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  • 1
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: Agricultural production management is facing a new era of intelligence and automation. With developments in sensor technologies, the temporal, spectral, and spatial resolution from ground/air/space platforms have been notably improved. Optical sensors play an essential role in agriculture production management. Specifically, monitoring plant health, growth conditions, and insect infestation has traditionally involved extensive fieldwork. We believe that sensors, artificial intelligence, and machine learning are not simply scientific experiments but opportunities to make our agricultural production management more efficient and cost-effective, further contributing to the healthy development of natural–human systems. This reprint compiles the latest research on optical sensors and machine learning in agricultural monitoring, including related topics: Machine learning approaches for crop health, growth, and yield monitoring; Combined multisource/multi-sensor data to improve the crop parameters mapping; Crop-related growth models, artificial intelligence models, algorithms, and precision management; Farmland environmental monitoring and management; Ground, air, and space platforms application in precision agriculture; Development and application of field robotics; High-throughput field information survey; Phenological monitoring.
    Keywords: soil moisture content ; spectral processing technology ; hyperspectral ; principal component analysis ; feature parameters extraction ; yield estimation ; rice ; unmanned aerial vehicle (UAV) ; tasseled cap transformation ; precision agriculture ; weed identification ; YOLOv4-Tiny ; attention mechanism ; multiscale detection ; angle normalization ; vegetation canopy reflectance ; geostationary satellite ; path length correction ; Minnaert model ; GOCI ; winter wheat ; LSTM ; LAI ; deep learning ; land use ; land cover ; classification ; random forest ; Sentinel data ; SRTM ; feature selection ; accuracy ; validation ; unmanned aerial vehicle ; soybean ; convolutional neural network ; multispectral imagery ; fusarium head blight ; texture indices ; machine learning ; cropland ; multi-seasonal ; fractal feature ; feature extraction ; accuracy evaluation ; black soil ; UAV ; chlorophyll ; fractional vegetation cover ; maturity monitoring ; anomaly detection ; smart agriculture ; detection of apple leaf diseases ; YOLOv5 ; transformer ; CBAM ; crop type classification ; multi-temporal ; remote sensing ; dairy cows ; body condition score ; 3D TOF sensor ; non-contact evaluation ; recognize area of interest ; sugarcane clones ; canopy cover ; light interception ; biomass ; cane yield ; peanut southern blight ; reflection spectrum ; spectral index ; continuous wavelet transform ; VGNet ; corn diseases ; leaf detection ; lightweight ; transfer learning ; agriculture ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Language: English
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The integration of information technologies with industry has marked the beginning of the fourth industrial revolution and promoted the development of industrial engineering. However, the depletion of resources and industrial waste caused by increasing amounts of industrial production pose a huge threat to nature. The application of sustainable supply chains in industrial engineering and management is one of the ways to balance the economy, society and environment. Therefore, it is a key concern for us to explore the construction of sustainable supply chains in industrial engineering and management. Moreover, to understand the impact of low-carbon, sustainable and recycled supply chains on industrial engineering, we need more in-depth investigations.This Special Issue aims to solicit original research and review articles discussing sustainable supply chain decision-making in industrial engineering and management to improve the sustainability of enterprise operations. Moreover, this Special Issue also shows mixed methods (e.g., modeling plus a case study) and rigorous quantitative/qualitative empirical studies of sustainable supply chains.
    Keywords: coordination degree model ; logistics industry ; digital economy ; industrial integration ; regional IEE system ; multimodel decision ; coupling coordination ; decision support methods ; online retailer ; consumer purchase behavior ; return strategy ; return insurance ; supply chain management ; real-time ; home delivery ; business modeling ; e-commerce ; time window ; lightweight ; carbon emissions ; low carbon benefits ; optimization design ; wheel hub ; subsidy policy ; remanufacturing industry ; donation strategy ; prisoner’s dilemma ; water-efficient products ; quality improvement ; DMAIC ; smart water closets ; carbon abatement ; cost sharing ; capital constraint ; environmental externality ; innovative products ; remanufacturing ; differential game ; bass model ; strategic emerging industries ; industrial structure ; employment effect ; artificial intelligence hardware ; data classification ; deep learning ; emission control ; industrial manufacturing ; bilateral matching decision making ; interval-valued hesitant fuzzy information ; bidirectional projection technology ; organizational quality-specific immunity ; automotive supply chain disruption ; supply chain resilience ; disruption risk ; bibliometric analysis ; co-citation analysis ; NGU ; self-attention ; CNN ; silver prediction ; data-driven ; composite systems ; synergy ; sustainability ; blockchain ; collection channel ; recycling strategies ; uncertain demand ; game theory ; federated learning ; intelligent manufacturing ; sustainable energy ; low-carbon strategy ; livestreaming marketing mode ; consumer low-carbon preference ; level of low-carbon promotion effort ; power structures ; 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
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: Biomedical sensors stand at the forefront of modern medical technologies, serving as indispensable components in diverse instruments and equipment. These sensors unravel the intricacies of biological processes and medical interventions. The recent surge in high-density sensor systems, characterized by arrangements in matrix arrays and other configurations, has ushered in a new era of functional evaluation. This spans electrophysiological activity, the metabolic responses of organs and tissues, and motor control analysis, all enriched with crucial spatial information. Functional mapping, a burgeoning approach in various biomedical techniques such as EEG, EMG, ECG, NIRS, and MEG, is proving to be transformative. Its integration enhances our comprehension of complex biological behaviors, where the precise spatial localization of sensing methodologies becomes paramount. The applications of functional mapping using biomedical sensors extend across multiple fields, including neuroscience, neuromuscular physiology, rehabilitation, and cardiology. Its utility ranges from diagnostic purposes to assessing the effectiveness of therapeutic interventions. The primary objective of this reprint was to collect papers that delineate the forefront of techniques, methods, and applications in the realm of biomedical sensors. Additionally, the focus extends to specific algorithms for data processing, ensuring a robust understanding of functional information intricately associated with spatial localization.
    Keywords: EMG ; EEG ; rehabilitation ; neuromotor ; evaluation ; assessment ; review ; machine learning ; biofeedback ; transfer learning ; random forest classifier ; COVID-19 ; intubation ; tracheoesophageal fistula ; tracheal lesions ; acute respiratory distress syndrome ; modeling ; intensive care unit ; muscle synergies ; whole body FES ; neurological patients ; photodynamic therapy ; fluorescence ; laser ; fluorophores ; enamel ; effective connectivity ; kurtosis ; resting-state connectivity ; stationarity ; sleep monitoring ; pressure bed sensor (PBS) ; unobtrusive measure ; multi-scale analysis ; sleep apnea–hypopnea syndrome (SAHS) ; shift-working ; optically detected magnetic resonance ; quantum magnetometer ; magnetoencephalography ; time domain ; functional near infrared spectroscopy ; diffuse optics ; brain ; hemodynamics ; resting-state brain oscillation ; mental workload ; signal processing ; reliability ; cognitive performance ; Simon task ; emotion detection ; valence ; arousal ; wearable sensors ; regression ; classification ; technology acceptance model ; rehabilitation exoskeletons ; therapists ; neuro-rehabilitation ; multiple linear regression ; Pearson’s correlation ; integrated sensor systems ; hand function ; hand osteoarthritis ; electromyography ; diagnosis ; discriminant analysis ; photoplethysmogram ; microcirculation ; deep learning ; convolutional neural network ; modelling ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: In the orthopedic surgical field, knee surgeries, including articular cartilage repair procedures, meniscus surgery, ligament reconstruction surgery, osteotomy surgery, and partial/total knee arthroplasty surgery, have made great advances over the last few decades. This Special Issue highlights and focuses on the surgical concepts and techniques, decision-making processes, perioperative management protocols, and clinical outcomes of the recent various advanced knee surgery procedures.
    Keywords: high tibial osteotomy ; TomoFix ; plate position ; anatomical conformity ; dual-energy CT ; Hounsfield unit ; bone mineral density ; volumetric phantomless BMD ; opportunistic CT ; orthopedic surgeon ; planning ; survey ; total knee arthroplasty ; unicompartmental knee arthroplasty ; anterior cruciate ligament ; reconstruction ; bone tunnel widening ; adjustable-loop device ; interference screw ; hamstring tendon ; autograft ; tibial component alignment ; radiographic references ; extramedullary system ; tranexamic acid ; clamping time ; transfusion ; estimated blood loss ; continuous cold flow therapy ; cryotherapy ; pain ; opioids consumption ; patient satisfaction ; bone marrow lesion ; knee ; meniscus ; root tear ; root repair ; femorotibial joint ; chondromalacia ; aging ; body mass index ; magnetic resonance imaging ; automated detection ; detection algorithm ; deep learning ; venous thromboembolism ; medial collateral ligament ; strain ; video extensometer ; medial opening-wedge high tibial osteotomy ; central sensitization ; patient-reported outcomes ; osteotomy site pain ; minimal clinically important difference ; human umbilical cord blood derived mesenchymal stem cells ; cartilage regeneration ; cartilage repair ; osteoarthritis treatment ; stem cell therapy ; Outerbridge ; degeneration ; spacer block ; intramedullary rod ; femorotibial congruence ; unicompartmental arthroplasty ; osteoarthritis ; cartilage ; stem cells ; umbilical cord blood ; femur fracture ; polyethylene insert ; osteoporosis ; multivariate logistic analysis ; atelocollagen ; microfracture ; ACIC ; bone marrow aspirate concentrate ; human umbilical cord blood-derived mesenchymal stem cells ; knee osteoarthritis ; loosening ; arthroplasty ; machine learning ; transfer learning ; review ; prosthesis ; meniscus root ; medial meniscus posterior root ; medial meniscus posterior root tear ; meniscus root repair ; transtibial pull-out repair ; bone tunnel enlargement ; anterior cruciate ligament reconstruction ; landmark ; lateral tibial spine ; anatomy ; bic Book Industry Communication::M Medicine
    Language: English
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: Oral cancer is a commonly occurring head and neck cancer, with 90% of cases diagnosed as oral squamous cell carcinoma (OSCC). Histologically, OSCC is derived from a multistep mechanism known as oral carcinogenesis, which progresses from normal epithelium to hyperplasia, followed by dysplasia and carcinoma in situ, and precedes the development of invasive squamous cell carcinoma. This multistep mechanism is characterized by mutations related to copy number alteration and epigenetic modifications. Precision medicine based on genomic profiling is also becoming more prevalent. It relies on the genetic information of individual patients or specific cancer cells and how their genes interact with each other and the environment. This method can potentially provide more effective treatment strategies as approaches can be customized for the specific genetic profiles of patients. Completing the TCGA HNSCC database has led to the development of new therapeutic approaches and targeted therapies. Lately, immune checkpoint inhibitors have been recognized as one of the standards of care in HNSCC. However, although treating invasive SCC is crucial, implementing prevention strategies to preclude malignant transformation has been useful in clinical management. Topics of interest for this Special Issue include, but are not limited to: Precision medicine, i.e., targeted therapies that inhibit oral carcinogenesis and tumorigenesis mechanisms; Combination of novel therapeutic approaches with standard-of-care regimens in OSCC; Biomarkers, i.e., predictive and prognostic markers for therapeutic approaches.
    Keywords: oral carcinogenesis ; oral tumorigenesis ; oral squamous cell carcinoma ; immune checkpoint inhibitor ; mutation ; biomarkers ; chemoradiation ; targeted therapies ; cisplatin ; preclinical models ; deep learning ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: The research field of data analysis and mining has attracted the interest of both academia and industry in recent years. This reprint contains 17 papers, which cover different topics of the broad research field of data analysis and mining. Each paper presents new data mining algorithms and techniques, as well as applications of data analysis and mining in real-world domains.
    Keywords: chi-square test ; constrained likelihood ratio test ; Fisher test ; gamma distribution ; uniformly most powerful test ; key interested frame ; commodity video ; clustering ; deep neural network ; frequent subtree ; parallel algorithms ; data partitioning ; load balancing ; trust inference ; trust propagation ; online social network ; social network analysis ; probabilistic graphical model ; message passing ; belief propagation ; model interpretability ; sequential rule mining ; non redundant sequential rules ; TRuleGrowth ; top-k non redundant rules ; closed sequential patterns ; multivariate time series ; deep spatiotemporal information ; down-sampling convolution ; attention ; graph neural network ; mobility patterns ; social media data ; artificial intelligence ; tourist clusters ; tourist flows ; forecasting ; univariate ; time series ; Python ; PSF ; spam detection ; deep learning ; semantic similarity ; social network security ; web analytics ; web log mining ; clickstream analysis ; sequence mining ; sequitur ; graph techniques ; feature subset selection ; data mining ; educational data mining ; machine learning ; metaheuristics ; artificial neural networks ; random decision forests ; posttraumatic stress disorder ; DSM-V ; emergency cesarean section ; elective cesarean section ; postpartum period ; text similarity calculation ; passage-level event connection graph ; vector tuning ; graph embedding ; meteorological data mining and machine learning ; class imbalance ; classification ; randomized undersampling ; SMOTE oversampling ; undersampling using temporal distances ; recommender systems ; session-based recommendations ; e-commerce ; data and web mining ; item co-occurrence ; graph data model ; next-item and next-basket recommendations ; graph-based recommendations ; purchase intent ; LSTM-RNN ; signal processing ; smart device ; electromagnetic field ; non-ionizing radiation protection ; SAR ; ANOVA ; data science ; selection ; constraint satisfaction ; preprocessing ; mobile technology ; statistics ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-01-08
    Description: Various classes of natural and synthetic molecules that can be classified as biomaterials find application in all fields of dentistry. Biomaterials should be biocompatible to minimise toxicity and bioactivity to ensure or simulate biological effects. They are used, for instance, to enhance antibacterial activity and improve the healing process. Calcium silicates, for illustration, are biomaterials used in endodontics that have proven their excellent biological, physico-chemical, and mechanical properties. However, some of these are considered too soluble, and this is almost completely due to their hardness when used as endodontic sealers, making endodontic retreatment very difficult. Despite manufacturers' best efforts, it is sometimes difficult to marry bioactivity, biocompatibility, and clinical benefits in a biomaterial; therefore, in this content, the work of researchers is invaluable.
    Keywords: calcium silicate cement ; retrograde materials ; premixed cement ; powder–liquid cement ; chemical composition ; EDX ; caries prevention ; anterior restorations ; ceramic ; dental veneers ; follow-up ; non-vital teeth ; porcelain laminate veneers ; vital teeth ; antimicrobial ; osseointegration ; surface modification ; tissue engineering ; root canal retreatment ; calcium silicate-based cement ; ProTaper Universal Retreatment ; D-Race ; dentin hypersensitivity ; desensitizing agents ; calcium phosphate ; hydroxyapatite ; nano-hydroxyapatite ; peri-implantitis ; periodontitis ; periapical radiograph ; deep learning ; neural networks ; image enhancement ; carious lesion activity ; irreversible pulpitis ; partial pulpotomy ; vital pulp therapy ; mineral trioxide aggregate ; furcation involvement ; image segmentation ; Gaussian high-pass filtering ; image preprocessing ; CNN ; calcium silicate material ; confocal laser scanning microscope ; deciduous tooth ; digital microscopy ; flowability ; micro-CT ; pulpectomy primary teeth ; root canal filling ; SEM ; zinc oxide eugenol ; bic Book Industry Communication::M Medicine
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  • 8
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management.
    Keywords: ANN ; roadside IoT sensors ; simulations of the gridded rainstorms ; 2D inundation simulation and real-time error correction ; weather types and features ; meteorological feature extraction ; artificial neural network ; self-organizing map (SOM) ; urban agriculture ; resource utilization efficiency ; urban northern Taiwan ; machine learning ; random forest ; regression analysis ; support vector machine ; threshold rainfall ; threshold runoff ; XGBoost ; stochastic rainfall generator ; Huff rainfall curve ; copula ; GeoAI ; artificial intelligence ; hydrological ; hydraulic ; fluvial ; water quality ; geomorphic ; modeling ; anomaly detection ; deep reinforcement learning ; telemetry water level ; time series ; ensemble ; multi-model ensemble ; precipitation ; forecasting ; persian gulf ; deep learning ; dam inflow ; RNN ; LSTM ; GRU ; hyperparameter ; rainfall time series ; artificial neural networks ; Multiple Linear Regression ; Chania ; CNN ; ELM ; temporary rivers ; hydrological extremes ; multivariate stochastic model ; autoregressive model ; Markov model ; daily temperature ; temperature generator ; Bayesian neural network ; forecasting uncertainty ; multi-step ahead forecasting ; probabilistic streamflow forecasting ; variational inference ; smart microclimate-control system (SMCS) ; system dynamics ; water–energy–food nexus ; agricultural resilience ; hydroinformatics ; hydrological modeling ; early warning ; uncertainty ; sustainability
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: The reprint focuses on the latest research in cybersecurity and data science. Digital transformation turns data into the new oil, so the increasing availability of big data, structured and unstructured datasets, raises new challenges in cybersecurity, efficient data processing and knowledge extraction. The field of cybersecurity and data science fuels the data-driven economy. Innovations in this field require strong foundations in mathematics, statistics, machine learning and information security. The unprecedented increase in the availability of data in many fields of science and technology (e.g., genomic data, data from industrial environments, network traffic, streaming media, sensory data of smart cities, and social network data) ask for new methods and solutions for data processing, information extraction and decision support. This stimulates the development of new methods of data analysis, including those adapted to the analysis of new data structures and the growing volume of data. The papers included in this reprint discuss various topics ranging from cyberattacks, steganography, anomaly detection, evaluation of the attacker skills, modelling of the threats, and wireless security evaluation, as well as artificial intelligence, machine learning, and deep learning. Given this diversity of topics the book represents a valuable reference for researchers in cybersecurity security and data science.
    Keywords: steganography ; network security ; steganography detection ; steganalysis ; machine learning ; big data ; IoT ; pattern mining ; wireless communications ; covert channel ; dirty constellation ; wireless postmodulation steganography ; phase drift ; drift correction modulation ; undetectability ; security ; quadrature amplitude modulation ; spam ; phishing ; classification ; augmented dataset ; multi-language emails ; cybersecurity ; data protection ; SoC ; threat agents ; motivation ; opportunity ; capability ; user profiling ; implicit ; modeling ; real-time user monitoring ; complexity threat agent ; threat assessment ; network traffic analysis ; convolutional neural networks ; network traffic images ; visualization of traffic ; classifiers ; e-mail ; ham ; data science ; datasets ; cyber threats modeling ; multi-agent systems ; cyber deception ; pseudorandom sequences generators ; prime numbers ; additive Fibonacci generator ; statistical characteristics ; android device ; BrainShield ; hybrid model ; malware detection ; Omnidroid ; image processing ; BOSS database ; ensemble classifier ; deep learning ; stegomalware ; traffic analysis ; network probe ; hash function ; SHA-3 ; FPGA ; cognitive security ; cyberattacks ; game software ; threat matrix computing ; evaluation function ; data modeling ; authentication ; bit template ; information-processing electronic device ; Poisson pulse sequences generators ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Modern materials and structures are significantly different from conventional ones. Their sizes can be orders of magnitude smaller, and their compositions are so sophisticated that traditional characteristic methods are inapplicable. Non-conventional methods are essential to tackle these issues, which must often be approached in an interdisciplinary fashion. This Special Issue is a collection of articles that shed light on these problems.
    Keywords: analytical solution ; Fourier cosine series ; vibrations ; FGM rectangular plates ; Mindlin plate theory ; phased array transducer ; transducer optimization ; beam focusing ; pulse–echo mode ; harmonic generation ; stress-free boundary ; total correction ; acoustic emission ; electrical resistance ; damage monitoring ; criticality ; natural time analysis ; nonlinear parameter ; noncontact reception ; air-coupled receiver ; aluminum samples ; corrections ; field theory ; deformation and fracture ; 7075 aluminum alloy ; electronic speckle pattern interferometry ; concrete beam ; bending ; cementitious matrix ; FRCM ; analytical model ; numerical model ; linear low-density polyethylene ; digital image correlation ; optical non-destructive testing ; speckle ; fourier scaling theorem ; gaussian filtering ; optical methods ; AlSi10Mg ; SLM ; NDE ; deep learning ; CNN ; k-fold cross validation ; non-destructive testing ; optical interferometry ; residual stress ; thermal expansion ; elasticity ; high entropy alloys ; complex concentrated alloys ; refractory metal intermetallic composites ; high entropy phases ; complex concentrated phases ; Nb silicide-based alloys ; alloy design ; biomechanics ; Achilles tendon ; beam-to-beam contact ; arbitrary cross-section ; ANCF ; lithium-ion batteries ; redox-active organic anode ; organic anode materials ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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  • 11
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Complex systems have long been an integral part of modern life and can be encountered everywhere. Undertaking a comprehensive study of such systems is a challenging problem, one which is impossible to solve without the use of contemporary mathematical modeling techniques. Mathematical models form the basis for the optimal design and control of complex systems. The present reprint contains all the articles accepted and published in the Special Issue of Mathematics entitled "Control, Optimization, and Mathematical Modeling of Complex Systems". This Special Issue is focused on recent theoretical and computational studies of complex systems modeling, control, and optimization. The topics addressed in this Special Issue cover a wide range of areas, including numerical simulation in physical, social, and life sciences; the modeling and analysis of complex systems based on mathematical methods and AI/ML approaches; control problems in robotics; design optimization of complex systems, modeling in economics and social sciences; stochastic models in physics and engineering; mathematical models in material science; and high-performance computing for mathematical modeling. It is our hope that the scientific results presented in this reprint will serve as valuable sources of documentation and inspiration to those seeking to delve into complex systems modeling, control, and optimization and examine their wide-ranging applications.
    Keywords: optimal control problem ; evolutionary computation ; robotics applications ; optimal control ; Lyapunov stability ; equilibrium point ; symbolic regression ; Pontryagin’s maximum principle ; continuous-time Markov chains ; ergodicity bounds ; discrete state space ; rate of convergence ; logarithmic norm ; interval analysis ; function approximation ; global optimization ; convexity evaluation ; overestimators ; underestimators ; machine learning control ; general synthesis problem ; evolutionary algorithm ; adaptive interpolation algorithm ; interval ordinary differential equations (ODEs) ; sparse grids ; hierarchical basis ; multidimensional interpolation ; high dimensions ; molecular dynamics modeling ; randomized maximum entropy estimation ; probability density functions ; Lagrange multipliers ; Lyapunov-type problems ; implicit function ; rotation of vector field ; asymptotic efficiency ; thermokarst lakes ; forecasting ; dynamical tracking target ; ship towing system ; relative curvature ; adaptive control ; discrete velocity method ; lattice Boltzmann method ; computational fluid dynamics ; mathematical modeling ; estimation ; minimax techniques ; pareto optimization ; regression analysis ; statistical uncertainty ; proton exchange membrane ; proton electrolyte membrane ; PEM ; fuel cell ; PEMFC ; power electronic converter ; DC–DC boost converter ; model predictive control ; MPC ; self-scalable robots ; modular robots ; origami structures ; complex system ; synergistic effect ; performance indicator ; structure change ; soft robotics ; continuum mechanisms ; modeling of complex systems ; kinematic model of soft robots ; mathematical modeling of complex systems ; non-linear models ; soft robotic neck ; tendon-driven actuators ; mathematical modelling ; modelling in economics ; impact of the COVID-19 ; logistics businesses ; fractional-order virus models ; stuxnet virus ; numerical computing ; supervisory control and data acquisition systems ; computer networks ; lyapunov analysis ; image segmentation ; remote sensing ; terrain identification ; data synthesis ; transfer learning ; controllability ; observability ; stochastic linear systems in finite and infinite dimensional spaces ; stochastic singular linear systems in finite and infinite dimensional spaces ; semigroup ; evolution operator ; GE-semigroup ; GE-evolution operator ; stochastic GE-evolution operator ; feature selection ; finite normal mixtures ; moving separation of mixtures ; deep LSTM ; neural network architectures ; deep learning ; turbulent plasma ; air–sea fluxes ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 12
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: Rapid developments have taken place over the recent years in the interventional cardiac electrophysiology. New methods and tools in the diagnosis and treatment of cardiac arrhythmia have emerged. There are many questions which still present a challenge, such as the ablation of refractory ventricular tachycardia, how to improve the long-term success rate of persistent atrial fibrillation, the long-term effectiveness and safety of His–Purkinje conduction system pacing. Accordingly, we dedicate this Special Issue Current Updates on Interventional Cardiac Electrophysiology to gathering the most recent progress in this field. Its aim is to present an overview of the current knowledge, latest evidence, and unresolved issues in this field. More specifically, the topics of interest include but are not limited to: atrial fibrillation; cryoablation; radiofrequency ablation; cardiac resynchronization therapy; His–Purkinje conduction system pacing; stereotactic radiotherapy for refractory ventricular tachycardia; pulsed electric field ablation; leadless pacemakers; and implantable cardioverter-defibrillators.
    Keywords: atrial fibrillation ; catheter ablation ; left atrial appendage occlusion ; stereotactic body radiotherapy ; refractory ventricular tachycardia ; treatment ; ablation ; elderly patients ; younger patients ; outcomes ; deep learning ; convolution neural network ; paroxysmal supraventricular tachycardia ; electrocardiography ; detection ; syncope ; vasovagal syncope ; ganglionated plexus ; high-frequency stimulation ; atrial fibrillation (AF) ; vein of Marshall (VOM) ; ethanol infusion ; coronary sinus (CS) ; coronary sinus ostium (CSo) ; cardiac implantable electronic device infection ; pocket infection ; antimicrobial therapy ; risk factors ; preventive strategies ; ventricular arrhythmias ; electrocardiogram ; algorithm ; left ventricular outflow tract ; COVID-19 pandemic ; interventional therapy ; percutaneous left atrial appendage occlusion ; pharmacotherapy ; amiodarone ; arrhythmogenic right ventricular cardiomyopathy ; abnormal electrograms ; ventricular tachycardia ; iatrogenic atrial septal defect ; intracardiac echocardiography ; left atrial appendage closure ; right-to-left shunt ; vein of Marshall ; collateral circulation ; slow injection ; paroxysmal atrial fibrillation ; high-power ; short-duration ; radiofrequency ablation ; ablation index ; pulmonary vein reconnection ; non-pulmonary vein triggers ; peri-device leak ; cardiac computed tomography angiography ; leadless single-chamber pacemaker ; complication ; atrioventricular synchrony ; leadless dual-chamber pacemaker ; strategy selection ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBG Medical equipment & techniques
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  • 13
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
    Keywords: tropical cyclone detection ; meteorological satellite images ; deep learning ; deep transfer learning ; generative adversarial networks ; image target detection ; multiple scales ; any angle object ; remote sensing of small objects ; point clouds ; 3D tracking ; state estimation ; Siamese network ; deep LK ; convolutional neural networks (CNNs) ; multilayer feature aggregation ; attention mechanism ; remote sensing image scene classification (RSISC) ; hyperspectral image classification ; variational autoencoder ; generative adversarial network ; crossed spatial and spectral interactions ; crater detection algorithm (CDA) ; R-FCN ; self-calibrated convolution ; split attention mechanism ; transfer learning ; remote sensing ; oriented object detection ; rotated inscribed ellipse ; remote sensing images ; keypoint-based detection ; gated aggregation ; eccentricity-wise ; object detection ; remote sensing image ; anchor free ; oriented bounding boxes ; deformable convolution ; three-dimensional radar imaging ; convolution neural network ; super-resolution ; side-lobe suppression ; terahertz radar ; aerial image generation ; satellite image generation ; structure map ; style vector ; high resolution image ; self-constructing graph ; semantic segmentation ; GAN ; image generation ; data augmentation ; remote sensing disaster image ; convolutional neural network ; double-stream structure ; feedback ; encoder–decoder network ; dense connections ; instance segmentation ; Swin transformer ; cascade mask R-CNN ; remote sensing image retrieval ; hashing algorithm ; binary code ; triplet ordinal relation preserving ; cross entropy ; feature distillation ; forest fire ; smoke segmentation ; Smoke-Unet ; residual block ; Landsat-8 ; band sensibility ; unsupervised domain adaptation ; bidirectional domain adaptation ; image-to-image translation ; generative adversarial networks (GANs) ; U-Net ; high-density laser scanning ; logging trails ; digital surface model ; canopy height model ; commercial thinning ; convolutional neural networks ; multiview ; satellite and UAV image ; joint description ; image matching ; neural network ; contextual information ; Anchor Free Region Proposal Network ; polar representation ; 3D object detection ; point cloud ; sampling ; single-stage ; rotated object detection ; angle-based detector ; angle-free framework ; rotated region of interests (RRoIs) ; representative points ; plastic ; UAVs ; contrastive learning ; mutual guidance ; spatial misalignment ; vehicle detection ; ANN ; automatic classification ; risk mitigation ; machine learning ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 14
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: This reprint focusses on Smartness, a multidisciplinary topic, which is examined from four perspectives: Sensors, IoT, and Data Generation; Data and Information Processing; Actuation; and Digital Systems and Infrastructure. We see smartness in the way sensing is embedded in a system, the way data and information are processed, how a system interacts internally and with its environment, and whether a system is ubiquitous or limited by space (cloud-based or edge-enabled). This reprint contains a total of 14 chapters, which are grouped according to their areas of application: mobility and transportation, healthcare, industrial environments, and other urban infrastructures. This book covers a range of topics, including mobility; healthcare; image analysis; permeable pavements; solid-waste management; sensor node and gateway architectures; cloud, fog, and edge computing; air-quality monitoring; thermal anomalies and smart helmets in industrial environments; smart airports; smart districts; smart travel choices; sensor cities; artificially intelligent cities; platform urbanism; and more.
