Search results: Found 11

Listing 1 - 10 of 11 << page
of 2
>>
Sort by
Mineral Fibres

Authors: --- --- ---
ISBN: 9783039211449 / 9783039211456 Year: Pages: 118 DOI: 10.3390/books978-3-03921-145-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-08-28 11:21:27
License:

Loading...
Export citation

Choose an application

Abstract

In the last decades, there has been increasing interest in Naturally Occurring Asbestos (NOA) and asbestos containing materials (ACMs) as a source of possible environmental risk. A crucial theme of interest related to environmental pollution is the enhanced mobilization of asbestos minerals affecting soils and rocks due to human activities (e.g., road construction, mining activity) in comparison with natural weathering processes. The volume has aimed to gather contributions and to compare results derived from various experiences of research groups regarding NOA minerals as a source of possible environmental risks for population. Case studies from various geological contexts are presented. Moreover, contributions presenting novel and classical approaches for ACM inertization and recycling, together with possible solutions for reducing asbestos exposure, has been also presented.

Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers

Author:
ISBN: 9783039212057 / 9783039212064 Year: Pages: 132 DOI: 10.3390/books978-3-03921-206-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Environmental Sciences
Added to DOAB on : 2019-12-09 16:10:12
License:

Loading...
Export citation

Choose an application

Abstract

In recent decades, there has been an increase in the development of strategies for water ecosystem mapping and monitoring. Overall, this is primarily due to legislative efforts to improve the quality of water bodies and oceans. Remote sensing has played a key role in the development of such approaches—from the use of drones for vegetation mapping to autonomous vessels for water quality monitoring. Within the specific context of vegetation characterization, the wide range of available observations—from satellite imagery to high-resolution drone aerial imagery—has enabled the development of monitoring and mapping strategies at multiple scales (e.g., micro- and mesoscales). This Special Issue, entitled “Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers”, collates recent advances in remote sensing-based methods applied to ocean, river, and lake vegetation characterization, including seaweed, kelp, submerged and emergent vegetation, and floating-leaf and free-floating plants. A total of six manuscripts have been compiled in this Special Issue, ranging from area mapping substrates in riverine environments to the identification of macroalgae in marine environments. The work presented leverages current state-of-the-art methods for aquatic vegetation monitoring and will spark further research within this field.

Brewing and Craft Beer

Author:
ISBN: 9783039214891 / 9783039214907 Year: Pages: 140 DOI: 10.3390/books978-3-03921-490-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Biochemistry
Added to DOAB on : 2019-12-09 16:10:12
License:

Loading...
Export citation

Choose an application

Abstract

Beer is a beverage with more than 8000 years of history, and the process of brewing has not changed much over the centuries. However, important technical advances have allowed us to produce beer in a more sophisticated and efficient way. The proliferation of specialty hop varieties has been behind the popularity of craft beers seen in the past few years around the world. Craft brewers interpret historic beer with unique styles. Craft beers are undergoing an unprecedented period of growth, and more than 150 beer styles are currently recognized. This Special Issue, Brewing and Craft Beer, comprises nine different works by researchers from five continents (North America, South America, Europe, Africa, and Oceania). This Special Issue reflects thus a broad perspective on the most important questions that concern the researchers in different parts of the world.

