• Journal of Korea Game Society
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• v.17 no.2
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• pp.117-122
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• 2017

This study verified the effects of promoting optimism by utilizing communication board games with university students. Since optimism is closely related to grade, self-efficacy, a sense of achievement, the importance of enhancing optimism was emphasized. This study seeks to investigate practical measures that can promote optimism utilizing games in a more casual environment based on the research of Seligman(1990), which claimed that the optimism can be learned regardless of temperaments. In Study1, the level of optimism increased from M=-4.7(t1) to M=12.8 in t2(p<.001). In Study2, a control group(n=22) was added with the experiment group(n=21). The level of optimism increased from M=-2.4(t1) to M=11.5(t2) in the experiment group(p<.001), whereas there was no difference in the control group.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.95-103
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• 2006

In this paper, the input pattern vectors are extracted and the learning algorithms is designed to recognize EEG pattern vectors. The frequency and amplitude of alpha rhythms and beta rhythms are used to compose the input pattern vectors. And the algorithm for EEG pattern recognition is used SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of the subclass layer. The weights of the proposed algorithm which is between the input layer and the subclass layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm, and pattern vectors is classified into subclasses by neurons which is being in the subclass layer, and the weights between subclass layer and output layer is learned to classify the classified subclass, which is enclosed a class. To classify the pattern vectors of EEG, the proposed algorithm is simulated with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional LVQ.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.6
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• pp.837-844
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• 2010

Dietary life was formed as being influenced by the people's cultural, social and environmental situations. The people's food culture is unique that was adapted to their surroundings. It was developed and industrialized in the ethnic food. Now the ethnic food was contributed to tour industry or culture industry. Then, food life style was change from the meat diet to the vegetable diet in the diffusion of well-being trends. So, we analyzed Koreans' Korean food image and investigated the difference as a demographics. We made questionnaire and did a survey to 220 bloggers using cooking internet sites on 10 August, 2009. We analyzed 206 questionnaires by SPSS package 12.0 except 14 untrustworthy questionnaires. We measured credibility and validity 39 items related Korean food image: Chronbach's ${\alpha}$ was highly 0.855. We checked that KMO examination was 0.775 and $x^2$ of Barttlet was 2482.342. After verymax rotation, we deducted 5 Koran food images-healthy, visuality, spicy, variety, low calorie. We analyzed ANOVA of 5 Korean food images according to demographics. We confirmed the differences by ages, monthly income and job except academic background (p<0.05). Therefore, Korean food images were learned and recognized in everyday life. Especially, we found that visuality and variety were recognized the more stronger high-income earners and teachers than others. So, Korean learned Korean food images in real life and recognized Korean food quite differently by demographics.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.61-70
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• 2011

In this paper, we propose a defense NPC control model in the soccer game by applying the Decision Tree learning algorithm. The proposed model extracts the direction patterns and the action patterns generated by many soccer game users, and applies these patterns to the Decision Tree learning algorithm. Then, the proposed model decides the direction and the action according to the learned Decision Tree. Experimental results show that the proposed model takes some time to learn the Decision Tree while the proposed model takes 0.001-0.003 milliseconds to decide the direction and the action based on the learned Decision Tree. Therefore, the proposed model can control NPC in the soccer game system in real time. Also, the proposed model achieves higher accuracy than a previous model (Letia98); because the proposed model can utilize current state information, its analyzed information, and previous state information.

• Journal of the Korean School Mathematics Society
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• v.15 no.4
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• pp.699-718
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• 2012

The purpose of mathematics eduction is to develop the ability of thinking mathematically. It informs method to solve problem through mathematical thinking that teach mathematical ability. Errors in the problem solving can be thought as those in the mathematical thinking. Therefore analysis and classification of mathematics errors is important to teach mathematics. This study researches the preceding studies on mathematics errors and presents the characteristic of them with analyzed models. The results achieved by analysis of the process of problem solving are as follows : ▸ Students feel much harder to solve words problems rather than multiple-choice problems. ▸ The length of sentence make some differences of understanding of the words problems. Students easy to understand short sentence problems than long sentence problems. ▸ If students feel difficulties on the pre-learned mathematical content, they feel the same difficulties on the words problems based on the pre-learned mathematics content.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.19-26
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• 2020

In this paper, we propose a method to analyze the loss region of the dictionary-based super resolution result learned for image quality improvement and to map the learning data according to the analyzed loss region. In the conventional learned dictionary-based method, a result different from the feature configuration of the input image may be generated according to the learning image, and an unintended artifact may occur. The proposed method estimate loss information of low resolution images by analyzing the reconstructed contents to reduce inconsistent feature composition and unintended artifacts in the example-based super resolution process. By mapping the training data according to the final interpolation feature map, which improves the noise and pixel imbalance of the estimated loss information using a Gaussian-based kernel, it generates super resolution with improved noise, artifacts, and staircase compared to the existing super resolution. For the evaluation, the results of the existing super resolution generation algorithms and the proposed method are compared with the high-definition image, which is 4% better in the PSNR (Peak Signal to Noise Ratio) and 3% in the SSIM (Structural SIMilarity Index).