    Keywords: artificial intelligence (AI) ; artificially intelligent city ; artificially intelligence commons ; smart city ; smart urban technology ; urban informatics ; sustainable urban development ; climate change ; pandemics ; natural disasters ; sensor city ; City 4.0 ; smart urbanism ; smart governance ; disruptive urban transition ; Internet-of-Things (IoT) ; technology giants ; sensors ; transit ; bus ; transfer ; smart card ; spatial analysis ; mode choice ; internet of everything (IoE) ; 6th generation (6G) networks ; artificial intelligence ; Distributed AI as a Service (DAIaaS) ; fog computing ; edge computing ; cloud computing ; smart airport ; smart districts ; PPE ; OHS ; risk detection ; naive Bayes ; support vector machine ; convolutional neural network ; deep learning ; microcontroller ; edge-fog-cloud computing ; Internet of Things ; robotics ; autonomous driving ; image registration ; smart sensor ; real time big data ; land-use ; air quality ; particulate matter (PM10 PM2.5) ; Intelligent Transportation Systems ; functional requirements ; machine learning ; model actionability ; model evaluation ; cloud server ; customized sensor node ; customized gateway ; FLoRa simulation ; LoRa range radio ; solid waste management ; smart cities ; big data ; event detection ; road traffic ; distributed machine learning ; automatic labeling ; social media ; data analytics ; social media analytics ; Arabic tweets ; 3D microstructure reconstruction ; permeable pavement ; generative adversarial networks ; tiny AI ; tiny ML ; distributed AI as a service (DAIaaS) ; skin disease diagnosis ; healthcare ; smart societies ; smart healthcare ; reference architecture ; TensorFlow ; visually impaired ; smart mobility ; LiDAR ; ultrasonic ; obstacle detection ; obstacle recognition ; assistive tools ; green computing ; sustainability ; Arduino Uno ; smart app ; 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
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  • 15
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: This reprint contains several articles where the molecular mechanisms and structural changes in target proteins on interaction with various viruses and bacteria were studied. In addition, drug-protein interactions, drug–drug interaction mechanisms, anti-Glycating, antioxidant, binding affinity, network pharmacology-driven investigations, and targeted anticancer treatments were also investigated.
    Keywords: RSV ; ectodomain G protein ; heparan sulfate ; protein–ligand interaction ; fluorescence quenching ; molecular docking ; molecular dynamic simulation ; quercetin ; CCL4 ; neurotoxicity ; VirtualToxLab ; oxidative stress markers ; Huperzine A ; molecular dynamics simulation ; fluorescence spectroscopy ; human serum albumin ; neurodegenerative disorders ; drug–protein interactions ; erlotinib ; bovine serum albumin ; binding interaction ; competition ; hepatitis E virus ; methyltransferase ; protein stability ; enzyme assay ; garlic ; antioxidant ; anti-glycation ; glycation ; AGEs ; HSA ; quetiapine ; hydrophobic interaction ; thermodynamic parameters ; seproxetine ; antidepressant ; charge transfer ; π-acceptors ; DFT ; haloperidol ; antipsychotics ; keratoconus ; MMP-2 ; MMP-9 ; molecular dynamics ; MM-GBSA calculations ; pharmacophore mapping ; α-amylase ; advanced glycation end-products ; caffeic acid ; coumaric acid ; coronary artery disease ; phytotherapy ; network pharmacology ; angiogenesis ; zebrafish ; dynamics molecular docking ; NEK7 ; virtual screening ; DFTs ; deep learning ; drug design ; drug repurposing ; structural-based ; cancer ; A. aspera ; β-amyrin ; C. gigantea ; C. procera ; GC-MS ; Minimum inhibitory concentration (MIC) ; Molecular docking ; MD simulations ; Tuberculosis (TB) ; n/a ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MM Other branches of medicine::MMG Pharmacology
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  • 16
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint includes impactful chapters related to document-image related visual sensing, which do present and comprehensively discuss selected scientific concepts, frameworks, architectures and ideas on sensing technologies and machine-learning techniques. Indeed, document imaging/scanning approaches are essential techniques for digitalizing documents in various real-world contexts. This reprint emerging from the Special Issue "Document-Image Related Visual Sensors and Machine Learning Techniques” can be viewed as a result of the crucial need for document management systems. Such technologies are being applied in various fields or different domains and parts of the world to address relevant challenges that could not be addressed without the advances made in these technologies. The reprint includes impactful chapters that present scientific concepts, frameworks, architectures and innovative ideas on sensing technologies and machine-learning techniques to overcome a series of key challenges related to document imaging/scanning, text detection, text recognition, and documents clustering.
    Keywords: feature learning ; incomplete multimedia data ; fuzzy c-means ; variational autoencoder ; multispectral imaging ; document scanning ; portable sensor ; depth image filtering ; point clouds filtering ; Kinect v2 ; depth resolution ; close range ; hand pose ; image binarization ; optical character recognition ; document images ; local thresholding ; image pre-processing ; natural images ; scene text recognition ; visual sensor ; text position correction ; encoder-decoder network ; chart recognition ; deep learning ; visualization ; classification ; detection ; perspective correction ; house architecture type classification ; house type classification ; convolutional neural networks ; document classification ; feature selection ; data augmentation ; imbalanced dataset ; scene text detection ; multiple scales ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
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  • 17
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This Special Issue explores empirical studies of emotional mechanisms, qualitative and quantitative measurements of emotion, the recognition of emotional contexts, and the application of emotion. We introduce fourteen papers, ranging from lab-based studies aimed at understanding emotional mechanisms to applying emotion recognition in the real world (e.g., in driving, games, education, and virtual avatars). This Special Issue explores empirical studies of emotional mechanisms, qualitative and quantitative measurements of emotion, the recognition of emotional contexts, and the application of emotion. We introduce fourteen papers, ranging from lab-based studies aimed at understanding emotional mechanisms to applying emotion recognition in the real world (e.g., in driving, games, education, and virtual avatars).
    Keywords: speech emotion recognition ; domain adaptation ; SER generalization ; Korean Emotional Speech Database ; ensemble model ; multi-path ; group-loss ; BLSTM network ; facial micromovement ; emotion recognition ; emotion authenticity ; HRV parameter ; game addiction ; League of Legends ; stress response ; sensitivity ; specificity ; logistic regression ; facial action unit ; facial aging ; facial expression ; posed emotion ; virtual avatar ; virtual human ; virtual character ; embodied conversational agent ; social interaction ; empathy ; CNN ; cognitive workload ; functional connectivity analysis ; LSTM ; mental workload ; mutual information ; phase locking value ; phase transfer entropy ; deep learning ; facial expression recognition (FER) ; 3D convolutional neural network (3D CNN) ; multirate signal processing ; minimum overlapped frame structure ; self-attention ; multi-depth network ; video content empathy ; micro-movement synchronization ; non-contact empathy measurement ; empathic advertisement ; multimodal affective computing ; catecholamines ; emotion classification ; wearable devices ; deep neural networks ; multispectral imaging ; face recognition ; in the wild ; driver emotion recognition ; multimodal ; self-report ; real-world driving ; EEG ; learning emotions ; attention ; convolutional neural network ; multi-channel band features ; eye movement ; brain connectivity ; review ; human emotions ; affective and physiological states ; Plutchik’s wheel of emotions ; sensors ; methods and applications ; statistical and multiple criteria analysis ; country success and publications maps of the world ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 18
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: After almost two decades of continuous development in bio, circular, and green economy, the time is ripe for the assessment of the major achievements and challenges that private and public enterprises face today to further enhance these global sustainability concepts. Due to the central role of political incentives for the development and implementation of environmentally friendly and sustainable practices, the present book project focuses on the nexus between public policies, institutions, quality of public sector management, and patterns of interaction between government and private businesses in backing bio, green, and circular economy practices and eco-innovation. In addition, the project also accommodates surveys that elaborate on the differences between the implementation of new organizational forms and scientific innovations in technologically advanced and developing settings.
    Keywords: energy demand ; renewable energy ; biomass ; energy policies ; organizational factors ; healthcare waste management practices ; public hospitals ; Libya ; consumers ; cluster analysis ; sustainable consumption ; mass media ; social media ; green hydrogen ; green hydrogen value chain ; developing countries ; renewable energy sources ; hydrogen strategy ; scaling ; upscaling ; scaling innovation ; innovation diffusion ; innovation ; systematic literature review ; garbage sorting ; urban garbage disposal ; rural garbage disposal ; willingness ; family life ; neighbourhood ; COVID-19 ; Pakistan economy ; economic scale ; Keynesian theory ; mitigation ; economic revival measures ; innovations ; renewable power ; rebound effect ; low-carbon economy ; carbon pricing policy ; border carbon tax ; Sino–US trade friction ; export grab effect ; firm innovation ; GDP prediction ; feature selection ; deep learning ; temporal convolutional network ; organizational sustainability ; social and economic sustainability ; knowledge sharing ; organizational agility ; organizational behavior ; sustainable organizations ; economic sustainability ; consumer experience ; sustainable commerce ; online consumer behaviour ; e-commerce platform ; online purchase intention ; online customer engagement ; energy security ; energy policy ; energy resources ; sustainability ; bibliometrics ; circular business model ; open business model ; sharing economy ; circular economy ; peer-to-peer ; electricity trading ; green product ; green consumer behavior ; environmental responsibility ; environmental concern ; green purchasing decisions ; green business ; consumption dimension ; production dimension ; financial dimension ; technological dimension ; fundraising campaigns ; social networking sites ; NPO ; humanitarian response ; Kuwait ; Bahrain ; Guatemala ; forest ; property rights ; community concession ; entrepreneurship ; forest sustainability ; economic development ; free-market environmentalism ; Latin America ; consumption coupons ; purchase probability ; inventory optimization ; minimum-cost maximum-flow ; bioeconomy ; green growth ; eco-innovation ; environmental Kuznets curve ; EKC ; environmental economics and policy ; ecological economics ; resource management ; sustainable development ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 19
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: The use of telemedicine and mobile devices is growing, and sensors might aid in creating creative solutions. Developing these solutions is crucial for monitoring senior citizens, lifestyles, and medical procedures. This Special Issue’s goal was to bring together academics and professionals in healthcare and medicine interested in using information and communication technologies (ICT) to serve people with special needs. The development of assistive technology for various users to follow sports and other activities is strongly tied to this study area. Data protection is crucial, and the development of these solutions for medical uses should be verified. The security and privacy of the information may be tied to other recognized research projects for their acceptability. ICT research has considerably improved quality of life and has fully assimilated all citizens into society through medical rehabilitation and assistive technology. The technologies and research fields that influence medical informatics include databases, networking, graphical user interfaces, data mining, machine learning, intelligent decision support systems, and specialized programming languages. Because mobile devices are commonly used for several everyday chores and are equipped with sensors that monitor various physical and physiological indicators, it is crucial to encourage the development of m-Health and e-Health solutions for healthcare practitioners. In this area, several solutions are now being developed. In addition, they can collaborate with emerging technologies for social assistance while enhancing life quality.
    Keywords: data privacy ; taxonomy ; IoT ; COVID-19 ; mobile application ; accelerometer sensor ; stand-up time ; total time ; aging ; linear-map convolutional neural network ; direct acyclic graph ; action recognition ; spatial feature ; temporal feature ; frailty ; home monitoring ; user-centered design ; usability ; user experience ; acceptance ; activity recognition ; Internet of Things ; smart house ; deep learning ; channel state information ; glaucoma screening ; retinal images ; segmentation ; classification ; precision nutrition ; food plans ; machine learning ; food logging ; Eight Hop Test ; systematic review ; measurement ; sensors ; diseases ; wrist-wearable device ; PPG processing ; physiological parameters ; web-based applications ; data analysis ; elderly monitoring ; successful aging ; gerontechnology ; AAL ; healthcare ; prevalidation ; deployment ; chronic heart failure ; large-scale pilot ; H2020 ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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  • 20
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Each year, natural hazards, such as earthquakes, landslides, avalanches, tsunamis, floods, wildfires, severe storms, and drought, , affect humans worldwide, resulting in deaths, suffering, and economic losses. According to insurance broker Aon, 2010–2019 was the worst decade on record for economic losses due to disasters triggered by natural hazards, amounting to USD 3 trillion, which is USD 1 trillion more than for the period of 2000–2009. In 2019, the economic losses from disasters caused by natural hazards were estimated at over USD 200 billion (UNDRR Annual Report, 2019). In this context, remote sensing shows high potential to provide valuable information, at various spatial and temporal scales, concerning natural processes and their associated risks. The recent advances in remote sensing technologies and analysis, in terms of sensors, platforms, and techniques, are strongly contributing to the development of natural hazards research. With this Special Issue titled “Remote Sensing for Natural Hazards Assessment and Control”, we proposed state-of-the-art research that specifically addresses multiple aspects on the use of remote sensing (RS) for Natural Hazards (NH). The aim was therefore to collect innovative methodologies, expertise, and capabilities to detect, assess, monitor, and model natural hazards. The present Special Issue of Remote Sensing encompasses 18 open access papers presenting scientific studies based on the exploitation of a broad range of RS data and techniques, as well as focusing on a well-assorted sample of NH types.
    Keywords: wildfires ; hillslope erosion ; satellite imagery ; rainfall erosivity ; RUSLE ; rockfall source areas ; identification ; relief ; slope angle ; rock mass strength ; rockfall susceptibility ; land subsidence ; Geographic Information System (GIS) ; InSAR ; machine learning algorithm ; meta-heuristics ; Iran ; k-Nearest Neighbor ; Random Forest ; fires ; Landsat 8 ; Sentinel 2 ; Terra ; ASTER ; MODIS ; burned ; mapping ; hazard chain ; turbidity ; suspended sediment detection ; extreme climate events ; tailing dam risk management ; spatiotemporal pattern mining ; El Niño ; remote sensing ; geographic information system ; flash floods ; visual analysis ; SAR offset tracking ; glacier surface velocity ; glacier instability ; glacier hazards ; ice avalanches ; ENSO ; glacier mass balance ; glacier surface energy ; earthquake ; coseismic effects ; field line resonance ; acoustic gravity waves ; lithosphere-magnetosphere coupling ; burnt area monitoring ; Australia ; Sydney ; wildfire ; earth observation ; mid-resolution sensors ; time series analysis ; burn severity ; climate zones ; deep learning ; PRISMA ; burned area ; Sentinel-2 ; morphological operator ; convolutional neural network ; casualty prediction ; importance assessment ; spatial division ; support vector regression ; digital image correlation ; phase correlation ; optical flow ; time series image stack ; landslides ; ground motion identification ; displacement mapping ; UAS ; risk assessment ; random forest ; DInSAR ; Yan’an city ; settlement prediction ; reclaimed land ; exponential model ; Asaoka method ; wide-area deformation ; deformation detection ; time-series InSAR ; stacking ; Turpan–Hami basin ; heavy rainfall ; shallow landslides ; TRIGRS model ; spatial distribution ; susceptibility assessment ; Longchuan County ; Guangdong Province ; MT-InSAR ; ground deformation monitoring ; Sentinel-1A/B ; image partition ; block adjustment ; Gaofen-2 ; Interferometric synthetic aperture radar (InSAR) ; freeze–thaw processes ; permafrost ; Qilian Mountains ; natural hazards ; hazard ; vulnerability ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
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  • 21
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Transportation is one of the most crucial aspects across the world, supporting the daily life of human beings and the sustainable development of the whole of society. Generally, meteorology causes various impacts on transportation operation, safety and efficiency. In the context of global warming, increasing numbers of extreme weather and climate events (such as fog, icy roads, and extreme winds) have been detected worldwide and are expected to occur more frequently in the future. Meanwhile, extreme events, such as dense fog, rainstorm, and blizzard, tend to damage transportation and traffic facilities (such as express ways, port, airport, and high-speed railway) and induce serious traffic blocks and accidents. In recent decades, concentrated and continuous efforts have been made to carry out meteorological analyses regardless of urban traffic or transportation conditions, including those of highways, shipping, aviation, etc. A number of methods and techniques have been intensively developed to promote the qualities of both observations and forecasts. More recently, state-of-the-art machine learning frameworks have also been widely introduced into studies regarding transportation meteorology and many other fields.
    Keywords: transportation meteorology ; pavement temperature prediction ; deep learning ; BiLSTM ; attention mechanisms ; winter icing ; air pollution ; traffic vitality ; built environment ; spatial correlation ; spatial lag model ; phone signaling data ; air quality ; behavioral habits ; activity density ; population distribution ; land use mix ; wind forecast ; error decomposition ; bias ; distribution ; sequence ; urban meteorology ; observation ; forecast ; early warning ; review ; China ; low-level wind shear ; ensemble learning classifiers ; Bayesian optimization ; SHapley Additive exPlanations ; wind shear ; go-around ; machine learning ; dynamic ensemble selection ; civil aviation safety ; pilot reports ; self-paced ensemble ; Shapley additive explanations ; climate change ; climatology ; sea ice ; marginal sea ; East Asia ; time-series modeling ; pavement temperature ; nowcasting ; variation characteristics ; forecast validation ; relative humidity ; microwave radiometer data ; total rainfall ; precipitation duration ; vertical distribution ; Beijing–Tianjin–Hebei region ; rail breakage ; frequency ; high-speed railway ; Siberian high ; teleconnection ; temperature ; Qinling mountains ; rainfall ; change characteristics ; geographical factors ; highways ; road blockage ; fuzzy analytic hierarchy process ; CRITIC weight assignment method ; road network vulnerability ; spatiotemporal distribution ; precipitation forecast ; ConvLSTM ; PredRNN ; expressway ; agglomerate fog ; risk level prediction of fog-related accidents ; meteorological conditions ; road hidden dangers ; traffic flow conditions ; visibility ; Yellow Sea and Bohai Sea ; observation data ; 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::TR Transport technology and trades
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  • 22
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: At present, data is constantly generated across various industries, including the internet. New technologies have emerged to trace data origins and assess their potential for collection, quantification, decoding, and analysis. Big data, signals, and images are of particular importance due to the wealth of domain-specific information they hold. These data play a critical role in addressing issues like national security, cybersecurity, marketing, medical informatics, and fraud detection. Deep learning techniques have gained immense popularity. They empower the analysis and understanding of vast amounts of unsupervised data, making them invaluable for processing when raw data lack categorization and labels. These applications extend to working with medical images and signal processing for wellness devices, remote monitoring, and neural devices. In industrial settings, data can be used for early warning systems in assembly lines, while massive datasets can be derived from electronic health records and hospital information systems, for example. This reprint is dedicated to exploring the application of deep learning in tackling significant challenges related to big data, images, and signals. It seeks to unravel the potential of these cutting-edge technologies in addressing complex real-world problems across diverse sectors.
    Keywords: big data ; image processing ; deep learning ; signal processing ; digital era ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 23
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports.
    Keywords: heterogeneous transformation ; SAR image ; optical image ; conditional generative adversarial nets (CGANs) ; self-supervised ; synthetic aperture radar (SAR) ; despeckling ; enhanced U-Net ; video synthetic aperture radar (Video-SAR) ; moving target tracking ; guided anchor Siamese network (GASN) ; interferometric synthetic aperture radar ; deep convolutional neural network ; phase unwrapping ; unsupervised change detection ; polarimetric synthetic aperture radar (PolSAR) ; UAVSAR ; multi-scale shallow block ; multi-scale residual block ; synthetic aperture radar ; image registration ; transformer ; deep learning ; SAR target detection ; multiscale learning ; ship detection ; SAR ship detection ; position-enhanced attention ; lightweight backbone ; image augmentation ; building extraction ; SAR ; semantic segmentation ; SAR dataset ; single-stage detector ; two-stage detector ; anchor free ; train from scratch ; oriented bounding box ; multi-scale detection ; computer vision ; low-grade road extraction ; remote sensing ; image segmentation ; optical images ; scene classification ; on-board ; lightweight self-supervised algorithm ; synthetic aperture radar (SAR) image ; arbitrary-oriented ship detection ; differentiable rotational IoU algorithm ; triangle distance IoU loss ; attention-weighted feature pyramid network ; multiple skip-scale connections ; attention-weighted feature fusion ; Rotated-SARShip dataset (RSSD) ; object classification ; radar image reconstruction ; convolutional neural networks ; ResNet18 ; GBSAR ; Omega-K algorithm ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 24
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-07-14
    Description: Advancements in medical imaging modalities have resulted in increasing the importance and demand of pediatric radiology. This reprint showcases various examples of advanced research in pediatric radiology and nuclear medicine. These include the use of medical imaging modalities such as computed tomography, general radiography, magnetic resonance imaging, positron emission tomography, single-photon emission computed tomography, and ultrasound for diagnosis, as well as the performance of artificial intelligence (AI) in computer-aided detection and diagnosis in the pediatric population. The radiation dose issue of pediatric radiological examinations and emerging AI technology for dose reduction, as well as the use of three-dimensional printing based on medical images for pediatric surgical planning, healthcare professional education, and patient–clinician communication are also covered.
    Keywords: as low as reasonably achievable ; computed tomography ; convolutional neural network ; deep learning ; dose reduction ; generative adversarial network ; image processing ; machine learning ; medical imaging ; noise ; contrast-enhanced ultrasound ; head ultrasound ; brain death ; infants ; ancillary test ; child ; paediatric ; infant ; adolescent ; chest X-ray ; CXR ; chest radiography ; COVID-19 ; SARS-CoV-2 ; coronavirus ; biliary atresia ; ultrasonography ; diagnostic accuracy ; intraoperative cholangiography (IOC) ; diagnostic performance ; elastography ; three-dimensional printing ; congenital heart disease ; children ; model ; personalized medicine ; application ; confusion matrix ; disease identification ; image interpretation ; pneumonia ; artificial intelligence (AI) ; deep learning (DL) ; paediatric pneumonia ; chest radiograph ; computer-aided detection (CAD) ; cumulative ; radiation dose ; acute tonsillitis ; shear wave elastography ; stiffness ; pediatric ; magnetic resonance imaging ; infection ; neck ; emergency medicine ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MM Other branches of medicine::MMG Pharmacology
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  • 25
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
    Keywords: tropical cyclone detection ; meteorological satellite images ; deep learning ; deep transfer learning ; generative adversarial networks ; image target detection ; multiple scales ; any angle object ; remote sensing of small objects ; point clouds ; 3D tracking ; state estimation ; Siamese network ; deep LK ; convolutional neural networks (CNNs) ; multilayer feature aggregation ; attention mechanism ; remote sensing image scene classification (RSISC) ; hyperspectral image classification ; variational autoencoder ; generative adversarial network ; crossed spatial and spectral interactions ; crater detection algorithm (CDA) ; R-FCN ; self-calibrated convolution ; split attention mechanism ; transfer learning ; remote sensing ; oriented object detection ; rotated inscribed ellipse ; remote sensing images ; keypoint-based detection ; gated aggregation ; eccentricity-wise ; object detection ; remote sensing image ; anchor free ; oriented bounding boxes ; deformable convolution ; three-dimensional radar imaging ; convolution neural network ; super-resolution ; side-lobe suppression ; terahertz radar ; aerial image generation ; satellite image generation ; structure map ; style vector ; high resolution image ; self-constructing graph ; semantic segmentation ; GAN ; image generation ; data augmentation ; remote sensing disaster image ; convolutional neural network ; double-stream structure ; feedback ; encoder–decoder network ; dense connections ; instance segmentation ; Swin transformer ; cascade mask R-CNN ; remote sensing image retrieval ; hashing algorithm ; binary code ; triplet ordinal relation preserving ; cross entropy ; feature distillation ; forest fire ; smoke segmentation ; Smoke-Unet ; residual block ; Landsat-8 ; band sensibility ; unsupervised domain adaptation ; bidirectional domain adaptation ; image-to-image translation ; generative adversarial networks (GANs) ; U-Net ; high-density laser scanning ; logging trails ; digital surface model ; canopy height model ; commercial thinning ; convolutional neural networks ; multiview ; satellite and UAV image ; joint description ; image matching ; neural network ; contextual information ; Anchor Free Region Proposal Network ; polar representation ; 3D object detection ; point cloud ; sampling ; single-stage ; rotated object detection ; angle-based detector ; angle-free framework ; rotated region of interests (RRoIs) ; representative points ; plastic ; UAVs ; contrastive learning ; mutual guidance ; spatial misalignment ; vehicle detection ; ANN ; automatic classification ; risk mitigation ; machine learning ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 26
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications.
    Keywords: incremental power and timing optimization ; Lagrangian relaxation ; gate sizing ; multimode multicorner ; physical optimization ; two-qubit states ; quantum computers ; quantum gates ; Rabi oscillations ; single qubit quantum computer ; quantum operations simulation ; vision transformers ; computer vision ; deep learning ; artistic style recognition ; memristor model ; tantalum oxide ; memory crossbar ; nonlinear dopant drift ; window function ; LTSPICE library memristor model ; stochastic computing ; stochastic filtering ; stochastic FIR filter ; unconventional computing ; electrical masking ; interconnection delay ; Single Event Multiple Transients ; Soft Error Rate ; STA ; TCAD ; timing-masking ; transient faults ; IoT ; wireless sensor networks ; hydroponics ; smart agriculture ; Network-on-Chip ; bufferless routing ; 3D NoC ; Markov chains ; visible light communication (VLC) ; wireless communication ; analog front end (AFE) ; pre-amplification ; classification ; COVID-19 ; lightweight neural network ; medical imaging ; chest X-rays ; image sensors ; 3D pixels ; 3D sequential integration ; 3DSI ; monolithic 3D ; M3D ; coupling ; parasitic capacitances ; memristor ; emulator ; analog design ; switched capacitor ; mixed signal ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 27
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: This Special Issue on advanced sensor technologies contains contributions on the latest developments in mobile robotic systems and related research. Various topics with different ideas and applications from mobile robotics have found their place. New ideas are presented for mobile robots that specialise in cleaning floors, power lines and HVAC systems. We also find innovative approaches for navigation path planning using local minima-free potential fields, novel path primitives and/or their parameterisation for minimum-time planning, and various control approaches ranging from visual serving to model predictive and adaptive trajectory tracking, applied to wheeled robots, humanoid manipulators and flying robots. Localisation approaches using LiDAR, motion capture systems, fingerprint-based and biomechanical gait systems are also discussed. In addition to advances in methodology, applications in healthcare, mining tunnels, cleaning, warehouses and other areas are mentioned.
