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  1. 15361

    Exploring Protein Conformational Changes Using a Large‐Scale Biophysical Sampling Augmented Deep Learning Strategy by Yao Hu, Hao Yang, Mingwei Li, Zhicheng Zhong, Yongqi Zhou, Fang Bai, Qian Wang

    Published 2024-11-01
    “…Abstract Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. …”
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    Article
  2. 15362

    Structural Damage Identification Based on Rough Sets and Artificial Neural Network by Chengyin Liu, Xiang Wu, Ning Wu, Chunyu Liu

    Published 2014-01-01
    “…An information entropy based discretization algorithm in RS is applied for dimension reduction of the original damage database obtained from finite element analysis (FEA). …”
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    Article
  3. 15363

    On the Potential of Bayesian Neural Networks for Estimating Chlorophyll-a Concentration from Satellite Data by Mohamad Abed El Rahman Hammoud, Nikolaos Papagiannopoulos, George Krokos, Robert J. W. Brewin, Dionysios E. Raitsos, Omar Knio, Ibrahim Hoteit

    Published 2025-05-01
    “…The performance of the proposed probabilistic model is compared to that of standard ocean color algorithms, namely ocean color 4 (OC4) and ocean color index (OCI). …”
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    Article
  4. 15364

    Federated Learning-Based State of Charge Estimation in Electric Vehicles Using Federated Adaptive Client Momentum by Metin Yilmaz, Eyup Cinar, Ahmet Yazici

    Published 2025-01-01
    “…Traditional Battery Management System (BMS) algorithms can be inadequate for State of Charge (SoC) estimation due to incorrect measurements and unobservable battery characteristics. …”
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    Article
  5. 15365

    State-of-the-Art on IoV-Based Deep Learning Framework for Enhanced Driving Behavior Recognition: Recent Progress, Technology Updates, Challenges, and Future Direction by Hongguang Li, Shafrida Sahrani, Mahidur R. Sarker, Yinglin Xiao

    Published 2025-01-01
    “…However, these advanced algorithms still face several challenges. We analyze relevant literature from 2015 to 2024, to uncover key trends and gaps in the development of applications for identifying dangerous driving behaviors, with a primary focus on optimizing integration to improve the accuracy and real-time capability of driving behavior prediction. …”
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    Article
  6. 15366

    A Survey on the Deep Learning-Based Mismatch Removal: Principles and Methods by Shiyu Chen, Cailong Deng, Yong Zhang, Yong Wang, Qixin Zhang, Zhimin Zhou

    Published 2023-01-01
    “…Due to the inherent limitations of matching algorithms and the complexities associated with image contents, mismatches are inevitable and can have detrimental effects on downstream tasks in computer vision and remote sensing. …”
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    Article
  7. 15367
  8. 15368

    Deep Learning Based Early Intrusion Detection in IIoT using Honeypot by Abbasgholi Pashaei, Mohammad Esmaeil Akbari, Mina Zolfy Lighvan, Asghar Charmin

    Published 2023-06-01
    “…The accuracy of DL algorithms has been shown across a range of scientific fields. …”
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    Article
  9. 15369

    Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

    Published 2024-12-01
    “…The system is able to function independently thanks to the use of machine learning algorithms, including LSTM for prediction, Kalman filter for data cleaning, Isolation Forest for anomaly detection, and K-means for clustering sleep patterns.…”
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    Article
  10. 15370

    Integrative multi-omics and machine learning reveal critical functions of proliferating cells in prognosis and personalized treatment of lung adenocarcinoma by Shun Wang, Dingtao Hu, Ruohuang Wang, Jie Huang, Baoqing Wang

    Published 2025-07-01
    “…An integrative machine learning program, comprising 111 algorithms, was developed to construct a Scissor+ proliferating cell risk score (SPRS). …”
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    Article
  11. 15371

    Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

    Published 2025-02-01
    “…The present research utilized the Isolation Forest algorithm to detect outliers in high-dimensional data sets. …”
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    Article
  12. 15372

    Two‐stage video anomaly detection based on dual‐stream networks and multi‐instance learning by Dejun Zhang, Wenbo Fang, Yuhang Liu, Zirong Lyu, Chen Xiong, Zhan Wang

    Published 2024-12-01
    “…Therefore, it is crucial to develop intelligent algorithms for video anomaly detection. The method can detect whether segments of a video contain abnormal events. …”
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    Article
  13. 15373

    Gradient-based optimization for parameter identification of lithium-ion battery model for electric vehicles by Motab Turki Almousa, Mohamed R. Gomaa, Mostafa Ghasemi, Mohamed Louzazni

    Published 2024-12-01
    “…The findings were contrasted to those from various algorithms, such as whale optimization algorithm, multi-verse optimizer, sine cosine algorithm, arithmetic optimization algorithm, particle swarm optimization, red kite optimization algorithm, tree-seed algorithm, and white shark optimizer. …”
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    Article
  14. 15374

    Link and Loss Aware GW-COOP Routing Protocol for FANETs by Shahzad Hameed, Saleh Alyahya, Qurratul-Ain Minhas, Shabana Habib, Asif Nawaz, Sheeraz Ahmed, Atif Ishtiaq, Muhammad Islam, Sheroz Khan

    Published 2021-01-01
    “…This paper proposes GW-COOP (Gray Wolf Algorithm using Cooperative Diversity Technique) routing protocol for FANETs. …”
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    Article
  15. 15375

    A Novel Toolbox for Generating Realistic Biological Cell Geometries for Electromagnetic Microdosimetry by Mehrdad Saviz, A.H. Buchali Safiee, Elham Sharifi

    Published 2020-06-01
    “…We have designed a free, user-friendly tool in MATLAB that combines several known or new algorithms for easy production of three-dimensional complex cell shapes based on minimum data. …”
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    Article
  16. 15376

    Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks by Ankur Bhatt, Ko Watanabe, Jayasankar Santhosh, Andreas Dengel, Shoya Ishimaru

    Published 2024-01-01
    “…The outcomes of this research pave the way for more personalized and effective educational interventions, ultimately contributing to improved learning experiences and outcomes.…”
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    Article
  17. 15377

    Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

    Published 2025-03-01
    “…This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. …”
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    Article
  18. 15378

    A vehicular network–based intelligent transport system for smart cities by Tayyaba Zaheer, Asad Waqar Malik, Anis Ur Rahman, Ayesha Zahir, Muhammad Moazam Fraz

    Published 2019-11-01
    “…Our results show reduced travel times of up to 33.3% when compared to a traditional fixed route-selection algorithm.…”
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  19. 15379

    AI-Driven Advances in Parkinson’s Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes by José E. Valerio, Guillermo de Jesús Aguirre Vera, Maria P. Fernandez Gomez, Jorge Zumaeta, Andrés M. Alvarez-Pinzon

    Published 2025-05-01
    “…Machine learning (ML) algorithms and big data analytics enable precise patient stratification, risk assessment, and outcome prediction, accelerating the development of novel therapeutic approaches. …”
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    Article
  20. 15380

    A Review of Abnormal Crowd Behavior Recognition Technology Based on Computer Vision by Rongyong Zhao, Feng Hua, Bingyu Wei, Cuiling Li, Yulong Ma, Eric S. W. Wong, Fengnian Liu

    Published 2024-10-01
    “…Its goal is to use computer vision technology and abnormal behavior detection models to accurately perceive, predict, and intervene in potential abnormal behaviors of the crowd and monitor the status of the crowd system in public places in real time, to effectively prevent and deal with public security risks and ensure public life safety and social order. …”
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    Article