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Special Protein Molecules Computational Identification

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ISBN: 9783038970439 9783038970446 Year: Pages: VIII, 296 Language: english
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medical technology
Added to DOAB on : 2018-08-09 12:10:11
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It is time consuming and costly to detect new molecules of some special proteins. These special proteins include cytokines, enzymes, cell-penetrating peptides, anticancer peptides, cancer lectins, G-protein-coupled receptors, etc. Researchers often employ computer programs to list some candidates, and to validate the candidates with molecular experiments. These computer programs are key to possible savings on wet experiment costs. Software results with high false positive will lead to high costs in the validation process.In this Special Issue, we focus on these computer program approaches and algorithms. Some "golden features" from protein primary sequences have been proposed for these problems, such as Chou’s PseAAC (pseudo amino acid composition). PseAAC has been tried on nearly all kinds of protein identification, together with SVM (support vector machines, a type of classifier). However, I prefer special features, and classification methods should be proposed for special protein molecules. "Golden features" cannot work well on all kinds of proteins. I hope that submissions will focus on a type of special protein molecule, collect related data sets, obtain better prediction performance (especially low false positives), and develop user-friendly software tools or web servers.

Wine Traceability

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ISBN: 9783039217687 9783039217694 Year: Pages: 138 DOI: 10.3390/books978-3-03921-769-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Biochemistry
Added to DOAB on : 2019-12-09 11:49:16
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Wine traceability is a central theme in the current world market where consumers are increasingly demanding the quality and origin of food and drink. The wine production chain and wine composition are generally controlled by different laws (International Organization of Vine and Wine (OIV), European Union (EU), and national governments) and need specific documentation. Nevertheless, wine production is subject to fraud. Consequently, the improvement of the methods applied to verify the origin and quality of wines is very important to protect wine consumers and producers. In this book, eight different papers—six research papers and two reviews—address the topic from different points of view.

Uncertainty Quantification Techniques in Statistics

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ISBN: 9783039285464 / 9783039285471 Year: Pages: 128 DOI: 10.3390/books978-3-03928-547-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Sociology
Added to DOAB on : 2020-06-09 16:38:57
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Uncertainty quantification (UQ) is a mainstream research topic in applied mathematics and statistics. To identify UQ problems, diverse modern techniques for large and complex data analyses have been developed in applied mathematics, computer science, and statistics. This Special Issue of Mathematics (ISSN 2227-7390) includes diverse modern data analysis methods such as skew-reflected-Gompertz information quantifiers with application to sea surface temperature records, the performance of variable selection and classification via a rank-based classifier, two-stage classification with SIS using a new filter ranking method in high throughput data, an estimation of sensitive attribute applying geometric distribution under probability proportional to size sampling, combination of ensembles of regularized regression models with resampling-based lasso feature selection in high dimensional data, robust linear trend test for low-coverage next-generation sequence data controlling for covariates, and comparing groups of decision-making units in efficiency based on semiparametric regression.

Systems Analytics and Integration of Big Omics Data

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ISBN: 9783039287444 / 9783039287451 Year: Pages: 202 DOI: 10.3390/books978-3-03928-745-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Therapeutics
Added to DOAB on : 2020-06-09 16:38:57
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A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.

Keywords

tissue-specific expressed genes --- transcriptome --- tissue classification --- support vector machine --- feature selection --- bioinformatics pipelines --- algorithm development for network integration --- miRNA–gene expression networks --- multiomics integration --- network topology analysis --- candidate genes --- gene–environment interactions --- logic forest --- systemic lupus erythematosus --- Gene Ontology --- KEGG pathways --- enrichment analysis --- proteomic analysis --- plot visualization --- Alzheimer’s disease --- dementia --- cognitive impairment --- neurodegeneration --- Gene Ontology --- annotation --- biocuration --- amyloid-beta --- microtubule-associated protein tau --- artificial intelligence --- genotype --- phenotype --- deep phenotype --- data integration --- genomics --- phenomics --- precision medicine informatics --- epigenetics --- chromatin modification --- sequencing --- regulatory genomics --- disease variants --- machine learning --- multi-omics --- data integration --- curse of dimensionality --- heterogeneous data --- missing data --- class imbalance --- scalability --- genomics --- pharmacogenomics --- cell lines --- database --- drug sensitivity --- data integration --- omics data --- genomics --- RNA expression --- non-omics data --- clinical data --- epidemiological data --- challenges --- integrative analytics --- joint modeling --- multivariate analysis --- multivariate causal mediation --- distance correlation --- direct effect --- indirect effect --- causal inference --- n/a

