• Korean journal of communication and information
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• v.46
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• pp.449-484
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• 2009

It has been said that Gwangjudream, nevertheless a free press, plays a role as a local press that it should be, in a situation that other local papers do not. This study aims to reveal the forces that influence the article production of Gwangjudream, and to examine the interrelations between them, through using the methods of participant observations and depth interviews. In this course, it is eventually purpose of providing more deep understandings on the present circumstances and problems of the local papers and having a chance to concern the concrete ways to enhance them. This study results in revealing the five forces that primarily influence the article production of Gwangjudream: 1) as a historical force, keeping the spirit of the first publication that look forward to playing a role as a local press that it sound be, 2) as an individual force, the habitus of its members that is critical of mainstream society and culture, 3) as an organizational force, non-hierarchical culture and the independence of the editorial rights, 4) as a habitual force, the deny of beat system, 5) as an economical force, the power of sponsors, financial poorness, and the competition for attracting subscribers. While the historical force and the individual force play a role as fundamental circumstances and the organizational force and the habitual force as practical circumstances for producing articles, they encourage to emerge the characteristics of the articles that are related to citizens' everyday life and reflect locality, and criticize and keep an eye on government and other public offices. However, the economical force provides the circumstances that weaken the characteristics of Gwangjudream. The results of this study question the perspective to overly regard it as coming from their economical weakness that the local newspaper do not play a role as a local press that it should be.

• Journal of The Korean Association For Science Education
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• v.31 no.1
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• pp.78-98
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• 2011

The purpose of this study was to analyze elementary school students' interpretation of data characteristics by cognitive style. Participants were elementary students in sixth grade who can use integrated inquiry process skills. The students were divided into two groups, analytic cognitive style and wholistic cognitive style according to their response to Cognitive Style Analysis. They performed scientific interpretation of data activity. To collect data for this study, participants recorded the result on scientific interpretation of data activity paper and researcher recorded the situation on videotape and interviewed with participants after the end of interpretation of data to get additional data. And the findings of this study were as follows: First, the study analyzed interpretation of data characteristics by the operator regarding different situations of interpreting data according to cognitive style. For example, in the intermediate state, analytic-cognitive style students showed high achievement in identifying variables, and wholistic-cognitive style students were active in using prior knowledge to interpret data. Second, the result of analysis on the direction of interpreting data and preference for data types in interpreting data activities according to cognitive style are as follows: Wholistic-cognitive style students showed relatively high perception of information through the top-down approach. On the other hand, analytic-cognitive style students usually used the bottom-up approach gradually expanding detailed information to the scientific question-related answer and showed a preference data of the table type. Through the result, this study aimed to help establish a data interpretation strategy for learners to solve problems based on understanding of interpretation of data characteristics according to learners' cognitive style, and purposed the instruction design suggesting the data requiring various data interpretation strategies to develop learners' data interpretation ability.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.3
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• pp.351-363
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• 2007

