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Cutting-Edge Technologies for Renewable Energy Production and Storage

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ISBN: 9783039360000 / 9783039360017 Year: Pages: 124 DOI: 10.3390/books978-3-03936-001-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2020-06-09 16:38:57
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Anthropogenic greenhouse gas (GHG) emissions are dramatically influencing the environment, and research is strongly committed to proposing alternatives, mainly based on renewable energy sources. Low GHG electricity production from renewables is well established but issues of grid balancing are limiting their application. Energy storage is a key topic for the further deployment of renewable energy production. Besides batteries and other types of electrical storage, electrofuels and bioderived fuels may offer suitable alternatives in some specific scenarios. This Special Issue includes contributions on the energy conversion technologies and use, energy storage, technologies integration, e-fuels, and pilot and large-scale applications.

Applications of Computational Intelligence to Power Systems

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ISBN: 9783039217601 9783039217618 Year: Pages: 116 DOI: 10.3390/books978-3-03921-761-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-11-08 11:31:56
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Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in electrical engineering applications. This Special Issue represents a thorough treatment of computational intelligence from an electrical power system engineer’s perspective. Thorough, well-organised, and up-to-date, it examines in detail some of the important aspects of this very exciting and rapidly emerging technology, including machine learning, particle swarm optimization, genetic algorithms, and deep learning systems. Written in a concise and flowing manner by experts in the area of electrical power systems who have experience in the application of computational intelligence for solving many complex and difficult power system problems, this Special Issue is ideal for professional engineers and postgraduate students entering this exciting field.

Entropy Measures for Data Analysis: Theory, Algorithms and Applications

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ISBN: 9783039280322 9783039280339 Year: Pages: 260 DOI: 10.3390/books978-3-03928-033-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2020-01-07 09:21:22
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Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Keywords

experiment of design --- empirical mode decomposition --- signal analysis --- similarity indices --- synchronization analysis --- auditory attention --- entropy measure --- linear discriminant analysis (LDA) --- support vector machine (SVM) --- auditory attention classifier --- electroencephalography (EEG) --- vague entropy --- distance induced vague entropy --- distance --- complex fuzzy set --- complex vague soft set --- entropy, entropy visualization --- entropy balance equation --- Shannon-type relations --- multivariate analysis --- machine learning evaluation --- data transformation --- sample entropy --- treadmill walking --- center of pressure displacement --- dual-tasking --- analog circuit --- fault diagnosis --- cross wavelet transform --- Tsallis entropy --- parametric t-distributed stochastic neighbor embedding --- support vector machine --- information transfer --- Chinese stock sectors --- effective transfer entropy --- market crash --- system coupling --- cross-visibility graphs --- image entropy --- geodesic distance --- Dempster-Shafer evidence theory --- uncertainty of basic probability assignment --- belief entropy --- plausibility transformation --- weighted Hartley entropy --- Shannon entropy --- learning --- information --- novelty detection --- non-probabilistic entropy --- learning systems --- permutation entropy --- embedded dimension --- short time records --- signal classification --- relevance analysis --- global optimization --- meta-heuristic --- firefly algorithm --- cross-entropy method --- co-evolution --- symbolic analysis --- ordinal patterns --- Permutation entropy --- conditional entropy of ordinal patterns --- Kolmogorov-Sinai entropy --- algorithmic complexity --- information entropy --- particle size distribution --- selfsimilar measure --- simulation --- data analysis --- entropy --- entropy measures --- automatic learning

Smart Energy Management for Smart Grids

Authors: ---
ISBN: 9783039281428 9783039281435 Year: Pages: 350 DOI: 10.3390/books978-3-03928-143-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.

