Context-Aware Beam Selection for IRS-Assisted mmWave V2I Communications by Ricardo Suarez del Valle, Abdulkadir Kose, Haeyoung Lee

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Speech Emotion Recognition Using a Multi-Time-Scale Approach to Feature Aggregation and an Ensemble of SVM Classifiers by Antonina STEFANOWSKA, Sławomir Krzysztof ZIELIŃSKI

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Semi-supervised Federated Learning for Digital Twin 6G-enabled IIoT: A Bayesian estimated approach by Yuanhang Qi, M. Shamim Hossain

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Multiobjective programming model for a class of flood disaster emergency material allocation by Li Huang, Zhicheng Yu, Wei Wang, Yue Song, Yunqing Wang

“…Moreover, we use the evolutionary algorithm based on the Pareto concept and simulate the calculation using computer simulation. …”
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An Unequal Clustering and Multi-Hop Routing Protocol Based on Fuzzy Logic and Q-Learning in WSNs by Zhen Wang, Jin Duan

“…To overcome this challenge and enhance network lifespan, this study presents FQ-UCR, a hybrid approach that merges unequal clustering based on fuzzy logic (FL) with routing optimized through Q-learning. In FQ-UCR, a tentative CH employs a fuzzy inference system (FIS) to compute its probability of being selected as the final CH. …”
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Efficient Markerless Motion Classification Using Radar by Changhyeon Eom, Sooji Han, Sabin Chun, Soyoung Joo, Jisu Yoon, Min Kim, Jongchul Park, Sanghong Park

“…Experimental results demonstrate that to optimize training data and increase computational efficiency, the sampling duration and sampling interval must be set appropriately.…”
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Inversion Method for Permitting Loadings of Pollutant from Lateral Effluents Based on Adjoint Equations by SHI Xiaoyan, ZHANG Hong, TAO Chunhua, LU Lingjiang, WAN Xin, LIU Zhaowei

“…The adjustment value for lateral effluents is calculated by solving the adjoint equations and employing the BFGS optimization algorithm, iteratively determining the permitted pollutant loadings from lateral discharges. …”
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Helicopter Turboshaft Engines’ Neural Network System for Monitoring Sensor Failures by Serhii Vladov, Łukasz Ścisło, Nina Szczepanik-Ścisło, Anatoliy Sachenko, Tomasz Perzyński, Viktor Vasylenko, Victoria Vysotska

“…The developed system demonstrated anomaly detection accuracy at 99.327% after 200 training epochs, with a reduction in loss from 2.5 to 0.5%, indicating stability in anomaly processing. A training algorithm incorporating temporal regularization and a combined optimization method (SGD with RMSProp) accelerated neural network convergence, reducing the training time to 4 min and 13 s while achieving an accuracy of 0.993. …”
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Neuroeconomics in the Age of AI: how machine learning alters human decision-making at the neural level by Dumitru Alexandru BODISLAV, Raluca Iuliana GEORGESCU

“…It highlights the modulation of neural circuits – such as the ventral striatum, prefrontal cortex, and anterior cingulate cortex – through algorithmic feedback, personalization, and reward optimization mechanisms. …”
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IMSBA: A Novel Integrated Sensing and Communication Beam Allocation Based on Multi-Agent Reinforcement Learning for mmWave Internet of Vehicles by Jinxiang Lai, Deqing Wang, Yifeng Zhao

“…Within this framework, MAPPO leverages vehicle perception data to dynamically optimize V2V beam steering and frequency selection, while the Stackelberg game reduces computational complexity through hierarchical decision-making and optimizes the joint power allocation among V2V users. …”
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Enhancing and Generalizing Position-Velocity Tracking in Imperfect <italic>mm</italic>Wave Systems Using a Low-Complexity Neural Network by Deeb Assad Tubail, Mohammed Zourob, Salama Ikki

