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  • Books  (588)
  • machine learning  (588)
  • MDPI - Multidisciplinary Digital Publishing Institute  (588)
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  • 1
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.
    Keywords: cluster analysis ; equity index networks ; machine learning ; copulas ; dependence structures ; quotient of random variables ; density functions ; distribution functions ; multi-factor model ; risk factors ; OLS and ridge regression model ; python ; chi-square test ; quantile ; VaR ; quadrangle ; CVaR ; conditional value-at-risk ; expected shortfall ; ES ; superquantile ; deviation ; risk ; error ; regret ; minimization ; CVaR estimation ; regression ; linear regression ; linear programming ; portfolio safeguard ; PSG ; equity option pricing ; factor models ; stochastic volatility ; jumps ; mathematics ; probability ; statistics ; finance ; applications ; investment home bias (IHB) ; bivariate first-degree stochastic dominance (BFSD) ; keeping up with the Joneses (KUJ) ; correlation loving (CL) ; return spillover ; volatility spillover ; optimal weights ; hedge ratios ; US financial crisis ; Chinese stock market crash ; stock price prediction ; auto-regressive integrated moving average ; artificial neural network ; stochastic process-geometric Brownian motion ; financial models ; firm performance ; causality tests ; leverage ; long-term debt ; capital structure ; shock spillover ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Language: English
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Commodity markets have evolved substantially since the early 2000s and have become more financialized. The recent cold war between the U.S.A. and China, the outbreak of COVID-19, and Russia's invasion of Ukraine have caused resource prices to soar, leading to greater volatility in the commodity markets. The volatility of the commodity markets has increased, and at the same time, financial markets such as the stock market, bond market, and foreign exchange market have become unstable. This has increased the linkage between the commodity and financial markets and has led to a great deal of attention being paid to the commodity markets by governments, companies, and investors.This reprint delves into recent developments in the commodity markets and elucidates the multifaceted factors that have shaped their trajectory. It examines how the interwoven dynamics of supply and demand, geopolitics, technology, and financialization have brought about a new era in commodity trading. By providing a comprehensive survey of these developments, we aim to provide insights that will help stakeholders successfully navigate the challenges and opportunities presented by this evolving landscape.
    Keywords: Russia and Ukraine conflict ; commodities ; G7 and BRIC markets ; TVP-VAR ; connectedness ; oil price uncertainty shocks ; international equity markets ; global vector autoregressive model ; arbitrage ; efficiency ; futures ; liquidity ; market integration ; platinum ; COVID-19 ; pandemic ; agriculture ; commodity ; MF-DFA ; high frequency ; asymmetric volatility spillover ; bitcoin ; altcoin ; cryptocurrency ; frequency connectedness ; Bitcoin ; machine learning ; random forest regression ; LSTM ; energy market volatility ; oil price dynamics ; fear index ; Markov-regime switching models ; volatility risk premium (VRP) ; implied and realized volatility ; oil and stock returns ; financialization ; Bermudan commodity options ; multi-layer perceptron ; multi-asset stochastic volatility model ; hybrid forecasting approaches ; two-step forecasting approaches ; gold ; euro ; sentiment analysis ; ARIMA ; wavelet transformation ; seasonal decomposition ; long short-term memory ; random forest ; eXtreme gradient boosting ; stock ; markets ; cycles ; investing ; risk ; returns ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Language: English
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.
    Keywords: fintech ; financial technology ; blockchain ; deep learning ; regtech ; environment ; social sciences ; machine learning ; learning analytics ; student field forecasting ; imbalanced datasets ; explainable machine learning ; intelligent tutoring system ; adversarial machine learning ; transfer learning ; cognitive bias ; stock market ; behavioural finance ; investor’s profile ; Teheran Stock Exchange ; unsupervised learning ; clustering ; big data frameworks ; fault tolerance ; stream processing systems ; distributed frameworks ; Spark ; Hadoop ; Storm ; Samza ; Flink ; comparative analysis ; a survey ; data science ; educational data mining ; supervised learning ; secondary education ; academic performance ; text-to-SQL ; natural language processing ; database ; machine translation ; medical image segmentation ; convolutional neural networks ; SE block ; U-net ; DeepLabV3plus ; cyber-security ; medical services ; cyber-attacks ; data communication ; distributed ledger ; identity management ; RAFT ; HL7 ; electronic health record ; Hyperledger Composer ; cybersecurity ; password security ; browser security ; social media ; ANOVA ; SPSS ; internet of things ; cloud computing ; computational models ; metaheuristics ; phishing detection ; website phishing ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Sports Medicine and Physical Fitness has been a successful Special Issue, which addressed novel topics in any subject related to sports medicine, physical fitness, and human movement. The article collection was able to positively evaluate three systematic reviews, nineteen original articles, and one brief report. These encompassed a broad range of topics ranging from accident kinematics, soccer monitoring, children’s physical evaluation, adapted physical activity, physical evaluation for people with intellectual disabilities, performance analysis in rowers, ultramarathon racers, karateka’s, rugby players, volleyball and basketball players, and cross-fit athletes, and also aspects related to biomechanics, fatigue and injury prevention in racing motorcycle riders, gymnasts, and cyclists.These scientific contributions within the field of Sports Medicine and Physical Fitness broaden the understanding of specific aspects of each analyzed discipline.It has been a pleasure for the Editorial Team to have served the International Journal Of Environmental Research and Public Health.
