Browse > Article
http://dx.doi.org/10.13067/JKIECS.2020.15.4.725

Variation for Mental Health of Children of Marginalized Classes through Exercise Therapy using Deep Learning  

Kim, Myung-Mi (Kyonggy University, Alternative medicine)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.15, no.4, 2020 , pp. 725-732 More about this Journal
Abstract
This paper uses variables following as : to follow me well(0-9), it takes a lot of time to make a decision (0-9), lethargy(0-9) during physical activity in the exercise learning program of the children in the marginalized class. This paper classifies 'gender', 'physical education classroom', and 'upper, middle and lower' of age, and observe changes in ego-resiliency and self-control through sports rehabilitation therapy to find out changes in mental health. To achieve this, the data acquired was merged and the characteristics of large and small numbers were removed using the Label encoder and One-hot encoding. Then, to evaluate the performance by applying each algorithm of MLP, SVM, Dicesion tree, RNN, and LSTM, the train and test data were divided by 75% and 25%, and then the algorithm was learned with train data and the accuracy of the algorithm was measured with the Test data. As a result of the measurement, LSTM was the most effective in sex, MLP and LSTM in physical education classroom, and SVM was the most effective in age.
Keywords
Machine learning; Support vector machine; Decision tree; Multi-perceptron; Recurent Neural Network; Long Short Term Memory;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
연도 인용수 순위
1 C. Jung, R. Jang, D. Nyang, and K. Lee, "A Study of User Behavior Recognition-Based PIN Entry Using Machine Learning Technique," Korea Information Processing Society review, computer and communication systems, vol. 7, no. 2, 2018, pp. 127-136.
2 G. Lee, H. Ha, H. Hong, and H. Kim, "Exploratory Research on Automating the Analysis of Scientific Argumentation Using Machine Learning," J. of the Korean Association for Science Education, vol. 38, no. 2, 2018, pp. 219-234.   DOI
3 J. Lee and S. Yoo, "Deep learning based emotion classification using multi modal bio-signals," J. Korea Multimedia Society, vol. 23, no. 2, 2020, pp. 146-154.
4 D. Hwang, S. Kim, and Y. Bae, "A prediction of bid price using k-nearest neighbors algorithm," J. Korea institute of intelligent Systems, vol. 29, no. 6, 2019, pp. 482-487.   DOI
5 G. Bak, H. Yoon, and Y. Bae, "Prediction of groundwater level lstm algorithm of using data-based learning," J. Korea institute of intelligent Systems, vol. 30, no. 2, 2020, pp. 161-166.   DOI
6 G. Bak and Y. Bae, "Performance comparison of machine learning in the various kind of prediction," J. of the Korea Institute of Electronic Communication Sciences, vol. 14, no. 1, 2019, pp. 169-178.   DOI
7 G. Bak and Y. Bae, "Groundwater level prediction using ANFIS algorithm," J. of the Korea Institute of Electronic Communication Sciences, vol. 14, no. 6, 2019, pp. 1235-1240.   DOI
8 J. H. Block and J. block, "The role of ego-control and ego-resiliency in the organization of behavior," In Minnesota symposium on child psychology, vol. 61, no. 4, 1980, pp. 315-327.
9 H. Koo and S. Hwang, "A validity study on ego resilience scale and ego control scale of California child Q - Set ( CCQ )," Korean Journal Clinical Psychology, vol. 20, no. 2, 2001, pp. 345-358.
10 D. McNair, M. Lorr, and L. F. Droppleman, "Profile of mood states manual (revision): educational and industrial testing service," San Diego, CA: Educational and Industrial Testing Service.
11 M. Han, "Study on the POMS's Predictability of Athletic Performances," Korean Society of Sport Psychology, vol. 13, no. 2, 2002, pp. 119-132.
12 D. W. Ruck, S. K. Rogers, M. Kabrisky, M. E. Oxley, and B. W. Suter, "The multilayer perceptron as an approximation to a bayes optimal discriminant function," IEEE transactions on neural networks, vol. 1. no. 4, 1990, pp. 296-298.   DOI
13 J. A. K. Suykens and J. Vandewalle, "Least squares support vector machine classifiers," Neural processing letters, 1999, pp. 293-300.
14 S. Hochreiter and J. Schmidhuber, "Long short-term memory," Massachusetts institute of technology, vol. 9, no. 8, 1997, pp. 1735-1780.
15 M. A. Friedl and C. E. Brodley, "Decision tree classification of land cover from remotely sensed data," Remote sensing of environment, vol. 61, no. 3, 1997, pp. 399-409.   DOI
16 T. Mikolov, S. Kombrink, L. Burget, J. Cernocky, and S. Khudanpur, "Extensions of recurrent neural network language model," IEEE, International Conference on Acoustics, speech and signal precessing(ICASSP), Prague, Czech Republic, 2011, pp. 5528-5531.