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    Learning-Based Image Restorations of Sparse-View CT Data: Is It Reliable? by Philip Maurice Trapp, Elias Eulig, Joscha Maier, Frederic Ballach, Raoul Christoph, Ralf Christoph, Marc Kachelrieß

    Published 2025-02-01
    “…  Learning-based methods for the restoration of computed tomography (CT) images promise very good image quality even in areas with insufficient data sampling and thus suggest enormous savings in measurement time. …”
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    Article
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    The Impact of Internet on Teaching and Learning of Geography in Secondary Schools in Kabale Municipality. by Kato Brian

    Published 2023
    “…This research intended to examine the contribution of internet in teaching and learning of geography in Kabale Municipality. It was guided by objectives which were to which were to examine the impact of internet use on teaching and learning in secondary schools in Kabale Municipality, to examine teachers’ and students’ perception on the use of internet in teaching and learning in secondary schools in Kabale Municipality and to identify the challenges associated with the use of internet in in secondary schools in Kabale Municipality. …”
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    University e-learning methodologies and their financial implications: evidence from Uganda by Eton, Marus, Rest, Chance

    Published 2022
    Subjects: “…University education, Digitalization in universities, E-learning, Financial implications, Information and communications technology…”
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    Article
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    Virtual game-based learning environments to promote self-regulated learning skills in foreign language learners [version 1; peer review: 1 approved, 2 approved with reservations] by Maira Alejandra Noriega Cortes, Laura Carreño-Bolivar

    Published 2024-12-01
    Subjects: “…Gamification; self-regulated learning- self regulation; Language Learning; virtual learning environment- virtual learning- blended learning environment.…”
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    Analysis Of Backscatter To Extraction Of Shoreline Using Machine Learning Methods In The Bangkalan Regency by Arifin Fahmi, Wicaksono Ashari

    Published 2025-01-01
    “…The purpose of this research is to extract the coastline by segmenting the machine learning method and find out how far the machine learning model works to distinguish the water class and the land class. …”
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    Machine learning algorithms can predict emotional valence across ungulate vocalizations by Romain A. Lefèvre, Ciara C.R. Sypherd, Élodie F. Briefer

    Published 2025-02-01
    “…The present study used a machine learning algorithm (eXtreme Gradient Boosting [XGBoost]) to distinguish between contact calls indicating positive (pleasant) and negative (unpleasant) emotional valence, produced in various contexts by seven species of ungulates. …”
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