    Keywords: MotoGP ; video analysis ; collision ; accident ; safety ; disability ; tool ; health ; life span ; physical fitness ; reference values ; muscular strength profile ; quadriceps ; hamstring ; H/Q ratio ; total work ; sprint ; postactivation potentiation ; fixed seat rowing ; performance ; psychology ; odontology ; nutrition ; training ; stress ; running ; type 1 diabetes ; high-intensity interval training ; exercise ; VO2max ; anti-inflammatory ; machine learning ; PCA ; intensive training ; proprioception ; postural sway ; testing ; pacing ; cycling ; time trial ; RPE ; cognitive functions ; aging ; partnered dances ; fall prevention ; physical activity ; water polo ; biomechanics ; force-velocity relationship ; power-velocity relationship ; soccer ; match ; internal load ; external load ; fatigue ; young athletes ; cycling performance ; sport nutrition ; hydration ; PA ; MVPA ; accelerometer ; questionnaire ; children ; athlete ; high-intensity functional training ; cross-training ; functional fitness ; vitamin D ; explosive strength ; overload training ; wrist pain ; injury prevention ; overuse ; sitting position ; modified 505 test ; kinetic variables ; completion time ; foot contact ; predictors ; squat ; bench press ; strength ; speed ; interval training ; continuous training ; heart failure ; meta-analysis ; handgrip ; carpi radialis ; flexor digitorum superficialis ; neuromuscular fatigue ; motorcycle ; recovery ; spike jump ; block jump ; critical threshold ; specialization ; anaerobic power ; peak power ; HIFT, high-intensity functional training ; crossfit ; athletes ; field test ; hypertrophy ; katsu ; low-intensity training ; occlusive exercise ; sarcopenia ; diabetes type 1 ; HIIT ; sleep quality ; exercise motivation ; quality of life ; hypoxia ; hyperoxia ; hyperbaric breathing ; nitric oxide ; vascular reactions ; breathing ; extreme environments ; thema EDItEUR::W Lifestyle, Hobbies and Leisure
    Language: English
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: 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: QA75.5-76.95 ; T58.5-58.64 ; metadata ; image classification ; sensitivity analysis ; ROI detection ; residual learning ; image alignment ; adaptive convolutional kernels ; Hough transform ; class imbalance ; land surface temperature ; inundation mapping ; multiscale representation ; object-based ; convolutional neural networks ; scene classification ; morphological profiles ; hyperedge weight estimation ; hyperparameter sparse representation ; semantic segmentation ; vehicle classification ; flood ; Landsat imagery ; target detection ; multi-sensor ; building damage detection ; optimized kernel minimum noise fraction (OKMNF) ; sea-land segmentation ; nonlinear classification ; land use ; SAR imagery ; anti-noise transfer network ; sub-pixel change detection ; Radon transform ; segmentation ; remote sensing image retrieval ; TensorFlow ; convolutional neural network ; particle swarm optimization ; optical sensors ; machine learning ; mixed pixel ; optical remotely sensed images ; object-based image analysis ; very high resolution images ; single stream optimization ; ship detection ; ice concentration ; online learning ; manifold ranking ; dictionary learning ; urban surface water extraction ; saliency detection ; spatial attraction model (SAM) ; quality assessment ; Fuzzy-GA decision making system ; land cover change ; multi-view canonical correlation analysis ensemble ; land cover ; semantic labeling ; sparse representation ; dimensionality expansion ; speckle filters ; hyperspectral imagery ; fully convolutional network ; infrared image ; Siamese neural network ; Random Forests (RF) ; feature matching ; color matching ; geostationary satellite remote sensing image ; change feature analysis ; road detection ; deep learning ; aerial images ; image segmentation ; aerial image ; multi-sensor image matching ; HJ-1A/B CCD ; endmember extraction ; high resolution ; multi-scale clustering ; heterogeneous domain adaptation ; hard classification ; regional land cover ; hypergraph learning ; automatic cluster number determination ; dilated convolution ; MSER ; semi-supervised learning ; gate ; Synthetic Aperture Radar (SAR) ; downscaling ; conditional random fields ; urban heat island ; hyperspectral image ; remote sensing image correction ; skip connection ; ISPRS ; spatial distribution ; geo-referencing ; Support Vector Machine (SVM) ; very high resolution (VHR) satellite image ; classification ; ensemble learning ; synthetic aperture radar ; conservation ; convolutional neural network (CNN) ; THEOS ; visible light and infrared integrated camera ; vehicle localization ; structured sparsity ; texture analysis ; DSFATN ; CNN ; image registration ; UAV ; unsupervised classification ; SVMs ; SAR image ; fuzzy neural network ; dimensionality reduction ; GeoEye-1 ; feature extraction ; sub-pixel ; energy distribution optimizing ; saliency analysis ; deep convolutional neural networks ; sparse and low-rank graph ; hyperspectral remote sensing ; tensor low-rank approximation ; optimal transport ; SELF ; spatiotemporal context learning ; Modest AdaBoost ; topic modelling ; multi-seasonal ; Segment-Tree Filtering ; locality information ; GF-4 PMS ; image fusion ; wavelet transform ; hashing ; machine learning techniques ; satellite images ; climate change ; road segmentation ; remote sensing ; tensor sparse decomposition ; Convolutional Neural Network (CNN) ; multi-task learning ; deep salient feature ; speckle ; canonical correlation weighted voting ; fully convolutional network (FCN) ; despeckling ; multispectral imagery ; ratio images ; linear spectral unmixing ; hyperspectral image classification ; multispectral images ; high resolution image ; multi-objective ; convolution neural network ; transfer learning ; 1-dimensional (1-D) ; threshold stability ; Landsat ; kernel method ; phase congruency ; subpixel mapping (SPM) ; tensor ; MODIS ; GSHHG database ; compressive sensing ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Despite being one of the most popular sports worldwide, basketball has received limited research attention compared to other team sports. Establishing a strong evidence base with high-quality and impactful research is essential in enhancing decision-making processes to optimize player performance for basketball professionals. Consequently, the book entitled Improving Performance and Practice in Basketball provides a collection of novel research studies to increase the available evidence on various topics with strong translation to practice in basketball. The book includes work by 40 researchers from 16 institutions or professional organizations from 9 countries. In keeping with notable topics in basketball research, the book contains 2 reviews focused on monitoring strategies to detect player fatigue and considerations for travel in National Basketball Association players. In addition, 8 applied studies are also included in the book, focused on workload monitoring, game-related statistics, and the measurement of physical and skill attributes in basketball players. This book also has a strong focus on increasing the evidence available for female basketball players, who have traditionally been under-represented in the literature. The outcomes generated from this book should provide new insights to inform practice in many areas for professionals working in various roles with basketball teams.
