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  • thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general  (855)
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  • 1
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    Advances in Computer-Aided Technology (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-03-24
    Beschreibung: This book reprints articles from the Special Issue "Advances in Computer-Aided Technology" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of thirteen published articles. This Special Issue belongs to the "Mechatronic and Intelligent Machines" section. Industry 4.0 is characterized by the integration of advanced technologies, such as artificial intelligence, the Internet of Things, and cloud computing, into traditional manufacturing and production processes. CAx (Computer-Aided Systems) systems are a set of computer software tools used in engineering and product design, covering various stages of the product development cycle. Advanced CAx tools combine many different aspects of product lifecycle management (PLM), including design, finite element analysis (FEA), manufacturing, production planning and product. In connection with the transition to Industry 4.0 concepts, the concept of the digital twin comes to the fore, and existing CAx systems must adapt to this trend. The Special Issue deals with a number of research areas, such as: - New trends in CAx systems; Digital manufacturing; Internet of Things in manufacturing; Simulation of production systems and processes; Systems for advanced finite element analysis; Material engineering; Digitization and 3D scanning.
    Schlagwort(e): tensor glyph ; golden section ; vector space ; sandwich ; springback ; Vegter yield criterion ; numerical simulation ; PAM-STAMP 2G ; isotropic hardening law ; kinematic hardening law ; bending ; Bauschinger effect ; machine learning ; artificial neural network ; additive manufacturing ; high precision metrology ; CAD ; predictive model ; ship hull structure ; computer-aided design of structure ; database ; function soft block ; gun drill tool ; deep-drilling technology ; optimization ; tool life ; angle ; digital implant impression ; interimplant distance ; intraoral scanner ; trueness ; sewing machine ; needle bar ; floating needle ; electromagnet ; electromagnetic simulation ; noise reduction ; cycloidal gearbox ; friction ; actuator ; servomotor ; permanent magnet synchronous machine ; fixture design ; machining ; sustainable manufacturing ; process innovation ; complex-shape part ; signal processing ; monitoring system ; laser profiler ; surface roughness ; quality assessment ; non-contact method ; vision-based method ; frequency analysis ; abrasive water jet ; wood plastic composite ; natural reinforcement ; knitting machine ; stroke ; drive ; simulation ; cylinder ; dynamic modeling ; load spectrum reconstruction ; fatigue test ; hydraulic excavator ; n/a ; thema EDItEUR::C Language and Linguistics
    Sprache: Englisch
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  • 2
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    Wave and Tidal Energy (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-03-27
    Beschreibung: Concerns relating to energy supply and climate change have driven renewable energy targets around the world. Marine renewable energy could make a significant contribution to reducing greenhouse gas emissions and mitigating the consequences of climate change, while providing a high-technology industry. The conversion of wave and tidal energy into electricity has many advantages. Individual tidal and wave energy devices have been installed and proven, with commercial arrays planned throughout the world. The wave and tidal energy industry has developed rapidly in the past few years; therefore, it seems timely to review current research and map future challenges. Methods to improve understanding of the resource and interactions (between energy extraction, the resource and the environment) are considered, such as resource characterisation (including electricity output), design considerations (e.g., extreme and fatigue loadings) and environmental impacts, at all timescales (ranging from turbulence to decadal) and all spatial scales (from device and array scales to shelf sea scales).
