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  • 1
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Nondestructive testing and evaluation (NDT&E) is one of the most important techniques for determining the quality and safety of materials, components, devices, and structures. NDT&E technologies include ultrasonic testing (UT), magnetic particle testing (MT), magnetic flux leakage testing (MFLT), eddy current testing (ECT), radiation testing (RT), penetrant testing (PT), and visual testing (VT), and these are widely used throughout the modern industry. However, some NDT processes, such as those for cleaning specimens and removing paint, cause environmental pollution and must only be considered in limited environments (time, space, and sensor selection). Thus, NDT&E is classified as a typical 3D (dirty, dangerous, and difficult) job. In addition, NDT operators judge the presence of damage based on experience and subjective judgment, so in some cases, a flaw may not be detected during the test. Therefore, to obtain clearer test results, a means for the operator to determine flaws more easily should be provided. In addition, the test results should be organized systemically in order to identify the cause of the abnormality in the test specimen and to identify the progress of the damage quantitatively.
    Schlagwort(e): composites ; multi-scale ; embedded damage ; non-destructive testing ; photoacoustic ; ultrasonic representation ; terahertz ; coded-aperture imaging ; convolution neural network (CNN) ; fast image reconstruction ; nondestructive evaluation ; acoustic nonlinearity parameter ; indirect method ; laser ultrasound ; fully non-contact ; surface acoustic wave ; UWB-PPM ; UWB-OOK ; buried objects ; nondestructive environment ; Levenberg–Marquardt method ; textured surface anomaly detection ; computer vision ; deep learning ; attention mechanism ; adaptive fusion ; power quality disturbances ; long short term memory ; convolutional neural network ; short time Fourier transform ; leaky Lamb wave ; semi-analytical finite element (SAFE) ; waveguide sensor ; finite-width plate ; waveguide plate ; width modes ; spatial beating ; Rayleigh–Sommerfeld integral (RSI) ; weld cracks ; eddy current nondestructive testing ; gradiently relative magnetic permeability ; heat affected zone ; austenitic stainless steel ; circulating fluidized bed combustion boiler ; water-cooled wall tube ; magnetic sensor array ; magnetic flux density ; flexible ultrasonic probe ; neutron irradiation embrittlement ; reactor pressure vessel ; magnetic nondestructive evaluation ; micromagnetic multiparameter microstructure and stress analysis 3MA ; magnetic adaptive testing ; 3D imaging of metal grains ; non-destructive testing methods ; stacking images ; SA106 carbon steel ; terahertz waves ; refractive index ; thickness measurement ; Shim stock films ; composite materials ; reflection mode ; neutron radiography ; Bragg-edge imaging ; gas tungsten arc welding (GTAW) ; low transformation temperature (LTT) steel ; austenite-to-martensite transformation ; Debye–Waller factor ; 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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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-23
    Beschreibung: This Special Issue includes contributions about occupants’ sustainable living in buildings and communities, highlighting issues surrounding the sustainable development of our environments and lives by emphasizing smart and green design perspectives. This Special Issue specifically focuses on research and case studies that develop promising methods for the sustainable development of our environment and identify factors critical to the application of a sustainable paradigm for quality of life from a user-oriented perspective. After a rigorous review of the submissions by experts, fourteen articles concerning sustainable living and development are published in this Special Issue, written by authors sharing their expertise and approaches to the concept and application of sustainability in their fields. The fourteen contributions to this special issue can be categorized into four groups, depending on the issues that they address. All the proposed methods, models, and applications in these studies contribute to the current understanding of the adoption of the sustainability paradigm and are likely to inspire further research addressing the challenges of constructing sustainable buildings and communities resulting in a sustainable life for all of society.
    Schlagwort(e): sustainability ; regionalism ; climate ; unit plan ; apartment ; Singapore ; Korea ; sustainable architecture ; space syntax ; partitioning theory ; total depth ; intelligibility ; movement economies ; architecture ; building performance simulation ; performance-based design ; agent-based model ; Gaussian process ; electroencephalography ; virtual reality ; monument architecture ; stress ; data visualization ; deep learning ; smart building ; interactive experience ; “five senses” interaction ; people-oriented ; embedding ; recommender system ; collaborative filtering ; housing preference ; housing decision ; human behavior simulation ; virtual users ; social sustainability ; performance analysis ; evaluation method ; architectural design education ; eye tracking ; virtual environment ; street robbery ; CPTED ; crime prevention ; fixation count ; people with physical disabilities ; job retention ; path analysis ; perceived workplace safety ; workplace disability facilities ; work satisfaction ; social housing ; social economy actors ; Seoul ; South Korea ; sustainable development ; sustainable design ; energy efficiency ; public rental housing ; building simulation ; elderly ; biophilia ; biophilic experience ; smart home ; smart-home service ; service framework ; water distribution ; water war ; conflict ; ownership ; divided Cyprus ; blue-collar workers ; intervention study ; health promotion ; cardiovascular disease ; n/a ; thema EDItEUR::A The Arts ; thema EDItEUR::A The Arts::AM Architecture
    Sprache: Englisch
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this Special Issue (SI) is dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement artificial intelligence (AI) into food and beverage production and for consumer assessment. This SI published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products, such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products.
    Schlagwort(e): sensory ; physicochemical measurements ; artificial neural networks ; near infra-red spectroscopy ; wine quality ; machine learning modeling ; weather ; consumer acceptance prediction ; data fusion ; emotion recognition ; facial expression recognition ; galvanic skin response ; machine learning ; neural networks ; sensory analysis ; avocado ; cultivars ; preference mapping ; sensory evaluation ; sensory descriptive analysis ; consumer science ; unifloral honeys ; botanical origin ; physicochemical parameters ; classification ; natural language processing ; deep learning ; sensory science ; flavor lexicon ; long short-term memory ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
    Sprache: Englisch
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective.
    Schlagwort(e): subject-dependent emotion recognition ; subject-independent emotion recognition ; electrodermal activity (EDA) ; deep learning ; convolutional neural networks ; automatic facial emotion recognition ; intensity of emotion recognition ; behavioral biometrical systems ; machine learning ; artificial intelligence ; driving stress ; electrodermal activity ; road traffic ; road types ; Viola-Jones ; facial emotion recognition ; facial expression recognition ; facial detection ; facial landmarks ; infrared thermal imaging ; homography matrix ; socially assistive robot ; EEG ; arousal detection ; valence detection ; data transformation ; normalization ; mental stress detection ; electrocardiogram ; respiration ; in-ear EEG ; emotion classification ; emotion monitoring ; elderly caring ; outpatient caring ; stress detection ; deep neural network ; convolutional neural network ; wearable sensors ; psychophysiology ; sensor data analysis ; time series analysis ; signal analysis ; similarity measures ; correlation statistics ; quantitative analysis ; benchmarking ; boredom ; emotion ; GSR ; classification ; sensor ; face landmark detection ; fully convolutional DenseNets ; skip-connections ; dilated convolutions ; emotion recognition ; physiological sensing ; multimodal sensing ; flight simulation ; activity recognition ; physiological signals ; thoracic electrical bioimpedance ; smart band ; stress recognition ; physiological signal processing ; long short-term memory recurrent neural networks ; information fusion ; pain recognition ; long-term stress ; electroencephalography ; perceived stress scale ; expert evaluation ; affective corpus ; multimodal sensors ; overload ; underload ; interest ; frustration ; cognitive load ; stress research ; affective computing ; human-computer interaction ; deep convolutional neural network ; transfer learning ; auxiliary loss ; weighted loss ; class center ; stress sensing ; smart insoles ; smart shoes ; unobtrusive sensing ; stress ; center of pressure ; regression ; signal processing ; arousal ; aging adults ; musical genres ; emotion elicitation ; dataset ; emotion representation ; feature selection ; feature extraction ; computer science ; virtual reality ; head-mounted display ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: Animal production (e.g., milk, meat, and eggs) provides valuable protein production for human beings and animals. However, animal production is facing several challenges worldwide such as environmental impacts and animal welfare/health concerns. In animal farming operations, accurate and efficient monitoring of animal information and behavior can help analyze the health and welfare status of animals and identify sick or abnormal individuals at an early stage to reduce economic losses and protect animal welfare. In recent years, there has been growing interest in animal welfare. At present, sensors, big data, machine learning, and artificial intelligence are used to improve management efficiency, reduce production costs, and enhance animal welfare. Although these technologies still have challenges and limitations, the application and exploration of these technologies in animal farms will greatly promote the intelligent management of farms. Therefore, this Special Issue will collect original papers with novel contributions based on technologies such as sensors, big data, machine learning, and artificial intelligence to study animal behavior monitoring and recognition, environmental monitoring, health evaluation, etc., to promote intelligent and accurate animal farm management.
    Schlagwort(e): pig weight ; body size ; estimation ; deep learning ; convolutional neural network ; pig identification ; mask scoring R-CNN ; soft-NMS ; group-housed pigs ; audio ; dairy cow ; mastication ; jaw movement ; forage management ; precision livestock management ; equine behavior ; wearable sensor ; intermodality interaction ; class-balanced focal loss ; absorbing Markov chain ; cow behavior analysis ; prediction of calving time ; cow identification ; EfficientDet ; YOLACT++ ; cascaded model ; instance segmentation ; generative adversarial network ; machine learning ; automated medical image processing ; deep neural network ; animal science ; CT scans ; computer vision ; cow ; extensive livestock ; sensorized wearable device ; monitoring ; parturition prediction ; radar sensors ; radar signal processing ; animal farming ; computational ethology ; signal classification ; wavelet analysis ; dairy welfare ; hierarchical clustering ; mutual information ; precision livestock farming ; time budgets ; unsupervised machine learning ; wearables design ; animal-centered design ; animal telemetry ; modularity ; smart collar ; design contributions ; additive manufacturing ; low-frequency tracking ; commercial aviary ; laying hens ; false registrations ; tree-based classifier ; animal behaviour ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Sprache: Englisch
    Format: application/octet-stream
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-28
    Beschreibung: This Urological Cancer 2020 collection contains a set of multidisciplinary contributions to the extraordinary heterogeneity of tumor mechanisms, diagnostic approaches, and therapies of the renal, urinary tract, and prostate cancers, with the intention of offering to interested readers a representative snapshot of the status of urological research.
    Schlagwort(e): renal cell carcinoma ; iron ; macrophages ; chelation therapy ; urothelial carcinoma ; transcriptome ; microtubule ; MAP1B ; prognosis ; KLF5 ; androgen receptor ; cell proliferation ; tumorigenesis ; prostate cancer ; precision medicine ; whole genome sequencing ; optical mapping ; therapy ; prostate carcinoma ; prostate mpMRI ; machine learning ; artificial intelligence ; deep learning ; neural network ; angiogenesis ; angiogenic growth factors ; antiangiogenic therapy ; renal tumors ; prevention ; α1-adrenoceptor antagonists ; anoikis ; vascularity ; research model ; oncogenes ; tumor suppressor genes ; MR-guided ; radiotherapy ; MRgRT ; stereotactic ablative radiotherapy ; stereotactic ablative radiation therapy (SABR) ; renal cell cancer ; RCC ; online adaptive ; [68Ga]Ga-PSMA PET/CT ; dual-time point imaging ; delayed imaging ; biphasic imaging ; lesion positivity rate ; CXCL9 ; PD1 ; PD-L1 ; stage T1 NMIBC ; prostatic neoplasms/mortality ; prostatic neoplasms/epidemiology ; SEER Program ; bladder cancer ; transurethral resection ; en-bloc resection ; CPT1A ; fatty acids ; serine ; androgen response ; ROS ; oxidative stress ; DONSON ; Downstream Neighbor of SON ; biomarker ; metastatic spread ; diagnosis ; differential diagnosis ; histopathology ; immunohistochemistry ; stroma signature ; patient-derived xenografts ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
    Sprache: Englisch
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: According to the National Research Council, the use of embedded systems throughout society could well overtake previous milestones in the information revolution. Mechatronics is the synergistic combination of electronic, mechanical engineering, controls, software and systems engineering in the design of processes and products. Mechatronic systems put “intelligence” into physical systems. Embedded sensors/actuators/processors are integral parts of mechatronic systems. The implementation of mechatronic systems is consistently on the rise. However, manufacturers are working hard to reduce the implementation cost of these systems while trying avoid compromising product quality. One way of addressing these conflicting objectives is through new automatic control methods, virtual sensing/estimation, and new innovative hardware topologies.
    Schlagwort(e): independent-wheel drive ; steering assistance ; nonlinear system ; active disturbance rejection control ; smooth road feeling ; city bus transport ; electric vehicles ; electrification ; software tool ; planning ; control ; charging management ; simulation ; analysis ; energy management ; hybrid electric vehicle ; powertrain electrification ; equivalent consumption minimization ; supercharging ; hardware-in-the-loop experiments ; driving force distribution ; decentralized traction system ; 4WD electric vehicle ; energy efficiency ; traction control ; efficiency optimization ; air mobility ; fuel cell hybrid aircraft ; stochastic optimal control ; drift counteraction optimal control ; normal force estimation ; unbiased minimum variance estimation ; controller output observer ; youla parameterization ; adaptive cruise control ; automated driving ; energy-saving ; fuel-saving ; optimal control ; passenger comfort ; new energy vehicles ; speed prediction ; macroscopic traffic model ; traffic big-data ; deep learning ; vehicle lateral dynamic and control ; unresolved issues ; application of speed prediction ; electric vehicle ; hybrid vehicle ; lithium ion ; ultracapacitor ; battery aging ; EHB ; EMB ; EWB ; system modeling ; bond graph ; optimization ; control design ; Youla parameterization ; robust control ; nonlinear optimization ; brake-by-wire ; actuator ; electro-mechanical brake ; electronic wedge brake ; electro-hydraulic brake ; 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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: This Special Issue of Entropy, titled “Recent Advances in Single-Particle Tracking: Experiment and Analysis”, contains a collection of 13 papers concerning different aspects of single-particle tracking, a popular experimental technique that has deeply penetrated molecular biology and statistical and chemical physics. Presenting original research, yet written in an accessible style, this collection will be useful for both newcomers to the field and more experienced researchers looking for some reference. Several papers are written by authorities in the field, and the topics cover aspects of experimental setups, analytical methods of tracking data analysis, a machine learning approach to data and, finally, some more general issues related to diffusion.
    Schlagwort(e): diauxic growth ; replicator equation ; mesoscopic model ; integro-differential equations ; anomalous diffusion ; statistical analysis ; single-particle tracking ; trajectory classification ; fractional Brownian motion ; estimation ; autocovariance function ; neural network ; Monte Carlo simulations ; multifractional Brownian motion ; power of the statistical test ; machine learning classification ; feature engineering ; confinement ; information theory ; Brownian particle ; stochastic thermodynamics ; CTRW ; diffusing-diffusivity ; occupation time statistics ; wound healing dynamics ; single pseudo-particle tracking ; phase contrast image segmentation ; 3D single-particle tracking ; Fisher information ; non-uniform illumination ; SPT ; deep learning ; residual neural networks ; random walk ; heterogeneous ; endosomes ; single particle trajectory ; stochastic processes ; trapping ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
    Sprache: Englisch
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments.
    Schlagwort(e): big data applications ; data processing ; data visualization ; neural networks ; reduction ; coastal waters ; urban expansion ; remote sensing and GIS ; expansion types and rates ; major explanatory factors ; Miami metropolitan area ; cliff coastlines ; cliff retreat ; time-series analysis ; airborne laser scanner ; warm upwelling ; sea surface temperature ; numerical modelling ; winter ; southern Baltic Sea ; beach monitoring ; mobile terrestrial LiDAR ; intensity calibration ; beach surface moisture ; Baltic coast ; Poland ; CORINE Land Cover ; land cover flow ; urbanisation ; afforestation ; deforestation ; spatial analysis ; SDGs ; coastal habitats ; ecosystem monitoring ; land cover mapping ; random forest algorithm ; Sentinel-2 ; modified soil-adjusted vegetation index 2–MSAVI2 ; normalized difference water index 2–NDWI2 ; brightness index 2–BI2 ; oil spill ; remote sensing ; review ; machine learning ; deep learning ; trajectory modeling ; vulnerability assessment ; coastal geomorphology ; shoreline change ; coastal process ; monitoring ; geomatic techniques ; Po River Delta ; archival multi-temporal data ; coastline changes ; emerged/submerged surfaces ; land subsidence ; relative sea level rise 2100 ; land cover ; dune coast ; air photograph ; South Baltic Sea ; coastal monitoring ; estuaries ; IoT ; lidar ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Myxobacteria are fascinating and important prokaryotes. They have large genomes and exhibit a wide range of interesting behaviors, including multicellular fruiting body formation, social interaction, predation, and secondary metabolite production. Substantial progress is being made in understanding their ecological roles and the evolutionary forces that have shaped their phenotypes and behaviors. Novel species of myxobacteria are regularly described, often producing unusual metabolites and enzymes which can be of significant biotechnological interest. Molecular studies, ranging in subject from individual enzymes to entire ‘omes, continue to provide rich insights into myxobacterial biology. This collected volume brings together five research articles and three reviews, to provide a snapshot of current myxobacterial research in all its diversity.
    Schlagwort(e): carotenoids ; comparative genomics ; development ; fruiting body formation ; one-component systems ; quorum signalling ; two-component systems ; myxobacteria ; Myxococcales ; germination ; bacterial cell wall ; sporulation ; morphology ; photoreceptor ; photosensitizer ; photoregulation ; singlet oxygen ; plasmalogens ; CarF ; vitamin B12 ; CarH ; ECF-sigma ; CarD-CdnL ; microbial food web ; trophic interactions ; predator–prey interactions ; mesopredator ; social bacteria ; nematodes ; experimental community ; behavior ; Myxococcus sp. ; Corallococcus sp. ; Melittangium sp. ; Archangium sp. ; biosynthetic gene clusters ; Myxococcus xanthus ; phase contrast microscopy ; fluorescence microscopy ; aggregation ; rippling ; deep learning ; generative adversarial network ; pretator-prey coevolution ; antagonism ; mucoidy ; predatory bacteria ; bacterial predation ; prey diversity ; negative frequency dependence ; experimental evolution ; MyxoEE-6 ; functional genomics ; genome evolution ; genome organisation ; pan-genome ; proteomics ; taxonomy ; transcriptomics ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSG Microbiology (non-medical)
    Sprache: Englisch
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  • 11
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-28
    Beschreibung: The need for energy is increasing and at the same time production from the conventional reservoirs is declining quickly. This requires an economically and technically feasible source of energy for the coming years. Among some alternative future energy solutions the most approachable source is from unconventional reservoirs. As the name “unconventional” implies it requires different and challenging approach to characterize and to develop such a resource. This special issue covers some of the technical challenges for developing unconventional energy sources from shale gas/oil, tight gas sand, and coalbed methane.
    Schlagwort(e): bedding fractures ; failure criterion ; lamina ; tight oil ; tight sandstone ; finite element simulation ; numerical simulation ; unconventional reservoir ; permeability ; group method of data handling ; artificial neural network ; well logs ; sensitivity analysis ; tight gas reservoir ; multi-fractured horizontal well (MFHW) ; unstable productivity model ; productivity forecast ; influencing factor analysis ; horizontal well with multiple finite-conductivity fractures ; elliptical-shaped drainage ; productivity index ; non-Darcy flow ; pressure-dependent conductivity ; reservoir properties ; void space structure ; porosity ; complex rocks ; NMR ; MICP ; CT ; SEM ; coal-bearing tight sandstone ; organic-rich clasts ; occurrence ; classifications ; formation mechanisms ; Ordos Basin ; hydraulic fracturing ; fracturing fluids ; fluids-rock interaction ; environmental implication ; history matching ; semianalytic model ; unconventional gas reservoirs ; multistage fractured horizontal wells ; fractal theory ; pore structure ; heterogeneity ; NMR measurements ; multifractal analysis ; shale reservoir ; elastic properties ; brittleness ; rock physics ; brittle spot identification ; shale gas ; reservoir characteristics ; gas content ; eastern Sichuan Basin ; the Da’anzhai member ; pulse decay method ; gas adsorption ; dual media ; unconventional core ; natural fracture ; influencing factor ; oil production ; carbonate rock ; basement reservoir ; Jizhong Sub-basin ; dynamic pore network modeling ; shale reservoirs ; water imbibition ; discrete element method ; modified fluid-mechanical coupling algorithm ; injection sequence ; well spacing ; stress shadow effect ; seismic location ; microseismic events ; waveform stacking ; induced seismicity ; CBM ; surfactant ; solid-free drilling fluid ; CBM reservoir wettability ; machine learning ; lithofacies ; umiat ; Alaska ; proppant transportation ; cross fractures ; CFD simulation ; dimensional analysis ; equilibrium proppant height ; coalbed methane ; Lattice Boltzmann method ; gas diffusion ; adsorption–desorption ; pore-scale ; clay minerals ; pore structures ; tight gas reservoirs ; Xujiaweizi Rift ; Northern Songliao Basin ; methane adsorption isotherm ; coal properties ; gradient boosting decision tree ; estimation model ; shale gas reservoir ; geology ; Gibbs excess adsorption ; supercritical adsorption ; gas viscosity ; high voltage spark discharge ; electrohydraulic effect ; electrical conductivity ; drilling ; rock damage ; pressure waves ; water fracturing ; turbulence effect ; Eulerian multiphase modeling ; proppant transport mechanism ; equilibrium height prediction model ; adaptive filtering ; complex noise canceling ; electromagnetic telemetry ; multifractured horizontal wells ; production analysis ; irregular stimulated region ; natural gas hydrate ; seismic modeling ; fractional derivatives ; gas geochemical characteristics ; noble gas ; shale gas evolution ; Large Igneous Province (LIP) ; gas loss ; geological structure ; gas controlling pattern ; neutral surface ; tectonic movement ; Bumu region ; seismic interpretation ; depositional environments characteristics ; Wheeler diagram ; seismic attributes ; heterogeneous sequence ; sample size ; neutron scattering ; mercury injection capillary pressure ; adsorption ; shale ; junggar basin ; hong-che fault zone ; carboniferous ; volcanic reservoir ; main controlling factors of hydrocarbon accumulation ; fracture ; vug ; micro CT ; carbonate ; wave velocity ; amorphous SiO2 ; X-ray diffraction ; X-ray fluorescence spectrometry ; scanning electron microscope ; quantitative analysis ; void ratio ; FEM ; ABAQUS ; matrix porosity ; kerogen porosity ; water saturation ; gas hydrate ; saturation ; deep learning ; recurrent neural network ; molecular simulation ; enhanced oil recovery ; methane ; shale petroleum ; technological development ; patent ; network analysis ; imbibition ; osmosis ; unconventional formations ; EOR ; water flooding ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 12
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: The concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites.The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained.More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products.This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry.
