• Title/Summary/Keyword: Panel Decision

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A Study on Improving Classification Performance for Manufacturing Process Data with Multicollinearity and Imbalanced Distribution (다중공선성과 불균형분포를 가지는 공정데이터의 분류 성능 향상에 관한 연구)

  • Lee, Chae Jin;Park, Cheong-Sool;Kim, Jun Seok;Baek, Jun-Geol
    • Journal of Korean Institute of Industrial Engineers
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    • v.41 no.1
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    • pp.25-33
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    • 2015
  • From the viewpoint of applications to manufacturing, data mining is a useful method to find the meaningful knowledge or information about states of processes. But the data from manufacturing processes usually have two characteristics which are multicollinearity and imbalance distribution of data. Two characteristics are main causes which make bias to classification rules and select wrong variables as important variables. In the paper, we propose a new data mining procedure to solve the problem. First, to determine candidate variables, we propose the multiple hypothesis test. Second, to make unbiased classification rules, we propose the decision tree learning method with different weights for each category of quality variable. The experimental result with a real PDP (Plasma display panel) manufacturing data shows that the proposed procedure can make better information than other data mining procedures.

Longitudinal Study on the Major Factors Affecting Divorce Choices among Women: Focused on Survival Analysis (여성의 이혼선택 요인에 관한 종단 연구: 생존분석을 중심으로)

  • Park, Su Sun;Park, Tai Young
    • Journal of Family Resource Management and Policy Review
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    • v.26 no.3
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    • pp.65-85
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    • 2022
  • This study aims to contribute to social work practice in understanding marriage and divorce as transitions and in helping women make meaningful decisions on whether to stay or leave the marriage by examining the factors that impact women's divorce decision making over time. This is a longitudinal study that used survival analysis by Korean Longitudinal Survey of Women and Families' panel data. Finally, cox regression analysis was used to evaluate the impact of each factor on divorce decision making, and accordingly, all regression models were appropriate for analysis.

Forecasting performance and determinants of household expenditure on fruits and vegetables using an artificial neural network model

  • Kim, Kyoung Jin;Mun, Hong Sung;Chang, Jae Bong
    • Korean Journal of Agricultural Science
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    • v.47 no.4
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    • pp.769-782
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    • 2020
  • Interest in fruit and vegetables has increased due to changes in consumer consumption patterns, socioeconomic status, and family structure. This study determined the factors influencing the demand for fruit and vegetables (strawberries, paprika, tomatoes and cherry tomatoes) using a panel of Rural Development Administration household-level purchases from 2010 to 2018 and compared the ability to the prediction performance. An artificial neural network model was constructed, linking household characteristics with final food expenditure. Comparing the analysis results of the artificial neural network with the results of the panel model showed that the artificial neural network accurately predicted the pattern of the consumer panel data rather than the fixed effect model. In addition, the prediction for strawberries was found to be heavily affected by the number of families, retail places and income, while the prediction for paprika was largely affected by income, age and retail conditions. In the case of the prediction for tomatoes, they were greatly affected by age, income and place of purchase, and the prediction for cherry tomatoes was found to be affected by age, number of families and retail conditions. Therefore, a more accurate analysis of the consumer consumption pattern was possible through the artificial neural network model, which could be used as basic data for decision making.

Mandatory Retirement and the Determinant of Aged Workers' Retirement (정년제도와 중고령자 은퇴결정요인 분석)

  • Cho, Donghun
    • Journal of Labour Economics
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    • v.37 no.3
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    • pp.101-122
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    • 2014
  • This paper empirically estimates the decision of aged workers related to the retirement decision. Using the supplemental survey for aged people of the Korean panel data set, the paper analyses the correlation between the retirement decision of middle-aged people (aged 50 years or older) and personal characteristics and job characteristics of main jobs that aged people had worked, particularly focusing on the mandatory job retirement regulation and its regulation of retirement ages. The empirical results show that the regulated retirement age is more important than the existence of mandatory retirement system in related to the workers' retirement decision.