    Keywords: UAVs ; inspection and maintenance ; mobile robots ; insulators ; artificial intelligence ; mobile cleaning robot ; vibration source classification ; predictive maintenance ; deep learning ; 1D CNN ; defect detection ; Faster R-CNN ; object detection ; IoRT ; inspection robot ; navigation ; model predictive control ; path planing ; warehouse automation ; underground mining robots ; scan matching ; localization and SLAM in tunnels ; 2D lidar navigation ; GPS-denied environment ; robot navigation ; path planning ; potential field ; bilinear interpolation ; dynamic local re-planning ; domestic dirt ; dirt dataset ; audit robot ; cleaning benchmark ; dirt classification ; robot-aided cleaning auditing ; geometrical feature ; cleaning auditing ; swarm algorithms ; motion trajectory prediction ; kinematical models ; gait biomechanics ; spherical robot ; model ; simulation ; CoppeliaSim (V-REP) ; visual servoing ; autonomous landing ; monocular vision ; aerial robotics ; localization and SLAM ; 3D lidar ; range sensing ; Uniform Second-Order Sliding Mode Observer ; Prescribed Performance Control ; robot manipulators ; finite-time Stability ; feature detection ; light-weight mapping ; B-splines ; localization ; mobile robot ; complete coverage ; path smoothing ; velocity profile optimization ; humanoid robot ; state estimation ; motion capture ; Whole-Body Control ; ADHD ; screening ; skeleton ; position estimation ; indoor positioning ; sensor fusion ; RSSI ; magnetometer ; fingerprint ; wheeled mobile robots ; trajectory generation ; velocity profile ; trajectory optimization ; Bézier curves ; 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
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: The reliability of high-voltage equipment is critical to the safe operation of the power grid. This reprint focuses on the new developments and advances in both fundamental and applied research on the testing, monitoring, and diagnostics of high-voltage equipment, including insulators, transformers, etc.
    Keywords: HV bushing ; dielectric response ; paper–oil insulation ; temperature distribution ; distribution transformers ; failure analysis ; monitoring ; diagnostic method ; frequency response ; open and short-circuit response ; hydro-generators ; partial discharges ; PD Spectral Pulse Counting Map (PD-SPCM) ; microstrip antenna ; UHF method ; Frequency Resolved Partial Discharges (FRPD) ; AC breakdown characteristics ; arresters ; lightning protection insulator ; electric field calculation ; icing conditions ; cable insulation ; contact surface ; dielectric breakdown ; electrical breakdown ; polymeric insulation ; solid–solid interface ; surface roughness ; insulator ; deicing ; hot water jet ; numerical calculation ; temperature spatial distribution ; pollution insulators ; nonsoluble deposit density ; flashover characteristics ; arc parameters ; high voltage apparatus ; deep learning ; classification ; localization ; partial discharge ; faults ; outdoor insulators ; railway electrification system ; outdoor porcelain insulators ; low-frequency flashover AC voltage ; lightning impulse critical-flashover voltage ; icing ; anti-icing ; de-icing transmission lines ; ice-melting ; icing disaster ; diameter-expanded conductor ; current transferred ; 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
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: Non-destructive testing and evaluation are commonly referred to as the vast group of analysis techniques used in civil, medical, and industrial sectors to evaluate the properties of materials, tissues, components, or structures, without causing any damage. Automation offers many benefits for non-destructive testing to cope with increasing demands, including improved reliability and higher inspection speeds. Additionally, robots enable inspections in locations that are not easily accessible to human operators and allow for humans to be removed from potentially dangerous environments. However, the perceived complexity and high costs have limited the adoption of automation. As a result, the full potential that could be derived from the seamless integration of robotic platforms with sensors, actuators, and software has not been fully explored; it could still revolutionise the way that automated inspections are performed and conceived. The recent advancements in electronics, robotics, sensor technology and software pave the way for new developments in automated testing and data-driven autonomous robotic inspections in several sectors. This Special Issue aimed to attract the latest research outcomes in the field of robotic sensing. Five papers relate to inspection systems based on robotic fixed-base manipulators, three of which are associated with in-process inspection in manufacturing applications (robotic wire-arc welding and additive manufacturing). Four papers report research advancements in mobile robotic-enabled sensing.
    Keywords: wall-climbing robot ; passive adaptive mechanism ; magnetic circuit optimization ; flexible detection method ; welding robot ; seam tracking ; laser sensor ; feature point extracting ; complex welding seam ; UAVs ; inspection ; soft robotics ; non-destructive evaluation ; robotic NDE ; robotic welding ; robotic control ; in-process NDE ; ultrasonic NDE ; ultrasound ; image motion analysis ; image processing ; optical flow ; underwater robotic ; NDT ; free-form surface profiling ; autonomous robotic systems ; in-process robotic NDE ; Wire + Arc Additive Manufacture (WAAM) ; ultrasound testing ; total focusing method ; defect recognition ; aircraft inspection ; deep learning ; CNN ; UAV ; defect classification ; AI ; underwater vehicle–manipulator system ; robotics emulator ; contact management ; remote inspection ; force control ; automated eddy current testing ; eddy current arrays ; robotics ; thermography ; non-destructive testing ; image alignment ; image blending ; n/a ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The present reprint contains all of the articles in the second edition of the Special Issue titled “Statistical Data Modeling and Machine Learning with Applications II”. This Special Issue belongs to the “Mathematics and Computer Science” Section and aims to publish research on the theory and application of statistical data modeling and machine learning. New mathematical methods and approaches, new algorithms and research frameworks, and their applications aimed at solving diverse and nontrivial practical problems are proposed and developed in this SI. We believe that the chosen papers are attractive and useful to the international scientific community and will contribute to further research in the field of statistical data modeling and machine learning.
    Keywords: forecasting model ; electricity energy consumption ; grey model ; artificial neural network ; machine learning ; rotation CART ensemble ; bagging ; boosting ; arcing ; simplified selective ensemble ; linear stacked model ; IoV ; xNN ; K-MEANS ; anomaly detection ; single-index models ; composite quantile regression ; SCAD ; Laplace error penalty (LEP) ; causality ; Bayesian networks ; scalability ; group lasso penalty ; data integration ; network estimation ; stability selection ; time series model ; wavelet transform ; neural network NARX ; ionospheric parameters ; gambling ; jackpot ; multidimensional integrals ; Monte Carlo methods ; lattice sequences ; digital sequences ; surface approximation ; surface segmentation ; surface denoising ; gaussian process latent variable model ; line geometry ; line elements ; regression ; classification ; prediction ; meteorological parameters ; traffic incidents ; multi-agent architecture ; air pollution ; random forest ; ARIMA errors ; MIMO averaging strategy ; multi-step ahead prediction ; unmeasured forecast ; Explainableartificial intelligence ; credit card frauds ; deep learning ; long short-term memory ; fraud classification ; lung cancer ; tumor ; CT image ; one-stage detector ; YOLO ; multi-scale ; receptive field ; data analysis ; decision trees ; LightGBM ; SHAP ; leisure time ; influencing factors ; time allocation ; neural networks ; cosmic rays ; space weather ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint showcases a selection of bleeding-edge articles about medical image processing and segmentation workflows based on artificial intelligence algorithms. The proposed papers are applied to multiple and different anatomical districts and clinical scenarios.
    Keywords: fundus image ; image registration ; deep learning ; computer vision applications ; nuclei segmentation ; histopathology ; Grad-CAM ; semantic segmentation ; instance segmentation ; nuclei detection ; pap smear ; cervical net ; shuffle net ; canonical correlation analysis (CCA) ; support vector machine (SVM) ; random forest (RF) ; k-nearest neighbour (KNN) ; artificial neural network (ANN) ; dual-energy CT ; two-step method ; limited-angular range ; directional total variation ; PA ; CNN ; tooth disease recognition ; image segmentation ; image preprocessing ; breast cancer ; mitotic nuclei classification ; histopathology images ; artificial hummingbird algorithm ; medical imaging ; cervical cancer ; feature fusion ; feature selection ; deep learning structures ; support vector machine ; disease discrimination accuracy ; performance comparisons ; 2D/3D registration ; orthogonal X-ray ; breast density ; CAD ; image enhancement ; textural ; auto-segmentation ; neuroimaging ; magnetic resonance imaging ; ovarian tumor ; 2D ultrasound image ; image inpainting ; lesion segmentation ; attention mechanism ; GAN ; medical image analysis ; synthetic CT ; MRI guidance ; MRI-only ; image-guided radiotherapy ; carbon ion radiotherapy ; particle therapy ; rare tumor ; PCNSL ; radiomics ; image normalization ; MRI ; prostate cancer ; prostate segmentation ; U-Net ; mp-MRI ; loss function ; automatic volume measurement ; ultrasound bladder scanner ; edge computing ; urinary disease ; artificial intelligence ; mandible ; segmentation ; 3D virtual reconstruction ; CBCT ; CT ; Convolutional Neural Networks ; comparison ; in-house ; software ; patch size ; Cranio-Maxillofacial surgery ; DICOM ; osteoarthritis ; histopathological ; hematoxylin eosin ; safranin O fast green ; DarkNet-19 ; MobileNet ; NasNet ; ResNet-101 ; ShuffleNet ; PCA ; ALO ; ensemble learning ; OCT ; pyramidal network ; scale-adaptive ; teeth segmentation ; panoramic radiographs ; mask-transformer-based networks ; panoptic segmentation ; tuberous sclerosis complex ; children ; convolutional neural network ; multi-contrast MRI ; rare neurodevelopmental disorder ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: When adopting remote sensing techniques in precision agriculture, there are two main areas to consider: data acquisition and data analysis methodologies. Imagery and remote sensor data collected using different platforms provide a variety of information volumes and formats. For example, recent research in precision agriculture has used multispectral images from different platforms, such as satellites, airborne, and, most recently, drones. These images have been used for various analyses, from the detection of pests and diseases, growth, and water status of crops to yield estimations. However, accurately detecting specific biotic or abiotic stresses requires a narrow range of spectral information to be analyzed for each application. In data analysis, the volume and complexity of data formats obtained using the latest technologies in remote sensing (e.g., a cube of data for hyperspectral imagery) demands complex data processing systems and data analysis using multiple inputs to estimate specific categorical or numerical targets. New and emerging methodologies within artificial intelligence, such as machine learning and deep learning, have enabled us to deal with these increasing data volumes and the analysis complexity.
    Keywords: vineyard ; pesticide application ; variable rate application ; unmanned aerial vehicle ; satellite ; nanosatellite ; monsoon crops ; leaf area index ; leaf chlorophyll concentration ; crop water content ; multispectral ; hyperspectral ; deep learning ; forage dry matter yield ; high-throughput phenotyping ; Brazilian pasture ; nitrogen indicator ; nitrogen nutrition diagnosis ; optical sensor ; spectral index ; UAV ; wheat lodging ; lightweight ; digital surface model (DSM) ; winter wheat ; fractional order differential ; continuous wavelet transform ; optimal subset regression ; support vector machine ; wheat powdery mildew ; machine learning ; information fusion ; remote sensing monitoring ; hyperspectral imaging ; dimensionality reduction ; LDA ; PLS ; PCA ; RandomForest ; ReliefF ; XGB ; Meloidogyne ; Solanum tuberosum ; soil salinity sensitive parameter ; random forest ; optimal retrieval model ; remote sensing ; high throughput phenotyping ; UAV/drone ; biomass estimation ; oats ; wheat ; yield prediction ; random forests ; satellite imagery ; Normalized Difference Vegetation Index (NDVI) ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Collectively, the studies presented in this reprint have used various validated biomechanical models or proposed novel methods of motion analysis to gain new insights into health-related problems and sports performance.
    Keywords: human ankle model ; product of exponentials formula ; anthropometry ; biomechanics ; coordinate measuring machines ; kinematics ; pose estimation ; position measurement ; biomedical informatics ; adolescent idiopathic scoliosis (AIS) ; surface electromyography (sEMG) ; paraspinal muscle ; Schroth exercise ; paraspinal muscle symmetry index (PMSI) ; negative heel shoes ; positive heel shoes ; gait ; pregnant women ; OpenSim ; IDEEA ; dentistry ; dental unit chair systems ; muscle fatigue ; muscle activation ; in vivo study ; femoral neck fracture ; internal fixation ; intramedullary fixation ; finite element analysis ; finite element ; proximal junctional failure ; spinal reconstruction ; thoracolumbar ; rollback ; ligament strain ; kinematic alignment ; mechanical alignment ; total knee arthroplasty ; markerless motion capture system ; gait analysis ; joint moment ; joint power ; running economy ; running style ; duty factor ; vertical oscillation ; stride frequency ; freezing of gait ; gait initiation ; Parkinson’s disease ; posture ; segmental centers of mass ; anthropometric measurement ; base of support ; hand exoskeleton design ; motion simulation ; rehabilitation ; intention recognition ; machine learning ; deep learning ; two-dimensional (2D) image ; marker-free video ; walking speed ; walking speed classification ; bi-LSTM ; redundant feature ; ratio-based body measurement ; optimal feature ; surface topography ; rasterstereographic back shape analysis ; normative data ; healthy adults ; posture analysis ; spine ; intelligent system ; classroom behavior ; motion identification ; shoulder activity ; sensor ; rehabilitation protocol ; proximal humerus fracture ; ground reaction force ; knee and hip ; lower limb ; normal walking ; musculoskeletal multibody dynamics ; spinal biomechanics ; spinal alignment ; spinal loading ; muscle force computation ; thoracolumbar spine ; biomechanical model ; electromyography ; inertial measurement units ; gait-phase prediction ; spinal cord injury (SCI) ; muscle fiber conduction velocity (MFCV) ; surface electromyography (EMG) ; EMG–force relation ; composite index ; characteristic points ; multivariable linear regression ; anterior cruciate ligament deficiency ; competitive swimming ; performance ; velocity fluctuations ; multibody simulation ; finite element method ; co-simulation ; sports ; degeneration ; intervertebral disc ; coupled ; embryo implantation ; human choriocarcinoma cell ; extracellular matrix ; stiffness ; durotaxis ; n/a ; thema EDItEUR::M Medicine and Nursing
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market). This collection gathers the advanced studies of novel deep learning algorithms/frameworks and their applications in real-world scenarios. The topics cover, but are not limited to, supervised learning, explainable deep learning, finance, healthcare, and sciences.
    Keywords: Convolutional Neural Network (CNN) ; pooling ; deep learning ; computer vision ; image analysis ; benchmark ; lithium-ion battery ; prognostics ; long short-term memory ; ARIMA ; reinforcement learning ; generative adversarial networks ; deep-learning ; crop/weed classification ; transfer learning ; feature extraction ; natural language processing ; image-text matching ; cheapfakes ; misinformation ; transformer encoder ; RoGPT2 ; control tokens ; summarization ; text generation ; human evaluation ; tricalcium silicate ; analytical model ; ion activity ; dissolution kinetics ; deep forest ; subsurface fluid flow ; Fourier neural operator ; small-shape data ; finite element method ; convolutional neural network ; sensitivity analysis ; source code comments ; classification ; machine learning techniques ; ANN flow law ; constitutive behavior ; radial return algorithm ; numerical implementation ; VUHARD ; GrC15 ; Abaqus Explicit ; defect detection ; surface defect detection ; defect detection for X-ray images ; defect recognition ; photoacoustic imaging ; image processing ; simulation ; reconstruction ; residual echo suppression ; acoustic echo cancellation ; speech enhancement ; graph neural network ; variational autoencoder ; nearest neighbours ; acute myeloid leukemia ; risk factors ; average treatment effect ; uplift modelling ; machine learning ; benzene ; ANOVA ; Shapley values ; self-explaining neural networks ; generalised additive models ; interpretability ; Siamese networks ; synthetic data ; cyclic learning ; unsupervised learning ; data augmentation ; single cell cultivation ; bioimage analysis ; finite element simulation ; plausibility checks ; convolutional neural networks ; storm surge ; hurricane ; forecasting ; CNN ; LSTM ; physics informed neural network ; dynamic force identification ; duffing’s equation ; spring mass damper system ; non-linear oscillators ; massive MIMO ; hybrid beamforming ; compressive measurement matrix ; long short-term memory network ; capsule network ; routing algorithm ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: In this Special Issue, we aim to represent the vibrant state of protein structure studies at the end of 2021. Recent decades have brought significant changes to the protein structure research field. Thanks to the genome projects and advances in structure determination methods, the number of solved protein structures has increased significantly. Protein structure research is experiencing a new renaissance, and in 2020 the number of deposited structures in the PDB database reached a new record. An assortment of many new frontiers are presented in this collection. A single Special Issue cannot give a comprehensive overview of a large field such as proteins science, but we aim to give a broad overview of current research.
    Keywords: configurational entropy ; force fields ; intrinsically disordered proteins ; protein folding ; NMR ; high hydrostatic pressure ; thermodynamic stability ; α-helical bundle ; Li-Fraumeni syndrome ; hereditary breast cancer ; germline TP53 missense variants ; quantitative prediction model ; protein conformation ; protein–protein interactions ; protein–protein binding ; protein–protein complex ; coarse-grained modeling ; multiscale modeling ; UFM1 ; UBA5 ; UFC1 ; protein-protein interactions ; complex structure ; oxidative stress ; Nrf2 ; Keap1 ; nuclear magnetic resonance spectroscopy ; hydrogen/deuterium exchange ; mass spectrometry ; circular dichroism ; intrinsically disordered ; bifidobacteria ; fucosidases ; glycosyl hydrolases ; conserved domains ; human milk ; analytical ultracentrifugation ; CO2 concentrating mechanism ; diffusion-ordered NMR spectroscopy ; electrospray ionization mass spectrometry ; homotetramer ; manganese ; metalloprotein ; photosynthesis ; small-angle X-ray scattering ; C1q ; calcium binding proteins ; genetic variation ; otoconia ; otolin-1 ; OTOL1 ; site-directed mutagenesis ; thermal shift assay ; B.1.1.7 ; B.1.617.2 ; COVID-19 ; E484Q ; T478K and L452R mutation ; N501Y mutation ; spike protein ; tetrabromobisphenol A ; tetrabromobisphenol S ; erythrocyte membrane ; retardants ; erythrocytes ; protein–ligand interactions ; protein dynamics ; FK506-binding protein ; FKBP12 ; FKBP51 ; oxidative folding ; glutathionylation ; nitrosylation ; cysteine reactivity ; ribosomal exit tunnel ; transient complex ; glutathione ; phosphorylation ; transmembrane proteins ; saturation mutagenesis ; deep sequencing ; residue packing ; deep learning ; convolutional neural network ; bidirectional long-short term memory ; protein ; prediction ; contact ; distance ; alphafold ; ProSPr ; CASP ; dataset ; retrainable ; mutual synergetic folding ; solvent accessibility of peptide bonds ; inter-subunit interaction ; solvent-accessible surface area ; Shannon information entropy ; amino acid composition ; glucose ; GlcNAc ; galactose ; GalNAc ; mannose ; xylose ; fucose ; Neu5Ac ; glucuronate ; iduronate ; tetrahydropyran ; entropy ; free energy ; free energy landscape ; energy-dependent protein folding ; co-translational protein folding ; molecular chaperones ; physical model of protein folding ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This Special Issue is dedicated to Professor Reinhard Schlickeiser on the occasion of his 70th birthday. Reinhard Schlickeiser’s internationally well-recognized work, comprising several hundred research articles and the comprehensive monograph “Cosmic Ray Astrophysics,” has had a lasting influence in several areas of astrophysics. He has also inspired a large number of junior researchers, many of whom are now pursuing successful academic careers. Over the last few decades, he has motivated and established many fruitful collaborations that have triggered new ideas and provided new insights into various plasma and astrophysical topics. This Special Issue aims to present original papers by Reinhard Schlickeiser’s collaborators that document the breadth of his scientific accomplishments and the subsequent studies that he has directly or indirectly influenced as a collaborator or as a teacher. This Special Issue may serve as inspiration for others to follow in his path and to accept the challenges awaiting them in the many areas of astrophysics that have been, for many years, Reinhard’s turf.
    Keywords: Langmuir waves ; Landau damping ; particle wave interactions ; space physics ; plasma physics ; n/a ; nucleus-acoustic waves ; nonlinear waves ; nonplanar geometries ; non-thermal radiation mechanisms ; relativistic jets ; relativistic processes ; BL Lacertae objects ; active galaxies ; blazars ; diffusive shock acceleration ; radiative transport ; gamma-rays ; solar wind ; plasmas ; instabilities ; waves ; cosmic rays ; galactic anti-matter ; solar modulation ; solar cycle ; dissipative solitary waves ; magnetized plasma ; superthermal trapped electrons ; kappa distribution ; Schamel equation ; oblique propagation of electrostatic plasma waves ; suprathermals ; cosmic-ray transport ; turbulence ; plasma waves ; particle-in-cell simulations ; automated driving ; data-driven modeling ; deep learning ; scene prediction ; trajectory prediction ; Alfvén waves ; wave–wave interactions ; magnetic loops ; solar corona ; particle transport ; numerical methods ; modelling ; cosmic-ray diffusion ; active galactic nuclei (AGN) ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Cybersecurity models include provisions for legitimate user and agent authentication, as well as algorithms for detecting external threats, such as intruders and malicious software. In particular, we can define a continuum of cybersecurity measures ranging from user identification to risk-based and multilevel authentication, complex application and network monitoring, and anomaly detection. We refer to this as the “anomaly detection continuum”. Machine learning and other artificial intelligence technologies can provide powerful tools for addressing such issues, but the robustness of the obtained models is often ignored or underestimated. On the one hand, AI-based algorithms can be replicated by malicious opponents, and attacks can be devised so that they will not be detected (evasion attacks). On the other hand, data and system contexts can be modified by attackers to influence the countermeasures obtained from machine learning and render them ineffective (active data poisoning). This Special Issue presents ten papers that can be grouped under five main topics: (1) Cyber–Physical Systems (CPSs), (2) Intrusion Detection, (3) Malware Analysis, (4) Access Control, and (5) Threat intelligence.AI is increasingly being used in cybersecurity, with three main directions of current research: (1) new areas of cybersecurity are being addressed, such as CPS security and threat intelligence; (2) more stable and consistent results are being presented, sometimes with surprising accuracy and effectiveness; and (3) the presence of an AI-aware adversary is recognized and analyzed, producing more robust solutions.
    Keywords: Internet of Things ; cybersecurity ; cyber threats ; malware detection ; machine learning ; network traffic ; cooperative intelligent transportation systems (cITSs) ; IDS ; vehicular ad-hoc networks (VANET) ; adaptive model ; deep belief network (DBN) ; NIDS ; deep learning ; false negative rate ; artificial neural network ; MITRE ATT&CK Matrix ; techniques classification ; BERT-based multi-labeling ; formal ontology ; risk identification ; vulnerability ; portable executable malware ; tree-based ensemble ; performance comparison ; statistical significance test ; adversarial examples ; face recognition ; mask matrix ; targeted attack ; non-targeted attack ; anomaly detection ; attack detection ; cyber-physical system ; datasets ; evaluation metrics ; biometric cryptosystem ; iris identification ; error-correcting codes ; intrusion detection ; smart grid ; neural networks ; 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::TG Mechanical engineering and materials
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint, entitled “Process Control and Smart Manufacturing for Industry 4.0”, contains the extended papers from the Series of annual IFSA conferences on Automation, Robotics and Communications for Industry 4.0/5.0 (ARCI) on the following topics: Process Automation, Process Control and Monitoring, Design Principles in Industry 4.0, Smart Manufacturing and Technologies, Smart Factories, Machine Learning and Artificial Intelligence in Manufacturing. The reprint contains 13 chapters written by 54 ARCI conference participants from seven countries: China, Croatia, Denmark, Germany, Italy, Poland and Romania. This reprint will inform readers of cutting-edge developments in the field and provide effective starting points and a road map for further research and development. All chapters follow the same structure: firstly, an introduction to the specific topic under study; secondly, a description of the field, including sensing or/and measuring applications. Each chapter ends with a curated list of references, including books, journals, conference proceedings and websites. “Process Control and Smart Manufacturing for Industry 4.0” is intended for researchers and scientists from academia and industry, as well as for postgraduate students.
    Keywords: steel alloys ; resistance spot welding ; RSW ; electrode wear ; electrode tip-dressing ; process monitoring ; mushrooming ; plateau forming ; quality control ; COVID-19 ; FDM ; 3D printing ; injection molding ; personal protection ; rapid prototyping ; protective face shields ; mechatronics line ; visual servoing system ; wheeled mobile robot ; industrial robotic manipulator ; Industry 4.0 ; NDT ; magnetic particle inspection ; optimization ; condition monitoring ; vibration ; acoustic emission ; drive train ; data fusion ; machine learning ; product morphology ; core data model ; phase rule filter ; phase private data model ; storage system ; forklift AGV ; deep learning ; semantic segmentation ; H-Swish ; community transformation ; community innovation governance ; ternary space ; coupling and coordination analysis ; lean manufacturing ; lean principles ; pull principle ; production control mechanisms ; production processes ; lean implementation ; batch process ; partial least squares ; multi-phase ; multi-mode ; master production scheduling ; make-to-order ; mathematical programming ; agent-based ; overtime ; earliness ; tardiness ; equipment selection decision ; business compass ; energy consumption ; processing time ; beetle antennae search algorithm ; sustainable blank dimension design ; energy-saving ; low-carbon ; grey wolf algorithm ; gas–solid ; cyclone ; separator ; gas dynamics ; erosion ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PN Chemistry
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: This Special Issue is intended to lay the foundation of AI applications focusing on oral health, including general dentistry, periodontology, implantology, oral surgery, oral radiology, orthodontics, and prosthodontics, among others.
    Keywords: machine learning ; artificial intelligence ; malocclusion ; diagnostic imaging ; active learning ; maxillary sinusitis ; convolutional neural network ; deep learning ; segmentation ; oral microbiota ; LEfSe ; PCoA ; alloprevotella ; prevotella ; core microbiota ; artificial neural networks ; oral cancer diagnosis ; oral cancer prediction ; pit and fissure sealants ; caries assessment ; visual examination ; clinical evaluation ; convolutional neural networks ; transfer learning ; deep learning network ; YOLOv4 ; mandibular third molar ; inferior alveolar nerve ; contact relationship ; panoramic radiograph ; deep learning methods ; caries diagnosis ; dental panoramic images ; radiography ; Fourier transform infrared spectroscopy ; FTIR imaging ; spectral biomarker ; multivariate analysis ; discriminant model ; oral squamous cell carcinoma ; oral epithelial dysplasia ; oral potentially malignant disorder ; risk stratification ; early oral cancer detection ; dentigerous cysts ; histopathology images ; image classification ; odontogenic keratocysts ; radicular cysts ; AI ; screening ; diagnosis ; dentistry ; ultrasonography ; tongue ; algorithm ; dysphagia ; impacted ; tooth ; detection ; neural networks ; proximal caries ; training strategy ; small dataset ; periapical radiograph ; X-ray ; tooth extraction ; oroantral fistula ; operative planning ; n/a ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: This reprint collected a set of papers where our section Editorial Board Members discuss key topics that typify the very best insightful and influential original articles or reviews in the “Communications” field. We expect these papers to be widely read and highly influential within the field.