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1841-1848
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• 1999

DELVAUX is a genetics-based inductive learning system that learns a rule-set, which consists of Bayesian classification rules, from sets of examples for classification tasks. One problem that DELVAUX faces in the rule-set learning process is that, occasionally, the learning process ends with a local optimum without finding the best rule-set. Another problem is that, occasionally, the learning process ends with a rule-set that performs well for the training examples but not for the unknown testing examples. This paper describes efforts to alleviate these two problems centering on the N-version learning approach, in which multiple rule-sets are learning and a classification system is constructed with those learned rule-sets to improve the overall performance of a classification system. For the implementation of the N-version learning approach, we propose a decision-making scheme that can draw a decision using multiple rule-sets and a genetic algorithm approach to find a good combination of rule-sets from a set of learned rule-sets. We also present empirical results that evaluate the effect of the N-version learning approach in the DELVAUX learning environment.

• The Journal of Korean Society for School & Community Health Education
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• v.6
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• pp.1-16
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• 2005

This study was conducted to the middle and high school students in some Seoul and Kyunki areas to identify the smoking behavior characteristics among adolescences. A self-administered survey was conducted to the 2nd grad students in 4 middle schools and 6 high schools and the survey Questionnaire included general characteristics, smoking and drug use history, the close people's smoking and drug use, smoking and drug abuse prevention education, smoking intention, and smoking attitude. A total of 2,452 youths finished the survey (1,182 middle school students and 1,270 high school students). Current smoking students were 14.6%, the ex-smokers were 5.5%, and the never smokers were 85.4%. Majority of students smoked less than 5 bars of cigarettes and their first smoking experiences were related to their family members (siblings, parents, and relatives), friends, advertisement in order. Other GYTS countries reported the similar sources of the smoking start and friend was prior smoking start factor to the other sources. The students who wanted to Quit smoking were 6.7% and the students who ever had tried to Quit smoking were 9.1%. The major reasons of Quitting smoking were for their health and for their financial burden. Approximately 60% learned about smoking and drug abuse in their regular school classes, 8.4% were in the special school activities, and 7.9% were in the class closing time sometimes in order. The students who learned in any regular class were smaller in the high school students than in the middle school students. The learning experiences in school of other GYTS countries were similar to that of Korea. In conclusion, students' smoking was affected not only by the preventive activities in school but also by the close people's behaviors and care in this study; therefore, the active partnership between school and family must be a strong strategy for youth's smoking prevention.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.181-188
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• 2019

The purpose of this study is to implement the convergence thinking in problem-based learning (PBL) on paramedic education. PBL scenario course was conducted for 78 students in the third year of emergency medical technology during the first semester of 15 weeks in 2017. After 15 weeks, data of 73 students were analyzed. Among questions about learning interest in PBL, 'neutral' was the most frequent response with 38% for "PBL scenario classes were more effective in learning and acquiring knowledge than lecture class". For "The lessons learned in the class helped to improve the ability to come up with appropriate solutions for problem solving", 57.5% responded 'agree', and for "The lessons learned in the class helped with confidence in the emergency scene", 50.7% responded 'agree'. PBL will be an effective and efficient way of teaching as a learning curriculum for understanding the field situation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.6
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• pp.423-433
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• 2022

This paper introduces the case studies of launch environmental test for cube nanosatellites and lessons learned of the design and integration from those. Generally, nanosatellites are launched and deployed in space while being contained in nanosatellite deployers, mechanical loads of launch are transferred through the deployer. This characteristic make nanosatellites under larger loads and higher possibilities of mechanical failure. This study represents guidelines of the design and the integration of the nanosatellites by showing the cases of launch environmental test of nanosatellite system. Moreover, it is suggested that the modern nanosatellite deployer with the capability of fixing the internal nanosatellite be preferable to conventional deployer by comparing the test results with those deployers.