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  • MDPI - Multidisciplinary Digital Publishing Institute  (378)
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  • 1
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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
    Language: English
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
    Keywords: QA75.5-76.95 ; T58.5-58.64 ; metadata ; image classification ; sensitivity analysis ; ROI detection ; residual learning ; image alignment ; adaptive convolutional kernels ; Hough transform ; class imbalance ; land surface temperature ; inundation mapping ; multiscale representation ; object-based ; convolutional neural networks ; scene classification ; morphological profiles ; hyperedge weight estimation ; hyperparameter sparse representation ; semantic segmentation ; vehicle classification ; flood ; Landsat imagery ; target detection ; multi-sensor ; building damage detection ; optimized kernel minimum noise fraction (OKMNF) ; sea-land segmentation ; nonlinear classification ; land use ; SAR imagery ; anti-noise transfer network ; sub-pixel change detection ; Radon transform ; segmentation ; remote sensing image retrieval ; TensorFlow ; convolutional neural network ; particle swarm optimization ; optical sensors ; machine learning ; mixed pixel ; optical remotely sensed images ; object-based image analysis ; very high resolution images ; single stream optimization ; ship detection ; ice concentration ; online learning ; manifold ranking ; dictionary learning ; urban surface water extraction ; saliency detection ; spatial attraction model (SAM) ; quality assessment ; Fuzzy-GA decision making system ; land cover change ; multi-view canonical correlation analysis ensemble ; land cover ; semantic labeling ; sparse representation ; dimensionality expansion ; speckle filters ; hyperspectral imagery ; fully convolutional network ; infrared image ; Siamese neural network ; Random Forests (RF) ; feature matching ; color matching ; geostationary satellite remote sensing image ; change feature analysis ; road detection ; deep learning ; aerial images ; image segmentation ; aerial image ; multi-sensor image matching ; HJ-1A/B CCD ; endmember extraction ; high resolution ; multi-scale clustering ; heterogeneous domain adaptation ; hard classification ; regional land cover ; hypergraph learning ; automatic cluster number determination ; dilated convolution ; MSER ; semi-supervised learning ; gate ; Synthetic Aperture Radar (SAR) ; downscaling ; conditional random fields ; urban heat island ; hyperspectral image ; remote sensing image correction ; skip connection ; ISPRS ; spatial distribution ; geo-referencing ; Support Vector Machine (SVM) ; very high resolution (VHR) satellite image ; classification ; ensemble learning ; synthetic aperture radar ; conservation ; convolutional neural network (CNN) ; THEOS ; visible light and infrared integrated camera ; vehicle localization ; structured sparsity ; texture analysis ; DSFATN ; CNN ; image registration ; UAV ; unsupervised classification ; SVMs ; SAR image ; fuzzy neural network ; dimensionality reduction ; GeoEye-1 ; feature extraction ; sub-pixel ; energy distribution optimizing ; saliency analysis ; deep convolutional neural networks ; sparse and low-rank graph ; hyperspectral remote sensing ; tensor low-rank approximation ; optimal transport ; SELF ; spatiotemporal context learning ; Modest AdaBoost ; topic modelling ; multi-seasonal ; Segment-Tree Filtering ; locality information ; GF-4 PMS ; image fusion ; wavelet transform ; hashing ; machine learning techniques ; satellite images ; climate change ; road segmentation ; remote sensing ; tensor sparse decomposition ; Convolutional Neural Network (CNN) ; multi-task learning ; deep salient feature ; speckle ; canonical correlation weighted voting ; fully convolutional network (FCN) ; despeckling ; multispectral imagery ; ratio images ; linear spectral unmixing ; hyperspectral image classification ; multispectral images ; high resolution image ; multi-objective ; convolution neural network ; transfer learning ; 1-dimensional (1-D) ; threshold stability ; Landsat ; kernel method ; phase congruency ; subpixel mapping (SPM) ; tensor ; MODIS ; GSHHG database ; compressive sensing ; thema EDItEUR::U Computing and Information Technology::UY Computer science
    Language: English
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.