    Keywords: network security ; double defense ; zero trust ; situation awareness ; immunology ; blind modulation classification ; orthogonal frequency division multiplexing ; higher-order cumulant and cyclic cumulant ; maximum-likelihood ; maximum a posteriori ; deep learning ; convolutional neural networks ; probability of correct classification ; testbed implementation ; drone ; UAV ; RF methods ; software-defined radio ; detection system ; defense system ; TSN ; Industry 4.0 ; smart distributed measurement systems ; IIoT ; IoT ; Ethernet ; Wi-Fi ; bit error rate ; fading channels ; Internet of things ; LoRa ; performance evaluation ; Named Data Networking ; information centric networking ; caching ; edge networks ; 6G ; IEEE 802.11be ; multilink operation ; channel access ; backoff ; coexistence ; Bluetooth ; wireless passive human sensing ; wireless sensor networks ; cyber-attacks ; intrusion-detection system ; MCDM ; q-rung orthopair fuzzy sets ; q-ROFWG ; 5G ; 5G-AKA ; authentication ; blockchain ; BAN logic ; Scyther ; radio channel ; path loss ; signal strength ; receivers ; transmitters ; wireless communication ; computational modeling ; path planning ; electromagnetic propagation ; loss measurement ; propagation loss ; reconfigurable antenna ; metasurface ; varactor diode ; beam-scanning ; high gain ; actor–critic learning ; energy-efficiency ; O-RAN ; RAN optimization ; low power wide-area networks ; large-scale LoRa networks ; single-channel LoRa gateways ; multi-objective ; quantum computing ; quantum optimization algorithms ; quantum routing optimization ; 6G communication networks ; SNR estimation ; optical wireless communications ; intensity modulation ; digital signature ; elliptic curve cryptography ; key exchange ; platoons ; Sybil attack ; 3D indoor localization ; location-based services ; Internet of Things ; computer vision ; biomedical imaging ; biometrics ; remote sensing ; cybersecurity ; natural language processing ; audio and speech processing ; control system and robotics ; information system ; food ; agriculture ; chemistry ; characteristic mode ; parasitic loading ; slit loading ; low-profile ; wearable antenna ; platoon ; traffic congestion ; collision avoidance ; CACC ; merge maneuver ; join maneuver ; lane change ; clustering ; information element ; MAC de-randomization ; OPTICS ; probe request ; WiFi-enabled device detection ; wireless sensing device ; 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
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint focuses on fish otoliths, as one of the most useful and important biological structures for fishery scientists and managers around the world. Collected papers cover several different research areas, from the otolith macro- to the microstructure and microchemistry, analyzing different types of otoliths and investigating various freshwater and marine species in their larval, juvenile and adult stages. Special attention is given to different approaches in otolith research and to many practical applications of such studies. The obtained data served to determine the age and growth of individual fish; to study habitat interactions, migration patterns, or habitats that the fish live in; to detect water temperatures or the presence of certain pollutants in the environment; and to reveal all other vital information about the life history of the fish.
    Keywords: sagittal otolith ; somatic growth ; long-lived fishes ; ontogeny ; teleost anatomy ; development ; fish morphology ; Fourier ; marking ; alizarin complexone ; hard tissue ; fin ray ; otolith ; scale ; silver carp (Hypophthalmichthys molitrix) ; age ; growth ; otoliths ; morphometry ; Sphyraena sphyraena ; fish age determination ; Greenland halibut ; deep learning ; dataset shift ; domain adaptation ; red snapper ; wavelet ; genetic diversity ; population structure ; asteriscus ; side effect ; otolith shape ; geographical effect ; temperature effect ; pH ; brook trout ; fish kill ; anadromy ; otolith microchemistry ; crucian carp ; strontium ; marking efficiency ; restocking ; time delay ; fish otoliths ; CNN ; age determination ; web tool ; Kokanee ; homing ; stocking ; Anguilla anguilla ; fish biology ; ecosystem variability ; minho river ; stock assessment ; Coilia nasus ; river estuary ; Yellow Sea ; elemental signature ; stable isotopic signature ; stock spatial structure ; atherinids ; trade-off ; daily growth ; spawning ; European hake ; length–frequency distribution ; sex-ratio ; hydro-morpho-sedimentary characteristics ; marginal increment analysis ; band deposition ; Thunnus thynnus ; growth curves ; edge analysis ; growth performance index ; quartile of marginal growth band method ; k-fold cross-validation ; back-calculation ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Given the current growth in global challenges, the need for smart agriculture practices and effective strategies is emerging as an imminent issue at a planetary scale. Agriculture 4.0 involves a large variety of mobile apps, web applications, Internet of Things (IoT) devices and platforms, drones, robots, and smart machinery for precision agriculture. The expansion of cloud technologies, artificial intelligence (AI), machine learning (ML), deep learning (DL), and big data collection are setting the stage for Agriculture 5.0. Agriculture science and natural sciences are further promoting this trend with the development of leading-edge scientific models and platforms, including stochastic, process-based, and data-driven machine learning modeling. This Special Issue covers the most recent and up-to-date progress in all aspects of internet and computer software applications in agriculture, focusing on the development of web applications and mobile apps, smart IoT devices and platforms, AI, ML and DL solutions in precision agriculture for detection, recognition, classification, monitoring, cultivation, harvesting, and marketing; development of cloud technologies for smart agriculture; computer and machine vision methods and applications for drones and smart machinery, and sensors for field operations; diagnostics and data collection; big data science; scientific process-based and stochastic modeling; and machine learning modeling for agriculture, agroecosystems and natural ecosystems. The research in this Special Issue will contribute to the promotion of modern agriculture practices in the current climate and in the future.
    Keywords: grape varieties identification ; Support Vector Machine (SVM) ; Convolutional Neural Network (CNN) ; deep feature fusion ; Canonical Correlation Analysis (CCA) ; smart machinery ; digital agriculture ; Chinese agricultural diseases and pests ; named entity recognition ; adversarial training ; semantic enhancement ; technology innovation ; food processing ; transition pathways ; sustainable food systems ; transformation ; smart farming ; IoT ; WSN ; containerization ; multi-agent ; neural network ; LSTM ; leisure agricultural park ; traveler group ; COVID-19 pandemic ; fuzzy collaborative intelligence ; machine vision ; maize seeds ; classification ; deep learning ; convolutional neural network ; decision support systems ; agricultural water management ; water security ; data-driven modeling ; conceptual resilience model ; input uncertainty ; climate extreme ; process-based modeling ; vehicle routing problem ; fresh agricultural products ; split delivery ; NSGA-II algorithm ; farm management information system ; farmers’ information needs assessment ; soft system methodology ; smallholder farmers ; conceptual model ; Indonesian chili farmers ; residual block ; attention mechanism ; grape leaf disease ; aquatic products price forecast ; VMD ; IBES ; hybrid model ; precision agriculture ; sensor network ; semi-literate farmers ; interactive interface ; User Interface (UI) ; Android apps ; machine learning ; regression algorithms ; web application ; early prediction of crop yield ; grape detection ; self-attention ; buffalo breeds ; Neural Networks ; Self Activated CNN ; DeepLabv3+ ; semantic segmentation ; picking point identification ; e-commerce interest linkage ; participation willingness and behaviors ; government policies ; farmers’ cognition ; evolutionary game model ; structural equation model ; object detection ; YOLOv7 ; hemp duck count ; smart agriculture ; LoRaWAN ; water status ; supply chain ; horticulture ; logistics ; operations ; planning framework ; decision support ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: In total, this Special Issue includes 11 papers. Firstly, Qi et al. conducted research on the large-scale non-uniform parallel solution of the two-dimensional Saint-Venant equations for flood behavior modeling. Zhang et al. proposed an efficient deep learning-based mineral identification method. Subsequently, Huang et al. proposed a named entity recognition method for geological news based on BERT model. Yang et al. proposed an automatic landslide identification method to solve the problem of the time-consuming nature and low efficiency of traditional landslide identification methods. Du et al. analyzed the potential of unsupervised machine learning methods for submarine landslide prediction. Wang et al. performed parallel computations on the inversion algorithm of the two-dimensional ZTEM. Xu et al. used the sliding window method and gray relational analysis to extract features from multi-source real-time monitoring data of landslides. Furthermore, Cao et al. proposed a new method called dual encoder transform (DualET) for the short-term prediction of photovoltaic power. Hao et al. conducted a series of parallel optimizations and large-scale parallel simulations on the high-resolution ocean model. Wang et al. proposed a time series prediction model for landslide displacements using mean-based low-rank autoregressive tensor completion. Finally, Yang et al. developed a measure of site-level gross primary productivity (GPP) using the GeoMAN model.
    Keywords: Saint-Venant equations ; finite difference method ; parallel computing ; heterogeneous computing ; deep learning ; image enhancement ; mineral identification ; convolutional neural networks ; BERT ; named entity recognition ; geological news ; CRF ; semantic segmentation ; PSPNet ; landslide ; submarine landslide ; machine learning ; hazard susceptibility ; spatial distribution ; ZTEM ; 2D forward modeling ; inversion ; parallel algorithm ; tipper ; disaster precursor identification ; early warning ; association rule mining ; particle swarm optimization ; k-means clustering ; Apriori algorithm ; gray relation analysis ; transformer ; photovoltaic power forecasting ; satellite images ; LICOM ; meteorological model ; parallel optimization ; time series ; missing data ; tensor completion ; autoregressive norm ; displacement prediction ; GeoMAN model ; gross primary productivity ; attention mechanism ; interdisciplinary ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This second Special Issue was compiled because of the interest demonstrated by the great success of the first Special Issue devoted to "Sensor Systems for Gesture Recognition".We believe this reprint acts as a meaningful window towards "Gesture Recognition" and the related sensors allowing the gathering of necessary data.
    Keywords: abnormal gait behavior ; OpenPose ; machine learning ; XGBoost ; random forest ; horse locomotion ; training effect ; inertial measurement units ; sports technology ; football ; motion analysis ; IMU ; trajectory reconstruction ; human-computer interactive ; data glove ; virtual hand ; emotion driven ; test ; visual tracking ; Siamese tracker ; tracking drift ; background clutter ; deep learning ; surgical skills assessment ; computer vision ; surgical education ; biomedical engineering ; multi-modal ; human activity recognition ; markerless ; RGB-D ; general movements ; infant movement analysis ; movement disorders ; surface electromyography ; forearm amputee ; hand posture ; visual feedback training ; pattern recognition ; artificial neural network ; hand gesture recognition ; electromyography ; inertial measurement unit ; reinforcement learning ; deep Q-network ; extreme learning machine ; force myography ; grasshopper optimization algorithm ; k-tournament selection ; frequency emphasis ; ensemble learning ; sign language recognition ; gloss prediction ; transformer ; pose-based approach ; pose estimation ; emotion judgment system ; adaptive interactive game ; set of optimal signal features ; sensor ; MARG ; MIMU ; orientation estimation ; sensor fusion algorithm ; dataset ; orientation algorithm benchmarking ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint includes 14 articles in Biomedical Data Science in honor of Professor Philip Bourne. Contributed by world-renowned experts, these articles cover a broad range of topics in machine learning, biophysics, bioinformatics, and systems biology.
    Keywords: structure-based drug discovery ; ligand binding sites ; deep learning ; graph neural network ; CRISPR/Cas9 ; genome editing ; machine learning ; SHAP values ; binding energy ; off-targets ; drug discovery ; retrosynthesis ; reaction template ; recurrent neural network ; and graph neural network ; mutational signatures ; smoking ; lung cancers ; APOBEC ; immune response to smoking ; cell-type composition ; goblet cells ; ciliated cells ; basal cells ; Protein Data Bank ; Open Access ; Worldwide Protein Data Bank ; macromolecular crystallography ; cryogenic electron microscopy ; cryogenic electron tomography ; electron crystallography ; micro-electron diffraction ; nuclear magnetic resonance spectroscopy ; biological macromolecules ; proteins ; nucleic acids ; DNA ; RNA ; carbohydrates ; small-molecule ligands ; social determinants of health ; electronic health records ; real-world evidence ; census tract ; data science ; protein database ; search tool ; prioritization algorithm ; drug repositioning ; quantum machine learning ; quantum metric learning ; kernel method ; kernel classifiers ; structural bioinformatics ; function annotation ; specificity annotation ; MSA ; entropy ; variability ; amino acids ; Philip Bourne ; FAIR ; bioinformatics ; n/a ; protein kinases ; functional families ; KinFams ; KinBase classification ; large language models ; pharmacovigilance ; social media ; drugs of abuse ; DNA sequencing ; read classification ; metagenomics ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint covers the following topics in the field of smart grids: 1. Optimal dg location and sizing to minimize losses and improve the voltage profile using garra rufa optimization. 2. Solar and wind energy forecasting for the green and intelligent migration of traditional energy sources. 3. Optimized micro-grid’s operation with electrical-vehicle-based hybridized sustainable algorithm. 4. The detection of nontechnical losses in smart meters using a MLP-GRU deep model and augmenting data via theft attacks. 5. A hybrid deep-learning-based model for the detection of electricity losses using big data in power systems. 6. Load frequency control and automatic voltage regulation in a multi-area interconnected power system using nature-inspired computation-based control methodology. 7. Line overload alleviations in wind energy integrated power systems using automatic generation control. 8. Electric price and load forecasting using a CNN-based ensembler in a smart grid. 9. Day-ahead energy forecasting in a smart grid considering the demand response and microgrids. 10. A dragonfly optimization algorithm for extracting the maximum power of grid-interfaced pv systems. 11. An economic load dispatch problem with multiple fuels and valve point effects using a hybrid genetic–artificial fish swarm algorithm. 12. Incentive-based dynamic pricing in a smart grid.
    Keywords: demand side management ; demand response ; load scheduling ; real time pricing ; genetic algorithm ; dynamic incentives ; artificial fish swarm algorithm ; economic load dispatch ; hybrid genetic–artificial fish swarm algorithm ; multi-objective optimization ; sustainable power generating system ; photovoltaic (PV) ; partial shading ; maximum power point tracking (MPPT) ; dragonfly optimization algorithm (DOA) ; adaptive cuckoo search optimization (ACSO) ; fruit fly optimization algorithm combined with general regression neural network (FFO-GRNN) ; improved particle swarm optimization (IPSO) ; voltage source inverter (VSI) ; total harmonic distortion (THD) ; energy optimization ; day ahead energy prediction ; artificial neural network ; renewable energy sources ; microgrid ; smart grid ; electricity price forecasting ; energy management ; electricity load forecasting ; convolutional neural network ; corona virus herd immunity optimization ; sustainable cities ; requirement-gathering tool ; qualitative comparison ; requirement engineering ; software engineering ; requirement-management tools ; automatic generation control ; wind energy ; transmission line security ; dispatch strategies ; Pakistan power system ; PI-PD controller ; load frequency control ; automatic voltage regulator ; nature-inspired optimization ; multi-area interconnected power system ; class imbalance ; gated recurrent units ; electricity theft detection ; non-technical losses ; smart grids ; deep learning ; GRU ; healthcare ; MLP ; PRECON ; smart cities ; smart meters ; sustainable society ; electric vehicles ; flexible load ; optimization ; renewable energy ; forecasting ; machine learning ; energy efficiency ; sustainability ; low carbon emission ; distribution generation ; Garra Rufa ptimization ; PSO ; GA ; power system ; urban sustainability ; local growth ; regional cities ; cultural heritage ; real estate ; intelligent regions ; innovation systems ; circular economy ; regional policies ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The present reprint contains 33 articles accepted and published in the Special Issue entitled “Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics, 2022” in the MDPI journal, Mathematics, which covers a wide range of topics connected to the theory and applications of feature representation learning for image processing, artificial intelligence, data mining and robotics. These topics include, among others, elements from image blurring, image aesthetic quality assessment, pedestrian detection, visual tracking, vehicle re-identification, face recognition, 3D reconstruction, the stability of switched systems, domain adaption, deep reinforcement, sentiment analysis, graph convolutional networks, knowledge graphs, geometric metric learning, etc. It is hoped that this reprint will be interesting and useful for those working in the area of image processing, computer vision, machine learning, natural language processing and robotics, as well as for those with backgrounds in machine learning who are willing to become familiar with recent advancements in artificial intelligence, which, today, is present in almost all aspects of human life and activities.
    Keywords: head detection ; YoloV4 ; NMS ; soft-NMS ; people counting ; vehicle re-identification ; license plate recognition ; video surveillance ; feature extraction ; pedestrian detection ; machine learning ; end-to-end ; anchor-free ; feature reuse ; correlation filters ; second-order fitting ; visual tracking ; DCNN-BiLSTM ; domain adaptation ; MMD ; fine-tuning ; C-MAPSS ; cross-working ; small sample ; blind image deblurring ; image prior ; sparse channel ; sparsity ; multi-output ; kNN ; metric learning ; cost-weighted ; geometric mean metric ; motion deblurring ; image super-resolution ; multi-order attention ; gated learning ; decoupling ; face recognition ; second-order gradient ; image gradient orientations ; collaborative-representation-based classification ; image aesthetic assessment ; semi-supervised learning ; label propagation ; deep learning ; computer vision ; garbage quantity identification ; YOLOX ; Soft-NMS ; stability ; switched system ; state-dependent switching ; time delay ; multi-source domain adaptation ; Dempster–Shafer evidence theory ; cross-domain classification ; 3D reconstruction ; multi-view stereo ; structure from motion ; background matting ; adversarial example ; feature transformation ; black-box attack ; ensemble attack ; deep neural network ; intelligent design ; data analysis ; models and algorithms ; extension theory ; scheme design ; adversarial learning ; adversarial equilibrium ; transferability quantification ; power load forecasting ; routing, modulation and spectrum assignment ; elastic optical networks ; deep reinforcement learning ; knowledge distillation ; aspect-based sentiment analysis ; graph neural networks ; dependency trees ; dependency types ; graph attention mechanism ; syntactic ; semantic ; vehicle color recognition ; low–high level joint task ; object detection ; joint semantic learning ; rainy image recovery ; XSS attack ; traffic detection ; payloads ; fusion verification ; hypergraph matching ; similarity metric ; information-theoretic metric learning ; mixed noise removal ; matrix nuclear norm ; logarithm norm ; ADMM ; plug-and-play ; aspect-level sentiment classification ; external knowledge ; KGE ; GCN ; discriminative feature learning ; multidimensional scaling ; fuzzy k-means ; pairwise constraint propagation ; iterative majorization algorithm ; Aspect Level Sentiment Classification ; Contrasitve Learning ; Graph Convolutional Networks ; graph convolutional networks ; commonsense knowledge graph ; anomaly detection ; cyber–physical ; industrial control systems ; image classification ; large-margin technique ; robustness ; anti-noise performance ; cross-domain sentiment classification ; word embedding ; GAT ; hate speech detection ; contrastive learning ; multi-task learning ; attention mechanism ; state reconstruction ; gait adjustment ; uncertain temporal knowledge graph ; temporal knowledge graph ; knowledge graph embedding ; confidence score ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: Research performed on robotic applications has significantly expanded in the last decade, and currently, robotic systems are being utilized for many purposes. To achieve this generalized application of robots, researchers have endeavoured to study a wide variety of methods and algorithms in order to properly employ robotic systems in many real-life scenarios. At present, many types of robotic platforms are being employed in various applications, e.g., dual-arm robots, parallel robots, mobile robots, humanoid robots, aerial robots, underwater robots, and micro/nano robots. Moreover, some theoretical tools are specially being used to obtain correct robot performance, e.g., machine learning, artificial intelligence, multi-agent systems, and control and planning theory. The purpose of this reprint is to exhibit the current state of robotic applications. In particular, in addition to introducing novel theories and methods, this reprint is particularly focused on the application of robotic systems in real-life situations. Thus, the presentation of experimental results makes evident the feasibility and usefulness of robotic systems in practical cases. Obviously, this reprint does not intend to exhaustively demonstrate all the current existing robotic applications but rather give an overview of them, revealing the high level of activity in this area. This reprint contains an Editorial, together with 30 contributions in total from countries all around the world, addressing a broad range of robotic applications.
    Keywords: 6D pose estimation ; learning-based approach ; 2D-information-based approach ; 3D-information-based approach ; textureless and reflective objects ; foreground occlusion ; background clutter ; automated parking system ; fuzzy comprehension evaluation ; Floyd algorithm ; human-operated vehicle ; autonomous vehicle ; agriculture ; cooperative robots ; key technology ; control ; humanoid and bipedal locomotion ; legged robots ; passive walking ; foot placement estimation ; nonprehensile manipulation ; robotic batting ; high-speed object manipulation ; ball recognition ; trajectory estimation ; motion control ; weighted least square ; mobile robot ; formation ; motion coordination ; attitude observer ; trajectory tracking ; path tracking ; compliance control ; human–robot interaction ; sliding mode controller ; manual guidance ; path planning ; pure pursuit controller ; deep learning ; robot kidnapping detection ; autonomous navigation ; topological mapping ; field robotics ; mining automation ; robotic assembly ; deep neural networks ; peg-in-hole ; dual-arm ; human–robot collaboration ; assembly task ; user studies ; user preferences ; quality of task execution ; usability ; autonomous loading system ; manipulator motion planning ; manipulability ; stochastic planner ; robotics ; service robots ; healthcare robots ; robot-as-a-service ; smart cities ; AGV ; AMR ; industrial robots ; collaborative robots ; machine learning in robotics ; computer vision ; system identification ; flapping-wing micro air vehicle ; longitudinal mode ; model refinement ; gray box model ; onboard sensors ; robot calibration ; robot remastering ; calibration uncertainty ; part probing ; uncertainty reduction ; sensor feedback ; nanoelectromechanical system (NEMS) ; nanorobots ; ion channel Kv10.1 ; mathematical modeling ; control algorithm ; pose estimation ; 3D reconstruction ; charuco cuboid ; pediatric stroke ; upper limb ; hand rehabilitation ; device ; Gloreha Sinfonia ; case report ; robot system ; augmented reality ; robot teleoperation ; face recognition ; face tracking ; face detection ; face alignment ; person identification ; intelligent robots ; interactive systems ; time-of-flight ; lidar ; field of view redirection ; passive redirection ; clean mirror ; dusted mirror ; prism ; robot-assisted laparoscopic surgery ; surgical robot ; da Vinci Research Kit ; IoT ; multiple object tracking ; MOT ; self-driving ; SLAM ; KITTI ; MOTChallenges ; MOT15 ; MOT16 ; MOT17 ; UA_DETRAC ; symmetry ; sit-to-stand ; elevation angle ; coordination ; backpropagation ; optimization methods ; inverse kinematics ; bipedal robot ; bio-inspired design ; simulation ; model-based design ; LIPM ; passive walker ; Unmanned aerial vehicles (UAVs) ; detection technologies ; radio frequency-based (RF) ; radar ; acoustic ; electro optical ; hybrid fusion ; controller detection ; bird song ; soundscape ; ecoacoustics ; sound source localization ; robot audition ; HARK ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events.
    Keywords: landslide monitoring ; early warning ; emergency management ; dissemination ; urbanized areas ; benefit evaluation ; gray correlation method ; soil erosion ; soil physical properties ; earthquake fatalities ; deep learning ; random forest ; feature importance ; structure type ; flash flood ; driving factor ; sensitivity analysis ; subregion of landcover ; Yunnan Province ; flood risk ; Bayesian networks ; integrated index for flood risk assessment ; WSN ; pipeline leakage ; human-induced sinkhole ; leakage detection ; sewer pipeline ; sensors ; highway waterfall ice ; ground water ; mathematical model ; formation mechanism ; natural hazards ; multi-agent system ; emergency relief ; public participation ; contamination indices ; geo-accumulation factor ; heavy metals ; GIS ; hazard ; social vulnerability ; hydrological and hydrodynamic model ; analytic hierarchy process ; fuzzy Delphi ; Athens metropolitan area ; urban fires ; analytical hierarchy process ; flooding ; structural vulnerability ; seismicity ; Wastewater Treatment Plants ; sustainability ; Ioannina polje ; soil quality ; agricultural soil ; aircraft emissions ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The delicate balance of resource intensity and efficiency of a solution for a very complex problem raises the issue of how these aspects constitute a symmetrical or asymmetrical system. Computational Intelligence (CI) offers a plethora of efficient tools for the potential and rather good quality solution of highly complex, often mathematically intractable problems. This "toolbox" is one of the best examples for the study of the above mentioned issue, namely, how to find the best balance, how to establish a symmetry of weights or costs in a particular field, for a particular problem. This special issue presents a number of interesting novel applications of CI for the tackling of a wide variety of difficult problems. The Introduction gives a short insight into the symmetry and asymmetry aspect of the topic.
    Keywords: lung nodule segmentation ; 3D-UNet ; 3D-Res2UNet ; multi-scale features ; deep learning ; butterfly optimization algorithm (BOA) ; particle swarm optimization (PSO) ; cubic map ; nonlinear ; high dimension ; extensional fuzzy numbers ; MI-algebras ; similarity ; arithmetics of fuzzy numbers ; orderings ; fuzzy interpolation ; economic data ; air defense system ; artificial immune system ; command and control ; learning classifier system ; multi-agent systems ; weapon-target assignment ; energy optimization ; genetic algorithms ; multi-objective optimization ; artificial neural network simulator ; artificial intelligence ; artificial bee colony algorithm ; global optimization ; neural network ; nonlinear static system ; behavioural finance ; imprecision ; oriented fuzzy number ; oriented present value ; oriented return ; S-divergence ; S-distance ; spectral clustering ; text summarization ; recurrent neural network ; embedding ; dynamic memory network ; fuzzy-rough cognitive network ; fuzzy cognitive map ; granular computing ; fuzzy-rough sets ; stability ; convergence ; discrete bacterial memetic evolutionary algorithm ; simulated annealing ; flow shop scheduling problem ; global sensitivity analysis ; Sobol procedure ; fast algorithm ; convolutional neural network ; structure reduction ; pruning ; quality ; feature selection ; machine learning ; asexual ; genetic algorithm ; android malicious application detection ; bees algorithm ; training deep neural networks ; metaheuristics ; opinion mining ; recurrent neural networks ; sentiment classification ; natural language processing ; data augmentation ; fine-tuning ; generative models ; StyleGAN ; transfer learning ; present value ; discount factor ; portfolio ; finance ; optimization ; tourist trip design ; vehicle routing ; key performance indicator (KPI) ; anomaly detection ; variational auto-encoder (VAE) ; support vector data description (SVDD) ; FMEA ; Fuzzy Logic ; greenhouse gases ; blockchain ; difficulty adjustment ; proof-of-work ; ANN ; AlexNet ; COVID-19 ; TSA ; commonsense ; knowledge graph ; linguistic terms ; language models ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This Special Issue explores empirical studies of emotional mechanisms, qualitative and quantitative measurements of emotion, the recognition of emotional contexts, and the application of emotion. We introduce fourteen papers, ranging from lab-based studies aimed at understanding emotional mechanisms to applying emotion recognition in the real world (e.g., in driving, games, education, and virtual avatars). This Special Issue explores empirical studies of emotional mechanisms, qualitative and quantitative measurements of emotion, the recognition of emotional contexts, and the application of emotion. We introduce fourteen papers, ranging from lab-based studies aimed at understanding emotional mechanisms to applying emotion recognition in the real world (e.g., in driving, games, education, and virtual avatars).
    Keywords: speech emotion recognition ; domain adaptation ; SER generalization ; Korean Emotional Speech Database ; ensemble model ; multi-path ; group-loss ; BLSTM network ; facial micromovement ; emotion recognition ; emotion authenticity ; HRV parameter ; game addiction ; League of Legends ; stress response ; sensitivity ; specificity ; logistic regression ; facial action unit ; facial aging ; facial expression ; posed emotion ; virtual avatar ; virtual human ; virtual character ; embodied conversational agent ; social interaction ; empathy ; CNN ; cognitive workload ; functional connectivity analysis ; LSTM ; mental workload ; mutual information ; phase locking value ; phase transfer entropy ; deep learning ; facial expression recognition (FER) ; 3D convolutional neural network (3D CNN) ; multirate signal processing ; minimum overlapped frame structure ; self-attention ; multi-depth network ; video content empathy ; micro-movement synchronization ; non-contact empathy measurement ; empathic advertisement ; multimodal affective computing ; catecholamines ; emotion classification ; wearable devices ; deep neural networks ; multispectral imaging ; face recognition ; in the wild ; driver emotion recognition ; multimodal ; self-report ; real-world driving ; EEG ; learning emotions ; attention ; convolutional neural network ; multi-channel band features ; eye movement ; brain connectivity ; review ; human emotions ; affective and physiological states ; Plutchik’s wheel of emotions ; sensors ; methods and applications ; statistical and multiple criteria analysis ; country success and publications maps of the world ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-08-08
    Description: Rural development is an essential constituent of the global economy. However, within agriculture, a decrease in the quantity and quality of crop harvest and livestock productivity is observed due to a deterioration in soil fertility, environment, and irrational use of natural resources. At the same time, agricultural areas are under pressure from population growth, requiring more food production. As a result, it encourages people to move into intact primary areas in order to increase the area of crops, pastures, etc., which leads to the destruction of natural diversity. The solution to avoid disaster is increasing agricultural production efficiency to expand crop harvest and livestock productivity without deteriorating quality. It requires introducing innovative engineering technologies to agriculture. Fortunately, technology is developing rapidly nowadays, and new driving scientific forces are emerging. The Special Issue collected high-quality research and review articles from academics and industry-related researchers in the areas of Agricultural Engineering covering the following topics: harvesting and planting crops, livestock production, livestock and agrofood waste utilization, seed treatment and transportation, water treatment, agricultural robotic applications, solutions for digital and precision agriculture, hardware and software support for pest and weed control, machine learning, energy efficiency and conservation in agriculture.
