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The topic of this thesis is to study and compare local ranking methods applied to ensembles of trees with the aim to interpret each prediction of a model. This work contributes to the understanding of the ensembles of trees through the study of methods that locally identify the variables that are important for a prediction. The second contribution of the thesis is the further application of local ranking methods to the Gene Regulatory Network inference problem. The results of the local methods are compared with ground-truth data inferred from a simulator and their performances are compared to the state of the art method of that field.

local importance, MDA, MDI, SHAP, Saabas, GRN --- Ingénierie, informatique & technologie > Sciences informatiques

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Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research.

Research & information: general --- street view --- remote sensing --- urban environmental elements --- ensemble learning --- green view --- sky view --- building view --- SHAP --- convolutional neural network --- water body extraction --- GaoFen-1 --- multiple scales --- deep learning --- Line Simplification --- Douglas-Peucker Algorithm --- Monotonic Chain --- Dichotomy --- vegetation --- partial correlation analysis --- trend prediction --- the source region of the Yellow River --- revetment --- damage signature --- dense point clouds --- unmanned aerial vehicle (UAV) --- gradient operator --- OpenStreetMap (OSM) --- road network density --- urban economy --- regression analysis --- spatial metric --- pre-hospital emergency --- spatiotemporal demand --- GPS data --- seasonal clustering --- short-term forecast --- tourism flow forecast --- optimization algorithm --- Random Forest --- landslide hazard risk --- integrated multisource dataset --- field sample rasterization --- weight assignment --- urban forest --- forest biomass --- biomass distribution --- geographic detector --- poverty probability --- random forest --- nighttime lights --- spatiotemporal characteristics --- geographic information systems --- land cover --- land dynamics --- regional studies --- sustainable planning --- ultra-peripheral territories --- fire station --- fire risk evaluation --- parcel-pickup lockers --- site-suitability analysis --- GIS-based --- bivariate logistic regression model --- suitability classification --- n/a

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This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine.

Technology: general issues --- History of engineering & technology --- electrocardiogram --- deep metric learning --- k-nearest neighbors classifier --- premature ventricular contraction --- dimensionality reduction --- classifications --- Laplacian eigenmaps --- locality preserving projections --- compressed sensing --- convolutional neural network --- EEG --- epileptic seizure detection --- RISC-V --- ultra-low-power --- sepsis --- atrial fibrillation --- prediction --- heart rate variability --- feature extraction --- random forest --- annotations --- myoelectric prosthesis --- sEMG --- grasp phases analysis --- grasp classification --- machine learning --- electronic nose --- liver dysfunction --- cirrhosis --- semiconductor metal oxide gas sensor --- vagus nerve --- intraneural --- decoding --- intrafascicular --- recording --- carbon nanotube --- artificial intelligence --- lens-free shadow imaging technique --- cell-line analysis --- cell signal enhancement --- deep learning --- ECG signal --- reconstruction dictionaries --- projection matrices --- signal classifications --- osteopenia --- sarcopenia --- XAI --- SHAP --- IMU --- gait analysis --- sensors --- convolutional neural networks --- Parkinson’s disease --- biomedical monitoring --- accelerometer --- pressure sensor --- disease management --- electromyography --- correlation --- high blood pressure --- hypertension --- photoplethysmography --- electrocardiography --- calibration --- classification models --- COVID-19 --- ECG trace image --- transfer learning --- Convolutional Neural Networks (CNN) --- feature selection --- sympathetic activity (SNA) --- skin sympathetic nerve activity (SKNA) --- electrodes --- electrocardiogram (ECG) --- cardiac time interval --- dynamic time warping --- fiducial point detection --- heart failure --- seismocardiography --- wearable electroencephalography --- motor imagery --- motor execution --- beta rebound --- brain–machine interface --- EEG classification --- n/a --- Parkinson's disease --- brain-machine interface

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In recent years, the implementation of sustainable concrete systems has been a topic of great interest in the field of construction engineering worldwide, as a result of the large and rapid increase in carbon emissions and environmental problems resulting from traditional concrete production and industry. For example, the uses of supplementary cementitious materials, geopolymer binder, recycled aggregate and industrial/agricultural wastes in concrete are all approaches to building a sustainable concrete system. However, such materials have inherent flaws due to their variety of sources, and exhibit very different properties compared with traditional concrete. Therefore, they require specific modifications in preprocessing, design, and evaluation before use in concrete. This reprint, entitled “Advances in Sustainable Concrete System”, covers a broad range of advanced concrete research in environmentally friendly concretes, cost-effective admixtures, and waste recycling, specifically including the design methods, mechanical properties, durability, microstructure, various models, hydration mechanisms, and practical applications of solid wastes in concrete systems.

