A distributed deep learning approach with mobile edge computing for next generation IoT networks security

Along with recent development in Next Generation IoT, the Deep Learning (DL) has become a promising paradigm to perform various tasks such as computation and analysis. Many security researchers have proposed distributed DL supporting DL task at the IoT device level to deliver low latency and high accuracy. However, due to limited computing capabilities of IoT devices, distributed DL is failed to maintain Quality-of-service demand in practical IoT applications. To this end, BlockDeepEdge, a Blockchain-based Distributed DL with Mobile Edge Computing (MEC) is proposed where MEC supports the lightweight IoT devices by delivering computing operations to them at the edge of the network. The blockchain provide a secure, decentralized and P2P interaction among IoT devices and MEC server to carryout distributed DL operation

Design of X-Band Bicontrollable Metasurface Absorber Comprising Graphene Pixels on Copper-Backed YIG Substrate

The planewave response of a bicontrollable metasurface absorber with graphene-patched pixels was simulated in the X band using commercial software. Each square meta-atom is a 4x4 array of 16 pixels, some patched with graphene and the others unpatched. The pixels are arranged on a PVC skin which is placed on a copper-backed YIG substrate. Graphene provides electrostatic controllability and YIG provides magnetostatic controllability. Our design delivers absorptance equal to or in excess of 0.9 over a 100-MHz spectral regime in the X band, with 360 MHz/kA magnetostatic controllabity rate and 1 Hz m/V electrostatic controllability rate. Notably, electrostatic control via graphene in the GHz range is novel.Comment: 9 pages, 4 figures, 1 tabl

Supervised machine-learning predictive analytics for national quality of life scoring

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Wearable Computing for Defence Automation : Opportunities and Challenges in 5G Network

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FS-OpenSecurity : A taxonomic modeling of security threats in SDN for future sustainable computing

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Compound Scaling Encoder-Decoder (CoSED) Network for Diabetic Retinopathy Related Bio-marker Detection

ACKNOWLEDGMENT For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. This work was supported by Cancer Research UK (CRUK) under Grant EDDPJT-May23/100001Peer reviewedPostprin

Underwater acoustic sensor networks node localization based on compressive sensing in water hydrology

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ETHNOMEDICINAL, PHYTOCHEMICAL, AND PHARMACOLOGICAL ASPECTS OF GENUS ACANTHUS

Acanthus (family Acanthaceae) is a genus of the major group angiosperms (flowering plants) comprising more than 29 species widely distributed in the tropical and subtropical region. The aim of this review is to offer thorough scientific information on ethnomedicinal uses, phytochemical, and pharmacological activities of the plant species belonging to the genus Acanthus. Numerous traditional uses of the genus have been supported in this article from the results, and executed by the extracts and/or pure compounds obtained from pharmacological studies will provide a single platform to help future researches on the genus Acanthus. Furthermore, ethnomedicinal evaluation using fractions or isolation of medicinal principles was extensively explored by databases like Google, Google Scholar, and ScienceDirect at the same time.Â

Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

Funding Information: Funding Statement: This work was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 62172058) and the Hunan Provincial Natural Science Foundation of China (Grant Nos. 2022JJ10052, 2022JJ30624). Publisher Copyright: © 2023 Tech Science Press. All rights reserved.Peer reviewedPublisher PD

LogEvent2vec : LogEvent-to-vector based anomaly detection for large-scale logs in internet of things

Funding: This work was funded by the National Natural Science Foundation of China (Nos. 61802030), the Research Foundation of Education Bureau of Hunan Province, China (No. 19B005), and the International Cooperative Project for “Double First-Class”, CSUST (No. 2018IC24), the open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education (No. JZNY201905), the Open Research Fund of the Hunan Provincial Key Laboratory of Network Investigational Technology (No. 2018WLZC003). This work was funded by the Researchers Supporting Project No. (RSP-2019/102) King Saud University, Riyadh, Saudi Arabia. Acknowledgments: We thank Researchers Supporting Project No. (RSP-2019/102) King Saud University, Riyadh, Saudi Arabia, for funding this research. We thank Francesco Cauteruccio for proofreading this paper.Peer reviewedPublisher PD