    Keywords: microclimate ; ceiling fans ; electric thermal storage unit ; energy–saving ; heat supply system ; discrete element method ; soybean seed ; ellipsoidal shape ; parameter calibration ; rolling friction coefficient ; pulsed LED light ; continuous LED ; scanning LED light ; energy saving ; lettuce ; vertical farms ; growth ; cultivation ; pneumatic seeder ; pressure loss characteristics ; complex airway ; airway optimization ; harvesting ; force action ; potato ; working body ; harvesting machines ; device for assessing the suitability for harvesting ; transition metal ; charge compensator ; red emission ; artificial lighting ; photosynthetic pigments ; count red jujubes ; red jujube ; improved YOLOv5s ; ShuffleNet V2 Unit ; Stem ; BiFPN ; impact sprinkler ; non-circular nozzle ; water distribution ; aspect ratio ; 2D video disdrometer ; droplet kinetic energy distribution ; wild blueberry ; Vaccinium angustifolium ; Monilinia vaccinii-corymbosi ; deep learning ; coordinated attention ; synthetic data ; prediction accuracy ; multi-objective evolutionary algorithms ; double wishbone mechanisms ; multibody dynamics ; pareto solution set ; amaranth inflorescence wastes ; pyrolysis ; thermogravimetric analysis ; hydrocarbon rich bio-oil ; indoor climate ; air cooling ; water-evaporative systems ; sprayed panels ; heat recovery units ; technological process ; rod elevator ; lifting angle ; displacement ; experiment ; cleaning machine ; grain plants seeds ; Fusarium ; photoluminescence ; linear regression models ; green cold chain delivery ; fresh agricultural products ; customer value ; time-dependent road network ; biomass ; Amaranthus retroflexus ; bio-oil ; biochar ; WCH ; DCH ; feed length of the stalk ; conveying performance ; fuel consumption ; high-voltage electrical pulse ; processing ; plant tissue ; irreversible damage ; intracellular structure ; green energy supply ; agricultural electrification ; high-efficiency photovoltaic equipment ; complex energy supply systems ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In this Special Issue, we aim to represent the vibrant state of protein structure studies at the end of 2021. Recent decades have brought significant changes to the protein structure research field. Thanks to the genome projects and advances in structure determination methods, the number of solved protein structures has increased significantly. Protein structure research is experiencing a new renaissance, and in 2020 the number of deposited structures in the PDB database reached a new record. An assortment of many new frontiers are presented in this collection. A single Special Issue cannot give a comprehensive overview of a large field such as proteins science, but we aim to give a broad overview of current research.
    Keywords: configurational entropy ; force fields ; intrinsically disordered proteins ; protein folding ; NMR ; high hydrostatic pressure ; thermodynamic stability ; α-helical bundle ; Li-Fraumeni syndrome ; hereditary breast cancer ; germline TP53 missense variants ; quantitative prediction model ; protein conformation ; protein–protein interactions ; protein–protein binding ; protein–protein complex ; coarse-grained modeling ; multiscale modeling ; UFM1 ; UBA5 ; UFC1 ; protein-protein interactions ; complex structure ; oxidative stress ; Nrf2 ; Keap1 ; nuclear magnetic resonance spectroscopy ; hydrogen/deuterium exchange ; mass spectrometry ; circular dichroism ; intrinsically disordered ; bifidobacteria ; fucosidases ; glycosyl hydrolases ; conserved domains ; human milk ; analytical ultracentrifugation ; CO2 concentrating mechanism ; diffusion-ordered NMR spectroscopy ; electrospray ionization mass spectrometry ; homotetramer ; manganese ; metalloprotein ; photosynthesis ; small-angle X-ray scattering ; C1q ; calcium binding proteins ; genetic variation ; otoconia ; otolin-1 ; OTOL1 ; site-directed mutagenesis ; thermal shift assay ; B.1.1.7 ; B.1.617.2 ; COVID-19 ; E484Q ; T478K and L452R mutation ; N501Y mutation ; spike protein ; tetrabromobisphenol A ; tetrabromobisphenol S ; erythrocyte membrane ; retardants ; erythrocytes ; protein–ligand interactions ; protein dynamics ; FK506-binding protein ; FKBP12 ; FKBP51 ; oxidative folding ; glutathionylation ; nitrosylation ; cysteine reactivity ; ribosomal exit tunnel ; transient complex ; glutathione ; phosphorylation ; transmembrane proteins ; saturation mutagenesis ; deep sequencing ; residue packing ; deep learning ; convolutional neural network ; bidirectional long-short term memory ; protein ; prediction ; contact ; distance ; alphafold ; ProSPr ; CASP ; dataset ; retrainable ; mutual synergetic folding ; solvent accessibility of peptide bonds ; inter-subunit interaction ; solvent-accessible surface area ; Shannon information entropy ; amino acid composition ; glucose ; GlcNAc ; galactose ; GalNAc ; mannose ; xylose ; fucose ; Neu5Ac ; glucuronate ; iduronate ; tetrahydropyran ; entropy ; free energy ; free energy landscape ; energy-dependent protein folding ; co-translational protein folding ; molecular chaperones ; physical model of protein folding ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: "Health and Public Health Applications for Decision Support Using Machine Learning" is a reprint that explores the intersection of machine learning and health sciences. It presents a collection of research and innovations showcasing how data-driven algorithms can transform patient care, disease diagnosis, and public health management. The reprint covers a wide range of topics, including natural language processing for biomedical relation extraction, ensemble learning for blood glucose level forecasting in diabetes management, machine learning for predicting walking stability and fall risk among the elderly, deep learning for pneumonia-infected lung volume quantification, and more.The reprint also discusses applications in precision medicine, early detection of renal damage, cardiac health monitoring, stress classification for mental health assessment, and early diagnosis of intracranial internal carotid artery stenosis. It emphasizes the role of machine learning in managing health crises, such as COVID-19 detection using ECG, voice, and X-ray systems, and reviews AI models in diagnosing adult-onset dementia disorders.Overall, this reprint aims to inspire researchers and healthcare professionals by showcasing the transformative potential of machine learning in healthcare. It hopes to encourage further research and collaboration to advance healthcare and technological innovations for a healthier future.
    Keywords: adult-onset dementia ; Alzheimer’s disease ; magnetic resonance imaging ; artificial intelligence ; machine learning ; neural networks ; atherosclerosis ; Doppler ultrasound ; internal carotid artery ; hemodynamic modeling ; stroke ; stress ; emotion ; action units ; speech ; audio visual ; RNN-LSTM ; petri-plates ; colonies ; machine-learning models ; discrimination ; Measurement uncertainty ; Monte Carlo method ; ECG ; Cardiac health ; COVID-19 ; signal processing ; image processing ; computerized diagnostic systems ; subclinical renal damage ; risk assessment tool ; group-based trajectory modeling ; screening strategy ; CVD classification ; data selection ; convolutional neural network ; pretrained model ; deep learning ; transfer learning ; infected lung segmentation ; quantification of lung disease severity ; comparison between manual and automated image segmentation ; deep neural network ; COVID-19 detection ; COVID-19 severity assessment ; gait ; neuromuscular control ; movement synergy ; overground walking ; principal component analysis (PCA) ; largest Lyapunov exponent (LyE) ; time-series forecasting ; blood glucose ; diabetes ; ensemble learning ; artificial neural network ; DDI (drug–drug interaction) ; CPR (chemical–protein relation) ; transformer ; self-attention ; GAT (graph-attention network) ; relation extraction ; ChemProt ; T5 (text-to-text transfer transformer) ; n/a
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-05
    Description: This volume is focused on a wide range of topics, including adaptive optic components and tools, wavefront sensing, different control algorithms, astronomy, and propagation through turbulent and turbid media.
    Keywords: adaptive optics ; influence function ; wavefront correction ; adaptive retroreflector ; tunable lens ; adaptive lens ; polymer optics ; divergence control ; fluidic lens ; tunable optics ; wavefront aberrations ; adaptive method ; Zernike functions ; wavefront sensor ; multichannel diffractive optical element ; coherent beam combining ; neural network ; laser beam array ; deep learning ; atmospheric turbulence ; optical vortices ; Zernike polynomials ; laser beam focusing ; scattering medium ; spatial light modulator ; Shack-Hartmann sensor ; deformable mirror ; laser ablation ; parallel-gap resistance microwelding ; wavefront control ; tip-tilt mirror ; FPGA ; angular stabilization system ; bimorph mirror ; fast adaptive optical system ; turbulence ; spectral analysis ; lattice geometry ; Walsh functions ; thema EDItEUR::P Mathematics and Science::PN Chemistry
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-31
    Description: This reprint discussed the role of retinal and optic nerve imaging in addition to its application in ophthalmic diseases and clinical medicine. It includes some high-quality articles containing original research results as well as review articles of exceptional merit.
    Keywords: rhegmatogenous retinal detachment ; optical coherence tomography angiography ; vitrectomy ; foveal avascular zone ; macular vessel density ; Boswellia serrata ; curcumin ; diabetic macular edema ; celiac disease ; OCT ; optical coherence tomography ; retinal layers ; RNFL ; quality of life ; canaloplasty ; trabeculectomy ; medical therapy ; central serous chorioretinopathy ; pachychoroid ; en face optical coherence tomography ; choroid ; choroidal vascularity index ; oculomics ; artificial intelligence ; machine learning ; deep learning ; retinal imaging ; color fundus photograph ; systemic diseases ; cardiovascular diseases ; neurodegenerative diseases ; COVID ; SARS-CoV-2 ; retinal vein occlusion ; RVO ; vaccination ; branch retinal vein occlusion ; optic disc drusen ; visible optic disc drusen ; deep convolutional neural network ; DCNN ; inceptionv3 ; dyslexia ; reading ; retina ; macula ; fovea ; parafovea ; perifovea ; thickness ; segmentation ; Best disease ; choroideremia ; inherited retinal diseases ; retinitis pigmentosa ; Stargardt disease ; thema EDItEUR::M Medicine and Nursing ; thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Speech is the most spontaneous and natural means of communication, as well as the preferred modality for interacting with mobile or fixed electronic devices, but speech in-terfaces have drawbacks, such as a lack of user privacy; non-inclusivity for certain users; poor robustness in noisy conditions; and the difficulty of creating complex man–machine interfaces. The Special Issue “Future Speech Interfaces with Sensors and Machine Intelligence” assembles eleven contributions that cover multimodal and silent speech interfaces; lip reading applications; novel sensors for speech interfaces; and enhanced speech inclusivity tools for future speech interfaces. The articles make important improvements beyond the state of the art, advancing the state of the art to new frontiers in some cases. Short summaries of all articles, grouped by topic, are presented, followed by a global commentary and evaluation.
    Keywords: neural machine translation (NMT) ; transformer ; Arabic dialects ; modern standard Arabic ; subword units ; multi-head attention ; shared vocabulary ; self-attention ; 3D densely connected CNN ; 3D multi-layer feature fusion CNN ; convolutional neural network ; deep learning ; lipreading ; speech recognition ; visual speech recognition ; silent speech ; continuous-wave radar ; European Portuguese ; machine learning ; multimodal speech ; lip reading ; ultrasound tongue imaging ; pose estimation ; speech kinematics ; keypoints ; landmarks ; audio-visual speech recognition ; lip-reading ; application programming interface ; multi-modal interaction ; deep neural networks ; multi-view VSR ; attention mechanism ; spatial attention module ; local self-attention ; connectionist temporal classification ; text-to-lip ; speech synthesis ; text-to-speech ; speech-to-lip ; zero-shot adaptation ; generative models ; artificial intelligence ; objective measures ; hybrid models ; end-to-end recognition ; reliability measures ; decision fusion net ; articulation-to-speech synthesis ; silent speech interface ; speaker adaption ; voice conversion ; audiovisual speech recognition ; multimodal interaction ; edutainment ; virtual aquarium ; speech processing ; ultrasound imaging ; silent speech interfaces ; speech sensors ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint sought high-quality contributions that highlight novel research results and emerging applications, addressing recent breakthroughs in UAS autonomous navigation and related fields, such as flight mechanics and control, structural design, sensor design, etc. The topics of interest included the following: two-dimensional and three-dimensional mapping, target detection, and obstacle avoidance; the active perception of targets in cluttered environments (foliage, forests, etc.); vision-based and optical flow techniques; sensors and sensor fusion techniques; design models for guidance and controlled flight; state estimation, data analysis and filtering techniques (KF, EKF, particle filtering, fuzzy logic, etc.); path planning and path management; optimal control and strategies (neural networks, fuzzy logic, reinforcement learning, evolutionary and genetic algorithms, AI, etc.); navigation in GPS-denied environments; autolanding and safe landing area definition (SLAD); environmental effects on UAVs (wind, etc.); autonomous UAV or MAV swarms, and distributed architectures; BVLOS autonomous navigation.
    Keywords: quadcopter ; unnamed aerial vehicle ; dynamic model ; PID controller ; fuzzy logic ; genetic algorithm ; intelligent control ; unmanned aircraft systems (UASs) ; IMU ; pressure sensors ; angle-of-attack estimation ; autonomous flight ; flight mechanics ; flight maneuvers ; hybrid data and model driven ; key-frame ; motion primitives ; iterative learning ; sliding mode control ; unmanned arial vehicles ; trajectory tracking ; air data system ; flow angle ; angle-of-attack ; angle-of-sideslip ; flight dynamics ; flight testing ; synthetic sensor ; analytical redundancy ; model-free ; physics-based ; flying ad-hoc network (FANET) ; millimeter-wave (mmWave) ; neighbor discovery ; unmanned aerial vehicle (UAV) ; free-space optical communication ; spatial mode diversity ; unmanned aerial vehicle ; emergency recovery communications ; floods ; beach litter ; object detection ; drone surveys ; unmanned aerial vehicles (UAVs) ; deep learning ; yolov5 ; geolocation ; litter monitoring ; beach cleaning ; digital elevation models ; unmanned aircraft systems ; ZED 2 stereo camera ; indoor localization ; real-time application ; sensor integrity ; collision avoidance ; sensor fusion ; unmanned vehicles ; 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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-07-14
    Description: The fast development of the industrial internet is boosting the evolution of the manufacturing industry to a new stage of socialization, servitization, universal interaction and connection, and platformization. Under this background, social manufacturing emerged as a new kind of manufacturing paradigm, established based on the self-driven, self-organizing and self-adaptive cyber-physical–social interaction among extensive numbers of socialized manufacturing resource providers. Up until now, social manufacturing has drawn attention from both academic and industrial fields due to its promising research and application values. However, social manufacturing is still at its infant stage as the fast development of the industrial internet, artificial intelligence, collective intelligence, cloud/edge/fog computing, and a new generation of information and communication technologies, etc., are changing the interaction, configuration and operation mechanisms of social manufacturing every day. In this regard, this Special Issue is established to explore precisely how the newly emerged social manufacturing paradigm influences the trends of mass customization and the configuration/operation patterns during order delivery, and exactly how the advanced information technologies can boost the development and application of social manufacturing
    Keywords: social manufacturing ; additive manufacturing ; production planning ; distributed manufacturing systems ; heuristic algorithms ; graph matching ; Graph Convolutional Network (GCN) ; attention mechanism ; fully connected neural network ; cloud manufacturing ; Industrial Internet of Things ; data acquisition ; cloud–edge collaboration ; resource virtualization ; gateway ; decentralized Industrial Internet of Things ; blockchain middleware ; data security ; Industry 5.0 ; resilient manufacturing ; data acquisition network ; real-time energy consumption ; characteristic analysis ; intelligent workshops ; social value chain system ; value-adding ; key supporting technologies ; digital-driven technologies ; industry 4.0 ; turnkey project ; manufacturing system configuration ; manufacturing system operation ; key enabling tools ; industrial internet ; equipment asset management ; digitalization ; social digitalization platform ; system engineering ; fuzzy DEMATEL-TOPSIS ; industrial manufacturing ; deep learning ; data augmentation ; defect generation ; defect detection ; remote monitoring ; maintenance ; Industrial Internet ; dimensional error prediction ; grinding process ; bagging–GA–ELM ; robust analysis ; conductive particles ; LCD module ; ACF bonding ; automated optical inspection ; visual-alignment ; fieldbus control system ; synchronization control ; distributed clock ; ethernet fieldbus ; CANopen ; multimodal data ; product customization ; 3D content generation ; blockchain ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint, "Flexible Micromanipulators and Micromanipulation," is a collection of 12 full research articles that provide insights into the latest development and applications in the field of micromanipulation which has important applications in areas, such as metal additive manufacturing, medical devices, and robotics. The topics of the reprint cover the design and fabrication of magnetic actuators, electromagnetic levitation systems, compliant manipulators and robots, micromanipulation of microparticles and microcapsules to characterize mechanical properties of microscale objects, and inchworm robot for inspection, assembly, and maintenance.
    Keywords: electromagnetism ; magnetic manipulator ; magnetic actuator ; deep learning ; ANN ; ANN/SA ; magnetic levitation ; additive manufacturing ; eddy current levitation ; direct energy deposition ; tripteron ; triaxial ; parallel-kinematic ; compliant manipulator ; compact structure ; micromanipulation ; microparticles ; motion control ; vibrations ; dry friction ; control ; oscillating platform ; automatic data analysis ; mechanical strength ; algorithms ; multibody systems ; CSFH ; event-driven scheme ; non-smooth contact ; LN-model ; Moreau time-stepping scheme ; capillary force ; water ; vision feedback ; non-contact ; flexible parallel mechanism ; 3-PSS ; optimal design ; kinematics ; dynamics ; compliant mechanisms ; flexible elements ; element transfer matrix ; transfer matrix approach ; micro-grippers ; micro-manipulators ; flexure ; CFSH ; compliant mechanism ; the tangent stiffness matrix ; plant-based ; non-synthetic ; microcapsules ; intrinsic mechanical properties ; apparent elastic modulus ; mathematical modelling ; finite element analysis ; XYθ position control ; holonomic inchworm robot ; optical encoder ; closed-loop control ; calibration ; crosstalk error ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: With the development of computer technology and communication technology, various industries have collected a large amount of data in different forms, so-called big data. How to obtain valuable knowledge from these data is a very challenging task. Machine learning is such a direct and effective method for big data analytics. In recent years, a variety of advanced machine learning technologies have emerged, and they continue to play important roles in the era of big data. Considering advanced machine learning and big data together, we have selected a series of relevant works in this Special Issue to showcase the latest research advancements in this field. Specifically, a total of thirty-three articles are included in this Special Issue, which can be roughly categorized into six groups: time series analysis, evolutionary computation, pattern recognition, computer vision, image encryption, and others.
    Keywords: energy storage ; model predictive control ; peak shaving and frequency regulation ; output optimization ; global optimization ; meta-heuristic ; support vector machine swarm intelligence ; hyperspectral image classification ; CNN ; ELM ; PSO ; deep feature ; butterfly optimization algorithm ; random replacement ; crisscross search ; overseas Chinese associations ; support vector machine ; short-term traffic-flow forecasting ; bagging model ; stacking model ; ridge regression ; error coefficient ; least squares method ; support vector machines ; principal component analysis ; quick access recorder ; mean absolute error ; high-plateau flight ; event extraction ; event type ; event trigger words ; stock announcement news ; stock return ; traffic flow forecasting ; long short-term memory network ; graph convolutional network ; target detection ; infrared ; deep learning ; YOLOv5 algorithm ; design science research ; performance analysis ; machine learning ; classification algorithms ; clustering algorithms ; pilot abnormal behavior ; behavior detection ; YOLOv4 algorithm ; CBAM ; flight safety ; fault diagnosis ; variational mode decomposition ; composite multi-scale dispersion entropy ; particle swarm optimization ; deep belief network ; CBCFI ; combined prediction model ; ARMA ; GM ; GA ; BP ; hierarchical clustering ; Jaccard distance ; membership grade ; community clustering ; lightweight neural networks ; attentional mechanisms ; Hemerocallis citrina Baroni ; maturity detection ; cloud ; digital archives ; confidentiality management ; information system ; emotion-cause pair extraction ; heterogeneous graph ; graph attention network ; hierarchical model ; spatial-temporal systems ; neural networks ; information systems ; forecasting ; time series ; coupled map lattice ; polymorphic mapping ; color image ; hash function ; pixel level ; differential evolution ; capacitated vehicle routing planning ; saving mileage ; gravity search ; object detection ; computer vision ; border patrol ; COVID-19 ; warning system ; PROPHET ; health ; quantum dynamics ; neural architecture search ; image classification ; swarm intelligence ; whale optimization algorithm ; extreme learning machine ; talent stability prediction ; adversarial attacks ; document classification ; NLP ; convolutional neural networks ; disease classification ; generative adversarial network ; tomato leaf ; multi-strategy ; dual-update strategy ; mean-semivariance model ; portfolio optimization ; DNA computing ; DNA sequences design ; improved matrix particle swarm optimization algorithm (IMPSO) ; opposition-based learning ; signal-to-noise ratio distance ; time series classification ; complementary ensemble empirical mode decomposition (CEEMD) ; MultiRocket ; feature selection ; hybrid model ; multi-behavior recommendation ; sequential recommendation ; graph neural network ; embedding propagation ; 1D quadratic chaotic system ; image encryption ; splicing model ; DNA coding ; BaaS system ; blockchain consensus algorithm ; KNN ; service level agreement ; transaction priority ; data stream mining ; forex ; online learning ; adaptive learning ; incremental learning ; sliding window ; concept drift ; financial time series forecasting ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: This topic has been successfully completed. A total of 180 scientific articles were sent, of which 66 have been accepted for publication. These 66 articles are published in this reprint.
    Keywords: artificial intelligence ; expert systems ; machine learning ; deep learning ; modeling ; prediction ; probabilistic models ; prediction models ; sustainable mobility ; smart cities ; smart grids ; sustainable energy systems ; renewable energy sources ; nonrenewable energy sources ; electrical storage ; green hydrogen ; sustainable greenhouses ; wind ; microgrids ; tidal ; solar ; biomass ; power network ; solar thermal ; solar photovoltaic ; hydraulics ; ANN ; neural networks, fuzzy logic, genetic algorithms ; hybrid models based on artificial intelligence ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-07-14
    Description: Computational modeling and simulation are essential to solid and structural mechanics. They have not only covered entire engineering fields (civil, aerospace, mechanical, etc.) but also various scales (from nano to macro) and physics (mono- and multiphysics). Recently, they have been found to be able to offer theoretical backgrounds of digital transformation. Society at large is increasingly enthusiastic about data-driven modeling and simulation, and the possibilities they offer. The aim of this Special Issue reprint was to provide a forum for researchers to discuss recent advanced computational modeling and simulation techniques of solids and structures, and applications to solve challenging engineering problems.
    Keywords: carbon nanotube ; strain sensor ; piezoresistive mechanism ; sensor pattern design ; learning tools ; teaching methodology ; educational software ; mechanism science ; problem-based learning ; bolted joints ; parameter identification ; thin-layer element ; pre-tightening torque ; contact interface ; FEM ; surrogate modeling ; mesh-free ; machine learning ; deep learning ; SIMP method ; impact condition ; non-matching interface ; condensed mortar method ; periodic structures ; polar coordinates ; wave propagation ; forced response of plates and shells ; finite element analysis ; unbounded structures ; deployment dynamics ; truss-link mechanism ; synthetic aperture radar ; friction compensation ; GP regression ; multi-objective optimization ; hot metal forming ; Inconel 625 ; multibody dynamics ; automotive driveshafts ; forced bending vibrations ; asymptotic method ; principal parametric resonance ; dynamic stability frontiers ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: Cancer is a leading cause of death worldwide, claiming millions of lives each year. Cancer biology is an essential research field to understand how cancer develops, evolves, and responds to therapy. By taking advantage of a series of “omics” technologies (e.g., genomics, transcriptomics, and epigenomics), computational methods in bioinformatics and machine learning can help scientists and researchers to decipher the complexity of cancer heterogeneity, tumorigenesis, and anticancer drug discovery. Particularly, bioinformatics enables the systematic interrogation and analysis of cancer from various perspectives, including genetics, epigenetics, signaling networks, cellular behavior, clinical manifestation, and epidemiology. Moreover, thanks to the influx of next-generation sequencing (NGS) data in the postgenomic era and multiple landmark cancer-focused projects, such as The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), machine learning has a uniquely advantageous role in boosting data-driven cancer research and unraveling novel methods for the prognosis, prediction, and treatment of cancer.
    Keywords: tumor mutational burden ; DNA damage repair genes ; immunotherapy ; biomarker ; biomedical informatics ; breast cancer ; estrogen receptor alpha ; persistent organic pollutants ; drug-drug interaction networks ; molecular docking ; NGS ; ctDNA ; VAF ; liquid biopsy ; filtering ; variant calling ; DEGs ; diagnosis ; ovarian cancer ; PUS7 ; RMGs ; CPA4 ; bladder urothelial carcinoma ; immune cells ; T cell exhaustion ; checkpoint ; architectural distortion ; image processing ; depth-wise convolutional neural network ; mammography ; bladder cancer ; Annexin family ; survival analysis ; prognostic signature ; therapeutic target ; R Shiny application ; RNA-seq ; proteomics ; multi-omics analysis ; T-cell acute lymphoblastic leukemia ; CCLE ; sitagliptin ; thyroid cancer (THCA) ; papillary thyroid cancer (PTCa) ; thyroidectomy ; metastasis ; drug resistance ; n/a ; biomarker identification ; transcriptomics ; machine learning ; prediction ; variable selection ; major histocompatibility complex ; bidirectional long short-term memory neural network ; deep learning ; cancer ; incidence ; mortality ; modeling ; forecasting ; Google Trends ; Romania ; ARIMA ; TBATS ; NNAR ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint, named “Landslides in Forests around the World: Causes and Mitigation”, covers various topics, such as the impact mechanism of tree roots on landslide stability, landslide deformation monitoring, landslide disaster prevention and control engineering technology, the automatic identification of regional landslides, susceptibility and hazard assessment, and a rainfall-induced mass landslide warning.
