• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.415-423
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• 2022

Economic evaluations in the healthcare are used to assess economic efficiency of pharmaceuticals and medical interventions such as diagnoses and medical procedures. This study introduces the main concepts of economic evaluation across its key steps: planning, outcome and cost calculation, modeling, cost-effectiveness results, uncertainty analysis, and decision-making. When planning an economic evaluation, we determine the study population, intervention, comparators, perspectives, time horizon, discount rates, and type of economic evaluation. In healthcare economic evaluations, outcomes include changes in mortality, the survival rate, life years, and quality-adjusted life years, while costs include medical, non-medical, and productivity costs. Model-based economic evaluations, including decision tree and Markov models, are mainly used to calculate the total costs and total effects. In cost-effectiveness or costutility analyses, cost-effectiveness is evaluated using the incremental cost-effectiveness ratio, which is the additional cost per one additional unit of effectiveness gained by an intervention compared with a comparator. All outcomes have uncertainties owing to limited evidence, diverse methodologies, and unexplained variation. Thus, researchers should review these uncertainties and confirm their robustness. We hope to contribute to the establishment and dissemination of economic evaluation methodologies that reflect Korean clinical and research environment and ultimately improve the rationality of healthcare policies.

• Journal of Environmental Health Sciences
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• v.44 no.3
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• pp.217-226
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• 2018

Objectives: Despite the positive effects of Off-site risk assessment (ORA) system such as prevention of chemical accidents, some problems have been constantly raised. The purpose of this study is to analyze the problems that have occurred through the implementation of the ORA system for the past three years and to suggest reasonable directions for improvement in the future. Methods: In order to identify the problems with the methodology and procedure of ORA system, we analyzed statutes, administrative rules and documents related to the ORA system. A survey of ORA reviewers in National Institute of Chemical Safety was conducted to investigate the weight of determinants considered when judging the level of total risk in ORA. Results: In this study, we found out the uncertainty of the estimation of the number of people in the impact range in the procedure of the risk assessment of individual handling facilities, the lack of quantitative risk analysis methods for environmental receptors, and the ambiguity of the criteria for the total risk. In addition to suggesting solutions to the problems mentioned above, we also, suggested a decision tree for total risk in ORA. Conclusion: We anticipate that the solutions including the systematic decision tree for total risk suggested will contribute to the smooth operation of the ORA system.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.67-77
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• 2018

Currently, there are many problems due to the decline in school-age population. Moreover, Korea has the largest number of universities compared to the population, and the university enrollment rate is also the highest in the world. As a result, the minimum student retention rate required for the survival of each university is becoming increasingly important. The purpose of this study was to examine the effects of reducing the number of graduates of education and the social climate that prioritizes employment. And to determine what the basic direction is for students to manage the student retention rate, which can be maintained from admission to graduation, to determine the optimal input variables, Based on the input parameters, we will make associative analysis using apriori algorithm to collect training data that is most suitable for maintenance rate management and make base data for development of the most efficient Deep Learning module based on it. The accuracy of Deep Learning was 75%, which is a measure of graduation using decision trees. In decision tree, factors that determine whether to graduate are graduated from general high school and students who are female and high in residence in urban area have high probability of graduation. As a result, the Deep Learning module developed rather than the decision tree was identified as a model for evaluating the graduation of students more efficiently.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.77-84
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• 2014

The purpose of this research is to identify and develop technology protection plans for small and medium-sized enterprises (SMEs) by analyzing past technology leakage patterns which were experienced by SMEs. We identified factors which affect the technology leakage, and analyzed patterns of the influences using a data mining algorithms. A decision tree analysis showed several significant factors which lead to technology leakage, so we conclude that preemptive actions must be put in place for prevention. We expect that this research will contribute to determining the priority of activities necessary to prevent technology leakage accidents in Korean SMEs. We expect that this research will help SMEs to determine the priority of preemptive actions necessary to prevent technology leakage accidents within their respective companies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.231-234
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• 2007