    Keywords: GV557-1198.995 ; n/a ; talent selection ; classification tree ; Movement Assessment Battery for Children-2 ; NBA ; basketball ; maturation ; body composition ; fatigue ; countermovement jump ; athletic performance ; circadian rhythm ; injury ; basketball tactics ; female ; athlete ; non-linear analysis ; monitoring ; basketball performance ; performance analysis ; training load ; variability ; game-related statistics ; sleep ; youth athletes ; accelerometer ; women athletes ; fat free mass ; collegiate athletes ; workloads ; team sports ; machine learning ; microtechnology ; motor manual sequences ; elite sport ; attention ; visuo-spatial working memory ; playing position ; smallest worthwhile change ; body fat ; thema EDItEUR::V Health, Relationships and Personal development::VX Mind, body, spirit::VXH Complementary therapies, healing and health::VXHT Traditional medicine and herbal remedies
    Language: English
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
    Keywords: virtual power plant (VPP) ; power quality (PQ) ; global index ; distributed energy resources (DER) ; energy storage systems (ESS) ; power systems ; long-term assessment ; battery energy storage systems (BESS) ; smart grids ; conducted disturbances ; power quality ; supraharmonics ; 2–150 kHz ; Power Line Communications (PLC) ; intentional emission ; non-intentional emission ; mains signalling ; virtual power plant ; data mining ; clustering ; distributed energy resources ; energy storage systems ; short term conditions ; cluster analysis (CA) ; nonlinear loads ; harmonics, cancellation, and attenuation of harmonics ; waveform distortion ; THDi ; low-voltage networks ; optimization techniques ; different batteries ; off-grid microgrid ; integrated renewable energy system ; cluster analysis ; K-means ; agglomerative ; ANFIS ; fuzzy logic ; induction generator ; MPPT ; neural network ; renewable energy ; variable speed WECS ; wind energy conversion system ; wind energy ; frequency estimation ; spectrum interpolation ; power network disturbances ; COVID-19 ; time-varying reproduction number ; social distancing ; load profile ; demographic characteristic ; household energy consumption ; demand-side management ; energy management ; time series ; Hidden Markov Model ; short-term forecast ; sparse signal decomposition ; supervised dictionary learning ; dictionary impulsion ; singular value decomposition ; discrete cosine transform ; discrete Haar transform ; discrete wavelet transform ; transient stability assessment ; home energy management ; binary-coded genetic algorithms ; optimal power scheduling ; demand response ; Data Injection Attack ; machine learning ; critical infrastructure ; smart grid ; water treatment plant ; power system ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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  • 8
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; swarm-robotics ; drag-based system ; PID algorithm ; human–robot interaction ; behaviour dynamics ; state constraints ; fair optimisation ; micro mobile robot ; robot ; actuators ; high-gain observer ; turning model LIP ; space robot ; manipulation action sequences ; subgoal graphs ; remotely operated vehicle ; constrained motion ; joint limit avoidance ; curvilinear obstacle ; rehabilitation system ; stability criterion ; system design ; quad-tilt rotor ; iterative learning ; spiral curve ; cable detection ; SEA ; douglas–peuker polygonal approximation ; predictable trajectory planning ; ATEX ; obstacle avoidance system ; kinematic singularity ; collision avoidance ; biologically-inspired ; jumping robot ; differential wheeled robot ; design and modeling ; control efficacy ; robotics ; extremum-seeking ; object-oriented ; non-holonomic mobile robot ; magneto-rheological fluids ; rendezvous consensus ; altitude controller ; master-slave ; switching control ; deep reinforcement learning ; mechanism ; expansion logic strategy ; negative buoyancy ; action generation ; radial basis function neural networks ; unmanned aerial vehicles ; extend procedure ; glass façade cleaning robot ; convolutional neural network ; climbing robot ; micro air vehicle ; car-like kinematics ; variable speed ; machine learning ; dynamical model ; transportation ; geodesic ; unmanned surface vessel ; medical devices ; stopper ; extended state observer (ESO) ; high efficiency ; object mapping ; multi-objective optimization ; hybrid robot ; robot learning ; auto-tuning ; cable disturbance modeling ; manipulation planning ; pesticide application ; high-speed target ; sparse pose adjustment (SPA) ; service robot ; lumped parameter method ; Geometric Algebra ; dynamic coupling analysis ; Thau observer ; tri-tilt-rotor ; industrial robotic manipulator ; hardware-in-the-loop simulation ; robotic drilling ; muscle activities ; small size ; chameleon ; continuous hopping ; wall climbing robot ; hover mode ; 3D-SLAM ; curvature constraints ; PSO ; drilling end-effector ; Rodrigues parameters ; gait adaptation ; static environments ; position/force cooperative control ; snake-like robot ; shape-fitting ; powered exoskeleton ; input saturation ; kinematic identification ; methane ; human–machine interactive navigation ; q-learning ; path following ; hopping robot ; mobile manipulation ; high step-up ratio ; actuatorless ; monocular vision ; stability analysis ; compact driving unit ; snake robot ; non-holonomic