Because academic entrepreneurship is an innovation driving force in China’s economy, teachers are key knowledge creators in the process of entrepreneurship. Therefore, it is particularly important to give attention to the individual psychological mechanism factors at play in the process of teachers in higher education academic entrepreneurship. The purpose of this study is to identify individual psychological capital and role conflict issues among university teachers in China. To accomplish this aim, we investigated the emergence of positive academic entrepreneurial intents, continued (...) through the process of academic entrepreneurship, and clarified the impact of psychological capital and role conflict on entrepreneurial intent. Based on the theory of planned behavior, we constructed a research model from the perspective of entrepreneurial intent prior to entrepreneurial action. We established a cohort of teachers in 17 higher education institutions in southern China, with psychological capital and role conflict as the prior independent variables and the teachers’ academic entrepreneurial intent as the dependent variable. Using quantitative analysis, SPSS 22.0, and AMOS 23.0, we conducted reliability and validity tests, correlation analysis, and structural equation models on the collected data. We reached the following conclusions: psychological capital has a positive effect on attitudes toward academic entrepreneurship; psychological capital has a positive effect on perceived behavioral control; role conflict has a negative effect on perceived behavioral control; academic entrepreneurial attitudes have a positive effect on academic entrepreneurial intent; perceived behavioral control has a positive effect on academic entrepreneurial intent; subjective norms have a positive effect on academic entrepreneurial intent. We also provide some suggestions about academic entrepreneurship for university administrators. (shrink)

Social networking applications have been designed as innovative technologies used by the higher education section to enhance the acquisition of literacy skills, driving learners to engage in online learning platforms. Such tools such as social networking have also been proven to facilitate teaching and learning; therefore, educational programs and universities are increasingly making use of networking sites to form connections with students and to offer online instructional content. This trend has placed questions, regarding the effect of social media on language (...) learning and its potential use as an effective instructional tool. The constructive role of enjoyment did not obtain equal academic consideration in the EFL learning milieu until Positive Psychology was presented to L2 education. Using social networking, users find online tasks appealing and experience the enjoyment that, in turn, impacts their behavioral intention to use them positively. Commitment is another factor that refers to the degree to which students are involved in learning enthusiastically. This construct concerns the extent to which students are loyal to learning, textbooks, and class etiquette. As it contributes to the quality of learning, it is considered a prerequisite for students’ academic success and educational attainment. Based on the role of the above-mentioned constructs in language learning, the present review tries to consider the role of social networking in boosting EFL students’ commitment and enjoyment. Consequently, some implications are presented for academic stakeholders in the quest of considering the role of social networking in language education. (shrink)

The making of infrared templates is of great significance for improving the accuracy and precision of infrared imaging guidance. However, collecting infrared images from fields is difficult, of high cost, and time-consuming. In order to address this problem, an infrared image generation method, infrared generative adversarial networks, based on conditional generative adversarial networks architecture is proposed. In I-GANs, visible images instead of random noise are used as the inputs, and the D-LinkNet network is also utilized to build the generative model, (...) enabling improved learning of rich image textures and identification of dependencies between images. Moreover, the PatchGAN architecture is employed to build a discriminant model to process the high-frequency components of the images effectively and reduce the amount of calculation required. In addition, batch normalization is used to optimize the training process, and thereby, the instability and mode collapse of the generated adversarial network training can be alleviated. Finally, experimental verification is conducted on the produced infrared/visible light dataset. The experimental results reveal that high-quality and reliable infrared data are generated by the proposed I-GANs. (shrink)

Financial market and economic growth and development trends can be regarded as an extremely complex system, and the in-depth study and prediction of this complex system has always been the focus of attention of economists and other scholars. Emotion recognition algorithm is a pattern recognition technology that integrates a number of emerging science and technology, and has good non-linear system fitting capabilities. However, using emotion recognition algorithm models to analyze and predict financial market and economic growth and development trends can (...) yield more accurate prediction results. This article first gives a detailed introduction to the existing financial development and economic growth status and development trend forecasting problems, and then gives a brief overview of the concept of emotion recognition algorithms. Then, it describes the emotion recognition methods, including statistical emotion recognition methods, mixed emotion recognition methods, and emotion recognition methods based on knowledge technology, and conducts in-depth research on the three algorithm models of statistical emotion recognition methods, they are the support vector machine algorithm model, the artificial neural network algorithm model, and the long and short-term memory network algorithm model. Finally, these three algorithm models are applied to the financial market and economic growth and development trend prediction experiments. Experimental results show that the average absolute error of the three algorithms is below 25, which verifies that the emotion recognition algorithm has good operability and feasibility for the prediction of financial market and economic growth and development trends. (shrink)

