Showing 3,361 - 3,380 results of 5,810 for search '((ping OR ((fine OR line) OR ((amin OR amalin) OR min))) OR ((pinn OR lin) OR link))', query time: 0.23s Refine Results
  1. 3361

    Fungal colonization of rice straw and palm press fibre in the rumen of cattle and buffalo by Ho, Y.W., Abdullah, N., Jalaludin, S.

    Published 1991
    “…In both animal species, attachment to rice straw by rumen fungal zoospores was rapid, within 15 min of rumen incubation. At 6 h of rumen incubation, thin- and thick-walled tissues were colonized by fungal hyphae and by 24 h fungal colonization was extensive. …”
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    Article
  2. 3362

    Mobility patterns are associated with experienced income segregation in large US cities by Moro, Esteban, Calacci, Dan, Dong, Xiaowen, Pentland, Alex

    Published 2021
    “…To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). …”
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    Article
  3. 3363

    Exploiting irregular parallelism to accelerate FPGA routing by Zhu, Alan Y.

    Published 2024
    “…This parallelism can be exploited on parallel architectures that provide hardware support for ordered tasks and fine-grained speculation, such as the Swarm architecture. …”
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    Thesis
  4. 3364

    Temporal perturbation of ERK dynamics reveals network architecture of FGF2/MAPK signaling by Blum, Yannick, Mikelson, Jan, Dobrzyński, Maciej, Ryu, Hyunryul, Jacques, Marc‐Antoine, Jeon, Noo L., Khammash, Mustafa, Pertz, Olivier

    Published 2024
    “…Our results provide novel insights into how different receptor tyrosine kinase (RTK) systems differentially wire the MAPK network to fine‐tune fate decisions at the cell population level.…”
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    Article
  5. 3365
  6. 3366

    Generating domain-specific paraphrases of questions from FAQ by Ng, Jing Rui

    Published 2021
    “…Firstly, T5 is used to fine-tune on the paraphrase dataset for the task of paraphrase generation. …”
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    Final Year Project (FYP)
  7. 3367
  8. 3368

    Aspect-based sentiment analysis using BERT by Kheriwala, Hussain Khozema

    Published 2022
    “…Aspect-based sentiment analysis extracts and identifies fine-grained sentiment polarities for a specific aspect. …”
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    Final Year Project (FYP)
  9. 3369

    The city you'll never meet by Lim, Ying Quan

    Published 2022
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    Final Year Project (FYP)
  10. 3370

    Soulvurn by Tan, Sherneese

    Published 2022
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    Final Year Project (FYP)
  11. 3371

    Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art by Ong, Zi Feng

    Published 2023
    “…The core data will be gathered from existing art databases, such as the Library of Congress (LCC) (Class-N - Fine Arts) and the Universal Decimal Classification (UDC) (73/76 Various arts & crafts); and controlled vocabulary systems such as Art & Architecture Thesaurus (AAT). …”
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    Thesis-Master by Research
  12. 3372

    Deep learning for fabric defect detection by Nangia, Saniya

    Published 2024
    “…The base models, YOLOv8 and RT-DETR, are fine-tuned on a dataset of patterned fabric defects to find the optimal model configurations. …”
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    Final Year Project (FYP)
  13. 3373

    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)
  14. 3374

    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)
  15. 3375

    Singapore premiere. by Ong, Shannon.

    Published 2013
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    Final Year Project (FYP)
  16. 3376

    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
  17. 3377

    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
  18. 3378

    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
  19. 3379

    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
  20. 3380

    A comparative analysis of missing data imputation techniques on sedimentation data by Loh, Wing Son, Ling, Lloyd, Chin, Ren Jie, Lai, Sai Hin, Loo, Kar Kuan, Seah, Choon Sen

    Published 2024
    “…A comparative analysis on the missing fine sediment data imputation performance was made based on four different techniques, namely the k-Nearest Neighbourhood (k-NN), Support Vector Regression (SVR), Multiple Regression (MR), and Artificial Neural Network (ANN), under the single imputation (SI) and multiple imputation (MI) regimes. …”
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    Article