• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.5
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• pp.86-92
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• 1999

Effluent concentration estimation equations for wetland system were developed throught statistical analysis of treatment wetland experimental data. Existin g empirical equations were reviewed for thier accuracy with experimental data, and compared with the estimatin equations. About 70 experimental data sets were used for multiple regression, and variables include influent concentration, hydraulic loading rate, average daily air temperature , and plant coverage. The estimatin equations developed for BOD5 , SS ,T-P, and T-N predicted effluent concentrations moderately well, and coefficient fo determination ($R^2$) for them was 0.74 , 0.60, 0.59 and 0.58 respectively. The equations obtained from same data but excluding plant coverage showed relatively lower $R^2$ than the former case, and it was 0.66, 0.52, 0.41 and 0.57 respectively. The EPA, WPCF , and Kadlec and Knight equations worked poorly and $R^2$ for them was significantly lower than the estimation equation developed in the study. The reason might be that the existing equations were oversimplified that they did ot include important parameters such as air temperature and plant coverage. Therefore, developing reasonable estimation equations from experiment under realistic condition is highly recommended rather than using exiting estimation equations.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.19-25
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• 2019

This study was attempted to identify the convergence factors that affected the gambling abstinence self-efficacy among college students using gambling. The participants were 134 students with gambling experience at two universities in C city and G city. The results of this study are as follows. Stress(r=-.314, p<.001) and gambling change motivation(r=.272, p=.001) showed a significant correlation with gambling abstinence self-efficacy in correlation analysis. The greatest influence on gambling abstinence self-efficacy in multiple regression analysis was identified in order of stress(${\beta}=-.29$, p<.001), gambling change motivation (${\beta}=.25$, p=.003). The results of this study suggest that a gambling prevention education program which can manage stress and strengthen the gambling change motivation of college students using gambling is needed to improve the gambling abstinence self-efficacy.

• Journal of Families and Better Life
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• v.9 no.1 s.17
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• pp.179-186
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• 1991

본 연구는 미국 Utah주의 Logan시에 있는 유타주립대하(USU)Credit Union의 멤버들을 대상으로, 신용사용과 신용에 대한 태도가 그들의 경제적 만족도와 어느정도 관련이 있는지를 조사하였다. 연구는 1989년 3월에서 5월까지 걸쳐 USU Credit Union의 지원으로 이루어졌으며, 자료는 21세에서 65세까지의 멤버들 중 500명을 임의 추출하여 설문지 조사를 실시하여(설문지는 본 연구를 위한 문항과 Credit Union 멤버 Survey문항이 함께 이루어졌다) 그중 274명(54.8%)으 답변이 자료분석에 사용되었다. 대부분의 사람들은 집이나 차, 또는 교육비, 의료비에 신용을 사용하는데 긍정적 태도를 보였으며, 반수 이상의 사람들이 신용을 사용함으로써 수수료 또는 이자를 지불하고 있었다. 월평균 신용 납부액은 $643이였으며, 반수 이상의 응답자가 그들의 신용차입액에 대해 걱정하고 있는 반면, 4.4%의 응답자만이 신용을 사용하지 않고 있다고 대답했다. t-테스트, 변량분석, 그리고 상관관계 분석에 의해 경제적 만족도와 의미있는 관계를 가지고 있는 요인들이 단계별 다중 희귀분석에 이용되었는데, 그 결과 사람들의 신용부담액에 대한 근심도가 그 어느것보다도 경제적 만족도와 강하게 연관되어 있는 것으로 나타났다. 이는 과거의 조사들이 가정의 빚, 즉 신용부담액과 수입에 대한 비율로써 가정의 경제적 만족정도(financial well-being)를 측정해온 것에 반한 사실로서, 경제적 만족도는 개인의 주관적 측정인 신용부담액에 대한 근심도와 큰 관련이 있음을 보여주었다.

• 한국노년학
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• v.28 no.4
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• pp.887-905
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• 2008

This study investigated the effects of education for the elderly on their psychological well-being. Loneliness(negative state of emotion) and life satisfaction(positive state of emotion) were compared between participants and non-participants of educational programs for the elderly in order to learn whether participating educational programs influences their psychological well-being. The subjects of this research were 288(146 participants and 142 non participants) elderly who are 60 years and older, living in Seoul City and Gyeong Gi Do. They were selected by the judgmental sampling method and surveyed using structured questionnaire. Research instruments were consisted of the UCLA Loneliness Scale, Life Satisfaction Index-Z Scale(LSIZ) and several background questions. The result showed that the participants of the educational programs had a lower level of loneliness and a higher level of life satisfaction. The educational program for the elderly was effective for the psychological well-being of the aged. Multiple regression results showed that subjective health played the most important role in explaining the loneliness, followed by education level, elderly education participation, financial states. The results also showed that subjective health played the most important role in explaining the life satisfaction, followed by elderly education participation, religious activity participation, financial status. Implications for policy, practice, and further research were discussed.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.53-58
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• 2018

