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  • data science
  • forecasting
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  • English  (120)
  • Danish
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  • 1
    Unknown
    Basel, Boston, Berlin : Birkhäuser
    Keywords: fog ; clouds ; forecasting
    Description / Table of Contents: This topical volume of the Journal of Pure and Applied Geophysics utilizes new information not previously accessible for fog related research. It focuses on surface and remote sensing observations of fog, various numerical model applications using new parameterizations, fog climatology, and new statistical methods. The results presented in this special issue come from research efforts in North America and Europe, mainly from the Canadian Fog Remote Sensing And Modeling (FRAM) and European COST-722 fog/visibility related projects. Students, postgraduates, and researchers, interested in cloud physics, physical meteorology, aviation meteorology, climate, weather forecasting, and in other adjacent disciplines, can use this book as a basis for future developments in fog research. It is hoped that this book will lead to new scientific challenges in fog related research, teaching, and applications.
    Pages: Online-Ressource (316 Seiten)
    ISBN: 9783764384180
    Language: English
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  • 2
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    Keywords: data science
    Description / Table of Contents: About Data --- Identifying Data Problems --- Getting Started with R --- Follow the Data --- Rows and Columns --- Beer, Farms and Peas --- Sample in a Jar --- Big Data? Big Deal! --- Onward with R-Studio --- Tweet, Tweet! --- Popularity Contest --- String Theory --- Word Perfect --- Storage Wars
    Pages: Online-Ressource (195 pages) , illustrations, diagrams
    Edition: version 3
    Language: English
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  • 3
    Keywords: data science
    Description / Table of Contents: Chapter 1 Introduction --- Overview --- Data Science Is OSEMN --- Intermezzo Chapters --- What Is the Command Line? --- Why Data Science at the Command Line? --- A Real-World Use Case --- Further Reading --- Chapter 2 Getting Started --- Overview --- Setting Up Your Data Science Toolbox --- Essential Concepts and Tools --- Further Reading --- Chapter 3 Obtaining Data --- Overview --- Copying Local Files to the Data Science Toolbox --- Decompressing Files --- Converting Microsoft Excel Spreadsheets --- Querying Relational Databases --- Downloading from the Internet --- Calling Web APIs --- Further Reading --- Chapter 4 Creating Reusable Command-Line Tools --- Overview --- Converting One-Liners into Shell Scripts --- Creating Command-Line Tools with Python and R --- Further Reading --- Chapter 5 Scrubbing Data --- Overview --- Common Scrub Operations for Plain Text --- Working with CSV --- Working with HTML/XML and JSON --- Common Scrub Operations for CSV --- Further Reading --- Chapter 6 Managing Your Data Workflow --- Overview --- Introducing Drake --- Installing Drake --- Obtain Top Ebooks from Project Gutenberg --- Every Workflow Starts with a Single Step --- Well, That Depends --- Rebuilding Specific Targets --- Discussion --- Further Reading --- Chapter 7 Exploring Data --- Overview --- Inspecting Data and Its Properties --- Computing Descriptive Statistics --- Creating Visualizations --- Further Reading --- Chapter 8 Parallel Pipelines --- Overview --- Serial Processing --- Parallel Processing --- Distributed Processing --- Discussion --- Further Reading --- Chapter 9 Modeling Data --- Overview --- More Wine, Please! --- Dimensionality Reduction with Tapkee --- Clustering with Weka --- Regression with SciKit-Learn Laboratory --- Classification with BigML --- Further Reading --- Chapter 10 Conclusion --- Let’s Recap --- Three Pieces of Advice --- Where to Go from Here? --- Getting in Touch
    Pages: Online-Ressource (XVII, 191 pages) , illustrations, diagrams
    ISBN: 9781491947852
    Language: English
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  • 4
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    Rijeka : InTech
    Keywords: time series analysis ; TSA ; data science ; forecasting
    Description / Table of Contents: Chapter 1: Introductory Chapter: Time Series Analysis (TSA) for Anomaly Detection in IoT by Nawaz Mohamudally --- Chapter 2: Anxiety, Worry and Fear: Quantifying the Mind Using EKG Time Series Analysis by Toru Yazawa --- Chapter 3: Agricultural Monitoring in Regional Scale Using Clustering on Satellite Image Time Series by Renata Ribeiro do Valle Gonçalves, Jurandir Zullo Junior, Bruno Ferraz do Amaral, Elaine Parros Machado Sousa and Luciana Alvim Santos Romani --- Chapter 4: Volatility Parameters Estimation and Forecasting of GARCH(1,1) Models with Johnson’s SU Distributed Errors by Mohammed Elamin Hassan, Henry Mwambi and Ali Babikir --- Chapter 5: Generation of Earth’s Surface Three-Dimensional (3-D) Displacement Time-Series by Multiple-Platform SAR Data by Antonio Pepe --- Chapter 6: Time Series and Renewable Energy Forecasting by Mahmoud Ghofrani and Musaad Alolayan --- Chapter 7: Modeling Nonlinear Vector Time Series Data by Jiancheng Jiang and Sha Yu --- Chapter 8: Symbolic Time Series Analysis and Its Application in Social Sciences by Wiston Adrián Risso --- Chapter 9: State-Space Models for Binomial Time Series with Excess Zeros by Fan Tang and Joseph E. Cavanaugh --- Chapter 10: Ensemble Prediction of Stream Flows Enhanced by Harmony Search Optimization by Milan Cisty and Veronika Soldanova
    Pages: Online-Ressource (178 Seiten)
    ISBN: 9789535137436
    Language: English
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  • 5
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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
    Language: English
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  • 6
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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
    Language: English
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  • 7
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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
    Language: English
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  • 8
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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
    Language: English
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  • 9
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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
    Language: English
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Since the conceptualization of bounded rationality, management scholars started investigating how people—managers and entrepreneurs—really make decisions within (and for) organizations. The aim of this eBook is to deeply investigate trends that have flourished within this pivotal research area in conceptual and/or empirical terms, trying to provide new insights on how managers and entrepreneurs make decisions within and for organizations. In this vein, readers that approach this eBook will be taken by hand and accompanied to the discovery of how the mind of decision makers is at the basis of organizational developments or failures. In this regard, published contributions in this eBook underline how executives and entrepreneurs must be ecologically rational, thus be aware of the negative and positive effects that biases can have depending on the context and use them at their advantage. Managerial and entrepreneurial decision-making are phenomena that cannot be detached from the environment in which executives and entrepreneurs are embedded, claiming to establish new approaches to research that looks at decision-making as an individual/group/organization-environment dialectical and multi-level phenomenon.
    Keywords: behavioral strategy ; decision-making ; core self-evaluations ; intuition ; overconfidence ; performance ; nurse manager ; time pressure ; self-leadership ; stress ; entrepreneurial decision-making ; resource-based view ; opportunity identification ; competitive advantage ; critical assessments ; managerial process ; decision making ; critical infrastructure elements ; resilience ; disruption ; indication ; data lake ; data governance ; data quality ; big data ; digital transformation ; data science ; asset management ; boundary condition ; SME entrepreneurs ; accountants ; cognitive biases ; debiasing ; clinical decision-making process ; clinical reasoning ; orthopaedics ; follow-up decision ; healthcare decision ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJC Business strategy ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJM Management and management techniques::KJMV Management of specific areas
    Language: English
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  • 11
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Complex systems have long been an integral part of modern life and can be encountered everywhere. Undertaking a comprehensive study of such systems is a challenging problem, one which is impossible to solve without the use of contemporary mathematical modeling techniques. Mathematical models form the basis for the optimal design and control of complex systems. The present reprint contains all the articles accepted and published in the Special Issue of Mathematics entitled "Control, Optimization, and Mathematical Modeling of Complex Systems". This Special Issue is focused on recent theoretical and computational studies of complex systems modeling, control, and optimization. The topics addressed in this Special Issue cover a wide range of areas, including numerical simulation in physical, social, and life sciences; the modeling and analysis of complex systems based on mathematical methods and AI/ML approaches; control problems in robotics; design optimization of complex systems, modeling in economics and social sciences; stochastic models in physics and engineering; mathematical models in material science; and high-performance computing for mathematical modeling. It is our hope that the scientific results presented in this reprint will serve as valuable sources of documentation and inspiration to those seeking to delve into complex systems modeling, control, and optimization and examine their wide-ranging applications.
    Keywords: optimal control problem ; evolutionary computation ; robotics applications ; optimal control ; Lyapunov stability ; equilibrium point ; symbolic regression ; Pontryagin’s maximum principle ; continuous-time Markov chains ; ergodicity bounds ; discrete state space ; rate of convergence ; logarithmic norm ; interval analysis ; function approximation ; global optimization ; convexity evaluation ; overestimators ; underestimators ; machine learning control ; general synthesis problem ; evolutionary algorithm ; adaptive interpolation algorithm ; interval ordinary differential equations (ODEs) ; sparse grids ; hierarchical basis ; multidimensional interpolation ; high dimensions ; molecular dynamics modeling ; randomized maximum entropy estimation ; probability density functions ; Lagrange multipliers ; Lyapunov-type problems ; implicit function ; rotation of vector field ; asymptotic efficiency ; thermokarst lakes ; forecasting ; dynamical tracking target ; ship towing system ; relative curvature ; adaptive control ; discrete velocity method ; lattice Boltzmann method ; computational fluid dynamics ; mathematical modeling ; estimation ; minimax techniques ; pareto optimization ; regression analysis ; statistical uncertainty ; proton exchange membrane ; proton electrolyte membrane ; PEM ; fuel cell ; PEMFC ; power electronic converter ; DC–DC boost converter ; model predictive control ; MPC ; self-scalable robots ; modular robots ; origami structures ; complex system ; synergistic effect ; performance indicator ; structure change ; soft robotics ; continuum mechanisms ; modeling of complex systems ; kinematic model of soft robots ; mathematical modeling of complex systems ; non-linear models ; soft robotic neck ; tendon-driven actuators ; mathematical modelling ; modelling in economics ; impact of the COVID-19 ; logistics businesses ; fractional-order virus models ; stuxnet virus ; numerical computing ; supervisory control and data acquisition systems ; computer networks ; lyapunov analysis ; image segmentation ; remote sensing ; terrain identification ; data synthesis ; transfer learning ; controllability ; observability ; stochastic linear systems in finite and infinite dimensional spaces ; stochastic singular linear systems in finite and infinite dimensional spaces ; semigroup ; evolution operator ; GE-semigroup ; GE-evolution operator ; stochastic GE-evolution operator ; feature selection ; finite normal mixtures ; moving separation of mixtures ; deep LSTM ; neural network architectures ; deep learning ; turbulent plasma ; air–sea fluxes ; 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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  • 12
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    Frontiers Media SA
    Publication Date: 2024-04-04
    Description: Forecasting volcanic eruptions and their potential impacts are primary goals in Natural Hazards research. Active volcanoes are nowadays monitored by different ground and space-based instruments providing a wealth of seismic, geodetic, and chemical data for academic volcanologists and monitoring agencies. We have better insights into volcanic systems thanks to steady improvements in research tools and data processing techniques. The integration of these data into physics-based models allows us for example to constrain magma migration at depth and to derive the pressure evolution inside volcanic conduits and reservoirs, which ultimately help monitor evolving volcanic hazard. Yet, it remains challenging to answer the most crucial questions when the threat of an eruption looms over us: When will it occur? What will be its style? Will it switch during its course? How long will the eruption last? And most importantly: will we have enough time to alert and evacuate population? Addressing these questions is crucial to reduce the social and economic impact of volcanic eruptions, both at the local and global scales. For example, the 2014 eruption at Ontake (Japan) had only limited spatial impact but killed dozens of hikers; in contrast, the 2010 Eyjafjallajökull eruption (Iceland) did not cause any human loss but paralyzed the European air space for weeks. Several limitations arise when approaching these questions. For example, short-term eruption forecasts and models that relate changes in monitoring parameters to the probability, timing, and nature of future activity are particularly uncertain. More reliable and useful quantitative forecasting requires the development of optimized and integrated monitoring networks, standardized approaches and nomenclature, and a new range of statistical methods and models that better capture the complexity of volcanic processes and system dynamics.
    Keywords: volcanology ; monitoring ; forecasting ; earth science ; volcano ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGB Physical geography and topography
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  • 13
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: The sustainable development of our planet depends on the use of energy. The increasing world population inevitably causes an increase in the demand for energy, which, on the one hand, threatens us with the potential to encounter a shortage of energy supply, and, on the other hand, causes the deterioration of the environment. Therefore, our task is to reduce this demand through different innovative solutions (i.e., both technological and social). Social marketing and economic policies can also play their role by affecting the behavior of households and companies and by causing behavioral change oriented to energy stewardship, with an overall switch to renewable energy resources. This reprint provides a platform for the exchange of a wide range of ideas, which, ultimately, would facilitate driving societies toward long-term energy efficiency.
    Keywords: natural resources ; globalization ; energy ; nonparametric causality in quantiles ; energy security ; power market ; near-zero emission technologies ; oxy-fuel combustion cycles ; emission rights sales mechanism ; economic assessment ; Oil Companies ; innovations ; investments in R&amp ; D ; forecasting the Innovation activities ; industry 4.0 ; Agenda 2030 ; sustainable human development ; measuring development ; energy sustainability ; indirect measurement ; composed indexes ; forecasting ; linear regression ; planning ; polynomial regression ; power supply ; green building ; housing projects management ; sustainable construction ; renewable energy sources ; real estate developers ; deviation ; energy dependence ; energy efficiency management ; energy saving ; cost ; risk limit ; energy industry ; energy supply ; energy intensity ; energy efficiency ; energy industry risks ; dilemma ; development ; Kazakhstan ; energy transitions ; Latin America ; power system ; sustainability ; economic growth ; pollution ; renewable energy ; oil and gas industry ; investments ; rating ; competitiveness ; financial analysis ; risk ; profitability ; merchandising technologies ; correlation ; scenario ; social development ; optimization ; investment ; financial portfolio ; financial leverage ; integral rating ; industry rating ; high-tech company ; decision-making ; minimax ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics
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  • 14
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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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  • 15
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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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  • 16
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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: With the increase in data processing and storage capacity, a large amount of data is available. Data without analysis does not have much value. Thus, the demand for data analysis is increasing daily, and the consequence is the appearance of a large number of jobs and published articles. Data science has emerged as a multidisciplinary field to support data-driven activities, integrating and developing ideas, methods, and processes to extract information from data. This includes methods built from different knowledge areas: Statistics, Computer Science, Mathematics, Physics, Information Science, and Engineering. This mixture of areas has given rise to what we call Data Science. New solutions to the new problems are reproducing rapidly to generate large volumes of data. Current and future challenges require greater care in creating new solutions that satisfy the rationality for each type of problem. Labels such as Big Data, Data Science, Machine Learning, Statistical Learning, and Artificial Intelligence are demanding more sophistication in the foundations and how they are being applied. This point highlights the importance of building the foundations of Data Science. This book is dedicated to solutions and discussions of measuring uncertainties in data analysis problems.
    Keywords: model-based clustering ; mixture model ; EM algorithm ; integrated approach ; density estimation ; distribution free ; non-parametric statistical test ; decoy distributions ; size invariance ; scaled quantile residual ; maximum entropy method ; scoring function ; outlier detection ; overfitting detection ; time series of counts ; Bayesian hierarchical modeling ; Bayesian nonparametrics ; Pitman–Yor process ; prior sensitivity ; clustering ; Bayesian forecasting ; singular spectrum analysis ; robust singular spectrum analysis ; time series forecasting ; mutual investment funds ; relative entropy ; cross-entropy ; uncertain reasoning ; inductive logic ; confirmation measure ; semantic information ; medical test ; raven paradox ; Markov random fields ; probabilistic graphical models ; multilayer networks ; objective Bayesian inference ; intrinsic prior ; variational inference ; binary probit regression ; mean-field approximation ; multi-attribute emergency decision-making ; intuitionistic fuzzy cross-entropy ; grey correlation analysis ; earthquake shelters ; attribute weights ; time series ; Bayesian inference ; hypothesis testing ; unit root ; cointegration ; Rényi entropy ; discrete Kalman filter ; continuous Kalman filter ; algebraic Riccati equation ; nonlinear differential Riccati equation ; cloud model ; fuzzy time series ; stock trend ; Heikin–Ashi candlestick ; water resources ; channel ; mathematical entropy model ; bank profile shape ; gene expression programming (GEP) ; entropy ; genetic programming ; artificial intelligence ; data science ; big data ; 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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    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: 2022-05-06
    Description: Droughts are one of the main extreme meteorological, and hydrological phenomena, which influence both the functioning of ecosystems, and many important sectors of human economic activity. Throughout the world, various direct changes in meteorological, and climatic conditions, such as: air temperature, humidity, and evapotranspiration can be observed. They have a significant influence upon the shaping of the phenomenon of drought. Land cover and land use can also be indirect factors influencing evapotranspiration, and, by the same token, the water balance in the water catchment area. They can also influence the course of the process of the drought. The observed climate change, manifested mainly by increases in temperature, in turn, influencing evapotranspiration, may cause intensification in terms of both the degree and frequency of droughts. Droughts related to changes in the hydrological regime, and to the decrease in water resources. Its results can be observed in various sectors, related, among others, to a demand for water for people, agriculture and the Industry. It can also prove problematic for water ecosystems. To reflect the aforementioned information, a reasonable drought risk management is indispensable in order to ease the water demand related problems in various sectors of human activity. This book presents original research on various drought indicators, modern measurement techniques used, among others, for monitoring and predicting droughts, drought indicator trends, the impact of insufficient precipitation on human activity in the context of climate change, and examples of modern solutions devised to prevent water shortages.
    Keywords: extensive green roofs ; climate change ; summer drought ; urban vegetation ; phytomass ; fertilizer ; biodiversity ; blue green infrastructure ; pan evaporation ; ANN ; WANN ; SVM-RF ; SVM-LF ; Pusa station ; drought ; SPI ; run theory ; Sen’s estimator ; Mann–Kendall ; Wadi Cheliff Basin ; water stress ; soil moisture ; atmospheric evaporative demand ; eddy covariance ; gross primary productivity ; meteorological drought ; agricultural drought ; atmospheric circulation ; elementary circulation mechanism (ECM) ; information entropy ; atmospheric blocking ; hydrological drought ; trends ; central Poland ; lotic systems ; refuge habitats ; fish ; risk management ; forecasting ; ARIMA ; Standardized Precipitation Evapotranspiration Index (SPEI) ; mitigation ; atmospheric drought ; forest drought ; Carpathian Mts. ; beech ; vertical climate zones ; Copernicus Sentinel-1 ; electrical resistivity tomography ; expansive clay ; InSAR ; shrink-swell risk ; SMOS surface soil moisture ; wavelet analysis ; precipitation ; precipitation deficit ; climatic water balance ; 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: 2024-04-11
    Description: The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.
    Keywords: TA1-2040 ; T1-995 ; supervised machine learning ; proper orthogonal decomposition (POD) ; PGD compression ; stabilization ; nonlinear reduced order model ; gappy POD ; symplectic model order reduction ; neural network ; snapshot proper orthogonal decomposition ; 3D reconstruction ; microstructure property linkage ; nonlinear material behaviour ; proper orthogonal decomposition ; reduced basis ; ECSW ; geometric nonlinearity ; POD ; model order reduction ; elasto-viscoplasticity ; sampling ; surrogate modeling ; model reduction ; enhanced POD ; archive ; modal analysis ; low-rank approximation ; computational homogenization ; artificial neural networks ; unsupervised machine learning ; large strain ; reduced-order model ; proper generalised decomposition (PGD) ; a priori enrichment ; elastoviscoplastic behavior ; error indicator ; computational homogenisation ; empirical cubature method ; nonlinear structural mechanics ; reduced integration domain ; model order reduction (MOR) ; structure preservation of symplecticity ; heterogeneous data ; reduced order modeling (ROM) ; parameter-dependent model ; data science ; Hencky strain ; dynamic extrapolation ; tensor-train decomposition ; hyper-reduction ; empirical cubature ; randomised SVD ; machine learning ; inverse problem plasticity ; proper symplectic decomposition (PSD) ; finite deformation ; Hamiltonian system ; DEIM ; GNAT ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: In recent years, several projects and studies have been launched towards the development and use of new methodologies, in order to assess, monitor, and support clean forms of energy. Accurate estimation of the available energy potential is of primary importance, but is not always easy to achieve. The present Special Issue on ‘Renewable Energy Resource Assessment and Forecasting’ aims to provide a holistic approach to the above issues, by presenting multidisciplinary methodologies and tools that are able to support research projects and meet today’s technical, socio-economic, and decision-making needs. In particular, research papers, reviews, and case studies on the following subjects are presented: wind, wave and solar energy; biofuels; resource assessment of combined renewable energy forms; numerical models for renewable energy forecasting; integrated forecasted systems; energy for buildings; sustainable development; resource analysis tools and statistical models; extreme value analysis and forecasting for renewable energy resources.
