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  • 1
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-24
    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 ; thema EDItEUR::C Language and Linguistics
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
    Keywords: virtual power plant (VPP) ; power quality (PQ) ; global index ; distributed energy resources (DER) ; energy storage systems (ESS) ; power systems ; long-term assessment ; battery energy storage systems (BESS) ; smart grids ; conducted disturbances ; power quality ; supraharmonics ; 2–150 kHz ; Power Line Communications (PLC) ; intentional emission ; non-intentional emission ; mains signalling ; virtual power plant ; data mining ; clustering ; distributed energy resources ; energy storage systems ; short term conditions ; cluster analysis (CA) ; nonlinear loads ; harmonics, cancellation, and attenuation of harmonics ; waveform distortion ; THDi ; low-voltage networks ; optimization techniques ; different batteries ; off-grid microgrid ; integrated renewable energy system ; cluster analysis ; K-means ; agglomerative ; ANFIS ; fuzzy logic ; induction generator ; MPPT ; neural network ; renewable energy ; variable speed WECS ; wind energy conversion system ; wind energy ; frequency estimation ; spectrum interpolation ; power network disturbances ; COVID-19 ; time-varying reproduction number ; social distancing ; load profile ; demographic characteristic ; household energy consumption ; demand-side management ; energy management ; time series ; Hidden Markov Model ; short-term forecast ; sparse signal decomposition ; supervised dictionary learning ; dictionary impulsion ; singular value decomposition ; discrete cosine transform ; discrete Haar transform ; discrete wavelet transform ; transient stability assessment ; home energy management ; binary-coded genetic algorithms ; optimal power scheduling ; demand response ; Data Injection Attack ; machine learning ; critical infrastructure ; smart grid ; water treatment plant ; power system ; 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::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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  • 3
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    Springer Nature | Springer Nature Switzerland
    Publication Date: 2024-04-14
    Description: This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23–28, 2022. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: – 3rd International Workshop on Event Data and Behavioral Analytics (EDBA) – 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics) – 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – 3rd International Workshop on Streaming Analytics for Process Mining (SA4PM) – 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) – 1st International Workshop on Education meets Process Mining (EduPM) – 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM)
    Keywords: process mining ; process discovery ; process analytics ; process querying ; conformance checking ; predictive process monitoring ; data science ; knowledge graphs ; event data ; streaming analytics ; machine learning ; deep learning ; business process management ; health informatics ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBH Digital and information technologies: Health and safety aspects
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management.
    Keywords: ANN ; roadside IoT sensors ; simulations of the gridded rainstorms ; 2D inundation simulation and real-time error correction ; weather types and features ; meteorological feature extraction ; artificial neural network ; self-organizing map (SOM) ; urban agriculture ; resource utilization efficiency ; urban northern Taiwan ; machine learning ; random forest ; regression analysis ; support vector machine ; threshold rainfall ; threshold runoff ; XGBoost ; stochastic rainfall generator ; Huff rainfall curve ; copula ; GeoAI ; artificial intelligence ; hydrological ; hydraulic ; fluvial ; water quality ; geomorphic ; modeling ; anomaly detection ; deep reinforcement learning ; telemetry water level ; time series ; ensemble ; multi-model ensemble ; precipitation ; forecasting ; persian gulf ; deep learning ; dam inflow ; RNN ; LSTM ; GRU ; hyperparameter ; rainfall time series ; artificial neural networks ; Multiple Linear Regression ; Chania ; CNN ; ELM ; temporary rivers ; hydrological extremes ; multivariate stochastic model ; autoregressive model ; Markov model ; daily temperature ; temperature generator ; Bayesian neural network ; forecasting uncertainty ; multi-step ahead forecasting ; probabilistic streamflow forecasting ; variational inference ; smart microclimate-control system (SMCS) ; system dynamics ; water–energy–food nexus ; agricultural resilience ; hydroinformatics ; hydrological modeling ; early warning ; uncertainty ; sustainability
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-03-21
    Description: This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners.
    Keywords: truck dispatching ; mining equipment uncertainties ; orebody uncertainty ; discrete event simulation ; Q-learning ; grinding circuits ; minerals processing ; random forest ; decision trees ; machine learning ; knowledge discovery ; variable importance ; mineral prospectivity mapping ; random forest algorithm ; epithermal gold ; unstructured data ; blast impact ; empirical model ; mining ; fragmentation ; mine worker fatigue ; random forest model ; health and safety management ; stockpiles ; operational data ; mine-to-mill ; geostatistics ; ore control ; mine optimization ; digital twin ; modes of operation ; geological uncertainty ; multivariate statistics ; partial least squares regression ; oil sands ; bitumen extraction ; bitumen processability ; mine safety and health ; accidents ; narratives ; natural language processing ; random forest classification ; hyperspectral imaging ; multispectral imaging ; dimensionality reduction ; neighbourhood component analysis ; artificial intelligence ; mining exploitation ; masonry buildings ; damage risk analysis ; Bayesian network ; Naive Bayes ; Bayesian Network Structure Learning (BNSL) ; rock type ; mining geology ; bluetooth beacon ; classification and regression tree ; gaussian naïve bayes ; k-nearest neighbors ; support vector machine ; transport route ; transport time ; underground mine ; tactical geometallurgy ; data analytics in mining ; ball mill throughput ; measurement while drilling ; non-additivity ; coal ; petrographic analysis ; macerals ; image analysis ; semantic segmentation ; convolutional neural networks ; point cloud scaling ; fragmentation size analysis ; structure from motion ; 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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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new materials and products. Additionally, this gives rise to new paradigms in bridging raw material data and processing to the induced properties and performance. This present topical issue is a compilation of contributions on novel ideas and concepts, addressing several key challenges using data and artificial intelligence, such as:- proposing new techniques for data generation and data mining;- proposing new techniques for visualizing, classifying, modeling, extracting knowledge, explaining and certifying data and data-driven models;- processing data to create data-driven models from scratch when other models are absent, too complex or too poor for making valuable predictions;- processing data to enhance existing physic-based models to improve the quality of the prediction capabilities and, at the same time, to enable data to be smarter; and- processing data to create data-driven enrichment of existing models when physics-based models exhibit limits within a hybrid paradigm.
    Keywords: plasticity ; machine learning ; constitutive modeling ; manifold learning ; topological data analysis ; GENERIC ; soft living tissues ; hyperelasticity ; computational modeling ; data-driven mechanics ; TDA ; Code2Vect ; nonlinear regression ; effective properties ; microstructures ; model calibration ; sensitivity analysis ; elasto-visco-plasticity ; Gaussian process ; high-throughput experimentation ; additive manufacturing ; Ti–Mn alloys ; spherical indentation ; statistical analysis ; Gaussian process regression ; nanoporous metals ; open-pore foams ; FE-beam model ; data mining ; mechanical properties ; hardness ; principal component analysis ; structure–property relationship ; microcompression ; nanoindentation ; analytical model ; finite element model ; artificial neural networks ; model correction ; feature engineering ; physics based ; data driven ; laser shock peening ; residual stresses ; data-driven ; multiscale ; nonlinear ; stochastics ; neural networks ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: The eradication of vector-borne diseases is threatened by the limited range of available insecticides, leading, inevitably, to the development of resistance. This is particularly concerning for malaria control, which relies heavily on insecticide-treated nets (ITNs) and indoor residual sprays (IRS). New chemistries are being developed, and innovative deployment of insecticides may play a role in overcoming resistance, either through new types of tools or new means of distribution. A variety of novel product types and vector control strategies are under development and evaluation, which is to be celebrated, but a strong evidence base is needed to guide effective operational deployment decisions. Novel approaches should be supported by robust data collected using appropriate and validated methods to monitor efficacy, durability, and any emerging resistance. This reprint presents original research into developing and characterizing new vector control products, as well as understanding and monitoring insecticide resistance. Review articles explore the impact of insecticide resistance and offer guidance on insecticide choice in the face of pyrethroid resistance. Consensus methodologies are presented, in the form of standard operating procedures (SOPs) designed to be adopted and used to generate reproducible data that can be compared and interpreted across and between studies. It is hoped that this collection of articles offers inspiration and guidance on how consistent data can be generated to inform more effective development, evaluation, and use of new and existing vector control tools.
    Keywords: prallethrin ; insecticide ; spatial treatment ; mosquito fitness ; protection ; pyrethroids ; Aedes albopictus ; Culex pipiens ; life tables ; mosquito ; bite-proof garment ; model ; textile ; non-insecticidal ; physical barrier ; insecticide selection ; out-crossing ; strain authentication ; laboratory screening ; pyrethroid ; pyrethroid resistance ; insecticide resistance ; insecticide resistance management ; vector control ; malaria ; malaria control ; Anopheles ; host-seeking behavior ; insecticide exposure ; pathogen transmission ; Aedes aegypti ; Anopheles gambiae ; ATSB ; Culex quinquefasciatus ; Iroquois ; RNAi ; Saccharomyces cerevisiae ; yeast ; Anopheles mosquito ; fertility ; ovary development ; pyriproxyfen (PPF) ; side-effects ; machine learning ; image classification ; automated identification ; convolutional neural network ; insecticide-treated net (ITN) ; PBO ITN ; synergist ITN ; dual-AI ITN ; insecticide resistance management (IRM) ; method validation ; durability monitoring ; bioinsecticide ; disease transmission ; insecticide-resistance ; mosquito-borne disease ; mosquito control ; natural compounds ; phytochemical ; malaria vector ; insecticide treated nets ; cytochrome P450s ; kdr ; cuticular resistance ; deltamethrin ; imidacloprid ; bifenthrin ; β-cyfluthrin ; etofenprox ; α-cypermethrin ; λ-cyhalothrin ; thiacloprid ; mosquitoes ; Attractive Toxic Sugar Bait (ATSB) ; Attractive Targeted Sugar Bait (ATSB) ; diagnostic bioassay ; resistance monitoring ; insecticide-treated nets (ITN) ; strain characterisation ; method development ; product evaluation ; quality control (QC) ; dual active ingredients (dual-AI) ; bioefficacy ; IRS ; application technology ; broflanilide ; clothianidin ; pirimiphos-methyl ; WHO tube ; WHO tunnel test ; ITNs ; interceptor ; interceptor G2 ; membrane ; human arm ; rabbit ; bioassay ; bio-efficacy ; 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::P Mathematics & science::PS Biology, life sciences::PSB Biochemistry
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  • 8
    Publication Date: 2024-03-27
    Description: This Special Issue provides an insight, collated from 26 articles, focusing on various aspects of the Fit-For-Purpose Land Administration (FFPLA) concept and its application. It presents some influential and innovative trends and recommendations for designing, implementing, maintaining and further developing Fit-For-Purpose solutions for providing secure land rights at scale. The first group of 14 articles is published in Volume One and discusses various conceptual innovations related to spatial, legal and institutional aspects and its wider applications within land use management. The second group of 12 articles is published in Volume Two and focuses on case studies from various countries throughout the world, providing evidence and lessons learned from the FFPLA implementation process.
    Keywords: complete cadastre ; legal element ; fixing boundary ; eligible landowner ; agreement ; boundary marker ; fit-for-purpose land administration (FFP LA) ; violent conflict ; United Nations ; extra-legal ; transitional justice ; peace building ; land governance ; power relations ; securing land rights ; land registration ; development impacts ; fit-for-purpose land administration ; land administration ; decentralization ; India ; fit-for-purpose ; institutions ; governance ; politics ; Amazon ; deforestation ; Fit-For-Purpose land administration ; participatory mapping ; indigenous land conflict ; Cumaribo ; Colombia ; community-based land adjudication ; components of adjudication ; land tenure ; land rights ; good practices ; updating land records ; systematic land registration ; unconventional approach ; case study ; Benin ; cadaster ; land administration domain model ; LADM ; cadastre ; FFPLA ; customary tenure ; land inventory ; land management ; mobile-based applications ; pro-poor ; land surveying ; tenure security ; land rights and tenure ; fit-for-purpose approach ; human rights ; design science research ; design thinking ; fit for purpose ; spatial data quality ; spatial data quality assurance ; maintenance ; update ; upgrade ; upkeep ; renewal ; data quality ; spatial framework ; STDM ; technology ; UAV ; feature extraction ; rapid urbanization ; climate change ; pandemic ; urban resilience ; spatial ; legal ; and institutional frameworks ; land tenure security ; pro-poor land recordation ; land governance reform ; cost effectiveness ; innovative technology ; case studies ; Uganda ; customary land tenure ; land recordation tools ; semantic technologies ; land information system ; fit-for-purpose land management ; aerial and street level imagery ; machine learning ; integrated land programs ; land policy ; pilot study ; informal settlements ; urban development ; Brazil ; community-based crowdsourcing ; SiGIT ; Ecuador ; land and resources rights ; public-private partnerships ; corporate social responsibility ; poverty reduction ; business driven solutions ; social enterprises ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Language: English
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: Today, the flow of electricity is bidirectional, and not all electricity is centrally produced in large power plants. With the growing emergence of prosumers and microgrids, the amount of electricity produced by sources other than large, traditional power plants is ever-increasing. These alternative sources include photovoltaic (PV), wind turbine (WT), geothermal, and biomass renewable generation plants. Some renewable energy resources (solar PV and wind turbine generation) are highly dependent on natural processes and parameters (wind speed, wind direction, temperature, solar irradiation, humidity, etc.). Thus, the outputs are so stochastic in nature. New data-science-inspired real-time solutions are needed in order to co-develop digital twins of large intermittent renewable plants whose services can be globally delivered.
    Keywords: self-healing grid ; machine-learning ; feature extraction ; event detection ; optimization techniques ; manta ray foraging optimization algorithm ; multi-objective function ; radial networks ; optimal power flow ; automatic P2P energy trading ; Markov decision process ; deep reinforcement learning ; deep Q-network ; long short-term delayed reward ; inter-area oscillations ; modal analysis ; reduced order modeling ; dynamic mode decomposition ; machine learning ; artificial neural networks ; steady-state security assessment ; situation awareness ; cellular computational networks ; load flow prediction ; contingency ; fuzzy system ; change detection ; data analytics ; data mining ; filtering ; optimization ; power quality ; signal processing ; total variation smoothing ; 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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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this Special Issue (SI) is dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement artificial intelligence (AI) into food and beverage production and for consumer assessment. This SI published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products, such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products.
    Keywords: sensory ; physicochemical measurements ; artificial neural networks ; near infra-red spectroscopy ; wine quality ; machine learning modeling ; weather ; consumer acceptance prediction ; data fusion ; emotion recognition ; facial expression recognition ; galvanic skin response ; machine learning ; neural networks ; sensory analysis ; avocado ; cultivars ; preference mapping ; sensory evaluation ; sensory descriptive analysis ; consumer science ; unifloral honeys ; botanical origin ; physicochemical parameters ; classification ; natural language processing ; deep learning ; sensory science ; flavor lexicon ; long short-term memory ; 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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  • 11
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-04
    Description: Numerical simulation is a powerful tool used in various fields of science and engineering to model complex systems and predict their behavior. It involves developing mathematical models that describe the behavior of a system and using computer algorithms to solve these models numerically. By doing so, researchers and engineers can study the behavior of a system in detail, which may only be possible with analytical methods. Numerical simulation has many advantages over traditional analytical methods. It allows researchers and engineers to study complex systems’ behavior in detail and predict their behavior in different scenarios. It also allows for the optimization of systems and the identification of design flaws before they are built. However, numerical simulation has its limitations. It requires significant computational resources, and the accuracy of the results depends on the quality of the mathematical models and the discretization methods used. Nevertheless, numerical simulation remains a valuable tool in many fields and its importance is likely to grow as computational resources become more powerful and widely available. Numerical simulation is widely used in physics, engineering, computer science, and mathematics. In physics, for example, numerical simulation is used to study the behavior of complex systems such as weather patterns, fluid dynamics, and particle interactions. In engineering, it is used to design and optimize systems such as aircraft, cars, and buildings. In computer science, numerical simulation models and optimization algorithms and data structures. In mathematics, it is used to study complex mathematical models and to solve complex equations. This book familiarizes readers with the practical application of the numerical simulation technique to solve complex analytical problems in different industries and sciences.
    Keywords: machine learning ; artificial intelligence ; optimization ; heat transfer ; cfd ; image processing ; thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
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  • 12
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: This book mainly deals with recent advances in biomedical sensing and imaging. More recently, wearable/smart biosensors and devices, which facilitate diagnostics in a non-clinical setting, have become a hot topic. Combined with machine learning and artificial intelligence, they could revolutionize the biomedical diagnostic field. The aim of this book is to provide a research forum in biomedical sensing and imaging and extend the scientific frontier of this very important and significant biomedical endeavor.
    Keywords: finite element method ; thin shell model ; β dispersion ; Maxwell–Wagner effect ; bio-impedance spectroscopy ; multisensory ; electromyography ; pattern recognition ; rehabilitation ; blood coagulation ; image sensing ; image classification ; electrical impedance tomography ; frequency difference ; time difference ; lung imaging ; electromagnetic detection and biosensors ; electromagnetic biological theory ; biomedical application ; frequency ; machine learning ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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  • 13
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; swarm-robotics ; drag-based system ; PID algorithm ; human–robot interaction ; behaviour dynamics ; state constraints ; fair optimisation ; micro mobile robot ; robot ; actuators ; high-gain observer ; turning model LIP ; space robot ; manipulation action sequences ; subgoal graphs ; remotely operated vehicle ; constrained motion ; joint limit avoidance ; curvilinear obstacle ; rehabilitation system ; stability criterion ; system design ; quad-tilt rotor ; iterative learning ; spiral curve ; cable detection ; SEA ; douglas–peuker polygonal approximation ; predictable trajectory planning ; ATEX ; obstacle avoidance system ; kinematic singularity ; collision avoidance ; biologically-inspired ; jumping robot ; differential wheeled robot ; design and modeling ; control efficacy ; robotics ; extremum-seeking ; object-oriented ; non-holonomic mobile robot ; magneto-rheological fluids ; rendezvous consensus ; altitude controller ; master-slave ; switching control ; deep reinforcement learning ; mechanism ; expansion logic strategy ; negative buoyancy ; action generation ; radial basis function neural networks ; unmanned aerial vehicles ; extend procedure ; glass façade cleaning robot ; convolutional neural network ; climbing robot ; micro air vehicle ; car-like kinematics ; variable speed ; machine learning ; dynamical model ; transportation ; geodesic ; unmanned surface vessel ; medical devices ; stopper ; extended state observer (ESO) ; high efficiency ; object mapping ; multi-objective optimization ; hybrid robot ; robot learning ; auto-tuning ; cable disturbance modeling ; manipulation planning ; pesticide application ; high-speed target ; sparse pose adjustment (SPA) ; service robot ; lumped parameter method ; Geometric Algebra ; dynamic coupling analysis ; Thau observer ; tri-tilt-rotor ; industrial robotic manipulator ; hardware-in-the-loop simulation ; robotic drilling ; muscle activities ; small size ; chameleon ; continuous hopping ; wall climbing robot ; hover mode ; 3D-SLAM ; curvature constraints ; PSO ; drilling end-effector ; Rodrigues parameters ; gait adaptation ; static environments ; position/force cooperative control ; snake-like robot ; shape-fitting ; powered exoskeleton ; input saturation ; kinematic identification ; methane ; human–machine interactive navigation ; q-learning ; path following ; hopping robot ; mobile manipulation ; high step-up ratio ; actuatorless ; monocular vision ; stability analysis ; compact driving unit ; snake robot ; non-holonomic robot ; curvature constraint ; phase-shifting ; dialytic elimination ; gesture recognition ; snake robots ; series elastic actuator ; flapping ; servo valve ; motion camouflage control ; biomimetic robot ; minimally invasive surgery robot ; centralized architecture ; trajectory planning ; computing time ; adaptive control law ; kinematics ; facial and gender recognition ; single actuator ; victim-detection ; shape memory alloys ; undiscovered sensor values ; discomfort ; Differential Evolution ; numerical evaluation ; quadruped robot ; coverage path planning ; localization ; MPC ; n/a ; fault diagnosis ; neural networks ; disturbance-rejection control ; sample gathering problem ; cart ; bio-inspired robot ; opposite angle-based exact cell decomposition ; optimization ; safety ; goal exchange ; hierarchical planning ; ocean current ; robot motion ; nonlinear differentiator ; mapping ; finite-time currents observer ; Newton iteration ; inverse kinematics ; deposition uniformity ; spatial pyramid pooling ; hierarchical path planning ; end effector ; head-raising ; fault recovery ; LOS ; path tracking ; non-inertial reference frame ; step climbing ; obstacle avoidance ; sliding mode control ; symmetrical adaptive variable impedance ; lane change ; quadcopter UAV ; singularity analysis ; biped mechanism ; fault-tolerant control ; dynamic neural networks ; mobile robots ; data association ; UAV ; enemy avoidance ; reinforcement learning ; grip optimization ; safety recovery mechanism ; exoskeleton ; dynamic environment ; uncertain environments ; hybrid bionic robot ; potential field ; robot navigation ; cleaning robot ; unmanned aerial vehicle ; non-singular fast-terminal sliding-mode control ; contact planning ; Lyapunov-like function ; piezoelectric actuator ; transition mode ; non-prehensile manipulation ; multiple mobile robots ; Tetris-inspired ; real-time action recognition ; integral line-of-sight ; topological map ; alpine ski ; target tracking ; closed-loop detection ; working efficiency ; mathematical modeling ; curve fitting ; force control ; biped robots ; NSGA-II ; mobile robot ; load carriage ; prescription map translation ; artificial fish swarm algorithm ; Q-networks ; self-reconfigurable robot ; G3-continuity ; autonomous vehicle ; loop closure detection ; excellent driver model ; robots ; graph representation ; regional growth ; target assignment ; evolutionary operators ; intelligent mobile robot ; motion sensor ; exploration ; droplets penetrability ; dynamic uncertainty ; simultaneous localization and mapping (SLAM) ; area decomposition ; multi-criteria decision making ; 4WS4WD vehicle ; biped climbing robots ; skiing robot ; ROS ; decision making ; smart materials ; centrifugal force ; missile control system ; formation of robots ; electro-rheological fluids ; pneumatics ; variable spray ; inertial measurement unit (IMU) ; Robot Operating System ; trajectory interpolation ; formation control ; immersion and invariance ; dragonfly ; parallel navigation ; harmonic potential field ; pallet transportation ; mobile robot navigation ; negative-buoyancy ; grip planning ; manipulator ; position control ; external disturbance ; legged robot ; passive skiing turn ; autonomous underwater vehicle (AUV) ; gait cycle ; path planning ; sliding mode observer ; dynamic gait ; self-learning ; polyomino tiling theory ; coalmine ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 14
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.