    Keywords: shallow landslide ; probability of occurrence ; typhoon ; data-driven model ; Ningguo City ; landslide susceptibility ; antecedent effective precipitation ; daily precipitation ; hybrid landslide warning model ; multibaseline InSAR techniques ; Guang’an Village Landslide ; InSAR ; time-series analysis ; post-event deformation mapping ; root-soil composite ; root reinforcement coefficient ; shear strength parameters ; root distribution angle ; root diameter ; landslide susceptibility mapping ; random forest model ; qualitative analysis ; quantitative evaluation ; Yunyang County ; granular flow ; ring-shear test ; fluctuation characteristics ; landslide ; susceptibility ; tree species ; age group ; woodland type ; forest origin ; YOLOv3 ; deep learning ; automatic landslide identification ; remote sensing image ; flexible rockfall barrier ; energy capacity ; landslide debris ; field investigation ; coupled numerical simulation ; land-use suitability ; Hechuan District ; landslide susceptibility assessment ; machine learning ; Three Gorges Reservoir area ; early-warning model ; Random Forest ; model study ; nucleation process ; waveform similarity ; repeating earthquakes ; neighboring earthquakes ; reinforcement of roots ; slope stability ; growth and decay ; Japanese cedar trees ; shallow landslides ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics
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  • 66
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: Digital health, virtual assistance, and telemedicine are terms often used interchangeably to refer to remote medical assistance, monitoring and care. Several studies and insights have developed these issues, analyzing the advantages and disadvantages and successes and failures and offering reflections on the implications and issues of these technologies in the health domain. The results of these investigations are affecting the redesign of hospital and outpatient management based on digital innovation using eHealth and mHealth. During the COVID-19 pandemic, this approach made it possible to offer assistance and continue care at home, protecting patients, preserving health workers, limiting the spread of the virus, and reducing the need for hospitalization. This reprint contains contributions dealing with the development of DH during the COVID-19 pandemic. The contributions are from various experts in different fields regarding the application of digital health, which, in some cases is also integrated with artificial intelligence, including digital contact tracing, mHealth, virtual reality, mental health, physiology, and rehabilitation.
    Keywords: n/a ; digital contact tracing ; IMMUNI app ; COVID-19 ; students ; digital care visit ; online consultation ; medical staff ; healthcare personnel ; user experience ; magnetic resonance imaging (MRI) ; brain tumor ; machine learning ; digital health ; e-health ; pandemic ; physical activity ; performance evaluation ; eHealth ; self-care ; chronic diseases ; mental health ; mindfulness ; mobile health ; social isolation ; mental stress ; feature selection ; artificial intelligence ; human health ; lock down ; normative activation model ; COVID-19 prevention ; prevention intention ; IoT ; obesity ; classification ; regression ; real-time system ; COVID-19 pandemic ; contact tracing ; CNN ; chest X-ray images ; hybrid learning ; computer-aided diagnosis ; remote psychotherapy ; psychotherapy via telephone ; psychotherapy via videoconferencing ; tele-health ; e-mental-health ; psychotherapy ; qualitative psychotherapy research ; mixed-methods psychotherapy research ; exergaming ; breast neoplasms ; physical function ; telehealth ; (d)health literacy ; health literacy ; health intervention ; health strategy ; medical data ; medical imaging ; data classification ; image detection ; YOLOv4 ; logistic regression ; AI ; deep learning ; chatbot ; health ; health domain ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBP Health systems & services::MBPK Mental health services
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The reprint focuses on artificial intelligence-based learning approaches and their applications in remote sensing fields. The explosive development of machine learning, deep learning approaches and its wide applications in signal processing have been witnessed in remote sensing. The new developments in remote sensing have led to a high resolution monitoring of ground on a global scale, giving a huge amount of ground observation data. Thus, artificial intelligence-based deep learning approaches and its applied signal processing are required for remote sensing. These approaches can be universal or specific tools of artificial intelligence, including well known neural networks, regression methods, decision trees, etc. It is worth compiling the various cutting-edge techniques and reporting on their promising applications.
    Keywords: pine wilt disease dataset ; GIS application visualization ; test-time augmentation ; object detection ; hard negative mining ; video synthetic aperture radar (SAR) ; moving target ; shadow detection ; deep learning ; false alarms ; missed detections ; synthetic aperture radar (SAR) ; on-board ; ship detection ; YOLOv5 ; lightweight detector ; remote sensing image ; spectral domain translation ; generative adversarial network ; paired translation ; synthetic aperture radar ; ship instance segmentation ; global context modeling ; boundary-aware box prediction ; land-use and land-cover ; built-up expansion ; probability modelling ; landscape fragmentation ; machine learning ; support vector machine ; frequency ratio ; fuzzy logic ; artificial intelligence ; remote sensing ; interferometric phase filtering ; sparse regularization (SR) ; deep learning (DL) ; neural convolutional network (CNN) ; semantic segmentation ; open data ; building extraction ; unet ; deeplab ; classifying-inversion method ; AIS ; atmospheric duct ; ship detection and classification ; rotated bounding box ; attention ; feature alignment ; weather nowcasting ; ResNeXt ; radar data ; spectral-spatial interaction network ; spectral-spatial attention ; pansharpening ; UAV visual navigation ; Siamese network ; multi-order feature ; MIoU ; imbalanced data classification ; data over-sampling ; graph convolutional network ; semi-supervised learning ; troposcatter ; tropospheric turbulence ; intercity co-channel interference ; concrete bridge ; visual inspection ; defect ; deep convolutional neural network ; transfer learning ; interpretation techniques ; weakly supervised semantic segmentation ; 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::TQ Environmental science, engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: The forest, as the main body of the terrestrial ecosystem, has a huge carbon sink function and plays an important role in coping with global climate change. This reprint on “Monitoring forest carbon sequestration with remote sensing” mainly focuses on new remote sensing theories, methods, and technologies for monitoring carbon sinks in forest ecosystems (including urban forest ecosystems).
    Keywords: forest height ; synthetic aperture radar (SAR) ; interferometry ; random volume over ground (RVoG) model ; three-stage inversion method ; bamboo forest ; BEPS model ; gross primary productivity ; net primary productivity ; spatiotemporal evolution ; climate change ; backscatter coefficients ; polarization decomposition ; collinearity ; ridge regression ; RF ; PCA ; aboveground carbon density ; LiDAR ; stratified estimation ; machine learning algorithm ; Northeast China ; canopy closure ; the GOST model ; fisheye camera photos ; transects ; LAI ; forest height inversion ; three-stage algorithm ; coherence optimization ; complex coherence amplitude inversion ; SRTM ; random forest ; stochastic gradient boosting ; random forest Kriging ; wavelet analysis ; carbon storage ; land use/cover change ; scenario simulation ; PLUS model ; InVEST model ; remote sensing inversion ; dynamic change ; driving factors ; Shaoguan City ; above-ground biomass (AGB) ; airborne LiDAR ; airborne hyperspectral ; wavelet transform ; feature fusion ; Landsat time-series ; VCT model ; classifying forest types ; forest aboveground biomass ; forest aboveground biomass (AGB) ; scale effect ; random forest (RF) ; scale correction ; phenology ; dynamic threshold method ; northeast China ; TIMESAT ; forest carbon stocks ; simulation ; LUCC ; multi-source data ; feature selection ; aboveground biomass ; habitat dataset ; Landsat 8-OLI images ; pine forest ; model comparison ; 3D green volume ; UAV-Lidar ; urban forest ; random forest model ; remote sensing ; MODIS ; FY-3C VIRR ; Yunnan Province ; mangrove forests ; Hainan Island ; deep learning ; influential mechanism ; Bayesian hierarchical modelling ; geostatistics ; Eucalyptus grandis ; Eucalyptus camaldulensis ; Pinus patula ; spatial random effects ; spatially varying coefficient ; rubber plantation ; time series ; shapelet ; Landsat ; Pinus densata ; terrain niche index ; dynamic model ; canopy volume ; diameter at breast height (DBH) ; aboveground biomass (AGB) ; stem volume (V) ; near-infrared reflectance of vegetation ; carbon budget ; L-band PolInSAR ; RVoG model ; forest density ; terrain slope ; coherence ; extinction coefficient ; signal penetration ; 3-PG model ; eucalyptus ; forest age ; forest structure ; sensitivity ; clumping index ; estimation ; impact analysis ; field measurement ; Sentinel-2 images ; artificial neural network ; random forests ; quantile regression neural network ; Pinus densata forests ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science ; thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Fast, non-destructive detection technology and equipment for food quality and safety is a powerful technical support tool to ensure the development of food industry informatization and intelligence, with the advantages of fast speed, convenient operation, and easy online inspection. During the past two decades, such technologies have found numerous successful applications for food and agricultural product detection and processing. Owing to improvements in the manufacturing of photoelectric sensor pieces and progress in artificial intelligence and software algorithms, fast non-destructive detection technologies are able to provide more accurate, reliable, and stable solutions for food quality and safety detection and processing. They are closely integrated with the Internet of Things and intelligent manufacturing, promoting a new wave of innovation in intelligent manufacturing in the food industry. The application of new sensing technology and equipment in the fast, non-destructive detection of food has always been at the forefront of scientific and technological research. This Special Issue aims to focus on the latest research progress of this application and jointly discuss the focus of development of this research direction.
    Keywords: maize ; moldy level ; catalase activity ; hyperspectral image ; data fusion ; feature selection ; fruit quality monitoring ; room-temperature ethylene sensor ; density functional theory ; adsorption energy ; band energy alignment ; apple ; NIR ; size correction ; extinction coefficient ; fruit diameter difference ; acceptability ; benchtop NMR ; mandarins ; NMR ; successive projective algorithm ; uninformative variable elimination ; support vector regression ; Korla fragrant pear ; stone cell content ; intelligent evaluation ; cultivation ; visible/near infrared spectrum ; fresh jujube ; model update ; variable fusion ; defective apples ; apple grading ; deep learning ; object detection ; semantic segmentation ; shrimp ; hot air drying ; quality change ; hyperspectral images ; low field magnetic resonance ; micro Raman ; microfluidic chip ; fungal spores ; crop disease ; numerical simulation ; degree of milling ; multi-scale information fusion ; residual network model ; Bayesian optimization algorithm ; hyperspectral imaging ; maize seeds ; defect detection ; convolutional neural network ; tomato ; leaf mildew ; terahertz time-domain spectroscopy ; near infrared hyperspectral technology ; multi-source information fusion ; YOLOv5 ; walnut kernels ; impurities detection ; small object detection ; liposomes ; high stability ; freshness ; bi-layer indicator ; light penetration depth ; spatial-frequency domain imaging ; depth-resolved ; bruise ; scattering ; near infrared spectroscopy ; vegetables ; anthocyanidins ; fast determination ; Curcumae Longae Rhizoma ; volatile oil ; 60Co ; GC–IMS ; SERS detection ; chromium contamination ; tea sample ; carbimazole hydrolysate ; Au@Ag nanoparticles ; PAEs ; Raman ; DFT ; HF ; theoretical study ; gas sensor ; spoilage monitoring ; early warning ; logistics control ; simulated annealing ; surface-enhanced Raman spectroscopy ; flexible substrate ; polycyclic aromatic hydrocarbons ; in situ detection ; common carp ; texture ; machine learning ; visualization ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
    Keywords: lung ; conventional radiography ; diagnostic procedure ; chronic obstructive pulmonary disease ; COVID-19 ; computed tomography ; lungs ; variability ; segmentation ; hybrid deep learning ; artificial intelligence ; deep learning ; computer-based devices ; radiology ; thoracic diagnostic imaging ; chest X-ray ; CT ; observer tests ; performance ; lung CT images ; nodule detection ; VGG-SegNet ; pre-trained VGG19 ; cardiac amyloidosis ; AL/TTR amyloidosis ; hypertrophic cardiomyopathy ; left ventricular hypertrophy ; convolutional neural network ; Tuberculosis (TB) ; drug resistance ; chest X-rays ; generalization ; localization ; Electrical Impedance Tomography ; lung imaging ; cardiopulmonary monitoring ; aorta ; lung cancer ; pulmonary artery ; pulmonary hypertension ; modality-specific knowledge ; object detection ; RetinaNet ; ensemble learning ; pneumonia ; mean average precision ; source data set ; supervised classification ; coronary artery disease ; machine learning ; cardiopulmonary disease ; faster CNN ; medical imaging ; X-rays ; transfer learning ; explainability ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
    Keywords: lung ; conventional radiography ; diagnostic procedure ; chronic obstructive pulmonary disease ; COVID-19 ; computed tomography ; lungs ; variability ; segmentation ; hybrid deep learning ; artificial intelligence ; deep learning ; computer-based devices ; radiology ; thoracic diagnostic imaging ; chest X-ray ; CT ; observer tests ; performance ; lung CT images ; nodule detection ; VGG-SegNet ; pre-trained VGG19 ; cardiac amyloidosis ; AL/TTR amyloidosis ; hypertrophic cardiomyopathy ; left ventricular hypertrophy ; convolutional neural network ; Tuberculosis (TB) ; drug resistance ; chest X-rays ; generalization ; localization ; Electrical Impedance Tomography ; lung imaging ; cardiopulmonary monitoring ; aorta ; lung cancer ; pulmonary artery ; pulmonary hypertension ; modality-specific knowledge ; object detection ; RetinaNet ; ensemble learning ; pneumonia ; mean average precision ; source data set ; supervised classification ; coronary artery disease ; machine learning ; cardiopulmonary disease ; faster CNN ; medical imaging ; X-rays ; transfer learning ; explainability ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint addresses the unique opportunities and challenges associated with human–computer interaction with intelligent systems. First, state-of-the-art reviews are presented about speech emotions, automatic spelling correction, and art usage in virtual reality. We encouraged authors to submit reports describing systems built for different languages and multilingual systems. The linguistic, emotional, prosodic, and dialogue aspects of speech communication are investigated. Special attention is given to sentiment and emotional analysis from text and speech. Speech audiometry, offline speech recognition, and text-independent speaker verification systems are elaborated. The rapidly growing domain of virtual reality applications is of interest both as an application domain in which new interfaces and interaction methods are needed and as a potential testbed for evaluating speech and other interface modalities.
    Keywords: pediatric speech audiometry ; hearing tests ; conditioned play audiometry ; human–computer interaction ; mechatronic devices ; Internet of Things ; cyber-physical systems ; system control ; augmented reality ; mixed reality ; Azure cloud ; sentiment analysis ; opinion classification ; lexicon-based approach ; hybrid approach ; lexicon generation ; lexicon labelling ; particle swarm optimization ; spelling correction ; natural language processing ; diacritization ; error model ; context model ; Natural Language Processing ; deep learning ; grammar error detection ; word embedding ; text-independent speaker verification system ; self-attentive pooling ; multi-layer aggregation ; feature recalibration ; deep length normalization ; speaker embedding ; shortcut connections ; convolutional neural networks ; ResNet ; human–robot interaction ; dictionary approach ; machine learning approach ; social robotics ; human-robot interaction ; mental workload ; heart rate variability ; machine learning ; sentiment level evaluation ; handicraft product ; 3D handicraft products ; smartphone applications ; user interaction ; user’s attracting attention ; question-answering forum ; healthcare informatics ; recommendation system ; user study ; speech emotion recognition ; attention mechanism ; recurrent neural network ; long short-term memory ; user experience ; usability evaluation methods ; domain usability ; domain-specific languages ; graphical user interfaces ; virtual reality ; art therapy ; rehabilitation ; neurorehabilitation ; neuroplasticity ; brain injury ; ASR ; speech-to-text ; edge AI ; Wav2Vec ; transformers ; PyTorch ; emotion recognition ; dimensional to categorical emotion representation mapping ; activation ; arousal and valence regression ; X-vectors ; SVM ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: "Advances in UAV Detection, Classification and Tracking" is a comprehensive book that explores the latest techniques and advancements in unmanned aerial vehicle (UAV) detection, classification, and tracking. As UAV technology continues to evolve and become more accessible, there is a growing need for effective methods to detect, identify, and track these devices in various scenarios. This reprint provides a thorough overview of the state-of-the-art approaches for UAV detection, classification, and tracking, covering both theoretical and practical aspects.The reprint begins by introducing the basics of UAVs and their various applications, followed by a detailed overview of the challenges associated with UAV detection, classification, and tracking. The authors then present the latest techniques and algorithms used in the field, including machine-learning-based approaches, computer vision techniques, and sensor fusion techniques. The reprint also covers the challenges of real-world applications, such as dealing with occlusions, sensor noise, and environmental factors.With contributions from leading experts in the field, "Advances in UAV Detection, Classification and Tracking" is an essential resource for researchers, engineers, and practitioners working on UAV detection, classification, and tracking. It is also a valuable reference for graduate students and anyone interested in the latest advancements in this rapidly evolving field.
    Keywords: distributed electric propulsion ; coordinated thrust control ; fault-tolerant control ; flight simulation ; autonomous navigation ; gimbal design ; obstacle avoidance ; target tracking ; unmanned aerial vehicles ; law enforcement ; tiltrotor ; blade element theory ; flight mechanical model ; stability analysis ; social learning ; ant colony optimization ; multi-agent system ; visual tracking system ; embedded system ; drone ; omnidirectional mobile robot ; multi-target association ; topological sequences ; triangular networks ; global consistency ; similar transformation invariance ; micro-Doppler ; radar ; target ; classification ; unmanned aerial vehicle ; motion planning ; optimization techniques ; attention mechanism ; anti-occlusion ; location prediction ; convolutional neural network CNN ; YOLO deep learning ; UAV ; drone detection ; drone recognition ; automatic target recognition (ATR) ; classify while scan (CWS) ; drone detection radar ; detection response time (DRT) ; unmanned air traffic management (UTM) ; object detection ; deep learning ; adaptive cluster ; cognitive micro-Doppler radar ; Doppler resolution ; JEM signals ; radar dwell time ; advancement ; tracking and communication threats ; three-dimensional circumnavigation control ; elliptical multi-orbit ; UAV group ; small-object detection ; backbone design ; object positioning ; object classification ; UAV flight experiment ; astronaut detection ; astronaut accompanying ; intravehicular visual navigation ; semi-structured environment ; dynamic scenes ; 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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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Renewable energy resources are used as distributed generation (DG) units and installed near to where the energy is converted and consumed. Further, the integration of renewable energy sources at home is very important. IoT helps smart grids to support various network functions throughout the generation, distribution, and consumption of energy by incorporating IoT devices (such as sensors, actuators, and smart meters), as well as by providing connectivity, automation, and tracking for such devices. For these applications, the use of low-power long-range wireless networks (LPWAN) is fundamental to facilitate all the necessary tasks in the smart grids in City 4.0 and Industry 4.0. The integration of renewable energies (photovoltaic solar, wind energy, biomass energy, hydroelectric energy, and other sources) in smart grids implies the monitoring of households, cities, industries, and electric vehicles at all times. In this sense, the development of monitoring and control applications using mobile devices is a fundamental tool in this type of system, which complements all the possibilities offered by the IoT. Smart energy meters are used to allow for communication between consumers and utility command centers to exchange messages about electrical consumption. Thus, it is essential to have access from any location and instant access to information using mobile devices or computers.
    Keywords: knowledge-based sensor ; Internet of Things ; high-concentration photovoltaic systems ; sun tracker ; buildings energy management ; deep learning ; energy consumption prediction ; LSTM ; autoencoder ; load forecasting ; smart sensors ; smart meter ; temporal data granularity ; electric load profile ; time slices ; time series ; advanced metering infrastructure ; monitoring ; data acquisition systems ; renewable energy ; multi-objective optimization ; reactive power (RP) planning ; hybrid algorithm ; virus colony search ; particle swarm optimization ; LoRaWAN ; smart irrigation systems ; smart energy ; IoT ; renewable energy sources ; photovoltaic energy ; I-V curve ; monitoring and data acquisition ; microgrid ; open-source ; communication protocols ; DC interrupting ; digitization ; remote control ; electric energy measurement ; miniature circuit breaker ; power meter ; internet of things ; load control ; energy meter ; smart socket ; intelligent campus ; smart building ; internet of things platform ; remote monitoring and control ; classification ; data anomalies ; data imputation ; energy consumption data ; ensemble classifiers ; machine learning ; smart home data ; smart meter data ; tracebase dataset ; home energy management system ; smart home ; cloud infrastructure ; distributed PV ; energy management system ; energy storage units ; charging piles ; smart grid ; redundancy ; Home Assistant ; low-carbon island ; Kinmen ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: Polymer-processing techniques are of the utmost importance for producing polymeric parts. They must produce parts with the desired qualities, which are usually related to mechanical performance, dimensional conformity, and appearance. Aiming to maximize the overall efficiency of the polymer-processing techniques, advanced modeling codes along with experimental measurements are needed to simulate and optimize the processes. Thus, this reprint exploits the digital transformation of the plastics industry, both through the creation of more robust and accurate modeling tools and the development of cutting-edge experimental techniques. Furthermore, it addresses advanced topics, such as crystallization during the solidification processes, prediction of fiber orientation in the cases of short and long fiber composites, prediction of the foaming process (such as microcellular foaming), and flow instabilities by including viscoelastic constitutive equations.
    Keywords: polymer electrolyte membrane for fuel cell ; molecular dynamics simulations ; side chain ; penetration ; injection molding ; thermoplastic composites ; mold heating ; mold temperature control ; melt filling ; thin wall injection molding ; suspensions ; micro-polar fluids ; yield stress ; extrusion ; extrudate swell ; interface tracking ; least-squares volume-to-point interpolation ; consistent PISO ; finite volume method ; OpenFOAM ; poly(ether ether ketone) ; thermo–mechanical response ; constitutive modeling ; polymer processing ; elongational flow ; vane extruder ; eccentric rotor extruder ; numerical simulation ; warpage ; prediction ; crystallinity ; multi-layer structure ; simulation ; annocatacin B ; ND1 subunit ; mitochondrial respiratory complex I ; MRC-I ; MD ; Hirshfeld charges ; MM/PBSA ; poly(lactic acid) ; urea ; melt blending ; slow-release fertilizer ; leakage flow ; modeling and simulation ; sheet die design ; manufacturing process design ; coat-hanger die ; modeling ; rheology ; constant shear-rate die ; non-Newtonian fluids ; poly (3-hydroxybutyric-co-3-hydroxyvaleric acid) (PHBV) ; flax ; hemp ; short fibers ; properties ; lithium-ion ; high energy pouch cell ; state of charge ; electrolyte ; load position ; motor core ; iron sheet ; computer-aided engineering tools ; gluing ; machine learning ; multilayer perceptron ; neural network ; regression ; plasticizing ; polymers ; basic settings ; data-based ; model ; quality ; conformal cooling ; sustainability ; industrial design ; manufacturing ; degree of assembly ; a family mold system ; CAE-DOE optimization ; green channels ; temperature maps ; finite difference methods ; meshless interpolation ; numerical solution ; polymer flows ; viscoelastic flows ; plastic optical barrel ; roundness ; concentricity ; Taguchi method ; RGD peptide (1FUV) ; ab initio molecular dynamics ; total bond order ; partial charge ; dielectric function ; suspension ; rodlike particles ; micropolar fluids ; anisotropy ; hysteresis ; fiber reinforced polymer composites ; lead nanoparticles ; shielding ; attenuation coefficient ; empirical derivation ; PEG-PCL ; non-isothermal crystallization ; flash differential scanning calorimeter ; polymer blends ; microstructure ; multiscale simulation ; hybrid injection molding ; continuous fiber-reinforced thermoplastics ; finite element analysis (fem) ; FDM ; Taguchi ; multilateral ; CAE ; transfer learning ; LDPE ; triangular-loop shear ; trapezoidal-loop shear ; time-dependent viscoelastic property ; Rivlin–Sawyers equation ; fillers ; rubber compounds ; viscoelasticity ; thixotropy ; structure ; tailings flocculation ; seawater ; calcium and magnesium removal ; lime ; sodium carbonate ; FEM ; pipe die ; polymer melt ; Herschel–Bulkley fluids ; free-surfaces ; conformal cooling channel ; rapid tooling technology ; mold material ; cooling medium ; polymer solution ; Giesekus ; eXtended Pom-Pom ; visualization ; analytical solution ; deep learning ; stacked learning ; Oldroyd-B fluid ; Giesekus fluid ; sphere drag coefficient ; plastic pallet ; flatness ; sequential valve gate system ; molding flow analysis ; particle settling ; dilute polymeric solutions ; Oldroyd-B model ; microfluidic rheometry ; drag coefficient ; hydraulic fracturing ; polyethylene recycling ; artificial engineering ; polymer extrusion ; mold additive manufacturing ; polymer molds ; subtractive manufacturing ; mold characterization ; rapid tooling ; thermal homogenisation ; pre-distribution ; heat pipe ; blown film extrusion ; CFD ; n/a ; pyrolysis ; mixed polymers ; thermogravimetric analyzer (TGA) ; artificial neural networks (ANN) ; polypropylene ; glass fiber ; fiber reinforced ; fiber shortening ; compound ; SIGMA ; dynamic image analysis ; Monte Carlo ; nanoporous matter ; proton ; transport behavior ; GEANT4 code ; boundary layer ; Herschel–Bulkley fluid ; Carbopol ; cement ; bacterial cellulose ; plasma treatment ; magnetron sputtering ; silver nanoparticles ; antimicrobial activity ; X-ray photoelectron spectroscopy ; fully implicit coupled solver ; viscoelastic flow ; log-conformation tensor approach ; non-isothermal effects ; Phan-Thien-Tanner constitutive equation ; semi-analytical method ; solvent viscosity contribution ; pipe flow ; channel flow ; Au nanoparticles ; plasmonics ; polymer matrix ; nanocomposite ; thermal annealing ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In recent years, we have been witnessing the exponential proliferation of the Internet of Things (IoT), networks of physical devices, vehicles, appliances and other items embedded with electronics, software, sensors, actuators and connectivity that enables these objects to connect and exchange data. Enabling the introduction of highly efficient IoT, wireless sensing and network technologies will reduce the need for traditional processes that are currently be carried out manually, thus freeing up the precious resources of dwindling working staff, to do more meaningful and human-centered work. This reprint aims to bring together innovative developments in areas related to IoT, wireless sensing and networking. The aspects covered include software-defined network (SDN)-based IoT networks, artificial intelligence (AI) for IoT, industrial IoT, smart sensors, optimization of energy efficiency for IoT, and wireless sensor networks, IoT applications for agriculture, smart cities, healthcare, localization and environment monitoring.
    Keywords: lawful interception ; hybrid SDN ; intercept access point ; minimum vertex cover ; text detection ; natural scene ; feature fusion ; soil water content ; sensor networks ; distributed sensing ; IoT measurements ; Precision Agriculture ; moisture sensor ; wireless communication ; LoRa ; LoRaWAN™ ; indoor localisation ; fingerprinting ; landmark ; wearable device ; inertial measurement device ; motion mode detection ; body shadowing compensation ; nearest neighbour ; label-free biosensor ; machine learning ; support vector machine ; artificial neural network ; principal component analysis ; Green IoT ; IIoT ; edge computing ; AI ; edge AI ; sustainability ; digital transition ; digital circular economy ; Industry 5.0 ; direction-of-arrival estimation ; geometric algebra ; ESPRIT algorithm ; electromagnetic vector-sensor array ; hardware security ; electromagnetic sensing ; real time ; cybersecurity ; anomaly detection ; the Internet of Things ; deep learning ; blockchain ; 5G/6G ; URLLC ; tactile Internet ; industrial IoT ; network emulator ; robotic simulator ; virtual testbed ; wireless power transfer ; energy harvesting ; power conversion efficiency ; single diode rectifier ; voltage doubler ; harmonic balance method ; autonomous sensor node ; wireless sensor network ; multi-tone signal ; full-wave simulations of PCB ; millimeter wave ; new radio ; unmanned aerial vehicles ; LoS blockage ; closed-from approximation ; rooftop deployments ; coverage path planning ; unmanned aerial vehicle ; cell decomposition ; decomposition methods ; energy-aware approaches ; energy optimal path ; multi-robot systems ; multi-UAV ; smart cities ; Internet of Things (IoT) ; sensors ; 6G ; wireless communications ; resilience ; climate change ; connectivity ; data ; wireless systems ; mobile sensors ; D2D ; technological development ; Internet of things ; LoRaWAN ; reliability ; downlink ; safety ; IoT ; LPWAN ; proximal soil sensor device ; conventional communication methods ; ultralow power consumption ; long-distance transmission ; economic value ; inventoried sensor devices ; digital twin ; LSTM model ; 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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  • 77
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Polymer-processing techniques are of the utmost importance for producing polymeric parts. They must produce parts with the desired qualities, which are usually related to mechanical performance, dimensional conformity, and appearance. Aiming to maximize the overall efficiency of the polymer-processing techniques, advanced modeling codes along with experimental measurements are needed to simulate and optimize the processes. Thus, this reprint exploits the digital transformation of the plastics industry, both through the creation of more robust and accurate modeling tools and the development of cutting-edge experimental techniques. Furthermore, it addresses advanced topics, such as crystallization during the solidification processes, prediction of fiber orientation in the cases of short and long fiber composites, prediction of the foaming process (such as microcellular foaming), and flow instabilities by including viscoelastic constitutive equations.
