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  1. 4701

    Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline by HongYi Li, Jun-Fen Fu, Andre Python

    Published 2025-07-01
    “…General-purpose LLMs may not perform well in specialized areas as they often require lightweight prompt engineering methods or fine-tuning techniques based on specific datasets to improve model performance. Most LLMs with multimodal abilities are closed-source models and, therefore, lack of transparency, model customization, and fine-tuning for specific clinical tasks and may also pose challenges regarding data protection and privacy, which are common requirements in clinical settings. …”
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  2. 4702

    Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction by Jose Daniel Cuellar Lobo, Zhen Lei, Hexu Liu, Hong Xian Li, SangHyeok Han

    Published 2021-01-01
    “…The integration of BIM with other analytical algorithms also allows optimization of designs, such as the generative design that can parametrize the design. …”
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  3. 4703
  4. 4704

    Inversion Study of Hydrogeological Parameters for Metro Foundation Pit Confined Aquifiers Based on Surrogate Modeling by YE Ru, DI Honggui, ZHU Zhitai, ZHU Yilong, JIANG Bin, XIANG Longsheng, CHAI Dongsheng, YAO Qiyu

    Published 2025-07-01
    “…The use of deep learning-based surrogate modeling combined with optimization algorithms enables efficient and accurate inversion analysis of groundwater parameters.…”
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  5. 4705

    A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

    Published 2025-03-01
    “…For linear models, it is well known that there exists a regularization path connecting the sparsest solution in terms of the ℓ1 norm, i.e., zero weights and the non-regularized solution. …”
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  6. 4706

    Comparison of Kolmogorov–Arnold Networks and Multi-Layer Perceptron for modelling and optimisation analysis of energy systems by Talha Ansar, Waqar Muhammad Ashraf

    Published 2025-05-01
    “…Considering the improved interpretable performance of Kolmogorov–Arnold Networks (KAN) algorithm compared to multi-layer perceptron (MLP) algorithm, a fundamental research question arises on how modifying the loss function of KAN affects its modelling performance for energy systems, particularly industrial-scale thermal power plants. …”
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  7. 4707

    Power supply vehicle routing problem: formulation and solution by Lizhe You, Shengjun Huang, Haowei Zhang, Rui Wang, Tao Zhang

    Published 2025-07-01
    “…Building on this definition, this problem is formulated as a two-stage mixed-integer nonlinear programming model. To solve this model, we adopted a genetic algorithm as the main algorithm framework. …”
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  8. 4708
  9. 4709

    Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

    Published 2025-01-01
    “…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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    Article
  10. 4710

    Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

    Published 2025-01-01
    “…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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    Article
  11. 4711

    Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

    Published 2025-06-01
    “…Specifically, the particle swarm optimization (PSO) algorithm was employed to optimize the hyperparameters of a long short-term memory (LSTM) neural network, leading to the development of a PSO-LSTM fault detection model. …”
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  12. 4712

    Exponential Squared Loss-Based Robust Variable Selection with Prior Information in Linear Regression Models by Hejun Wei, Tian Jin, Yunquan Song

    Published 2025-07-01
    “…Experimental results demonstrate that our model significantly improves estimation robustness compared to existing methods, even in outlier-contaminated scenarios.…”
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  13. 4713

    Numerical model of surface morphology and solid-liquid contact angle in wire electrical discharge machining by Zhi Chen, Yifei Zhou, Zefeng Yang, Zhizhong Zhang, Jian Li, Guojun Zhang, Fenglin Han

    Published 2025-03-01
    “…Combining the established numerical model and multi-objective optimization algorithm, the contact angle of the surface machined by WEDM is greater than 125°, and the stability and controllability of hydrophobic surface preparation are greatly improved. …”
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  14. 4714

    Apple Rootstock Cutting Drought-Stress-Monitoring Model Based on IMYOLOv11n-Seg by Xu Wang, Hongjie Liu, Pengfei Wang, Long Gao, Xin Yang

    Published 2025-07-01
    “…The neck part is optimized by the KFHA module (Kalman filter and Hungarian algorithm model), and the head part enhances post-processing effects through HIoU-SD (hierarchical IoU–spatial distance filtering algorithm). …”
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  15. 4715

    High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

    Published 2025-07-01
    “…The priors are constructed using cosine similarity, mean, and intensity, where intensity is computed using the improved Papoulis–Gerchberg algorithm. The image is reconstructed using the probabilistic maximum a posteriori estimate. …”
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  16. 4716

    Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

    Published 2025-07-01
    “…In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency improvements, and resource allocation. This paper examines the application of artificial intelligence and supervised machine learning techniques to modeling and predicting the energy consumption patterns in the smart grid sector of a commercial building located in Singapore. …”
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  17. 4717

    Threat analysis model to control IoT network routing attacks through deep learning approach by K. Janani, S. Ramamoorthy

    Published 2022-12-01
    “…A deep learning hybrid model based on a Long-Short-Term Memory (LSTM) network and adaptive Mayfly Optimization Algorithm (LAMOA) was presented for the classification of IoT attacks. …”
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  18. 4718

    Storage life evaluation of photodetector based on multi-parameter performance degradation and competitive failure by ZHANG Yeping, YANG Tongbo, LI Ziwei

    Published 2025-04-01
    “…This method comprehensively considered whether the key performance parameters of the sample have deteriorated or improved trend. Firstly, the optimal degradation model with a single parameter was selected by performance degradation modeling, so that the pseudo-life of the sample with increasing degradation trend was calculated according to the failure threshold, and the pseudo-life was regarded as the right-censored data for the sample with decreasing degradation trend. …”
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  19. 4719

    Dimensionless analysis and novel configuration for enhanced natural convection cooling in lithium-ion batteries by Congyu Mao, Min Liang Wang, Kewei Gao, Hongdi Jin, Woo Young Cho, Hernando Leon-Rodriguez, Kootaek Hong, Seunghwoi Han, Jihoon Jeong, Hyun Wook Kang

    Published 2025-10-01
    “…A dimensionless analysis framework was developed and coupled with response surface models and a multi-objective genetic algorithm to optimize battery layouts for heat dissipation and temperature uniformity. …”
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  20. 4720

    Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

    Published 2024-12-01
    “…This study aims to develop an intelligent solution for predicting student performance using supervised machine learning algorithms. This proposed focus on addressing the limitations of existing prediction models and enhancing prediction accuracy. …”
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