    Keywords: data envelopment analysis ; Kohonen self-organizing maps ; factor analysis ; multiple regression ; energy efficiency ; social media ; energy-consuming activities ; energy consumption ; machine learning ; ontology ; energy performance certificate ; heating energy demand ; buildings ; data mining ; classification ; regression ; decision tree ; support vector machine ; random forest ; artificial neural network ; open data ; electrification modelling ; Malawi ; OnSSET ; MESSAGEix ; reproducibility ; collaborative work ; open modelling and data ; data-handling ; integrated assessment modelling ; data pre- and post-processing ; space heating ; domestic hot water ; market assessment ; EU28 ; district heating ; data analytics ; big data ; forecasting ; energy ; polygeneration ; clustering ; kNN ; pattern recognition ; heating ; building stock ; heat map ; spatial analysis ; heat density map ; building performance simulation ; parametric modelling ; energy management ; model calibration ; Passive House ; energy planning ; energy potential mapping ; urban energy atlas ; urban energy transition ; energy data ; data-aware planning ; spatial planning ; open data analytics ; smart cities ; open energy governance ; urban database ; energy mapping ; building dataset ; energy modelling ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 15
    Publication Date: 2023-05-10
    Description: Current approaches to Natural Language Processing (NLP) have shown impressive improvements in many important tasks: machine translation, language modeling, text generation, sentiment/emotion analysis, natural language understanding, and question answering, among others. The advent of new methods and techniques, such as graph-based approaches, reinforcement learning, or deep learning, have boosted many NLP tasks to a human-level performance (and even beyond). This has attracted the interest of many companies, so new products and solutions can benefit from advances in this relevant area within the artificial intelligence domain.This Special Issue reprint, focusing on emerging techniques and trendy applications of NLP methods, reports on some of these achievements, establishing a useful reference for industry and researchers on cutting-edge human language technologies.
    Keywords: natural language processing ; distributional semantics ; machine learning ; language model ; word embeddings ; machine translation ; sentiment analysis ; quality estimation ; neural machine translation ; pretrained language model ; multilingual pre-trained language model ; WMT ; neural networks ; recurrent neural networks ; named entity recognition ; multi-modal dataset ; Wikimedia Commons ; multi-modal language model ; concreteness ; curriculum learning ; electronic health records ; clinical text ; relationship extraction ; text classification ; linguistic corpus ; deception ; linguistic cues ; statistical analysis ; discriminant function analysis ; fake news detection ; stance detection ; social media ; abstractive summarization ; monolingual models ; multilingual models ; transformer models ; transfer learning ; discourse analysis ; problem–solution pattern ; automatic classification ; machine learning classifiers ; deep neural networks ; question answering ; machine reading comprehension ; query expansion ; information retrieval ; multinomial naive bayes ; relevance feedback ; cause-effect relation ; transitive closure ; word co-occurrence ; automatic hate speech detection ; multisource feature extraction ; Latin American Spanish language models ; fine-grained named entity recognition ; k-stacked feature fusion ; dual-stacked output ; unbalanced data problem ; document representation ; semantic analysis ; conceptual modeling ; universal representation ; trend analysis ; topic modeling ; Bert ; geospatial data technology and application ; attention model ; dual multi-head attention ; inter-information relationship ; question difficult estimation ; named-entity recognition ; BERT model ; conditional random field ; pre-trained model ; fine-tuning ; feature fusion ; attention mechanism ; task-oriented dialogue systems ; Arabic ; multi-lingual transformer model ; mT5 ; language marker ; mental disorder ; deep learning ; LIWC ; spaCy ; RobBERT ; fastText ; LIME ; conversational AI ; intent detection ; slot filling ; retrieval-based question answering ; query generation ; entity linking ; knowledge graph ; entity embedding ; global model ; DISC model ; personality recognition ; predictive model ; text analysis ; data privacy ; federated learning ; transformer ; 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: 2024-03-30
    Description: This Special Issue includes 14 contributions, with 2 review contributions and 12 research contributions. The review contributions provide a survey with an overview of the state of the art in detecting and projecting cyber-attack scenarios, and the review of a specific application area, the safety of autonomous haulage systems in the mining environment related to both cybersecurity and communication. 10 research contributions are addressing the area of advanced services for intrusion detection systems: (a) the use of different machine learning models depending on the specific scenarios and datasets; (b) the use of deep learning techniques for the detection of zero-day attacks; (c) a proposal of an integrated scalable framework aimed at efficiently detecting anomalous events on large amounts of unlabeled data logs; (d) a spatiotemporal characterization of cyber-attacks for detecting such attacks; (e) a two-stage intrusion detection system for industrial control networks; (f) a chatbot for detecting online sex offenders, based on an artificial conversational entity (ACE); and (g) an open-source platform for manipulating both streaming and archived network flow data in real time. This Special Issue also contains two protection-related research contributions, including: (a) a countermeasure for on–off web defacement attacks and (b) the evaluation of multi-path routing as a protection feature against network attacks and failures.
    Keywords: cybersecurity ; machine learning ; intrusion detection ; cybersecurity awareness&nbsp ; 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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  • 17
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Robotics and control are both research and application domains that have been frequently engineered through the use of interdisciplinary approaches like cybernetics. Cognition is a particular concept of this approach, abstracted from the context of living organisms to that of artificial devices, and is concerned with knowledge acquisition and understanding through thought, experience, and the senses. Cognitive robotics and control refer to knowledge processing as much as knowledge generation from problem understanding, leading to special forms of architectures that enable systems to behave in an autonomous way. The main aim of this book is to highlight emerging applications and address recent breakthroughs in the domain of cognitive robotics and control and related areas. Procedures, algorithms, architectures, and implementations for reasoning, problem solving, or decision making are considered in the domain of robotics and control.
    Keywords: initial trajectory ; trajectory optimization ; Bézier surface ; robotics ; open FPGAs ; robot control ; surgical robotics ; human–machine interaction ; autonomous guidance ; low-cost platform ; FPGA ; S-curve ; motion control ; SoC ; telemanipulation ; haptics ; machine learning ; gesture recognition ; upper limb rehabilitation robot ; particle swam optimization (PSO) ; artificial bee colony (ABC) ; Ziegler Nichols ; Maximum sensitivity ; ontology ; robot task planning ; knowledge base ; knowledge representation ; industrial collaborative robots ; shared robotic tasks ; physical human–robot interaction ; human intention recognition ; time series classification ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 18
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Personalised medicine is the next step in healthcare, especially when applied to genetically diverse diseases such as cancers. Naturally, a host of methods need to evolve alongside this, in order to allow the practice and implementation of individual treatment regimens. One of the major tasks for the development of personalised treatment of cancer is the identification and validation of a comprehensive, robust, and reliable panel of biomarkers that guide the clinicians to provide the best treatment to patients. This is indeed important with regards to radiotherapy; not only do biomarkers allow for the assessment of treatability, tumour response, and the radiosensitivity of healthy tissue of the treated patient. Furthermore, biomarkers should allow for the evaluation of the risks of developing adverse late effects as a result of radiotherapy such as second cancers and non-cancer effects, for example cardiovascular injury and cataract formation. Knowledge of all of these factors would allow for the development of a tailored radiation therapy regime. This Special Issue of the Journal of Personalised Medicine covers the topic of Radiation Response Biomarkers in the context of individualised cancer treatments, and offers an insight into some of the further evolution of radiation response biomarkers, their usefulness in guiding clinicians, and their application in radiation therapy.
    Keywords: carbon-ion radiotherapy ; head-and-neck tumors ; squamous cell carcinoma ; radiosensitivity ; relative biological effectiveness ; lung cancer ; radiotherapy ; radiotherapy monitoring ; radiation-induced lung injury ; RILI ; pneumonitis ; radiation-induced lung fibrosis ; RILF ; circulating biomarkers ; microRNA ; micronuclei ; uterine cervical cancer ; cGAS ; STING ; abscopal effect ; immunotherapy ; PBMCS ; micronucleus assay ; biological dosimetry ; human blood ; genotoxicity tests ; ionizing radiation ; biomarkers ; dicentric assay ; gamma H2AX foci assay ; health surveillance analyses ; clonogenic assays ; methods ; plating ; cancer ; radiation ; head and neck cancer ; exosomes ; serum ; metabolomics ; GC/MS ; biodosimetry ; chromosome aberrations ; normal tissue toxicity ; predictive tests ; normal tissue ; biomarker ; protein ; immune infiltrate ; stroma ; tumour microenvironment ; proteomics ; telomeres ; chromosomal instability ; inversions ; prostate cancer ; IMRT ; machine learning ; individual radiosensitivity ; late effects ; personalized medicine ; liquid biopsy ; circulating tumour cells ; extracellular vesicles ; microRNAs ; immune system ; inflammation ; n/a
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  • 19
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In recent years, the implementation of sustainable concrete systems has been a topic of great interest in the field of construction engineering worldwide, as a result of the large and rapid increase in carbon emissions and environmental problems resulting from traditional concrete production and industry. For example, the uses of supplementary cementitious materials, geopolymer binder, recycled aggregate and industrial/agricultural wastes in concrete are all approaches to building a sustainable concrete system. However, such materials have inherent flaws due to their variety of sources, and exhibit very different properties compared with traditional concrete. Therefore, they require specific modifications in preprocessing, design, and evaluation before use in concrete. This reprint, entitled “Advances in Sustainable Concrete System”, covers a broad range of advanced concrete research in environmentally friendly concretes, cost-effective admixtures, and waste recycling, specifically including the design methods, mechanical properties, durability, microstructure, various models, hydration mechanisms, and practical applications of solid wastes in concrete systems.
    Keywords: high-strength concrete ; energy evolution ; elastic strain energy ; brittleness evaluation index ; concrete ; humidity ; moisture absorption ; moisture desorption ; numerical simulation ; acoustic emission ; AE rate process theory ; corrosion rate ; damage evolution ; axial load ; precast concrete structure ; lattice girder semi-precast slabs ; bending resistance ; FE modelling ; concrete damage ; GSP ; high strength ; hydration ; strength ; penetrability ; rice husk ash ; sustainable concrete ; artificial neural networks ; multiple linear regression ; eco-friendly concrete ; green concrete ; sustainable development ; artificial intelligence ; data science ; machine learning ; bagasse ash ; mechanical properties ; natural coarse aggregate ; recycled coarse aggregate ; two-stage concrete ; materials design ; recycled concrete ; crumb rubber concrete ; crumb rubber ; NaOH treatment ; lime treatment ; water treatment ; detergent treatment ; compressive strength ; materials ; adhesively-bonded joint ; temperature aging ; residual strength ; mechanical behavior ; failure criterion ; steel slag powder ; compound activator ; mortar strength ; orthogonal experiment ; GM (0, N) model ; ultrafine metakaolin ; silica fume ; durability ; fiber-reinforced concrete ; damage mechanism ; uniaxial tension ; cracked concrete ; crack width ; crack depth ; tortuosity ; sustainability ; concrete composites ; sulfate and acid attacks ; WPFT fibers ; coal gangue ; gradation ; cement content ; unconfined compressive strength ; freeze–thaw cycle ; minimum energy dissipation principle ; three-shear energy yield criterion ; damage variable ; constitutive model ; phosphorus slag ; limestone ; sulphate-corrosion resistance ; volume deformation ; blast furnace ferronickel slag ; alkali-activated material ; dosage of activator ; reactive powder concrete ; beam-column joint ; FE modeling ; crack ; cementitious gravel ; fly ash ; age ; optimal dosage ; bamboo ; sawdust ; pretreatment ; bio-based material ; mechanical property ; self-compacting concrete ; supplementary cementitious materials ; hydration mechanisms ; microstructure ; fresh properties ; synthetic polymer ; high temperature ; bentonite-free drilling fluid ; rheology ; filtration ; FRP reinforced concrete slab ; punching shear strength ; SHAP ; 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::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: 2024-04-11
    Description: This book is a collection of recent publications from researchers all over the globe in the broad area of high-voltage engineering. The presented research papers cover both experimental and simulation studies, with a focus on topics related to insulation monitoring using state-of-the-art sensors and advanced machine learning algorithms. Special attention was given in the Special Issue to partial discharge monitoring as one of the most important techniques in insulation condition assessment. Moreover, this Special Issue contains several articles which focus on different modeling techniques that help researchers to better evaluate the condition of insulation systems. Different power system assets are addressed in this book, including transformers, outdoor insulators, underground cables, and gas-insulated substations.
    Keywords: TA1-2040 ; T1-995 ; artificial neural network ; simulation ; high-frequency ; artificial flashover tests ; wide bandgap power modules ; tracking ; electrical field strength ; fast-rise square wave voltages ; FDTD simulation ; cable joint ; corona discharge ; feature selection ; post insulator ; earthing systems ; wind speed ; surface discharge ; oil/paper insulation ; oil-paper insulation ; high-magnitude currents and impulse polarity ; UFVM ; Tettex 9520 ; electrical tree ; flashover characteristics ; composite insulator ; partial discharge ; numerical modeling ; saline mechanism ; thermal parameters ; space charge density ; seasonal ; ion flow field ; denoising ; DDX 9121b ; temperature ; transformer asset management ; cavity discharge ; space/interface charge ; insulation health index ; heat transfer model ; leakage current ; machine learning ; partial discharges (PD) ; RF signal ; flashover ; high impulse conditions ; grounding electrodes ; generalized finite difference time domain ; curve fitting ; grounding ; plasma discharge ; outdoor insulators ; flashover dynamic model ; wavelet transform ; degradation ; thermal properties ; bipolar charge transport model ; UHF sensor ; cable ; random walk theory ; tracking test setup ; GIL ; pressure ; modelling ; non-uniform pollution between windward and leeward sides ; calibrator ; secondary arc ; polymeric insulation ; optical-UHF integrated detection ; shoreline ; dry band arcing ; photoelectric fusion pattern ; DDX 8003 ; XLPE ; silicone gel ; partial discharge modeling ; electric field analysis ; NSCT ; electrode’s geometry ; gas ; Comsol Multiphysics ; fast-impulses ; laying modes ; ageing ; cable ampacity ; residual resistance formulation ; finite element analysis ; thermal effect ; hydrophobicity ; soil resistivity ; charge simulation method ; short-circuit discharge ; dry band formation ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective.
    Keywords: subject-dependent emotion recognition ; subject-independent emotion recognition ; electrodermal activity (EDA) ; deep learning ; convolutional neural networks ; automatic facial emotion recognition ; intensity of emotion recognition ; behavioral biometrical systems ; machine learning ; artificial intelligence ; driving stress ; electrodermal activity ; road traffic ; road types ; Viola-Jones ; facial emotion recognition ; facial expression recognition ; facial detection ; facial landmarks ; infrared thermal imaging ; homography matrix ; socially assistive robot ; EEG ; arousal detection ; valence detection ; data transformation ; normalization ; mental stress detection ; electrocardiogram ; respiration ; in-ear EEG ; emotion classification ; emotion monitoring ; elderly caring ; outpatient caring ; stress detection ; deep neural network ; convolutional neural network ; wearable sensors ; psychophysiology ; sensor data analysis ; time series analysis ; signal analysis ; similarity measures ; correlation statistics ; quantitative analysis ; benchmarking ; boredom ; emotion ; GSR ; classification ; sensor ; face landmark detection ; fully convolutional DenseNets ; skip-connections ; dilated convolutions ; emotion recognition ; physiological sensing ; multimodal sensing ; flight simulation ; activity recognition ; physiological signals ; thoracic electrical bioimpedance ; smart band ; stress recognition ; physiological signal processing ; long short-term memory recurrent neural networks ; information fusion ; pain recognition ; long-term stress ; electroencephalography ; perceived stress scale ; expert evaluation ; affective corpus ; multimodal sensors ; overload ; underload ; interest ; frustration ; cognitive load ; stress research ; affective computing ; human-computer interaction ; deep convolutional neural network ; transfer learning ; auxiliary loss ; weighted loss ; class center ; stress sensing ; smart insoles ; smart shoes ; unobtrusive sensing ; stress ; center of pressure ; regression ; signal processing ; arousal ; aging adults ; musical genres ; emotion elicitation ; dataset ; emotion representation ; feature selection ; feature extraction ; computer science ; virtual reality ; head-mounted display ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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  • 22
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: The reprint focuses on the latest research in cybersecurity and data science. Digital transformation turns data into the new oil, so the increasing availability of big data, structured and unstructured datasets, raises new challenges in cybersecurity, efficient data processing and knowledge extraction. The field of cybersecurity and data science fuels the data-driven economy. Innovations in this field require strong foundations in mathematics, statistics, machine learning and information security. The unprecedented increase in the availability of data in many fields of science and technology (e.g., genomic data, data from industrial environments, network traffic, streaming media, sensory data of smart cities, and social network data) ask for new methods and solutions for data processing, information extraction and decision support. This stimulates the development of new methods of data analysis, including those adapted to the analysis of new data structures and the growing volume of data. The papers included in this reprint discuss various topics ranging from cyberattacks, steganography, anomaly detection, evaluation of the attacker skills, modelling of the threats, and wireless security evaluation, as well as artificial intelligence, machine learning, and deep learning. Given this diversity of topics the book represents a valuable reference for researchers in cybersecurity security and data science.
    Keywords: steganography ; network security ; steganography detection ; steganalysis ; machine learning ; big data ; IoT ; pattern mining ; wireless communications ; covert channel ; dirty constellation ; wireless postmodulation steganography ; phase drift ; drift correction modulation ; undetectability ; security ; quadrature amplitude modulation ; spam ; phishing ; classification ; augmented dataset ; multi-language emails ; cybersecurity ; data protection ; SoC ; threat agents ; motivation ; opportunity ; capability ; user profiling ; implicit ; modeling ; real-time user monitoring ; complexity threat agent ; threat assessment ; network traffic analysis ; convolutional neural networks ; network traffic images ; visualization of traffic ; classifiers ; e-mail ; ham ; data science ; datasets ; cyber threats modeling ; multi-agent systems ; cyber deception ; pseudorandom sequences generators ; prime numbers ; additive Fibonacci generator ; statistical characteristics ; android device ; BrainShield ; hybrid model ; malware detection ; Omnidroid ; image processing ; BOSS database ; ensemble classifier ; deep learning ; stegomalware ; traffic analysis ; network probe ; hash function ; SHA-3 ; FPGA ; cognitive security ; cyberattacks ; game software ; threat matrix computing ; evaluation function ; data modeling ; authentication ; bit template ; information-processing electronic device ; Poisson pulse sequences generators ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: The book provides a comprehensive overview of nanostructures and methods used to design biosensors, as well as applications for these biosensor nanotechnologies in the biological, chemical, and environmental monitoring fields. Biological sensing has proven to be an essential tool for understanding living systems, but it also has practical applications in medicine, drug discovery, food safety, environmental monitoring, defense, personal security, etc. In healthcare, advancements in telecommunications, expert systems, and distributed diagnostics are challenging current delivery models, while robust industrial sensors enable new approaches to research and development. Experts from around the world have written five articles on topics including:Diagnosing and treating intraocular cancers such as retinoblastoma; Nanomedicine in cancer management; Engineered nanomaterials in osteosarcoma diagnosis and treatment; Practical design of nanoscale devices; Detect alkaline phosphatase quantitatively in clinical diagnosis; Progress in the area of non-enzymatic sensing of dual/multi biomolecules; Developments in non-enzymatic glucose and H2O2 (NEGH) sensing; Multi-functionalized nanocarrier therapies for targeting retinoblastoma; Galactose functionalized nanocarriers; Sensing performance, electro-catalytic mechanism, and morphology and design of electrode materials; Biosensors along with their applications and the benefits of machine learning; Innovative approaches to improve the NEGH sensitivity, selectivity, and stability in real-time applications; Challenges and solutions in the field of biosensors.
    Keywords: advanced nanomaterials ; dual in-line sensing ; bi-functional properties ; non-enzymatic ; electrochemical sensing ; glucose and H2O2 ; nanotechnology ; bone diseases ; drug delivery ; nanocarriers ; osteosarcoma ; tumor-targeted ; retinoblastoma ; rare cancer ; surface-tailored multi-functionalized nanoparticles ; metallic nanoparticle ; tumor-suppressor gene mutation ; alkaline phosphatase ; terminal protection ; copper nanoparticle ; fluorescence ; biosensor ; electrochemical ; sensitivity ; amperometric ; voltammetric ; food quality monitoring ; machine learning ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 24
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: Animal production (e.g., milk, meat, and eggs) provides valuable protein production for human beings and animals. However, animal production is facing several challenges worldwide such as environmental impacts and animal welfare/health concerns. In animal farming operations, accurate and efficient monitoring of animal information and behavior can help analyze the health and welfare status of animals and identify sick or abnormal individuals at an early stage to reduce economic losses and protect animal welfare. In recent years, there has been growing interest in animal welfare. At present, sensors, big data, machine learning, and artificial intelligence are used to improve management efficiency, reduce production costs, and enhance animal welfare. Although these technologies still have challenges and limitations, the application and exploration of these technologies in animal farms will greatly promote the intelligent management of farms. Therefore, this Special Issue will collect original papers with novel contributions based on technologies such as sensors, big data, machine learning, and artificial intelligence to study animal behavior monitoring and recognition, environmental monitoring, health evaluation, etc., to promote intelligent and accurate animal farm management.
    Keywords: pig weight ; body size ; estimation ; deep learning ; convolutional neural network ; pig identification ; mask scoring R-CNN ; soft-NMS ; group-housed pigs ; audio ; dairy cow ; mastication ; jaw movement ; forage management ; precision livestock management ; equine behavior ; wearable sensor ; intermodality interaction ; class-balanced focal loss ; absorbing Markov chain ; cow behavior analysis ; prediction of calving time ; cow identification ; EfficientDet ; YOLACT++ ; cascaded model ; instance segmentation ; generative adversarial network ; machine learning ; automated medical image processing ; deep neural network ; animal science ; CT scans ; computer vision ; cow ; extensive livestock ; sensorized wearable device ; monitoring ; parturition prediction ; radar sensors ; radar signal processing ; animal farming ; computational ethology ; signal classification ; wavelet analysis ; dairy welfare ; hierarchical clustering ; mutual information ; precision livestock farming ; time budgets ; unsupervised machine learning ; wearables design ; animal-centered design ; animal telemetry ; modularity ; smart collar ; design contributions ; additive manufacturing ; low-frequency tracking ; commercial aviary ; laying hens ; false registrations ; tree-based classifier ; animal behaviour ; 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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  • 25
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: A collection of 18 scientific papers written in honor of Professor Karlheinz Schwarz's 80th birthday. The main topics include spectroscopy, excited states, DFT developments, results analysis, solid states, and surfaces.
