmful emissions.
    Keywords: steelmaking ; oxygen consumption ; GPR ; prediction model ; secondary refining ; water model ; mixing time ; slag entrapment ; stainless steel slag ; heating time ; Cr2O3 ; spinel ; crystal size ; processing maps ; nickel-based alloy ; flow behavior ; arrhenius equation ; hearth ; drainage ; PCA ; analysis tool ; pattern ; tapholes ; blast furnace ; coke ; carbon solution loss ; numerical simulation ; pellet pile ; Discrete Element Method ; porosity distribution ; angle of repose ; coordination number ; bubble motion ; interfacial phenomena ; entrainment ; moving path ; arsenopyrite ; arsenic removal ; mechanism ; roasting ; arsenate ; dust ash ; arsenic recovery ; titanium distribution ratio ; thermodynamic model ; ion–molecule coexistence theory ; LF refining slags ; electric arc furnace ; simulation ; process model ; COREX ; raceway zone ; gas flow ; COREX melter gasifier ; mixed charging ; burden layer structure ; burden pile width ; DEM ; burden distribution ; particle flow ; validation ; tire cord steel ; TiN inclusion ; solidification ; segregation models ; hot rolling ; TOU electricity pricing ; hot rolling planning ; genetic algorithm ; C-H2 smelting reduction furnace ; double-row side nozzles ; dimensional analysis ; multiple linear regression ; ironmaking blast furnace ; coke bed ; trickle flow ; molten slag ; liquid iron ; SPH ; charging system ; mathematical model ; radar data ; main trough ; transient fluid of hot metal and molten slag ; wall shear stress ; conjugate heat transfer ; refractory ; shape rolling ; flat rolling ; wire rod ; temperature distribution ; machine learning ; artificial intelligence ; neural network ; BOS reactor ; copper smelting ; SKS ; Shuikoushan process ; oxygen bottom blown ; gated recurrent unit ; support vector data description ; time sequence prediction ; fault detection and identification ; Lignite ; microwave and ultrasound modification ; structural characterization ; 3D molecular model ; structural simulation ; coke combustion rate ; charcoal combustion rate ; iron ore sintering process ; biomass ; quasi-particle ; quasi-particle structure ; monomer blended fuel ; quasi-particle fuel ; apparent activation energy ; coupling effect ; dynamic model ; basic oxygen furnace ; computational fluid dynamics ; CFD–DEM ; coalescence ; settling ; funneling flow ; horizontal single belt casting process (HSBC) ; computational fluid dynamics (CFD) ; double impingement feeding system ; supersonic coherent jet ; decarburization ; steel refining ; EAF ; CFD ; mass transfer coefficient ; physical modeling ; mathematical modeling ; kinetic models ; natural gas ; fuel injection ; combustion ; RAFT ; roll design ; flat-rolled wire ; strain inhomogeneity ; normal pressure ; macroscopic shear bands ; numerical model ; dual gas injection ; slag eye ; electrical energy consumption ; Electric Arc Furnace ; scrap melting ; statistical modeling ; raceway evolution ; raceway size ; flow pattern ; Eulerian multiphase flow ; blast furnace hearth ; dead man ; iron and slag flow ; lining wear ; hearth drainage ; Industry 4.0 ; copper smelter ; nickel-copper smelter ; radiometric sensors ; Peirce-smith converting ; matte-slag chemistry ; discrete event simulation ; adaptive finite differences ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Language: English
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  • 106
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The modeling and processing of empirical data is one of the main subjects and goals of statistics. Nowadays, with the development of computer science, the extraction of useful and often hidden information and patterns from data sets of different volumes and complex data sets in warehouses has been added to these goals. New and powerful statistical techniques with machine learning (ML) and data mining paradigms have been developed. To one degree or another, all of these techniques and algorithms originate from a rigorous mathematical basis, including probability theory and mathematical statistics, operational research, mathematical analysis, numerical methods, etc. Popular ML methods, such as artificial neural networks (ANN), support vector machines (SVM), decision trees, random forest (RF), among others, have generated models that can be considered as straightforward applications of optimization theory and statistical estimation. The wide arsenal of classical statistical approaches combined with powerful ML techniques allows many challenging and practical problems to be solved. This Special Issue belongs to the section “Mathematics and Computer Science”. Its aim is to establish a brief collection of carefully selected papers presenting new and original methods, data analyses, case studies, comparative studies, and other research on the topic of statistical data modeling and ML as well as their applications. Particular attention is given, but is not limited, to theories and applications in diverse areas such as computer science, medicine, engineering, banking, education, sociology, economics, among others. The resulting palette of methods, algorithms, and applications for statistical modeling and ML presented in this Special Issue is expected to contribute to the further development of research in this area. We also believe that the new knowledge acquired here as well as the applied results are attractive and useful for young scientists, doctoral students, and researchers from various scientific specialties.
    Keywords: mathematical competency ; assessment ; machine learning ; classification and regression tree ; CART ensembles and bagging ; ensemble model ; multivariate adaptive regression splines ; cross-validation ; dam inflow prediction ; long short-term memory ; wavelet transform ; input predictor selection ; hyper-parameter optimization ; brain-computer interface ; EEG motor imagery ; CNN-LSTM architectures ; real-time motion imagery recognition ; artificial neural networks ; banking ; hedonic prices ; housing ; quantile regression ; data quality ; citizen science ; consensus models ; clustering ; Gower’s interpolation formula ; Gower’s metric ; mixed data ; multidimensional scaling ; classification ; data-adaptive kernel functions ; image data ; multi-category classifier ; predictive models ; support vector machine ; stochastic gradient descent ; damped Newton ; convexity ; METABRIC dataset ; breast cancer subtyping ; deep forest ; multi-omics data ; categorical data ; similarity ; feature selection ; kernel density estimation ; non-linear optimization ; kernel clustering ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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  • 107
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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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  • 108
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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
    Language: English
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  • 109
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market). This collection gathers the advanced studies of novel deep learning algorithms/frameworks and their applications in real-world scenarios. The topics cover, but are not limited to, supervised learning, explainable deep learning, finance, healthcare, and sciences.
    Keywords: Convolutional Neural Network (CNN) ; pooling ; deep learning ; computer vision ; image analysis ; benchmark ; lithium-ion battery ; prognostics ; long short-term memory ; ARIMA ; reinforcement learning ; generative adversarial networks ; deep-learning ; crop/weed classification ; transfer learning ; feature extraction ; natural language processing ; image-text matching ; cheapfakes ; misinformation ; transformer encoder ; RoGPT2 ; control tokens ; summarization ; text generation ; human evaluation ; tricalcium silicate ; analytical model ; ion activity ; dissolution kinetics ; deep forest ; subsurface fluid flow ; Fourier neural operator ; small-shape data ; finite element method ; convolutional neural network ; sensitivity analysis ; source code comments ; classification ; machine learning techniques ; ANN flow law ; constitutive behavior ; radial return algorithm ; numerical implementation ; VUHARD ; GrC15 ; Abaqus Explicit ; defect detection ; surface defect detection ; defect detection for X-ray images ; defect recognition ; photoacoustic imaging ; image processing ; simulation ; reconstruction ; residual echo suppression ; acoustic echo cancellation ; speech enhancement ; graph neural network ; variational autoencoder ; nearest neighbours ; acute myeloid leukemia ; risk factors ; average treatment effect ; uplift modelling ; machine learning ; benzene ; ANOVA ; Shapley values ; self-explaining neural networks ; generalised additive models ; interpretability ; Siamese networks ; synthetic data ; cyclic learning ; unsupervised learning ; data augmentation ; single cell cultivation ; bioimage analysis ; finite element simulation ; plausibility checks ; convolutional neural networks ; storm surge ; hurricane ; forecasting ; CNN ; LSTM ; physics informed neural network ; dynamic force identification ; duffing’s equation ; spring mass damper system ; non-linear oscillators ; massive MIMO ; hybrid beamforming ; compressive measurement matrix ; long short-term memory network ; capsule network ; routing algorithm ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 110
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-10-25
    Description: In recent years, improving the sustainability of the steel industry and reducing its CO2 emissions has become a global focus. To achieve this goal, further process optimization in terms of energy and resource efficiency and the development of new processes and process routes are necessary. Modeling and simulation have established themselves as invaluable sources of information for otherwise unknown process parameters and as an alternative to plant trials that involves lower costs, risks, and time. Models also open up new possibilities for model-based control of metallurgical processes. This Special Issue focuses on recent advances in the modeling and simulation of unit processes in iron and steelmaking. It includes reviews on the fundamentals of modeling and simulation of metallurgical processes, as well as contributions from the areas of iron reduction/ironmaking, steelmaking via the primary and secondary route, and continuous casting.
    Keywords: liquid metals ; bubble generation ; bubble size distribution ; porous plugs ; bubble deformation ; drag force ; lift force ; mathematical modelling ; computational fluid dynamic ; slag heat recovery ; heat exchanger ; drying ; slag energy content ; heat recovery technology ; RecHeat ; rotary kiln ; reduction process ; numerical simulation ; pre-reduction ; scrap preheating ; electric arc furnace ; continuous charging ; turbulence modelling ; RANS/LES/DNS ; inflow condition ; model validation ; model application ; energy demand ; regression ; artificial neural network ; Gaussian process regression ; Köhle formula ; evaluation model ; quantitative relationship ; scrap melting ; mass transfer coefficient ; steelmaking process ; direct current ; arc impingement ; arc gap ; gas density ; electric arc ; magneto hydrodynamics ; computational fluid dynamics ; real-time model ; estimation ; model predictive control ; steel refining ; mathematical modeling ; carbon composite briquette ; blast furnace ironmaking ; reaction kinetics ; coke saving ; direct reduction ; Midrex ; HYL ; Rist diagram ; energy consumption ; profile optimization ; modelling ; machine learning ; steelmaking ; fuzzy modelling ; evolving modelling ; continuous casting ; near net shape casting ; twin roll (Bessemer) casting ; horizontal single belt casting ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 111
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: This Special Issue book covers a wide scope in the research field of 3D-printing, including: the use of 3D printing in system design; AM with binding jetting; powder manufacturing technologies in 3D printing; fatigue performance of additively manufactured metals, such as the Ti-6Al-4V alloy; 3D-printing methods with metallic powder and a laser-based 3D printer; 3D-printed custom-made implants; laser-directed energy deposition (LDED) process of TiC-TMC coatings; Wire Arc Additive Manufacturing; cranial implant fabrication without supports in electron beam melting (EBM) additive manufacturing; the influence of material properties and characteristics in laser powder bed fusion; Design For Additive Manufacturing (DFAM); porosity evaluation of additively manufactured parts; fabrication of coatings by laser additive manufacturing; laser powder bed fusion additive manufacturing; plasma metal deposition (PMD); as-metal-arc (GMA) additive manufacturing process; and spreading process maps for powder-bed additive manufacturing derived from physics model-based machine learning.
    Keywords: powder-bed additive manufacturing (AM) ; powder spreading ; spreading process map ; discrete element method (DEM) ; machine learning ; GMA additive manufacturing ; weld reinforcement ; visual features ; neural network ; selective laser melting ; magnesium alloys ; properties ; plasma metal deposition ; additive manufacturing ; 316L ; processing conditions ; mechanical properties ; microstructure ; virgin ; recycled ; metal powders ; laser powder bed fusion ; laser additive manufacturing ; 316l ss ; nickel alloy ; tribological behavior ; porosity ; rough surface ; ultrasonic testing ; convolutional neural network ; deep neural network ; multi-layer perceptron ; key performance indicators ; topology optimization ; design for additive manufacturing ; design for additive manufacturing services ; selective laser melting (SLM) ; laser powder bed fusion (LPBF) ; powder ; particle size distribution ; particle morphology ; powder layer density ; part density ; flowability ; Hausner ratio ; electron beam melting ; customized implant ; cost analysis ; fitting accuracy ; cranial reconstruction ; thin wall manufacturing ; process modelling ; ultrasonic vibration ; laser directed energy deposition ; coating ; TiC-TMC ; extremity ; revision ; limb salvage surgery ; 3D printing ; customized ; implant ; powder metallurgy ; simulated body fluid ; biomaterial ; fatigue ; titanium ; direct laser deposition ; Inconel 625 ; parametrisation ; microhardness ; preheating ; binder jetting ; sand casting ; aluminum alloy ; corrosion ; pressure drop ; heat exchanger ; surface textures ; dimples ; drag reduction ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 112
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: People living in both developed and developing countries face serious health challenges related to sedentary lifestyles. It is therefore essential to find new ways to improve health so that people can live longer and can age well. With an ever-growing number of smart sensing systems developed and deployed across the globe, experts are primed to help coach people toward healthier behaviors. The increasing accountability associated with app- and device-based behavior tracking not only provides timely and personalized information and support but also gives us an incentive to set goals and to do more. This book presents some of the recent efforts made towards automatic and autonomous identification and coaching of troublesome behaviors to procure lasting, beneficial behavioral changes.
    Keywords: activity recognition ; wearable devices ; inertial sensors ; Bluetooth beacons ; machine learning ; e-coaching ; m-health intervention ; personalization ; healthy lifestyle ; physical activity ; tangible user interface ; affordance ; multimodal cueing ; animate objects ; activities of daily living ; human activity recognition ; context-awareness ; Bayesian network ; mobile application ; wearable computing ; wrist-worn heart rate devices ; cardiac rehabilitation ; real-time wearable monitoring ; fuzzy logic ; fuzzy linguistic approach ; m-health ; remote coaching ; telemonitoring ; telehealth ; cadence ; marathon ; elevation change analysis ; personalized assistance level ; coaching ; electric bicycles ; ubiquitous computing ; health ; human-centered computing ; digital coaching ; diabetes education ; serious gaming ; self-management ; user evaluations ; sedentary lifestyle ; context recognition ; unhealthy sitting habits ; wearable sensors ; smartphones ; smart objects ; behavior change ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 113
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: Remote sensing is a powerful technique for characterizing and monitoring crop or vegetation properties at reasonable temporal and spatial resolutions. Remote sensing uses airborne and spaceborne platforms to collect various imageries and is widely applied for the vegetation monitoring of local- or large-scale interest concerning the effect of geophysical and climate parameters. The Special Issue highlights vegetation monitoring using remote sensing data acquired from satellite or unmanned aerial vehicle platforms. In addition to the optical data, thermal data is utilized to estimate crop yield or production, orchard water status, chlorophyll content, forest diversity mapping, or vegetation phenology.
    Keywords: rice and wheat ; nitrogen remote sensing ; quantitative retrieval ; research prospect ; vegetation phenology ; snow cover ; vegetation index ; SOS ; Tibetan Plateau ; remote sensing ; forest diversity ; GEDI LiDAR ; Sentinel-2 ; machine Learning ; yield forecasting ; logistic model ; normalization method ; crop canopy temperature ; maize ; broadband vegetation indices ; chlorophyll content ; leaf angle distribution ; WorldView-2 ; RapidEye ; GaoFen-6 ; random forest ; land evaluation ; soil ; biomass ; Hungary ; gross primary productivity ; soil health ; soil quality ; coastal marsh ; continuum removal ; hyperspectral ; spectral signatures ; unmanned aerial vehicle (UAV) ; vegetation species discrimination ; second derivative transformation ; canopy temperature ; crop water status index ; accuracy assessment ; peach orchard ; stem water potential ; backscatter ; gradient boosting ; machine learning ; NDVI ; precision agriculture ; forest stock volume ; NDVIRE ; Helan mountains ; convolutional neural networks (CNNs) ; unmanned aerial vehicles (UAVs) ; semi-natural grasslands ; plant communities ; time series ; reconstruction algorithm ; smoothing ; optical remote sensing ; cropping intensity ; temporal mixture analysis ; endmember ; unmixing ; time series images ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
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  • 114
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section.
    Keywords: induction machines ; electrical machines ; vector control ; SVPWM modulation ; frequency inverter ; artificial intelligence ; photovoltaics ; fault detection ; machine learning ; operation and maintenance ; renewable energy ; water-in-crude oil emulsion ; water content ; ultrasound ; propagation velocity ; exoskeletons ; test bench ; industry ; benchmarking ; microgrid model-based systems engineering ; service systems ; goal-oriented requirements engineering ; safety instrumented system ; ventricular assist device Bayesian network ; Petri net ; control strategy ; UAV ; fuzzy ; PID controller ; ROS ; Industry 4.0 ; database ; data models ; big data and analytics ; asset administration shell ; MLOps ; digital twin ; IoT ; prediction ; coordinate metrology ; optical scanning ; noise reduction ; digital manufacturing ; integrated inspection system ; data analytics ; uncertainty ; convolutional neural networks ; warehouse management ; image classification ; ensemble learning ; synthetic data ; depth image ; electrical maintenance ; COVID-19 ; thermography ; fever ; computer vision ; intelligent systems ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-11-17
    Description: The impact of buildings on the environment is nothing short of devastating. In recent years, much attention has been given to creating an environmentally friendly built environment. Nonetheless, it has been levied on new buildings. Residential buildings make up at least 80% of the built environment, most of which were built before any energy efficiency guidelines or regulations were introduced. Retrofitting existing residential buildings is a key yet neglected priority in effecting the transition to an environmentally friendly, sustainable built environment. It is pivotal to reducing a building’s energy consumption while simultaneously improving indoor environmental quality and minimizing harmful emissions. This Special Issue showcases studies investigating applications of environmental technology that is tailored to enhance the sustainable performance of existing residential buildings. It helps to better understand the innovations that have been taking place in retrofitting residential buildings, as well as highlighting many opportunities for future research in this field.
    Keywords: automatically generated heating ventilating and air conditioning (HVAC) controllers ; Building Information Modelling (BIM) ; Industry Foundation Classes (IFC) ; advanced building controls ; HVAC control ; occupancy prediction ; energy consumption ; thermal comfort ; smart building ; smart city ; Bayesian networks ; elevator control algorithm ; intelligent elevator system ; decision theory ; decision support systems ; solar PV ; battery ; costs ; CO2 emissions ; electric vehicle ; high-density residential district ; pedestrian wind environment ; computational fluid dynamics ; enclosure boundary ; lift-up design ; bushfire ; retrofit ; ember attack ; pressure differential ; urban fringe ; rural housing ; pyro-tornadogenesis ; backdraft ; self-consumption ; solar photovoltaics ; heat pumps ; thermal storage ; space heating ; space cooling ; residential construction ; retrofitting ; sustainable construction ; literature review ; research trends ; scientometric review ; carbon emission ; Green Building-Rating System (GBS) ; cross laminated timber (CLT) ; hybrid structure system ; radiant system ; conditioning system ; residential building ; BIM ; IFC ; architecture model enrichment ; machine learning ; IfcSpace ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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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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    IntechOpen | IntechOpen
    Publication Date: 2024-04-14
    Description: This book provides an overview of Data and Decision Sciences (DDS) and recent advances and applications in space-based systems and business, medical, and agriculture processes, decision optimization modeling, and cognitive decision-making. Written by experts, this volume is organized into four sections and seven chapters. It is a valuable resource for educators, engineers, scientists, and researchers in the field of DDS.
    Keywords: machine learning ; simulation ; sustainable agriculture ; regression ; decision support system ; data analytics ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Cybersecurity models include provisions for legitimate user and agent authentication, as well as algorithms for detecting external threats, such as intruders and malicious software. In particular, we can define a continuum of cybersecurity measures ranging from user identification to risk-based and multilevel authentication, complex application and network monitoring, and anomaly detection. We refer to this as the “anomaly detection continuum”. Machine learning and other artificial intelligence technologies can provide powerful tools for addressing such issues, but the robustness of the obtained models is often ignored or underestimated. On the one hand, AI-based algorithms can be replicated by malicious opponents, and attacks can be devised so that they will not be detected (evasion attacks). On the other hand, data and system contexts can be modified by attackers to influence the countermeasures obtained from machine learning and render them ineffective (active data poisoning). This Special Issue presents ten papers that can be grouped under five main topics: (1) Cyber–Physical Systems (CPSs), (2) Intrusion Detection, (3) Malware Analysis, (4) Access Control, and (5) Threat intelligence.AI is increasingly being used in cybersecurity, with three main directions of current research: (1) new areas of cybersecurity are being addressed, such as CPS security and threat intelligence; (2) more stable and consistent results are being presented, sometimes with surprising accuracy and effectiveness; and (3) the presence of an AI-aware adversary is recognized and analyzed, producing more robust solutions.
