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Real-time and networked embedded systems are important bidirectional bridges between the physical and the information worlds. Embedded intelligence is increasingly pervading industry, infrastructure, and public and private spaces, being identified as an emerging societal and economic “neural system” that supports both societal changes and economic growth. As cost/performance improves, objects connected in everyday life increasingly rely on embedded intelligence in an ever-growing array of application fields, specialized technologies, and engineering disciplines.While this process gradually builds the IoT, it exposes a series of specific non-trivial timing and other extra-functional requirements and system properties that are less common in other computing areas. The ten articles in this book propose solutions to the specific open problems of cyber–physical and real-time embedded systems applicable to both traditional application domains, such as industrial automation and control, energy management, automotive, aerospace and defense systems, as well as emerging domains, such as medical devices, household appliances, mobile multimedia, gaming, and entertainment systems.]

Embedded Systems --- Real-Time Systems --- Cyber-Physical Systems --- Internet of Things (IoT)

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Despite the significant decrease in bullying that has been reported in many countries during the last two decades, bullying continues to be a significant problem among young people. Given the increase of internet use among youth, researchers have started to pay attention to cyberspace, understanding that it may be a fertile ground for bullying behaviors, specifically, what is known as cyberbullying. “Family, Bullying and Cyberbullying” examines the association of several family variables with bullying in offline and online environments during childhood and adolescence. Contributors from the Americas, Canada, Asia, and Europe offer cutting-edge research on family dynamics, bystander behaviors, parents’ and educators’ perceptions, and bullying and cyberbullying prevention and intervention strategies of bullying for school and home. This book also provides an analysis of the current research on the influence of family in the electronic bullying. Research topics included in the book: 1) Parental education and bullying and cyberbullying; 2) Parental monitoring and cyberbullying; 3) Parental communication and feelings of affiliation; 4) Student and educator perspective on cyberbullying; 5) Parents’ responses to bullying; 6) Parental mediation and bystander behaviors; 7) Development of scales to measure cyberbullying and high internet risks. “Family, Bullying and Cyberbullying” is an essential resource for researchers, graduate students, families, and practitioners in social education, social work, teacher education, and psychology.

parental control --- restriction --- supervision --- high-risk behaviours --- internet --- adolescence --- bullying --- cyberbullying --- family --- parents --- bullying awareness --- coping strategies --- cyberbullying --- bystander --- bystanding --- victimization --- perpetration --- bully --- parental mediation --- cyberbullying --- prevention --- cyber-kindness --- parents --- K-12 --- private school --- boarding students --- information and communication technology --- cyberbullying --- parenting --- adolescence --- parental monitoring --- cyberbullying --- perpetration --- victimization --- parental communication --- affiliation --- peers --- bullying --- young children --- wang-ta --- mothers --- aggression --- cyber-victimization --- scale development --- psychometric properties --- adolescence --- school coexistence --- cyberbullying --- education --- family --- victims --- prevention --- management --- training --- perceptions --- pre-service teachers --- teacher education --- parenting --- socialization --- violence --- victimization --- teenagers --- cyberbullying --- cybervictimization --- family functioning --- self-concept --- adolescence --- cyberbullying --- cybervictimization --- parent --- family --- systematic review

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Open-source electronics are becoming very popular, and are integrated with our daily educational and developmental activities. At present, the use open-source electronics for teaching science, technology, engineering, and mathematics (STEM) has become a global trend. Off-the-shelf embedded electronics such as Arduino- and Raspberry-compatible modules have been widely used for various applications, from do-it-yourself (DIY) to industrial projects. In addition to the growth of open-source software platforms, open-source electronics play an important role in narrowing the gap between prototyping and product development. Indeed, the technological and social impacts of open-source electronics in teaching, research, and innovation have been widely recognized.