Keywords

seawater pumped storage --- renewable energy --- active distribution networks --- two-stage --- scheduling --- distributed generation --- storage device --- MILP --- ToU tariff --- optimization --- daily consumption curve --- peak/off-peak --- programmable appliances --- smart grid --- smart energy --- sustainability --- values --- technology acceptance --- technology adoption --- smart grid --- Smart Grid Station --- renewable energy sources --- energy management system --- smart metering --- feedback --- households --- energy and water consumption --- theories of social practice --- smart grid --- differentiation --- development demand --- comprehensive evaluation --- energy management system --- energy storage system --- semantic web technologies --- rules --- ontology --- engineering support --- smart grid architecture model --- model driven architecture --- IEC 61850 --- IEC 61499 --- energy storage system --- electricity charge discount program --- peak reduction --- economic feasibility analysis --- policy effectiveness evaluation --- occupant behavior --- single-person household --- energy consumption --- Korean Time Use Survey --- EnergyPlus --- data mining --- K-modes clustering --- support vector machine --- Gaussian process regression --- combined dispatch (CD) strategy --- optimization --- HOMER --- net present cost (NPC) --- sensitivity analysis --- renewable energy --- solar power generation prediction --- smart grid --- photovoltaic power --- machine learning --- electrical distribution system --- graph theory --- micro grids --- heuristic --- optimization --- planning --- unbalanced three-phase distribution networks --- optimal power flows --- genetic algorithm --- holomorphic embedding load flow method --- simulation --- forecasting --- solar generation --- storage capacity --- game theory --- nash equilibrium --- distributed energy management algorithm --- micro grid --- meta heuristic techniques --- R&amp --- D planning --- patent analysis --- sustainable smart grid technology --- R&amp --- D strategy --- STEEP analysis --- scenario planning --- electric vehicle charging technology --- multilayer perceptron neural network --- support vector machine --- cyberattacks --- optimal power flow --- smart grid security --- intruder detection system

Advances in Near Infrared Spectroscopy and Related Computational Methods

Authors: ---
ISBN: 9783039280520 9783039280537 Year: Pages: 496 DOI: 10.3390/books978-3-03928-053-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Chemistry (General) --- Analytical Chemistry
Added to DOAB on : 2020-01-30 16:39:46
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In the last few decades, near-infrared (NIR) spectroscopy has distinguished itself as one of the most rapidly advancing spectroscopic techniques. Mainly known as an analytical tool useful for sample characterization and content quantification, NIR spectroscopy is essential in various other fields, e.g. NIR imaging techniques in biophotonics, medical applications or used for characterization of food products. Its contribution in basic science and physical chemistry should be noted as well, e.g. in exploration of the nature of molecular vibrations or intermolecular interactions. One of the current development trends involves the miniaturization and simplification of instrumentation, creating prospects for the spread of NIR spectrometers at a consumer level in the form of smartphone attachments—a breakthrough not yet accomplished by any other analytical technique. A growing diversity in the related methods and applications has led to a dispersion of these contributions among disparate scientific communities. The aim of this Special Issue was to bring together the communities that may perceive NIR spectroscopy from different perspectives. It resulted in 30 contributions presenting the latest advances in the methodologies essential in near-infrared spectroscopy in a variety of applications.

