• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.827-833
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• 2020

In this paper, to reduce the unpaid rate of local governments, the internal data elements affecting the arrears in Water-INFOS are searched through interviews with meter readers in certain local governments. Candidate data affecting arrears from national statistical data were derived. The influence of the independent variable on the dependent variable was sampled by examining the disorder of the dependent variable in the data set called information gain. We also evaluated the higher prediction rates of decision tree and logistic regression using n-fold cross-validation. The results confirmed that the decision tree can find more accurate customer payment patterns than logistic regression. In the process of developing an analysis algorithm model using machine learning, the optimal values of two environmental variables, the minimum number of data and the maximum purity, which directly affect the complexity and accuracy of the decision tree, are derived to improve the accuracy of the algorithm.

• Industry Promotion Research
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• v.7 no.1
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• pp.1-8
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• 2022

We investigated various types of machine learning methods that can be applied to censored data. Exploratory data analysis reveals the distribution of each feature, relationships among features. Next, classification problem has been set up where the dependent variable is death_event while the rest of the features are independent variables. After applying various machine learning methods to the data, it has been found that just like many other reports from the artificial intelligence arena random forest performs better than logistic regression. But recently well performed artificial neural network and gradient boost do not perform as expected due to the lack of data. Finally Kaplan-Meier and Cox proportional hazard model have been employed to explore the relationship of the dependent variable (t_i, δ_i) with the independent variables. Also random forest which is used in machine learning has been applied to the survival analysis with censored data.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.115-125
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• 2022

This study examines the effect of performers on the number of views and likes of entertainment show clips consumed on AVOD short form platform. Multiple regression analysis was performed, setting program viewing factors and performer's topicality index as independent variables, and setting the number of views and likes of clips as dependent variables. As a result of the analysis, performer's topicality index had a positive(+) effect on both dependent variables. According to standardized coefficient, on the number of views, the standardization coefficient of the performer's topicality index was the second highest, and on the number of likes it was the highest among variables. The results suggest that performers contribute a lot to the success of clips on AVOD short form platform.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.75-83
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• 1995

본 연구는 12명의 컴퓨터 작업자를 대상으로 테이터 입력 방법과 소음 수준이 데이터 입력 작업 수행도에 미치는 영향을 분석하였다. 다른 형태의 Database Format 및 Interaction Technique을 갖는 3가지 데이터 입력 방법(Card Format/Keyvoard 입력, Card Format/Menu방식을 이용한 Mouse Click, Table Format/Keyboard 입력)과 소음의 2수준(60 .approx. 65dBA, 80 .approx. 85dBA)을 독립실험인자로 채택하였다. 에러 문제를 효율적으로 다루기 위해 에러 방지(error prevention)와 에러 관리(error management)의 두 가지 전략을 고려하여 두 가지 실험을 실시하였다. 실험 1에서는 에러를 효율적으로 예방할 수 있는 데이터 입력 방법 및 작업 환경을 알아보고자 데이터 입력작업 완료시간과 데이터 입력 시 발생하는 에러의 수를 종속변수로 측정하였으며, 실험 2에서는 에러의 효율적인 관리를 위한 데이터 입력 방법 및 작업 환경을 알아보고자 에러수정시간을 종속변수로하여 측정하였다. 통계분석결과, 높은 소음 수준하에서 에러수정시간이 많이 걸렸다. Form Fill-in 형식으로 입력하는 방법을 이용했을 경우 입력작업 완료시간이 적게 걸렸으며 Card format을 갖는 입력방식을 이용했을 때 적은 에러 수정시간을 나타내었다.

• Environmental and Resource Economics Review
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• v.5 no.2
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• pp.291-302
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• 1996

환경질 개선의 편익추정에 사용되는 헤도닉 가격모형에서 제1단계 헤도닉 함수 추정시 그 함수형태에 따라 결과가 편의를 가질 수 있다. 본 논문에서는 13가지의 각기 다른 비선형 및 선형 헤도닉 함수 등을 한국 주택시장에 적용하여 그 적합성을 이론 및 실증적 방법을 병행하여 검증하였다. 그 결과, 고전적으로 종속변수만을 변환시키는 Box-Cox 함수형태나 Box-Cox 변형계수가 사전적으로 0과 1사이에 있음을 가정하는 오목한(concave) 한 함수형태가 기존 연구와는 달리 한국시장에는 적합한 함수형태가 아니라는 결과를 이끌어 냈다. 나아가 서울 주택시장에 가장 적합한 함수형태는 종속 및 독립변수를 각각 다르게 변환시키는 헤도닉 함수형태임을 보여 주었다. 아울러 본 연구는 간접적으로 헤도닉 가격모형 적용시 그 지역의 주택시장 특성에 관한 연구가 선행되어야 함을 시사하고 있다.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.120-127
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• 1997

