Joint Optimization of Resource Allocation and Task Offloading Strategies in Multi-Cell Dynamic MEC Systems Using Multi-Agent DRL by Yuntao Hu, Ming Chen, Haowen Sun, Yinlu Wang, Yihan Cang

“…The energy consumption minimization is achieved by jointly optimizing the task offloading proportions, transmit power allocations, and computational resource distributions while ensuring the overall deadline constraints and the minimum processing size requirements in each scheduling cycle. …”
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Improving PM2.5 and Visibility Predictions in China Using Machine Learning and Ensemble Forecasting by Ziyin Zhang, Jing Xu, Xiujuan Zhao, Siyu Cheng

“…Furthermore, we introduce a new ensemble forecasting algorithm, RCHEM‐AI, which capitalizes on dynamic RMSE and TCC weights based on machine learning predictions. …”
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Voronoi-GRU-Based Multi-Robot Collaborative Exploration in Unknown Environments by Yang Lei, Jian Hou, Peixin Ma, Mingze Ma

“…In the lower layer, navigation planning is achieved using A* and Timed Elastic Band (TEB) algorithms, while an improved Cartographer algorithm is used to construct a joint map for the multi-robot system. …”
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Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case by Ivan Izonin, Roman Tkachenko, Nazarii Hovdysh, Oleh Berezsky, Kyrylo Yemets, Ivan Tsmots

“…The approach utilizes two artificial intelligence tools: the first Probabilistic Neural Network generates output signals that expand the independent attributes of an augmented dataset, while the second machine learning algorithm performs the final classification. …”
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Green logistics optimization for coal supply in a power plant connecting maritime port by Mingsheng Qiu, Liping Gao, Zhouyong Lin, Minghong Zheng, Qingzhong Lin

“…Numerical experiments demonstrate the algorithm’s superior performance compared to traditional solvers like Gurobi, particularly in handling large-scale instances. …”
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Leveraging ensemble learning-based stock preselection with multiobjective investment optimization for stepwise decision-supported portfolio management by Jui-Sheng Chou, Tran-Bao-Quyen Pham

“…This stage leverages a newly developed algorithm tailored to address the expanded mean–variance problem, effectively decomposing and optimizing it while balancing multiple objectives. …”
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Hippopotamus based optimization for reliable and cost-effective designing of stand-alone hybrid renewable system for a remote area by Sanjeev Gupta, Sanjeev Gupta, Yashwant Sawle, Kishor Thakre, M. Thirunavukkarasu, M. Thirunavukkarasu

“…Also, the outcomes of the proposed algorithm were contrasted with those of the HOMER platform. …”
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The Effectiveness of Peyton’s 4-Step Approach to Teach Resuscitation Skills: A Randomized Controlled Clarification Study by Denisa Cenaj, Leonie Schulte-Uentrop, Leonie Fee Laura Kröger, Josephine Küllmei, Jan-Marcus Haus, Parisa Moll-Khosrawi

“…Undergraduates of the intervention group reported significant higher learning gains for procedural ACLS skills, like performing the algorithm ( P  < .001). Conclusion Integrating Peyton's 4-step approach into structured ACLS training enhances procedural cardiopulmonary resuscitation skills, adherence to the ACLS algorithm, and skill retention in advanced stages of medical education, especially when undergraduates have prior resuscitation experience. …”
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E²VRP-CPP: An Energy-Efficient Approach for Multi-UAV Multi-Region Coverage Path Planning Optimization in the Enhanced Vehicle Routing Problem by Yuechao Zang, Xueqin Huang, Min Lu, Qianzhen Zhang, Xianqiang Zhu

“…We propose an approach that optimizes UAV flight speeds to minimize energy consumption, supported by an accurate energy estimation algorithm. In addition, a heuristic algorithm is developed to balance the distribution of tasks among UAVs, considering both the scanning and transit times. …”
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Secure and efficient trust enabled routing in mobile ad hoc network using game theory and grey wolf optimisation techniques by Ujwala Ravale, Gautam M. Borkar

“…This protocol's novel ability to dynamically scale performance measures as nodes expand improves efficiency and adaptability. While improving performance metrics, the proposed algorithm also efficiently identifies malicious nodes and re‐routes the transmission, excluding the found malicious nodes. …”
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Efficient resource allocation for D2D-enabled social IoT networks: A tripartite and time-scale optimization approach by Saurabh Chandra, Rajeev Arya, Maheshwari Prasad Singh

“…The proposed approach prioritizes maintaining Quality of Service (QoS) and resource allocation to minimize power consumption while maximizing sum throughput. Simulated results demonstrate the superiority of the proposed algorithm over standard benchmark schemes. …”
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A Collaborative Transit Signal Priority Method Considering Gaming among Traffic Participants by Bing Wu, Haishan Wang, Yanli Wang, Ben Zhai, TanXing Xue

“…A finite state machine-based algorithm is developed to estimate the average delays of nontransit vehicles. …”
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Deep Reinforcement Learning-Based Impact Angle-Constrained Adaptive Guidance Law by Zhe Hu, Wenjun Yi, Liang Xiao

“…We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. …”
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In situ fully vectorial tomography and pupil function retrieval of tightly focused fields by Xin Liu, Shijie Tu, Yiwen Hu, Yifan Peng, Yubing Han, Cuifang Kuang, Xu Liu, Xiang Hao

“…When combined with our decoding algorithm, this strategy mitigates the imperfections in the detection path. …”
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Two-Timescale Cross-Layer Design for URLLC Over Parallel Fading Channels With Imperfect CSI by Hongsen Peng, Meixia Tao

“…Based on the small timescale optimization method, we adopt the ternary search algorithm to optimize the pilot length and pilot power through Monte Carlo evaluations in the large timescale. …”
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Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images by Gregory Starr, Sebastijan Mrak, Yukitoshi Nishimura, Michael Hirsch, Prakash Ishwar, Joshua Semeter

“…Because no ground truth labels exist for the MIT, we extensively characterize the behavior of the algorithm by comparing it to the method developed by Aa, Zou, et al. (2020, doi:https://doi.org/10.1029/2019JA027583). …”
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Investigating the Machining Behavior of the Additively Manufactured Polymer-Based Composite Using Adaptive Neuro-Fuzzy Learning by Anastasios Tzotzis, Dumitru Nedelcu, Simona-Nicoleta Mazurchevici, Panagiotis Kyratsis

“…Multi-objective optimization using the Non-Dominated Sorting Genetic Algorithm 2 (NSGA-II) algorithm was employed to minimize both <i>Ra</i> and <i>T</i> simultaneously. …”
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Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

“…To tackle this issue, we introduce "Beyond Orion," a novel lossless compression method designed to optimize data compression in IoT systems. The algorithm employs advanced techniques such as Lempel Ziv-Welch and Huffman encoding, while also integrating strategies like pipelining, parallelism, and serialization for greater efficiency and lower resource usage. …”
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System identification and robust PID controller tuning of quarter car suspension system using hybrid optimization techniques by S. Sakthiya Ram, C. Kumar, R. Saravanakumar, David Banjerdpongchai

“…After validating the resulting dynamic model, various PID controllers are designed using standard metaheuristic algorithms—Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA). …”
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FEXGBIDS: Federated XGBoost-Based Intrusion Detection System for In-Vehicle Network by Jie Li, Yuanyuan Song, Ming-Gang Zheng, Shuo Zhang, Han Liang

“…We use the BatchCrypt algorithm to batch encrypt first- and second-order gradients to reduce the computational and communication overhead of Paillier homomorphic encryption. …”
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