Showing 1,401 - 1,420 results of 2,212 for search '(((pinn OR (pinned OR finned)) OR (fine OR pinened)) OR (((pinna OR pingna) OR pin) OR min))', query time: 0.20s Refine Results
  1. 1401

    Suppressing condensation frosting using micropatterned ice walls by Zuo, Zichao, Zhao, Yugang, Li, Kang, Zhang, Hua, Yang, Chun

    Published 2024
    “…To ensure vapor preferentially depositing on upper sidewalls, a critical ice wall height exists, below which fine ice grains initiate in the adjacent of the substrate base and grow substantially faster, compromising the anti-frosting performance. …”
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    Journal Article
  2. 1402

    Complex coacervates loaded with nano enzymes as microreactor by Ng, Si Yi

    Published 2024
    “…Furthermore, the properties of nanozymes are controllable and can be fine-tuned for optimal efficiency alongside its versatility for specific applications. …”
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    Final Year Project (FYP)
  3. 1403

    Antielectric potential synthesis of plasmonic Au-Ag multidimensional dimers array for high-resolution encrypted information by Zeng, Pan, Yang, Fan, Chen, Zhiming, Wei, Ying, Cao, An, Wen, Lulu, Zhong, Shichuan, Wang, Yifan, Zhang, Tao, Li, Yue

    Published 2024
    “…Experiments and theoretical simulations reveal that patterned 3D Au-2D Ag and 3D Au-3D Ag dimer arrays with line widths of 400 nm exhibit cerulean and cyan colors, respectively, and achieve fine color modulation and ultrahigh information resolution. …”
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    Journal Article
  4. 1404

    ContrastSense: domain-invariant contrastive learning for in-the-wild wearable sensing by Dai, Gaole, Xu, Huatao, Yoon, Hyungjun, Li, Mo, Tan, Rui, Lee, Sung-Ju

    Published 2025
    “…In addition, ContrastSense designs a parameter-wise penalty to preserve domaininvariant knowledge during fine-tuning to further maintain model robustness. …”
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    Journal Article
  5. 1405

    Influence diffusion detection using the influence style (INFUSE) model by Tan, Luke Kien-Weng, Na, Jin-Cheon, Ding, Ying

    Published 2016
    “…While previous studies had focused on the existence of influence between linked bloggers in detecting influence diffusion, our INFUSE model is shown to provide a fine-grained description of the manner in which influence is diffused based on the bloggers’ influence styles.…”
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    Journal Article
  6. 1406

    Localization and velocity tracking of human via 3 IMU sensors by Yuan, Qilong, Chen, I-Ming

    Published 2016
    “…In the method, a reference root point on the pelvis is chosen to represent the velocity and location of the person. Through acceleration fine tuning algorithm, the acceleration data is refined and combined with the velocity calculated from body kinematics to get a drift-free and accurate 3D velocity result. …”
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    Journal Article
  7. 1407

    Statistical methods and analyses in autoimmune diseases by Inshaw, J

    Published 2020
    “…</p> <p>Finally, I performed an ImmunoChip-wide meta-analysis of 59, 974 individuals, approxi- mately twice the sample size of the previous largest T1D genetic analysis, and identified 74 chromosome regions associated with T1D, including 22 novel regions. I fine mapped each region and confirmed that prioritised variants were enriched in open chromatin re- gions in lymphoid cells. …”
    Thesis
  8. 1408

    Variational models in martensitic phase transformations with applications to steels by Muehlemann, A

    Published 2016
    “…</p> <p>In Chapter 4, we focus on highly compatible, so called self-accommodating, martensitic structures and present new results on their fine properties such as estimates on their minimum complexity and bounds on the relative proportion of each martensitic variant in them. …”
    Thesis
  9. 1409

    Optimization of surface roughness on duplex stainless steel in dry milling by Nurul Hidayah, Razak, Mohammad Rizal, Md Ali

    Published 2024
    “…An optimum machining parameters speed of cutting of 78.283 mm/min, rate of feed of 0.100 mm/tooth and axial depth of 0.834 mm is identified as the optimum values.…”
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    Conference or Workshop Item
  10. 1410

    Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

    Published 2024
    “…Before training, the dataset is normalized using the min-max normalization technique to reduce the influence of noise. …”
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    Article
  11. 1411

    Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation stud by Mones, Enys, Stopczynski, Arkadiusz, Pentland, Alex, Hupert, Nathaniel, Lehmann, Sune

    Published 2021
    “…Here, we study the digital communication activity of more than 500 individuals along with their person-to-person contacts at a 5-min temporal resolution. We then simulate different disease transmission scenarios on the person-to-person physical contact network to determine whether cyber communication networks can be harnessed to advance the goal of targeted vaccination for a disease spreading on the network of physical proximity. …”
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    Article
  12. 1412

    Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation study by Mones, Enys, Stopczynski, Arkadiusz, Pentland, Alex, Hupert, Nathaniel, Lehmann, Sune

    Published 2021
    “…Here, we study the digital communication activity of more than 500 individuals along with their person-to-person contacts at a 5-min temporal resolution. We then simulate different disease transmission scenarios on the person-to-person physical contact network to determine whether cyber communication networks can be harnessed to advance the goal of targeted vaccination for a disease spreading on the network of physical proximity. …”
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    Article
  13. 1413

    Query lower bounds for log-concave sampling by Chewi, Sinho, de Dios Pont, Jaume, Li, Jerry, Lu, Chen, Narayanan, Shyam

    Published 2024
    “…In this work, we establish the following query lower bounds: (1) sampling from strongly log-concave and log-smooth distributions in dimension ≥ 2 requires Ω(log) queries, which is sharp in any constant dimension, and (2) sampling from Gaussians in dimension (hence also from general log-concave and log-smooth distributions in dimension) requires Ωe(min( √ log,)) queries, which is nearly sharp for the class of Gaussians. …”
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    Article
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