Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks by Rafiq Fajar Ramadhan, Wahid Miftahul Ashari

“…Despite the small difference in accuracy, Decision Tree demonstrated faster prediction times, making it more efficient for time-sensitive applications. This research concludes that while Random Forest provides higher accuracy for complex datasets, Decision Tree offers a more time-efficient solution with comparable accuracy.…”
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Complex PM2.5 Pollution and Hospital Admission for Respiratory Diseases over Big Data in Cloud Environment by Yi Zhou, Lianshui Li

“…Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. Second, an efficient attention module search strategy is proposed to replace traditional fully connected layer structures, which not only increases detection accuracy but also reduces computational overhead. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…Existing models have high false and missed detection rates in complex weather and multi-scale equipment scenarios. …”
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Negotiation impact in Supply Chain Management by Elena-Simona Ionel

“…It is determining critical decisions like supplier selection, contract terms, pricing, warranty, liability and dispute resolution becoming key activity in aligning with stakeholders objectives and mitigating risks in complex global markets. …”
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An optimized stacking-based TinyML model for attack detection in IoT networks. by Anshika Sharma, Shalli Rani, Mohammad Shabaz

“…With the expansion of Internet of Things (IoT) devices, security is an important issue as attacks are constantly gaining more complex. Traditional attack detection methods in IoT systems have difficulty being able to process real-time and access limitations. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…For practical implementation and validation, a PMSM simulation model is constructed in MATLAB/Simulink, serving as an interactive training platform for the DRL agent and facilitating efficient, robust training. The simulation results validate the effectiveness and superiority of the proposed optimization strategy, demonstrating its applicability and potential for precise and robust control in complex nonlinear defect detection systems.…”
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Subsea Nodule Recognition and Deployment Detection Method Based on Improved YOLOv8s by Jixin Li, Junchao Li, Bin Su, Yuxin Cui

“…An improved small-target detection model based on YOLOv8s is proposed to address the challenges associated with deep-sea polymetallic nodule detection, such as complex target shapes, small sizes, and strong environmental interference. …”
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A Rapid Concrete Crack Detection Method Based on Improved YOLOv8 by Yongzhen Wang, Jiacong He

“…An improved YOLOv8 (You Only Look Once version 8) model is proposed to tackle the challenges of low detection accuracy and slow speed resulting from the complex background and shape diversity of concrete cracks. …”
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YOLOv-MA: A High-Precision Foreign Object Detection Algorithm for Rice by Jiahui Wang, Mengdie Jiang, Tauseef Abbas, Hao Chen, Yuying Jiang

“…Additionally, the adaptive spatial feature fusion (ASFF) module is employed to improve multi-scale feature fusion in rice foreign object detection, significantly boosting YOLOv8’s object detection capability in complex scenarios. …”
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Inline Wear Detection in High-Speed Progressive Dies Using Photometric Stereo by Moske Jonas, Kutlu Hasan, Steinmeier Adrian, Groenewold Phil, Santos Pedro, Kuijper Arjan, Weinmann Andreas, Groche Peter

“…The progressive forming of complex components, including blanking, deep-drawing, and bending, represents an economically efficient sheet metal processing method. …”
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Double-layer membrane framework-based gold microelectrode for determination of natural labile copper in complex water environments by Xinyue Hu, Haitao Han, Shanshan Wang, Dawei Pan

“…However, the determination of low concentration labile Cu (CuLabile) in complex water environments remains a huge challenge. …”
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Multicarrier dual-index permuted chaos shift keying system for efficiency improvement in chaotic communications by Bavatharani Gurusamy, Laxmikandan Thangavelu, Manimekalai Thirunavukkarasu

“…The proposed system improves the energy andspectrum efficiencies with a tradeoff in computational complexity. …”
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Balancing cleaner energy and geopolitical interests in the complex transition of the European electricity mix: from Fukushima to the Ukraine war by Marcio Cataldi, Nieves Espinosa, Sonia Jerez, Juan Pedro Montávez, Larissa Haringer Martins Da Silveira, Jairton Dupont, Marcos Alexandre Teixeira

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Detecting eavesdropping nodes in the power Internet of Things based on Kolmogorov-Arnold networks. by Rong Wang, Weibin Jiang, Yanjin Shen, Qiqing Yue, Kan-Lin Hsiung

“…Traditional eavesdropping detection methods struggle to adapt to complex and dynamic attack patterns, necessitating the exploration of more intelligent and efficient anomaly localization approaches. …”
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Improved YOLOv8n Models for Object Detection in Remote Sensing Images by Young-Long Chen, Kai-Chun Hung, Jia-Yun Zhang, Ling-Wei Lin

“…However, applying these models to remote sensing images remains challenging due to complex backgrounds, high object scale variation, and the difficulty of detecting small objects. …”
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Application of the YOLOv11-seg algorithm for AI-based landslide detection and recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…Compared with traditional methods, YOLOv11-seg performs better in detecting complex boundaries and handling occlusion, demonstrating superior detection accuracy and segmentation quality. …”
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Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture by Zheng Huang, Xiuhua Zhang, Hongsen Wang, Huajie Wei, Yi Zhang, Guihong Zhou

“…This model provides technical support for Xinli No. 7 fruit detection and model deployment in complex environments.…”
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AutoML based workflow for design of experiments (DOE) selection and benchmarking data acquisition strategies with simulation models by Xukuan Xu, Donghui Li, Jinghou Bi, Michael Moeckel

“…Results obtained from electrical circuit models with varying complexity show that not all AL sampling strategies outperform conventional DOE strategies, depending on the available data volume, the complexity of the dataset, and data uncertainties. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…However, dense planting patterns and complex environments within greenhouses present challenges for accurately detecting growth stages. …”
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