• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.1-8
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• 2005

The consequences of rapid industrial advancement, diversified types of business and unexpected industrial accidents have caused a lot of damage to many unspecified persons both in a human way and a material way Although various previous studies have been analyzed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. The main objective of this study is to find an optimal algorithm for data analysis of industrial accidents and this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and AnswerTree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work chosen from 19,574 data related to construction industries during three years ($2002\sim2004$) in Korea.

• Korean Journal of Child Studies
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• v.31 no.2
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• pp.183-195
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• 2010

This study sought to investigate the environmental predictors of atopic dermatitis in children. The participants were 1050 (age 3-5) children taken from data data from the Ministry for Health, Welfare and Family Affairs. A data mining decision tree model revealed that the factors of medical neglect, breakfast, attachment to mother, and mother's depression influenced atopic dermatitis in children. Our results revealed that in the factors considered above, medical neglect had the greatest influence upon atopic dermatitis in children.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.1
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• pp.130-145
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• 2007

Background and purpose: The purpose of this study is to search recognition patients in Eight constitution Oriental Medical Clinic. And we compare Eight constitution acupuncture methods with the another acupuncture methods. Methods: The subjects were comprised of 200 volunteers. In 3 Eight constitution Oriental Medical Clinic participants were chosen through questionnaire. Finishing answer participants put in their lacked name questionnaire to gathering box. DecisionTree (AnswerTree 3.0 Ver.) statistical software was used for statistical analysis. Results and Conclusion: As a result of the analysis of cognition to Eight constitution acupuncture methods was influenced to patients health, dietetic therapy is best influenced. Next influenced acupuncture reflex degree, age, job, constitution, cure periods, sex distinction, cure degree, diagnosed participant's Constitution by pulse diagnosis in 8 Constitution Medicine.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.595-601
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• 2014

With the advent of the Smart information-communication era, the number of data has increased exponentially. Accordingly, figuring out and analyzing in which area and circumstance the data has been created becomes one of the factors for prompt actions. In this paper identifies how to analyze the data by implementing a route from the lowest module to highest one in an inverse order for the part judgement for the particular data. The script first identifies cluster analisys, paralizes the analysis using the sum of each factors of the cluster with the tree structure, and finally transpose the answer into number. Also, it is designed to place priority on particular answer, thereafter, draws the wanted answer real-time.

• The Korean Journal of Emergency Medical Services
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• v.15 no.3
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• pp.57-70
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• 2011

Purpose : The purpose of this study was to reveal some factors of ROSC & survival for cardiac arrests from sport & leisure activities(CASLs). Methods : A retrospective study of the 1,341 out of hospital cardiac arrests(OHCAs) treated by EMS in Gyeonggi Provincial Fire and Disaster Headquarters from January to December in 2008 was conducted. The primary end-point was admission to emergency room. To clarify the factors through comparison of CASLs(n=58) with ROSCs & survivals(n=58), Answer Tree analysis for data mining with the CHAID algorithm was performed and alpha was set at .05. Mean, median, and percentile of time intervals, distances, and age on the 58 CASLs, 75 ROSCs, and 27 survivals(patients admitted to emergency room) were analysed. Results : Fourteen CASLs(24.1%), 41 ROSCs(54.7%), 16 survivals(59.3%) were treated with CPR within 5 min., and only 2 CASLs(3.4%), 11 ROSCs(14.7%), 10 survivals(37.0%) were treated with defilbrillation within 10 min. from arrest. If time recording from arrest to defilbrillation, the patients were classified 81.0%($X^2=9.83$, p=.005) into ROSCs & survivals. And the patients with no history, 100.0%($X^2=5.44$, p=.020). The other patients with no intention, 87.5%($X^2=7.00$, p=.024). Whereas the other patients with intention, treated with CPR after 4 min. from arrest were classified 67.2%($X^2=3.99$, p=.046) into CASLs. Conclusion : CPR within 4 minutes was the most important factor that discriminates between CASLs and ROSCs & survivals to record cardiac arrests-defilbrillation time. CPR within 4 min. from arrest, no history, and no intention were factors for improved ROSC & survival.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.59-67
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• 2005

The main objective of the statistical analysis about industrial accidents is to find out what is the dangerous factor in its own industrial field so that it is possible to prevent or decrease the number of the possible accidents by educating those who work in the fields for safety tools. However, so far, there is no technique of quantitative evaluation on danger. Almost all previous researches as to industrial accidents have only relied on the frequency analysis such as the analysis of the constituent ratio on accidents. As an application of data mining technique, this paper presents analysis on the efficiency of the CHAID algorithm to classify types of industrial accidents data and thereby identifies potential weak points in accident risk grouping.

