The rapidly advancing Convolutional Neural Networks(CNNs)have brought about a paradigm shift in various computer vision tasks,while also garnering increasing interest and application in sensor-based Human Activity Rec...
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The rapidly advancing Convolutional Neural Networks(CNNs)have brought about a paradigm shift in various computer vision tasks,while also garnering increasing interest and application in sensor-based Human Activity Recognition(HAR)***,the significant computational demands and memory requirements hinder the practical deployment of deep networks in resource-constrained *** paper introduces a novel network pruning method based on the energy spectral density of data in the frequency domain,which reduces the model’s depth and accelerates activity *** traditional pruning methods that focus on the spatial domain and the importance of filters,this method converts sensor data,such as HAR data,to the frequency domain for *** emphasizes the low-frequency components by calculating their energy spectral density ***,filters that meet the predefined thresholds are retained,and redundant filters are removed,leading to a significant reduction in model size without compromising performance or incurring additional computational ***,the proposed algorithm’s effectiveness is empirically validated on a standard five-layer CNNs backbone *** computational feasibility and data sensitivity of the proposed scheme are thoroughly ***,the classification accuracy on three benchmark HAR datasets UCI-HAR,WISDM,and PAMAP2 reaches 96.20%,98.40%,and 92.38%,***,our strategy achieves a reduction in Floating Point Operations(FLOPs)by 90.73%,93.70%,and 90.74%,respectively,along with a corresponding decrease in memory consumption by 90.53%,93.43%,and 90.05%.
This study introduces two novel hybrid machine-learning architectures for multilabel anomaly detection in electrocardiograms (EKGs): a 1D modified ResNet combined with a transformer encoder and an equivalent 2D ResNet...
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The growing concerns over mitigating climate change effects resulted in power system planning and generation expansion strategies that aim in increasing penetration of intermittent renewable energy sources (RES) to fu...
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Fully Homomorphic Encryption (FHE) allows computational processing of encrypted data on cloud servers, providing high security and enabling safe data utilization. As homomorphic multiplication progresses with encrypte...
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In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing ***,the limited energy resources of Sensor Nodes(SNs)a...
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In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing ***,the limited energy resources of Sensor Nodes(SNs)are a big challenge for ensuring their efficient and reliable *** data gathering involves the utilization of a mobile sink(MS)to mitigate the energy consumption problem through periodic network *** mobile sink(MS)strategy minimizes energy consumption and latency by visiting the fewest nodes or predetermined locations called rendezvous points(RPs)instead of all cluster heads(CHs).CHs subsequently transmit packets to neighboring *** unique determination of this study is the shortest path to reach *** the mobile sink(MS)concept has emerged as a promising solution to the energy consumption problem in WSNs,caused by multi-hop data collection with static *** this study,we proposed two novel hybrid algorithms,namely“ Reduced k-means based on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans with ANN”(DBRkM-ANN)for designing a fast,efficient,and most proficient MS path depending upon rendezvous points(RPs).The first algorithm optimizes the MS’s latency,while the second considers the designing of delay-bound paths,also defined as the number of paths with delay over bound for the *** methods use a weight function and k-means clustering to choose RPs in a way that maximizes efficiency and guarantees network-wide *** addition,a method of using MS scheduling for efficient data collection is *** simulations and comparisons to several existing algorithms have shown the effectiveness of the suggested methodologies over a wide range of performance indicators.
The ever-increasing number of Internet-of-Thing devices requires the development of edge-computing platforms to address the associated demand for big data processing at low power consumption while minimizing cloud com...
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We study the problem of game-theoretic robot allocation where two players strategically allocate robots to compete for multiple sites of interest. Robots possess offensive or defensive capabilities to interfere and we...
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Supervisory control and data acquisition (SCADA) systems are vital in monitoring and controlling industrial processes through the web. However, while such systems result in lower costs, greater utilisation efficiency,...
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As more and more data is produced,finding a secure and efficient data access structure has become a major research *** centralized systems used by medical institutions for the management and transfer of Electronic Med...
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As more and more data is produced,finding a secure and efficient data access structure has become a major research *** centralized systems used by medical institutions for the management and transfer of Electronic Medical Records(EMRs)can be vulnerable to security and privacy threats,often lack interoperability,and give patients limited or no access to their own *** this paper,we first propose a privilege-based data access structure and incorporates it into an attribute-based encryption mechanism to handle the management and sharing of big data *** proposed privilege-based data access structure makes managing healthcare records using mobile healthcare devices efficient and feasible for large numbers of *** then propose a novel distributed multilevel EMR(d-EMR)management scheme,which uses blockchain to address security concerns and enables selective sharing of medical records among staff members that belong to different levels of a hierarchical *** deploy smart contracts on Ethereum blockchain and utilize a distributed storage system to alleviate the dependence on the record-generating institutions to manage and share patient *** preserve privacy of patient records,our smart contract is designed to allow patients to verify attributes prior to granting access *** provide extensive security,privacy,and evaluation analyses to show that our proposed scheme is both efficient and practical.
Roads are an important part of transporting goods and products from one place to another. In developing countries, the main challenge is to maintain road conditions regularly. Roads can deteriorate from time to time. ...
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