    Keywords: short-term forecasts ; direct normal irradiance ; concentrating solar power ; system advisor model ; operational strategies ; central solar receiver ; solar irradiance forecasts ; numerical weather prediction model ; different horizontal resolution ; forecast errors ; validation ; ramp rates ; renewable energy forecasting ; solar radiation ; shark algorithm ; particle swarm optimization ; ANFIS ; nowcasting ; Kalman-Bayesian filter ; WRF ; high-resolution ; complex terrain ; wind ; solar irradiation ; photovoltaic solar energy ; deep learning ; prediction ; biofuel ; risk analysis ; sustainable development ; renewable energy ; biomass ; biotechnology ; anthropogenic waste processing ; energy resource assessment ; tidal-stream energy ; thrust force coefficient ; momentum sink ; unbounded flow ; open channel flows ; shock-capturing capability ; global horizontal irradiance (GHI) ; forecasting ; clearness coefficient ; Markov chains ; weather research and forecasting model ; solar resource ; heat supply of industrial processes ; solar collectors ; economic efficiency ; cross border trading ; Granger causality ; electricity trading ; spot prices ; deformable models ; electric energy demand ; functional statistics ; Kalman filtering ; shape-invariant model ; developing countries ; concentrated solar ; thermochemical ; energy ; renewable energy sources ; climate policy ; forecast ; the European Green Deal ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    Springer Nature
    Publication Date: 2024-04-07
    Description: geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data science
    Keywords: geospatial analytics ; social observatory ; big earth data ; open data ; citizen science ; open innovation ; earth system science ; crowdsourced geospatial data ; citizen science ; science in society ; data science ; 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: This book brings together the latest research results of air quality assessment standards and sustainable development in developing countries. The content is full and the discussion is vivid. These articles are suitable for students and researchers at all levels seeking to understand the status of air pollution, governance standards, and governance effects in developing countries.
    Keywords: TD172-193.5 ; GE1-350 ; Q1-390 ; greenhouse gases ; collaborative filtering ; Euclid approach degree method ; hierarchical linear model ; pollution ; adaptive clustering analysis ; evolutionary game ; fuzzy comprehensive evaluation ; spatial and temporal difference ; livestock ; AQI ; rough set ; air pollutant ; fuzzy optimization model ; air quality ; Beijing-Tianjin-Hebei region ; functional ANOVA ; environmental supervision ; environmental governance ; primary pollutants ; emission inventory ; N) model ; Beijing ; sustainable development ; PM2.5 concentrations ; environmental target-setting ; entropy weight method ; comprehensive pollution index analysis ; attribute reduction ; functional principal component analysis ; AQI indicators ; Jiangsu province ; vehicle ; haze ; air quality evaluation standards ; China ; interval grey number ; PM2.5 ; carbon emissions ; linear time-varying GM(1 ; forecasting ; grey correlation analysis ; measurement and environment ; performance ; whistleblowing ; relevance analysis ; PSR Model ; wind power development ; air pollution ; spatial and temporal distribution characteristics ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology::TQK Pollution control
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market). This collection gathers the advanced studies of novel deep learning algorithms/frameworks and their applications in real-world scenarios. The topics cover, but are not limited to, supervised learning, explainable deep learning, finance, healthcare, and sciences.
    Keywords: Convolutional Neural Network (CNN) ; pooling ; deep learning ; computer vision ; image analysis ; benchmark ; lithium-ion battery ; prognostics ; long short-term memory ; ARIMA ; reinforcement learning ; generative adversarial networks ; deep-learning ; crop/weed classification ; transfer learning ; feature extraction ; natural language processing ; image-text matching ; cheapfakes ; misinformation ; transformer encoder ; RoGPT2 ; control tokens ; summarization ; text generation ; human evaluation ; tricalcium silicate ; analytical model ; ion activity ; dissolution kinetics ; deep forest ; subsurface fluid flow ; Fourier neural operator ; small-shape data ; finite element method ; convolutional neural network ; sensitivity analysis ; source code comments ; classification ; machine learning techniques ; ANN flow law ; constitutive behavior ; radial return algorithm ; numerical implementation ; VUHARD ; GrC15 ; Abaqus Explicit ; defect detection ; surface defect detection ; defect detection for X-ray images ; defect recognition ; photoacoustic imaging ; image processing ; simulation ; reconstruction ; residual echo suppression ; acoustic echo cancellation ; speech enhancement ; graph neural network ; variational autoencoder ; nearest neighbours ; acute myeloid leukemia ; risk factors ; average treatment effect ; uplift modelling ; machine learning ; benzene ; ANOVA ; Shapley values ; self-explaining neural networks ; generalised additive models ; interpretability ; Siamese networks ; synthetic data ; cyclic learning ; unsupervised learning ; data augmentation ; single cell cultivation ; bioimage analysis ; finite element simulation ; plausibility checks ; convolutional neural networks ; storm surge ; hurricane ; forecasting ; CNN ; LSTM ; physics informed neural network ; dynamic force identification ; duffing’s equation ; spring mass damper system ; non-linear oscillators ; massive MIMO ; hybrid beamforming ; compressive measurement matrix ; long short-term memory network ; capsule network ; routing algorithm ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Childhood obesity continues to be a global problem, with several regions showing increasing rates and others having one in every three children overweight despite an apparent halt or downward trend. Children are exposed to nutritional, social, and obesogenic environmental risks from different settings, and this affects their lifelong health. There is a consensus that high-quality multifaceted smart and cost-effective interventions enable children to grow with a healthy set of habits that have lifelong benefits to their wellbeing. The literature has shown that dietary approaches play key roles in improving children’s health, not only on a nutritional level but also in diet quality and patterns. An association between the nutritional strategy and other lifestyle components promotes a more comprehensive approach and should be envisioned in intervention studies. This Special Issue entitled “Child Obesity and Nutrition Promotion Intervention” combines original research manuscripts or reviews of the scientific literature concerning classic or innovative approaches to tackle this public health issue. It presents several nutritional interventions alongside lifestyle health factors, and outcome indicators of effectiveness and sustainability from traditional to ground-breaking methods to exploit both qualitative and quantitative approaches in tackling child obesity.
    Keywords: serious game ; gamification ; eating behavior ; food neophobia ; willingness to taste ; nutritional status ; obesity ; dietary habits ; allergy ; pulmonary function ; allergic rhinitis ; asthma ; dietary habit ; vegetable consumption ; food intake ; preschool children ; Japan ; nutrition ; stress ; mental health ; family ; health behavior ; childhood obesity ; health intervention ; healthy lifestyle intervention ; school-based intervention ; MVPA ; overweight and obesity ; self-efficacy ; adolescent girls ; parent–child dyads ; food availability ; advertising ; healthy diet ; promotion programs ; community-based program ; school meals ; salt intake ; sodium consumption ; schools ; canteen ; adolescents ; implementation ; purchase behaviour ; overweight ; machine learning ; deep learning ; statistical models ; data science ; BMI ; child ; surveillance ; health ; noncommunicable diseases ; children ; fruit ; vegetables ; soft drinks ; energy balance-related behaviors ; self-regulation skills ; preschoolers ; randomized controlled trial ; intervention effects ; parental educational level ; intervention mapping ; multicomponent intervention ; school children ; food and nutrition ; intervention ; healthy eating ; food acceptance ; tactile play ; cooking ; fish ; health promotion ; childhood overweight ; risk ; community ; screening ; tool ; food environment ; home ; school ; food consumption patterns ; dietary intakes ; macronutrients ; micronutrients ; Eastern Mediterranean Region ; review ; parental role modelling ; family environment ; availability and accessibility ; cluster randomised controlled trial ; minority ; parents ; prevention ; diet ; nutrition promotion ; Black/African American ; Hispanic ; qualitative ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFC Cultural studies::JFCV Food & society
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This reprint focuses on the mechanisms, modeling and controlling techniques of flash flood disasters, mainly in mountainous areas. Flash floods are among the most severe natural disasters, and the current publication will not only inspire future research but also enrich the current practice of flash flood disaster prevention and mitigation. This collection focusses on the engaged efforts in mitigating flash flood disasters, deepening the understanding of the causes of disasters in existing cases, finding appropriate modeling approaches, and implementing mitigation strategies. The readers will find within this reprint significant contributions for improving prevention and developing mitigation strategies, as well as protecting the safety of exposed populations.
    Keywords: flood monitoring ; forecasting ; hazard exposure ; emergency response ; Vaisigano River ; Samoa ; SWAT ; CMADS ; TRMM ; the Danjiang river basin ; flash flood ; bifurcation ; confluence ; shallow-water models ; flash-flood modelling system ; disaster mechanism ; runoff generation component ; disaster amplification effect ; economic losses from flood disasters ; flash flood disaster control ; Kaya identity ; LMDI technique decomposition method ; flood hazard ; morphometry ; PCA ; logistic regression ; Sinai ; Egypt ; grass coverage rate ; grass spatial arrangement patterns ; slope-gully system ; erosion ; debris flow ; lateral erosion ; strong earthquake area ; model experiment ; erosion pattern ; Tlalnepantla River ; flash floods ; hyetograph shape ; Hec Ras 2d ; Dorrigo diagram ; regionalization ; hydrological model ; hydrodynamic model ; disaster review analysis ; heavy rainfall in Henan ; periglacial debris flow ; southeast Tibet ; small sample imbalanced data ; prediction model ; random forest ; mountain torrents ; distributed hydrological model ; parameters regionalization ; machine learning ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    Springer Nature | Springer International Publishing
    Publication Date: 2022-07-14
    Description: This is an open access book. This book comprises all the single courses given as part of the First Summer School on Process Mining, PMSS 2022, which was held in Aachen, Germany, during July 4-8, 2022. This volume contains 17 chapters organized into the following topical sections: Introduction; process discovery; conformance checking; data preprocessing; process enhancement and monitoring; assorted process mining topics; industrial perspective and applications; and closing.
    Keywords: business process management ; process mining ; process discovery ; conformance checking ; knowledge graphs ; data science ; data mining ; stream data management ; RPA - Robotic Process Automation ; bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJQ Business mathematics & systems ; bic Book Industry Communication::U Computing & information technology::UB Information technology: general issues ; bic Book Industry Communication::U Computing & information technology::UN Databases::UNF Data mining
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems.
    Keywords: hydraulic modelling ; pressure control valve ; pressure management ; remote real-time control ; stochastic consumption ; water distribution system ; fault identification ; hydraulic transient ; inverse transient analysis (ITA) ; water distribution network ; optimization approach ; water distribution monitoring ; optimal sensor placement ; water network partitioning ; topological centrality ; smart water system ; framework ; smartness ; cyber wellness ; leakage ; sensitivity ; uncertainty ; entropy ; multi-criteria decision-making ; DEMATEL ; clustering ; district metered area ; network sectorization ; smart city ; water quality monitoring ; Internet of Things ; wireless sensor networks ; water treatment plant ; data analytics ; nitrate ; nitrite ; water demand forecasting ; hybrid model ; error correction ; chaotic time series ; least square support vector machine ; cross-correlation ; data spatial aggregation ; finite population effect ; metering ; sample mean ; sampling design ; standard error ; stochastic analysis ; water demand peak factor ; water distribution networks ; comparative analysis ; hydraulic measure ; multi-criteria decision analysis (MCDA) ; reliability index ; water distribution network (WDN) ; smart stormwater ; machine learning ; cluster analysis ; data science ; flooding detection ; rainwater harvesting ; water trading ; dual reticulation ; decentralized water supply ; agent-based modeling ; urban water management ; urban water consumption ; water demand data ; water data accessibility ; data resolution ; smart meter ; smart water systems ; cyber–physical security ; cyber-security ; cyber–physical attacks ; n/a ; water distribution systems ; cyber-attack detection ; blind sources separation ; FastICA ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: Streams and rivers are subject to considerable hydrodynamic loads. Flow interactions with natural or man-made structures in open channels lead to the development of complex dynamic processes, requiring further studies to comprehend fully. This Special Issue has been conceived to facilitate improvement or propose new approaches, summarize the most important findings of previous studies, and encourage the development of further knowledge in the field of open-channel flows. Various topics are addressed in this SI, including flow interaction with hydraulic structures, flow dynamics in estuaries, flow-vegetation interactions, bed sediment effects on flow structures, and the effect of channel curvature on flow behaviors and sediment transport. The studies published in this Special Issue certainly help readers understand the turbulent flow involved in open channels and apply that understanding to the design and practice of hydraulic engineering and river management.
    Keywords: sinuous channel ; velocity fluctuations ; river bend erosion ; structure function ; debris flows ; flow velocity ; sediment concentration ; prevision ; river hydraulics ; vegetation ; flow resistance ; turbulence ; numerical methods ; scour ; equilibrium condition ; velocity field ; secondary currents ; acoustic Doppler velocimeter ; rough bed ; secondary flow ; turbulent bursting ; turbulence kinetic energy ; friction coefficient ; open-channel flow ; entropy ; Reynolds number ; rigid vegetation ; bed roughness ; turbulent flow ; Turbulent Kinetic Energy (TKE) ; energy spectra ; bridge scour ; empirical formulae ; riprap sloping structure ; flow contraction ; overtopping flow ; stochastic analysis ; forecasting ; extreme events ; solitary wave ; turbulent coherent structures ; length scales ; wavelet transform ; turbulent velocity ; transport mechanism ; tidal range ; suspended sediment flux ; Oued Sebou estuary ; bathymetry ; dredging ; SWAN ; wave spreading ; flow hydrodynamic structures ; lateral deflectors ; gentle-slope tunnel ; water-wing ; shock wave ; energy dissipation ; 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: 2024-04-11
    Description: This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.
    Keywords: TA1-2040 ; T1-995 ; programmable appliances ; energy management system ; MILP ; sensitivity analysis ; simulation ; development demand ; meta heuristic techniques ; feedback ; patent analysis ; optimization ; scenario planning ; micro grids ; solar generation ; IEC 61499 ; distributed energy management algorithm ; technology adoption ; ToU tariff ; photovoltaic power ; seawater pumped storage ; peak reduction ; planning ; K-modes clustering ; Gaussian process regression ; multilayer perceptron neural network ; economic feasibility analysis ; EnergyPlus ; intruder detection system ; occupant behavior ; HOMER ; smart grid security ; D strategy ; smart energy ; IEC 61850 ; cyberattacks ; semantic web technologies ; renewable energy sources ; optimal power flows ; forecasting ; heuristic ; households ; machine learning ; micro grid ; support vector machine ; comprehensive evaluation ; electricity charge discount program ; model driven architecture ; sustainable smart grid technology ; rules ; daily consumption curve ; genetic algorithm ; renewable energy ; combined dispatch (CD) strategy ; scheduling ; technology acceptance ; electric vehicle charging technology ; energy consumption ; ontology ; theories of social practice ; R&amp ; unbalanced three-phase distribution networks ; game theory ; sustainability ; distributed generation ; energy storage system ; energy and water consumption ; active distribution networks ; policy effectiveness evaluation ; peak/off-peak ; differentiation ; graph theory ; D planning ; data mining ; values ; optimal power flow ; Smart Grid Station ; Korean Time Use Survey ; smart grid architecture model ; single-person household ; holomorphic embedding load flow method ; storage device ; smart grid ; smart metering ; engineering support ; two-stage ; net present cost (NPC) ; nash equilibrium ; STEEP analysis ; electrical distribution system ; solar power generation prediction ; storage capacity ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 31
    Publication Date: 2024-04-06
    Description: The theme of ‘Managing the digital transformation of the construction industry’ emphasises the importance of considering various dimensions of digitalisation and optimising the built environment. This review aims to present methodological approaches from existing literature that elucidate location-related factors impacting the capital cost of data centres. These findings facilitate adjustments to historical cost data when estimating total costs for new data centres. A systematic literature review method was employed to ensure an objective and comprehensive synthesis. In conjunction with Bayes's theory, this review identifies that a Delphi methodology is the most suitable methodological approach for forecasting and modelling capital expenditure for hyper-scale data centres. The methodology enables collective decision-making and consensus building, recognising the stakeholder's pivotal role in shaping the future of data centres. These findings offer valuable insights for researchers and practitioners in forming a methodological approach for further investigations into the location-related factors impacting the capital cost of data centres. Embracing this knowledge allows us to align research and practice, ensuring that these practices become integral to shaping the future of data centres and the digitalisation and optimisation of the built environment
    Keywords: cost ; decision analysis ; forecasting ; data centres ; thema EDItEUR::U Computing and Information Technology
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.
    Keywords: allied in-situ injection and production (AIIP) ; CO2 huff and puff ; shale oil reservoirs ; enhanced oil recovery ; renewable energy sources ; forecasting ; Weibull distribution ; neural networks ; optimal economic dispatch ; particle swarm optimization ; distribution network (DN) ; doubly-fed induction generator (DFIG) ; feeder automation (FA) ; compatibility ; adaptive control strategy (ACS) ; coordination technology ; air-cooled condenser ; mechanical draft wet-cooling towers ; hot recirculation rate ; complex building environment ; numerical simulation ; Neutral Point Clamped Z-Source Inverter (NPCZSI) ; shoot-through duty ratio ; modulation index ; voltage gain ; power quality ; dynamic modeling ; DC-DC converter ; electric vehicle (EV) ; charge pump capacitor ; fuzzy logic control ; maximum power point tracking ; photovoltaic ; push pull converter ; off-grid voltage source inverter ; medium voltage distribution network ; switch station ; electric vehicle ; DC–DC converter ; reconfiguration ; orderly charging ; grey wolf optimizer ; electrical harmonics ; harmonic estimation ; total harmonic distortion ; battery energy storage system ; third-harmonic current injection ; high efficiency ; active damping ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 33
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint includes 14 articles in Biomedical Data Science in honor of Professor Philip Bourne. Contributed by world-renowned experts, these articles cover a broad range of topics in machine learning, biophysics, bioinformatics, and systems biology.
    Keywords: structure-based drug discovery ; ligand binding sites ; deep learning ; graph neural network ; CRISPR/Cas9 ; genome editing ; machine learning ; SHAP values ; binding energy ; off-targets ; drug discovery ; retrosynthesis ; reaction template ; recurrent neural network ; and graph neural network ; mutational signatures ; smoking ; lung cancers ; APOBEC ; immune response to smoking ; cell-type composition ; goblet cells ; ciliated cells ; basal cells ; Protein Data Bank ; Open Access ; Worldwide Protein Data Bank ; macromolecular crystallography ; cryogenic electron microscopy ; cryogenic electron tomography ; electron crystallography ; micro-electron diffraction ; nuclear magnetic resonance spectroscopy ; biological macromolecules ; proteins ; nucleic acids ; DNA ; RNA ; carbohydrates ; small-molecule ligands ; social determinants of health ; electronic health records ; real-world evidence ; census tract ; data science ; protein database ; search tool ; prioritization algorithm ; drug repositioning ; quantum machine learning ; quantum metric learning ; kernel method ; kernel classifiers ; structural bioinformatics ; function annotation ; specificity annotation ; MSA ; entropy ; variability ; amino acids ; Philip Bourne ; FAIR ; bioinformatics ; n/a ; protein kinases ; functional families ; KinFams ; KinBase classification ; large language models ; pharmacovigilance ; social media ; drugs of abuse ; DNA sequencing ; read classification ; metagenomics ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.
    Keywords: vacuum tank degasser ; rule extraction ; extreme learning machine ; classification and regression trees ; wind power: wind speed: T–S fuzzy model: forecasting ; linearization ; machine learning ; photovoltaic output power forecasting ; hybrid interval forecasting ; relevance vector machine ; sample entropy ; ensemble empirical mode decomposition ; high permeability renewable energy ; blockchain technology ; energy router ; QoS index of energy flow ; MOPSO algorithm ; scheduling optimization ; Adaptive Neuro-Fuzzy Inference System ; insulator fault forecast ; wavelet packets ; time series forecasting ; power quality ; harmonic parameter ; harmonic responsibility ; monitoring data without phase angle ; parameter estimation ; blockchain ; energy internet ; information security ; forecasting ; clustering ; energy systems ; classification ; integrated energy system ; risk assessment ; component accident set ; vulnerability ; hybrid AC/DC power system ; stochastic optimization ; renewable energy source ; Volterra models ; wind turbine ; maintenance ; fatigue ; power control ; offshore wind farm ; Interfacial tension ; transformer oil parameters ; harmonic impedance ; traction network ; harmonic impedance identification ; linear regression model ; data evolution mechanism ; cast-resin transformers ; abnormal defects ; partial discharge ; pattern recognition ; hierarchical clustering ; decision tree ; industrial mathematics ; inverse problems ; intelligent control ; artificial intelligence ; energy management system ; smart microgrid ; optimization ; Volterra equations ; energy storage ; load leveling ; cyber-physical systems ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 35
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-11-17
    Description: The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields.
    Keywords: readmission prediction ; intensive care unit (ICU) ; recurrent neural network (RNN) ; longshort-term memory (LSTM) ; machine learning (ML) ; time series analysis ; health forecasting ; spectrum ; utilization ; prediction ; time-series ; clustering ; K-Means ; LSTM ; CNN ; outlier detection ; outlier detection in time series ; time series clustering ; time series cluster evaluation ; time series ; anomaly detection ; predictive maintenance ; model evaluation ; error diagnosis ; convolutional neural network ; all sky images ; cloud-base height ; machinelearning ; : financial market volatility ; VAR-DCC-GARCH ; wavelet-based random forest ; forecasting ; synthetic data ; shareable data ; privacy ; cross-correlation ; DCCA method ; oil derivatives ; energy ; accessibility ; retainability ; Markov chain ; K-mean clustering ; mobile data traffic ; multivariate prediction ; temporal ; spatial ; COVID-19 ; time series forecasting ; NARNN ; ARIMA ; dynamic convergence ; stationarity ; unit root ; ecosystem respiration ; dynamic mode decomposition with control ; time delay embedding ; ordinal patterns ; structural breaks ; non-stationary time series ; hydrological data ; prediction intervals ; seq2seq ; oil production ;  automated machine learning ; machine learning ; time-series forecasting ;  PV systems ; faults ; diagnosis ; signal processing ; time series data ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The fluid flow in fracture porous media plays a significant role in the assessment of deep underground reservoirs, such as through CO2 sequestration, enhanced oil recovery, and geothermal energy development. Many methods have been employed—from laboratory experimentation to theoretical analysis and numerical simulations—and allowed for many useful conclusions. This Special Issue aims to report on the current advances related to this topic. This collection of 58 papers represents a wide variety of topics, including on granite permeability investigation, grouting, coal mining, roadway, and concrete, to name but a few. We sincerely hope that the papers published in this Special Issue will be an invaluable resource for our readers.