Sensors in Agriculture

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ISBN: 9783038974123 9783038974130 Year: Pages: 346 DOI: 10.3390/books978-3-03897-413-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Sensors in Agriculture

Author:
ISBN: 9783038977445 9783038977452 Year: Pages: 354 DOI: 10.3390/books978-3-03897-745-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Optimization Methods Applied to Power Systems: Volume 1

Authors: ---
ISBN: 9783039211302 9783039211319 Year: Pages: 382 DOI: 10.3390/books978-3-03921-131-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.

Keywords

Cable joint --- internal defect --- thermal probability density --- power system optimization --- optimal power flow --- developed grew wolf optimizer --- energy internet --- prosumer --- energy management --- consensus --- demand response --- day-ahead load forecasting --- modular predictor --- feature selection --- micro-phasor measurement unit --- mutual information theory --- stochastic state estimation --- two-point estimation method --- JAYA algorithm --- multi-population method (MP) --- chaos optimization algorithm (COA) --- economic load dispatch problem (ELD) --- optimization methods --- constrained parameter estimation --- extended Kalman filter --- power systems --- C&I particle swarm optimization --- ringdown detection --- optimal reactive power dispatch --- loss minimization --- voltage deviation --- hybrid method --- tabu search --- particle swarm optimization --- artificial lighting --- simulation --- calibration --- radiance --- GenOpt --- street light points --- DC optimal power flow --- power transfer distribution factors --- generalized generation distribution factors --- unit commitment --- adaptive consensus algorithm --- distributed heat-electricity energy management --- eight searching sub-regions --- islanded microgrid --- dragonfly algorithm --- metaheuristic --- optimal power flow --- particle swarm optimization --- CCHP system --- energy storage --- off-design performance --- dynamic solving framework --- battery energy storage system --- micro grid --- MILP --- PCS efficiency --- piecewise linear techniques --- renewable energy sources --- optimal operation --- UC --- demand bidding --- demand response --- genetic algorithm --- load curtailment --- optimization --- hybrid renewable energy system --- pumped-hydro energy storage --- off-grid --- optimization --- HOMER software --- rural electrification --- sub-Saharan Africa --- Cameroon --- building energy management system --- HVAC system --- energy storage system --- energy flow model --- dependability --- sustainability --- data center --- power architectures --- optimization --- AC/DC hybrid active distribution --- hierarchical scheduling --- multi-stakeholders --- discrete wind driven optimization --- multiobjective optimization --- optimal power flow --- metaheuristic --- wind energy --- photovoltaic --- smart grid --- transformer-fault diagnosis --- principal component analysis --- particle swarm optimization --- support vector machine --- wind power --- integration assessment --- interactive load --- considerable decomposition --- controllable response --- SOCP relaxations --- optimal power flow --- current margins --- affine arithmetic --- interval variables --- optimizing-scenarios method --- power flow --- wind power --- active distribution system --- virtual power plant --- stochastic optimization --- decentralized and collaborative optimization --- genetic algorithm --- multi-objective particle swarm optimization algorithm --- artificial bee colony --- IEEE Std. 80-2000 --- Schwarz’s equation --- fuzzy algorithm --- radial basis function --- neural network --- ETAP --- distributed generations (DGs) --- distribution network reconfiguration --- runner-root algorithm (RRA) --- inter-turn shorted-circuit fault (ISCF) --- strong track filter (STF) --- linear discriminant analysis (LDA) --- switched reluctance machine (SRM) --- charging/discharging --- electric vehicle --- energy management --- genetic algorithm --- intelligent scatter search --- electric vehicles --- heterogeneous networks --- demand uncertainty --- power optimization --- Stackelberg game --- power system unit commitment --- hybrid membrane computing --- cross-entropy --- the genetic algorithm based P system --- the biomimetic membrane computing --- transient stability --- two-stage feature selection --- particle encoding method --- fitness function --- power factor compensation --- non-sinusoidal circuits --- geometric algebra --- evolutionary algorithms --- electric power contracts --- electric energy costs --- cost minimization --- evolutionary computation --- bio-inspired algorithms --- congestion management --- low-voltage networks --- multi-objective particle swarm optimization --- affinity propagation clustering --- optimal congestion threshold --- optimization --- magnetic field mitigation --- overhead --- underground --- passive shielding --- active shielding --- MV/LV substation --- n/a

Optimization Methods Applied to Power Systems: Volume 2

Authors: ---
ISBN: 9783039211562 9783039211579 Year: Pages: 306 DOI: 10.3390/books978-3-03921-157-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.