    Keywords: academic cheating ; tax evasion ; informality ; pairs trading ; hurst exponent ; financial markets ; long memory ; co-movement ; cointegration ; risk ; delay ; decision-making process ; probability ; discount ; detection ; mean square error ; multicollinearity ; raise regression ; variance inflation factor ; derivation ; intertemporal choice ; decreasing impatience ; elasticity ; GARCH ; EGARCH ; VaR ; historical simulation approach ; peaks-over-threshold ; EVT ; student t-copula ; generalized Pareto distribution ; centered model ; noncentered model ; intercept ; essential multicollinearity ; nonessential multicollinearity ; commodity prices ; futures prices ; number of factors ; eigenvalues ; volatility cluster ; Hurst exponent ; FD4 approach ; volatility series ; probability of volatility cluster ; S&amp ; P500 ; Bitcoin ; Ethereum ; Ripple ; bitcoin ; deep learning ; deep recurrent convolutional neural networks ; forecasting ; asset pricing ; financial distress prediction ; unconstrained distributed lag model ; multiple periods ; Chinese listed companies ; cash flow management ; corporate prudential risk ; the financial accelerator ; financial distress ; induced risk aversion ; liquidity constraints ; liquidity risk ; macroeconomic propagation ; multiperiod financial management ; non-linear macroeconomic modelling ; Tobin’s q ; precautionary savings ; pharmaceutical industry ; scale economies ; profitability ; biotechnological firms ; non-parametric efficiency ; productivity ; DEA ; dispersion trading ; option arbitrage ; volatility trading ; correlation risk premium ; econometrics ; computational finance ; ensemble empirical mode decomposition (EEMD) ; autoregressive integrated moving average (ARIMA) ; support vector regression (SVR) ; genetic algorithm (GA) ; energy consumption ; cryptocurrency ; gold ; P 500 ; DCC ; copula ; copulas ; Markov Chain Monte Carlo simulation ; local optima vs. local minima ; SRA approach ; foreign direct investment ; bilateral investment treaties ; regional trade agreements ; structural gravity model ; policy uncertainty ; stock prices ; dynamically simulated autoregressive distributed lag (DYS-ARDL) ; threshold regression ; United States ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Language: English
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Photoacoustic (or optoacoustic) imaging, including photoacoustic tomography (PAT) and photoacoustic microscopy (PAM), is an emerging imaging modality with great clinical potential. PAI’s deep tissue penetration and fine spatial resolution also hold great promise for visualizing physiology and pathology at the molecular level. PAI combines optical contrast with ultrasonic resolution, and is capable of imaging at depths of up to 7 cm with a real-time scalable spatial resolution of 10 to 500 µm. PAI has demonstrated applications in brain imaging and cancer imaging, such as breast cancer, prostate cancer, ovarian cancer etc. This Special Issue focuses on the novel technological developments and pre-clinical and clinical biomedical applications of PAI. Topics include but are not limited to: brain imaging; cancer imaging; image reconstruction; quantitative imaging; light source and delivery for PAI; photoacoustic detectors; nanoparticles designed for PAI; photoacoustic molecular imaging; photoacoustic spectroscopy.
    Keywords: photoacoustic imaging ; tomography ; thermoacoustic ; radio frequency ; image quality assessment ; image formation theory ; image reconstruction techniques ; sparsity ; signal processing ; deconvolution ; empirical mode decomposition ; signal deconvolution ; photoacoustics ; tissue characterization ; absorption ; Photoacoustic Computed Tomography (PACT) ; ring array ; fast imaging ; low cost ; photoacoustic tomography ; full-field detection ; wave equation ; final time inversion ; uniqueness ; stability ; iterative reconstruction ; 3D photoacoustic tomography ; full-view illumination and ultrasound detection ; photoacoustic coplanar ; quartz bowl ; correlation matrix filter ; time reversal operator ; photo-acoustic tomography ; reflection artifacts ; deep learning ; convolutional neural network ; time reversal ; Landweber algorithm ; U-net ; optoacoustic imaging ; respiratory gating ; motion artifacts ; full-ring illumination ; diffused-beam illumination ; point source illumination ; ultrasound tomography (UST) ; photoacoustic tomography (PAT) ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: After almost two decades of continuous development in bio, circular, and green economy, the time is ripe for the assessment of the major achievements and challenges that private and public enterprises face today to further enhance these global sustainability concepts. Due to the central role of political incentives for the development and implementation of environmentally friendly and sustainable practices, the present book project focuses on the nexus between public policies, institutions, quality of public sector management, and patterns of interaction between government and private businesses in backing bio, green, and circular economy practices and eco-innovation. In addition, the project also accommodates surveys that elaborate on the differences between the implementation of new organizational forms and scientific innovations in technologically advanced and developing settings.
