• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.215-226
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• 2017

This study analyzed trends in agricultural and food marketing studies from 1984 to 2015 using text-mining techniques. Text-mining is a part of Big-data analysis, which is an effective tool to objectively process large amounts of information based on categorization and trend analysis. In the present study, frequency analysis, topic analysis and association rules were conducted. Titles of agricultural and food marketing studies in four journals and reports were used for placing the analysis. The results showed that 1,126 total theses related to agricultural and food marketing could be categorized into six subjects. There were significant changes in research trends before and after the 2000s. While research before 2000s focused on farm and wholesale level marketing, research after the 2000s mainly covered consumption, (processed)food, exports and imports. Local food and school meals are new subjects that are increasingly being studied. Issues regarding agricultural supply and demand were the only subjects investigated in policy research studies. Interest in agricultural supply and demand was lost after the 2000s. A number of studies after the 2010s analyzed consumption, primarily consumption trends and consumer behavior.

• Journal of Korean Home Economics Education Association
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• v.22 no.2
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• pp.1-13
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• 2010

This study was planned to provide basic information to help teachers guide lookism-prone students in their home and school life, and to guide them in the unit relating to clothing in school curriculums. To carry out this experiment questionnaires were administered to 481 students in their first and second year in middle and high schools in Gwangju city. The questionnaires are composed of 3 themes; 'general matters', 'attitudes about and recognition of appearance management' and 'school adaptation'. The collected data was analyzed with Component analysis(Varimax rotation) and Cronbach's ${\alpha}$, T-test, one-way ANOVA, Duncan-test, Pearson's correlation analysis and multiple regression analysis using the SPSS WIN 14.0(Kr). The results of this study were as follows; 1. The more they managed their behavior relating to appearance and cleanliness, the better they felt their friendships. 2. The less they concentrated management relating to appearance, the better they felt about their relationships with their teachers. 3. The less they concentrated management relating to appearance but the more they managed cleanliness the easier they adjusted to school rules. 4. The less they pursued a trendy appearance but the more they managed cleanliness, the better they studied.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.151-161
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• 2016

As part of a policy to address climate change and pollution problem, the government introduced a green credit card scheme in order to motivate pro-environmental behaviors in July 2011. It is important to present the specific ways to facilitate pro-environmental behaviors using the consumer behavior pattern data. This study was a result of data from total fifty seven thousands customer purchasing history data of green credit card to be created for the 3 months from January to March 2015. As the analysis process is put in to operation the analysis of the purchasing customer's profile firstly, and the second come into association analysis to consider the buying associations for green products purchasing networks, the third estimate the useful parameters to affect the customer's pro-environmental behavior and customer characteristics. It shows that royal customers are from 30 to 40 years old and their incomes are from 30 million won to 40 million won. Especially, they live in Daegu, Gyeonggi, and Seoul.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.240-263
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• 2021

A study on the public design rules of the government and each local government showed that the historical and cultural street landscape was included in the public design field, but it did not provide a clear evaluation index for the historical and cultural street public design. Against this background, this study intends to provide basic data for the improvement and improvement of the public design of the historical and cultural street in the future by producing an evaluation index for the public design of the historical and cultural street landscape. First, in this study, 6 evaluation indicators and 19 detailed items were derived by conducting expert Delphi survey twice on the basis of previous studies. Second, exploratory factor analysis and AHP analysis were conducted through a survey to verify the validity of the evaluation index and the priority of the index items, and as a result of the analysis, the Cronbach'α coefficient and the consistency ratio were verified. Among the evaluation indicators objectively derived through the above method, the priority was 'historical and culture-related> public-related> safety-related> accessibility-related> lasting-related> related to aesthetic harmony. The results of this study are meaningful in that they can provide basic data for the improvement and improvement of public design of historical and cultural streets in the future.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.499-506
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• 2021

Hackers' cyber attack techniques are becoming more sophisticated and diversified, with a form of attack that has never been seen before. In terms of information security vulnerability standard code (CVE), about 90,000 new codes were registered from 2015 to 2020. This indicates that security threats are increasing rapidly. When new security vulnerabilities occur, damage should be minimized by preparing countermeasures for them, but in many cases, companies are insufficient to cover the security management level and response system with a limited security IT budget. The reason is that it takes about a month for analysts to discover vulnerabilities through manual analysis, prepare countermeasures through security equipment, and patch security vulnerabilities. In the case of the public sector, the National Cyber Safety Center distributes and manages security operation policies in a batch. However, it is not easy to accept the security policy according to the characteristics of the manufacturer, and it takes about 3 weeks or more to verify the traffic for each section. In addition, when abnormal traffic inflow occurs, countermeasures such as detection and detection of infringement attacks through vulnerability analysis must be prepared, but there are limitations in response due to the absence of specialized security experts. In this paper, we proposed a method of using the security policy information sharing site "snort.org" to prepare effective countermeasures against new security vulnerability attacks.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.97-106
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• 2014

The development of big data technology was to more accurately predict diversified contemporary society and to more efficiently operate it, and to enable impossible technique in the past. This technology can be utilized in various fields such as the social science, economics, politics, cultural sector, and science technology at the national level. It is a prerequisite to find valuable information by data mining techniques in order to analyze big data. Data mining techniques associated with big data involve text mining, opinion mining, cluster analysis, association rule mining, and so on. The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between each set of items based on the association thresholds such as support, confidence, lift, similarity measures, etc.This paper proposed cosine net confidence as association thresholds, and checked the conditions of interestingness measure proposed by Piatetsky-Shapiro, and examined various characteristics. The comparative studies with basic confidence and cosine similarity, and cosine net confidence were shown by numerical example. The results showed that cosine net confidence are better than basic confidence and cosine similarity because of the relevant direction.