    Keywords: Internet of Things ; cybersecurity ; cyber threats ; malware detection ; machine learning ; network traffic ; cooperative intelligent transportation systems (cITSs) ; IDS ; vehicular ad-hoc networks (VANET) ; adaptive model ; deep belief network (DBN) ; NIDS ; deep learning ; false negative rate ; artificial neural network ; MITRE ATT&CK Matrix ; techniques classification ; BERT-based multi-labeling ; formal ontology ; risk identification ; vulnerability ; portable executable malware ; tree-based ensemble ; performance comparison ; statistical significance test ; adversarial examples ; face recognition ; mask matrix ; targeted attack ; non-targeted attack ; anomaly detection ; attack detection ; cyber-physical system ; datasets ; evaluation metrics ; biometric cryptosystem ; iris identification ; error-correcting codes ; intrusion detection ; smart grid ; neural networks ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: Comprehensive understanding of surface water and groundwater interaction is essential for effective water resources management. Groundwater and surface water are closely connected components that constantly interact with each other within the Earth’s hydrologic cycle. Many studies utilized observations to explain the surface water and groundwater interactions by carefully analyzing the behavior of surface water features (streams, lakes, reservoirs, wetlands, and estuaries) and the related aquifer environments. However, unlike visible surface water, groundwater, an invisible water resource, is not easy to measure or quantify directly. Nevertheless, demand for groundwater that is highly resilient to climate change is growing rapidly. Furthermore, groundwater is the prime source for drinking water supply and irrigation, and hence critical to global food security. Groundwater needs to be managed wisely, protected, and especially sustainably used. However, this task has become a challenge to many hydrologic systems in arid to even humid regions because of added stress caused by changing environment, climate, land use, population growth, etc. In this issue, the editors present contributions on various research areas such as the integrated surface water and groundwater analysis, sustainable management of groundwater, and the interaction between surface water and groundwater. Methodologies, strategies, case studies as well as quantitative techniques for dealing with combined surface water and groundwater management are of interest for this issue.
    Keywords: groundwater-surface water interaction ; analytical ; numerical ; FEMME ; STRIVE ; MODFLOW ; Long Short-Term Memory ; groundwater level prediction ; groundwater withdrawal impact ; groundwater level variation ; machine learning ; integrated surface water and groundwater analysis ; climate change ; hydraulic fracturing ; construction of well pads ; MIKE-SHE ; MIKE-11 ; northwestern Alberta ; SWAT+ ; groundwater ; modeling ; groundwater–surface water interactions ; rainwater harvesting ; climate variability ; small island developing states ; improved water governance ; national sustainable development plans ; SDG6 ; community participation ; drinking water supply ; water supply scheme ; surface water/groundwater interactions ; managed aquifer recharge ; induced riverbank filtration ; groundwater resource management ; water curtain cultivation ; surface–groundwater interaction ; water budget analysis ; Nera River ; carbonate aquifer ; recession curves ; seismic sequence ; permafrost hydrology ; Russian Arctic ; water tracks ; hydrological connectivity ; stable water isotopes ; dissolved organic carbon ; electrical resistivity tomography ; taliks ; flood ; surface and groundwater interactions ; HEIFLOW ; Managed Aquifer Recharge ; groundwater tracer ; heat transport ; surface–ground-water interactions ; infiltration basin ; groundwater hydrology ; young water fraction ; global meteoric water line ; northern Italian Apennines ; stakeholder participation ; surface water-groundwater interaction ; scenario modelling ; integrated water management ; agent-based modelling ; SimCopiapo ; water balance ; water table fluctuation method ; irrigated pastures ; deep percolation ; aquifer recharge ; clay soils ; flood irrigation ; water management ; surface water ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Childhood obesity continues to be a global problem, with several regions showing increasing rates and others having one in every three children overweight despite an apparent halt or downward trend. Children are exposed to nutritional, social, and obesogenic environmental risks from different settings, and this affects their lifelong health. There is a consensus that high-quality multifaceted smart and cost-effective interventions enable children to grow with a healthy set of habits that have lifelong benefits to their wellbeing. The literature has shown that dietary approaches play key roles in improving children’s health, not only on a nutritional level but also in diet quality and patterns. An association between the nutritional strategy and other lifestyle components promotes a more comprehensive approach and should be envisioned in intervention studies. This Special Issue entitled “Child Obesity and Nutrition Promotion Intervention” combines original research manuscripts or reviews of the scientific literature concerning classic or innovative approaches to tackle this public health issue. It presents several nutritional interventions alongside lifestyle health factors, and outcome indicators of effectiveness and sustainability from traditional to ground-breaking methods to exploit both qualitative and quantitative approaches in tackling child obesity.
    Keywords: serious game ; gamification ; eating behavior ; food neophobia ; willingness to taste ; nutritional status ; obesity ; dietary habits ; allergy ; pulmonary function ; allergic rhinitis ; asthma ; dietary habit ; vegetable consumption ; food intake ; preschool children ; Japan ; nutrition ; stress ; mental health ; family ; health behavior ; childhood obesity ; health intervention ; healthy lifestyle intervention ; school-based intervention ; MVPA ; overweight and obesity ; self-efficacy ; adolescent girls ; parent–child dyads ; food availability ; advertising ; healthy diet ; promotion programs ; community-based program ; school meals ; salt intake ; sodium consumption ; schools ; canteen ; adolescents ; implementation ; purchase behaviour ; overweight ; machine learning ; deep learning ; statistical models ; data science ; BMI ; child ; surveillance ; health ; noncommunicable diseases ; children ; fruit ; vegetables ; soft drinks ; energy balance-related behaviors ; self-regulation skills ; preschoolers ; randomized controlled trial ; intervention effects ; parental educational level ; intervention mapping ; multicomponent intervention ; school children ; food and nutrition ; intervention ; healthy eating ; food acceptance ; tactile play ; cooking ; fish ; health promotion ; childhood overweight ; risk ; community ; screening ; tool ; food environment ; home ; school ; food consumption patterns ; dietary intakes ; macronutrients ; micronutrients ; Eastern Mediterranean Region ; review ; parental role modelling ; family environment ; availability and accessibility ; cluster randomised controlled trial ; minority ; parents ; prevention ; diet ; nutrition promotion ; Black/African American ; Hispanic ; qualitative ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFC Cultural studies::JFCV Food & society
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-11-17
    Description: Today’s power system is facing the challenges of increasing global demand for electricity, high-reliability requirements, the need for clean energy and environmental protection, and planning restrictions. To move towards a green and smart electric power system, centralized generation facilities are being transformed into smaller and more distributed ones. As a result, the microgrid concept is emerging, where a microgrid can operate as a single controllable system and can be viewed as a group of distributed energy loads and resources, which can include many renewable energy sources and energy storage systems. The energy management of a large number of distributed energy resources is required for the reliable operation of the microgrid. Microgrids and nanogrids can allow for better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and technical disruptive events. Microgrid networking with optimal energy management will lead to a sort of smart grid with numerous benefits such as reduced cost and enhanced reliability and resiliency. They include small-scale renewable energy harvesters and fixed energy storage units typically installed in commercial and residential buildings. In this challenging context, the objective of this book is to address and disseminate state-of-the-art research and development results on the implementation, planning, and operation of microgrids/nanogrids, where energy management is one of the core issues.
    Keywords: energy demand ; long-term forecasting ; machine learning ; R programming ; solar power generation ; support vector regression ; economic energy ; Bonobo Optimizer ; hybrid renewable energy system ; microgrid ; PV panels ; wind turbine ; energy storage ; hierarchical control ; primary ; secondary control ; droop control ; frequency restoration ; voltage restoration ; grid synchronization ; proportional resonant controller ; robust control ; distributed generation, microgrid ; LMI ; optimization ; lightning attachment procedure optimization (LAPO) algorithm ; photovoltaic panel ; uncertainty ; cooperation ; energy ; reliability ; Monte Carlo ; smart energy control ; grid-synchronization ; dynamic voltage restorer ; converter control system ; sliding mode control ; economic scheduling ; clean energy ; quantum mayfly algorithm (QMA) ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint, entitled “Process Control and Smart Manufacturing for Industry 4.0”, contains the extended papers from the Series of annual IFSA conferences on Automation, Robotics and Communications for Industry 4.0/5.0 (ARCI) on the following topics: Process Automation, Process Control and Monitoring, Design Principles in Industry 4.0, Smart Manufacturing and Technologies, Smart Factories, Machine Learning and Artificial Intelligence in Manufacturing. The reprint contains 13 chapters written by 54 ARCI conference participants from seven countries: China, Croatia, Denmark, Germany, Italy, Poland and Romania. This reprint will inform readers of cutting-edge developments in the field and provide effective starting points and a road map for further research and development. All chapters follow the same structure: firstly, an introduction to the specific topic under study; secondly, a description of the field, including sensing or/and measuring applications. Each chapter ends with a curated list of references, including books, journals, conference proceedings and websites. “Process Control and Smart Manufacturing for Industry 4.0” is intended for researchers and scientists from academia and industry, as well as for postgraduate students.
    Keywords: steel alloys ; resistance spot welding ; RSW ; electrode wear ; electrode tip-dressing ; process monitoring ; mushrooming ; plateau forming ; quality control ; COVID-19 ; FDM ; 3D printing ; injection molding ; personal protection ; rapid prototyping ; protective face shields ; mechatronics line ; visual servoing system ; wheeled mobile robot ; industrial robotic manipulator ; Industry 4.0 ; NDT ; magnetic particle inspection ; optimization ; condition monitoring ; vibration ; acoustic emission ; drive train ; data fusion ; machine learning ; product morphology ; core data model ; phase rule filter ; phase private data model ; storage system ; forklift AGV ; deep learning ; semantic segmentation ; H-Swish ; community transformation ; community innovation governance ; ternary space ; coupling and coordination analysis ; lean manufacturing ; lean principles ; pull principle ; production control mechanisms ; production processes ; lean implementation ; batch process ; partial least squares ; multi-phase ; multi-mode ; master production scheduling ; make-to-order ; mathematical programming ; agent-based ; overtime ; earliness ; tardiness ; equipment selection decision ; business compass ; energy consumption ; processing time ; beetle antennae search algorithm ; sustainable blank dimension design ; energy-saving ; low-carbon ; grey wolf algorithm ; gas–solid ; cyclone ; separator ; gas dynamics ; erosion ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PN Chemistry
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: This Special Issue is intended to lay the foundation of AI applications focusing on oral health, including general dentistry, periodontology, implantology, oral surgery, oral radiology, orthodontics, and prosthodontics, among others.
    Keywords: machine learning ; artificial intelligence ; malocclusion ; diagnostic imaging ; active learning ; maxillary sinusitis ; convolutional neural network ; deep learning ; segmentation ; oral microbiota ; LEfSe ; PCoA ; alloprevotella ; prevotella ; core microbiota ; artificial neural networks ; oral cancer diagnosis ; oral cancer prediction ; pit and fissure sealants ; caries assessment ; visual examination ; clinical evaluation ; convolutional neural networks ; transfer learning ; deep learning network ; YOLOv4 ; mandibular third molar ; inferior alveolar nerve ; contact relationship ; panoramic radiograph ; deep learning methods ; caries diagnosis ; dental panoramic images ; radiography ; Fourier transform infrared spectroscopy ; FTIR imaging ; spectral biomarker ; multivariate analysis ; discriminant model ; oral squamous cell carcinoma ; oral epithelial dysplasia ; oral potentially malignant disorder ; risk stratification ; early oral cancer detection ; dentigerous cysts ; histopathology images ; image classification ; odontogenic keratocysts ; radicular cysts ; AI ; screening ; diagnosis ; dentistry ; ultrasonography ; tongue ; algorithm ; dysphagia ; impacted ; tooth ; detection ; neural networks ; proximal caries ; training strategy ; small dataset ; periapical radiograph ; X-ray ; tooth extraction ; oroantral fistula ; operative planning ; n/a ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This reprint focuses on the mechanisms, modeling and controlling techniques of flash flood disasters, mainly in mountainous areas. Flash floods are among the most severe natural disasters, and the current publication will not only inspire future research but also enrich the current practice of flash flood disaster prevention and mitigation. This collection focusses on the engaged efforts in mitigating flash flood disasters, deepening the understanding of the causes of disasters in existing cases, finding appropriate modeling approaches, and implementing mitigation strategies. The readers will find within this reprint significant contributions for improving prevention and developing mitigation strategies, as well as protecting the safety of exposed populations.
    Keywords: flood monitoring ; forecasting ; hazard exposure ; emergency response ; Vaisigano River ; Samoa ; SWAT ; CMADS ; TRMM ; the Danjiang river basin ; flash flood ; bifurcation ; confluence ; shallow-water models ; flash-flood modelling system ; disaster mechanism ; runoff generation component ; disaster amplification effect ; economic losses from flood disasters ; flash flood disaster control ; Kaya identity ; LMDI technique decomposition method ; flood hazard ; morphometry ; PCA ; logistic regression ; Sinai ; Egypt ; grass coverage rate ; grass spatial arrangement patterns ; slope-gully system ; erosion ; debris flow ; lateral erosion ; strong earthquake area ; model experiment ; erosion pattern ; Tlalnepantla River ; flash floods ; hyetograph shape ; Hec Ras 2d ; Dorrigo diagram ; regionalization ; hydrological model ; hydrodynamic model ; disaster review analysis ; heavy rainfall in Henan ; periglacial debris flow ; southeast Tibet ; small sample imbalanced data ; prediction model ; random forest ; mountain torrents ; distributed hydrological model ; parameters regionalization ; machine learning ; 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: 2023-06-23
    Description: “Soft Computing and Machine Learning in Dam Engineering” is a comprehensive, edited Special Issue that explores the latest advances in the application of soft computing and machine learning techniques to dam engineering. This reprint covers a range of topics, including dam design, construction, monitoring, and maintenance, and provides readers with a deep understanding of the theoretical foundations and practical applications of these techniques.Featuring contributions from leading experts in the field, the reprint presents a collection of 11 papers that offer insights into state-of-the-art approaches in dam engineering. The chapters cover topics such as fuzzy logic, genetic algorithms, artificial neural networks, and support vector machines, and provide practical examples of how these techniques can be applied to solve real-world dam engineering problems.Whether you are a researcher, engineer, or student in the field of dam engineering, “Soft Computing and Machine Learning in Dam Engineering” provides a valuable resource for staying up-to-date with the latest techniques and approaches in the field.
    Keywords: dams ; Polynomial Chaos Expansion ; random fields ; random forest ; vibration analysis ; gravity dams ; safety assessment ; probabilistic analysis ; parameter uncertainty ; sample optimization ; variance-based sensitivity analysis ; sensitivity analysis ; polynomial chaos expansion ; uncertainty ; deep neural networks ; rockfill dams ; anomaly detection ; machine learning ; support vector machines ; one-class classification ; concrete dam ; machine learning methods ; structural behaviour ; model validation ; ice loads ; concrete dams ; back-calculation ; dam safety ; monitoring ; arch dams ; seismic safety ; endurance time analysis ; non-linear seismic analysis ; concrete damage model ; tensile and compressive damage ; design variable ; finite element ; feasibility design ; surrogate ; AutoML ; roller compacted concrete (RCC) ; risk-informed design ; Cascadia subduction zone (CSZ) ; non-linear structural analysis ; multilayer perceptron neural network model ; structural health monitoring ; threshold definition ; moving average of the residuals ; moving standard deviation of the residuals ; DBSCAN ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.
    Keywords: rolling bearing ; performance degradation ; hybrid kernel function ; krill herd algorithm ; SVR ; acoustic-based diagnosis ; gear fault diagnosis ; attention mechanism ; convolutional neural network ; stacked auto-encoder ; weighting strategy ; deep learning ; bearing fault diagnosis ; intelligent leak detection ; acoustic emission signals ; statistical parameters ; support vector machine ; wavelet denoising ; Shannon entropy ; adaptive noise reducer ; gaussian reference signal ; gearbox fault diagnosis ; one against on multiclass support vector machine ; varying rotational speed ; fault detection and diagnosis ; faults estimation ; actuator and sensor fault ; observer design ; Takagi-Sugeno fuzzy systems ; automotive ; perception sensor ; lidar ; fault detection ; fault isolation ; fault identification ; fault recovery ; fault diagnosis ; fault detection and isolation (FDIR) ; autonomous vehicle ; model predictive control ; path tracking control ; fault detection and isolation ; braking control ; nonlinear systems ; fault tolerant control ; iterative learning control ; neural networks ; cryptography ; wireless sensor networks ; machine learning ; scan-chain diagnosis ; artificial neural network ; NARX ; control valve ; decision tree ; signature matrix ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc.
    Keywords: Automatic Voltage Regulation system ; Chaotic optimization ; Fractional Order Proportional-Integral-Derivative controller ; Yellow Saddle Goatfish Algorithm ; two-stage method ; mono and multi-objective optimization ; multi-objective optimization ; optimal design ; Gough–Stewart ; parallel manipulator ; performance metrics ; diversity control ; genetic algorithm ; bankruptcy problem ; classification ; T-junctions ; neural networks ; finite elements analysis ; surrogate ; beam improvements ; beam T-junctions models ; artificial neural networks (ANN) limited training data ; multi-objective decision-making ; Pareto front ; preference in multi-objective optimization ; aeroacoustics ; trailing-edge noise ; global optimization ; evolutionary algorithms ; nearly optimal solutions ; archiving strategy ; evolutionary algorithm ; non-linear parametric identification ; multi-objective evolutionary algorithms ; availability ; design ; preventive maintenance scheduling ; encoding ; accuracy levels ; plastics thermoforming ; sheet thickness distribution ; evolutionary optimization ; genetic programming ; control ; differential evolution ; reusable launch vehicle ; quality control ; roughness measurement ; machine vision ; machine learning ; parameter optimization ; distance-based ; mutation-selection ; real application ; experimental study ; global optimisation ; worst-case scenario ; robust ; min-max optimization ; optimal control ; multi-objective optimisation ; robust design ; trajectory optimisation ; uncertainty quantification ; unscented transformation ; spaceplanes ; space systems ; launchers ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems.
    Keywords: hydraulic modelling ; pressure control valve ; pressure management ; remote real-time control ; stochastic consumption ; water distribution system ; fault identification ; hydraulic transient ; inverse transient analysis (ITA) ; water distribution network ; optimization approach ; water distribution monitoring ; optimal sensor placement ; water network partitioning ; topological centrality ; smart water system ; framework ; smartness ; cyber wellness ; leakage ; sensitivity ; uncertainty ; entropy ; multi-criteria decision-making ; DEMATEL ; clustering ; district metered area ; network sectorization ; smart city ; water quality monitoring ; Internet of Things ; wireless sensor networks ; water treatment plant ; data analytics ; nitrate ; nitrite ; water demand forecasting ; hybrid model ; error correction ; chaotic time series ; least square support vector machine ; cross-correlation ; data spatial aggregation ; finite population effect ; metering ; sample mean ; sampling design ; standard error ; stochastic analysis ; water demand peak factor ; water distribution networks ; comparative analysis ; hydraulic measure ; multi-criteria decision analysis (MCDA) ; reliability index ; water distribution network (WDN) ; smart stormwater ; machine learning ; cluster analysis ; data science ; flooding detection ; rainwater harvesting ; water trading ; dual reticulation ; decentralized water supply ; agent-based modeling ; urban water management ; urban water consumption ; water demand data ; water data accessibility ; data resolution ; smart meter ; smart water systems ; cyber–physical security ; cyber-security ; cyber–physical attacks ; n/a ; water distribution systems ; cyber-attack detection ; blind sources separation ; FastICA ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-07-06
    Description: Artificial intelligence (AI) is changing the world as we know it. Recent advances are enabling people, companies, and governments to envision and experiment with new methods of interacting with computers and modifying how virtual and physical processes are carried out. One of the fields in which this transformation is taking place is education. After years of witnessing the incorporation of technological innovations into learning/teaching processes, we can currently observe many new research works involving AI. Moreover, there has been increasing interest in this research area after the COVID-19 pandemic, driven toward fostering digital education. Among recent research in this field, AI applications have been applied to enhance educational experiences, studies have considered the interaction between AI and humans while learning, analyses of educational data have been conducted, including using machine learning techniques, and proposals have been presented for new paradigms mediated by intelligent agents. This book, entitled “AI in Education”, aims to highlight recent research in the field of AI and education. The included works discuss new advances in methods, applications, and procedures to enhance educational processes via artificial intelligence and its subfields (machine learning, neural networks, deep learning, cognitive computing, natural language processing, computer vision, etc.).