    Keywords: energy demand ; renewable energy ; biomass ; energy policies ; organizational factors ; healthcare waste management practices ; public hospitals ; Libya ; consumers ; cluster analysis ; sustainable consumption ; mass media ; social media ; green hydrogen ; green hydrogen value chain ; developing countries ; renewable energy sources ; hydrogen strategy ; scaling ; upscaling ; scaling innovation ; innovation diffusion ; innovation ; systematic literature review ; garbage sorting ; urban garbage disposal ; rural garbage disposal ; willingness ; family life ; neighbourhood ; COVID-19 ; Pakistan economy ; economic scale ; Keynesian theory ; mitigation ; economic revival measures ; innovations ; renewable power ; rebound effect ; low-carbon economy ; carbon pricing policy ; border carbon tax ; Sino–US trade friction ; export grab effect ; firm innovation ; GDP prediction ; feature selection ; deep learning ; temporal convolutional network ; organizational sustainability ; social and economic sustainability ; knowledge sharing ; organizational agility ; organizational behavior ; sustainable organizations ; economic sustainability ; consumer experience ; sustainable commerce ; online consumer behaviour ; e-commerce platform ; online purchase intention ; online customer engagement ; energy security ; energy policy ; energy resources ; sustainability ; bibliometrics ; circular business model ; open business model ; sharing economy ; circular economy ; peer-to-peer ; electricity trading ; green product ; green consumer behavior ; environmental responsibility ; environmental concern ; green purchasing decisions ; green business ; consumption dimension ; production dimension ; financial dimension ; technological dimension ; fundraising campaigns ; social networking sites ; NPO ; humanitarian response ; Kuwait ; Bahrain ; Guatemala ; forest ; property rights ; community concession ; entrepreneurship ; forest sustainability ; economic development ; free-market environmentalism ; Latin America ; consumption coupons ; purchase probability ; inventory optimization ; minimum-cost maximum-flow ; bioeconomy ; green growth ; eco-innovation ; environmental Kuznets curve ; EKC ; environmental economics and policy ; ecological economics ; resource management ; sustainable development ; 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
    Language: English
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.
    Keywords: TA1-2040 ; T1-995 ; optical sensor ; spectral analysis ; response surface sampling ; sensor evaluation ; electromagnetic induction ; multivariate water quality parameters ; mandarin orange ; crop inspection platform ; SPA-MLR ; object tracking ; feature selection ; simultaneous measurement ; diseases ; genetic algorithms ; processing of sensed data ; electrochemical sensors ; thermal image ; ECa-directed soil sampling ; handheld ; recognition patterns ; salt concentration ; clover-grass ; bovine embedded hardware ; weed control ; soil ; field crops ; vineyard ; connected dominating set ; water depth sensors ; SS-OCT ; wheat ; striped stem-borer ; silage ; geostatistics ; detection ; NIR hyperspectral imaging ; electronic nose ; machine learning ; virtual organizations of agents ; packing density ; data validation and calibration ; dataset ; Wi-SUN ; temperature sensors ; geoinformatics ; gas sensor ; X-ray fluorescence spectroscopy ; vegetable oil ; photograph-grid method ; Vitis vinifera ; WSN distribution algorithms ; laser-induced breakdown spectroscopy ; irrigation ; quality assessment ; energy efficiency ; wireless sensor network (WSN) ; geo-information ; Fusarium ; texture features ; weeds ; discrimination ; big data ; soil moisture sensors ; meat spoilage ; land cover ; stereo imaging ; near infrared sensors ; biological sensing ; compound sensor ; pest management ; moisture ; plant localization ; heavy metal contamination ; artificial neural networks ; spectral pre-processing ; moisture content ; apparent soil electrical conductivity ; data fusion ; semi-arid regions ; smart irrigation ; back propagation model ; wireless sensor network ; energy balance ; light-beam ; fluorescent measurement ; agriculture ; precision agriculture ; deep learning ; spectroscopy ; hulled barely ; dielectric probe ; RPAS ; water supply network ; rice leaves ; mobile app ; gradient boosted machines ; hyperspectral camera ; one-class ; nitrogen ; LiDAR ; total carbon ; chemometrics analysis ; rice ; agricultural land ; on-line vis-NIR measurement ; CARS ; obstacle detection ; stratification ; neural networks ; regression estimator ; Kinect ; proximity sensing ; distributed systems ; pest ; noninvasive detection ; texture feature ; soil mapping ; classification ; soil salinity ; visible and near-infrared reflectance spectroscopy ; germination ; computer vision ; hyperspectral imaging ; diffusion ; dielectric dispersion ; UAS ; random forests ; case studies ; total nitrogen ; thermal imaging ; cameras ; dry matter composition ; near-infrared ; salt tolerance ; deep convolutional neural networks ; soil type classification ; water management ; preprocessing methods ; wireless sensor networks (WSN) ; remote sensing image classification ; precision plant protection ; radar ; spatial variability ; GF-1 satellite ; plant disease ; naked barley ; leaf area index ; CIE-Lab ; change of support ; radiative transfer model ; 3D reconstruction ; plant phenotyping ; vine ; near infrared ; vegetation indices ; remote sensing ; greenhouse ; time-series data ; scattering ; sensor ; crop area ; speckle ; spatial data ; grapevine breeding ; wide field view ; partial least squares-discriminant analysis ; spiking ; area frame sampling ; chromium content ; machine-learning ; RGB-D sensor ; pest scouting ; PLS ; Capsicum annuum ; spatial-temporal model ; drying temperature ; boron tolerance ; ambient intelligence ; laser wavelength ; fuzzy logic ; dynamic weight ; landslide ; management zones ; real-time processing ; event detection ; crop monitoring ; apple shelf-life ; rice field monitoring ; wireless sensor ; birth sensor ; proximal sensor ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering.
