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  1. 2661

    探析中国打工妹之婚恋 = A study on love and marriage of Chinese female migrant workers by 朱嘉怡 Zhu, Jiayi

    Published 2017
    “…This paper, in a new perspective, aims to discuss the dual marginalized identity of migrant women who have experienced a unique marriage and love life. Some migrant workers choose to return to the rural villages, some willing to use their body in exchange with the benefits of goods from global capitalism and some inspired to create a marvellous life with their own hands. …”
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    Final Year Project (FYP)
  2. 2662

    论包公形象在不同文本中的呈现方式 :以陈州粜米故事为例 = An investigation on the representations of Magistrate Bao in different operatic texts on the story of “selling rice at Chen Zhou”... by 欧思敏 Au, Sze Mien

    Published 2010
    “…This paper investigates different representations of Magistrate Bao in different texts such as Yuan drama “Bao Dai Zhi Chen Zhou Tiao Mi”, Ming dynasty “Singing narrative on Bao Long Tu’s ‘Selling rice in Chen Zhou’” (Xin Kan Quan Xiang Shuo Chang Bao Long Tu Chen Zhou Tiao Mi Ji), Qing dynasty popular fiction “San Xia Wu Yi”, as well as folk operas “Chen Zhou Yuan” and “Bao Gong Gan Lu”.…”
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    Final Year Project (FYP)
  3. 2663
  4. 2664

    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
  5. 2665

    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
  6. 2666

    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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