    Keywords: performance measurement ; key performance indicators ; educational data mining ; institutes performance ; governance ; educational mining ; machine learning ; artificial intelligence ; decision support systems ; systematic literature review ; learning styles ; hybrid university teaching ; e-behaviour ; big five personality ; student performance ; plagiarism ; ethics ; academic dishonesty ; online education ; higher education ; AS&P model ; Pakistan ; 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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    Frontiers Media SA
    Publication Date: 2024-04-04
    Description: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
    Keywords: water ; numerical modeling ; Inverse problem ; hydrogeophysics ; machine learning ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; 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: 2022-06-21
    Description: Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems.
    Keywords: smart grids ; device authentication ; situational awareness ; home area networks ; time-delay switch attack ; networked control systems ; secure control design ; Lyapunov theory ; attack estimation ; hardware-in-the-loop testing ; machine learning ; industrial control systems ; anomaly detection ; fault detection ; intrusion detection system ; blockchain ; security ; privacy ; financial transactions ; transportation systems ; autonomous vehicles ; power system resilience ; disaster ; Federated Learning ; edge intelligence ; resilience management systems ; resource-limitations ; demand response ; remedial testing ; greybox fuzzing ; vulnerability detection ; enhanced security ; traffic microsimulation tool ; cooperative automated driving systems ; vehicle powertrain ; safety ; road capacity ; contested environments ; anomaly isolation ; artificial neural networks ; Cyber Physical System ; out-of-bounds ; vulnerable detection ; patch ; inverter-based energy resources ; islanded microgrids ; resilient control design ; secondary control ; false data injection ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives.
    Keywords: Ground Penetrating Radar (GPR) ; Unmanned Aerial Vehicles (UAVs) ; Synthetic Aperture Radar (SAR) ; Real Time Kinematic (RTK) ; Ultra-Wide-Band (UWB) ; landmine and IED detection ; non-destructive testing ; GPR ; coherence ; semblance ; attribute analysis ; imaging ; GPR trace ; high-resolution data ; large-scale survey ; archaeological prospection ; Ground-Penetrating Radar ; velocity analysis ; coherency functionals ; GPR data processing ; GPR data migration ; spatial-variant convolution neural network (SV-CNN) ; spatial-variant convolution kernel (SV-CK) ; radar image enhancing ; MIMO radar ; neural networks ; imaging radar ; ground penetrating radar ; wavelet scattering network ; machine learning ; support vector machine ; pipeline identification ; snow ; snow water equivalent (SWE) ; stepped-frequency continuous wave radar (SFCW) ; software defined radio (SDR) ; snowpack multilayer reflectance ; Ground Penetrating Radar ; Synthetic Aperture Radar ; landmine ; Improvised Explosive Device ; radar ; noise attenuation ; Gaussian spike impulse noise ; deep convolutional denoising autoencoders (CDAEs) ; deep convolutional denoising autoencoders with network structure optimization (CDAEsNSO) ; applied geophysics ; digital signal processing ; enhancement of 3D-GPR datasets ; clutter noise removal ; spectral filtering ; ground-penetrating radar ; nondestructive testing ; pipelines detection ; modeling ; signal processing ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: Breast cancer is acknowledged as an international priority in healthcare. It is currently the most common cancer in women worldwide, with demographic trends indicating a continuous increase in incidence. Over the years, increasing efforts and resources have been devoted to the search for a systematic and optimized strategy in breast cancer diagnosis and treatment. Today, the Breast Unit model is considered the gold standard in order to ensure optimal patient-centered and research-based clinical services through multidisciplinary and integrated management.Surgical treatment has gradually evolved toward less aggressive approaches with the adoption of new therapeutic strategies. The evolution of evidence-based guidelines in such leading disciplines as radiation and medical oncology has led to a steady improvement in survival rates. This Special Issue will highlight innovations in the integrated management of breast cancer, their potential advantages, and the many open issues that still need to be properly defined and addressed.
    Keywords: metastatic breast cancer ; breast surgery ; immune system ; metabolic derangements ; precision medicine ; integrated therapies ; advanced breast cancer ; mTOR inhibitor ; CDK4/6 inhibitor ; endocrine resistance ; breast cancer ; pregnancy ; chemotherapy ; tailoring ; personalization ; DataMart ; real world data ; predictive model ; healthcare ; breast-conserving surgery ; non-palpable breast lesions ; image-guided localization ; preoperative breast localization ; breast ultrasound ; large database ; standardized data collection ; networks ; nipple-sparing mastectomy ; immediate breast reconstruction ; acellular dermal matrix (ADM) ; aesthetic and oncological outcomes ; quality of life ; rare breast cancer ; osteoclast-like giant cells ; gene profiling ; Oncotype Dx ; adjuvant treatment ; neoadjuvant chemotherapy ; sentinel lymph node ; systemic treatment ; locally advanced breast cancer ; mini-invasive treatment ; liver metastases ; hepatic surgery ; personalized medicine ; sarcopenia ; physical performance ; frailty ; older cancer patients ; clinical trial ; patient enrollment ; artificial intelligence ; machine learning ; lung cancer ; oncology ; web app ; conventional CT and CT angiography ; DIEP flap planning ; multidisciplinary treatment ; evidence-based medicine ; personalized treatment ; oncological outcomes ; patient quality of life ; normal breast ; breast pathology ; hormone receptor ; hormone expression ; lymphedema ; lymphaticovenous anastomosis ; vascularized lymph node transfer ; lymphatic microsurgery ; radiotherapy ; oligometastatic breast cancer ; locoregional therapy ; CDK4/6 inhibitors ; multidisciplinary ; AMH ; ovarian reserve ; pregnancy desire ; subtypes breast cancer ; miRNAs ; breast cancer treatment ; next-generation-sequencing ; target therapy ; old age ; survival ; vitamin D ; ductal breast cancer ; in situ breast cancer ; lobular breast cancer ; histology ; n/a ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MM Other branches of medicine::MMG Pharmacology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Given the current growth in global challenges, the need for smart agriculture practices and effective strategies is emerging as an imminent issue at a planetary scale. Agriculture 4.0 involves a large variety of mobile apps, web applications, Internet of Things (IoT) devices and platforms, drones, robots, and smart machinery for precision agriculture. The expansion of cloud technologies, artificial intelligence (AI), machine learning (ML), deep learning (DL), and big data collection are setting the stage for Agriculture 5.0. Agriculture science and natural sciences are further promoting this trend with the development of leading-edge scientific models and platforms, including stochastic, process-based, and data-driven machine learning modeling. This Special Issue covers the most recent and up-to-date progress in all aspects of internet and computer software applications in agriculture, focusing on the development of web applications and mobile apps, smart IoT devices and platforms, AI, ML and DL solutions in precision agriculture for detection, recognition, classification, monitoring, cultivation, harvesting, and marketing; development of cloud technologies for smart agriculture; computer and machine vision methods and applications for drones and smart machinery, and sensors for field operations; diagnostics and data collection; big data science; scientific process-based and stochastic modeling; and machine learning modeling for agriculture, agroecosystems and natural ecosystems. The research in this Special Issue will contribute to the promotion of modern agriculture practices in the current climate and in the future.
    Keywords: grape varieties identification ; Support Vector Machine (SVM) ; Convolutional Neural Network (CNN) ; deep feature fusion ; Canonical Correlation Analysis (CCA) ; smart machinery ; digital agriculture ; Chinese agricultural diseases and pests ; named entity recognition ; adversarial training ; semantic enhancement ; technology innovation ; food processing ; transition pathways ; sustainable food systems ; transformation ; smart farming ; IoT ; WSN ; containerization ; multi-agent ; neural network ; LSTM ; leisure agricultural park ; traveler group ; COVID-19 pandemic ; fuzzy collaborative intelligence ; machine vision ; maize seeds ; classification ; deep learning ; convolutional neural network ; decision support systems ; agricultural water management ; water security ; data-driven modeling ; conceptual resilience model ; input uncertainty ; climate extreme ; process-based modeling ; vehicle routing problem ; fresh agricultural products ; split delivery ; NSGA-II algorithm ; farm management information system ; farmers’ information needs assessment ; soft system methodology ; smallholder farmers ; conceptual model ; Indonesian chili farmers ; residual block ; attention mechanism ; grape leaf disease ; aquatic products price forecast ; VMD ; IBES ; hybrid model ; precision agriculture ; sensor network ; semi-literate farmers ; interactive interface ; User Interface (UI) ; Android apps ; machine learning ; regression algorithms ; web application ; early prediction of crop yield ; grape detection ; self-attention ; buffalo breeds ; Neural Networks ; Self Activated CNN ; DeepLabv3+ ; semantic segmentation ; picking point identification ; e-commerce interest linkage ; participation willingness and behaviors ; government policies ; farmers’ cognition ; evolutionary game model ; structural equation model ; object detection ; YOLOv7 ; hemp duck count ; smart agriculture ; LoRaWAN ; water status ; supply chain ; horticulture ; logistics ; operations ; planning framework ; decision support ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint brings together fifteen articles published in the Special Issue of the journal Atmosphere, entitled “High-Performance Computing Serving Atmospheric Transport & Dispersion Modelling”. These articles cover a wide variety of topics related to air quality in urban areas and nature-based solutions to improve it in the context of climate change; impact studies on human health and the environment of facilities and infrastructure projects as well as risk studies; the assessment of emerging threats; and preparations for and responses to emergencies involving toxic, flammable, or explosive atmospheric releases. As the fifteen articles presented here remarkably illustrate, what these contemporary topics have in common is the implementation of multi-scale simulations of atmospheric transport and dispersion by means of physical models of computational fluid dynamics (CFDs), whose potential is enhanced by high-performance computing (HPC). This reprint thus addresses the answers provided by modelling and the most advanced simulations to some societal matters of major interest.
    Keywords: operational emergency modeling ; atmospheric release ; high-resolution metric grid ; 3D ; PMSS modeling system ; Code_Saturne ; EMERGENCIES project ; lattice Boltzmann method ; large eddy simulation ; pollutant dispersion ; urban physics ; urban air pollution ; nature-based solutions ; green infrastructure ; PMSS Lagrangian model ; NOx ; PM10 ; large-eddy simulation ; plume dispersion ; urban area ; coupling simulation ; mesoscale meteorological simulation model ; meteorological observation ; graphics processing unit computing ; atmospheric dispersion modelling ; microscale dispersion ; model validation ; database ; on-site meteorological observation ; water mist dispersion ; lagrangian dispersion model ; web visualization ; web mapping ; emergencies project ; atmospheric boundary layer ; OpenFOAM ; gas dispersion ; CFD ; turbulence model ; hazard assessment ; horizontal homogeneity ; wind field ; deposition ; machine learning ; hazardous release ; WRF ; FLEXPART ; prediction ; air pollution ; air quality modelling ; ADMS-Urban ; high performance computing ; HPC ; West Midlands ; air quality ; urban scale ; traffic emissions ; micro-scale dispersion models ; aerosols ; South Asia ; WRF-Chem ; precipitation ; CAPE ; CIN ; urban dispersion ; complex terrain ; fast-response dispersion modeling ; computational fluid dynamics ; RANS ; urban dispersion modelling ; Reynolds-averaged Navier–Stokes ; situational awareness ; CityGML ; air quality impact study ; PMSS model ; high resolution grid ; bic Book Industry Communication::M Medicine
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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: 2024-03-30
    Description: In total, this Special Issue includes 11 papers. Firstly, Qi et al. conducted research on the large-scale non-uniform parallel solution of the two-dimensional Saint-Venant equations for flood behavior modeling. Zhang et al. proposed an efficient deep learning-based mineral identification method. Subsequently, Huang et al. proposed a named entity recognition method for geological news based on BERT model. Yang et al. proposed an automatic landslide identification method to solve the problem of the time-consuming nature and low efficiency of traditional landslide identification methods. Du et al. analyzed the potential of unsupervised machine learning methods for submarine landslide prediction. Wang et al. performed parallel computations on the inversion algorithm of the two-dimensional ZTEM. Xu et al. used the sliding window method and gray relational analysis to extract features from multi-source real-time monitoring data of landslides. Furthermore, Cao et al. proposed a new method called dual encoder transform (DualET) for the short-term prediction of photovoltaic power. Hao et al. conducted a series of parallel optimizations and large-scale parallel simulations on the high-resolution ocean model. Wang et al. proposed a time series prediction model for landslide displacements using mean-based low-rank autoregressive tensor completion. Finally, Yang et al. developed a measure of site-level gross primary productivity (GPP) using the GeoMAN model.
    Keywords: Saint-Venant equations ; finite difference method ; parallel computing ; heterogeneous computing ; deep learning ; image enhancement ; mineral identification ; convolutional neural networks ; BERT ; named entity recognition ; geological news ; CRF ; semantic segmentation ; PSPNet ; landslide ; submarine landslide ; machine learning ; hazard susceptibility ; spatial distribution ; ZTEM ; 2D forward modeling ; inversion ; parallel algorithm ; tipper ; disaster precursor identification ; early warning ; association rule mining ; particle swarm optimization ; k-means clustering ; Apriori algorithm ; gray relation analysis ; transformer ; photovoltaic power forecasting ; satellite images ; LICOM ; meteorological model ; parallel optimization ; time series ; missing data ; tensor completion ; autoregressive norm ; displacement prediction ; GeoMAN model ; gross primary productivity ; attention mechanism ; interdisciplinary ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Additive manufacturing (AM) or, more commonly, 3D printing is one of the fundamental elements of Industry 4.0. and the fourth industrial revolution. It has shown its potential example in the medical, automotive, aerospace, and spare part sectors. Personal manufacturing, complex and optimized parts, short series manufacturing and local on-demand manufacturing are some of the current benefits. Businesses based on AM have experienced double-digit growth in recent years. Accordingly, we have witnessed considerable efforts in developing processes and materials in terms of speed, costs, and availability. These open up new applications and business case possibilities all the time, which were not previously in existence. Most research has focused on material and AM process development or effort to utilize existing materials and processes for industrial applications. However, improving the understanding and simulation of materials and AM process and understanding the effect of different steps in the AM workflow can increase the performance even more. The best way of benefit of AM is to understand all the steps related to that—from the design and simulation to additive manufacturing and post-processing ending the actual application.The objective of this Special Issue was to provide a forum for researchers and practitioners to exchange their latest achievements and identify critical issues and challenges for future investigations on “Modeling, Simulation and Data Processing for Additive Manufacturing”. The Special Issue consists of 10 original full-length articles on the topic.
    Keywords: selective laser melting ; finite element analysis ; thermodynamic behavior ; substrate preheating ; scanning strategy ; 24CrNiMo alloy steel ; additive manufacturing ; rapid manufacturing ; rapid prototyping ; 3D printing ; medical ; implants ; dental ; processes ; methods ; clinical ; laser additive manufacturing ; Inconel 718 ; pure Ti ; finite element modeling ; melt-pool formation ; thermo-mechanical modelling ; residual stresses ; microstructure ; Ti-6Al-4V ; acoustics ; porous materials ; material extrusion ; design for additive manufacturing ; sound absorption ; artificial neural network ; machine learning ; quality control management ; process optimization ; computing techniques ; ICT systems ; laser powder bed fusion (LPBF) ; benchmark test artifact ; numerical simulations ; dimensional metrology ; geometric dimensioning and tolerancing (GD&T) ; selective laser melting (SLM) ; lattice structure ; bimetallic composite ; mechanical properties ; finite element analysis (FEA) ; digital image correlation (DIC) ; hybrid manufacturing ; inconel 625 ; EDS microanalysis ; automatic image analysis ; laser melting ; laser sintering ; AlSi10Mg ; PA12 ; Round-Robin ; n/a ; 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: 2024-03-28
    Description: Global climate changes, particularly extreme events, affect terrestrial carbon, water, and energy exchanges between the atmosphere, biosphere, and lithosphere, thus controlling freshwater availability, floods, and droughts. Therefore, it is urgent and necessary to develop advanced climate simulation and observation approaches and models related to extreme climate events. Advanced climate simulation and observation can improve the accurate prediction of climate change and long-term trends, which can mitigate climate events' impacts on human society. Under these conditions, this reprint aims to introduce advanced climate simulation and observation approaches to various practical studies related to climate variations, including the global climate models (GCMs) and regional climate models (RCMs), mitigation studies of high-impact climate events, predictions of climate variations, and some new artificial intelligence. Twenty-two papers have been collected in this reprint, with eight original research articles reporting on climate change and six papers reporting on climate change's impact on society and the economy. Meanwhile, three papers reported climate change's impact on agriculture, and climate change's impact on human health was studied in five articles.
    Keywords: hydrological modeling ; gridded datasets ; sensitivity analysis ; water balance ; snowmelt ; SWAT ; Upper Vakhsh River Basin ; economic loss prediction ; machine learning ; input-output model ; flooding ; regional climate model ; RegCM4.5 ; western Tianshan Mountains ; parameterization scheme ; air quality satisfaction ; quality of life ; binomial logistic regression ; health utility value ; experienced utility ; elevated [CO2] ; warming ; SPAD ; leaf nitrogen monitoring ; nitrogen management ; Issyk-Kul ; accumulated temperature ; yield per unit area of beans ; climate change ; panel spatial error model ; air pollution ; respiratory disease ; generalized additive model ; scenario analysis ; assessment of economic losses ; arid climate ; geothermal energy ; underground temperature ; greenhouse ; heat exchanger ; agricultural air pollution ; labor migration ; mediation effect ; income effect ; economy of scale ; collective effect ; haze pollution ; scale effect ; special spillover effect ; urban population agglomeration ; AQI ; visual analysis ; heat map ; ARIMA model ; neural network model ; pulmonary tuberculosis ; penalized distributed lag non-linear model ; meteorological factors ; apparent temperature ; cumulative risk ; HDI ; decoupling index ; carbon emission performance ; LMDI ; 10 m wind speed ; cumulus parameterization schemes ; sensitivity of physical processes ; WRF ; mainland China ; environmental regulation ; green innovation efficiency ; SBM of super-efficiency ; system GMM estimation ; model evaluation ; rainfall simulation ; interannual variation ; IAP-AGCM ; Thailand ; China ; environmental Kuznets curve ; geographically weighted regression ; haze ; spatial heterogeneity ; air pollutants ; sustained exposure to pollution ; respiratory and cardiovascular diseases ; CiteSpace ; co-occurrence keywords ; burst words ; mountain-type zoonotic visceral leishmaniasis ; climate variables ; environmental variables ; ecological niche model ; transmission risk prediction ; drought ; cropland ; CMIP6 ; exposure ; scPDSI ; weather radar nowcasting ; generative adversarial network (GAN) ; Temporal and Spatial GAN (TSGAN) ; heavy precipitation ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences::RBP Meteorology and climatology
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  • 143
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load.
