• Journal of KIISE:Software and Applications
• /
• v.31 no.9
• /
• pp.1246-1257
• /
• 2004

To find an optimal solution with genetic algorithm, it is desirable to maintain the population sire as large as possible. In some cases, however, the cost to evaluate each individual is relatively high and it is difficult to maintain large population. To solve this problem we propose a novel genetic algorithm based on fuzzy clustering, which considerably reduces evaluation number without any significant loss of its performance by evaluating only one representative for each cluster. The fitness values of other individuals are estimated from the representative fitness values indirectly. We have used fuzzy c-means algorithm and distributed the fitness using membership matrix, since it is hard to distribute precise fitness values by hard clustering method to individuals which belong to multiple groups. Nine benchmark functions have been investigated and the results are compared to six hard clustering algorithms with Euclidean distance and Pearson correlation coefficients as fitness distribution method.

• The Journal of the Korea Contents Association
• /
• v.10 no.7
• /
• pp.23-30
• /
• 2010

It is important for the strategy of cosmetic sales to investigate the sensibility and the preference degree in the environment that the makeup style has been changed focusing on the consumer center. We proposed the human sensibility ergonomics makeup recommendation system (MakeupRS) using the context sensor information applying the collaborative filtering technique as one of methods in the makeup style development centered on the consumer's sensibility and the preference. In the collaborative filtering technique, the Pearson correlation coefficient applying to the case amplification is used to calculate similarity weights between the users. To investigate the sensibility according to the effect of makeup styles, the makeup styles were analyzed in terms of 6 style factors, such as, the foundation, the color lens, the eye shadow, the eye lash, the cheek brusher, and the lipstick. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the human sensibility ergonomics makeup recommendation system.

• The Journal of the Korea Contents Association
• /
• v.13 no.12
• /
• pp.840-850
• /
• 2013

This study examined influencing factors on the attitudes toward elders with a focus on empathy. Data were gathered from 291 nurses working at 14 geriatric hospitals in Kyunggi-Do, Chungchung-Do and Incheon. In analyzing the data, Pearson correlation coefficients, t-test, ANOVA, and regression analysis were adopted. Attitudes toward elders were neutral on the average; those nurses revealed both positive and negative aspects such as friendly, good, kind, conservative, sick and dependent. Of the four empathy scales, only empathic concern revealed significant correlation with the attitudes toward elders. Regression model included empathic concern and the nurses' characteristics. Empathic concern was significant in predicting the attitudes toward elders after controlling for the effects of the nurses' characteristics. Experience of voluntary work for elders was the only predictor among individual characteristics. Explanatory power of the model was 10.7%. We need to develop intervention programs raising empathy among nurses. The instrument measuring empathy needs to be examined.

• Journal of the Korean Society for information Management
• /
• v.24 no.4
• /
• pp.267-283
• /
• 2007

In this study, measures of distributional similarity such as KL-divergence are applied to cluster documents instead of traditional cosine measure, which is the most prevalent vector similarity measure for document clustering. Three variations of KL-divergence are investigated; Jansen-Shannon divergence, symmetric skew divergence, and minimum skew divergence. In order to verify the contribution of distributional similarities to document clustering, two experiments are designed and carried out on three test collections. In the first experiment the clustering performances of the three divergence measures are compared to that of cosine measure. The result showed that minimum skew divergence outperformed the other divergence measures as well as cosine measure. In the second experiment second-order distributional similarities are calculated with Pearson correlation coefficient from the first-order similarity matrixes. From the result of the second experiment, secondorder distributional similarities were found to improve the overall performance of document clustering. These results suggest that minimum skew divergence must be selected as document vector similarity measure when considering both time and accuracy, and second-order similarity is a good choice for considering clustering accuracy only.

