Nam, D.T. (2026) Research on the Selection of Master’s Thesis Topics for Vietnamese Chinese Language Majors—A Case Study of Vietnam National University, Hanoi . Open Access Library Journal, 13, 1-9.

Tessellations aren’t just eye-catching patterns—they can be used to crack complex mathematical problems. By repeatedly ...

Discover how Fourier Analysis breaks down complex time series data into simpler components to identify trends and patterns, despite its limitations in stock forecasting.

The Voynich manuscript has long been shorthand for the unsolved and the unknowable, a late medieval codex filled with looping ...

The purpose of this research is to define the conditions under which developing countries find themselves implementing Artificial Intelligence in their governance systems. This scientific contribution ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

On November 8, 2025, the Faculty of Education at East China Normal University hosted a grand ceremony to present the second ...

Learn how the Least Squares Criterion determines the line of best fit for data analysis, enhancing predictive accuracy in finance, economics, and investing.

After exploring this problem, the researchers determined that the assumptions these confidence interval methods rely on don't hold up when data vary spatially. Assumptions are like rules that must be ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

The research fills a gap in standardized guidance for lipidomics/metabolomics data analysis, focusing on transparency and reproducibility using R and Python. The approach offers modular, interoperable ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.