    Keywords: Prophet model ; Holt–Winters model ; long-term forecasting ; peak load ; prophet model ; multiple seasonality ; time series ; demand ; load ; forecast ; DIMS ; irregular ; galvanizing ; short-term electrical load forecasting ; machine learning ; deep learning ; statistical analysis ; parameters tuning ; CNN ; LSTM ; short-term load forecast ; Artificial Neural Network ; deep neural network ; recurrent neural network ; attention ; encoder decoder ; online training ; bidirectional long short-term memory ; multi-layer stacked ; neural network ; short-term load forecasting ; power system ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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  • 144
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-14
    Description: We are living in an age of digital transformation, where internet connectivity is totally transparent for end users. Since the development of internet of things technologies and artificial intelligence algorithms, we have also been experiencing new business models and applications. In Ubiquitous and Pervasive Computing - New Trends and Opportunities, novel concepts and applications in this area are described, and the expectations and challenges of the next ten years are discussed. Individual chapters focus on data science, the internet of things, big data, Industry 4.0, high-performance computing, intelligent applications, and cloud computing environments.
    Keywords: machine learning ; fog computing ; iot ; cloud computing ; healthcare ; security ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMZ Software Engineering
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  • 145
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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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  • 146
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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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  • 147
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The importance of evapotranspiration is well-established in different disciplines such as hydrology, agronomy, climatology, and other geosciences. Reliable estimates of evapotranspiration are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term estimates of water supply, demand and use, design and management of water resources infrastructure, and evaluation of the effect of land use and management changes on the water balance. The objective of this Special Issue is to define and discuss several ET terms, including potential, reference, and actual (crop) ET, and present a wide spectrum of innovative research papers and case studies.
    Keywords: evapotranspiration ; machine learning ; local ; spatial ; subhumid climate ; agricultural drought ; drought characteristics ; evapotranspiration deficit index ; parameter sensitivity ; temporal scale sensitivity ; water stress anomaly ; interception ; linear storage model ; evaporation ; cover crop ; water balance ; faba bean ; GK2A/AMI ; artificial neural network ; Korean Peninsula ; CWSI ; UAV ; remote sensing ; micrometeorological data ; spatial IRT measurements ; crop irrigation scheduling and management ; infrared radiometer sensors ; real-time data analysis ; water reservoir ; regression ; observed data ; ERA5-Land data ; R language ; precipitation ; drought ; Mann–Kendall ; trend analysis ; actual evapotranspiration ; potential evapotranspiration ; reference evapotranspiration ; evaporation paradox ; global dimming ; wind stilling ; forest fires ; groundwater ; stochastic simulation ; marginal structure ; long-range dependence ; Hurst–Kolmogorov dynamics ; RASPOTION ; parametric model ; hydrological calibration ; evapotranspiration estimation ; urban rain gardens ; lysimeters ; evapotranspiration models ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 148
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This second Special Issue was compiled because of the interest demonstrated by the great success of the first Special Issue devoted to "Sensor Systems for Gesture Recognition".We believe this reprint acts as a meaningful window towards "Gesture Recognition" and the related sensors allowing the gathering of necessary data.
    Keywords: abnormal gait behavior ; OpenPose ; machine learning ; XGBoost ; random forest ; horse locomotion ; training effect ; inertial measurement units ; sports technology ; football ; motion analysis ; IMU ; trajectory reconstruction ; human-computer interactive ; data glove ; virtual hand ; emotion driven ; test ; visual tracking ; Siamese tracker ; tracking drift ; background clutter ; deep learning ; surgical skills assessment ; computer vision ; surgical education ; biomedical engineering ; multi-modal ; human activity recognition ; markerless ; RGB-D ; general movements ; infant movement analysis ; movement disorders ; surface electromyography ; forearm amputee ; hand posture ; visual feedback training ; pattern recognition ; artificial neural network ; hand gesture recognition ; electromyography ; inertial measurement unit ; reinforcement learning ; deep Q-network ; extreme learning machine ; force myography ; grasshopper optimization algorithm ; k-tournament selection ; frequency emphasis ; ensemble learning ; sign language recognition ; gloss prediction ; transformer ; pose-based approach ; pose estimation ; emotion judgment system ; adaptive interactive game ; set of optimal signal features ; sensor ; MARG ; MIMU ; orientation estimation ; sensor fusion algorithm ; dataset ; orientation algorithm benchmarking ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 149
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint includes 14 articles in Biomedical Data Science in honor of Professor Philip Bourne. Contributed by world-renowned experts, these articles cover a broad range of topics in machine learning, biophysics, bioinformatics, and systems biology.
    Keywords: structure-based drug discovery ; ligand binding sites ; deep learning ; graph neural network ; CRISPR/Cas9 ; genome editing ; machine learning ; SHAP values ; binding energy ; off-targets ; drug discovery ; retrosynthesis ; reaction template ; recurrent neural network ; and graph neural network ; mutational signatures ; smoking ; lung cancers ; APOBEC ; immune response to smoking ; cell-type composition ; goblet cells ; ciliated cells ; basal cells ; Protein Data Bank ; Open Access ; Worldwide Protein Data Bank ; macromolecular crystallography ; cryogenic electron microscopy ; cryogenic electron tomography ; electron crystallography ; micro-electron diffraction ; nuclear magnetic resonance spectroscopy ; biological macromolecules ; proteins ; nucleic acids ; DNA ; RNA ; carbohydrates ; small-molecule ligands ; social determinants of health ; electronic health records ; real-world evidence ; census tract ; data science ; protein database ; search tool ; prioritization algorithm ; drug repositioning ; quantum machine learning ; quantum metric learning ; kernel method ; kernel classifiers ; structural bioinformatics ; function annotation ; specificity annotation ; MSA ; entropy ; variability ; amino acids ; Philip Bourne ; FAIR ; bioinformatics ; n/a ; protein kinases ; functional families ; KinFams ; KinBase classification ; large language models ; pharmacovigilance ; social media ; drugs of abuse ; DNA sequencing ; read classification ; metagenomics ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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  • 150
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-31
    Description: Non-invasive biomedical sensors for monitoring physiological parameters from the human body for potential future therapies and healthcare solutions. Today, a critical factor in providing a cost-effective healthcare system is improving patients' quality of life and mobility, which can be achieved by developing non-invasive sensor systems, which can then be deployed in point of care, used at home or integrated into wearable devices for long-term data collection. Another factor that plays an integral part in a cost-effective healthcare system is the signal processing of the data recorded with non-invasive biomedical sensors. In this book, we aimed to attract researchers who are interested in the application of signal processing methods to different biomedical signals, such as an electroencephalogram (EEG), electromyogram (EMG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response, pulse oximetry, photoplethysmogram (PPG), etc. We encouraged new signal processing methods or the use of existing signal processing methods for its novel application in physiological signals to help healthcare providers make better decisions.
    Keywords: movement intention ; brain–computer interface ; movement-related cortical potential ; neurorehabilitation ; phonocardiogram ; machine learning ; empirical mode decomposition ; feature extraction ; mel-frequency cepstral coefficients ; support vector machines ; computer aided diagnosis ; congenital heart disease ; statistical analysis ; convolutional neural network (CNN) ; long short-term memory (LSTM) ; emotion recognition ; EEG ; ECG ; GSR ; deep neural network ; physiological signals ; electroencephalography ; Brain-Computer Interface ; multiscale principal component analysis ; successive decomposition index ; motor imagery ; mental imagery ; classification ; hybrid brain-computer interface (BCI) ; home automation ; electroencephalogram (EEG) ; steady-state visually evoked potential (SSVEP) ; eye blink ; short-time Fourier transform (STFT) ; convolution neural network (CNN) ; human machine interface (HMI) ; rehabilitation ; wheelchair ; quadriplegia ; Raspberry Pi ; image gradient ; AMR voice ; Open-CV ; image processing ; acoustic ; startle ; reaction ; response ; reflex ; blink ; mobile ; sound ; stroke ; EMG ; brain-computer interface ; myoelectric control ; pattern recognition ; functional near-infrared spectroscopy ; z-score method ; channel selection ; region of interest ; channel of interest ; respiratory rate (RR) ; Electrocardiogram (ECG) ; ECG derived respiration (EDR) ; auscultation sites ; pulse plethysmograph ; biomedical signal processing ; feature selection and reduction ; discrete wavelet transform ; hypertension ; thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniques
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  • 151
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: Optical fiber communication industry has gained unprecedented opportunities and achieved rapid progress in recent years. However, with the increase of data transmission volume and the enhancement of transmission demand, the optical communication field still needs to be upgraded to better meet the challenges in the future development. Artificial intelligence technology in optical communication and optical network is still in its infancy, but the existing achievements show great application potential. In the future, with the further development of artificial intelligence technology, AI algorithms combining channel characteristics and physical properties will shine in optical communication. This reprint introduces some recent advances in optical fiber communication and optical network, and provides alternative directions for the development of the next generation optical fiber communication technology.
    Keywords: optical communication ; frame transmission ; synchronization word ; blind recognition ; Hough transform ; machine learning ; optical communications ; patent analysis ; network analysis ; technical analysis ; fiber nonlinearities ; deep learning (DL) ; artificial intelligence (AI) ; BPSK-VSB ; BPSK-SSB ; fiber transmission ; optical neural networks ; time lens ; fiber ; dispersion Fourier transform ; high-flux imaging ; classification ; cancer cell recognition ; photon time stretching (PTS) ; passive optical networks ; laser tuning time ; TWDM ; Dynamic Bandwidth Allocation ; optical access networks ; scheduling ; FSOC system ; omnidirectional communication ; miniaturization ; ASE noise ; ICC ; DWDM-FSO/PON optical fiber network ; hybrid OOK/M-ary DPPM-M-PAPM ; hybrid fiber FSO (HFFSO) link ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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  • 152
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint contains a series of articles and reviews that illustrate the state-of-the-art knowledge about Gamma Ray Bursts and provide deep insights on the challenges that will be faced in GRB physics in the next decade.
    Keywords: gamma rays bursts ; radiation mechanisms ; non-thermal ; quark matter ; up-down quark nuggets ; quark star crusts ; white dwarfs ; gamma ray bursts ; fireball model ; circularity problem ; standard candles ; calibration ; dark energy ; dark matter ; cosmography ; cosmological parameters ; Gamma-ray bursts ; massive stars ; supernova ; spectroscopy ; binary stars ; metallicity ; rotation rate ; gamma-ray bursts ; polarization ; jet structure ; instruments & methods ; GRB ; radio ; redshift evolution ; instrumentation—detectors ; gamma rays: general ; gamma-ray bursts: general ; gamma-ray burst ; gravitational wave ; neutron stars ; magnetosphere ; shock breakout ; SVOM (Space-based multiband astronomical Variable Objects Monitor) ; time-domain astronomy ; γ-ray burst ; multi-messenger astrophysics ; nano-satellites ; supernovae ; Ia ; cosmology ; Hubble ; tension ; ΛCDM ; evolution ; modified ; gravity ; theories ; prompt emission ; relativistic jets ; gamma–rays: bursts ; cosmology: early universe ; multi-messenger astrophysics: gravitational waves ; neutrinos ; instrumentation: X/gamma–ray astrophysics from space ; fundamental physics ; non-thermal processes ; Cherenkov telescopes ; very high energy ; IACTs ; clustering ; statistical analysis ; feature extraction ; machine learning ; gamma-ray burst: general ; relativistic processes ; magnetohydrodynamics ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics ; thema EDItEUR::P Mathematics and Science::PG Astronomy, space and time
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  • 153
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-08-12
    Description: Over the past few decades, modern information technology has made a significant impact on people’s daily lives worldwide. In the field of health care and prevention, there has been a progressing penetration of assistive health services such as personal health records, supporting apps for chronic diseases, or preventive cardiological monitoring. In 2020, the range of personal health services appeared to be almost unmanageable, accompanied by a multitude of different data formats and technical interfaces. The exchange of health-related data between different healthcare providers or platforms may therefore be difficult or even impossible. In addition, health professionals are increasingly confronted with medical data that were not acquired by themselves, but by an algorithmic “black box”. Even further, externally recorded data tend to be incompatible with the data models of classical healthcare information systems.From the individual’s perspective, digital services allow for the monitoring of their own health status. However, such services can also overwhelm their users, especially elderly people, with too many features or barely comprehensible information. It therefore seems highly relevant to examine whether such “always at hand” services exceed the digital literacy levels of average citizens.In this context, this reprint presents innovative, health-related applications or services emphasizing the role of user-centered information technology, with a special focus on one of the aforementioned aspects.
    Keywords: fever ; FeverApp ; ecological momentary assessment ; user behavior ; sociodemographic characteristics ; registry ; guidelines ; feasibility ; usability ; routine health information system ; health management information system ; health system performance ; machine learning ; digital health ; registry analysis ; ClinicalTrials.gov ; device regulation ; new information technology ; Technology Acceptance Model (TAM) ; institution ; institutionalism ; digital informatics ; human–computer interaction ; personal health informatics ; consumer health data ; consumer health information ; self-tracking ; quantified self ; mHealth apps ; telemonitoring ; telemedicine ; telecardiology ; cardiology ; wearable ; sensors ; consumer health devices ; cardiovascular disease ; heart failure ; atrial fibrillation ; mental health ; psychiatry ; psychiatric record ; psychiatric notes ; patient accessible electronic health record ; PAEHR ; open notes ; policies ; COVID-19 ; technology acceptance ; user survey ; wearable health monitor ; ECG patch ; personal electronic health records ; technology adoption ; endogenous motivations ; health information privacy concern ; mixed-methods ; ePA ; online review helpfulness ; signaling theory ; sentiment analysis ; physician rating websites ; consumer decision-making ; health information technology ; information exchange ; hospital ; market ; bic Book Industry Communication::M Medicine
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  • 154
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This book focuses on the tools and methods used for tackling the complexity of the different hydrological and hydrogeological set-ups, the hydrodynamic patterns, the site specifications, and the wide variability of internal and external factors and/or processes on the catchment-scale level that impose the need for combined integrated approaches of robust methods. This Special Issue aims to provide successful applications or new insights on the stand-alone or joint considerations of groundwater resources assessment and characterization methods and explore new state-of-the-art methodological concepts in light of a rapidly changing environment.
    Keywords: drought ; precipitation ; SPI ; groundwater salinization ; karst ; seawater intrusion ; Soil and Water Assessment Tool ; SEAWAT model ; irrigation management ; groundwater ; climate change ; sea level rise ; nitrate ; leachate ; modelling ; validation ; state scale ; integrated water resources management ; coastal agricultural basin ; groundwater nitrate pollution ; hydrochemistry ; hydrodynamics ; environmental isotopes ; Tirnavos basin ; groundwater recharge ; groundwater sustainability ; hydrology models ; Modder River ; sustainability index ; GALDIT ; monthly vulnerability ; seawater intrusion (SWI) ; vulnerability assessment ; effective weight ; densely populated area ; freshwater–saltwater interactions ; multilayer coastal aquifer ; hydro-geochemistry ; Tevere River delta ; Ostia Antica archaeological park ; drinking and irrigation water scarcity ; groundwater potential mapping ; machine learning ; remote sensing ; GIS ; karstic mountainous aquifers ; Morocco ; hydrogeological properties ; natural groundwater fluctuations ; semi-arid zones ; depleting groundwater resources ; Guadalupe Valley Aquifer ; chromium ; ultramafic rocks ; springs ; water–rock interaction ; natural background levels ; aquifer ; intrinsic vulnerability ; RIVA method ; index-overlay method ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 155
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This book reprints articles from the Special Issue "Advances in Computer-Aided Technology" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of thirteen published articles. This Special Issue belongs to the "Mechatronic and Intelligent Machines" section. Industry 4.0 is characterized by the integration of advanced technologies, such as artificial intelligence, the Internet of Things, and cloud computing, into traditional manufacturing and production processes. CAx (Computer-Aided Systems) systems are a set of computer software tools used in engineering and product design, covering various stages of the product development cycle. Advanced CAx tools combine many different aspects of product lifecycle management (PLM), including design, finite element analysis (FEA), manufacturing, production planning and product. In connection with the transition to Industry 4.0 concepts, the concept of the digital twin comes to the fore, and existing CAx systems must adapt to this trend. The Special Issue deals with a number of research areas, such as: - New trends in CAx systems; Digital manufacturing; Internet of Things in manufacturing; Simulation of production systems and processes; Systems for advanced finite element analysis; Material engineering; Digitization and 3D scanning.
    Keywords: tensor glyph ; golden section ; vector space ; sandwich ; springback ; Vegter yield criterion ; numerical simulation ; PAM-STAMP 2G ; isotropic hardening law ; kinematic hardening law ; bending ; Bauschinger effect ; machine learning ; artificial neural network ; additive manufacturing ; high precision metrology ; CAD ; predictive model ; ship hull structure ; computer-aided design of structure ; database ; function soft block ; gun drill tool ; deep-drilling technology ; optimization ; tool life ; angle ; digital implant impression ; interimplant distance ; intraoral scanner ; trueness ; sewing machine ; needle bar ; floating needle ; electromagnet ; electromagnetic simulation ; noise reduction ; cycloidal gearbox ; friction ; actuator ; servomotor ; permanent magnet synchronous machine ; fixture design ; machining ; sustainable manufacturing ; process innovation ; complex-shape part ; signal processing ; monitoring system ; laser profiler ; surface roughness ; quality assessment ; non-contact method ; vision-based method ; frequency analysis ; abrasive water jet ; wood plastic composite ; natural reinforcement ; knitting machine ; stroke ; drive ; simulation ; cylinder ; dynamic modeling ; load spectrum reconstruction ; fatigue test ; hydraulic excavator ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 156
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The number of patient health data has been estimated to have reached 2314 exabytes by 2020. Traditional data analysis techniques are unsuitable to extract useful information from such a vast quantity of data. Thus, intelligent data analysis methods combining human expertise and computational models for accurate and in-depth data analysis are necessary. The technological revolution and medical advances made by combining vast quantities of available data, cloud computing services, and AI-based solutions can provide expert insight and analysis on a mass scale and at a relatively low cost. Computational intelligence (CI) methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods, have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. CI-based systems can learn from data and evolve according to changes in the environments by taking into account the uncertainty characterizing health data, including omics data, clinical data, sensor, and imaging data. The use of CI in healthcare can improve the processing of such data to develop intelligent solutions for prevention, diagnosis, treatment, and follow-up, as well as for the analysis of administrative processes. The present Special Issue on computational intelligence for healthcare is intended to show the potential and the practical impacts of CI techniques in challenging healthcare applications.
    Keywords: sEMG ; deep learning ; neural networks ; gait phase ; classification ; everyday walking ; convolutional neural network ; CRISPR ; leukemia nucleus image ; segmentation ; soft covering rough set ; clustering ; machine learning algorithm ; soft computing ; multistage support vector machine model ; multiple imputation by chained equations ; SVM-based recursive feature elimination ; unipolar depression ; diabetic retinopathy (DR) ; pre-trained deep ConvNet ; uni-modal deep features ; multi-modal deep features ; transfer learning ; 1D pooling ; cross pooling ; IMU ; gait analysis ; long-term monitoring ; multi-unit ; multi-sensor ; time synchronization ; Internet of Medical Things ; body area network ; MIMU ; early detection ; sepsis ; evaluation metrics ; machine learning ; medical informatics ; feature extraction ; physionet challenge ; electrocardiogram ; Premature ventricular contraction ; sparse autoencoder ; unsupervised learning ; Softmax regression ; medical diagnosis ; artificial neural network ; e-health ; Tri-Fog Health System ; fault data elimination ; health status prediction ; health status detection ; health off ; diffusion tensor imaging ; ensemble learning ; decision support systems ; healthcare ; computational intelligence ; Alzheimer’s disease ; fuzzy inference systems ; genetic algorithms ; next-generation sequencing ; ovarian cancer ; interpretable models ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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  • 157
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Mangrove forests are in constant flux due to both natural and anthropogenic forces. The changing mangroves will have significant consequences to coastal communities. Observation and monitoring of the distribution and dynamics of mangroves is central to a wide range of scientific investigations conducted in both terrestrial and marine ecosystems. Recent advancements in remote sensing data availability, image-processing methodologies, computing and information technology, and human resource development have provided an opportunity to observe and monitor mangroves from local to global scales on a regular basis. The spectral, spatial, and temporal resolution of remote sensing data and their availability have improved, making it possible to observe and monitor mangroves with unprecedented spatial thematic and temporal details. This journal Remote Sensing Special Issue reprint dedicated to the observation and monitoring of mangroves using remote sensing from local to global scales. The Issue broadly covers the application of remote sensing using optical (multi-spectral and hyperspectral), radar, and Lidar data obtained from multiple platforms including ground, air, and space. The research papers published use the latest techniques to acquire, manage, exploit, process, and analyze a wide variety of remote sensing data for mangrove forest applications. Both research papers and innovative review papers are included.