    Keywords: density functional theory ; Coulomb systems ; excited states ; nodal variational principle ; DFT ; anatase TiO2(101) surface ; adsorption energy ; Bader charge ; helium atom ; screened Coulomb potential ; variational Monte Carlo method ; Lagrange mesh method ; comparison theorem ; TD-DFT ; MC-PDFT ; Lie–Clementi ; Colle–Salvetti ; OLEDs ; subphthalocyanines ; UV–visible spectra ; axial substituents ; peripheral substituents ; time-dependent DFT ; hexatetra-carbon ; electrical properties ; molecular aggregates ; singlet excitons ; triplet excitons ; TDDFT ; charge-transfer states ; charge-resonance states ; Frenkel states ; localized excitations ; diabatic states ; adiabatic states ; semiconductors ; oscillator strength ; hybrid exchange-correlation functional ; non-local potential ; statistics ; methods comparison ; benchmarking ; band gaps ; atomization energy ; DFT codes ; electronic structure calculation ; numerical accuracy and precision ; kinetic functional ; Yukawa potential ; periodic DFTB ; deMonNano ; graphene ; graphite ; benzene dimers ; deposited benzene ; supported clusters ; weighted mulliken charges ; LAPW method ; APW+lo method ; all-electron DFT ; density matrix functional embedding ; density-functional theory ; householder transformation ; He atomic basis sets ; helium dimer ; He2 potential well ; correlation energy ; complete basis set ; sigma basis set ; atomic multiplet theory ; crystal/ligand-field theory ; coordination compounds ; electronic structure ; Cu2OCl2 ; Cu2OBr2 ; Cu2OI2 ; oxyhalides ; magnetic couplings ; Néel temperature ; chemical pressure ; NMR ; machine learning ; zeolites ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PN Chemistry::PNR Physical chemistry
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  • 26
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-11
    Description: This book includes six chapters on wind turbine icing. For wind turbines operating in cold regions, icing often occurs on blade surfaces in winter. This ice accretion can change the aerodynamic shape of the blade airfoil, causing performance degradation and loss of power generation, even leading to operational accidents. This book focuses on the recent research progress on wind turbine icing. Chapters address such topics as the effect of icing conditions on the icing distribution characteristics of a blade airfoil for vertical-axis wind turbines, power loss estimation in wind turbines due to icing, wind turbine icing prediction methods, especially those using machine learning, the icing process of a single water droplet on a cold aluminum plate surface, the main theories of the icing adhesive mechanism, and theoretical and experimental studies on the ultrasonic de-icing method for wind turbine blades. This book is a valuable reference for researchers and engineers engaged in wind turbine icing and anti-icing research.
    Keywords: machine learning ; cfd ; numerical simulation ; artificial neural network ; wind energy ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-21
    Description: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe chronic health condition that is often misunderstood or ignored by health establishments. The lack of definitive diagnostic markers to separate ME/CFS patients from the healthy population as well as from other chronic disorders is problematic for both health professionals and researchers. A consortium of Australian researchers gathered to systematically understand ME/CFS, ranging from a deep analysis of clinical and pathology data to metabolomic profiles and the investigation of mitochondrial function. From this broad collaboration, a number of compelling insights have arisen that may form the basis of specific serum, blood, and/or urinary biomarkers of ME/CFS. This Special Edition reports on a conference centred on these biomedical discoveries, with other contributions, with a translation focus for predictive markers for ME/CFS diagnosis. By supporting health professionals with developments in diagnostics for this condition, the patients and their families will hopefully benefit from an improved recognition of the biomedical underpinnings of the condition and will be better able to access the care that is urgently required. This Special Edition contains a mix of speaker submissions and other accepted manuscripts that contributed to our objective of advancing biomedical insights to enable the accurate diagnosis of ME/CFS.
    Keywords: R5-920 ; RM1-950 ; fatigue syndrome ; n/a ; work rehabilitation ; tryptophan metabolism ; substrate inhibition ; myalgic encephalomyelitis ; 3-dioxygenase ; ME (Myalgic Encephalomyelitis) ; assessment ; myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) ; muscles ; hypoacetylation ; circadian rhythm ; immune system ; chronic ; CFS (Chronic Fatigue Syndrome) ; energy metabolism ; ME/CFS ; immunological ; cytokine ; bistability ; diagnosis ; biomarker ; symptoms ; kynurenine pathway ; inflammation and immunity ; metabolism ; neuro-inflammation ; pathology ; signaling ; exercise ; Epstein Barr virus ; methylhistidine ; hypothalamic–pituitary–adrenal axis ; potential biomarkers ; critical point ; inflammation ; histone deacetylation ; participatory research ; neurology ; neuroimmune ; activin ; mitochondria ; patient-driven questionnaire ; medical retirement ; machine learning ; prognosis ; gut microbiota ; post-exertional malaise ; chronic fatigue syndrome ; mathematical model ; reference intervals ; diagnostic biomarker ; indoleamine-2 ; bic Book Industry Communication::M Medicine
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  • 28
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This Urological Cancer 2020 collection contains a set of multidisciplinary contributions to the extraordinary heterogeneity of tumor mechanisms, diagnostic approaches, and therapies of the renal, urinary tract, and prostate cancers, with the intention of offering to interested readers a representative snapshot of the status of urological research.
    Keywords: renal cell carcinoma ; iron ; macrophages ; chelation therapy ; urothelial carcinoma ; transcriptome ; microtubule ; MAP1B ; prognosis ; KLF5 ; androgen receptor ; cell proliferation ; tumorigenesis ; prostate cancer ; precision medicine ; whole genome sequencing ; optical mapping ; therapy ; prostate carcinoma ; prostate mpMRI ; machine learning ; artificial intelligence ; deep learning ; neural network ; angiogenesis ; angiogenic growth factors ; antiangiogenic therapy ; renal tumors ; prevention ; α1-adrenoceptor antagonists ; anoikis ; vascularity ; research model ; oncogenes ; tumor suppressor genes ; MR-guided ; radiotherapy ; MRgRT ; stereotactic ablative radiotherapy ; stereotactic ablative radiation therapy (SABR) ; renal cell cancer ; RCC ; online adaptive ; [68Ga]Ga-PSMA PET/CT ; dual-time point imaging ; delayed imaging ; biphasic imaging ; lesion positivity rate ; CXCL9 ; PD1 ; PD-L1 ; stage T1 NMIBC ; prostatic neoplasms/mortality ; prostatic neoplasms/epidemiology ; SEER Program ; bladder cancer ; transurethral resection ; en-bloc resection ; CPT1A ; fatty acids ; serine ; androgen response ; ROS ; oxidative stress ; DONSON ; Downstream Neighbor of SON ; biomarker ; metastatic spread ; diagnosis ; differential diagnosis ; histopathology ; immunohistochemistry ; stroma signature ; patient-derived xenografts ; 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
    Language: English
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    Unknown
    Publication Date: 2023-05-10
    Description: The management of wildlife populations and their habitats are interdisciplinary fields that encompass many scientific disciplines that also impact the lives of people. Therefore, these are truly applied sciences where human dimensions play an important role.This book highlights the importance of conducting rigorous studies to design and implement the effective management and restoration of wild populations and their habitats. A new paradigm in conservation is developing that goes beyond the boundaries of protected areas to achieve the goal of sustainable development. The 16 papers in this book, including reviews and a project report, cover a broad range of topics, exploring a diversity of subjects that are representative of current practices and novel applications.We would like to thank both the MDPI publishers and editorial staff for their support and help during the process of editing this book, in addition to the authors for their contributions.
    Keywords: road safety ; roadkill ; clustering ; growth rate ; traffic intensity ; mitigation measures ; roadkill analysis ; movement patterns ; habitat characterisation ; multiple criteria ; multi-objective ranking ; environmental awareness ; machine learning ; random forest model ; structural equation modelling ; latent class analysis ; visitor mapping ; social–ecological systems ; cultural rural landscape ; protected areas ; rewilding ; rural socioeconomics ; forest expansion ; rural to urban land conversion ; biocultural heritage ; biodiversity ; naturalness ; land-cover change ; habitat quality ; InVEST ; ecosystem-based approach and assessment ; nature-based solution ; decision-making support ; national park management ; wildlife protection ; biodiversity conservation ; policy framework ; policy formulation ; China ; agricultural management ; amphibians ; beta diversity ; community ecology ; metacommunities ; constructed wetlands ; bats ; urban ecology ; long-term monitoring ; acoustics ; city parks ; community dynamics ; conservation evaluation ; at-risk species ; golden-winged warbler ; landowner incentives ; New England cottontail ; Natural Resources Conservation Service ; U.S. Department of Agriculture ; Working Lands for Wildlife ; camera-trapping ; conservation puma ; relative integrated anthropization index ; INRA ; South American grey fox ; habitat adaptability ; habitat model ; habitat selection ; habitat suitability ; use versus availability ; Maxent ; presence points ; GPS radio-collars ; anthropogenic variables ; species distribution models ; Spermophilus citellus ; maximum entropy modeling ; species distribution modeling ; climate change refugia ; urodela ; salamandridae ; caudata ; biosphere reserve ; habitat restoration ; species management ; life project ; activity patterns ; Lepus granatensis ; population decline ; niche ; Oryctolagus cuniculus ; roadside census ; predator–prey relationships ; spatio-temporal behavior ; abundance ; distance sampling ; population density ; R package ; wildlife survey ; uncertainty ; occupancy modeling ; road ecology ; n/a ; 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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    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: Artificial intelligence ; machine learning ; predictive model ; computational pharmacology ; translational medicine ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
    Keywords: tropical cyclone detection ; meteorological satellite images ; deep learning ; deep transfer learning ; generative adversarial networks ; image target detection ; multiple scales ; any angle object ; remote sensing of small objects ; point clouds ; 3D tracking ; state estimation ; Siamese network ; deep LK ; convolutional neural networks (CNNs) ; multilayer feature aggregation ; attention mechanism ; remote sensing image scene classification (RSISC) ; hyperspectral image classification ; variational autoencoder ; generative adversarial network ; crossed spatial and spectral interactions ; crater detection algorithm (CDA) ; R-FCN ; self-calibrated convolution ; split attention mechanism ; transfer learning ; remote sensing ; oriented object detection ; rotated inscribed ellipse ; remote sensing images ; keypoint-based detection ; gated aggregation ; eccentricity-wise ; object detection ; remote sensing image ; anchor free ; oriented bounding boxes ; deformable convolution ; three-dimensional radar imaging ; convolution neural network ; super-resolution ; side-lobe suppression ; terahertz radar ; aerial image generation ; satellite image generation ; structure map ; style vector ; high resolution image ; self-constructing graph ; semantic segmentation ; GAN ; image generation ; data augmentation ; remote sensing disaster image ; convolutional neural network ; double-stream structure ; feedback ; encoder–decoder network ; dense connections ; instance segmentation ; Swin transformer ; cascade mask R-CNN ; remote sensing image retrieval ; hashing algorithm ; binary code ; triplet ordinal relation preserving ; cross entropy ; feature distillation ; forest fire ; smoke segmentation ; Smoke-Unet ; residual block ; Landsat-8 ; band sensibility ; unsupervised domain adaptation ; bidirectional domain adaptation ; image-to-image translation ; generative adversarial networks (GANs) ; U-Net ; high-density laser scanning ; logging trails ; digital surface model ; canopy height model ; commercial thinning ; convolutional neural networks ; multiview ; satellite and UAV image ; joint description ; image matching ; neural network ; contextual information ; Anchor Free Region Proposal Network ; polar representation ; 3D object detection ; point cloud ; sampling ; single-stage ; rotated object detection ; angle-based detector ; angle-free framework ; rotated region of interests (RRoIs) ; representative points ; plastic ; UAVs ; contrastive learning ; mutual guidance ; spatial misalignment ; vehicle detection ; ANN ; automatic classification ; risk mitigation ; machine learning ; 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: Emotion is a complex phenomenon that varies from person to person. Different emotional states of a person can be inferred through external and internal reactions that change in different situations. Emotion recognition has become a research milestone in cognitive science, neuroscience, computer science, psychology, artificial intelligence, and other areas. Emotion recognition research uses non-physiological signals such as facial expression, speech, and body movement, as well as physiological signals and images such as electrical skin resistance (GSR), heart rate (HR), electrocardiogram (ECG), functional magnetic resonance imaging (fMRI), electroencephalogram (EEG) and magnetoencephalogram (MEG). This book provides a comprehensive overview of the different techniques used in emotion recognition and discusses recent developments, perspectives, and applications in the field.
    Keywords: machine learning ; deep learning ; feature extraction ; emotional intelligence ; creativity ; consumer behavior ; 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: 2024-04-09
    Description: This reprint focusses on Smartness, a multidisciplinary topic, which is examined from four perspectives: Sensors, IoT, and Data Generation; Data and Information Processing; Actuation; and Digital Systems and Infrastructure. We see smartness in the way sensing is embedded in a system, the way data and information are processed, how a system interacts internally and with its environment, and whether a system is ubiquitous or limited by space (cloud-based or edge-enabled). This reprint contains a total of 14 chapters, which are grouped according to their areas of application: mobility and transportation, healthcare, industrial environments, and other urban infrastructures. This book covers a range of topics, including mobility; healthcare; image analysis; permeable pavements; solid-waste management; sensor node and gateway architectures; cloud, fog, and edge computing; air-quality monitoring; thermal anomalies and smart helmets in industrial environments; smart airports; smart districts; smart travel choices; sensor cities; artificially intelligent cities; platform urbanism; and more.
    Keywords: artificial intelligence (AI) ; artificially intelligent city ; artificially intelligence commons ; smart city ; smart urban technology ; urban informatics ; sustainable urban development ; climate change ; pandemics ; natural disasters ; sensor city ; City 4.0 ; smart urbanism ; smart governance ; disruptive urban transition ; Internet-of-Things (IoT) ; technology giants ; sensors ; transit ; bus ; transfer ; smart card ; spatial analysis ; mode choice ; internet of everything (IoE) ; 6th generation (6G) networks ; artificial intelligence ; Distributed AI as a Service (DAIaaS) ; fog computing ; edge computing ; cloud computing ; smart airport ; smart districts ; PPE ; OHS ; risk detection ; naive Bayes ; support vector machine ; convolutional neural network ; deep learning ; microcontroller ; edge-fog-cloud computing ; Internet of Things ; robotics ; autonomous driving ; image registration ; smart sensor ; real time big data ; land-use ; air quality ; particulate matter (PM10 PM2.5) ; Intelligent Transportation Systems ; functional requirements ; machine learning ; model actionability ; model evaluation ; cloud server ; customized sensor node ; customized gateway ; FLoRa simulation ; LoRa range radio ; solid waste management ; smart cities ; big data ; event detection ; road traffic ; distributed machine learning ; automatic labeling ; social media ; data analytics ; social media analytics ; Arabic tweets ; 3D microstructure reconstruction ; permeable pavement ; generative adversarial networks ; tiny AI ; tiny ML ; distributed AI as a service (DAIaaS) ; skin disease diagnosis ; healthcare ; smart societies ; smart healthcare ; reference architecture ; TensorFlow ; visually impaired ; smart mobility ; LiDAR ; ultrasonic ; obstacle detection ; obstacle recognition ; assistive tools ; green computing ; sustainability ; Arduino Uno ; smart app ; 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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments.
    Keywords: big data applications ; data processing ; data visualization ; neural networks ; reduction ; coastal waters ; urban expansion ; remote sensing and GIS ; expansion types and rates ; major explanatory factors ; Miami metropolitan area ; cliff coastlines ; cliff retreat ; time-series analysis ; airborne laser scanner ; warm upwelling ; sea surface temperature ; numerical modelling ; winter ; southern Baltic Sea ; beach monitoring ; mobile terrestrial LiDAR ; intensity calibration ; beach surface moisture ; Baltic coast ; Poland ; CORINE Land Cover ; land cover flow ; urbanisation ; afforestation ; deforestation ; spatial analysis ; SDGs ; coastal habitats ; ecosystem monitoring ; land cover mapping ; random forest algorithm ; Sentinel-2 ; modified soil-adjusted vegetation index 2–MSAVI2 ; normalized difference water index 2–NDWI2 ; brightness index 2–BI2 ; oil spill ; remote sensing ; review ; machine learning ; deep learning ; trajectory modeling ; vulnerability assessment ; coastal geomorphology ; shoreline change ; coastal process ; monitoring ; geomatic techniques ; Po River Delta ; archival multi-temporal data ; coastline changes ; emerged/submerged surfaces ; land subsidence ; relative sea level rise 2100 ; land cover ; dune coast ; air photograph ; South Baltic Sea ; coastal monitoring ; estuaries ; IoT ; lidar ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: Agricultural production management is facing a new era of intelligence and automation. With developments in sensor technologies, the temporal, spectral, and spatial resolution from ground/air/space platforms have been notably improved. Optical sensors play an essential role in agriculture production management. Specifically, monitoring plant health, growth conditions, and insect infestation has traditionally involved extensive fieldwork. We believe that sensors, artificial intelligence, and machine learning are not simply scientific experiments but opportunities to make our agricultural production management more efficient and cost-effective, further contributing to the healthy development of natural–human systems. This reprint compiles the latest research on optical sensors and machine learning in agricultural monitoring, including related topics: Machine learning approaches for crop health, growth, and yield monitoring; Combined multisource/multi-sensor data to improve the crop parameters mapping; Crop-related growth models, artificial intelligence models, algorithms, and precision management; Farmland environmental monitoring and management; Ground, air, and space platforms application in precision agriculture; Development and application of field robotics; High-throughput field information survey; Phenological monitoring.
    Keywords: soil moisture content ; spectral processing technology ; hyperspectral ; principal component analysis ; feature parameters extraction ; yield estimation ; rice ; unmanned aerial vehicle (UAV) ; tasseled cap transformation ; precision agriculture ; weed identification ; YOLOv4-Tiny ; attention mechanism ; multiscale detection ; angle normalization ; vegetation canopy reflectance ; geostationary satellite ; path length correction ; Minnaert model ; GOCI ; winter wheat ; LSTM ; LAI ; deep learning ; land use ; land cover ; classification ; random forest ; Sentinel data ; SRTM ; feature selection ; accuracy ; validation ; unmanned aerial vehicle ; soybean ; convolutional neural network ; multispectral imagery ; fusarium head blight ; texture indices ; machine learning ; cropland ; multi-seasonal ; fractal feature ; feature extraction ; accuracy evaluation ; black soil ; UAV ; chlorophyll ; fractional vegetation cover ; maturity monitoring ; anomaly detection ; smart agriculture ; detection of apple leaf diseases ; YOLOv5 ; transformer ; CBAM ; crop type classification ; multi-temporal ; remote sensing ; dairy cows ; body condition score ; 3D TOF sensor ; non-contact evaluation ; recognize area of interest ; sugarcane clones ; canopy cover ; light interception ; biomass ; cane yield ; peanut southern blight ; reflection spectrum ; spectral index ; continuous wavelet transform ; VGNet ; corn diseases ; leaf detection ; lightweight ; transfer learning ; agriculture ; 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: Social media has the potential to provide rapid insights into unfolding public health emergencies such as infectious disease outbreaks. They can also be drawn upon for rapid, survey-based insights into various health topics. Social media has also been utilised by medical professionals for the purposes of sharing scholarly works, international collaboration, and engaging in policy debates. One benefit of using social media platforms to gain insight into health is that they have the ability to capture unfiltered public opinion in large volumes, avoiding the potential biases introduced by surveys or interviews. Social media platforms can also be utilised to pilot surveys, for instance, though the use of Twitter polls. Social media data have also been drawn upon in medical emergencies and crisis situations as a public health surveillance tool. A number of software and online tools also exist, developed specifically to aide public health research utilising social media data. In recent years, ethical issues regarding the retrieval and analysis of data have also arisen.
    Keywords: social media ; disordered eating behaviours ; body image ; female ; university students ; telemedicine ; carbon dioxide ; air pollutants ; vehicle emissions ; primary care ; machine learning ; teleconsultation ; remote consultation ; classification ; public health ; short video ; social network ; TAM ; cost analysis ; health technology assessment ; provider-to-provider telemedicine ; telehealth ; economic analysis ; questionnaires and surveys ; validation studies ; health personnel ; electronic nicotine delivery systems ; smoking ; twitter ; poor doctor-patient relationship ; healthcare consultation ; mobile context ; computer-mediated communication ; point-of-care systems ; ultrasonography ; traffic-related pollution ; primary health care ; acceptability of health care ; surveys and questionnaires ; health communication ; Spanish official medical colleges ; stakeholders ; Twitter ; systemic lupus erythematosus (SLE) ; network analysis ; topic modeling ; text analysis ; online media ; vaccination ; social marketing ; stroke ; prehospital emergency care ; training ; stroke code ; large vessel occlusion ; prehospital scales ; hearing loss ; latent topic ; LDA ; social Q&amp ; A ; public voice ; public health emergency ; policy evolution ; product innovation ; cooperative governance ; COVID-19 ; coronavirus ; masks ; transmission ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBN Public health & preventive medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Global health, conceived as a discipline, aims to train, research and respond to problems of a transboundary nature, in order to improve health and health equity at the global level. The current worldwide situation is ruled by globalization, and therefore the concept of global health involves not only health-related issues, but also those related to the environment and climate change. Therefore, in this Special Issue, the problems related to global health have been addressed from a bibliometric approach in four main areas: environmental issues, diseases, health, education and society.
    Keywords: social networks ; health ; young people ; bibliometric study ; scientometrics ; obesity ; interventions ; children ; youths ; pediatrics ; reclaimed water ; advanced oxidation process ; microorganisms ; concern emergent contaminant ; worldwide ; content analysis ; text mining ; diabetes ; QOL ; artificial intelligence ; machine learning ; bibliometric ; LDA ; HIV/AIDS ; quality of life ; global health ; public health ; scientometric study ; knowledge map ; visualization analysis ; CiteSpace ; COPD ; QoL ; medicinal plants ; drugs ; worldwide research ; bibliometrics ; traditional medicine ; asthma ; HRQoL ; Scival ; patents ; Spain ; Research and Development (R&amp ; D) ; social returns ; COVID-19 ; biomechanics ; musculoskeletal disorders ; RULA ; ergonomics ; applications ; climate change ; infectious diseases ; bibliometric analysis ; co-word analysis ; biclustering ; strategic diagram ; academic performance ; citation network ; motivation ; microplastics ; network analysis ; VOSviewer software ; research hotspots ; pulmonary disease ; musculoskeletal risks ; wastewater treatment ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-01-05
    Description: This book focuses on fundamental and applied research on construction project management. It presents research papers and practice-oriented papers. The execution of construction projects is specific and particularly difficult because each implementation is a unique, complex, and dynamic process that consists of several or more subprocesses that are related to each other, in which various aspects of the investment process participate. Therefore, there is still a vital need to study, research, and conclude the engineering technology and management applied in construction projects. This book present unanimous research approach is a result of many years of studies, conducted by 35 well experienced authors. The common subject of research concerns the development of methods and tools for modeling multi-criteria processes in construction engineering.
    Keywords: earned value method—EVM ; time variances ; cost variances ; schedule ; cadastre ; land surveyor ; construction surveying ; building layout ; polar coordinates ; stake-out methods ; total station ; construction reports ; construction contracts ; natural language processing ; machine learning ; simulation modeling ; bridge expansion and contraction installation (BECI) ; decision making (DM) ; technical condition assessment ; analytic hierarchy process (AHP) ; whale optimization algorithm ; Tent chaotic mapping ; Lévy flight ; resilience ; baseline schedule ; uncertainty ; taxonomy ; construction project ; PERT ; theory of constraint (TOC) ; drum-buffer-rope (DBR) ; construction schedule ; monitoring progress ; construction phase ; automated monitoring ; digital tools ; as-built ; as-planned ; efficiency ; risk ; randomization ; association analysis ; tabu search ; delay ; time schedules ; project risk ; construction project management ; Time-at-Risk (TaR) ; investment-construction process model ; Monte Carlo simulation ; decision-making process ; decision modelling in construction activities ; decisions in civil engineering ; liquid cooling system ; flow calibration ; differential pressure ; experimental method ; aircraft ; building information modelling (BIM) ; automatisation ; facilities design ; domestic plumbing and sanitation ; management ; project cost ; investment schedule ; risk mitigation ; randomness ; fuzziness ; health and safety control ; 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: 2022-06-21
    Description: This reprint includes contributions from leaders in the field of personalized medicine in ophthalmology. The contributions are diverse and cover pre-clinical and clinical topics. We hope you enjoy reading the articles.