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What Influences Decision on Seasoned Equity Offerings of Listed Vietnamese Companies?

  • LE, Long Hau;NGUYEN, Thi Binh Nhi;PHAM, Xuan Quynh;VUONG, Quoc Duy;LE, Tan Nghiem
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.5
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    • pp.1-7
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    • 2020
  • This paper investigates the determinants on decision to conduct seasoned equity offerings (SEOs) of listed companies on the Ho Chi Minh Stock Exchange in Vietnam. Seasoned equity offerings (SEOs) are defined as the issue of more stocks by a firm to raise more capital after a primary issue. Using panel data collected from audited financial statements of 99 listed companies on the Ho Chi Minh Stock Exchange during 2014-2018, the study employs a logit regression model by fixed effects method to examine factors that affect the decision to implement seasoned equity offerings of those companies. The findings of this study show that profit, revenue growth and company's size have a positively significant impact on the decision, while dividend pay-out ratio negatively significantly influences the equity issuing decision. Furthermore, these results are robust after controlling for the forms of equity offerings, i.e. bonus stocks, stock dividends and rights to buy shares. These findings are consistent with economic theories such as agency theory, pecking order theory, and growth opportunity theory, and also could be explained by the real situations of the Vietnamese stock exchange. This study has important implications for corporate managers, policy makers and investors.

Development of the Preliminary Cost Estimate Method for the Free-Form Building Facade Trade in Conjunction with the Panel Optimization Algorithm Process (곡면 최적화 알고리즘을 활용한 비정형 건축물 외장공사비 개산견적에 관한 연구)

  • Lim, Jang Sik;Ock, Jong Ho
    • Korean Journal of Construction Engineering and Management
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    • v.15 no.4
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    • pp.95-106
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    • 2014
  • The outer surfaces of free form buildings contain panels with two-directional curvatures. To construct these panels, complex geometric surfaces should be divided into forms and sizes that can be manufactured and constructed efficiently. Because the bigger the curvatures of these panel, the more expensive the construction costs, these complex curvatures should go through optimal process of reinterpretation to minimize the curved surfaces with complex two-directional curvatures, which is called panel optimization. Small construction and design companies have trouble in calculating even rough estimate and cannot adjust expected construction cost of the panels based on comparison of design alternatives in conjunction with panel optimization process due to lack of knowledge and experience. This study conducts the research that can support designers' cost decision-making in the design stage of the free form buildings with respect to the panel optimization process. A 3D commercial application specialized to modeling free form shapes is used for the purpose.

Finding factors on employment by adult life cycle using decision tree model (의사결정나무모형을 사용한 성인 생애주기별 취업 영향요인 분석)

  • Kwak, Minjung;Rhee, Sung-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.6
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    • pp.1537-1545
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    • 2016
  • Due to global economy recession with low oil price, Korea has stepped into a stage of sluggish development, and the unemployment has become a major issue. Hence, we study various risk factors influencing on unemployment using the Korean labor and income panel data of 2014. We first divide the adult life cycle into three categories, such as young adult, adult, and old adult. Then we consider demographic variables, occupational variables and health related variables as risk factors. The decision tree models have shown that education and gender are the most important factors respectively in young adult group and in adult group. Gender, health status, and education are influential factors in old adult group.

The Effects of Achievement Motivation on Career Decision of Multicultural Adolescents: Sequential Mediating Effects of Social Withdrawal and Depression (다문화 청소년의 성취동기가 진로결정성에 미치는 영향 : 사회적 위축과 우울의 순차적 매개효과)

  • Park, Dong-Jin;Kim, Song-Mi
    • Journal of Convergence for Information Technology
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    • v.11 no.8
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    • pp.100-108
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    • 2021
  • The purpose of this study is to examine the sequential mediating effects of social withdrawal and depression in the relationship between achievement motivation and career decision of multicultural adolescents. To this end, we analyzed adolescents data from the 8th year survey(2018) of the 'Multicultural Adolescent Panel Study(MAPS)' provided by the National Youth Policy Institute(NYPI). As a result of the study, first, achievement motivation was found to have a significant and positive effect on career decision. Second, it was found that social withdrawal did not mediate the relationship between achievement motivation and career decision. Third, it was found that depression mediates the relationship between achievement motivation and career decision. Fourth, it was found that social withdrawal and depression sequentially mediate the relationship between achievement motivation and career decision. Based on the results of this study, we searched for social support measures to improve the career decision of multicultural adolescents and support their career paths, and suggested implications and limitations of the results of this study and suggestions for follow-up studies.