Previous neurological studies of shyness have focused on the hemispheric asymmetry of alpha spectral power. To the best of our knowledge, few studies have focused on the interaction between different frequencies bands in the brain of shyness. Additionally, shy individuals are even shyer when confronted with a group of people they consider superior to them. This study aimed to reveal the neural basis of shy individuals using the delta-beta correlation. Further, it aimed to investigate the effect of evaluators’ facial attractiveness (...) on the delta-beta correlation of shyness during the speech anticipation phase. We recorded electroencephalogram activity of 94 participants during rest and anticipation of the public speaking phase. Moreover, during the speech anticipation phase, participants were presented with high or low facial attractiveness. The results showed that, as predicted, the delta-beta correlation in the frontal region was more robust for high shyness than for low shyness during the speech anticipation phase. However, no significant differences were observed in the delta-beta correlation during the baseline phase. Further exploration found that the delta-beta correlation was more robust for high facial attractiveness than low facial attractiveness in the high shyness group. However, no significant difference was found in the low-shyness group. This study suggests that a stronger delta-beta correlation might be the neural basis for shy individuals. Moreover, high facial attractiveness might enhance the delta-beta correlation of high shyness in anticipation of public speaking. (shrink)

Entrepreneurship plays a significant role in promoting the social and economic development of a country. At present, entrepreneurship education is widely carried out in universities and colleges in order to improve students’ entrepreneurial ability, and then to provide support for the formation of a comprehensive entrepreneurial situation. As entrepreneurship education has gradually become a hot topic of teaching for innovation and entrepreneurship education of international students, studies on the influencing mechanism of entrepreneurship education of international students in relation to their (...) entrepreneurial behavior are conducive to providing theoretical basis and empirical evidence for international students’ entrepreneurship education, so as to pertinently guide international students’ innovation and entrepreneurship practice. This study aims to explore the influence of entrepreneurship education, government support for entrepreneurship, global competence, entrepreneurial self-efficacy, and entrepreneurial intention on the entrepreneurial behavior of international students in the Republic of Korea. It summarized and drew on the results of the existing literature research. According to the contents and points of research, this study takes the international students studying in Korea as the sample and uses statistical analysis software, SPSS 22.0 and AMOS 24.0, to establish a structural equation model to conduct empirical study on the influencing mechanism of entrepreneurial behavior of international students in Korea, so as to better understand the influence of entrepreneurship education in Korean universities and colleges on entrepreneurial behavior of international students in Korea. Based on the analysis results, this study puts forward the theoretical basis for the policies related to effective management of entrepreneurship, which will help alleviate the unemployment of young people studying in Korea and the tight labor market supply and demand. (shrink)

Purpose of the article Knowledge has been considered as the strategic assets and become the source of competitive advantage in organizations. Knowledge management thus receives the extraordinary attention from the top management. Many organizational factors have influences on knowledge management practices. This paper attempts to explore the empirical relationship between knowledge management and organizational culture in the specific situation of China’s commercial banking industry. Methodology/methods The relationship between knowledge management and organizational culture is quantitatively investigated by surveying bank managers. The (...) scale of SECI modes is used to measure knowledge management process and the scale of Denison Organizational Culture Survey is used to measure organizational culture. We explore the underlying relationship by employing the statistical analyses such as correlation, regression and structural equation modeling. Scientific aim The research aims at testing the relationship between knowledge management and organizational culture, and furthermore if there exist linkages between cultural traits and SECI modes. Findings The results of the empirical study confirm the great and positive effect that organizational culture has on knowledge management. Different cultural traits contribute to different SECI modes. Conclusions For obtaining successful knowledge management practices in organizations, it is better to concern about the relationship between knowledge management and organizational culture. The limitation in the paper is the sampling size, which will be solved by an industry-wide survey in our future research. (shrink)