Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

“…ABSTRACT Detection of faults in solar photovoltaic (PV) systems is an important concern to guarantee that renewable energy source generation keeps its efficiency and reliability. …”
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Enhancing the Distinguishability of Minor Fluctuations in Time Series Classification Using Graph Representation: The MFSI-TSC Framework by He Nai, Chunlei Zhang, Xianjun Hu

“…Compared with ten benchmark methods, MFSI-TSC exhibits both high accuracy and computational efficiency, making it more suitable for deployment in sensor systems to complete incipient fault detection tasks.…”
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Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

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Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

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A reliable approach for identifying acute lymphoblastic leukemia in microscopic imaging by Mimosette Makem, Levente Tamas, Lucian Bușoniu

“…In this study, we deployed a pre-trained CNN model (MobileNet) that has a small size and low complexity, making it suitable for mobile applications and embedded systems. …”
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Identification of leaves of wild Ussurian Pear (Pyrus ussuriensis) based on YOLOv10n-MCS by Niman Li, Niman Li, Xingguang Dong, Yongqing Wu, Luming Tian, Ying Zhang, Hongliang Huo, Dan Qi, Jiayu Xu, Chao Liu, Zhiyan Chen, Yulu Mou

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A Method for Recognizing Dead Sea Bass Based on Improved YOLOv8n by Lizhen Zhang, Chong Xu, Sai Jiang, Mengxiang Zhu, Di Wu

“…Therefore, it is necessary to promptly detect dead fish and take countermeasures. Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. …”
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Red Tide Detection Method Based on a Time Series Fusion Network Model: A Case Study of GOCI Data in the East China Sea by Tianhong Ding, Zhiqiang Xu, Yunjie Wang, Qinglian Hou, Xiangyong Liu, Fengshuang Ma

“…Experimental results demonstrate that CSF-RTDNet achieves robust detection of red tides with complex boundaries and continuous temporal patterns, attaining an accuracy of 95.89%, precision of 93.03%, recall of 96.34%, and a Kappa coefficient of 0.95. …”
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Underwater Side-Scan Sonar Target Detection: An Enhanced YOLOv11 Framework Integrating Attention Mechanisms and a Bi-Directional Feature Pyramid Network by Junhui Zhu, Houpu Li, Min Liu, Guojun Zhai, Shaofeng Bian, Ye Peng, Lei Liu

“…To address these issues, this paper proposes the ABFP-YOLO model, which was designed to enhance the accuracy of underwater target detection. Specifically, the bi-directional feature pyramid network (BiFPN) structure is integrated into the model to efficiently fuse the features of different scales, significantly improving the capability of the network to recognize targets of varying scales, especially small targets in complex scenarios. …”
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Core–Shell Magnetic Gold Nanoparticles with Chitosan Coating as a SERS Substrate: A Rapid Detection Strategy for Malachite Green Contamination in Aquatic Foods by Yihui Yang, Tao Huang, Sijia Hu, Hang Ye, Jiali Xing, Shengnan Zhan

“…In this study, we developed a novel SERS-active magnetic substrate (MBs@CS@AuNPs) for detecting malachite green (MG) in aquatic products, including shrimp, cod, and aquaculture water. …”
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An enzyme-free electrochemical biosensor for sensitive and specific detection of microRNA-21 based on target recycling amplification and non-linear hybridization chain reaction by Jing Guo, Shou-feng Zhao, Shuang Chen, Wei-qing Song, Li-qun Li

“…Abstract A novel electrochemical biosensor with high amplification efficiency was explored for serum microRNA-21 (miRNA-21) detection. …”
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Application of Doehlert design combined with chemometrics tools: Example of the optimization of the elution of neurotransmitters and metabolites by HPLC by Camille Rosier, Bruno P. Guiard, Guillaume Gotti

“…Doehlert designs, in particular, are valued for their efficiency in exploring experimental space with minimal experiments, providing detailed insights into complex processes. …”
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Performance Evaluation of YOLOv11 and YOLOv12 Deep Learning Architectures for Automated Detection and Classification of Immature Macauba (<i>Acrocomia aculeata</i>) Fruits by David Ribeiro, Dennis Tavares, Eduardo Tiradentes, Fabio Santos, Demostenes Rodriguez

“…Inference throughput averaged 3.9 ms per image for YOLOv11x and 6.7 ms for YOLOv12x, highlighting a trade-off between speed and architectural complexity. Fused model representations revealed optimized layer fusion and reduced computational overhead (GFLOPs), facilitating efficient deployment. …”
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An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction by Ahmed Hadded, Mossaad Ben Ayed, Shaya A. Alshaya

“…Notably, the findings presented in this work are based exclusively on comprehensive simulations using COMSOL and MATLAB, as no physical prototypes or biomarker detection experiments were conducted. The SiNW-FET biosensor, functionalized with antibodies specific to viral antigens, detects impedance shifts caused by antibody–antigen interactions, providing a highly sensitive platform for viral detection. …”
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Civil structural health monitoring and machine learning: a comprehensive review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…These models may be used to estimate the compressive strength of masonry or repair mortars, probable damage scenarios in buildings, concrete models, beams, and columns for determining the mechanical characteristics of materials, damage detection in civil structures, and so on. This comprehensive review aims to clarify the array of ML-based methods employed in civil engineering, specifically focusing on their efficacy in strengthening energy efficiency and cost-effectiveness. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…These limitations include the complexity of the models and their poor ability to generalize. …”
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FedAV: Federated learning for cyberattack vulnerability and resilience of cooperative driving automation by Guanyu Lin, Sean Qian, Zulqarnain H. Khattak

“…The anomaly detection performance was enhanced by average and weighted aggregation strategies. …”
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Multi-scale target intelligent detection method for coal, foreign object and early damage of conveyor belt surface under low illumination and dust fog by Hongwei FAN, Jinpeng LIU, Xiangang CAO, Chao ZHANG, Xuhui ZHANG, Man LI, Hongwei MA, Qinghua MAO

“…Finally, a lightweight and efficient channel attention mechanism is introduced into the backbone network and feature fusion network to improve channel utilization and early damage detection accuracy. …”
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Adaptive Multi-Sensor Fusion for SLAM: A Scan Context-Driven Approach by Yijing Zhang, Jia Liu, Runxi Cao, Yunxi Zhang

“…This paper proposes a novel multi-sensor fusion SLAM algorithm, named SC-LVI-SAM, based on scanning context, to address the issues of decreased positioning accuracy caused by missing feature points and prolonged motion in complex large-scale scenes in multi-sensor fusion SLAM algorithms. …”
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Civil Structural Health Monitoring and Machine Learning: A Comprehensive Review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…These models may be used to estimate the compressive strength of masonry or repair mortars, probable damage scenarios in buildings, concrete models, beams, and columns for determining the mechanical characteristics of materials, damage detection in civil structures, and so on.  This comprehensive review aims to clarify the array of ML-based methods employed in civil engineering, specifically focusing on their efficacy in strengthening energy efficiency and cost-effectiveness. …”
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