    Keywords: TA1-2040 ; T1-995 ; deformation feature ; minerals ; microstructure ; mixing ; permeability ; gas concentration ; water–rock interaction ; loose gangue backfill material ; unified pipe-network method ; fracture ; roof-cutting resistance ; crack ; similar-material ; movable fluid ; gob-side entry retaining (GER) ; rock-soil mechanics ; bed separation ; orthogonal tests ; charge separation ; water soaked height ; fluid flow in reclaimed soil ; laboratory experiment ; longwall mining ; grading broken gangue ; MIP ; elastic modulus ; effective stress ; permeability coefficient ; mixer ; naturally fracture ; SEM ; microstructure characteristics ; artificial joint rock ; fractured rock ; strata movement ; conservative solute ; particle velocity ; dry-wet cycles ; hydraulic fractures ; numerical calculation ; mechanical behaviors ; normalized conductivity-influence function ; fractured porous rock mass ; PPCZ ; segmented grouting ; non-aqueous phase liquid ; intelligent torque rheometer ; numerical analysis ; temperature ; unsaturated soil ; uniaxial compressive strength ; mine shaft ; coalbed methane (CBM) ; nonlinear flow in fractured porous media ; similar simulation ; forecasting ; tight sandstones ; oriented perforation ; hydro-mechanical coupling ; constant normal stiffness conditions ; cohesive soils ; layered progressive grouting ; chemical grouts ; grain size of sand ; Darcy’s law ; soft coal masses ; hydro-power ; cyclic heating and cooling ; cohesive element method ; cement-based paste discharge ; tectonically deformed coal ; split grouting ; fault water inrush ; filtration effects ; T-stress ; particle flow modeling ; new cementitious material ; strength ; stabilization ; fractured porous medium ; brine concentration ; initial water contained in sand ; XRD ; fracture criteria ; hydraulic conductivity ; roadway deformation ; backfill mining ; adsorption/desorption properties ; pore pressure ; roughness ; cement–silicate grout ; compressive stress ; discrete element method ; dynamic characteristics ; strain-based percolation model ; thermal-hydrological-chemical interactions ; pore distribution characteristics ; transversely isotropic rocks ; nitric acid modification ; disaster-causing mechanism ; CH4 seepage ; crack distribution characteristics ; micro-CT ; relief excavation ; Darcy flow ; hydraulic fracturing ; mixed-form formulation ; propagation ; scanning electron microscope (SEM) images ; propagation pattern ; consolidation process ; rheological deformation ; gas adsorption ; soft filling medium ; ground pressure ; orthogonal ratio test ; rock fracture ; coal seams ; high-steep slope ; interface ; orthogonal test ; stress interference ; physical and mechanical parameters ; fracture propagation ; fluid–solid coupling theory ; coupling model ; surface characteristics ; numerical manifold method ; gas ; lignite ; water inrush prevention ; coupled THM model ; hard and thick magmatic rocks ; Ordos Basin ; porosity ; damage mechanics ; seepage ; degradation mechanism ; high temperature ; visualization system ; bentonite-sand mixtures ; contamination ; conductivity-influence function ; water-rock interaction ; deterioration ; seepage pressure ; glutenite ; adhesion efficiency ; mechanical behavior transition ; bedding plane orientation ; n/a ; enhanced gas recovery ; debris-resisting barriers ; reinforcement mechanism ; on-site monitoring ; geophysical prospecting ; cyclic wetting-drying ; scoops3D ; semi-analytical solution ; enhanced permeability ; management period ; seepage control ; deformation ; Yellow River Embankment ; impeded drainage boundary ; rheological test ; circular closed reservoir ; grout penetration ; viscoelastic fluid ; coal-like material ; paste-like slurry ; floor failure depth ; supercritical CO2 ; gravel ; numerical model ; fractal ; gas-bearing coal ; shear-flow coupled test ; rheological limit strain ; CO2 flooding ; flotation ; goaf ; slope stability ; damage ; coal and gas outburst ; hydraulic fracture ; anisotropy ; high-order ; effluents ; FLAC ; limestone roof ; sandstone ; TG/DTG ; Xinjiang ; two-phase flow ; model experiment ; coal particle ; volumetric strain ; failure mode ; land reclamation ; sandstone and mudstone particles ; contiguous seams ; CO2 geological storage ; numerical simulation ; geogrid ; stress relief ; optimum proportioning ; roadside backfill body (RBB) ; pervious concrete ; mudstone ; hydraulic fracture network ; grouted sand ; fractal pore characteristics ; refraction law ; segmented rheological model ; ductile failure ; heterogeneity ; flow law ; fracture closure ; coal measures sandstone ; tight sandstone gas reservoirs ; gob behaviors ; water-dripping roadway ; creep characteristics ; internal erosion ; warning levels of fault water inrush ; hydraulic aperture ; bolt support ; discontinuous natural fracture ; microscopic morphology ; critical hydraulic gradient ; mixed mode fracture resistance ; differential settlement ; alternate strata ; finite element method ; crushing ratio ; chloride ; glauberite cavern for storing oil &amp ; macroscopic mechanical behaviors ; collision angle ; adsorption performance ; failure mechanism ; mechanical properties ; transmissivity ; damage evolution ; gas fracturing ; multitude parameters ; deviatoric stress ; Jiaohe ; coal ; soil properties ; acoustic emission ; pore structure ; grouting experiment ; concrete ; confining pressures ; green mining ; gas drainage ; fluid viscosity ; compression deformation ; Unsaturation ; adsorption–desorption ; seepage-creep ; constitutive model ; soil particle size ; Pseudo Steady-State (PPS) constant ; soil–structure interface ; debris flow ; fracture grouting ; initial settlement position ; regression equation ; electrical potential ; secondary fracture ; surrounding rock ; solid backfill coal mining ; time variation ; excess pore-pressures ; finite-conductivity fracture ; permeability characteristics ; rainfall-unstable soil coupling mechanism(R-USCM) ; shaft lining ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint covers the following topics in the field of smart grids: 1. Optimal dg location and sizing to minimize losses and improve the voltage profile using garra rufa optimization. 2. Solar and wind energy forecasting for the green and intelligent migration of traditional energy sources. 3. Optimized micro-grid’s operation with electrical-vehicle-based hybridized sustainable algorithm. 4. The detection of nontechnical losses in smart meters using a MLP-GRU deep model and augmenting data via theft attacks. 5. A hybrid deep-learning-based model for the detection of electricity losses using big data in power systems. 6. Load frequency control and automatic voltage regulation in a multi-area interconnected power system using nature-inspired computation-based control methodology. 7. Line overload alleviations in wind energy integrated power systems using automatic generation control. 8. Electric price and load forecasting using a CNN-based ensembler in a smart grid. 9. Day-ahead energy forecasting in a smart grid considering the demand response and microgrids. 10. A dragonfly optimization algorithm for extracting the maximum power of grid-interfaced pv systems. 11. An economic load dispatch problem with multiple fuels and valve point effects using a hybrid genetic–artificial fish swarm algorithm. 12. Incentive-based dynamic pricing in a smart grid.
    Keywords: demand side management ; demand response ; load scheduling ; real time pricing ; genetic algorithm ; dynamic incentives ; artificial fish swarm algorithm ; economic load dispatch ; hybrid genetic–artificial fish swarm algorithm ; multi-objective optimization ; sustainable power generating system ; photovoltaic (PV) ; partial shading ; maximum power point tracking (MPPT) ; dragonfly optimization algorithm (DOA) ; adaptive cuckoo search optimization (ACSO) ; fruit fly optimization algorithm combined with general regression neural network (FFO-GRNN) ; improved particle swarm optimization (IPSO) ; voltage source inverter (VSI) ; total harmonic distortion (THD) ; energy optimization ; day ahead energy prediction ; artificial neural network ; renewable energy sources ; microgrid ; smart grid ; electricity price forecasting ; energy management ; electricity load forecasting ; convolutional neural network ; corona virus herd immunity optimization ; sustainable cities ; requirement-gathering tool ; qualitative comparison ; requirement engineering ; software engineering ; requirement-management tools ; automatic generation control ; wind energy ; transmission line security ; dispatch strategies ; Pakistan power system ; PI-PD controller ; load frequency control ; automatic voltage regulator ; nature-inspired optimization ; multi-area interconnected power system ; class imbalance ; gated recurrent units ; electricity theft detection ; non-technical losses ; smart grids ; deep learning ; GRU ; healthcare ; MLP ; PRECON ; smart cities ; smart meters ; sustainable society ; electric vehicles ; flexible load ; optimization ; renewable energy ; forecasting ; machine learning ; energy efficiency ; sustainability ; low carbon emission ; distribution generation ; Garra Rufa ptimization ; PSO ; GA ; power system ; urban sustainability ; local growth ; regional cities ; cultural heritage ; real estate ; intelligent regions ; innovation systems ; circular economy ; regional policies ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
    Language: English
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  • 38
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Twenty interesting studies on, among others, risks towards firm performance, financial risk and financial uncertainties, risk consequences for European countries’ businesses and economies from the Russia and Ukraine conflict, the effects of adopting enterprise risk management on the performance and risks of European publicly listed insurance firms, the management of financial risks while performing international commercial transactions, market liquidity and its dimensions, benchmarking as a way of finding risk factors in business performance, the effect of risk disclosure for trade credit, risk perception, accounting, and resilience in public sector organizations, and psychological effects from potential unexpected environmental disasters on investors. Although disasters are associated with risk, investors tend to have a different perspective depending on the source of the disaster. More specifically, if a country is facing a natural disaster, where no one can be blamed, the foreign investors who may hold a country’s bonds will continue to trust the country due to the “innocence” of the country. On the other hand, when a firm causes a technological disaster, such as a nuclear power plant explosion, investors, if this corporation is publicly traded, will “punish” the firm by selling its shares at any price to avoid a bigger loss.
    Keywords: na-tech ; systematic risk ; market reaction ; unexpected events ; investing ; banking ; clearinghouses ; systemic risk ; derisking ; drivers and implications of derisking ; risk management ; antimoney laundering (AML) ; combatting the financing of terrorism (CFT) ; financial services ; Malta ; small EU state ; proportionality ; conditional value-at-risk ; CVaR ; CVaR regression ; drawdown ; conditional drawdown-at-risk ; fund style classification ; resilience capacity ; cut-back management ; crisis ; Plato ; fairness ; commercial transactions ; international trade ; game theory ; risk disclosure ; trade credit ; content analysis ; Tunisian listed companies ; benchmarking ; best value ; business ; data envelopment analysis (DEA) ; performance ; risk factors ; microblogging data ; data mining ; investor sentiments ; asset pricing ; market liquidity ; liquidity dimensions ; option pricing ; utility indifference pricing ; transaction costs ; Hamilton-Jacobi-Bellman equation ; penalty methods ; finite difference approximation ; financial risk ; financial institutions ; international commerce ; profiteering ; non-fraudulent currency ; classical Athens ; risk ; bonds ; equities ; hedge funds ; forecasting ; GARCH ; value at risk ; enterprise risk management ; firm characteristics ; firm performance ; firm risk ; insurance firms ; COVID-19 ; helping behavior ; in-group identity ; risk perception ; severity of a local pandemic ; financial ; non-stationary ; time-series ; copula ; dependence ; univariate ; bivariate ; war in Ukraine ; Europe ; consequences ; economy ; companies ; embargo ; institutional volatility ; institutional rigidity ; political and social change ; regime risks ; Sparta ; Athens ; transformational change ; nonprofits ; NDIS Implementation Framework ; business models ; sustainability ; energy crisis risks ; nuclear energy ; renewable energy ; greenhouse gases emissions ; nuclear accidents ; nuclear weapons ; nuclear waste management ; capabilities ; reputation risk ; mediation model ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJC Business strategy ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
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  • 39
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-11-17
    Description: This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI.
    Keywords: artificial intelligence ; computer-aided diagnosis ; computed tomography ; lung cancer ; deep learning ; lung nodule detection ; lung nodule segmentation ; convolutional neural network ; cellular automaton ; reconstruction ; complexity ; optimization ; high energy physics ; Reddit ; user-based model ; polarization ; local search optimization ; hate speech ; hate spread ; countermeasures ; social networks ; opinion diffusion ; education ; deferring hate content ; cyber activism ; classical Arabic ; short vowels ; audio dataset ; convolutional neural networks ; regularization ; machine learning ; segmentation ; clustering ; forecasting ; book copies ; publishing industry ; gamification ; adaptive gamification ; player types ; computational finance ; fuzzy logic ; membership function ; Type-1 fuzzy sets ; T1FLS ; Type-2 fuzzy sets ; T2FLS ; women ; research ; CURE ; hierarchical clustering ; cluster validity indices ; Calinski–Harabasz index ; bootstrapping ; Industry 4.0 ; 3D printing ; cognitive states ; mental workload ; EEG analysis ; neural networks ; multimodal data fusion ; peer assessment ; multiagent system ; probabilistic model ; comparative analysis ; Bayesian network ; Artificial Intelligence ; urban water cycle ; hydrosocial urban cycle ; urban political ecology ; gender gap ; equity ; explainable AI ; fuzzy rules ; dominance-based rough set approach ; diabetic retinopathy ; AI ; disease surveillance ; pandemics ; global public health ; ethics ; data ; missing datasets ; data-driven studies ; women in artificial intelligence ; women in data science ; women in STEM ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 40
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: This reprint presents advances in operation and maintenance in solar plants, wind farms and microgrids. This compendium of scientific articles will help clarify the current advances in this subject, so it is expected that it will please the reader.
    Keywords: wind turbine ; electric generator ; spectral analysis ; fault diagnosis ; photovoltaic power forecasting ; data-driven ; deep learning ; variational autoencoders ; RNN ; angle swinging ; grid frequency oscillations ; electromechanical system ; inertial masses ; microgrids ; coordination protection ; distributed generation ; photovoltaic resources ; DigSILENT ; photovoltaic module ; defect detection ; power plant ; efficiency ; thermal image ; photovoltaic aging ; dark I-V curves ; bidirectional power inverter ; online distributed measurement of dark I-V curves ; sustainability ; compressive strength ; Bolomey formula ; sustainable concrete ; glass powder ; solar cell ; solar panel ; parameter extraction ; analytical ; Lambert W-function ; spacecraft solar panels ; I-V curve ; modeling ; wind power ; non-conventional renewable energy ; forecasting ; energy bands ; combinatorial optimization ; deep learning (DL) ; unmanned aerial vehicle (UAV) ; photovoltaic (PV) systems ; image-processing ; image segmentation ; semantic segmentation ; faults diagnostic ; artificial intelligence ; unbalanced datasets ; synthetic data ; artificial neural network based MPPT ; hybrid boost converter ; renewable energies ; solar power system ; microgrid ; control system ; storage system ; primary control ; photovoltaic (PV) plants ; coverage path planning (CPP) ; corrosion monitoring ; FPGA ; offshore wind turbines ; ultrasound ; thickness loss ; SCADA ; visualisation ; software ; wind-turbine ; windfarm ; cross-platform ; HMI ; GUI ; corrosion ; monitoring ; photovoltaic systems ; expected energy models ; fleet-scale ; lasso regression ; performance modeling ; machine learning ; fault location in photovoltaic arrays ; failure modes simulation ; fault detection criterion ; adaptive protection ; distributed power generation ; power distribution ; power system protection ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems.
    Keywords: passive house ; enclosure structure ; heat transfer coefficient ; energy consumption ; turbo-propeller ; regional ; fuel ; weight ; range ; design ; CO2 reduction ; multi-objective combinatorial optimization ; meta-heuristics ; ant colony optimization ; non-intrusive load monitoring ; appliance classification ; appliance feature ; recurrence graph ; weighted recurrence graph ; V–I trajectory ; convolutional neural network ; energy baselines ; machine learning ; clustering ; neural methods ; smart intelligent systems ; building energy consumption ; building load forecasting ; energy efficiency ; thermal improved of buildings ; anti-icing ; heat and mass transfer ; heating power distribution ; heat load reduction ; optimization method ; experimental validation ; big data process ; predictive maintenance ; fracturing roofs to maintain entry (FRME) ; field measurement ; numerical simulation ; side abutment pressure ; strata movement ; energy ; manufacturing ; prediction ; forecasting ; modelling ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 42
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The protection and maintenance of environmental resources for future generations require responsible interaction between humans and the environment in order to avoid wasting natural resources. According to an ancient Native American proverb, “We do not inherit the Earth from our ancestors; we borrow it from our children.” This indigenous wisdom has the potential to play a significant role in defining environmental sustainability. Recent technological advances could sustain humankind and allow for comfortable living. However, not all of these advancements have the potential to protect the environment for future generations. Developing societies and maintaining the sustainability of the ecosystem require appropriate wisdom, technology, and management collaboration. This book is a collection of 19 important articles (15 research articles, 3 review papers, and 1 editorial) that were published in the Special Issue of the journal Sustainability entitled “Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development” during 2021-2022.addresses the policymakers and decision-makers who are willing to develop societies that practice environmental sustainability, by collecting the most recent contributions on the appropriate wisdom, technology, and management regarding the different aspects of a community that can retain environmental sustainability.
    Keywords: metals ; arsenic ; pollution ; Mexico ; developing countries ; landfill ; urban solid waste ; disposal ; waste management ; sustainable development goals ; ethnobotany ; human health ; poverty ; traditional knowledge ; sustainable agriculture ; wheat ; seed rate ; yield effect ; dose–response ; seed recycling ; cost–benefit analysis ; blockchain ; SDGs ; innovation ; COVID-19 ; green recovery ; scorecard ; construction sector ; economy ; intersectoral linkages ; VECM ; forecasting ; sustainable development ; eco-friendly sound-absorbing material ; corrugated cardboard ; perforated corrugated cardboard ; sound-absorption coefficient ; sound transmission loss ; transfer function method ; transfer matrix method ; multi-frequency resonator ; self-compacting concrete ; crumb rubber ; strength ; silica fume ; response surface methodology ; biodiesel ; engine performance ; emissions ; natural feedstocks ; production method ; ethical marketing ; extended marketing mix ; consumer brand relationships ; brand loyalty ; sustainability ; rice husk ; power plants ; CO2 ; emission reductions ; Clean Development Mechanism ; rural clean heating project ; rural Gansu ; potential solutions ; benchmarking ; fisheries ; aquaculture ; food security ; Bangladesh ; humanitarian logistics ; pandemic ; economic reactivation ; spatial modelling ; sustainable construction ; construction waste reduction ; modelling of waste (reduce, reuse and recycle) ; PLS-SEM ; industry 4.0 ; circular economy ; environmental regulations ; manufacturing supply chains ; Internet of Things (IoT) ; groundwater level ; groundwater resource ; groundwater management models ; groundwater monitoring system ; wireless sensor network ; MENA Islamic cities ; urban management ; sustainable built environment ; supplier selection ; product life cycle cost ; geometric mean weighting ; penalty weighting ; multiobjective linear programming ; revised multichoice goal programming ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
    Language: English
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  • 43
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The fluid flow in fracture porous media plays a significant role in the assessment of deep underground reservoirs, such as through CO2 sequestration, enhanced oil recovery, and geothermal energy development. Many methods have been employed—from laboratory experimentation to theoretical analysis and numerical simulations—and allowed for many useful conclusions. This Special Issue aims to report on the current advances related to this topic. This collection of 58 papers represents a wide variety of topics, including on granite permeability investigation, grouting, coal mining, roadway, and concrete, to name but a few. We sincerely hope that the papers published in this Special Issue will be an invaluable resource for our readers.