    Keywords: subthreshold micropulse laser ; 577-nm laser ; laser fixed parameters ; diabetic retinopathy ; diabetic macular edema ; optical coherence tomography ; autofluorescence ; real-life ; diabetic macular oedema ; visual prognosis ; indicators ; personalized medicine ; age-related macular degeneration ; choroidal neovascularization ; classification ; machine learning ; type 2 diabetes ; retinopathy ; ethnicity ; general practice ; risk factors ; progression ; glycemic gap ; glucose variability ; ETDRS classification ; biomarkers ; phenotypes ; anti-vascular endothelial growth factor ; diabetic retinopathy severity scale ; panretinal leakage index ; neovascular age-related macular degeneration ; anti-VEGF therapy ; retinal thickness ; visual acuity ; variability ; leakage index ; microaneurysms ; intravitreal aflibercept ; neovascularization ; ultra-widefield fluorescein angiography ; retinal imaging ; quantitative biomarkers ; precision medicine ; autoantibodies ; AT1-receptor ; PAR1 ; VEGF-A ; VEGF-B ; VEGF-receptor 2 ; AMD ; complement system ; semi-quantitative multiplex profilin ; mass spectrometry ; C4 ; vitronectin ; factor I ; genetic variants ; metabolites ; HDL ; central area thickness ; biomarker ; microRNA ; anti-VEGF ; retina ; edema ; OCT ; tomography ; microphysiological systems ; blood-neural barriers ; neurovascular unit ; disease modeling ; 3D models ; organ-on-a-chip ; inner blood-retinal barrier ; 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: 2024-03-28
    Description: The need for energy is increasing and at the same time production from the conventional reservoirs is declining quickly. This requires an economically and technically feasible source of energy for the coming years. Among some alternative future energy solutions the most approachable source is from unconventional reservoirs. As the name “unconventional” implies it requires different and challenging approach to characterize and to develop such a resource. This special issue covers some of the technical challenges for developing unconventional energy sources from shale gas/oil, tight gas sand, and coalbed methane.
    Keywords: bedding fractures ; failure criterion ; lamina ; tight oil ; tight sandstone ; finite element simulation ; numerical simulation ; unconventional reservoir ; permeability ; group method of data handling ; artificial neural network ; well logs ; sensitivity analysis ; tight gas reservoir ; multi-fractured horizontal well (MFHW) ; unstable productivity model ; productivity forecast ; influencing factor analysis ; horizontal well with multiple finite-conductivity fractures ; elliptical-shaped drainage ; productivity index ; non-Darcy flow ; pressure-dependent conductivity ; reservoir properties ; void space structure ; porosity ; complex rocks ; NMR ; MICP ; CT ; SEM ; coal-bearing tight sandstone ; organic-rich clasts ; occurrence ; classifications ; formation mechanisms ; Ordos Basin ; hydraulic fracturing ; fracturing fluids ; fluids-rock interaction ; environmental implication ; history matching ; semianalytic model ; unconventional gas reservoirs ; multistage fractured horizontal wells ; fractal theory ; pore structure ; heterogeneity ; NMR measurements ; multifractal analysis ; shale reservoir ; elastic properties ; brittleness ; rock physics ; brittle spot identification ; shale gas ; reservoir characteristics ; gas content ; eastern Sichuan Basin ; the Da’anzhai member ; pulse decay method ; gas adsorption ; dual media ; unconventional core ; natural fracture ; influencing factor ; oil production ; carbonate rock ; basement reservoir ; Jizhong Sub-basin ; dynamic pore network modeling ; shale reservoirs ; water imbibition ; discrete element method ; modified fluid-mechanical coupling algorithm ; injection sequence ; well spacing ; stress shadow effect ; seismic location ; microseismic events ; waveform stacking ; induced seismicity ; CBM ; surfactant ; solid-free drilling fluid ; CBM reservoir wettability ; machine learning ; lithofacies ; umiat ; Alaska ; proppant transportation ; cross fractures ; CFD simulation ; dimensional analysis ; equilibrium proppant height ; coalbed methane ; Lattice Boltzmann method ; gas diffusion ; adsorption–desorption ; pore-scale ; clay minerals ; pore structures ; tight gas reservoirs ; Xujiaweizi Rift ; Northern Songliao Basin ; methane adsorption isotherm ; coal properties ; gradient boosting decision tree ; estimation model ; shale gas reservoir ; geology ; Gibbs excess adsorption ; supercritical adsorption ; gas viscosity ; high voltage spark discharge ; electrohydraulic effect ; electrical conductivity ; drilling ; rock damage ; pressure waves ; water fracturing ; turbulence effect ; Eulerian multiphase modeling ; proppant transport mechanism ; equilibrium height prediction model ; adaptive filtering ; complex noise canceling ; electromagnetic telemetry ; multifractured horizontal wells ; production analysis ; irregular stimulated region ; natural gas hydrate ; seismic modeling ; fractional derivatives ; gas geochemical characteristics ; noble gas ; shale gas evolution ; Large Igneous Province (LIP) ; gas loss ; geological structure ; gas controlling pattern ; neutral surface ; tectonic movement ; Bumu region ; seismic interpretation ; depositional environments characteristics ; Wheeler diagram ; seismic attributes ; heterogeneous sequence ; sample size ; neutron scattering ; mercury injection capillary pressure ; adsorption ; shale ; junggar basin ; hong-che fault zone ; carboniferous ; volcanic reservoir ; main controlling factors of hydrocarbon accumulation ; fracture ; vug ; micro CT ; carbonate ; wave velocity ; amorphous SiO2 ; X-ray diffraction ; X-ray fluorescence spectrometry ; scanning electron microscope ; quantitative analysis ; void ratio ; FEM ; ABAQUS ; matrix porosity ; kerogen porosity ; water saturation ; gas hydrate ; saturation ; deep learning ; recurrent neural network ; molecular simulation ; enhanced oil recovery ; methane ; shale petroleum ; technological development ; patent ; network analysis ; imbibition ; osmosis ; unconventional formations ; EOR ; water flooding ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools.
    Keywords: bfast ; Mann–Kendall ; Sen’s slope ; East Africa ; NDVI ; breakpoint analysis ; vegetation trends ; greening ; browning ; Kenya ; Uganda ; trend analysis ; land use ; land cover ; spatial heterogeneity ; mining development ; geographically weighted regression (GWR) ; Mann-Kendall ; arid and semi-arid areas ; salinization ; irrigated systems ; Niger River basin ; salinity index ; vegetation index ; TI-NDVI ; Sentinel-2 images ; high temporal resolution ; wind erosion modeling ; RWEQ ; GEE ; central Asia ; spatial-temporal variation ; land degradation ; archetypes ; self-organizing maps ; drivers ; savannah ; Nigeria ; reference levels ; REDD+ ; greenhouse gas emissions ; Xishuangbanna ; monitoring and reporting ; Normalised Difference Vegetation Index (NDVI) ; Vegetation Condition Index (VCI) ; drought ; land use-land cover ; remote sensing ; Botswana ; developing countries ; Google Earth Engine ; Landsat time series analysis ; semi-arid areas ; sustainable land management programmes ; precipitation ; breakpoints and timeseries analysis ; ecosystem structural change ; BFAST ; land degradation neutrality ; SDG ; land productivity ; Landsat ; vegetation-precipitation relationship ; soil organic carbon ; Kobresia pygmaea community ; unmanned aerial vehicle ; Gaofen satellite ; spatial distribution ; aridity index ; satellite-based aridity index ; remote sensing index ; salinized land degradation index (SDI) ; Amu Darya delta (ADD) ; satellite imagery ; gully mapping ; machine learning ; random forest ; support vector machines ; South Africa ; semi-arid environment ; shrub encroachment ; slangbos ; Earth observation ; time series ; Sentinel-1 ; Sentinel-2 ; Synthetic Aperture Radar (SAR) ; Soil Adjusted Vegetation Index (SAVI) ; Kyrgyzstan ; pastures ; MODIS ; land surface phenology ; drought impacts ; drought adaptation ; drought index ; vegetation resilience ; drought vulnerability ; standardized precipitation evapotranspiration index ; AVHRR ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-01
    Description: This book discusses various topics in pharmacovigilance. The first section addresses such topics as approaches to minimize adverse drug reactions, different stakeholders and their importance in pharmaceutical policy development, changing needs for pharmacovigilance in the African region, machine learning applications in pharmacovigilance, and pharmacovigilance of biological drugs. The second section discusses signal detection, which is a promising approach that helps in the early identification of new, rare drug reactions (desired or undesired).
    Keywords: machine learning ; data mining ; elderly ; biosimilar ; supervised learning ; mental disorders ; thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Today, modern Geotechnical Engineers, who in the past would have considered the phenomena occurring in the (primarily soil) environment, are faced with developments in environmental sciences that are becoming increasingly more detailed and sophisticated, with the natural phenomena and processes surrounding the civil engineering infrastructure being modeled, designed, monitored, and assessed in a more holistic way. This book brings together the state of the art in geotechnics with a focus on sustainable design, resilience, construction, and monitoring of the performance of geotechnical assets from ground investigations, through foundation and drainage design to soil stabilization and reinforcement. Engineers and scientists working in the fields of green infrastructure, nature-based solutions, sustainable drainage, eco-engineering, hydro-geology, landscape planning, plant science, environmental biology or bio-chemistry, earth sciences, GIS, and remote sensing are represented here by articles that show significant geotechnical components or applications. Case studies showcasing the application of the sustainable development principles (e.g., reuse, recycle, reduce; stakeholder engagement; public health; UN Global Sustainability Goals) in Geotechnics are also included in this book.
    Keywords: machine learning ; random forest ; particle swarm optimization ; Vietnam ; Seepage ; Earth-fill dam ; Experimental analysis ; Numerical analysis ; SEEP/W model ; Dam safety and sustainability ; highway construction ; environmental protection ; soil loss ; erosion control ; risk ; hazard ; vulnerability ; landslides ; multicriteria assessment ; analytical hierarchy process ; calcium sulfoaluminate cement ; stabilized soil ; unconfined compressive strength ; hydration products ; microstructure ; sustainability ; geosynthetics ; poly(lactic acid) ; biopolymers ; geogrids ; tensile strength ; 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: This book 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 testing of different materials and elements in civil engineering, from building materials to building structures. The current trend in the development of testing of materials and elements in civil engineering is mainly concerned with the detection of flaws and defects in concrete elements and structures, and acoustic methods predominate in this field. As in medicine, the trend is towards designing test equipment that allows one to obtain a picture of the inside of the tested element and materials. Interesting results with significance for building practices were obtained.
    Keywords: rock bolt ; grouting quality ; dynamic response ; natural frequency ; finite element method ; monitoring ; historical masonry wall ; hygrothermal processes ; internal insulation ; testing of building materials ; test uncertainty ; validation of test methods ; sustainable test methods ; recycling ; foamed asphalt mixtures with cement (FAC) ; base layer ; reclaimed asphalt pavement (RAP) ; fatigue durability ; GFRP ; FRP reinforcement ; shear ; capacity ; reinforced concrete beams ; column ; stiffness ; FRCM ; PBO mesh ; PBO–FRCM ; carpentry joints ; scarf and splice joints ; stop-splayed scarf joints (‘bolt of lightning’) ; static behaviour ; experimental research ; concrete ; non-destructive testing ; ultrasounds ; ultrasonic tomography ; acoustic methods ; defects ; diagnostic ; detection ; convolutional neural networks ; transfer learning ; monitoring FBG ; power transmission tower ; civil engineering ; X-ray microtomography ; microstructure characteristics ; infiltration damage ; high-strength concrete ; steel fibres ; flexural tensile strength ; fracture energy ; numerical analysis ; concrete floors ; compressive strength ; strength distribution ; industrial floors ; ultrasound tests ; ventilated facades ; large-scale facade model ; fire safety ; fiber cement board ; large-slab ceramic tile ; plasterboards ; moisture content ; hydration processes ; mechanical properties ; ultrasound measurements ; ESD resin ; expansion joint ; quasi-plastic material ; energy absorption ; asphalt mix ; compaction index ; volumetric parameters ; stiffness modulus ; moisture resistance ; roughness ; texture ; close-range photogrammetry ; bond strength ; random field generation ; semivariograms ; hybrid truss bridge ; steel–concrete connection joint ; mechanical behavior ; failure mode ; strain ; static test ; static elastic modulus ; dynamic elastic modulus ; machine learning ; P-wave ; S-wave ; resonance frequency test ; nondestructive method ; Al–Ti laminate ; fracture ; acoustic emission diagnostic ; pattern recognition ; clustering AE signal ; storage systems ; tab connector ; flexural test ; capable design moment ; restrained ring test ; autogenous shrinkage cracking ; concrete cracking test ; concrete shrinkage cracking test ; restrined ring calibration ; cement–fiber boards ; acoustic emission method ; k-means algorithm ; wavelet analysis ; fiber composites ; ground penetrating radar (GPR) ; HMA dielectric constant ; road pavement thickness estimation ; early age concrete ; damage processes detection before loading ; strength of structures ; aggregate ; classification ; wire mesh ; roundness ; tilting angle ; opening size ; concrete centrifugation ; morphology ; image processing ; porosity ; cement ; waste paper sludge ash (WPSA) ; controlled low-strength material (CLSM) ; unconfined compressive strength ; bearing capacity ; backfill material ; P-wave velocity ; amplitude attenuation ; resistivity ; CT scan ; sandstone ; damage variable ; nuclear magnetic resonance ; spin-lattice relaxometry ; proton ; hydration kinetics ; superplasticizer ; ready-mixed concrete ; construction material ; quality assessment ; conformity criteria ; statistical-fuzzy method ; FRTP ; rivet ; connection ; polyethylene pipe ; mechanical properties of polyethylene ; resistance strain ; computer simulation ; residual shear stress ; particle crushing ; ring shear test ; particle flow code (PFC2D) ; frictional work ; fibre-reinforced concrete ; recycled steel fibres ; micro-computed tomography ; scanning electron microscopy ; tensile strength ; reinforced concrete ; diagnostic testing ; corrosion ; carbonation ; galvanostatic pulse method ; phase composition analysis ; X-ray analysis ; thermal analysis ; quasi-brittle cement composites ; low-module polypropylene fibres ; elastic range ; digital image correlation ; Arcan shear test ; wood ; orthotropic shear modulus ; elastic-plastic material ; shear wave velocity ; sand ; bender elements test ; grain-size characteristics ; complex modulus ; shrinkage analysis ; reclaimed asphalt ; mineral–cement emulsion mixtures ; cement dusty by-products (UCPPs) ; degradation of glass panels ; effective area ratio ; relative mass loss ; visible light transmittance ; windblown sand ; wood-plastic composites ; methods of testing resistance to fungi ; methods of assessment ; ground-penetrating radar (GPR) ; non-destructive techniques (NDT) ; corrosion of reinforcement ; slip resistance ; granite floor ; slip resistance value ; ramp test ; acceptance angle ; sliding friction coefficient ; comparability of test methods ; wall temperature ; fibre bragg grating sensors ; freeze-thaw cycles ; signal analysis ; short-time Fourier transform ; fast Fourier transform ; brine ; sodium chloride ; X-ray ; partition walls ; brick walls ; bending strength ; cracking ; post-tension ; cable ; girder ; destructive test ; non-destructive test ; structural health monitoring ; safety ; monitoring fibre Bragg grating ; mining areas ; strain/stress distribution ; geopolymer concrete ; fly-ash ; bottom-ash ; neural network ; sustainability ; industrial waste management ; flexural strength ; cladding ; AE acoustic emission ; micro-events ; sound spectrum ; traditional and quasi-brittle cement composites ; residual-state creep ; saturation front ; landslides ; erosional stability ; laboratory testing ; grout mixtures ; groundwater ; test apparatus ; testing ; building materials ; elements ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.
    Keywords: TA1-2040 ; T1-995 ; optical sensor ; spectral analysis ; response surface sampling ; sensor evaluation ; electromagnetic induction ; multivariate water quality parameters ; mandarin orange ; crop inspection platform ; SPA-MLR ; object tracking ; feature selection ; simultaneous measurement ; diseases ; genetic algorithms ; processing of sensed data ; electrochemical sensors ; thermal image ; ECa-directed soil sampling ; handheld ; recognition patterns ; salt concentration ; clover-grass ; bovine embedded hardware ; weed control ; soil ; field crops ; vineyard ; connected dominating set ; water depth sensors ; SS-OCT ; wheat ; striped stem-borer ; silage ; geostatistics ; detection ; NIR hyperspectral imaging ; electronic nose ; machine learning ; virtual organizations of agents ; packing density ; data validation and calibration ; dataset ; Wi-SUN ; temperature sensors ; geoinformatics ; gas sensor ; X-ray fluorescence spectroscopy ; vegetable oil ; photograph-grid method ; Vitis vinifera ; WSN distribution algorithms ; laser-induced breakdown spectroscopy ; irrigation ; quality assessment ; energy efficiency ; wireless sensor network (WSN) ; geo-information ; Fusarium ; texture features ; weeds ; discrimination ; big data ; soil moisture sensors ; meat spoilage ; land cover ; stereo imaging ; near infrared sensors ; biological sensing ; compound sensor ; pest management ; moisture ; plant localization ; heavy metal contamination ; artificial neural networks ; spectral pre-processing ; moisture content ; apparent soil electrical conductivity ; data fusion ; semi-arid regions ; smart irrigation ; back propagation model ; wireless sensor network ; energy balance ; light-beam ; fluorescent measurement ; agriculture ; precision agriculture ; deep learning ; spectroscopy ; hulled barely ; dielectric probe ; RPAS ; water supply network ; rice leaves ; mobile app ; gradient boosted machines ; hyperspectral camera ; one-class ; nitrogen ; LiDAR ; total carbon ; chemometrics analysis ; rice ; agricultural land ; on-line vis-NIR measurement ; CARS ; obstacle detection ; stratification ; neural networks ; regression estimator ; Kinect ; proximity sensing ; distributed systems ; pest ; noninvasive detection ; texture feature ; soil mapping ; classification ; soil salinity ; visible and near-infrared reflectance spectroscopy ; germination ; computer vision ; hyperspectral imaging ; diffusion ; dielectric dispersion ; UAS ; random forests ; case studies ; total nitrogen ; thermal imaging ; cameras ; dry matter composition ; near-infrared ; salt tolerance ; deep convolutional neural networks ; soil type classification ; water management ; preprocessing methods ; wireless sensor networks (WSN) ; remote sensing image classification ; precision plant protection ; radar ; spatial variability ; GF-1 satellite ; plant disease ; naked barley ; leaf area index ; CIE-Lab ; change of support ; radiative transfer model ; 3D reconstruction ; plant phenotyping ; vine ; near infrared ; vegetation indices ; remote sensing ; greenhouse ; time-series data ; scattering ; sensor ; crop area ; speckle ; spatial data ; grapevine breeding ; wide field view ; partial least squares-discriminant analysis ; spiking ; area frame sampling ; chromium content ; machine-learning ; RGB-D sensor ; pest scouting ; PLS ; Capsicum annuum ; spatial-temporal model ; drying temperature ; boron tolerance ; ambient intelligence ; laser wavelength ; fuzzy logic ; dynamic weight ; landslide ; management zones ; real-time processing ; event detection ; crop monitoring ; apple shelf-life ; rice field monitoring ; wireless sensor ; birth sensor ; proximal sensor ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: The use of telemedicine and mobile devices is growing, and sensors might aid in creating creative solutions. Developing these solutions is crucial for monitoring senior citizens, lifestyles, and medical procedures. This Special Issue’s goal was to bring together academics and professionals in healthcare and medicine interested in using information and communication technologies (ICT) to serve people with special needs. The development of assistive technology for various users to follow sports and other activities is strongly tied to this study area. Data protection is crucial, and the development of these solutions for medical uses should be verified. The security and privacy of the information may be tied to other recognized research projects for their acceptability. ICT research has considerably improved quality of life and has fully assimilated all citizens into society through medical rehabilitation and assistive technology. The technologies and research fields that influence medical informatics include databases, networking, graphical user interfaces, data mining, machine learning, intelligent decision support systems, and specialized programming languages. Because mobile devices are commonly used for several everyday chores and are equipped with sensors that monitor various physical and physiological indicators, it is crucial to encourage the development of m-Health and e-Health solutions for healthcare practitioners. In this area, several solutions are now being developed. In addition, they can collaborate with emerging technologies for social assistance while enhancing life quality.
    Keywords: data privacy ; taxonomy ; IoT ; COVID-19 ; mobile application ; accelerometer sensor ; stand-up time ; total time ; aging ; linear-map convolutional neural network ; direct acyclic graph ; action recognition ; spatial feature ; temporal feature ; frailty ; home monitoring ; user-centered design ; usability ; user experience ; acceptance ; activity recognition ; Internet of Things ; smart house ; deep learning ; channel state information ; glaucoma screening ; retinal images ; segmentation ; classification ; precision nutrition ; food plans ; machine learning ; food logging ; Eight Hop Test ; systematic review ; measurement ; sensors ; diseases ; wrist-wearable device ; PPG processing ; physiological parameters ; web-based applications ; data analysis ; elderly monitoring ; successful aging ; gerontechnology ; AAL ; healthcare ; prevalidation ; deployment ; chronic heart failure ; large-scale pilot ; H2020 ; 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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    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 ; 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: 2024-03-27
    Description: Nowadays, forecast applications are receiving unprecedent attention thanks to their capability to improve the decision-making processes by providing useful indications. A large number of forecast approaches related to different forecast horizons and to the specific problem that have to be predicted have been proposed in recent scientific literature, from physical models to data-driven statistic and machine learning approaches. In this Special Issue, the most recent and high-quality researches about forecast are collected. A total of nine papers have been selected to represent a wide range of applications, from weather and environmental predictions to economic and management forecasts. Finally, some applications related to the forecasting of the different phases of COVID in Spain and the photovoltaic power production have been presented.
    Keywords: Direct Normal Irradiance (DNI) ; IFS/ECMWF ; forecast ; evaluation ; DNI attenuation Index (DAI) ; bias correction ; nowcast ; meteorological radar data ; optical flow ; deep learning ; Bates–Granger weights ; uniform weights ; (REG) ARIMA ; ETS ; Hodrick–Prescott trend ; Google Trends indices ; Himalayan region ; streamflow forecast verification ; persistence ; snow-fed rivers ; intermittent rivers ; costumer relation management ; business to business sales prediction ; machine learning ; predictive modeling ; microsoft azure machine-learning service ; travel time forecasting ; time series ; bus service ; transit systems ; sustainable urban mobility plan ; bus travel time ; learning curve ; forecasting ; production cost ; cost estimating ; semi-empirical model ; logistic map ; COVID-19 ; SARS-CoV-2 ; PV output power estimation ; PV-load decoupling ; behind-the-meter PV ; baseline prediction ; n/a ; 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: The Internet of Things (IoT) has emerged as a popular area of research and has piqued the interest of academics and scholars worldwide. As such, many works have been done on IoT in a variety of application areas. Written by leading experts in the field, this book serves as a showcase of the breadth of IoT research conducted in recent years for people who, while not experts in the field, do have prior knowledge of the IoT. The book also serves curious, non-technical readers, enabling them to understand necessary concepts and terminologies associated with the IoT.