    Schlagwort(e): tide-surge-wave model ; Taiwanese waters ; sea-state hindcast ; wave power ; wave energy ; unstructured grid model ; resource characterization ; WaveWatch III ; SWAN ; tidal energy ; experimental testing ; acoustic Doppler profiler ; Strangford Lough ; dc-dc bidirectional converter ; finite control set-model predictive control (FCS-MPC) ; oscillating water column (OWC) ; supercapacitor energy storage (SCES) ; wave climate variability ; wavelet analysis ; teleconnection patterns ; marine renewable energy ; ocean energy ; environmental effects ; wave modeling ; wave propagation ; numerical modeling ; sediment dynamics ; risk assessment ; marine current energy ; spiral involute blade ; hydrodynamic analysis ; numerical simulation ; wave energy trends ; reanalysis wave data ; Chilean coast ; renewable energy ; wave energy converters ; annual mean power production ; wave energy converter ; transmission coefficient ; absorption ; surfing amenity ; resource ; impact assessment ; feasibility study ; floating offshore wave farm ; WEC ; IRR ; LCOE ; marine energy ; unmanned ocean device ; multi-type floating bodies ; nonlinear Froude-Krylov force ; energy efficiency ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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  • 3
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    Physicochemical, Sensory and Nutritional Properties of Foods Affected by Processing and Storage (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-03-27
    Beschreibung: Processing and storage can cause changes and interactions in food components that have effects on nutritional value, organoleptic characteristics or even food safety. This book includes 19 research works showing important and interesting advances, as well as new approaches, in this research topic. Four articles are dedicated to studying the effect of canning conditions (filling media and some ingredients) on the diverse parameters of quality for fish and pet foods. Three articles are devoted to studying the effects of dehydration (pre-treatments and drying procedures). One article is dedicated to monitoring the elaboration of a fermented and dehydrated product (sausage) using a portable NIRS device. The ninth article of this book studies the effect of low-dose electron beam irradiation on cooking quality, moisture migration, and thermodynamics, as well as the digestion properties of the isolated starches in newly harvested and dried rice. The next contribution studies the use of different preservatives to avoid the formation of undesirable volatile organic compounds in stracciatella cheese. Another article examines the impact of source material, kibble size, temperature, and duration on the efficiency of the aqueous extraction of sugars and phenolics from carob kibbles by conventional heat-assisted (HAE) and ultrasound-assisted (UAE) methods. In two articles, marinating with different extracts, alone or combined with other seasoning/conditioning methods, was essayed to tenderize beef or to improve the sensory quality of chicken leg and breast meat. The effect of various cooking methods on the quality, structure, pasting, water distribution and protein oxidation of fish and meat-based snacks is studied in the fourteenth article. The last five articles are dedicated to the study of the effects of storage on several foods (olive oil, blueberry, beetroot and Atlantic mackerel).
    Schlagwort(e): Electron Beam Irradiation ; rice ; moisture ; physicochemical properties ; rabbiteye blueberry ; postharvest storage ; firmness ; aroma compounds ; off-odor ; dry-fermented sausages ; near infrared spectroscopy ; portable device ; PLS-DA ; Scomber colias ; prior chilling ; Fucus spiralis ; packaging medium ; canning ; lipid damage ; colour ; trimethylamine ; quality ; carob kibbles ; carob juice ; aqueous extraction ; sugars ; phenolics ; free amino acids ; biogenic amines ; filling medium ; European eels ; stracciatella cheese ; volatile organic compounds ; sensory characteristics ; natural preservatives ; cheese storage ; pineapple by-products ; hydrostatic pressure ; bromelain ; enzyme activity ; marinade ; meat ; texture ; water status and distribution ; microstructure ; secondary structure of protein ; Atlantic mackerel ; saffron quality ; secondary metabolites ; drying ; high performance liquid chromatography-diode array detection (HPLC-DAD) ; spectrophotometry ; canned eels ; olive oil ; sunflower oil ; oxidation ; antioxidants ; total phenols ; vitamin E ; fresh wet noodles ; humidity-controlled dehydration ; microorganisms ; shelf-life ; noodle quality ; “Rocha” pear ; ultrasound ; microwave ; quality characteristics ; empirical models ; beetroot ; organic farming ; storage ; bioactive compounds ; betalain ; nitrate ; sugar ; phenolic compounds ; total dry matter ; chicken meat ; sensory evaluation ; superheated steam ; marination ; hot smoking ; storage effect ; extra virgin olive oil ; phenols ; sterols ; tocopherols ; temperature ; argon ; freeze-thaw cycles ; anthocyanins ; gas chromatography-mass spectrometry ; aroma profiles ; hot-air drying ; blueberry ; cooking methods ; fish meat snacks ; LF-NMR ; SEM ; protein oxidation ; expressible moisture ; gel ; gum ; heat penetration ; thermally processed ; wet pet food ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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  • 4
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    Machine Learning and Data Mining Applications in Power Systems (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
    Schlagwort(e): virtual power plant (VPP) ; power quality (PQ) ; global index ; distributed energy resources (DER) ; energy storage systems (ESS) ; power systems ; long-term assessment ; battery energy storage systems (BESS) ; smart grids ; conducted disturbances ; power quality ; supraharmonics ; 2–150 kHz ; Power Line Communications (PLC) ; intentional emission ; non-intentional emission ; mains signalling ; virtual power plant ; data mining ; clustering ; distributed energy resources ; energy storage systems ; short term conditions ; cluster analysis (CA) ; nonlinear loads ; harmonics, cancellation, and attenuation of harmonics ; waveform distortion ; THDi ; low-voltage networks ; optimization techniques ; different batteries ; off-grid microgrid ; integrated renewable energy system ; cluster analysis ; K-means ; agglomerative ; ANFIS ; fuzzy logic ; induction generator ; MPPT ; neural network ; renewable energy ; variable speed WECS ; wind energy conversion system ; wind energy ; frequency estimation ; spectrum interpolation ; power network disturbances ; COVID-19 ; time-varying reproduction number ; social distancing ; load profile ; demographic characteristic ; household energy consumption ; demand-side management ; energy management ; time series ; Hidden Markov Model ; short-term forecast ; sparse signal decomposition ; supervised dictionary learning ; dictionary impulsion ; singular value decomposition ; discrete cosine transform ; discrete Haar transform ; discrete wavelet transform ; transient stability assessment ; home energy management ; binary-coded genetic algorithms ; optimal power scheduling ; demand response ; Data Injection Attack ; machine learning ; critical infrastructure ; smart grid ; water treatment plant ; power system ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
    Sprache: Englisch
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  • 5
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    Process Mining Workshops (2023)
    Springer Nature | Springer Nature Switzerland
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    Publikationsdatum: 2024-04-14
    Beschreibung: 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)
    Schlagwort(e): 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
    Sprache: Englisch
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  • 6
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    Artificial Intelligence Techniques in Hydrology and Water Resources Management (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2023-06-23
    Beschreibung: 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.
