Showing 801 - 820 results of 1,810 for search '((\ (source OR sources) detection functions\ ) OR (( resources OR resources) detection function\ ))', query time: 0.29s Refine Results
  1. 801

    Accelerating two-dimensional electronic spectroscopy simulations with a probe qubit protocol by José D. Guimarães, James Lim, Mikhail I. Vasilevskiy, Susana F. Huelga, Martin B. Plenio

    Published 2025-05-01
    “…We evaluate the computational resources necessary for this protocol in detail, demonstrating its function as a dynamic frequency-filtering method through numerical simulations. …”
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    A survey on the applications of transfer learning to enhance the performance of large language models in healthcare systems by Anmol Rahujo, Daniya Atif, Syed Azeem Inam, Abdullah Ayub Khan, Sajid Ullah

    Published 2025-06-01
    “…This research analyzes different transfer learning methods, including inductive, transductive, and unsupervised techniques, while demonstrating their effectiveness in detecting COVID-19 from chest X-rays and multi-source disease evaluation. …”
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  5. 805

    Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

    Published 2025-04-01
    “…Software defect detection is a critical research topic in the field of software engineering, aiming to identify potential defects during the development process to improve software quality and reduce maintenance costs. …”
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    Restoration of Turbid Underwater Images of Cobalt Crusts Using Combined Homomorphic Filtering and a Polarization Imaging System by Enzu Peng, Chengyi Liu, Haiming Zhao

    Published 2025-02-01
    “…Marine cobalt-rich crusts, extensively used in industries such as aerospace, automotive, and electronics, are crucial mineral resources located on the ocean floor. To effectively exploit these valuable resources, underwater imaging is essential for real-time detection and distribution mapping in mining areas. …”
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    Responsive cellulose nanocrystal‐based liquid crystals: From structural color manipulation to applications by Jiao Liu, Ye‐Ming Qing, Jun‐Jie Wu, Jing‐Qi Tian, Chi‐Bo Feng, Xin‐Yu Zhou, Yun Ma, Bing‐Xiang Li, Yan‐Qing Lu, Quan Li

    Published 2025-08-01
    “…Cellulose nanocrystals (CNCs), obtained through the acidic hydrolysis of cellulose‐based materials including wood, cotton, and additional sources, have attracted significant attention in areas, for example, energy storage, cosmetics, and medical devices. …”
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  12. 812

    Generation of Cas9 Knock-In <i>Culex quinquefasciatus</i> Mosquito Cells by Elizabeth Walsh, Tran Zen B. Torres, Brian C. Prince, Claudia Rückert

    Published 2025-01-01
    “…In comparison to the RNAi-mediated gene silencing of <i>dicer-2</i>, <i>argonaute-2b</i>, and <i>piwi5</i>, our Cas9/sgRNA approach showed an enhanced ability to detect antiviral effects. <b>Conclusions</b>: We propose that this cell line offers a new tool for studying gene function in <i>Cx. quinquefasciatus</i> mosquitoes that avoids the use of RNAi. …”
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    A novel deep learning technique for multi classify Alzheimer disease: hyperparameter optimization technique by A. S. Elmotelb, Fayroz F. Sherif, A. S. Abohamama, A. S. Abohamama, Mahmoud Fakhr, Amr M. Abdelatif

    Published 2025-04-01
    “…A progressive brain disease that affects memory and cognitive function is Alzheimer’s disease (AD). To put therapies in place that potentially slow the progression of AD, early diagnosis and detection are essential. …”
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    CLASSIFYING LIVER DISEASE WITH BOOSTING MACHINE LEARNING APPROACHES by Erol Özçekiç, Ümit Yılmaz

    Published 2025-08-01
    “…Liver diseases pose a significant global health challenge due to their impact on metabolic function and the difficulty of early detection. Traditional diagnostic methods such as liver biopsy have limitations due to their invasive nature and high costs. …”
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  20. 820

    Evaluating LiDAR‐Derived Structural Metrics for Predicting Bee Assemblages in Managed Forests by Marissa H. Chase, Alexandra Harmon‐Threatt, Samuel F. Stickley, Brian Charles, Jennifer M. Fraterrigo

    Published 2025-04-01
    “…We investigated whether structural metrics derived from light detection and ranging (LiDAR) data could predict bee diversity and abundance, as well as bee functional trait composition within managed and unmanaged forests in the central hardwood region in southern Illinois, United States of America. …”
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