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  1. 2021

    Value investment with machine learning by Wang, Jiwei

    Published 2024
    “…Further optimization led to the creation of the Improved Fundamental and Technical Factors Model, which achieved an impressive annualized return of 50\% and a Sharpe ratio of 1.85. After fine-tuning key parameters, the final optimized model demonstrated exceptional performance, with an annualized return of 59.82\%, a Sharpe ratio of 2.13, and a win rate of 75\%. …”
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    Final Year Project (FYP)
  2. 2022

    Ig.n.is. by Ong, Jian'an.

    Published 2011
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    Final Year Project (FYP)
  3. 2023

    Microstructural evolution during mechanical milling of Nd-Fe-B nanocomposites by Toh, Hon Kun.

    Published 2011
    “…The rate of chemical disorder as a function of milling intensity was studied by Extended X-ray Absorption Fine Structure (EXAFS) technique. XRD results revealed that higher milling intensity increased the rate of phase transformation and the rate of change in crystal sizes and strain but did not affect the steady state phase composition. …”
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    Final Year Project (FYP)
  4. 2024

    Singapore premiere. by Ong, Shannon.

    Published 2013
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    Final Year Project (FYP)
  5. 2025

    Plateau by Png, Hui Min, Goh Timothy Wei Wen

    Published 2016
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    Final Year Project (FYP)
  6. 2026

    Parametric study of gravure printing process for R2R printed electronics by Pua, Suan Tai

    Published 2017
    “…In this study, however, various printing parameters were investigated to establish their effects on printed line width and film thickness, in an attempt to achieve fine line printing resolution over a large printing area. …”
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    Final Year Project (FYP)
  7. 2027

    A supervised two-channel learning method for hidden Markov model and application on lip reading by Foo, Say Wei, Dong, Liang

    Published 2009
    “…This method is specially designed to train HMMs for fine recognition from similar observations. The prominent features of this method are 1.) the criterion function is based on the difference between training sequences, and 2.) a twochannel structure is adopted to maintain the validity of the HMM. …”
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    Conference Paper
  8. 2028

    Elastic modulus, hardness and creep performance of SnBi alloys using nanoindentation by Shen, Lu, Septiwerdani, Pradita, Chen, Zhong

    Published 2013
    “…At the intermediate stress region (200–370 MPa), dislocation climb is the dominant creep mechanism with stress exponents around 5–8. When fine lamellar structure is the dominant constituent of the microstructure, phase boundary sliding is identified as the rate-controlling mechanism in the low stress region (<200 MPa).…”
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    Journal Article
  9. 2029

    DECA : recovering fields of physical quantities from incomplete sensory data by Vasilakos, Athanasios V., Xiang, Liu, Luo, Jun, Deng, Chenwei, Lin, Weisi

    Published 2013
    “…Exploiting both the low-rank nature of real-world events and the redundancy in sensory data, DECA combines matrix completion with a fine-tuned compressed sensing technique to conduct a dual-level reconstruction process. …”
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    Conference Paper
  10. 2030

    Knowledge-based reactive planning and re-planning – a case-study approach by Djemai, Ramzi, Vassilev, Vassil, Ouazzane, Karim, Dey, Maitreyee

    Published 2024
    “…Planning for uncertainties arising from indoor evacuations can be complex as there’s a fine balance to strike between a too-detailed plan and one that’s too vague. …”
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    Conference or Workshop Item
  11. 2031

    Vision-language modelling for radiological imaging and reports in the low data regime by Windsor, R, Jamaludin, A, Kadir, T, Zisserman, A

    Published 2024
    “…Combined, they significantly improve retrieval compared to fine-tuning CLIP, roughly equivalent to training with 10x the data. …”
    Conference item
  12. 2032
  13. 2033
  14. 2034
  15. 2035
  16. 2036
  17. 2037
  18. 2038
  19. 2039
  20. 2040