Keywords

Cable joint --- internal defect --- thermal probability density --- power system optimization --- optimal power flow --- developed grew wolf optimizer --- energy internet --- prosumer --- energy management --- consensus --- demand response --- day-ahead load forecasting --- modular predictor --- feature selection --- micro-phasor measurement unit --- mutual information theory --- stochastic state estimation --- two-point estimation method --- JAYA algorithm --- multi-population method (MP) --- chaos optimization algorithm (COA) --- economic load dispatch problem (ELD) --- optimization methods --- constrained parameter estimation --- extended Kalman filter --- power systems --- C&I particle swarm optimization --- ringdown detection --- optimal reactive power dispatch --- loss minimization --- voltage deviation --- hybrid method --- tabu search --- particle swarm optimization --- artificial lighting --- simulation --- calibration --- radiance --- GenOpt --- street light points --- DC optimal power flow --- power transfer distribution factors --- generalized generation distribution factors --- unit commitment --- adaptive consensus algorithm --- distributed heat-electricity energy management --- eight searching sub-regions --- islanded microgrid --- dragonfly algorithm --- metaheuristic --- optimal power flow --- particle swarm optimization --- CCHP system --- energy storage --- off-design performance --- dynamic solving framework --- battery energy storage system --- micro grid --- MILP --- PCS efficiency --- piecewise linear techniques --- renewable energy sources --- optimal operation --- UC --- demand bidding --- demand response --- genetic algorithm --- load curtailment --- optimization --- hybrid renewable energy system --- pumped-hydro energy storage --- off-grid --- optimization --- HOMER software --- rural electrification --- sub-Saharan Africa --- Cameroon --- building energy management system --- HVAC system --- energy storage system --- energy flow model --- dependability --- sustainability --- data center --- power architectures --- optimization --- AC/DC hybrid active distribution --- hierarchical scheduling --- multi-stakeholders --- discrete wind driven optimization --- multiobjective optimization --- optimal power flow --- metaheuristic --- wind energy --- photovoltaic --- smart grid --- transformer-fault diagnosis --- principal component analysis --- particle swarm optimization --- support vector machine --- wind power --- integration assessment --- interactive load --- considerable decomposition --- controllable response --- SOCP relaxations --- optimal power flow --- current margins --- affine arithmetic --- interval variables --- optimizing-scenarios method --- power flow --- wind power --- active distribution system --- virtual power plant --- stochastic optimization --- decentralized and collaborative optimization --- genetic algorithm --- multi-objective particle swarm optimization algorithm --- artificial bee colony --- IEEE Std. 80-2000 --- Schwarz’s equation --- fuzzy algorithm --- radial basis function --- neural network --- ETAP --- distributed generations (DGs) --- distribution network reconfiguration --- runner-root algorithm (RRA) --- inter-turn shorted-circuit fault (ISCF) --- strong track filter (STF) --- linear discriminant analysis (LDA) --- switched reluctance machine (SRM) --- charging/discharging --- electric vehicle --- energy management --- genetic algorithm --- intelligent scatter search --- electric vehicles --- heterogeneous networks --- demand uncertainty --- power optimization --- Stackelberg game --- power system unit commitment --- hybrid membrane computing --- cross-entropy --- the genetic algorithm based P system --- the biomimetic membrane computing --- transient stability --- two-stage feature selection --- particle encoding method --- fitness function --- power factor compensation --- non-sinusoidal circuits --- geometric algebra --- evolutionary algorithms --- electric power contracts --- electric energy costs --- cost minimization --- evolutionary computation --- bio-inspired algorithms --- congestion management --- low-voltage networks --- multi-objective particle swarm optimization --- affinity propagation clustering --- optimal congestion threshold --- optimization --- magnetic field mitigation --- overhead --- underground --- passive shielding --- active shielding --- MV/LV substation --- n/a

Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

Authors: ---
ISBN: 9783039212156 9783039212163 Year: Pages: 438 DOI: 10.3390/books978-3-03921-216-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Mechanical Engineering
Added to DOAB on : 2019-12-09 11:49:15
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As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.

