• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.58-65
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• 2001

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that he selected solution become the global optimal solution by optimizing the Akaikes information criterion expressing the quality of the inference rules. The trajectory tracking simulation and experiment of the polishing robot show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

• Communications for Statistical Applications and Methods
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• 제17권6호
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• pp.909-916
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• 2010

A trend in software reliability engineering is to take into account the coverage growth behavior during testing. A coverage growth function that represents the coverage growth behavior is an essential factor in software reliability models. When multiple competitive coverage growth functions are available, there is a need for a criterion to select the best coverage growth functions. This paper proposes a selection criterion based on the prediction error. The conditional coverage growth function is introduced for predicting future coverage growth. Then the sum of the squares of the prediction error is defined and used for selecting the best coverage growth function.

• Advances in environmental research
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• 제3권2호
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• pp.131-149
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• 2014

Two different model selection indices, the Akaike information criterion (AIC) and the coefficient of determination ($R^2$), are used to discriminate competing isotherm equations for aqueous pollutant removal systems. The former takes into account model accuracy and complexity while the latter considers model accuracy only. The five types of isotherm shape in the Brunauer-Deming-Deming-Teller (BDDT) classification are considered. Sorption equilibrium data taken from the literature were correlated using isotherm equations with fitting parameters ranging from two to five. For the isotherm shapes of types I (favorable) and III (unfavorable), the AIC favors two-parameter equations which can easily track these simple isotherm shapes with high accuracy. The $R^2$ indicator by contrast recommends isotherm equations with more than two parameters which can provide marginally better fits than two-parameter equations. To correlate the more intricate shapes of types II (multilayer), IV (two-plateau) and V (S-shaped) isotherms, both indices favor isotherm equations with more than two parameters.

• 정보보호학회논문지
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• 제1권1호
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• pp.85-90
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• 1991

본 논문에서는 Bent 함수와 SAC(Strict Avalanche Criterion)조건을 만족하는 함수를 정의하고 상호관계를 증명하였다. 즉, 최대차 SAC 조건을 만족한다. 그러나, Bent 함수는 블럭 암호의 s-box나 스트림 암호의 비선형 혼합기들으로 사용할 수 있느나, 함수 자체의 0/1 분균형성과 입력이 짝수인 경우에만 존재하므로 전단사 함수를 필요로 하는 암호 함수로 사용할 때는 이용할 수 없는 단점이 있다.

• 지적과 국토정보
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• 제48권2호
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• pp.197-211
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• 2018

본 연구에서는 건강에 대한 공간적 연구에서 통상적으로 사용되는 센서스에 기반한 지역 박탈지수의 대안으로 지역 주택가격이 사용될 수 있는지 평가하였다. 평가를 위해 개인을 1수준으로, 수도권의 보건소 구역을 2수준으로 하는 다수준 로지스틱 모델이 추정되었다. 다수준 모델에는 개인의 점심식사후 칫솔질과 치간실 사용을 설명하기 위한 개인수준의 변수들과 보건소 구역을 대표하는 사회적 박탈지수 및 지역주택가격 수준이 포함되었다. 추정된 모델들의 설명력은 Akaike Information Criterion (AIC)와 Bayesian Information Criterion (BIC)를 이용하여 평가되었다. 모델의 추정결과는 사회적 박탈지수 및 지역 주택가격이 모두 개인의 치아관리 행동을 설명하는 데 기여하나 지역 주택가격을 사용한 모델의 AIC 및 BIC가 통상적인 센서스 기반 지역 박탈지수를 사용한 경우 보다 낮은 것을 보여 주었다. 본 연구결과는 센서스에 기반한 박탈지수를 생성하는 데 사용된 센서스 변수가 시점의 차이 등의 이유로 적절하지 않을 경우 지역 주택가격이 지역의 사회경제적 수준을 대표하기 위해 대안적으로 사용될 수 있음을 보여준다.

• 한국통신학회논문지
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• 제15권10호
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• pp.842-849
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• 1990

본 논문에서는 array processing에서, sensor array를 통해 들어오는 source signal들의 개수를 결정하는 방법들을 판정의 정확도의 관점에서 연구 고찰한다. 첫번째 방법은 Akaike의 Akaike's Information Criterion(AIC)이고, 다른 하나는 Schwartz와 Rissanen의 Minimum Description Length(MDL)이다. 실용적인 측면에서 볼 때, 신호대잡음비 (S/N)가 매우 낮은 상태에서 얻어진 한정된 양의 data를 이용하여 제한된 갯수의 sensor들로 이루어진 array로 부터, 매우 근접해 있는 source signal들의 갯수를 예측해 내는 것은 대단히 중요한 일이다. 본 논문은 simulation 결과를 통하여, source signal들이 근접해 있을수록, array의 sensor 갯수가 줄어들수록, 이용할 data의 양이 한정될수록 또 S/N가 낮아질수록, AIC이 MDL에 비해서 높은 신뢰도를 가짐을 보여준다.