    Keywords: TA1-2040 ; T1-995 ; deformation feature ; minerals ; microstructure ; mixing ; permeability ; gas concentration ; water–rock interaction ; loose gangue backfill material ; unified pipe-network method ; fracture ; roof-cutting resistance ; crack ; similar-material ; movable fluid ; gob-side entry retaining (GER) ; rock-soil mechanics ; bed separation ; orthogonal tests ; charge separation ; water soaked height ; fluid flow in reclaimed soil ; laboratory experiment ; longwall mining ; grading broken gangue ; MIP ; elastic modulus ; effective stress ; permeability coefficient ; mixer ; naturally fracture ; SEM ; microstructure characteristics ; artificial joint rock ; fractured rock ; strata movement ; conservative solute ; particle velocity ; dry-wet cycles ; hydraulic fractures ; numerical calculation ; mechanical behaviors ; normalized conductivity-influence function ; fractured porous rock mass ; PPCZ ; segmented grouting ; non-aqueous phase liquid ; intelligent torque rheometer ; numerical analysis ; temperature ; unsaturated soil ; uniaxial compressive strength ; mine shaft ; coalbed methane (CBM) ; nonlinear flow in fractured porous media ; similar simulation ; forecasting ; tight sandstones ; oriented perforation ; hydro-mechanical coupling ; constant normal stiffness conditions ; cohesive soils ; layered progressive grouting ; chemical grouts ; grain size of sand ; Darcy’s law ; soft coal masses ; hydro-power ; cyclic heating and cooling ; cohesive element method ; cement-based paste discharge ; tectonically deformed coal ; split grouting ; fault water inrush ; filtration effects ; T-stress ; particle flow modeling ; new cementitious material ; strength ; stabilization ; fractured porous medium ; brine concentration ; initial water contained in sand ; XRD ; fracture criteria ; hydraulic conductivity ; roadway deformation ; backfill mining ; adsorption/desorption properties ; pore pressure ; roughness ; cement–silicate grout ; compressive stress ; discrete element method ; dynamic characteristics ; strain-based percolation model ; thermal-hydrological-chemical interactions ; pore distribution characteristics ; transversely isotropic rocks ; nitric acid modification ; disaster-causing mechanism ; CH4 seepage ; crack distribution characteristics ; micro-CT ; relief excavation ; Darcy flow ; hydraulic fracturing ; mixed-form formulation ; propagation ; scanning electron microscope (SEM) images ; propagation pattern ; consolidation process ; rheological deformation ; gas adsorption ; soft filling medium ; ground pressure ; orthogonal ratio test ; rock fracture ; coal seams ; high-steep slope ; interface ; orthogonal test ; stress interference ; physical and mechanical parameters ; fracture propagation ; fluid–solid coupling theory ; coupling model ; surface characteristics ; numerical manifold method ; gas ; lignite ; water inrush prevention ; coupled THM model ; hard and thick magmatic rocks ; Ordos Basin ; porosity ; damage mechanics ; seepage ; degradation mechanism ; high temperature ; visualization system ; bentonite-sand mixtures ; contamination ; conductivity-influence function ; water-rock interaction ; deterioration ; seepage pressure ; glutenite ; adhesion efficiency ; mechanical behavior transition ; bedding plane orientation ; n/a ; enhanced gas recovery ; debris-resisting barriers ; reinforcement mechanism ; on-site monitoring ; geophysical prospecting ; cyclic wetting-drying ; scoops3D ; semi-analytical solution ; enhanced permeability ; management period ; seepage control ; deformation ; Yellow River Embankment ; impeded drainage boundary ; rheological test ; circular closed reservoir ; grout penetration ; viscoelastic fluid ; coal-like material ; paste-like slurry ; floor failure depth ; supercritical CO2 ; gravel ; numerical model ; fractal ; gas-bearing coal ; shear-flow coupled test ; rheological limit strain ; CO2 flooding ; flotation ; goaf ; slope stability ; damage ; coal and gas outburst ; hydraulic fracture ; anisotropy ; high-order ; effluents ; FLAC ; limestone roof ; sandstone ; TG/DTG ; Xinjiang ; two-phase flow ; model experiment ; coal particle ; volumetric strain ; failure mode ; land reclamation ; sandstone and mudstone particles ; contiguous seams ; CO2 geological storage ; numerical simulation ; geogrid ; stress relief ; optimum proportioning ; roadside backfill body (RBB) ; pervious concrete ; mudstone ; hydraulic fracture network ; grouted sand ; fractal pore characteristics ; refraction law ; segmented rheological model ; ductile failure ; heterogeneity ; flow law ; fracture closure ; coal measures sandstone ; tight sandstone gas reservoirs ; gob behaviors ; water-dripping roadway ; creep characteristics ; internal erosion ; warning levels of fault water inrush ; hydraulic aperture ; bolt support ; discontinuous natural fracture ; microscopic morphology ; critical hydraulic gradient ; mixed mode fracture resistance ; differential settlement ; alternate strata ; finite element method ; crushing ratio ; chloride ; glauberite cavern for storing oil &amp ; macroscopic mechanical behaviors ; collision angle ; adsorption performance ; failure mechanism ; mechanical properties ; transmissivity ; damage evolution ; gas fracturing ; multitude parameters ; deviatoric stress ; Jiaohe ; coal ; soil properties ; acoustic emission ; pore structure ; grouting experiment ; concrete ; confining pressures ; green mining ; gas drainage ; fluid viscosity ; compression deformation ; Unsaturation ; adsorption–desorption ; seepage-creep ; constitutive model ; soil particle size ; Pseudo Steady-State (PPS) constant ; soil–structure interface ; debris flow ; fracture grouting ; initial settlement position ; regression equation ; electrical potential ; secondary fracture ; surrounding rock ; solid backfill coal mining ; time variation ; excess pore-pressures ; finite-conductivity fracture ; permeability characteristics ; rainfall-unstable soil coupling mechanism(R-USCM) ; shaft lining ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.
    Keywords: TA1-2040 ; T1-995 ; online community ; bibliometric analysis ; KDE ; big data analytic methods ; TP organics ; skills ; topic analysis ; systematic and replicable patent analysis method ; SDE ; Guangzhou ; filtering ; point of interests (POI) ; framing ; innovation in sustainable agriculture ; researchers ; sentiment polarity classification ; illegal accommodation ; dynamic topic model ; network data analysis ; decision-making ; learning analytics ; research frontier ; prediction grades ; framings ; opinion mining ; association rule ; big data research ; Hong Kong ; place sustainability ; spatial accessibility of residential public services ; maturity model ; data science ; educational data mining ; spatiotemporal analysis ; information systems ; information diffusion ; smart citizens ; policy ; back-propagation neural network ; innovation ; social media big data ; lbsn ; GWR ; context–problem network ; Social network ; machine learning ; web science ; social good ; social sciences ; online data ; resource optimisation ; data commons ; sustainable agri-food systems ; social and humanistic computing ; product attributes ; analytics ; car review ; technology platforms ; big data ; community detection ; technopolitics ; transaction costs ; problem-solved concept ; sales prediction ; sentiment analysis ; Barcelona ; TripAdvisor ; innovation networks ; sustainability ; sustainable development ; experimental cities ; online travel review ; check-in density ; decision making ; smart cities ; GDPR ; hype cycle ; advanced business analytics ; institutional innovation ; temporal analytics ; data mining ; decision-makers ; online word-of-mouth ; knowledge management ; semantic network analysis ; sustainable wireless energy transmission technology ; housing problem ; social impact ; paradox ; early career ; Greek Attica ; text mining ; user-generated content ; social media ; big data analytics ; social networks ; sustainability development ; building stock management ; data analyst ; NodeXL ; review voting ; promising technology ; social inclusive economic growth ; destination image ; Xiamen City ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-14
    Description: Smart Farming - Integrating Conservation Agriculture, Information Technology, and Advanced Techniques for Sustainable Crop Production is a timely and comprehensive volume that explores the latest advances and opportunities in an emerging field. The book brings together experts from various disciplines to discuss the principles, practices, and technologies of smart farming, and their potential for sustainable agriculture. Topics include the adoption of conservation agriculture, information technology drivers in smart farming management systems, physiological breeding, and nanotechnology applications in smart farming. This book is intended for researchers, policymakers, and practitioners in the field of agriculture who are interested in exploring the latest developments in smart farming and its potential for enhancing crop production, reducing environmental impact, and increasing farmers’ profits.
    Keywords: remote sensing ; carbon nanotubes ; antibiotics ; iot ; sustainable agriculture ; data science ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming::TVB Agricultural science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-01-31
    Description: The concept of sustainability is important for companies both in the case of SMEs and worldwide multinational companies. Some key factors to help a company achieve its sustainability objectives are based on human resource management. Sustainable human resource management is a typical cross-functional task that becomes increasingly important at the strategic level of a company. Industry 4.0 technologies, Internet of Things, and competitive demands, as signs of globalization, have led to significant changes across the organizational structures and human resource strategies of companies. The increasing importance of sophisticated human resource strategies in the life of companies and the intention to find optimal design and operation strategies for sustainable human resource management were a motivation for launching this book. This book offers a selection of papers which explain the impact of smart human resource management on economy. Authors from 14 countries published working examples and case studies resulting from their research in this field. The aim of this book is to help students at the level of BSc, MSc, and PhD level, as well as managers and researchers, to understand and appreciate the concept, design, and implementation of sustainable human resource management solutions.
    Keywords: HF5549-5549.5 ; HF5001-6182 ; subordinates’ Moqi with supervisors ; talent management ; skills ; analytics ; autonomy ; administrative innovation ; HRM practices ; personal trait regulatory focus ; perceived insider status ; promotion of employees ; employee innovation ; employee motivation ; conceptual framework ; knowledge-sharing ; social support ; sustainable human resource management ; public sector universities ; strategic human resource management ; sustainability ; Semantic Web ; employee loyalty ; selection ; sustainable work systems ; regulating effect ; social network analysis ; teleworkers’ abilities ; job satisfaction ; participation ; manufacturing flexibility ; gender culture ; organizational cynicism ; labor market in postal sector ; training ; human resource policies ; telework ; stakeholders ; corporate social responsibility ; machine operator ; work–life balance ; high-commitment HRM system ; gender differences ; youth generation ; social exchange theory ; Afghanistan Ministry of Mines and Petroleum ; female CEOs ; Pakistan ; data science ; characteristics of sustainable human resource management ; product development ; personal resources ; social implications of telework ; process innovation ; employee empowerment ; organizational political climate ; power distance orientation ; job category ; industry 4.0 ; job performance ; organizational sustainability ; organizational socialization ; absorbing Markov-chain ; career path ; environment ; occupational stress ; collaboration ; sustainable organization ; employee structure ; employee satisfaction ; sustainable human resources ; sustainable HRM practices
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Existing competitiveness between companies in the global market requires a high degree of proactivity, with an aim of reducing costs, increasing quality, and providing the market with innovative products that are in line with the natural evolution of customer demands. The concepts of the Toyota Production System, which have led to the adoption of lean manufacturing, have helped industrial managers to implement tools and practices that eliminate or substantially reduce wastes that normally exist in conventional production lines. However, the need for successive increase in flexibility necessitates a more favorable evolution with technological advancements in the programming of equipment and devices, along with the use of robotics and the integration of information throughout the product manufacturing cycle using the IoT or powerful networks. This concept, usually referred to as Industry 4.0, is in line with the principles of lean manufacturing, although it can only be supported by a true technological revolution involving remote programming of machines, integration of manufacturing processes, and real-time control of the work performed through an entire production cycle. This Special Issue showcases important contributions in the area of lean manufacturing and Industry 4.0, with innovative concepts that will certainly enthuse and strengthen readers’ knowledge.
    Keywords: OEE ; KPIs ; action research ; lean ; operation process ; performance ; agroindustry ; lean manufacturing ; single minute exchange of die ; reduce setup time ; productivity gain ; shipbuilding ; sales ; lean management ; value stream mapping ; improvement ; yarn winding ; reels ; yarn coil extraction ; robotic manipulator ; robotic arm ; order release ; backlog sequencing ; re-entrant flow shop ; simulation ; Industry 4.0 ; medical device ; Medtech ; regulatory compliance ; engineering change management ; product lifecycle management ; Regulatory 4.0 ; Lean 4.0 ; determinants ; industry 4.0 ; logistics 4.0 ; ISM ; fuzzy MICMAC ; lean–green ; sustainability ; competitive priority ; operations strategy ; supplier ; milkrun ; in-plant logistics ; flexible assembly ; high-mix low-volume ; smart and sustainable manufacturing system ; dynamic lean 4.0 tools ; quality management ; Industry 5.0 ; data science ; social sustainability open data ; open-source tools ; 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
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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: microbiome ; metagenomics ; metabolomics ; multi-omics ; biostatistics ; computational biology ; statistical genomics ; data science ; thema EDItEUR::P Mathematics and Science::PD Science: general issues ; thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFN Medical genetics
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    Publication Date: 2023-12-20
    Description: The Helmholtz Association funded the ""Large-Scale Data Management and Analysis"" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities.
    Keywords: QA75.5-76.95 ; Data Science ; Datenlebenszyklus ; Datenmanagement ; data management ; data analysis ; data science ; Big Data ; Datenanalyse ; data life cycle ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-08-12
    Description: This book is a collection of the accepted papers presented at the Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) in conjunction with the 36th AAAI Conference on Artificial Intelligence 2022. During AIBSD 2022, the attendees addressed the existing issues of data bias and scarcity in Artificial Intelligence and discussed potential solutions in real-world scenarios. A set of papers presented at AIBSD 2022 is selected for further publication and included in this book.
    Keywords: out-of-distribution generalization ; forecasting ; temporal bias ; permutation equivariance ; optimization ; face-recognition models ; facial attributes ; social bias ; fairness ; natural language processing ; gender bias ; bias detection ; contextualized embeddings ; deep learning ; contrastive learning ; supervised contrastive learning ; transfer learning ; robustness ; noisy labels ; coresets ; 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: The construction industry is growing rapidly and time has changed the construction methods used. The traditional way of construction is becoming obsolete and technology is taking over. In this case, sustainable construction is the future and the new norm in the construction industry. Although there are various opportunities in this sector, there are also some challenges that exist and hinder productivity. Hence, this reprint covers the opportunities and challenges in sustainable construction.
    Keywords: thin film ; organic solar cell ; efficiency ; DBR ; temperature ; life cycle ; impact assessment ; recycled material ; geopolymer concrete ; sustainability ; workforce diversity ; technical skills ; motivation ; psychosocial ; construction worker ; productivity ; BIM ; post-disaster reconstruction ; construction industry ; scientometric analysis ; visualization ; PRISMA ; review ; RWL ; time series ; RHR ; seasonality ; prediction ; ANN ; SARIMA ; wastewater ; oil palm leaves activated carbon ; chemical activation ; COD ; adsorption ; green technology ; marble dust ; air pollution ; health hazards ; environmental pollution ; econometric analysis ; construction sector ; sustainable construction ; circular economy ; forecasting ; causal loop diagram ; construction management ; resilient supply chain ; sustainable supply chain ; supply chain management ; systems thinking ; forecasting models ; energy consumption ; smart buildings ; machine learning ; LSTM technique ; GIS ; PCA ; groundwater quality ; health risk ; solid waste ; error management climate ; psychological capital ; job stress ; aeronautical industry ; structural equation modeling ; IR 4.0 ; health and safety ; AHP ; barriers ; small contractors ; SEM ; Malaysia ; economy ; eco-materials ; energy ; environmental impact ; lean construction ; pollution ; prefabricated construction ; mediation analysis ; trust ; satisfaction ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-08
    Description: This volume gathers papers from the fields of philosophy, theology, and empirical psychology on the topic of gratitude to God. Central themes include the difference between gratitude to God and gratitude to human benefactors and correlations between gratitude to God and important life outcomes.
    Keywords: gratitude ; religiosity ; spirituality ; well-being ; Aquinas ; virtue ; religion ; gratitude to God ; health ; federal funding ; systematic review ; conceptual metaphor ; analogy ; anthropomorphism ; God concepts ; gratitude expressions ; public gratitude ; social media ; data science ; machine learning ; challenges ; review ; God ; supernatural attribution ; gift ; divine attributions ; religious attributions ; religious appraisals ; measurement ; religious belief ; liturgy ; group action ; joint action ; social ontology ; extraversion ; optimism ; vitality ; self-esteem ; agreeableness ; honesty–humility ; entitlement ; secure attachment ; construal ; religiousness ; Christianity ; theism ; Dietrich Bonhoeffer ; Jonathan Edwards ; Soren Kierkegaard ; Karl Barth ; creation ; Mozart ; Beethoven ; Bible ; doctrine of Scripture ; tradition ; inspiration ; church ; canon ; theology ; acceptance ; pantheism ; axiarchism ; ultimism ; Stoicism ; Kierkegaard ; local evils ; suffering ; transcendent gratitude ; cosmic gratitude ; transcendence ; beliefs ; case study ; qualitative ; doubt ; atheism ; agnosticism ; bic Book Industry Communication::H Humanities::HR Religion & beliefs ; thema EDItEUR::Q Philosophy and Religion::QR Religion and beliefs
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue presents the latest state-of-the-art research on solid fuels technology with dedicated, focused research papers. There are a variety of topics to choose from among the seven published re-search works to bring you up to date with the current trends in academia and industry.
    Keywords: peak shaving ; battery storage ; peak demand pricing ; lithium-ion ; tariff structure ; receiving-end system ; multi-infeed HVDCs ; security assessment ; emergency control strategy ; electromagnetic transient (EMT)-transient stability (TS) hybrid simulation ; impedance determination ; lossy compression algorithms ; singular value decomposition ; wavelet transformation ; voltage control ; deep deterministic policy gradient ; deep reinforcement learning ; model uncertainties ; energy communities ; machine learning ; forecasting ; abnormal data ; wind power ; outliers ; electricity consumption representative profiles ; self-consumption ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-01-31
    Description: This book focuses on sustainable energy systems. While several innovative and alternative concepts are presented, the topics of energy policy, life cycle assessment, thermal energy, and renewable energy also play a major role. Models on various temporal and geographical scales are developed to understand the conditions of technical as well as organizational change. New methods of modeling, which can fulfil technical and physical boundary conditions and nevertheless consider economic environmental and social aspects, are also developed.
    Keywords: Q1-390 ; QC1-999 ; coal-fired power unit ; capacity investment ; energy density ; sensitivity analysis ; fuel ; renewable energy source penetration ; AHP ; torrefaction ; Active Disturbance Rejection Control ; swell effect disturbance ; renewable energy ; resource efficiency ; choice experiment ; pseudo-Huber loss ; integrated model ; Probabilistic Robustness ; sustainable energy ; Energy Life-Cycle Assessment ; hysteresis switching ; areal grey relational analysis ; market power ; photovoltaic with energy storage system ; wind power plants ; power system stability ; alternative energy ; hollow rollers ; efficiency ; generation system scheduling ; energy from biomass ; fuelwood value index ; manufacturing industry ; game theory ; energy modelling ; peach ; grindability ; artificial neural networks control ; sustainability ; large bearings ; levelized cost of energy ; renewable energies ; ash recovery ; thermodynamic cycle concepts ; modified cycle concepts ; HOMER simulation ; low-carbon economy ; energy systems ; fuzzy logic control ; basic plan for long-term electricity supply and demand ; LCOE comparison ; post-harvest ; heating value ; power supply reliability ; Pinus pinaster ; doubly fed induction generator ; willingness to pay ; multilayer perception ; robust optimization ; forecasting model for electricity demand ; transient impact ; uncertainty ; power electronics ; electrostatic devices ; flexibility ; active power harmonics filter ; Monte Carlo ; energy storage systems ; energy costs ; SWOT analysis ; tidal stream generator ; textile industrial sector ; stochastic approach ; deficit ; uncertainty analysis ; rotary reactor ; biomass ; secondary air regulation ; forecasting ; photovoltaic ; electricity ; Internet of Things ; dynamic planning ; fuzzy rough set ; flexible resource ; wind resources ; op-amp ; maximum power point tracking ; nexus concept
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.
    Keywords: QA75.5-76.95 ; T58.5-58.64 ; Ensemble Empirical Mode Decomposition ; Brain Storm Optimization ; asset management ; institutional investors ; state transition algorithm ; kernel ridge regression ; energy price hedging ; multi-objective grey wolf optimizer ; five-year project ; complementary ensemble empirical mode decomposition (CEEMD) ; active investment ; portfolio management ; Long Short Term Memory ; time series forecasting ; LEM2 ; improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) ; feature selection ; Markov-switching GARCH ; condition-based maintenance ; substation project cost forecasting model ; Gaussian processes regression ; deep convolutional neural network ; individual ; wind speed ; empirical mode decomposition (EMD) ; crude oil prices ; artificial intelligence techniques ; intrinsic mode function (IMF) ; multi-step wind speed prediction ; support vector regression (SVR) ; short term load forecasting ; energy futures ; General Regression Neural Network ; metamodel ; sparse Bayesian learning (SBL) ; commodities ; ensemble ; comparative analysis ; crude oil price forecasting ; electrical power load ; differential evolution (DE) ; fuzzy time series ; kernel learning ; short-term load forecasting ; data inconsistency rate ; renewable energy consumption ; long short-term memory ; energy forecasting ; modified fruit fly optimization algorithm ; forecasting ; combination forecasting ; Markov-switching ; weighted k-nearest neighbor (W-K-NN) algorithm ; hybrid model ; interpolation ; particle swarm optimization (PSO) algorithm ; regression ; diversification ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    The MIT Press | The MIT Press
    Publication Date: 2024-04-11
    Description: How is digitalization of the offshore oil industry fundamentally changing how we understand work and ways of knowing? Digitalization sits at the forefront of public and academic conversation today, calling into question how we work and how we know. In Digital Oil, Eric Monteiro uses the Norwegian offshore oil and gas industry as a lens to investigate the effects of digitalization on embodied labor and, in doing so, shows how our use of new digital technology transforms work and knowing. For years, roughnecks have performed the dangerous and unwieldy work of extracting the oil that lies three miles below the seabed along the Norwegian continental shelf. Today, the Norwegian oil industry is largely digital, operated by sensors and driven by data. Digital representations of physical processes inform work practices and decision-making with remotely operated, unmanned deep-sea facilities. Drawing on two decades of in-depth interviews, observations, news clips, and studies of this industry, Monteiro dismantles the divide between the virtual and the physical in Digital Oil. What is gained or lost when objects and processes become algorithmic phenomena with the digital inferred from the physical? How can data-driven work practices and operational decision-making approximate qualitative interpretation, professional judgement, and evaluation? How are emergent digital platforms and infrastructures, as machineries of knowing, enabling digitalization? In answering these questions Monteiro offers a novel analysis of digitalization as an effort to press the limits of quantification of the qualitative.
