• Journal of The Korean Association of Information Education
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• v.3 no.1
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• pp.116-124
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• 1999

Cyber education and teacher training is the distance training program which is operating in the Korea National University of Education for teachers and citizen. In this paper, we suggest a model for establishing legal basis of cyber teacher training, by analyzing laws and processing-laws in the parliament and cyber teacher training institutes. The model contain 'The Rule for Operating CTTI(Cyber Teacher Training Institute)', 'The Rule for Using CIT Systems', 'The Rule for Operation CIT'.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.121-123
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• 2004

본 논문은 데이터 마이닝에서 사용되는 연관규칙(Association Rule)을 활용하여 고객에게 상품을 추천하는 방법을 제안한다. 일반적으로 한명의 고객에 대하여 적용할 수 있는 연관규칙의 개수가 한 개 이상이 될 수 있다는 가정하에, 고객과 연관규칙과의 적합성 여부를 값으로 나타내는 방안을 고안하고 이를 이용하여 고객에 대한 연관규칙의 순위를 부여하는 방식을 연구한다. 또한 상품 추천 시 범위 값을 가지는 속성을 고려하여 상품을 추천하도록 하는 방법을 제안하고 이 방법의 타당성과 타 방식과의 비교우위를 실험을 통하여 검증한다.

• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.15-23
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• 2002

As recently the network environment and application services have been more complex and diverse, there has. In this paper we introduce a scheme the extract useful information for network management by analyzing traffic data in user login file. For this purpose we use classification and association rule based on episode concept in data mining. Since login data has inherently time series characterization, convertible data mining algorithms cannot directly applied. We generate virtual transaction, classify transactions above threshold value in time window, and simulate the classification algorithm.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.365-377
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• 2006

Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein interaction is intrinsic to most cellular processes, prediction of protein interaction is an important issue in post-genomic biology where abundant interaction data have been produced by many research groups. In this paper, we present an associative feature mining method to predict implicit protein-protein interactions of Saccharomyces cerevisiae from public protein interaction data. We discretized continuous-valued features by maximal interdependence-based discretization approach. We also employed feature dimension reduction filter (FDRF) method which is based on the information theory to select optimal informative features, to boost prediction accuracy and overall mining speed, and to overcome the dimensionality problem of conventional data mining approaches. We used association rule discovery algorithm for associative feature and rule mining to predict protein interaction. Using the discovered associative feature we predicted implicit protein interactions which have not been observed in training data. According to the experimental results, the proposed method accomplished about 96.5% prediction accuracy with reduced computation time which is about 29.4% faster than conventional method with no feature filter in association rule mining.

• Korean Journal of Health Education and Promotion
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• v.21 no.1
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• pp.197-216
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• 2004

The purpose of this study was to compare beliefs about social rule, differential peer association, perceived behavioral control, intention of smoking, and self efficacy for rejecting smoking among smokers, reformed smokers, and non smokers in adolescence. The subjects were 576 adolescents in middle and high school, living in K city. The data was collected through questionnaires from December 1st to 18th, 2002 was analyzed using descriptive statistics, x²-test, and ANOVA. 1) The general characteristics and characteristics related to smoking among smokers, reformed smokers, and non smokers in adolescence showed differences as follows： sex, mother's education, monthly allowance, thinking about teacher's smoking, feelings about the smoking scene, thinking about father's smoking, drinking, satisfaction of school, and sexual experience. 2) Belief about social rule, differential peer association, perceived behavioral control, intention of smoking, and self efficacy for rejecting smoking among the three groups showed differences as follows： smokers have a lower belief about social rule, lower perceived behavioral control, lower self-efficacy for rejecting smoking, but higher differential peer association and higher intention of smoking than those of reformed smokers and non smokers. We recommend the development of a nursing program for anti-smoking behavior including the research factors affecting attitudes of smoking adolescents.

• The Journal of Information Systems
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• v.30 no.1
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• pp.123-149
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• 2021

Purpose The purpose of this study is to define the anti-ESG activities of companies recognized by media by reflecting ESG recently attracted attention. This study extracts keywords for ESG controversies through association rule mining. Design/methodology/approach A research framework is designed to extract keywords for ESG controversies as follows: 1) From DeepSearch DB, we collect 23,837 articles on anti-ESG activities exposed to 130 media from 2013 to 2018 of 294 listed companies with ESG ratings 2) We set keywords related to environment, social, and governance, and delete or merge them with other keywords based on the support, confidence, and lift derived from association rule mining. 3) We illustrate the importance of keywords and the relevance between keywords through density, degree centrality, and closeness centrality on network analysis. Findings We identify a total of 26 keywords for ESG controversies. 'Gapjil' records the highest frequency, followed by 'corruption', 'bribery', and 'collusion'. Out of the 26 keywords, 16 are related to governance, 8 to social, and 2 to environment. The keywords ranked high are mostly related to the responsibility of shareholders within corporate governance. ESG controversies associated with social issues are often related to unfair trade. As a result of confidence analysis, the keywords related to social and governance are clustered and the probability of mutual occurrence between keywords is high within each group. In particular, in the case of "owner's arrest", it is caused by "bribery" and "misappropriation" with an 80% confidence level. The result of network analysis shows that 'corruption' is located in the center, which is the most likely to occur alone, and is highly related to 'breach of duty', 'embezzlement', and 'bribery'.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.1
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• pp.33-43
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• 2013