Cadmium Sources and Toxicity

Author:
ISBN: 9783038979845 / 9783038979852 Year: Pages: 130 DOI: 10.3390/books978-3-03897-985-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Public Health
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Cadmium (Cd) is an environmental toxicant of continuing public health concern worldwide, because total diet studies have shown that Cd is present in virtually all foodstuffs. Consequently, foods that are frequently consumed in large quantities, such as rice, potatoes, wheat, leafy salad vegetables, and other cereal crops, are the most significant dietary Cd sources. Moreover, Cd has chemical propensities that confer the potential to interfere with the physiological functions of calcium and zinc. Evidence of a wide range of diverse, toxic effects of Cd is increasingly apparent. In this collection, environmental Cd exposure is linked to an increased risk of chronic kidney disease that is known to be a cause of morbidity and mortality worldwide. Cd is also implicated in an early onset of menarche and deaths from cancer, especially in the uterus, kidney, and urinary tract. Moreover, Cd-induced kidney injury is replicated in Sprague Dawley rats, as is Cd-induced periodontal disease. Experimental studies suggest that the development of kidneys in fetuses and the function of insulin-producing cells may be adversely affected by Cd and that metformin, an anti-diabetic drug, is ineffective in Cd-intoxicated Wistar rats.

Image Processing Using FPGAs

Author:
ISBN: 9783038979180 / 9783038979197 Year: Pages: 204 DOI: 10.3390/books978-3-03897-919-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs.

Towards New Promising Discoveries for Lung Cancer Patients: A Selection of Papers from the First Joint Meeting on Lung Cancer of the FHU OncoAge (Nice, France) and the MD Anderson Cancer Center (Houston, TX, USA)

Authors: --- ---
ISBN: 9783039214518 / 9783039214525 Year: Pages: 230 DOI: 10.3390/books978-3-03921-452-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Oncology
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

This Special Issue of Cancers (Basel) is mainly dedicated to selecting papers from the talks given during the first Joint Meeting on Lung Cancer (JMLC) between the MD Anderson Cancer Center (Houston, Texas USA) and the Hospital University Federation (HUF) OncoAge (University Côte d’Azur, Nice, France) (Nice, September 2018). The central theme of JMLC is to discuss new advances and exchange ideas regarding lung cancer. Notably, the talks covered different topics on new therapeutic strategies (targeted therapy and immuno-oncology), molecular and cellular biology, biomarkers, and the epidemiology of lung cancer. Special attention was also given to lung cancer in elderly patients. The articles published in this Special Issue covered subjects such as the assessment of new biomarkers and new approaches for the early detection of lung cancer, epidemiological data, and emphasized a place for the newly characterized cellular pathways in lung cancer, which opens room for therapeutic perspectives for lung cancer patients.

Entropy in Image Analysis

Author:
ISBN: 9783039210923 / 9783039210930 Year: Pages: 456 DOI: 10.3390/books978-3-03921-093-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.

Keywords

image retrieval --- multi-feature fusion --- entropy --- relevance feedback --- chaotic system --- image encryption --- permutation-diffusion --- SHA-256 hash value --- dynamic index --- entropy --- keyframes --- Shannon’s entropy --- sign languages --- video summarization --- video skimming --- image encryption --- multiple-image encryption --- two-dimensional chaotic economic map --- security analysis --- image encryption --- chaotic cryptography --- cryptanalysis --- chosen-plaintext attack --- image information entropy --- blind image quality assessment (BIQA) --- information entropy, natural scene statistics (NSS) --- Weibull statistics --- discrete cosine transform (DCT) --- ultrasound --- hepatic steatosis --- Shannon entropy --- fatty liver --- metabolic syndrome --- multi-exposure image fusion --- texture information entropy --- adaptive selection --- patch structure decomposition --- image encryption --- time-delay --- random insertion --- information entropy --- chaotic map --- uncertainty assessment --- deep neural network --- random forest --- Shannon entropy --- positron emission tomography --- reconstruction --- field of experts --- additive manufacturing --- 3D prints --- 3D scanning --- image entropy --- depth maps --- surface quality assessment --- machine vision --- image analysis --- Arimoto entropy --- free-form deformations --- normalized divergence measure --- gradient distributions --- nonextensive entropy --- non-rigid registration --- pavement --- macrotexture --- 3-D digital imaging --- entropy --- decay trend --- discrete entropy --- infrared images --- low contrast --- multiscale top-hat transform --- image encryption --- DNA encoding --- chaotic cryptography --- cryptanalysis --- image privacy --- computer aided diagnostics --- colonoscopy --- Rényi entropies --- structural entropy --- spatial filling factor --- binary image --- Cantor set --- Hénon map --- Minkowski island --- prime-indexed primes --- Ramanujan primes --- Kapur’s entropy --- color image segmentation --- whale optimization algorithm --- differential evolution --- hybrid algorithm --- Otsu method --- image encryption --- dynamic filtering --- DNA computing --- 3D Latin cube --- permutation --- diffusion --- fuzzy entropy --- electromagnetic field optimization --- chaotic strategy --- color image segmentation --- multilevel thresholding --- contrast enhancement --- sigmoid --- Tsallis statistics --- q-exponential --- q-sigmoid --- q-Gaussian --- ultra-sound images --- person re-identification --- image analysis --- hash layer --- quantization loss --- Hamming distance --- cross-entropy loss --- image entropy --- Shannon entropy --- generalized entropies --- image processing --- image segmentation --- medical imaging --- remote sensing --- security

