Mu (em-power-you) : a jewelry brand inspired by the stories of different communities by Cho, Cecilia Hyunjae

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

“…Aspect-based sentiment analysis extracts and identifies fine-grained sentiment polarities for a specific aspect. …”
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The city you'll never meet by Lim, Ying Quan

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Soulvurn by Tan, Sherneese

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

“…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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Deep learning for fabric defect detection by Nangia, Saniya

“…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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Value investment with machine learning by Wang, Jiwei

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

“…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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Singapore premiere. by Ong, Shannon.

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Plateau by Png, Hui Min, Goh Timothy Wei Wen

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

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

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

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

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

“…Combined, they significantly improve retrieval compared to fine-tuning CLIP, roughly equivalent to training with 10x the data. …”

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

“…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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Relationship between synoptic scale meteorology, aircraft parameters, and observable contrails by Barbosa, Maria Paula

“…Long-lasting or "persistent" contrails are line-shaped clouds that form when airplanes fly through cold and humid parts of the atmosphere that are ice-supersaturated. …”
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Public bus transit service modeling and optimization: from conventional to autonomous vehicles by Tian, Qingyun

“…In the first part, this thesis proposes a novel tri-level model for a transit service operation design problem that primarily determines the optimal bus line frequency setting. Unlike the existing studies, the strategy choices of passengers in presence of congested common lines are explicitly considered. …”
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Anti-leukaemic and chemotherapy supportive effects of berberis vulgaris l. Fruit crude extract on in vitro and in vivo models by Saedi, Tayebeh Azam

“…For the in vitro method, cytotoxic effects of BVFCE were evaluated using MTT assay to determine the IC50 values and compare with non-leukaemic cell line (The 3T3 cell). Observation of the morphological changes in the treated leukaemic cell lines with BVFCE and Doxorubicin (Doxo) was examined using inverted microscope. …”
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Disrupted working memory event-related network dynamics in multiple sclerosis by Rossi, C, Vidaurre, D, Costers, L, D’hooghe, MB, Akbarian, F, D’haeseleer, M, Woolrich, M, Nagels, G, Van Schependom, J

“…First, the activation of an early theta prefrontal network linked to stimulus encoding and attentional control significantly decreases in MS compared to HC. …”