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Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS.
AUTOSAR --- DAG --- runnable scheduling --- control-scheduling codesign --- lagrange multiplier --- Mobile Cyber-Physical Systems (MCPS) --- industry --- Mobile Sink Groups (MSG) --- group mobility --- real-time data delivery --- Intelligent Transportation System (ITS) --- deep neural network --- Red Light Runner (RLR) --- dynamic signal control --- intersection safety --- mixed-criticality --- power-aware --- real-time scheduling --- DVFS --- security taxonomies --- event-based systems --- mobile cyber physical systems --- security flaws --- searchable encryption --- PEKS --- forward privacy --- trusted execution environment --- SGX --- data quality --- large-scale --- high-dimensionality --- linear discriminant analysis --- random projection --- bootstrapping --- controller area network bus --- authentication --- authenticity --- resiliency --- sustainability --- formal verification --- model checking --- in-vehicle network --- model compression --- adversarial robustness --- weight pruning --- adversarial training --- distillation --- embedded system --- secure AI --- n/a
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Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS.
Technology: general issues --- AUTOSAR --- DAG --- runnable scheduling --- control-scheduling codesign --- lagrange multiplier --- Mobile Cyber-Physical Systems (MCPS) --- industry --- Mobile Sink Groups (MSG) --- group mobility --- real-time data delivery --- Intelligent Transportation System (ITS) --- deep neural network --- Red Light Runner (RLR) --- dynamic signal control --- intersection safety --- mixed-criticality --- power-aware --- real-time scheduling --- DVFS --- security taxonomies --- event-based systems --- mobile cyber physical systems --- security flaws --- searchable encryption --- PEKS --- forward privacy --- trusted execution environment --- SGX --- data quality --- large-scale --- high-dimensionality --- linear discriminant analysis --- random projection --- bootstrapping --- controller area network bus --- authentication --- authenticity --- resiliency --- sustainability --- formal verification --- model checking --- in-vehicle network --- model compression --- adversarial robustness --- weight pruning --- adversarial training --- distillation --- embedded system --- secure AI --- AUTOSAR --- DAG --- runnable scheduling --- control-scheduling codesign --- lagrange multiplier --- Mobile Cyber-Physical Systems (MCPS) --- industry --- Mobile Sink Groups (MSG) --- group mobility --- real-time data delivery --- Intelligent Transportation System (ITS) --- deep neural network --- Red Light Runner (RLR) --- dynamic signal control --- intersection safety --- mixed-criticality --- power-aware --- real-time scheduling --- DVFS --- security taxonomies --- event-based systems --- mobile cyber physical systems --- security flaws --- searchable encryption --- PEKS --- forward privacy --- trusted execution environment --- SGX --- data quality --- large-scale --- high-dimensionality --- linear discriminant analysis --- random projection --- bootstrapping --- controller area network bus --- authentication --- authenticity --- resiliency --- sustainability --- formal verification --- model checking --- in-vehicle network --- model compression --- adversarial robustness --- weight pruning --- adversarial training --- distillation --- embedded system --- secure AI
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The recent successes of machine learning, especially regarding systems based on deep neural networks, have encouraged further research activities and raised a new set of challenges in understanding and designing complex machine learning algorithms. New applications require learning algorithms to be distributed, have transferable learning results, use computation resources efficiently, convergence quickly on online settings, have performance guarantees, satisfy fairness or privacy constraints, incorporate domain knowledge on model structures, etc. A new wave of developments in statistical learning theory and information theory has set out to address these challenges. This Special Issue, "Machine Learning and Information Theory", aims to collect recent results in this direction reflecting a diverse spectrum of visions and efforts to extend conventional theories and develop analysis tools for these complex machine learning systems.
Technology: general issues --- History of engineering & technology --- supervised classification --- independent and non-identically distributed features --- analytical error probability --- empirical risk --- generalization error --- K-means clustering --- model compression --- population risk --- rate distortion theory --- vector quantization --- overfitting --- information criteria --- entropy --- model-based clustering --- merging mixture components --- component overlap --- interpretability --- time series prediction --- finite state machines --- hidden Markov models --- recurrent neural networks --- reservoir computers --- long short-term memory --- deep neural network --- information theory --- local information geometry --- feature extraction --- spiking neural network --- meta-learning --- information theoretic learning --- minimum error entropy --- artificial general intelligence --- closed-loop transcription --- linear discriminative representation --- rate reduction --- minimax game --- fairness --- HGR maximal correlation --- independence criterion --- separation criterion --- pattern dictionary --- atypicality --- Lempel–Ziv algorithm --- lossless compression --- anomaly detection --- information-theoretic bounds --- distribution and federated learning
Choose an application
Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS.
Technology: general issues --- AUTOSAR --- DAG --- runnable scheduling --- control-scheduling codesign --- lagrange multiplier --- Mobile Cyber-Physical Systems (MCPS) --- industry --- Mobile Sink Groups (MSG) --- group mobility --- real-time data delivery --- Intelligent Transportation System (ITS) --- deep neural network --- Red Light Runner (RLR) --- dynamic signal control --- intersection safety --- mixed-criticality --- power-aware --- real-time scheduling --- DVFS --- security taxonomies --- event-based systems --- mobile cyber physical systems --- security flaws --- searchable encryption --- PEKS --- forward privacy --- trusted execution environment --- SGX --- data quality --- large-scale --- high-dimensionality --- linear discriminant analysis --- random projection --- bootstrapping --- controller area network bus --- authentication --- authenticity --- resiliency --- sustainability --- formal verification --- model checking --- in-vehicle network --- model compression --- adversarial robustness --- weight pruning --- adversarial training --- distillation --- embedded system --- secure AI --- n/a
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