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    Applications of the Mittag-Leffler law to linear kinetic models & diffusion equations by Victor Tebogo Monyayi, Emile Franc Doungmo Goufo, Ignace Tchangou Toudjeu

    Published 2025-05-01
    “…We observe that when we increase the number of computing terms, the series becomes closer to the exact solution so that the absolute error between the exact solution and the approximate solution becomes very small. …”
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  3. 803

    Energy efficient design and implementation of approximate adder for image processing applications by Naik Jatothu Brahmaiah, Kumar Kanagala Sateesh, Krishnaiah Kondragunta Rama, Koteswararao Seelam

    Published 2025-01-01
    “…Approximate computing is a new technique that promises to speed up computations while preserving a level of precision suitable for error-tolerant systems such as neural networks and graphics. …”
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    Application of Machine Learning for Estimating the Physical Parameters of Three-Dimensional Fractures by Fadhillah Akmal, Ardian Nurcahya, Aldenia Alexandra, Intan Nurma Yulita, Dedy Kristanto, Irwan Ary Dharmawan

    Published 2024-12-01
    “…However, these methods are time-consuming and resource-intensive; therefore, this research explores the application of machine learning as an alternative method to predict the physical parameters of fractures such as permeability, surface roughness, and mean aperture. …”
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  6. 806

    Research progress on the application of digital technology in the diagnosis and treatment of tooth wear by HE Yi, WANG Dingjie, XIAO Yuhong

    Published 2024-12-01
    “…In recent years, researchers have extensively studied the application of digital technology in tooth wear research from the perspectives of digital support devices, cutting-edge deep learning applications, technology diagnosis, design and prediction, and current limitations. …”
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  7. 807

    Multi-Mode Coupling Enabled Broadband Coverage for Terahertz Biosensing Applications by Dongyu Hu, Mengya Pan, Yanpeng Shi, Yifei Zhang

    Published 2025-06-01
    “…This work establishes a paradigm for miniaturized THz biosensors, advancing applications in practical molecular diagnostics and multi-analyte screening.…”
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  8. 808

    Artificial intelligence in personalized rehabilitation: current applications and a SWOT analysis by Elpidio Attoh-Mensah, Arnaud Boujut, Arnaud Boujut, Mikaël Desmons, Anaick Perrochon

    Published 2025-07-01
    “…Automation of certain tasks can reduce human error and alleviate clinician workload, allowing more time for direct patient care. …”
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    The Representative Points of Generalized Alpha Skew-<i>t</i> Distribution and Applications by Yong-Feng Zhou, Yu-Xuan Lin, Kai-Tai Fang, Hong Yin

    Published 2024-10-01
    “…This paper includes two real-data applications in which the GAST model appears adaptable to various types of data.…”
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  13. 813

    A systematic review of neural network applications for groundwater level prediction by Samuel K. Afful, Cyril D. Boateng, Emmanuel Ahene, Jeffrey N. A. Aryee, David D. Wemegah, Solomon S. R. Gidigasu, Akyana Britwum, Marian A. Osei, Jesse Gilbert, Haoulata Touré, Vera Mensah

    Published 2025-08-01
    “…This systematic review investigates the application of NNs for GWL prediction, focusing on the architectures of the various NN models employed. …”
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  14. 814

    Image Similarity Quantum Algorithm and Its Application in Image Retrieval Systems by Qingchuan Yang, Xianing Feng, Lianfu Wei

    Published 2025-01-01
    “…The measurement of image similarity represents a fundamental task within the domain of image processing, enabling the application of sophisticated computational techniques to ascertain the degree of similarity between two images. …”
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    Application of Observation Perturbation-based EDA Method to CMA Ensemble Forecasting by Zhang Hanbin, Xia Yu, Cao Yajie

    Published 2025-03-01
    “…It can be concluded that the observation perturbation scheme developed for CMA-MESO aligns with actual observation error characteristics, it can address uncertainties in the model initial analysis field stemming from observations, and multiple sets of observations generated can effectively represent uncertainties in observations. …”
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