• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.95-106
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• 2013

The study compares accuracies between humans and computer algorithms in the discrimination of spontaneous smiles from posed smiles. For this purpose, subjects performed two tasks, one was judgment with single pictures and the other was judgment with pair comparison. At the task of judgment with single pictures, in which pictures of smiling facial expression were presented one by one, subjects were required to judge whether smiles in the pictures were spontaneous or posed. In the task for judgment with pair comparison, in which two kinds of smiles from one person were presented simultaneously, subjects were to select spontaneous smile. To calculate the discrimination algorithm accuracy, 8 kinds of facial features were used. To calculate the discriminant function, stepwise linear discriminant analysis (SLDA) was performed by using approximately 50 % of pictures, and the rest of pictures were classified by using the calculated discriminant function. In the task of single pictures, the accuracy rate of SLDA was higher than that of humans. In the analysis of accuracy on pair comparison, the accuracy rate of SLDA was also higher than that of humans. Among the 20 subjects, none of them showed the above accuracy rate of SLDA. The facial feature contributed to SLDA effectively was angle of inner eye corner, which was the degree of the openness of the eyes. According to Ekman's FACS system, this feature corresponds to AU 6. The reason why the humans had low accuracy while classifying two kinds of smiles, it appears that they didn't use the information coming from the eyes enough.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1904-1905
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• 2007

한의학적 중요 진단방법의 하나인 맥진은 한의사 경험에 의해 구전되거나 전수되어 판단 기준이 모호하여 객관화 및 표준화하기 어려운 상황이다. 이를 위해 한의사가 맥진에서 측정하는 물리적 요소를 신뢰성 있게 측정할 수 있는 맥진기 개발이 진행되었으며, 측정된 맥진기 데이터를 이용하여 맥의 부/침, 허/실, 대/세의 정도를 판별할 수 있는 함수식을 만들어 향후 맥진을 자동으로 진단할 수 있도록 알고리즘을 산출하는 연구를 수행중이다. 그런데 맥진기는 환자의 맥파 신호 이외에 다른 정보를 고려하고 있지 않고 있지만 임상에서 한의사들은 환자의 키와 몸집 등 눈으로 관찰된 환자정보를 반영하여 맥진을 한다. 따라서 본 연구에서는 환자의 기초 정보 중, BMI가 맥진에 영향을 줄 것으로 가정하고, BMI와 연관성이 있을 것으로 예상되는 부/침, 허/실, 대/세의 판별함수 결과 값을 이용하여 BMI의 등급에 따라 비교 분석하였다. 그 결과 부/침의 정도는 비만인 그룹에서 맥이 가라앉아있고 저체중인 그룹에서는 맥이 떠있는 경향이 나타났고, 대/세의 정도는 비만인 그룹에서는 맥의 굵기가 넓고 저체중의 집단에서는 맥의 굵기가 좁은 경향이 나타났다. 따라서 부/침, 대/세를 판별하는 진단 알고리즘을 개발할 경우 개인의 BMI를 고려한 진단 알고리즘이 연구되어야 하겠다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.3
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• pp.244-249
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• 2008

In this paper, the stable region for missile guidance loop employing an integrated proportional navigation guidance law is derived. The missile guidance loop is formulated as a closed-loop control system consisting of a linear time-invariant feed-forward block and a time-varying feedback gain. By applying the circle criterion to the system, a bound for the time of flight up to which stability can be assured is established as functions of flight time. Less conservative results, as compared to the result by Popov criterion, are obtained.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.539-547
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• 2012

Increasing the mode transfer volume between public transportation modes has known to be necessary for efficiency improvement of public transportation system operation and it is also found to be important to have relevant transfer point selection with reflection of current travel pattern. This study is in regards to providing a selection guideline for the location of transfer point between public transport modes. This case study has been carried out for Daegu Metropolitan City especially for public transportation users behaviour by analysis of daily usage of transportation card to identify the transfer travel pattern. A cluster analysis was applied to categorize the pattern of transfer stop which induces many users and a discriminant analysis also utilized for grouping the stops by number of transfer trip. This research produces the estimation result of transfer volume for urban railway system no.3 in Daegu City which is currently under construction. In addition, the locations of transfer center has also been proposed.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.9-20
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• 2005

Accident type and/or factor identification is important in accident reduction planning. The aim of this paper is to apply the hierarchical approach with binomial distribution and logistic regression analysis to find out types and factors, respectively. Based on 2001 Suwon city black spot data, a binomial distribution modeling approach has been applied to diagnose the black spots, with the help of safety performance modeling approach has been applied to diagnose the black spots, with the help of safety performance function. Then, the logistic regression analysis has been employed to identify the critical factors. Some accident remedies are also reviewed in the light of the model outcomes. The proposed research framework sheds light on a different accident related research and can also be successfully applied to similar studies and sites.