    Keywords: artificial intelligence ; iot ; machine learning ; healthcare ; ai ; ehealth ; thema EDItEUR::U Computing and Information Technology::UD Digital Lifestyle and online world: consumer and user guides::UDF Email: consumer / user guides
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book introduces and provides solutions to a variety of problems faced by society, companies and individuals in a quickly changing and technology-dependent world. The wide acceptance of artificial intelligence, the upcoming fourth industrial revolution and newly designed 6G technologies are seen as the main enablers and game changers in this environment. The book considers these issues not only from a technological viewpoint but also on how society, labor and the economy are affected, leading to a circular economy that affects the way people design, function and deploy complex systems.
    Keywords: Industry 4.0 ; cognitive manufacturing ; cognitive load ; human–computer interaction ; 6GIIoE priorities ; 6GIIoE challenges ; 6GIIoE applications ; information system ; sequential methodology ; 6GIIoE theoretical framework ; circular economy ; circular building ; implementation strategies ; design strategies ; circular resource flows ; digital twin ; digital model ; system optimization ; predictive maintenance ; artificial and human intelligence ; security ; risks and risk management ; quality of life ; common welfare ; socio-political assessment ; assembly ; process planning systems ; concurrent engineering ; automotive industry applications ; manufacturing industry applications ; artificial intelligence ; sustainable development ; construction ; civil engineering ; machine learning ; construction engineering ; cognitive data intelligence ; cognitive healthcare ; tiny machine learning ; 6GCIoHE theoretical framework ; data science ; statistical data processing ; predictive analytics ; classification ; clustering ; labor productivity ; health management ; health-saving strategies ; electric power industry ; bridge ; expansion joint ; joint gap ; smart bridge maintenance equipment ; sensor ; structural health monitoring ; line-scan camera ; machine vision ; change management ; COVID-19 ; decision-support model ; digitization ; employee motivation ; employee satisfaction ; human resources ; software tool ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: 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: 2024-04-11
    Description: The book Green, Energy-Efficient and Sustainable Networks provides insights and solutions for a range of problems in the field of obtaining greener, energy-efficient, and sustainable networks. The book contains the outcomes of the Special Issue on “Green, Energy-Efficient and Sustainable Networks” of the Sensors journal. Seventeen high-quality papers published in the Special Issue have been collected and reproduced in this book, demonstrating significant achievements in the field. Among the published papers, one paper is an editorial and one is a review, while the remaining 15 works are research articles. The published papers are self-contained peer-reviewed scientific works that are authored by more than 75 different contributors with both academic and industry backgrounds. The editorial paper gives an introduction to the problem of information and communication technology (ICT) energy consumption and greenhouse gas emissions, presenting the state of the art and future trends in terms of improving the energy-efficiency of wireless networks and data centers, as the major energy consumers in the ICT sector. In addition, the published articles aim to improve energy efficiency in the fields of software-defined networking, Internet of things, machine learning, authentication, energy harvesting, wireless relay systems, routing metrics, wireless sensor networks, device-to-device communications, heterogeneous wireless networks, and image sensing. The last paper is a review that gives a detailed overview of energy-efficiency improvements and methods for the implementation of fifth-generation networks and beyond. This book can serve as a source of information in industrial, teaching, and/or research and development activities. The book is a valuable source of information, since it presents recent advances in different fields related to greening and improving the energy-efficiency and sustainability of those ICTs particularly addressed in this book
    Keywords: TA1-2040 ; T1-995 ; node speed ; linear recovery ; resource block allocation ; social awareness ; internet-of-things ; scheduling algorithm ; renewables ; neural network ; battery capacity ; energy awareness ; measurement structure ; optimization ; energy efficiency ; charging efficiency ; random structural matrices ; SDN ; water filling algorithm ; ONOS ; energy harvesting ; malware detection ; node density ; HetNets ; sustainability ; cooperative smart community ; adversarial samples ; spatial modulation ; NOMA ; 5G ; light-weight authentication ; green networking ; Device-to-Device (D2D) ; lightweight cipher ; mobile edge computing ; wireless power transfer ; adaptive link rate ; successive interference cancellation (SIC) ; directional charging vehicle ; self-interference cancellation ; proportional rate constraint ; inter-meeting time ; sustainable ; RWSN ; channel state information ; stochastic geometry ; networks ; green internet of things (IoT) ; PHY-layer ; IoT ; Markov chain ; traffic engineering ; QoS ; energy-efficient Ethernet ; power ; lightweight authentication ; energy aware routing ; authentication ; wired access ; amplify-and-forward ; software defined networking (SDN) ; image compressive sensing (CS) ; green ; edge computing ; LTE-A ; opportunistic networks ; RF Fingerprinting ; data centre ; multiple-input multiple-output ; Internet of Things ; machine learning ; peer discovery ; full-duplex ; industrial ; carbon footprint ; WSN ; imperfect CSI ; data center ; symbol error probability ; physical-layer authentication ; interference coordination ; clustering ; control and data plane ; wireless ; ICT ; bisection based optimal power allocation ; energy-efficiency ; consumer preferences ; real-time traffic ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint focuses on the current progress in sports medicine, with a specific interest in surgery, exercise therapy, and multi-disciplinary research. With the advancement of society, more attention is paid to the quality of life, which emphasizes the importance of sports and exercise. Correspondingly, there is a great need for sports medicine. This issue collected novel findings on sports medicine in surgery, conservative therapy, and the application of exercise training in other disorders
    Keywords: shoulder ; rotator cuff ; allografts ; demineralized bone matrix ; biologics ; diabetes mellitus ; aerobic training ; resistance training ; vascular function ; meta-analysis ; femoroacetabular impingement ; hip arthroscopy ; longitudinal capsulotomy ; femoroplasty ; labrum repair ; degenerative lumbar diseases ; albumin-to-alkaline phosphatase ratio ; spinal fusion rate ; prognostic marker ; arterial hypertension ; exercise hypertension ; blood pressure ; exercise testing ; sports injuries ; machine learning ; injury prediction ; sports monitorization ; elite football ; performance ; systemic inflammation ; physical endurance ; physical fitness ; maximal aerobic capacity ; gingivitis ; cardiac rehabilitation ; exercise therapy ; balance exercises ; cardiovascular diseases ; ACLR ; hamstring tendon with preserved tibial insertion ; MRI ; T2 ; cartilage volume ; gait retraining ; running-related injuries ; kinetics ; kinematics ; rehabilitation ; rotator cuff tear ; rotator cuff repair ; bone quality ; osteopenia ; osteoporosis ; anchor pullout ; pullout strength ; n/a ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-05
    Description: Beer is a beverage with more than 8000 years of history, and the process of brewing has not changed much over the centuries. However, important technical advances have allowed us to produce beer in a more sophisticated and efficient way. The proliferation of specialty hop varieties has been behind the popularity of craft beers seen in the past few years around the world. Craft brewers interpret historic beer with unique styles. Craft beers are undergoing an unprecedented period of growth, and more than 150 beer styles are currently recognized. This Special Issue, Brewing and Craft Beer, comprises nine different works by researchers from five continents (North America, South America, Europe, Africa, and Oceania). This Special Issue reflects thus a broad perspective on the most important questions that concern the researchers in different parts of the world.
    Keywords: QH301-705.5 ; QD415-436 ; Q1-390 ; polyphenols ; n/a ; nutrient ; audible sound ; wet milling ; brewing technology ; robotics ; fast-screening ; lactose ; image analysis ; bottle refermentation ; beer aging ; sensory attributes ; brewing ; automation ; bitterness ; stout beer ; beer ; craft beer ; foamability ; Safrari ; adjuncts ; fermentation rate ; barley milling ; preference ; germ ; beer wort ; machine learning ; carbonation ; quality ; FAN ; granulometry ; sensory evaluation ; coffee ; beer acceptability ; computer vision ; fermentation ; economic contribution analysis ; short-chain fatty acids ; local value chain ; AEDA ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering.
    Keywords: SVM ; budding rate ; UAV ; geometric consistency ; radiometric consistency ; point clouds ; ICP ; reflectance maps ; vegetation indices ; Parrot Sequoia ; artificial intelligence ; precision agriculture ; agricultural robot ; optimization algorithm ; online operation ; segmentation ; coffee leaf rust ; machine learning ; deep learning ; remote sensing ; Fourth Industrial Revolution ; Agriculture 4.0 ; failure strain ; sandstone ; digital image correlation ; Hill–Tsai failure criterion ; finite element method ; reference evapotranspiration ; moisture sensors ; machine learning regression ; frequency-domain reflectometry ; randomizable filtered classifier ; convolutional neural network ; U-Net ; land use ; banana plantation ; Panama TR4 ; aerial photography ; remote images ; systematic mapping study ; agriculture ; applications ; total leaf area ; mixed pixels ; Cabernet Sauvignon ; NDVI ; Normalized Difference Vegetation Index ; precision viticulture ; 3D model ; spatial vision ; fertirrigation ; teaching–learning ; spectrometry ; Sentinel-2 ; pasture quality index ; normalized difference vegetation index ; normalized difference water index ; supplementation ; decision making ; digital agriculture ; grape yield estimate ; berries counting ; Dilated CNN ; machine learning algorithms ; classification performance ; winter wheat mapping ; large-scale ; water stress ; Prunus avium L. ; stem water potential ; low-cost thermography ; thermal indexes ; canopy temperature ; non-water-stressed baselines ; non-transpiration baseline ; soil moisture ; andosols ; image processing ; greenhouse ; automatic tomato harvesting ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Various molecular techniques based on omics (transcriptomics, proteomics, genomics) and phylogenetics have been applied in biological sciences. Molecular dynamics and approaches evolved over time into various quantitative tools that allow researchers from multiple disciplines to design different studies. The molecular-based techniques can be comprehensive and systematic, as they allow identification, resolve genetic differences, molecular docking, and prediction models of ecological niches and taxonomic ranks. Investigating genomics, proteomics, and phylogenetic techniques utilize a novel class of DNA elements, such as microsatellites from mitochondria and chloroplast and retrotransposons, resulting in genetic variations using molecular data. In addition to this, the advantages and limitations of molecular approaches have been well studied and acknowledged. The combination of molecular phylogenetic and omics techniques and expression and pathways analysis may greatly increase our capacity to understand and develop new molecular mechanisms and stress responses in biological systems. Furthermore, these techniques offer extensive opportunities for researchers to develop targeted therapy approaches and disease diagnoses using molecular data. It is necessary to evaluate and explore how data from diverse molecular techniques can be applied to different biological studies. The study and applications of molecular approaches hold significant potential for advancing genomics, proteomics, and phylogenetic techniques in biological sciences.
    Keywords: autophagy-related protein ; degradation ; ubiquitin ; proteasome ; autophagy ; Bacillus thuringiensis ; Cry toxin ; nematicidal activity ; pore-formation ; diabetes ; vaccines ; clinical trials ; insulin ; GLP ; nitric oxide ; antioxidants ; metal-stress related transcripts ; rice ; Pb-stress ; Aurisin A ; beta-cyclodextrins ; inclusion complex ; lung cancer ; ruxolitinib ; JAK inhibitor ; rheumatoid arthritis ; molecular modeling ; TOR ; photosynthesis ; cell growth ; AZD8055 ; Auxenochlorella pyrenoidosa ; ovarian cancer ; somatic BRCA mutational status ; digital pathology ; machine learning ; artificial intelligence ; super-secondary structure ; 3β-corner ; folding nuclei ; structure stability ; H Ferritin subunit ; PRDX6 ; protein-protein interaction ; seed-specific transcription factors ; signaling pathways ; seed size ; seed development ; juvenile idiopathic arthritis ; transcriptome-wide association study ; gene-based association analysis ; enrichment analysis ; gene regulatory network ; computational cancer biology ; precision medicine ; oxaliplatin and capecitabine (XELOX) ; data bank ; AlphaFold 2.0 ; graph neural network ; protein features ; nasopharyngeal carcinoma ; bioinformatics ; genes ; melon ; CmSUN ; IQ67 domain ; expression analysis ; overexpression phenotype ; fruit shape regulation ; protein interaction ; smooth muscle titin ; protein aggregates ; amyloid aggregation ; amyloids ; cross-β ; 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: 2024-04-02
    Description: Higher education has been considered both an ‘engine’ for innovation and a ‘catalyst’ for sustainability development; the integration of both the innovation engine and sustainability catalyst roles are discussed in a recently published Special Issue on the theme of Higher Education in Innovation Ecosystems in the journal Sustainability. Based on 16 articles contributing to the Special Issue from various perspectives, the Special Issue editors have developed an overarching framework about the relationships between higher education and innovation ecosystems. In the framework, we re-define the concept of innovation ecosystem and identify emerging roles of universities in developing sustainable innovation ecosystems. Re-conceptualization of innovation ecosystems In the editorial of the Special Issue, innovation ecosystem is defined as: co-innovation networks in which actors from organizations concerned with the functions of knowledge production, wealth creation, and norm control interact with each other in forming co-evolution and interdependent relations (both direct or indirect) in cross-geographical contexts and through which new ideas and approaches from various internal and external sources are integrated into a platform to generate shared values for the sustainable transformation of society. Compared with most commonly cited definitions of innovation ecosystem, our definition highlights three new aspects of interactions in co-innovation networks: cross-sectoral, transnational, and indirect, drawing insights from the literature including innovation, geography, and biology studies. The roles of universities in innovation ecosystems The emerging roles of universities in innovation ecosystems are as follows: (1) The role of universities is changing from being a central player in technology transfer to being an anchor in knowledge exchange; (2) universities are assuming a new role in trust-building between actors in innovation ecosystems; and (3) universities are not merely an entrepreneurial universities but are also institutional entrepreneur in the innovation ecosystem. The three emerging roles all indicate that universities are becoming the catalysts for sustainable development in innovation ecosystems. Knowledge exchange is crucial for sustainability; trust is the foundation of the sustainable networks; social entrepreneurship is indispensable for sustainable social change. Evidence in wider contexts A total of 44 authors from 10 countries contributed to the discussions on the changing roles of higher education in innovation ecosystems from varying perspectives. They also report transformations within higher education and universities’ responses to both external and internal transformations. When addressing these issues, the studies provide both theoretical and methodological contributions to the research on higher education in innovation ecosystems. The 16 articles can be generally placed into four categories: (1) new demands for universities arising from the transformation in society toward innovation ecosystems, (2) transformations within higher education responding to emerging societal demands, (3) dynamics of the interaction of university with other innovation actors in a transnational context, and (4) academic and student mobility for higher education innovation. Calling for a new research agenda While societal changes demand broader roles of universities, they also call for and leads to substantial changes within the internal fabric of the university. The innovations in both society and the universities necessitate a renewed understanding of higher education in society, which has become a new research agenda in studies on innovation in higher education. We hope our Special Issue will inspire and encourage more scholars to join the research field.
    Keywords: transnational industry cooperation ; transnational university cooperation ; transnational innovation ecosystem ; EU–China ; science, technology and innovation cooperation ; transdisciplinary approach ; artificial intelligence ; machine learning ; Higher Education ; University ; Entrepreneurial competences ; Employability ; Theory of Planned Behaviour (TPB) ; Open Innovation ; business creation ; technology transfer ; innovation ; innovation ecosystem ; entrepreneurship education ; science and technology ; sustainability ; higher education ; educational innovation ; Mexico ; academic mobility ; knowledge transfer ; higher education innovation ; institutional environment ; postgraduate education ; education level ; discipline background ; graduation institution ; R&amp ; D investment ; triple helix ; synergy mechanism ; national system of innovation ; China ; Belt and Road Initiative ; developmental model of intercultural sensitivity ; general model of instructional communication ; instructional beliefs model ; intercultural communication competence model ; green GDP ; environment ; sustainable development ; global innovation systems ; Chinese research university ; faculty income ; academic labor market ; ordinary labor market ; joint R&amp ; D institute ; institutional logics ; China’s innovation system ; China’s transnational Triple Helix linkages ; problem-solving ; critical reflection ; knowledge integration ; social learning ; systemic thinking ; entrepreneurial university ; entrepreneurship ; influencing factors ; sustainable universities ; corporate sustainability ; tensions ; integrative framework ; Finnish universities ; higher education system ; social entrepreneurship ; entrepreneurial universities ; business model innovation ; socialist economies ; Cuba ; knowledge brokers ; knowledge intensive policies ; smart specialisation ; innovation ecosystems ; global talent ; social integration ; economic integration ; Chinese student ; Finland ; university ; third mission ; knowledge-based society ; global innovation networks ; thema EDItEUR::N History and Archaeology::NH History ; thema EDItEUR::J Society and Social Sciences::JN Education
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –
    Keywords: Traffic sign detection and tracking (TSDR) ; advanced driver assistance system (ADAS) ; computer vision ; 3D convolutional neural networks ; machine learning ; CT brain ; brain hemorrhage ; visual inspection ; one-class classifier ; grow-when-required neural network ; evolving connectionist systems ; automatic design ; bio-inspired techniques ; artificial bee colony ; image analysis ; feature extraction ; ship classification ; marine systems ; citrus ; pests and diseases identification ; convolutional neural network ; parameter efficiency ; vehicle detection ; YOLOv2 ; focal loss ; anchor box ; multi-scale ; deep learning ; neural network ; generative adversarial network ; synthetic images ; tool wear monitoring ; superalloy tool ; image recognition ; object detection ; UAV imagery ; vehicular traffic flow detection ; vehicular traffic flow classification ; vehicular traffic congestion ; video classification ; benchmark ; semantic segmentation ; atrous convolution ; spatial pooling ; ship radiated noise ; underwater acoustics ; surface electromyography (sEMG) ; convolution neural networks (CNNs) ; hand gesture recognition ; fabric defect ; mixed kernels ; cross-scale ; cascaded center-ness ; deformable localization ; continuous casting ; surface defects ; 3D imaging ; defect detection ; object detector ; object tracking ; activity measure ; Yolo ; deep sort ; Hungarian algorithm ; optical flows ; spatiotemporal interest points ; sports scene ; CT images ; convolutional neural networks ; hepatic cancer ; visual question answering ; three-dimensional (3D) vision ; reinforcement learning ; human–robot interaction ; few shot learning ; SVM ; CNN ; cascade classifier ; video surveillance ; RFI ; artefacts ; InSAR ; image processing ; pixel convolution ; thresholding ; nearest neighbor filtering ; data acquisition ; augmented reality ; pose estimation ; industrial environments ; information retriever sensor ; multi-hop reasoning ; evidence chains ; complex search request ; high-speed trains ; hunting ; non-stationary ; feature fusion ; multi-sensor fusion ; unmanned aerial vehicles ; drone detection ; UAV detection ; visual detection ; 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: 2022-05-06
    Description: This Special Issue focuses on the current state of pharmacogenomics (PGx) and the extensive translational process, including the identification of functionally important PGx variation; the characterization of PGx haplotypes and metabolizer statuses, their clinical interpretation, clinical decision support, and the incorporation of PGx into clinical care.
    Keywords: pharmacogenomics ; return of results ; genetic counseling ; qualitative ; pharmacogenetics ; implementation ; pharmacogenetics service ; screening ; pre-emptive ; personalized medicine ; precision medicine ; community pharmacy ; pharmacogenomic testing ; genetic privacy ; pharmaco-economics ; polymorphisms ; pharmacogenes ; pharmacogenomic ; machine learning ; adaptation ; human evolution ; US Food and Drug Administration ; clinical actionability ; clinical translation ; chronic kidney disease ; CYP3A5 ; polymorphism ; progression ; pharmacogenomics (PGx) ; pediatrics ; best practice alerts (BPAs) ; electronic health records (EHR) ; genomic indicators ; clinical decision support (CDS) ; phenotype ; genotype ; polypharmacy ; chronic disease ; medication management ; electronic medical record ; artificial intelligence ; 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: 2024-04-11
    Description: Transportation is one of the most crucial aspects across the world, supporting the daily life of human beings and the sustainable development of the whole of society. Generally, meteorology causes various impacts on transportation operation, safety and efficiency. In the context of global warming, increasing numbers of extreme weather and climate events (such as fog, icy roads, and extreme winds) have been detected worldwide and are expected to occur more frequently in the future. Meanwhile, extreme events, such as dense fog, rainstorm, and blizzard, tend to damage transportation and traffic facilities (such as express ways, port, airport, and high-speed railway) and induce serious traffic blocks and accidents. In recent decades, concentrated and continuous efforts have been made to carry out meteorological analyses regardless of urban traffic or transportation conditions, including those of highways, shipping, aviation, etc. A number of methods and techniques have been intensively developed to promote the qualities of both observations and forecasts. More recently, state-of-the-art machine learning frameworks have also been widely introduced into studies regarding transportation meteorology and many other fields.
    Keywords: transportation meteorology ; pavement temperature prediction ; deep learning ; BiLSTM ; attention mechanisms ; winter icing ; air pollution ; traffic vitality ; built environment ; spatial correlation ; spatial lag model ; phone signaling data ; air quality ; behavioral habits ; activity density ; population distribution ; land use mix ; wind forecast ; error decomposition ; bias ; distribution ; sequence ; urban meteorology ; observation ; forecast ; early warning ; review ; China ; low-level wind shear ; ensemble learning classifiers ; Bayesian optimization ; SHapley Additive exPlanations ; wind shear ; go-around ; machine learning ; dynamic ensemble selection ; civil aviation safety ; pilot reports ; self-paced ensemble ; Shapley additive explanations ; climate change ; climatology ; sea ice ; marginal sea ; East Asia ; time-series modeling ; pavement temperature ; nowcasting ; variation characteristics ; forecast validation ; relative humidity ; microwave radiometer data ; total rainfall ; precipitation duration ; vertical distribution ; Beijing–Tianjin–Hebei region ; rail breakage ; frequency ; high-speed railway ; Siberian high ; teleconnection ; temperature ; Qinling mountains ; rainfall ; change characteristics ; geographical factors ; highways ; road blockage ; fuzzy analytic hierarchy process ; CRITIC weight assignment method ; road network vulnerability ; spatiotemporal distribution ; precipitation forecast ; ConvLSTM ; PredRNN ; expressway ; agglomerate fog ; risk level prediction of fog-related accidents ; meteorological conditions ; road hidden dangers ; traffic flow conditions ; visibility ; Yellow Sea and Bohai Sea ; observation data ; 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::TR Transport technology and trades
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: This reprint addresses healthcare transformation towards personalized, participative, preventive, predictive, and precision medicine (5P Medicine) with the support of new technologies such as micro-, nano-, and bio-techniques, as well as artificial intelligence and learning systems. It focuses, therefore, on the representation and management of knowledge from different domains and their actors, using their methodologies and languages but also individual skills and experiences. The outcome is a system-oriented, architecture-centric, ontology-based, policy-driven approach allowing a formal representation and management of health ecosystems, including their integration and interoperability. Such development is accompanied by security, privacy, and ethical challenges to be resolved. The reprint describes the principles, methodologies, and standards for successfully managing the transformation of health and social care, illustrated by many practical examples and implemented use cases. The reprint is based on papers published in the context of the pHealth 2021 Conference in Genoa, Italy. However, the content goes far beyond the focus and size of the original papers.
