Edge Computing for AI-Based Brain MRI Applications: A Critical Evaluation of Real-Time Classification and Segmentation by Khuhed Memon, Norashikin Yahya, Mohd Zuki Yusoff, Rabani Remli, Aida-Widure Mustapha Mohd Mustapha, Hilwati Hashim, Syed Saad Azhar Ali, Shahabuddin Siddiqui

“…Edge computing devices and handheld gadgets can serve as useful tools to process medical data in remote areas with limited network and computational resources. …”
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Understanding Mantle Edge Pigmentation Through Comprehensive Transcriptomic Profiling of the Chilean Oyster (<i>Ostrea chilensis</i>) by Camila Godoy-Diaz, Katalina Llanos-Azócar, Gonzalo J. Ruiz-Tagle, Jorge E. Toro, Pablo A. Oyarzún, Juan A. Valdés

“…The RNA-seq analysis revealed 746 differentially expressed transcripts, 573 up-regulated and 173 transcripts down-regulated, between dark- and white-mantle edge Chilean Oyster. KEGG enrichment analysis revealed notable differences in the expression profiles allowing the detection of differential expressed transcripts associated with specific pathways such as Ribosome, Citrate cycle, and Protein processing in endoplasmic reticulum. …”
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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…Objectives: To make full use of the abundant data distributed at the edge of the network to serve the training of artificial intelligence models, edge intelligence technology represented by federated edge learning emerges as the times require. …”
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Medical Data over Sound—CardiaWhisper Concept by Radovan Stojanović, Jovan Đurković, Mihailo Vukmirović, Blagoje Babić, Vesna Miranović, Andrej Škraba

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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection by Muhammad Shafiq, J. Kavitha, Dhruva R. Rinku, N. K. Senthil Kumar, Kamal Poon, Amar Y. Jaffar, V. Saravanan

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DSC-SeNet: Unilateral Network with Feature Enhancement and Aggregation for Real-Time Segmentation of Carbon Trace in the Oil-Immersed Transformer by Liqing Liu, Hongxin Ji, Junji Feng, Xinghua Liu, Chi Zhang, Chun He

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Energy Efficiency Maximization in RISs-Assisted UAVs-Based Edge Computing Network Using Deep Reinforcement Learning by Chuanwen Luo, Jian Zhang, Jianxiong Guo, Yi Hong, Zhibo Chen, Shuyang Gu

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Autoencoder neural network-based abnormal data detection in edge computing enabled large-scale IoT systems by Tianqi YU, Yongxu ZHU, Xianbin WANG

“…Given the advantages of low cost and easy deployment,large-scale Internet of things (IoT) has been deployed for environment monitoring pervasively.Within such systems,cloud platform is typically utilized as a remote data and control center.However,tremendous amount of data uploading and processing induce huge challenges on bandwidth load and real-time data gathering.In order to overcome these challenges,edge computing enabled IoT system architecture was proposed for environmental monitoring.As the intermediate layer,local processing could be supported for end devices with low latency and assist with preliminary analysis to offload computational tasks from cloud and the amount of data uploading could be reduced.Based on this system architecture,an autoencoder neural network-based abnormal data detection scheme was developed newly.Performance evaluation has been conducted based on the practical oceanic atmospheric data.Simulation results indicate that the proposed scheme can accurately detect the abnormal data by fully exploiting the spatial data correlation.…”
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Spatiotemporal distribution patterns and assembly mechanisms of eukaryotic plankton communities in Liujiaxia Reservoir at the northeastern edge of the Tibetan Plateau by Lingyun Chen, Jihua Cheng, Yangcuo Wanma, Shiying Zhu, Alan Warren, Yingzhi Ning

“…The Liujiaxia Reservoir is located at the northeastern edge of the Tibetan Plateau and is a vital resource for communities and agriculture in the region. …”
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Secure Latency-Aware Task Offloading Using Federated Learning and Zero Trust in Edge Computing for IoMT by Waleed Almuseelem

“…The exponential growth of wearable medical devices generates massive healthcare data within the Internet of Medical Things (IoMT) framework, necessitating efficient and secure task processing. Although offloading medical tasks to Edge Servers (ESs) improves the agility of medical services and enhances real-time processing capabilities, it simultaneously introduces significant security and trust concerns in heterogeneous and delay-sensitive IoMT environments. …”
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HOODIE: Hybrid Computation Offloading via Distributed Deep Reinforcement Learning in Delay-Aware Cloud-Edge Continuum by Anastasios E. Giannopoulos, Ilias Paralikas, Sotirios T. Spantideas, Panagiotis Trakadas

