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  1. 1

    Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling by Guth, Stephen, Katsidoniotaki, Eirini, Sapsis, Themistoklis P.

    Published 2024
    “…Accurately determining hydrodynamic force statistics is crucial for designing offshore engineering structures, including offshore wind turbine foundations, due to the significant impact of nonlinear wave–structure interactions. …”
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    Article
  2. 2

    Towards haptic intelligence in robots by learning from demonstration by Turlapati Sri Harsha

    Published 2022
    “…This is motivated by the observation that classical kinaesthetic teaching by physically guiding the robot through a particular task is not sufficient for learning the haptics of the task. This is because the forces the human applies on the robot are also recorded along with the task forces, thus "corrupting" any useful strategy. …”
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    Thesis-Doctor of Philosophy
  3. 3

    Theoretical study of spermatozoa sorting by dielectrophoresis or magnetophoresis with supervised learning by Koh, James Boon Yong

    Published 2019
    “…The flagellum waveform is prescribed analytically, and subsequently solved from force and moment balance. The hydrodynamic force acting on the sperm is computed using Resistive Force Theory as well as Slender Body Theory, and the resulting velocity is compared qualitatively and quantitatively. …”
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    Thesis
  4. 4

    Challenges and Solution of Online Learning and Assessment Amidst the COVID-19 Pandemic: A Case Study in Universiti Utara Malaysia (S/O 14793) by Mohd Nordin, Nur Rasyidah, Omar, Wafa, Mohd Ridzuan, Iliya Nurul Iman

    Published 2021
    “…However, with the pandemic, language instructors are forced to utilize online platforms to teach and assess the students. …”
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    Monograph
  5. 5

    A study on open set recognition methods by Sun, Xin

    Published 2021
    “…We combine the proposed loss function with the Softmax loss function, which is used in most Convolutional Neural Networks (CNNs), to force learned features in different classes to be close to different centroids for Gaussian modeling. …”
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    Thesis-Doctor of Philosophy