    Schlagwort(e): unmanned aerial vehicle ; urban LULC ; GEOBIA ; multiscale classification ; unmanned aircraft system (UAS) ; deep learning ; super-resolution (SR) ; convolutional neural network (CNN) ; generative adversarial network (GAN) ; structure-from-motion ; photogrammetry ; remote sensing ; UAV ; 3D-model ; surveying ; vertical wall ; snow ; remotely piloted aircraft systems ; structure from motion ; lidar ; forests ; orthophotography ; construction planning ; sustainable construction ; urbanism ; BIM ; building maintenance ; unmanned aerial vehicle (UAV) ; structure-from-motion (SfM) ; ground control points (GCP) ; accuracy assessment ; point clouds ; corridor mapping ; UAV photogrammetry ; terrain modeling ; vegetation removal ; unmanned aerial vehicles ; power lines ; image-based reconstruction ; 3D reconstruction ; unmanned aerial systems ; time series ; accuracy ; reproducibility ; orthomosaic ; validation ; drone ; GNSS RTK ; precision ; elevation ; multispectral imaging ; vegetation indices ; nutritional analysis ; correlation ; optimal harvest time ; UAV images ; monoscopic mapping ; stereoscopic plotting ; image overlap ; optimal image selection ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Sprache: Englisch
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  • 13
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: 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.
    Schlagwort(e): 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
    Sprache: Englisch
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  • 14
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –
    Schlagwort(e): Traffic sign detection and tracking (TSDR) ; advanced driver assistance system (ADAS) ; computer vision ; 3D convolutional neural networks ; machine learning ; CT brain ; brain hemorrhage ; visual inspection ; one-class classifier ; grow-when-required neural network ; evolving connectionist systems ; automatic design ; bio-inspired techniques ; artificial bee colony ; image analysis ; feature extraction ; ship classification ; marine systems ; citrus ; pests and diseases identification ; convolutional neural network ; parameter efficiency ; vehicle detection ; YOLOv2 ; focal loss ; anchor box ; multi-scale ; deep learning ; neural network ; generative adversarial network ; synthetic images ; tool wear monitoring ; superalloy tool ; image recognition ; object detection ; UAV imagery ; vehicular traffic flow detection ; vehicular traffic flow classification ; vehicular traffic congestion ; video classification ; benchmark ; semantic segmentation ; atrous convolution ; spatial pooling ; ship radiated noise ; underwater acoustics ; surface electromyography (sEMG) ; convolution neural networks (CNNs) ; hand gesture recognition ; fabric defect ; mixed kernels ; cross-scale ; cascaded center-ness ; deformable localization ; continuous casting ; surface defects ; 3D imaging ; defect detection ; object detector ; object tracking ; activity measure ; Yolo ; deep sort ; Hungarian algorithm ; optical flows ; spatiotemporal interest points ; sports scene ; CT images ; convolutional neural networks ; hepatic cancer ; visual question answering ; three-dimensional (3D) vision ; reinforcement learning ; human–robot interaction ; few shot learning ; SVM ; CNN ; cascade classifier ; video surveillance ; RFI ; artefacts ; InSAR ; image processing ; pixel convolution ; thresholding ; nearest neighbor filtering ; data acquisition ; augmented reality ; pose estimation ; industrial environments ; information retriever sensor ; multi-hop reasoning ; evidence chains ; complex search request ; high-speed trains ; hunting ; non-stationary ; feature fusion ; multi-sensor fusion ; unmanned aerial vehicles ; drone detection ; UAV detection ; visual detection ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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  • 15
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches.
    Schlagwort(e): CIELab ; component Substitution ; Pan sharpening ; Pléiades VHR Image ; coal ; inertinite macerals ; classification ; multifractal analysis ; support vector machine ; block-based coding ; video coding ; H.265/HEVC ; affine motion compensation ; image registration ; homography matrix ; local homography transformation ; convolutional neural network ; moving direct linear transformation ; super-resolution (SR) ; convolution neural network (CNN) ; Gene Expression Programming (GEP) ; deep learning ; image preclassification ; suspicious behavior detection ; motion ; magnitude ; gradient ; reactivity ; saliency ; haze removal ; dark channel ; atmospheric-light estimation ; coarse-to-fine search strategy ; sparse dictionary ; stable recovery ; frame ; RIP ; local dimming ; retinex theory ; bi-histogram equalization ; contrast ratio ; details preservation ; pansharpening ; image fusion ; image quality ; Satellite Pour l’Observation de la Terre (SPOT) 6 ; spectral consistency ; spatial consistency ; synthesis ; artificial intelligence ; dental application ; images ; detection ; parseval frame ; transform ; sparse representation ; octave convolution ; bilingual scene text reading ; Ethiopic script ; attention ; nasal cytology ; automatic cell segmentation ; rhinology ; image analysis ; feature extraction ; shape context ; plant recognition ; DPCNN ; BOF ; numeral spotting ; historical document analysis ; convolutional neural networks ; deep transfer learning ; handwritten digit recognition ; spectrum correction ; intensity correction ; compressed sensing ; tradeoff process ; IKONOS ; remote sensing ; fine-tuning ; learning rate scheduler ; cyclical learning rates ; label smoothing ; classification accuracy ; neural networks ; salient object detection ; RGB-D ; object detection ; small object ; multi-scale sampling ; balanced sampling ; texture ; structure ; optical ; coke ; iron ore ; sinter ; image processing ; segmentation ; identification ; action recognition ; silhouette sequences ; shape features ; ambient assisted living ; active ageing ; n/a ; 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
    Sprache: Englisch
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  • 16
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: In the past few years, knowledge about glaucoma diagnosis and follow up has evolved dramatically through advances in intraocular pressure (IOP) measurement, corneal biomechanics, structural and functional assessment of the ocular surface, anterior chamber, retina, optic nerve and intracranial visual pathways, as well as the advent of artificial intelligence. In addition, the development of new modalities of IOP-lowering and non-IOP-lowering drugs, alternative deliveries, refined laser technologies, and minimally invasive glaucoma surgery (MIGS) techniques with different implants have widened the therapeutic possibilities for treating this disease. Finally, current insights into risk factors and quality of life in relation to glaucomatous impairment are emerging. The purpose of this Special Issue is to present the latest exciting clinical developments that are taking place in the field of glaucoma.
    Schlagwort(e): ripasudil ; suture trabeculotomy ab interno ; Schlemm’s canal incision ; aqueous outflow ; open-angle glaucoma ; glaucoma ; inflammation ; oxidative stress ; phenotype ; polymorphism ; susceptibility ; intraocular pressure ; ocular inflammation ; cornea biomechanics ; Corvis® ST ; subclinical keratoconus ; ocular hypertension ; tears ; miRNAs ; next generation sequencing ; biomarkers ; genes ; signaling pathways ; apoptosis ; neurodegeneration ; glaucoma suspect ; lamina cribrosa ; optical coherence tomography angiography ; peripapillary vessel density ; OCTA ; vessel density ; disc ; peripapillary ; NTG ; BRVO ; corneal hysteresis ; corneal biomechanics ; ocular biomarkers ; deep learning ; perimetry ; optic nerve ; obesity ; risk factor ; young adults ; multifocal visual evoked potentials ; mfVEP ; physical exercise ; sport ; acrobatic gymnastics ; baseline intraocular pressure ; central corneal thickness ; ocular health ; tumbling skills ; hand balance ; cytokines ; BDNF ; VEGF ; fractalkine ; microglia ; saffron ; crocin ; retinal glial cells ; microperimetry ; OCT ; macula ; structure ; function ; correlation ; retina ; inner ; outer ; macular segmentation ; optical coherence tomography-angiography ; vascular density ; blood flow ; biomarker ; myopia ; n/a ; bic Book Industry Communication::M Medicine
    Sprache: Englisch
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  • 17
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-28
    Beschreibung: The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.
    Schlagwort(e): forest structure change ; EBLUP ; small area estimation ; multitemporal LiDAR and stand-level estimates ; forest cover ; Sentinel-1 ; Sentinel-2 ; data fusion ; machine-learning ; Germany ; South Africa ; temperate forest ; savanna ; classification ; Sentinel 2 ; land use land cover ; improved k-NN ; logistic regression ; random forest ; support vector machine ; statistical estimator ; IPCC good practice guidelines ; activity data ; emissions factor ; removals factor ; Picea crassifolia Kom ; compatible equation ; nonlinear seemingly unrelated regression ; error-in-variable modeling ; leave-one-out cross-validation ; digital surface model ; digital terrain model ; canopy height model ; constrained neighbor interpolation ; ordinary neighbor interpolation ; point cloud density ; stereo imagery ; remotely sensed LAI ; field measured LAI ; validation ; magnitude ; uncertainty ; temporal dynamics ; state space models ; forest disturbance mapping ; near real-time monitoring ; CUSUM ; NRT monitoring ; deforestation ; degradation ; tropical forest ; tropical peat ; forest type ; deep learning ; FCN8s ; CRFasRNN ; GF2 ; dual-FCN8s ; random forests ; error propagation ; bootstrapping ; Landsat ; LiDAR ; La Rioja ; forest area change ; data assessment ; uncertainty evaluation ; inconsistency ; forest monitoring ; drought ; time series satellite data ; Bowen ratio ; carbon flux ; boreal forest ; windstorm damage ; synthetic aperture radar ; C-band ; genetic algorithm ; multinomial logistic regression ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics
    Sprache: Englisch
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  • 18
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: This book focuses on a variety of interdisciplinary perspectives concerning the theory and application of artificial intelligence (AI) in medicine, medically oriented human biology, and healthcare. The list of topics includes the application of AI in biomedicine and clinical medicine, machine learning-based decision support, robotic surgery, data analytics and mining, laboratory information systems, and usage of AI in medical education. Special attention is given to the practical aspect of a study. Hence, the inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly highlighted.
    Schlagwort(e): computational intelligence ; medical assistance ; instance-based learning ; healthcare ; clinical decision support systems ; deep neural networks ; medical imaging ; backdoor attacks ; security and privacy ; COVID-19 ; gastric cancer ; endoscopy ; deep learning ; convolutional neural network ; brain ; pituitary adenoma ; dysembryoplastic neuroepithelial tumor ; DNET ; ganglioglioma ; digital pathology ; computer vision ; machine learning ; CNN ; ATLAS ; HarDNet ; Swin transformer ; segmentation ; U-Net ; cerebral infarction ; CycleGAN ; advanced statistics ; schizophrenia ; aggression ; forensic psychiatry ; medical image segmentation ; CT image segmentation ; kernel density ; semi-automated labeling tool ; Bayesian learning ; neuroimaging ; feature selection ; kernel formulation ; mental disorders ; MRI ; visual acuity ; fundus images ; ophthalmology ; SVM ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Sprache: Englisch
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  • 19
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: Urbanization is a dominant driver of landscape transformation across the world, with cities representing centers of economic and socio-cultural development. Today, more than 4.2 billion people live in urban areas, which represent ~3% of the Earth’s land area. By 2050, it is predicted this number will increase to 6.6 billion people (~70% of the predicted global population). As the human population grows, cities around the globe will continue to expand, increasing the demand for food and services. Within cities, urban forests provide multiple nature-based solutions, as well as other environmental services and socio-economic benefits, such as heat mitigation and social integration. Urban forests are also important for coping with psychological stress during events, such as the COVID-19 pandemic. Therefore, urban forests are a priority for basic and applied forest research because they are intimately connected with people’s physical, cultural, and economic well-being in the urban environment, and can also be important reservoirs of biodiversity. To promote a better understanding of urban forests and landscape ecology, this book in “Urban Forests and Landscape Ecology” compiled research set in urban forests and focused on some spatially explicit processes. Studies presented in this book are highly interdisciplinary and use a wide range of research approaches. This book present nine scientific publications from global urban forests demonstrating that these forests, as a nature-based solution, provide multiple environmental services and are crucial to improve urban livability and thereby the wellbeing of city dwellers.
    Schlagwort(e): aesthetics ; causal effects ; crown form ; foliage form ; urban forests ; urban forest ; NATURA 2000 area ; soundscape ; birds ; biological diversity ; ecosystem disservices ; Mediterranean region ; green infrastructure ; urban forest types ; indicators ; microclimate ; human thermal comfort ; outdoor thermal environment ; public health ; ecological services ; urban green space ; remote sensing ; deep learning ; convolutional neural network ; residual structure ; attention mechanism ; n/a ; urban biodiversity ; urban habitat quality ; InVEST model ; land surface temperature ; Moran’s I ; Zhengzhou ; social media data ; spatiotemporal utilization ; Shanghai ; ecological function ; landscape structure ; GIS ; air pollution alleviation ; accumulation on leaves ; PM2.5 ; encapsulated particles ; urban trees ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
    Sprache: Englisch
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  • 20
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: Machine learning (ML) technologies are emerging in Mechanical Engineering, driven by the increasing availability of datasets, coupled with the exponential growth in computer performance. In fact, there has been a growing interest in evaluating the capabilities of ML algorithms to approach topics related to metal forming processes, such as: Classification, detection and prediction of forming defects; Material parameters identification; Material modelling; Process classification and selection; Process design and optimization. The purpose of this Special Issue is to disseminate state-of-the-art ML applications in metal forming processes, covering 10 papers about the abovementioned and related topics.
    Schlagwort(e): sheet metal forming ; uncertainty analysis ; metamodeling ; machine learning ; hot rolling strip ; edge defects ; intelligent recognition ; convolutional neural networks ; deep-drawing ; kriging metamodeling ; multi-objective optimization ; FE (Finite Element) AutoForm robust analysis ; defect prediction ; mechanical properties prediction ; high-dimensional data ; feature selection ; maximum information coefficient ; complex network clustering ; ring rolling ; process energy estimation ; metal forming ; thermo-mechanical FEM analysis ; artificial neural network ; aluminum alloy ; mechanical property ; UTS ; topological optimization ; artificial neural networks (ANN) ; machine learning (ML) ; press-brake bending ; air-bending ; three-point bending test ; sheet metal ; buckling instability ; oil canning ; artificial intelligence ; convolution neural network ; hot rolled strip steel ; defect classification ; generative adversarial network ; attention mechanism ; deep learning ; mechanical constitutive model ; finite element analysis ; plasticity ; parameter identification ; full-field measurements ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTU Mining technology and engineering
    Sprache: Englisch
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  • 21
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-10-25
    Beschreibung: This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read.
    Schlagwort(e): data hiding ; AMBTC ; BTC ; Hamming code ; LSB ; predicate encryption ; inner product encryption ; constant-size private key ; efficient decryption ; constant pairing computations ; watermarking ; self-embedding ; digital signature ; fragile watermarking ; constrained backtracking matching pursuit ; sparse reconstruction ; compressed sensing ; greedy pursuit algorithm ; image processing ; visual surveillance ; deep learning ; object detection ; latency optimization ; mobile edge cloud ; connected autonomous cars ; smart city ; video surveillance ; physical layer security ; secure transmission ; secrecy capacity ; secrecy capacity optimization artificial noise ; power allocation ; channel estimation error ; neural network ; transfer learning ; scalograms ; MFCC ; Log-mel ; pre-trained models ; seismic patch classification ; CNN-features ; data complexity ; handwritten text recognition ; Residual Network ; Transformer model ; named entity recognition ; 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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  • 22
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-12-06
    Beschreibung: Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such applications may include water pollution and toxic waste in environmental monitoring, pesticide residual detection in food safety and inspection, plant and crop disease detection in agriculture, tumor detection and breast cancer detection in medical imaging, drug traffic in law enforcement, etc. Nevertheless, this reprint book provides many techniques which may find their ways in these applications as well.
    Schlagwort(e): hyperspectral image few-shot classification ; deep learning ; meta-learning ; relation network ; convolutional neural network ; constrained-target optimal index factor band selection (CTOIFBS) ; hyperspectral image ; underwater spectral imaging system ; underwater hyperspectral target detection ; band selection (BS) ; constrained energy minimization (CEM) ; lightweight convolutional neural networks ; hyperspectral imagery classification ; transfer learning ; air temperature ; spatial measurement ; FTIR ; MWIR ; carbon dioxide absorption ; target detection ; coffee beans ; insect damage ; hyperspectral imaging ; band selection ; visualization ; color formation models ; multispectral image ; image fusion ; joint tensor decomposition ; anomaly detection ; constrained sparse representation ; hyperspectral imagery ; moving target detection ; spatio-temporal processing ; hyperspectral remote sensing ; image classification ; constraint representation ; superpixel segmentation ; multiscale decision fusion ; plug-and-play ; denoising ; nonlinear unmixing ; spectral reconstruction ; residual augmented attentional u-shape network ; spatial augmented attention ; channel augmented attention ; boundary-aware constraint ; atmospheric transmittance ; temperature ; emissivity ; separation ; midwave infrared ; hyperspectral images ; hyperspectral image super-resolution ; data fusion ; spectral-spatial residual network ; self-supervised training ; hyperspectral ; vegetation ; generative adversarial network ; data augmentation ; classification ; rice leaf blast ; hyperspectral imaging data ; deep convolutional neural networks ; fused features ; evolutionary computation ; heuristic algorithms ; machine learning ; unmanned aerial vehicles (UAVs) ; vegetation mapping ; upland swamps ; mine environment ; rice ; rice leaf folder ; hyperspectral image classification ; change detection ; self-supervised learning ; attention mechanism ; multi-source image fusion ; SFIM ; least square estimation ; spatial filter ; hyperspectral imaging (HSI) ; hyperspectral target detection ; hyperspectral reconstruction ; hyperspectral unmixing ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 23
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: Special Issue “Advances in Management of Voice and Swallowing Disorders” is dedicated to innovations in screening and assessment and the effectiveness of interventions in both dysphonia and dysphagia. In contemporary practice, novel techniques have been introduced in diagnostics and rehabilitative interventions (e.g., machine learning, electrical stimulation). Similarly, advancements in methodological approaches to validate measures have been introduced (e.g., item response theory using Rasch analysis), prompting the need to develop new, robust measures for use in clinics and intervention studies. Against this backdrop, this Special Issue focuses on studies aiming to improve early diagnostics of laryngological disorders and its management. This issue also welcomes the submission of studies on diagnostic accuracy and psychometrics performance of existing and newly developed measures. This includes but is not limited to studies investigating screening tools with sound diagnostic accuracy and robust psychometric properties. Furthermore, interventions with high levels of evidence in relation to clinical outcome using robust methodology (e.g., sophisticated meta-analytic approaches) are of great interest. This issue provides an overview of the latest advances in voice and swallowing disorders.
