Using Artificial Intelligence in Employment: Problems and Prospects of Legal Regulation by D. A. Novikov

“…Objective: to identify the legal problems of using artificial intelligence in hiring employees and the main directions of solving them.Methods: formal-legal analysis, comparative-legal analysis, legal forecasting, legal modeling, synthesis, induction, deduction.Results: a number of legal problems arising from the use of artificial intelligence in hiring were identified, among which are: protection of the applicant’s personal data, obtained with the use of artificial intelligence; discrimination and unjustified refusal to hire due to the bias of artificial intelligence algorithms; legal responsibility for the decision made by a generative algorithm during hiring. …”
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A Forecasting Approach for Wholesale Market Agricultural Product Prices Based on Combined Residual Correction by Bo Li, Yuanqiang Lian

“…Initially, the sparrow search algorithm (SSA) is used to optimize the penalty factors and kernel parameters of support vector regression (SVR) and the input weights and hidden layer biases of the extreme learning machine (ELM), thereby improving the convergence rate and predictive accuracy of these models. …”
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Bolt Anchorage Quality Levels Classification Method Based on HO‐VMD‐CNN‐BiLSTM by Fan Kesong, Zhang Can, Liu Shaowei, Feng Mengyin, Yan Ao, Fu Mengxiong, He Deyin, Nie Zhibin

“…The model incorporates the Logistic‐Tent chaotic mapping optimization algorithm, which enhances global search capability, improves feature extraction, and increases detection efficiency and accuracy. …”
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CFD-Guided Design of Non-Uniform Flow Channels in PEMFCs for Waste Heat Utilization in District Heating Networks by Dai Cui, Dong Liu, Peng Yu, Jiayi Li, Zhi Zhou, Meishan Zhang, Qun Chen, Fang Yuan

“…These findings validate the algorithm’s efficacy in resolving coupled transport constraints and underscore the necessity of multi-component optimization for advancing PEMFC design.…”
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Stochastic robot failure management in an assembly line under industry 4.0 environment by Kuldip Singh Sangwan, Anirudh Tusnial, Suveg V Iyer

“…A particle swarm optimization (PSO) algorithm is developed to solve the proposed integrated model. …”
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Adaptive data driven multi period power supply recovery method for distribution networks by Xi Ye, Meng Yang, Zhihong Yang, Qing Xiang, Yazhuo Li

“…Finally, simulations on the improved IEEE-33 bus system and actual example systems verify that the adaptive data driven power supply recovery model for distribution networks can reduce conservatism and improve the robustness of the optimization results. …”
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A deep learning-based hybrid method for PM2.5 prediction in central and western China by Zuhan Liu, Zihai Fang, Yuanhao Hu

“…The model integrates the transformer and LSTM architectures and employs parameter optimization through the particle swarm optimization (PSO) algorithm. …”
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An Innovative Online Adaptive High-Efficiency Controller for Micro Gas Turbine: Design and Simulation Validation by Rui Yang, Yongbao Liu, Xing He, Zhimeng Liu

“…When the DL_ELM model detects a gas turbine’s performance change, a particle swarm optimization (PSO) algorithm is employed to iteratively calculate the DFF_DL_OSELM model, determining the optimal speed control scheme to ensure the gas turbine operates at maximum efficiency. …”
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Control Strategy of In-Port U-Turn for Ships Based on Arctangent Function Nonlinear Feedback by Shihang Gao, Xianku Zhang

“…The strategy integrates a closed-loop gain-shaping algorithm with nonlinear feedback control, applied to a nonlinear motion mathematical model specifically designed for low-speed operations in shallow waters. …”
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Generative Adversarial and Transformer Network Synergy for Robust Intrusion Detection in IoT Environments by Pardis Sadatian Moghaddam, Ali Vaziri, Sarvenaz Sadat Khatami, Francisco Hernando-Gallego, Diego Martín

“…Additionally, an improved non-dominated sorting biogeography-based optimization (INSBBO) algorithm is employed to fine-tune the hyper-parameters of the hybrid model, further enhancing learning stability and detection performance. …”
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UAM Vertiport Network Design Considering Connectivity by Wentao Zhang, Taesung Hwang

“…To efficiently solve the problem and improve solution quality, a hybrid genetic algorithm is developed by incorporating a Minimum Spanning Tree (MST)-based connectivity enforcement mechanism, a fundamental concept in graph theory that connects all nodes in a given network with minimal total link cost, enhanced by a greedy initialization strategy. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
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Application of Machine Learning for Adaptive Trajectory Control of UAVs Under Uncertainty by Alexander S. Ermilov, Olga A. Saltykova

“…Special attention is given to the practical application of ML for environmental change prediction and flight trajectory optimization. Examples of real-world ML algorithm implementations include successful developments by Russian and foreign companies, demonstrating high levels of autonomy and adaptive control. …”
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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
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Stackelberg Game Based on Trajectory Prediction for Lane Change in Mixed Traffic by Baichuan Shi, Li Zhai, Chang Liu

“…The method develops a utility function for human-driven vehicles incorporating driving styles and safety-comfort-efficiency factors, with a corresponding cost function for autonomous vehicles. An improved Stackelberg game model integrates trajectory prediction of human-driven vehicles, while a bi-level optimization algorithm combining model predictive control and genetic algorithms jointly optimizes acceleration sequences and lane-change timing. …”
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New Hybrid Method for Buffer Positioning and Production Control Using DDMRP Logic in Smart Manufacturing by Sahar Habbadi, Ismail El Mouayni, Brahim Herrou, Souhail Sekkat

“…To identify the optimal buffer locations, a Genetic Algorithm (GA) is employed. …”
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Classification of Fritillaria thunbergii appearance quality based on machine vision and machine learning technology by DONG Chengye, LI Dongfang, FENG Huaiqu, LONG Sifang, XI Te, ZHOU Qin’an, WANG Jun

“…In addition, to optimize YOLO-X, according to the unique features of F. thunbergii dataset, a dilated convolution structure was embedded into the end of the backbone feature extraction network of YOLO-X as it could improve the model sensitivity to the dimension feature. …”
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SPARCQ: Enhancing Scalability and Adaptability of Proactive Edge Caching Through Q-Learning by Shruti Lall, Johan de Clercq, Nelishia Pillay, Bodhaswar T. Maharaj

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No-load and on-load performance analysis of 10-stator-slots five phase flux switching machines with non-overlapped winding configurations by Muhammad Yousuf, Faisal Khan, Ahmed Tameemi, Wasiq Ullah

“…An evolutionary optimization process based on the genetic algorithm (GA) integrated with the JMAG software is executed to optimize the machine models, resulting in significant improvements in the analyzed WFFS machine models. …”
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