Jiangxi University of Finance and Economics

About: Jiangxi University of Finance and Economics is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Fuzzy logic & China. The organization has 2865 authors who have published 3556 publications receiving 41567 citations.

The Influencing Factors of Enterprise Sustainable Innovation: An Empirical Study

Abstract: Sustainable innovation is the inexhaustible source of development of enterprises. Within fierce market competition, only by depending on continuous innovation can an enterprise exist and develop. By conducting an exploratory factor analysis and a confirmatory factor analysis, this paper proposes a theoretical model, dividing enterprise sustainable innovation ability into three aspects: knowledge innovation capability, production innovation capability, and market innovation capability, and analyzes the influencing factors respectively. Finally, applying this theoretical model to a practical case, with system dynamics method, the simulation results show that they are consistent with real enterprise facts. Therefore, the framework of determinants of sustainable innovation built in this paper has already been verified theoretically and practically. It not only lays a theoretical foundation for further research, but also provides a clear ground for firms to improve their sustainable innovation.

Just Noticeable Difference Estimation for Screen Content Images

Abstract: We propose a novel just noticeable difference (JND) model for a screen content image (SCI). The distinct properties of the SCI result in different behaviors of the human visual system when viewing the textual content, which motivate us to employ a local parametric edge model with an adaptive representation of the edge profile in JND modeling. In particular, we decompose each edge profile into its luminance, contrast, and structure, and then evaluate the visibility threshold in different ways. The edge luminance adaptation, contrast masking, and structural distortion sensitivity are studied in subjective experiments, and the final JND model is established based on the edge profile reconstruction with tolerable variations. Extensive experiments are conducted to verify the proposed JND model, which confirm that it is accurate in predicting the JND profile, and outperforms the state-of-the-art schemes in terms of the distortion masking ability. Furthermore, we explore the applicability of the proposed JND model in the scenario of perceptually lossless SCI compression, and experimental results show that the proposed scheme can outperform the conventional JND guided compression schemes by providing better visual quality at the same coding bits.