    Schlagwort(e): T1a glottic carcinoma ; transoral laser microsurgery ; treatment outcome ; vocal function ; objective voice diagnostics ; vocal extent measure (VEM) ; occupational voice disorders ; prevention ; prophylaxis ; teachers ; occupational health ; voice training ; balneotherapy ; dysphagia ; swallowing ; laryngeal penetration or aspiration ; deglutition ; reliability ; videofluoroscopic swallowing study ; deep learning ; machine learning ; Voice Handicap Index (VHI-9i) ; international short scale ; VHI-9i severity levels ; test–retest reliability ; validation of classification ranges ; self-assessed vocal impairment (VHIs) ; hoarseness ; dysphonia severity categories ; voice diagnostics ; deglutition disorders ; tongue ; exercise ; ageing ; Sob Voice Therapy ; Optimal Phonation Task ; Negative Practice ; auditory-perceptual analysis ; acoustic voice analysis ; laryngeal sensory dysfunction ; chronic refractory cough ; botulinum toxin ; larynx ; laryngeal hypersensitivity ; cough hypersensitivity syndrome ; globus pharyngeus ; laryngopharyngeal reflux ; neuropathic cough ; throat irritation ; auditory discrimination ; voice control ; voice assessment ; voice disorders ; swallowing disorders ; RCT ; intervention ; compensation ; rehabilitation ; classic test theory ; measure ; psychometrics ; videofluoroscopic swallow studies ; VMV ; neuromuscular electrical stimulation ; pharyngeal electrical stimulation ; PES ; NMES ; repetitive transcranial magnetic stimulation ; transcranial direct current stimulation ; rTMS ; tDCS ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PN Chemistry
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  • 24
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that.
    Schlagwort(e): data mining ; decision-making system ; rough set ; mixed integer linear programming ; assembly clearance ; diesel engine quality ; Internet of things ; Wireless nodes ; Hybrid clustering ; Multi-hop routing ; Network lifetime ; Artificial intelligence ; data envelopment analysis ; decision making ; artificial intelligence ; performance ; visual analytics ; system ; air quality ; spatiotemporal ; multivariate ; dimension reduction ; clustering ; regular patterns ; anomalies ; speech recognition ; Long Short Term Memory (LSTM) ; speech output correction ; most-matching ; empirical correlations ; rheological properties ; real-time ; water-based drill-in fluid ; artificial neural network ; elastic parameters ; Poisson’s ratio ; sandstone ; self-adaptive differential evolution ; total organic carbon ; barnett shale ; devonian shale ; fishbone multilateral wells ; predictive models ; well productivity ; international research ; knowledge map visualization ; policy documents quantification ; research hotspot ; policy keyword ; minimum miscibility pressure (MMP) ; CO2 flooding ; new models ; face recognition ; security ; spoofing ; histogram of oriented gradients ; smart cities ; deep learning ; LSTM ; neural networks ; location prediction ; trajectories ; smart tourism ; static Young’s modulus ; sandstone formations ; machine learning ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
    Sprache: Englisch
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  • 25
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being.
    Schlagwort(e): vibratory stimulation device ; local muscle vibration ; proprioceptors ; low back pain ; response frequency ; postural control ; Vater-Pacini corpuscles ; electroencephalography ; deep learning ; driving fatigue ; feature extraction ; convolutional neural network ; rehabilitation ; robotics ; technological devices ; upper limb impairment ; organizational model ; inkjet printing ; respiratory rate ; strain gauge ; stretchable and wearable sensors ; silver nanoparticles ; clinical evaluation ; body posture ; upper limb rehabilitation ; serious games ; haptic feedback ; electromyography sensors ; virtual reality ; smoothness ; wearable sensors ; gait analysis ; stumbling ; plantar visualization ; remote fetal monitor ; measurement uncertainty ; standard deviation ; Monte-Carlo method (MMC) ; efficient estimator ; automated assessment ; UE-FMA ; pinch force ; pulling force ; slip onset ; stroke ; anorexia nervosa ; electrodermal activity ; time-domain analysis ; frequency-domain analysis ; nonlinear analysis ; virtual reality exposure therapy ; driving phobia ; post-traumatic stress disorder ; physiological signal ; piezo-fluid-structural coupled simulation ; APS ; valveless micropump ; closed-loop insulin pump ; Individual verification ; Electrocardiogram (ECG) ; Interval based LDA ; biometrics ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Sprache: Englisch
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  • 26
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-10-25
    Beschreibung: Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations.
    Schlagwort(e): physical human-robot interaction ; game theory ; adaptive optimal control ; robot control ; tandem force sensor ; traction force sensor ; human–robot interaction ; contact task ; imitation learning ; safe physical human–robot collaboration ; collision detection ; human action recognition ; artificial intelligence ; industrial automation ; reinforcement learning ; social robotics ; human-robot interaction ; reward design ; physical embodiment ; human robot collaboration ; human robot interaction ; path planning ; bidirectional awareness ; haptic feedback device ; human machine interface ; collision identification ; collaborative robot ; deep learning ; uncertainty estimation ; knowledge distillation ; human–robot collaboration ; speed and separation monitoring ; human–machine differentiation ; thermal cameras ; protective separation distance ; collaborative robots ; motion planning ; human motion prediction ; human-following robots ; teleoperation ; high-speed image processing ; machine learning ; finger position recognition ; grasp type estimation ; human-robot collaboration ; human-centered robotics ; task planning ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Sprache: Englisch
    Format: application/octet-stream
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  • 27
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: 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.
    Schlagwort(e): 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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  • 28
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.
    Schlagwort(e): rolling bearing ; performance degradation ; hybrid kernel function ; krill herd algorithm ; SVR ; acoustic-based diagnosis ; gear fault diagnosis ; attention mechanism ; convolutional neural network ; stacked auto-encoder ; weighting strategy ; deep learning ; bearing fault diagnosis ; intelligent leak detection ; acoustic emission signals ; statistical parameters ; support vector machine ; wavelet denoising ; Shannon entropy ; adaptive noise reducer ; gaussian reference signal ; gearbox fault diagnosis ; one against on multiclass support vector machine ; varying rotational speed ; fault detection and diagnosis ; faults estimation ; actuator and sensor fault ; observer design ; Takagi-Sugeno fuzzy systems ; automotive ; perception sensor ; lidar ; fault detection ; fault isolation ; fault identification ; fault recovery ; fault diagnosis ; fault detection and isolation (FDIR) ; autonomous vehicle ; model predictive control ; path tracking control ; fault detection and isolation ; braking control ; nonlinear systems ; fault tolerant control ; iterative learning control ; neural networks ; cryptography ; wireless sensor networks ; machine learning ; scan-chain diagnosis ; artificial neural network ; NARX ; control valve ; decision tree ; signature matrix ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 29
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load.
    Schlagwort(e): Prophet model ; Holt–Winters model ; long-term forecasting ; peak load ; prophet model ; multiple seasonality ; time series ; demand ; load ; forecast ; DIMS ; irregular ; galvanizing ; short-term electrical load forecasting ; machine learning ; deep learning ; statistical analysis ; parameters tuning ; CNN ; LSTM ; short-term load forecast ; Artificial Neural Network ; deep neural network ; recurrent neural network ; attention ; encoder decoder ; online training ; bidirectional long short-term memory ; multi-layer stacked ; neural network ; short-term load forecasting ; power system ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
    Sprache: Englisch
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  • 30
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-11-17
    Beschreibung: The use of robots in marine and underwater applications is growing rapidly. These applications share the common requirement of modeling the environment and estimating the robots’ pose. Although there are several mapping, SLAM, target detection and localization methods, marine and underwater environments have several challenging characteristics, such as poor visibility, water currents, communication issues, sonar inaccuracies or unstructured environments, that have to be considered. The purpose of this Special Issue is to present the current research trends in the topics of underwater localization, mapping, SLAM, and target detection and localization. To this end, we have collected seven articles from leading researchers in the field, and present the different approaches and methods currently being investigated to improve the performance of underwater robots.
    Schlagwort(e): underwater acoustic signal processing ; channel model ; signal enhancement ; signal denoising ; passive detection ; underwater localization ; electric field ; subspace scanning ; meta-EP PSO ; multi robot ; Simultaneous Localization and Mapping ; visual loop closure ; image global signatures ; sonar ; underwater robotics ; acoustic image segmentation ; neural network ; robust adaptive beamforming ; steering vector mismatch ; interference-plus-noise covariance matrix ; array errors ; point cloud segmentation ; deep learning ; pipe and valve recognition ; underwater perception ; computer vision ; autonomous navigation ; range sensing ; inspection and maintenance ; 3D vision ; 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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  • 31
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-10-25
    Beschreibung: The present book contains ten articles illustrating the different possible uses of UAVs and satellite remotely sensed data integration in Geographical Information Systems to model and predict changes in both the natural and the human environment. It illustrates the powerful instruments given by modern geo-statistical methods, modeling, and visualization techniques. These methods are applied to Arctic, tropical and mid-latitude environments, agriculture, forest, wetlands, and aquatic environments, as well as further engineering-related problems. The present Special Issue gives a balanced view of the present state of the field of geoinformatics.
    Schlagwort(e): mosaicking ; urban image ; seamline determination ; deep learning ; D-LinkNet ; climate change ; evergreen plants ; extreme events ; flavonol and chlorophyll sensor (Dualex) ; greenness indices ; mosses ; near-remote sensing active and passive NDVI sensors ; Sentinel-2 ; subarctic vegetation damage ; crop growth ; reflectance saturation ; crop model ; assimilation ; crop growth stage ; method combinations ; sentinel-2A image ; UAV image ; remote sensing ; soil salinity ; Love/Shida numbers ; satellite laser ranging (SLR) ; Yarragadee station ; Mount Stromlo station ; LAGEOS ; STELLA ; STARLETTE satellites ; SLR stations coordinates ; ITRF2014 ; Lake Ladoga ; CMEMS GlobColour CHL-OC5 ; eutrophication ; water quality assessment ; pulp and paper mill ; ecological status ; phytoplankton and chlorophyll-a ; chemical wastewater pollution ; ArcGIS ; big data ; blueberries ; image analysis ; orthomosaics ; segmentation refinement ; UAVs ; HAPS ; UAV ; monitoring ; constrained multiple objective optimization ; temporal hierarchical task planning ; GNSS stations ; tectonic plate motion parameters ; ITRF ; vegetation monitoring ; drivers of deforestation ; Zambezi region ; land degradation ; vegetation cover change ; wildlife management ; TSS-RESTREND ; greening and browning ; MODIS ; Mann–Kendall ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
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  • 32
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: The number of patient health data has been estimated to have reached 2314 exabytes by 2020. Traditional data analysis techniques are unsuitable to extract useful information from such a vast quantity of data. Thus, intelligent data analysis methods combining human expertise and computational models for accurate and in-depth data analysis are necessary. The technological revolution and medical advances made by combining vast quantities of available data, cloud computing services, and AI-based solutions can provide expert insight and analysis on a mass scale and at a relatively low cost. Computational intelligence (CI) methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods, have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. CI-based systems can learn from data and evolve according to changes in the environments by taking into account the uncertainty characterizing health data, including omics data, clinical data, sensor, and imaging data. The use of CI in healthcare can improve the processing of such data to develop intelligent solutions for prevention, diagnosis, treatment, and follow-up, as well as for the analysis of administrative processes. The present Special Issue on computational intelligence for healthcare is intended to show the potential and the practical impacts of CI techniques in challenging healthcare applications.
    Schlagwort(e): sEMG ; deep learning ; neural networks ; gait phase ; classification ; everyday walking ; convolutional neural network ; CRISPR ; leukemia nucleus image ; segmentation ; soft covering rough set ; clustering ; machine learning algorithm ; soft computing ; multistage support vector machine model ; multiple imputation by chained equations ; SVM-based recursive feature elimination ; unipolar depression ; diabetic retinopathy (DR) ; pre-trained deep ConvNet ; uni-modal deep features ; multi-modal deep features ; transfer learning ; 1D pooling ; cross pooling ; IMU ; gait analysis ; long-term monitoring ; multi-unit ; multi-sensor ; time synchronization ; Internet of Medical Things ; body area network ; MIMU ; early detection ; sepsis ; evaluation metrics ; machine learning ; medical informatics ; feature extraction ; physionet challenge ; electrocardiogram ; Premature ventricular contraction ; sparse autoencoder ; unsupervised learning ; Softmax regression ; medical diagnosis ; artificial neural network ; e-health ; Tri-Fog Health System ; fault data elimination ; health status prediction ; health status detection ; health off ; diffusion tensor imaging ; ensemble learning ; decision support systems ; healthcare ; computational intelligence ; Alzheimer’s disease ; fuzzy inference systems ; genetic algorithms ; next-generation sequencing ; ovarian cancer ; interpretable models ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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  • 33
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-24
    Beschreibung: The book, “Optimization and Energy Maximizing Control Systems for Wave Energy Converters”, presents eleven contributions on the latest scientific advancements of 2020-2021 in wave energy technology optimization and control, including holistic techno-economic optimization, inclusion of nonlinear effects, and real-time implementations of estimation and control algorithms.
    Schlagwort(e): wave energy ; wave energy converter ; PeWEC ; techno-economic optimisation ; genetic algorithm ; cost of energy ; CaPex ; CWR ; arrays ; experiments ; wave tank ; scale test ; point absorber ; array optimization ; energy-maximising control ; optimal control ; impedance-matching ; renewable energy systems ; paramertic resonance ; wave energy conversion ; real-time detection ; recursive least squares ; Kalman Filter ; Neural Network ; wave excitation forces ; estimation ; Optimal Control ; Wave Energy Converter ; control ; reinforcement learning ; deep reinforcement learning ; deep learning ; adaptive control ; wave energy converters ; spectral control ; power take-off ; WECs ; size optimization ; techno-economic performance ; PTO sizing ; causal control ; Model Predictive Control ; wave-energy converter ; absorbed power ; nonlinear model predictive control ; two degrees of freedom wave energy converter ; nonlinear hydrodynamics ; nonlinear power take-off ; nonlinear model ; Froude-Krylov force ; sliding mode control ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 34
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: This book compiles a set of original and innovative papers included in the Special Issue on UAVs for vegetation monitoring, which proves the wide scope of UAVs in very diverse vegetation applications, both in agricultural and forestry scenarios, ranging from the characterization of relevant vegetation features to the detection of plant or crop stressors. New methods and techniques are developed and applied to diverse vegetation scenarios to meet the main challenge of sustainability.
    Schlagwort(e): UAS ; UAV ; vegetation cover ; multispectral ; land cover ; forest ; Acacia ; Indonesia ; tropics ; vegetation ground cover ; vegetation indices ; agro-environmental measures ; olive groves ; southern Spain ; sUAS ; water stress ; ornamental ; container-grown ; artificial intelligence ; machine learning ; deep learning ; neural network ; visual recognition ; precision agriculture ; canopy cover ; image analysis ; crop mapping ; evapotranspiration (ET) ; GRAPEX ; remote sensing ; Two Source Energy Balance model (TSEB) ; contextual spatial domain/resolution ; data aggregation ; eddy covariance (EC) ; Fusarium wilt ; crop disease ; banana ; multispectral remote sensing ; purple rapeseed leaves ; unmanned aerial vehicle ; U-Net ; plant segmentation ; nitrogen stress ; Glycine max ; RGB ; canopy height ; close remote sensing ; growth model ; curve fitting ; NDVI ; solar zenith angle ; flight altitude ; time of day ; operating parameters ; CNN ; Faster RCNN ; SSD ; Inception v2 ; patch-based CNN ; MobileNet v2 ; detection performance ; inference time ; disease detection ; cotton root rot ; plant-level ; single-plant ; plant-by-plant ; classification ; UAV remote sensing ; crop monitoring ; RGB imagery ; multispectral imagery ; century-old biochar ; semantic segmentation ; random forest ; crop canopy ; multispectral image ; chlorophyll content ; remote sensing technique ; individual plant segmentation ; plant detection ; transfer learning ; maize tassel ; tassel branch number ; convolution neural network ; VGG16 ; plant nitrogen estimation ; vegetation index ; image segmentation ; transpiration ; method comparison ; oil palm ; multiple linear regression ; support vector machine ; artificial neural network ; UAV hyperspectral ; wheat yellow rust ; disease monitoring ; texture ; spatial resolution ; RGB camera ; thermal camera ; drought tolerance ; forage grass ; HSV ; CIELab ; broad-sense heritability ; phenotyping gap ; high throughput field phenotyping ; UAV digital images ; winter wheat biomass ; multiscale textures ; red-edge spectra ; least squares support vector machine ; variable importance ; drone ; hyperspectral ; thermal ; nutrient deficiency ; weed detection ; disease diagnosis ; plant trails ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 35
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: This book is about JIDOKA, a Japanese management technique coined by Toyota that consists of imbuing machines with human intelligence. The purpose of this compilation of research articles is to show industrial leaders innovative cases of digitization of value creation processes that have allowed them to improve their performance in a sustainable way. This book shows several applications of JIDOKA in the quest towards an integration of human and AI within Industry 4.0 Cyber Physical Manufacturing Systems. From the use of artificial intelligence to advanced mathematical models or quantum computing, all paths are valid to advance in the process of human–machine integration.
    Schlagwort(e): healthy operator 4.0 ; human–cyber–physical system ; industrial internet of things ; industry 4.0 ; smart workplaces ; EEG sensors ; manufacturing systems ; shopfloor management ; machine learning ; deep learning ; reference architecture model ; interoperability ; digital twin ; distributed ledger technology ; GDPR ; RAMI 4.0 ; LASFA ; quantum computing ; strategic organizational design ; Industry 4.0 ; complex networks ; cyber-physical systems ; lean management systems ; quantum strategic organizational design ; quantum circuits ; quantum simulation ; JIDOKA ; Operator 4.0 ; process variability ; integration explaining variability ; quantum approximate optimization algorithm ; value–stream networks ; optimization ; maintenance interval ; maintenance model ; semi-Markov process ; right-censored data ; finite horizon ; maintenance cost ; Cyber-Physical Systems ; Lean Manufacturing ; Directed Acyclic Graphs ; scikit-learn ; pipegraph ; machine learning models ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 36
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-11-17
    Beschreibung: 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.
    Schlagwort(e): 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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  • 37
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-24
    Beschreibung: Fruit production has faced many challenges in recent years as society seeks to increase fruit consumption while increasing safety and reducing the harmful effects of intensive farming practices (e.g., pesticides and fertilizers). In the last 50 years, the population has more than doubled and is expected to grow to 9 billion people by 2050. Per capita consumption of fruit is also increasing during this time and the global fruit industry is facing a major challenge to produce enough fruit in quantity and quality. The need for sustainable production of nutritious food is critical for human and environmental health.This book provides some answers to people who are increasingly concerned about the sustainability of fruit production and the fruit industry as a whole.
    Schlagwort(e): Cornus mas ; yield ; weight ; biochemical characteristics ; business models ; innovation ; resource efficiency ; sustainability ; environmental assessment ; fruit production ; cleaner production ; life cycle assessment (LCA) ; carbon footprint ; stevia leaves ; aronia pomace ; encapsulation ; polyphenols ; Halyomorpha halys ; green insecticides ; anthocyanin ; ExtendayTM ; fruit colouration ; light reflection ; LumilysTM ; plastic recycling ; reflective films ; resource conservation ; sustainable horticulture ; sea buckthorn ; biodiversity ; biochemical composition ; underutilized fruit ; fruit and nut trees ; chilling ; heat accumulation ; modeling ; New Mexico ; computing image analysis ; deep learning ; yield mapping in an orchard ; fruit counting ; computer vision ; apricot ; Sekerpare ; nutraceuticals ; Prunus persica L. ; colour ; chemical contents ; antioxidant capacity ; sugar ; native germplasm ; temperate fruit ; wild fig ; conservation ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
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  • 38
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: The present book contains 14 articles that were accepted for publication in the Special Issue “Numerical Computation, Data Analysis and Software in Mathematics and Engineering” of the MDPI journal Mathematics. The topics of these articles include the aspects of the meshless method, numerical simulation, mathematical models, deep learning and data analysis. Meshless methods, such as the improved element-free Galerkin method, the dimension-splitting, interpolating, moving, least-squares method, the dimension-splitting, generalized, interpolating, element-free Galerkin method and the improved interpolating, complex variable, element-free Galerkin method, are presented. Some complicated problems, such as tge cold roll-forming process, ceramsite compound insulation block, crack propagation and heavy-haul railway tunnel with defects, are numerically analyzed. Mathematical models, such as the lattice hydrodynamic model, extended car-following model and smart helmet-based PLS-BPNN error compensation model, are proposed. The use of the deep learning approach to predict the mechanical properties of single-network hydrogel is presented, and data analysis for land leasing is discussed. This book will be interesting and useful for those working in the meshless method, numerical simulation, mathematical model, deep learning and data analysis fields.
    Schlagwort(e): cold-roll forming ; longitudinal strain ; cubic spline function ; cumulative chord ; elastic–plastic problem ; complex variable meshless method ; interpolating shape function ; singular weight function ; complete basis function ; mathematical model ; leased price ; total leased area ; data analysis ; residential land ; Beijing ; meshless method ; dimension splitting–interpolating moving least squares (DS-IMLS) method ; improved interpolating element-free Galerkin (IEFG) method ; potential problem ; traffic flow ; two-dimensional lattice hydrodynamic model ; driver’s predictive effect ; finite element method ; alkali-activated slag ceramsite compound insulation block ; ANSYS CFX ; thermal and mechanical performances ; indoor thermal environment ; dimension splitting method ; dimension splitting generalized interpolating element-free Galerkin method ; convection–diffusion–reaction problem ; deep learning ; hydrogel network ; mechanical property ; convolutional neural network ; self-avoiding walk ; personnel health monitoring ; construction site management ; smart helmet ; infrared temperature measurement ; temperature error compensation ; BP neural network ; COVID-19 ; peridynamics ; dual-horizon ; crack propagation ; variable horizon ; multi-grid ; car-following model ; visual angle model ; electronic throttle angle ; stability analysis ; heavy haul ; railway tunnel ; basement structure ; dynamic response characteristics ; defects ; the lattice hydrodynamic model ; control signal ; strong wind ; optimal estimation of flux difference integral ; improved element-free Galerkin method ; Helmholtz equation ; penalty method ; improved moving least-squares approximation ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
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  • 39
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: 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.
