Area extraction and growth monitoring of sugarcane from multi-source remote sensing images under a polarimetric SAR data compensation based on buildings by Yong Hong, Tianjin Xie, Lengkun Luo, Mi Wang, Deren Li, Qing Zhang, Ting Xu

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Analysis of the Current State of Digitalization İmplementation in the Banking System of Azerbaijan by K. N. Atayev

“…The results of the conducted research reveal that the process of digitalization in Azerbaijan’s banking sector has been developing in a consistent and systematic manner in recent years. …”
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Changes in sarcopenia and incident cardiovascular disease in prospective cohorts by Qingyue Zeng, Lijun Zhao, Qian Zhong, Zhenmei An, Shuangqing Li

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An Automated and Efficient Slope Unit Division Method Coupled with Computer Graphics and Hydrological Principles by Ting Xiao, Li Zhu, Lichang Wang, Beibei Yang, Can Wang, Haipeng Yao

“…The research findings indicate that this method significantly enhances the scientific validity and practical applicability of slope unit delineation, providing reliable spatial analysis units for multidisciplinary surface process modeling.…”
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Phenotyping of masked hypertension based on the clustering of 24-hour blood pressure monitoring data by B. I. Geltser, K. I. Shakhgeldyan, V. N. Kotelnikov, O. O. Vetrova, V. V. Orlova-Ilyinskaya, R. S. Karpov

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SRW-YOLO: A Detection Model for Environmental Risk Factors During the Grid Construction Phase by Yu Zhao, Fei Liu, Qiang He, Fang Liu, Xiaohu Sun, Jiyong Zhang

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A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data by Qiongqiong Lan, Yaqing He, Qijin Han, Yongguang Zhao, Wan Li, Lu Xu, Dongping Ming

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PyAMARES, an Open-Source Python Library for Fitting Magnetic Resonance Spectroscopy Data by Jia Xu, Michael Vaeggemose, Rolf F. Schulte, Baolian Yang, Chu-Yu Lee, Christoffer Laustsen, Vincent A. Magnotta

“…<b>Methods</b>: PyAMARES was developed as a Python library, implementing the AMARES algorithm with additional features such as multiprocessing capabilities and customizable objective functions. …”
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Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning by Johan Helleberg, Anna Sundelin, Johan Mårtensson, Olav Rooyackers, Ragnar Thobaben

“…This approach shows promise for improving the accuracy of research and clinical applications relying on blood gas data.…”
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Conjunctival biomicroscopy in the diagnosis of microcirculatory disorders in systemic sclerosis: A new look at the “old” method by N. V. Korneeva, E. N. Otteva, K. V. Zhmerenetsky, M. A. Kovaleva, T. S. Panevin

“…Quantitative parameters of MC are compared with the clinical manifestations of SS by the methods of linear Pearson correlation and Spearman non-linear correlation. …”
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Deepfakes Detection by Iris Analysis by Elisabeth Tchaptchet, Elie Fute Tagne, Jaime Acosta, Danda B. Rawat, Charles Kamhoua

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Analyzing the impact of non-Newtonian nanofluid flow on pollutant discharge concentration in wastewater management using an artificial computing approach by Sidra Jubair, Jie Yang, Bilal Ali, Bandar Bin-Mohsin, Hamiden Abd El-Wahed Khalifa

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Characteristics of pore-fracture structure and three-dimensional spatial distribution differences in deep and shallow coal reservoirs: A case study of Junggar Basin by WANG Pengxiang, ZHANG Zhou, YU Wanying, ZOU Qiang, YANG Zhengtao

“…The differences in pore-fracture structures between deep and shallow coal reservoirs significantly affect coalbed methane extraction. Research on these structural differences provides theoretical support for exploring their physical properties and identifying favorable zones for coalbed methane exploration and development. …”
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What are the implications of using individual and combined sources of routinely collected data to identify and characterise incident site-specific cancers? a concordance and valida... by Rachael Williams, Helen Strongman, Krishnan Bhaskaran

“…We calculated positive predictive values and sensitivities of each definition, compared with a gold standard algorithm that used information from all linked data sets to identify first cancers. …”
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Stage-induced learning-based cooperative target hunting strategy for multiple unmanned surface vehicles by Xingru QU, Yuze JIANG, Feifei LONG, Rubo ZHANG, Ying GAO

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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…This research optimizes an electric vehicle (EV) sharing system for a university campus, focusing on different demand patterns and peak times within an Intelligent Transportation System (ITS) framework. …”
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Neural network backstepping control of OWC wave energy system by Priyanka Nath, Sunil Kumar Mishra, Amitkumar Vidyakant Jha, Bhargav Appasani, Akshaya Kumar Pati, Vijay Kumar Verma, Philibert Nsengiyumva, Avireni Srinivasulu

“…To address these challenges, this research paper introduces a Chebyshev NN within the BSC framework, leveraging its high approximation accuracy and computational efficiency. …”
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Real-Time DTM Generation with Sequential Estimation and OptD Method by Wioleta Błaszczak-Bąk, Waldemar Kamiński, Michał Bednarczyk, Czesław Suchocki, Andrea Masiero

“…Since DTM generation occurs simultaneously with data acquisition, the proposed algorithm also incorporates data reduction techniques to manage the large dataset. …”
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Few-Shot Learning With Prototypical Networks for Improved Memory Forensics by Muhammad Fahad Malik, Ammara Gul, Ayesha Saadia, Faeiz M. Alserhani

“…Memory forensics analyzes memory dumps to identify malicious activity, but faces challenges including large and complex datasets, constantly evolving malware threats, and limited labeled data for training algorithms among others. This research introduces a novel approach for malware detection using memory forensics and prototypical networks. …”
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Intellectual code analysis in automation grading by Denys Seliutin, Elena Yashyna

“…The syntactic analysis enabled the detection of problematic and erroneous code blocks and the identification of fraudulent attempts (manipulating the program's output instead of performing the algorithm). Conclusions. Most current automatic student work evaluation systems rely on testing, which involves comparing the program's inputs and outputs. …”
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