Showing 641 - 660 results of 2,992 for search '((\ sources selection functions\ ) OR (( (resource OR source) OR resources) detection function\ ))', query time: 0.40s Refine Results
  1. 641
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    Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium by Sandra Hoyek, Eleni Konstantinou, Francesco Romano, Darren Chen, Celine Chaaya, Magdalena G. Krzystolik, Daniel Hu, Rachel Huckfeldt, Demetrios G. Vavvas, Leo A. Kim, Jason Lee, Elise De, John B. Miller, Nimesh A. Patel

    Published 2025-07-01
    “…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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  3. 643

    Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction by P. Kumudha, R. Venkatesan

    Published 2016-01-01
    “…Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. …”
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  4. 644

    Uncovering functional deterioration in the rhizosphere microbiome associated with post-green revolution wheat cultivars by Monique E. Smith, Vanessa N. Kavamura, David Hughes, Rodrigo Mendes, George Lund, Ian Clark, Tim H. Mauchline

    Published 2025-06-01
    “…Of the 113 functional genes that were differentially abundant between heritage and modern cultivars, 95% were depleted in modern cultivars and 65% of differentially abundant reads best mapped to genes involved in staurosporine biosynthesis (antibiotic product), plant cell wall degradation (microbial mediation of plant root architecture, overwintering energy source for microbes) and sphingolipid metabolism (signal bioactive molecules). …”
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  5. 645

    FCMI-YOLO: An efficient deep learning-based algorithm for real-time fire detection on edge devices. by Junjie Lu, Yuchen Zheng, Liwei Guan, Bing Lin, Wenzao Shi, Junyan Zhang, Yunping Wu

    Published 2025-01-01
    “…The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …”
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  6. 646

    Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations. by Chisom Soremekun, Tafadzwa Machipisa, Opeyemi Soremekun, Fraser Pirie, Nashiru Oyekanmi, Ayesha A Motala, Tinashe Chikowore, Segun Fatumo

    Published 2023-01-01
    “…<h4>Conclusions</h4>Using multivariate GWAS method improves the power to detect novel genotype-phenotype associations for liver functions not found with the standard univariate GWAS in the same dataset.…”
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  7. 647
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    A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism by Bixiong Luo, Peng Zuo, Lijun Zhu, Wei Hua

    Published 2025-02-01
    “…Wind power, as a pivotal renewable energy source, is anticipated to play a critical role in ensuring the reliability, security, and stability of the global energy supply system. …”
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  9. 649

    Spatio-temporal dynamics of ecosystem service value functions in response to landscape fragmentation in Boma-Gambella trans-boundary landscape, Southwest Ethiopia and East South Su... by Azemir Berhanu Getahun, Amare Bantider Dagnew, Desalegn Yayeh Ayal

    Published 2025-07-01
    “…Google Earth Explorer was utilized to randomly select 200 sample training points to assess the accuracy of the Land Use Land Cover classification for both 2009 and 2020. …”
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    Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

    Published 2025-01-01
    “…The Industrial Internet of Things (IIoT) faces significant cybersecurity threats due to its ever-changing network structures, diverse data sources, and inherent uncertainties, making robust intrusion detection crucial. …”
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    Computational Temporal Ghost Imaging Using Intensity-Only Detection Over a Single Optical Fiber by Jiang Tang, Yongwen Tang, Kun He, Luluzi Lu, Di Zhang, Mengfan Cheng, Lei Deng, Deming Liu, Minming Zhang

    Published 2018-01-01
    “…We propose a method of computational temporal ghost imaging over a single optical fiber using simple optical intensity detection instead of coherent detection. The transfer function of a temporal ghost imaging system over a single optical fiber is derived, which is a function of the total fiber dispersion and the power density spectrum of the light source. …”
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  15. 655

    Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach by Wenxuan Yao, Hui Li, Yanlin Li

    Published 2024-10-01
    “…Firstly, the regression method learns the image features of the dataset and the specific region growth threshold, and the regression function is trained by using the open-source dataset to determine the region growth threshold using the characteristics of the images included in the tests. …”
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    Intelligent Firefighting Technology for Drone Swarms with Multi-Sensor Integrated Path Planning: YOLOv8 Algorithm-Driven Fire Source Identification and Precision Deployment Strateg... by Bingxin Yu, Shengze Yu, Yuandi Zhao, Jin Wang, Ran Lai, Jisong Lv, Botao Zhou

    Published 2025-05-01
    “…This study aims to improve the accuracy of fire source detection, the efficiency of path planning, and the precision of firefighting operations in drone swarms during fire emergencies. …”
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    Antimicrobial Activity of Chitosan from Different Sources Against Non-<i>Saccharomyces</i> Wine Yeasts as a Tool for Producing Low-Sulphite Wine by Francesco Tedesco, Rocchina Pietrafesa, Gabriella Siesto, Carmen Scieuzo, Rosanna Salvia, Patrizia Falabella, Angela Capece

    Published 2024-10-01
    “…Finally, the efficiency of different antimicrobial treatments was evaluated during laboratory-scale fermentations inoculated with a selected <i>S. cerevisiae</i> strain. The tested strains exhibited medium/high resistance to the chitosan; in some cases, the behaviour varied in the function of species/strain, and only four strains exhibited different resistance levels, depending on the chitosan source. …”
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