    Schlagwort(e): 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
    Sprache: Englisch
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  • 40
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Recent advances in information technology have brought forth a paradigm shift in science, especially in the biology and medical fields. Statistical methodologies based on high-performance computing and big data analysis are now indispensable for the qualitative and quantitative understanding of experimental results. In fact, the last few decades have witnessed drastic improvements in high-throughput experiments in health science, for example, mass spectrometry, DNA microarray, next generation sequencing, etc. Those methods have been providing massive data involving four major branches of omics (genomics, transcriptomics, proteomics, and metabolomics). Information about amino acid sequences, protein structures, and molecular structures are fundamental data for the prediction of bioactivity of chemical compounds when screening drugs. On the other hand, cell imaging, clinical imaging, and personal healthcare devices are also providing important data concerning the human body and disease. In parallel, various methods of mathematical modelling such as machine learning have developed rapidly. All of these types of data can be utilized in computational approaches to understand disease mechanisms, diagnosis, prognosis, drug discovery, drug repositioning, disease biomarkers, driver mutations, copy number variations, disease pathways, and much more. In this Special Issue, we have published 8 excellent papers dedicated to a variety of computational problems in the biomedical field from the genomic level to the whole-person physiological level.
    Schlagwort(e): water temperature ; bathing ; ECG ; heart rate variability ; quantitative analysis ; t-test ; hypertrophic cardiomyopathy ; data mining ; automated curation ; molecular mechanisms ; atrial fibrillation ; sudden cardiac death ; heart failure ; left ventricular outflow tract obstruction ; cardiac fibrosis ; myocardial ischemia ; compound–protein interaction ; Jamu ; machine learning ; drug discovery ; herbal medicine ; data augmentation ; deep learning ; ECG quality assessment ; drug–target interactions ; protein–protein interactions ; chronic diseases ; drug repurposing ; maximum flow ; adenosine methylation ; m6A ; RNA modification ; neuronal development ; genetic variation ; copy number variants ; disease-related traits ; sequential order ; association test ; blood pressure ; cuffless measurement ; longitudinal experiment ; plethysmograph ; nonlinear regression ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 41
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: Extremely popular for statistical inference, Bayesian methods are also becoming popular in machine learning and artificial intelligence problems. Bayesian estimators are often implemented by Monte Carlo methods, such as the Metropolis–Hastings algorithm of the Gibbs sampler. These algorithms target the exact posterior distribution. However, many of the modern models in statistics are simply too complex to use such methodologies. In machine learning, the volume of the data used in practice makes Monte Carlo methods too slow to be useful. On the other hand, these applications often do not require an exact knowledge of the posterior. This has motivated the development of a new generation of algorithms that are fast enough to handle huge datasets but that often target an approximation of the posterior. This book gathers 18 research papers written by Approximate Bayesian Inference specialists and provides an overview of the recent advances in these algorithms. This includes optimization-based methods (such as variational approximations) and simulation-based methods (such as ABC or Monte Carlo algorithms). The theoretical aspects of Approximate Bayesian Inference are covered, specifically the PAC–Bayes bounds and regret analysis. Applications for challenging computational problems in astrophysics, finance, medical data analysis, and computer vision area also presented.
    Schlagwort(e): bifurcation ; dynamical systems ; Edward–Sokal coupling ; mean-field ; Kullback–Leibler divergence ; variational inference ; Bayesian statistics ; machine learning ; variational approximations ; PAC-Bayes ; expectation-propagation ; Markov chain Monte Carlo ; Langevin Monte Carlo ; sequential Monte Carlo ; Laplace approximations ; approximate Bayesian computation ; Gibbs posterior ; MCMC ; stochastic gradients ; neural networks ; Approximate Bayesian Computation ; differential evolution ; Markov kernels ; discrete state space ; ergodicity ; Markov chain ; probably approximately correct ; variational Bayes ; Bayesian inference ; Markov Chain Monte Carlo ; Sequential Monte Carlo ; Riemann Manifold Hamiltonian Monte Carlo ; integrated nested laplace approximation ; fixed-form variational Bayes ; stochastic volatility ; network modeling ; network variability ; Stiefel manifold ; MCMC-SAEM ; data imputation ; Bethe free energy ; factor graphs ; message passing ; variational free energy ; variational message passing ; approximate Bayesian computation (ABC) ; differential privacy (DP) ; sparse vector technique (SVT) ; Gaussian ; particle flow ; variable flow ; Langevin dynamics ; Hamilton Monte Carlo ; non-reversible dynamics ; control variates ; thinning ; meta-learning ; hyperparameters ; priors ; online learning ; online optimization ; gradient descent ; statistical learning theory ; PAC–Bayes theory ; deep learning ; generalisation bounds ; Bayesian sampling ; Monte Carlo integration ; PAC-Bayes theory ; no free lunch theorems ; sequential learning ; principal curves ; data streams ; regret bounds ; greedy algorithm ; sleeping experts ; entropy ; robustness ; statistical mechanics ; complex systems ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
    Sprache: Englisch
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  • 42
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
    Schlagwort(e): depthwise separable convolution (DSC) ; all convolutional network (ACN) ; batch normalization (BN) ; ensemble convolutional neural network (ECNN) ; electrocardiogram (ECG) ; MIT-BIH database ; cephalometric landmark ; X-ray ; deep learning ; ResNet ; registration ; electronic human-machine interface ; blindness ; gesture recognition ; inertial sensors ; IMU ; dynamic contrast-enhanced MRI ; kidney perfusion ; glomerular filtration rate ; pharmacokinetic modeling ; multi-layer perceptron ; parameter estimation ; instance segmentation ; computer vision ; retinal blood vessel image ; computer-aided diagnosis ; U-shaped neural network ; residual learning ; semantic gap ; intracranial hemorrhage ; computed tomography ; random forest ; sleep disorder ; obstructive sleep disorder ; overnight polysomnogram ; EEG ; EMG ; ECG ; HRV signals ; Electronic Medical Record (EMR) ; disease prediction ; Amyotrophic Lateral Sclerosis (ALS) ; weighted Jaccard index (WJI) ; lung cancer ; CT images ; CNN ; pulmonary fibrosis ; radiotherapy ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 43
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: This book is a reprint of the Special Issue entitled "The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?". Artificial intelligence is extending into the world of both digital radiology and digital pathology, and involves many scholars in the areas of biomedicine, technology, and bioethics. There is a particular need for scholars to focus on both the innovations in this field and the problems hampering integration into a robust and effective process in stable health care models in the health domain. Many professionals involved in these fields of digital health were encouraged to contribute with their experiences. This book contains contributions from various experts across different fields. Aspects of the integration in the health domain have been faced. Particular space was dedicated to overviewing the challenges, opportunities, and problems in both radiology and pathology. Clinal deepens are available in cardiology, the hystopathology of breast cancer, and colonoscopy. Dedicated studies were based on surveys which investigated students and insiders, opinions, attitudes, and self-perception on the integration of artificial intelligence in this field.
    Schlagwort(e): n/a ; eHealth ; medical devices ; mHealth ; digital radiology ; picture archive and communication system ; artificial intelligence ; electronic surveys ; chest CT ; chest radiography ; AI ; radiology ; awareness ; radiographers ; radiologists ; e-health ; m-health ; digital-pathology ; cytology ; histology ; diagnostic pathology ; breast cancer ; bibliometric analysis ; healthcare ; medical imaging ; VOSviewer ; digital-radiology ; artificial-intelligence ; acceptance ; consensus ; information technology ; cardiology ; imaging ; cervical cancer screening ; colposcopy ; deep learning ; machine learning ; medical students ; perceptions ; digitization in medicine ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBG Medical equipment & techniques
    Sprache: Englisch
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  • 44
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: 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.
    Schlagwort(e): 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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  • 45
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: As faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present their novel computational methods that have engineering and physics applications.
    Schlagwort(e): radial basis functions ; finite difference methods ; traveling waves ; non-uniform grids ; chaotic oscillator ; one-step method ; multi-step method ; computer arithmetic ; FPGA ; high strain rate impact ; modeling and simulation ; smoothed particle hydrodynamics ; finite element analysis ; hybrid nanofluid ; heat transfer ; non-isothermal ; shrinking surface ; MHD ; radiation ; multilayer perceptrons ; quaternion neural networks ; metaheuristic optimization ; genetic algorithms ; micropolar fluid ; constricted channel ; MHD pulsatile flow ; strouhal number ; flow pulsation parameter ; multiple integral finite volume method ; finite difference method ; Rosenau-KdV ; conservation ; solvability ; convergence ; transmission electron microscopy (TEM) ; convolutional neural networks (CNN) ; anomaly detection ; principal component analysis (PCA) ; machine learning ; deep learning ; neural networks ; Gallium-Arsenide (GaAs) ; radiation-based flowmeter ; two-phase flow ; feature extraction ; artificial intelligence ; time domain ; Boltzmann equation ; collision integral ; convolutional neural network ; annular regime ; scale layer-independent ; petroleum pipeline ; volume fraction ; dual energy technique ; prescribed heat flux ; similarity solutions ; dual solutions ; stability analysis ; RBF-FD ; node sampling ; lebesgue constant ; complex regions ; finite-difference methods ; data assimilation ; model order reduction ; finite elements analysis ; high dimensional data ; welding ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
    Sprache: Englisch
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  • 46
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic.
    Schlagwort(e): automated driving ; scenario-based testing ; software framework ; traffic signs ; ADAS ; traffic sign recognition system ; cooperative perception ; ITS ; digital twin ; sensor fusion ; edge cloud ; autonomous drifting ; model predictive control (MPC) ; successive linearization ; adaptive control ; vehicle motion control ; varying road surfaces ; vehicle dynamics ; Mask R-CNN ; transfer learning ; inverse gamma correction ; illumination ; instance segmentation ; pedestrian custom dataset ; deep learning ; wheel loaders ; throttle prediction ; state prediction ; automation ; safety validation ; automated driving systems ; decomposition ; modular safety approval ; modular testing ; fault tree analysis ; adaptive cruise control ; informed machine learning ; physics-guided reinforcement learning ; safety ; autonomous vehicles ; autonomous conflict management ; UTM ; UAV ; UGV ; U-Space ; framework development ; lane detection ; simulation and modelling ; multi-layer perceptron ; convolutional neural network ; driver drowsiness ; ECG signal ; heart rate variability ; wavelet scalogram ; automated driving (AD) ; driving simulator ; expression of trust ; acceptance ; simulator case study ; NASA TLX ; advanced driver assistant systems (ADAS) ; system usability scale ; driving school ; virtual validation ; ground truth ; reference measurement ; calibration method ; simulation ; traffic evaluation ; simulation and modeling ; connected and automated vehicle ; driver assistance system ; virtual test and validation ; radar sensor ; physical perception model ; virtual sensor model ; 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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  • 47
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.
    Schlagwort(e): real-time hybrid simulation ; H∞ control ; time delay ; mixed sensitivity ; structural health monitoring ; deep learning ; data anomaly detection ; convolutional neural network ; time–frequency extraction ; micro inertial measurement unit (MIMU) ; variational mode decomposition (VMD) ; Hilbert–Huang transform (HHT) ; frequency-domain integration approach (FDIA) ; torsion angle calculation ; offshore oil platform ; self-anchored suspension bridge ; cable clamp ; slippage ; force analysis ; high formwork ; ARMA ; BPNN ; stress trend prediction ; crack detection ; improved YOLOv4 ; concrete surface ; substructure shake table testing ; integration algorithm ; finite element method ; damper ; digital twin ; prestressed steel structure ; construction process ; safety assessment ; intelligent construction ; structural health monitoring (SHM) ; vibration ; frequency domain ; time domain ; time-frequency domain ; technical codes ; multiple square loops (MSL)-string ; seismic excitation ; dynamic response ; seismic pulse ; near and far field ; three-dimensional laser scanning ; surface flatness of initial support of tunnel ; curved surface fitting ; flatness calculation datum ; curvedcontinuous girder bridge ; collision response ; seismic mitigation ; pounding mitigation and unseating prevention ; heavy-duty vehicle ; road ; coupling model ; terrestrial laser scanning ; RGB ; genetic algorithm ; artificial neutral network ; 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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  • 48
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-11-17
    Beschreibung: The reprint “Land Administration 2.0” is an extension of the previous reprint “Remote Sensing for Land Administration”, another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as “Land Administration 2.0” in reference to both this Special Issue being the second volume on the topic “Land Administration” and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information.
    Schlagwort(e): UAV ; cadastral mapping ; data quality ; geometric accuracy ; impact assessment ; ground control points ; feature extraction ; flight plan ; image segmentation ; deep-learning ; building outlines ; cadastre modernization ; FCN ; high-resolution aerial orthoimages ; LiDAR data ; remote sensing ; land tenure ; land administration ; geospatially informed analysis ; knowledge co-production ; land ; visible boundary ; deep learning ; neural network ; classification ; building footprint extraction ; cadastre ; change detection ; VHR aerial images ; property valuation ; property taxation ; photogrammetry ; aerial imagery ; HRSI ; lidar ; artificial intelligence ; cadastral survey ; detail survey ; handheld LiDAR scanner ; calibration ; LiDAR system ; segmentation ; edge detection ; agricultural land boundary ; LiDAR ; automated feature extraction ; cadaster ; land registration ; land use planning ; 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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  • 49
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems.
    Schlagwort(e): high-level synthesis ; HLS ; SDSoC ; support vector machines ; SVM ; code refactoring ; Zynq ; ZedBoard ; extreme edge ; embedded edge computing ; internet of things deployment ; hardware design ; IoT security ; Contiki-NG ; trustability ; embedded systems ; collaborative filtering ; recommender systems ; parallelism ; reconfigurable hardware ; neuroevolution ; block-based neural network ; dynamic and partial reconfiguration ; scalability ; reinforcement learning ; embedded system ; artificial intelligence ; hardware acceleration ; neuromorphic processor ; power consumption ; harsh environment ; fog computing ; edge computing ; cloud computing ; IoT gateway ; LoRa ; WiFi ; low power consumption ; low latency ; flexible ; smart port ; quantisation ; evolutionary algorithm ; neural network ; FPGA ; Movidius VPU ; 2D graphics accelerator ; line-drawing ; Bresenham’s algorithm ; alpha-blending ; anti-aliasing ; field-programmable gate array ; deep learning ; performance estimation ; Gaussian process ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
    Sprache: Englisch
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  • 50
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-24
    Beschreibung: This Special Issue of Metabolites, entitled “Islet Biology and Metabolism” is dedicated to islet research and the impact of islet function in metabolic health and disease. Specific topics include, but are not limited to, islet hormone processing and secretion, islet transplant research, novel proteins of the insulin secretory pathway, as well as islet drug targets for the management of T1D and T2D.
    Schlagwort(e): insulin secretory granule ; beta-cells ; granule protein purification ; free fatty acid receptor (FFA) 2 ; FFA3 ; gut microbiome ; incretin ; insulin secretion ; short-chain fatty acids ; type 1 diabetes ; cytosolic calcium concentration ; glucose ; metabolic amplification ; mitochondria ; nutrient secretagogues ; diabetes ; hypoglycemic unaware ; ischaemia ; islet cell transplantation ; organ donation ; pancreas ; insulin ; beta cell ; human ; islet ; polarisation ; machine learning ; deep learning ; cell segmentation ; automation ; pancreatic islets ; leptin ; exocytosis ; tissue-engineering ; in vivo imaging ; metabolism ; β-cell ; viral transduction ; transplantation ; amplifying pathway ; hyperglycemia ; adenylyl cyclase ; incretins ; glucokinase ; forskolin ; cAMP ; exenatide ; islets ; bioenergetics ; glucose-stimulated insulin secretion ; respiration ; advanced glycation end products ; alagebrium chloride ; cross-link breaker ; immunopeptidome ; MIN6N8 cell line ; NOD mouse ; autoimmune diabetes ; pancreatic beta-cells ; intrauterine growth restriction ; maternal obesity ; developmental programming ; islet amyloid polypeptide (IAPP) ; granin ; secretory pathway ; trans-Golgi network (TGN) ; granule ; pancreatic β-cell ; amino acid ; aminoaciduria ; diabetes incidence ; insulitis ; neutral amino acid transporter ; non-obese diabetic mouse ; pancreatic islet ; Slc6a19 deficiency ; n/a ; bic Book Industry Communication::M Medicine
    Sprache: Englisch
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  • 51
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-03-21
    Beschreibung: This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field.
    Schlagwort(e): electrocardiographic imaging (ECGI) ; heart failure (HF) ; cardiac resynchronization therapy (CRT) ; ultrasound ; strain ; speckle tracking echocardiography ; in silico ; electrophysiology ; electrocardiogram ; ECG ; cardiac disease ; arrhythmia ; ischemia ; standardization ; computerized ECG ; personalized medicine ; telemedicine ; digital ECG data interchange protocol ; eHealth ; ECG equipment ; computerized electrocardiograph ; ECG analysis algorithms ; computerized ECG interpretation ; interatrial block ; partial interatrial block ; advanced interatrial block ; atypical patterns ; electrocardiogram (ECG) ; automated ECG analysis ; CSE study ; age ; sex ; race ; historical aspects ; electronic cohort ; mortality ; big data ; telehealth ; alarm fatigue ; annotation of ECG data ; arrhythmia alarms ; intensive care unit ; patient monitoring ; ambulatory ECG ; machine learning ; deep learning ; pattern recognition ; noise reduction ; Holter ECG ; ECG interpretation ; artificial intelligence ; body surface mapping ; electrocardiographic imaging ; image processing ; clinical applications ; n/a ; bic Book Industry Communication::M Medicine
    Sprache: Englisch
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  • 52
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs.
    Schlagwort(e): model-based design ; FPGA ; HDL code generation ; wearable sensors ; embedded devices ; face recognition ; face verification ; biometric sensors ; deep learning ; distillation ; convolutional neural networks ; spatial transformer network ; video coding ; discrete cosine transform ; directional transform ; VLSI ; alternative representations to float numbers ; posit arithmetic ; Deep Neural Networks (DNNs) ; neural network activation functions ; surface electromyography ; event-driven ; functional electrical stimulation ; embedded system ; resampling ; interpolating polynomial ; polyphase filter ; digital circuit design ; ASIC ; bitmap indexing ; processing in memory ; memory wall ; big data ; internet of things ; intelligent sensors ; autonomous driving ; cyber security ; HW accelerator ; on-chip random number generator (RNG) ; SHA2 ; ASIC standard-cell ; machine learning ; edge computing ; edge analytics ; ANN ; k-NN ; SVM ; decision trees ; ARM ; X-Cube-AI ; STM32 Nucleo ; rad-hard ; PLL (phase-locked loop) ; SEE (single event effects) ; Spacefibre ; TID (total ionization dose) ; charge pump ; phase/frequency detector ; frequency divider ; ring oscillator ; LC-tank oscillator ; SpaceFibre ; rad-hard circuits ; radiation effects ; high-speed data transfer ; support attitude ; inertial measurement unit ; coal mining ; unscented Kalman filter ; quaternion ; gradient descent ; research data collection and sharing ; connected and automated driving ; deployment and field testing ; vehicular sensors ; impact assessment ; knowledge management ; collaborative project methodology ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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  • 53
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: Photonics has had a decisive influence on recent scientific and technological achievements. It includes aspects of photon generation and photon–matter interaction. Although it finds many applications in the whole optical range of the wavelengths, most solutions operate in the visible and infrared range. Since the invention of the laser, a source of highly coherent optical radiation, optical measurements have become the perfect tool for highly precise and accurate measurements. Such measurements have the additional advantages of requiring no contact and a fast rate suitable for in-process metrology. However, their extreme precision is ultimately limited by, e.g., the noise of both lasers and photodetectors. The Special Issue of the Applied Science is devoted to the cutting-edge uses of optical sources, detectors, and optoelectronics systems in numerous fields of science and technology (e.g., industry, environment, healthcare, telecommunication, security, and space). The aim is to provide detail on state-of-the-art photonic technology for precision metrology and identify future developmental directions. This issue focuses on metrology principles and measurement instrumentation in optical technology to solve challenging engineering problems.
