• Communications of Mathematical Education
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• v.24 no.2
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• pp.415-444
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• 2010

The purpose of this study is to provide information that will help understand unique characteristics of mathematically gifted students and that can be utilized for special programs for mathematically gifted students, by investigating difference and relationship between attribution styles and attitude toward mathematics of mathematically gifted students and those of regular students. For that purpose, 202 mathematically gifted students and 415 regular students in 5th and 6th grades at elementary schools were surveyed in terms of attribution styles and attitude toward mathematics, and the result of the study is as follows. First, as for attribution styles, there was no difference between gifted students and regular students in terms of grade and gender, but there was significant difference in sub factors because of giftedness. Second, there was not significant difference between grades. but there was significant difference in sub factors between genders. Mathematically gifted students were more positive than regular students in every sub factor excepting gender role conformity, and especially they showed higher confidence and motivation. Third, according to the result of correlation analysis, there was significant static correlation between inner tendencies and attitude toward mathematics with both groups. The gifted group showed higher correlation between attribution of effort and attitude toward mathematics and inner tendencies and confidence than the regular group. The gifted group showed higher correlation in sub factors, and especially there was high static correlation between attribution of talent and confidence, and attribution of effort and motivation. Fourth, according to the result of multiple regression analysis, inner tendencies showed significant relation to attitude toward mathematics with both groups, and especially the influence of attribution of effort was high. Both attribution of effort and attribution of talent were higher in the gifted group than the regular group, and attribution of effort had a major influence on practicality and attribution of talent had a major influence on confidence.

• Journal of KIISE
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• v.43 no.10
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• pp.1124-1130
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• 2016

A controlled group is closed compared to other organizations, which hinders collection of data and accurate analysis, so that it is hard to evaluate a controlled group's power structure and predict future changes using usual analytical methods including sociological approach. Analyzing a controlled group using SNA can allow for evaluation of inner power structure by revealing the relationships between members and identifying members with central roles given limited data. In this study, in order to evaluate changes in power structure, time-sequential SNA research was conducted by analyzing eigenvector centrality, which reflects individual influence and reveals the overall power structure. The result showed an improvement in accuracy compared to other centralities that contain individual degree or closeness, and made it possible to presume structural changes such as promotion or purge of a member.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.458-467
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• 2016

An expert search method using a large amount of academic data that can provide users with representative research results and advice is required. Since the existing expert search methods perform the expert search based on user profile or activity information, they have a problem that it is hard to discriminate the expert when we do not know the user profile or activity information. In this paper, we propose an academic expert search method using the importance and quality of a paper. The importance of a paper is computed by considering its scarcity and up-to-date topics. The quality of a paper is evaluated by considering the number of citations, IF of Journal, recency and author relations. To show the superiority of the proposed method, we compare it with the existing scheme through the performance evaluation in terms of recall and precision.

• Journal of the Korean Society of Food Culture
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• v.14 no.4
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• pp.289-304
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• 1999

The purpose of this study was to examine the consumers' acceptance of irradiated foods according to sociodemographic characteristics and the factors to distinguish subjects with differential levels of their willingness to buy them. Data were collected from the 365 women living in Youngnam area by the self-administered questionnaire. The results from this study were as follows. First, consumers were concerned regarding food safety issues in general and particularly preservatives. Second, many subjects had not heard of the irradiated foods and showed wait-and-see attitude in the willingness to accept them. Consumers' willingness to purchase them were higher than any other cases if radiation would not remain in foods. Third, the results from the discriminant analyses showed that the concern toward food safety, perceived innovativeness, willingness to pay more for organic foods, and knowledge of irradiation were the factors to distinguish groups with differential levels of willingness to purchase the irradiated foods. The results from the study imply that accurate and scientific information about food irradiation should be given to the consumers.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.11
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• pp.1435-1442
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• 2008

The purpose of this study was to identify the influence of consumption value on healthy functional food choice. Also, this study explored the role of health motivation, health concern, and food involvement as a moderating variable in the relationship between consumption value and healthy functional food choice. A total of 281 responses were collected using on-site survey (response rate 96.0%) from college students in Daegu, Gyeoungbuk Province. The questionnaire contained questions on consumption value, health motivation, health concern, food involvement, and purchasing intention of healthy functional food. The respondents rated the items using a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). According to the confirmatory factor analysis, item evaluating using factor loading resulted in the retention of 25 consumption value items loading on seven factors, four health motivation items loading one factor, six health concern items loading on one factor, and four food involvement items loading on one factor with an internal consistency. Results of stepwise regression found that social value-I, emotional, functional, epistemic, and conditional values among consumption value determined the purchasing intention of healthy functional food. Results of hierarchical regression showed that health concern had a positive effect on the relationship between social value-I and purchasing intention of healthy functional food.