    Keywords: syntactical parsing ; natural language processing ; electronic health records ; Node2Vec ; automatic text labeling ; graph algorithms ; mobile application ; mHealth ; digital technology ; emergency service ; hospital ; emergency department ; clinical laboratory information systems ; communication ; text messaging ; pediatrics ; postoperative risks ; aortic aneurysm ; integrated data ; predictive modeling ; feature extraction ; machine learning ; privacy ; trust ; modelling ; antecedents ; Fuzzy attractiveness rating ; didactic ; Healthcare IT ; citizens ; E-Learning ; digitalization ; digitization ; patient empowerment ; education ; healthcare communications ; surgical biobank ; post-traumatic arthritis ; osteomyelitis ; semantic data integration ; system theory ; biomedical ontologies ; knowledge representation ; ascending aortic dilatation ; aneurysm ; risk factors ; echocardiography ; social media ; physical activity ; chatbot ; health ; participatory health ; usability ; conversational agent ; behavior change ; genomics ; security ; modular architecture ; GIPAMS ; standards ; Markov model ; periprosthetic joint infection ; revision arthroplasty ; total hip replacement ; decision trees ; oncohematology ; epilepsy risk ; epilepsy modeling ; COVID-19 ; pneumonia ; dynamical Bayesian networks ; treatment trajectories ; auto ML ; eHealth ; data democratization ; health data infrastructure ; privacy-enhancing technologies ; hospital-acquired infections ; international coding system ; laboratory information systems ; information extraction ; stress detection ; individual learning ; centralized learning ; federated learning ; smartwatch ; health transformation ; ecosystems ; knowledge representation and management ; architecture ; n/a ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBN Public health & preventive medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: Gastrointestinal (GI) cancer is a major cause of morbidity and mortality in the world. Since early diagnosis and optimal treatment selection are crucial to improving the prognosis of these diseases, the discovery of useful biomarkers has the potential to greatly reduce their burden. Recent technical and mechanical developments have allowed for the detection of tiny differences in various factors modified in physical conditions, which could contribute to the discovery of novel biomarkers for some diseases.In this Special Issue, we aim to focus on novel biomarkers for GI cancers, including esophageal cancer, gastric cancer, colorectal cancer, liver cancer, pancreatic cancer and biliary cancer. In addition, any samples (tissue, blood, urine and feces) are useful as biomarker sources, although body-fluid-based biomarkers are promising as diagnostic biomarkers due to their noninvasiveness. This Special Issue aims to collect novel insights clarifying the current situation and future perspective in this field.
    Keywords: colorectal cancer ; advanced adenoma ; screening ; stool ; mRNA ; n/a ; cancer screening ; cirrhosis ; AFP ; machine learning ; MALDI-TOF ; proteomics ; CXCR4 ; prognosis ; overall survival ; rectal cancer ; neoadjuvant chemoradiation ; mouse model ; biomarkers ; urokinase plasminogen activator (uPA) ; urokinase plasminogen activator receptor (uPAR) ; plasminogen activator inhibitor type 1 (PAI-1) ; circulating tumour cell (CTC) ; gastric cancer ; oesophageal cancer ; serine proteases ; tumour microenvironment ; serpins ; biomarker ; chemoresistance ; liquid biopsy ; microRNA ; long non-coding RNA ; colorectal neoplasms ; cancer screening tests ; early detection of cancer ; precision medicine ; unfolded protein ; hepatocellular cancer ; GSVA ; unfolded protein score ; epigenetic regulation genes ; somatic mutations ; molecular genetic markers ; extracellular vesicles ; microbiome ; 16S rRNA amplicon ; metagenomics ; liver fibrosis ; hepatocellular carcinoma ; recurrence ; SHG/TPEF microscopy ; artificial intelligence ; advanced gastric cancer ; targeted therapy ; urinary miRNA ; miR-129-1-3p ; miR-566 ; bic Book Industry Communication::M Medicine::MJ Clinical & internal medicine::MJC Diseases & disorders::MJCL Oncology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: There has been significant growth in branches of industry directly related to new materials, such as metals, polymers, and composite materials. Considering the increase in material costs, it has become exceedingly important to produce lightweight constructions through the use of certified materials with appropriate mechanical properties. Many composite materials, especially in building engineering, are characterized by the use of waste materials, allowing them to meet environmental demands and often also positively affecting the performance (as well as mechanical) properties of the whole construction. A similar phenomenon has been noticed in polymers and metals, with the “ecologically friendly” factor having increasing influence in such materials. The main aim of our Special Issue was to gather novel research results concerning different materials available for all important industries—building engineering, the heavy industry, automotive, aerospace, and medicine. Such a general title has been proposed to also include different manufacturing technologies using various materials—conventional (milling, casting, forming, and turning) and novel (hybrid and additive manufacturing).
    Keywords: additive manufacturing ; powder bed fusion ; 316L stainless steel ; ultrasonic atomization ; gas atomization ; three-point bending ; polyamide-based composites ; fused filament fabrication ; concrete additives ; concrete fibers ; concrete strength tests ; threshold effect ; flake graphene ; graphene oxide ; reduced graphene oxide ; lubricants ; grease ; fatigue life prediction ; CuZn37 brass ; machine learning ; IPCs ; ceramic preform ; ceramic–elastomer composite ; silane coupling agent ; hot isostatic pressing (HIP) ; wettability ; mechanical properties ; mechanical engineering ; laser powder bed fusion ; 21 NiCrMo2 steel ; process parameters ; post-heat treatment ; torsional strength ; cellular structures ; 20MnCr5 Steel ; cement–glass composite bricks ; digital image correlation analysis ; material extrusion ; PET-G ; waste disposal ; hybrid additive manufacturing ; lattice structures ; hot isostatic pressing ; fatigue behaviour ; polymer–straw boards ; thermoplastic polymers ; annual plants ; 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::TGM Materials science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-03-21
    Description: This Special Issue includes papers on physical phenomena, such as wind-driven flows, coastal flooding, and turbidity currents, and modeling techniques, such as model comparison, model coupling, parallel computation, and domain decomposition. These papers illustrate the need for modeling coastal ocean flows with multiple physical processes at different scales. Additionally, these papers reflect the current status of such modeling of coastal ocean flows, and they present a roadmap with numerical methods, data collection, and artificial intelligence as future endeavors.
    Keywords: high performance computing ; HPC ; PETSc ; parallelization ; scalability ; parallel performance ; streams ; curvilinear ; non-hydrostatic ; ocean modeling ; GCCOM ; open boundaries ; domain decomposition ; variational data assimilation ; inverse problems ; shallow water equations ; boundary conditions ; mathematical modelling ; coastal ocean modelling ; computational methods ; hydrodynamic ; modeling ; sea level rise ; mobile application ; app ; crowdsourcing ; SCHISM ; Tidewatch ; StormSense ; Catch the King ; downstream blocking ; compound flooding ; coastal storm surge and inundation ; explosive lateral flooding ; hurricane inland and upland flooding ; coastal modelling ; operational forecasting ; model evaluation ; inter-comparison ; NEMO ; FVCOM ; Ocean Protection Plan ; turbidity current ; suspended sediment ; numerical model ; Gulf of Mexico ; cold front ; Hurricane Barry ; numerical simulation ; subtidal hydrodynamics ; multi-inlet ; volume flux ; multiscale ; multiphysics ; model coupling ; data collection ; machine learning ; 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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    Publication Date: 2024-04-11
    Description: heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.
    Keywords: TA1-2040 ; T1-995 ; TA170-171 ; geophysical monitoring ; data scarcity ; missing data ; climate extreme indices (CEIs) ; rule extraction ; Dataset Licensedatabase ; data assimilation ; data imputation ; support vector machines ; environmental observations ; multi-class classification ; earth-science data ; remote sensing ; magnetotelluric monitoring ; soil texture calculator ; machine learning ; ClimPACT ; invasive species ; species distribution modeling ; 3D-Var ; ensemble learning ; data quality ; water quality ; microhabitat ; k-Nearest Neighbors ; Expert Team on Climate Change Detection and Indices (ETCCDI) ; decision trees ; processing ; attribute reduction ; Expert Team on Sector-specific Climate Indices (ET-SCI) ; core attribute ; rough set theory ; GLDAS ; arthropod vector ; environmental modeling ; statistical methods ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: This Special Issue publishes the latest advances and developments concerning the modelling of flooding in urban areas and contributes to our scientific understanding of the flooding processes and the appropriate evaluation of flood impacts. This issue contains contributions of novel methodologies including flood forecasting methods, data acquisition techniques, experimental research in urban drainage systems and/or sustainable drainage systems, and new numerical and simulation approaches in nine papers with contributions from over forty authors.
    Keywords: machine learning ; flash flood ; GIS ; Iran ; decision trees ; ensemble techniques ; manhole flooding ; urban flooding ; grid-based modeling ; SWWM ; FIRM ; pollutant transport ; hydraulic structures ; urban drainage ; CFD ; dual drainage ; Iber ; SWMM ; hazard ; artificial neural network ; resilient backpropagation ; multistep urban flood forecast ; demographic change ; urbanization ; flooding ; drainage system ; vulnerability ; Sub-Saharan Africa ; Antananarivo ; parameterised power-linear model ; hyper concentration ; dilute concentration ; suspended sediment transport ; flood ; sediment size parameter ; rouse number ; mean concentration ; flow depth ; urban flood modeling ; porosity ; shallow-water model ; urban flood management ; flood forecasting ; weather radar ; integrated hydraulic modeling ; and evacuation lead time ; 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: 2023-07-14
    Description: Advancements in medical imaging modalities have resulted in increasing the importance and demand of pediatric radiology. This reprint showcases various examples of advanced research in pediatric radiology and nuclear medicine. These include the use of medical imaging modalities such as computed tomography, general radiography, magnetic resonance imaging, positron emission tomography, single-photon emission computed tomography, and ultrasound for diagnosis, as well as the performance of artificial intelligence (AI) in computer-aided detection and diagnosis in the pediatric population. The radiation dose issue of pediatric radiological examinations and emerging AI technology for dose reduction, as well as the use of three-dimensional printing based on medical images for pediatric surgical planning, healthcare professional education, and patient–clinician communication are also covered.
    Keywords: as low as reasonably achievable ; computed tomography ; convolutional neural network ; deep learning ; dose reduction ; generative adversarial network ; image processing ; machine learning ; medical imaging ; noise ; contrast-enhanced ultrasound ; head ultrasound ; brain death ; infants ; ancillary test ; child ; paediatric ; infant ; adolescent ; chest X-ray ; CXR ; chest radiography ; COVID-19 ; SARS-CoV-2 ; coronavirus ; biliary atresia ; ultrasonography ; diagnostic accuracy ; intraoperative cholangiography (IOC) ; diagnostic performance ; elastography ; three-dimensional printing ; congenital heart disease ; children ; model ; personalized medicine ; application ; confusion matrix ; disease identification ; image interpretation ; pneumonia ; artificial intelligence (AI) ; deep learning (DL) ; paediatric pneumonia ; chest radiograph ; computer-aided detection (CAD) ; cumulative ; radiation dose ; acute tonsillitis ; shear wave elastography ; stiffness ; pediatric ; magnetic resonance imaging ; infection ; neck ; emergency medicine ; 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: 2023-03-07
    Description: In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
    Keywords: tropical cyclone detection ; meteorological satellite images ; deep learning ; deep transfer learning ; generative adversarial networks ; image target detection ; multiple scales ; any angle object ; remote sensing of small objects ; point clouds ; 3D tracking ; state estimation ; Siamese network ; deep LK ; convolutional neural networks (CNNs) ; multilayer feature aggregation ; attention mechanism ; remote sensing image scene classification (RSISC) ; hyperspectral image classification ; variational autoencoder ; generative adversarial network ; crossed spatial and spectral interactions ; crater detection algorithm (CDA) ; R-FCN ; self-calibrated convolution ; split attention mechanism ; transfer learning ; remote sensing ; oriented object detection ; rotated inscribed ellipse ; remote sensing images ; keypoint-based detection ; gated aggregation ; eccentricity-wise ; object detection ; remote sensing image ; anchor free ; oriented bounding boxes ; deformable convolution ; three-dimensional radar imaging ; convolution neural network ; super-resolution ; side-lobe suppression ; terahertz radar ; aerial image generation ; satellite image generation ; structure map ; style vector ; high resolution image ; self-constructing graph ; semantic segmentation ; GAN ; image generation ; data augmentation ; remote sensing disaster image ; convolutional neural network ; double-stream structure ; feedback ; encoder–decoder network ; dense connections ; instance segmentation ; Swin transformer ; cascade mask R-CNN ; remote sensing image retrieval ; hashing algorithm ; binary code ; triplet ordinal relation preserving ; cross entropy ; feature distillation ; forest fire ; smoke segmentation ; Smoke-Unet ; residual block ; Landsat-8 ; band sensibility ; unsupervised domain adaptation ; bidirectional domain adaptation ; image-to-image translation ; generative adversarial networks (GANs) ; U-Net ; high-density laser scanning ; logging trails ; digital surface model ; canopy height model ; commercial thinning ; convolutional neural networks ; multiview ; satellite and UAV image ; joint description ; image matching ; neural network ; contextual information ; Anchor Free Region Proposal Network ; polar representation ; 3D object detection ; point cloud ; sampling ; single-stage ; rotated object detection ; angle-based detector ; angle-free framework ; rotated region of interests (RRoIs) ; representative points ; plastic ; UAVs ; contrastive learning ; mutual guidance ; spatial misalignment ; vehicle detection ; ANN ; automatic classification ; risk mitigation ; machine learning ; 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 | Palgrave Macmillan
    Publication Date: 2023-11-17
    Description: This open access book presents three future consumption trends—technology, sustainability, and wellbeing—and discusses what impact those trends will have on the ways we shop. What will be important to the consumers of the future? And how will their retail experiences look and feel? Will technology, sustainability, and wellbeing trends fundamentally change how we consume? And how should retail managers respond to these trends in order to provide the customer experiences of the future? Blending academic perspectives with reflections from innovative retailers, this book explores all these questions and more. Essential reading for retail managers who want to know how future consumption trends will affect the industry, this book also benefits students and researchers of retail and consumption who want to better understand how these interdependent fields are linked.
    Keywords: consumer behaviour ; Retail ; sustainability ; digital ; artificial intelligence ; machine learning ; bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJS Sales & marketing ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNP Distributive industries
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-01-05
    Description: The aim of carbon capture, utilization, and storage (CCUS) is to reduce the amount of CO2 released into the atmosphere and to mitigate its effects on climate change. Over the years, naturally occurring CO2 sources have been utilized in enhanced oil recovery (EOR) projects in the United States. This has presented an opportunity to supplement and gradually replace the high demand for natural CO2 sources with anthropogenic sources. There also exist incentives for operators to become involved in the storage of anthropogenic CO2 within partially depleted reservoirs, in addition to the incremental production oil revenues. These incentives include a wider availability of anthropogenic sources, the reduction of emissions to meet regulatory requirements, tax incentives in some jurisdictions, and favorable public relations. The United States Department of Energy has sponsored several Regional Carbon Sequestration Partnerships (RCSPs) through its Carbon Storage program which have conducted field demonstrations for both EOR and saline aquifer storage. Various research efforts have been made in the area of reservoir characterization, monitoring, verification and accounting, simulation, and risk assessment to ascertain long-term storage potential within the subject storage complex. This book is a collection of lessons learned through the RCSP program within the Southwest Region of the United States. The scope of the book includes site characterization, storage modeling, monitoring verification reporting (MRV), risk assessment and international case studies.
    Keywords: geologic CO2 sequestration ; CO2 and brine leakage ; underground source of drinking water ; risk assessment ; response surface methodology ; early detection criteria ; multi-objective optimization ; CO2-WAG ; machine learning ; numerical modeling ; hybrid workflows ; morrow ; Farnsworth ; Anadarko ; incised valley ; geological carbon sequestration ; reactive surface area ; mineral trapping ; enhanced oil recovery with CO2 (CO2-EOR) ; geochemical reactions ; workflow ; workshop ; process influence diagram ; response surface model ; polynomial chaos expansion ; NRAP ; relative permeability ; geologic carbon storage ; multi-phase flow simulation ; life cycle analysis ; CO2-enhanced oil recovery ; anthropogenic CO2 ; global warming potential ; greenhouse gas (GHG) ; carbon storage ; CO2-EOR ; CO2 sequestration ; geomechanics ; reservoir fluid flow modelling ; tightness of caprock ; CO2 leakage ; threshold pressure ; reactive solute transport ; multi-phase fluid flow ; Farnsworth Unit ; STOMP ; GEM ; TOUGHREACT ; 4D ; time lapse ; CO2 ; EOR ; WAG ; sequestration ; monitoring ; carbon sequestration ; caprock integrity ; noble gas migration ; seal by-pass ; carbon dioxide storage ; storage efficiency factor ; probabilistic ; expectation curve ; Monte Carlo ; Farnsworth Field ; petroleum system modeling ; CO2 migration ; 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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    Springer Nature | Humana
    Publication Date: 2024-04-05
    Description: This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Comprehensive and cutting, Machine Learning for Brain Disorders is a valuable resource for researchers and graduate students who are new to this field, as well as experienced researchers who would like to further expand their knowledge in this area. This book will be useful to students and researchers from various backgrounds such as engineers, computer scientists, neurologists, psychiatrists, radiologists, and neuroscientists.
    Keywords: machine learning ; deep learning ; brain disorders ; neurology ; psychiatry ; data science ; neural networks ; statistical learning ; neuroimaging ; clinical data ; biomarkers ; omics ; electronic health records ; mobile devices ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: As the most heavily populated areas in the world, coastal zones host the majority and some of the most important human settlements, infrastructures and economic activities. Harbour and coastal structures are essential to the above, facilitating the transport of people and goods through ports, and protecting low-lying areas against flooding and erosion. While these structures were previously based on relatively rigid concepts about service life, at present, the design—or the upgrading—of these structures should effectively proof them against future pressures, enhancing their resilience and long-term sustainability. This Special Issue brings together a versatile collection of articles on the modelling of harbour and coastal structures, covering a wide array of topics on the design of such structures through a study of their interactions with waves and coastal morphology, as well as their role in coastal protection and harbour design in present and future climates.
    Keywords: beach morphology ; beach nourishment performance ; sustainable development ; General Shoreline beach model ; United Arab Emirates ; Saadiyat Island ; breakwater ; extreme learning machine ; stability assessment ; machine learning ; column-stabilized fish cage ; horizontal wave force ; least squares method ; hydrodynamic coefficient ; vertical breakwater ; reliability analysis ; overall stability ; sliding failure ; overturning failure ; bearing capacity analysis ; breakwater’s foundation failure ; rubble-mound ; zero-freeboard ; porous-media ; immersed-boundary ; level-set ; Smagorinsky subgrid scale model ; wave reflection ; wave transmission ; wave overtopping ; wave setup ; Nowshahr port ; field measurements ; numerical simulation ; wave ; current ; sediment transport ; rubble mound breakwaters ; historical review ; damage measurement ; damage characterization ; damage ; damage model ; damage progression ; input reduction ; wave schematization ; pick-up rate ; MIKE21 CM FM ; long-term morphological modelling ; numerical model ; OpenFOAM ; scour ; vertical breakwaters ; mortar-grouted riprap revetment ; full-scale hydraulic tests ; design of revetments ; Balearic Islands ; Boumerdès ; current speed ; harbor ; tsunami ; model uncertainty ; reliability ; pile settlement ; piles in granular soil ; base resistance ; skin friction ; t-z curves ; climate change ; coastal flooding ; coastal structures ; numerical modelling ; Boussinesq equations ; 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: 2022-02-24
    Description: This special issue on the genetics of Alzheimer's disease was edited by Drs. Laura Ibanez and Justin Miller in 2021. It contains 10 original articles and reviews that help readers understand specific genetic contributions to Alzheimer's disease and how genetics will play a role in future Alzheimer's disease research.
    Keywords: Alzheimer disease ; expression quantitative trait loci (eQTL) ; rare variants ; set-based eQTL ; SKAT-O ; pathways ; immune system ; inflammation ; ROSMAP ; ADNI ; complement ; complement receptor 1 ; clusterin ; late-onset Alzheimer’s disease ; genetics ; neuroinflammation ; Alzheimer’s disease ; cytokines and growth factors ; genome-wide association study (GWAS) ; Polygenic Risk Score (PRS)-based analysis ; TOMM40 gene ; RNA transcription ; pseudogene ; mitochondrial dysfunction ; ITIM ; ITAM ; SIGLEC14 ; SIGLEC5 ; copy number variation ; CNV ; GWAS ; long non-coding RNA ; biomarkers ; peripheral system ; amyloid β ; tau ; APOE ; TREM2 ; OMICS ; therapeutics ; pairwise feature correlation ; feature reduction ; machine learning ; n/a ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: As we move further into the 21st century, despite the fact that new technologies have emerged, machining remains the key operation to achieve high productivity and precision for high-added value parts in several sectors, but recent advances in computer applications should close the gap between simulations and industrial practices. This book, “Machining Dynamics and Parameters Process Optimization”, is oriented toward the different strategies and paths when it comes to increasing productivity and reliability in metal removal processes. The topics include the dynamic characterization of machine tools, experimental dampening techniques, and optimization algorithms combined with signal monitoring.
    Keywords: CNC parameters ; machining mode ; high speed ; high accuracy ; high surface quality ; five-axis linear-segment toolpath ; path smoothing ; B-spline curve-fitting ; path synchronization ; feedrate scheduling ; flute-grinding ; evolution algorithms ; wheel location and orientation ; thin-floor machining ; chatter ; magnetorheological damper ; bull-nose end mill ; tool wear monitoring ; milling ; complex part ; deep learning ; autoencoder ; deep multi-layer perceptron ; tool condition monitoring ; tool change policy ; Industry 4.0 ; machine learning ; CNN ; AI ; additive manufacturing ; thin walled machining ; dynamics ; machining cycle optimization ; multivariable tool ; stable peninsula ; homotopy perturbation method ; machining robot ; natural frequency prediction ; model optimization ; dynamic performance ; stability ; machining ; grinding ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    KIT Scientific Publishing
    Publication Date: 2023-12-20
    Description: This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fully Bayesian approach for efficient RL in continuous-valued state and action spaces when no expert knowledge is available. PILCO takes model uncertainties consistently into account during long-term planning to reduce model bias. Second, we propose principled algorithms for robust filtering and smoothing in GP dynamic systems.
    Keywords: QA75.5-76.95 ; autonomous learning ; Gaussian processes ; control ; machine learning ; Bayesian inference ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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    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: Dementia ; machine learning ; biomarkers ; Structural image analysis ; Functional image analysis ; Diagnosis and prognosis ; 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::PSAN Neurosciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: The adequate assessment of key apparatus conditions is a hot topic in all branches of industry. Various online and offline diagnostic methods are widely applied to provide early detections of any abnormality in exploitation. Furthermore, different sensors may also be applied to capture selected physical quantities that may be used to indicate the type of potential fault. The essential steps of the signal analysis regarding the technical condition assessment process may be listed as: signal measurement (using relevant sensors), processing, modelling, and classification. In the Special Issue entitled “Advances in Sensors and Sensing for Technical Condition Assessment and NDT”, we present the latest research in various areas of technology.
