Towards Privacy-Aware and Trustworthy Data Sharing Using Blockchain for Edge Intelligence by Youyang Qu, Lichuan Ma, Wenjie Ye, Xuemeng Zhai, Shui Yu, Yunfeng Li, David Smith

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Synergistic task-offloading in 6G edge networks based on propagation dynamics by Chao Zhu, Yuexia Zhang, Xinyi Wang, Xuzhen Zhu

“…This model describes the dynamic transmission process of offloaded tasks in 6G edge networks and constructs two linear threshold functions to characterize the differences in task processing capabilities between UT and edge servers (ES). …”
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Randomized Quantization for Privacy in Resource Constrained Machine Learning at-the-Edge and Federated Learning by Ce Feng, Parv Venkitasubramaniam

“…The increasing adoption of machine learning at the edge (ML-at-the-edge) and federated learning (FL) presents a dual challenge: ensuring data privacy as well as addressing resource constraints such as limited computational power, memory, and communication bandwidth. …”
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An efficient IoT group association and data sharing mechanism in edge computing paradigm by Haowen Tan

“…Despite its benefits and promising future, security and privacy challenges for the IoT wireless communication of edge computing environment remain unaddressed. As a result, proper authentication mechanisms are critical, especially in the extreme scenario where some edge facilities are not functional. …”
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Design and Optimization of a Compliant Morphing Trailing Edge for High-Lift Generation by Salvatore Ameduri, Bernardino Galasso, Maria Chiara Noviello, Ignazio Dimino, Antonio Concilio, Pietro Catalano, Francesco Antonio D’Aniello, Giovanni Marco Carossa, Laurent Pinazo, John Derry, Britney Biju, Shruthi Shreedharan

“…Repeating the genetic process starting from different initial populations, some optimized configurations were identified. …”
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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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Low-Power 8T SRAM Compute-in-Memory Macro for Edge AI Processors by Hye-Ju Shin, Sung-Hun Jo

“…Based on these strengths, it can achieve higher battery efficiency in AI edge devices and improve system performance. The proposed integrated circuit was simulated in a 90 nm CMOS process and operated on a 1 V supply voltage.…”
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AoI-aware task scheduling in edge-assisted real-time applications by WANG Hongyan, SUN Qibo, MA Xiao, ZHOU Ao, WANG Shangguang

“…To address the issue where the resource limitations of wireless devices caused state extraction delays that cannot meet the freshness requirements of real-time applications, considering the limited processing capacity of edge nodes, a scheduling method that jointly considered information freshness and real-time performance was proposed. …”
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A Double-Edged Sword: The Effects of Stressors on Job Crafting and Career Sustainability by Xintian Li, Hainan Liu, Peng Peng

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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Abstract The article presents an adaptive approach to modelling and managing the service process of requests at peripheral nodes of edge-IoT systems. …”
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Numerical Simulation Analysis on a Composite Edge Terminal Reverse Blocking IGBT by Lei CUI, Tong YANG, Ruliang ZHANG, Li MA, Yichen LI

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Quantum Edge Detection and Convolution Using Paired Transform-Based Image Representation by Artyom Grigoryan, Alexis Gomez, Sos Agaian, Karen Panetta

“…Classical edge detection algorithms often struggle to process large, high-resolution image datasets efficiently. …”
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Community detection algorithm of hybrid node analysis and edge analysis in complex networks by Kun DENG, Qingfeng JIANG, Xingyan LIU

“…The community detection of hybrid node analysis and edge analysis in complex networks (CDHNE), a novel community detection algorithm, was proposed aiming at the problem that both edge community detection and node-based community detection algorithms had corresponding shortcomings in the process of detecting communities, which affected the quality of complex network community detection.The relatively stable characteristics of the edge in the networks were firstly used by the algorithm to construct a more accurate community structure through edge community detection at the early stage of algorithm execution.Then, after the formation of the edge communities, the flexible characteristics of the node were used to accurately detect the boundary of edge communities, so as to more accurately detect the community structure in the complex networks.In the computer-generated network experiments, when the community structure of the network gradually became fuzzy, the number of overlapping nodes and the number of communities to which the overlapping nodes belonged kept increasing.Compared to traditional algorithms, the accuracy of community detection and overlapping nodes detection were improved by an average of 10% and 15%, respectively, by the CDHNE algorithm.In the real network experiments, the tightness of the community structure detected by the CDHNE algorithm was better.Especially when facing large-scale networks with more than 100 000 nodes, the detection task was completed by the CDHNE algorithm with high quality, and the EQ value reached 0.412 1.The experimental results show that the CDHNE algorithm has advantages in operational stability and handling large-scale networks.…”
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Multibranch semantic image segmentation model based on edge optimization and category perception. by Zhuolin Yang, Zhen Cao, Jianfang Cao, Zhiqiang Chen, Cunhe Peng

“…Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”
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Glutamine’s double-edged sword: fueling tumor growth and offering therapeutic hope by Liguang Fang, Dandan Gao, Zuomin Jiang, Guoliang Li, Ming Li, Ming Li

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Ultimate Compression: Joint Method of Quantization and Tensor Decomposition for Compact Models on the Edge by Mohammed Alnemari, Nader Bagherzadeh

“…Our approach uniquely combines tensor decomposition techniques with binary neural networks to create efficient deep neural network models optimized for edge inference. The process includes training floating-point models, applying tensor decomposition algorithms, binarizing the decomposed layers, and fine tuning the resulting models. …”
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Effect of parameters on thermal stress in transpiration cooling of leading-edge with layered gradient by Chen Weijie, Wang Yongqing, An Bo, Zhang Qin, Su Huijuan, Wang Ke

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Two-Criteria Technique for the Resource-Saving Computing in the Fog and Edge Network Tiers by A. B. Klimenko

“…At present, the concepts of fog and edge computing are used in a wide range of applications of various kinds. …”
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SBDNet: A Scale and Edge Guided Bidecoding Network for Land Parcel Extraction by Wei Wu, Yapeng Liu, Lixin Tang, Haiping Yang, Liao Yang, Jin Li, Chen Zuohui

“…In addition, small targets are easily lost in the process, and the boundary may be broken, further affecting the accuracy of the task. …”
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Application of different edge detection methods for faults identification in Anza Basin, Kenya by Gege Li, Qing Chen, Bingqiang Yuan, Xianfeng Tan, Hao Chen, Xiaoyu Huang, Lang Pan

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