    Schlagwort(e): 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
    Sprache: Englisch
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  • 7
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    Advances in Computational Intelligence Applications in the Mining Industry (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2022-03-21
    Beschreibung: This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners.
    Schlagwort(e): truck dispatching ; mining equipment uncertainties ; orebody uncertainty ; discrete event simulation ; Q-learning ; grinding circuits ; minerals processing ; random forest ; decision trees ; machine learning ; knowledge discovery ; variable importance ; mineral prospectivity mapping ; random forest algorithm ; epithermal gold ; unstructured data ; blast impact ; empirical model ; mining ; fragmentation ; mine worker fatigue ; random forest model ; health and safety management ; stockpiles ; operational data ; mine-to-mill ; geostatistics ; ore control ; mine optimization ; digital twin ; modes of operation ; geological uncertainty ; multivariate statistics ; partial least squares regression ; oil sands ; bitumen extraction ; bitumen processability ; mine safety and health ; accidents ; narratives ; natural language processing ; random forest classification ; hyperspectral imaging ; multispectral imaging ; dimensionality reduction ; neighbourhood component analysis ; artificial intelligence ; mining exploitation ; masonry buildings ; damage risk analysis ; Bayesian network ; Naive Bayes ; Bayesian Network Structure Learning (BNSL) ; rock type ; mining geology ; bluetooth beacon ; classification and regression tree ; gaussian naïve bayes ; k-nearest neighbors ; support vector machine ; transport route ; transport time ; underground mine ; tactical geometallurgy ; data analytics in mining ; ball mill throughput ; measurement while drilling ; non-additivity ; coal ; petrographic analysis ; macerals ; image analysis ; semantic segmentation ; convolutional neural networks ; point cloud scaling ; fragmentation size analysis ; structure from motion ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Sprache: Englisch
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  • 8
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    Advances in Antimicrobial Coatings (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-03-28
    Beschreibung: This book is motivated by our passion to compile recent research on antimicrobial surfaces. We aimed to assemble research papers on the preparation of new materials, antimicrobial testing using different pathogens (bacteria, fungi, and viruses), and the relationship between the coating nanostructure and its reactivity towards the studied pathogen(s). We believe that a good antimicrobial coating should by characterized by (i) a fast activity towards the pathogen, (ii) sustainable activity based on the stability of the coating, and (iii) the lowest possible toxicity for humans and reduced risks for the environment. Striking a compromise between these different challenges is difficult and requires more research.