Previously, we analyzed for nutrition knowledge and the use of nutrition knowledge in the everyday lives of students in order to develop nutrition education programs that focus on desirable behavior change. From this, we found that female students desired to participate in nutrition education more than male students, and regarding their concerns for nutrition education, 73.2% of the females and 50.0% of the males displayed interest in 'obesity and the regulation of body weight'. Therefore, this study showed female students give more attention to the obesity and the regulation of body weight than male students(p=.000<.001). In addition, female students had higher interests($8.63{\pm}1.67$) than male students ($7.45{\pm}2.03$) in nutrition knowledge(p=.000<.001). By investigating the use of nutrition knowledge in everyday life, our research indicated that the actual use of nutrition knowledge was less. To encourage students to persue dietary lives addressing the concerns confirmed above, the following needed to occur. 1) Provide them nutrition information for the main processed foodstuffs encountered when dining out(breads, cakes, cookies, and carbonated beverage). 2) Teach them to read food nutrition labels. 3) Help them find a lifestyle connection through lasting self-management methods and the generation of social support. Accordingly, this required developing effective and practical nutrition education programs that considered regional characteristics and gender differences. The most important factors considered during nutrition education program development were the need for motivation and ongoing education by stage of change, rather than temporal education through specific problem analysis, in order that those being educated may bring about a change of behavior by themselves. Therefore, from this study, we have suggested the use of multilateral operating strategies for successful nutrition education. In addition the phase model of behavior change should be applied. Our programs were aimed at self owned nutritional management so that students could master their own methods for acquiring skills and enjoying dietary life. The research may be summed up as follows. First, the purpose of education at the recognition stage of change was to attempt motivation for nutrition improvement, by analyzing the problems such as food buying habit and the main purchasing viewpoints when dining out. Second, the purpose of education at the action stage of change was to help students acquire of concrete methods for behavior modification by linking the program to their home as well as to teachers with various activities that suited the situation at school. This was done by analyzing the processes and decisions pertaining to dining out the main processed foodstuffs and principal components, etc. through data and experimental practice. Third, the purpose of education for changing of habits and values, or the maintenance stage, was to investigate the various reasons that undesirable behaviors were induced, and then determine a lasting self-management method as well as how to generate social support. If the nutrition education program developed in this study is utilized on site, someone in the primary role as the nutrition educator and trained specifically in nutrition, can help induce the health promotion in the community as well as lasting dietary management, by executing a link with families in parallel with educating teaching staff and students' parents. In addition, this program can playa role in the government policies related to the health promotion for our youth who are the foundation of our nation and who can enhance our national competitive power.

• Management & Information Systems Review
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• v.31 no.4
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• pp.167-195
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• 2012

This study focuses on the characteristic of socio-psychological gender of a consumer except a biological gender. Socio-psychological gender is the self-image of a consumer which is related to the gender role. The goal of this study is, first, to examine if socio-psychological gender has more effect on the purchase intention than biological gender. Second, by classifying a group with femininity among socio-psychological gender, it is to examine what kinds of shopping value it aims at. Finally, it is to examine the difference between men and women from the purchase intention according to the circumstances. The result of this study is summarized as follows. First, a consumer can have both characteristics of biological gender and socio-psychological gender. There are masculinity, femininity, bisexuality, and undifferentiated type for the classification of socio-psychological gender. This study shows that there is relatively much bisexuality which has masculinity and femininity at the same time. The outcome showed that the purchase intention was higher for the product which corresponds to socio-psychological gender of a consumer than biological gender. Second, it indicated that a group with femininity pursued pleasurable shopping as compared to a group with masculinity. By contrast, it showed that a group with masculinity aimed at practical shopping more greatly. Finally, it showed that while women are less sensitive to the purchase intention at the male-dominated circumstances, men's purchase intention get lower at the female-dominated circumstances.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.41-54
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• 2020

This study was conducted to provide basic data for a transparent and fair bidding system by identifying problems and suggesting improvement measures through an analysis of the bidding status for construction projects and service-related landscaping of multi-family housing. To this end, we used the data from the "Multi-Family Housing Management Information System (K-apt)" that provides the history of apartment maintenance, bidding information, and the electronic bidding system to examine the winning bid status and amount, along with the size and trends of the winning bids by year, and the results of the selection of operators by construction type. As a result, it was found that out of the total number of successful bids (36,831), 4.4% (16,631) were in the landscaping business, and the average winning bid value was found to be about 24 million won. According to the data, 73% of the landscaping cases were valued between 3 million won and 30 million won, and 58.6% of the cases were in the field of "pest prevention and maintenance". 36% of the total number of bids were awarded from February to April, with "general competitive bidding" accounting for 59.8% of the bidding methods. As for the method of selecting the winning bidder, 55% adopted the "lowest bid" and "electronic bidding method," and 45% adopted the "qualification screening system" and "direct bidding method." As an improvement to the problems derived from the bidding status data, the following are recommended: First, the exception clause to the current 'electronic bidding method' application regulations must be minimized to activate the electronic bidding method so that a fair bidding system can be operated. Second, landscaping management standards for green area environmental quality of multi-family housing must be prepared. Third, the provisions for preparing design books, such as detailed statements and drawings before the bidding announcement, and calculating the basic amount shall be prepared so that fair bidding can be made by specifying the details of the project concretely and objectively must be made. Fourth, for various bidding conditions in the 'business operator selection guidelines', detailed guidelines for each condition, not the selection, need to be prepared to maintain fairness and consistency. These measures are believed to beuseful in the fair selection of landscaping operators for multi-family housing projects and to prepare objective and reasonable standards for the maintenance of landscaping facilities and a green environment.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Korea Science and Art Forum
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• v.37 no.1
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• pp.87-97
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• 2019