• Journal of the Korea Safety Management & Science
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• v.8 no.1
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• pp.53-64
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• 2006

Many researches and analyses have been focused on industrial accidents in order to predict and reduce them. As a similar endeavor, this paper is to develop an expert system for prevention of industrial accidents. Although various previous studies have been performed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. As an initial step for the purpose of this study, this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and Answer Tree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work was chosen from 10,536 data related to manufacturing industries during three years$(2002\sim2004)$ in korea. The initial sample includes a range of different businesses including the construction and manufacturing industries, which are typically vulnerable to industrial accidents.

• IE interfaces
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• v.22 no.3
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• pp.278-286
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• 2009

The anti-collision algorithms to identify a number of tags in real-time in RFID systems are divided into the anti-collision algorithms based on the Framed slotted ALOHA that randomly select multiple slots to identify the tags, and the anti-collision algorithms based on the Tree-based algorithm that repeat the questions and answer process to identify the tags. In the hybrid algorithm which is combined the advantages of these algorithms, tags are distributed over the frames by selecting one frame among them and then identified by using the Query tree frame by frame. In this hybrid algorithm, however, the time of identifying all tags may increase if many tags are concentrated in a few frames. In this study, to improve the performance of the hybrid algorithm, we suggest an improved algorithm that the tags select a specific group of frames based on the earlier bits of the tag ID so that the tags are distribute equally over the frames. By using the simulation and mathematical analysis, we show that the suggested algorithm outperforms traditional hybrid algorithm from the viewpoint of the number of queries per frame and the time of identifying all tags.

• Journal of the Korea Safety Management & Science
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• v.7 no.4
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• pp.61-71
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• 2005

Many researches have been focused on the analysis of industry disasters in order to reduce them. As a similar endeavor, this paper provides a propensity analysis of injured people from various industries using classification and regression tree(CART), a data mining algorithm. The sample for this work was chosen from 25,157data related to various industries during one year ( $2003.2\sim2004.1$ ) at Kangwon-Do in Korea. For the purpose of this paper, eight independent variables (injured date, injured time, injured month, type of Injured person, continuous service period, sex, company size, age)are taken from injured person group. According to the analysis result, it is found that five out of the eight factors that are predicted as significant have salient effects. Factors of season, time/hour, day of the week, or month which disasters happened do not show any significant effect. This paper provides common features of injured people. The provided analysis result will be helpful as a starting point for root cause analysis and reduction of industry disasters and also for development of a guideline of safety management.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.993-1003
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• 2012

The purpose of this study was to estimate the determinants of victory and defeat through analyzing records of Korean men pro-basketball. Statistical models of victory and defeat were established by collecting present basketball records (2010-2011, 2011-2012 season). Korea Basketball League (KBL) informs records of every pro-basketball game data. The six offence variables (2P%, 3P%, FT%, OR, AS, TO), and the four defense variables (DR, ST, GD, BS) were used in this study. PASW program was used for logistic regression and Answer Tree program was used for the decision tree. All significance levels were set at .05. Major results were as follows. In the logistic regression, 2P%, 3P%, and TO were three offense variables significantly affecting victory and defeat, and DR, ST, and BS were three significant defense variables. Offensive variables 2P%, 3P%, TO, and AS are used in constructing the decision tree. The highest percentage of victory was 80.85% when 2P% was in 51%-58%, 3P% was more than 31 percent, and TO was less than 11 times. In the decision tree of the defence variables, the highest percentage of victory was 94.12% when DR was more than 24, ST was more than six, and BS was more than two times.