• Korean Journal of Food Science and Technology
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• v.46 no.3
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• pp.352-357
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• 2014

In this study, 100 consumers (men, 50; women, 50; age group, 20-50 years) rated their overall preferences for 24 Korean raspberry wines by using a 9-point hedonic scale. The analysis of variance was constructed to evaluate the effect of gender, age, and samples on the preference scores of the wine products. Significant differences were observed in overall preferences for the 24 samples; however, no interactions based on preferences by age and gender groups were noted. Cluster analysis was performed to determine sample clustering based on the frequencies from the preference data. Three clusters were obtained; these three clusters were well separated based on the mean overall preference scores for the samples. Discriminant analysis based on the three clusters also confirmed the same grouping of samples with 100% accuracy.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.83-92
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• 2010

Along with the advance of industrial technology in mobile telecommunications and diversity in customer needs, today's Korean mobile telecommunication market has rapidly expanded due to stronger competition among businesses as well as increasing the number of subscribers. 3G roll-outs of mobile telecommunications service, so called "HSDPA" has seriously promoted marketing strategies among mobile telecommunication companies which led to move to the next generation customers. Understanding the competitive situation, mobile telecommunications companies are currently focusing on increasing sales per subscriber as well as increasing the number of subscribers as a solution to occupy the leading position in the mobile telecommunications industry in the future. The purpose of this study was to classify the customers in mobile telecommunications service with or without higher tendency of intention to subscribe and use the service using discriminant analysis. Through the discriminant analysis, discriminant function which classifying the critical user has been identified. The result of this study will give useful marketing strategies in competitive HSDPA mobile telecommunications market.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.190-192
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• 2003

소비자의 신용 대출 규모가 점차 증가하면서 기업에서 고객의 신용 등급에 의한 정확한 고객 분류를 필요로 하고 있다 이를 위해 판별 분석과 신경망의 역전파(BP: Back Propagation)를 이용한 고객 분류 시스템이 연구되었다. 그러나, 판별 분석을 사용한 방법은 불규칙한 신용 거래의 성향을 보이는 비정규 분포의 고객 데이터의 영향으로 여러 개의 판별 함수와 판별점이 존재하여 분류 정확도가 떨어지는 단점이 있다. 신경망을 이용한 방법은 불규칙한 신용 거래의 성향을 보이는 고객 데이터에 의해서, 지역 최소점(Local Minima)에 빠져 최대의 분류 정확률을 보이는 분류자를 얻지 못하는 경우가 발생할 수 있다. 본 논문에서는 이러한 기존 연구의 분류 정확률을 저하시키는 단점을 해결하기 위해 SVM(Support Vector Machine)을 사용하여 고객의 신용 등급을 분류하는 방법을 제안한다. SVM은 SV(Support Vector)의 수에 의해서 학습 성능이 좌우되므로, 불규칙한 거래 성향을 보이는 고객에 대해서도 높은 차원으로의 매핑을 통하여, 효과적으로 학습시킬 수 있어 분류의 정확도를 높일 수 있다 하지만, SVM은 근사화 알고리즘(Approximation Algorithms)을 이용하므로 분류 정확도가 이론적인 성능에 미치지 못한다. 따라서, 본 논문은 점진적 앙상블 SVM을 사용하여, 기존의 고객 분류 시스템의 문제점을 해결하고 실제적으로 SVM의 분류 정확률을 높인다. 실험 결과는 점진적 앙상블 SVM을 이용한 방법의 정확성이 기존의 방법보다 높다는 것을 보여준다.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.187-224
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• 2014

We present key issues to consider in estimating damages from price-fixing cases and then apply the procedure addressing those issues to a transportation fuel market. Among the five methods of overcharge calculation, the regression analysis incorporating the yardstick method is the best. If the price equation relates the domestic price to the foreign price and the exchange rate as in the transportation fuel market, the functional form satisfying both logical consistency and modeling flexibility is the log-log functional form. If the data under analysis is of time series in nature, then the ARDL model should be the base model for each market and the regression analysis incorporating the yardstick method combines these ARDL equations to account for inter-market correlation and arrange constant terms and collusion-period dummies across component equations appropriately so as to identify the overcharge parameter. We propose a two-step test for the benchmarked market: (a) conduct market-by-market Spearman or Kendall test for randomness of the individual market price series first and (b) then conduct across-market Friedman test for homogeneity of the market price series. Statistical significance is the minimal requirement to establish the alleged proposition in the world of uncertainty. Between the sensitivity analysis and the model selection process for the best fitting model, the latter is far more important in the economic analysis of damage in price-fixing litigation. We applied our framework to a transportation fuel market and could not reject the null hypothesis of no overcharge.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.73-86
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• 2024

A radial chart of Excel is very useful graphical method in delivering information for numerical data. However, it is not easy to discriminate or classify many individuals. In this case, after shaping each individual of a radial chart, we need to apply shape analysis. For a radial chart, since landmarks for shaping are formed as many as the number of variables representing the characteristics of the object, we consider a shape that connects them to a line. If the shape becomes complicated due to the large number of variables, it is difficult to easily grasp even if visualized using a radial chart. Principal component analysis (PCA) is performed on variables to create a visually effective shape. The classification table and classification rate are checked by applying the techniques of traditional discriminant analysis, support vector machine (SVM), and artificial neural network (ANN), before and after principal component analysis. In addition, the difference in discrimination between the two coordinates of generalized procrustes analysis (GPA) coordinates and Bookstein coordinates is compared. Bookstein coordinates are obtained by converting the position, rotation, and scale of the shape around the base landmarks, and show higher rate than GPA coordinates for the classification rate.