“…Specifically, our method trains a NN that performs effectively under any noise conditions, without needing to recognize the transition model or initial state. To manage the computational demands of the training phase, we employ a low-complexity algorithm, the Extreme Learning Machine (ELM), which calculates weights and biases through closed-form solution, avoiding complex optimization processes. …”
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The Fault-Tolerant Control Strategy for the Steering System Failure of Four-Wheel Independent By-Wire Steering Electric Vehicles by Qianlong Han, Chengye Liu, Jingbo Zhao, Haimei Liu

“…Subsequently, considering the uncertainties in the drive control system and the complexities of the road obstacle model, the differential steering torque is computed via the sliding mode control method; the lower-level controller implements the torque optimization distribution strategy based on the quadratic programming algorithm. …”
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Study on the mechanisms associating community outdoor public spaces with elderly behavior by Lei Wang, Wenqi He, Shan Wu, Bo Zhang, Xiaorui Zhang, Hu Yin

“…The spatial elements are classified into four metrics: spatial, greenness, functional facilities, and accessibility. A computer vision-based behavior detection algorithm is then constructed to effectively identify six typical activities of the elderly: exercising, jogging, sitting, standing, walking, and playing chess or cards. …”
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Multiantenna Clustering Collaboration for WPCNs Based on Nonlinear EH by Lina Yuan, Huajun Chen, Anran Zhou, Rong Wang, Xianli Wen

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Joint Optical Performance Monitoring and Modulation Format&#x002F;Bit-Rate Identification by CNN-Based Multi-Task Learning by Xiaojie Fan, Yulai Xie, Fang Ren, Yiying Zhang, Xiaoshan Huang, Wei Chen, Tianwen Zhangsun, Jianping Wang

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State of Health Estimation for Lithium-Ion Batteries Using Electrochemical Impedance Spectroscopy and a Multi-Scale Kernel Extreme Learning Machine by Jichang Peng, Ya Gao, Lei Cai, Ming Zhang, Chenghao Sun, Haitao Liu

“…A multi-scale kernel extreme learning machine (MS-KELM), optimized by the Sparrow Search Algorithm (SSA), estimates battery SOH with an average mean absolute error (MAE) of 1.37% and a root mean square error (RMSE) of 1.76%. …”
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An Efficient Fine-Grained Access Control Scheme Based on Policy Protection in SGs by Xiaoqing Guo, Huayi Wu, Zhen Qin, Ruonan Ying, Jilai Yang

“…This data sharing plays a crucial role in improving power system stability, optimizing energy distribution, and enhancing energy efficiency. …”
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Forecasting Tunnel-Induced Ground Settlement: A Hybrid Deep Learning Approach and Traditional Statistical Techniques With Sensor Data by Syed Mujtaba Hussaine, Linlong Mu, Yimin Lu, Syed Sajid Hussain

“…Extensive evaluations using real-world sensor datasets from tunnelling projects demonstrated that the proposed Conv-GRU2D model achieved superior performance, with a R-squared of 0.94, an RMSE of 0.12, and MAPE of 0.32, surpassing both Conv-LSTM2D and optimized ARIMA/SARIMA models. These results highlight the effectiveness of convolutional mechanisms in deep learning and the advantage of optimized ARIMA/SARIMA models in capturing complex temporal patterns and improving forecasting precision for optimizing ground settlement. …”
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Multi-Stream Transmission for Directional Modulation Network via Distributed Multi-UAV-Aided Multi-Active-IRS by Ke Yang, Rongen Dong, Wei Gao, Feng Shu, Weiping Shi, Yan Wang, Xuehui Wang, Jiangzhou Wang

“…To achieve a lower computational complexity, a maximum trace method, called Max-TR-SVD, is proposed by optimizing the PSM of all IRSs. …”
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Markov approach for inventory control with meta-heuristics in intermittent demand environment. by Ferhat Yuna, Burak Erkayman, Mustafa Yılmaz

“…A mathematical model has been proposed for stock level optimization, but no feasible solution has been found. …”
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