human-computer interface (HCI) --- electrooculogram (EOG) --- electromyogram (EMG) --- modified sliding window algorithm --- piecewise linear approximation (PLA) --- support vector regression --- eye tracking --- blockchain --- ontology --- context --- cyber-physical systems --- robotics --- interaction --- coalition --- individual management of livestock --- momentum data sensing --- remote sensing platform --- sensor networks --- technology convergence --- industry 4.0 --- distributed measurement systems --- automation networks --- node-RED --- cloud computing --- OPC UA --- hardware trojan taxonomy --- thermal imaging --- side channel analysis --- infrared --- FPGA --- Internet of Things --- wireless sensor networks --- Cloud of Things --- virtual sensor --- sensor detection --- smart cities --- Internet of Things --- Raspberry Pi --- BeagleBoard --- Arduino --- Internet of Things --- open hardware --- smart farming --- teaching robotics --- science teaching --- STEM --- robotic tool --- Python --- Raspberry Pi --- PiCamera --- vision system --- service learning --- robotics --- open platform --- automated vehicle --- EPICS --- open-source platform --- visual algorithms --- digital signal controllers --- embedded systems education --- dsPIC --- Java --- smart converter --- maximum power point tracking (MPPT) --- photovoltaic (PV) system --- Field Programmable Gate Array (FPGA) --- Digital Signal Processor (DSP) --- interleaved --- DC/DC converter --- distributed energy resource --- n/a

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Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.

cutting insert selection --- cutting parameter optimization --- artificial neural networks --- genetic algorithm --- connected enterprise --- smart manufacturing --- big data --- machine learning --- data reduction --- predictive analytics --- in-line dimensional inspection --- warm forming --- 3D mesh reconstruction --- optical system --- revolution workpiece --- defect detection --- polymer lithium-ion battery --- convolutional neural network --- deep learning --- blister defect --- flower pollination algorithm --- Industry 4.0 --- anomaly detection --- scheduling --- neural network --- skyline queries --- Cyber-Physical Systems (CPS) --- scalability test --- Internet of Things (IoT) --- INDUSTRY 4.0 --- economic recession --- research and development indicators --- maintenance expert --- competence --- decision support --- micro-armature --- defect detection --- convolutional neural networks --- computer vision --- capacity control --- job shop systems --- RMTs --- operator theory --- 4th industrial revolution --- industry 4.0 --- AHP --- QFD --- matching --- fibre of preserved Szechuan pickle --- contour detection --- dilated convolutions --- HED --- social network --- industry 4.0 --- industrial knowledge graph --- deep learning --- industrial big data --- intellectualization of industrial information --- digital manufacturing --- smart factory --- Industry 4.0 --- digital platforms --- automated surface inspection --- D-VGG16 --- bilinear model --- Grad-CAM --- classification --- localization --- elliptical paraboloid array --- self-calibration method --- vertex distance --- optical slope sensor --- geometric relationship --- relative angle --- fabric defect detection --- LGM --- FCM --- image smoothing --- Industry 4.0 --- marketing innovations --- innovative marketing tools --- impacts marketing innovations --- Industry 4.0 --- configure-to-order --- BIM --- construction equipment --- digital information flow --- lean assembly --- digital twins --- cyber-physical production systems --- depthwise separable convolution --- YOLOv3 --- feature pyramid --- aircraft structure crack detection --- industrial load management --- demand-side management --- demand-side response --- energy flexibility --- IT concept --- platform-based ecosystem --- control service --- smart service --- control as a service --- cloud-based control system --- automation system --- chatter --- train wheel --- smart system --- turning --- edge computing --- n/a

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This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

