• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.6
• /
• pp.477-484
• /
• 2016

Small industrial appliances such as fan, audio, electric rice cooker mostly consist of ABS, PP, PS materials. In colored plastics, it is possible to classify by near infrared(NIR) spectroscopy, while in black plastics, it is very difficult to classify black plastic because of the characteristic of black material that absorbs the light. So the RBFNNs pattern classifier is introduced for sorting electrical and electronic waste plastics through LIBS(Laser Induced Breakdown Spectroscopy) spectrometer. At the preprocessing part, PCA(Principle Component Analysis), as a kind of dimension reduction algorithms, is used to improve processing speed as well as to extract the effective data characteristics. In the condition part, FCM(Fuzzy C-Means) clustering is exploited. In the conclusion part, the coefficients of linear function of being polynomial type are used as connection weights. PSO and 5-fold cross validation are used to improve the reliability of performance as well as to enhance classification rate. The performance of the proposed classifier is described based on both optimization and no optimization.

• Industry Promotion Research
• /
• v.9 no.3
• /
• pp.285-294
• /
• 2024

This study aims to provide basic data for improving academic self-efficacy by identifying the mediating effect of teacher support and the moderating effect of growth mindset in the impact of academic burnout on academic self-efficacy. The subjects of the survey were 300 college students majoring in stomatology and stomatology technology in Guangzhou Medical College who were intentionally sampled from a university in Guangdong, China. Data was collected using an online questionnaire. Data analysis was performed using SPSS PC+ Win. ver. 25.0 and SPSS PROCESS macro ver. 4.2. The statistical techniques used were descriptive statistics, reliability analysis, correlation analysis, and indirect effect and conditional direct effect analysis. The research results are as follows. First, academic burnout showed a significant negative correlation with teacher support, growth mindset, and academic self-efficacy. Teacher support showed a significant positive correlation with growth mindset and academic self-efficacy. Second, in the relationship between academic burnout and academic self-efficacy, teacher support played a mediating role, and growth mindset played a moderating role. To improve academic self-efficacy, this study proposed ways to utilize teacher support to offset and growth mindset to buffer the impact of academic burnout on academic self-efficacy.