    Keywords: digitalization ; datafication ; data science ; quantification of quality ; work practices ; knowing ; digital transformation ; offshore oil and gas ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::U Computing and Information Technology::UY Computer science ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJM Management and management techniques::KJMK Knowledge management
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    Springer Nature | Apress
    Publication Date: 2024-04-14
    Description: This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will Learn Optimize core operations based on N-dimensional arrays Design and implement an industry-level algorithmic differentiation module Implement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiation Design and optimize a computation graph module, and understand the benefits it brings to the numerical computing library Accommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computation Use the Zoo system for efficient scripting, code sharing, service deployment, and composition Design and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up.
    Keywords: programming language ; OCaml ; scientific computing ; computational ; debugging ; open source ; source ; code ; numerical ; data science ; big data ; owl ; functional ; math ; scientific ; engineering ; thema EDItEUR::U Computing and Information Technology ; thema EDItEUR::U Computing and Information Technology::UY Computer science ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
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    Collège de France
    Publication Date: 2022-02-01
    Description: Relational database management systems, using as foundations a formal language, first-order logic, serve as mediators between individuals and machines. With the increase in the volume of data disseminated on the Web, a “collective intelligence” is currently emerging, shaped by large search engines whose monopoly raises ethical and political questions. One of the main challenges for the coming years is the development of technologies that will make it possible to find, evaluate, validate, veri...
    Keywords: inaugural lecture ; computer science ; data science ; Web ; knowledge ; algorithm
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-29
    Description: Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.
    Keywords: level, slope, and curvature of the yield curve ; Nelson-Siegel factors ; supervised factor models ; combining forecasts ; principal components ; Minimum variance portfolio ; risk ; shrinkage ; S&amp ; P 500 ; high-frequency ; volatility ; forecasting ; realized measures ; bivariate GARCH ; Japanese candlestick ; ordered fuzzy number ; Kosiński’s number ; oriented fuzzy number ; dynamic analysis of securities ; integrated volatility ; high-frequency data ; jumps ; realized skewness ; cross-sectional stock returns ; signed jump variation ; long-range dependence ; log periodogram regression ; smoothed periodogram ; subsampling ; intraday returns ; portfolio selection ; maximum diversification ; regularization ; thema EDItEUR::K Economics, Finance, Business and Management
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: With the development of computer technology and communication technology, various industries have collected a large amount of data in different forms, so-called big data. How to obtain valuable knowledge from these data is a very challenging task. Machine learning is such a direct and effective method for big data analytics. In recent years, a variety of advanced machine learning technologies have emerged, and they continue to play important roles in the era of big data. Considering advanced machine learning and big data together, we have selected a series of relevant works in this Special Issue to showcase the latest research advancements in this field. Specifically, a total of thirty-three articles are included in this Special Issue, which can be roughly categorized into six groups: time series analysis, evolutionary computation, pattern recognition, computer vision, image encryption, and others.
    Keywords: energy storage ; model predictive control ; peak shaving and frequency regulation ; output optimization ; global optimization ; meta-heuristic ; support vector machine swarm intelligence ; hyperspectral image classification ; CNN ; ELM ; PSO ; deep feature ; butterfly optimization algorithm ; random replacement ; crisscross search ; overseas Chinese associations ; support vector machine ; short-term traffic-flow forecasting ; bagging model ; stacking model ; ridge regression ; error coefficient ; least squares method ; support vector machines ; principal component analysis ; quick access recorder ; mean absolute error ; high-plateau flight ; event extraction ; event type ; event trigger words ; stock announcement news ; stock return ; traffic flow forecasting ; long short-term memory network ; graph convolutional network ; target detection ; infrared ; deep learning ; YOLOv5 algorithm ; design science research ; performance analysis ; machine learning ; classification algorithms ; clustering algorithms ; pilot abnormal behavior ; behavior detection ; YOLOv4 algorithm ; CBAM ; flight safety ; fault diagnosis ; variational mode decomposition ; composite multi-scale dispersion entropy ; particle swarm optimization ; deep belief network ; CBCFI ; combined prediction model ; ARMA ; GM ; GA ; BP ; hierarchical clustering ; Jaccard distance ; membership grade ; community clustering ; lightweight neural networks ; attentional mechanisms ; Hemerocallis citrina Baroni ; maturity detection ; cloud ; digital archives ; confidentiality management ; information system ; emotion-cause pair extraction ; heterogeneous graph ; graph attention network ; hierarchical model ; spatial-temporal systems ; neural networks ; information systems ; forecasting ; time series ; coupled map lattice ; polymorphic mapping ; color image ; hash function ; pixel level ; differential evolution ; capacitated vehicle routing planning ; saving mileage ; gravity search ; object detection ; computer vision ; border patrol ; COVID-19 ; warning system ; PROPHET ; health ; quantum dynamics ; neural architecture search ; image classification ; swarm intelligence ; whale optimization algorithm ; extreme learning machine ; talent stability prediction ; adversarial attacks ; document classification ; NLP ; convolutional neural networks ; disease classification ; generative adversarial network ; tomato leaf ; multi-strategy ; dual-update strategy ; mean-semivariance model ; portfolio optimization ; DNA computing ; DNA sequences design ; improved matrix particle swarm optimization algorithm (IMPSO) ; opposition-based learning ; signal-to-noise ratio distance ; time series classification ; complementary ensemble empirical mode decomposition (CEEMD) ; MultiRocket ; feature selection ; hybrid model ; multi-behavior recommendation ; sequential recommendation ; graph neural network ; embedding propagation ; 1D quadratic chaotic system ; image encryption ; splicing model ; DNA coding ; BaaS system ; blockchain consensus algorithm ; KNN ; service level agreement ; transaction priority ; data stream mining ; forex ; online learning ; adaptive learning ; incremental learning ; sliding window ; concept drift ; financial time series forecasting ; 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: 2024-04-11
    Description: Modern power systems are affected by many sources of uncertainty, driven by the spread of renewable generation, by the development of liberalized energy market systems and by the intrinsic random behavior of the final energy customers. Forecasting is, therefore, a crucial task in planning and managing modern power systems at any level: from transmission to distribution networks, and in also the new context of smart grids. Recent trends suggest the suitability of ensemble approaches in order to increase the versatility and robustness of forecasting systems. Stacking, boosting, and bagging techniques have recently started to attract the interest of power system practitioners. This book addresses the development of new, advanced, ensemble forecasting methods applied to power systems, collecting recent contributions to the development of accurate forecasts of energy-related variables by some of the most qualified experts in energy forecasting. Typical areas of research (renewable energy forecasting, load forecasting, energy price forecasting) are investigated, with relevant applications to the use of forecasts in energy management systems.
    Keywords: TA1-2040 ; T1-995 ; forecast combination ; solar energy ; electricity price forecasting ; calibration window ; heuristic algorithm ; deep learning ; electric load forecasting ; smart grids ; hierarchical load forecasting ; predictive distribution ; solar PV ; solar farm ; microgrid ; energy management ; lower and upper bound estimation ; solar power prediction ; interval prediction ; kernel density estimation ; average probability forecast ; probabilistic forecasting ; forecasting ; distributed energy resources ; photovoltaic power ; conditional predictive ability ; clearness index ; Fourier series ; combining forecasts ; weather station combination ; distributed generation ; clear sky index ; extreme learning machine ; ensemble methods ; pinball score ; autoregression ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    The MIT Press | The MIT Press
    Publication Date: 2022-02-21
    Description: A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
    Keywords: non-binary ; genderqueer ; big data ; data science ; artificial intelligence ; emancipation ; #MeToo ; justice ; race ; class ; sexuality ; power ; intersectionality ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFF Social issues & processes::JFFK Feminism & feminist theory ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFS Social groups::JFSJ Gender studies, gender groups::JFSJ5 Gender studies: transsexuals & hermaphroditism ; bic Book Industry Communication::P Mathematics & science::PD Science: general issues::PDR Impact of science & technology on society
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: Cancer is a leading cause of death worldwide, claiming millions of lives each year. Cancer biology is an essential research field to understand how cancer develops, evolves, and responds to therapy. By taking advantage of a series of “omics” technologies (e.g., genomics, transcriptomics, and epigenomics), computational methods in bioinformatics and machine learning can help scientists and researchers to decipher the complexity of cancer heterogeneity, tumorigenesis, and anticancer drug discovery. Particularly, bioinformatics enables the systematic interrogation and analysis of cancer from various perspectives, including genetics, epigenetics, signaling networks, cellular behavior, clinical manifestation, and epidemiology. Moreover, thanks to the influx of next-generation sequencing (NGS) data in the postgenomic era and multiple landmark cancer-focused projects, such as The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), machine learning has a uniquely advantageous role in boosting data-driven cancer research and unraveling novel methods for the prognosis, prediction, and treatment of cancer.
    Keywords: tumor mutational burden ; DNA damage repair genes ; immunotherapy ; biomarker ; biomedical informatics ; breast cancer ; estrogen receptor alpha ; persistent organic pollutants ; drug-drug interaction networks ; molecular docking ; NGS ; ctDNA ; VAF ; liquid biopsy ; filtering ; variant calling ; DEGs ; diagnosis ; ovarian cancer ; PUS7 ; RMGs ; CPA4 ; bladder urothelial carcinoma ; immune cells ; T cell exhaustion ; checkpoint ; architectural distortion ; image processing ; depth-wise convolutional neural network ; mammography ; bladder cancer ; Annexin family ; survival analysis ; prognostic signature ; therapeutic target ; R Shiny application ; RNA-seq ; proteomics ; multi-omics analysis ; T-cell acute lymphoblastic leukemia ; CCLE ; sitagliptin ; thyroid cancer (THCA) ; papillary thyroid cancer (PTCa) ; thyroidectomy ; metastasis ; drug resistance ; n/a ; biomarker identification ; transcriptomics ; machine learning ; prediction ; variable selection ; major histocompatibility complex ; bidirectional long short-term memory neural network ; deep learning ; cancer ; incidence ; mortality ; modeling ; forecasting ; Google Trends ; Romania ; ARIMA ; TBATS ; NNAR ; 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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    Publication Date: 2022-01-31
    Description: Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (〈A〉, 〈neutA〉, 〈antiA〉), where 〈A〉 is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, 〈antiA〉 is the opposite of 〈A〉, while 〈neutA〉 is the neutral (or indeterminate) between them, i.e., neither 〈A〉 nor 〈antiA〉.Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc.
    Keywords: QA1-939 ; Q1-390 ; similarity measure ; generalized partitioned Bonferroni mean operator ; normal distribution ; school administrator ; complex neutrosophic set ; expert set ; neutrosophic classification ; multi-attribute decision-making (MADM) ; multi-criteria decision-making (MCDM) techniques ; criterion functions ; matrix representation ; possibility degree ; quantum computation ; typhoon disaster evaluation ; NT-subgroup ; generalized neutrosophic ideal ; three-way decisions ; decision-making ; G-metric ; multiple attribute group decision-making (MAGDM) ; SVM ; semi-neutrosophic triplets ; LA-semihypergroups ; power operator ; fuzzy graph ; neutrosophic cubic graphs ; LNGPBM operator ; neutrosophic c-means clustering ; (commutative) ideal ; region growing ; clustering algorithm ; Neutrosophic cubic sets ; forecasting ; vector similarity measure ; totally dependent-neutrosophic soft set ; Fenyves identities ; TODIM model ; similarity measures ; CI-algebra ; Dice measure ; de-neutrosophication methods ; DSmT ; semigroup ; VIKOR model ; multigranulation neutrosophic rough set (MNRS) ; simplified neutrosophic linguistic numbers ; Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) ; multi-criteria group decision making ; multi-attribute group decision-making (MAGDM) ; exponential operational laws of interval neutrosophic numbers ; simplified neutrosophic weighted averaging operator ; neutro-epimorphism ; Choquet integral ; fixed point theory (FPT) ; computability ; neutrosophic triplet set ; interval-valued neutrosophic set ; simplified neutrosophic sets (SNSs) ; totally dependent-neutrosophic set ; Maclaurin symmetric mean ; recursive enumerability ; loop ; photovoltaic plan ; intersection ; neutrosophic bipolar fuzzy set ; big data ; inclusion relation ; dual aggregation operators ; Hamming distance ; neutro-automorphism ; neutrosophic set theory ; multiple attribute decision-making ; multicriteria decision-making ; pseudo primitive elements ; medical diagnosis ; neutrosophic G-metric ; bipolar fuzzy set ; NC power dual MM operator (NCPDMM) operator ; neutrosophic sets (NSs) ; emerging technology commercialization ; neutrosophic triplet groups ; probabilistic rough sets over two universes ; neutrosophic triplet set (NTS) ; neutrosophic triplet cosets ; MM operator ; TOPSIS ; cloud model ; extended ELECTRE III ; extended TOPSIS method ; 2ingle-valued neutrosophic set ; dual domains ; probabilistic single-valued (interval) neutrosophic hesitant fuzzy set ; Jaccard measure ; data mining ; BE-algebra ; neutrosophic soft set ; aggregation operators ; image segmentation ; multiple attribute decision making (MADM) ; neutrosophic duplets ; fundamental neutro-homomorphism theorem ; neutro-homomorphism ; power aggregation operator ; linear and non-linear neutrosophic number ; multi-attribute decision making ; first neutro-isomorphism theorem ; MCGDM problems ; neutrosophic bipolar fuzzy weighted averaging operator ; Bonferroni mean ; analytic hierarchy process (AHP) ; quasigroup ; action learning ; weak commutative neutrosophic triplet group ; generalized aggregation operators ; single valued neutrosophic multiset (SVNM) ; sustainable supplier selection problems (SSSPs) ; LNGWPBM operator ; skin cancer ; oracle computation ; n/a ; fault diagnosis ; interval valued neutrosophic support soft sets ; neutrosophic triplet normal subgroups ; soft set ; multi-criteria decision-making ; neutrosophic triplet ; generalized group ; neutrosophic multiset (NM) ; two universes ; algorithm ; multi-attribute decision making (MADM) ; PA operator ; BCI-algebra ; neutrosophic triplet group (NTG) ; single valued trapezoidal neutrosophic number ; quasi neutrosophic triplet loop ; neutrosophy ; complex neutrosophic graph ; S-semigroup of neutrosophic triplets ; and second neutro-isomorphism theorem ; MADM ; dermoscopy ; linguistic neutrosophic sets ; defuzzification ; construction project ; potential evaluation ; neutrosophic big data ; decision-making algorithms ; neutosophic extended triplet subgroups ; applications of neutrosophic cubic graphs ; fuzzy time series ; TFNNs VIKOR method ; two-factor fuzzy logical relationship ; oracle Turing machines ; grasp type ; interval neutrosophic sets ; multi-criteria group decision-making ; interval neutrosophic weighted exponential aggregation (INWEA) operator ; power aggregation operators ; neutrosophic triplet group ; MGNRS ; 2-tuple linguistic neutrosophic sets (2TLNSs) ; computation ; filter ; multi-valued neutrosophic set ; integrated weight ; Bol-Moufang ; prioritized operator ; interval number ; logic ; pseudo-BCI algebra ; interval neutrosophic set (INS) ; neutrosophic rough set ; soft sets ; Q-neutrosophic ; Linguistic neutrosophic sets ; fuzzy measure ; homomorphism theorem ; commutative generalized neutrosophic ideal ; neutrosophic association rule ; shopping mall ; dependent degree ; Q-linguistic neutrosophic variable set ; quasi neutrosophic loops ; symmetry ; neutrosophic sets ; neutrosophic logic ; neutrosophic cubic set ; complement ; robotic dexterous hands ; neutro-monomorphism ; group ; analytic network process ; Muirhead mean ; maximizing deviation ; classical group of neutrosophic triplets ; neutrosophic triplet quotient groups ; generalized neutrosophic set ; multi-criteria group decision-making (MCGDM) ; support soft sets ; decision making ; generalized De Morgan algebra ; multiple attribute group decision making (MAGDM) ; single-valued neutrosophic multisets ; 2TLNNs TODIM method ; membership ; grasping configurations ; single valued neutrosophic set (SVNS) ; multiple attribute decision making problem ; SWOT analysis ; neutrosophic clustering ; hesitant fuzzy set ; interval neutrosophic numbers (INNs) ; quasi neutrosophic triplet group ; triangular fuzzy neutrosophic sets (TFNSs) ; interdependency of criteria ; aggregation operator ; cosine measure ; neutrosophic set ; neutrosophic computation ; decision-making trial and evaluation laboratory (DEMATEL) ; partial metric spaces (PMS) ; NCPMM operator ; clustering
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    Publication Date: 2024-04-11
    Description: This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.
    Keywords: TA1-2040 ; T1-995 ; faster region-based CNN ; visual tracking ; intelligent tire manufacturing ; eye-tracking device ; neural networks ; A* ; information measure ; oral evaluation ; GSA-BP ; tire quality assessment ; humidity sensor ; rigid body kinematics ; intelligent surveillance ; residual networks ; imaging confocal microscope ; update mechanism ; multiple linear regression ; geometric errors correction ; data partition ; Imaging Confocal Microscope ; image inpainting ; lateral stage errors ; dot grid target ; K-means clustering ; unsupervised learning ; recommender system ; underground mines ; digital shearography ; optimization techniques ; saliency information ; gated recurrent unit ; multivariate time series forecasting ; multivariate temporal convolutional network ; foreign object ; data fusion ; update occasion ; generative adversarial network ; CNN ; compressed sensing ; background model ; image compression ; supervised learning ; geometric errors ; UAV ; nonlinear optimization ; reinforcement learning ; convolutional network ; neuro-fuzzy systems ; deep learning ; image restoration ; neural audio caption ; hyperspectral image classification ; neighborhood noise reduction ; GA ; MCM uncertainty evaluation ; binary classification ; content reconstruction ; kinematic modelling ; long short-term memory ; transfer learning ; network layer contribution ; instance segmentation ; smart grid ; unmanned aerial vehicle ; forecasting ; trajectory planning ; discrete wavelet transform ; machine learning ; computational intelligence ; tire bubble defects ; offshore wind ; multiple constraints ; human computer interaction ; Least Squares method ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development.
    Keywords: supply chain optimization ; oil and gas supply chain ; maintenance scheduling ; operation planning ; energy ; order picking ; wave planning ; warehouses ; distribution centers ; mixed integer programming ; non-linear programming ; Hadi-Vencheh model ; multiple criteria ABC inventory classification ; nonlinear weighted product model ; building material distributors ; central composite design (CCD) ; Box–Behnken design (BBD) ; optimal cost ; customer service level ; forecasting ; order planning ; inventory management ; resource-constrained project scheduling problem ; discounted cash flow maximization ; milestones payments ; simulated annealing algorithm ; slotting ; storage strategies ; stackability ; SKU ; product family ; heuristic ; metaheuristics ; scheduling ; injection molding ; hospital catering ; production scheduling ; flexible job shop problem ; mathematical model ; genetic algorithm ; local search method ; iterated local search algorithm ; competitive hub location problem ; network design ; food systems ; rural development ; mathematical programming ; crow search ; process planning ; operation sequencing ; precedence constraints ; manufacturing scheduling ; smart manufacturing ; intelligent manufacturing systems ; scheduling requirements ; cyber-physical production systems ; postman delivery ; vehicle routing problem ; particle swarm optimization algorithm ; differential evolution algorithm ; multi-criteria optimization ; simulation optimization ; production control ; multiple flexible job shop scheduling ; priority rules ; smart health care systems ; planning ; logistic systems ; benchmark ; workload balancing ; identical parallel machines ; normalized sum of square for workload deviations ; maximum completion time ; minimum completion time ; terminal location ; intermodal transportation ; simulated annealing ; mixed integer program ; incomplete networks ; 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: Regulations that cover the legal obligations that manufacturers are bound to are essential for keeping the general public safe. Companies need to follow the regulations in order to bring their products to market. A good understanding of the regulations and the regulatory pathway defines how fast and at what cost the manufacturer can introduce innovations to the market. Regulatory technology and data science can lead to new regulatory processes and evidence in the medical field. It can equip stakeholders with unique tools that can make regulatory decisions more objective, efficient, and accurate. This book describes the latest research within the broader domain of Medical Regulatory Technology (MedRegTech). It covers concepts such as the complexity and user-friendliness of medical device regulations, novel algorithms for regulatory navigation, descriptive datasets from a health service provider, regulatory data science techniques, and considerations of the environmental impacts within a national health service. This book brings all these aspects together to offer an introduction into MedRegTech research. In the long term, these technologies and methods will help optimize the regulatory strategy for individual healthcare innovations and revolutionize the way we engage with regulatory services.
    Keywords: medical technology ; digital healthcare ; data science ; regulations ; machine learning ; software ; medical device regulations ; healthcare provider ; software as medical device ; technology translation ; quality management system ; law ; medical devices ; regulatory data science ; natural language processing ; linguistic analysis ; optimisation ; medical device ; ecodesign ; environmental impact ; classification ; healthcare ; innovation ; regulation ; decision tree complexity ; 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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    IntechOpen | IntechOpen
    Publication Date: 2023-09-05
    Description: Earthquakes - Recent Advances, New Perspectives and Applications is a compilation of nine chapters covering aspects of tectonics, seismicity, earthquake forecasting, geotechnical engineering, and buildings. It presents state-of-the-art techniques for calculating moment tensors, rupture inversions, and hypocentral locations. It also presents methodologies to test probabilistic earthquake distributions on clustered and declustered catalogs and improves on classical methodologies to estimate bearing capacity and slope stability analysis. The final section discusses the structural behavior of vernacular and modern structures in the nonlinear range and the consequences of modifying the original structural system of a building.