• Journal of Labour Economics
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• v.29 no.1
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• pp.129-152
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• 2006

The purpose in this study is to analyze the effect of expected public pension assets (or social security wealth) and retirement incentives on retirement behaviors of two wage earners households. For the purpose of the study, an empirical analysis was conducted. In the empirical step, it was found that the empirical results were significant for men, but not for women namely, statistically asymmetric if behaviors of two couples are interdependent. The cause for the statistically asymmetric results were then determined. The Bivariate Probit model was used for estimation in the first step and the KLIPS(Korean Labor and Income Panel Study) was used as data for estimation. According to the empirical analysis, the results showed statistically significant asymmetry for men, however not for women, in expected public pension assets and other retirement incentives, non-wage assets, age difference, spouse's health status, spouse's monthly wages per hour and aging of their spouse In this study, cause of statistically asymmetric result in asymmetric complementarities of leisure of couples were found, then explained through different methods of comparison from the most recent studies. First, spouse's cross wage elasticity of self leisure demand(retirement) was calculated and determined whether complementarities of leisure of couples is positive or negative. Then, the degree of complementarities of leisure was distinguished in comparison with the relative size of two cross elasticities. Thus, men have relatively strong complementarities of leisure. But for women, it may roughly cancel out due to the substitution effect and the income effect. Therefore, women have relatively weak complementarities of leisure.

• Knowledge Management Research
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• v.21 no.3
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• pp.177-195
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• 2020

The social consciousness on fake reviews has triggered researchers to suggest ways to cope with them by analyzing contents of fake reviews or finding ways to discover them by means of structural characteristics of them. This research tried to collect data from blog posts in Naver and detect habitual patterns users use unconsciously by variables extracted from blogs and blog posts by a machine learning model and wanted to use the technique in predicting fake reviews. Data analysis showed that there was a very high relationship between the number of all the posts registered in the blog of the writer of the related writing and the date when it was registered. And, it was found that, as model to detect advertising reviews, Random Forest is the most suitable. If a review is predicted to be an advertising one by the model suggested in this research, it is very likely that it is fake review, and that it violates the guidelines on investigation into markings and advertising regarding recommendation and guarantee in the Law of Marking and Advertising. The fact that, instead of using analysis of morphemes in contents of writings, this research adopts behavior analysis of the writer, and, based on such an approach, collects characteristic data of blogs and blog posts not by manual works, but by automated system, and discerns whether a certain writing is advertising or not is expected to have positive effects on improving efficiency and effectiveness in detecting fake reviews.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1075-1081
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• 2013

Twitter, Facebook, and KakaoStory are the major SNS in Korea. Social knowledge production is being produced by those services from numerous collaboration and co-participation in those SNS. Wikipedia or Naver JishikIN service was regarded as the representative product of collective knowledge production during the wired internet era. However now at the wireless internet era centered with smart phones, various forms of collective knowledge production would be achieved by connecting to SNS in real-time. In this thesis, the survey data of collective knowledge production for users of three SNS have been compared and analyzed. The difference of the collective knowledge production mechanism among Twitter, Facebook and KakaoStory has been studied and compared through three variables: the motivation of collective knowledge production, the preference of collective knowledge production model, and collective knowledge production cultural perception. As a result of the analysis of the discriminant factors for three SNS user groups, it turns out that the diversity-toward usage motivation, personal contribution motivation, and collective knowledge production tendency perception are the most influential variables. This thesis is of significance in that it unites the value of social science such as social capital and collective knowledge production from the viewpoint of computer science and opens the new chapter of collective knowledge production with the real-time SNS of wireless internet from the wired internet.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Asia Marketing Journal
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• v.7 no.1
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• pp.21-42
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• 2005

Customer Relationship Management (CRM) is a corporate marketing strategy maintaining and managing customers. And with CRM companies maximize the customer's value through a series of processes of new customer retention, VIP customer retention, customer value increase, potential customer activation, and customers for lifetime by collecting the customer information and taking advantage of it effectively. In particular, as the competitive environment is changing rapidly and getting more intense, maintaining the customer retention through customer churn management becomes more important in order to increase the customer value for maximizing the company's profit and to build up the relationship with customers. For example, the financial industry has managed the customer churn with the concept of customer segmentation. Recently the customer retention and churn management is becoming increasingly important in all business fields as well as financial industry since the companies expect the effect of preventing the customer churn by identifying characteristics of customers. However, despite the increasing interest and importance of the management of the customer churn, not many of studies are systematically executed by analyzing the data of customer churn. In this study we analyze the actual data of CRM activities for the customer retention, specifically the data of TV home-shopping. By doing so, we hope to identify the differences of demographic attributes and transaction specific characteristics in consumer behaviors between the churning customer and the retained customers. In addition, we try to find out the variables which can impact the churning of the customers and to predict the churn rate of individual customer through our proposed model of customer churn. In the end, based on our findings we suggest the possible marketing strategies for TV home-shopping companies.