    Schlagwort(e): infrared thermometer ; mid-wave infrared ; indium arsenide antimony photodiode ; uncooled thermometer ; fibreoptic coupling ; chopper stabilised op-amp ; zero-drift pre-amplifier ; ammonia detection ; NH3 ; MOX sensors ; polymer sensors ; laser absorption spectroscopy ; CRDS ; CEAS ; MUPASS ; PAS ; HOT IR detectors ; HgCdTe ; P-i-N ; BLIP condition ; 2D material photodetectors ; colloidal quantum dot photodetectors ; low-light photodetectors ; fluorescence microscopy ; time-resolved fluorescence microscopy ; hybrid photodetector (HPD) ; single-molecule fluorescence detection ; fourier ptychography ; image classification ; deep learning ; neural network ; electro-optic modulator ; frequency modulation ; displacement measuring interferometer ; quantum cascade laser ; laser controller ; infrared modulator ; laser spectroscopy ; free space optics ; photonic metrology ; accuracy ; precision ; resolution ; FTIR ; absorption spectroscopy ; gas sensors ; optoelectronic sensors ; 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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  • 54
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens.
    Schlagwort(e): star image ; image denoising ; reinforcement learning ; maximum likelihood estimation ; mixed Poisson–Gaussian likelihood ; machine learning-based classification ; non-uniform foundation ; stochastic analysis ; vehicle–pavement–foundation interaction ; forest growing stem volume ; coniferous plantations ; variable selection ; texture feature ; random forest ; red-edge band ; on-shelf availability ; semi-supervised learning ; deep learning ; image classification ; machine learning ; explainable artificial intelligence ; wildfire ; risk assessment ; Naïve bayes ; transmission-line corridors ; image encryption ; compressive sensing ; plaintext related ; chaotic system ; convolutional neural network ; color prior model ; object detection ; piston error detection ; segmented telescope ; BP artificial neural network ; modulation transfer function ; computer vision ; intelligent vehicles ; extrinsic camera calibration ; structure from motion ; convex optimization ; temperature estimation ; BLDC ; electric machine protection ; touchscreen ; capacitive ; display ; SNR ; stylus ; laser cutting ; quality monitoring ; artificial neural network ; burr formation ; cut interruption ; fiber laser ; semi-supervised ; fuzzy ; noisy ; real-world ; plankton ; marine ; activity recognition ; wearable sensors ; imbalanced activities ; sampling methods ; path planning ; Q-learning ; neural network ; YOLO algorithm ; robot arm ; target reaching ; obstacle avoidance ; 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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  • 55
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: Size reduction processes represent a significant part of the capital as well as the operating cost in ore processing. Advancing the understanding of and improving such processes is worthwhile since any measurable enhancement may lead to benefits, which may materialize as reductions in energy consumption or wear or improved performance in downstream processes. This book contains contributions dealing with various aspects of comminution, including those intended to improve our current level of understanding and quantification of particle breakage and ore characterization techniques that are relevant to size reduction, as well as studies involving modeling and simulation techniques. The affiliations of the authors of the articles published in this book span 14 countries around the globe, which attests to the highly international nature of research in this field. The themes of the manuscripts also vary widely, from several that are more focused on experimental studies to those that deal, in greater detail, with the development and application of modeling and simulation techniques in comminution. Size reduction technologies more directly addressed in the manuscripts include jaw crushing, vertical shaft impact crushing, SAG milling, stirred milling, planetary milling, and vertical roller milling. Ores involved directly in the investigations include those of copper, lead–zinc, gold, and iron as well as coal, talc, and quartz.
    Schlagwort(e): nanoscale talc ; wet milling ; high-energy ball milling ; ball size ; aggregation ; quantitative microstructural analysis ; X-ray computed tomography ; selective comminution ; texture ; structure ; mineral processing ; crushing ; grinding ; grinding behaviors ; energy consumption characterization ; sulfur content ; heterogeneous breakage ; split energy ; mining operation ; ore milling ; ore grinding ; rock ; liberation ; bed breakage ; iron ore ; comminution ; saturation ; piston-and-die ; compaction ; compression ; breakage ; single particle breakage ; energy input ; drop-weight tester ; breakage modelling ; grinding prediction ; jaw crusher ; Discrete Element Method ; Particle Replacement Model ; simulation ; modeling ; primary crushing ; particle breakage ; semi-autogenous grinding mill ; operational hardness ; energy consumption ; mining ; deep learning ; long short-term memory ; quartz ; shear stress ; tribochemistry ; fracturing ; mixed sulfides ; sphalerite ; galena ; VSI ; DEM ; sand ; modelling ; Vertimill ; Tower Mill ; liner wear ; fine grinding ; discrete element method ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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  • 56
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot.
    Schlagwort(e): dynamic objects identification and localization ; laser cluster ; radial velocity similarity ; Pearson correlation coefficient ; particle filter ; trilateral indoor positioning ; RSSI filter ; RSSI classification ; stability ; accuracy ; inertial navigation system ; artificial neural network ; motion tracking ; sensor fusion ; indoor navigation system ; indoor positioning ; indoor navigation ; radiating cable ; leaky feeder ; augmented reality ; Bluetooth ; indoor positioning system ; smart hospital ; indoor ; positioning ; visually impaired ; deep learning ; multi-layered perceptron ; inertial sensor ; smartphone ; multi-variational message passing (M-VMP) ; factor graph (FG) ; second-order Taylor expansion ; cooperative localization ; joint estimation of position and clock ; RTLS ; indoor positioning system (IPS) ; position data ; industry 4.0 ; traceability ; product tracking ; fingerprinting localization ; Bluetooth low energy ; Wi-Fi ; performance metrics ; positioning algorithms ; location source optimization ; fuzzy comprehensive evaluation ; DCPCRLB ; UAV ; unmanned aerial vehicles ; NWPS ; indoor positioning systems ; GPS denied ; GNSS denied ; autonomous vehicles ; visible light positioning ; mobile robot ; calibration ; appearance-based localization ; computer vision ; Gaussian processes ; manifold learning ; robot vision systems ; image manifold ; descriptor manifold ; indoor fingerprinting localization ; Gaussian filter ; Kalman filter ; received signal strength indicator ; channel state information ; indoor localization ; visual-inertial SLAM ; constrained optimization ; path loss model ; particle swarm optimization ; beacon ; absolute position system ; cooperative algorithm ; intercepting vehicles ; robot framework ; UWB sensors ; Internet of Things (IoT) ; wireless sensor network (WSN) ; switched-beam antenna ; electronically steerable parasitic array radiator (ESPAR) antenna ; received signal strength (RSS) ; fingerprinting ; down-conversion ; GPS ; navigation ; RF repeaters ; up-conversion ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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  • 57
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application.
    Schlagwort(e): falls ; slips ; trips ; postural perturbations ; wearables ; stretch-sensors ; ankle kinematics ; rowing ; technology ; inertial sensor ; accelerometer ; performance ; signal processing ; sEMG ; knee ; random forest ; principal component analysis ; back propagation ; estimation model ; knee angle ; deep learning ; neural networks ; gait-phase classification ; electrogoniometer ; EMG sensors ; walking ; gait-event detection ; automotive radar ; machine learning ; walking analysis ; seated posture ; cognitive engagement ; stress level ; load cells ; embedded systems ; sensorized seat ; flexion-relaxation phenomenon ; surface electromyography ; wearable device ; WBSN ; automatic detection of the FRP ; Internet of Things (IoT) ; human activity recognition (HAR) ; motion analysis ; wearable sensors ; cerebral palsy ; hemiplegia ; motor disorders ; gait variability ; coefficient of variation ; surface EMG ; statistical gait analysis ; activation patterns ; co-activation ; Parkinson’s disease ; activity recognition ; rate invariance ; Lie group ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 58
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: • provide novel insights into the functional properties of the IB; • discuss the IB principle (and its derivates) as an objective for training multi-layer machine learning structures such as neural networks and decision trees; and • offer a new perspective on neural network learning via the lens of the IB framework. Our collection thus contributes to a better understanding of the IB principle specifically for deep learning and, more generally, of information–theoretic cost functions in machine learning. This paves the way toward explainable artificial intelligence.
    Schlagwort(e): information theory ; variational inference ; machine learning ; learnability ; information bottleneck ; representation learning ; conspicuous subset ; stochastic neural networks ; mutual information ; neural networks ; information ; bottleneck ; compression ; classification ; optimization ; classifier ; decision tree ; ensemble ; deep neural networks ; regularization methods ; information bottleneck principle ; deep networks ; semi-supervised classification ; latent space representation ; hand crafted priors ; learnable priors ; regularization ; deep learning ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
    Sprache: Englisch
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  • 59
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-03-21
    Beschreibung: The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity.
    Schlagwort(e): ARIMA model ; time series analysis ; online optimization ; online model selection ; precipitation nowcasting ; deep learning ; autoencoders ; radar data ; generalization error ; recurrent neural networks ; machine learning ; model predictive control ; nonlinear systems ; neural networks ; low power ; quantization ; CNN architecture ; multi-objective optimization ; genetic algorithms ; evolutionary computation ; swarm intelligence ; Heating, Ventilation and Air Conditioning (HVAC) ; metaheuristics search ; bio-inspired algorithms ; smart building ; soft computing ; training ; evolution of weights ; artificial intelligence ; deep neural networks ; convolutional neural network ; deep compression ; DNN ; ReLU ; floating-point numbers ; hardware acceleration ; energy dissipation ; FLOW-3D ; hydraulic jumps ; bed roughness ; sensitivity analysis ; feature selection ; evolutionary algorithms ; nature inspired algorithms ; meta-heuristic optimization ; computational intelligence ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
    Sprache: Englisch
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  • 60
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-11-17
    Beschreibung: This reprint is a collection of 31 original papers and four reviews, published from 2021 to 2022, focused on the application of a wide range of computational tools in medicinal chemistry projects: from molecular docking to artificial intelligence approaches. Applications of in silico tools are crucial in the early stages of drug design, such as planning more efficient and economic synthetic routes for chemical administration, screening of huge databases, as well as proposing hypotheses for probable mechanisms of action of drugs in macromolecular targets. Such endeavors are extremely complex and require the usage of modern and sophisticated approaches, such as artificial intelligence, data mining, computational molecular simulations through classical mechanics and quantum mechanics, molecular docking, chemoinformatics, applied mathematics, and biostatistics.
    Schlagwort(e): T-type calcium channel blocker ; homology modeling ; computer-aid drug design ; virtual drug screening ; L-type calcium channel ; mTOR kinase ; marine natural products ; ATP-competitive inhibitors ; structure-based pharmacophore modeling ; virtual screening ; molecular docking ; molecular dynamics simulations ; binding free energy ; in silico ADMET ; α-Glucosidase ; QSAR modeling ; ADMET profiling ; cervical cancer management ; computer-aided drug design ; E6 inhibitors ; in silico studies ; human papillomavirus ; manifold learning ; machine learning ; rdkit ; embeddings ; Tox21 ; principal component analysis ; autoencoder ; skin sensitization ; toxicity prediction ; in silico prediction ; random forest ; conformal prediction ; bioactivity descriptors ; SARS coronavirus ; SARS-CoV-2 main protease ; structure-based virtual screening ; molecular dynamic simulation ; hit identification ; Alzheimer’s disease ; multitarget ; natural-like compounds ; library of integrated network-based cellular signatures (LINCS) ; longevity ; gene regulating effects ; gene descriptors ; molecular fingerprints ; deep neural network ; drug repurposing ; Variola virus ; thymidylate kinase ; smallpox ; docking ; molecular dynamics ; molecular modeling ; permeability ; membrane disruption ; membrane proteins ; drugs ; antimicrobial peptides ; Ras ; RasGRF1 ; hydrogen-bond surrogate ; computational residue scanning ; MM-GBSA ; protein–protein interaction ; ERK signalling ; cocaine addiction ; intellectual disability (ID) ; autism spectrum disorder (ASD) ; gated recurrent unit ; recurrent neural network ; transfer learning ; caspase-6 ; inhibitor ; molecular design ; computational drug design ; deep learning ; multiscale ; polypharmacology ; Mycobacterium tuberculosis ; mycolic acid methyltransferases ; fragment-based ligand discovery ; binding energies ; molecular modelling ; heat shock protein ; HSP70 ; nucleotide-binding domain ; piperlongumine ; fluorescence spectroscopy ; circular dichroism ; molecular mechanics Poisson–Boltzmann surface area ; Parkinson’s disease ; catechol-O-methyltransferase ; inhibitors ; bioinformatics ; pharmacophore modeling ; cytotoxicity ; computational drug discovery ; chemical space ; parallelization ; high-performance computers and accelerators ; sulfonamides ; arylsulfonamide ; anticancer compounds ; telomerase inhibitors ; structure-based drug design ; computer drug design ; MolAr ; DNA intercalating agents ; SARS-CoV-2 ; main protease, Mpro ; docking benchmark ; non-steroidal anti-inflammatory drugs ; drug discovery ; lipoxygenase ; cyclooxygenase ; Hsp90 ; cancer ; QSAR ; pharmacophores ; in-silico drug design ; AlphaFold ; anti-CRISPR proteins ; prokaryotic defence mechanisms ; bacteriophages ; structural biology ; protein drug ; Merkel cell polyomavirus ; Merkel cell carcinomas ; drug design ; ADMET ; MD simulation ; antimicrobial peptide database ; antiviral peptides ; database filtering technology ; Ebola virus ; peptide design ; G-quadruplex DNA ; TERRA ; mass spectrometry ; biological assays ; mangrove natural products ; KRASG12C ; ligand-based pharmacophore modeling ; computational biology ; RVFV ; RdRp ; structural modeling ; GlyT1 ; schizophrenia ; DAT ; MD ; chagas ; leishmaniasis ; naphthoquinones ; antiprotozoal evaluation ; ADME ; COVID-19 ; NSP3 ; TCM ; MD simulations ; mutagenesis ; artificial intelligence ; biased signaling ; G protein-coupled receptor ; immunology ; flavonoids ; IDO1 ; free energy ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PN Chemistry
    Sprache: Englisch
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  • 61
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass customization); and from agent-based manufacturing (2000s) to cloud manufacturing (2010s) (both deploying the value stream complexity into the material and information flow, respectively). The next natural evolutionary step is to provide value by creating industrial cyber-physical assets with human-like intelligence. This will only be possible by further integrating strategic smart sensor technology into the manufacturing cyber-physical value creating processes in which industrial equipment is monitored and controlled for analyzing compression, temperature, moisture, vibrations, and performance. For instance, in the new wave of the ‘Industrial Internet of Things’ (IIoT), smart sensors will enable the development of new applications by interconnecting software, machines, and humans throughout the manufacturing process, thus enabling suppliers and manufacturers to rapidly respond to changing standards. This reprint of “Sense and Respond” aims to cover recent developments in the field of industrial applications, especially smart sensor technologies that increase the productivity, quality, reliability, and safety of industrial cyber-physical value-creating processes.
    Schlagwort(e): EEG sensors ; manufacturing systems ; problem-solving ; deep learning ; TDOA ; sensor networks ; hyperboloids ; node distribution ; genetic algorithms ; asynchronous ; Cramér–Rao lower bound ; heteroscedasticity ; soft sensors ; industrial optical quality inspection ; artificial vision ; long-term monitoring benefits ; indoor air quality ; low cost ; occupational safety and health ; industry 4.0 ; IOTA tangle ; Industry 4.0 ; IIoT ; geometric deep learning ; lean management ; cramer rao lower bound ; localization ; LPS ; multi-objective optimization ; sensor failure ; wireless sensor networks ; conceptual framework ; sensors ; approaches ; tools ; data ; application ; project engineering ; LCA ; SDG 9 ; SDG 11 ; 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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  • 62
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-01
    Beschreibung: The analysis of Big Data in biomedical as well as business and financial research has drawn much attention from researchers worldwide. This book provides a platform for the deep discussion of state-of-the-art statistical methods developed for the analysis of Big Data in these areas. Both applied and theoretical contributions are showcased.
    Schlagwort(e): high-dimensional ; nonlocal prior ; strong selection consistency ; estimation consistency ; generalized linear models ; high dimensional predictors ; model selection ; stepwise regression ; deep learning ; financial time series ; causal and dilated convolutional neural networks ; nuisance ; post-selection inference ; missingness mechanism ; regularization ; asymptotic theory ; unconventional likelihood ; high dimensional time-series ; segmentation ; mixture regression ; sparse PCA ; entropy-based robust EM ; information complexity criteria ; high dimension ; multicategory classification ; DWD ; sparse group lasso ; L2-consistency ; proximal algorithm ; abdominal aortic aneurysm ; emulation ; Medicare data ; ensembling ; high-dimensional data ; Lasso ; elastic net ; penalty methods ; prediction ; random subspaces ; ant colony system ; bayesian spatial mixture model ; inverse problem ; nonparamteric boostrap ; EEG/MEG data ; feature representation ; feature fusion ; trend analysis ; text mining ; 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
    Sprache: Englisch
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  • 63
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: This book includes 23 published papers on Special issues of "Image and Video Processing and Recognition Based on Artificial Intelligence" in the journal Sensors. The purpose of this Special Issue was to invite high-quality and state-of-the-art academic papers on challenging issues in the field of AI-based image and video processing and recognition.
    Schlagwort(e): emotion recognition ; brain computer interface ; bag of deep features ; continuous wavelet transform ; face image analysis ; deep learning ; face parsing ; facial attributes classification ; building extraction ; convolutional neural networks ; mask R-CNN ; high-resolution remote sensing image ; autoencoders ; semi-supervised learning ; computer vision ; pathology ; epidermis ; skin ; image processing ; generative models ; generative adversarial net ; depth map ; super-resolution ; guidance ; residual network ; channel interaction ; pose estimation ; body orientation ; multi-person ; multi-task ; surface defect detection ; active learning ; generative adversarial network ; presentation attack detection ; artificial image generation ; presentation attack face images ; ultrasound image ; malignant thyroid nodule ; artificial intelligence ; weighted binary cross-entropy loss ; infrared circumferential scanning system ; target recognition ; deep convolutional neural networks ; data augmentation ; transfer learning ; bounding box regression ; loss function ; medical image fusion ; convolutional neural network ; image pyramid ; multi-scale decomposition ; armature ; surface inspection ; action recognition ; social robotics ; common spatial patterns ; vehicle recognition ; multi resolution network ; optimization ; semantic segmentation ; global context ; local context ; fully convolutional networks ; image-to-image conversion ; image de-raining ; label to photos ; edges to photos ; generative adversarial network (GAN) ; remote sensing ; helicopter footage ; crowd counting ; multitask learning ; normalized cross-correlation ; Marr wavelets ; entropy and response ; graph matching ; RANSAC ; GC–LSTM model ; typhoon ; satellite image ; prediction system ; monocular depth estimation ; feature distillation ; joint attention ; finger-vein recognition ; camera position ; finger position ; lighting ; unobserved database ; heterogeneous database ; domain adaptation ; cycle-consistent adversarial networks ; SDUMLA-HMT-DB ; HKPolyU-DB ; biometrics ; face recognition ; single-sample face recognition ; binarized statistical image features ; K-nearest neighbors ; sparse coding ; fast approximation ; homotopy iterative hard thresholding ; object recognition ; character recognition ; orthogonal polynomials ; orthogonal moments ; Krawtchouk polynomials ; Tchebichef polynomials ; support vector machine ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 64
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot.
    Schlagwort(e): text mining ; big data ; analytics ; review ; self-organization ; computational philosophy ; brain ; synaptic learning ; adaptation ; functional plasticity ; activity-dependent resonance states ; circular causality ; somatosensory representation ; prehensile synergies ; robotics ; COVID-19 ; social media ; hashtag networks ; emotional profiling ; cognitive science ; network science ; sentiment analysis ; computational social science ; Twitter ; VADER scoring ; correlation ; semantic network analysis ; intellectual disability ; adolescents ; EEG ; emotional states ; working memory ; depression ; anxiety ; graph theory ; classification ; machine learning ; neural networks ; phonotactic probability ; neighborhood density ; sub-lexical representations ; lexical representations ; phonemes ; biphones ; cognitive network ; smart assistants ; knowledge generation ; intelligent systems ; web components ; deep learning ; web-based interaction ; cognitive network science ; text analysis ; natural language processing ; artificial intelligence ; emotional recall ; cognitive data ; AI ; pharmacological text corpus ; automatic relation extraction ; gender stereotypes ; story tropes ; movie plots ; network analysis ; word co-occurrence network ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
    Sprache: Englisch
    Format: application/octet-stream
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  • 65
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-28
    Beschreibung: The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet.
