Major depressive disorder (MDD) is a leading world-wide psychiatric disorder with high recurrence rate, therefore, it is desirable to identify current MDD (cMDD) and remitted MDD (rMDD) for their appropriate therapeutic interventions. In the study, 19 cMDD, 19 rMDD and 19 well-matched healthy controls (HC) were enrolled and scanned with the resting-state functional magnetic resonance imaging (rs-fMRI). The Hurst exponent (HE) of rs-fMRI in AAL-90 and AAL-1024 atlases were calculated and compared between groups. Then, a radial basis function (RBF) based support vector machine was proposed to identify every pair of the cMDD, rMDD and HC groups using the abnormal HE features, and a leave-one-out cross-validation was used to evaluate the classification performance. Applying the proposed method with AAL-1024 and AAL-90 atlas respectively, 87% and 84% subjects were correctly identified between cMDD and HC, 84% and 71% between rMDD and HC, and 89% and 74% between cMDD and rMDD. Our results indicated that the HE was an effective feature to distinguish cMDD and rMDD from HC, and the recognition performances with AAL-1024 parcellation were better than that with the conventional AAL-90 parcellation.
This study conducted a questionnaire survey on the physical condition of high school students based on FIT. The correlation between sedentary behavior, exercise level and physical fitness was studied. In this paper, the fuzzy C-average clustering method of the BP neural network is used to make statistics and classification of students’ physical condition. This paper collates the biological quality data of college students. Then this paper makes a comprehensive classification, classification and quantitative assessment of the data. The study found that college students’ sedentary habits varied from individual and family backgrounds. Family factors influence students’ physical exercise. Physical exercise was positively correlated with sedentary behavior and body mass index in adolescents. The accuracy of clustering combined with the BP neural network can reach 94%.
Fusion training model of electromagnetic spectrum technology and management specialty under the guidance of "Emerging Engineering" is studied in this paper. Firstly, implementation of fusion training is introduced. Secondly, key problems to be solved in the process of implementation are listed. Thirdly, goals achieved with implementation are given. Lastly, significance of implementation are summarized. Fusion training model can provide theoretical guidance and practical support for personnel training under the concept "Emerging Engineering" in colleges and universities.
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