The study began in recent years with the aim of grasping the nation's medical status following the fast-growing trend of international medical tourism and attracting foreign patients, among other things, Busan, which ranks second in attracting foreign patients after the nation's capital, Seoul, has been highly active in the past eight years, with foreign patients rising by about 426 percent, and Russian patients entering the sea. In addition, Gimhae and Changwon, the Busan-based Gyeongsangnam-do region, ranked first and second in number of foreign residents, and are inhabited by a variety of foreign workers. Medical institutions, such as hospitals, should be able to find directions within hospitals. It is also a space where information in various languages, including Korean, English, Chinese, or Russian, must be delivered in a single medium. Based on this research, the purpose of this research is to provide converged information that helps foreigners who are not familiar with Korean language easily understand the proposed recognition system when visiting hospitals. Therefore, this paper is applied to a multi-language survey of six medical institutions (A, B, C, D, E, F) at the university hospital in Busan, and 10 medical institutions (R, J) in Gimhae, South Gyeongsang Province with high foreign residents. Research results and contents are as follows. First, the results of analyzing the design of the sinusoidal system show that the font uses colorless Gothic fonts, arrows, and pictograms to introduce the design of a typical hospital sign system. Second, the results of the multi-lingual situation were found to have only two languages in the system, such as Korean and English, and to have four languages, including Korean, English, Chinese, and Russian, according to their geographical location. However, it was judged that most medical institutions currently have only two languages (Korean, English) that may cause some discomfort in terms of language for foreign patients in non-English speaking countries. Based on these findings, it is necessary to propose designs that are considered by Koreans as well as foreign users in the use of multilingual hospital sign systems.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.63-72
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• 2019

As a sub-concept of corporate or organization governance, business governance and IT governance have become major research topics in academia. However, despite the importance of process as a construct for mediating the domain between business and information technology, research on process governance is relatively inadequate. Process Governance focuses on activities that link business strategy with IT system implementation and explains the creation of corporate core values. The researcher studied the basic conceptual governance models of political science, sociology, public administration, and classified governance styles into six categories. The researcher focused on the series of metamodels. For examples, the traditional Strategy Alignment Model(SAM) by Henderson and Venkatraman which is replaced by the neo-SAM model, organizational governance network model, sequential organization governance model, organization governance meta model, process governance CUBE model, COSO and process governance CUBE comparison model, and finally Process Governance Framework and etc. The Major difference between SAM and neo-SAM model is Process Governance domain inserted between Business Governance and IT Governance. Among several metamodels, Process Governance framework, the core conceptual model consists of four activity dimensions: strategic aligning, human empowering, competency enhancing, and autonomous organizing. The researcher designed five variables for each activity dimensions, totally twenty variables. Besides four activity dimensions, there are six driving forces for Process Governance cycle: De-normalizing power, micro-power, vitalizing power, self-organizing power, normalizing power and sense-making. With four activity dimensions and six driving powers, an organization can maintain the flexibility of process governance cycle to cope with internal and external environmental changes. This study aims to propose the Process Governance competency model and Process Governance variables. The situation of the industry is changing from the function-oriented organization management to the process-oriented perspective. Process Governance framework proposed by the researcher will be the contextual reference models for the further diffusion of the research on Process Governance domain and the operational definition for the development of Process Governance measurement tools in detail.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.