The research on data mining that can manage a large amount of information efficiently has grown with the drastic increment of information. Privacy-preserving data mining can protect the privacy of data owners. There are several privacy-preserving association rule, clustering and classification protocols. A privacy-preserving association rule protocol is used to find association rules among data, which is often used for marketing. In this paper, we propose a privacy-preserving k-bits inner product protocol based on Shamir's secret sharing.

• Journal of the Korean Society of Safety
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• v.37 no.6
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• pp.40-49
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• 2022

Simple statistical frequency based analysis, such as Pareto analysis, are widely used in conventional accident analysis. However, due to the dynamic and complex nature of construction works, many factors can simultaneously affect or involve the occurrence of accidents in construction projects. Therefore, the identification of the complex relationship between such factors is important to establish relevant and effective safety management policies and/or programs. In this study, characteristic factors and their relationships' contribution to non-fatal accidents in construction projects are analyzed using the association rule mining (ARM) technique. To this end, a total of 59,202 construction accident data are collected from 2015 to 2019 and the ARM is performed to retrieve specific relationships -named as association rules-among classified factors in the data. Characteristics of the retrieved relationships are analyzed and compared with the results of conventional Pareto analysis. Based on the results, it is found that both fall and trip are notable accident forms having characteristic relations with other factors for non-fatal accidents in construction projects. It is also found that small-scale construction, age of 50s, less than 1 month of working period, and architectural construction are important factors for non-fatal accidents in construction projects.

• Asian review of World Histories
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• v.1 no.1
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• pp.45-84
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• 2013

Empirical research into Đại Việt before the $14^{th}$ century has made little progress since the 1990s. To improve this situation, I here examine how the L$\acute{y}$ dynasty (1009-1226), the first long-lasting dynasty of Đại Việt, established stable local ruleafter the "Tang-Song Transition" in China that changed the entire picture of East Asia (including both Southeast and Northeast Asia). This paper focuses on two issues. First are the local administrative units and their governors. The nature of both higher units like lộ(circuits), phủ and ch$\hat{a}$u (provinces), and basic units like hươg and gi$\acute{a}$p (districts?) will be examined. Second, I examine non-institutional channels of local rule by the imperial family. By combining such administrative and non-administrative means, the L$\acute{y}$ central court enforced a considerably stable local rule for two centuries. Finally, I attempt some preliminary comparisons with the local rule of Goryeo (918-1392) in the Korean peninsula, a polity that shared many features with Đại Việt in the process of localization of the Tang and Song models. I hope this approach of viewing small empires from the standpoint not of their "goal" (modern states) but of their "start" (charter polities), will enrich the discussion of East Asian small empires.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.22 no.2
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• pp.134-139
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• 2012

Objectives: This study was conducted to study the analytical variability of A & B counting rules in counting using a phase contrast microscope airborne fibers collected on filters in man-made mineral or vitreous fibers (MMMFs) industries. Methods: Fibers in filters were counted using A & B rules of NIOSH Method 7400. Intra-counter and inter-counter variations by fiber type and density were obtained. The types of MMMFs analyzed were glass wool fiber, rock wool fiber, slag wool fiber, and refractory ceramic fibers. The densities of fibers classified were <20 $fibers/mm^2,$ 20 - <50 $fibers/mm^2$, 50 - <100 $fibers/mm^2,$ and ${\geq}100$ $fibers/mm^2,$ respectively. Results: Intra-counter relative standard deviations by rule A were 0.084, 0.102, 0.071 for glass wool fibers, rock wool fibers and refractory ceramic fibers, and those by rule B were 0.139, 0.120 and 0.142, respectively. Inter-counter relative standard deviations by rule A were 0.281, 0.296, 0.180 for glass wool fibers, rock wool fibers and refractory ceramic fibers, and those by rule B were 0.396, 0.337 and 0.238, respectively. Conclusions: Intra-counter variation was not different significantly among fiber types (p>0.05), but B rule variation for ceramic fibers approximately 2 times greater than corresponding A rule estimates, and intra-counter and inter-counter variations were higher in the low fiber density.