    Schlagwort(e): polymer optical fibers ; ammonia detection ; optical fiber coating ; aquaculture ; French Alps ; optical remote sensing ; multitemporal ; linear spectral unmixing ; NDVI ; drought ; Rana temporaria ; ecohydrology ; mountain temporary pools ; Lake Tana ; water hyacinth ; waterbody temperature ; turbidity ; lake level ; Planetscope ; remote sensing ; sensors ; ocean color ; sediment ; turbid water ; chlorophyll ; geostationary satellite ; aquaculture ponds ; extraction ; inland lake ; self-attention ; Ulva ; Sentinel-2 ; satellite ; algal bloom ; coral reefs ; Pacific lagoons ; HAB ; multi-source remote sensing ; MODIS ; Landsat ; sentinel ; Chaohu Lake ; ecological status class of lakes ; European Union Water Framework Directive (2000/60/EC) ; water quality parameters ; water level ; Sentinel-3 ; Cryosat-2 ; shallow lakes ; synergy ; altimetry data ; optical data ; CDOM absorbance ; spectroscopic indices ; DOC ; Arctic ; shelf seas ; estuarial and coastal areas ; drone applications ; surface water ; groundwater ; photogrammetry ; optical sensing ; thermal infrared ; deep learning ; convolutional neural network ; chlorophyll-a ; hydrodynamic model ; empirical models ; multiple regression ; Paldang Reservoir ; SAR ; Doppler Centroid Anomaly ; inland waters ; physical limnology ; hydrodynamics ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
    Sprache: Englisch
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  • 66
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal.
    Schlagwort(e): smart grid ; nontechnical losses ; electricity theft detection ; synthetic minority oversampling technique ; K-means cluster ; random forest ; smart grids ; smart energy system ; smart meter ; GDPR ; data privacy ; ethics ; multi-label learning ; Non-intrusive Load Monitoring ; appliance recognition ; fryze power theory ; V-I trajectory ; Convolutional Neural Network ; distance similarity matrix ; activation current ; electric vehicle ; synthetic data ; exponential distribution ; Poisson distribution ; Gaussian mixture models ; mathematical modeling ; machine learning ; simulation ; Non-Intrusive Load Monitoring (NILM) ; NILM datasets ; power signature ; electric load simulation ; data-driven approaches ; smart meters ; text convolutional neural networks (TextCNN) ; time-series classification ; data annotation ; non-intrusive load monitoring ; semi-automatic labeling ; appliance load signatures ; ambient influences ; device classification accuracy ; NILM ; signature ; load disaggregation ; transients ; pulse generator ; smart metering ; smart power grids ; power consumption data ; energy data processing ; user-centric applications of energy data ; convolutional neural network ; energy consumption ; energy data analytics ; energy disaggregation ; real-time ; smart meter data ; transient load signature ; attention mechanism ; deep neural network ; electrical energy ; load scheduling ; satisfaction ; Shapley Value ; solar photovoltaics ; review ; deep learning ; deep neural networks ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Sprache: Englisch
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  • 67
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: Increasing energy efficiency; reducing energy demand, greenhouse gas emissions, and the use of waste; and integrating renewable and recycled heat from low-temperature sources are significant challenges today and are key parts of 4th Generation District Heating (4GDH) concept. On the other hand, currently about one billion people around the world are suffering from water scarcity, and another three billion are approaching this situation. Only 2.5% of all water on the planet is freshwater, of which around 70% is not available and only 0.4% constitutes the most valuable portion of freshwater. Adsorption cooling technology is one of the most effective ways of addressing both these issues. This technology cools and produces potable water from the renewable and wasted heat of the near ambient temperature, including from sewage water, solar heat, and underground resources. This Special Issue Reprint Book provides the detailed information concerning the above-mentioned issues.
    Schlagwort(e): adsorption chiller ; coefficient of performance ; desalination ; energy efficiency ; low-temperature heat ; silica gel ; specific cooling power ; waste heat recovery ; sorption processes ; deep learning ; neural networks ; Long Short-Term Memory (LSTM) ; additives ; sorption capacity ; sorption process time ; kinetics sorption ; adsorption ; exergy ; dead state ; adsorption cooling ; reheat cycle, mass recovery ; chiller ; adsorptive water harvesting from the atmosphere ; metal–organic frameworks ; MIL-160 ; water vapor adsorption ; specific water productivity ; specific energy consumption ; zeolite ; SAPO-34 ; mass recovery ; variable mode ; adsorption working pairs ; coated beds ; comparative analysis ; natural refrigerants ; preheating ; steam ; copper ; cycle time ; CFD ; metal organic silica ; nanocomposites ; sorption ; thermal diffusivity ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering
    Sprache: Englisch
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  • 68
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Since the 1990s, ultrasound (US) has played a major role in the assessment of thyroid nodules and their risk of malignancy. Over the last decade, the most eminent international societies have published US-based systems for the risk stratification of thyroid lesions, namely, Thyroid Imaging Reporting And Data Systems (TIRADSs). The introduction of TIRADSs into clinical practice has significantly increased the diagnostic power of US to a level approaching that of fine-needle aspiration cytology (FNAC). At present, we are probably approaching a new era in which US could be the primary tool to diagnose thyroid cancer. However, before using US in this new dominant role, we need further proof. This Special Issue, which includes reviews and original articles, aims to pave the way for the future in the field of thyroid US. Highly experienced thyroidologists focused on US are asked to contribute to achieve this goal.
    Schlagwort(e): n/a ; thyroid ; ultrasonography ; follicular neoplasm ; follicular lesion of unknown significance ; follicular thyroid cancer ; papillary thyroid carcinoma ; neoplasm metastasis ; biopsy ; fine-needle ; thyroglobulin ; US-guided minimally invasive techniques ; radiofrequency ablation ; RFA ; benign thyroid nodules ; thyroid cancer ; DTC recurrences ; PTMC ; long term ; follow-up ; regrowth ; classification system ; ultrasound classification system ; TIRAD ; nodule ; risk stratification ; TI-RADS ; fine-needle aspiration ; cancer ; ultrasound ; scintigraphy ; non-autonomously functioning ; thyroid imaging reporting and data systems (TIRADS) ; risk of malignancy (ROM) ; thyroid nodules ; paediatrics ; radiotherapy ; risk assessment ; DTC ; thyroid neoplasm ; medical imaging ; artificial intelligence ; machine learning ; deep learning ; radiomics ; prediction ; diagnosis ; Thyroid Imaging Reporting and Data Systems (TIRADS) ; pediatric thyroid nodules ; neck ultrasound ; contrast-enhanced ultrasound (CEUS) ; papillary thyroid cancer ; TIRADS ; thyroid nodule ; fine-needle aspiration biopsy ; elastosonography ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MJ Clinical & internal medicine
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  • 69
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: This Special Issue highlights the most recent research being carried out in the NLP field to discuss relative open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding interactively or autonomously from data in cognitive and neural systems, as well as on their potential or real applications in different domains.
    Schlagwort(e): tourism big data ; text mining ; NLP ; deep learning ; clinical named entity recognition ; information extraction ; multitask model ; long short-term memory ; conditional random field ; relation extraction ; entity recognition ; long short-term memory network ; multi-turn chatbot ; dialogue context encoding ; WGAN-based response generation ; BERT word embedding ; text summary ; reinforce learning ; FAQ classification ; encoder-decoder neural network ; multi-level word embeddings ; BERT ; bidirectional RNN ; cloze test ; Korean dataset ; machine comprehension ; neural language model ; sentence completion ; primary healthcare ; chief complaint ; virtual medical assistant ; spoken natural language ; disease diagnosis ; medical specialist ; protein–protein interactions ; deep learning (DL) ; convolutional neural networks (CNN) ; bidirectional long short-term memory (bidirectional LSTM) ; dialogue management ; user simulation ; reward shaping ; conversation knowledge ; multi-agent reinforcement learning ; language modeling ; classification ; error probability ; error assessment ; logic error ; neural network ; LSTM ; attention mechanism ; programming education ; neural architecture search ; word ordering ; Korean syntax ; adversarial attack ; adversarial example ; sentiment classification ; dual pointer network ; context-to-entity attention ; text classification ; rule-based ; word embedding ; Doc2vec ; paraphrase identification ; encodings ; R-GCNs ; contextual features ; sentence retrieval ; TF−ISF ; BM25 ; partial match ; sequence similarity ; word to vector ; word embeddings ; antonymy detection ; polarity ; text normalization ; natural language processing ; deep neural networks ; causal encoder ; question classification ; multilingual ; convolutional neural networks ; Natural Language Processing (NLP) ; transfer learning ; open information extraction ; recurrent neural networks ; bilingual translation ; speech-to-text ; LaTeX decompilation ; word representation learning ; word2vec ; sememes ; structural information ; sentiment analysis ; zero-shot learning ; news analysis ; cross-lingual classification ; multilingual transformers ; knowledge base ; commonsense ; sememe prediction ; attention model ; ontologies ; fixing ontologies ; quick fix ; quality metrics ; online social networks ; rumor detection ; Cantonese ; XGA model ; delayed combination ; CNN dictionary ; named entity recognition ; deep learning NER ; bidirectional LSTM CRF ; CoNLL ; OntoNotes ; toxic comments ; neural networks ; n/a ; 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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  • 70
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.
    Schlagwort(e): groundwater potential ; specific capacity ; machine learning ; boosted tree ; ensemble models ; prototype selection ; river pollution ; supervised classification ; WSN ; probabilistic method ; Monte Carlo simulation ; physical slope model ; Mt. Umyeon landslides ; Seoul ; synthetic aperture radar ; land subsidence ; GIS ; time-series ; Jakarta ; land subsidence susceptibility mapping ; time-series InSAR ; StaMPS processing ; seismic vulnerability map ; DPM method ; Sentinel-1 ; seismic literacy ; neural networks ; urban vegetation ; urban open spaces ; Monterrey Metropolitan Area ; sustainable development ; deep learning ; transfer learning ; artificial intelligence ; remote sensing ; earth observation ; DInSAR ; change detection ; space data science ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
    Sprache: Englisch
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  • 71
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others.
    Schlagwort(e): sleep stage scoring ; neural network-based refinement ; residual attention ; T-end annotation ; signal quality index ; tSQI ; optimal shrinkage ; emotion ; EEG ; DEAP ; CNN ; surgery image ; disgust ; autonomic nervous system ; electrocardiogram ; galvanic skin response ; olfactory training ; psychophysics ; smell ; wearable sensors ; wine sensory analysis ; accuracy ; convolution neural network (CNN) ; classifiers ; electrocardiography ; k-fold validation ; myocardial infarction ; sensitivity ; sleep staging ; electroencephalography (EEG) ; brain functional connectivity ; frequency band fusion ; phase-locked value (PLV) ; wearable device ; emotional state ; mental workload ; stress ; heart rate ; eye blinks rate ; skin conductance level ; emotion recognition ; electroencephalogram (EEG) ; photoplethysmography (PPG) ; machine learning ; feature extraction ; feature selection ; deep learning ; non-stationarity ; individual differences ; inter-subject variability ; covariate shift ; cross-participant ; inter-participant ; drowsiness detection ; EEG features ; drowsiness classification ; fatigue detection ; residual network ; Mish ; spatial transformer networks ; non-local attention mechanism ; Alzheimer’s disease ; fall detection ; event-centered data segmentation ; accelerometer ; window duration ; 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
    Sprache: Englisch
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  • 72
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: The rapid growth of the world population has resulted in an exponential expansion of both urban and agricultural areas. Identifying and managing such earthly changes in an automatic way poses a worth-addressing challenge, in which remote sensing technology can have a fundamental role to answer—at least partially—such demands. The recent advent of cutting-edge processing facilities has fostered the adoption of deep learning architectures owing to their generalization capabilities. In this respect, it seems evident that the pace of deep learning in the remote sensing domain remains somewhat lagging behind that of its computer vision counterpart. This is due to the scarce availability of ground truth information in comparison with other computer vision domains. In this book, we aim at advancing the state of the art in linking deep learning methodologies with remote sensing image processing by collecting 20 contributions from different worldwide scientists and laboratories. The book presents a wide range of methodological advancements in the deep learning field that come with different applications in the remote sensing landscape such as wildfire and postdisaster damage detection, urban forest mapping, vine disease and pavement marking detection, desert road mapping, road and building outline extraction, vehicle and vessel detection, water identification, and text-to-image matching.
    Schlagwort(e): synthetic aperture radar ; despeckling ; multi-scale ; LSTM ; sub-pixel ; high-resolution remote sensing imagery ; road extraction ; machine learning ; DenseUNet ; scene classification ; lifting scheme ; convolution ; CNN ; image classification ; deep features ; hand-crafted features ; Sinkhorn loss ; remote sensing ; text image matching ; triplet networks ; EfficientNets ; LSTM network ; convolutional neural network ; water identification ; water index ; semantic segmentation ; high-resolution remote sensing image ; pixel-wise classification ; result correction ; conditional random field (CRF) ; satellite ; object detection ; neural networks ; single-shot ; deep learning ; global convolution network ; feature fusion ; depthwise atrous convolution ; high-resolution representations ; ISPRS vaihingen ; Landsat-8 ; faster region-based convolutional neural network (FRCNN) ; single-shot multibox detector (SSD) ; super-resolution ; remote sensing imagery ; edge enhancement ; satellites ; open-set domain adaptation ; adversarial learning ; min-max entropy ; pareto ranking ; SAR ; Sentinel–1 ; Open Street Map ; U–Net ; desert ; road ; infrastructure ; mapping ; monitoring ; deep convolutional networks ; outline extraction ; misalignments ; nearest feature selector ; hyperspectral image classification ; two stream residual network ; Batch Normalization ; plant disease detection ; precision agriculture ; UAV multispectral images ; orthophotos registration ; 3D information ; orthophotos segmentation ; wildfire detection ; convolutional neural networks ; densenet ; generative adversarial networks ; CycleGAN ; data augmentation ; pavement markings ; visibility ; framework ; urban forests ; OUDN algorithm ; object-based ; high spatial resolution remote sensing ; Generative Adversarial Networks ; post-disaster ; building damage assessment ; anomaly detection ; Unmanned Aerial Vehicles (UAV) ; xBD ; feature engineering ; orthophoto ; unsupervised segmentation ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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  • 73
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue.
    Schlagwort(e): pancreas ; segmentation ; computed tomography ; deep learning ; data augmentation ; neoplasm metastasis ; ovarian neoplasms ; radiation exposure ; tomography ; x-ray computed ; prostate carcinoma ; microscopic ; convolutional neural network ; machine learning ; handcrafted ; oral carcinoma ; medical image segmentation ; colon cancer ; colon polyps ; OCT ; optical biopsy ; animal rat models ; CADx ; airway volume analysis ; artificial intelligence ; coronary artery disease ; SPECT MPI scans ; convolutional neural networks ; transfer learning ; classification models ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 74
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine.
    Schlagwort(e): electrocardiogram ; deep metric learning ; k-nearest neighbors classifier ; premature ventricular contraction ; dimensionality reduction ; classifications ; Laplacian eigenmaps ; locality preserving projections ; compressed sensing ; convolutional neural network ; EEG ; epileptic seizure detection ; RISC-V ; ultra-low-power ; sepsis ; atrial fibrillation ; prediction ; heart rate variability ; feature extraction ; random forest ; annotations ; myoelectric prosthesis ; sEMG ; grasp phases analysis ; grasp classification ; machine learning ; electronic nose ; liver dysfunction ; cirrhosis ; semiconductor metal oxide gas sensor ; vagus nerve ; intraneural ; decoding ; intrafascicular ; recording ; carbon nanotube ; artificial intelligence ; lens-free shadow imaging technique ; cell-line analysis ; cell signal enhancement ; deep learning ; ECG signal ; reconstruction dictionaries ; projection matrices ; signal classifications ; osteopenia ; sarcopenia ; XAI ; SHAP ; IMU ; gait analysis ; sensors ; convolutional neural networks ; Parkinson’s disease ; biomedical monitoring ; accelerometer ; pressure sensor ; disease management ; electromyography ; correlation ; high blood pressure ; hypertension ; photoplethysmography ; electrocardiography ; calibration ; classification models ; COVID-19 ; ECG trace image ; transfer learning ; Convolutional Neural Networks (CNN) ; feature selection ; sympathetic activity (SNA) ; skin sympathetic nerve activity (SKNA) ; electrodes ; electrocardiogram (ECG) ; cardiac time interval ; dynamic time warping ; fiducial point detection ; heart failure ; seismocardiography ; wearable electroencephalography ; motor imagery ; motor execution ; beta rebound ; brain–machine interface ; EEG classification ; 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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  • 75
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: This book focuses on fundamental and applied research on geo-information technology, notably optical and radar remote sensing and algorithm improvements, and their applications in environmental monitoring. This Special Issue presents ten high-quality research papers covering up-to-date research in land cover change and desertification analyses, geo-disaster risk and damage evaluation, mining area restoration assessments, the improvement and development of algorithms, and coastal environmental monitoring and object targeting. The purpose of this Special Issue is to promote exchanges, communications and share the research outcomes of scientists worldwide and to bridge the gap between scientific research and its applications for advancing and improving society.
    Schlagwort(e): earthquake ; damaged groups of buildings ; classification ; remote sensing images ; Convolution Neural Network (CNN) ; block vector data ; shoreline change ; landsat ; planet scope ; coastline ; morphological changes ; building extraction ; improved anchor-free instance segmentation ; high-resolution remote sensing images ; deep learning ; land use/land cover (LULC) ; GF-6 WFV ; object-oriented ; change detection ; double constraints ; REE mines ; mining and restoration assessment indicators (MRAIs) ; damage ; time trajectory ; effectiveness of management ; aeolian process ; desertification ; multi-sensor fusion ; interferometric SAR ; time-series analysis ; mussel farming ; high-resolution image ; transitional water management ; environmental pollution ; open source software ; synthetic aperture radar (SAR) ; target ; sea surface ; multiple scattering ; geo-hazard mapping ; Gaofen-1 satellite ; land cover ; environmental factors ; susceptibility ; post-classification differencing ; generalized difference vegetation index (GDVI) ; multiple linear regression ; logistic regression ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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  • 76
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: Energy systems are transiting from conventional energy systems to modernized and smart energy systems. This Special Issue covers new advances in the emerging technologies for modern energy systems from both technical and management perspectives. In modern energy systems, an integrated and systematic view of different energy systems, from local energy systems and islands to national and multi-national energy hubs, is important. From the customer perspective, a modern energy system is required to have more intelligent appliances and smart customer services. In addition, customers require the provision of more useful information and control options. Another challenge for the energy systems of the future is the increased penetration of renewable energy sources. Hence, new operation and planning tools are required for hosting renewable energy sources as much as possible.
    Schlagwort(e): hybrid systems ; photovoltaic ; wind energy ; energy economics ; RES investments ; Zimbabwe ; Africa and energy security ; electricity price forecasting (EPF) ; wind power forecasting (WPF) ; spot market ; balancing market ; ARMAX ; NARX-ANN ; 100% renewable power system ; secondary voltage control ; tertiary voltage control ; grid code ; wind farms ; photovoltaic parks ; energy transition ; renewable energy sources ; island power systems ; hybrid power plants ; wind turbines ; battery energy storage systems ; marine microgrid ; tidal generation system ; black widow optimization ; supplementary control ; fractional integrator ; non-linear fractional integrator ; 100% renewable power generation ; nexus ; food ; energy ; water ; greenhouse gas emission ; microgrid ; ancillary services ; energy storage ; power management ; solar hot waters ; thermosyphon ; thermal performance ; Morocco ; economic outcomes ; CO2 environmental assessment ; solar system ; domestic hot water production ; solar water heaters ; individual and collective solar water heater systems ; dynamic simulation ; TRNbuild ; TRNSYSstudio ; energy management ; residential and commercial loads ; short-term load forecasting ; deep learning ; bidirectional long short-term memory (Bi-LSTM) ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Sprache: Englisch
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  • 77
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-07-06
    Beschreibung: The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.
    Schlagwort(e): large margin nearest neighbor regression ; distance metrics ; prototypes ; evolutionary algorithm ; approximate differential optimization ; multiple point hill climbing ; adaptive sampling ; free radical polymerization ; autonomous driving ; object tracking ; trajectory prediction ; deep neural networks ; stochastic methods ; applied machine learning ; classification and regression ; data mining ; ensemble model ; engineering informatics ; gender-based violence in Mexico ; twitter messages ; class imbalance ; k-nearest neighbor ; instance-based learning ; graph neural network ; deep learning ; hyperparameters ; machine learning ; optimization ; inference ; metaheuristics ; animal-inspired ; exploration ; exploitation ; hot rolled strip steel ; surface defects ; defect classification ; knockout tournament ; dynamic programming algorithm ; computational complexity ; combinatorics ; intelligent transport systems ; traffic control ; spatial-temporal variable speed limit ; multi-agent systems ; reinforcement learning ; distributed W-learning ; urban motorways ; multi-agent framework ; .NET framework ; simulations ; agent-based systems ; agent algorithms ; software design ; multisensory fingerprint ; interoperability ; DeepFKTNet ; classification ; generative adversarial networks ; image classification ; transfer learning ; plastic bottle ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
    Sprache: Englisch
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  • 78
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue "Hyperspectral Imaging and Applications" is to publish new ideas and technologies to facilitate the utility of hyperspectral imaging in data exploitation and to further explore its potential in different applications. This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories with the number of papers published in every category included in its open parenthesis. 1. Data Unmixing (2 papers)2. Spectral variability (2 papers)3. Target Detection (3 papers)4. Hyperspectral Image Classification (6 papers)5. Band Selection (2 papers)6. Data Fusion (2 papers)7. Applications (8 papers) Under every category each paper is briefly summarized by a short description so that readers can quickly grab its content to find what they are interested in.