robot ; curvature constraint ; phase-shifting ; dialytic elimination ; gesture recognition ; snake robots ; series elastic actuator ; flapping ; servo valve ; motion camouflage control ; biomimetic robot ; minimally invasive surgery robot ; centralized architecture ; trajectory planning ; computing time ; adaptive control law ; kinematics ; facial and gender recognition ; single actuator ; victim-detection ; shape memory alloys ; undiscovered sensor values ; discomfort ; Differential Evolution ; numerical evaluation ; quadruped robot ; coverage path planning ; localization ; MPC ; n/a ; fault diagnosis ; neural networks ; disturbance-rejection control ; sample gathering problem ; cart ; bio-inspired robot ; opposite angle-based exact cell decomposition ; optimization ; safety ; goal exchange ; hierarchical planning ; ocean current ; robot motion ; nonlinear differentiator ; mapping ; finite-time currents observer ; Newton iteration ; inverse kinematics ; deposition uniformity ; spatial pyramid pooling ; hierarchical path planning ; end effector ; head-raising ; fault recovery ; LOS ; path tracking ; non-inertial reference frame ; step climbing ; obstacle avoidance ; sliding mode control ; symmetrical adaptive variable impedance ; lane change ; quadcopter UAV ; singularity analysis ; biped mechanism ; fault-tolerant control ; dynamic neural networks ; mobile robots ; data association ; UAV ; enemy avoidance ; reinforcement learning ; grip optimization ; safety recovery mechanism ; exoskeleton ; dynamic environment ; uncertain environments ; hybrid bionic robot ; potential field ; robot navigation ; cleaning robot ; unmanned aerial vehicle ; non-singular fast-terminal sliding-mode control ; contact planning ; Lyapunov-like function ; piezoelectric actuator ; transition mode ; non-prehensile manipulation ; multiple mobile robots ; Tetris-inspired ; real-time action recognition ; integral line-of-sight ; topological map ; alpine ski ; target tracking ; closed-loop detection ; working efficiency ; mathematical modeling ; curve fitting ; force control ; biped robots ; NSGA-II ; mobile robot ; load carriage ; prescription map translation ; artificial fish swarm algorithm ; Q-networks ; self-reconfigurable robot ; G3-continuity ; autonomous vehicle ; loop closure detection ; excellent driver model ; robots ; graph representation ; regional growth ; target assignment ; evolutionary operators ; intelligent mobile robot ; motion sensor ; exploration ; droplets penetrability ; dynamic uncertainty ; simultaneous localization and mapping (SLAM) ; area decomposition ; multi-criteria decision making ; 4WS4WD vehicle ; biped climbing robots ; skiing robot ; ROS ; decision making ; smart materials ; centrifugal force ; missile control system ; formation of robots ; electro-rheological fluids ; pneumatics ; variable spray ; inertial measurement unit (IMU) ; Robot Operating System ; trajectory interpolation ; formation control ; immersion and invariance ; dragonfly ; parallel navigation ; harmonic potential field ; pallet transportation ; mobile robot navigation ; negative-buoyancy ; grip planning ; manipulator ; position control ; external disturbance ; legged robot ; passive skiing turn ; autonomous underwater vehicle (AUV) ; gait cycle ; path planning ; sliding mode observer ; dynamic gait ; self-learning ; polyomino tiling theory ; coalmine ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Robotics and control are both research and application domains that have been frequently engineered through the use of interdisciplinary approaches like cybernetics. Cognition is a particular concept of this approach, abstracted from the context of living organisms to that of artificial devices, and is concerned with knowledge acquisition and understanding through thought, experience, and the senses. Cognitive robotics and control refer to knowledge processing as much as knowledge generation from problem understanding, leading to special forms of architectures that enable systems to behave in an autonomous way. The main aim of this book is to highlight emerging applications and address recent breakthroughs in the domain of cognitive robotics and control and related areas. Procedures, algorithms, architectures, and implementations for reasoning, problem solving, or decision making are considered in the domain of robotics and control.
    Keywords: initial trajectory ; trajectory optimization ; Bézier surface ; robotics ; open FPGAs ; robot control ; surgical robotics ; human–machine interaction ; autonomous guidance ; low-cost platform ; FPGA ; S-curve ; motion control ; SoC ; telemanipulation ; haptics ; machine learning ; gesture recognition ; upper limb rehabilitation robot ; particle swam optimization (PSO) ; artificial bee colony (ABC) ; Ziegler Nichols ; Maximum sensitivity ; ontology ; robot task planning ; knowledge base ; knowledge representation ; industrial collaborative robots ; shared robotic tasks ; physical human–robot interaction ; human intention recognition ; time series classification ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: 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.
    Keywords: 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 ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNK Building construction and materials::TNKX Conservation of buildings and building materials
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