    Keywords: mangrove ; natural recovery ; artificial neural network ; Sentinel-2 ; transfer learning ; change detection ; coastal region ; remote sensing ; fragmentation ; productivity ; land cover change ; mangrove ecosystem ; random forest (RF) ; Google Earth Engine (GEE) ; Sentinel ; synthetic aperture radar (SAR) ; optical ; aerial roots ; global sensitivity analysis ; PAWN ; canopy reflectance model ; vegetation index (VI) ; mangroves ; Landsat ; mangrove forests ; time series ; Google Earth Engine ; random forests ; phenology ; TIMESAT ; climate ; monitoring ; Great Barrier Reef ; Hainan Island ; CLUE-S ; spatio-temporal simulation ; future change trends ; mangrove species ; spectrometer ; spectral reflectance ; WorldView-2 ; dendrogram ; extent ; mapping ; sentinel-2 ; global mangrove watch ; remote sensing-based monitoring ; plantation ; restoration ; dieback ; Bay of Bengal ; Red River Delta ; Vietnam ; vegetation index ; mangrove index ; mangrove forest ; mangrove above ground ; biomass ; carbon sink ; bibliometric analysis ; Sembilang National Park (Indonesia) ; machine learning ; satellites images ; geoprocessing ; rehabilitation program of mangroves ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry
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  • 158
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This overview of the most recent advances in the field of SMA research and applications in civil engineering aims to help remove the knowledge barriers across disciplines and sheds considerable light on the opportunity to commercialize SMA products in the construction industry.
    Keywords: seismic analysis ; rocking pier ; shape memory alloy ; ECC material ; bridge engineering ; television transmission tower ; seismic excitation ; shape memory alloy damper ; parametric study ; vibration control ; shape memory alloys ; engineered cementitious composites ; composites materials ; self-recovery capacity ; bending behavior ; machine learning ; artificial neural networks ; superelastic ; parameter identification ; constitutive model ; thermodynamic parameters ; shape memory alloy (SMA) ; self-centering SMA brace ; loading rate ; initial strain ; energy dissipation coefficient ; self-centering ; beam-column joints ; seismic performance ; iron-based shape memory alloy (Fe-SMA) ; shape memory effect ; martensitic transformation ; prestressing ; low cycle fatigue ; seismic ; damping ; transmission tower ; wind excitation ; SMA damper ; energy response ; viscoelastic ; brace ; hybrid control ; seismic resilience ; self-centering rocking (SCR) piers ; seismic fragility ; resilience ; life-cycle loss ; ferrous shape memory alloys ; prestress ; recovery stress ; relaxation ; thermomechanical behavior ; fatigue ; active materials ; low-cost SMAs ; civil engineering applications ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 159
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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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  • 160
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-11-17
    Description: The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields.
    Keywords: readmission prediction ; intensive care unit (ICU) ; recurrent neural network (RNN) ; longshort-term memory (LSTM) ; machine learning (ML) ; time series analysis ; health forecasting ; spectrum ; utilization ; prediction ; time-series ; clustering ; K-Means ; LSTM ; CNN ; outlier detection ; outlier detection in time series ; time series clustering ; time series cluster evaluation ; time series ; anomaly detection ; predictive maintenance ; model evaluation ; error diagnosis ; convolutional neural network ; all sky images ; cloud-base height ; machinelearning ; : financial market volatility ; VAR-DCC-GARCH ; wavelet-based random forest ; forecasting ; synthetic data ; shareable data ; privacy ; cross-correlation ; DCCA method ; oil derivatives ; energy ; accessibility ; retainability ; Markov chain ; K-mean clustering ; mobile data traffic ; multivariate prediction ; temporal ; spatial ; COVID-19 ; time series forecasting ; NARNN ; ARIMA ; dynamic convergence ; stationarity ; unit root ; ecosystem respiration ; dynamic mode decomposition with control ; time delay embedding ; ordinal patterns ; structural breaks ; non-stationary time series ; hydrological data ; prediction intervals ; seq2seq ; oil production ;  automated machine learning ; machine learning ; time-series forecasting ;  PV systems ; faults ; diagnosis ; signal processing ; time series data ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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  • 161
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This book is a collection of feature articles published in Risks in 2020. They were all written by experts in their respective fields. In these articles, they all develop and present new aspects and insights that can help us to understand and cope with the different and ever-changing aspects of risks. In some of the feature articles the probabilistic risk modeling is the central focus, whereas impact and innovation, in the context of financial economics and actuarial science, is somewhat retained and left for future research. In other articles it is the other way around. Ideas and perceptions in financial markets are the driving force of the research but they do not necessarily rely on innovation in the underlying risk models. Together, they are state-of-the-art, expert-led, up-to-date contributions, demonstrating what Risks is and what Risks has to offer: articles that focus on the central aspects of insurance and financial risk management, that detail progress and paths of further development in understanding and dealing with...risks. Asking the same type of questions (which risk allocation and mitigation should be provided, and why?) creates value from three different perspectives: the normative perspective of market regulator; the existential perspective of the financial institution; the phenomenological perspective of the individual consumer or policy holder.
    Keywords: medical services’ consumption ; lifestyle factors ; insurance plan ; structural equation model ; stock–bond correlation ; VIX ; economic policy uncertainty ; monetary policy uncertainty ; fiscal policy uncertainty ; agricultural commodity futures ; price discovery ; market reflexivity ; Hawkes process ; poisson autoregressive models ; contagion ; predictive monitoring ; information-based asset pricing ; Lévy processes ; gamma processes ; variance gamma processes ; Brownian bridges ; gamma bridges ; nonlinear filtering ; house price prediction ; real estate ; machine learning ; random forest ; Lévy process ; subordination ; option pricing ; risk sensitivity ; stochastic volatility ; Greeks ; time-change ; time series ; volatility ; probability-integral transform ; ARMA model ; copula
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  • 162
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-01
    Description: People with congenital and/or acquired disabilities constitute a great number of dependents today. Robotic platforms to help people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance to improve their quality of life. A high demand for robotic platforms that provide assistance during rehabilitation is expected because of the health status of the world due to the COVID-19 pandemic. The pandemic has resulted in countries facing major challenges to ensure the health and autonomy of their disabled population. Robotic platforms are necessary to ensure assistance and rehabilitation for disabled people in the current global situation. The capacity of robotic platforms in this area must be continuously improved to benefit the healthcare sector in terms of chronic disease prevention, assistance, and autonomy. For this reason, research about human–robot interaction in these robotic assistance environments must grow and advance because this topic demands sensitive and intelligent robotic platforms that are equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms. This Special Issue has published eight papers covering recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. The papers address innovative solutions in this field, including affordable assistive robotics devices, new techniques in computer vision for intelligent and safe human–robot interaction, and advances in mobile manipulators for assistive tasks.
    Keywords: sensors ; electronic platform ; machine learning ; wearables ; hand motor rehabilitation ; sEMG ; hand pose ; social robot ; physical human-robot interaction ; assistive robotics ; collaborative robots ; brain–machine interfaces ; EEG ; exoskeleton ; motor imagery ; human–robot interaction ; human pose estimation ; robotic rehabilitation ; visually impaired assistance ; navigation system ; knowledge graph ; dialogue system ; NLP ; reasoning ; multimodal interfaces ; robotic exoskeleton ; 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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  • 163
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Our era is characterized by two major phenomena. On the one hand, we are confronted by climate and environmental crises constituted by, among others, changing weather patterns, loss of biodiversity and natural wildlife, and ecosystem degradation. On the other hand, we are experiencing an ongoing technological evolution culminating in the rise of artificial intelligence (AI). The popular notion of “AI for Sustainability” constitutes an attempt to connect these two phenomena in a beneficial way by using AI to alleviate climate and environmental worries. AI is increasingly being used in the analysis, mitigation, and prevention of the climate and environmental crises and their effects. Much less attention has been paid to the idea of the “Sustainability of AI”, which focusses on the materiality of AI technologies themselves. Indeed, what are the hidden costs of AI? Although we use AI in combatting the climate and environmental crises, does it not have its own contributions to these crises? And, if so, how do we account for these contributions? The Special Issue is the first attempt to address the topic of “Sustainable AI” from a multi-disciplinary perspective. The authors that contributed to this issue come from diverse fields such as philosophy, ethics, sociology, law, and engineering. The included papers represent the first steps in understanding what it means to tackle the climate and environmental crises with AI while refraining from aggravating these crises.
    Keywords: artificial intelligence ; Sustainable Development Goals ; ESG ; CSR ; reporting ; disclosure ; sustainability ; sustainable AI ; greenwashing ; unfair commercial practices ; AI Act ; digitalization ; sustainable digitalization ; sustainable development ; SDGs ; Assessment Framework ; mindful ; digital age ; digitainability ; digital technologies ; qualitative research ; environmental impact ; carboncentric ; technocentric ; surrogate-based optimisation ; surrogate model ; sequential model-based optimisation ; Bayesian optimisation ; Green AI ; machine learning ; intergenerational justice ; future generations ; policy-making ; explainability ; transparency ; AI ; AI governance ; ethics ; ethical AI ; differential privacy ; AI certification ; ethics of AI ; AI ethics ; checklist ethics ; ethics of carefulness ; ethics of desirability ; climate justice ; infrastructure ; climate change ; nudging ; digital nudging ; libertarian paternalism ; autonomy ; carbon footprint ; LCA ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 164
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint covers the following topics in the field of smart grids: 1. Optimal dg location and sizing to minimize losses and improve the voltage profile using garra rufa optimization. 2. Solar and wind energy forecasting for the green and intelligent migration of traditional energy sources. 3. Optimized micro-grid’s operation with electrical-vehicle-based hybridized sustainable algorithm. 4. The detection of nontechnical losses in smart meters using a MLP-GRU deep model and augmenting data via theft attacks. 5. A hybrid deep-learning-based model for the detection of electricity losses using big data in power systems. 6. Load frequency control and automatic voltage regulation in a multi-area interconnected power system using nature-inspired computation-based control methodology. 7. Line overload alleviations in wind energy integrated power systems using automatic generation control. 8. Electric price and load forecasting using a CNN-based ensembler in a smart grid. 9. Day-ahead energy forecasting in a smart grid considering the demand response and microgrids. 10. A dragonfly optimization algorithm for extracting the maximum power of grid-interfaced pv systems. 11. An economic load dispatch problem with multiple fuels and valve point effects using a hybrid genetic–artificial fish swarm algorithm. 12. Incentive-based dynamic pricing in a smart grid.
    Keywords: demand side management ; demand response ; load scheduling ; real time pricing ; genetic algorithm ; dynamic incentives ; artificial fish swarm algorithm ; economic load dispatch ; hybrid genetic–artificial fish swarm algorithm ; multi-objective optimization ; sustainable power generating system ; photovoltaic (PV) ; partial shading ; maximum power point tracking (MPPT) ; dragonfly optimization algorithm (DOA) ; adaptive cuckoo search optimization (ACSO) ; fruit fly optimization algorithm combined with general regression neural network (FFO-GRNN) ; improved particle swarm optimization (IPSO) ; voltage source inverter (VSI) ; total harmonic distortion (THD) ; energy optimization ; day ahead energy prediction ; artificial neural network ; renewable energy sources ; microgrid ; smart grid ; electricity price forecasting ; energy management ; electricity load forecasting ; convolutional neural network ; corona virus herd immunity optimization ; sustainable cities ; requirement-gathering tool ; qualitative comparison ; requirement engineering ; software engineering ; requirement-management tools ; automatic generation control ; wind energy ; transmission line security ; dispatch strategies ; Pakistan power system ; PI-PD controller ; load frequency control ; automatic voltage regulator ; nature-inspired optimization ; multi-area interconnected power system ; class imbalance ; gated recurrent units ; electricity theft detection ; non-technical losses ; smart grids ; deep learning ; GRU ; healthcare ; MLP ; PRECON ; smart cities ; smart meters ; sustainable society ; electric vehicles ; flexible load ; optimization ; renewable energy ; forecasting ; machine learning ; energy efficiency ; sustainability ; low carbon emission ; distribution generation ; Garra Rufa ptimization ; PSO ; GA ; power system ; urban sustainability ; local growth ; regional cities ; cultural heritage ; real estate ; intelligent regions ; innovation systems ; circular economy ; regional policies ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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  • 165
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: As the scaling of electronic semiconductor devices displays signs of saturation, the main focus of research in microelectronics is shifting towards finding new computing paradigms. Electron spin offers additional functionality to digital charge-based devices. Several fundamental problems, including spin injection to a semiconductor, spin propagation and relaxation, and spin manipulation by the gate voltage, have been successfully resolved to open a path towards spin-based reprogrammable electron switches. Devices employing electron spin are nonvolatile; they are able to preserve the stored information without external power. Emerging nonvolatile devices are electrically addressable, possess a simple structure, and offer endurance and speed superior to flash memory. Having nonvolatile memory very close to CMOS offers a prospect of data processing in the nonvolatile segment, where the same devices are used to store and process the information. This opens perspectives for conceptually new low-power computing paradigms within Artificial Intelligence of Things (AIoT). This Special Issue focuses on all topics related to spintronic devices such as spin-based switches, magnetoresistive memories, energy harvesting devices, and sensors that can be employed in in-memory computing concepts and in Artificial Intelligence.
    Keywords: magnetic contacts ; reliability ; practical tests ; reaction distance ; extreme conditions ; spin-orbit torque MRAM ; reinforcement learning ; two-pulse switching scheme ; magnetic field-free switching ; machine learning ; torque ; the calculation in memory ; automation ; magnetic recording ; magnetic read heads ; current perpendicular-to-the-plane giant magnetoresistance ; Heusler alloys ; bit-patterned media ; exchange-coupled-composite media ; microwave-assisted magnetic recording ; hysteresis loop ; combined spin-transfer torque (STT) and spin-orbit torque (SOT) switching ; field like torque ; damping like torque ; magnetic tunnel junction ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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  • 166
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    Frontiers Media SA
    Publication Date: 2024-04-04
    Description: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
    Keywords: machine learning ; ecological interactions ; environmental DNA (eDNA) ; ecological networks ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAF Ecological science, the Biosphere
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  • 167
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This book compiles a set of original and innovative papers included in the Special Issue on UAVs for vegetation monitoring, which proves the wide scope of UAVs in very diverse vegetation applications, both in agricultural and forestry scenarios, ranging from the characterization of relevant vegetation features to the detection of plant or crop stressors. New methods and techniques are developed and applied to diverse vegetation scenarios to meet the main challenge of sustainability.
    Keywords: UAS ; UAV ; vegetation cover ; multispectral ; land cover ; forest ; Acacia ; Indonesia ; tropics ; vegetation ground cover ; vegetation indices ; agro-environmental measures ; olive groves ; southern Spain ; sUAS ; water stress ; ornamental ; container-grown ; artificial intelligence ; machine learning ; deep learning ; neural network ; visual recognition ; precision agriculture ; canopy cover ; image analysis ; crop mapping ; evapotranspiration (ET) ; GRAPEX ; remote sensing ; Two Source Energy Balance model (TSEB) ; contextual spatial domain/resolution ; data aggregation ; eddy covariance (EC) ; Fusarium wilt ; crop disease ; banana ; multispectral remote sensing ; purple rapeseed leaves ; unmanned aerial vehicle ; U-Net ; plant segmentation ; nitrogen stress ; Glycine max ; RGB ; canopy height ; close remote sensing ; growth model ; curve fitting ; NDVI ; solar zenith angle ; flight altitude ; time of day ; operating parameters ; CNN ; Faster RCNN ; SSD ; Inception v2 ; patch-based CNN ; MobileNet v2 ; detection performance ; inference time ; disease detection ; cotton root rot ; plant-level ; single-plant ; plant-by-plant ; classification ; UAV remote sensing ; crop monitoring ; RGB imagery ; multispectral imagery ; century-old biochar ; semantic segmentation ; random forest ; crop canopy ; multispectral image ; chlorophyll content ; remote sensing technique ; individual plant segmentation ; plant detection ; transfer learning ; maize tassel ; tassel branch number ; convolution neural network ; VGG16 ; plant nitrogen estimation ; vegetation index ; image segmentation ; transpiration ; method comparison ; oil palm ; multiple linear regression ; support vector machine ; artificial neural network ; UAV hyperspectral ; wheat yellow rust ; disease monitoring ; texture ; spatial resolution ; RGB camera ; thermal camera ; drought tolerance ; forage grass ; HSV ; CIELab ; broad-sense heritability ; phenotyping gap ; high throughput field phenotyping ; UAV digital images ; winter wheat biomass ; multiscale textures ; red-edge spectra ; least squares support vector machine ; variable importance ; drone ; hyperspectral ; thermal ; nutrient deficiency ; weed detection ; disease diagnosis ; plant trails ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 168
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: Biomedical sensors stand at the forefront of modern medical technologies, serving as indispensable components in diverse instruments and equipment. These sensors unravel the intricacies of biological processes and medical interventions. The recent surge in high-density sensor systems, characterized by arrangements in matrix arrays and other configurations, has ushered in a new era of functional evaluation. This spans electrophysiological activity, the metabolic responses of organs and tissues, and motor control analysis, all enriched with crucial spatial information. Functional mapping, a burgeoning approach in various biomedical techniques such as EEG, EMG, ECG, NIRS, and MEG, is proving to be transformative. Its integration enhances our comprehension of complex biological behaviors, where the precise spatial localization of sensing methodologies becomes paramount. The applications of functional mapping using biomedical sensors extend across multiple fields, including neuroscience, neuromuscular physiology, rehabilitation, and cardiology. Its utility ranges from diagnostic purposes to assessing the effectiveness of therapeutic interventions. The primary objective of this reprint was to collect papers that delineate the forefront of techniques, methods, and applications in the realm of biomedical sensors. Additionally, the focus extends to specific algorithms for data processing, ensuring a robust understanding of functional information intricately associated with spatial localization.