    Keywords: finite element method ; viscosity ; plasticity ; forecasting ; seismic ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RB Earth sciences::RBC Volcanology & seismology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue is a platform to fill the gaps in drought risk analysis with field experience and expertise. It covers (1) robust index development for effective drought monitoring; (2) risk analysis framework development and early warning systems; (3) impact investigations on hydrological and agricultural sectors; (4) environmental change impact analyses. The articles in the Special Issue cover a wide geographic range, across China, Taiwan, Korea, and the Indo-China peninsula, which covers many contrasting climate conditions. Hence, the results have global implications: the data, analysis/modeling, methodologies, and conclusions lay a solid foundation for enhancing our scientific knowledge of drought mechanisms and relationships to various environmental conditions.
    Keywords: extreme spring drought ; atmospheric teleconnection patterns ; drought prediction ; China ; SPI ; reference precipitation ; reference period ; climate change ; drought ; GAMLSS ; nonstationarity ; meteorological drought ; standardized precipitation evapotranspiration index ; climate variability ; seasonal drought ; drought return period ; extreme drought ; Indochina Peninsula ; Indian Ocean Dipole ; intentionally biased bootstrap method ; drought risk ; human activities ; quantitative attribution ; artificial neural network ; stochastic model ; ARIMA model ; drought forecasting ; southern Taiwan ; bivariate frequency analysis ; hydrologic risk ; global warming ; maize yield ; Songliao Plain maize belt ; comprehensive drought monitoring ; Hubei Province ; multivariate ; multisource data ; assessment ; forecasting ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Extreme hydrological phenomena are one of the most common causes of human life loss and material damage as a result of the manifestation of natural hazards around human communities. Climatic changes have directly impacted the temporal distribution of previously known flood events, inducing significantly increased frequency rates as well as manifestation intensities. Understanding the occurrence and manifestation behavior of flood risk as well as identifying the most common time intervals during which there is a greater probability of flood occurrence should be a subject of social priority, given the potential casualties and damage involved. However, considering the numerous flood analysis models that have been currently developed, this phenomenon has not yet been fully comprehended due to the numerous technical challenges that have arisen. These challenges can range from lack of measured field data to difficulties in integrating spatial layers of different scales as well as other potential digital restrictions.The aim of the current book is to promote publications that address flood analysis and apply some of the most novel inundation prediction models, as well as various hydrological risk simulations related to floods, that will enhance the current state of knowledge in the field as well as lead toward a better understanding of flood risk modeling. Furthermore, in the current book, the temporal aspect of flood propagation, including alert times, warning systems, flood time distribution cartographic material, and the numerous parameters involved in flood risk modeling, are discussed.
    Keywords: flood maps ; flood risk management ; HAND model ; WebAssembly ; flood risk mapping ; web systems ; floods ; urban flooding ; flood analysis ; design floods ; HEC-HMS ; HEC-RAS ; dam break ; unsteady ; flood mapping ; Kesem ; flood risk ; poorly gauged watersheds ; regional flood frequency ; flood modeling ; GPU-parallel numerical scheme ; bridges ; story maps ; disaster risk reduction ; slide ; GARI tool ; risk communication ; climate change ; flood early warning ; forecasting ; hydrological extremes ; machine learning ; Andes ; Nilwala river basin ; coupled flood modelling ; iRIC ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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    Taylor & Francis | Routledge
    Publication Date: 2024-04-04
    Description: "This book inquires into the use of prediction at the intersection of politics and academia, and reflects upon the implications of future-oriented policymaking across different fields. The volume focuses on the key intricacies and fallacies of prevision in a time of complexity, uncertainty and unpredictability. The first part of the book discusses different academic perspectives and contributions to future-oriented policymaking. The second part discusses the role of future knowledge in decision-making across different empirical issues such as climate, health, finance, bio- and nuclear weapons, civil war, and crime. It analyses how prediction is integrated into public policy and governance, and how in return governance structures influence the making of knowledge about the future. Contributors integrate two analytical dimensions in their chapters– the epistemology of prevision and the political and ethical implications of prevision. In this way, the volume contributes to a better understanding of the complex interaction and feedback loops between the processes of creating knowledge about the future and the application of this future knowledge in public policy and governance. This book will be of much interest to students of security studies, political science, sociology, technology studies and IR."
    Keywords: bio-weapons ; climate change ; epistemology ; forecasting ; governance ; health care ; healthcare ; nuclear weapons ; policy-making ; prevision ; thema EDItEUR::N History and Archaeology::NH History::NHW Military history ; thema EDItEUR::J Society and Social Sciences::JP Politics and government ; thema EDItEUR::J Society and Social Sciences::JP Politics and government::JPS International relations ; thema EDItEUR::J Society and Social Sciences::JP Politics and government::JPV Political control and freedoms ; thema EDItEUR::J Society and Social Sciences::JW Warfare and defence ; thema EDItEUR::J Society and Social Sciences::JP Politics and government::JPP Public administration
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-02-01
    Description: Energies is open to submissions for a Special Issue on “Renewable Energy Production from Energy Crops and Agricultural Residues”. Biomass represents an important source of renewable and sustainable energy production. Its increasing consumption is mainly related to the increase in global energy demand and fossil fuel prices, but also to a lower environmental impact compared to non-renewable fuels. These factors take RED II directives into consideration. In the past, forestry interventions were the main supply source of biomass, but in recent decades two others sources have entered the international scene. These are dedicated energy crops and agricultural residues, which are important sources of biomass for biofuel and bioenergy. Below, we consider four main value chains: • Oil crops: Oil production from non-food oilseed crops (such as camelina, Crambe, safflower, castor, cuphea, cardoon, etc.), oil extraction, and oil utilization for fuel production. • Lignocellulosic crops: Biomass production from perennial grasses (miscanthus, giant reed, switchgrass, reed canary grass, etc.), woody crops (willow, poplar, Robinia, eucalyptus, etc.), and agricultural residues (pruning, maize cob, maize stalks, wheat chaff, sugar cane straw, etc.), considering two main transformation systems: 1. Electricity/heat production 2. Second-generation ethanol production • Carbohydrate crops (cereals, sweet sorghum, sugar beets, sugar cane, etc.) for ethanol production. • Fermentable crops (maize, barley, triticale, Sudan grass, sorghum, etc.) and agricultural residues (chaff, maize stalks and cob, fruit and vegetable waste, etc.) for production of biogas and/or biomethane.
    Keywords: bioenergy ; crop by-products ; harvesting methods ; maize cob ; wheat chaff ; combine harvesting ; olive groves ; pruning ; stationary chipper ; harvesting system ; hog fuel ; pruning supply chain ; populus ; biomass ; yield energy value ; lower heating value ; ash content ; sulphur ; circular bioeconomy ; oil crops ; agricultural residues ; thermophysical and chemical features ; wheat ; straw ; weed seed ; biocommodity ; threshing ; pruning harvesting ; biomass quality ; slope ; work productivity ; bioresource ; cereals ; commodity ; harvest index ; staple foods ; triticum ; Miscanthus x giganteus ; environmental impact ; agricultural production ; digestate ; eucalyptus ; woody biomass ; storage of fine wood chips ; moisture content ; calorific value ; dry matter loss ; Eucalyptus ; tree whole stem ; firewood logs ; storage system ; renewable energy ; harvesting ; suitable areas ; Central Italy ; Corine Land Cover ; short rotation coppice ; Salix ; genotype × site interaction ; nitrogen content ; sulphur content ; willow biomass ; soil organic carbon ; life cycle assessment ; spatial analysis ; greenhouse gas emissions ; energy return on investment ; lignocellulosic biomass ; hydrothermal pretreatment ; enzymatic hydrolysis ; sugar yield ; high-performance liquid chromatography (HPLC) analysis ; externalities ; economic analysis ; willow biomass production ; new varieties ; sustainable production ; renewable energy sources ; biofuels ; agriculture residues ; forecasting ; modelling ; Poland ; work performance ; harvesting loss ; fuelwood ; cable yarder ; CO2 emission ; pine plantations ; time study ; energy efficiency ; agroenvironmental mapping ; energy crop ; Jatropha curcas L. ; land suitability ; bio-based supply chains ; integrated biomass logistical center ; mixed integer programming model ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-08-08
    Description: The concept of the ‘Zero Energy Mass Custom Home’ or ZEMCH is emerging with the aim of exploring opportunities to make our built environment more socially, economically, environmentally, and humanly sustainable. The built environment is indeed a system of energy and environment that is occupied by the masses, embracing diverse cultural and economic backgrounds. Today, the United Nations articulates the 17 Sustainable Development Goals that reflect necessary global actions for humanity and the planet. In view of these agendas, the delivery of built environments is becoming more demanding and complex than ever, and it is now required that developers accommodate the social, economic, environmental, and human dimensions of these sustainability challenges. This volume encompasses a wide spectrum of ZEMCH research and development knowledge that concerns design engineering, construction management, material innovation, renewable energy technology, and community planning.
    Keywords: sustainable ; architecture ; Zero Energy Mass Custom Homes (ZEMCH) ; energy ; efficiency ; forecasting ; ethics ; climate change ; log burning ; natural ventilation ; solar chimney ; Trombe wall ; renewable energy ; passive ventilation ; building application ; energy management ; green building performance ; office building ; SEM-PLS ; domestic environment ; occupant experience ; environmental design ; health and wellbeing ; housing production ; low-cost ; design quality ; social housing ; government programs ; post-occupancy ; healthy environments ; mass customization ; age-friendly ; active ageing ; ageing in place ; walkability ; bikeability ; accessibility ; BREEAM ; CASBEE ; Green Star ; LEED ; multi-criteria assessment ; sustainable building ; degrowth ; post-growth ; built environment ; sustainability transformations ; wood ; additional floor construction ; sustainability ; Finland ; (summer) cottage ; second home ; (summer) villa ; holiday home ; urban regeneration ; phytoremediation ; Bagnoli former area ; thermal bridge ; sustainable architecture ; finite element modeling ; energy performance ; heat transfer ; heat equation ; simulation ; computational design ; thermal modeling ; computational methods ; bio-based material ; construction ; environment ; circular economy ; life cycle ; behavioural factors ; developing and developed countries ; domestic sector ; electricity use per capita ; energy subsidy ; Iran ; Passivhaus ; ZEMCH ; affordable housing ; synergies ; 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: 2022-01-31
    Description: The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust ?-synthesis for microgrids, and neuro-fuzzy systems in energy storage.
    Keywords: Q1-390 ; QC1-999 ; energy management system ; artificial neural network ; control architecture ; intelligent buildings ; sensitivity analysis ; neural networks ; active balance ; photovoltaic system ; fast frequency response ; artificial intelligence ; MPPT operation ; model uncertainty ; load frequency control ; decision tree ; multi-agent control ; hybrid power plant ; Fault Ride Through Capability ; optimization ; small scale compressed air energy storage (SS-CAES) ; smart micro-grid ; current distortion ; hybrid electric vehicle ; parameter estimation ; railway ; ANFIS ; solar monitoring system ; urban microgrids ; phase-load balancing ; model reduction ; high-speed railway ; energy internet ; coordination of reserves ; differential evolution ; photovoltaic array ; ancillary service ; adjacent areas ; instantaneous optimization minimum power loss ; model predictive control ; HVAC systems ; sliding mode control ; MPPT: maximum power point tracking ; power oscillations ; thyristor ; interaction minimization ; occupancy model ; fuzzy logic controller ; power transformer winding ; RLS ; integrated energy systems ; vibration characteristics ; battery safety ; error estimation ; error compensation ; static friction ; convolutional neural network ; forecasting ; continuous voltage control ; medium voltage ; bridgeless SEPIC PFC converter ; building climate control ; PEM fuel cell ; proton exchange membrane fuel cell ; compound structured permanent-magnet motor ; occupancy-based control ; four phases interleaved boost converter ; long short term memory ; line switching ; lithium-ion battery pack ; back propagation (BP) neural network ; doubly-fed induction generator ; double forgetting factors ; current controller design ; repetitive controller ; exhaust gas recirculation (EGR) valve system ; neural network controller ; step-up boost converter ; internal short circuit resistance ; electric power consumption ; electric vehicle ; multiphysical field analysis ; energy efficiency ; multi-energy complementary ; system identification ; ?-synthesis ; network sensitivity ; intelligent control ; ?-class function ; frequency support ; multi-step forecasting ; frequency containment reserve ; orthogonal least square ; rule-based control ; industrial process ; hierarchical Petri nets ; wind integrated power system ; probabilistic power flow ; voltage controlling ; adaptive backstepping ; AC-DC converters ; line loss ; demand side management ; energy systems ; short-circuit experiment ; winding-fault characteristics ; neutral section ; stochastic power system operating point drift ; neural network algorithm ; operation limit violations ; fractional order fuzzy PID controller ; preventive control ; AC static switch ; battery packs ; model-based fault detection ; automotive application ; nonlinear power systems ; adaptive damping control ; pilot point ; energy management ; position control ; frequency control dead band ; fuzzy ; voltage violations ; distribution network planning ; frequency regulation ; energy management strategy ; multiple-point control ; electric meter ; polynomial expansion ; commercial/residential buildings ; system modelling ; three-stage ; soft internal short circuit ; demand response
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    Cambridge University Press
    Publication Date: 2024-04-14
    Description: Algorithms influence every facet of modern life. However, delegating important decisions to machines gives rise to deep moral concerns about responsibility, transparency, fairness, and democracy. This book examines these concerns by connecting them to the human value of autonomy. This title is also available as Open Access on Cambridge Core.
    Keywords: algorithms ; automated decision making ; law and technology ; autonomy ; agency ; information studies ; data science ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures ; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues::JBFV Ethical issues and debates::JBFV5 Ethical issues: scientific, technological and medical developments ; thema EDItEUR::L Law::LA Jurisprudence and general issues::LAB Methods, theory and philosophy of law ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-06-21
    Description: Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management.
    Keywords: data sharing ; data management ; data science ; big data ; healthcare ; depression ; psychological treatment ; task sharing ; primary care ; pilot study ; non-specialist health worker ; training ; digital technology ; mental health ; COVID-19 ; SARS-CoV-2 ; pneumonia ; computed tomography ; case fatality rate ; social distancing ; smoking ; metabolically healthy obese phenotype ; metabolic syndrome ; obesity ; coronavirus ; machine learning ; social media ; apache spark ; Twitter ; Arabic language ; distributed computing ; smart cities ; smart healthcare ; smart governance ; Triple Bottom Line (TBL) ; thoracic pain ; tree classification ; cross-validation ; hand-foot-and-mouth disease ; early-warning model ; neural network ; genetic algorithm ; sentinel surveillance system ; outbreak prediction ; artificial intelligence ; vascular access surveillance ; arteriovenous fistula ; end stage kidney disease ; dialysis ; kidney failure ; chronic kidney disease (CKD) ; end-stage kidney disease (ESKD) ; kidney replacement therapy (KRT) ; risk prediction ; naïve Bayes classifiers ; precision medicine ; machine learning models ; data exploratory techniques ; breast cancer diagnosis ; tumors classification ; 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: 2022-08-12
    Description: The importance and usefulness of subjects and topics involving social data and artificial intelligence are becoming widely recognized. This book contains invited review, expository, and original research articles dealing with, and presenting state-of-the-art accounts pf, the recent advances in the subjects of social data and artificial intelligence, and potentially their links to Cyberspace.
    Keywords: centrality metric ; graph visualisation ; visual analytics ; data processing ; social network ; stock market ; community detection ; complex networks ; Hadoop ; modularity increment ; geometric analysis ; lidar scanning signal ; micro-distortion ; detection technology ; TCD1209DG ; lossless signal transmission ; person re-identification ; multiple granularity features ; Siamese Multiple Granularity Network ; multi-channel weighted fusion loss ; temporal links prediction ; gravity model ; multilayer network ; label propagation algorithm ; H-index ; automatic speech recognition ; speech corpus ; text corpus ; data acquisition ; multi-layer neural network ; natural language processing ; markov switching ; breakpoint test ; crude oil price ; structural change ; artificial intelligence ; ice-snow tourism ; sustainable development ; Python ; text mining ; pancreatic cancer ; twin support vector machine ; linear kernel ; polynomial kernel ; RBF kernel ; cryptography ; RSA cryptosystem ; RSA cryptanalysis ; partial key exposure attack ; social network simulation ; ABMS ; Spark ; two-tier partition algorithm ; visual style ; context-aware ; preference analysis ; fashion recommendation ; Facebook advertising post ; social media marketing ; recommendation system ; topic model ; post engagement ; blockchain ; client/server ; electronic health records ; health information management ; privacy ; security ; innovation ; business ; machine learning ; decision tree ; predictive analytics ; social data science ; contingencies ; asymmetry ; tele-education ; digitalization ; ICT infrastructure ; digital teacher training ; replace face-to-face education ; telemedicine ; technology acceptance ; robust partial least squares path modeling ; data-mining techniques ; data-discretization methods ; feature-selection methods ; industry data applications ; advanced multicomponential discretization models ; social networks ; behavior analysis ; social behavior ; social networking satisfaction ; data science ; DBLP platform ; Twitter ; deep reinforcement learning ; keyphrase extraction ; unsupervised method ; feature selection ; weighted non-negative matrix factorization ; hierarchical information ; tag information ; deep factorization ; combinatorial optimization problem ; heuristics method ; nature-inspired algorithm ; NP-hard problem ; plant root ; healthcare data ; data management ; digital services ; cybernetics ; symmetrical designing ; overlapping community discovery ; gravitational degree ; greedy strategy ; two expansions ; cloud computing ; color revolution operator ; imperialist competitive algorithm ; quality of service ; service composition ; service time-cost ; 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: 2024-04-09
    Description: The pandemic period has caused severe socio-economic damage, but it is accompanied by environmental deterioration that can also affect economic opportunities and social equity. In the face of this double risk, future generations are ready to be resilient and make their contribution not only on the consumption side, but also through their inclusion in all companies by bringing green and circular principles with them. Policy makers can also favor this choice.
    Keywords: mobility choice ; COVID-19 ; best–worst method ; multi-criteria decision making ; air pollution ; air quality ; health effects ; economic burden ; food system ; circular economy ; sustainability ; EU ; Twitter ; COVID-19 pandemic ; local community ; perception analysis ; econometric modeling ; data science ; reflexive governance ; climate change ; infrastructure ; urban resilience ; social sustainability ; economic sustainability ; environmental sustainability ; China ; business ; innovation ecosystem ; innovation strategy ; electric vehicle ; dominant design ; crisis ; pandemic ; higher education ; digitalization ; distance learning ; Covid-19 outbreak ; resilience ; n/a ; strategic resilience ; multi-domain resilience ; strategic agility ; change ; sustainability strategy ; financialization ; TFP ; innovation ; resilience of city ; infectious disease ; urban planning ; supply chain resilience ; IT disruptions ; efficiency measurement ; warehouse logistics ; DEA ; resilient supply chains ; external capital ; customer–supplier relationship ; circular network ; cyber-security ; e-commerce ; Europe ; supply chain collaboration ; small- and medium-sized enterprises ; grey DEMATEL ; fuzzy best-worst method ; agrivoltaic system ; solar photovoltaics ; agronomic management ; crop production ; Food-Energy-Water nexus ; sustainable integration ; women’s leadership ; America Latina ; small and medium-sized enterprises ; renewable energy ; sustainable electricity production ; socio-economic sustainability ; sustainable development goals ; emission level ; levelized cost ; gross domestic product ; pig farmers ; adoption willingness of IoT traceability technology ; Unified Theory of Acceptance and Use of Technology ; Latent Moderate Structural Equations ; biomethane ; natural gas grid ; bioenergy ; biogas ; gas supply decarbonization ; incentives ; competences ; digitization ; digital transformation ; Asia Pacific ; CO2 emission ; demand shock ; hypothetical extraction method ; input–output model ; sectoral linkage ; emerging cities ; sustainable operations ; case studies ; the Asian region ; resilience decisions ; cybersecurity ; consumers’ awareness ; methodology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This volume gathers papers from the fields of philosophy, theology, and empirical psychology on the topic of gratitude to God. Central themes include the difference between gratitude to God and gratitude to human benefactors and correlations between gratitude to God and important life outcomes.
    Keywords: gratitude ; religiosity ; spirituality ; well-being ; Aquinas ; virtue ; religion ; gratitude to God ; health ; federal funding ; systematic review ; conceptual metaphor ; analogy ; anthropomorphism ; God concepts ; gratitude expressions ; public gratitude ; social media ; data science ; machine learning ; challenges ; review ; God ; supernatural attribution ; gift ; divine attributions ; religious attributions ; religious appraisals ; measurement ; religious belief ; liturgy ; group action ; joint action ; social ontology ; extraversion ; optimism ; vitality ; self-esteem ; agreeableness ; honesty–humility ; entitlement ; secure attachment ; construal ; religiousness ; Christianity ; theism ; Dietrich Bonhoeffer ; Jonathan Edwards ; Soren Kierkegaard ; Karl Barth ; creation ; Mozart ; Beethoven ; Bible ; doctrine of Scripture ; tradition ; inspiration ; church ; canon ; theology ; acceptance ; pantheism ; axiarchism ; ultimism ; Stoicism ; Kierkegaard ; local evils ; suffering ; transcendent gratitude ; cosmic gratitude ; transcendence ; beliefs ; case study ; qualitative ; doubt ; atheism ; agnosticism ; 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: 2024-03-29
    Description: Recent developments in the natural gas industry warrant new analysis of related issues. Environmental, social, and governance (ESG) investments have accelerated the shift away from coal as the dominant source of electricity. Its low environmental impact, reduced volume, and broad availability make liquefied natural gas (LNG) a popular alternative, during this time of transition between traditional fuels and newer options. In the United States, the shale gas revolution has made natural gas a game changer. In this book, we focus on empirical analyses of the natural gas market and its growing relevance worldwide.
