Structural Fault Detection and Diagnosis for Combine Harvesters: A Critical Review by Haiyang Wang, Liyun Lao, Honglei Zhang, Zhong Tang, Pengfei Qian, Qi He

“…Combine harvesters, as essential equipment in agricultural engineering, frequently experience structural faults due to their complex structure and harsh working conditions, which severely affect their reliability and operational efficiency, leading to significant downtime and reduced agricultural productivity during critical harvesting periods. …”
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SWMD-YOLO: A Lightweight Model for Tomato Detection in Greenhouse Environments by Quan Wang, Ye Hua, Qiongdan Lou, Xi Kan

“…The accurate detection of occluded tomatoes in complex greenhouse environments remains challenging due to the limited feature representation ability and high computational costs of existing models. …”
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Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

“…Fire has consistently posed a significant disaster risk worldwide. Current fire detection methods primarily rely on traditional physical sensors such as light, smoke, and temperature detectors, which often struggle in complex environments. …”
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A Model For Optimization of Knowledge Management Outsourcing Decision Using Genetic Algorithm by Ameneh Khadivar, Fatemeh Abbasi, Sheyda Akbarian

“…It analyzes the criteria for selecting knowledge management outsourcing providers using a genetic algorithm. …”
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Detection of Hydrophobicity Grade of Composite Insulators Based on MDC‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Haichao Sun, Keyu Li, Mianxiao Wu, Bo Lan

“…ABSTRACT In the field of power equipment inspection, the aging condition of composite insulators is often determined by the detection of water repellency. However, the existing detection methods are difficult to effectively extract the water repellency level features in the complex background, and it is difficult to meet the real‐time requirements. …”
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Curb Detection and Mapping via Robust Iterative Gaussian Process Regression by Di Wang, Si Chen, Zhenni Ma, Jiajia Shi, Fuchun Zhang

“…Curb detection and mapping are of great importance to ensure the safety and efficiency of intelligent vehicles. …”
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A low-complexity M-shaped reconfigurable intelligent meta-surface for mitigating pathloss in wireless systems by Maira Khafagy, Sherief Fathi, Ahmed Magdy

“…This study presents a novel Low-Complexity M-shaped Reconfigurable Intelligent Metasurface (LCM-RIM) designed to mitigate path loss in indoor environments. …”
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Moving Vehicles Detection and Tracking on Highways and Transportation System for Smart Cities by Manoj Kumar, Susmita Ray, Dileep Kumar Yadav

“…In this paper, various approaches related to moving vehicle detection for the transportation system especially for highways are considered. …”
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Three-Dimensional Outdoor Object Detection in Quadrupedal Robots for Surveillance Navigations by Muhammad Hassan Tanveer, Zainab Fatima, Hira Mariam, Tanazzah Rehman, Razvan Cristian Voicu

“…Our model selection process, tailored to the specific needs of quadrupedal robots, emphasizes considerations such as model complexity, inference speed, and customization flexibility, achieving an accuracy of up to 99.93%. …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Abstract The ever-growing number of complex cyber attacks requires the need for high-level intrusion detection systems (IDS). …”
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Lightweight RT-DETR with Attentional Up-Downsampling Pyramid Network by Nan Li, Xiao Han, Xingguo Song, Xu Fang, Mengming Wu, Qiulin Yu

“…To address this, we propose an improved RT-DETR R18 model tailored for companion robots. This lightweight, efficient design integrates YOLOv9’s ADown module, the RepNCSPELAN4 module, and custom attention-based AdaptiveGateUpsample and AdaptiveGateDownsample modules for enhanced multi-scale feature fusion, reducing weight and complexity while optimizing real-time detection. …”
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Simple Cobalt Nanoparticle-Catalyzed Reductive Amination for Selective Synthesis of a Broad Range of Primary Amines by Bingxiao Zheng, Liqin Yang, Yashuang Hei, Ling Yu, Sisi Wen, Lisi Ba, Long Ao, Zhiju Zhao

“…This work presents a facile, aqueous-phase synthesis of highly active cobalt catalysts (Co-Ph@SiO₂(x)) via pyrolysis of silica-supported cobalt–phenanthroline complexes. The optimized Co-Ph@SiO₂(900) catalyst achieved exceptional performance (>99% conversion, >98% selectivity) in the reductive amination of acetophenone to 1-phenylethanamine using NH₃/H₂. …”
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Microscopic Origin of Polarity‐Dependent VTH Shift in Amorphous Chalcogenides for 3D Self‐Selecting Memory by Ha‐Jun Sung, Minwoo Choi, Zhe Wu, Hwasung Chae, Sung Heo, Youngjae Kang, Bonwon Koo, Jong‐Bong Park, Wooyoung Yang, Yongyoung Park, Yongnam Ham, Kiyeon Yang, Chang Seung Lee

“…Abstract Ovonic threshold switching (OTS) selectors based on amorphous chalcogenides can revolutionize 3D memory technology owing to their self‐selecting memory (SSM) behavior. However, the complex mechanism governing the memory writing operation limits compositional and device optimization. …”
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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

“… In recent years, Deep Neural Networks (DNN) have demonstrated remarkable success in various domains, including Intrusion Detection Systems (IDS). The ability of DNN to learn complex patterns from large datasets has significantly improved IDS performance, leading to more accurate and efficient threat detection. …”
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A Sparse Pooling Adversarial Learning Framework for Anomaly Event Detection by ZHANG, M., HU, H., LI, Z.

“…However, due to factors of complex background, large changes in scale, and the randomness of abnormal events, causing abnormal event detection poses significant challenges. …”
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The acoustic change complex as a diagnostic tool for cochlear dead regions evaluated in normally hearing adults by Anna Schelenz, Emanuele Perugia, Lin Wu, Ewa Skrodzka, Karolina Kluk

“…We found that the bootstrap method was most efficient at detecting ACC and was two times faster to administer than the commonly used British Society of Audiology method. …”
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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

“… In recent years, Deep Neural Networks (DNN) have demonstrated remarkable success in various domains, including Intrusion Detection Systems (IDS). The ability of DNN to learn complex patterns from large datasets has significantly improved IDS performance, leading to more accurate and efficient threat detection. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…Road event detection is critical for tasks such as monitoring, anomaly detection, and optimization. …”
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Enhancing surface detection: A comprehensive analysis of various YOLO models by G. Deepti Raj, B. Prabadevi

“…Version 5 of You Only Look Once (YOLO), a precisely optimized learning model, has undergone extensive testing on steel strip datasets, providing effective solutions for recognition and detection in industry environments. This study presents an improved YOLOv5 detection model, exploiting the efficient channel attention (ECA) and coordinated attention (CoordAtt) mechanisms. …”
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Explainable Anomaly Detection Based on Operational Sequences in Industrial Control Systems by Ka-Kyung Kim, Joon-Seok Kim, Ieck-Chae Euom

“…Many anomaly detection algorithms based on deep learning models have good performance but often involve complex neural network structures, creating a black-box issue where users cannot interpret the decisions made by the models. …”
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