    Keywords: EMG ; EEG ; rehabilitation ; neuromotor ; evaluation ; assessment ; review ; machine learning ; biofeedback ; transfer learning ; random forest classifier ; COVID-19 ; intubation ; tracheoesophageal fistula ; tracheal lesions ; acute respiratory distress syndrome ; modeling ; intensive care unit ; muscle synergies ; whole body FES ; neurological patients ; photodynamic therapy ; fluorescence ; laser ; fluorophores ; enamel ; effective connectivity ; kurtosis ; resting-state connectivity ; stationarity ; sleep monitoring ; pressure bed sensor (PBS) ; unobtrusive measure ; multi-scale analysis ; sleep apnea–hypopnea syndrome (SAHS) ; shift-working ; optically detected magnetic resonance ; quantum magnetometer ; magnetoencephalography ; time domain ; functional near infrared spectroscopy ; diffuse optics ; brain ; hemodynamics ; resting-state brain oscillation ; mental workload ; signal processing ; reliability ; cognitive performance ; Simon task ; emotion detection ; valence ; arousal ; wearable sensors ; regression ; classification ; technology acceptance model ; rehabilitation exoskeletons ; therapists ; neuro-rehabilitation ; multiple linear regression ; Pearson’s correlation ; integrated sensor systems ; hand function ; hand osteoarthritis ; electromyography ; diagnosis ; discriminant analysis ; photoplethysmogram ; microcirculation ; deep learning ; convolutional neural network ; modelling ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 169
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Floods are one of the most common natural hazards that substantially affect human lives and properties globally. Engineering is of key importance to cope with flood risk as it provides integrated solutions associated with hydrological–hydraulic and coastal-advanced techniques for analysing flooding risk, for designing flood infrastructures for direct protection, for providing natural retention measures that enhance environmental and river restoration, for developing flood warning systems, and for presenting integrated construction and non-construction measures in order to adapt to emerging climatic challenges and develop resilience under the modern city environment.This Special Issue highlights the current efforts being made to advance the science and applications in flood engineering and, more specifically, in a wide spectrum of its related geosciences, such as hydrology, hydraulics, sedimentation, and river restoration.
    Keywords: ombrian curves ; intensity–duration–frequency curves ; rainfall extremes ; regionalization ; regional frequency analysis ; spatial rainfall ; design rainfall ; IANOS ; medicane ; Karditsa ; HEC-HMS ; HEC-RAS ; remote sensing ; SENTINEL ; machine learning ; sewer model ; LSTM neural network ; urban sewer flooding ; flood exposure ; geospatial analysis ; open-access data ; infrastructure ; forensic hydrology ; flood modeling ; open dataset ; MIKE FLOOD ; Eastern Uganda ; flood plains ; flood hazard maps ; return period ; SWAT ; dams ; numerical simulations ; physical modeling ; water management ; wetlands ; nature-based solutions ; flood mitigation ; coastal flooding ; tidal watersheds ; compound flooding ; D-vine copula ; trivariate joint analysis ; Bernstein estimator ; beta kernel estimator ; parametric copulas ; kernel density estimation ; return periods ; extreme rainfall ; default urban fraction ; Kampala ; urban parameter ; updated urban fraction ; WRF model ; ensemble empirical mode decomposition (EEMD) ; flood period ; tidal river ; water level forecasting ; hydraulic simulation ; flood maps ; digital elevation model ; random forests ; UAV mapping ; DEM sensitivity ; DEM errors ; flood extent ; flood risk assessment ; numerical modelling ; storm surge ; sea level elevation ; inundation maps ; Manning coefficient ; raster grid ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 170
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The present reprint contains 33 articles accepted and published in the Special Issue entitled “Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics, 2022” in the MDPI journal, Mathematics, which covers a wide range of topics connected to the theory and applications of feature representation learning for image processing, artificial intelligence, data mining and robotics. These topics include, among others, elements from image blurring, image aesthetic quality assessment, pedestrian detection, visual tracking, vehicle re-identification, face recognition, 3D reconstruction, the stability of switched systems, domain adaption, deep reinforcement, sentiment analysis, graph convolutional networks, knowledge graphs, geometric metric learning, etc. It is hoped that this reprint will be interesting and useful for those working in the area of image processing, computer vision, machine learning, natural language processing and robotics, as well as for those with backgrounds in machine learning who are willing to become familiar with recent advancements in artificial intelligence, which, today, is present in almost all aspects of human life and activities.
    Keywords: head detection ; YoloV4 ; NMS ; soft-NMS ; people counting ; vehicle re-identification ; license plate recognition ; video surveillance ; feature extraction ; pedestrian detection ; machine learning ; end-to-end ; anchor-free ; feature reuse ; correlation filters ; second-order fitting ; visual tracking ; DCNN-BiLSTM ; domain adaptation ; MMD ; fine-tuning ; C-MAPSS ; cross-working ; small sample ; blind image deblurring ; image prior ; sparse channel ; sparsity ; multi-output ; kNN ; metric learning ; cost-weighted ; geometric mean metric ; motion deblurring ; image super-resolution ; multi-order attention ; gated learning ; decoupling ; face recognition ; second-order gradient ; image gradient orientations ; collaborative-representation-based classification ; image aesthetic assessment ; semi-supervised learning ; label propagation ; deep learning ; computer vision ; garbage quantity identification ; YOLOX ; Soft-NMS ; stability ; switched system ; state-dependent switching ; time delay ; multi-source domain adaptation ; Dempster–Shafer evidence theory ; cross-domain classification ; 3D reconstruction ; multi-view stereo ; structure from motion ; background matting ; adversarial example ; feature transformation ; black-box attack ; ensemble attack ; deep neural network ; intelligent design ; data analysis ; models and algorithms ; extension theory ; scheme design ; adversarial learning ; adversarial equilibrium ; transferability quantification ; power load forecasting ; routing, modulation and spectrum assignment ; elastic optical networks ; deep reinforcement learning ; knowledge distillation ; aspect-based sentiment analysis ; graph neural networks ; dependency trees ; dependency types ; graph attention mechanism ; syntactic ; semantic ; vehicle color recognition ; low–high level joint task ; object detection ; joint semantic learning ; rainy image recovery ; XSS attack ; traffic detection ; payloads ; fusion verification ; hypergraph matching ; similarity metric ; information-theoretic metric learning ; mixed noise removal ; matrix nuclear norm ; logarithm norm ; ADMM ; plug-and-play ; aspect-level sentiment classification ; external knowledge ; KGE ; GCN ; discriminative feature learning ; multidimensional scaling ; fuzzy k-means ; pairwise constraint propagation ; iterative majorization algorithm ; Aspect Level Sentiment Classification ; Contrasitve Learning ; Graph Convolutional Networks ; graph convolutional networks ; commonsense knowledge graph ; anomaly detection ; cyber–physical ; industrial control systems ; image classification ; large-margin technique ; robustness ; anti-noise performance ; cross-domain sentiment classification ; word embedding ; GAT ; hate speech detection ; contrastive learning ; multi-task learning ; attention mechanism ; state reconstruction ; gait adjustment ; uncertain temporal knowledge graph ; temporal knowledge graph ; knowledge graph embedding ; confidence score ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    Frontiers Media SA
    Publication Date: 2024-04-04
    Description: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
    Keywords: FinTech ; SupTech ; RegTech ; AI ; machine learning ; P2P lending ; Blockchain ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Catalytic oxidation or reduction processes are among the most efficient processes for water and wastewater treatment. These include photocatalysis, sulfate and hydroxyl-radical-based advanced oxidation processes.This Special Issue contains the contributions of different research groups and discusses the recent progress and advances in catalytic processes in water and wastewater treatment.
    Keywords: photocatalytic degradation ; graphene quantum dots ; nanocomposites ; free radical generation ; post-processing modification ; surface-engineered biochar ; dye removal ; machine learning ; artificial neural network ; photocatalysis ; sodium persulfate ; antibiotics ; water treatment ; hybrid system ; water matrix ; MTBE ; arsenic ; Fe2O3/MgO catalyst ; AOP ; modeling ; optimization ; Auramine O ; basic dye ; titania nanoparticle ; mechanism ; CuS nanostructures ; heterojunctions ; organic pollutants ; wastewater treatment ; water purification ; ZnO nanostructures ; hydrothermal synthesis ; seedless ; building materials ; synthetic dyes ; anionic–anionic co-doping ; BaTiO3 ; Heyd–Scuseria–Ernzerhof (HSE06) ; photocatalytic water splitting ; TiO2 ; photocatalysts ; photodegradation ; methylene blue ; methyl green ; g-C3N4 ; pharmaceuticals ; amisulpride ; reactive species ; transformation products ; ecotoxicity ; biochar ; sulfamethoxazole ; persulfate ; electron transfer ; psychiatric drugs ; hospital wastewaters ; solar photocatalysis ; 1MoS2/g-C3N4 ; CNTs ; Ag2S ; cadmium ; adsorption ; alizarin yellow R ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PN Chemistry
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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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    Frontiers Media SA
    Publication Date: 2024-04-04
    Description: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
    Keywords: GWAS—genome-wide association study ; machine learning ; complex diseases ; gene-gene interaction ; epistasis ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFN Medical genetics
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  • 175
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-07-14
    Description: The book is the reprint of the Special Issue 'Advances in Sustainable and Digitalized Factories: Manufacturing, Measuring Technologies and Systems' published in the journal Applied Science (MDPI). It contains 17 articles, including 1 Editorial, 14 Research Papers, and 2 Reviews.
    Keywords: Industry 4.0 ; continuous improvement ; lean manufacturing ; lean production systems ; lean 4.0 ; systematic literature review ; tiny RFID ; metallic electromagnetic isolation ; analog manometer ; Ansys HFSS simulator ; passive digitization ; ontology ; production simulation ; multi-agent ; digital twin ; augmented reality ; industry 4.0 ; quality 4.0 ; metrology ; assembly ; turbine blades ; re-manufacturing ; uncertainty ; robust scheduling ; case-based reasoning ; failure mode ; effect and criticality analysis ; knowledge-based system ; nearest neighbor ; reliability-centered maintenance ; virtual reality ; cyber physical system ; OPC UA ; CAD ; industrial IoT ; prototyping ; retrofitting solutions ; embedded solutions ; low-cost ; value chain ; additive manufacturing ; subtractive manufacturing ; cost comparison ; plant simulation ; technology comparison ; hybrid dependability modelling ; production scheduling ; dynamic failure rate ; discrete event simulation ; time-driven simulation ; machine learning ; manufacturing ; artificial intelligence ; smart manufacturing ; digitization ; smart surface ; friction force field ; under-actuation ; feeding ; simulation ; material flow handling ; intralogistics ; robotic bin-picking ; simulation model ; ADAMS ; pick-point determination ; MATLAB/Simulink ; 2-F robotic gripper ; performance analysis ; plastic injection molding ; design of experiments ; process optimization ; facility layout problem ; evolutionary algorithms ; numerical modeling ; multi-objective optimization ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-14
    Description: Cyber security providers are facing a continuous stream of new, sophisticated cyberattacks on cyber critical infrastructures worldwide. These cyberattacks are often triggered by malware and ransomware. This book presents a collection of selected papers addressing malware detection, which is necessary to create reliable and resilient cyber and computer security mechanisms.
    Keywords: machine learning ; artificial intelligence ; big data ; privacy ; crime ; bifurcation ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTC Cloud computing
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-10-25
    Description: Over the last few years, the subject of food authenticity and food fraud has received increasing attention from consumers and other stakeholders, such as government agencies and policymakers, control labs, producers, industry, and the research community. Among the different approaches aiming to identify, tackle, and/or deter fraudulent practices in the agri-food sector, the development of new, fast, and accurate methodologies to evaluate food authenticity is of major importance. This book, entitled “Target and Non-Target Approaches for Food Authenticity and Traceability”, gathers original research and review papers focusing on the development and application of both targeted and non-targeted methodologies applied to verify food authenticity and traceability. The contributions regard different foods, among which some are frequently considered as the most prone to adulteration, such as olive oil, honey, meat, and fish. This book is intended for readers aiming to enrich their knowledge through reading contemporary and multidisciplinary papers on the topic of food authentication.
    Keywords: COIBar–RFLP (cytochrome oxidase I barcode–restriction fragment length polymorphism) ; seafood ; fraud ; DNA barcoding ; food authenticity ; food adulteration ; food fraud ; donkey ; cytochrome b ; real-time PCR ; meat products ; honey ; regional origin ; chemometric analysis ; mineral content ; Montenegro ; Sepia ; common cuttlefish ; Sepia officinalis ; real-time PCR (Polymerase Chain Reaction) ; species identification ; food authentication ; COI (Cytochrome Oxidase I) ; Olea europaea var Sylvestris ; oleaster ; olive ; olive oil ; adulteration ; SNP ; DNA ; virgin olive oil ; quality ; volatile compounds ; sensory analysis ; chemometrics ; anti food fraud ; Curcuma longa ; DNA markers ; SYBR-GREEN real-time PCR ; Zea mays ; pasta ; Triticum aestivum ; Triticum durum ; genetic traceability ; digital PCR ; semolina ; species ; truffle ; Tuber spp. ; species differentiation ; near-infrared spectroscopy ; red deer ; roe deer ; water deer ; multiplex PCR ; capillary electrophoresis ; perilla ; sesame ; geographic origin ; metabolomics ; multivariate analysis ; metabolite profiling ; quantification ; chicken ; guinea fowl ; pheasant ; quail ; turkey ; authentication ; authenticity ; chemometric ; fish ; origin ; meat ; milk ; spectroscopy ; 1H-NMR ; GC-MS ; HPLC-UV/VIS ; protein hydrolysate ; free amino acid contents ; ProHydrAdd ; monofloral honey ; direct analysis in real time (DART) ; high resolution mass spectrometry (HRMS) ; geographical origin ; Ginkgo biloba ; plant infusions ; real-time polymerase chain reaction ; DNA extraction ; opium poppy ; seed ; pollen grains ; bakery product ; oil ; PCR ; Salmo salar L. ; fatty acids ; mislabeling ; machine learning ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Genomics technologies revolutionised biomedicine research, but the genome alone is not sufficient to capture biological complexity. Postgenomic methods, typically based on mass spectrometry, comprise the analysis of metabolites, lipids, and proteins and are an essential complement to genomics and transcriptomics. Multidimensional omics is becoming established to provide accurate and comprehensive state descriptions. This book covers the latest methodological developments for, and applications of integrative multi-omics in biomedical research.
    Keywords: target identification ; target validation ; label-free method for drugs ; anti-angiogenesis ; mechanism of action ; receptor tyrosine kinases ; curcumin ; natural products ; lipid ; lipidomics ; cardiac metaplasia ; Barrett’s esophagus ; esophageal adenocarcinoma ; microbiota ; DNA sensing ; IFI16 ; cGAS ; innate immunity ; protein interactions ; virus–host interactions ; post-translational modifications ; mass spectrometry ; proteomics ; transcriptomics ; multi-omics ; multi-omics analysis ; study design ; bioinformatics ; machine learning ; analysis flow ; metabolomics ; planned myocardial infarction (PMI) ; myocardial infarction (MI) ; exercise ; heart ; cheminformatics ; batch variations ; eicosanoids ; fetal calf serum ; peroxisomes ; host-pathogen interactions ; secretome ; macrophages ; acute myeloid leukemia ; HL-60 cell line ; ATRA ; induced differentiation ; transcriptome ; proteome ; transcription factors ; key molecules ; regulatory pathway modelling ; SRM ; endometriosis ; inflammation ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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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: This reprint was proposed and organized as a means to present recent developments in the field of testing of materials and elements in civil engineering. For this reason, the articles highlighted in this editorial relate to different aspects of this topic, from building materials to building structures. The current trend in the development of materials testing in civil engineering is mainly concerned with the detection of flaws and defects in elements and structures using destructive, semidestructive, and nondestructive testing.
    Keywords: timber structures ; estimating mechanical parameters ; small clear specimens ; non-destructive tests ; semi-destructive tests ; resistance drilling ; ultrasonic wave ; stress wave ; visual grading ; concrete ; NDT ; finite element method ; experiment ; automated inspection ; frequency domain ; validation ; sulfate attack ; physical and mechanical properties ; damage model ; microstructure ; external thermal insulation systems ; mechanical properties of bonds ; polyurethane adhesive ; timber frame building ; bond strength ; shear properties ; residual magnetic field ; Barkhausen noise ; LCR circuits ; plastic deformation ; austenitic steel ; steel fibre-reinforced concrete ; steel fibres ; waste sand properties ; reinforced beam ; shear cracking ; shear capacity ; non-destructive testing ; damage detection ; vibrations ; modal analysis ; continuous wavelet transform ; concrete beam ; strengthening ; adhesive joint ; debonding ; S355 steel ; uniaxial tensile test ; strength properties ; true stress-strain relationships ; confining pressure ; expansive clay ; fiber ; flexible wall permeameter ; hydraulic conductivity ; lime ; rigid wall permeameter ; concrete corrosion ; concrete protection ; steel corrosion ; concrete durability ; coating materials ; masonry structures ; autoclaved aerated concrete masonry units (AAC) ; compressive strength ; minor-destructive (MDT) techniques ; non-destructive (NDT) techniques ; ultrasonic testing ; acoustoelastic effect (AE) ; hydrostatic stresses ; modeling ; DIC technique ; ready-mixed concrete ; construction architecture material ; inter-laboratory comparisons (ILC) ; proficiency testing (PT) ; concrete quality assessment ; fracture mechanics ; ductile fracture ; material microstructure ; void growth ; FEM model ; material testing ; geodesic dome ; seismic response ; dynamic analysis ; seismic analysis ; high temperature ; fire temperature ; residual strength ; heat accumulation factor ; variational asymptotic method ; reduced-order plate model ; orthogrid-stiffened panel ; free-vibration analysis ; global buckling ; steel plates ; ultrasonic tomography ; base material ; rock ; post-installed anchors ; adhesive anchor ; mechanical anchor ; load-bearing capacity ; GSI ; RMR ; rebound value ; rebound hammer ; semi-flexible pavement ; fatigue resistance ; cracking mechanism ; fatigue prediction ; fracture surface ; cement–cellulose composites ; ventilated façade ; acoustic emission method ; frequencies of acoustic emission signals ; geosynthetic ; design ; pullout resistance ; effective length ; reinforced earth ; clay bricks ; cement lime mortar ; infill masonry wall ; destructive force ; self-stressed anti-washout concrete ; segment assembly ; undrained strengthening ; axial compression test ; mechanical properties ; CFRP grid ; PCM ; interface ; mechanical model ; pull-out test ; finite element analysis ; external walls ; thermal measurements ; R-value ; thermal resistance ; temperature-based method ; heat flow meter method ; infrared thermography method ; 3D textile composite ; equivalent model ; buckling analysis ; interlaboratory comparison (ILC) ; risk analysis ; measurements uncertainty (MU) ; ceramic tiles adhesive (CTA) ; assessment and verification of constancy of performance (AVCP) ; construction product ; market surveillance ; artificial weathering testing in civil engineering ; construction profiles ; natural fibre-reinforced polymer composites ; building performance assessment ; microstructure analysis ; stairs ; masonry ; clay brick ; arch ; vault ; management ; quality ; light detection and ranging (LiDAR) ; TLS ; low-temperature construction additive ; preparation method ; volumetric properties ; modification mechanism ; mixture performance ; bio-rejuvenated additive ; 100% rejuvenation ; reclaimed asphalt pavement ; regeneration mechanism ; pavement performance ; macro-strain mode ; medium- and small-span bridges ; wavelet transform ; cross-correlation function ; hygrothermal simulation ; capillary active internal insulation ; mould risk ; moisture effects ; subgrade ; static load test ; deformation modulus ; reliability ; fine-grain concrete ; bond ; industrial computed tomography ; numerical simulation ; xCT ; rectangular profile ; torsional stiffness ; stiffness increase ; research ; guided waves ; longitudinal wave ; discrete element method ; numerical modelling ; dispersion curves ; recycled aggregate concrete ; sustainable aggregate ; flexural strength ; gradient boosting ; random forest ; ventilated facades ; large-scale model ; fibre cement boards ; fire exposure ; Bayesian approach ; prestressing force ; saw-cut method ; assessment ; pre-tensioned members ; waste from enrichment of water-soluble ores ; artificially supported mining method ; backfill ; activation ; nanomodifier astralene ; ultimate compressive strength ; cement ; air-entraining admixture ; plasticizing ; porosity ; air-content ; strength ; freeze-thawing resistance ; storage systems ; looseness ; stiffness ; beam-end connection ; bending ; gap ; clearance ; plastic viscosity ; yield stress ; machine learning ; volcanic soil ; mechanical property ; strength index ; particle crushing ; road engineering ; pavement ; fatigue ; modules ; FEM ; light weight deflectometer ; solid fired brick ; defects in the internal structure ; resonant pulse method ; material durability ; drying of soil ; microwave heating ; soil structure ; computed microtomography ; water content ; buckling ; stability ; civil engineering ; slender bars ; columns ; numerical analysis ; variable cross-section ; waste glass ; recycling ; construction materials ; sustainable concrete ; steel fiber ; building material ; fibers ; mortar ; hybrid ; artificial neural networks ; fibre-cement boards ; acoustic emission ; SEM ; steel fibers ; steel fiber-reinforced concrete ; backfill mining ; loading rate ; cumulative ringing count ; damage constitutive model ; CFRP ; bond–slip law ; RC slab ; retrofit ; strengthen ; self-compacting concrete ; prediction models ; FRP ; continuous RC slab ; optimal design ; asphalt aging ; material property ; climate condition ; pavement structure ; field rut depth ; precast concrete products ; quality control ; OC curve ; AOQ curve ; shear wave velocity ; bender elements ; triaxial testing ; micromechanics ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNK Building construction and materials::TNKX Conservation of buildings and building materials
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: At present, the manufacturing industry is focused on the production of lighter weight components with better mechanical properties and always fulfilling all the environmental requirements. These challenges have caused a need for developing manufacturing processes in general, including obviously those devoted in particular to the development of thin-walled metallic shapes, as is the case with tubular and sheet metal parts and devices.This Special Issue is thus devoted to research in the fields of sheet metal forming and tube forming, and their applications, including both experimental and numerical approaches and using a variety of scientific and technological tools, such as forming limit diagrams (FLDs), analysis on formability and failure, strain analysis based on circle grids or digital image correlation (DIC), and finite element analysis (FEA), among others.In this context, we are pleased to present this Special Issue dealing with recent studies in the field of tube and sheet metal forming processes and their main applications within different high-tech industries, such as the aerospace, automotive, or medical sectors, among others.