• The Journal of the Korea Contents Association
• /
• v.18 no.3
• /
• pp.557-567
• /
• 2018

This paper studies the relationship between general investors' allotment ratio and underpricing for the companies that were newly listed in KOSDAQ market after the 20% rule, from March 2004 to December 2013, by empirical analysis. It is shown that the excess allotment ratio over 20% has a strong explanatory power for underpricing ratio under the 1% significance level. Furthermore, the general investors' allotment ratio is a significant explanatory variable of underpricing ratio under the 5% significance level. There are many hypotheses about underpricing, however, if underpricing is evident with high allocation ratio for general investors, it can be regarded as a signal of company's confidence in earnings after listing. In conclusion, this study reveals that general investors' allotment ratio can be used as a major explanatory variable that has a significant effect on the degree of undervaluation in the IPO market.

• Journal of The Korean Association of Information Education
• /
• v.11 no.3
• /
• pp.281-288
• /
• 2007

Collaborative filtering is a method to predict preference items of a user based on the evaluations of items provided by others with similar preferences. Collaborative filtering helps general people make smart decisions in today's information society where information can be easily accumulated and analyzed. We designed, implemented, and evaluated a course recommendation system experimentally. This system can help university students choose courses they prefer to. Firstly, the system needs to collect the course preferences from students and store in a database. Users showing similar preference patterns are considered into similar groups. We use Pearson correlation as a similarity measure. We select K-nearest students to predict the unknown preferences of the student and provide a ranked list of courses based on the course preferences of K-nearest students. We evaluated the accuracy of the recommendation by computing the mean absolute errors of predictions using a survey on the course preferences of students.

• Korean Journal of Childcare and Education
• /
• v.12 no.1
• /
• pp.37-55
• /
• 2016

The purpose of this study was to analyze the effects of young children's playfulness, emotional control, and emotional instability on their peer play behavior, focusing on age differences. A total of 209 4- and 5-year-old children attending a child care center in South Korea participated in this study. The instruments used in this study were the Playfulness Scale, Emotion Regulation Checklist, and Penn Interactive Peer Play Scale. The collected data were analyzed using a Student's t-test, Pearson's partial correlation, and stepwise regressions with the SPSS software ver. 16.0. The main results of this study are as follows: First, there was a significant age difference in young children's emotional control, emotional instability, playfulness and peer play behavior. Second, the factors of emotional control and playfulness significantly predicted young children's play interaction irrespective of age. Third, the factors of emotional instability and playfulness significantly predicted young children's play disruption and play disconnection. Further, implications for the use of early intervention targeting specific emotional control and emotional instability problems have been discussed.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.3
• /
• pp.147-155
• /
• 2014

While variety of content on the internet has increased with the development of IT and person's needs about suitable information are increasing rapidly, studies for personalized service have been actively performed. In the study, we proposed the Hypertension and Diabetes risk analysis system according to personal food intake preference using the analysis method of buying preferences in product recommendation system. For the analysis of food intake preference, the Pearson correlation coefficient is used to calculate similarity weights between each reference analysis data and sample data and then reference data should be grouping into the similarity weights and calculating risk of hypertension and diabetes each group. To evaluate the significance of this system, 1,021 subjects are applied the system. Hypertension and diabetes groups' risk is significant higher than normal group statistically so, it is confirmed that food intake preference and the diseases were relevant. In this paper, we verify the validity of hypertension and diabetes risk analysis system using a personal food intake preference.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.3
• /
• pp.292-297
• /
• 2014

As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.3
• /
• pp.1515-1521
• /
• 2014

This study applies simulation-based education and care for acute myocardial infarction nursing students to investigate the effect of critical thinking, problem solving, and academic achievement of a single group before and after the raw experimental design. A total of 137 subjects were arbitration period September-October 2011, enforcement and arbitration were evaluated after simulation-based training six weeks total. Data analysis was performed using SPSS Win17.0, Paired t-test, the mean and standard deviation, Pearson's correlation coefficient was used. Research results of simulation-based training program to improve critical thinking, problem solving, and academic achievement were As increase critical thinking and problem solving ability was improved. whereas, Critical thinking skills and problem solving ability was no significant difference with academic achievement. Simulation-based training program to improve the practical skills of nursing students learning was found how useful it, that there is a need to take advantage of hands-on training in a variety of cases that can be common in the field of clinical scenarios developed by. To do this, It seems to be necessary to the development and operation more varied and appropriate hands-on training method.