“…The CEC is coupled with the need for hybrid task offloading, where the task placement decisions concern whether the tasks are processed locally, offloaded vertically to the cloud, or horizontally to interconnected edge servers. …”
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Evaluating QoS in Dynamic Virtual Machine Migration: A Multi-Class Queuing Model for Edge-Cloud Systems by Anna Kushchazli, Kseniia Leonteva, Irina Kochetkova, Abdukodir Khakimov

“…This study addresses the challenges of dynamically balancing server loads while minimizing downtime and migration costs under stochastic task arrivals and variable processing times. We propose a queuing theory-based model employing continuous-time Markov chains (CTMCs) to capture the interplay between VM migration decisions, server resource constraints, and task processing dynamics. …”
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Enhancing Contact Pressure Uniformity in Strip Drawing Tests: A Geometric Approach to Mitigate Edge Stress Risers by Llavori Iñigo, de Argandoña Eneko Saenz, Zabala Alaitz, McClosky Alex, Uribe Maitane, Otegi Nagore

“…The strip drawing test is widely used to assess the friction coefficient in sheet metal forming processes. A significant challenge in these tests is the presence of stress risers at the edges of flat punch configurations with rounded edges, which result in uneven contact pressure distributions and complicate friction characterization. …”
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MultiModal Ensemble Approach Leveraging Spatial, Skeletal, and Edge Features for Enhanced Bangla Sign Language Recognition by Khan Abrar Shams, Md. Rafid Reaz, Mohammad Ryan Ur Rafi, Sanjida Islam, Md. Shahriar Rahman, Rafeed Rahman, Md. Tanzim Reza, Mohammad Zavid Parvez, Subrata Chakraborty, Biswajeet Pradhan, Abdullah Alamri

“…To address this, we propose a procedure that reduces these uncertainties by considering three modalities: spatial information, skeleton awareness, and edge awareness. We introduce three image pre-processing techniques alongside three CNN models. …”
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Penerapan Machine Learning untuk Mengendalikan Parameter Budidaya Tanaman Hidroponik Berbasis Edge dan Cloud Computing by Helmy Helmy, Arif Nursyahid, Thomas Agung Setyawan

“…Edge computing allows real-time data processing at the hydroponic system's sensor devices, while cloud computing provides large storage and processing capacities. …”
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An Efficient Algorithm for Resource Allocation in Mobile Edge Computing Based on Convex Optimization and Karush–Kuhn–Tucker Method by Kaijing Wang, Shelily F. Akhtar, Fahad Ahmed Al-Zahrani

“…It offers a significant amount of processing and storage resources to the edge of networks, offloading applications from vehicle terminals that are computation-intensive and delay-sensitive. …”
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Concurrent Deterministic Execution Semantics for IEC 61499-Based OT&#x2013;IT Convergence Industrial Edge Applications by Wenbin Dai, Shang Gao, Kaiyun Qin, Chuanyang Yu, Dongdong Zhang, Likuan Zhang, Hui Zhang

“…Also, those tasks may include operation technologies, such as real-time control, and information technologies, such as data processing. Using a generic modeling language to design those new industrial edge applications becomes a challenge for site engineers. …”
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Parallel Task Offloading and Trajectory Optimization for UAV-Assisted Mobile Edge Computing via Hierarchical Reinforcement Learning by Tuo Wang, Xitai Na, Yusen Nie, Jinglong Liu, Wenda Wang, Zhenduo Meng

“…With the rapid growth of IoT data and increasing demands for low-latency computation, UAV-assisted mobile edge computing (MEC) offers a flexible solution to overcome the limitations of fixed MEC servers. …”
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Optimal dispatch of distributed renewable energy and energy storage systems via optimal configuration of mobile edge computing by He Jiang, Yan Zhao, Hang Zhou

“…To improve the efficiency of data processing and the flexibility of each unit dispatching, first, the areas are divided according to the load characteristics. …”
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The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing by Wen-Chung Shih, Zheng-Yao Wang, Endah Kristiani, Yi-Jun Hsieh, Yuan-Hsin Sung, Chia-Hsin Li, Chao-Tung Yang

“…Overall, the findings contribute valuable insights into building efficient edge computing architectures that support real-time video processing and streaming.…”
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