Discussing the Construction of Gratefulness Education in Modern Times

Gratefulness is Chinese traditional virtue, which gives Chinese the power to go upper ,encourages Chinese to understand others, having a important meaning to cultivate personal character, perfect the life meaning. In addition to this, it is necessary to build the harmonious camp and society. However, at present as a necessary part of the students’ education in university, it is also weak. There is no delay to strengthen the gratefulness education. This dissertation aims at probing into the reasons of loss of gratitude feeling, thereafter puts forward the countermeasures for this issue

Analysing the Effectiveness of University Scientific Research Projects on the Knowledge Management

This paper briefly analyzes the connotation and characteristic of knowledge management. Elaborating the problems which exist in the present scientific research project management, analyzing the relationship between university scientific research project management and knowledge management; putting forward the knowledgeable, informatization, modernization and humanization strategy into the process of scientific research project management under the view of knowledge management, and exploring theory and method to make full use of knowledge management, establishing the comprehensive and whole process management mechanism in local university scientific research project management, so as to improve the efficiency of scientific research project management, promoting the development of local colleges and universities’ scientific research

Characteristics of University’s Scientific Research Project Management i n the New Times

Along with the comprehensive deepening of reform and open, China\u27s economic has developed rapidly. National and provincial’s longitudinal and transverse scientific research projects are increasing. In particular, our country has many universities and they have close relationship with economics’ development. Also, scientific research projects that involved are multitude of names. Understand our country’s characteristics of scientific research project i n the new period correctly. Adjust local university’s scientific research project management method, means and key in time, and make out corresponding management system to promote local universities’ further development

Research of multi-concurrent fault diagnosis of rotating machinery based on VMD and KICA

In order to improve the multi-concurrent fault diagnosis of rotating machinery, a feature extraction method based on variational mode decomposition (VMD) and kernel independent component analysis (KICA) is proposed. First, use VMD to improve the dimension of single-channel vibration signal. Then, calculate the correlation coefficient between the signal of each dimension and the original signal. Finally, high correlation signals are used to form a new observation signal and the fault signals will be extracted by KICA. Compared with ensemble empirical mode decomposition (EEMD) + fast independent component analysis (FastICA), the better performance of the proposed method is demonstrated by an analysis of rolling bearing with the fault of inner ring and outer ring mixed. Furthermore, an experiment with the fault of outer ring of rolling bearing and gear breaking mixed verifies the effectiveness of this method. The result demonstrates that the proposed method is efficient for fault diagnosis of single-channel vibration signal of rotating machinery with multi-concurrent faults

An intelligent bearing fault diagnosis method based on the AFEEMD and 1D CNNs

To process the non-stationary vibration signals and improve accuracy of bearing fault diagnosis, this paper presents a novel intelligent fault diagnosis method based on the adaptive fast ensemble empirical mode decomposition (AFEEMD) and one-dimensional convolutional neural networks (1D CNNs). First, the AFEEMD algorithm is utilized to decompose the raw signals into intrinsic mode functions (IMFs). Then, the time and frequency statistic features of the first several IMFs are analyzed to form feature vector, which are used as the input of 1D CNNs to identify the bearing fault. The performance of the proposed method is validated using the dataset from the Case Western Reserve University (CWRU). Compared with the traditional back propagation neural network (BPNN), the results show that the proposed AFEEMD-1D CNNs method not only can obtain higher accuracy and achieve more reliable performance, but also can improve the generalization performance. Due to the end-to-end feature learning capacity, it can be extended to other machinery for fault diagnosis

Burnout and study engagement among medical students at Sun Yat-sen University, China: A cross-sectional study.

This study aims to investigate burnout and study engagement among medical students at Sun Yat-sen University, China.A cross-sectional survey was conducted among undergraduate medical students of Sun Yat-sen University, China. A total of 453 undergraduate students completed a self-administered, structured questionnaire between January and February, 2016. Burnout and study engagement were measured using the Maslach Burnout Inventory-Student Survey (MBI-SS) and the UTRECHT Work Engagement Scale-Students (UWES-S), respectively. Subjects who scored high in emotional exhaustion subscale, high in cynicism subscale, and low in professional efficacy subscale simultaneously were graded as having high risk of burnout. Independent sample t tests and chi-square tests were used to compare the differences in burnout and work engagement between genders, majors, and grade levels.The means (standard deviations) of the MBI-SS subscales were 3.42 (1.45) for emotional exhaustion, 2.34 (1.64) for cynicism, and 3.04 (1.30) for professional efficacy. The means (standard deviations) of the UWES-S subscales were 3.13 (1.49) for vigor, 3.44 (1.47) for dedication and 3.00 (1.51) for absorption. Approximately 1 in 11 students experienced a high risk of burnout. There were no statistically significant gender differences in burnout and study engagement. There were also no statistically significant differences in burnout and study engagement subscales according to student major. Students in higher grades displayed increased burnout risk, higher mean burnout subscale score of cynicism, lower mean burnout subscale score of professional efficacy, and decreased mean study engagement subscale scores of dedication and absorption. There were strong correlations within study engagement subscales.Chinese medical students in this university experience a high level of burnout. Students at higher-grade level experience more burnout and decreased study engagement compared with students in lower level