• Journal of the Korean Data and Information Science Society
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• 제19권3호
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• pp.967-977
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• 2008

We consider densities of quotient Y/X and ratio X/(X+Y), and estimation of reliability P(Y

• Journal of the Korean Data and Information Science Society
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• 제7권2호
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• pp.219-226
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• 1996

Basic objective in cluster analysis is to discover natural groupings of items or variables. In general, variable clustering was conducted based on some similarity measures between variables which have binary characteristics. We propose a variable clustering method when variables have more categories ordered in some sense. We also consider some measures of association as a similarity between variables. Numerical example is included.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.555-563
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• 2004

In classification and discrimination, we often face with incomplete group variable arising typically from many missing values and/or incredible cases. This paper suggests the use of K-means clustering for pre-adjusting incompleteness and in turn classification based on generalized statistical distance is performed. For illustrating the proposed procedure, simulation study is conducted comparatively with CART in data mining and traditional techniques which are ignoring incompleteness of group variable. Simulation study manifests that our methodology out-performs.

• 대한교통학회지
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• 제27권5호
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• pp.51-62
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• 2009

VMS(Variable Message Signs)는 도로를 주행하는 불특정 다수의 운전자에게 실시간으로 교통정보를 제공하는 대표적인 수단으로써 널리 보급되어 있다. VMS를 통해 제공되는 메시지는 운전자에게 교통운영 및 교통제어의 기능을 수행하며, 경고정보 메시지는 교통사고와 직접적으로 관련된 개별차량의 속도와 운전자의 주행경로 선정에 많은 영향을 미친다. 그러나 VMS를 통한 정보제공 방안 중 교통사고 예방을 위한 경고정보 메시지 설계에 대한 연구는 미비한 실정이다. 그러므로 본 연구에서는 경고정보 메시지를 효과적으로 전달 할 수 있는 메시지 설계 방안을 도출하기 위하여 특정지점에 이동하여 설치 운영할 수 있는 PVMS(Portable Variable Message Signs)를 이용한 실험 및 분석을 수행하였다. 본 연구에서는 실험을 1 2차로 구분하여 실시하였다. 1차실험은 TEXT 표출방법, '픽토그램 또는 기호' 표출 방법, TEXT와 '픽토그램 또는 기호'의 조합을 통한 표출방법으로 구분하여 이용자 선호도를 조사하였다. 또한, 2차 실험은 1차 실험(이용자 선호도 조사)의 결과를 조합하여 PVMS 메시지를 설계 후 실제 주행환경에 적용하여 1차 실험 결과의 현장 적용 타당성을 평가하였다. 본 연구 결과는 정보 설계를 위한 기초자료로서 유용하게 활용될 것으로 기대된다.

• 응용통계연구
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• 제21권2호
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• pp.301-312
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• 2008

상호정보(mutual information: MI)는 설명변수의 목적변수에 대한 예측정도를 나타내는 척도로서, 목적변수에 대한 설명 변수의 중요도 순위를 구하거나 목적 변수를 잘 설명해주는 설명변수의 집합을 구하는 변수선택문제에 유용하게 사용된다. 본 논문에서는 연속형 설명변수와 범주형 목적변수로 구성된 데이터로부터 결합확률분포를 추정하지 않고도 MI 추정량을 구할 수 있는 Sample-spacing 방법에 대한 연구를 수행하였다. 몬테 칼로 모의 실험과 실제데이터에 대한 실험결과, MI 추정을 위해 Sample-spacing 방법을 사용할 때 m = 1을 사용하면 충분히 신뢰할만한 결과를 얻을 수 있다는 것을 알 수 있었다.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.251-261
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• 2022

As AI has a wide range of influence on human social life, issues of transparency and ethics of AI are emerging. In particular, it is widely known that due to the existence of historical bias in data against ethics or regulatory frameworks for fairness, trained AI models based on such biased data could also impose bias or unfairness against a certain sensitive group (e.g., non-white, women). Demographic disparities due to AI, which refer to socially unacceptable bias that an AI model favors certain groups (e.g., white, men) over other groups (e.g., black, women), have been observed frequently in many applications of AI and many studies have been done recently to develop AI algorithms which remove or alleviate such demographic disparities in trained AI models. In this paper, we consider a problem of using the information in the sensitive variable for fair prediction when using the sensitive variable as a part of input variables is prohibitive by laws or regulations to avoid unfairness. As a way of reflecting the information in the sensitive variable to prediction, we consider a two-stage procedure. First, the sensitive variable is fully included in the learning phase to have a prediction model depending on the sensitive variable, and then an imputed sensitive variable is used in the prediction phase. The aim of this paper is to evaluate this procedure by analyzing several benchmark datasets. We illustrate that using an imputed sensitive variable is helpful to improve prediction accuracies without hampering the degree of fairness much.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권4호
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• pp.301-306
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• 2007

The people information is distributed in various forms such as database, web page, text, and so on, where the world wide web is one of the main sources of publicly-available people information. It has a characteristic that the information on people is intrinsically temporal. Therefore, the reconstruction of the information is needed for an individual or a company to use it efficiently. In order to maintain or manage the temporal people information, it must distinguish the variable information from invariable information of people. In this paper, we propose a method that constructs an ontology based on events to manage the variable people information efficiently. In addition, we present a system which reconstructs people information that satisfies the users' demand with the ontology.

• 전자공학회논문지A
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• 제31A권6호
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• pp.149-158
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• 1994

Through high level synthesis, designers can obtain the precious information on the area and speed trade-offs as well as synthesized datapaths from behavioral design descriptions. While previous researches were concentrated on the synthesis of pipelined, datapaths with fixed DII (Data Initiation Interval) by inserting delay elements where needed, we propose a novel methodology of synthesizing pipeline structures with variable DIIs. Determining the time-overlapping of pipeline stages with variable DIIs, the proosed algorithm performs scheduling and module allocation using the time-overlapping information. Experimental results show that significant improvement can be achieved both in speed and in area.

• Journal of the Korean Data and Information Science Society
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• 제27권6호
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• pp.1653-1660
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• 2016

Smoothly clipped absolute deviation (SCAD) penalty is known to satisfy the desirable properties for penalty functions like as unbiasedness, sparsity and continuity. In this paper, we deal with the regression function estimation and variable selection based on SCAD penalized censored regression model. We use the local linear approximation and the iteratively reweighted least squares algorithm to solve SCAD penalized log likelihood function. The proposed method provides an efficient method for variable selection and regression function estimation. The generalized cross validation function is presented for the model selection. Applications of the proposed method are illustrated through the simulated and a real example.

• Journal of Power Electronics
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• 제14권6호
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• pp.1243-1253
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• 2014

The phase inductance of a switch reluctance motor (SRM) is significantly nonlinear. With different saturation conditions, the phase inductance shape is clearly changed. This study focuses on the relationship between coefficient and current in an inductance model with ignored harmonics above the order of 3. A position estimation method based on the variable coefficient inductance model is proposed in this paper. A four-quadrant sensorless control system of the SRM drive is constructed based on the relationship between variable coefficient inductance and rotor position. The proposed algorithms are implemented in an experimental SRM test setup. Experimental results show that the proposed method estimates position accurately in operating two/four-quadrants. The entire system also has good static and dynamic performance.