Task collaborative offloading scheme in vehicle multi-access edge computing network by Guanhua QIAO, Supeng LENG, Hao LIU, Kaisheng HUANG, Fan WU

“…In order to solve the problem that traditional mobile edge computing network can’t be straightforwardly applied to the Internet of vehicles (IoV) due to high speed mobility and dynamic network topology,a vehicular edge multi-access computing network (VE-MACN) was introduced to realize collaborative computing offloading between roadside units and smart vehicles.In this context,the collaborative computation offloading was formulated as a joint multi-access model selection and task assignment problem to realize the good balance between long-term system utility,diverse needs of IoV applications and energy consumption.Considering the complex joint optimization problem,a deep reinforcement learning-based collaborative computing offloading scheme was designed to overcome the curse of dimensionality for Q-learning algorithm.The simulation results demonstrate that the feasibility and effectiveness of proposed offloading scheme.…”
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Federated Synergy: Hierarchical Multi-Agent Learning for Sustainable Edge Computing in IIoT by S. Benila, K. Devi

“…This paper introduces the Hierarchical Multi-Agent Federated Actor-Critic (HMAFAC) algorithm. This novel approach integrates hierarchical reinforcement learning with multi-agent federated learning to enhance decision-making in dynamic edge computing environments. …”
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A dynamic service migration strategy based on mobility prediction in edge computing by Lanlan Rui, Shuyun Wang, Zhili Wang, Ao Xiong, Huiyong Liu

“…Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge to satisfy the increasing amounts of low-latency tasks. …”
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Bregman divergences for physically informed discrepancy measures for learning and computation in thermomechanics by Andrieux, Stéphane

“…With view on the context of convex thermomechanics, we propose tools based on the concept of Bregman divergence, a notion introduced in the 1960s and used in learning and optimization as well. This study is motivated by the need of “discrepancy measures” between physically constrained fields that are used both in traditional algorithms, analysis methods and data driven modelling or applications as well.We give also a characterization of symmetrical Bregman divergences through their generating functions which can only be quadratic forms. …”
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Application of Brain-Computer Interfaces in Rehabilitation of Central Nervous System Disorders by GE Yi, ZHONG Ying, HONG Wenjun, XU Rong

“…However, the clinical application of BCI is still in the experimental stage and faces many challenges, such as the need to break through hardware bottlenecks and optimize algorithms at the technical level, and the need to promote large-scale clinical trials, establish a global ethical and regulatory framework, and cross-disciplinary collaboration at the clinical translation level.…”
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Computer Methods for the Antimicrobial Efficacy of Metal Nanoparticles Against MDR Microbes by Shanza Anzar, Ayesha Sohail, Lubna Sherin, Peter S. Kim

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TinderAI: Support System for Matching AI Algorithms and Embedded Devices by Matteo Francobaldi, Allegra De Filippo, Andrea Borghesi, Nikola Pizˇurica, Igor Jovančević, Tim Llewellynn, Miguel de Prado

“…The widespread adoption of AI algorithms is reflected in the extensive range of HW devices on which they can be deployed, from high-performance computing nodes to low-power embedded devices. …”
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Application of EEG-Based Brain-Computer Interface Technology in Stroke Rehabilitation by SHU Yuhong, FU Jianming, YAO Yunhai, ZENG Ming, GU Xudong

“…The shortcomings of the application include large signal noise, low spatial resolution, and insufficient personalized schemes. By optimizing deep learning algorithms, establishing personalized treatment systems, ethical norms for multimodal fusion, and phased clinical translation strategies, EEG-BCI technology is expected to provide more precise and safe rehabilitation plans for stroke patients.…”
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Hybridization of metaheuristic algorithms for resource scheduling in distributed robotic control system by P. Anand Raj, M. Rajakumaran, S. Palani Murugan, S. Senthilkumar