• Journal of the Korean Data and Information Science Society
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• 제27권3호
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• pp.653-661
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• 2016

본 연구에서는 한국 프로야구의 승률을 추정하기 위하여 야구 경기의 피타고라스 정리라고 불리우는 방법을 사용하였고, 이 방법을 확장한 일반화 피타고라스 정리도 이용하면서 일반화 피타고라스 정리의 최적 지수 값을 찾아보았다. 그리고 다른 추정 방법들인 로지스틱 모형과 프로빗 모형의 사용을 제안하였다. 평균제곱오차의 제곱근 (RMSE)을 판정기준으로, 피타고라스 정리와 제안된 모형들의 효율성을 서로 비교하였다. 사용한 자료는 1982년부터 2015년 7월까지의 모든 한국 프로야구 기록이며, 제안한 방법은 일반화 피타고라스 정리를 이용한 승률 추정 방법보다 평균제곱오차의 관점에서 다소 나아졌음을 보여준다.

• 가족자원경영과 정책
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• 제11권4호
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• pp.1-20
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• 2007

The purpose of this study was to identify the criteria of evaluating a price-comparison website, and to investigate the consumers' perceived importance and satisfaction of each criterion. Also, it compared both the importance and satisfaction levels based on consumers' socio-economic and Internet-usage characteristics. Data for this study came from a questionnaire completed by consumers (n=417), who had used the price-comparison website, and were analyzed through factor analysis, t-test, and ANOVA. The findings of the study were as follows: First, the evaluation criteria of the price-comparison website were categorized into five variety of information, accuracy, convenience, credibility, and the website system. Second, convenience of searching information was seen by consumers as both the most important and most satisfactory criterion. Variety of information was also considered important. For most of the evaluation criteria, the level of consumers' satisfaction was significantly lower than the level of consumers' recognized importance. Third, consumers in their 20s, students, and housewives were less likely to be satisfied by the price-comparison website overall. Older people were less likely to be satisfied with the convenience of the website, and the higher-income group was less likely to be satisfied with the variety of information on hand.

• Industrial Engineering and Management Systems
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• 제12권2호
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• pp.112-117
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• 2013

The $\overline{x}$ control chart for the process mean and either the R or s control chart for the process dispersion have been used together to monitor the manufacturing processes. However, it has been pointed out that this procedure is flawed by a fault that makes it difficult to capture the behavior of process condition visually by considering the relationship between the shift in the process mean and the change in the process dispersion because the respective characteristics are monitored by an individual control chart in parallel. Then, the ($\overline{x}$, s) control chart has been proposed to enable the process managers to monitor the changes in the process mean, process dispersion, or both. On the one hand, identifying which process parameters are responsible for out-of-control condition of process is one of the important issues in the process management. It is especially important in the ($\overline{x}$, s) control chart where some parameters are monitored at a single plane. The previous literature has proposed the multiple decision method based on the statistical hypothesis tests to identify the parameters responsible for out-of-control condition. In this paper, we propose how to identify parameters responsible for out-of-control condition using the information criterion. Then, the effectiveness of proposed method is shown through some numerical experiments.

• Genomics & Informatics
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• 제18권3호
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• pp.30.1-30.7
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• 2020

The novel coronavirus pandemic that has originated from China and spread throughout the world in three months. Genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) predecessor, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) play an important role in understanding the concept of genetic variation. In this paper, the genomic data accessed from National Center for Biotechnology Information (NCBI) through Molecular Evolutionary Genetic Analysis (MEGA) for statistical analysis. Firstly, the Bayesian information criterion (BIC) and Akaike information criterion (AICc) are used to evaluate the best substitution pattern. Secondly, the maximum likelihood method used to estimate of transition/transversions (R) through Kimura-2, Tamura-3, Hasegawa-Kishino-Yano, and Tamura-Nei nucleotide substitutions model. Thirdly and finally nucleotide frequencies computed based on genomic data of NCBI. The results indicate that general times reversible model has the lowest BIC and AICc score 347,394 and 347,287, respectively. The transition/transversions bias for nucleotide substitutions models varies from 0.56 to 0.59 in MEGA output. The average nitrogenous bases frequency of U, C, A, and G are 31.74, 19.48, 28.04, and 20.74, respectively in percentages. Overall the genomic data analysis of SARS-CoV-2, SARS-CoV, and MERS-CoV highlights the close genetic relationship.