오늘날 자동차는 자동차 자체에 대한 기능적 측면뿐만 아니라 운전자 및 탑승자에게 적절한 거주 공간을 제공하여야 한다는 인간공학적 측면을 동시에 만족시켜야 한다. 특히 부적절한 거주 공간에서 비롯된 좋지 않은 운전 자세는 운전시 신체 각 부위에 과다한 피로를 유발시키고 운전 성능에도 영향 을 미칠 수 있기 때문에 안전 측면에서도 매우 중요하다. 거주 공간의 설계시 출발점이 되는 것은 SgRP(Seating Reference Point)이며 이의 설정은 운전 자세에 직접적인 영향을 미치므로 운전자의 불편도 (Discomfort)를 최소로 하며 운전성능을 높일 수 있도록 설정되어야한다. 본 연구에서는 Driving Simulator 를 이용하여 운전자가 취할 수 있는 Seat의 전후, 상하 위치에 따른 여러 운전 자세에서 운전자가 느끼는 불편도 및 각종 Control의 조작성등의 주관적인 Measure와 운전시의 운전성능을 나타내는 객관적 Measure를 측정, 평가하였다. Seat의 위치는 Whole Body Discomfort, Steering Wheel, Gear, Pedal의 조작성 등의 주관적 종속 변수에는 유의한 영향을 미치는 것으로 나타났으며, 객관적 종속변수에는 유의한 영향이 나타 나지 않았다. 실험 결과를 바탕으로 Regression식을 도출하였으며 이를 바탕으로 Isocomfort Surface를 제시 하였다. 본 연구의 결과는 한국인에 적합한 SgRP 및 Seat Track 설정의 자료로 활용될 수 있을 것으로 기대 된다.

• Journal for History of Mathematics
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• v.24 no.4
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• pp.97-118
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• 2011

This study aimed finding effective models for the teaching the concept of function. We selected two models. One is discrete model which focuses on the 'corresponding relation of the elements of the sets(domain and range). The other is continuous model which focuses on the dependent relationship of the two variables connected in variable phenomenon. A vending machine model was used as a discrete model, and a water bucket model was used as a continuous model in our study. We taught 2 times about the concept of function using two models to the 60 students (7th grade, 2 classes) living in Taebak city, and tested it twice, after class and about 3 months later. A vending machine model was helpful in understanding the definition of function in the 7th grade math textbook. Also, it was helpful to making concept image and to recalling it. On the other hand, students who used the water bucket model had a difficultly in understanding the all independent variables of the domain corresponding to the dependent variables. But they excelled in tasks making formula expression and understanding changing situations.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.366-370
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• 2013

Regression Analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variable and response variables. This paper introduce Theil's method to find a fuzzy regression model which explain the relationship between explanatory variable and response variables. Theil's method is a robust method which is not sensive to outliers. Theil's method use medians of rate of increment based on randomly chosen pairs of each components of ${\alpha}$-level sets of fuzzy data in order to estimate the coefficients of fuzzy regression model. We propose an example to show Theil's estimator is robust than the Least squares estimator.

• Korean Journal of Logic
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• v.22 no.1
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• pp.183-209
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• 2019

In this paper, I first examine Reiss'(2005) arguments for the causal instrumental variable. Second, I argue that the conditions for causal transitivity I consider meet what the causal instrumental variables and the interveners of the manipulation theory of causation are intended to hold. Reiss shows that two conditions for instrumental variables are not sufficient for causal significance of independent variables for dependent variables. Reiss articulates and reformulates the conditions for instrumental variables in terms of the conditions on causality, while naming his instrumental variables as causal instrumental variables. Reiss argues that the causal instrumental variables are similar to the interveners of the manipulation, or intervention theory of causation. He further argues that the causal instrumental variables do a better job the interveners do. I argue that the conditions for causal transitivity I consider meet the goal the conditions for the causal instrumental variables and the conditions for the interveners both are intended to achieve.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1561-1570
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• 1997

This study explores the treatment of the max-value cost function over a parameter interval in parametric optimization. To avoid the computational burden of the transformation treatment using an artificial variable, a direct treatment of the original max-value cost function is proposed. It is theoretically shown that the transformation treatment results in demanding an additional equality constraint of dual variables as a part of the Kuhn-Tucker necessary conditions. Also, it is demonstrated that the usability and feasibility conditions on the search direction of the transformation treatment retard convergence rate. To investigate numerical performances of both treatments, typical optimization algorithms in ADS are employed to solve a min-max steady-state response optimization. All the algorithm tested reveal that the suggested direct treatment is more efficient and stable than the transformation treatment. Also, the better performing of the direct treatment over the transformation treatment is clearly shown by constrasting the convergence paths in the design space of the sample problem. Six min-max transient response optimization problems are also solved by using both treatments, and the comparisons of the results confirm that the performances of the direct treatment is better than those of the tranformation treatment.