Marine Geomorphometry

Authors: --- ---
ISBN: 9783038979548 / 9783038979555 Year: Pages: 400 DOI: 10.3390/books978-3-03897-955-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:07
License:

Loading...
Export citation

Choose an application

Abstract

Geomorphometry is the science of quantitative terrain characterization and analysis, and has traditionally focused on the investigation of terrestrial and planetary landscapes. However, applications of marine geomorphometry have now moved beyond the simple adoption of techniques developed for terrestrial studies, driven by the rise in the acquisition of high-resolution seafloor data and by the availability of user-friendly spatial analytical tools. Considering that the seafloor represents 71% of the surface of our planet, this is an important step towards understanding the Earth in its entirety.This volume is the first one dedicated to marine applications of geomorphometry. It showcases studies addressing the five steps of geomorphometry: sampling a surface (e.g., the seafloor), generating a Digital Terrain Model (DTM) from samples, preprocessing the DTM for subsequent analyses (e.g., correcting for errors and artifacts), deriving terrain attributes and/or extracting terrain features from the DTM, and using and explaining those terrain attributes and features in a given context. Throughout these studies, authors address a range of challenges and issues associated with applying geomorphometric techniques to the complex marine environment, including issues related to spatial scale, data quality, and linking seafloor topography with physical, geological, biological, and ecological processes. As marine geomorphometry becomes increasingly recognized as a sub-discipline of geomorphometry, this volume brings together a collection of research articles that reflect the types of studies that are helping to chart the course for the future of marine geomorphometry.

Keywords

bedforms --- forage fish --- Pacific sand lance --- sediment habitats --- bathymetry --- currents --- seabed mapping --- marine geology --- submarine topography --- marine geomorphology --- terrain analysis --- multibeam echosounder --- bathymetry --- DEM --- satellite imagery --- multi beam echosounder --- filter --- geomorphology --- coral reefs --- Acoustic applications --- object segmentation --- seafloor --- underwater acoustics --- Cretaceous --- Cenomanian–Turonian --- paleobathymetry --- paleoclimate --- paleoceanography --- reconstruction --- simulation --- shelf-slope-rise --- geomorphometry --- GIS --- spatial scale --- spatial analysis --- terrain analysis --- seafloor geomorphometry --- domes --- volcanoes --- digital elevation models (DEMs) --- Canary Basin --- Atlantic Ocean --- cold-water coral --- carbonate mound --- habitat mapping --- spatial prediction --- image segmentation --- geographic object-based image analysis --- random forest --- accuracy --- confidence --- global bathymetry --- Seabed 2030 --- Nippon Foundation/GEBCO --- seafloor mapping technologies --- seafloor mapping standards and protocols --- benthic habitats --- shelf morphology --- eastern Brazilian shelf --- geomorphometry --- terrain analysis --- bathymetry --- surface roughness --- benthic habitat mapping --- python --- geomorphology --- submerged glacial bedforms --- deglaciation --- sedimentation --- multibeam --- acoustic-seismic profiling --- swath geometry --- multibeam spatial resolution --- integration artefacts --- Multibeam bathymetry --- benthic habitat mapping --- multiscale --- Random Forests --- pockmarks --- automated-mapping --- ArcGIS --- Glaciated Margin --- North Sea --- Malin Basin --- Barents Sea --- bathymetry --- thalwegs --- canyons --- Alaska --- Bering Sea --- multibeam sonar --- carbonate banks --- semi-automated mapping --- polychaete --- Northwestern Australia --- Oceanic Shoals Australian Marine Park --- Bonaparte Basin --- Timor Sea --- bathymetry --- digital terrain analysis --- geomorphometry --- geomorphology --- habitat mapping --- marine remote sensing