    Keywords: pulse compression ; scattering ; attenuation ; insulation ; ultrasonic testing ; OLTC ; AE sensor ; acoustic emission ; feature extraction ; supervised classification ; machine learning ; contrast-enhanced ultrasound ; muscle perfusion ; Nakagami parameter ; compounding Nakagami imaging ; low-frequency sensor ; power transformer ; low-frequency noise ; genetic algorithm ; geometric layout of railway track ; track axis identification ; tramway loop ; route’s polygon ; GNSS mobile measurements ; vibroarthography ; VAG ; knee joint ; spectral features ; frequency analysis ; non-invasive examination ; lateral temperature gradient ; temperature field ; boundary conditions ; solar radiation intensity ; temperature monitoring ; non-destructive evaluation ; eddy current ; 3D sensing ; inverse problem ; wavelet transform ; principal component analysis ; neural network ; incubation ; spectrum ; image processing ; ROC curve ; infrasound measurement system ; wind turbine ; infrasound correlation analysis ; measuring scale ; thermoelastic deformation ; coefficient of thermal expansion ; elastic waves ; laser ultrasound ; Fizeau fiber interferometer ; defect identification ; high-current pulses ; current measurement ; high-current shunts ; circuit modeling ; Rogowski coil ; electrodynamic accelerators ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Smart textiles are the textiles that are sensitive to any environmental conditions and can respond accordingly. Using passive and active coatings to generate high sensitivity to textiles is among the most recent research trends by engineers around the World. This has resulted in expansion in the application of smart textiles in various industrial fields including medicals, electronics and protective clothing. The aim of this special issue is to introduce the most state-of-the-art research and review articles by distinguished researchers in the field of smart coatings on textiles. The guest editor hopes that content will be useful for researchers, students and companies for continuation of research and development with the concept of smart textiles.
    Keywords: TA1-2040 ; T1-995 ; TA401-492 ; chitosan ; pilling ; cyclodextrin ; polypropylene ; actuator ; UHMWPE ; hydrophobic ; separation ; reactive vapor deposition ; e-textiles ; image processing ; fiber ; conducting polymers ; conductive coatings ; dip coating technique ; textile ; triboelectricity ; smart textiles ; hernia meshes ; microgel ; optical fiber sensors ; polymer ; nanoparticle-laden elastomer ; touch sensor ; textile electronics ; structural color ; PLA fiber ; wearable technology ; carbon nanotubes ; electrospinning ; assembly ; photonic crystal ; electrospun nanofibers ; plasma treatment ; coating ; nanoparticle assemblies ; sodium alginate ; flexible electronics ; Janus material ; machine learning ; polymer actuators ; oxygen-plasma treatment ; polydopamine ; plain weave ; absorbant ; surface functionalization ; penetration resistance ; lab-on-fiber technology ; layer-by-layer method ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    Amsterdam University Press
    Publication Date: 2022-05-02
    Description: Profiling the European citizen: why today's democracy needs to look harder at the negative potential of new technology than at its positive potential.
    Keywords: Fundamental rights ; machine learning ; transparency ; automated decision-making ; presumption of innocence ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-07-06
    Description: This book focuses on a variety of interdisciplinary perspectives concerning the theory and application of artificial intelligence (AI) in medicine, medically oriented human biology, and healthcare. The list of topics includes the application of AI in biomedicine and clinical medicine, machine learning-based decision support, robotic surgery, data analytics and mining, laboratory information systems, and usage of AI in medical education. Special attention is given to the practical aspect of a study. Hence, the inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly highlighted.
    Keywords: computational intelligence ; medical assistance ; instance-based learning ; healthcare ; clinical decision support systems ; deep neural networks ; medical imaging ; backdoor attacks ; security and privacy ; COVID-19 ; gastric cancer ; endoscopy ; deep learning ; convolutional neural network ; brain ; pituitary adenoma ; dysembryoplastic neuroepithelial tumor ; DNET ; ganglioglioma ; digital pathology ; computer vision ; machine learning ; CNN ; ATLAS ; HarDNet ; Swin transformer ; segmentation ; U-Net ; cerebral infarction ; CycleGAN ; advanced statistics ; schizophrenia ; aggression ; forensic psychiatry ; medical image segmentation ; CT image segmentation ; kernel density ; semi-automated labeling tool ; Bayesian learning ; neuroimaging ; feature selection ; kernel formulation ; mental disorders ; MRI ; visual acuity ; fundus images ; ophthalmology ; SVM ; 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: 2024-03-07
    Description: Access to health care is the ability to receive health services for the prevention, detection, and treatment of disorders that affect health. For health care to be accessible, it must be affordable and able to protect and improve health. There are myriad reasons that may make access to health services difficult or even impossible. These include economic problems, conflicts, climate change, internal and external migrations, beliefs, and so on. This book examines many of these barriers to health care and proposes solutions for overcoming them.
    Keywords: climate change ; public health ; primary health care ; machine learning ; breast cancer ; pandemic ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBN Public health & preventive medicine::MBNH Personal & public health::MBNH9 Health psychology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: The year 2021 marks the 10th anniversary of Journal of Clinical Medicine, and as one of the major sections of JCM, we are launching a 10th anniversary Special Issue in the section “Gastroenterology & Hepatopancreatobiliary Medicine”. We accepted papers for the Special Issue, titled "Recent diagnostic and therapeutic advance in Gastroenterology & Hepatopancreatobiliary Medicine". This medical field is a complex and wide-ranging field that deals with diseases in multiple organs such as the gastrointestinal tract and hepatobiliary pancreas. With recent advances in diagnostic imaging and interventional treatment, those in endoscopic diagnosis and treatment, those in functional test and those in genetic diagnosis and drug therapy, including the molecular-targeted therapy, many new medical findings have been accumulated. In this Special Issue, we looked for reports that make full use of advances in diagnostics and therapeutics in the field of Gastroenterology and Hepatopancreatobiliary Medicine.
    Keywords: TXI ; sessile serrated lesion ; hyperplastic polyp ; colonoscopy ; endoscopic submucosal dissection ; colorectal tumor ; traction method ; carbon dioxide ; CO2 insufflation ; abdominal pain ; abdominal distention ; transnasal endoscopy ; health check ; tranexamic acid ; gastrointestinal bleeding ; mortality ; thromboembolic events ; liver metastases ; colorectal liver metastases ; non-colorectal and non-neuroendocrine liver metastases ; liver resection ; Crohn’s disease ; biologics ; small-molecule drugs ; health-related quality of life (HRQoL) ; gastric cancer ; gastric cancer screening ; endoscopy ; H. pylori ; eradication therapy ; n/a ; functional bowel disorders ; gut microbiota ; personalized diet ; machine learning ; personalized medicine ; Turkey ; machine perfusion ; normothermic ; hypothermic ; liver transplant ; survival ; ustekinumab ; perianal fistula ; radiological fistula remission ; metastatic pancreatic carcinoma ; FOLFIRINOX ; sarcopenia ; oxaliplatin ; L3 skeletal muscle index ; percutaneous endoscopic gastrostomy ; prognostic factor ; bic Book Industry Communication::M Medicine
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    Publication Date: 2024-04-11
    Description: Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.
    Keywords: TA1-2040 ; T55.4-60.8 ; T1-995 ; localization ; smart system ; n/a ; connected enterprise ; digital manufacturing ; AHP ; YOLOv3 ; decision support ; neural network ; vertex distance ; depthwise separable convolution ; cutting insert selection ; smart service ; contour detection ; convolutional neural networks ; platform-based ecosystem ; in-line dimensional inspection ; dilated convolutions ; fabric defect detection ; classification ; FCM ; LGM ; digital information flow ; turning ; computer vision ; control service ; blister defect ; RMTs ; feature pyramid ; research and development indicators ; maintenance expert ; polymer lithium-ion battery ; IT concept ; Industry 4.0 ; matching ; data reduction ; competence ; fibre of preserved Szechuan pickle ; elliptical paraboloid array ; relative angle ; geometric relationship ; optical system ; configure-to-order ; aircraft structure crack detection ; digital twins ; smart factory ; D-VGG16 ; optical slope sensor ; smart manufacturing ; self-calibration method ; convolutional neural network ; industry 4.0 ; skyline queries ; machine learning ; scalability test ; cyber-physical production systems ; Cyber-Physical Systems (CPS) ; demand-side response ; cutting parameter optimization ; image smoothing ; marketing innovations ; genetic algorithm ; automation system ; defect detection ; scheduling ; job shop systems ; big data ; operator theory ; micro-armature ; train wheel ; industrial knowledge graph ; industrial load management ; bilinear model ; artificial neural networks ; 4th industrial revolution ; INDUSTRY 4.0 ; construction equipment ; lean assembly ; capacity control ; Grad-CAM ; revolution workpiece ; chatter ; anomaly detection ; QFD ; social network ; deep learning ; control as a service ; warm forming ; automated surface inspection ; cloud-based control system ; innovative marketing tools ; Internet of Things (IoT) ; flower pollination algorithm ; HED ; edge computing ; predictive analytics ; BIM ; digital platforms ; industrial big data ; energy flexibility ; impacts marketing innovations ; intellectualization of industrial information ; economic recession ; 3D mesh reconstruction ; demand-side management ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The devastating effects caused by the recent catastrophic earthquakes that took place all over the world from Japan, New Zealand, to Chile, as well as those occurring in the Mediterranean basin, have once again shown that ground motion, although a serious source of direct damage, is not the only parameter to be considered, with most damage being the result of coseismic geological effects that are directly connected to the earthquake source or caused by ground shaking. The primary environmental effects induced by earthquakes as well as the secondary effects (sensu Environmental Seismic Intensity - ESI 2007 scale) must be considered for a more correct and complete evaluation of seismic hazards, at both regional and local scales. This Special Issue aims to collect all contributions that, using different methodologies, integrate new data produced with multi-disciplinary and innovative methods. These methodologies are essential for the identification and characterization of seismically active areas, and for the development of new hazard models, obtained using different survey techniques. The topic attracted a lot of interest, 19 peer-reviewed articles were collected; moreover, different areas of the world have been analyzed through these methodologies: Italy, USA, Spain, Australia, Ecuador, Guatemala, South Korea, Kyrgyzstan, Mongolia, Russia, China, Japan, and Nepal.
    Keywords: Arctic–Asian seismic belt ; regional segment ; active fault ; paleoseismogenic structure ; Late Cenozoic deformation ; earthquake mechanism ; seismotectonic deformation ; potential seismicity ; earthquake hazard ; DIC ; CPO ; model selection ; Pohang earthquake ; South Korea ; ground effects ; liquefaction ; geological control ; fault barrier ; seismic hazard ; earthquake hazards ; ESI scale 2007 ; EEE database ; microtremor H/V spectral ratio ; inversion ; shear-wave velocity structure ; site amplification ; Ulaanbaatar ; earthquake environmental effects ; Suusamyr earthquake ; Kyrgyzstan ; Tien Shan ; surface rupture ; landslide ; digital elevation model (DEM) ; Structure-from-Motion ; earthquake-induced landslide ; fully probabilistic technique ; Newmark’s method ; Sakhalin Island ; risk ; machine learning ; expert estimate ; maximum possible magnitudes of earthquakes ; one class classification ; seismic zoning ; earthquake forecasting ; paleoliquefaction ; paleoearthquake ; ESI-07 scale ; earthquake environmental effects (EEEs) ; earthquake archaeological effects (EAEs) ; intensity maps ; seismic scenarios ; earthquake catalogues ; Spain ; emergency shelter ; earthquake ; disaster ; weighted coefficient ; suitability analysis ; geographic information systems (GIS) ; catalog incompleteness ; coseismic landslides ; macroseismic intensity ; Pedernales earthquake ; Ecuador ; georisk ; probabilistic seismic hazard ; ESI scale ; ground-shaking map ; Guatemala ; Intraplate earthquake ; Australian earthquakes ; reverse earthquake ; ESI 2007 scale ; historical and recent earthquakes ; attenuation ; GMPE ; crustal model ; MMI ; intraplate region ; mass movements ; inventory map ; amalgamation ; earth observation (EO) ; spatial resolution ; in situ tests ; laboratory tests ; soil liquefaction ; cyclic triaxial tests ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: Ciguatoxins (CTXs), which are responsible for Ciguatera fish poisoning (CFP), are liposoluble toxins produced by microalgae of the genera Gambierdiscus and Fukuyoa. This book presents 18 scientific papers that offer new information and scientific evidence on: (i) CTX occurrence in aquatic environments, with an emphasis on edible aquatic organisms; (ii) analysis methods for the determination of CTXs; (iii) advances in research on CTX-producing organisms; (iv) environmental factors involved in the presence of CTXs; and (v) the assessment of public health risks related to the presence of CTXs, as well as risk management and mitigation strategies.
    Keywords: ciguatoxins ; HRMS ; Q-TOF ; ciguatera poisoning ; C-CTX1 ; fragmentation pathways ; maitotoxins ; Gambierdiscus ; Fukuyoa ; LC-MS/MS ; QToF ; neuroblastoma cell assay ; matrix effect ; ciguatera monitoring ; SPATT passive samplers ; HP20 resin ; CBA-N2a ; WS artificial substrate ; qPCR ; HTS metabarcoding ; ciguatera ; ciguatoxin ; cytotoxicity assay ; ELISA ; HPLC ; immunoassay ; mouse bioassay ; receptor-binding assay ; ciguatoxins (CTXs) ; neuroblastoma cell-based assay (CBA) ; immunosensor ; pacific ciguatoxins ; natural product ; polycyclic ether ; ring-closing metathesis ; Tsuji-Trost allylation ; French Polynesia ; epidemiology ; toxicological analyses ; risk management ; climate change ; Gambierdiscus polynesiensis ; toxin profile ; nitrate ; urea ; culture medium acidification ; CTX1B ; 52-epi-54-deoxyCTX1B ; 54-deoxyCTX1B ; Dictyota ; Caribbean ; dinoflagellate ; benthic algae ; algal toxin ; harmful algal bloom ; the Indian Ocean ; Arabian sea ; Kuwait bay ; Aden Gulf ; Red Sea ; Gulf of Aqaba ; Andaman Sea ; Bay of Bengal ; seafood safety ; foodborne disease ; experimental exposure ; lionfish ; trophic transfer ; toxin accumulation ; Selvagens Islands ; morphology ; phylogeny ; benthic dinoflagellate ; Beibu Gulf ; Chinese waters ; least absolute shrinkage and selection operator ; machine learning ; data science ; medical informatics ; survival analysis ; foodborne diseases ; Ciguatera Fish Poisoning ; digital technologies ; open data ; risk analysis ; marine biotoxins ; Lagodon rhomboides ; pinfish ; bioaccumulation ; depuration ; Caribbean ciguatoxin ; growth dilution ; model ; kinetics ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MM Other branches of medicine::MMG Pharmacology::MMGT Medical toxicology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The present reprint contains all of the articles in the second edition of the Special Issue titled “Statistical Data Modeling and Machine Learning with Applications II”. This Special Issue belongs to the “Mathematics and Computer Science” Section and aims to publish research on the theory and application of statistical data modeling and machine learning. New mathematical methods and approaches, new algorithms and research frameworks, and their applications aimed at solving diverse and nontrivial practical problems are proposed and developed in this SI. We believe that the chosen papers are attractive and useful to the international scientific community and will contribute to further research in the field of statistical data modeling and machine learning.
    Keywords: forecasting model ; electricity energy consumption ; grey model ; artificial neural network ; machine learning ; rotation CART ensemble ; bagging ; boosting ; arcing ; simplified selective ensemble ; linear stacked model ; IoV ; xNN ; K-MEANS ; anomaly detection ; single-index models ; composite quantile regression ; SCAD ; Laplace error penalty (LEP) ; causality ; Bayesian networks ; scalability ; group lasso penalty ; data integration ; network estimation ; stability selection ; time series model ; wavelet transform ; neural network NARX ; ionospheric parameters ; gambling ; jackpot ; multidimensional integrals ; Monte Carlo methods ; lattice sequences ; digital sequences ; surface approximation ; surface segmentation ; surface denoising ; gaussian process latent variable model ; line geometry ; line elements ; regression ; classification ; prediction ; meteorological parameters ; traffic incidents ; multi-agent architecture ; air pollution ; random forest ; ARIMA errors ; MIMO averaging strategy ; multi-step ahead prediction ; unmeasured forecast ; Explainableartificial intelligence ; credit card frauds ; deep learning ; long short-term memory ; fraud classification ; lung cancer ; tumor ; CT image ; one-stage detector ; YOLO ; multi-scale ; receptive field ; data analysis ; decision trees ; LightGBM ; SHAP ; leisure time ; influencing factors ; time allocation ; neural networks ; cosmic rays ; space weather ; 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: 2023-09-11
    Description: Nowadays, computational and mathematical methods provide effective tools for handling vast quantities of data and information in the fields of big data analytics, knowledge discovery and decision-making for solving complex problems in the world. The present reprint contains all of the articles accepted and published in the first edition of the Special Issue titled “Computational and Mathematical Methods in Information Science and Engineering”. The objective of this Special Issue is to provide a channel through which members of the scientific community can exchange insights regarding recent advances in the theory and application of computational and mathematical methods in information science and engineering, with the long-term goal being to solve data-handling problems in practice. We hope that the papers published in this Special Issue will be considered impactful by the international scientific community and motivate further research into computational and mathematical methods that can solve complex problems in various fields and applications.
    Keywords: multi-scale ; local interaction ; lightweight image reconstruction network ; global fusion ; green supply chain ; environmental awareness ; information acquisition ; outsourcing ; in-house ; career choice ; prediction ; machine learning ; college students ; non-cooperative equilibrium ; complex supply chain network ; environmental policies ; circular economy ; structural balance ; feedback mechanism ; opinions polarization ; reservoir characterization ; productivity prediction ; knowledge interaction neural network ; embedded model ; egg shape equation ; displacement of volume method ; egg volume ; classical retrial policy ; queue dependent service rate ; waiting time analysis ; infinite orbit ; private set intersection ; quantum authentication ; oblivious quantum key distribution ; Internet of Things ; multi-objective optimization ; mining plan ; metal mines ; adaptive ; hybrid mutation ; multi-facility location problem ; clustering algorithm ; center-of-gravity method ; hybrid multi-attribute ; three-way group decision making ; VIKOR model ; grey correlation analysis ; interval-valued intuitionistic fuzzy numbers ; tourist arrival forecast ; variational mode decomposition ; empirical mode decomposition ; multiscale analysis ; deep learning model ; convolutional neural network model ; seasonal ARIMA ; ARIMA ; sales forecasting ; demand pattern ; dynamic weighting ; model selection ; retail ; malicious network traffic ; GAN ; imbalanced classification ; partial discharge (PD) ; phase-resolved PD (PRPD) ; rotating machine ; stator coil ; buffer wards ; mixed-integer programming ; dynamic bed allocation ; patient admission control ; COVID-19 pandemic ; regression ; data stream ; non-convex loss function ; noise-resilient ; online-learning ; ARL ; control charts ; COVID-19 data ; deviance residuals ; link functions ; logistic profiling ; Pearson residuals ; conditional autoregressive model ; Markov chain Monte Carlo ; occurrence rate ; spatial Poisson model ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
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  • 87
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-03-21
    Description: This book includes articles written by over 80 specialists from many countries that demonstrate the biological functions of ultrasonic vocalizations and how they are used in studies of vocal expression of emotional states and in numerous animal models of neuropsychiatric diseases and disorders. Results of investigations of emissions of ultrasonic vocalizations are useful in studies of emotional disturbances, affective disorders, autism spectrum disorders, addiction, developmental abnormalities, and many other pathologies.
    Keywords: ultrasonic vocalization ; maternal immune activation ; autism ; communication ; rat ; sex differences ; social play ; rats ; anxiety ; observational fear learning ; USV ; maternal separation ; pup ; vasopressin antagonists ; righting reflex ; negative geotaxis ; ACTH ; corticosterone ; Brattleboro rat ; larynx ; female ; male ; 50-khz ultrasonic vocalizations (USVs) ; individual differences ; chronic variable stress (CVS) ; dopamine ; nucleus accumbens ; microdialysis ; evolution of vocalization ; 22 kHz calls ; 50 kHz calls ; infant isolation calls ; emotional arousal ; mesolimbic dopaminergic system ; mesolimbic cholinergic system ; hedonia ; ultrasonic vocalizations ; cognitive development ; respiration ; brain oscillations ; Cav1.2 ; calcium ; animal model ; rough-and-tumble play ; social approach ; playback ; social contact call ; alarm call ; social buffering ; distress ; emotional contagion ; fear contagion ; aversive state ; automated scoring ; addiction ; mental health ; machine learning ; drug discovery ; drug development ; Parkinson’s disease ; alpha-synuclein ; 6-OHDA ; Pink1 ; DJ1 ; exercise ; pharmacology ; pathology ; hypervigilance ; hyperreactivity ; exaggerated reactivity ; generalization ; PTSD ; depression ; heart rate ; Wistar ; 22-kHz calls ; 50-kHz calls ; affect ; aversion ; NOR ; reward ; working memory ; Y maze ; opioids ; fentanyl ; self-administration ; play ; food ; dam–pup interaction ; ethanol ; pup isolation ; rat pup ; 50 kHz vocalizations ; 22 kHz vocalizations ; amphetamine ; chemogenetics ; clozapine-n-oxide ; UMAP ; males ; females ; vocalizations ; fear extinction ; pain ; n/a ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences
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  • 88
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Machine learning (ML) technologies are emerging in Mechanical Engineering, driven by the increasing availability of datasets, coupled with the exponential growth in computer performance. In fact, there has been a growing interest in evaluating the capabilities of ML algorithms to approach topics related to metal forming processes, such as: Classification, detection and prediction of forming defects; Material parameters identification; Material modelling; Process classification and selection; Process design and optimization. The purpose of this Special Issue is to disseminate state-of-the-art ML applications in metal forming processes, covering 10 papers about the abovementioned and related topics.
    Keywords: sheet metal forming ; uncertainty analysis ; metamodeling ; machine learning ; hot rolling strip ; edge defects ; intelligent recognition ; convolutional neural networks ; deep-drawing ; kriging metamodeling ; multi-objective optimization ; FE (Finite Element) AutoForm robust analysis ; defect prediction ; mechanical properties prediction ; high-dimensional data ; feature selection ; maximum information coefficient ; complex network clustering ; ring rolling ; process energy estimation ; metal forming ; thermo-mechanical FEM analysis ; artificial neural network ; aluminum alloy ; mechanical property ; UTS ; topological optimization ; artificial neural networks (ANN) ; machine learning (ML) ; press-brake bending ; air-bending ; three-point bending test ; sheet metal ; buckling instability ; oil canning ; artificial intelligence ; convolution neural network ; hot rolled strip steel ; defect classification ; generative adversarial network ; attention mechanism ; deep learning ; mechanical constitutive model ; finite element analysis ; plasticity ; parameter identification ; full-field measurements ; 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::TT Other technologies and applied sciences::TTU Mining technology and engineering
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  • 89
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: The deployment of distributed renewable energy resources (DRERs) has accelerated globally due to environmental concerns and an increasing demand for electricity. DRERs are considered to be solutions to some of the current challenges related to power grids, such as reliability, resilience, efficiency, and flexibility. However, there are still several technical and non-technical challenges regarding the deployment of distributed renewable energy resources. Technical concerns associated with the integration and control of DRERs include, but are not limited, to optimal sizing and placement, optimal operation in grid-connected and islanded modes, as well as the impact of these resources on power quality, power system security, stability, and protection systems. On the other hand, non-technical challenges can be classified into three categories—regulatory issues, social issues, and economic issues. This Special Issue will address all aspects related to the integration and control of distributed renewable energy resources. It aims to understand the existing challenges and explore new solutions and practices for use in overcoming technical challenges.
