A single study has addressed actuator failure reconstruction for the One-sided Lipschitz (OSL) family of nonlinear systems. The predicted fault vector in that work does not provide any insight into the underlying prob...
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ISBN:
(纸本)9781665482622
A single study has addressed actuator failure reconstruction for the One-sided Lipschitz (OSL) family of nonlinear systems. The predicted fault vector in that work does not provide any insight into the underlying problematic physical characteristics of the system, which is a significant shortcoming. In this work, we offer a way for estimating the incorrect physical parameters of actuators using an adaptive observer strategy. To demonstrate the utility of the suggested method, a numerical example and simulation research are provided.
The 5th generation mobile communications aims at connecting everything and future Internet of Things(IoT)will get everything smartly *** realize it,there exist many *** key challenge is the battery problem for small d...
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The 5th generation mobile communications aims at connecting everything and future Internet of Things(IoT)will get everything smartly *** realize it,there exist many *** key challenge is the battery problem for small devices,such as sensors or *** backscatter,also referred to as or battery-free backscatter,is a new potential technology to address this *** early and typical type of batteryless backscatter is ambient ***,batteryless backscatter utilizes environmental wireless signals to enable battery-free devices to communicate with each *** devices first harvest energy from ambient wireless signals and then backscatter these signals so as to transmit their own *** paper reviews the current studies about batteryless backscatter,including various backscatter schemes and theoretical works,and then introduces open problems for future research.
Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind i...
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Recent years have seen a rapid development in Machine Learning, which has profoundly influenced many areas of science and engineering. Among them, computer vision takes the leading place, where important tasks are ima...
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ISBN:
(数字)9798331542726
ISBN:
(纸本)9798331542733
Recent years have seen a rapid development in Machine Learning, which has profoundly influenced many areas of science and engineering. Among them, computer vision takes the leading place, where important tasks are image classifications powered by CNNs. Despite the great performance of CNNs in complicated scenarios, they remain sensitive to so-called adversarial attacks, and deliberate perturbations leading them to incorrect predictions. Besides more innocuous consequences, this has serious security implications for critical applications, in-cluding medical diagnostics, where misclassifications might result in disastrous outcomes. This research work discusses adversarial attacks on CNNs and other DNNs in computer vision, studying a full range of the generation and detection methods with details while discussing intrinsic vulnerability and robustness. It also proposes a learning framework that will enhance the robustness and security of DNNs and CNNs against such adversarial perils. The ultimate goal is directed to an improvement in the reliability of such models in absolutely critical scenarios for safe deployment into applications where accuracy is crucial.
Coatings on dental implants are still being developed in order to obtain an ideal balance between their cytocompatibility and antibacterial properties. This paper presents the bacteriostatic and biological properties ...
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Assembly in future smart factories needs to address three challenges, including human centricity, sustainability, and resilience. Conventional approaches for automation in assembly have reached a bottleneck in terms o...
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This paper considers the problem of decentralized optimization on compact submanifolds, where a finite sum of smooth (possibly non-convex) local functions is minimized by n agents forming an undirected and connected g...
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Ensuring robust tracking of controllers’ movement is critical for human-robot interaction in virtual reality (VR) scenarios. This paper proposes a robust tracking algorithm based on a novel wearable ring-shaped contr...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
Ensuring robust tracking of controllers’ movement is critical for human-robot interaction in virtual reality (VR) scenarios. This paper proposes a robust tracking algorithm based on a novel wearable ring-shaped controller equipped with an inertial measurement unit (IMU) and a light-emitting diode (LED). This novel controller design allows users to free up their hands for more immersive experiences. To track the controller’s motion accurately and robustly, we resort to various forms of visual measurements, including 6 DoF and 5 DoF pose measurements from hand gesture detection, as well as 3 DoF position measurement and 2 DoF image measurement derived from the LED. We theoretically analyze the performances of these observation models and propose an optimal observation model combination scheme. Moreover, the necessity and rationale of online estimating system gravity are illustrated. The effectiveness of our tracking method is validated through extensive experiments.
Since the cumbersome collection process and high cost, the collected degradation of the product is basically small samples, which will affect the accuracy of reliability evaluation. It is necessary to expand the degra...
Since the cumbersome collection process and high cost, the collected degradation of the product is basically small samples, which will affect the accuracy of reliability evaluation. It is necessary to expand the degradation to improve the accuracy of later reliability assessment. Therefore, a degradation generation and prediction method is proposed combining the time series generator adversarial network (TimeGAN) and stochastic process. Firstly, the input degradation is expanded by the sliding window to improve the later training accuracy; Then, the construction of the generator in TimeGAN is linked with the stochastic process to make the generation data more realistic. Finally, the results of degradation prediction by the Gated Recurrent Unit (GRU) can be obtained. Two datasets and different generation methods are adopted to evaluate the effectiveness of the proposed method. The results shows that the Kullback-Leibler(KL) divergence is the smallest, and the prediction error is the smallest compared with the other methods. So, the proposed method is proved that it is valid in the degradation generation and prediction, and can be used for the further reliability assessment of the product in the industrial system.
This review article introduces the concepts, server architecture and application scenarios of Mobile Edge Computing (MEC) and Wireless Sensor Network (WSN). By differentiating between rechargeable and non-rechargeable...
This review article introduces the concepts, server architecture and application scenarios of Mobile Edge Computing (MEC) and Wireless Sensor Network (WSN). By differentiating between rechargeable and non-rechargeable systems, it presents the research status of task offloading in WSN in an edge computing environment. Various strategies are analyzed and compared in terms of their characteristics and application domains. The existing methods can reduce offloading latency and energy consumption, but still face some issues. Based on this, the research hotspots of edge computing task offloading for WSN are summarized, and its research and development trends are pointed out.
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