Showing 441 - 460 results of 1,810 for search '((( source OR sources) detection functions ) OR ( resource detection function ))', query time: 0.33s Refine Results
  1. 441
  2. 442

    Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

    Published 2025-01-01
    “…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
    Get full text
    Article
  3. 443

    DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

    Published 2025-06-01
    “…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
    Get full text
    Article
  4. 444
  5. 445

    TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

    Published 2025-05-01
    “…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
    Get full text
    Article
  6. 446

    YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

    Published 2025-04-01
    “…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
    Get full text
    Article
  7. 447
  8. 448
  9. 449
  10. 450

    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. …”
    Get full text
    Article
  11. 451

    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.…”
    Get full text
    Article
  12. 452
  13. 453
  14. 454
  15. 455

    A fuzzy track-to-track association algorithm with dynamic time warping for trajectory-level vehicle detection by Siqi Wan, Huaqiao Mu, Ke Han, Taesu Cheong, Chi Xie

    Published 2025-03-01
    “…Multi-source track-to-track association (TTTA), which identifies trajectories from multiple sensors or data sources of the same dynamic vehicle, is an important data fusion technique widely applied to vehicle detection in the fields of road, marine, and aviation transportation. …”
    Get full text
    Article
  16. 456

    Ibai mag blinds blindana tiuhan? (Luke 6,39). Pragmatic functions and syntactic strategies in the Gothic left sentence periphery by Marina Buzzoni

    Published 2025-01-01
    “…The interference role of the Greek and Latin source texts will also be taken into consideration, mainly in order to ascertain whether the grammaticalization processes which those elements underwent were either induced or implemented by the models. …”
    Get full text
    Article
  17. 457

    Ibai mag blinds blindana tiuhan? (Luke 6,39). Pragmatic functions and syntactic strategies in the Gothic left sentence periphery by Marina Buzzoni

    Published 2025-01-01
    “…The interference role of the Greek and Latin source texts will also be taken into consideration, mainly in order to ascertain whether the grammaticalization processes which those elements underwent were either induced or implemented by the models. …”
    Get full text
    Article
  18. 458

    Arlclustering: an R package for community detection in social networks based on user interaction and association rule learning by Mohamed El-Moussaoui, Mohamed Hanine, Ali Kartit, Tarik Agouti

    Published 2025-07-01
    “…Abstract ARLClustering is an open-source R package for community detection in social networks. …”
    Get full text
    Article
  19. 459

    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. …”
    Get full text
    Article
  20. 460