Search results: Found 4

Listing 1 - 4 of 4
Sort by
Process Modelling and Simulation

Authors: --- ---
ISBN: 9783039214556 / 9783039214563 Year: Pages: 298 DOI: 10.3390/books978-3-03921-456-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Keywords

process model validation --- partial least square regression --- phytochemicals --- natural extracts --- wheat germ --- fluidized bed drying --- mathematical model --- moisture content --- condensation --- simulation --- Pharmaceutical Processes --- Mammalian Cell Culture --- sensitivity analysis --- parameter estimation --- Design of Experiments --- algebraic modeling language --- dynamic optimization --- model predictive control --- moving horizon estimation --- fluid bed granulation --- heat and mass balance --- population balance model --- binder dissolution --- kernel development --- robust optimization --- uncertainty --- point estimation method --- equality constraints --- parameter correlation --- barley --- simulation --- hydration --- swelling --- cooking --- porridge --- extents --- graph theory --- model identification --- observability --- optimal clustering --- parameter estimation --- state decoupling --- data-mining --- machine learning --- neural networks --- chemistry --- materials --- engineering --- energy --- grey-box model --- machine learning --- SOS programming --- process modeling --- scrap dissolution --- scrap melting --- thermodynamics --- kinetics --- dynamic converter modelling --- Combined Heat and Power --- gray-box model --- utility management --- CHP legislation --- optimization --- polyacrylonitrile-based carbon fiber --- coagulation bath --- dry-jet wet spinning process --- computational fluid dynamics --- wave resonance --- maximum wave amplitude --- reactor coolant pump --- vane --- costing stopping --- mathematical model --- idling test --- n/a

Salinity Tolerance in Plants

Author:
ISBN: 9783039210268 / 9783039210275 Year: Pages: 422 DOI: 10.3390/books978-3-03921-027-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Biochemistry
Added to DOAB on : 2019-06-26 10:09:00
License:

Loading...
Export citation

Choose an application

Abstract

Salt stress is one of the most damaging abiotic stresses because most crop plants are susceptible to salinity to different degrees. According to the FAO, about 800 million Has of land are affected by salinity worldwide. Unfortunately, this situation will worsen in the context of climate change, where there will be an overall increase in temperature and a decrease in average annual rainfall worldwide. This Special Issue presents different research works and reviews on the response of plants to salinity, focused from different points of view: physiological, biochemical, and molecular levels. Although an important part of the studies on the response to salinity have been carried out with Arabidopsis plants, the use of other species with agronomic interest is also notable, including woody plants. Most of the conducted studies in this Special Issue were focused on the identification and characterization of candidate genes for salt tolerance in higher plants. This identification would provide valuable information about the molecular and genetic mechanisms involved in the salt tolerance response, and it also supplies important resources to breeding programs for salt tolerance in plants.

Keywords

Arabidopsis --- Brassica napus --- ion homeostasis --- melatonin --- NaCl stress --- nitric oxide --- redox homeostasis --- Chlamydomonas reinhardtii --- bZIP transcription factors --- salt stress --- transcriptional regulation --- photosynthesis --- lipid accumulation --- Apocyni Veneti Folium --- salt stress --- multiple bioactive constituents --- physiological changes --- multivariate statistical analysis --- banana (Musa acuminata L.) --- ROP --- genome-wide identification --- abiotic stress --- salt stress --- MaROP5g --- rice --- genome-wide association study --- salt stress --- germination --- natural variation --- Chlamydomonas reinhardtii --- salt stress --- transcriptome analysis --- impairment of photosynthesis --- underpinnings of salt stress responses --- chlorophyll fluorescence --- J8-1 plum line --- mandelonitrile --- Prunus domestica --- redox signalling --- salicylic acid --- salt-stress --- soluble nutrients --- Arabidopsis thaliana --- VOZ --- transcription factor --- salt stress --- transcriptional activator --- chlorophyll fluorescence --- lipid peroxidation --- Na+ --- photosynthesis --- photosystem --- RNA binding protein --- nucleolin --- salt stress --- photosynthesis --- light saturation point --- booting stage --- transcriptome --- grapevine --- salt stress --- ROS detoxification --- phytohormone --- transcription factors --- Arabidopsis --- CDPK --- ion homeostasis --- NMT --- ROS --- salt stress --- antioxidant enzymes --- Arabidopsis thaliana --- ascorbate cycle --- hydrogen peroxide --- reactive oxygen species --- salinity --- SnRK2 --- RNA-seq --- DEUs --- flax --- NaCl stress --- EST-SSR --- Salt stress --- Oryza sativa --- proteomics --- iTRAQ quantification --- cell membrane injury --- root activity --- antioxidant systems --- ion homeostasis --- melatonin --- salt stress --- signal pathway --- SsMAX2 --- Sapium sebiferum --- drought, osmotic stress --- salt stress --- redox homeostasis --- strigolactones --- ABA --- TGase --- photosynthesis --- salt stress --- polyamines --- cucumber --- abiotic stresses --- high salinity --- HKT1 --- halophytes --- glycophytes --- poplars (Populus) --- salt tolerance --- molecular mechanisms --- SOS --- ROS --- Capsicum annuum L. --- CaDHN5 --- salt stress --- osmotic stress --- dehydrin --- Gossypium arboretum --- salt tolerance --- single nucleotide polymorphisms --- association mapping. --- n/a

Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li

Authors: --- ---
ISBN: 9783038972709 Year: Volume: 1 Pages: 404 DOI: 10.3390/books978-3-03897-271-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-03-08 11:42:05
License:

Loading...
Export citation

Choose an application

Abstract

Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

Keywords

evapotranspiration --- Northeast China --- MS–PT algorithm --- spatial-temporal variations --- controlling factors --- potential evapotranspiration --- vegetation remote sensing --- reflectance model --- spectra --- leaf --- copper --- PROSPECT --- leaf area density --- terrestrial LiDAR --- tree canopy --- vertical structure --- voxel --- spatial representativeness --- heterogeneity --- validation --- land-surface temperature products (LSTs) --- observations --- HiWATER --- remote sensing --- spatiotemporal representative --- cost-efficient, sampling design --- heterogeneity --- validation --- FY-3C/MERSI --- GLASS --- Land surface temperature --- Land surface emissivity --- GPP --- SIF --- MuSyQ-GPP algorithm --- BEPS --- vegetation phenology --- Tibetan Plateau --- MODIS --- NDVI --- start of growing season (SOS) --- end of growing season (EOS) --- GLASS LAI time series --- forest disturbance --- disturbance index --- latent heat --- machine learning algorithms --- plant functional type --- high-resolution freeze/thaw --- AMSR2 --- MODIS --- LAI --- ZY-3 MUX --- GF-1 WFV --- HJ-1 CCD --- maize --- PROSPECT-5B+SAILH (PROSAIL) model --- spatial heterogeneity --- variability --- evapotranspiration --- land surface variables --- probability density function --- HiWATER --- spectral --- albedometer --- interference filter --- photoelectric detector --- validation --- land surface albedo --- multi-scale validation --- rugged terrain --- MRT-based model --- MCD43A3 C6 --- precipitation --- statistics methods --- China --- Tibetan Plateau --- South China’s --- drought --- SPI --- TMI data --- crop-growing regions --- downward shortwave radiation --- machine learning --- gradient boosting regression tree --- AVHRR --- CMA --- BRDF --- aerosol --- MODIS --- sunphotometer --- arid/semiarid --- solar-induced chlorophyll fluorescence --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- SCOPE --- Fraunhofer Line Discrimination (FLD) --- gross primary productivity (GPP) --- longwave upwelling radiation (LWUP) --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- surface radiation budget --- hybrid method --- remote sensing --- leaf age --- leaf spectral properties --- leaf area index --- Cunninghamia --- Chinese fir --- canopy reflectance --- NIR --- EVI2 --- geometric optical radiative transfer (GORT) model --- land surface albedo --- snow-free albedo --- rugged terrain --- topographic effects --- black-sky albedo (BSA) --- GPP --- NPP --- MODIS --- validation --- phenology --- RADARSAT-2 --- rice --- Synthetic Aperture Radar (SAR) --- decision tree --- forest canopy height --- aboveground biomass --- ICESat GLAS --- Landsat --- random forest model --- anisotropic reflectance --- BRDF --- rugged terrain --- solo slope --- composite slope --- surface solar irradiance --- geostationary satellite --- polar orbiting satellite --- LUT method --- SURFRAD --- downward shortwave radiation --- daily average value --- Antarctica --- sinusoidal method --- cloud fraction --- interpolation --- boreal forest --- GPP --- spatiotemporal distribution and variation --- meteorological factors --- phenological parameters --- multisource data fusion --- aerosol retrieval --- urban scale --- vegetation dust-retention --- multiple ecological factors --- geographical detector model --- snow cover --- passive microwave --- FY-3C/MWRI --- algorithmic assessment --- China --- land surface temperature --- satellite observations --- flux measurements --- latitudinal pattern --- land cover change --- fractional vegetation cover (FVC) --- multi-data set --- northern China --- spatio-temporal --- inter-annual variation --- uncertainty --- standard error of the mean --- downscaling --- GPP --- spatial heterogeneity --- remote sensing --- subpixel information --- LiDAR --- point cloud --- leaf --- gap fraction --- 3D reconstruction --- biodiversity --- remote sensing --- species richness --- metric comparison --- metric integration --- leaf area index --- MODIS products --- Landsat --- high resolution --- homogeneous and pure pixel filter --- pixel unmixing --- vertical vegetation stratification --- gross primary production (GPP) --- light use efficiency --- dense forest --- MODIS --- VPM --- temperature profiles --- humidity profiles --- n/a --- geometric-optical model --- thermal radiation directionality --- quantitative remote sensing inversion --- scale effects --- comprehensive field experiment

Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li

Authors: --- ---
ISBN: 9783038972761 Year: Volume: 2 Pages: 404 DOI: 10.3390/books978-3-03897-277-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-03-08 11:42:05
License:

Loading...
Export citation

Choose an application

Abstract

Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

Keywords

evapotranspiration --- Northeast China --- MS–PT algorithm --- spatial-temporal variations --- controlling factors --- potential evapotranspiration --- vegetation remote sensing --- reflectance model --- spectra --- leaf --- copper --- PROSPECT --- leaf area density --- terrestrial LiDAR --- tree canopy --- vertical structure --- voxel --- spatial representativeness --- heterogeneity --- validation --- land-surface temperature products (LSTs) --- observations --- HiWATER --- remote sensing --- spatiotemporal representative --- cost-efficient, sampling design --- heterogeneity --- validation --- FY-3C/MERSI --- GLASS --- Land surface temperature --- Land surface emissivity --- GPP --- SIF --- MuSyQ-GPP algorithm --- BEPS --- vegetation phenology --- Tibetan Plateau --- MODIS --- NDVI --- start of growing season (SOS) --- end of growing season (EOS) --- GLASS LAI time series --- forest disturbance --- disturbance index --- latent heat --- machine learning algorithms --- plant functional type --- high-resolution freeze/thaw --- AMSR2 --- MODIS --- LAI --- ZY-3 MUX --- GF-1 WFV --- HJ-1 CCD --- maize --- PROSPECT-5B+SAILH (PROSAIL) model --- spatial heterogeneity --- variability --- evapotranspiration --- land surface variables --- probability density function --- HiWATER --- spectral --- albedometer --- interference filter --- photoelectric detector --- validation --- land surface albedo --- multi-scale validation --- rugged terrain --- MRT-based model --- MCD43A3 C6 --- precipitation --- statistics methods --- China --- Tibetan Plateau --- South China’s --- drought --- SPI --- TMI data --- crop-growing regions --- downward shortwave radiation --- machine learning --- gradient boosting regression tree --- AVHRR --- CMA --- BRDF --- aerosol --- MODIS --- sunphotometer --- arid/semiarid --- solar-induced chlorophyll fluorescence --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- SCOPE --- Fraunhofer Line Discrimination (FLD) --- gross primary productivity (GPP) --- longwave upwelling radiation (LWUP) --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- surface radiation budget --- hybrid method --- remote sensing --- leaf age --- leaf spectral properties --- leaf area index --- Cunninghamia --- Chinese fir --- canopy reflectance --- NIR --- EVI2 --- geometric optical radiative transfer (GORT) model --- land surface albedo --- snow-free albedo --- rugged terrain --- topographic effects --- black-sky albedo (BSA) --- GPP --- NPP --- MODIS --- validation --- phenology --- RADARSAT-2 --- rice --- Synthetic Aperture Radar (SAR) --- decision tree --- forest canopy height --- aboveground biomass --- ICESat GLAS --- Landsat --- random forest model --- anisotropic reflectance --- BRDF --- rugged terrain --- solo slope --- composite slope --- surface solar irradiance --- geostationary satellite --- polar orbiting satellite --- LUT method --- SURFRAD --- downward shortwave radiation --- daily average value --- Antarctica --- sinusoidal method --- cloud fraction --- interpolation --- boreal forest --- GPP --- spatiotemporal distribution and variation --- meteorological factors --- phenological parameters --- multisource data fusion --- aerosol retrieval --- urban scale --- vegetation dust-retention --- multiple ecological factors --- geographical detector model --- snow cover --- passive microwave --- FY-3C/MWRI --- algorithmic assessment --- China --- land surface temperature --- satellite observations --- flux measurements --- latitudinal pattern --- land cover change --- fractional vegetation cover (FVC) --- multi-data set --- northern China --- spatio-temporal --- inter-annual variation --- uncertainty --- standard error of the mean --- downscaling --- GPP --- spatial heterogeneity --- remote sensing --- subpixel information --- LiDAR --- point cloud --- leaf --- gap fraction --- 3D reconstruction --- biodiversity --- remote sensing --- species richness --- metric comparison --- metric integration --- leaf area index --- MODIS products --- Landsat --- high resolution --- homogeneous and pure pixel filter --- pixel unmixing --- vertical vegetation stratification --- gross primary production (GPP) --- light use efficiency --- dense forest --- MODIS --- VPM --- temperature profiles --- humidity profiles --- n/a --- geometric-optical model --- thermal radiation directionality --- quantitative remote sensing inversion --- scale effects --- comprehensive field experiment

Listing 1 - 4 of 4
Sort by
Narrow your search

Publisher

MDPI - Multidisciplinary Digital Publishing Institute (4)


License

CC by-nc-nd (4)


Language

eng (4)


Year
From To Submit

2019 (4)