Graph Neural Network With Hessian-Based Locally Linear Embedding for Cancer Metastasis Analysis in Lymph Nodes Using DeepLab Segmentation by Senthil Jayapal, R. Annamalai

“…To accomplish better preservation of the geometry of high-dimensional data and more effective feature extraction, the HLLE algorithm is applied. These features are then inputted into a GNN, which utilizes the graph structure to identify and analyze metastatic patterns. …”
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Improving Fall Classification Accuracy of Multi-Input Models Using Three-Axis Accelerometer and Heart Rate Variability Data by Seunghui Kim, Jae Eun Ko, Seungbin Baek, Daechang Kim, Sungmin Kim

“…To solve this problem, a fall prevention algorithm using an acceleration sensor has been developed, and research is being conducted to enable continuous monitoring using a Holter electrocardiograph. …”
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Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…Our method first preprocesses reviews and extracts key linguistic features based on extravagant words using a fuzzy logic-based membership function that highlights extreme linguistic patterns. Simultaneously, BERT embeddings capture the deep semantic meaning of the text. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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Correlation and Prediction Analysis of Cyanobacteria with Water Environment Data by Sang-Leen Yun

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PSYCHOLOGICAL ASPECTS OF INVOLVEMENT OF YOUNG PEOPLE IN EXTREMIST GROUPS IN THE INTERNET ENVIRONMENT by Olga V. Kruzhkova, Irina V. Vorobyeva, Darya M. Nikiforova

“…The materials of the research can be used to identify and effectively prevent the influence of extremist groups on young Internet users.…”
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Hydroecological limitations of the use of water resources of transboundary rivers of the steppe zone (through the example of the Ural and Tobol Rivers, Russia) by Zh. T. Sivohip, V. M. Pavleichik, A. A. Chibilev, Yu. A. Padalko, M. A. Kozlova, O. B. Popova

“…To identify the main types of hydroecological restriction on the use of water resources and their spatial patterns in the Ural and Tobol river basins within the steppe zone.A comprehensive assessment of the water‐environmental situation in the regions of the studied basins studied was carried out on the basis of the calculation of water‐environmental stress – the ratio of water intake and free flow (average long‐term flow minus ecological). …”
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A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy by Ilyas Nurmemet, Yilizhati Aili, Yang Xiang, Aihepa Aihaiti, Yu Qin, Bilali Aizezi

“…Furthermore, this study significantly expands the application potential of SAR data in soil salinization research.…”
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INTEGRATED ASSESSMENT AND MAPPING OF ANTHROPOGENIC IMPACT ON THE NATURAL ENVIRONMENT OF RUSSIAN REGIONS by V. S. Tikunov, S. K. Belousov

“…Materials and methods of the research. The calculated relative indicators of anthropogenic impact on the natural environment for the assessment were compiled into two data sets: for 2018 and for 2010-2018. …”
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Exploring Passengers’ Dependency Variety on Stations’ Functions in Urban Subway by Xia Zhao, Pengpeng Jiao, Yong Zhang, Chenjing Zhou

“…Meanwhile, passengers in the rest three groups possess a low dependency on urban subway and display extreme travel patterns in time and frequency, greatly increasing management difficulties for transit operators. …”
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Transformer attention fusion for fine grained medical image classification by Danyal Badar, Junaid Abbas, Raed Alsini, Tahir Abbas, Wang ChengLiang, Ali Daud

“…This model uses self-attention mechanics to improve spatial connections between single scales and cross-attention to automatically match feature patterns across multiple scales, thereby developing a comprehensive information structure. …”
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Two Decades of Coastal Development across the Arabian Gulf: Insights from Remote Sensing and Machine Learning by B. Dahy, R. Sousa, M. Sultan, J. A. Burt

“…These findings emphasize the complex interactions between urbanization and environmental processes, underscoring the need for sustainable planning strategies. Future research will focus on detailed analyses of vegetation, urbanization trends, and long-term inundation patterns to better support climate adaptation and regional resilience planning in the Arabian Gulf.…”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…This method provides an advanced risk management tool for power companies, helping to increase the operational efficiency of smart grids and encouraging further research toward greater intelligence in the field.…”
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Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors by Priyanka Shrivastava

“…Additionally, the manuscript now highlights demographic diversity, including variations in age, gender, and academic discipline, as relevant to AI adoption patterns. Ethical concerns, including algorithmic bias, data ownership, and the labor market impact of AI, are addressed to offer a more holistic understanding of resistance behavior. …”
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An enhanced integrated fuzzy logic-based deep learning techniques (EIFL-DL) for the recommendation system on industrial applications by Yasir Rafique, Jue Wu, Abdul Wahab Muzaffar, Bilal Rafique

“…It is quickly becoming an integral part of operations, as it yields successful and convenient results. This research provides an enhanced integrated fuzzy logic-based deep learning technique (EIFL-DL) for recent industrial challenges. …”
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Evaluation of future land use change impacts on soil erosion for holota watershed, Ethiopia by Abebe Chala Guder, Worku Firomsa Kabeta

“…In the Holota watershed of Ethiopia, rapid population growth and urbanization have accelerated unplanned land use and land cover (LULC) changes, significantly affecting soil erosion patterns. This study aims to assess the spatiotemporal changes in LULC and their impact on soil erosion from 2000 to 2050. …”
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Characterizing and Detecting Multiscenario Degradation of the Maidika Alpine Wetland Nature Reserve in the Qinghai–Tibet Plateau Using Landsat Time Series by Ye Chen, Ren Ci, Dongping Zhong, Liangyun Liu, Jinyuan Yu, Dongdong Zhang, Yindong Tong, Yingchun Fu

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Building an Associative Classification Data Model Based on the Apriori Method by K. V. Mulyukova, V. M. Kureichik

“…The results can be used both for the purpose of the initial research of technologies for analyzing large web data, and as an addition to the content management system for the intelligent analysis of web data. …”
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Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma by Bingxin Zhang, Dong Zheng, Shuxia Zhu, Xinyi Zhang, Quanqiang Wang, Zhili Lin, Ziwei Zheng, Shujuan Zhou, Zixing Chen, Sisi Zheng, Enqing Lan, Luning Cui, Hansen Ying, Yu Zhang, Xuanru Lin, Qiang Zhuang, Honglan Qian, Xudong Hu, Yan Zhuang, Qianying Zhang, Zhouxiang Jin, Songfu Jiang, Yongyong Ma, Yongyong Ma, Yongyong Ma

“…Finally, in vitro experiments examined the expression patterns of disulfidptosis-related genes (DRGs) in MM.ResultsBy cluster analysis, we obtained three subtypes with C2 having a worse prognosis than C3. …”
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What patients and caregivers want to know when consenting to the use of digital behavioral markers by Anika Sonig, Christine Deeney, Meghan E. Hurley, Eric A. Storch, John Herrington, Gabriel Lázaro-Muñoz, Casey J. Zampella, Birkan Tunc, Julia Parish-Morris, Jenny Blumenthal-Barby, Kristin Kostick-Quenet

“…Abstract Artificial intelligence (AI)-based computational tools for deriving digital behavioral markers are increasingly able to automatically detect clinically relevant patterns in mood and behavior through algorithmic analysis of continuously and passively collected data. …”
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