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  1. 421

    Optimizing Cancer Detection: Swarm Algorithms Combined with Deep Learning in Colon and Lung Cancer using Biomedical Images by HariKrishna Pathipati, Lova Naga Babu Ramisetti, Desidi Narsimha Reddy, Swetha Pesaru, Mashetty Balakrishna, Thota Anitha

    Published 2025-03-01
    “…This research presents an Optimizing Cancer Detection using whale optimizer with Deep Learning in Colon and Lung Cancer (OCDWO-DLCLC) model on Biomedical Images. …”
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    Article
  2. 422

    Evolution, reconfiguration and low-carbon performance of green space pattern under diverse urban development scenarios: A machine learning-based simulation approach by Yujie Ren, Mengdie Zhou, Antian Zhu, Shucheng Shi, Hao Zhu, Yuzhu Chen, Shanshan Li, Tianhui Fan

    Published 2024-12-01
    “…However, as urban land-use patterns become increasingly complex and development trajectories more diverse, the relationship between green space morphology and carbon dynamics (emissions and sequestration) reveals notable heterogeneity and non-linear characteristics. …”
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    Capturing drug use patterns at a glance: An n-ary word sufficient statistic for repeated univariate categorical values. by Gabriel J Odom, Laura Brandt, Clinton Castro, Sean X Luo, Daniel J Feaster, Raymond R Balise, CTN-0094 Team

    Published 2023-01-01
    “…<h4>Discussion</h4>Representing substance use patterns as a "word" allows researchers and clinicians an "at a glance" assessment of participants' responses to treatment over time. …”
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    Article
  6. 426

    The dietary patterns of water deer recently rediscovered in Northeast China exhibit remarkable similarities to those observed in other regions by Zongzhi Li, Zhicheng Yao, Mingchun Zhang, Romaan Hayat Khattak, Xingzhi Han, Jia Sun, Zhongyu Li, Jianmin Lang, Chong Chen, Jing Jin, Zhensheng Liu, Liwei Teng

    Published 2025-03-01
    “…The results revealed that water deer consume 110 plant species from 86 genera and 40 families annually. The dietary patterns observed in this study align closely with those reported in other regions, reflecting species-specific foraging characteristics and further validating the reliability of deep learning algorithms in ecological research. …”
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  7. 427
  8. 428

    Exploring trans-regional harvesting operation patterns based on multi-scale spatiotemporal partition using GNSS trajectory data by Daoye Zhu, Boyong Xiao, Haoling Xie, Dong Li, Haitong He, Weixin Zhai

    Published 2025-08-01
    “…Identifying agricultural machinery operations is crucial for enhancing agricultural productivity and promoting the transition to data-driven agriculture. Current research focuses solely on administrative divisions, overlooking the links between machinery movement, natural spatial patterns, and spatiotemporal dependencies. …”
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    Article
  9. 429

    Evaluating Spatial Patterns of Ecosystem Services based on a Comparative Approach on Spatial Statistics in the Central Part of Isfahan Province by Sedighe Abdollahi, Alireza Ildoromi, Abdolrassoul Salmanmahini, Sima Fakheran

    Published 2021-02-01
    “…Overall, according to the results, the Getis-Ord Gi indicates higher spatial accuracy than Local Moran’s I method for three ecosystem services, and the Receiving Operator Characteristic is an appropriate index to evaluate the accuracy of the analytical approaches used in This research. The findings of this study can be applied by decision makers and land planner to identify and management spatial correlation patterns of ecosystem services.…”
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  10. 430
  11. 431

    Crack-Based Estimation of Seismic Damage Level in Confined Masonry Walls in the Lima Metropolitan Area Using Deep Learning Techniques by Miguel Diaz, Luis Lopez, Michel Amancio, Italo Inocente, Jhianpiere Salinas, Sergio Isuhuaylas, Erika Flores, Edisson Moscoso

    Published 2025-05-01
    “…On the other hand, an experimental database of cyclic loading tests on confined masonry walls is available, supporting numerical simulations with calibrated mathematical models to estimate damage levels. This research extends the application of this database by analyzing the crack pattern imagery from the tested walls and correlating it with the lateral deformation (drift) to identify the damage levels. …”
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  12. 432

    Quantum behaved Intelligent Variant of Gravitational Search Algorithm with Deep Neural Networks for Human Activity Recognition by Sonika Jindal, Monika Sachdeva, Alok K. S. Kushwaha

    Published 2023-03-01
    “…The recognition of activities from videos and image sequences with higher exactitude is the major challenge. This research work presents an automated system to recognize individual and group activities with major focus is the proposal of a novel quantum behaved intelligent variant of gravitational search algorithm to optimize the features for activity recognition. …”
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  13. 433

    Predicting Financial Distress through Ranking Working Capital Management Components Using Random Forest Algorithm by Pouya Sadeghi, Daryush Farid, Hamid Reza Mirzaei, Abolfazl Dehghani

    Published 2025-03-01
    “…The primary objective of this research was to analyze the relative importance of working capital management factors in predicting financial distress among companies. …”
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    Outlier Traffic Flow Detection and Pattern Analysis Under Unplanned Disruptions: A Low-Rank Robust Decomposition Model by Zhipeng Duan

    Published 2025-01-01
    “…The spatiotemporal patterns of detected outlier traffic flow are analyzed at a station level. …”
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  17. 437

    “Human – Social Robot” Interaction: Through Overcoming Barriers to Hybrid Communication by V. I. Ignatyev, K. I. Spiridonova

    Published 2022-12-01
    “…A nonobtrusive (unobtrusive) research method was applied, which excludes the contact of the researcher with the object of study. …”
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    An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999–2018 by Qun Tang, Yong Wang, Yan Luo

    Published 2025-03-01
    “…Abstract Current research on the association between demographic variables and dietary patterns with atherosclerotic cardiovascular disease (ASCVD) is limited in breadth and depth. …”
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