    Keywords: micro tube ; hollow sinking ; plastic anisotropy ; surface quality ; size effect ; plasticity ; strength ; metallic tubes ; finite element analysis ; accumulative extrusion bonding ; kinematic bending ; product properties ; local heating ; profile bending ; asymmetric profile ; warping ; superimposed hydrostatic pressure ; shear damage growth ; fracture strain ; finite element analysis (FEA) ; additive manufacturing ; rapid prototyping ; sheet metal forming ; V-bending ; groove pressing ; HA-SPIF ; surface finish ; machine learning ; Ti6Al4V ; R-value ; thickness strain ; digital image correlation ; multi-camera DIC ; non-destructive testing ; single point incremental forming ; tube expansion ; formability ; fracture ; stress-triaxiality ; strain-hardening ; viscoplasticity ; bending ; semi-analytic solution ; Ti-6Al-4V ELI ; superplastic forming ; custom prosthesis ; in vivo tests ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic.
    Keywords: Computer Communication Networks ; Artificial Intelligence ; Information Systems Applications (incl. Internet) ; Special Purpose and Application-Based Systems ; Computer System Implementation ; User Interfaces and Human Computer Interaction ; Computer and Information Systems Applications ; open access ; artificial intelligence ; communication systems ; computer vision ; databases ; hci ; human-computer interaction ; image processing ; Internet of Things ; IoT ; machine learning ; network protocols ; sensors ; signal processing ; software architecture ; software design ; telecommunication networks ; telecommunication systems ; user interfaces ; wireless telecommunication systems ; Network hardware ; Artificial intelligence ; Information retrieval ; Internet searching ; Expert systems / knowledge-based systems ; Systems analysis & design ; User interface design & usability ; thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNH Information retrieval ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYD Systems analysis and design ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction::UYZG User interface design and usability
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The delicate balance of resource intensity and efficiency of a solution for a very complex problem raises the issue of how these aspects constitute a symmetrical or asymmetrical system. Computational Intelligence (CI) offers a plethora of efficient tools for the potential and rather good quality solution of highly complex, often mathematically intractable problems. This "toolbox" is one of the best examples for the study of the above mentioned issue, namely, how to find the best balance, how to establish a symmetry of weights or costs in a particular field, for a particular problem. This special issue presents a number of interesting novel applications of CI for the tackling of a wide variety of difficult problems. The Introduction gives a short insight into the symmetry and asymmetry aspect of the topic.
    Keywords: lung nodule segmentation ; 3D-UNet ; 3D-Res2UNet ; multi-scale features ; deep learning ; butterfly optimization algorithm (BOA) ; particle swarm optimization (PSO) ; cubic map ; nonlinear ; high dimension ; extensional fuzzy numbers ; MI-algebras ; similarity ; arithmetics of fuzzy numbers ; orderings ; fuzzy interpolation ; economic data ; air defense system ; artificial immune system ; command and control ; learning classifier system ; multi-agent systems ; weapon-target assignment ; energy optimization ; genetic algorithms ; multi-objective optimization ; artificial neural network simulator ; artificial intelligence ; artificial bee colony algorithm ; global optimization ; neural network ; nonlinear static system ; behavioural finance ; imprecision ; oriented fuzzy number ; oriented present value ; oriented return ; S-divergence ; S-distance ; spectral clustering ; text summarization ; recurrent neural network ; embedding ; dynamic memory network ; fuzzy-rough cognitive network ; fuzzy cognitive map ; granular computing ; fuzzy-rough sets ; stability ; convergence ; discrete bacterial memetic evolutionary algorithm ; simulated annealing ; flow shop scheduling problem ; global sensitivity analysis ; Sobol procedure ; fast algorithm ; convolutional neural network ; structure reduction ; pruning ; quality ; feature selection ; machine learning ; asexual ; genetic algorithm ; android malicious application detection ; bees algorithm ; training deep neural networks ; metaheuristics ; opinion mining ; recurrent neural networks ; sentiment classification ; natural language processing ; data augmentation ; fine-tuning ; generative models ; StyleGAN ; transfer learning ; present value ; discount factor ; portfolio ; finance ; optimization ; tourist trip design ; vehicle routing ; key performance indicator (KPI) ; anomaly detection ; variational auto-encoder (VAE) ; support vector data description (SVDD) ; FMEA ; Fuzzy Logic ; greenhouse gases ; blockchain ; difficulty adjustment ; proof-of-work ; ANN ; AlexNet ; COVID-19 ; TSA ; commonsense ; knowledge graph ; linguistic terms ; language models ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: This book is about JIDOKA, a Japanese management technique coined by Toyota that consists of imbuing machines with human intelligence. The purpose of this compilation of research articles is to show industrial leaders innovative cases of digitization of value creation processes that have allowed them to improve their performance in a sustainable way. This book shows several applications of JIDOKA in the quest towards an integration of human and AI within Industry 4.0 Cyber Physical Manufacturing Systems. From the use of artificial intelligence to advanced mathematical models or quantum computing, all paths are valid to advance in the process of human–machine integration.
    Keywords: healthy operator 4.0 ; human–cyber–physical system ; industrial internet of things ; industry 4.0 ; smart workplaces ; EEG sensors ; manufacturing systems ; shopfloor management ; machine learning ; deep learning ; reference architecture model ; interoperability ; digital twin ; distributed ledger technology ; GDPR ; RAMI 4.0 ; LASFA ; quantum computing ; strategic organizational design ; Industry 4.0 ; complex networks ; cyber-physical systems ; lean management systems ; quantum strategic organizational design ; quantum circuits ; quantum simulation ; JIDOKA ; Operator 4.0 ; process variability ; integration explaining variability ; quantum approximate optimization algorithm ; value–stream networks ; optimization ; maintenance interval ; maintenance model ; semi-Markov process ; right-censored data ; finite horizon ; maintenance cost ; Cyber-Physical Systems ; Lean Manufacturing ; Directed Acyclic Graphs ; scikit-learn ; pipegraph ; machine learning models ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-11-17
    Description: This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI.
    Keywords: artificial intelligence ; computer-aided diagnosis ; computed tomography ; lung cancer ; deep learning ; lung nodule detection ; lung nodule segmentation ; convolutional neural network ; cellular automaton ; reconstruction ; complexity ; optimization ; high energy physics ; Reddit ; user-based model ; polarization ; local search optimization ; hate speech ; hate spread ; countermeasures ; social networks ; opinion diffusion ; education ; deferring hate content ; cyber activism ; classical Arabic ; short vowels ; audio dataset ; convolutional neural networks ; regularization ; machine learning ; segmentation ; clustering ; forecasting ; book copies ; publishing industry ; gamification ; adaptive gamification ; player types ; computational finance ; fuzzy logic ; membership function ; Type-1 fuzzy sets ; T1FLS ; Type-2 fuzzy sets ; T2FLS ; women ; research ; CURE ; hierarchical clustering ; cluster validity indices ; Calinski–Harabasz index ; bootstrapping ; Industry 4.0 ; 3D printing ; cognitive states ; mental workload ; EEG analysis ; neural networks ; multimodal data fusion ; peer assessment ; multiagent system ; probabilistic model ; comparative analysis ; Bayesian network ; Artificial Intelligence ; urban water cycle ; hydrosocial urban cycle ; urban political ecology ; gender gap ; equity ; explainable AI ; fuzzy rules ; dominance-based rough set approach ; diabetic retinopathy ; AI ; disease surveillance ; pandemics ; global public health ; ethics ; data ; missing datasets ; data-driven studies ; women in artificial intelligence ; women in data science ; women in STEM ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: This reprint presents advances in operation and maintenance in solar plants, wind farms and microgrids. This compendium of scientific articles will help clarify the current advances in this subject, so it is expected that it will please the reader.
    Keywords: wind turbine ; electric generator ; spectral analysis ; fault diagnosis ; photovoltaic power forecasting ; data-driven ; deep learning ; variational autoencoders ; RNN ; angle swinging ; grid frequency oscillations ; electromechanical system ; inertial masses ; microgrids ; coordination protection ; distributed generation ; photovoltaic resources ; DigSILENT ; photovoltaic module ; defect detection ; power plant ; efficiency ; thermal image ; photovoltaic aging ; dark I-V curves ; bidirectional power inverter ; online distributed measurement of dark I-V curves ; sustainability ; compressive strength ; Bolomey formula ; sustainable concrete ; glass powder ; solar cell ; solar panel ; parameter extraction ; analytical ; Lambert W-function ; spacecraft solar panels ; I-V curve ; modeling ; wind power ; non-conventional renewable energy ; forecasting ; energy bands ; combinatorial optimization ; deep learning (DL) ; unmanned aerial vehicle (UAV) ; photovoltaic (PV) systems ; image-processing ; image segmentation ; semantic segmentation ; faults diagnostic ; artificial intelligence ; unbalanced datasets ; synthetic data ; artificial neural network based MPPT ; hybrid boost converter ; renewable energies ; solar power system ; microgrid ; control system ; storage system ; primary control ; photovoltaic (PV) plants ; coverage path planning (CPP) ; corrosion monitoring ; FPGA ; offshore wind turbines ; ultrasound ; thickness loss ; SCADA ; visualisation ; software ; wind-turbine ; windfarm ; cross-platform ; HMI ; GUI ; corrosion ; monitoring ; photovoltaic systems ; expected energy models ; fleet-scale ; lasso regression ; performance modeling ; machine learning ; fault location in photovoltaic arrays ; failure modes simulation ; fault detection criterion ; adaptive protection ; distributed power generation ; power distribution ; power system protection ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: Recent advances in information technology have brought forth a paradigm shift in science, especially in the biology and medical fields. Statistical methodologies based on high-performance computing and big data analysis are now indispensable for the qualitative and quantitative understanding of experimental results. In fact, the last few decades have witnessed drastic improvements in high-throughput experiments in health science, for example, mass spectrometry, DNA microarray, next generation sequencing, etc. Those methods have been providing massive data involving four major branches of omics (genomics, transcriptomics, proteomics, and metabolomics). Information about amino acid sequences, protein structures, and molecular structures are fundamental data for the prediction of bioactivity of chemical compounds when screening drugs. On the other hand, cell imaging, clinical imaging, and personal healthcare devices are also providing important data concerning the human body and disease. In parallel, various methods of mathematical modelling such as machine learning have developed rapidly. All of these types of data can be utilized in computational approaches to understand disease mechanisms, diagnosis, prognosis, drug discovery, drug repositioning, disease biomarkers, driver mutations, copy number variations, disease pathways, and much more. In this Special Issue, we have published 8 excellent papers dedicated to a variety of computational problems in the biomedical field from the genomic level to the whole-person physiological level.
    Keywords: water temperature ; bathing ; ECG ; heart rate variability ; quantitative analysis ; t-test ; hypertrophic cardiomyopathy ; data mining ; automated curation ; molecular mechanisms ; atrial fibrillation ; sudden cardiac death ; heart failure ; left ventricular outflow tract obstruction ; cardiac fibrosis ; myocardial ischemia ; compound–protein interaction ; Jamu ; machine learning ; drug discovery ; herbal medicine ; data augmentation ; deep learning ; ECG quality assessment ; drug–target interactions ; protein–protein interactions ; chronic diseases ; drug repurposing ; maximum flow ; adenosine methylation ; m6A ; RNA modification ; neuronal development ; genetic variation ; copy number variants ; disease-related traits ; sequential order ; association test ; blood pressure ; cuffless measurement ; longitudinal experiment ; plethysmograph ; nonlinear regression ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 188
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: Extremely popular for statistical inference, Bayesian methods are also becoming popular in machine learning and artificial intelligence problems. Bayesian estimators are often implemented by Monte Carlo methods, such as the Metropolis–Hastings algorithm of the Gibbs sampler. These algorithms target the exact posterior distribution. However, many of the modern models in statistics are simply too complex to use such methodologies. In machine learning, the volume of the data used in practice makes Monte Carlo methods too slow to be useful. On the other hand, these applications often do not require an exact knowledge of the posterior. This has motivated the development of a new generation of algorithms that are fast enough to handle huge datasets but that often target an approximation of the posterior. This book gathers 18 research papers written by Approximate Bayesian Inference specialists and provides an overview of the recent advances in these algorithms. This includes optimization-based methods (such as variational approximations) and simulation-based methods (such as ABC or Monte Carlo algorithms). The theoretical aspects of Approximate Bayesian Inference are covered, specifically the PAC–Bayes bounds and regret analysis. Applications for challenging computational problems in astrophysics, finance, medical data analysis, and computer vision area also presented.
    Keywords: bifurcation ; dynamical systems ; Edward–Sokal coupling ; mean-field ; Kullback–Leibler divergence ; variational inference ; Bayesian statistics ; machine learning ; variational approximations ; PAC-Bayes ; expectation-propagation ; Markov chain Monte Carlo ; Langevin Monte Carlo ; sequential Monte Carlo ; Laplace approximations ; approximate Bayesian computation ; Gibbs posterior ; MCMC ; stochastic gradients ; neural networks ; Approximate Bayesian Computation ; differential evolution ; Markov kernels ; discrete state space ; ergodicity ; Markov chain ; probably approximately correct ; variational Bayes ; Bayesian inference ; Markov Chain Monte Carlo ; Sequential Monte Carlo ; Riemann Manifold Hamiltonian Monte Carlo ; integrated nested laplace approximation ; fixed-form variational Bayes ; stochastic volatility ; network modeling ; network variability ; Stiefel manifold ; MCMC-SAEM ; data imputation ; Bethe free energy ; factor graphs ; message passing ; variational free energy ; variational message passing ; approximate Bayesian computation (ABC) ; differential privacy (DP) ; sparse vector technique (SVT) ; Gaussian ; particle flow ; variable flow ; Langevin dynamics ; Hamilton Monte Carlo ; non-reversible dynamics ; control variates ; thinning ; meta-learning ; hyperparameters ; priors ; online learning ; online optimization ; gradient descent ; statistical learning theory ; PAC–Bayes theory ; deep learning ; generalisation bounds ; Bayesian sampling ; Monte Carlo integration ; PAC-Bayes theory ; no free lunch theorems ; sequential learning ; principal curves ; data streams ; regret bounds ; greedy algorithm ; sleeping experts ; entropy ; robustness ; statistical mechanics ; complex systems ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
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  • 189
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Electrification plays a key role in decarbonizing energy consumption for various sectors, including transportation, heating, and cooling. There are several essential infrastructures for a smart city, including smart grids and transportation networks. These infrastructures are the complementary solutions to successfully developing novel services, with enhanced energy efficiency and energy security. This Special Issue includes high-quality papers that address issues related to cutting-edge smart city technologies in the electrification process, including but not limited to the following: Electrification of building environments and transportation systems; Role and impact of smart grids for smart cities; ICT and IoT infrastructures with big data for smart city electrification; Market, services, and business models for smart city electrification; Standards and implementation for smart city electrification; Advanced smart grid technology integration in smart cities, such as energy storage, demand-side management, and distributed energy resources.
    Keywords: coordinated operation ; natural gas network ; electrical network ; credit rank indicator ; data fusion ; main drive chain ; fault diagnosis ; wind turbine ; demand response programs ; social welfare maximization ; utility function ; power supply–demand balance ; electricity price ; rebate level ; fault-cause identification ; transmission line ; sparse learning ; multiview learning ; feature selection ; solar irradiance forecasting ; short-term and long-term predictions ; machine learning ; support vector machine ; Facebook Prophet ; contextual optimisation ; adaptive kernel ; multiple classifiers ; graph theory ; hydraulic model ; multi-criteria decision-making ; electric city bus ; energy consumption ; winter ; weather ; temperature ; infrastructure ; driving style ; cooling ; heating ; emissions ; Blockchain ; technology adoption theories ; technology adoption models ; systematic review ; multi-view learning ; subspace representation ; graph learning ; one-step clustering ; cyber security ; software-defined networking ; network security ; cyber-physical systems ; cross-layered ; power systems ; demand response ; coordinated preheating ; inverter air conditioner ; equivalent thermal parameter model ; smart grid ; e-bus powertrain ; tuning and optimization ; iSOPT ; digital twins ; internet-of-things ; local energy markets ; consumer digital twin ; transactive energy ; thermal comfort ; DER ; transportation ; influencing factors ; index decomposition approach ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
    Keywords: artificial intelligence ; communication systems ; computer hardware ; computer networks ; computer programming ; computer systems ; computer vision ; deep learning ; distributed computer systems ; image analysis ; image processing ; machine learning ; network protocols ; neural networks ; signal processing ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction::UYZG User interface design and usability ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications
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  • 191
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Commodity markets have evolved substantially since the early 2000s and have become more financialized. The recent cold war between the U.S.A. and China, the outbreak of COVID-19, and Russia's invasion of Ukraine have caused resource prices to soar, leading to greater volatility in the commodity markets. The volatility of the commodity markets has increased, and at the same time, financial markets such as the stock market, bond market, and foreign exchange market have become unstable. This has increased the linkage between the commodity and financial markets and has led to a great deal of attention being paid to the commodity markets by governments, companies, and investors.This reprint delves into recent developments in the commodity markets and elucidates the multifaceted factors that have shaped their trajectory. It examines how the interwoven dynamics of supply and demand, geopolitics, technology, and financialization have brought about a new era in commodity trading. By providing a comprehensive survey of these developments, we aim to provide insights that will help stakeholders successfully navigate the challenges and opportunities presented by this evolving landscape.