광고는 우리 생활 속에 많은 영향을 끼친다. 광고는 다양한 분야에서 활용되고 있으며, 새로운 기술과 사회문화 전반을 반영하기 때문에 다양한 정보와 지식을 필요로 한다. 광고 제작자는 다양한 광고 수용자 층을 포괄하기 위해 다채로운 전달 매체와 기법 등을 이용하여 광고 크리에이티브(광고 제작을 위한 아이디어) 전략을 수립하게 된다. 이를 바탕으로 광고 메시지의 효과적인 전달을 위하여 크리에이티브 컨셉(광고의 주요 소재, 테마)을 세우게 되는데, 이 때 주목하는 점은 독창적이고 영향력이 있는 아이디어야 한다는 것이다. 광고는 대중매체를 통해 전달되므로 목표 수용자의 크기는 쉽게 예상할 수는 있다. 하지만 제작의 과정은 복잡하고 창의적인 방향을 지향하므로 수용자를 고려하였다고 하더라도 어떤 반응을 일으키는지 예측하는 것은 어렵다. 본 논문에서는 이미 매체를 통해 전달된 광고들을 광고의 제작과정에서 사용되는 요소 중에서 수용자들이 평가 가능한 기준을 설정해 수용자들의 반응을 수집, 수치화하여 결정트리에 적용하였다. 이률 이용하여 새로이 제작되는 광고가 수용자에게 어떤 반응을 불러일으킬지 판단하는 시스템을 설계하였다.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.185-192
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• 2005

There are many data mining techniques such as association rule, decision tree, neural network analysis, clustering, genetic algorithm, bayesian network, memory-based reasoning, etc. We analyze 2003 Gyeongnam social indicator survey data using k-means clustering technique for environmental information. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. In this paper, we used k-means clustering of several clustering techniques. The k-means clustering is classified as a partitional clustering method. We can apply k-means clustering outputs to environmental preservation and environmental improvement.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.7
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• pp.13-22
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• 2005

Main purpose of this article is to classify reservoirs corresponding to their physical characteristics, for example, dam height, dam width, age, repair-works history. First of all, data set of 13,976 reservoirs was analyzed using k means and self organized maps. As a result of these analysis, lots of reservoirs have been classified into four clusters. Factors and their critical values to classify the reservoirs into four groups have been founded by generating a decision tree. The path rules to each group seem reasonable since their survivor function showed unique pattern.

• Proceedings of the Technology Innovation Conference
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• 2005.08a
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• pp.113-137
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• 2005

본 연구는 각 프로세스가 조직에 미치는 상대적 영향을 고려한 조직 전체의 효율성을 평가하고, 조직의 효율성을 개선하기 위하여 조직을 구성하는 여러 프로세스 중에서 어떤 프로세스를 우선적으로 개선해야 하는지를 결정하며, 더 나아가 비효율적인 프로세스를 개선하기 위하여 어떤 프로세스를 벤치마킹해야 하는지를 결정할 수 있는 체계적인 방법을 제공한다. 이를 위하여 본 연구는 다음과 같은 중요한 세 가지 과정을 따른다. 첫째, DEA(data envelopment analysis)의 CCR 모형을 이용하여 프로세스의 투입요소와 산출 요소를 바탕으로 개별 프로세스의 효율성을 평가한다. 둘째, 도출된 개별프로세스의 효율성을 Lovell과 Pastor의 순수 산출요소(또는 투입요소) DEA 모형의 산출요소로 이용하여 서비스 단위 조직 전체의 효율성을 평가한다. 셋째, 앞서 도출된 개별프로세스의 효율성과 서비스 단위 조직의 전체 효율성을 각각 DT(decision tree)의 예측변수와 목표변수로 활용하여 각 서비스 단위 조직의 특성 및 상황에 따라 개선해야 할 프로세스를 선택하는 규칙을 생성한다. 제안한 방법을 통하여 기업은 비효율적 조직과 프로세스를 발견하고 조직의 효율성을 개선하기 위하여 어떤 프로세스를 우선적으로 개선해야 하는지를 결정할 수 있다. 이를 통하여 기업은 오늘날 기업 경쟁력의 핵심인 프로세스를 좀 더 효과적으로 평가 및 관리할 수 있을 것으로 기대된다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.857-862
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• 2017

The management of the electric power facilities became important in accordance with the industrial development and electric power facilities were influenced by weather. Even if the same kind of electric power facilities is estimated for extracting the time-varying failure rate, the failure rate could be different depending on external effect such as climate. This research will show the data mining modeling of the weather-related outage and influence of weather on the electric power facility with recent data.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.141-149
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• 1998

One of the difficulties in using the current Boolean-based information retrieval systems is that it is hard for a user, especially a novice, to formulate an effective Boolean query. One solution to this problem is to let the system formulate a query for a user from his relevance feedback documents in this research, an intelligent query reformulation mechanism based on ID3 is proposed and the sensitivity of its retrieval effectiveness, i.e., recall, precision, and E-measure, to various input settings is analyzed. The parameters in the input settings is the number of relevant documents. Experiments conducted on the test set of Medlars revealed that the effectiveness of the proposed system is in fact sensitive to the number of the initial relevant documents. The case with two or more initial relevant documents outperformed the case with one initial relevant document with statistical significances. It is our conclusion that formulation of an effective query in the proposed system requires at least two relevant documents in its initial input set.