Processing-Structure-Property Relationships in Metals

Authors: ---
ISBN: 9783039217700 / 9783039217717 Year: Pages: 240 DOI: 10.3390/books978-3-03921-771-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 16:39:37
License:

Loading...
Export citation

Choose an application

Abstract

In the industrial manufacturing of metals, the achievement of products featuring desired characteristics always requires the control of process parameters in order to obtain a suitable microstructure. The strict relationship among process parameters, microstructure, and mechanical properties is a matter of interest in different areas, such as foundry, plastic forming, sintering, welding, etc., and regards both well-established and innovative processes. Nowadays, circular economy and sustainable technological development are dominant paradigms and impose an optimized use of resources, a lower energetic impact of industrial processes and new tasks for materials and products. In this frame, this Special Issue covers a broad range of research works and contains research and review papers.

Keywords

titanium composites --- in situ secondary phases --- microstructure --- inductive hot pressing --- intermetallic --- bainite rail --- tempering --- retained austenite --- tensile property --- impact toughness --- cryorolling --- reduction --- ultrafine grain --- secondary recrystallization --- high strength --- microstructure inhomogeneity --- non-monotonic simple shear strains --- shear strain reversal --- severe plastic deformation --- texture inhomogeneity --- tensile properties --- Mg-10Y-6Gd-1.5Zn-0.5Zr --- ultra-fine grain --- aging treatment --- precipitation behavior --- mechanical property --- multimodal --- AZ91 alloy --- equal channel angular pressing --- aging --- high pressure die casting --- aluminum alloy --- prediction model --- process monitoring --- static mechanical behavior --- fracture surface --- microstructure. --- casting --- Al 6061 alloys --- shrinkage --- porosity --- steering knuckles --- Al alloys --- warm working --- mechanical properties --- dental materials --- metal posts --- computer-aided design (CAD) --- image analysis --- mechanical properties --- finite element analysis --- additive manufacturing --- Al alloys --- wear --- cavitation erosion --- SEM --- microstructure --- high speed steel --- nanostructured coatings --- thin films --- FEGSEM --- tribology --- Nb tube --- caliber-rolling --- grain boundaries --- texture --- electron backscatter diffraction --- damping --- aluminum film --- grain boundary --- anelasticity --- thin aluminum sheet --- alloys --- aeronautic applications --- mechanical properties --- corrosion resistance --- EBM --- SEBM --- macro-instrumented indentation test --- property-microstructure-process relationship --- mechanical properties --- indentation hardness --- indentation modulus --- tensile properties --- Ti-6Al-4V alloy --- ?-platelet thickness --- columnar microstructure --- n/a

Learning to Understand Remote Sensing Images

Author:
ISBN: 9783038976844 / 9783038976851 Year: Volume: 1 Pages: 426 DOI: 10.3390/books978-3-03897-685-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Listing 1 - 10 of 11 << page
of 2
>>
Sort by
Narrow your search

Publisher

MDPI - Multidisciplinary Digital Publishing Institute (11)


License

CC by-nc-nd (11)


Language

eng (11)


Year
From To Submit

2019 (11)