In the great practice of long-term revolution, construction and reform, the red gene created and developed by the CPC is a noble belief and noble emotion that has been continuously precipitated and inherited in the blood and struggle of countless people throughout the country, and has been deeply rooted in the blood and soul of the people of the CPC. Against the backdrop of the continuous development of modern education, integrating the red gene into the daily ideological and political education work of college students requires a clear understanding of its practical significance, and establishing the basic principle of integration based on the red gene, further promoting reform and innovation in inheriting and promoting the red gene in universities, and comprehensively enhancing the ideological and political awareness of college students, Provide a strong talent force for China's socialist construction.
Nowadays, the scale of graduate education in our country has been growing, but the quality of graduate education has not been improved. Therefore, how to effectively improve the quality of postgraduate education has become the most concerned issue in the academic circle and universities, which directly highlights that the internal guarantee mechanism of postgraduate students to improve the quality of postgraduate education has become the focus of academic research, in which tutors are the main influencing factors of postgraduate education quality. The tutor plays a positive and dominant role in stimulating, demonstrating, modeling, guiding and infecting the postgraduate's behavior. This paper analyzes the existing problems in exerting the role of postgraduate tutors, and from the problems, puts forward the countermeasures and suggestions to exert and mobilize the initiative of tutors.
In this study, the authors propose a method that combines CNN and LSTM networks to recognize facial expressions. To handle illumination changes and preserve edge information in the image, the method uses two different preprocessing techniques. The preprocessed image is then fed into two independent CNN layers for feature extraction. The extracted features are then fused with an LSTM layer to capture the temporal dynamics of facial expressions. To evaluate the method's performance, the authors use the FER2013 dataset, which contains over 35,000 facial images with seven different expressions. To ensure a balanced distribution of the expressions in the training and testing sets, a mixing matrix is generated. The models in FER on the FER2013 dataset with an accuracy of 73.72%. The use of Focal loss, a variant of cross-entropy loss, improves the model's performance, especially in handling class imbalance. Overall, the proposed method demonstrates strong generalization ability and robustness to variations in illumination and facial expressions. It has the potential to be applied in various real-world applications such as emotion recognition in virtual assistants, driver monitoring systems, and mental health diagnosis.
Tennis, as an important project of sports, has an obvious role in cultivating students' physical quality, observation ability and reaction speed. Under the background that the country attaches great importance to students' physical literacy, the traditional single and passive teaching has been unable to meet the practical needs, so it is necessary to strengthen the innovation of teaching methods. With the recognition of many teachers, the teaching method of "combining competition and practice" has been continuously promoted. The paper takes the combination of competition and practice as the teaching mode, and studies the teaching of college tennis sports.
As a result of China's evolving higher education landscape, private universities have emerged as significant players, fostering democratization and fulfilling key roles. However, these institutions face distinct challenges shaped by legal, societal, and internal factors. In the knowledge-driven economy, employee satisfaction is crucial for success. Understanding pivotal factors and conducting satisfaction surveys are essential for effective management and talent retention. This study focuses on Chengdu's private university educators, analyzing how factors like belongingness, self-actualization, and rewards influence job satisfaction. Through surveys, data analysis, and literature review, this study refines its findings and uncovers underlying causes. The study offers actionable insights for educators and institutions, aimed at enhancing job satisfaction.
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