Keywords

hyperspectral imaging --- variety discrimination --- Chrysanthemum --- deep convolutional neural network --- DNA --- FTIR spectroscopy --- rapid identification --- PLS-DA --- animal origin --- near-infrared hyperspectral imaging --- raisins --- support vector machine --- pixel-wise --- object-wise --- maize kernel --- hyperspectral imaging technology --- accelerated aging --- principal component analysis --- support vector machine model --- standard germination tests --- blackberries --- Rubus fructicosus --- phenolics --- carotenoids --- bioanalytical applications --- near infrared --- chemometrics --- VIS/NIR hyperspectral imaging --- corn seed --- classification --- freeze-damaged --- image processing --- imaging visualization --- wavelength selection --- NIR spectroscopy --- binary dragonfly algorithm --- ensemble learning --- quantitative analysis modeling --- NIR --- SCiO --- pocket-sized spectrometer --- cheese --- fat --- moisture --- multivariate data analysis --- Fourier-transform near-infrared spectroscopy --- glucose --- fructose --- dry matter --- partial least square regression --- Ewing sarcoma --- Fourier transform infrared spectroscopy --- FTIR --- chemotherapy --- bone cancer --- calibration transfer --- NIR spectroscopy --- PLS --- quantitative analysis model --- melamine --- FT-IR --- NIR spectroscopy --- quantum chemical calculation --- anharmonic calculation --- overtones --- combination bands --- near infrared spectroscopy --- Trichosanthis Fructus --- geographical origin --- chemometric techniques --- crude drugs --- prepared slices --- support vector machine-discriminant analysis --- near-infrared fluorescence --- fluorescent probes --- Zn(II) --- di-(2-picolyl)amine --- living cells --- cellular imaging --- near-infrared (NIR) spectroscopy --- calibration transfer --- affine invariance --- multivariate calibration --- partial least squares (PLS) --- NIR --- direct model transferability --- MicroNIR™ --- SVM --- hier-SVM --- SIMCA --- PLS-DA --- TreeBagger --- PLS --- calibration transfer --- agriculture --- photonics --- imaging --- spectral imaging --- spectroscopy --- handheld near-infrared spectroscopy --- pasta/sauce blends --- partial least squares calibration --- nutritional parameters --- bootstrapping soft shrinkage --- partial least squares --- extra virgin olive oil --- adulteration --- FT-NIR spectroscopy --- near-infrared spectroscopy --- ethanol --- anharmonic quantum mechanical calculations --- isotopic substitution --- overtones --- combinations bands --- seeds vitality --- rice seeds --- near-infrared spectroscopy --- hyperspectral image --- discriminant analysis --- near-infrared spectroscopy --- counter propagation artificial neural network --- detection --- auxiliary diagnosis --- BRAF V600E mutation --- colorectal cancer --- tissue --- paraffin-embedded --- deparaffinized --- stained --- ultra-high performance liquid chromatography --- Folin–Ciocalteu --- total hydroxycinnamic derivatives --- phytoextraction --- near-infrared spectroscopy --- origin traceability --- data fusion --- Paris polyphylla var. yunnanensis --- Fourier transform mid-infrared spectroscopy --- near-infrared spectroscopy --- aquaphotomics --- water --- light --- near infrared spectroscopy --- water-mirror approach --- perturbation --- biomeasurements --- biodiagnosis --- biomonitoring --- Vitis vinifera L. --- proximal sensing --- precision viticulture --- near infrared --- chemometrics --- non-destructive sensor --- NIRS --- osteopathy --- late preterm --- brain --- splanchnic --- Raman spectroscopy --- hyperspectral imaging --- analytical spectroscopy --- counterfeit and substandard pharmaceuticals --- DFT calculations --- chemometrics --- PLSR --- API --- lumefantrine --- artemether --- antimalarial tablets --- FT-NIR spectroscopy --- PLS-R --- water --- glucose --- test set validation --- RMSEP --- hyperspectral image processing --- perfusion measurements --- clinical classifications --- n/a

Groundwater Resources and Salt Water Intrusion in a Changing Environment

Authors: ---
ISBN: 9783039211975 9783039211982 Year: Pages: 176 DOI: 10.3390/books978-3-03921-198-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:16
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This Special Issue presents the work of 30 scientists from 11 countries. It confirms that the impacts of global change, resulting from both climate change and increasing anthropogenic pressure, are huge on worldwide coastal areas (and critically so on some islands in the Pacific Ocean), with highly negative effects on coastal groundwater resources, which are widely affected by seawater intrusion. Some improved research methods are proposed in the contributions: using innovative hydrogeological, geophysical, and geochemical monitoring; assessing impacts of the changing environment on the coastal groundwater resources in terms of quantity and quality; and using modelling, especially to improve management approaches. The scientific research needed to face these challenges must continue to be deployed by different approaches based on the monitoring, modelling and management of groundwater resources. Novel and more efficient methods must be developed to keep up with the accelerating pace of global change.

Statistical Analysis and Stochastic Modelling of Hydrological Extremes

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ISBN: 9783039216642 9783039216659 Year: Pages: 294 DOI: 10.3390/books978-3-03921-665-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Meteorology and Climatology
Added to DOAB on : 2019-12-09 16:10:12
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Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes: Historical changes in hydrological extremes; Projected changes in hydrological extremes; Downscaling of hydrological extremes; Early warning and forecasting systems for drought and flood; Interconnections of hydrological extremes; Applicability of satellite data for hydrological studies.