    Schlagwort(e): active packaging ; chitosan ; methylcellulose ; natamycin ; antimicrobial action ; quaternary ammonium groups ; acrylic acid ; glycidyl methacrylate ; crosslinking reaction ; coating ; edible films ; edible coatings ; antimicrobial agents ; fresh fish ; spoilage ; shelf-life ; black anther disease ; orchid cut flower ; silver nanoparticles ; antifouling efficacy ; flow-through ; triangular box ; Amphibalanus amphitrite ; cuprous oxide ; dynamic aging ; repellant activity ; raft experiment ; bioassay ; biofouling of ships’ hull ; polypropylene ; hernia meshes ; antibacterial ; drug release ; polydopamine ; antimicrobial ; citric acid ; cross-linked ; cold plasma ; antimicrobial activity ; brilliant green ; crystal violet ; demethylation ; lignin ; polyurethane coatings ; triphenylmethane dyes ; 3D printing ; catheters ; dialysis ; extrusion ; infections ; manufacturing ; infection ; coatings ; silver ; nanomaterials ; plasma deposition ; titanium-based thin films ; copper ; magnetron sputtering ; super-elastic coatings ; E. coli inactivation ; 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
    Sprache: Englisch
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  • 9
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    Empowering Materials Processing and Performance from Data and AI (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-09
    Beschreibung: Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new materials and products. Additionally, this gives rise to new paradigms in bridging raw material data and processing to the induced properties and performance. This present topical issue is a compilation of contributions on novel ideas and concepts, addressing several key challenges using data and artificial intelligence, such as:- proposing new techniques for data generation and data mining;- proposing new techniques for visualizing, classifying, modeling, extracting knowledge, explaining and certifying data and data-driven models;- processing data to create data-driven models from scratch when other models are absent, too complex or too poor for making valuable predictions;- processing data to enhance existing physic-based models to improve the quality of the prediction capabilities and, at the same time, to enable data to be smarter; and- processing data to create data-driven enrichment of existing models when physics-based models exhibit limits within a hybrid paradigm.
    Schlagwort(e): plasticity ; machine learning ; constitutive modeling ; manifold learning ; topological data analysis ; GENERIC ; soft living tissues ; hyperelasticity ; computational modeling ; data-driven mechanics ; TDA ; Code2Vect ; nonlinear regression ; effective properties ; microstructures ; model calibration ; sensitivity analysis ; elasto-visco-plasticity ; Gaussian process ; high-throughput experimentation ; additive manufacturing ; Ti–Mn alloys ; spherical indentation ; statistical analysis ; Gaussian process regression ; nanoporous metals ; open-pore foams ; FE-beam model ; data mining ; mechanical properties ; hardness ; principal component analysis ; structure–property relationship ; microcompression ; nanoindentation ; analytical model ; finite element model ; artificial neural networks ; model correction ; feature engineering ; physics based ; data driven ; laser shock peening ; residual stresses ; data-driven ; multiscale ; nonlinear ; stochastics ; neural networks ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 10
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    Integrated Water Resources Research (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-03-27
    Beschreibung: Anthropogenic and natural disturbances to freshwater quantity and quality are a greater issue for society than ever before. To successfully restore water resources requires understanding the interactions between hydrology, climate, land use, water quality, ecology, and social and economic pressures. This Special Issue of Water includes cutting edge research broadly addressing investigative areas related to experimental study designs and modeling, freshwater pollutants of concern, and human dimensions of water use and management. Results demonstrate the immense, globally transferable value of the experimental watershed approach, the relevance and critical importance of current integrated studies of pollutants of concern, and the imperative to include human sociological and economic processes in water resources investigations. In spite of the latest progress, as demonstrated in this Special Issue, managers remain insufficiently informed to make the best water resource decisions amidst combined influences of land use change, rapid ongoing human population growth, and changing environmental conditions. There is, thus, a persistent need for further advancements in integrated and interdisciplinary research to improve the scientific understanding, management, and future sustainability of water resources.
    Schlagwort(e): physical habitat ; aquatic ecology ; stream health ; environmental flows ; land use ; hydrology ; hydroecology ; ecohydrology ; climate change ; Appalachia ; reforestation ; land use-land cover ; land-atmosphere coupling ; water quality ; environmental perceptions ; human dimensions ; spatial models ; socioeconomics ; urban watershed management ; municipal watershed ; water quality impairment ; collaborative adaptive management ; water resources ; urban watersheds ; endocrine disrupting chemical ; opioid ; pathway analysis ; ontology ; metabolomics ; decision-making ; logit regression ; farmer perceptions ; social networks ; public funds ; water conservation adoption ; good governance ; sanitation ; sustainability ; water supply ; water-saving agriculture ; Chinese provincial input efficiency ; three-stage DEA model ; environmental variables ; Boufakrane river watershed ; remote sensing ; LULCC ; water balances ; vulnerability ; total dissolved solids ; drinking water ; Appalachian Mountains ; streamflow sensitivity ; water security ; water balance partitioning ; Budyko ; Escherichia coli ; Suspended particulate matter ; Water quality ; Land use practices ; Watershed management ; basin ; hydrologic model ; reaeration rates ; stream metabolism ; watershed ; physicochemistry ; land use practices ; experimental watershed ; suspended particulate matter ; stream water temperature ; watershed management ; bacteria ; land-use practices ; environmental persistence ; saturated hydraulic conductivity ; pedotransfer function ; model validation ; Chesapeake Bay Watershed ; experimental watershed study ; human dimensions of water ; watershed modeling ; hydrological modeling ; water pollutants ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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