Driver fatigue is a major cause of traffic accidents. Automatic vision-based driver fatigue recognition is one of the most prospective commercial applications based on facial expression analysis technology. Generally, factors such as noise, illumination effects, image scaling, and redundant data affect the performance of facial expression recognition systems. In this paper, we have proposed an efficient algorithm, which is not only capable of working with multi-scale images but also able to overcome the mentioned obstacles. The proposed framework can be divided into three main phases. In the first step, the input image is converted into four sub-band images by applying a discrete wavelet transform, which preserves the important information of face image. Also, the original image is down-sampled to obtain the image of different sizes. Based on entropy analysis, each image is then further divided into a number of blocks classified as either informative or non-informative blocks. In the second step, the high variance features are selected in a zigzag manner using discrete cosine transform. In the final step, classifiers are trained and tested to accurately classify the expressions into seven generic expression classes. The empirical results suggest that the proposed framework not only effectively utilizes the multi-scale images but also outperforms other similar techniques in terms of classification accuracy rate.

Purpose: The purpose of this paper is to study the influence mechanism of different levels of social capital (Structure holes–local network attributes and indirect ties–global network attributes) and organizational culture on the creativity of key inventors, and the role of organizational culture between social capital and creativity.Design/methodology/approach: The paper tested the hypotheses with a sample of patent data accumulated from 46 firms in Chinese electronic information and automobile sectors. Negative binomial regression was used to explore the factors influencing the creativity of key inventors.Findings: The paper discovers that structural holes are valuable social capital for the creativity of key inventors and very important in firms with a collective and conservative culture. Moreover, it also locates that key inventor are more creative in firms with an individualistic and competitive culture than those in firms with a collective and conservative culture.Originality/value: This study emphasizes the influence of social capital on creativity and contributes to R&D management. It highlights structural holes are certainly important to key inventors in a collective and conservative culture, thus contradicting preceding studies that locate structural holes useful solely in an individualistic culture. This finding broadens our knowledge of the benefits of this network structure. Also, this debate challenges several basic views on structural holes currently.

The preferential attachment mechanism that forms scale-free network cannot display assortativity, i.e., the degree of one node is positively correlated with that of their neighbors in the network. Given the attributes of network nodes, a cultural trait-matching mechanism is further introduced in this paper. Both theoretical analysis and simulation results indicate that the higher selection probability of such mechanism, the more obvious the assortativity is shown in networks. Further, the degree of nodes presents a positive logarithm correlation with that of adjacent ones. Finally, this study discusses the theoretical and practical significances of the introduction of such a cultural trait-matching mechanism.

In this study, researchers looked at how management working capital affected the profitability of manufacturing companies producing cement in Khyber Pakhtunkhwa, Pakistan. Our sample consisted of three manufacturing company’s registered on the Karachi Stock Exchange, and we examined their performance over a 12-year period from 2008 to 2020. Our primary independent variables were inventory turnover in days (ITID) and average collection period (ACP), while the dependent variables included return on equity (ROE) and net profit margin (NPM). To examine how management working capital and business performance are related, Studies employed panel data analysis techniques. Our findings suggest a positive influence of management working capital on firm profitability. Importantly, this association was found to be statistically importance at the 5 percent level, indicating that effective management of working capital contributes positively to shareholder value. Our study highlights the significant of sound management working capital practices in enhancing the performance of cement manufacturing companies in Khyber Pakhtunkhwa, Pakistan, ultimately benefiting their shareholders.