    Schlagwort(e): biodiversity ; peatland ; vegetation type ; classification ; hyperspectral ; in situ measurements ; hyperspectral image (HSI) ; multiscale union regions adaptive sparse representation (MURASR) ; multiscale spatial information ; imaging spectroscopy ; airborne laser scanning ; minimum noise fraction ; class imbalance ; Africa ; agroforestry ; tree species ; hyperspectral unmixing ; endmember extraction ; band selection ; spectral variability ; prototype space ; ensemble learning ; rotation forest ; semi-supervised local discriminant analysis ; optical spectral region ; thermal infrared spectral region ; mineral mapping ; data integration ; HyMap ; AHS ; raw material ; remote sensing ; nonnegative matrix factorization ; data-guided constraints ; sparseness ; evenness ; hashing ensemble ; hierarchical feature ; hyperspectral classification ; band expansion process (BEP) ; constrained energy minimization (CEM) ; correlation band expansion process (CBEP) ; iterative CEM (ICEM) ; nonlinear band expansion (NBE) ; Otsu’s method ; sparse unmixing ; local abundance ; nuclear norm ; hyperspectral detection ; target detection ; sprout detection ; constrained energy minimization ; iterative algorithm ; adaptive window ; hyperspectral imagery ; recursive anomaly detection ; local summation RX detector (LS-RXD) ; sliding window ; band selection (BS) ; band subset selection (BSS) ; hyperspectral image classification ; linearly constrained minimum variance (LCMV) ; successive LCMV-BSS (SC LCMV-BSS) ; sequential LCMV-BSS (SQ LCMV-BSS) ; vicarious calibration ; reflectance-based method ; irradiance-based method ; Dunhuang site ; 90° yaw imaging ; terrestrial hyperspectral imaging ; vineyard ; water stress ; machine learning ; tree-based ensemble ; progressive sample processing (PSP) ; real-time processing ; image fusion ; hyperspectral image ; panchromatic image ; structure tensor ; image enhancement ; weighted fusion ; spectral mixture analysis ; fire severity ; AVIRIS ; deep belief networks ; deep learning ; texture feature enhancement ; band grouping ; hyperspectral compression ; lossy compression ; on-board compression ; orthogonal projections ; Gram–Schmidt orthogonalization ; parallel processing ; anomaly detection ; sparse coding ; KSVD ; hyperspectral images (HSIs) ; SVM ; composite kernel ; algebraic multigrid methods ; hyperspectral pansharpening ; panchromatic ; intrinsic image decomposition ; weighted least squares filter ; spectral-spatial classification ; label propagation ; superpixel ; semi-supervised learning ; rolling guidance filtering (RGF) ; graph ; deep pipelined background statistics ; high-level synthesis ; data fusion ; data unmixing ; hyperspectral imaging ; 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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  • 79
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: Fluid–structure interactions (FSIs) play a crucial role in the design, construction, service and maintenance of many engineering applications, e.g., aircraft, towers, pipes, offshore platforms and long-span bridges. The old Tacoma Narrows Bridge (1940) is probably one of the most infamous examples of serious accidents due to the action of FSIs. Aircraft wings and wind-turbine blades can be broken because of FSI-induced oscillations. To alleviate or eliminate these unfavorable effects, FSIs must be dealt with in ocean, coastal, offshore and marine engineering to design safe and sustainable engineering structures. In addition, the wind effects on plants and the resultant wind-induced motions are examples of FSIs in nature. To meet the objectives of progress and innovation in FSIs in various scenarios of engineering applications and control schemes, this book includes 15 research studies and collects the most recent and cutting-edge developments on these relevant issues. The topics cover different areas associated with FSIs, including wind loads, flow control, energy harvesting, buffeting and flutter, complex flow characteristics, train–bridge interactions and the application of neural networks in related fields. In summary, these complementary contributions in this publication provide a volume of recent knowledge in the growing field of FSIs.
    Schlagwort(e): aerodynamic forces ; pressure distribution ; turbulence intensity ; twin-box girder ; trailing-edge reattachment ; trailing edge ; trailing-edge-changeable streamlined section mode ; limit cycle flutter ; hard flutter ; flutter stability ; wind engineering ; wind tunnel test ; wind-train-bridge system ; flow visualization ; flapping fringe ; CFD simulation ; vortex attenuation ; aerodynamics enhancement ; unsteady aerodynamic force ; single box girder ; Strouhal number ; linear stability analysis ; high-speed train ; enclosed housing for sound emission alleviation ; pressure wave ; unsteady aerodynamic pressure ; load patterns ; wake control ; drag reduction ; MSBC ; square cylinder ; numerical simulation ; wind characteristics ; wind tunnel testing ; complex terrain ; model truncation ; transition section ; deep learning ; prediction ; aerostatic performance ; shape ; convolutional neural networks ; long-span bridge ; buffeting response ; sectional model ; aerodynamic admittance ; integrated transfer function ; flow control ; traveling wave wall ; circular cylinder ; CFD ; wind turbines ; aerodynamic characteristics ; vortex shedding ; time domain method ; frequency domain method ; background and resonance coupled components ; wind induced dynamic responses ; equivalent static wind load ; aerodynamic shape optimization ; surrogate model ; wind energy harvester ; galloping ; passive jet control ; tower wake characteristics ; cobra probe ; 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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  • 80
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.
    Schlagwort(e): online signature verification ; shape contexts ; function features ; SC-DTW ; symbolic representation ; two-stage method ; finger features ; multimodal recognition ; local coding ; Gabor filter ; LGS ; human identification ; biomarker ; ECG ; machine learning ; Physionet ; Lviv Biometric Dataset ; biometry ; identification ; bloodstream ; image recognition ; multi-biometrics ; bit planes ; block ; mutual information ; cross-device ; dorsal hand vein recognition ; person re-identification ; superpixel ; temporally aligned pooling ; walking cycle ; automatic recognition ; face ; voice ; body motion ; autism spectrum disorder (ASD) ; assessment ; intervention ; curve similarity ; curve similarity model ; curve similarity transformation ; similarity distance ; segmentation matching ; evolutionary computation ; finger vein recognition ; hand vein recognition ; contactless acquisition device ; public vascular pattern dataset ; biometric recognition performance evaluation ; face verification ; optical correlation ; Hausdorff distance ; image classification ; face detection ; depth map ensemble ; filtering ; geometric deep learning ; ear detection ; structured prediction ; semantic segmentation ; rotation equivariance ; Gaussian mixture model ; superpixels ; face recognition systems ; person identification ; biometric systems ; survey ; automatic signature verification ; touch-screen sensor ; data quality ; enrollment phase ; performance assessment ; augmented signature ; security enhancement ; mobile conditions ; biometric recognition ; visible light iris images ; image quality assessment ; image covariates ; quality filtering ; vascular biometric recognition ; wrist vein recognition ; contactless dataset ; pattern recognition ; infrared camera ; non-contact devices ; Scale-Invariant Feature Transform (SIFT®) ; Speeded Up Robust Features (SURF®) ; Oriented FAST and Rotated BRIEF (ORB) ; fingerprint ; presentation attack detection ; deep learning ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 81
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-12-06
    Beschreibung: Recent advances in artificial intelligence have the potential to further develop current big data research. The Special Issue on ‘Intelligent Computing for Big Data’ highlighted a number of recent studies related to the use of intelligent computing techniques in the processing of big data for text mining, autism diagnosis, behaviour recognition, and blockchain-based storage.
    Schlagwort(e): multimodal data ; behavior recognition ; dog detection ; fusion model ; deep learning ; older people ; long-term care ; artificial intelligence ; blockchain technology ; decentralized architecture ; autism spectrum disorder (ASD) ; big data ; bioinformatics ; machine learning ; classification ; bio-inspired algorithms ; Grey Wolf Optimization (GWO) ; Support Vector Machine (SVM) ; convolution neural network ; spatio-temporal document ; document classification ; big text data ; proxy re-encryption ; blockchain ; storage ; proof-of-replication ; n/a ; 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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  • 82
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: Biomedical image processing is an interdisciplinary field involving a variety of disciplines, e.g., electronics, computer science, physics, mathematics, physiology, and medicine. Several imaging techniques have been developed, providing many approaches to the study of the human body. Biomedical image processing is finding an increasing number of important applications in, for example, the study of the internal structure or function of an organ and the diagnosis or treatment of a disease. If associated with classification methods, it can support the development of computer-aided diagnosis (CAD) systems, which could help medical doctors in refining their clinical picture.
    Schlagwort(e): MR brain segmentation ; fuzzy clustering ; object extraction ; silhouette analysis ; DICOM processing ; 3D modeling ; semantic segmentation ; convolutional neural networks ; kidney biopsy ; kidney transplantation ; glomerulus detection ; glomerulosclerosis ; pattern recognition ; hemoglobin ; anemia ; human tissues ; conjunctiva ; non-invasive medical device ; training size ; deep learning ; convolutional neural network ; U-Net ; segmentation ; artificial intelligence ; digital pathology ; kidney fibrosis ; blood vessel segmentation ; inferior vena cava ; ultrasound imaging ; binary tree model ; pulsatility ; fluid volume assessment ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 83
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: Our Special Issue we publish at a turning point, which we have not dealt with since World War II. The interconnected long-term global shocks such as the coronavirus pandemic, the war in Ukraine, and catastrophic climate change have imposed significant humanitary, socio-economic, political, and environmental restrictions on the globalization process and all aspects of economic and social life including the existence of individual people. The planet is trapped—the current situation seems to be the prelude to an apocalypse whose long-term effects we will have for decades. Therefore, it urgently requires a concept of the planet's survival to be built—only on this basis can the conditions for its development be created. The Special Issue gives evidence of the state of econophysics before the current situation. Therefore, it can provide excellent econophysics or an inter-and cross-disciplinary starting point of a rational approach to a new era.
    Schlagwort(e): energy ; economic growth ; output elasticities ; entropy production ; emissions ; optimization ; speculative attacks ; currency crisis ; neural networks ; deep learning ; Quantum-Inspired Neural Network ; traveling salesman problem ; simulated annealing technique ; kinetic exchange model ; Gini index ; Kolkata index ; minority game ; Kolkata Paise Restaurant problem ; time series analysis ; cross-correlations ; power law classification scheme ; network analysis ; globalisation ; entropy ; portfolio optimization ; regularization ; renormalization ; econophysics ; highway freight transportation ; radiation model ; transportation network ; network diversity ; power law ; economic development ; decision-making ; bounded rationality ; complexity economics ; information-theory ; maximum entropy principle ; quantal response statistical equilibrium ; correlation coefficient ; detrended cross-correlation analysis ; COVID-19 ; mobility indices ; random geometry ; risk measurement ; disordered systems ; replica theory ; return distributions ; power-law tails ; stretched exponentials ; q-Gaussians ; financial markets ; financial complexity ; collective intelligence ; emergent property ; stock correlation ; lexical evolution of econophysics ; text as data ; correspondence analysis ; long-range memory ; 1/f noise ; absolute value estimator ; anomalous diffusion ; ARFIMA ; first-passage times ; fractional Lèvy stable motion ; Higuchi’s method ; mean squared displacement ; multiplicative point process ; correlation filtering ; minimal spanning tree ; planar maximally filtered graph ; topological data analysis ; SGX ; TAIEX ; complex systems ; ecological economics ; urban–regional economics ; income distribution ; financial market dynamics ; income tax ; tax deduction ; income redistribution ; government transfer ; government dependency ; poverty line ; basic income guarantee ; effective tax rate ; balanced budget ; elastic tax ; Cantor set ; fractals ; homeomorphism ; detrended fluctuation analysis ; Hurst exponent ; continuous time random walk ; intertrade times ; volatility clustering ; local transfer entropy ; long-short-term-memory ; Bitcoin ; cryptocurrencies ; multiscale analysis ; detrended cross-correlations ; covariance matrices ; copulas ; high-frequency trading ; market stability ; agent-based models ; structural entropy ; Economic Freedom of the World index ; Index of Economic Freedom ; rank-size law technique ; power law behaviour ; exponential behaviour ; multiscale partition function ; multifractal analysis ; company market ; export readiness ; internationalization ; options pricing ; mortality ; companies ; start-up ; FTSE100 ; Gompertz ; MinMax ; survival probability distribution ; high-frequency trader ; multivariate Hawkes process ; forex market ; wealth distribution ; kinetic models ; wealth inequalities ; compartmental epidemic modelling ; vaccination campaign ; flash crash ; systemic risk ; financial networks ; high frequency trading ; market microstructure ; phase transition ; criticality ; dynamics of complex networks ; cascading failure ; network science ; economic complexity ; relatedness ; products and services ; planar graph ; partial correlation ; discounting ; bond pricing ; real interest rates ; calendar anomalies ; day-of-the-week effect ; market indices ; multifractal detrended fluctuation analysis ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
    Sprache: Englisch
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  • 84
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.
    Schlagwort(e): interpretable/explainable machine learning ; image classification ; image processing ; machine learning models ; white box ; black box ; cancer prediction ; deep learning ; multimodal learning ; convolutional neural networks ; autism ; fMRI ; texture analysis ; melanoma ; glcm matrix ; machine learning ; classifiers ; explainability ; explainable AI ; XAI ; medical imaging ; diagnosis ; ARMD ; change detection ; unsupervised learning ; microwave breast imaging ; image reconstruction ; tumor detection ; digital pathology ; whole slide image processing ; multiple instance learning ; deep learning classification ; HER2 ; medical images ; transfer learning ; optimizers ; neo-adjuvant treatment ; tumour cellularity ; cancer ; breast cancer ; diagnostics ; imaging ; computation ; artificial intelligence ; 3D segmentation ; active surface ; discriminant analysis ; PET imaging ; medical image analysis ; brain tumor ; cervical cancer ; colon cancer ; lung cancer ; computer vision ; musculoskeletal images ; lung disease detection ; taxonomy ; convolutional neural network ; CycleGAN ; data augmentation ; dermoscopic images ; domain transfer ; macroscopic images ; skin lesion segmentation ; infection detection ; COVID-19 ; X-ray images ; bayesian inference ; shifted-scaled dirichlet distribution ; MCMC ; gibbs sampling ; object detection ; surgical tools ; open surgery ; egocentric camera ; computers in medicine ; segmentation ; MRI ; ECG signal detection ; portable monitoring devices ; 1D-convolutional neural network ; medical image segmentation ; domain adaptation ; meta-learning ; U-Net ; computed tomography (CT) ; magnetic resonance imaging (MRI) ; low-dose ; sparse-angle ; quantitative comparison ; n/a
    Sprache: Englisch
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  • 85
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems.
    Schlagwort(e): gait recognition ; biometrics ; regularized discriminant analysis ; particle swarm optimization ; grey wolf optimization ; whale optimization algorithm ; FMCW ; vital sign ; XGBoost ; MFCC ; COVID-19 ; 3D human pose estimation ; deep learning ; generalization ; optical sensing principle ; modular sensing unit ; plantar pressure measurement ; gait parameters ; 3D human mesh reconstruction ; deep neural network ; motion capture ; neural networks ; reconstruction ; gap filling ; FFNN ; LSTM ; BILSTM ; GRU ; pose estimation ; movement tracking ; computer vision ; artificial intelligence ; markerless motion capture ; assessment ; kinematics ; development ; machine learning ; human action recognition ; features fusion ; features selection ; recognition ; fall risk detection ; balance ; Berg Balance Scale ; human tracking ; elderly ; telemedicine ; diagnosis ; precedence indicator ; knowledge measure ; fuzzy inference ; rule induction ; posture detection ; aggregation function ; markerless ; human motion analysis ; gait analysis ; data augmentation ; skeletal data ; time series classification ; EMG ; pattern recognition ; robot ; cyber-physical systems ; RGB-D sensors ; human motion modelling ; F-Formation ; Kinect v2 ; Azure Kinect ; Zed 2i ; socially occupied space ; facial expression recognition ; facial landmarks ; action units ; convolutional neural networks ; graph convolutional networks ; artifact classification ; artifact detection ; anomaly detection ; 3D multi-person pose estimation ; absolute poses ; camera-centric coordinates ; deep-learning ; 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
    Sprache: Englisch
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  • 86
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews.
    Schlagwort(e): Machine vision ; image analysis ; item counting device ; electro-deposition industry ; digital intraoral radiography ; image preprocessing ; periapical lesions ; texture analysis ; prostate cancer ; histopathology ; microscopic ; tissue image ; segmentation ; morphological ; quantitative ; classification ; SVM ; image resizing ; local Tchebichef moments (LTM) ; scaling ; scale-and-stretch ; seam carving ; faster R-CNN ; cutting pieces ; multi-period pattern ; skew angle ; period length ; colored texture pattern classification ; global–local texture classification ; color–texture features ; color–texture feature extraction ; bagging post-processing ; BQMP and Haralick global–local feature integration ; maceral components ; image segmentation ; coal petrography ; random forest ; two-level clustering ; deep neural networks ; adaptive gradient methods ; stochastic gradient descent ; bounded scheduling method ; image classification ; language modeling ; texture ; deep learning ; MB-LBP ; surface defect detection ; feature extraction ; defect recognition ; mammogram ; meta-heuristics ; optimization ; breast cancer ; detection ; skin microrelief ; water sorption ; aging ; hair ; mathematics of colour and texture ; hand-designed image descriptors ; rank features ; partial orders ; river scene segmentation ; local binary pattern ; hue variance ; surface reflection ; audio classification ; dissimilarity space ; siamese network ; ensemble of classifiers ; pattern recognition ; animal audio ; co-saliency ; omnidirectional images ; video saliency ; visual saliency estimation ; 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
    Sprache: Englisch
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  • 87
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-01
    Beschreibung: Radiation detection is important in many fields, and it poses significant challenges for instrument designers. Radiation detection instruments, particularly for nuclear decommissioning and security applications, are required to operate in unknown environments and should detect and characterise radiation fields in real time. This book covers both theory and practice, and it solicits recent advances in radiation detection, with a particular focus on radiation detection instrument design, real-time data processing, radiation simulation and experimental work, robot design, control systems, task planning and radiation shielding.
    Schlagwort(e): passive radiation detection ; gamma-ray ; neutron ; illicit trafficking ; national security ; non-proliferation ; ground-penetrating radar ; gamma ray detector ; sensor fusion ; nuclear wastes ; nuclear decommissioning ; radiation detection ; radiological characterisation ; rheology ; rapid prototyping ; radiation sensing technologies ; partial discharges ; scintillations ; air insulation ; photomultiplier ; COTS commercial MAPS ; radiation response ; integral time ; gain ; high-energy α-particle detection ; low voltage ; thick depletion width detectors ; remote-depth profiling ; gamma spectral analysis ; Bayesian inference ; uncertainty estimation ; radioactive nuclear waste ; radiological characterization ; low-resolution detector ; remote depth profiling ; radioisotope identification ; low-level radioactive contaminants ; spectrum-to-dose conversion operator ; G(E) function ; gaussian process regression ; dose rate uncertainty ; real-time dosimetry ; operational quantities ; plastic gamma spectra ; energy broadening correction ; Compton edge reconstruction ; deep learning ; deep autoencoder ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Sprache: Englisch
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  • 88
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-30
    Beschreibung: This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.
    Schlagwort(e): machine learning ; deep learning ; image processing ; classification ; tea ; fermentation ; automated image coding ; data collection methods ; interdisciplinary learning theory ; research methods ; systematic literature review ; visitor use management ; image classification ; multi-instance learning ; divergence ; dissimilarity ; bag-to-class ; Kullback–Leibler ; segment-based temporal modeling ; two-stream network ; action recognition ; internet of things ; detection ; dataset ; plant disease recognition ; image segmentation ; aphid ; Aphoidea ; lemon ; breast cancer mammogram dataset ; ultrasound breast cancer scans ; BI-RADS ; clinical data ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
    Sprache: Englisch
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  • 89
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment.
    Schlagwort(e): fuzzy automata ; coalgebra ; fuzzy language ; bisimulation ; composition ; test data generation ; genetic algorithm ; specification-based testing ; regression testing ; mutation testing ; eventual property ; model checking ; Maude ; textual question answering ; visual question answering ; metamorphic testing ; metamorphic relations ; quality assessment ; software rejuvenation ; checkpointing ; optimal rejuvenation-trigger timing ; steady-state system availability ; phase expansion ; human-error factors ; petri net ; concurrent software systems ; model-checking ; data-flows ; software reliability model ; maximum likelihood estimation ; EM algorithm ; non-homogeneous Poisson process ; generalized failure count data ; moth flame optimization ; island-based model ; feature selection ; software defect prediction ; software reliability ; search-based test case generation ; branch coverage ; object-oriented ; deep learning ; long short-term memory ; project similarity and clustering ; cross-project prediction ; Nervos CKB ; consensus protocol ; UPPAAL ; 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
    Sprache: Englisch
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  • 90
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: Most of the treatments in medicine are patient specific, aren’t they? So why should we bother with individualizing implants if we adapt our therapy to patients anyway? Looking at the neighboring field of oncologic treatment, you would not question the fact that individualization of tumor therapy with personalized antibodies has led to the thriving of this field in terms of success in patient survival and positive responses to alternatives for conventional treatments. Regarding the latest cutting-edge developments in orthopedic surgery and biotechnology, including new imaging techniques and 3D-printing of bone substitutes as well as implants, we do have an armamentarium available to stimulate the race for innovation in medicine. This Special Issue of Journal of Personalized Medicine will gather all relevant new and developed techniques already in clinical practice. Examples include the developments in revision arthroplasty and tumor (pelvic replacement) surgery to recreate individual defects, individualized implants for primary arthroplasty to establish physiological joint kinematics, and personalized implants in fracture treatment, to name but a few.
