Standards Research Data

Compared with traditional finance, digital finance introduces digital technology for financial innovation, which largely reduces financial exclusion and discrimination, but improved financial services, such as mobile payment, online lending, virtual currency, and investment and wealth management, also involve potential risks. Hence, we propose a sentiment analysis model, GABP-News, to study the predictive ability of the information contained in news texts on digital financial development in China.

This DATASET includes the raw data set and the statistical analysis of a family of experiment to empirically study the factors that affect the effectiveness of MDD based on the measurement of accuracy.

The Numerical Latin Letters (DNLL) dataset consists of Latin numeric letters organized into 26 distinct letter classes, corresponding to the Latin alphabet. Each class within this dataset encompasses multiple letter forms, resulting in a diverse and extensive collection. These letters vary in color, size, writing style, thickness, background, orientation, luminosity, and other attributes, making the dataset highly comprehensive and rich.

Driving excitement may lead to speeding and serious traffic accidents. Although olfactory stimulation has been proven to be effective in regulating human emotions, the mechanism driving excitement is still unclear. This study aims to explore the regulatory effects of different arousal and valence levels of odors (mint, rose, banana, and musk) on driving excitement, deepening our understanding of the relationship between drivers emotions and driving experience.