Research on green supply chain finance risk identification based on two-stage deep learning by Ying Liu, Sizhe Li, Chunmei Yu, Mingli Lv

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Enhancing Customer Segmentation Through Factor Analysis of Mixed Data (FAMD)-Based Approach Using K-Means and Hierarchical Clustering Algorithms by Chukwutem Pinic Ufeli, Mian Usman Sattar, Raza Hasan, Salman Mahmood

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Research on the optimization of optimal blasting parameters and fragmentation control based on coal seam geological conditions by Zhouquan Liao, Xiaohua Ding, Mingzhi Liang, Jiangfeng Li, Zhongao Yang, Xin Liu, Bin Li, Yan Zhang

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Research and application of water drainage borehole design method based on three-dimensional geological model by Zhenrong WANG

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Research and analysis of differential gene expression in CD34 hematopoietic stem cells in myelodysplastic syndromes. by Min-Xiao Wang, Chang-Sheng Liao, Xue-Qin Wei, Yu-Qin Xie, Peng-Fei Han, Yan-Hui Yu

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IbI logics optimization algorithm-based high-order sliding mode control for DSIG within a wind turbine system by Khaled Benzaoui, Abderrahmen Bouguerra, Samir Zeghlache, Ahmed Elsanabary, Saad Mekhilef, Ahmed Bendib, Houssam eddine Ghadbane, Hegazy Rezk

“…To this end, the present paper proposes an innovative tuning method using an incomprehensible but intelligent-in-time logic algorithm (ILA) to ensure optimal HOSMC controller parameters tuning. …”
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An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

“…In this research study, we propose an empirical error model-based artifact removal approach for the cross-subject classification of motor imagery (MI) EEG data using a modified CNN-based deep learning algorithm, designed to assist wheelchair users with severe mobility issues. …”
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AI-Driven Particulate Matter Estimation Using Urban CCTV: A Comparative Analysis Under Various Experimental Conditions by Woochul Choi, Hongki Sung, Kyusoo Chong

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Hydrological Object‐Based Flow Direction Model for Constructing a Lake‐Stream Topological System by Fei Zhao, Liyang Xiong, Chuzhi Zhang, Hong Wei, Kai Liu, Guoan Tang

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Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiographyResearch in context by Jiesuck Park, Jiyeon Kim, Jaeik Jeon, Yeonyee E. Yoon, Yeonggul Jang, Hyunseok Jeong, Youngtaek Hong, Seung-Ah Lee, Hong-Mi Choi, In-Chang Hwang, Goo-Yeong Cho, Hyuk-Jae Chang

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Validation of a deep learning–based AI system for HER2-targeted breast cancer assessment using ultrasound imaging in a clinical setting by Kathryn Malherbe

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Thymic characteristics in patients with autoimmune diseases: a multicentre radiological observational studyResearch in context by Haoxiao Chang, Junqiang Yan, Anxin Wang, Ningning Wang, Peng Liu, Yemin Shi, Xin Zhao, Jinqiao Zhu, Yuan Cai, Xue Xia, Yunyi Hao, Shiyi Yin, Jing Wang, Xinli Wang, Lina Sun, Jia Ma, Xiaoyu Huang, Haonan Guan, De-Cai Tian, Kaibin Shi, Ganqin Du, Wenhao Huang, Guoyan Qi, Hao Li, Yongjun Wang, Fu-Dong Shi, Zhang Zhang, Wei-Na Jin

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A Method for Synthesizing Ultra-Large-Scale Clock Trees by Ziheng Li, Benyuan Chen, Wanting Wang, Hui Lv, Qinghua Lv, Jie Chen, Yan Wang, Juan Li, Cheng Zhang

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Comparative analysis of stomatal pore instance segmentation: Mask R-CNN vs. YOLOv8 on Phenomics Stomatal dataset by Thanh Tuan Thai, Thanh Tuan Thai, Thanh Tuan Thai, Ki-Bon Ku, Anh Tuan Le, Anh Tuan Le, San Su Min Oh, Ngo Hoang Phan, Ngo Hoang Phan, In-Jung Kim, Yong Suk Chung, Yong Suk Chung

“…Notably, YOLOv8 demonstrated superior performance over Mask R-CNN, particularly in accurately calculating stomata pore dimensions. Beyond this comparative study, the implications of our findings extend across diverse biological research, providing a robust foundation for advancing our understanding of plant physiology. …”
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Machine learning for prediction of 30-day mortality in patients with advanced cancer: comparing pan-cancer and single-cancer models by S. Bjerregaard-Michelsen, L.Ø. Poulsen, A. Bjerrum, M. Bøgsted, C. Vesteghem

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Linear Active Disturbance Rejection Control System for the Travel Speed of an Electric Reel Sprinkling Irrigation Machine by Lingdi Tang, Wei Wang, Chenjun Zhang, Zanya Wang, Zeyu Ge, Shouqi Yuan

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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

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Research on Control Method for DC Voltage of Cascaded Multi-level STATCOM Based on Flying-capacitor by 孙乐, 岳小龙, 熊连松, 卓放

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Survey on IPv6 address scanning technology based on seed sources by Guo LI, Lin HE, Guanglei SONG, Zhiliang WANG, Jiahai YANG, Zimu LI

“…Nowadays,the state-of-the-art technologies can spend a very short time to scan the whole IPv4 space,but these methods cannot be applied to the huge IPv6 space easily.Therefore,many researchers propose different heuristic algorithms for the sake of IPv6 scanning.The common way of these algorithms is to input collected IPv6 seed addresses and output new most likely active IPv6 addresses as candidates for later scanning.These methods greatly reduce the scanning range of the active address area.These technologies based on seed addresses were classified,analyzed and summarized,and detailed analysis of the advantages and disadvantages of each method was given.And the several challenges faced by the methods were discussed.73M seed addresses were collected in total from two sources,including published IPv6 datasets in papers and Beijing Node of China Education and Research Network.Through the proposed experiments,time performance and hit rate of four IPv6 address scanning technologies based on seed addresses was compared.Finally,the own thoughts on this field and some future research directions were proposed.…”
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Research on Maneuvering Motion Prediction for Intelligent Ships Based on LSTM-Multi-Head Attention Model by Dongyu Liu, Xiaopeng Gao, Cong Huo, Wentao Su

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