    Keywords: Russia and Ukraine conflict ; commodities ; G7 and BRIC markets ; TVP-VAR ; connectedness ; oil price uncertainty shocks ; international equity markets ; global vector autoregressive model ; arbitrage ; efficiency ; futures ; liquidity ; market integration ; platinum ; COVID-19 ; pandemic ; agriculture ; commodity ; MF-DFA ; high frequency ; asymmetric volatility spillover ; bitcoin ; altcoin ; cryptocurrency ; frequency connectedness ; Bitcoin ; machine learning ; random forest regression ; LSTM ; energy market volatility ; oil price dynamics ; fear index ; Markov-regime switching models ; volatility risk premium (VRP) ; implied and realized volatility ; oil and stock returns ; financialization ; Bermudan commodity options ; multi-layer perceptron ; multi-asset stochastic volatility model ; hybrid forecasting approaches ; two-step forecasting approaches ; gold ; euro ; sentiment analysis ; ARIMA ; wavelet transformation ; seasonal decomposition ; long short-term memory ; random forest ; eXtreme gradient boosting ; stock ; markets ; cycles ; investing ; risk ; returns ; 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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  • 192
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: "Health and Public Health Applications for Decision Support Using Machine Learning" is a reprint that explores the intersection of machine learning and health sciences. It presents a collection of research and innovations showcasing how data-driven algorithms can transform patient care, disease diagnosis, and public health management. The reprint covers a wide range of topics, including natural language processing for biomedical relation extraction, ensemble learning for blood glucose level forecasting in diabetes management, machine learning for predicting walking stability and fall risk among the elderly, deep learning for pneumonia-infected lung volume quantification, and more.The reprint also discusses applications in precision medicine, early detection of renal damage, cardiac health monitoring, stress classification for mental health assessment, and early diagnosis of intracranial internal carotid artery stenosis. It emphasizes the role of machine learning in managing health crises, such as COVID-19 detection using ECG, voice, and X-ray systems, and reviews AI models in diagnosing adult-onset dementia disorders.Overall, this reprint aims to inspire researchers and healthcare professionals by showcasing the transformative potential of machine learning in healthcare. It hopes to encourage further research and collaboration to advance healthcare and technological innovations for a healthier future.
    Keywords: adult-onset dementia ; Alzheimer’s disease ; magnetic resonance imaging ; artificial intelligence ; machine learning ; neural networks ; atherosclerosis ; Doppler ultrasound ; internal carotid artery ; hemodynamic modeling ; stroke ; stress ; emotion ; action units ; speech ; audio visual ; RNN-LSTM ; petri-plates ; colonies ; machine-learning models ; discrimination ; Measurement uncertainty ; Monte Carlo method ; ECG ; Cardiac health ; COVID-19 ; signal processing ; image processing ; computerized diagnostic systems ; subclinical renal damage ; risk assessment tool ; group-based trajectory modeling ; screening strategy ; CVD classification ; data selection ; convolutional neural network ; pretrained model ; deep learning ; transfer learning ; infected lung segmentation ; quantification of lung disease severity ; comparison between manual and automated image segmentation ; deep neural network ; COVID-19 detection ; COVID-19 severity assessment ; gait ; neuromuscular control ; movement synergy ; overground walking ; principal component analysis (PCA) ; largest Lyapunov exponent (LyE) ; time-series forecasting ; blood glucose ; diabetes ; ensemble learning ; artificial neural network ; DDI (drug–drug interaction) ; CPR (chemical–protein relation) ; transformer ; self-attention ; GAT (graph-attention network) ; relation extraction ; ChemProt ; T5 (text-to-text transfer transformer) ; n/a
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  • 193
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: The present reprint contains the 11 papers that were accepted and published in the Special Issue “Applied and Computational Mathematics for Digital Environments” of the MDPI Mathematics journal. The topics of interest include, among others, scientific research, applied tasks, and problems in the following areas: The construction of mathematical and information models of intelligent computer systems for monitoring and controlling the parameters of digital environments; The development of intelligent optimization algorithms that search for optimal parameter values of mathematical and information models in digital environments; Software and mathematical technologies in the implementation of intelligent monitoring and computer control of the parameters of digital environments; The development and application of mathematical and information models, machine learning methods, and artificial intelligence for the analysis and processing of big data in digital environments. I hope that this reprint will be useful to those who are interested in the real-world applications of applied and computational mathematics for digital environments in terms of solving actual, practical problems in all spheres of human life and activity.
    Keywords: mathematical model for evaluating the effectiveness of integrating information technology ; digital platforms ; virtual simulation infrastructures ; experimental virtual environment ; statistics ; multiscale analysis ; data analysis ; system on chip ; increasing traffic capacity ; percolation threshold ; transport link density ; transport network ; density of transport links ; computer algebra system ; wxMaxima ; Calculus ; symbolic computation ; mobile agents ; timeouts ; knowledge as set of trees ; behavioural equivalences ; nonlinear dynamics ; processes in social systems ; Fokker-Planck equation ; power law ; monitoring ; management ; image segmentation ; complex numbers ; CNN classifier ; outdoor environments ; relaxation subgradient methods ; space dilation ; nonsmooth minimization methods ; machine learning algorithm ; control synthesis ; optimal control ; stabilization ; symbolic regression ; machine learning ; evolutionary algorithm ; mobile robot ; problem decomposition ; large-scale global optimization ; self-adaptive differential evolution ; memetic algorithm ; cooperative co-evolution ; decision-making ; oncological disease ; kNN classifier ; SVM classifier ; dataset ; features ; UMAP algorithm ; entropy ; fractal dimension ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science
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  • 194
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems.
    Keywords: passive house ; enclosure structure ; heat transfer coefficient ; energy consumption ; turbo-propeller ; regional ; fuel ; weight ; range ; design ; CO2 reduction ; multi-objective combinatorial optimization ; meta-heuristics ; ant colony optimization ; non-intrusive load monitoring ; appliance classification ; appliance feature ; recurrence graph ; weighted recurrence graph ; V–I trajectory ; convolutional neural network ; energy baselines ; machine learning ; clustering ; neural methods ; smart intelligent systems ; building energy consumption ; building load forecasting ; energy efficiency ; thermal improved of buildings ; anti-icing ; heat and mass transfer ; heating power distribution ; heat load reduction ; optimization method ; experimental validation ; big data process ; predictive maintenance ; fracturing roofs to maintain entry (FRME) ; field measurement ; numerical simulation ; side abutment pressure ; strata movement ; energy ; manufacturing ; prediction ; forecasting ; modelling ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 195
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: The most influential research topic in the twenty-first century seems to be mathematics, as it generates innovation in a wide range of research fields. It supports all engineering fields, but also areas such as medicine, healthcare, business, etc. Therefore, the intention of this Special Issue is to deal with mathematical works related to engineering and multidisciplinary problems. Modern developments in theoretical and applied science have widely depended our knowledge of the derivatives and integrals of the fractional order appearing in engineering practices. Therefore, one goal of this Special Issue is to focus on recent achievements and future challenges in the theory and applications of fractional calculus in engineering sciences. The special issue included some original research articles that address significant issues and contribute towards the development of new concepts, methodologies, applications, trends and knowledge in mathematics. Potential topics include, but are not limited to, the following: Fractional mathematical models; Computational methods for the fractional PDEs in engineering; New mathematical approaches, innovations and challenges in biotechnologies and biomedicine; Applied mathematics; Engineering research based on advanced mathematical tools.
    Keywords: fractional order IMC ; first order plus dead-time processes ; event-based implementation ; numerical simulations ; comparative closed loop results ; nonlinear wave phenomen ; RBF ; local RBF-FD ; stability ; unmanned aerial vehicle (UAV) ; quaternion-based estimator ; low-cost design ; automatic optical inspection ; kinetic theory ; parallel robots ; robust control ; sliding mode control ; basinI ; basinII ; mean pressure head ; pressure head with different probabilities of occurrence ; standard deviation of the pressure fluctuations ; statistical modeling ; USBR ; desalination ; humidification-dehumidification ; waste heat recovery ; mathematical model ; yearly analysis ; thermo-economics ; multi-objective optimization ; cruise altitude ; fuel consumption ; time to climb ; Hermite-Simpson method ; trajectory optimization ; terminal residual analysis (TRA) ; m-σ terminal residual analysis (m-σ TRA) ; power transformer ; stray losses ; analytical methods ; finite element method ; gridshell structures ; shape ratio ; length ratio ; regularity ; particle swarm optimization ; genetic algorithm ; hybrid nanofluid ; dual solutions ; mixed convection ; stagnation point ; radiation ; stability analysis ; machine learning ; eXterme Gradient Boosting ; Computation Fluid Dynamics ; blade vibration ; unsteady aerodynamic model ; active disturbance rejection control (ADRC) ; multiobjective optimization ; time delay systems ; tuning rules ; soft robotics ; fractional calculus ; CACSD toolbox ; operating point linearization ; automatic uncertainty bound computation ; Model-in-the-Loop simulation ; hybrid simulation ; ℋ∞ control ; μ synthesis ; DC-to-DC power converters ; buck ; boost ; SEPIC ; rainfall-runoff model ; curve number ; inferential statistics ; 3D runoff difference model ; model calibration ; PAT model ; modified affinity laws ; hydraulic simulation tool ; μ-synthesis ; fractional-order control ; swarm optimization ; artificial bee colony optimization ; CNC machine ; mixed sensitivity ; D–K iteration ; Linear Matrix Inequality ; biotechnology ; fermentation process ; batch bioreactors ; modeling ; control system design and synthesis ; linear control ; adaptive control ; model reference adaptive control ; control system realization ; mixed-sensitivity ; FO-PID ; twin rotor aerodynamic system ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The reprint presents new approaches for bio- and immunosensors with nanodispersed labels and their optical registration. The use of nanoparticles as carriers and labels provides possibilities for simple measurements and reaching low detection limits. In this way, novel sensors obtain competitive advantages and good potential for implementation into diagnostic practice. The collected articles demonstrate the current state of developments and their most promising directions in the creation and characterization of such optical sensors.
    Keywords: mycotoxin ; food processing ; migration and transformation ; metabolites ; UPLC–MS/MS ; high-sensitive digital detection ; quantification ; functionalized gold nanoparticles ; microchips ; β-lactamases ; antibiotic-resistant bacteria ; luminescent composite particles ; carbon nanostructures ; luminescent carbon-based nanomaterials ; silica nanoparticles ; luminescence ; immunochromatography ; test strips ; RBD protein ; COVID-19 ; coronavirus ; microRNA detection ; polymerase-free isothermal amplification of nucleic acids ; mismatched catalytic hairpin assembly ; sulfonylureas ; broad-specificity ; antibody ; immunoassay ; adulteration ; functional foods ; thermoresponsive ; silver nanoparticles ; SERS ; 4-mercaptophenylboronic acid ; amphiphilic diblock copolymer ; poly(N,N-dimethylaminoethyl methacrylate) ; laser-induced aggregation ; plasmonic heating ; local laser exposure ; point-of-care test ; rapid diagnosis ; infectious diseases ; single-epitope sandwich ; double-epitope sandwich ; lumpy skin disease ; surface-enhanced Raman scattering (SERS) ; aptasensor ; SARS-CoV-2 virus ; surface-enhanced Raman spectroscopy ; influenza A virus ; influenza B virus ; detection ; machine learning ; catecholamines ; dopamine ; neurotransmitter ; resonance Raman spectroscopy ; surface-enhanced Raman spectroscopy (SERS) ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
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  • 197
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-01
    Description: The "Age-Friendly Cities & Communities: States of the Art and Future Perspectives" publication presents contemporary, innovative, and insightful narratives, debates, and frameworks based on an international collection of papers from scholars spanning the fields of gerontology, social sciences, architecture, computer science, and gerontechnology. This extensive collection of papers aims to move the narrative and debates forward in this interdisciplinary field of age-friendly cities and communities.
    Keywords: age-friendly cities ; physical environment/space ; urban ageing ; gentrification ; displacement ; aging in place ; physical activity ; aging ; social isolation ; cycling ; walking ; ICT ; older adults ; patent ; personalised ageing ; quality of life ; review ; smart ageing ; social robots ; ambient assisted living ; machine learning ; older adults care ; daily life activities monitoring ; technology limitation and acceptance ; care services models ; older citizens ; ageing ; technology ; digital ; smart cities initiatives ; smart city ; Romania ; public policies on smart cities ; evaluating smart cities initiatives ; older people ; connectedness ; social relationships ; later life ; age-friendliness ; community ; digital technology ; loneliness ; isolation ; intergenerational communication ; gerontology ; family ; cross-cultural research ; qualitative research ; housing ; elderly ; assisted living facilities ; seniors ; homes ; group living ; dwellings ; regulations ; rebellion ; governance ; law ; survey ; questionnaire ; validation ; age-friendly ; AFCCQ ; consultation-liaison psychiatry ; psycho-geriatrics ; general hospital ; age-friendly urban public transport ; smart mobility ; age-friendly transport ; mobility justice ; health ; indicators ; planning ; tools ; spatial ; neighbourhoods ; e-health ; urban planning ; smart ecosystem ; gerontechnology ; age in place ; coronavirus ; COVID-19 ; design hacking ; internet of things ; human-centered design ; smart cities ; digital citizenship ; urbanisation ; participatory action research ; cluster analysis ; thermal comfort ; design guidelines ; heating ; cooling ; participatory video design ; participation ; person-centered care ; co-creation ; perspective of older adults ; quality improvement ; use of technology ; Tāmaki Makaurau Auckland ; Polynesian population ; relational leadership ; Te Tiriti o Waitangi ; prisons ; prisoners ; older offenders ; ex-prisoners ; age-friendly cities and communities ; Kazan ; Russia ; health information ; ageism ; Cochrane ; evidence-based ; medicines ; consumers ; awareness ; Age-Friendly Cities ; photovoice ; healthy ageing ; active ageing ; social inclusion ; UK ; long-term care ; dementia ; physical environment ; social environment ; organizational environment ; environmental design ; policy ; case studies ; Global Network of Age-Friendly Cities and Communities ; World Health Organization ; social prescribing ; wearable technology ; digital data layer ; age-friendly communities ; citizen science ; well-being ; gender ; Coronavirus ; human centred design ; rural planning ; smart islands ; age-friendly homes ; innovation ; experiments ; 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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  • 198
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: This book represents one of the most up-to-date collections of articles on clinical practice and research in the field of Autism Spectrum Disorders (ASD). The scholars who contributed to this book are experts in their field, carrying out cutting edge research in prestigious institutes worldwide (e.g., Harvard Medical School, University of California, MIND Institute, King’s College, Karolinska Institute, and many others). The book addressed many topics, including (1) The COVID-19 pandemic; (2) Epidemiology and prevalence; (3) Screening and early behavioral markers; (4) Diagnostic and phenotypic profile; (5) Treatment and intervention; (6) Etiopathogenesis (biomarkers, biology, and genetic, epigenetic, and risk factors); (7) Comorbidity; (8) Adulthood; and (9) Broader Autism Phenotype (BAP). This book testifies to the complexity of performing research in the field of ASD. The published contributions underline areas of progress and ongoing challenges in which more certain data is expected in the coming years. It would be desirable that experts, clinicians, researchers, and trainees could have the opportunity to read this updated text describing the challenging heterogeneity of Autism Spectrum Disorder.
    Keywords: autism spectrum disorder ; infants ; frontal EEG alpha asymmetry ; early detection ; autism spectrum disorders ; toddlers ; eye tracking ; joint attention ; longitudinal ; regression ; cytokines ; PAI-1 ; neuroinflammation ; gastrointestinal ; autism ; literature review ; comorbidity ; early intervention ; early intensive behavioral intervention ; behavioral intervention ; First Year Inventory ; early screening ; risk ; cross-cultural generalisability ; validity ; preschool teachers ; self-efficacy ; knowledge ; belief ; skills ; identify ; autism spectrum disorder (ASD) ; level 1 and level 2 screening tools ; systematic review ; COSMIN ; PRISMA ; screening ; infection ; prion ; meta-analysis ; motion analysis ; video signal processing ; neurodevelopmental disorders ; infant screening ; n/a ; developmental language disorder ; semantic features ; word learning ; central coherence ; biomarker ; p-cresol ; mouse social behavior ; dopamine ; ASD ; vision ; proprioception ; self-motion ; immersive virtual reality ; IVR ; HMD ; technology ; persuasive text writing ; perspective-taking ; adolescence ; intervention ; sign language ; imitation ; cognition ; language acquisition ; prevalence estimate ; predictors ; surveillance review ; Autism Spectrum Disorder (ASD) ; early intensive intervention ; developmental trajectories ; moderators and mediators of intervention. ; psychosis ; schizophrenia ; psychopathology ; AQ ; accuracy ; attention to detail ; self-awareness ; insight ; preconception risk factor ; Gilles de la Tourette ; obsession ; compulsion ; social behavior ; social impairment ; sensory profile ; sensory responsiveness ; feeding problems ; short sensory profile (SSP) ; sensory experience questionnaire (SEQ) ; coronavirus ; 2019-nCoV ; neurodevelopment ; child and adolescent psychiatry ; mental health prevention ; Asperger syndrome ; adults ; cerebrospinal fluid ; antibodies ; blood–brain barrier ; GAD65 ; Early Start Denver Model ; high-risk infants ; motor development ; high-functioning autism ; language ; experience ; communication ; autonomic nervous system ; wearable technologies ; EEG ; theory of mind ; adults and adolescents ; human figure drawings ; Draw-a-Man ; drawings maturity ; social perception ; ERP ; reward response ; RewP ; sensitization ; social skills intervention ; PEERS® ; adulthood ; diagnosis ; autistic traits ; action observation ; action prediction ; context ; priors ; hypothalamus ; amygdala ; oxytocin ; social cognition ; social interaction ; affiliative behavior ; neuroimaging ; COVID-19 ; challenging behavior ; dental care ; oral health ; medical procedures ; ICT ; wearable sensors ; migration ; Europe ; health system ; autism in adulthood ; intellectual disability ; regressive autism ; epilepsy ; challenging behaviors ; empathy ; executive functions ; attention deficit and hyperactivity disorder ; disruptive behavior disorders ; alexithymia ; anxiety ; depression ; TAS-20 ; TSIA ; parents ; broader autism phenotype ; autistic-like features ; social-cognitive development ; stereotypical behaviors ; visual impairment ; language profiles ; grammatical comprehension ; cannabinoids ; cannabidiol ; cannabidivarin ; THC ; problem behaviors ; sleep ; hyperactivity ; side effects ; motor performance skills ; Gulf ; BOT-2 ; machine learning ; employment ; telehealth ; ABA ; RCT ; cortisol ; group activity ; stress ; art ; assessment ; sensorimotor integration ; postural balance ; false positive report probability (FPRP) ; Bayesian false-discovery probability (BFDP) ; Genome-Wide Association Studies (GWAS) ; microbiome ; metabolomics ; study design ; biomarker discovery ; precise medicine ; bipolar disorder ; suicidal ideation ; suicidal attempts ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue collates seven papers regarding the assessment or monitoring of hydrological disasters such as droughts and flood using remote sensing and geography information system (GIS) techniques.. The new published research focused on evaluations and models of various hydrological hazards such as droughts and floods. Furthermore, we include two original scientific articles addressing the subject of water quality. This Special Issue received investigations based on different techniques such as remote sensing, GIS, machine learning and monitoring. All papers present findings characterized as unconventional, provocative, innovative and methodologically new. Scientific findings presented in this Special Issue highlight how a combination of various modern analysis techniques (e.g., remote sensing, GIS) can improve our understanding of complex hydrological hazards such as droughts and floods. We hope that the research contained within this Special Issue is useful to the scientific community, policymakers and stakeholders at large in the field of hydrological hazards.
    Keywords: GRACE ; drought ; mainland China ; extreme climate ; climatic conditions ; urban floods ; rainfall movement direction (RMD) ; rainfall intensity (RI) ; peak runoff ; Linear Directional Mean (LDM) ; Shenzhen ; flood forecasting ; error correction ; residual property ; ridge coefficient criterion ; rainstorm mode ; high dimension ; dimension reduction ; cluster ; surface water ; monitoring history ; change trends in surface water quality ; water quality protection ; “Thirteenth Five-Year Plan” period ; water environment quality ; Heilongjiang Province ; correlation analysis ; manifold learning ; machine learning ; spatial–temporal distribution of rainstorms ; feature extraction ; Beijing ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
    Language: English
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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
    Language: English
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