Using Wireless Sensor Networks to Achieve Intelligent Monitoring for High-Temperature Gas-Cooled Reactor by Jianghai Li, Jia Meng, Xiaojing Kang, Zhenhai Long, Xiaojin Huang

“…This technology not only reduces the cost of regular monitoring but also enables intelligent monitoring. …”
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A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou, Xiaoming Qin

“…Nowadays, spatio-temporal series prediction algorithms are emerging, but their prediction accuracy requires improvement. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…However, system heterogeneity, communication costs, and data imbalance remain critical. Oversampling techniques, model optimization, and reduced communication rounds were used to mitigate the issues. …”
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Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…It was determined that their integrated application provides an increase in the accuracy of reserve assessment by 15–20 % and a reduction in operating costs by 10–15 %. Key development trends are identified: integration of digital technologies, improvement of methods of collecting and processing geospatial data, introduction of machine learning algorithms for risk prediction. …”
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Corrective soft bus-bar splitting for reliable operation of hybrid AC/DC grids by Basel Morsy, Matthew Deakin, Adolfo Anta, Jochen Cremer

“…As the original problem is NP-hard, this paper utilizes a column-and-constraint generation algorithm. Case studies on IEEE 5, 24, 39, and 67 hybrid AC/DC systems show superiority of the proposed method, manifested as significant improvement in operating costs, security, and converter redispatch needs, under different loading conditions.…”
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LSTM-MM: Efficient LSTM-Based Mobility Management for Power Inspection Vehicles in Smart Grids by Xiaoyan Wang, Xianfeng Xie, Shengnan Zhao

“…This scheme leverages Software-Defined Networking (SDN) technology to centrally manage vehicle communication and network traffic, integrating trajectory prediction algorithms to forecast the future movements of power inspection vehicles, optimizing route planning, and improving operational efficiency and network performance. …”
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Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…This Special Issue on “Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data” presents innovative strategies leveraging remote sensing technologies, artificial intelligence (AI), and non-destructive testing (NDT) to optimize road infrastructure assessment. The ten papers published in this issue explore diverse methodologies, including novel deep learning algorithms for road inventory, novel methods for pavement crack detection, AI-enhanced ground-penetrating radar (GPR) imaging for subsurface assessment, high-resolution optical satellite imagery for unpaved road assessment, and aerial orthophotography for road mapping. …”
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Construction of Industrial Economic Management Decision Model Based on Three Parameter Interval Grey Numbers by Pao-Ching Lin, Tzu-Jung Wu, Jui-Chan Huang

“…In addition, through comparative experiments with other decision models, this model has shown superiority in improving profit margins, increasing sales, reducing unit costs, and reducing prediction errors. …”
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Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…Among these, green hydrogen—particularly via water electrolysis and biomass gasification—received the most attention, reflecting its central role in decarbonization strategies. ML algorithms such as artificial neural networks (ANNs), random forest (RF), and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield, optimize operational conditions, reduce emissions, and improve process efficiency. …”
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GPU Assisted Brute Force Cryptanalysis of GPRS, GSM, RFID, and TETRA by Cihangir Tezcan, Gregor Leander

“…In this work we provide optimized implementations of several widely used algorithms on GPUs, leading to interesting insights on the cost of brute force attacks on several real-word applications. …”
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Consensus recommendations for diagnosis and management of pulmonary arterial hypertension patients in Egypt by Ayman Farghaly, Ahmed A. Aziz, Reem El Korashy, Marwa Abdelrady, Wael Soliman, Ahmed Hassan, Youssef Amin Soliman

“…This should be coupled with the development of screening algorithms tailored to the Egyptian setting. To develop such national screening algorithms, cost-effectiveness studies should be conducted in Egypt to better understand optimal screening frequency and the best use of algorithms. …”
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Validation of Sea Surface Temperature From GK-2A Geostationary Satellite and Error Reduction Considering Impact of Satellite Zenith Angle by Kyung-Ae Park, Hye-Jin Woo, Stephane Saux Picart, Anne O'Carroll, Eunha Sohn, HuiTae Joo, Joon-Soo Lee, Joon-Yong Yang

“…By proposing optimal algorithms for SST retrievals from geostationary satellites, this study is anticipated to improve the monitoring of SSTs in regions covered by GK-2A. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. We designed Wise-IoU as the model's loss function to optimize the regression accuracy of its bounding boxes and enhance robustness to low-quality samples. …”
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Progressive role of artificial intelligence in treatment decision-making in the field of medical oncology by Archana Reddy Bongurala, Dhaval Save, Ankit Virmani

“…AI-driven personalized medicine optimizes treatment strategies, improving patient outcomes and reducing costs. …”
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AI-Driven Belt Failure Prediction and Prescriptive Maintenance with Motor Current Signature Analysis by João Paulo Costa, José Torres Farinha, Mateus Mendes, Jorge O. Estima

“…The incorporation of LSTM networks and swarm intelligence algorithms led to a significant improvement in predictive capabilities, allowing for the early detection of degradation patterns and timely intervention. …”
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Development of a manipulator kinematic model using Abb Robot Studio by Артем Бронніков, Марія Бендеберя

“…Conclusions: a model and software module were developed for the adaptive execution of the production process as part of the virtual model of the ABB IRB 1200 robot, which allows to increase the efficiency of the roduction process, reduce downtime, and improve product quality. The optimization of trajectories and collision management allowed to reduce the maintenance and operation costs of the robot, which led to an overall reduction in production costs, which will also be reflected in long-term use. …”
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A Distributed Collaborative Navigation Strategy Based on Adaptive Extended Kalman Filter Integrated Positioning and Model Predictive Control for Global Navigation Satellite System/... by Wanqiang Chen, Yunpeng Jing, Shuo Zhao, Lei Yan, Quancheng Liu, Zichang He

“…This framework predicts and optimizes each robot’s kinematic model, thereby improving the system’s collaborative operations and dynamic decision-making capabilities. …”
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Reducing bias in coronary heart disease prediction using Smote-ENN and PCA. by Xinyi Wei, Boyu Shi

“…Its treatment and prevention face challenges such as high costs, prolonged recovery periods, and limited efficacy of traditional methods. …”
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DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection by Shijin Song, Sen Du, Yuefeng Song, Yongxin Zhu

“…However, existing pruning algorithms exhibit high sensitivity to network architectures and typically require multiple sessions of retraining to identify optimal structures. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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