    Keywords: SVM ; budding rate ; UAV ; geometric consistency ; radiometric consistency ; point clouds ; ICP ; reflectance maps ; vegetation indices ; Parrot Sequoia ; artificial intelligence ; precision agriculture ; agricultural robot ; optimization algorithm ; online operation ; segmentation ; coffee leaf rust ; machine learning ; deep learning ; remote sensing ; Fourth Industrial Revolution ; Agriculture 4.0 ; failure strain ; sandstone ; digital image correlation ; Hill–Tsai failure criterion ; finite element method ; reference evapotranspiration ; moisture sensors ; machine learning regression ; frequency-domain reflectometry ; randomizable filtered classifier ; convolutional neural network ; U-Net ; land use ; banana plantation ; Panama TR4 ; aerial photography ; remote images ; systematic mapping study ; agriculture ; applications ; total leaf area ; mixed pixels ; Cabernet Sauvignon ; NDVI ; Normalized Difference Vegetation Index ; precision viticulture ; 3D model ; spatial vision ; fertirrigation ; teaching–learning ; spectrometry ; Sentinel-2 ; pasture quality index ; normalized difference vegetation index ; normalized difference water index ; supplementation ; decision making ; digital agriculture ; grape yield estimate ; berries counting ; Dilated CNN ; machine learning algorithms ; classification performance ; winter wheat mapping ; large-scale ; water stress ; Prunus avium L. ; stem water potential ; low-cost thermography ; thermal indexes ; canopy temperature ; non-water-stressed baselines ; non-transpiration baseline ; soil moisture ; andosols ; image processing ; greenhouse ; automatic tomato harvesting ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 8
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Transportation is one of the most crucial aspects across the world, supporting the daily life of human beings and the sustainable development of the whole of society. Generally, meteorology causes various impacts on transportation operation, safety and efficiency. In the context of global warming, increasing numbers of extreme weather and climate events (such as fog, icy roads, and extreme winds) have been detected worldwide and are expected to occur more frequently in the future. Meanwhile, extreme events, such as dense fog, rainstorm, and blizzard, tend to damage transportation and traffic facilities (such as express ways, port, airport, and high-speed railway) and induce serious traffic blocks and accidents. In recent decades, concentrated and continuous efforts have been made to carry out meteorological analyses regardless of urban traffic or transportation conditions, including those of highways, shipping, aviation, etc. A number of methods and techniques have been intensively developed to promote the qualities of both observations and forecasts. More recently, state-of-the-art machine learning frameworks have also been widely introduced into studies regarding transportation meteorology and many other fields.
