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

“…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.…”
Get full text

A guide to being the elephant in the room : a study on the residual behaviours stemming from bodyweight stigma by Jayakumar Sandhya Pillai

Get full text

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

“…Firstly, T5 is used to fine-tune on the paraphrase dataset for the task of paraphrase generation. …”
Get full text

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

Get full text

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. …”
Get full text

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

Get full text

Soulvurn by Tan, Sherneese

Get full text

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). …”
Get full text

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. …”
Get full text

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\%. …”
Get full text

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. …”
Get full text

Singapore premiere. by Ong, Shannon.

Get full text

Plateau by Png, Hui Min, Goh Timothy Wei Wen

Get full text

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

“…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. …”
Get full text

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. …”
Get full text
Get full text

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).…”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text

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. …”
Get full text