Intelligent Trust Evaluation Method for Underwater Sensor Networks Based on Fuzzy Clustering and Dynamic Weight Allocation by Zhaohui WANG, Guangjie HAN, Jiaxin DU, Chuan LIN, Lei WANG

“…First, a hierarchical dynamic topology model of the USN was developed to enhance universality. …”
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LEO satellite Internet resource allocation strategy based on terminal traffic prediction by SHEN Fei, LYU Chengcheng, ZHANG Jiaxuan, RUAN Xiaoting

“…A resource allocation strategy for the low earth orbit (LEO) satellite Internet based on terminal traffic prediction was proposed to address the problems of blind coverage spots in ground network and the low resource utilization of satellite network. An improved LSTM-ARIMA algorithm was proposed with real datasets by the strategy to accurately predict the data traffic generated in the ground area over a certain period of time in the future. …”
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Application of Generative Adversarial Nets (GANs) in Active Sound Production System of Electric Automobiles by Kai Liang, Haijun Zhao

“…To improve the diversity and quality of sound mimicry of electric automobile engines, a generative adversarial network (GAN) model was used to construct an active sound production model for electric automobiles. …”
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FlyPhoneDB2: A computational framework for analyzing cell-cell communication in Drosophila scRNA-seq data integrating AlphaFold-multimer predictions by Mujeeb Qadiri, Ying Liu, Ah-Ram Kim, Myeonghoon Han, Eric Zhou, Austin Veal, Tzu-Chiao Lu, Hongjie Li, Yanhui Hu, Norbert Perrimon

“…However, the utility of FlyPhoneDB was limited by the relatively small number of available L-R pairs.Here, we present FlyPhoneDB2, a major upgrade featuring a significantly expanded knowledgebase that includes a greater number of L-R pairs, incorporating annotations from mammalian species and structural predictions from AlphaFold-Multimer. In addition, the algorithm has been optimized for improved performance and more effective noise filtering. …”
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Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

“…Design optimization of mechanical system components, such as spiral bevel gears, is important due to their complex geometry and design constraints. …”
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Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition by Dan QU, Wen-lin ZHANG

“…Original eigenphone speaker adaptation method performed well when the amount of adaptation data was suffi-cient.However,it suffered from server overfitting when insufficient amount of adaptation data was provided.A sparse group LASSO(SGL) constraint eigenphone speaker adaptation method was proposed.Firstly,the principle of eigenphone speaker adaptation was introduced in case of hidden Markov model-Gaussian mixture model (HMM-GMM) based speech recognition system.Then,a sparse group LASSO was applied to estimation of the eigenphone matrix.The weight of the SGL norm was adjusted to control the complexity of the adaptation model.Finally,an accelerated proximal gradient method was adopted to solve the mathematic optimization.The method was compared with up-to-date norm algorithms.Experiments on an mandarin Chinese continuous speech recognition task show that,the performance of the SGL con-straint eigenphone method can improve remarkably the performance of the system than original eigenphone method,and is also superior to l₁、l₂-norm and elastic net constraint methods.…”
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Physical Implementation and Experimental Validation of the Compensation Mechanism for a Ramp-Based AUV Recovery System by Zhaoji Qi, Lingshuai Meng, Haitao Gu, Ziyang Guo, Jinyan Wu, Chenghui Li

“…Based on the structural and geometric characteristics of the platform, a dual-channel closed-loop control strategy was proposed utilizing midpoint tracking of the capture window, accompanied by multi-level software limit protection and automatic centering mechanisms. The control algorithm was implemented using a discrete-time PID structure, with gain parameters optimized through experimental tuning under repeatable disturbance conditions. …”
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Cache Assignment for a Flexible Mobile User in Wireless Heterogeneous Networks by Mohammad Hossein Amerimehr, Parisa Eslami, Nahid Amani, sara Efazati

“…We exploit this property to provide an efficient approximate solution (i.e., a greedy algorithm) that is guaranteed to perform within a constant of  as well as the optimal solution. …”
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Enhancing stone matrix asphalt performance with sugarcane bagasse ash: Mechanical properties and machine learning-based predictions using XGBoost and random forest by Hamed Khani Sanij, Rezvan Babagoli, Reza Mohammadi Elyasi

