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Showing 421 - 440 results of 2,295 for search '((\ source selection function\ ) OR (( resource OR resourcess) detection functions\ ))', query time: 0.31s Refine Results
  1. 421

    A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

    Published 2025-01-01
    “…Abstract Wireless sensor networks (WSNs) are imperative to a huge range of packages, along with environmental monitoring, healthcare structures, army surveillance, and smart infrastructure, however they’re faced with numerous demanding situations that impede their functionality, including confined strength sources, routing inefficiencies, security vulnerabilities, excessive latency, and the important requirement to keep Quality of Service (QoS). …”
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  2. 422

    Securing Wireless Communications with Energy Harvesting and Multi-antenna Diversity by Nguyen Quang Sang, tran Cong Hung, tran Trung Duy, minh Tran, byung Seo Kim

    Published 2025-04-01
    “…Analytical expressions for the Signal-to-Noise Ratios (SNRs) at both the destination D and the eavesdropper E are derived, along with the Probability Density Function (PDF) and Cumulative Distribution Function (CDF) of these SNRs under block Rayleigh fading conditions. …”
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  3. 423
  4. 424

    The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review by Khadiza Tun Suha, Hugh Lubenow, Stefania Soria-Zurita, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

    Published 2025-03-01
    “…We envision that, through the combination of tele-echocardiography and AI, low-resource medical facilities may gain access to the effective detection of CHD at the prenatal stage.…”
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    Article
  5. 425

    Detection of Greenhouse and Typical Rural Buildings with Efficient Weighted YOLOv8 in Hebei Province, China by Bingkun Wang, Zhiyuan Liu, Jiangbo Xi, Siyan Gao, Ming Cong, Haixing Shang

    Published 2025-05-01
    “…The large-scale detection of greenhouses and rural buildings is important for natural resource surveys and farmland protection. …”
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  6. 426

    A Heterogeneity-Aware Semi-Decentralized Model for a Lightweight Intrusion Detection System for IoT Networks Based on Federated Learning and BiLSTM by Shuroog Alsaleh, Mohamed El Bachir Menai, Saad Al-Ahmadi

    Published 2025-02-01
    “…Most IoT devices have limited resource capabilities (e.g., memory capacity, processing power, and energy consumption) to function as conventional intrusion detection systems (IDSs). …”
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  7. 427

    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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  8. 428
  9. 429

    Energy-Efficiency using Critical Nodes Detection Problem in Industrial Wireless Sensor Networks (IWSNs) by Karima MOULEY, Mohamed Amin TAHRAOUI, Abdelaziz KELLA

    Published 2025-03-01
    “…Experiments simulation validates our proposed approach, approving its efficiency in reducing significant energy consumption while preserving connectivity and functionality for industrial systems. Furthermore, the results highlight the potential of using critical node analysis to support sustainable and efficient operations in resource-constrained industrial environments. …”
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  10. 430

    Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

    Published 2025-07-01
    “…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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  11. 431

    YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping by Huijiao Yu, Xuehui Zhang, Jun Yan, Xianyong Meng

    Published 2025-07-01
    “…The Focaler-IoU loss function is employed to improve keypoint localization accuracy. …”
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  12. 432

    Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

    Published 2024-01-01
    “…Although various technologies with wearables and vision systems that utilize artificial intelligence (AI) have been developed to detect falls, many AI models are complex and resource-intensive. …”
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  13. 433

    AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

    Published 2025-01-01
    “…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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  14. 434

    Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture by Bekir Eray Katı, Ecir Uğur Küçüksille, Güncel Sarıman

    Published 2025-01-01
    “…The model’s performance was compared with other methods evaluated on the DFDC dataset, highlighting its efficiency in resource utilization and overall effectiveness. The findings reveal that the proposed QTL-CaiT-based system provides a strong foundation for deepfake detection and contributes significantly to the academic literature. …”
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  15. 435

    Automated Artery Detection and Stenosis Classification in CTA Using Deep Learning for Peripheral Arterial Disease by Ali M. O. A. Anwer, Hacer Karacan, Muhammed Rabee, Levent Enver, Gonca Cabuk

    Published 2025-01-01
    “…We use Faster R-CNN with a ResNet-101 backbone driven by a custom loss function to achieve good artery localization and reduce false positives. …”
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  16. 436

    Effect of Cs atoms adsorption on the work function of the LaB6 (100) surface by Huaqing Zheng, Xin Zhang, Jun Hu, Yuhong Xu, Guangjiu Lei, Sanqiu Liu, Heng Li, Zilin Cui, Yiqin Zhu, Xiaolong Li, Xiaoqiao Liu, Shaofei Geng, Xiaochang Chen, Haifeng Liu, Xianqu Wang, Hai Liu, Jun Cheng, Changjian Tang

    Published 2025-03-01
    “…These results provide some reference for the selection of fusion plasma gird materials and the production of hydrogen negative ion sources for neutral beam injection.…”
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  17. 437

    F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

    Published 2025-01-01
    “…The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. …”
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  18. 438
  19. 439

    GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

    Published 2025-06-01
    “…It provides an invaluable resource for developing machine learning models aimed at the automatic diagnosis, classification, and detection of GERD and polyps, potentially improving the speed and accuracy of clinical decision-making. …”
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  20. 440

    Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

    Published 2025-02-01
    “…Chlorophyll fluorescence (ChlF) parameters serve as non-destructive indicators of vegetation photosynthetic function and are widely used as key input parameters in photosynthesis–fluorescence models. …”
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