linear regression --- covariance matrix --- data association --- sensor fusing --- SLAM --- multi-sensor data fusion --- conflicting evidence --- Dempster–Shafer evidence theory --- belief entropy --- similarity measure --- data classification --- fault diagnosis --- Bar-Shalom Campo --- Covariance Projection method --- data fusion --- distributed architecture --- Kalman filter --- linear constraints --- inconsistent data --- user experience evaluation --- user experience measurement --- eye-tracking --- facial expression --- galvanic skin response --- EEG --- interaction tracker --- self-reporting --- user experience platform --- mix-method approach --- image fusion --- multi-focus --- weight maps --- gradient domain --- fast guided filter. --- Dempster-Shafer evidence theory (DST) --- uncertainty measure --- open world --- closed world --- Deng entropy --- extended belief entropy --- sensor data fusion --- orthogonal redundant inertial measurement units --- data fusion architectures --- sensors bias --- fire source localization --- dynamic optimization --- global information --- the Range-Point-Range frame --- the Range-Range-Range frame --- sensor array --- SINS/DVL integrated navigation --- unscented information filter --- square root --- state probability approximation --- most suitable parameter form --- deep learning --- data preprocessing --- Human Activity Recognition (HAR) --- Internet of things (IoT) --- Industry 4.0 --- trajectory reconstruction --- low-cost sensors --- embedded systems --- powered two wheels (PTW) --- safe trajectory --- data fusion --- health management decision --- grey group decision-making --- health reliability degree --- maintenance decision --- sensor system --- least-squares filtering --- least-squares smoothing --- networked systems --- random parameter matrices --- random delays --- packet dropouts --- multi-sensor system --- multi-sensor information fusion --- particle swarm optimization --- sensor data fusion algorithm --- distributed intelligence system --- multi-sensor time series --- deep learning --- machine health monitoring --- time-distributed ConvLSTM model --- spatiotemporal feature learning --- optimal estimate --- unknown inputs --- distributed fusion --- augmented state Kalman filtering (ASKF) --- soft sensor --- coefficient of determination maximization strategy --- expectation maximization (EM) algorithm --- Gaussian mixture model (GMM) --- alumina concentration --- multi-sensor joint calibration --- high-dimensional fusion data (HFD) --- supervoxel --- Gaussian density peak clustering --- sematic segmentation --- multisensor data fusion --- multitarget tracking --- GMPHD --- sonar network --- RFS --- attitude estimation --- Kalman filter --- land vehicle --- magnetic angular rate and gravity (MARG) sensor --- quaternion --- yaw estimation --- network flow theory --- multitarget tracking --- spectral clustering --- A* search algorithm --- RTS smoother --- integer programming --- Surface measurement --- multi-sensor measurement --- surface modelling --- data fusion --- Gaussian process --- multi-sensor network --- observable degree analysis --- information fusion --- nonlinear system --- hybrid adaptive filtering --- weighted fusion estimation --- square-root cubature Kalman filter --- information filter --- surface quality control --- multi-sensor data fusion --- cutting forces --- vibration --- acoustic emission --- signal feature extraction methods --- predictive modeling techniques --- attitude --- orientation --- estimation --- Kalman filter --- quaternion --- manifold --- image registration --- evidential reasoning --- belief functions --- uncertainty --- DoS attack --- industrial cyber-physical system (ICPS) --- security zones --- mimicry security switch strategy --- fixed-point filter --- extended Kalman filter --- nested iterative method --- Steffensen’s iterative method --- convergence condition --- vehicular localization --- target positioning --- high-definition map --- vehicle-to-everything --- intelligent and connected vehicles --- intelligent transport system --- image registration --- non-rigid feature matching --- local structure descriptor --- Gaussian mixture model --- aircraft pilot --- workload --- multi-source data fusion --- fuzzy neural network --- principal component analysis --- parameter learning --- drift compensation --- domain adaption --- feature representations --- electronic nose --- data fusion --- dual gating --- MEMS accelerometer and gyroscope --- cardiac PET --- out-of-sequence --- multi-target tracking --- random finite set --- gaussian mixture probability hypothesis density --- multisensor system --- Gaussian process regression --- Bayesian reasoning method --- Dempster–Shafer evidence theory (DST) --- uncertainty measure --- novel belief entropy --- multi-sensor data fusion --- decision-level sensor fusion --- electronic nose --- subspace alignment --- interference suppression --- transfer --- evidence combination --- time-domain data fusion --- object classification --- uncertainty --- multirotor UAV --- precision landing --- artificial marker --- pose estimation --- sensor fusion --- camera --- LiDAR --- calibration --- plane matching --- ICP --- projection --- data fusion --- data registration --- adaptive distance function --- complex surface measurement --- Gaussian process model --- Dempster–Shafer evidence theory --- conflict measurement --- mutual support degree --- Hellinger distance --- Pignistic vector angle --- multi-sensor data fusion --- multi-environments --- state estimation --- unmanned aerial vehicle