    Keywords: polymer electrolyte membrane for fuel cell ; molecular dynamics simulations ; side chain ; penetration ; injection molding ; thermoplastic composites ; mold heating ; mold temperature control ; melt filling ; thin wall injection molding ; suspensions ; micro-polar fluids ; yield stress ; extrusion ; extrudate swell ; interface tracking ; least-squares volume-to-point interpolation ; consistent PISO ; finite volume method ; OpenFOAM ; poly(ether ether ketone) ; thermo–mechanical response ; constitutive modeling ; polymer processing ; elongational flow ; vane extruder ; eccentric rotor extruder ; numerical simulation ; warpage ; prediction ; crystallinity ; multi-layer structure ; simulation ; annocatacin B ; ND1 subunit ; mitochondrial respiratory complex I ; MRC-I ; MD ; Hirshfeld charges ; MM/PBSA ; poly(lactic acid) ; urea ; melt blending ; slow-release fertilizer ; leakage flow ; modeling and simulation ; sheet die design ; manufacturing process design ; coat-hanger die ; modeling ; rheology ; constant shear-rate die ; non-Newtonian fluids ; poly (3-hydroxybutyric-co-3-hydroxyvaleric acid) (PHBV) ; flax ; hemp ; short fibers ; properties ; lithium-ion ; high energy pouch cell ; state of charge ; electrolyte ; load position ; motor core ; iron sheet ; computer-aided engineering tools ; gluing ; machine learning ; multilayer perceptron ; neural network ; regression ; plasticizing ; polymers ; basic settings ; data-based ; model ; quality ; conformal cooling ; sustainability ; industrial design ; manufacturing ; degree of assembly ; a family mold system ; CAE-DOE optimization ; green channels ; temperature maps ; finite difference methods ; meshless interpolation ; numerical solution ; polymer flows ; viscoelastic flows ; plastic optical barrel ; roundness ; concentricity ; Taguchi method ; RGD peptide (1FUV) ; ab initio molecular dynamics ; total bond order ; partial charge ; dielectric function ; suspension ; rodlike particles ; micropolar fluids ; anisotropy ; hysteresis ; fiber reinforced polymer composites ; lead nanoparticles ; shielding ; attenuation coefficient ; empirical derivation ; PEG-PCL ; non-isothermal crystallization ; flash differential scanning calorimeter ; polymer blends ; microstructure ; multiscale simulation ; hybrid injection molding ; continuous fiber-reinforced thermoplastics ; finite element analysis (fem) ; FDM ; Taguchi ; multilateral ; CAE ; transfer learning ; LDPE ; triangular-loop shear ; trapezoidal-loop shear ; time-dependent viscoelastic property ; Rivlin–Sawyers equation ; fillers ; rubber compounds ; viscoelasticity ; thixotropy ; structure ; tailings flocculation ; seawater ; calcium and magnesium removal ; lime ; sodium carbonate ; FEM ; pipe die ; polymer melt ; Herschel–Bulkley fluids ; free-surfaces ; conformal cooling channel ; rapid tooling technology ; mold material ; cooling medium ; polymer solution ; Giesekus ; eXtended Pom-Pom ; visualization ; analytical solution ; deep learning ; stacked learning ; Oldroyd-B fluid ; Giesekus fluid ; sphere drag coefficient ; plastic pallet ; flatness ; sequential valve gate system ; molding flow analysis ; particle settling ; dilute polymeric solutions ; Oldroyd-B model ; microfluidic rheometry ; drag coefficient ; hydraulic fracturing ; polyethylene recycling ; artificial engineering ; polymer extrusion ; mold additive manufacturing ; polymer molds ; subtractive manufacturing ; mold characterization ; rapid tooling ; thermal homogenisation ; pre-distribution ; heat pipe ; blown film extrusion ; CFD ; n/a ; pyrolysis ; mixed polymers ; thermogravimetric analyzer (TGA) ; artificial neural networks (ANN) ; polypropylene ; glass fiber ; fiber reinforced ; fiber shortening ; compound ; SIGMA ; dynamic image analysis ; Monte Carlo ; nanoporous matter ; proton ; transport behavior ; GEANT4 code ; boundary layer ; Herschel–Bulkley fluid ; Carbopol ; cement ; bacterial cellulose ; plasma treatment ; magnetron sputtering ; silver nanoparticles ; antimicrobial activity ; X-ray photoelectron spectroscopy ; fully implicit coupled solver ; viscoelastic flow ; log-conformation tensor approach ; non-isothermal effects ; Phan-Thien-Tanner constitutive equation ; semi-analytical method ; solvent viscosity contribution ; pipe flow ; channel flow ; Au nanoparticles ; plasmonics ; polymer matrix ; nanocomposite ; thermal annealing ; 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
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  • 78
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
    Keywords: EEG ; transfer learning ; review ; decoding ; classification ; e-textile ; head phantom ; electroencephalography ; conductive material ; mental stress ; data analysis ; connectivity network ; machine Learning ; deep learning ; vigilance decrement ; sustained attention ; mental fatigue ; cross-participant ; cross-task ; task-generic ; electroencephalogram ; wavelet spectrum ; ridge ; segmentation ; phase connectivity ; epilepsy ; traumatic brain injury ; feature extraction ; functional connectivity network ; time-frequency features ; machine learning ; ALS ; classifier ; neural ; connectivity ; frequency-specific ; BCI ; acupuncture ; dimensionality ; neural subspace ; latent variables ; attractor ; adaptive threshold ; coherence ; functional connectivity ; multilayer network ; otsu ; phase locking value ; weighted phase lag index ; complex Pearson correlation coefficients ; transcranial magnetic stimulation ; cerebral cortex stimulation ; electromagnetic influence ; neurostimulation ; brain activity ; virtual reality ; neuropathic pain ; spinal cord injury ; fractal dimension ; ERP ; speech discrimination ; seizure detection ; features ; feature selection ; motion artifact ; electroencephalogram (EEG) ; functional near-infrared spectroscopy (fNIRS) ; wavelet packet decomposition (WPD) ; canonical correlation analysis (CCA) ; 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
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  • 79
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint, entitled “Process Control and Smart Manufacturing for Industry 4.0”, contains the extended papers from the Series of annual IFSA conferences on Automation, Robotics and Communications for Industry 4.0/5.0 (ARCI) on the following topics: Process Automation, Process Control and Monitoring, Design Principles in Industry 4.0, Smart Manufacturing and Technologies, Smart Factories, Machine Learning and Artificial Intelligence in Manufacturing. The reprint contains 13 chapters written by 54 ARCI conference participants from seven countries: China, Croatia, Denmark, Germany, Italy, Poland and Romania. This reprint will inform readers of cutting-edge developments in the field and provide effective starting points and a road map for further research and development. All chapters follow the same structure: firstly, an introduction to the specific topic under study; secondly, a description of the field, including sensing or/and measuring applications. Each chapter ends with a curated list of references, including books, journals, conference proceedings and websites. “Process Control and Smart Manufacturing for Industry 4.0” is intended for researchers and scientists from academia and industry, as well as for postgraduate students.
    Keywords: steel alloys ; resistance spot welding ; RSW ; electrode wear ; electrode tip-dressing ; process monitoring ; mushrooming ; plateau forming ; quality control ; COVID-19 ; FDM ; 3D printing ; injection molding ; personal protection ; rapid prototyping ; protective face shields ; mechatronics line ; visual servoing system ; wheeled mobile robot ; industrial robotic manipulator ; Industry 4.0 ; NDT ; magnetic particle inspection ; optimization ; condition monitoring ; vibration ; acoustic emission ; drive train ; data fusion ; machine learning ; product morphology ; core data model ; phase rule filter ; phase private data model ; storage system ; forklift AGV ; deep learning ; semantic segmentation ; H-Swish ; community transformation ; community innovation governance ; ternary space ; coupling and coordination analysis ; lean manufacturing ; lean principles ; pull principle ; production control mechanisms ; production processes ; lean implementation ; batch process ; partial least squares ; multi-phase ; multi-mode ; master production scheduling ; make-to-order ; mathematical programming ; agent-based ; overtime ; earliness ; tardiness ; equipment selection decision ; business compass ; energy consumption ; processing time ; beetle antennae search algorithm ; sustainable blank dimension design ; energy-saving ; low-carbon ; grey wolf algorithm ; gas–solid ; cyclone ; separator ; gas dynamics ; erosion ; 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
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: In the era of the Internet of Things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques. The topic of advances in the image enhancement of electronics is presented in this reprint, which brings together the research accomplishments of researchers from academia and industry. The secondary goal of this reprint is to display the latest research results of advances in image enhancement.
    Keywords: dual networks ; enhanced CNN ; fine learning block ; image super-resolution ; attention mechanism ; convolutional neural networks ; deep learning ; generative adversarial networks ; multiple domains ; translate images ; restart strategy ; adaptive adjustment ; particle swarm optimization ; spline interpolation ; image denoising ; GAN ; optimization algorithm ; autoencoder ; ResNet ; object detection ; YOLOv5s ; image segmentation ; wavelet scattering ; loss function ; active contour ; medical image ; image stitching ; camera calibration ; layered projection ; binocular ranging ; stereo correction ; HOG ; feature fusion ; DHV recognition ; image enhancement ; cross stage partial network ; zero-reference ; Ghost module ; NDT registration ; map building ; RandLa-Net ; random sampling ; semantic segmentation ; capsule network ; power line scene recognition ; complex background ; Visual SLAM ; dynamic scene ; YOLOv5 ; K-means clustering ; probability update ; side-scan sonar ; segmentation ; CNN ; SE-block ; multi-channel ; blockchain technology ; electronic bidding ; system design ; A-star algorithm ; artificial potential field method ; least squares method ; path planning ; night image dehazing ; encoder–decoder architecture ; image fusion ; multi-scale network ; serial architecture ; U-net ; blind watermark removal ; low illumination ; Retinex theory ; histogram equalization ; wavelet transform ; color moments ; non-local mean filter ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: In today's global food market, ensuring both consumer satisfaction and the highest standards of safety is paramount. Food quality analysis covers chemical composition, physical properties, taste evaluation, and even traceability. Traditional methods are often slow, expensive, and eco-unfriendly due to their destructive nature. Here's the exciting part! Advanced spectroscopy techniques offer solutions. Imagine using non-destructive methods like X-rays, hyperspectral imaging, NMR, and Raman—quick, cost-effective, and eco-friendly, using less solvent. Now, let's demystify chemometrics—it extracts hidden info from spectra or image data, creating models for both qualitative and quantitative food analysis. This reprint presents recent advances in spectroscopy and chemometrics, focusing on their role in food analysis, quality evaluation, safety, and practical industry use. It's all about ensuring safe, delicious, and trustworthy food. Whether you're a curious consumer, food enthusiast, or industry insider, this reprint unveils cutting-edge methods for maintaining top food standards. With advanced spectroscopy and chemometrics, we're on track to boost consumer confidence in the food we love.
    Keywords: hyperspectral imaging ; pesticide residue ; table grape ; deep learning ; non-destructive detection ; Salvia spp. ; GC/Q-ToF analysis ; chemometrics ; quality evaluation ; chemical fingerprints ; 1H-NMR ; carbohydrates ; fruits ; PCA ; LDA ; laser-induced breakdown spectroscopy ; brown rice flour adulteration ; time-resolved spectra ; machine learning ; red pepper powder ; multivariate analysis ; moisture adjustment ; Theobroma cacao L. ; dry matter ; fermentation index ; protein content ; meliponine honey ; physicochemical properties ; biomes ; antioxidant potential ; mineral profile ; mass spectrometry analysis ; spatial frequency domain imaging (SFDI) ; optical properties ; absorption ; reduced scattering ; long short-term memory (LSTM) ; FTIR ; mid-infrared ; caprine milk ; milk absorbance spectra ; variance components ; sources of variation ; Fritillaria thunbergii ; heavy metals ; variable selection ; food analysis ; food authenticity ; food chemicals ; spectroscopy techniques ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. Additionally, navigation rules and regulations (i.e., knowledge) offer valuable prior knowledge about ship manners at sea. Combining multisource heterogeneous big data and artificial intelligence techniques inspires innovative and important means for the development of MASS. This reprint collects twelve contributions published in “Data-/Knowledge-Driven Behavior Analysis of Maritime Autonomous Surface Ships” Special Issue during 2021–2022, aiming to provide new views on data-/knowledge-driven analytical tools for maritime autonomous surface ships, including data-driven behavior modeling, knowledge-driven behavior modeling, multisource heterogeneous traffic data fusion, risk analysis and management of MASS, etc.
    Keywords: unmanned surface vehicle ; velocity obstacle ; collision avoidance ; obstacles classification ; fuzzy rules ; mixed waterborne traffic ; ship behavior ; ship autonomy ; information perception ; intelligent decision-making ; execution ; COLREGs ; ship object ; formal expression ; complex waters ; ship traffic flow ; spatiotemporal dependence ; gate recurrent unit ; motion planning ; unmanned surface vehicle (USV) ; effects of wind and current ; regularization-trajectory cell ; inland waterway transportation ; AIS data ; trajectory classification ; clustering ; deep convolutional neural network ; ship intention identification ; AIS ; RANSAC ; Bayesian framework ; YOLO ; intersection ; maritime autonomous surface ships ; hybrid causal logic ; preliminary hazard analysis ; risk assessment ; hazard identification ; autonomous ship ; ship manoeuvrability ; deduction of the manoeuvring process ; ship exhaust behavior ; detection and tracking ; multi-sensor ; deep learning ; morphological operation ; collision alert system (CAS) ; available maneuvering margins (AMM) ; ship domain ; ship stability ; maritime safety ; semantic modeling ; cognitive space ; multi-scale analysis ; ontology ; 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::TR Transport technology and trades
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Nowadays, Forestry has become an important field for the Environmental and Earth sciences due to its importance in global systems. While forest recreation focuses on forests as the main destination for public recreational activities, landscape protection refers to the conservation and restoration of natural beauty. Urban and peri-urban forests have become a place for the recreational activities of people living in big cities. They provide benefits to the quality of life. Landscape protection is also important, not only for scientific and ecological reasons but also for social and cultural ones. This reprint presents different contributions by the authors dealing with recent scientific research on forestry, recreational activities, landscape management, ecosystem services, etc., in different areas of the world.
    Keywords: tree cover loss ; environment ; degradation ; Mediterranean Region ; forest recreation ; ecosystem services ; forest management ; visitors monitoring ; single-track bike trails ; NEP ; nature experience ; Asia ; outdoor recreation ; urban forest ; green space ; airborne particulate matter ; meteorological parameters ; height ; air pollution ; particulate matter ; WAI ; urban trees ; brown leaf area index ; protected area management ; text mining ; natural language processing ; sentiment analysis ; multidimensional scaling method ; web scraping ; customer satisfaction ; TripAdvisor reviews ; endemic ; landscape protection ; conservation ; Magnolia sulawesiana ; habitat characteristic ; spatial distribution ; forest landscape ; deepsentibank ; deep learning ; geotagged photos ; human health ; forest air ; monoterpenes ; path analysis ; Pinus pinaster ; mountain biking ; recreation ; trade-off ; use conflict ; commercial forestry ; plantation forest ; Pinus radiata ; New Zealand ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics
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  • 84
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-01-05
    Description: This book focuses on the characterization of the physical properties of the Earth’s ionosphere, contributing to unveiling the nature of several processes responsible for a plethora of space weather-related phenomena taking place in a wide range of spatial and temporal scales. This is made possible by the exploitation of a huge amount of high-quality data derived from both remote sensing and in situ facilities such as ionosondes, radars, satellites and Global Navigation Satellite Systems receivers.
    Keywords: electron temperature ; topside ionosphere ; ESA Swarm satellites ; International Reference Ionosphere model ; Langmuir Probes in-situ data ; Incoherent Scatter Radar data ; GNSS ; GBAS ; ionospheric gradient anomaly ; one class support vector machine ; earthquake ; pre-earthquake anomalies ; swarm satellites ; ionospheric plasma ; deep learning ; physical mechanisms ; τ ; geomagnetic equator ; magnetic storm ; ionosphere ; vertical pulse sounding ; ionosonde ; ionogram ; software-defined radio ; radar imaging ; aspect angle ; field-aligned plasma irregularities ; mid-latitude E region ; norm-constrained Capon ; VHF radar ; plasma turbulence ; ionospheric irregularities ; ionosphere F region ; high latitude ; pressure-gradient current ; diamagnetic current ; swarm measurements ; oblique ionogram ; automatic inversion ; electron density profile ; quasi-parabolic segments ; the sporadic E layer ; internal fine structure ; high-resolution ionosphere imaging ; frequency domain interferometry technique ; auroral ionosphere ; E × B plasma motion ; ionospheric scintillation ; GNSS-R ; CYGNSS ; earthquakes ; polar ionosphere ; VIPIR ; Dynasonde ; Jang Bogo Station (JBS) ; Antarctica ; solar eclipse ; precise point positioning ; total electron content ; rate of total electron content index ; Swarm satellite measurements ; electron density ; main ionospheric trough ; high latitude trough ; ring ionospheric trough ; low latitude trough ; auroral diffuse precipitation ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint contains a summary of what has been presented at the 19th “Calorimetry for High Energy Physics Experiment” (CALOR) conference, which was held at the University of Sussex (Brighton, UK) in May 2022. The state of the art of particle detection, as well as of simulation tools for particle interactions with material, is presented and discussed by world leaders in the Research & Development of particle detectors, as well as early career researchers, sparking very exciting conversations within the detector development community during the five days of the conference.
    Keywords: ATLAS ; Tile Calorimeter ; calorimeter calibration ; calorimeter performance ; liquid scintillator ; PMTs ; calibration ; energy nonlinearity ; energy resolution ; dual calorimetry ; fast-timing ; electromagnetic calorimetry ; radiation-hard detectors ; LAr ; upgrade ; calorimeter ; readout ; electronics ; electromagnetic calorimeter ; compact muon solenoid ; high luminosity large hadron collider ; liquid argon detectors ; liquid argon calibration ; signal processing ; particle identification ; resolution ; pre-shower ; scintillating glass ; hadronic calorimeter ; high granularity calorimetry ; silicon photomultiplier ; cosmic rays ; calorimeters ; space instrumentation ; large detector systems for particle and astroparticle physics ; energy reconstruction ; cluster splitting algorithm ; resistive plate chambers ; gaseous imaging and tracking detectors ; hadron calorimetry ; dual-readout calorimetry ; future colliders ; Phase-1 ; commissioning ; calorimetry ; particle detectors ; photomultipliers ; Higgs factory ; crystal ; SiPM ; high granularity ; Geant4 ; geant-val ; simulation ; hadronic interaction ; test-beam ; Cherenkov calorimeter ; high-granularity ; neural network ; GNN ; CNN ; electromagnetic showers ; Cherenkov light ; optical fibres ; liquid argon ; plasma light source ; scintillation light ; dark photon ; signal reconstruction ; machine learning ; graph neural network ; high energy physics ; calorimeter reconstruction ; secondary electron emission ; radiation hardness ; forward calorimetry ; dual-readout ; ADRIANO2 ; JUNO ; JUNO-TAO ; neutrino detectors ; reactor neutrinos ; MAPS ; silicon detectors ; linear collider ; astroparticles ; γ-ray astronomy ; scintillation ; light yield ; tile calorimeter ; large hadron collider ; FCC ; liquified noble gas ; irradiation ; crystals ; scintillators ; protons ; neutrons ; proton CT ; image reconstruction ; proton tracking ; deep learning ; SiPMs ; calorimetry for high energy physics ; dual readout detector R&D ; PbF2 ; mechanics ; LHC ; trigger ; FPGA ; SLR ; LYSO ; intensity frontier ; ceramics ; time of flight ; ultrafast calorimetry ; charge transfer luminescence ; fast timing ; front-end ; MPPC ; flavour violation ; hadron calorimeter ; silicon photomultipliers ; CMS ; phase-2 ; HGCAL ; particle flow ; TileCal ; Phase-II upgrade ; quality assurance testing ; burn-in ; transformer-coupled buck converters ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: Radiomics is one of the most successful branches of research in the field of image processing and analysis, as it provides valuable quantitative information for the personalized medicine. It has the potential to discover features of the disease that cannot be appreciated with the naked eye in both preclinical and clinical studies. In general, all quantitative approaches based on biomedical images, such as positron emission tomography (PET), computed tomography (CT) and magnetic resonance imaging (MRI), have a positive clinical impact in the detection of biological processes and diseases as well as in predicting response to treatment. This Special Issue, “Image Processing and Analysis for Preclinical and Clinical Applications”, addresses some gaps in this field to improve the quality of research in the clinical and preclinical environment. It consists of fourteen peer-reviewed papers covering a range of topics and applications related to biomedical image processing and analysis.
    Keywords: deep learning ; segmentation ; prostate ; MRI ; ENet ; UNet ; ERFNet ; radiomics ; gamma knife ; imaging quantification ; [11C]-methionine positron emission tomography ; cancer ; atrial fibrillation ; 4D-flow ; stasis ; pulmonary vein ablation ; convolutional neural network ; transfer learning ; maxillofacial fractures ; computed tomography images ; radiography ; xenotransplant ; cancer cells ; zebrafish image analysis ; in vivo assay ; convolutional neural network (CNN) ; magnetic resonance imaging (MRI) ; neoadjuvant chemoradiation therapy (nCRT) ; pathologic complete response (pCR) ; rectal cancer ; radiomics feature robustness ; PET/MRI co-registration ; image registration ; fundus image ; feature extraction ; glomerular filtration rate ; Gate’s method ; renal depth ; computed tomography ; computer-aided diagnosis ; medical-image analysis ; automated prostate-volume estimation ; abdominal ultrasound images ; image-patch voting ; soft tissue sarcoma ; volume estimation ; artificial intelligence ; Basal Cell Carcinoma ; skin lesion ; classification ; colon ; positron emission tomography-computed tomography ; nuclear medicine ; image pre-processing ; high-level synthesis ; X-ray pre-processing ; pipelined architecture ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PN Chemistry
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: Each year, natural hazards, such as earthquakes, landslides, avalanches, tsunamis, floods, wildfires, severe storms, and drought, , affect humans worldwide, resulting in deaths, suffering, and economic losses. According to insurance broker Aon, 2010–2019 was the worst decade on record for economic losses due to disasters triggered by natural hazards, amounting to USD 3 trillion, which is USD 1 trillion more than for the period of 2000–2009. In 2019, the economic losses from disasters caused by natural hazards were estimated at over USD 200 billion (UNDRR Annual Report, 2019). In this context, remote sensing shows high potential to provide valuable information, at various spatial and temporal scales, concerning natural processes and their associated risks. The recent advances in remote sensing technologies and analysis, in terms of sensors, platforms, and techniques, are strongly contributing to the development of natural hazards research. With this Special Issue titled “Remote Sensing for Natural Hazards Assessment and Control”, we proposed state-of-the-art research that specifically addresses multiple aspects on the use of remote sensing (RS) for Natural Hazards (NH). The aim was therefore to collect innovative methodologies, expertise, and capabilities to detect, assess, monitor, and model natural hazards. The present Special Issue of Remote Sensing encompasses 18 open access papers presenting scientific studies based on the exploitation of a broad range of RS data and techniques, as well as focusing on a well-assorted sample of NH types.
    Keywords: wildfires ; hillslope erosion ; satellite imagery ; rainfall erosivity ; RUSLE ; rockfall source areas ; identification ; relief ; slope angle ; rock mass strength ; rockfall susceptibility ; land subsidence ; Geographic Information System (GIS) ; InSAR ; machine learning algorithm ; meta-heuristics ; Iran ; k-Nearest Neighbor ; Random Forest ; fires ; Landsat 8 ; Sentinel 2 ; Terra ; ASTER ; MODIS ; burned ; mapping ; hazard chain ; turbidity ; suspended sediment detection ; extreme climate events ; tailing dam risk management ; spatiotemporal pattern mining ; El Niño ; remote sensing ; geographic information system ; flash floods ; visual analysis ; SAR offset tracking ; glacier surface velocity ; glacier instability ; glacier hazards ; ice avalanches ; ENSO ; glacier mass balance ; glacier surface energy ; earthquake ; coseismic effects ; field line resonance ; acoustic gravity waves ; lithosphere-magnetosphere coupling ; burnt area monitoring ; Australia ; Sydney ; wildfire ; earth observation ; mid-resolution sensors ; time series analysis ; burn severity ; climate zones ; deep learning ; PRISMA ; burned area ; Sentinel-2 ; morphological operator ; convolutional neural network ; casualty prediction ; importance assessment ; spatial division ; support vector regression ; digital image correlation ; phase correlation ; optical flow ; time series image stack ; landslides ; ground motion identification ; displacement mapping ; UAS ; risk assessment ; random forest ; DInSAR ; Yan’an city ; settlement prediction ; reclaimed land ; exponential model ; Asaoka method ; wide-area deformation ; deformation detection ; time-series InSAR ; stacking ; Turpan–Hami basin ; heavy rainfall ; shallow landslides ; TRIGRS model ; spatial distribution ; susceptibility assessment ; Longchuan County ; Guangdong Province ; MT-InSAR ; ground deformation monitoring ; Sentinel-1A/B ; image partition ; block adjustment ; Gaofen-2 ; Interferometric synthetic aperture radar (InSAR) ; freeze–thaw processes ; permafrost ; Qilian Mountains ; natural hazards ; hazard ; vulnerability ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Neurodegenerative disorders (NDs) are becoming more prevalent in our aging population, and traditional methods of monitoring ND symptoms can be challenging. Wearable technology offers several advantages, such as continuous monitoring, objective measurements, and remote monitoring. The present reprint includes a collection of eleven research and review articles that propose wearable solutions and explore signal processing, machine learning, and deep learning approaches for the computerized diagnosis and monitoring of NDs. Topics covered include using wearable technology to measure blood pressure, movement, sleep patterns, and brain activity, and developing predictive models to support clinicians in making informed decisions about treatment and care. This reprint is a valuable resource for anyone interested in the potential of wearable technology to improve the diagnosis and management of NDs.
    Keywords: gait analysis ; Parkinson’s disease ; convolutional neural networks ; gate recurrent units ; deep learning ; cardiovascular diseases ; blood pressure ; hypertension ; photoplethysmography ; artificial neural networks ; neurodegenerative disease ; remote monitoring ; telemonitoring ; wearable sensor ; Parkinson’s Disease ; image processing ; hypomimia ; FE ; classic techniques ; machine learning ; ANN ; KNN ; machine learning (ML) ; naïve Bayes classification ; SVM ; bradykinesia ; wearables ; inertial sensors ; artificial intelligence ; Internet of Things ; trust management ; healthcare ; digital revolution ; edge clouds ; security ; privacy preservation ; neurological disorders ; wearable sensors ; frequency harmonics ; gait impairments ; gait ; harmonic ratio (HR) ; smoothness ; symmetry ; older adults ; inertial sensor ; biofeedback ; neurodegenerative diseases ; movement anticipation ; rs-fMRI ; classifications ; high-order neuro-dynamic functional network ; Alzheimer’s disease ; sleep monitoring ; sleep disorders ; Parkinson disease ; dementia ; Alzheimer Disease ; video analysis ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This reprint focuses on monitoring and analysis of the relationship between urbanization and ecosystem services on the different scales. The use of innovative technologies for land cover change monitoring, ecosystem services modeling and mapping, innovation in land use planning, and which highlight the potential of technologies to tackle challenges such as sustainability of urbanization, climate change adaptation, sustainable land management, and food security are of particular interest.
