A New Hybrid Reinforcement Learning with Artificial Potential Field Method for UAV Target Search by Fang Jin, Zhihao Ye, Mengxue Li, Han Xiao, Weiliang Zeng, Long Wen

“…Reinforcement learning (RL) has demonstrated excellent performance in real-time UAV navigation through dynamic optimization of decision-making strategies, but its application in large-scale environments for target search and obstacle avoidance is still limited by slow convergence and low computational efficiency. …”
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Deep learning-based phase demodulation for distributed acoustic sensor by Yiming Tang, Kewei Liu, Chen Liu, Haiyong Wu, Rugang Wang, Mengmeng Chen, Fei Xu

“…The proposed approach aims to replace the computationally intensive processes of traditional demodulation algorithms, such as the Hilbert transform, in specific scenarios. …”
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Methodical Principles for Determination of Optimum Breaking Places of Distributive Electrical Networks with Due Account of Supply Network of 110 kV and Higher by M. I. Fursanov, A. A. Zalatoi, V. V. Makarevich, A. N. Mukha

“…A specified model and algorithm for optimization of slit points in a distributive 10 (6) kV electrical network with due account of supply network of 110 kV and higher have been developed in the paper. …”
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Research and Application of a Health Management Device for the Electrical Control Cabinet of the EMU by Yongshen WU, Jian FENG, Mingshuai ZHANG, Chaoyue JU, Feihong YI

“…In view of the accidental malfunction of relays and contactors during the operation of vehicles, a health management device for electrical cabinets was presented based on the concept of edge computing in this study. Specifically, the data of voltage and current of the key loops of electrical cabinets were obtained through health management device in real time with a high speed, the real-time monitoring, status assessment, logic control analysis, malfunction diagnosis and residual life prediction throughout the life cycle of electrical cabinets could be achieved based on a recognition algorithm model. …”
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A Deep Neural Network-Based Approach to Media Hotspot Discovery by Pan Luo

“…First, the text data features are extracted based on the graphical convolutional neural network, and the temporal correlation of numerical information is modeled using gated recurrent units, and the numerical feature vectors are fused with the text feature vectors. Then, the K-means algorithm is optimized for the initial point selection problem, and a clustering algorithm based on the maximum density selection method in the moving range is proposed. …”
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Designing a sustainable and resilient agri-food closed-loop supply chain network for porcine products by Álvaro Ronaldo Elizalde Camacho, Fatemeh Gholian-Jouybari, Behzad Mosallanezhad, Neale R. Smith, Mostafa Hajiaghaei-Keshteli

“…A suite of hybrid metaheuristic algorithms, combining classical and modern approaches, is employed to address the computational complexity. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. …”
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Power allocation under per-antenna power constraints in multiuser MIMO systems by Sheng-qian HAN, Chen-yang YANG

“…A low-complexity power allocation algorithm was investigated under per-antenna power constraints(PAPC)in multiuser multiple-input multiple-output (MIMO) systems.It was shown that the optimal power allocation subject to PAPC,aimed at maximizing the sum rate of multiple users with zero forcing (ZF) precoders,had the structure of water-filling with multiple water-levels.Based on this result,the equivalence between PAPC and weighted sum power constraints was proved and a low-complexity suboptimal power allocation method was then proposed.Simulation results show that the proposed method outperforms the existing equal power allocation method and the heuristic method,and it can efficiently reduce the computational complexity with a negligible performance loss compared with the optimal power allocation method.…”
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Generalized MPC-DSVPWM Methods: Reduction Techniques and Explainable Machine Learning With Conformal Prediction for PMSM Drives by Hasan Ali Gamal Al-Kaf, Sadeq Ali Qasem Mohammed, Kyo-Beum Lee

“…Addressing computational time challenges of model predictive control with discrete space vector pulse width modulation (MPC-DSVPWM) poses a significant hurdle. …”
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Breaking language barriers with image detection and natural language processing model for English to Spanish translation by Bakhita Salman, Andres Lopez, Nathanielle Delapena

“…Fine-tuning the transformer model parameters, including learning rate scheduling and gradient clipping, further optimized system performance. The research demonstrates a 93.7% translation accuracy, achieved by combining state-of-the-art image processing algorithms, advanced transformer architectures, and a robust training dataset. …”
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Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality by Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

“…We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. The optimal cluster model parameters –including k, the number of phenotypes– were chosen automatically, by maximizing the average Silhouette score across the training set. …”
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Efficient collision-avoidance navigation strategy for autonomous surface vehicles in unstructured and constricted marine environments by Wenlong Meng, Rongdian Ku, Yanbo Pu, Xiaoxiao Shi, Ya Gong

“…The results highlight the algorithm’s distinct advantages across multiple dimensions such as path construction success, computational efficiency, and trajectory refinement quality, thereby underscoring its potential to advance autonomous navigation in challenging maritime settings.…”
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Ensemble Machine Learning for the Prediction and Understanding of the Refractive Index in Chalcogenide Glasses by Miruna-Ioana Belciu, Alin Velea

“…This study employs various machine learning models to reliably predict the refractive index at 20 °C using a small dataset of 541 samples extracted from the SciGlass database. The input for the algorithms consists of a selected set of physico-chemical features computed for the chemical composition of each entry. …”
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Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem by Juan Wang, Guanghui Zhang, Xiaoling Li, Yanxiang Feng

“…The influence of parameters on the algorithm is investigated based on design-of-experiment and comprehensive computational experiments are used to evaluate the performance of all algorithms. …”
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Analysis of the Interaction of Robots as Part of a Robotic System for Biomaterial Aliquotation by Sergey Khalapyan, Larisa Rybak, Dmitry Malyshev, Vladislav Cherkasov, Vladislav Vorobyev

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Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network by Guokang Xu, Jianchuan Yin, Jianchuan Yin, Jinfeng Zhang, Nini Wang

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Deep Reinforcement Learning Object Tracking Based on Actor-Double Critic Network by Jing Xin, Jianglei Zhou, Xinhong Hei, Pengyu Yue, Jia Zhao

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Human intelligence for authors, reviewers and editors using artificial intelligence by Mauricio Palacios Gomez

“…We call artificial intelligence any machine that processes information with some purpose, complying with the logical rules of Turing's computation described more than 70 years ago.  These machines work with instructions called algorithms, a finite and well-defined sequence of information processing implemented by automata (computers) or any digital technology to optimize a process. …”
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Intrusion Detection Using Machine Learning for Risk Mitigation in IoT-Enabled Smart Irrigation in Smart Farming by Abhishek Raghuvanshi, Umesh Kumar Singh, Guna Sekhar Sajja, Harikumar Pallathadka, Evans Asenso, Mustafa Kamal, Abha Singh, Khongdet Phasinam

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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

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