Keywords

landslide --- bagging ensemble --- Logistic Model Trees --- GIS --- Vietnam --- colorization --- random forest regression --- grayscale aerial image --- change detection --- gully erosion --- environmental variables --- data mining techniques --- SCAI --- GIS --- mapping --- single-class data descriptors --- materia medica resource --- Panax notoginseng --- one-class classifiers --- geoherb --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- remote sensing image segmentation --- convolutional neural networks --- Gaofen-2 --- hybrid structure convolutional neural networks --- winter wheat spatial distribution --- classification-based learning --- real-time precise point positioning --- convergence time --- ionospheric delay constraints --- precise weighting --- landslide --- weights of evidence --- logistic regression --- random forest --- hybrid model --- traffic CO --- traffic CO prediction --- neural networks --- GIS --- land use/land cover (LULC) --- unmanned aerial vehicle --- texture --- gray-level co-occurrence matrix --- machine learning --- crop --- landslide susceptibility --- random forest --- boosted regression tree --- information gain --- landslide susceptibility map --- ALS point cloud --- multi-scale --- classification --- large scene --- coarse particle --- particulate matter 10 (PM10) --- landsat image --- machine learning --- support vector machine --- high-resolution --- optical remote sensing --- object detection --- deep learning --- transfer learning --- land subsidence --- Bayes net --- naïve Bayes --- logistic --- multilayer perceptron --- logit boost --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- leaf area index (LAI) --- machine learning --- Sentinel-2 --- sensitivity analysis --- training sample size --- spectral bands --- spatial sparse recovery --- constrained spatial smoothing --- spatial spline regression --- alternating direction method of multipliers --- landslide prediction --- machine learning --- neural networks --- model switching --- spatial predictive models --- predictive accuracy --- model assessment --- variable selection --- feature selection --- model validation --- spatial predictions --- reproducible research --- Qaidam Basin --- remote sensing --- TRMM --- artificial neural network --- n/a

Smart Sensors for Structural Health Monitoring

Authors: --- ---
ISBN: 9783039217588 9783039217595 Year: Pages: 342 DOI: 10.3390/books978-3-03921-759-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).

Keywords

optical crack growth sensor --- digital sampling moiré --- 2D crack growth --- calibration --- concrete crack --- feature extraction --- mapping construction --- fuzzy classification --- rotary ultrasonic array --- bending stiffness --- damage identification --- environmental noise --- bridge --- test vehicle --- structural impact monitoring --- sensors distribution optimization --- NSGA-II --- energy analysis of wavelet band --- principal component analysis --- transmission tower --- settlement --- wind force --- acceleration --- modal frequencies --- sudden event monitoring --- wireless smart sensors --- demand-based nodes --- event-triggered sensing --- data fusion --- patch antenna --- sensor --- structural health monitoring --- crack identification --- resonant frequency --- damage identification --- sensor optimization --- Virtual Distortion Method (VDM) --- Particle Swarm Optimization (PSO) algorithm --- sensitivity --- structural health monitoring --- piezoelectric wafer active sensors --- active sensing --- passive sensing --- damage detection --- acoustic emission --- uniaxial stress measurement --- structural steel members --- amplitude spectrum --- phase spectrum --- shear-wave birefringence --- acoustoelastic effect --- damage detection --- smartphones --- steel frame --- shaking table tests --- wavelet packet decomposition --- low-velocity impacts --- strain wave --- impactor stiffness --- data processing --- feature selection --- impact identification --- crack --- strain --- distributed dense sensor network --- structural health monitoring --- fibre bundle --- reflective optical sensor --- tip clearance --- turbine --- aero engine --- principal component analysis --- space window --- time window --- damage detection --- length effect --- stress detection --- electromagnetic oscillation --- steel strand --- concrete structures --- SHM --- stretching method --- model updating --- displacement sensor --- helical antenna --- resonant frequency --- perturbation theory --- normal mode --- wheel minor defect --- high-speed train --- online wayside detection --- Bayesian blind source separation --- FBG sensor array

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