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  1. 941
  2. 942

    Identification of Ship Maneuvering Behavior Using Singular Value Decomposition-Based Hydrodynamic Variations by Cem Guzelbulut

    Published 2025-03-01
    “…However, it is necessary to conduct dozens of experiments or computational fluid dynamics simulations to characterize the hydrodynamic behavior of the vessels, which require significant amounts of cost and time. …”
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  3. 943
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    Event-related potentials reveal incongruent behavior of autonomous vehicles in the moral machine dilemma by Maren A. K. Bertheau, Cindy Boetzel, Christoph S. Herrmann

    Published 2025-05-01
    “…This might be useful in brain computer interfaces research when, classifying single-trial ERP components, to dynamically adopt an AV’s behavior.…”
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  5. 945
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    Neuronal heterogeneity in the ventral tegmental area: Distinct contributions to reward circuitry and motivated behavior by N. Dalton Fitzgerald, Jeremy J. Day

    Published 2025-03-01
    “…Furthermore, this review highlights known projection targets and the role of diverse VTA cell types in motivated behavior. Finally, we highlight emerging intersectional techniques that enable targeted studies of the vast array of cell types and discuss areas of research important for the future direction of the field. …”
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  7. 947

    Object-gaze distance: Quantifying near-peripheral gaze behavior in real-world applications by Felix Wang, Julian Wolf, Mazda Farshad, Mirko Meboldt, Quentin Lohmeyer

    Published 2021-05-01
    “…We propose an algorithmic enhancement to a state-of-the-art ET analysis method, the Object-Gaze Distance (OGD), which additionally allows the quantification of near-peripheral gaze behavior in complex real-world environments. The algorithm uses machine learning for area of interest (AOI) detection and computes the minimal 2D Euclidean pixel distance to the gaze point, creating a continuous gaze-based time-series. …”
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  8. 948

    Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

    Published 2025-07-01
    “…This review synthesizes the current research on AI-powered behavioral monitoring tools and proposes a conceptual model, ReproBehaviorNet, that maps age- and sex-specific behaviors to biological processes and AI applications, supporting real-time decision-making in both intensive and semi-intensive systems. …”
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  9. 949

    The Influence of an Electromagnetic Field at a Radiofrequency of 900 MHz on the Behavior of a Honey Bee by Paweł Migdał, Mateusz Plotnik, Paweł Bieńkowski, Ewelina Berbeć, Krzysztof Latarowski, Natalia Białecka, Agnieszka Murawska

    Published 2025-06-01
    “…Bees in the control group were not exposed to RF fields, while the experimental groups were exposed to 900 MHz electromagnetic fields of different intensities and durations of exposure. Bees’ behavior was analyzed with an appropriate computer program. …”
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  10. 950

    Finite Element Modeling of the Behavior of a Hollow Cylinder in a Hydrogen-Containing Environment by Assia Amina Lakhdari, Serguey A. Bubnov, Aissa Seddak, Ilya I. Ovchinnikov, Igor G. Ovchinnikov

    Published 2020-01-01
    “…More attention is paid to the importance of predicting the behavior of charged metal structures under the influence of hydrogen embrittlement. …”
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  11. 951

    Wearable Sensors-Based Intelligent Sensing and Application of Animal Behaviors: A Comprehensive Review by Luyu Ding, Chongxian Zhang, Yuxiao Yue, Chunxia Yao, Zhuo Li, Yating Hu, Baozhu Yang, Weihong Ma, Ligen Yu, Ronghua Gao, Qifeng Li

    Published 2025-07-01
    “…The fundamental limitation restricting advancement in this field is the difficulty in maintaining high-fidelity recognition performance at reduced acquisition rates, particularly for integrated multi-behavior identification. Considering that the computational demands and limited adaptability to complex field environments remain significant constraints, Tiny Machine Learning (Tiny ML) could present opportunities to guide future research toward practical, scalable behavioral monitoring solutions. …”
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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

    Published 2024-12-01
    “…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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  15. 955

    Cost-efficient behavioral modeling of antennas by means of global sensitivity analysis and dimensionality reduction by Slawomir Koziel, Anna Pietrenko-Dabrowska

    Published 2025-01-01
    “…Abstract Computational tools, particularly electromagnetic (EM) solvers, are now commonplace in antenna design. …”
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    Creep behavior of clayey soil and its model prediction in the Cangzhou land subsidence area by Jianfeng Qi, Yongjie Xie, Chen Li, Haipeng Guo, Yunlong Wang

    Published 2025-03-01
    “…The objective of this paper is to develop a computational model to reflect the creep deformation of aquitards in this area. …”
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