“…The results revealed that the inclusion of 6 % SCBA yielded the most favorable outcomes. Marshall Stability increased significantly (up to 9.4 kN), ITS improved to 943 kPa, and moisture susceptibility was enhanced, demonstrating a higher tensile strength ratio compared to the control mixture. …”
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Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI by Tassilo Wald, Benjamin Hamm, Julius C. Holzschuh, Rami El Shafie, Andreas Kudak, Balint Kovacs, Irada Pflüger, Bastian von Nettelbladt, Constantin Ulrich, Michael Anton Baumgartner, Philipp Vollmuth, Jürgen Debus, Klaus H. Maier-Hein, Thomas Welzel

“…Leveraging cross-technique ground truth annotations during training improved the accuracy of DL models in detecting and segmenting BMs. …”
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Individual Travel Knowledge Graph-Based Public Transport Commuter Identification: A Mixed Data Learning Approach by Song Hu, Jiancheng Weng, Quan Liang, Wei Zhou, Peizhao Wang

“…The optimal model structure of neuron node number, transfer function, and learning rate are discussed quantitatively according to the minimization of model errors. …”
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Measurement Error Estimation Method of Field Service Electricity Energy Meters under the Condition of Big Data by DAI Yan-jie, DONG Xian-guang, LIU Ya-qi, LIANG Ya-jie, LIU Xiao, QI Jia, SUN Yong-quan

“…Firstly, the K-Means clustering algorithm is improved by optimizing the clustering evaluation index, and the field environmental data is analyzed by clustering. …”
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Uniform Physics Informed Neural Network Framework for Microgrid and Its Application in Voltage Stability Analysis by Renhai Feng, Khan Wajid, Muhammad Faheem, Jiang Wang, Fazal E. Subhan, Muhammad Shoaib Bhutta

“…This paper proposed an improved PINN, named Uniform Physics Informed Neural Network (UPINN), with Proximal Policy Optimization (PPO) based reinforcement learning, for extortion of parameters of these models. …”
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Equilibrium Analysis of Electricity Market with Multi-Agents Considering Uncertainty by Zhonghai Sun, Runyi Pi, Junjie Yang, Chao Yang, Xin Chen

“…A hybrid solution methodology integrating nonlinear complementarity formulations with genetic algorithm-based optimization was developed. Extensive numerical case studies validate the methodological efficacy, demonstrating improvements in solution optimality and computational efficiency compared to conventional approaches.…”
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OR-FCOS: an enhanced fully convolutional one-stage approach for growth stage identification of Oudemansiella raphanipes by Runze Fang, Huamao Huang, Nuoyan Guo, Haichuan Wei, Shiyi Wang, Haiying Hu, Ming Liu

“…The enhanced algorithm achieved a mean average precision (mAP) of 89.4% ( $$\hbox {mAP}_{50}$$ ) and 78.3% ( $$\hbox {mAP}_{50:95}$$ ), while the number of model parameters was reduced to 9.9 M, the model size was reduced to 40.1 MB, and the number of floating point operations per second (FLOPs) was reduced to 31.2 G. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Existing methods, including post-processing optimization, specific model based improvements, and body part feature based methods, have limitations such as inaccurate handling of heavily occluded positive samples, high computational complexity, and susceptible to background noise. …”
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Intelligent Counterforce Allocation Method Using Multi-Agent Reinforcement Learning for Ground Operations by Kiwoong Park, Sangheun Shim

“…The MARL agent is implemented using the Soft Actor-Critic algorithm and scaled through a Graph Attention Network to manage over 40 heterogeneous agents (infantry, tanks, and artillery). …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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A Systematic Review and Comparative Analysis Approach to Boom Gate Access Using Plate Number Recognition by Asaju Christine Bukola, Pius Adewale Owolawi, Chuling Du, Etienne Van Wyk

“…By optimizing the capabilities of advanced YOLO algorithms, the proposed method seeks to improve the reliability and effectiveness of access control through precise and rapid plate number recognition. …”
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MAB-RSP: Data pricing based on Stackelberg game in MCS by Yongjiao Sun, Xueyan Ma, Anrui Han

“…We introduce two novel contributions. First, the MAB-RS algorithm leverages multi-armed bandit reinforcement learning and a data freshness model to dynamically optimize seller recruitment, efficiently balancing exploration of unknown sellers and exploitation of high-quality ones. …”
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