A Comparative Study of Predictive Factors for Hypertension using Logistic Regression Analysis and Decision Tree Analysis

  • SoHyun Kim;SungHyoun Cho
    • Physical Therapy Rehabilitation Science
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    • v.12 no.2
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    • pp.80-91
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    • 2023
  • Objective: The purpose of this study is to identify factors that affect the incidence of hypertension using logistic regression and decision tree analysis, and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 9,859 subjects from the Korean health panel annual 2019 data provided by the Korea Institute for Health and Social Affairs and National Health Insurance Service. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In logistic regression analysis, those who were 60 years of age or older (Odds ratio, OR=68.801, p<0.001), those who were divorced/widowhood/separated (OR=1.377, p<0.001), those who graduated from middle school or younger (OR=1, reference), those who did not walk at all (OR=1, reference), those who were obese (OR=5.109, p<0.001), and those who had poor subjective health status (OR=2.163, p<0.001) were more likely to develop hypertension. In the decision tree, those over 60 years of age, overweight or obese, and those who graduated from middle school or younger had the highest probability of developing hypertension at 83.3%. Logistic regression analysis showed a specificity of 85.3% and sensitivity of 47.9%; while decision tree analysis showed a specificity of 81.9% and sensitivity of 52.9%. In classification accuracy, logistic regression and decision tree analysis showed 73.6% and 72.6% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. It is thought that both analysis methods can be used as useful data for constructing a predictive model for hypertension.

Paired analysis of tumor mutation burden calculated by targeted deep sequencing panel and whole exome sequencing in non-small cell lung cancer

  • Park, Sehhoon;Lee, Chung;Ku, Bo Mi;Kim, Minjae;Park, Woong-Yang;Kim, Nayoung K.D.;Ahn, Myung-Ju
    • BMB Reports
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    • v.54 no.7
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    • pp.386-391
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    • 2021
  • Owing to rapid advancements in NGS (next generation sequencing), genomic alteration is now considered an essential predictive biomarkers that impact the treatment decision in many cases of cancer. Among the various predictive biomarkers, tumor mutation burden (TMB) was identified by NGS and was considered to be useful in predicting a clinical response in cancer cases treated by immunotherapy. In this study, we directly compared the lab-developed-test (LDT) results by target sequencing panel, K-MASTER panel v3.0 and whole-exome sequencing (WES) to evaluate the concordance of TMB. As an initial step, the reference materials (n = 3) with known TMB status were used as an exploratory test. To validate and evaluate TMB, we used one hundred samples that were acquired from surgically resected tissues of non-small cell lung cancer (NSCLC) patients. The TMB of each sample was tested by using both LDT and WES methods, which extracted the DNA from samples at the same time. In addition, we evaluated the impact of capture region, which might lead to different values of TMB; the evaluation of capture region was based on the size of NGS and target sequencing panels. In this pilot study, TMB was evaluated by LDT and WES by using duplicated reference samples; the results of TMB showed high concordance rate (R2 = 0.887). This was also reflected in clinical samples (n = 100), which showed R2 of 0.71. The difference between the coding sequence ratio (3.49%) and the ratio of mutations (4.8%) indicated that the LDT panel identified a relatively higher number of mutations. It was feasible to calculate TMB with LDT panel, which can be useful in clinical practice. Furthermore, a customized approach must be developed for calculating TMB, which differs according to cancer types and specific clinical settings.