    Keywords: distribution system ; microgrids ; power quality ; power system management ; power system reliability ; smart grids ; distribution networks ; Monte Carlo simulations ; PV hosting capacity ; photovoltaics ; green communities ; energy independence ; HOMER ; wind turbines ; power losses ; power system optimization ; PV curves ; DG ; TSA/SCA ; solar-powered electric vehicle parking lots ; different PV technologies ; PLO’s profit ; uncertainties ; smart grid paradigm ; distributed generation ; model-based predictive control ; robustness ; worst-case scenario ; min–max optimisation ; intraday forecasting ; Gaussian process regression ; machine learning ; off-grid system ; composite control strategy ; solar photovoltaic panel ; wind turbine ; diesel generator ; energy storage system (ESS) ; synchronous machine (SM) ; permanent magnet brushless DC machine (PMBLDCM) ; power quality improvement ; 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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  • 90
    Publication Date: 2024-04-11
    Description: This Special Issue contains a series of excellent research works on telecommunications and signal processing, selected from the 2018 41st International Conference on Telecommunications and Signal Processing (TSP) which was held on July 4–6, 2018, in Athens, Greece. The conference was organized in cooperation with the IEEE Region 8 (Europe, Middle East, and Africa), IEEE Greece Section, IEEE Czechoslovakia Section, and IEEE Czechoslovakia Section SP/CAS/COM Joint Chapter by seventeen universities from the Czech Republic, Hungary, Turkey, Taiwan, Japan, Slovak Republic, Spain, Bulgaria, France, Slovenia, Croatia, and Poland, for academics, researchers, and developers, and serves as a premier international forum for the annual exchange and promotion of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors worldwide. This collection of 10 papers is highly recommended for researchers, and believed to be interesting, inspiring, and motivating for readers in their further research.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; dynamic time warping ; n/a ; Least Absolute Shrinkage and Selection Operator (LASSO) ; multispectral information ; transmission convergence layer ; 3D segmentation ; micrographia ; MATLAB ; neural network ; wireless communication ; identification ; interference alignment ; Parkinson’s disease dysgraphia ; NG-PON2 ; timing ; GPON ; semantic segmentation ; fractional-order filters ; maximum likelihood criterion ; kinematic analysis ; multitemporal data ; fractional calculus ; multi-hop relay network ; u-net ; interference leakage ; Richardson iteration ; activation process ; acoustic analysis ; follow-up study ; fractional-order derivative ; electrocardiogram (ECG) ; deep learning ; security ; modulo M quasi-stationary ; cognitive radio ; low-pass filters ; time-interleaved analog-to-digital converter (TIADC) ; sample-and-hold (S/H) mismatch ; authentication ; pattern recognition ; online handwriting ; sparse inference ; Taylor series ; EPON ; open-source ; spine ; machine learning ; brain ; signal representation ; magnitude responses ; Chebyshev filters ; XG-PON ; phonation ; hypokinetic dysarthria ; Parkinson’s disease ; overcomplete multi-scale dictionary construction ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 91
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-03-21
    Description: This book includes 17 papers published in the Special Issue/Article Collectoin “New Insights in the Genetics and Genomics of adrenocortical tumors and pheochromocytomas” including an editorial, 10 research papers and six review articles. Adrenal tumors represent a hot topic in contemporary endocrine oncology. Significant advancements in the genetics of genomics of these tumors have been made in recent years, and these articles give a useful and comprehensive overview of these issues. Questions regarding molecular pathogenesis, diagnosis (biomarkers) and even treatment are discussed in the papers written by international leaders of the field. Manuscripts are focused on three main topics: i. primary aldosteronism (the most common cause of secondary endocrine hypertension), ii. adrenocortical cancer and iii. pheochromocytoma/paraganglioma, which are the tumors with the highest heritability in humans. The book is edited by Prof. Peter Igaz (Department of Endocrinology, Faculty of Medicine, Semmelweis University).
    Keywords: pheochromocytoma ; paraganglioma ; genetics ; non-coding RNA ; malignancy ; biomarker ; treatment ; adaptive metabolism ; adrenal gland ; conn adenoma ; fatty acid metabolism ; ferroptosis ; hyperaldosteronism ; metabolic reprogramming ; β-oxidation ; PPARα ; tumor microenvironment ; Next Generation Sequencing ; hereditary cancer ; endocrine tumor syndrome ; KCNJ5 somatic mutation ; pulse wave velocity ; aldosterone-producing adenoma ; adrenalectomy ; propensity score matching ; arterial stiffness ; pheochromocytomas ; paragangliomas ; mutations ; susceptibility genes ; driver mutations ; hereditary ; germline ; somatic ; environment ; variants ; tumor suppressor genes ; metastatic ; RNAseq ; next generation sequencing ; adrenocortical carcinoma ; in silico analysis ; machine learning ; bioinformatic clustering ; biomarker prediction ; aldosterone producing adenoma ; ATP2B3 ; K416-F418delinsN mutation ; primary aldosteronism ; PPGL ; telomeres ; TERT ; ATRX ; NOP10 ; prognostic biomarker ; ALT ; phaeochromocytoma ; cancer ; mitochondrial complex II ; zebrafish ; therapy ; drug discovery ; redox balance pathway ; Vitamin C ; mitotane ; H295 strains ; microRNA ; aldosterone ; circulating ; adrenocortical ; transcriptomics ; epigenetics ; metabolomics ; epidemiology ; genetic analysis ; mortality ; surveillance ; TP53 R337H ; genetic testing ; adrenocortical tumor ; neonatal screening ; screening ; adenoma ; adrenal ; tissue ; artificial intelligence ; neural network ; n/a ; bic Book Industry Communication::M Medicine
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  • 92
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint focuses on recent advances in the processing of surface electromyography (EMG) signals acquired during human movement, as well as on innovative approaches to sense muscle activity. A wide range of methods is examined, including machine learning techniques to detect the onset/offset timing of muscle activity and approaches to evaluate muscle fatigue and analyze muscle synergies and co-contractions. Applications of these techniques are explored in different medical scenarios, e.g., for the benefit of patients suffering from low back pain, stroke survivors, and patients requiring polysomnography.
    Keywords: gait ; locomotion ; motor module ; number of synergies ; VAF ; gait analysis ; EMG ; muscle activation patterns ; movement analysis ; muscle synergies ; sEMG ; stroke ; factor analysis ; neurorehabilitation ; MRC ; dynamometer ; strength ; mechanomyography ; piezoelectric sensor ; vibration sensor ; human-machine interface ; prosthetic control ; hand gesture recognition ; convolutional neural network ; electromyography ; polysomnography ; REM sleep without atonia ; REM sleep behavior disorder ; RBD ; parkinsonism ; Parkinson’s disease ; spectral power ; sitting balance ; trunk control ; ipsilesional arm ; MFRT ; fatiguing frequency-dependent lifting ; low back pain ; trunk muscle coactivation ; onset detection ; muscle activation ; machine learning ; neural networks ; surface EMG ; sEMG processing ; force estimation ; isometric contractions ; surface EMG signal ; co-contraction detection ; muscular synergies ; the time–frequency domain ; wavelet transform ; power spectral density ; spectral estimation techniques ; Welch method ; Burg method ; autoregressive model ; 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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  • 93
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-12-06
    Description: Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such applications may include water pollution and toxic waste in environmental monitoring, pesticide residual detection in food safety and inspection, plant and crop disease detection in agriculture, tumor detection and breast cancer detection in medical imaging, drug traffic in law enforcement, etc. Nevertheless, this reprint book provides many techniques which may find their ways in these applications as well.
    Keywords: hyperspectral image few-shot classification ; deep learning ; meta-learning ; relation network ; convolutional neural network ; constrained-target optimal index factor band selection (CTOIFBS) ; hyperspectral image ; underwater spectral imaging system ; underwater hyperspectral target detection ; band selection (BS) ; constrained energy minimization (CEM) ; lightweight convolutional neural networks ; hyperspectral imagery classification ; transfer learning ; air temperature ; spatial measurement ; FTIR ; MWIR ; carbon dioxide absorption ; target detection ; coffee beans ; insect damage ; hyperspectral imaging ; band selection ; visualization ; color formation models ; multispectral image ; image fusion ; joint tensor decomposition ; anomaly detection ; constrained sparse representation ; hyperspectral imagery ; moving target detection ; spatio-temporal processing ; hyperspectral remote sensing ; image classification ; constraint representation ; superpixel segmentation ; multiscale decision fusion ; plug-and-play ; denoising ; nonlinear unmixing ; spectral reconstruction ; residual augmented attentional u-shape network ; spatial augmented attention ; channel augmented attention ; boundary-aware constraint ; atmospheric transmittance ; temperature ; emissivity ; separation ; midwave infrared ; hyperspectral images ; hyperspectral image super-resolution ; data fusion ; spectral-spatial residual network ; self-supervised training ; hyperspectral ; vegetation ; generative adversarial network ; data augmentation ; classification ; rice leaf blast ; hyperspectral imaging data ; deep convolutional neural networks ; fused features ; evolutionary computation ; heuristic algorithms ; machine learning ; unmanned aerial vehicles (UAVs) ; vegetation mapping ; upland swamps ; mine environment ; rice ; rice leaf folder ; hyperspectral image classification ; change detection ; self-supervised learning ; attention mechanism ; multi-source image fusion ; SFIM ; least square estimation ; spatial filter ; hyperspectral imaging (HSI) ; hyperspectral target detection ; hyperspectral reconstruction ; hyperspectral unmixing ; 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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  • 94
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-07-06
    Description: Special Issue “Advances in Management of Voice and Swallowing Disorders” is dedicated to innovations in screening and assessment and the effectiveness of interventions in both dysphonia and dysphagia. In contemporary practice, novel techniques have been introduced in diagnostics and rehabilitative interventions (e.g., machine learning, electrical stimulation). Similarly, advancements in methodological approaches to validate measures have been introduced (e.g., item response theory using Rasch analysis), prompting the need to develop new, robust measures for use in clinics and intervention studies. Against this backdrop, this Special Issue focuses on studies aiming to improve early diagnostics of laryngological disorders and its management. This issue also welcomes the submission of studies on diagnostic accuracy and psychometrics performance of existing and newly developed measures. This includes but is not limited to studies investigating screening tools with sound diagnostic accuracy and robust psychometric properties. Furthermore, interventions with high levels of evidence in relation to clinical outcome using robust methodology (e.g., sophisticated meta-analytic approaches) are of great interest. This issue provides an overview of the latest advances in voice and swallowing disorders.
    Keywords: T1a glottic carcinoma ; transoral laser microsurgery ; treatment outcome ; vocal function ; objective voice diagnostics ; vocal extent measure (VEM) ; occupational voice disorders ; prevention ; prophylaxis ; teachers ; occupational health ; voice training ; balneotherapy ; dysphagia ; swallowing ; laryngeal penetration or aspiration ; deglutition ; reliability ; videofluoroscopic swallowing study ; deep learning ; machine learning ; Voice Handicap Index (VHI-9i) ; international short scale ; VHI-9i severity levels ; test–retest reliability ; validation of classification ranges ; self-assessed vocal impairment (VHIs) ; hoarseness ; dysphonia severity categories ; voice diagnostics ; deglutition disorders ; tongue ; exercise ; ageing ; Sob Voice Therapy ; Optimal Phonation Task ; Negative Practice ; auditory-perceptual analysis ; acoustic voice analysis ; laryngeal sensory dysfunction ; chronic refractory cough ; botulinum toxin ; larynx ; laryngeal hypersensitivity ; cough hypersensitivity syndrome ; globus pharyngeus ; laryngopharyngeal reflux ; neuropathic cough ; throat irritation ; auditory discrimination ; voice control ; voice assessment ; voice disorders ; swallowing disorders ; RCT ; intervention ; compensation ; rehabilitation ; classic test theory ; measure ; psychometrics ; videofluoroscopic swallow studies ; VMV ; neuromuscular electrical stimulation ; pharyngeal electrical stimulation ; PES ; NMES ; repetitive transcranial magnetic stimulation ; transcranial direct current stimulation ; rTMS ; tDCS ; n/a ; 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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  • 95
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-01
    Description: This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare.
    Keywords: radiation-induced current ; dosimetry ; photodiodes ; phototransistors (MOSFETs) ; photovoltaic sensor ; CCD/CMOS ; cancer nodules detection ; phantom ; stiffness analysis ; ultrasound analysis ; visual analysis ; automatic robotic platform ; remote support for pathologists ; gait analysis ; gait correction ; electrostatic gait signal ; improved Detrended Cross-Correlation Analysis cross-correlation coefficient ; measuring system ; measurements ; contactless ; respiratory rate ; breathing pattern ; ECG electrode swaps ; ECG electrode potentials ; WCT potential change ; reconstructing correct ECG leads ; MSMinv transformation ; unicolor limb–chest electrodes ; torsional wave ; cervix ; pregnancy ; cervical stiffness ; fiber Bragg gratings ; smart textiles ; wearable systems ; cardiac monitoring ; respiratory monitoring ; precision sports ; archery ; body pressure distribution ; air-filled cell ; alternating pressure air mattress ; time of flight ; air flow ; active control system ; mobile EEG recordings ; montage-replaceable headsets ; BCI ; fiber Bragg grating ; plastic optical fiber ; non-invasive measurement ; pulse wave signals ; blood pressure ; partial least squares regression ; people counting ; bi-directional ; motion detection ; time of flight sensor ; force myography ; prosthetic fitting ; regression ; calibration ; error reduction ; linear regression ; random forest ; general regression neural network ; cross-talk ; force sensitive resistor ; MRI ; EMG ; graph theory ; electrical network ; muscle activity ; forearm ; COPD ; oxygen concentrator ; oxygen therapy ; automatic oxygen concentrator ; physical activity ; machine learning ; respiratory medicine ; portable oxygen concentrator ; oxygen delivery ; cerebral palsy ; game-based rehabilitation exercises ; computerized assessment methods ; motion tracking sensors ; Kinect sensor ; EEG ; PPG ; epilepsy ; signal processing ; brain monitoring ; artificial neural network ; predictive analysis ; dietary monitoring ; healthcare ; ring-type biosensor ; personalized digital medicine ; frailty syndrome ; sit-to-stand ; 30-s chair stand test ; wearable sensors ; fetal movement simulator ; fetal movement monitor ; maternal abdomen model ; acoustic sensor ; accelerometer ; piezoelectric diaphragm ; fiber Bragg grating sensors (FBGs) ; functional magnetic resonance imaging (fMRI) ; grasping actions detection ; motor assessment ; MR-compatible measuring systems ; abdominal movement signal ; hypopnea ; LSTM-RNN ; neural network ; oxygen saturation ; sleep apnea syndrome ; sleep–wake detection ; synchrosqueezing transform ; triaxial accelerometer ; thoracic movement signal ; multiple sclerosis ; kinematics ; surface EMG ; accelerator ; inertial sensor ; T10MW ; markerless motion capture ; automatic pushing analysis ; SCI patients ; RGB-D sensors ; respiration monitoring ; non-contact monitoring ; body movements detection ; thermal imaging ; natural sleep environments ; 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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  • 96
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: When adopting remote sensing techniques in precision agriculture, there are two main areas to consider: data acquisition and data analysis methodologies. Imagery and remote sensor data collected using different platforms provide a variety of information volumes and formats. For example, recent research in precision agriculture has used multispectral images from different platforms, such as satellites, airborne, and, most recently, drones. These images have been used for various analyses, from the detection of pests and diseases, growth, and water status of crops to yield estimations. However, accurately detecting specific biotic or abiotic stresses requires a narrow range of spectral information to be analyzed for each application. In data analysis, the volume and complexity of data formats obtained using the latest technologies in remote sensing (e.g., a cube of data for hyperspectral imagery) demands complex data processing systems and data analysis using multiple inputs to estimate specific categorical or numerical targets. New and emerging methodologies within artificial intelligence, such as machine learning and deep learning, have enabled us to deal with these increasing data volumes and the analysis complexity.
    Keywords: vineyard ; pesticide application ; variable rate application ; unmanned aerial vehicle ; satellite ; nanosatellite ; monsoon crops ; leaf area index ; leaf chlorophyll concentration ; crop water content ; multispectral ; hyperspectral ; deep learning ; forage dry matter yield ; high-throughput phenotyping ; Brazilian pasture ; nitrogen indicator ; nitrogen nutrition diagnosis ; optical sensor ; spectral index ; UAV ; wheat lodging ; lightweight ; digital surface model (DSM) ; winter wheat ; fractional order differential ; continuous wavelet transform ; optimal subset regression ; support vector machine ; wheat powdery mildew ; machine learning ; information fusion ; remote sensing monitoring ; hyperspectral imaging ; dimensionality reduction ; LDA ; PLS ; PCA ; RandomForest ; ReliefF ; XGB ; Meloidogyne ; Solanum tuberosum ; soil salinity sensitive parameter ; random forest ; optimal retrieval model ; remote sensing ; high throughput phenotyping ; UAV/drone ; biomass estimation ; oats ; wheat ; yield prediction ; random forests ; satellite imagery ; Normalized Difference Vegetation Index (NDVI) ; 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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  • 97
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: In the treatment of acute stroke, thrombolysis and thrombectomy have proven to be highly effective. Many patients have seen significant improvement after reperfusion therapy. This reprint aims to address current knowledge gaps and promote advancements in the use of thrombolysis and thrombectomy for the treatment of acute ischemic stroke.
    Keywords: ischemic stroke ; acute kidney injury ; contrast media ; endovascular treatment ; outcome ; hyperglycemia ; acute ischemic stroke ; large vessel occlusion ; mechanical thrombectomy ; stroke ; ischemia ; machine learning ; cerebral infarction ; biomarkers ; recanalization therapy ; reperfusion ; temperature ; time to admission ; prehospital delay ; prior stroke ; basilar artery ; brain ischemia ; intracranial atherosclerosis ; embolism ; infarction ; clinical symptoms ; intravenous thrombolysis ; endovascular therapy ; recanalization times ; clinical outcome ; hypoperfusion index ratio ; collateral circulation ; collateral scoring ; CTA ; CTP ; thrombolysis ; C-reactive protein ; white blood cell count ; prognosis ; hypoperfusion ; collaterality ; thrombectomy ; frailty ; elderly patients ; hospital frailty risk score ; acute stroke ; perfusion imaging ; CT perfusion ; MR perfusion ; RAPID ; fasting hyperglycemia ; fasting normoglycemia ; long-term outcome ; hemorrhagic transformation ; parenchymal hematoma ; GWAS ; single nucleotide variants ; anterior circulation ; bridging therapy ; recanalization ; stroke risk score ; COVID-19 ; Lithuania ; reperfusion therapies ; outcomes ; safety ; prehospital stroke diagnosis ; ultrasound ; brain perfusion ; SONAS® ; prehospital stroke scales ; point-of-care diagnostics ; 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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  • 98
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that.
    Keywords: data mining ; decision-making system ; rough set ; mixed integer linear programming ; assembly clearance ; diesel engine quality ; Internet of things ; Wireless nodes ; Hybrid clustering ; Multi-hop routing ; Network lifetime ; Artificial intelligence ; data envelopment analysis ; decision making ; artificial intelligence ; performance ; visual analytics ; system ; air quality ; spatiotemporal ; multivariate ; dimension reduction ; clustering ; regular patterns ; anomalies ; speech recognition ; Long Short Term Memory (LSTM) ; speech output correction ; most-matching ; empirical correlations ; rheological properties ; real-time ; water-based drill-in fluid ; artificial neural network ; elastic parameters ; Poisson’s ratio ; sandstone ; self-adaptive differential evolution ; total organic carbon ; barnett shale ; devonian shale ; fishbone multilateral wells ; predictive models ; well productivity ; international research ; knowledge map visualization ; policy documents quantification ; research hotspot ; policy keyword ; minimum miscibility pressure (MMP) ; CO2 flooding ; new models ; face recognition ; security ; spoofing ; histogram of oriented gradients ; smart cities ; deep learning ; LSTM ; neural networks ; location prediction ; trajectories ; smart tourism ; static Young’s modulus ; sandstone formations ; machine learning ; 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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  • 99
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.
    Keywords: TA1-2040 ; T1-995 ; supervised machine learning ; proper orthogonal decomposition (POD) ; PGD compression ; stabilization ; nonlinear reduced order model ; gappy POD ; symplectic model order reduction ; neural network ; snapshot proper orthogonal decomposition ; 3D reconstruction ; microstructure property linkage ; nonlinear material behaviour ; proper orthogonal decomposition ; reduced basis ; ECSW ; geometric nonlinearity ; POD ; model order reduction ; elasto-viscoplasticity ; sampling ; surrogate modeling ; model reduction ; enhanced POD ; archive ; modal analysis ; low-rank approximation ; computational homogenization ; artificial neural networks ; unsupervised machine learning ; large strain ; reduced-order model ; proper generalised decomposition (PGD) ; a priori enrichment ; elastoviscoplastic behavior ; error indicator ; computational homogenisation ; empirical cubature method ; nonlinear structural mechanics ; reduced integration domain ; model order reduction (MOR) ; structure preservation of symplecticity ; heterogeneous data ; reduced order modeling (ROM) ; parameter-dependent model ; data science ; Hencky strain ; dynamic extrapolation ; tensor-train decomposition ; hyper-reduction ; empirical cubature ; randomised SVD ; machine learning ; inverse problem plasticity ; proper symplectic decomposition (PSD) ; finite deformation ; Hamiltonian system ; DEIM ; GNAT ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields.
    Keywords: light emitting diode ; nonlinearity estimation and compensation ; probabilistic Bayesian learning ; visible light communication ; digital signal processing ; support vector machines ; BCSVM ; nonlinear equalization ; coherent detection ; k-nearest neighbor algorithm ; modulation format identification ; OSNR monitoring ; neural networks ; optical communications ; optimization ; equalizer ; tap estimation ; optical Fast-OFDM ; nonlinearity compensation ; optical fiber communications ; chromatic dispersion ; short-reach communication ; neural network ; hybrid signal processing ; fiber optics communications ; coherent communications ; machine learning ; clustering ; nonlinearity cancellation ; entanglement ; charge qubit ; position-based semiconductor qubits ; cryogenic technologies ; semiconductor photon communication ; Jaynes–Cummings–Hubbard formalism ; deep neural networks ; volterra equalization ; nonlinear systems ; coherent optical communication ; passive optical networks ; nonlinear compensation ; optical transmission ; optical networks ; artificial intelligence ; quality of transmission ; optical performance monitoring ; failure management ; artificial neural networks ; deep neural network ; image classification ; photonic integrated circuits ; semiconductor optical amplifiers ; photonic neural network ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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