    Schlagwort(e): patient specific implant ; custom made implant ; revision hip ; Paprosky ; pelvic discontinuity ; highly cancellous ; implant surface ; tibia ; titanium alloy ; 3D printing ; megaendoprosthesis ; orthopedic oncology ; limb salvage ; patient safety management ; vascular bypass ; soft tissue sarcoma ; vascular reconstruction ; shoulder arthroplasty ; X-ray images ; implant classification ; deep learning ; dense residual ensemble-network ; rotational invariant augmentation ; Three-Dimensional Printing (3DP) ; custom implant ; patient-specific implants (PSI) ; spinal surgery ; total knee replacement ; total knee arthroplasty ; kinematic alignment ; slope ; rotation ; navigation-assisted surgery ; tumor orthopedics ; oncologic orthopedics ; patient specific ; tumor surgery ; bone defects ; hip detection ; deep convolutional neural network ; radiography ; leg alignment ; patient-specific instruments ; custom-made implant ; rotational correction ; custom-made ; rTKA ; 3D-printed ; individual ; limb-salvage ; cone ; customised ; personalised ; knee replacement ; native knee morphology ; femoral J-Curve ; principal component analysis ; geometric parameter analysis ; individualized alignment ; restricted kinematic alignment ; robotic-assisted TKA ; MAKO ; safe zone ; pelvic tumors ; 3D printed prostheses ; computer aided design pelvic reconstruction ; arthroplasty ; complications ; bone tumor ; pelvis ; patient-specific ; individualized ; 3D-printing ; unicondylar knee arthroplasty ; unicompartmental knee replacement ; unicondylar knee replacement ; partial knee arthroplasty ; partial knee replacement ; UKA ; UKR ; augmented reality ; image-guided surgery ; intraoperative imaging ; simulation ; mixed reality ; reversed shoulder arthroplasty ; 3D planning ; total hip arthroplasty ; finite element method ; cemented and uncemented acetabular fixation ; polyethylene wear patterns ; cervical–diaphyseal angle ; center of rotation ; material head ; size head ; liner thickness ; preoperative planning ; patient-specific THA ; target zone ; leg length discrepancy ; range of motion ; edge loading ; TKA ; tricompartmental knee osteoarthritis ; iTotal ; n/a ; bic Book Industry Communication::M Medicine
    Sprache: Englisch
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  • 91
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-03-27
    Beschreibung: The book presents recent studies covering the aspects of challenges in predictive modelling and applications. Advanced numerical techniques for accurate and efficient real-time prediction and optimal management in coastal and hydraulic engineering are explored. For example, adaptive unstructured meshes are introduced to capture the important dynamics that operate over a range of length scales. Deep learning techniques enable rapid and accurate modelling simulations and pave the way towards both real-time forecasting and overall optimisation control over time, thus improving profitability and managing risk. The use of data assimilation techniques incorporates information from experiments and observations to reduce uncertainties in predictions and improve predictive accuracy. Targeted observation approaches can be used for identifying when, where, and what types of observations would provide the greatest improvement to specific model forecasts at a future time. Such targeted observations are important as they will allow the most effective use of available monitoring resources. The combination of deep learning and data assimilation enables a rapid and accurate response in emergencies. The technologies discussed here can be also used to determine the sensitivity of outputs to various operational conditions in engineering and management, thus providing reliable information to both the public and policy-makers
    Schlagwort(e): numerical modelling ; unstructured meshes ; finite volume ; North Sea ; salinity ; deep learning ; martinez boundary salinity generator ; Sacramento–San Joaquin Delta ; residence time ; exposure time ; transport time scale ; hyper-tidal estuary ; singular value decomposition ; data assimilation ; ocean models ; observation strategies ; ocean forecasting systems ; ocean Double Gyre ; 4D-Var ; ROMS ; MEOF ; initial ensemble ; ensemble spread ; LETKF ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Sprache: Englisch
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  • 92
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-01
    Beschreibung: Applications of Medical Physics” is a Special Issue of Applied Sciences that has collected original research manuscripts describing cutting-edge physics developments in medicine and their translational applications. Reviews providing updates on the latest progresses in this field are also included. The collection includes a total of 20 contributions by authors from 9 different countries, which cover several areas of medical physics, spanning from radiation therapy, nuclear medicine, radiology, dosimetry, radiation protection, and radiobiology.
    Schlagwort(e): medical imaging ; radiomics ; tomosynthesis ; acquisition angle ; percutaneous radioablation ; monte carlo dosimetry ; liver lesions ; molecular radiotherapy ; quality assurance ; in vivo dosimetry ; transmission radiation detectors ; whole breast irradiation ; MR-guided radiotherapy ; predictive models ; cervical cancer ; EOS ; conventional radiography ; computed tomography ; radiation dose ; enchondroma ; phantom ; medical worker ; radiological accident ; emergency response ; retrospective dosimetry ; ESR ; EPR ; fingernails ; antioxidant ; GEMPix ; GEMs ; Timepix ; Medipix ; radiation therapy ; hadron therapy ; microdosimetry ; gaseous detectors ; Covid-19 ; chest CT ; lungs ; HU density ; artificial intelligence ; deep learning ; medical physicist ; machine learning ; big data ; radioembolization ; internal dosimetry ; Monte Carlo-based dosimetry ; absorbed dose ; signal–noise ratio ; contrast–noise ratio ; figure of merit ; robust optimization ; high dose rate brachytherapy ; single plan approach ; median absolute deviation ; 99mTc-sestamibi ; breast-specific γ imaging ; breast cancer ; apoptosis ; theragnostic ; esophageal cancer ; neoadjuvant chemoradiation ; squamous cell carcinoma ; epicardial adipose tissue ; machine and deep learning ; partial volume effect ; quantitative analysis ; point spread function ; post-reconstruction-correction-method ; iterative reconstruction algorithms ; ASiR ; ASiR-V ; noise level ; noise spatial uniformity ; in vivo relative dosimetry ; proton ; radiotherapy ; quality controls ; beam monitoring ; nanoparticles ; scintillation ; ionizing energy deposition ; photodynamic therapy ; singlet oxygen ; protontherapy ; RBE ; radiobiology ; Geant4 ; n/a ; thema EDItEUR::N History and Archaeology::NH History ; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues
    Sprache: Englisch
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  • 93
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-10-25
    Beschreibung: The classification of human action or behavior patterns is very important for analyzing situations in the field and maintaining social safety. This book focuses on recent research findings on recognizing human action patterns. Technology for the recognition of human action pattern includes the processing technology of human behavior data for learning, technology of expressing feature values ​​of images, technology of extracting spatiotemporal information of images, technology of recognizing human posture, and technology of gesture recognition. Research on these technologies has recently been conducted using general deep learning network modeling of artificial intelligence technology, and excellent research results have been included in this edition.
    Schlagwort(e): human action recognition ; graph convolution ; high-order feature ; spatio-temporal feature ; feature fusion ; dynamic gesture recognition ; multi-modalities network ; class regularization ; 3D-CNN ; spatiotemporal activations ; class-specific features ; Dynamic Hand Gesture Recognition ; human-computer interaction ; hand shape features ; pose estimation ; stacked hourglass network ; deep learning ; convolutional receptive field ; hand gesture recognition ; human–machine interface ; artificial intelligence ; feedforward neural networks ; spatio-temporal image formation ; human activity recognition ; fusion strategies ; transfer learning ; activity recognition ; data augmentation ; multi-person pose estimation ; partitioned centerpose network ; partition pose representation ; continuous hand gesture recognition ; gesture spotting ; gesture classification ; multi-modal features ; 3D skeletal ; CNN ; spatiotemporal feature ; embedded system ; real-time ; action recognition ; Long Short-Term Memory ; spatio–temporal differential ; 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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  • 94
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-05-06
    Beschreibung: Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. It consists of works introducing a new mobile mapping dataset (‘Paris CARLA 3D’), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection.
    Schlagwort(e): LiDAR ; RetinaNet ; inception ; Mobile Laser Scanning ; point clouds ; data fusion ; Lidar ; point cloud density ; point cloud coverage ; mobile mapping systems ; 3D simulation ; Pandar64 ; Ouster OS-1-64 ; mobile laser scanning ; lever arm ; boresight angles ; plane-based calibration field ; configuration analysis ; accuracy ; controllability ; evaluation ; control points ; TLS reference point clouds ; visual–inertial odometry ; Helmert variance component estimation ; line feature matching method ; correlation coefficient ; point and line features ; mobile mapping ; manhole cover ; point cloud ; F-CNN ; transfer learning ; CAM localization ; loop closure detection ; visual SLAM ; semantic topology graph ; graph matching ; CNN features ; deep learning ; view planning ; imaging network design ; building 3D modelling ; path planning ; V-SLAM ; real-time ; guidance ; embedded-systems ; 3D surveying ; exposure control ; photogrammetry ; parking statistics ; vehicle detection ; robot operating system ; 3D camera ; RGB-D ; performance evaluation ; convolutional neural networks ; smart city ; georeferencing ; MSS ; IEKF ; DSIEKF ; geometrical constraints ; 6-DoF ; DTM ; 3D city model ; dataset ; laser scanning ; 3D mapping ; synthetic ; outdoor ; semantic ; scene completion ; 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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  • 95
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods.
    Schlagwort(e): filter ; finite memory structure ; infinite memory structure ; smoother ; target tracking ; Indoor Positioning System ; WLAN ; C-Means ; K-Means ; Access Point Selection ; RSS-fingerprint ; smartphone ; pedestrian dead reckoning ; heading estimation ; autoregressive model ; adaptive Kalman filter ; indoor localization ; Wi-Fi received signal strength indicator (RSSI) ; semisupervised learning ; feature extraction ; mobile fingerprinting ; trajectory learning ; localization ; hybrid localization ; Bluetooth Low Energy ; extended kalman filter ; internet of things ; proximity sensors ; smartphone sensors ; pedestrian dead reckoning (PDR) ; Wi-Fi indoor positioning ; sensor fusion frameworks ; Kalman filter ; location fingerprinting ; trilateration ; received signal strength indication (RSSI) ; indoor positioning ; 5G system ; hybrid positioning ; geometric dilution of precision ; closed-form solution ; Cramer-Rao lower bound ; visually impaired (VI) ; computer vision ; deep learning ; multi-label convolutional support vector machine (M-CSVM) ; assistive technology ; visually impaired ; navigational system ; indoor navigation ; markers ; mobile robots ; wireless sensor network ; time of arrival (TOA) ; NLOS ; modified probabilistic data association (MPDA) ; indoor location recognition ; received signal strength (RSS) ; Wi-Fi fingerprint positioning ; deep neural network (DNN) ; optimization methods ; adaptive filter ; hidden Markov models (HMM) ; I/O detection ; GPS signal ; machine learning ; positioning applications. ; PDR ; geomagnetic positioning ; particle filter ; genetic algorithm ; Wi-Fi fine timing measurement ; NLOS identification ; Gaussian model ; carrier phase ; differential pseudolite system ; extended Kalman filter ; reliability ; integrity monitoring ; transparent obstacle recognition ; reflection noise ; laser range finder ; path planning ; mobile robot ; automated data acquisition ; remote sensing technologies ; automated progress reporting ; data fusion ; tracking resources ; bearing estimation ; azimuth estimation ; signal processing ; position estimation ; photodiode array ; indoor ranging algorithm ; channel state information ; received signal strength indicator ; VPR ; fusion navigation ; UWB ; multi-path detection ; NLOS and MP discrimination ; SVM ; random forest ; multilayer perceptron ; LOS ; DWM1000 ; fingerprinting ; smart buildings ; mobile devices ; indoor localization technologies ; model based techniques ; quality control ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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  • 96
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-08-12
    Beschreibung: Metabolomics entails the comprehensive characterization of the ensemble of endogenous and exogenous metabolites present in a biological specimen. Metabolites represent, at the same time, the downstream output of the genome and the upstream input from various external factors, such as the environment, lifestyle, and diet. Therefore, in the last few years, metabolomic phenotyping has provided unique insights into the fundamental and molecular causes of several physiological and pathophysiological conditions. In parallel, metabolomics has been demonstrating an emerging role in monitoring the influence of different manufacturing procedures on food quality and food safety. In light of the above, this collection includes the latest research from various fields of NMR-based metabolomics applications ranging from biomedicine to data mining and food chemistry.
    Schlagwort(e): NMR metabolomics ; human plasma ; COVID-19 ; exhaled breath condensate ; nanoparticles exposure ; metabolomics ; colorectal cancer ; nuclear magnetic resonance ; surgery ; relapse ; phenotyping ; nuclear magnetic resonance spectroscopy ; coffee beans ; coffee processing ; coffee varieties ; post-harvest treatment ; NMR spectroscopy ; neonatal sepsis ; EOS ; LOS ; preterm birth ; NMR ; biomarkers ; clustering ; artificial intelligence ; machine learning ; deep learning ; health science ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSB Biochemistry
    Sprache: Englisch
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  • 97
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-06-21
    Beschreibung: The recent revolution in deep learning has enabled considerable development in the fields of object and activity detection. Visual object detection tries to find objects of target classes with precise localisation in an image and assign each object instance a corresponding class label. At the same time, activity recognition aims to determine the actions or activities of an agent or group of agents based on sensor or video observation data. It is a very important and challenging problem to detect, identify, track, and understand the behaviour of objects through images and videos taken by various cameras. Together, objects and their activity recognition in imaging data captured by remote sensing platforms is a highly dynamic and challenging research topic. During the last decade, there has been significant growth in the number of publications in the field of object and activity recognition. In particular, many researchers have proposed application domains to identify objects and their specific behaviours from air and spaceborne imagery. This Special Issue includes papers that explore novel and challenging topics for object and activity detection in remote sensing images and videos acquired by diverse platforms.
    Schlagwort(e): multi-camera system ; space alignment ; UAV-assisted calibration ; cross-view matching ; spatiotemporal feature map ; view-invariant description ; air-to-ground synchronization ; tidal flat water ; YOLOv3 ; similarity algorithm for water extraction ; arbitrary-oriented object detection in satellite optical imagery ; adaptive dynamic refined single-stage transformer detector ; feature pyramid transformer ; dynamic feature refinement ; synthetic aperture radar (SAR) ; ship detection ; convolutional neural network (CNN) ; deep learning (DL) ; feature pyramid network (FPN) ; quad feature pyramid network (Quad-FPN) ; crowd estimation ; 3D simulation ; unmanned aerial vehicle ; synthetic crowd data ; invasive species ; thermal imaging ; habitat identification ; deep learning ; drone ; multiview semantic vegetation index ; urban forestry ; green view index (GVI) ; semantic segmentation ; urban vegetation ; RGB vegetation index ; 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
    Format: application/octet-stream
    Standort Signatur Erwartet Verfügbarkeit
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  • 98
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-12-06
    Beschreibung: The analysis of big data in biomedical, business and financial research has drawn much attention from researchers worldwide. This collection of articles aims to provide a platform for an in-depth discussion of novel statistical methods developed for the analysis of Big Data in these areas. Both applied and theoretical contributions to these areas are showcased.
    Schlagwort(e): bandwidth selection ; correlation ; edge-preserving image denoising ; image sequence ; jump regression analysis ; local smoothing ; nonparametric regression ; spatio-temporal data ; linear mixed model ; ridge estimation ; pretest and shrinkage estimation ; multicollinearity ; asymptotic bias and risk ; LASSO estimation ; high-dimensional data ; big data adaptation ; dividend estimation ; options markets ; weighted least squares ; online health community ; social support ; network analysis ; cancer ; functional principal component analysis ; functional predictor ; linear mixed-effects model ; mobile device ; sparse group regularization ; wearable device data ; Bayesian modeling ; functional regression ; gestational weight ; infant birth weight ; joint modeling ; longitudinal data ; maternal weight gain ; transfer learning ; deep learning ; pretrained neural networks ; chest X-ray images ; lung diseases ; causal structure learning ; consistency ; FCI algorithm ; high dimensionality ; nonparametric testing ; PC algorithm ; fMRI ; functional connectivity ; brain network ; Human Connectome Project ; statistics ; 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
    Sprache: Englisch
    Format: image/jpeg
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  • 99
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    Unbekannt
    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2022-02-24
    Beschreibung: There is a growing concern about the climate; numerous voices stress that, in order to overcome the climate crisis, the transition to a low-carbon society is the most reasonable path to follow. In this type of society, individuals would be characterized by making mindful efforts to drastically decrease carbon and greenhouse gas emissions, and promote benign energy sources. In order to facilitate this transition, a social perspective in addition to technological, political and economic aspects must be integrated into the relevant decision-making processes. This is necessary because the public can strongly affect actions aimed at driving profound changes in traditional energy systems. To contribute to the effort of promoting energy transition, the Editors of this book invited scholars and practitioners conducting research in the areas of climate change and the energy transition to submit their work. This book includes studies that establish a valuable source of information which can be used to enhance decision-making processes which, in turn, can turn the energy transition into reality. Hopefully, efforts such as this collection of knowledge can help economies make a step towards a secure and sustainable energy future in which renewables will have replaced the centuries-long human dependence on fossil fuels.
    Schlagwort(e): ICT ; EU regional policy ; sustainable development ; multicriteria approach ; policy assessment ; bioclimatic buildings ; sustainable buildings ; bioclimatic housing design ; energy efficiency ; citizens’ views ; raising-awareness ; adaptation ; decision making ; bibliographical survey ; climatic factor ; energy industry ; world agriculture ; causal effects ; justice ; factorial surveys ; renewable energy ; vignette study ; foreign direct investment ; environmental efficiency ; non-radial metafrontier Malmquist index ; partial-factor CO2 emission performance ; India ; thermal comfort ; outdoor environments ; pedestrians ; heat mitigation ; microclimates ; wastewater ; sewerage ; liquid waste tanks (cesspool) ; partial correlation ; organic and biogenic pollution ; business communication ; energy corporations ; greening ; responsibility ; strategic management ; buildings ; energy efficiency improvement ; multi-objective optimization ; preference disaggregation ; preference elicitation ; value system ; utility function ; PV farms ; deep learning ; satellite imagery ; CNN ; automatic detection ; climate transitions ; climate justice ; regional development ; territorial plans ; place-based policy ; coal ; natural gas ; CO2 emissions ; public acceptance ; ordered probit model ; gas turbine ; air injection ; turboexpander ; performance enhancement ; emission reduction ; life cycle assessment ; analytical hierarchy process ; multi-perspective criteria ; carbon capture ; acceptance ; public perception ; industrial applications ; literature review ; knowledge ; awareness ; communication ; climate change ; energy and climate plan ; energy price ; energy transition ; Greece ; lignite ; RES ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics
    Sprache: Englisch
    Format: image/jpeg
    Standort Signatur Erwartet Verfügbarkeit
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  • 100
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-09
    Beschreibung: The great advances in information technology (IT) have implications for many sectors, such as bioinformatics, and has considerably increased their possibilities. This book presents a collection of 11 original research papers, all of them related to the application of IT-related techniques within the bioinformatics sector: from new applications created from the adaptation and application of existing techniques to the creation of new methodologies to solve existing problems.
    Schlagwort(e): machine learning ; metagenomics ; bioinformatics ; CTX-M ; data mining ; cluster ; clinical implications ; diabetes ; epidemiology ; forecast ; PART ; Decision table ; Weka ; real-life patients ; regression ; ear detection ; computer vision ; convolutional neural network ; image recognition ; video analysis ; gene clustering ; swarm intelligence ; biological functions detection ; informative genes ; fuel cell ; hydrogen energy ; intelligent systems ; hybrid systems ; Artificial Neural Networks ; power management ; Machine Learning ; personality assessment ; gradient boosting ; Affective Computing ; transposable elements ; metrics ; deep learning ; detection ; classification ; mitochondrial protein ; bi-directional LSTM ; plasmodium falciparum ; Particle Swarm Optimization ; Harmony Search ; parameter estimation ; Arabidopsis thaliana ; clinical data ; feature selection ; genetic programming ; evolutionary computation ; dynamic models ; evolutionary computing ; derivative-free optimization ; metabolism ; glycolysis ; yeast ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Sprache: Englisch
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