Effective integration of available resources within edge nodes is essential to improve the performance of vehicular edge computing (VEC) to support various randomly offloaded tasks with limited computing capacity and ...
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The traditional Intravenous (IV) system is vulnerable to human error and other risks like backflow of blood, air embolism and various other problems if unattended at a time. This research aims to develop a smart IoT b...
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The purpose of writing this paper is to find the optimized digital colour recommendation model based on the semantic colour synaesthesia annotation labels with digital HSV (Hue saturation and brightness value colour c...
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The suggested architecture's major goal is to improve stability and minimize leakage current by using various approaches on a 6T SRAM cell to reduce leakage power without compromising performance. Data in static r...
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To address challenges such as the lengthy development cycle, poor system stability, and safety concerns in the control strategy development for thermal management in new energy vehicles, a thermal management system co...
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This paper investigates the false data injection attack (FDIA) locational detection problem for power grids based on edge computing. Given the difficulty of constructing the exact model of the power grid, a locational...
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ISBN:
(纸本)9781665495721
This paper investigates the false data injection attack (FDIA) locational detection problem for power grids based on edge computing. Given the difficulty of constructing the exact model of the power grid, a locational detection model of convolutional neural network (CNN) is established to solve the FDIA locational detection problem. However, due to the limited computing power of the edge devices, the CNN model should be modified so that the inference process of the CNN is computationally lightweight. Therefore, the quantization method is adopted to lighten the computation burden, and the early exiting mechanism is proposed to speed up the inference of CNN. Finally, a locational detection model of CNN with lightweight computing capability is presented. The edge computing based FDIA locational detection is realized by applying the presented model. Experiments conducted on the IEEE 118-bus system show that the FDIA can be accurately detected and located using the presented fast locational detection model.
With the significant increase in the trend of aging society, the ability of elderly people to control bowel movements has become an important issue in the field of elderly rehabilitation. This article is based on the ...
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Smart mobility is a rising technology to provide a safe and efficient transportation system. Connected autonomous vehicles (AVs) are getting tremendous attention while considered smart mobility due to their emerging n...
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ISBN:
(纸本)9781665476874
Smart mobility is a rising technology to provide a safe and efficient transportation system. Connected autonomous vehicles (AVs) are getting tremendous attention while considered smart mobility due to their emerging nature. However, new hybrid and compact technologies are necessary to provide multiple services in less space and low cost and significantly improve the safety of the vehicles. The joint sensing and communication (SensCom) platform is a potential solution for integrated sensing and communication activity for connected AVs. In this paper, we developed a SensCom hardware platform to enable sensing and communication together. We have demonstrated through a working model that the mutual interference of sensing and communication signals can be easily mitigated, and thus both the functionalities can be achieved using the same hardware.
Message oriented and robotics middleware play an important role in facilitating robot control, abstracting complex functionality, and unifying communication patterns between sensors and devices. However, using multipl...
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ISBN:
(数字)9798400703225
ISBN:
(纸本)9798400703225
Message oriented and robotics middleware play an important role in facilitating robot control, abstracting complex functionality, and unifying communication patterns between sensors and devices. However, using multiple middleware frameworks presents a challenge in integrating diferent robots within a single system. To address this challenge, we present Wrapyf, a Python wrapper supporting multiple message oriented and robotics middleware, including ZeroMQ, YARP, ROS, and ROS 2. Wrapyf also provides plugins for exchanging deep learning framework data, without additional encoding or preprocessing steps. Using Wrapyf eases the development of scripts that run on multiple machines, thereby enabling cross-platform communication and workload distribution. We fnally present the three communication schemes that form the cornerstone of Wrapyf's communication model, along with examples that demonstrate their applicability.
In this paper, a new output feedback control scheme is proposed for nonlinear systems based on sampled-data input-output quantization. By sampling the output signal and using the quantizer to filter the sampled signal...
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