Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission ...
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Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart *** the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T ***,the impact of attackers on the accuracy of time synchronization cannot be *** solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization ***,we construct an abnormal clock source detection ***,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the ***,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing *** results show that the proposed algorithm has better time synchronization delay and accuracy performance.
The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this *** uncertainties are a ...
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The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this *** uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world ***,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)*** the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time *** three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise ***,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.
The topology selection plays a key role in minimizing the losses and improving the output waveform quality of an inverter. In addition, increasing the switching frequency of an inverter help to reduce the size of EMI ...
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As residential solar photovoltaic (PV) systems are increasingly integrated into distribution networks globally, there is a growing necessity to shift from traditional load forecasting to net load forecasting (i.e., pr...
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Research on the visual system and its development is not only crucial for understanding how we see and interpret the environment from basic visual processing to complex perception but also aids in the development of t...
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For the large amount of waste heat wasted in daily life and industrial production,we propose a new type of flexible thermoelectric generators(F-TEGs)which can be used as a large area bionic skin to achieve energy harv...
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For the large amount of waste heat wasted in daily life and industrial production,we propose a new type of flexible thermoelectric generators(F-TEGs)which can be used as a large area bionic skin to achieve energy harvesting of thermal *** reference to biological structures such as pinecone,succulent,and feathers,we have designed and fabricated a biomimetic flexible TEG that can be applied in a wide temperature range which has the highest temperature energy harvesting capability *** laminated free structure of the bionic F-TEG dramatically increases the efficiency and density of energy *** F-TEGs(single TEG only 101.2 mg in weight),without an additional heat sink,demonstrates the highest output voltage density of 286.1 mV/cm^(2)and the maximum power density is 66.5 mW/m^(2) at a temperature difference of nearly 1000℃.The flexible characteristics of F-TEGs make it possible to collect the diffused thermal energy by flexible attachment to the outer walls of high-temperature pipes and vessels of different diameters and *** work shows a new design and application concept for flexible thermal energy collectors,which fills the gap of flexible energy harvesting in high-temperature environment.
Deep neural networks (DNNs) have emerged as the most effective programming paradigm for computer vision and natural language processing applications. With the rapid development of DNNs, efficient hardware architecture...
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Deep neural networks (DNNs) have emerged as the most effective programming paradigm for computer vision and natural language processing applications. With the rapid development of DNNs, efficient hardware architectures for deploying DNN-based applications on edge devices have been extensively studied. Emerging nonvolatile memories (NVMs), with their better scalability, nonvolatility, and good read performance, are found to be promising candidates for deploying DNNs. However, despite the promise, emerging NVMs often suffer from reliability issues, such as stuck-at faults, which decrease the chip yield/memory lifetime and severely impact the accuracy of DNNs. A stuck-at cell can be read but not reprogrammed, thus, stuck-at faults in NVMs may or may not result in errors depending on the data to be stored. By reducing the number of errors caused by stuck-at faults, the reliability of a DNN-based system can be enhanced. This article proposes CRAFT, i.e., criticality-aware fault-tolerance enhancement techniques to enhance the reliability of NVM-based DNNs in the presence of stuck-at faults. A data block remapping technique is used to reduce the impact of stuck-at faults on DNNs accuracy. Additionally, by performing bit-level criticality analysis on various DNNs, the critical-bit positions in network parameters that can significantly impact the accuracy are identified. Based on this analysis, we propose an encoding method which effectively swaps the critical bit positions with that of noncritical bits when more errors (due to stuck-at faults) are present in the critical bits. Experiments of CRAFT architecture with various DNN models indicate that the robustness of a DNN against stuck-at faults can be enhanced by up to 105 times on the CIFAR-10 dataset and up to 29 times on ImageNet dataset with only a minimal amount of storage overhead, i.e., 1.17%. Being orthogonal, CRAFT can be integrated with existing fault-tolerance schemes to further enhance the robustness of DNNs aga
Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)...
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Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)is an indispensable functional module of ***,it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels of RSE,leading to severe estimation performance *** paper aims to present an overview of recent advances in cyber-attacks and defensive countermeasures,with a specific focus on integrity attacks against ***,two representative frameworks for the synthesis of optimal deception attacks with various performance metrics and stealthiness constraints are discussed,which provide a deeper insight into the vulnerabilities of ***,a detailed review of typical attack detection and resilient estimation algorithms is included,illustrating the latest defensive measures safeguarding RSE from ***,some prevalent attacks impairing the confidentiality and data availability of RSE are examined from both attackers'and defenders'***,several challenges and open problems are presented to inspire further exploration and future research in this field.
Deep neural networks (DNNs) have made significant strides in tackling challenging tasks in wireless systems, especially when an accurate wireless model is not available. However, when available data is limited, tradit...
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Reducing buildings' energy consumption through energy efficiency interventions has become a key priority to mitigate climate change. To this end, stakeholders involved in the implementation and financing of energy...
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