Enhanced Collaborative Edge Intelligence for Explainable and Transferable Image Recognition in 6G-Aided IIoT by Chen Chen, Ze Sun, Jiale Zhang, Junwei Dong, Peng Zhang, Jie Guo

“…IRCE leverages edge intelligence to optimize real-time performance while reducing computational costs and enhancing scalability. …”
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Precision Weed Management for Straw-Mulched Maize Field: Advanced Weed Detection and Targeted Spraying Based on Enhanced YOLO v5s by Xiuhong Wang, Qingjie Wang, Yichen Qiao, Xinyue Zhang, Caiyun Lu, Chao Wang

“…Secondly, we proposed an improved YOLO v5s network, incorporating a Convolutional Block Attention Module (CBAM), FasterNet feature extraction network, and a loss function to optimize the network structure and training strategy. …”
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Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives by Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, Obada Al-Khatib, Jeevan Kanesan

“…The global shift toward renewable energy, particularly wind power, underscores the critical need for advanced fault diagnosis systems to optimize wind turbine reliability and efficiency. While traditional diagnostic methods remain foundational, their limitations in addressing the nonlinear dynamics and operational complexity of modern turbines have accelerated the adoption of Artificial Intelligence (AI)-driven approaches. …”
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Urban Resilience and Energy Demand in Tropical Climates: A Functional Zoning Approach for Emerging Cities by Javier Urquizo, Hugo Rivera-Torres

“…The system’s capacity to adjust and optimize power distribution would be strengthened provided the algorithms were given the freedom to react dynamically to changes or disruptions brought about by distributed generation sources.…”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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An Active RIS-Aided DFRC System for Improved Multi-User Communications by Ravi Patel, Aayush Singh, Keshav Singh, Shahid Mumtaz, Chih-Peng Li, Sudip Biswas

“…We develop a optimization algorithm that leverages weighted minimum mean square error (WMMSE) and fractional programming techniques to maximize the weighted sum rate (WSR) for communication users while ensuring robust radar detection performance. …”
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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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Earthquake Design of Reinforced Concrete Buildings Using NSGA-II by Herian A. Leyva, Edén Bojórquez, Juan Bojórquez, Alfredo Reyes-Salazar, José H. Castorena, Eduardo Fernández, Manuel A. Barraza

“…In the present study, the optimal seismic design of reinforced concrete (RC) buildings is obtained. …”
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Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning by Shahin Sarhan, Marco Rinaldi, Stefano Primatesta, Giorgio Guglieri

“…The Deep Deterministic Policy Gradient (DDPG) algorithm optimizes flight paths, minimizing the noise impact, and balancing both the path length and the population density located under the UAV path. …”
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GARMT: Grouping-Based Association Rule Mining to Predict Future Tables in Database Queries by Peixiong He, Libo Sun, Xian Gao, Yi Zhou, Xiao Qin

“…However, data sparsity—where most fields in large table sets remain unused by most queries—leads to inefficiencies in access optimization. We propose a grouping-based approach (GARMT) that partitions SQL queries into fixed-size groups and applies a modified FP-Growth algorithm (GFP-Growth) to identify frequent table access patterns. …”
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Radar Coincidence Imaging for Off-Grid Target Using Frequency-Hopping Waveforms by Xiaoli Zhou, Hongqiang Wang, Yongqiang Cheng, Yuliang Qin, Haowen Chen

“…For off-grid RCI, the process is composed of two stages: grid matching and off-grid error (OGE) calibration, where two-dimension (2D) band-excluded locally optimized orthogonal matching pursuit (BLOOMP) and alternating iteration minimization (AIM) algorithms are proposed, respectively. …”
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A Biologically Inspired Cost-Efficient Zero-Trust Security Approach for Attacker Detection and Classification in Inter-Satellite Communication Networks by Sridhar Varadala, Hao Xu

“…The Manta Ray Foraging Optimization (MRFO) algorithm is used to minimize this cost, enabling effective classification of nodes as either trusted or malicious based on historical authentication records and real-time behavior. …”
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Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach by Yan Sun

“…In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. …”
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Hydrodynamic optimisation of a horizontal-axis hydrokinetic turbine for the River Ganga using a semi-analytical approach by Kripal, Anoop Kanjirakat

“…This enabled identification of an optimal configuration ensuring an efficient power curve while maintaining sufficient cavitation safety margin. …”
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Intelligent and automatic irrigation system based on internet of things using fuzzy control technology by Xinying Liu, Zhihuan Zhao, Amin Rezaeipanah

“…This paper presents an automatic, low-cost intelligent irrigation system based on a fuzzy rule-based inference approach and an energy-aware routing algorithm. The proposed system determines the optimal irrigation method using sensor data and ensures efficient information transmission through a fast fuzzy-based routing mechanism. …”
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A Machine Learning Approach for User Behavior Analysis in Developing Websites by Aeesha Shaheen

“…This data use for enhancement website interaction. While personalized recommendations design particularly for users based on predictable behavior, website optimization need prioritize influential pages.…”
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ARSOD-YOLO: Enhancing Small Target Detection for Remote Sensing Images by Yijuan Qiu, Xiangyue Zheng, Xuying Hao, Gang Zhang, Tao Lei, Ping Jiang

“…Moreover, our proposed ARSOD-YOLO optimized the network architecture, component modules, and loss functions based on YOLOv8, enhancing outstanding small target detection capabilities while preserving model efficiency. …”
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A Hierarchical Control Framework for Coordinating CAV-Dedicated Lane Allocation and Signal Timing at Isolated Intersections in Mixed Traffic Environments by Feng Chen, Cunbao Zhang, Yu Cao

“…The framework employs two collaborative agents based on the dueling double deep Q-network (D3QN) algorithm. The upper-level agent recommends optimal CAV-DLs configurations based on long-term traffic flow patterns, while the lower-level agent focuses on real-time signal control by adjusting signal parameters and green time allocations in response to current traffic demand. …”
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High Precision Navigation and Positioning for Multisource Sensors Based on Bibliometric and Contextual Analysis by Jiayi Wei, Min Song, Yunbin Yuan

“…By reviewing the evolution of integrated navigation technology, the study examines four typical integration modes: GNSS/INS, INS/visual, GNSS/INS/visual, and GNSS/INS/visual/LiDAR, discussing their complementarity, fusion algorithm optimization, and emerging application scenarios. …”
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