The study was done to compare quality of life by family therapy, self-esteem f teem insight factors which explain quality of life in individuals with schizophrenic patients. A questionnaire survey was conducted with 125 schizophrenia people in C region. The data were analyzed by SPSSWIN 21.0, t-test, ANOVA and Pearson correlation coefficient calculation and multiple regression analysis. The results were as follows. Impact quality of life of clients showed significant difference by religion, support team(p<.05). Quality of life were positively correleated with self-esteem and family support. Multiple regression analysis showed that 49.5% of the self esteem, insight, family support showed the quality of life. Development of programs for strengthening family support and self esteem is required for proper quality of life.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.11-17
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• 2018

This study was conducted to analyze the factor of suicide ideation in the elderly living alone. This study is a descriptive research study of 175 elderly living alone in K&C region. It is a frequency analysis, correlation analysis, simple rare analysis. AMOS statistics were performed. Data collection was from January 2017 to March 2017. The results of this study are as follows. social activity (r=-.106, p<.05), subjective health status (r=-.292, p<.01) Self-esteem (r=-.069, p<.05), mind control(r=-.201, p<.01), and depression(r=.023, p<.01), stress (r=.320, p<.05). Suicidal influence factor 43.5% explanatory power. In order to prevent the suicide of the elderly living alone, It will be necessary to seek active nursing intervention to help prevent suicide.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.665-668
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• 2006

After foreign exchange trouble, Korean government became effective an economy-invigorating policy that to raise the housing demand and transaction. In result, the rate economic growth kept up a high growth rate and the market recovered. But an economy-invigorating policy of continuance caused an excessive boom of housing market in the second half of 2001. Therefore Korean government enforced a speculation-restraint policy. But it caused a instability of economics. This study is to analyze the effect between the housing policy and the housing cost and is to apply the basis data of the next housing policy.

• Korea journal of population studies
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• v.15 no.2
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• pp.104-124
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• 1992

형제수, 출산순위, 출산터울, 모성의 출산시 연령 등 가족형성 양상은 아동의 신체적 발육 성장 및 지능발달과 강한 관련성을 보여 왔음이 세계 여러나라 아동을 대상으로 수행된 연구에서 보고되었다. 본 연구는 형제수와 출산순위, 그리고 출산시 모성의 연령은 아동의 신체적 지능적 발달과는 역상관관계를, 출산터울의 길이는 순상관관계를 나타낼 것이라는 가설을 증명하고자 1984년 한국중학생 1,2,3학년 약 46,000명을 대상으로 수행되었다. 지역별 그리고 사회경제적 상태별 비교를 위하여 서울시 고소득층이 주로 거주하는 학구내의 중학교와 저소득층이 거주하는 학구내 중학교 각각 5개를 선정하고 강원도내 전형적 농촌의 중학교 12개를 선정하여 신장, 체중, 좌고, 혈구용적 지능지수를 측정하였다. 이들 측정치들의 평균은 학부모와 담임선생님의 도움으로 작성된 가족형성 변수별로 비교되었으며 다중 희귀분석과 부분상관분석으로 연관성의 통계적 유의성을 검정하였다. 동일연령의 신체적 발육성장 지표들은 도시의 고소득지역 아동들이 가장 우수했으며 다음이 도시저소득 지역 아동이었고 농촌아동이 가장 빈약하였다. 남녀별 신체적 발육지표들의 차이는 연령이 많을수록 더 현저했으며 연령별 지역별 차이는 남학생에게서 더 두드러졌다. 평균 지능지수는 도시고소득지역 남학생들이 월등히 높아 114.8인데 비해 도시저소득지역 남학생들은 106.1, 그리고 농촌 남학생들은 105.3이었다. 남학생보다는 여학생의 지능지수가 낮았는데 이것은 대만 아동들도 여학생이 모든 연령에서 남학생보다 낮았다는 보고와 일치하였다. 한편 도시저소득지역과 농총지역 학생들은 남녀모두 평균지능지수가 비슷하였다. 가족형성변수들은 혼란변수들은 모든 제어했을 경우에도 아동들의 신체적 지능적 발달에 독립적으로 영향을 미쳤다. 발육지표중에 지능지수와 형제수가 가장 가족형성 변수들과의 연관성이 강했다.