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Computational and experimental study of thermal behavior in the oral cavity for biosensing applications by Yuanzhe Zhao, Jeroen H.M. Bergmann

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Cardiac Computed Tomography Measurements in Pulmonary Embolism Associated with Clinical Deterioration by Anthony J. Weekes, Angela M. Pikus, Parker L. Hambright, Kelly L. Goonan, Nathaniel O’Connell

“…Continuous measurements from computed tomography pulmonary angiograms (CTPAs) may improve risk stratification. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…The findings indicate that natural language processing efficiency and machine learning advancements have significant impacts on investment planning accuracy. Computational linguistics is deeply embedded in algorithmic financial models and reshapes cost forecasting frameworks through data-driven semantic interpretation. …”
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Coding for Young Learners: Enhancing Computational Thinking and Creativity in Elementary Education by Hilmiyah, Abd Muhith, Syamsul Bahri

“…Coding skills have become essential for young learners to develop computational thinking and creativity. This study explores the implementation of coding education to enhance computational thinking among elementary school students, particularly at SD Negeri 21 Dauh Puri Denpasar, where technological access is limited. …”
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Synthesis of a reversible quantum Vedic multiplier on IBM quantum computers by Mojtaba Noorallahzadeh, Mohammad Mosleh

“…They use quantum algorithms for improved performance and depend on reversible computations based on quantum physics and linear algebra. …”
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Adaptive Management of Multi-Scenario Projects in Cybersecurity: Models and Algorithms for Decision-Making by Vadim Tynchenko, Alexander Lomazov, Vadim Lomazov, Dmitry Evsyukov, Vladimir Nelyub, Aleksei Borodulin, Andrei Gantimurov, Ivan Malashin

“…Future studies will aim to refine scenario adaptation and optimize system response in high-risk project environments.…”
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A Systematic Review and Evaluation of Sustainable AI Algorithms and Techniques in Healthcare by Yehia Ibrahim Alzoubi, Ahmet E. Topcu, Ersin Elbasi

“…AI algorithms and tools are categorized into three groups: explicit AI algorithms for sustainability for energy efficiency (e.g., Federated Learning, Hybrid Quantum-Classical Optimization, Modified Lempel-Ziv-Welch (mLZW)), traditional AI algorithms for sustainable healthcare (e.g., Bidirectional Long Short-Term Memory (Bi-LSTM), Backpropagation Neural Networks (BPNNs), Convolutional Neural Networks (CNNs)), and sustainable AI techniques (e.g., Adaptive Sampling, AutoML for Model Compression (AMC)) that support low-power computing (e.g., edge computing, neuromorphic hardware, adaptive sampling). …”
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Computer-Aided Diagnosis and Staging of Pancreatic Cancer Based on CT Images by Min Li, Xiaohan Nie, Yilidan Reheman, Pan Huang, Shuailei Zhang, Yushuai Yuan, Chen Chen, Ziwei Yan, Cheng Chen, Xiaoyi Lv, Wei Han

“…The least absolute shrinkage and selection operator (LASSO) algorithm was chosen for feature selection. In contrast to no feature selection, the model optimization time decreased by 19.94 seconds while maintaining precision. …”
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MATHEMATICAL ANALYSIS OF NON-GAUSSIAN REGIME ORIGINATION IN NUMERICAL INTEGRATION OF ISOELECTROFOCUSING PROBLEM by Lyudmila V. Sakharova

“…Due to the problem analytic transformation, the development of the optimization algorithms and the numerical asymptotic testing, it is found that non-Gaussian regimes are the property of the original mathematical problem, and not the computational error accumulation consequence.…”
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Simulation modeling of parts stamping line with four presses by S. V. Lukyanets, S. V. Snisarenko, M. A. Lishay

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Estimating Canopy Chlorophyll Content of Potato Using Machine Learning and Remote Sensing by Xiaofei Yang, Hao Zhou, Qiao Li, Xueliang Fu, Honghui Li

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