Technology: general issues --- History of engineering & technology --- Conservation of buildings & building materials --- high-strength concrete --- energy evolution --- elastic strain energy --- brittleness evaluation index --- concrete --- humidity --- moisture absorption --- moisture desorption --- numerical simulation --- acoustic emission --- AE rate process theory --- corrosion rate --- damage evolution --- axial load --- precast concrete structure --- lattice girder semi-precast slabs --- bending resistance --- FE modelling --- concrete damage --- GSP --- high strength --- hydration --- strength --- penetrability --- rice husk ash --- sustainable concrete --- artificial neural networks --- multiple linear regression --- eco-friendly concrete --- green concrete --- sustainable development --- artificial intelligence --- data science --- machine learning --- bagasse ash --- mechanical properties --- natural coarse aggregate --- recycled coarse aggregate --- two-stage concrete --- materials design --- recycled concrete --- crumb rubber concrete --- crumb rubber --- NaOH treatment --- lime treatment --- water treatment --- detergent treatment --- compressive strength --- materials --- adhesively-bonded joint --- temperature aging --- residual strength --- mechanical behavior --- failure criterion --- steel slag powder --- compound activator --- mortar strength --- orthogonal experiment --- GM (0, N) model --- ultrafine metakaolin --- silica fume --- durability --- fiber-reinforced concrete --- damage mechanism --- uniaxial tension --- cracked concrete --- crack width --- crack depth --- tortuosity --- sustainability --- concrete composites --- sulfate and acid attacks --- WPFT fibers --- coal gangue --- gradation --- cement content --- unconfined compressive strength --- freeze–thaw cycle --- minimum energy dissipation principle --- three-shear energy yield criterion --- damage variable --- constitutive model --- phosphorus slag --- limestone --- sulphate-corrosion resistance --- volume deformation --- blast furnace ferronickel slag --- alkali-activated material --- dosage of activator --- reactive powder concrete --- beam-column joint --- FE modeling --- crack --- cementitious gravel --- fly ash --- age --- optimal dosage --- bamboo --- sawdust --- pretreatment --- bio-based material --- mechanical property --- self-compacting concrete --- supplementary cementitious materials --- hydration mechanisms --- microstructure --- fresh properties --- synthetic polymer --- high temperature --- bentonite-free drilling fluid --- rheology --- filtration --- FRP reinforced concrete slab --- punching shear strength --- SHAP --- n/a --- freeze-thaw cycle

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In recent years, the implementation of sustainable concrete systems has been a topic of great interest in the field of construction engineering worldwide, as a result of the large and rapid increase in carbon emissions and environmental problems resulting from traditional concrete production and industry. For example, the uses of supplementary cementitious materials, geopolymer binder, recycled aggregate and industrial/agricultural wastes in concrete are all approaches to building a sustainable concrete system. However, such materials have inherent flaws due to their variety of sources, and exhibit very different properties compared with traditional concrete. Therefore, they require specific modifications in preprocessing, design, and evaluation before use in concrete. This reprint, entitled “Advances in Sustainable Concrete System”, covers a broad range of advanced concrete research in environmentally friendly concretes, cost-effective admixtures, and waste recycling, specifically including the design methods, mechanical properties, durability, microstructure, various models, hydration mechanisms, and practical applications of solid wastes in concrete systems.

high-strength concrete --- energy evolution --- elastic strain energy --- brittleness evaluation index --- concrete --- humidity --- moisture absorption --- moisture desorption --- numerical simulation --- acoustic emission --- AE rate process theory --- corrosion rate --- damage evolution --- axial load --- precast concrete structure --- lattice girder semi-precast slabs --- bending resistance --- FE modelling --- concrete damage --- GSP --- high strength --- hydration --- strength --- penetrability --- rice husk ash --- sustainable concrete --- artificial neural networks --- multiple linear regression --- eco-friendly concrete --- green concrete --- sustainable development --- artificial intelligence --- data science --- machine learning --- bagasse ash --- mechanical properties --- natural coarse aggregate --- recycled coarse aggregate --- two-stage concrete --- materials design --- recycled concrete --- crumb rubber concrete --- crumb rubber --- NaOH treatment --- lime treatment --- water treatment --- detergent treatment --- compressive strength --- materials --- adhesively-bonded joint --- temperature aging --- residual strength --- mechanical behavior --- failure criterion --- steel slag powder --- compound activator --- mortar strength --- orthogonal experiment --- GM (0, N) model --- ultrafine metakaolin --- silica fume --- durability --- fiber-reinforced concrete --- damage mechanism --- uniaxial tension --- cracked concrete --- crack width --- crack depth --- tortuosity --- sustainability --- concrete composites --- sulfate and acid attacks --- WPFT fibers --- coal gangue --- gradation --- cement content --- unconfined compressive strength --- freeze–thaw cycle --- minimum energy dissipation principle --- three-shear energy yield criterion --- damage variable --- constitutive model --- phosphorus slag --- limestone --- sulphate-corrosion resistance --- volume deformation --- blast furnace ferronickel slag --- alkali-activated material --- dosage of activator --- reactive powder concrete --- beam-column joint --- FE modeling --- crack --- cementitious gravel --- fly ash --- age --- optimal dosage --- bamboo --- sawdust --- pretreatment --- bio-based material --- mechanical property --- self-compacting concrete --- supplementary cementitious materials --- hydration mechanisms --- microstructure --- fresh properties --- synthetic polymer --- high temperature --- bentonite-free drilling fluid --- rheology --- filtration --- FRP reinforced concrete slab --- punching shear strength --- SHAP --- n/a --- freeze-thaw cycle