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  1. 121

    Representation theoretic interpretation and interpolation properties of inhomogeneous spin q-Whittaker polynomials by Korotkikh, Sergei

    Published 2024
    “…Using this construction, we are able to prove a Cauchy-type identity for inhomogeneous spin q-Whittaker polynomials in full generality. …”
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    Article
  2. 122

    Modelling of spintronic terahertz emitters as a function of spin generation and diffusion geometry by Yang, Yingshu, Dal Forno, Stefano, Battiato, Marco

    Published 2023
    “…In particular, geometry, composition, pump laser frequency, and spin diffusion will be significant in understanding the pathways for further research developments. …”
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    Journal Article
  3. 123

    Synthesis and electrochemical performance of aluminum antimonide alloy anode prepared by melt spinning by Kharistal, Daniel Julian

    Published 2014
    “…Another advantage in using melt spinning process is that it can produce materials with high throughput and high purity metal alloy products with little to no impurities, which is beneficial to the battery performance. …”
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    Thesis
  4. 124

    Minimal projective reconstruction for combinations of points and lines in three views by Oskarsson, M, Zisserman, A, Åström, K

    Published 2004
    “…We also give tentative results for the case of nine lines in correspondence over three views, where experiments indicate that there may be up to 36 complex solutions.…”
    Journal article
  5. 125
  6. 126

    An Effective Med-VQA Method Using a Transformer with Weights Fusion of Multiple Fine-Tuned Models by Al-Hadhrami, Suheer, Menai, Mohamed El Bachir, Al-Ahmadi, Saad, Alnafessah, Ahmad

    Published 2024
    “…The second model, the greedy-soup-based model, uses a greedy soup technique based on the fusion of multiple fine-tuned models to set the model parameters. The greedy soup selects the model parameters by fusing the model parameters that have significant performance on the validation accuracy in training. …”
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    Article
  7. 127

    Evaluating Adaptive Layer Freezing through Hyperparameter Optimization for Enhanced Fine-Tuning Performance of Language Models by Figueroa, Reinaldo

    Published 2024
    “…When dealing with data scarcity, transfer learning has become the go-to method to use these models in specialized downstream tasks via fine-tuning. However, fine-tuning on small datasets can lead to overfitting and a lack of generalization. …”
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    Thesis
  8. 128
  9. 129

    Fine-tuning selective layer architecture of hydrogel membrane towards high separation performances for engineered osmosis by Qin, Detao, Liu, Zhaoyang, Bai, Hongwei, Song, Xiaoxiao, Li, Zhengtao, Sun, Darren Delai

    Published 2020
    “…Towards this goal, the architecture of hydrogel selective layer is finely tuned for the first time for improving engineered osmosis (EO) membrane performance. …”
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    Journal Article
  10. 130
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  13. 133

    On-line optimization of biomimetic undulatory swimming by an experiment-based approach by Zhou, Chunlin, Low, Kin Huat

    Published 2014
    “…An experiment-based approach is proposed to improve the performance of biomimetic undulatory locomotion through on-line optimization. The approach is implemented through two steps: (1) the generation of coordinated swimming gaits by artificial Central Pattern Generators (CPGs); (2) an on-line searching of optimal parameter sets for the CPG model using Genetic Algorithm (GA). …”
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    Journal Article
  14. 134
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  17. 137

    Conversion of 2D line drawings to 3D models by Tay, Wei Xian.

    Published 2012
    “…Both accurate and inaccurate 2D input line drawings of a range of objects were tested and discussed. …”
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    Final Year Project (FYP)
  18. 138
  19. 139

    Queue time approximation for a production line with large variability by Chua, Kurtz Yuan Feng

    Published 2017
    “…This paper will present ndings based on the simulation of a high variability production line. The almost linear properties of the intrinsic ratio provided in this paper, will provide insights to the approximation of queue times that will be applicable to real-life manufacturing processes.…”
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    Final Year Project (FYP)
  20. 140