    Keywords: spillover effect ; market integration ; natural gas market ; time frequency dynamics ; BRICS ; exchange rates ; connectedness ; time domain ; frequency domain ; natural gas ; crude oil ; electricity utilities sector index ; time–frequency dynamics ; ESG ; renewable energy ; copula ; value-at-risk ; electricity ; spot ; futures ; transmission ; pipelines ; external cost ; health ; property damage ; bodily injury ; uncertainty ; insurance ; coal ; spillover effects ; dynamic approaches ; forecasting ; logistic regression ; random forests ; support vector machines ; US natural gas crises ; XGboost ; neural networks ; oil futures prices crashes ; foresting ; logistical regression ; extreme gradient boosting ; moving window ; SVAR ; oil price ; gas price ; US macroeconomic aggregates ; GDP ; CPI ; thema EDItEUR::K Economics, Finance, Business and Management
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-20
    Description: At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational techniques in finance and economics. Examined topics span on issues at the center of the literature debate, with an eye not only on technical and theoretical aspects but also very practical cases.
    Keywords: HG1-9999 ; growth optimal portfolio ; Wishart model ; conditional Value-at-Risk (CoVaR) ; systemic risk ; utility functions ; current drawdown ; risk measure ; risk-based portfolios ; capital market pricing model ; systemic risk measures ; Big Data ; International Financial Reporting Standard 9 ; cartography ; stock prices ; copula models ; CoVaR ; quantitative risk management ; auto-regressive ; fractional Kelly allocation ; independence assumption ; deep learning ; structural models ; financial regulation ; data science ; efficient frontier ; weighted logistic regression ; estimation error ; financial markets ; capital allocation ; multi-step ahead forecasts ; target matrix ; value at risk ; random matrices ; credit risk ; portfolio theory ; convex programming ; admissible convex risk measures ; non-stationarity ; financial mathematics ; quantile regression ; Markowitz portfolio theory ; shrinkage ; loss given default ; ordered probit ; bic Book Industry Communication::W Lifestyle, sport & leisure::WC Antiques & collectables::WCF Coins, banknotes, medals, seals (numismatics)
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties, in a unified and coherent framework. This book contributes to this literature by collecting a set of carefully evaluated contributions that are grouped amongst two topics in financial economics. The first three papers refer to macro-finance issues for real economy, including the elasticity of factor substitution (ES) in the Cobb–Douglas production function, the effects of government public spending components, and quantitative easing, monetary policy and economics. The last three contributions focus on cryptocurrency and stock market predictability. All arguments are central ingredients in the current economic discussion and their importance has only been further emphasized by the COVID-19 crisis.
    Keywords: unconventional monetary policy ; transmission channel ; Bayesian TVP-SV-VAR ; Bayesian econometrics ; portfolio choice ; sentiments ; stock market predictability ; cryptocurrency ; Bitcoin ; forecasting ; point forecast ; density forecast ; dynamic model averaging ; dynamic model selection ; forgetting factors ; military and civilian spending ; DSGE model ; fiscal policy ; monetary policy ; Bayesian estimation ; Bayesian VAR ; density forecasting ; time-varying volatility ; ES ; CES function ; Bayesian nonlinear mixed-effects regression ; MCMC methods ; macroeconomic and financial applications ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    Stichting Archiefpublicaties
    Publication Date: 2024-04-11
    Description: Archives in Liquid Times aims to broaden and deepen the thinking about archives in today’s digital environment. It is a book that tries to fuel the debate about archives in different fields of research. It shows that in these liquid times, archives need and deserve to be considered from different angles. Archives in Liquid Times is a publication in which archival science is linked to philosophy (of information) and data science. Not only do the contributors try to open windows to new concepts and perspectives, but also to new uses of existing concepts concerning archives. The articles in this book contain philosophical reflections, speculative essays and presentations of new models and concepts alongside well-known topics in archival theory. Among the contributors are scholars from different fields of research, like Anne Gilliland, Wolfgang Ernst, Geoffrey Yeo, Martijn van Otterlo, Charles Jeurgens and Geert-Jan van Bussel. This book includes interviews with Luciano Floridi and Eric Ketelaar, in which they reflect on key issues arising from the contributions. The editors are Frans Smit, Arnoud Glaudemans and Rienk Jonker.
    Description: Archives in Liquid Times is een boek waarin een verbinding wordt gelegd tussen enerzijds archivistiek en anderzijds (informatie)filosofie en data science. De bijdragen in het boek zetten de ramen open naar frisse nieuwe inzichten en concepten, en naar nieuwe toepassingen van bestaande inzichten en oude concepten. Naast filosofische beschouwingen en soms speculatieve essays is er aandacht voor verdieping van archieftheoretische thema’s. Het boek bevat bijdragen van specialisten uit verschillende vakgebieden, waaronder Wolgang Ernst, Geoffrey Yeo, Anne Gilliland, Charles Jeurgens, Martijn van Otterlo en Geert-Jan van Bussel. Het boek wordt afgesloten door interviews met Luciano Floridi en Eric Ketelaar, waarin zij reflecteren op de bijdragen. Het jaarboek is volledig Engelstalig.
    Keywords: archiefwetenschap ; archival science ; informatiefilosofie ; information philosophy ; data science ; Ethics ; Metadata ; Provenance ; Speech act ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GL Library and information sciences / Museology::GLC Library, archive and information management
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Operational oceanography is maturing rapidly. Its capabilities are being noticeably enhanced in response to a growing demand for regularly updated ocean information. Today, several core forecasting and monitoring services, such as the Copernicus Marine ones focused on global and regional scales, are well-stablished. The sustained availability of oceanography products has favored the proliferation of specific downstream services devoted to coastal monitoring and forecasting. Ocean models are a key component of these operational oceanographic systems (especially in a context marked by the extensive application of dynamical downscaling approaches), and progress in ocean modeling is certainly a driver for the evolution of these services. The goal of this Special Issue is to publish research papers on ocean modeling that benefit model applications that support existing operational oceanographic services. This Special Issue is addressed to an audience with interests in physical oceanography and especially on its operational applications. There is a focus on the numerical modeling needed for a better forecasts in marine environments and using seamless modeling approaches to simulate global to coastal processes.
    Keywords: singular spectrum analysis ; altimeter waveform ; Json-1 ; mean sea surface height ; threshold retracker ; waveform retracking ; Northeast Atlantic ; ROMS ; ARGO ; tide gauges ; Irish coastal current ; river freshwater discharges ; operational ocean models ; sea surface salinity field ; IBI region ; LAMBDA river database ; IBI model validation ; model sensitivity tests ; barotropic solver ; PCG ; CA-PCG ; ocean general circulation model ; NEMO ; sea of Marmara ; Bosphorus strait ; Dardanelles strait ; Turkish strait system ; SHYFEM ; Black Sea ; wave-current interaction ; NEMOv4 ; WaveWatchIII ; operational oceanography ; physical oceanography ; biogeochemistry ; waves ; numerical modelling ; data assimilation ; forecasting ; reanalysis ; validation ; SAMOA ; coastal models ; operational forecasting ; port circulation ; dynamical downscaling ; nesting techniques in operational applications ; ocean model validation ; wave modeling ; current–wave coupling ; current forcing ; model validation ; wave altimetric products ; Copernicus Marine IBI ; freshwater discharges ; sea surface salinity ; land boundary ; estuarine proxy ; water continuum ; numerical models ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-01-31
    Description: Within the framework of tourism companies and tourist destinations, the question of sustainability is gaining importance. Tourists are increasingly aware of the importance of sustainability criteria, awarding greater value to sustainable destinations. Sustainability refers to a wide range of aspects related to climate change, the economic organization of tourism, social values or questions, job creation, and the necessary protection of the culture of destinations and the environment. Therefore, there is a need for studies that consider these aspects in order to achieve the sustainable development of tourist destinations. Fundamental to this is discovering to what degree tourism companies and destinations approach these questions in the strategies they use to deal with problems stemming from their attempts to be more sustainable. Conceptual papers and empirical research on the economic, social, cultural, and environmental aspects related to tourism companies and destinations are welcome. Studies that analyze how these questions and the concept of sustainability are included in tourism companies and destinations are necessary in these modern times. This book was established for these reasons, dedicated to examining sustainability in tourism. The papers included in this Special Issue can help us to determine the new directions being addressed in the research on sustainability tourism.
    Keywords: HB1-3840 ; the “health” of rural settlements ; sport tourism ; physical environment (PhE) ; tourism evaluation ; hotel industry ; internet search index ; deep learning framework ; visitor satisfaction ; discrete choice experiments ; invasive species control ; tourist satisfaction ; all-for-one tourism ; spatial analysis ; choice experiment ; two stage on-site sampling ; tourism and sustainability ; Apuseni mountains ; sporting event ; sustainability services marketing matrix ; compartmentalisation ; climate change ; regression discontinuity design ; supply chain ; TOWS matrix ; essential marketing ; LSTM model ; A’WOT ; time series ; museum planning ; sustainable daily practices ; negative externalities ; event quality ; sustainability ; certification ; sustainable development ; islands ; young adults ; semantic analysis ; sense of belonging ; agritourism ; behavioral intentions ; purchasing ; motivation ; pro-social/pro-environmental behavior ; tourism ; ecolabel adoption ; hotel accommodation demands ; tourism indicators ; local community ; destination development ; forecasting performance ; inbound tourism ; China ; visitor behavior ; cluster analysis ; campsites ; science museum ; qualitative methodology ; place attachment ; forecasting ; mountain areas ; ecolabel ; electricity ; tourists’ preferences ; value and tourism ; sustainable tourism ; strategic planning ; regional disparity ; community-based tourism ; forecast through a logistic model ; PM10 ; constraint ; air pollution ; learning-based tourism ; hotel management ; ICT
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In recent years, ironmaking and steelmaking have witnessed the incorporation of various new processes and technologies that can be operated and organized in different combinations depending on the properties of raw materials and the required quality of the final products. Indications from the steel industry and local and global government institutions suggest that the breakthrough technologies for decarbonization will be based on new fuels and energy vectors. For CO2-lean process routes, three major solutions have been identified: decarbonizing, whereby coal would be replaced by hydrogen or electricity in the hydrogen reduction or electrolysis of iron ore processes; the introduction of CCS technology; and the use of sustainable biomass. Today, hydrogen-based steelmaking is a potential low-carbon and economically attractive route, especially in countries where natural gas is cheap. By considering systems for increasing energy efficiency and reducing the environmental impact of steel production, CO2 emissions may be greatly reduced by hydrogen-based steel production if hydrogen is generated by means of carbon-free and renewable sources. Currently, the development of the hydrogen economy has received a great deal of attention in that H2 is considered a promising alternative to replace fossil fuels. Based on hydrogen, the “hydrogen economy” is a promising clean energy carrier for decarbonized energy systems if the hydrogen used is produced from renewable energy sources or coupled with carbon capture and storage (CCS) or nuclear energy.
    Keywords: electric arc furnace steelmaking ; bottom-stirring ; different smelting time ; molten steel flow ; numerical simulation ; blast furnaces ; silicon content ; maximal overlap discrete wavelet packet ; artificial neural network ; forecasting ; time series analysis ; double slag converter steelmaking process ; hot metal dephosphorization ; dephosphorization endpoint temperature ; dephosphorization ratio ; phosphorus distribution ratio ; optimum temperature of intermediate deslagging ; coal injection ; blast furnace ; drop tube furnace ; statistical correlation ; production ; ironmaking ; bio-coals ; carbonization ; gasification ; reactivity ; dilatation ; fluidity ; water electrolysis ; steelmaking ; purification ; desalinization ; direct reduction ; energy ; renewables ; high temperature ; low temperature ; mold width ; flow field in mold ; high-temperature measurement ; surface velocity ; direct reduced pellets ; open slag bath furnace ; slag ; blast furnace pellets ; hydrogen ; decarbonization ; steelworks gas valorization ; methane synthesis ; methanol synthesis ; predictive control ; carbon capture and usage ; hydrogen enrichment ; hydrogen metallurgy ; hydrogen reduction of iron oxides ; alternative ironmaking ; smelting reduction ; thermodynamic ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
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  • 87
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.
    Keywords: fintech ; financial technology ; blockchain ; deep learning ; regtech ; environment ; social sciences ; machine learning ; learning analytics ; student field forecasting ; imbalanced datasets ; explainable machine learning ; intelligent tutoring system ; adversarial machine learning ; transfer learning ; cognitive bias ; stock market ; behavioural finance ; investor’s profile ; Teheran Stock Exchange ; unsupervised learning ; clustering ; big data frameworks ; fault tolerance ; stream processing systems ; distributed frameworks ; Spark ; Hadoop ; Storm ; Samza ; Flink ; comparative analysis ; a survey ; data science ; educational data mining ; supervised learning ; secondary education ; academic performance ; text-to-SQL ; natural language processing ; database ; machine translation ; medical image segmentation ; convolutional neural networks ; SE block ; U-net ; DeepLabV3plus ; cyber-security ; medical services ; cyber-attacks ; data communication ; distributed ledger ; identity management ; RAFT ; HL7 ; electronic health record ; Hyperledger Composer ; cybersecurity ; password security ; browser security ; social media ; ANOVA ; SPSS ; internet of things ; cloud computing ; computational models ; metaheuristics ; phishing detection ; website phishing ; thema EDItEUR::U Computing and Information Technology
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  • 88
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Metal‒insulator transitions (MITs) constitute a core subject of fundamental condensed matter research. The localization of conduction electrons occurs in a large variety of materials and engenders intriguing quantum phenomena such as unconventional superconductivity and exotic magnetism. Nearby an MIT, minuscule changes of the interaction strength via chemical substitution, doping, physical pressure, or even disorder can trigger spectacular resistivity changes from zero in a superconductor to infinity in an insulator near T = 0. While approaching an insulating state from the conducting side, deviations from Fermi-liquid transport in bad and strange metals are the rule rather than the exception. As the drosophila of electron‒electron interactions, the Mott MIT receives particular attention from theory as it can be studied using the Hubbard model. On the experimental side, organic charge-transfer salts and transition metal oxides are versatile platforms for working toward solving the puzzles of correlated electron systems. This Special Issue provides a view into the ongoing research endeavors investigating emergent phenomena around MITs.
    Keywords: strongly correlated systems ; organic conductors ; relaxor-ferroelectrics ; dielectric spectroscopy ; infrared spectroscopy ; disordered systems ; metal insulator transition ; Anderson localization ; random disorder ; typical medium theory ; dynamical mean field theory ; coherent potential approximation ; dynamical cluster approximation ; cellular dynamical mean field theory ; cluster mean field theory ; FFLO ; organic superconductor ; penetration depth measurement ; resistance ; FFLO phase ; vortex dynamics ; charge-transfer salts ; (TMTTF)2X ; Fabre salts ; charge order ; strongly correlated electron systems ; extended Hubbard model ; bandwidth tuning ; partial chemical substitution ; negative chemical pressure ; phase transitions ; metal-insulator transitions ; optical conductivity ; vibrational spectroscopy ; FTIR ; strong electron correlations ; heat capacity ; Mott transition ; charge-transfer solid crystals ; two-dimensional metal ; carrier localization ; negative magnetoresistance ; phase coherence length ; organic conductor ; Mott insulator ; electric double-layer transistor ; uniaxial strain ; molecular conductors ; quantum spin liquid ; thermal conductivity ; cooling rate ; electrical resistivity ; low-temperature crystal structure ; 13C-NMR ; heavy fermion compounds ; strange metals ; Planckian dissipation ; quantum criticality ; Kondo destruction ; superconductivity ; nickelates ; molecular conductor ; manganites ; colossal magnetoresistance ; metal–insulator transition ; grain size ; variable range hopping ; core–shell model ; strongly correlated electrons ; metal-insulator transition ; charge glass ; charge crystal ; geometrical frustration ; organics ; charge density wave ; spin density wave ; spin liquid ; FFLO state ; materials database ; data science ; resistivity maxima ; dielectric response ; dilute 2DEGs ; Mott organics ; twisted transition-metal dichalcogenide bilayers ; percolation theory ; spinon theory ; anderson localization ; neural network ; quantum impurity solver ; Anderson impurity ; organic charge-transfer salts ; magnetic exchange beyond Heisenberg ; intra-dimer charge and spin degrees of freedom ; electron-lattice coupling ; disorder ; 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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  • 89
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting. In light of the above, this Special Issue collects the latest research on relevant topics, in particular in energy demand forecasts, and the use of advanced optimization methods and big data techniques. Here, by energy, we mean any kind of energy, e.g., electrical, solar, microwave, or wind
    Keywords: deep learning ; energy demand ; temporal convolutional network ; time series forecasting ; time series ; forecasting ; exponential smoothing ; electricity demand ; residential building ; energy efficiency ; clustering ; decision tree ; time-series forecasting ; evolutionary computation ; neuroevolution ; photovoltaic power plant ; short-term forecasting ; data processing ; data filtration ; k-nearest neighbors ; regression ; autoregression ; n/a ; 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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  • 90
    Publication Date: 2022-01-31
    Description: Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satellites. This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites.
    Keywords: GB3-5030 ; T1-995 ; social observatory ; earth system science ; science in society ; data science ; open innovation ; citizen science ; open data ; crowdsourced geospatial data ; geospatial analytics ; big earth data
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations. Employing technological tools for collection, processing, and analysis incorporates understanding the patient’s status and developing the treatment plan. Achieving highly accurate models requires a huge dataset. This issue can be solved by having enough knowledge around medical data processing and their analysis. This reprint shows state-of-the-art research in the field of medical data processing and analysis. The medical data are represented in signals, images, raw data, protein sequences, etc. Processing and analysis of any kind can indicate specific issues in the medical sector such as diagnosis, detection, prediction, and segmentation to enhance the visualization of the processed data
    Keywords: atrial fibrillation ; perfect matrix of Lagrange differences ; statistical indicator ; decision support system ; deep learning ; heart failure ; mortality ; risk prediction ; time-varying covariates ; motor imagery ; Isolation Forest ; anomaly detection ; EEG signals classification ; PIMA dataset ; Type-2 diabetes ; Recurrent Neural Networks ; weight optimization ; Hamlet Pattern ; protein sequence classification ; SARS-CoV-2 ; bioinformatics ; machine learning ; ensemble learning ; heart disease ; ECG ; iris-spectrogram ; scalogram ; CNN ; ResNet101 ; ShuffleNet ; heart rhythm ; H. pylori ; atrophic gastritis ; convolution neural network ; feature fusion ; Canonical Correlation Analysis ; ReliefF ; generalized additive model ; diabetes mellitus ; blood glucose prediction ; forecasting ; long short-term memory ; nature-inspired feature selection ; leukemia ; white blood cell ; classification ; medical imaging ; breast cancer ; histopathological image ; review ; COVID-19 pandemic ; hybrid models ; public health ; accuracy and efficiency ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-01
    Description: This compendium describes the impact of COVID-19 pandemic on all aspects of people lives. Data presented in this collection will be useful to understand the disruption in healthcare, learning, and socio-economic aspects amidst the pandemic. The sooner we begin to understand the impact, the better placed we will be to address the unmet needs of vulnerable population groups.
