Area-Time-Efficient Secure Comb Scalar Multiplication Architecture Based on Recoding by Zhantao Zhang, Weijiang Wang, Jingqi Zhang, Xiang He, Mingzhi Ma, Shiwei Ren, Hua Dang

“…The interleaved modular multiplication algorithm and modified binary inverse algorithm are used to achieve short clock cycle delay and high frequency while taking into account the need for a low area. …”
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Research on Machine Learning-Based Extraction and Classification of Crop Planting Information in Arid Irrigated Areas Using Sentinel-1 and Sentinel-2 Time-Series Data by Lixiran Yu, Hongfei Tao, Qiao Li, Hong Xie, Yan Xu, Aihemaiti Mahemujiang, Youwei Jiang

“…The newly developed framework exhibits exceptional precision in categorization while maintaining impressive adaptability, offering crucial insights for optimizing agricultural operations and sustainable resource allocation in irrigation-dependent arid zones.…”
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Using Graph Neural Networks in Reinforcement Learning With Application to Monte Carlo Simulations in Power System Reliability Analysis by Oystein Rognes Solheim, Boye Annfelt Hoverstad, Magnus Korpas

“…Recent efforts from the authors indicate that optimal power flow solvers could potentially be replaced with the policies of deep reinforcement learning agents, to obtain significant speedups of Monte Carlo simulations while retaining close to optimal accuracies. …”
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Control strategy of robotic manipulator based on multi-task reinforcement learning by Tao Wang, Ziming Ruan, Yuyan Wang, Chong Chen

“…To tackle this issue, instead of uniform parameter sharing, we propose an adjudicate reconfiguration network model, which we integrate into the Soft Actor-Critic (SAC) algorithm to address the optimization problems brought about by parameter sharing in multi-task reinforcement learning algorithms. …”
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A Hybrid Deep Learning Model for UAV Path Planning in Dynamic Environments by Junchi Zhang, Yanning Xian, Xun Zhu, Hongtao Deng

“…While its variants can converge to the optimal solution, they suffer from more memory and computation consumption. …”
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Interference-Aware AAV-TBS Coordinated NOMA: Joint User Scheduling, Power Allocation and Trajectory Design by Haiyong Zeng, Rui Zhang, Xu Zhu, Yufei Jiang, Zhongxiang Wei, Fu-Chun Zheng

“…With the proposed scheme, the interference links between TBS and AAV-served users are enabled to carry useful information, therefore, an enhanced degree of freedom is achieved, leading to a much higher sum-rate over the non-coordinated AAV-assisted NOMA systems where the interference of AAV-served users from TBS is extensively suppressed. Moreover, joint optimization of user scheduling, power allocation and AAV three-dimensional (3D) trajectory design is conducted to maximize the sum-rate of edge users while maintaining a high quality of service at cell-center users, with the consideration of imperfect channel estimation: a) A user scheduling principle dedicated for AAV-TBS coordinated NOMA systems is presented, based on which a two-step user scheduling and power allocation (USPA) algorithm is proposed, with the derivation of optimal power allocation solution; b) A joint USPA algorithm is proposed with closed-form results; c) Considering the line of sight (LoS) and non-LoS factors in the air to ground channel, the 3D trajectory of AAV is designed based on successive convex approximation. …”
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Symmetry-driven embedding of networks in hyperbolic space by Simon Lizotte, Jean-Gabriel Young, Antoine Allard

“…We show that the samples are consistent with current algorithms while providing added credible intervals for the coordinates and all network properties. …”
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A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production by Hongtao Hu, Yiwei Wu, Tingsong Wang

“…An improved solution algorithm based on particle swam optimization is developed to efficiently solve the proposed model. …”
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State-Aware Energy Management Strategy for Marine Multi-Stack Hybrid Energy Storage Systems Considering Fuel Cell Health by Pan Geng, Jingxuan Xu

“…A hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO) approach achieves global optimization. …”
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RL based transmission power control for energy harvesting sensor by LIU Nanjun, JIA Riheng, XU Wentao, LI Minglu

“…Experimental results demonstrate that the proposed algorithm outperformes baseline strategies and approaches the theoretical optimal in certain scenarios.…”
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Modeling Analysis of the Relationship between Adolescent Aerobic Exercise and Obesity Reduction Based on Deep Learning by Peng Mu

“…It also explains the constraint conditions that aerobic exercise has to meet in the reduction of adolescent obesity and introduces particle algorithm to establish a model of optimal aerobic exercise to reduce adolescent obesity. …”
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Improving Secrecy Capacity in the Face of Eavesdropping in SWIPT CIoT Networks With Actor-Critic DRL by Nada Abdel Khalek, Walaa Hamouda

“…We formulate the challenging non-convex optimization problem to maximize secrecy capacity while ensuring spectrum sharing and energy constraints and model the CIoT agent’s decision-making as a model-free Markov decision process (MDP). …”
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Leveraging Interactive Evolutionary Computation to Induce Serendipity in Informal Learning by Satoko Inoue, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru

“…We conducted both numerical simulations and experimental evaluations to assess the effectiveness of our content optimization algorithm and the impact of our approach on inducing serendipity in informal learning environments. …”
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UAV Mission Path Planning Based on Reinforcement Learning in Dynamic Environment by Gui Fu, Yang Gao, Liwen Liu, Mingye Yang, Xinyu Zhu

“…The path planning and optimization of UAV in dynamic environment is studied, and the path planning algorithm and Hungarian algorithm are added. …”
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User Cost Minimization and Load Balancing for Multiple Electric Vehicle Charging Stations Based on Deep Reinforcement Learning by Yongxiang Xia, Zhongyi Cheng, Jiaqi Zhang, Xi Chen

“…In the second stage, we use the DRL algorithm. In the DRL algorithm, we design a novel reward function that enables charging stations to meet user charging demands while minimizing user charging costs and reducing the load gap among distribution networks. …”
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SV-SAE: Layer-Wise Pruning for Autoencoder Based on Link Contributions by Joohong Rheey, Hyunggon Park

“…This paper introduces a layer-wise pruning algorithm specifically for multilayer perceptron-based autoencoders. …”
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YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…A new algorithm called YOLO-APDM is proposed to address low quality and multi-scale target detection issues in infrared road scenes. …”
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Multiobjective Coverage Control Strategy for Energy-Efficient Wireless Sensor Networks by Hui Zhou, Tian Liang, Chen Xu, Jing Xie

“…A new evolutionary algorithm named Multiobjective free search algorithm (MOFS) is designed for WSN optimization problem based on fitness functions and binary coding schemes. …”
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Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems by Ahmed Al Hammadi, Lina Bariah, Sami Muhaidat, Mahmoud Al-Qutayri, Paschalis C. Sofotasios, Merouane Debbah

“…Moreover, the synergy between the MPF and the DQL algorithms is investigated. To this end, we demonstrate that the MPF algorithm maximizes the fairness amongst the users while the DQL algorithm maximizes the overall SE and improves the robustness against the noise. …”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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