    Keywords: urbanization ; land use–land cover change ; landscape pattern ; green space area ; ecosystem services ; Jakarta ; Changchun ; China ; air pollution removal ; ecosystem assessment ; food security ; heat mitigation ; urban green areas ; urban recreation ; urban ecosystem services ; land cover ; Copernicus ; land monitoring ; CORINE land cover ; carbon storage capacity ; EAGLE matrix ; nature-based solutions ; conservative agriculture ; erosion protection ; water regulation and supply ; N balance ; ecosystem services flows ; land consumption ; Italy ; ecosystems governance ; knowledge ; regulations ; Urban Agenda for the EU ; under-used spaces ; urban regeneration ; carbon budget ; spatiotemporal patterns ; drivers ; Yangtze River Delta ; coupling coordination relationship ; Inner Mongolia ; deep learning ; convolutional neural networks ; land consumption mapping ; remote sensing ; semantic segmentation ; urban–rural continuum ; land use efficiency ; SDG ; urban expansions ; population dynamics ; ecosystem accounting ; SEEA-EA ; MAES ; EAGLE ; carbon stock ; crop production ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.
    Keywords: live fuel moisture content ; deep learning ; ensemble learning ; multi-source remote sensing ; spatiotemporal fusion ; dilated convolution ; improved transformer encoder ; global correlation information ; semantic segmentation ; attention mechanism ; robust deep learning ; remote sensing ; data fusion ; low-light image enhancement ; retinex theory ; remote-sensing ; orbital angular momentum ; mode detection ; fine-grained image classification ; attention pyramid ; atmospheric turbulence ; sea surface temperature ; mutual information ; LSTM ; self-attention ; interdimensional attention ; noise suppression deblurring ; curriculum learning ; image reconstruction ; turbulence degradation ; depthwise separable convolutional neural networks ; spectrogram augmentation ; sound detection ; vehicle detection ; image super-resolution ; model design ; evaluation methods ; maritime communication ; evaporation duct ; multi-dimensional prediction model ; digital surface model ; multimodal ; multi-scale supervision ; feature separation ; reconstruction refinement ; significant wave height ; autoencoder ; principal component analysis ; SAR ; altimeter ; Gaussian process regression ; convolutional neural network ; computer vision ; solar farm ; solar panel ; capacity estimation ; photovoltaics ; optical remote sensing ; peri-urban forests ; lightweight convolutional neural network ; FlexibleNet ; carbon sequestration ; semi-supervised learning ; few-shot learning ; SAR target recognition ; discriminative representation learning ; remote image ; CNN ; multiscale feature fusion ; Transformer ; improved Tversky loss ; two-step convolution model ; cloud detection ; cloud matting ; cloud removal ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint includes impactful chapters related to document-image related visual sensing, which do present and comprehensively discuss selected scientific concepts, frameworks, architectures and ideas on sensing technologies and machine-learning techniques. Indeed, document imaging/scanning approaches are essential techniques for digitalizing documents in various real-world contexts. This reprint emerging from the Special Issue "Document-Image Related Visual Sensors and Machine Learning Techniques” can be viewed as a result of the crucial need for document management systems. Such technologies are being applied in various fields or different domains and parts of the world to address relevant challenges that could not be addressed without the advances made in these technologies. The reprint includes impactful chapters that present scientific concepts, frameworks, architectures and innovative ideas on sensing technologies and machine-learning techniques to overcome a series of key challenges related to document imaging/scanning, text detection, text recognition, and documents clustering.
    Keywords: feature learning ; incomplete multimedia data ; fuzzy c-means ; variational autoencoder ; multispectral imaging ; document scanning ; portable sensor ; depth image filtering ; point clouds filtering ; Kinect v2 ; depth resolution ; close range ; hand pose ; image binarization ; optical character recognition ; document images ; local thresholding ; image pre-processing ; natural images ; scene text recognition ; visual sensor ; text position correction ; encoder-decoder network ; chart recognition ; deep learning ; visualization ; classification ; detection ; perspective correction ; house architecture type classification ; house type classification ; convolutional neural networks ; document classification ; feature selection ; data augmentation ; imbalanced dataset ; scene text detection ; multiple scales ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
    Language: English
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  • 92
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Sustainability is a critical global challenge that requires comprehensive assessments of environmental, social, and economic indicators. The formulation of the 17 Sustainable Development Goals (SDGs) represents a significant leap forward in humanity's pursuit of sustainability. The SDGs now serve as a shared platform for global development, guiding current actions towards and shaping visions of a sustainable future. Monitoring progress towards the SDGs and sustainability in general is essential. This is true not only at the global and national scales, but also at the subnational and landscape levels. Geographic information science (GIScience) and remote sensing (RS) have made significant advances in these areas. These breakthroughs include the increasing availability of geospatial data, a development which plays a crucial role in this regard. This Special Issue aimed to bring together novel contributions on the assessment of sustainability and sustainability-related indicators over space and time using geospatial data, tools, and techniques (GIScience and RS). This publication contains 11 peer-reviewed papers, including two review articles and nine research articles.
    Keywords: sustainable development ; Earth observation ; SDG indicators ; EO4SDG ; SDG global indicator framework ; global SDG indicators database ; social-ecological indicators ; Urban Surface Ecological Status (USES) ; Remotely Sensed Surface Ecological Index (RSUSEI) ; sustainability ; impervious surfaces ; US cities ; National Land Cover Database (NLCD) ; wetland ; muthurajawela marsh and negombo lagoon ; socio-ecological ; spatio-temporal analysis ; urban ecology ; remote sensing ; conflict resources monitoring ; disease control and prevention ; human rights ; genocide tracking ; human rights violation ; geopolitics ; population mapping ; Landsat ; deep learning ; multi-temporal ; ResNet-N ; Google Earth Engine ; China ; SDGs ; remote sensing ecological index ; ecological protection ; principal component analysis ; entropy value method ; spatial autocorrelation ; Wuhan city ; M-RSEQI ; DMSP ; entropy method ; coupling coordination degree model ; remote sensing data ; urbanization ; sustainable development path ; life service resources ; spatial justice ; GIScience ; Beijing ; SDG11 ; geospatial big data ; sustainable development goals ; earth observation ; Guilin ; intra-urban heat island ; space-time ; GIS ; land use and land cover change ; shifting cultivation ; tropical forest gain and loss ; topographic factors ; distance to roads ; logistic regression ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-01-05
    Description: This book focuses on the recent advancements in both fundamental and clinical research, focusing on identifying, developing, and applying new and improved biological markers for specific neurologic disorders in the future. The original research work and review articles published here highlight some unique mechanisms underlying the most prevalent pathophysiological conditions affecting human health. Other areas covered in the book include emerging treatment options and correct diagnoses using different biochemical and imaging techniques.
    Keywords: Alzheimer’s disease ; amyloid beta ; hippocampus ; Kir channels ; K+ channels ; glioblastoma multiforme ; low-grade glioma ; astrocytoma ; recurrence ; multifocal growth ; mRNA expression ; MPS1 ; TTK ; therapy ; EDTA chelation therapy ; neurodegenerative diseases ; metal detoxification ; reactive oxygen species (ROS) ; neuroinflammation ; neurodegeneration ; cognitive dysfunction ; neurofibrillary tangles ; diagnosis methods ; biomarkers ; perinatal stress ; NURR1 ; inflammation ; late-onset diseases ; early life ; artificial neural network ; deep learning ; Parkinson’s disease ; atypical parkinsonian syndrome ; dopamine transporter SPECT ; β-Amyloid ; calpain ; Collapsin Response Mediator Protein-2 ; human-neuroblastoma SH-SY5Y cells ; Somatostatin-14 ; somatostatin receptor ; brain injury ; quinpirole ; dopamine D2 receptors ; glial cell ; autophagy ; mitophagy ; multiple sclerosis ; biomarker ; neurons ; astrocytes ; Alzheimer’s and Parkinson’s diseases ; fluid and imaging biomarkers ; amyloid-β and tau ; miRNA ; extracellular vesicles ; exosomes and ectosomes ; PET ; radiotracers ; radiolabeled molecules ; n/a ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint compiles the articles, communications, and review articles from top researchers describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles. This reprint encompasses the key topics related to drone design, communications as well as autonomous Flight and Navigation. Special attention is paid to the drones’ applications to environmental and earth sciences, including in agriculture, forestry, water, and marine environments; other innovative applications are also explored including in relation to the field of application, such as the inclusion of new deep learning techniques.
    Keywords: convolutional neural network ; deep learning ; transfer learning ; point clouds ; structural damage assessment ; vegetation indices ; RGB cameras ; unmanned aerial vehicle (UAV) ; empirical line method ; Green leaf index ; open aerial map ; autonomous ; hexacopter ; water quality ; water stratification ; water temperature ; drones ; Martian atmosphere ; thermal analysis ; aerodynamics ; thermoelectric generators ; hyperspectral images ; multispectral data ; machine learning ; ice detection ; UAS ; GCP ; 3D point cloud ; DSM ; image processing accuracy ; actual evapotranspiration ; high spatiotemporal resolution ; multispectral imagery ; thermal infrared imagery ; METRIC energy balance model ; irrigated field crops ; precision agriculture ; travelling salesman problem ; UAV-based precision farming ; Euclidean distance ; Voronoi ; site-specific fertilizer spray ; UAV ; RPAAS ; aerial application ; backpack sprayer ; spray deposition ; droplet spectra ; palmer amaranth ; morningglory ; Reforming-Controlled Compression Ignition ; UAV applications ; exergy analysis ; hydrogen ; dimethyl ether ; fuel reactivity control ; FANETs ; ad hoc networking ; drone swarms ; efficient routing ; traffic monitoring ; 4G/LTE ; VPN ; real-time video ; computer vision ; unmanned aerial systems ; autonomous systems ; wildland fire ; forest fires ; fire detection ; UAVs ; safety ; signal processing ; condition-based maintenance ; structural health monitoring ; fault diagnostics ; fault mitigation ; contingency planning ; streamflow ; sediment loading ; digital terrain model ; rocky coast ; Galicia ; ecosystems ; geomorphic change detection ; GIS ; drone ; dragonfly ; insect ; biomimetic ; biological inspiration ; design ; remote sensing ; coral reefs ; linear unmixing ; R ; Google Earth Engine ; persistent surveillance ; hierarchical architecture of UAV teaming ; communication aware UAV formation ; dynamical object tracking ; intercommunication quality ; UAV-based monitoring ; agricultural robotics ; plant disease detection ; RGB images ; Cercospora leaf spot ; CNNs ; semantic segmentation ; phenotyping ; bog ; Oculus Quest 2 ; Mer Bleue ; SfM ; augmented reality ; AR ; unmanned aerial systems (UAS) ; aerial photogrammetry ; habitat monitoring ; braided river habitats ; efficiency ; data envelopment analysis (DEA) ; civilian use ; factors ; design and selection ; law-making ; mind-mining ; expert groups ; literature study ; triple helix model (THM) ; analytic hierarchy process (AHP) ; collision avoidance ; depth cameras ; point cloud ; CPU ; GPU ; spiral ; Mars ; autogyro ; gyroplane ; autonomous flight ; indoor positioning ; cyber pilot ; sensor fusion ; distributed electric propulsion ; boundary layer ingestion ; propeller ; fixed wing ; aerial drones ; autonomous navigation ; path planning ; reactive control ; obstacle avoidance ; sense-and-avoid ; hybrid navigation method ; dynamic environments ; small unmanned aircraft systems ; photogrammetry ; structure-from-motion ; wind impact ; turbulence ; crash scene reconstruction ; traffic incident management ; detection ; CBRNe ; MOX ; chemical sensor ; simulation ; fluid dynamics simulations ; green water ; integrated water management strategies ; smallholder farms ; water productivity ; localization ; communication ; drone swarm ; lidar ; streams ; canopy height ; roughness ; vegetation density ; change detection ; NB-IoT ; network analysis ; simulations ; landslides ; multispectral ; RGB ; vegetation monitoring ; legislation ; ethics ; spatial social sciences ; advanced leak detection ; advanced leak quantification ; source estimation ; environmental monitoring ; landfill ; natural gas ; human–swarm interaction ; situation awareness ; user-centered interface design ; thermal imaging ; blackbody ; emissivity ; thermography ; base stations ; cellular networks ; photovoltaic system ; battery ; search and rescue ; autonomous drones ; acceleration ; deceleration ; drone classification ; CNN ; HERM lines ; micro-Doppler ; radars ; aeromagnetics ; drone survey ; mineral exploration ; geophysical prospecting ; speed ; RFID ; inventory ; labor ; forecast ; drone technology ; aquaculture ; precision aquaculture ; aquaculture monitoring ; aquaculture drones ; internet of things ; swarm robotics ; unmanned aerial vehicle ; evolutionary game theory ; evolutionary algorithm ; surveillance system ; multi-objective optimisation ; digital elevation model (DEM) ; digital surface model (DSM) ; orthomosaic ; Earth observation ; unmanned aerial vehicles (UAV) ; social acceptance ; urban air mobility (UAM) ; CORUS-XUAM ; proper orthogonal decomposition ; cellular-enabled drones ; aerial base stations ; 5G/B5G/6G cellular networks ; gesture recognition ; small drone ; long-distance surveillance ; ground target tracking ; track-to-track association ; image-to-position conversion ; anti-collision radar ; autonomous flight unmanned aerial system ; obstacle detection ; radar mapping ; unmanned aerial system (UAS) ; n/a ; grazing density ; nutrient ; pasture management ; forage grass ; 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
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Agricultural productivity should increase to meet the growing food demand. Tillage is defined as the mechanical manipulation of agricultural soil, and it is an extremely vital part of crop production, particularly for seedbed preparation and weed control. Tillage operations are carried out using mechanical force, commonly with a tractor-drawn tool to achieve the cutting, inversion, pulverization, and disturbance of soil. A significant part of the energy (from fossil fuels) used in crop production is expended in tillage. This energy use results in greenhouse gas emissions. It is essential that we reduce energy use (hence, greenhouse gas emissions) to achieve sustainable farming practices and improve crop production and design new tillage tools or optimize the existing tools. Although the design and evaluation of tillage tools are generally carried out using analytical methods and field experiments, with recent technological improvements, computer technology has been used for the design and evaluation of tillage tools. Additionally, sensor technology can improve the efficiency of tillage tools. This Special Issue collated innovative papers that make a significant contribution to the design and application of agricultural equipment in tillage systems. It involved original research and review papers from different research fields, such as agricultural engineering, engineering simulation, and precision agriculture.
    Keywords: deep learning ; machine vision ; weeder ; smart agriculture ; mechanical control ; agricultural ; unmanned ; electrical tractor ; no-tillage ; disc ; spring-tine ; soil ; property ; traffic ; rapeseed transplanting ; hole-forming device ; key components ; experiment ; electric tractor ; motor efficiency ; dual motor coupling drive ; I-SA algorithm ; generalization ability ; parameter identification ; image processing ; two-wheeled robot trailer ; steering control ; strip farming ; no-tillage sowing ; sowing strip cleaning ; spiral discharge straw ; discrete element simulation ; anti-blocking and row-sorting ; compound planter ; ditching ; soil separation spiral ; discrete element method ; parameter optimization ; agricultural machinery ; HMCVT ; correction of characteristics ; I-PSO algorithm ; parameter match ; residual film recovery machine ; DEM ; virtual simulation ; hydro-mechanical continuously variable transmission ; tractor ; optimization design ; simulation experiments ; I-GA ; geometric principle ; plough ; ploughshares ; durability calculation method ; agricultural machine ; wear ; plasma-hardening surface ; simulation ; quality improvement ; improved genetic algorithm ; full-factorial test ; single evaluation index modeling method ; control strategy ; soil cover ; discrete element ; soil-covering thickness ; seed offset ; rice combine harvester ; throwing device ; wind blades ; fluid analysis ; deflector optimization ; throwing width ; cotton recovery device ; EDEM ; parameters optimization ; MBD ; coupled simulation ; seeding ; soybean ; seed–soil ; corn seed ; collision restitution coefficient ; residual film recovery device ; response surface regression model ; seedbed clearing and shaping ; stone removal rate ; seeding furrow ; dry direct-seeded rice ; discrete element modeling ; dual vs. single tyres ; rut depth ; soil bearing capacity ; soil displacement ; tractive efficiency ; tyre size and inflation pressure ; Kmeans ; DBSCAN ; GMM ; tilling depth ; well-cellar cavitating mechanism ; MBD-DEM bidirectional coupling model ; optimal design ; cavitating law ; flat disc ; analytical force prediction model ; discrete element method (DEM) ; soil-tool interaction ; disc seeder ; disc blade ; force prediction ; semi-analytical model ; sandy soil ; stubble management ; no-till sowing ; stalk cutting ; post-harvest ; prototype ; multi-body dynamics (MBD) ; DEM-MBD coupling ; topsoil burial ; tillage ; traction ; compaction ; neural networks ; support vector regression ; fuzzy inference system ; adaptive neuro-fuzzy inference system ; calibration ; DEM contact models ; soil dynamics ; soil failure ; soil forces ; cohesive and frictional soils ; 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
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint focuses on applications of machine learning models in a diverse range of fields and problems. It reports substantive results on a wide range of learning methods; discusses the conceptualization of problems, data representation, feature engineering, machine learning models; undertakes critical comparisons with existing techniques; and presents an interpretation of the results. The topics within the chapters of the publication fall into six categories: computer vision, teaching and learning, social media, forecasting, basic problems of machine learning, and other topics.
    Keywords: robust matrix factorization ; student grade prediction ; educational data mining ; side information graph ; personal teaching and learning ; deep multi-target prediction ; Felder–Silverman learning style ; adaptive e-learning systems ; artificial neural network ; deep learning ; transfer learning ; student performance prediction ; Machine learning analysis ; sentence modeling ; topic analysis ; cross referencing topic ; machine learning ; classification ; preprocessing ; instance selection ; data mining ; predictive analytics ; sales ; performance measurement ; human resources ; rumor refuter ; nature language processing ; XGBoost ; feature analysis ; Bitcoin ; higher order neural network ; volatility forecasting ; hybrid models ; warehouse optimization ; genetic algorithms ; crossover ; construction productivity ; construction safety ; synthetic data ; tracking ; academic performance ; course grades ; grade point average ; prediction ; undergraduate ; cloud detection ; superpixel segmentation ; convolutional neural networks ; support vector machines ; machine learning algorithms ; multiple linear regression ; SVM ; management ; social network services ; image representation ; local features ; autoencoder ; convolutional neural network ; user generated content ; sentiment analysis ; keyword extraction ; text representation ; sampling ; TripAdvisor ; adaptive camouflage ; convolutional neural network (CNN) ; k-means ; object detection ; image completion ; saliency detection ; social media ; micro-blogs (Twitter) ; towards recommending influencers based on topic classification ; investigation framework ; comparison of various techniques for topic classification ; cost-benefit function ; partial differential equations ; physics-informed neural network ; wave equation ; KdV-Burgers equation ; KdV equation ; neural network ; cyclical learning rate ; remote sensing ; scene classification ; backscatter data ; lidar ceilometer ; weather detection ; online taxi-hailing demand ; backpropagation neural network ; extreme gradient boosting ; real-time prediction ; climate zone ; climate change impact ; Jhelum River Basin ; Chenab River Basin ; support vector machine ; decision tree ; large-scale dataset ; relative support distance ; support vector candidates ; answer set programming ; non-deterministic automata induction ; grammatical inference ; geopolymer concrete ; deep neural network ; ResNet ; compressive strength ; fly ash ; sleep apnea ; airflow signal ; Gaussian Mixture Models (GMM) ; cyber security ; vulnerability detection ; word embedding ; drifter trajectory ; evolutionary computation ; NCLS ; stock performance ; earning rate ; volatility ; heatwaves ; big data ; random forest regression model ; semi-regression ; early prognosis ; interpretation ; COREG algorithm ; cascaded classifier ; computer vision ; construction site management ; consumer classification ; over-the-top ; time-aware classification ; code auto-completion ; GPT-2 model ; advanced design methods ; mass operator ; structural stress ; live prediction ; vibration test ; genetic programming ; parsing expression grammar ; BiLSTM ; BERT ; NLP ; context-aware ; LDA ; LSTM ; crowdfunding ; project recommendation system ; optimization ; weather nowcasting ; deep neural networks ; autoencoders ; Principal Component Analysis ; learning classifier systems ; anticipatory classifier systems ; reinforcement learning ; OpenAI gym ; healthcare ; COVID ; time-series predictions ; ARIMA ; Prophet ; GRNN ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
    Keywords: EEG ; transfer learning ; review ; decoding ; classification ; e-textile ; head phantom ; electroencephalography ; conductive material ; mental stress ; data analysis ; connectivity network ; machine Learning ; deep learning ; vigilance decrement ; sustained attention ; mental fatigue ; cross-participant ; cross-task ; task-generic ; electroencephalogram ; wavelet spectrum ; ridge ; segmentation ; phase connectivity ; epilepsy ; traumatic brain injury ; feature extraction ; functional connectivity network ; time-frequency features ; machine learning ; ALS ; classifier ; neural ; connectivity ; frequency-specific ; BCI ; acupuncture ; dimensionality ; neural subspace ; latent variables ; attractor ; adaptive threshold ; coherence ; functional connectivity ; multilayer network ; otsu ; phase locking value ; weighted phase lag index ; complex Pearson correlation coefficients ; transcranial magnetic stimulation ; cerebral cortex stimulation ; electromagnetic influence ; neurostimulation ; brain activity ; virtual reality ; neuropathic pain ; spinal cord injury ; fractal dimension ; ERP ; speech discrimination ; seizure detection ; features ; feature selection ; motion artifact ; electroencephalogram (EEG) ; functional near-infrared spectroscopy (fNIRS) ; wavelet packet decomposition (WPD) ; canonical correlation analysis (CCA) ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Energy plays a decisive role in realizing the Sustainable Development Goals (SDGs), such as employment growth, industry, innovation, and infrastructure, sustainable cities and communities, clean energy, and climate change. This reprint, titled “Recent Advancements in Sustainable Solar Photovoltaic Power Technology”, presents significant works in the field of solar photovoltaic systems and critical issues in solar power generation technology, as well as the latest achievements and current problems in solar power generation technology and proposing corresponding solutions to key technical challenges in the utilization of solar power, pointing out future directions for achieving the SDGs through solar power generation technology.This reprint provides a variety of comprehensive reviews on solar power generation technologies like maximum power point tracking (MPPT) techniques, power electronic converter topologies, and parameter estimation of PV cells. Along with reviews, this book also outlines the latest developments in the field of MPPTs, converters, cooling systems, rooftop, as well as grid-connected PV systems. This reprint will serve as a reference and update for academics, researchers, and practicing engineers to inspire new research and developments that pave the way for next-generation PV systems for residential and small commercial applications.This reprint includes three reviews and twelve articles focused on solar photovoltaic power technology.
    Keywords: brushless DC motor (BLDC) ; maximum peak point tracking (MPPT) ; photovoltaic (PV) systems ; electric vehicle (EV) applications ; marine predator algorithm (MPA) ; PV model ; parameter extraction ; metaheuristic ; current-mode control ; photovoltaic system ; bifurcations diagrams and Lyapunov exponent graphics ; Runge–Kutta method ; Matlab and PSIM software ; DC-DC converters ; inverted output voltage ; electric vehicles ; hybrid systems ; non-isolated converters ; Cuk converter ; Mahafzah converter ; continuous current mode ; building-integrated photovoltaics ; roof-integrated photovoltaics ; photovoltaic module temperature ; building-integrated photovoltaic system temperature ; three-phase interleaved parallel bidirectional converter ; electric vehicle ; output voltage stability ; power quality ; high-order sliding-mode control ; constant power load ; GPI observer ; algorithm ; GA ; PSO ; PSO–LSTM ; search space ; energy analysis ; microgrid ; photovoltaic cell ; deep learning ; distributed power generation ; multi-population ; HGTO-BWO ; parameters estimation ; PV cell/panel ; photovoltaic ; MPPT ; partial shading ; global peak ; MPPT classification ; horse herd optimization ; adaptive fractional order PID controller ; sensitivity analysis ; power quality and quantity analysis ; maximum power point tracking ; power loss ; shading scenarios ; fill factor ; improved Su-Do-Ku ; mismatch loss ; photovoltaic generation ; butterfly optimization algorithm ; particle swarm optimization ; partial shading conditions ; solar energy ; panel cooling systems ; multi-criteria evaluation ; Visual PROMETHEE ; Renewable Energy Sources (RESs) ; Photovoltaic (PV) systems ; Switched Capacitor (SC) ; Reduced Switch Count Multilevel Inverter (RSC-MLI) ; Common Ground Switched-Capacitor (CGSC) ; Reliability ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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  • 99
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Archaeology, geography, and the Earth sciences are an integrated field devoted to researching nature, the environment, humanity, and the social sciences. Remote sensing systems have been widely applied for data acquisition at various spatial scales. Innovations in image and signal processing, IoT, big data, and deep learning models induce new potentials in the reconstruction and exploration of ancient people’s material culture and lives. This Special Issue focuses on applying remote sensing techniques coupled with a data mining method to analyze and discuss humanity-, geography-, and environment-related contexts. The formal integration of archaeology and geography has been conducted over the past twenty or thirty years. In spite of this, continuous innovations, whether in imaging spectroscopy and multimodal imaging or in imaging computing using deep learning models, still motivate scholars to address related issues. The aim of this Special Issue is to compile the latest achievements in the field and to open up a forum where scholars can contribute their unique findings.
    Keywords: multi-sensor data ; landscape features ; landform recognition ; cultural relics ; deep learning ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint highlights the importance of Deep Learning (DL), which has garnered significant attention in science, industry, and academia. It draws inspiration from the functioning of the human brain and the concept of learning. Unlike traditional and machine learning methods, deep learning techniques emulate the human brain's neural networks at a lower scale, allowing them to process and analyze substantial quantities of unstructured data. The remarkable proficiency of deep learning in unveiling intricate structures within extensive datasets genuinely resembles the extraordinary aptitude of the brain to recognize patterns and form complex connections. This unique characteristic allows DL to excel in modeling and solving complex problems across various scientific and technological fields. Just as the brain learns from experience, DL architectures learn through algorithms from data by adjusting numerous parameters during training to optimize their performance and accuracy. This concept of learning and adaptation is fundamental to DL's success. This reprint serves as an excellent opportunity to disseminate current knowledge beyond academic boundaries, reaching a diverse audience encompassing academics, professionals, and the general public. This wide readership fosters the potential for meaningful connections to established projects and the cultivation of collaboration for future research endeavors.
    Keywords: PSO ; sign language recognition ; optimization of convolutional neural networks ; breast segmentation ; mammogram ; deep learning ; semantic segmentation ; radar image prediction ; rain radar ; precipitation nowcasting ; UNet ; PredRNN_v2 ; cubical complex ; cubical homology ; image classification ; persistent homology ; labor exports ; Northeast Asian Countries ; backpropagation neural network (BPNN) ; k-Nearest Neighbor (kNN) ; random forest regression (RFR) ; decision making ; emotion distribution learning ; text-based emotion analysis ; affective words ; multi-task CNN ; ghettos ; GIS ; networks ; Washington D.C. ; machine learning ; segregation ; hybrid deep learning ; time series ; LSTM ; Stacked LSTM ; CNN-LSTMs ; BDLSTM ; CNN ; GRU ; modeling ; SARS-CoV-2 ; generative adversarial network ; image generation ; image synthesis ; GAN ; generative model ; Inception score ; scoreGAN ; waste classification ; angle detection box ; dynamic smoothing ; YOLOv5 ; computer vision ; object detection ; traffic sign detection ; you only look once (YOLO) ; attention mechanism ; feature fusion ; barrier options ; Black–Scholes model ; polynomial regression ; random forest regression ; artificial neural network ; option Greeks ; data analysis ; ski goggles lenses ; surface defect ; automatic optical inspection ; Faster-RCNN ; fine-tune ; MobileNetV3 ; FPN ; RPN ; DNS ; firewall ; malicious ; domain ; name ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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