Keywords

rainfall --- monsoon --- high resolution --- TRMM --- drought prediction --- APCC Multi-Model Ensemble --- seasonal climate forecast --- machine learning --- sparse monitoring network --- Fiji --- drought analysis --- ANN model --- drought indices --- meteorological drought --- SIAP --- SWSI --- hydrological drought --- discrete wavelet --- global warming --- statistical downscaling --- HBV model --- flow regime --- uncertainty --- reservoir inflow forecasting --- artificial neural network --- wavelet artificial neural network --- weighted mean analogue --- variation analogue --- streamflow --- artificial neural network --- simulation --- forecasting --- support vector machine --- evolutionary strategy --- heavy storm --- hyetograph --- temperature --- clausius-clapeyron scaling --- climate change --- the Cauca River --- climate variability --- ENSO --- extreme rainfall --- trends --- statistical downscaling --- random forest --- least square support vector regression --- extreme rainfall --- polynomial normal transform --- multivariate modeling --- sampling errors --- non-normality --- extreme rainfall analysis --- statistical analysis --- hydrological extremes --- stretched Gaussian distribution --- Hurst exponent --- INDC pledge --- precipitation --- extreme events --- extreme precipitation exposure --- non-stationary --- extreme value theory --- uncertainty --- flood regime --- flood management --- Kabul river basin --- Pakistan --- extreme events --- innovative methods --- downscaling --- forecasting --- compound events --- satellite data

Remote Sensing Technology Applications in Forestry and REDD+

Authors: --- --- ---
ISBN: 9783039284702 9783039284719 Year: Pages: 244 DOI: 10.3390/books978-3-03928-471-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2020-04-07 23:07:09
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Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.

Keywords

sentinel imagery --- above-ground biomass --- predictive mapping --- machine learning --- geographically weighted regression --- canopy cover (CC) --- spectral --- texture --- digital hemispherical photograph (DHP) --- random forest (RF) --- gray level co-occurrence matrix (GLCM) --- forest inventory --- LiDAR --- tall trees --- overstory trees --- tree mapping --- crown delineation --- aboveground biomass --- Landsat --- random forest --- topography --- human activity --- aboveground biomass estimation --- remote sensing --- crown density --- low-accuracy estimation --- model comparison --- old-growth forest --- multispectral satellite imagery --- random forest --- forest classification --- remote sensing --- forestry --- phenology --- silviculture --- forest growing stock volume (GSV) --- full polarimetric SAR --- subtropical forest --- topographic effects --- environment effects --- geographic information system --- support vector machine --- random forest --- ensemble model --- hazard mapping --- 3D tree modelling --- aboveground biomass estimation --- destructive sampling --- Guyana --- LiDAR --- local tree allometry --- model evaluation --- quantitative structural model --- Pinus massoniana --- specific leaf area --- leaf area --- terrestrial laser scanning --- voxelization --- forest canopy --- REDD+ --- Cameroon --- reference level --- deforestation --- agriculture --- forest baseline --- airborne laser scanning --- terrestrial laser scanning --- remote sensing --- REDD+ --- forestry

Modeling, Design and Optimization of Multiphase Systems in Minerals Processing

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ISBN: 9783039284009 9783039284016 Year: Pages: 232 DOI: 10.3390/books978-3-03928-401-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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Mineral processing deals with complex particle systems with two-, three- and more phases. The modeling and understanding of these systems are a challenge for research groups and a need for the industrial sector. This Special Issue aims to present new advances, methodologies, applications, and case studies of computer-aided analysis applied to multiphase systems in mineral processing. This includes aspects such as modeling, design, operation, optimization, uncertainty analysis, among other topics. The special issue contains a review article and eleven articles that cover different methodologies of modeling, design, optimization, and analysis in problems of adsorption, leaching, flotation, and magnetic separation, among others. Consequently, the topics covered are of interest to readers from academia and industry.

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

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2020 (13)

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