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  1. 1061
  2. 1062

    Lightweight patch-level attention for efficient pig behavior detection: A novel dataset and approach by Shuo Wan, Zhongqiang Huang, Tao Han, Ying Sha

    Published 2025-12-01
    “…Pig behavior detection involves the automatic recognition and classification of pig behaviors in farm images using computer vision and deep learning techniques. …”
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  3. 1063

    Design of a home video behavior recognition system based on visual privacy security mechanism by D.M. Zhao

    Published 2025-04-01
    “…The rapid development of the Internet and advanced technology has brought great convenience to people’s lives; However, real-time video and other privacy information obtained from computers can be leaked, resulting in economic losses and not conducive to the construction of computer network security. …”
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  4. 1064
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  6. 1066

    Stable Inverse Reinforcement Learning via Leveraged Guided Motion Planner for Driving Behavior Prediction by Minglu Zhao, Masamichi Shimosaka

    Published 2025-01-01
    “…Driving behavior prediction has become increasingly important, owing to rapid advancements in autonomous vehicle technologies. …”
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  7. 1067
  8. 1068

    Association between sedentary behavior and dementia: a systematic review and meta-analysis of cohort studies by Jinyan Luo, Yiping Huang, Gangqiang Gao, Ching-Wen Chien, Tao-Hsin Tung

    Published 2025-05-01
    “…Abstract Objective This study aimed to assess the association between sedentary behavior (SB) and dementia among the general adult population. …”
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  9. 1069

    Dynamical behavior of damaged railway sleeper subjected to moving loads: Parametric study of crack properties by Thuy-Duong Le, Le-Hung Tran

    Published 2025-01-01
    “…This integrated model enables efficient computation of the dynamic behavior of damaged sleepers, where cracks are present at specific locations. …”
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  10. 1070
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  12. 1072

    Rethinking Poultry Welfare—Integrating Behavioral Science and Digital Innovations for Enhanced Animal Well-Being by Suresh Neethirajan

    Published 2025-04-01
    “…Third, I examine the transformative potential of computer vision, bioacoustics, and sensor-based technologies for the continuous, automated tracking of behavior and physiological indicators in commercial flocks. …”
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  13. 1073

    Dynamic behavior of nonuniform functionally graded Euler-Bernoulli beams under multiple moving forces by Le Thi Ha, Nguyen Dinh Kien, Vu Tuan Anh

    Published 2015-08-01
    “… The dynamic behavior of nonuniform Euler-Bernoulli beams made of transversely functionally graded material under multiple moving forces is studied by the finite element method. …”
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  14. 1074
  15. 1075

    Experimental Study on Compressive Capacity Behavior of Helical Anchors in Aeolian Sand and Optimization of Design Methods by Qingsheng Chen, Wei Liu, Linhe Li, Yijin Wu, Yi Zhang, Songzhao Qu, Yue Zhang, Fei Liu, Yonghua Guo

    Published 2025-07-01
    “…The research findings demonstrate the following: (1) Compressive capacity exhibits significant enhancement with increasing helix diameter yet displays limited sensitivity to helix number. (2) Load–displacement curves progress through three distinct phases—initial quasi-linear, intermediate non-linear, and terminal quasi-linear stages—under escalating pressure. (3) At embedment depths of <i>H</i> < 5<i>D</i>, tensile capacity diminishes by approximately 80% relative to compressive capacity, manifesting as characteristic shallow anchor failure patterns. (4) When <i>H</i> ≥ 5<i>D</i>, stress redistribution transitions from bowl-shaped to elliptical contours, with ≤10% divergence between uplift/compressive capacities, establishing 5<i>D</i> as the critical threshold defining shallow versus deep anchor behavior. (5) The helix spacing ratio (<i>S</i>/<i>D</i>) governs the failure mode transition, where cylindrical shear (CS) dominates at <i>S</i>/<i>D</i> ≤ 4, while individual bearing (IB) prevails at <i>S</i>/<i>D</i> > 4. (6) XGBoost feature importance analysis confirms internal friction angle, helix diameter, and embedment depth as the three parameters exerting the most pronounced influence on capacity. (7) The proposed computational models for <i>N</i><sub>q</sub> and <i>K</i><sub>u</sub> demonstrate exceptional concordance with numerical simulations (mean deviation = 1.03, variance = 0.012). …”
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  16. 1076

    Biological behavior of preneoplastic conditions of the endometrium: A retrospective 16-year study in south India by Rao Shalinee, Sundaram Sandhya, Narasimhan Raghavan

    Published 2009-12-01
    “…<b>Background:</b> The biological behavior of endometrial carcinoma differs in epidemiology, presentation, and prognosis, suggesting that there are two fundamentally different pathogenic types of disease: type I (estrogen related, endometrioid type) and type II (non-estrogen related, non-endometrioid type). …”
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  17. 1077

    On Modeling Agent Behavior Change Through Multi-Typed Information Diffusion in Online Social Networks by Masaaki Miyashita, Norihiko Shinomiya, Daisuke Kasamatsu, Genya Ishigaki

    Published 2025-01-01
    “…This model aims to depict the effectiveness of information in inhibiting selfish behavior (behavior-guiding information) in the phenomenon. …”
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  18. 1078
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    Formal Verification of Multi-Thread Minimax Behavior Using mCRL2 in the Connect 4 by Diego Escobar, Jesus Insuasti

    Published 2024-12-01
    “…The parallel version of minimax distributes computations across multiple threads, with each thread evaluating different successor states concurrently. …”
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  20. 1080

    On quantifying dynamic behavior of architected metal/polymer TPMS/lattices-based interpenetrating phase composites by K. B. Shingare, Andreas Schiffer, Kin Liao

    Published 2025-02-01
    “…Abstract This article presents the numerical analysis of architected metal/polymer-based interpenetrating phase composites (IPCs) to study their effective mechanical properties and dynamic behavior using finite element (FE) simulation. In this, we considered four types of Triply periodic minimal surfaces (TPMS) and lattice architectures, including gyroid, primitive, cubic, and octet, to form architected IPCs. …”
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