    Keywords: COVID-19 ; novel coronavirus ; social lockdown ; protection motivation theory ; health behavior ; health communication ; pregnant woman ; coronavirus ; infectious disease transmission ; vertical transmission ; obstetric management ; SARS-CoV-2 ; systematic review ; computerized tomography ; pneumonia ; risk factors ; echocardiography ; healthcare ; mental health ; Impact of event scale ; negative attitude ; Saudi Arabian females ; health services ; cost ; manual therapy ; chiropractic ; osteopathy ; physiotherapy ; direct RT-PCR ; molecular detection ; dental care ; dental health services ; dental visits ; dental service use ; postponed dental visits ; check-up ; dental examination ; pain ; dental complaints ; oral health ; Saudi Arabia ; blood donors ; seroprevalence ; ELISA ; antibodies ; lockdown ; multi-theory model ; behavior change ; pandemic ; handwashing ; young adults ; college students ; protective behavior changes ; individual ; family ; environmental factor ; COVID-19 spreading ; online survey ; awareness and knowledge ; ships ; seafarers ; SARS-COV-2 ; anxiety ; depression ; stress ; suicidal ideation ; students ; time-series ; ARIMA ; forecasting ; confirmed cases ; infectious disease ; international cruises ; health policy and regulation ; control strategies ; international cooperation ; global health governance ; ICF ; healthcare services ; interprofessional education ; medical students ; pharmacy students ; telehealth ; older adults ; artificial intelligence ; machine learning ; bibliometric analysis ; health ; novel design ; fabrication ; automated dispenser ; LDR based controller ; reduction of COVID-19 spread ; psychological symptom ; college student ; avoidance of infection ; social distancing ; free tickets for the aged ; subway use demand ; e-learning ; youth and children health ; visual health ; myopia ; routine care ; global pandemic ; role conflict ; role ambiguity ; social support ; dental precautions ; dental students ; India ; infection control ; knowledge ; perception ; survey ; face masks ; young people ; behaviors ; dentist ; infection control practices ; concerns ; dental practice ; social isolation ; social connectedness ; loneliness ; technology ; internet ; smartphones ; m-health ; severe acute respiratory syndrome ; post-graduate year training ; self-efficacy ; emotional traits ; Coronavirus ; prevention ; community ; public health nurse ; telephone consultation ; vaccine literacy ; Japan ; family carers for older adults ; sustainable ageing society ; health communications ; mass media ; HCWs ; personality traits ; intolerance of uncertainty ; coping strategies ; perceived stress ; resilience ; migration ; refugees ; fear ; modeling ; data analysis ; assessment ; effectiveness ; incidence rate ; restriction ; epidemic pattern ; exponential growth ; basic reproduction number (R0) ; spatio-temporal analysis ; demographic risk factor ; observational study ; public health ; Southeast Asia (SEA) ; vaccination rate ; basic reproduction number ; SARS-CoV ; African American ; COVID-19 vaccine ; vaccine hesitancy ; vaccine hesitant ; text classification ; SARS-CoV-2 infection ; survival rate ; hospitalized patients ; Hidalgo Mexico ; multimorbidity ; vaccination ; level 1 trauma ; health care workers ; information source trust ; COVID-19 stressor ; global south ; thema EDItEUR::N History and Archaeology::NH History ; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Short-term load forecasting (STLF) plays a key role in the formulation of economic, reliable, and secure operating strategies (planning, scheduling, maintenance, and control processes, among others) for a power system and will be significant in the future. However, there is still much to do in these research areas. The deployment of enabling technologies (e.g., smart meters) has made high-granularity data available for many customer segments and to approach many issues, for instance, to make forecasting tasks feasible at several demand aggregation levels. The first challenge is the improvement of STLF models and their performance at new aggregation levels. Moreover, the mix of renewables in the power system, and the necessity to include more flexibility through demand response initiatives have introduced greater uncertainties, which means new challenges for STLF in a more dynamic power system in the 2030–50 horizon. Many techniques have been proposed and applied for STLF, including traditional statistical models and AI techniques. Besides, distribution planning needs, as well as grid modernization, have initiated the development of hierarchical load forecasting. Analogously, the need to face new sources of uncertainty in the power system is giving more importance to probabilistic load forecasting. This Special Issue deals with both fundamental research and practical application research on STLF methodologies to face the challenges of a more distributed and customer-centered power system.
    Keywords: short-term load forecasting ; demand-side management ; pattern similarity ; hierarchical short-term load forecasting ; feature selection ; weather station selection ; load forecasting ; special days ; regressive models ; electric load forecasting ; data preprocessing technique ; multiobjective optimization algorithm ; combined model ; Nordic electricity market ; electricity demand ; component estimation method ; univariate and multivariate time series analysis ; modeling and forecasting ; deep learning ; wavenet ; long short-term memory ; demand response ; hybrid energy system ; data augmentation ; convolution neural network ; residential load forecasting ; forecasting ; time series ; cubic splines ; real-time electricity load ; seasonal patterns ; Load forecasting ; VSTLF ; bus load forecasting ; DBN ; PSR ; distributed energy resources ; prosumers ; building electric energy consumption forecasting ; cold-start problem ; transfer learning ; multivariate random forests ; random forest ; electricity consumption ; lasso ; Tikhonov regularization ; load metering ; preliminary load ; short term load forecasting ; performance criteria ; power systems ; cost analysis ; day ahead ; feature extraction ; deep residual neural network ; multiple sources ; electricity ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Greenhouse gas (GHG) emissions associated with transportation activities account for approximately 20 percent of all carbon dioxide (co2) emissions globally, making the transportation sector a major contributor to the current global warming. This book focuses on the latest advances in technologies aiming at the sustainable future transportation of people and goods. A reduction in burning fossil fuel and technological transitions are the main approaches toward sustainable future transportation. Particular attention is given to automobile technological transitions, bike sharing systems, supply chain digitalization, and transport performance monitoring and optimization, among others.
    Keywords: ANOVA-test ; clickbait news ; feature selection ; social network ; taxi demand ; forecasting ; multi-source data ; generative adversarial networks ; container ship traffic flow ; volatility ; generalized Hurst exponents ; long-range dependence ; multifractality ; city buses ; semi-Markov processes ; preventive maintenance ; corrective maintenance ; age-replacement ; minimal repair ; perfect repair ; profit per time unit ; availability ; railway transport ; passengers ; sustainable travel ; ARTIW method ; IHAMCI method ; MCDM ; facial recognition technology ; e-biker ; red-light running behavior ; privacy invasion ; content replacement ; content placement ; content-centric networking ; cache networks ; immaturity ; stretch reduction ; mineral exploration ; natural gamma-ray spectrometry ; ASTER ; fuzzy logic modelling ; Kelâat M’Gouna inlier ; Eastern Anti-Atlas ; Morocco ; collision avoidance ; fuzzy logic ; on board driver assistance ; semi-autonomous ; multi-factor ; VANET ; COVID-19 ; bike sharing system ; urban mobility ; regression analysis ; green transport ; continuous descent approach ; optimized profile descent ; climate change ; terminal maneuvering area ; environmental impact ; applied queueing theory ; air traffic management ; air transportation sustainability ; electric vehicle powertrain ; multispeed discrete transmission ; continuously variable transmission ; two-motors configuration ; four-motors configuration ; border crossings ; sentiments ; personal vehicles ; pedestrians ; US–Mexico ; Google Trends ; digitalization ; BPM ; business process model ; artificial intelligence ; big data ; virtual reality ; internet of things ; cloud computing ; digital security ; additive engineering ; smart cities ; Internet of Things (IoT) ; strategy ; monitoring ; transport equity ; distributional analysis ; accessibility ; space-time model ; transport policy ; OFDM ; LDACS ; aeronautical communication ; impulse noise ; pulse blanking ; ROAD statistics ; location planning ; vehicle scheduling ; electric buses ; charging stations ; partial charging ; human-machine interaction ; scenarios ; use cases ; remote operation ; highly automated vehicles ; user-centered design ; remote assistance ; remote driving ; bike-sharing system (BSS) ; mode choice ; stated choice experiment ; multinomial logit model ; transport demand model ; technological transitions ; automobiles ; system dynamics ; dynamical systems ; bifurcations ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 95
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-08-08
    Description: Obesity represents the most prevalent metabolic disease in the world, posing a significant public health threat. Obesity shortens life expectancy by increasing the risk of developing comorbidities such as type 2 diabetes or cardiovascular disease. A better understanding of the ethiopathology of excess adiposity represents the pillar on which to base the effective management of obesity. In this sense, this reprint expands our knowledge about the wide array of drivers that can facilitate or contribute to the development of obesity. Moreover, some of the latest progress made in lifestyle, pharmacological and surgical approaches in the treatment of obesity are summarised. Novel concepts regarding the different obesity phenotypes, the use of telemedicine for the treatment of overweight and obesity, or the use of personalised avatars in the management of obesity are also reviewed. This reprint will be of interest for specialists in Endocrinology and Nutrition, but also for any individual interested in health issues related to nutrition.
    Keywords: obesity ; diet ; ultra-processed food ; NOVA classification ; diet quality ; dietary pattern ; non-communicable disease ; lifestyle intervention ; telemedicine ; COVID-19 pandemic ; obesogens ; “exposome” ; environment ; epigenetics ; microbiota ; antibiotics ; viral infection ; sleep ; endocrine disruptors ; brown adipose tissue ; thermogenesis ; Endobarrier ; food preferences ; eating behaviour ; taste function ; semaglutide ; STEP program ; weight loss ; weight management ; clinical trial ; GLP-1 ; inherited ; acquired ; exercise ; mitochondria ; Mediterranean diet ; metabolic syndrome ; plant-based foods ; polyphenols ; polyunsaturated fatty acids ; metabolism ; deep learning ; gated recurrent unit ; wearables ; forecasting ; diet plans ; digital nutrition ; nutrition education ; DFU ; nutrition supplementation ; body composition ; phase angle ; protein ; macronutrients ; micronutrients ; chronic wounds ; wound healing ; diabetic foot ulcer ; adipose tissue ; advanced glycation end-products ; cardiometabolic risk ; cardiovascular risk factors ; novel targets ; skin autofluorescence ; ketogenic diet ; overweight ; modified Wishnofsky equation ; modelling ; long short-term memory ; transformer ; digital twin ; SARIMAX ; 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::J Society & social sciences::JF Society & culture: general::JFC Cultural studies::JFCV Food & society
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-21
    Description: This issue is a continuation of the previous successful Special Issue “Wind Turbines 2013”. Similarly, this issue also focuses on recent advances in the wind energy sector on a wide range of topics, including: wind resource mapping, wind intermittency issues, aerodynamics, foundations, aeroelasticity, wind turbine technologies, control of wind turbines, diagnostics, generator concepts including gearless concepts, power electronic converters, grid interconnection, ride-through operation, protection, wind farm layouts - optimization and control, reliability, operations and maintenance, effects of wind farms on local and global climate, wind power stations, smart-grid and micro-grid related to wind turbine operation.
    Keywords: TK1-9971 ; wind farm ; wind speed prediction ; wind power ; smart grid ; wind power integration ; forecasting ; reliability ; fault tree analysis ; vertical-axis wind turbines ; wind turbine generator system ; off shore ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNB Energy industries & utilities
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  • 97
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The book “Assessment of Renewable Energy Resources with Remote Sensing" focuses on disseminating scientific knowledge and technological developments for the assessment and forecasting of renewable energy resources using remote sensing techniques. The eleven papers inside the book provide an overview of remote sensing applications on hydro, solar, wind and geothermal energy resources and their major goal is to provide state of art knowledge to contribute with the renewable energy resource deployment, especially in regions where energy demand is rapidly expanding. Renewable energy resources have an intrinsic relationship with local environmental features and the regional climate. Even small and fast environment and/or climate changes can cause significant variability in power generation at different time and space scales. Methodologies based on remote sensing are the primary source of information for the development of numerical models that aim to support the planning and operation of an electric system with a substantial contribution of intermittent energy sources. In addition, reliable data and knowledge on renewable energy resource assessment are fundamental to ensure sustainable expansion considering environmental, financial and energetic security.
    Keywords: metaheuristic ; parameter extraction ; solar photovoltaic ; whale optimization algorithm ; cloud detection ; digitized image processing ; artificial neural networks ; solar irradiance estimation ; solar irradiance forecasting ; solar energy ; sky camera ; remote sensing ; CSP plants ; coastal wind measurements ; scanning LiDAR ; plan position indicator ; velocity volume processing ; Hazaki Oceanographical Research Station ; cloud coverage ; image processing ; total sky imagery ; geothermal energy ; geophysical prospecting ; time domain electromagnetic method ; electrical resistivity tomography ; potential well field location ; GES-CAL software ; smart island ; solar radiation forecasting ; light gradient boosting machine ; multistep-ahead prediction ; feature importance ; voxel-design approach ; shading envelopes ; point cloud data ; computational design method ; passive design strategy ; lake breeze influence ; hydropower reservoir ; solar irradiance enhancement ; solar energy resource ; wind speed ; extreme value analysis ; scatterometer ; feature engineering ; forecasting ; graphical user interface software ; machine learning ; photovoltaic power plant ; surface solar radiation ; global radiation ; satellite ; Baltic area ; coastline ; cloud ; convection ; climate ; renewable energy resource assessment and forecasting ; remote sensing data acquisition ; data processing ; statistical analysis ; machine learning techniques ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water
    Keywords: TA1-2040 ; T1-995 ; TA170-171 ; natural hazards & ; artificial neural network ; flood routing ; the Three Gorges Dam ; backtracking search optimization algorithm (BSA) ; lag analysis ; artificial intelligence ; classification and regression trees (CART) ; decision tree ; real-time ; optimization ; ensemble empirical mode decomposition (EEMD) ; improved bat algorithm ; convolutional neural networks ; ANFIS ; method of tracking energy differences (MTED) ; adaptive neuro-fuzzy inference system (ANFIS) ; recurrent nonlinear autoregressive with exogenous inputs (RNARX) ; disasters ; flood prediction ; ANN-based models ; flood inundation map ; ensemble machine learning ; flood forecast ; sensitivity ; hydrologic models ; phase space reconstruction ; water level forecast ; data forward prediction ; early flood warning systems ; bees algorithm ; random forest ; uncertainty ; soft computing ; data science ; hydrometeorology ; LSTM ; rating curve method ; forecasting ; superpixel ; particle swarm optimization ; high-resolution remote-sensing images ; machine learning ; support vector machine ; Lower Yellow River ; extreme event management ; runoff series ; empirical wavelet transform ; Muskingum model ; hydrograph predictions ; bat algorithm ; data scarce basins ; Wilson flood ; self-organizing map ; big data ; extreme learning machine (ELM) ; hydroinformatics ; nonlinear Muskingum model ; invasive weed optimization ; rainfall–runoff ; flood forecasting ; artificial neural networks ; flash-flood ; streamflow predictions ; precipitation-runoff ; the upper Yangtze River ; survey ; parameters ; Haraz watershed ; ANN ; time series prediction ; postprocessing ; flood susceptibility modeling ; rainfall-runoff ; deep learning ; database ; LSTM network ; ensemble technique ; hybrid neural network ; self-organizing map (SOM) ; data assimilation ; particle filter algorithm ; monthly streamflow forecasting ; Dongting Lake ; machine learning methods ; micro-model ; stopping criteria ; Google Maps ; cultural algorithm ; wolf pack algorithm ; flood events ; urban water bodies ; Karahan flood ; St. Venant equations ; hybrid & ; hydrologic model ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Earth’s weather and climate are complex nonlinear systems of dynamical/thermodynamical processes that are highly variable on all spatiotemporal scales. The analysis and prediction of those processes and their feedbacks with the other systems of the biosphere (land and ocean), from the viewpoints of both atmospheric science and dynamics/thermodynamics, can improve our knowledge and have a great impact on society. The main aim of this Special Issue was to gather observational, theoretical and modeling studies on the dynamics of the atmosphere and the climate system, as well as on their predictability at different spatiotemporal scales.
    Keywords: drought ; forecasting ; Latin America ; Lagrangian numerical method ; ocean modeling ; ocean mixing ; atmospheric sounding ; Costa Rica ; GPS ; MODIS ; precipitable water vapor ; Blizzards ; blowing snow ; climatology ; self-organizing maps ; synoptic typing ; anthropogenic land cover changes ; hydrological model MIKE-SHE ; time-series statistical analysis ; trend analysis ; Spercheios river basin ; cold fronts ; Mediterranean ; identification scheme ; Frontal Tracking Scheme (FTS) ; MedFTS ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    Publication Date: 2023-12-20
    Description: Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (〈A〉, 〈neutA〉, 〈antiA〉), where 〈A〉 is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, 〈antiA〉 is the opposite of 〈A〉, while 〈neutA〉 is the neutral (or indeterminate) between them, i.e., neither 〈A〉 nor 〈antiA〉.Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc.
    Keywords: QA1-939 ; Q1-390 ; similarity measure ; generalized partitioned Bonferroni mean operator ; normal distribution ; school administrator ; complex neutrosophic set ; expert set ; neutrosophic classification ; multi-attribute decision-making (MADM) ; multi-criteria decision-making (MCDM) techniques ; criterion functions ; matrix representation ; possibility degree ; quantum computation ; typhoon disaster evaluation ; NT-subgroup ; generalized neutrosophic ideal ; three-way decisions ; decision-making ; G-metric ; multiple attribute group decision-making (MAGDM) ; SVM ; semi-neutrosophic triplets ; LA-semihypergroups ; power operator ; fuzzy graph ; neutrosophic cubic graphs ; LNGPBM operator ; neutrosophic c-means clustering ; (commutative) ideal ; region growing ; clustering algorithm ; Neutrosophic cubic sets ; forecasting ; vector similarity measure ; totally dependent-neutrosophic soft set ; Fenyves identities ; TODIM model ; similarity measures ; CI-algebra ; Dice measure ; de-neutrosophication methods ; DSmT ; semigroup ; VIKOR model ; multigranulation neutrosophic rough set (MNRS) ; simplified neutrosophic linguistic numbers ; Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) ; multi-criteria group decision making ; multi-attribute group decision-making (MAGDM) ; exponential operational laws of interval neutrosophic numbers ; simplified neutrosophic weighted averaging operator ; neutro-epimorphism ; Choquet integral ; fixed point theory (FPT) ; computability ; neutrosophic triplet set ; interval-valued neutrosophic set ; simplified neutrosophic sets (SNSs) ; totally dependent-neutrosophic set ; Maclaurin symmetric mean ; recursive enumerability ; loop ; photovoltaic plan ; intersection ; neutrosophic bipolar fuzzy set ; big data ; inclusion relation ; dual aggregation operators ; Hamming distance ; neutro-automorphism ; neutrosophic set theory ; multiple attribute decision-making ; multicriteria decision-making ; pseudo primitive elements ; medical diagnosis ; neutrosophic G-metric ; bipolar fuzzy set ; NC power dual MM operator (NCPDMM) operator ; neutrosophic sets (NSs) ; emerging technology commercialization ; neutrosophic triplet groups ; probabilistic rough sets over two universes ; neutrosophic triplet set (NTS) ; neutrosophic triplet cosets ; MM operator ; TOPSIS ; cloud model ; extended ELECTRE III ; extended TOPSIS method ; 2ingle-valued neutrosophic set ; dual domains ; probabilistic single-valued (interval) neutrosophic hesitant fuzzy set ; Jaccard measure ; data mining ; BE-algebra ; neutrosophic soft set ; aggregation operators ; image segmentation ; multiple attribute decision making (MADM) ; neutrosophic duplets ; fundamental neutro-homomorphism theorem ; neutro-homomorphism ; power aggregation operator ; linear and non-linear neutrosophic number ; multi-attribute decision making ; first neutro-isomorphism theorem ; MCGDM problems ; neutrosophic bipolar fuzzy weighted averaging operator ; Bonferroni mean ; analytic hierarchy process (AHP) ; quasigroup ; action learning ; weak commutative neutrosophic triplet group ; generalized aggregation operators ; single valued neutrosophic multiset (SVNM) ; sustainable supplier selection problems (SSSPs) ; LNGWPBM operator ; skin cancer ; oracle computation ; fault diagnosis ; interval valued neutrosophic support soft sets ; neutrosophic triplet normal subgroups ; soft set ; multi-criteria decision-making ; neutrosophic triplet ; generalized group ; neutrosophic multiset (NM) ; two universes ; algorithm ; multi-attribute decision making (MADM) ; PA operator ; BCI-algebra ; neutrosophic triplet group (NTG) ; single valued trapezoidal neutrosophic number ; quasi neutrosophic triplet loop ; neutrosophy ; complex neutrosophic graph ; S-semigroup of neutrosophic triplets ; and second neutro-isomorphism theorem ; MADM ; dermoscopy ; linguistic neutrosophic sets ; defuzzification ; construction project ; potential evaluation ; neutrosophic big data ; decision-making algorithms ; neutosophic extended triplet subgroups ; applications of neutrosophic cubic graphs ; fuzzy time series ; TFNNs VIKOR method ; two-factor fuzzy logical relationship ; oracle Turing machines ; grasp type ; interval neutrosophic sets ; multi-criteria group decision-making ; interval neutrosophic weighted exponential aggregation (INWEA) operator ; power aggregation operators ; neutrosophic triplet group ; MGNRS ; 2-tuple linguistic neutrosophic sets (2TLNSs) ; computation ; filter ; multi-valued neutrosophic set ; integrated weight ; Bol-Moufang ; prioritized operator ; interval number ; logic ; pseudo-BCI algebra ; interval neutrosophic set (INS) ; neutrosophic rough set ; soft sets ; Q-neutrosophic ; Linguistic neutrosophic sets ; fuzzy measure ; homomorphism theorem ; commutative generalized neutrosophic ideal ; neutrosophic association rule ; shopping mall ; dependent degree ; Q-linguistic neutrosophic variable set ; quasi neutrosophic loops ; symmetry ; neutrosophic sets ; neutrosophic logic ; neutrosophic cubic set ; complement ; robotic dexterous hands ; neutro-monomorphism ; group ; analytic network process ; Muirhead mean ; maximizing deviation ; classical group of neutrosophic triplets ; neutrosophic triplet quotient groups ; generalized neutrosophic set ; multi-criteria group decision-making (MCGDM) ; support soft sets ; decision making ; generalized De Morgan algebra ; multiple attribute group decision making (MAGDM) ; single-valued neutrosophic multisets ; 2TLNNs TODIM method ; membership ; grasping configurations ; single valued neutrosophic set (SVNS) ; multiple attribute decision making problem ; SWOT analysis ; neutrosophic clustering ; hesitant fuzzy set ; interval neutrosophic numbers (INNs) ; quasi neutrosophic triplet group ; triangular fuzzy neutrosophic sets (TFNSs) ; interdependency of criteria ; aggregation operator ; cosine measure ; neutrosophic set ; neutrosophic computation ; decision-making trial and evaluation laboratory (DEMATEL) ; partial metric spaces (PMS) ; NCPMM operator ; clustering ; bic Book Industry Communication::P Mathematics & science
    Language: English
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