• Journal of the Korea Institute of Building Construction
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• v.10 no.3
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• pp.39-47
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• 2010

The government has routinely made efforts to improve the living environment and infrastructure of less-developed areas through large area urban remodeling projects, which are in themselves attempts to overcome the disadvantages of piecemeal local area development. Such projects are very complex, and various stakeholders are involved. However, the data on such projects has not been well managed, and has not lent itself to being easily adopted to similar projects. In addition, there are numerous fragmented mega-projects that seem to be performed based on "rules of thumb" To address this issue, the work process of many urban and residence project types should be standardized otherwise the participants will be confused to work properly. In particular, typical residents who lack knowledge about building redevelopment, building remodeling, urban environment improvement projects, and the like think that it is difficult to establish the preparation committees and association committees for the projects. Therefore, we examined previous researches related to the urban and building renovation to solve the prescribed present problems. This paper presents the three necessary research performances: first, we analyzed the administrative work process in the related laws; second, we examined the practical work process of the preparation committee and association committee stages; and finally we deduced the problem and presented the required improvements.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.601-609
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• 2014

The most widely used data mining technique for big data analysis is to generate meaningful association rules. This method has been used to find the relationship between set of items based on the association criteria such as support, confidence, lift, etc. Among them, confidence is the most frequently used, but it has the drawback that we can not know the direction of association by it. The attributably pure confidence was developed to compensate for this drawback, but the value was changed by the position of two item sets. In this paper, we propose four symmetrically and attributably pure confidence measures to compensate the shortcomings of confidence and the attributably pure confidence. And then we prove three conditions of interestingness measure by Piatetsky-Shapiro, and comparative studies with confidence, attributably pure confidence, and four symmetrically and attributably pure confidence measures are shown by numerical examples. The results show that the symmetrically and attributably pure confidence measures are better than confidence and the attributably pure confidence. Also the measure NSAPis found to be the best among these four symmetrically and attributably pure confidence measures.

• CELLMED
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• v.6 no.3
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• pp.15.1-15.4
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• 2016

Evidence based practice (EBP) is a system of applying the most current and valid high quality evidence to support clinical decision making in a healthcare setting. In the twenty five years since its inception, EBP has become the accepted benchmark for excellence in healthcare. Although the system emerged within the biomedical sciences, in the years since EBP has become normative across all healthcare modalities from dentistry, allied health to complementary and alternative medicine (CAM). Practicing evidence based medicine within any modality potentially offers the patient the best available care based on high quality evidence. Yet it is the nature of the evidence that provokes some questions about the suitability of EBP across all modalities of healthcare. The meta analysis of randomized controlled trial (RCT) stands at the pinnacle of the hierarchy of evidence in EBP. This forms a challenge to CAM due to the difficulty in reducing the elementals of a holistic naturopathic assessment of a patient into an answerable question to be tested within a RCT. On one level this makes EBP paradigmatically incompatible with CAM, yet on another level it presents the opportunity to redefine the parameters of what is considered high level evidence. EBP has become a tool, and at times a weapon wielded by governments and health insurance companies to direct healthcare funding and policy. The implications of the nature of accepted evidence are becoming far reaching. The pursuit of the best available healthcare for each individual is the focus of EBP. However, the injudicious use of this system to direct health policy is fraught with biomedical bias and dominance. This issue raises the challenge to CAM to present high level evidence according to the rules of evidence, or face the annihilation of centuries of empirical knowledge.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.97-121
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• 2001

Until now, we have believed that one of advantages of cyber market is that it can virtually display and sell goods because it does not necessary maintain expensive physical shops and inventories. But, in a highly competitive environment, business model that does away with goods in stock must be modified. As we know in the case of AMAZON, leading companies already consider merchandise management as a critical success factor in their business model. That is, a solution to compete against one's competitors in a highly competitive environment is merchandise management as in the traditional retail market. Cyber market has not only past sales data but also web log data before sales data that contains information of path that customer search and purchase on cyber market as compared with traditional retail market. So if we can correctly analyze the characteristics of before sales patterns using web log data, we can better prepare for the potential customers and effectively manage inventories and merchandises. We introduce a systematic analysis method to extract useful data for merchandise management - demand forecasting, evaluating & selecting - using web mining that is the application of data mining techniques to the World Wide Web. We use various techniques of web mining such as clustering, mining association rules, mining sequential patterns.