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    Distributed H∞ Consensus Filtering for Parabolic Distributed Parameter Systems with Multiple Missing Measurements: A Mobile Sensing Approach by Xueming Qian, Baotong Cui

    Published 2023-01-01
    “…In a framework of optimizing performance, a new approach to improving filter performance is proposed by employing mobile sensor networks. Moreover, the information missing in mobile sensor networks is modeled as a conditional probability distribution. …”
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    Visual detection of screen defects in occlusion and missing scenes by YIN Dongfu, DU Mingchen, HU Tianhao, LI Youming, ZHANG Xiaohong, YU Fei Richard

    Published 2023-11-01
    “…The modules for mobile phone screen detection, occlusion detection, missing detection, and screen content change detection are established in this system. …”
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    A Miss Kayapó: ritual, espetáculo e beleza by André Demarchi

    Published 2017-06-01
    “…The present article proposes an ethnographic interpretation of the event called « Miss Kayapó », a Beauty Contest, whose participants are indigenous women from the Mebêngôkre (Kayapó) people, located in the Amazon forest, who speak a Jê language. …”
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    Learning the Hit-or-Miss Transform-Based Morphological Neural Networks by Muhammad Aminul Islam, Sireesha Chimbili

    Published 2025-01-01
    “…In particular, the piecewise linear hit-or-miss transform improved the baseline accuracy for Cifar-10 by 10.7%.…”
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    SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks by Yao Wang, Zhongzhao Zhang, Lin Ma, Jiamei Chen

    Published 2014-01-01
    “…Spectrum mobility as an essential issue has not been fully investigated in mobile cognitive radio networks (CRNs). …”
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    Estimation of Missing DICOM Windowing Parameters in High-Dynamic-Range Radiographs Using Deep Learning by Mateja Napravnik, Natali Bakotić, Franko Hržić, Damir Miletić, Ivan Štajduhar

    Published 2025-05-01
    “…This study evaluates traditional histogram-based methods and explores the potential of deep learning for predicting window parameters in radiographs where such information is missing. A range of architectures, including MobileNetV3Small, VGG16, ResNet50, and ViT-B/16, were trained on high-bit-depth computed radiography images using various combinations of loss functions, including structural similarity (SSIM), perceptual loss (LPIPS), and an edge preservation loss. …”
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    Mapping and quantifying near-miss events involving vehicles and vulnerable road users in Reno and Sparks, Nevada by Scott Kelley, Cole Peiffer, Fei Guan, Hao Xu, James Okorocha, Kelly Dunn, Carlos Cardillo

    Published 2025-07-01
    “…Using an interactive map, 175 respondents identified 277 locations where they either previously experienced a near-miss or felt unsafe with traveling as a VRU. We deployed mobile roadside LiDAR sensors to continuously collect data over two 72-hour periods in October 2023 at the 10 most frequently identified intersections in the survey responses. …”
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    Multi-model based behaviour analysis for inclusive mobility by Vanderhaegen Frédéric, Richard Philippe

    Published 2024-01-01
    “…The analysis of combinations between these models generates scenarios that can affect inclusive mobility in terms of human health, system safety or fluidity of mobility. …”
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    Time based incremental backup scheme for mobile cloud computing by Yun-fei CI, Guo-zhen SHI, Rong-na XIE, Yao-ming PAN, Feng YANG, Si-shui YE

    Published 2016-08-01
    “…A time-based data secure backup mechanism for moving the cloud was presented.Time was considered as a parameter into the data encryption for the important information in mobile device and backups the users' data ac-cording to the time period.It had not only solved the issue of the latest timely backup sensitive data,but also solved the entire ciphertext leak caused by missing the backup key.…”
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    Usage of Mobile X-Rays in Active Case-Finding for Tuberculosis by Cindra Paskaria, Elizabeth Wianto, Hapnes Toba

    Published 2024-08-01
    “…More than 300,000 cases of tuberculosis in Indonesia have not been diagnosed or recorded, which are known as the missing cases. Undiagnosed tuberculosis patients will cause the spread of tuberculosis bacteria to other people. …”
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