    Keywords: transportation meteorology ; pavement temperature prediction ; deep learning ; BiLSTM ; attention mechanisms ; winter icing ; air pollution ; traffic vitality ; built environment ; spatial correlation ; spatial lag model ; phone signaling data ; air quality ; behavioral habits ; activity density ; population distribution ; land use mix ; wind forecast ; error decomposition ; bias ; distribution ; sequence ; urban meteorology ; observation ; forecast ; early warning ; review ; China ; low-level wind shear ; ensemble learning classifiers ; Bayesian optimization ; SHapley Additive exPlanations ; wind shear ; go-around ; machine learning ; dynamic ensemble selection ; civil aviation safety ; pilot reports ; self-paced ensemble ; Shapley additive explanations ; climate change ; climatology ; sea ice ; marginal sea ; East Asia ; time-series modeling ; pavement temperature ; nowcasting ; variation characteristics ; forecast validation ; relative humidity ; microwave radiometer data ; total rainfall ; precipitation duration ; vertical distribution ; Beijing–Tianjin–Hebei region ; rail breakage ; frequency ; high-speed railway ; Siberian high ; teleconnection ; temperature ; Qinling mountains ; rainfall ; change characteristics ; geographical factors ; highways ; road blockage ; fuzzy analytic hierarchy process ; CRITIC weight assignment method ; road network vulnerability ; spatiotemporal distribution ; precipitation forecast ; ConvLSTM ; PredRNN ; expressway ; agglomerate fog ; risk level prediction of fog-related accidents ; meteorological conditions ; road hidden dangers ; traffic flow conditions ; visibility ; Yellow Sea and Bohai Sea ; observation data ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: As we move further into the 21st century, despite the fact that new technologies have emerged, machining remains the key operation to achieve high productivity and precision for high-added value parts in several sectors, but recent advances in computer applications should close the gap between simulations and industrial practices. This book, “Machining Dynamics and Parameters Process Optimization”, is oriented toward the different strategies and paths when it comes to increasing productivity and reliability in metal removal processes. The topics include the dynamic characterization of machine tools, experimental dampening techniques, and optimization algorithms combined with signal monitoring.
    Keywords: CNC parameters ; machining mode ; high speed ; high accuracy ; high surface quality ; five-axis linear-segment toolpath ; path smoothing ; B-spline curve-fitting ; path synchronization ; feedrate scheduling ; flute-grinding ; evolution algorithms ; wheel location and orientation ; thin-floor machining ; chatter ; magnetorheological damper ; bull-nose end mill ; tool wear monitoring ; milling ; complex part ; deep learning ; autoencoder ; deep multi-layer perceptron ; tool condition monitoring ; tool change policy ; Industry 4.0 ; machine learning ; CNN ; AI ; additive manufacturing ; thin walled machining ; dynamics ; machining cycle optimization ; multivariable tool ; stable peninsula ; homotopy perturbation method ; machining robot ; natural frequency prediction ; model optimization ; dynamic performance ; stability ; machining ; grinding ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The integration of information technologies with industry has marked the beginning of the fourth industrial revolution and promoted the development of industrial engineering. However, the depletion of resources and industrial waste caused by increasing amounts of industrial production pose a huge threat to nature. The application of sustainable supply chains in industrial engineering and management is one of the ways to balance the economy, society and environment. Therefore, it is a key concern for us to explore the construction of sustainable supply chains in industrial engineering and management. Moreover, to understand the impact of low-carbon, sustainable and recycled supply chains on industrial engineering, we need more in-depth investigations.This Special Issue aims to solicit original research and review articles discussing sustainable supply chain decision-making in industrial engineering and management to improve the sustainability of enterprise operations. Moreover, this Special Issue also shows mixed methods (e.g., modeling plus a case study) and rigorous quantitative/qualitative empirical studies of sustainable supply chains.
    Keywords: coordination degree model ; logistics industry ; digital economy ; industrial integration ; regional IEE system ; multimodel decision ; coupling coordination ; decision support methods ; online retailer ; consumer purchase behavior ; return strategy ; return insurance ; supply chain management ; real-time ; home delivery ; business modeling ; e-commerce ; time window ; lightweight ; carbon emissions ; low carbon benefits ; optimization design ; wheel hub ; subsidy policy ; remanufacturing industry ; donation strategy ; prisoner’s dilemma ; water-efficient products ; quality improvement ; DMAIC ; smart water closets ; carbon abatement ; cost sharing ; capital constraint ; environmental externality ; innovative products ; remanufacturing ; differential game ; bass model ; strategic emerging industries ; industrial structure ; employment effect ; artificial intelligence hardware ; data classification ; deep learning ; emission control ; industrial manufacturing ; bilateral matching decision making ; interval-valued hesitant fuzzy information ; bidirectional projection technology ; organizational quality-specific immunity ; automotive supply chain disruption ; supply chain resilience ; disruption risk ; bibliometric analysis ; co-citation analysis ; NGU ; self-attention ; CNN ; silver prediction ; data-driven ; composite systems ; synergy ; sustainability ; blockchain ; collection channel ; recycling strategies ; uncertain demand ; game theory ; federated learning ; intelligent manufacturing ; sustainable energy ; low-carbon strategy ; livestreaming marketing mode ; consumer low-carbon preference ; level of low-carbon promotion effort ; power structures ; 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
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