• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.230-236
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• 1998

본 연구에서는 형용사로 감성 반응을 평가하는 일반적인 감성공학 연구에서 감성공학 연구에서 감성 공간을 보다 쉽게 도식화하고 평가 방법을 단순화시키는 전략을 제시하고자 한다. 기존의 감성공학연구에서는 수집된 감성 어휘를 순차적으로 정리해 줄이는 방법을 취한 다음 최종 어휘 목록을 이용하여 평가 대상이 다소 복잡하여 표본의 수가 많은 경우 어휘 목록을 인위적으로 줄이지 않으면 신뢰로운 반응을 기대하기 어렵다. 본 연구에서는 보다 단순한 방법으로 감성 반응을 포괄적으로 얻을 수 있도록 하기 위하여 감성 형용사를 설명하는데 필요한 최소 차원을 설정하고 차원 평정치에 따라 필요한 어휘군의 목록만 사용하여 어휘를 평가할 수 있는 방법을 제안하고자 한다.

• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.547-557
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• 2012

This study purposed to estimate the forest biomass using k-Nearest Neighbor (k-NN) algorithm. Multiple data sources were used for the analysis such as forest type map, field survey data and Landsat TM data. The accuracy of forest biomass was evaluated with the forest stratification, horizontal reference area (HRA) and spatial filtering. Forests were divided into 3 types such as conifers, broadleaved, and Korean pine (Pinus koriansis) forests. The applied radii of HRA were 4 km, 5 km and 10 km, respectively. The estimated biomass and mean bias for conifers forest was 222 t/ha and 1.8 t/ha when the value of k=8, the radius of HRA was 4 km, and $5{\times}5$ modal was filtered. The estimated forest biomass of Korean pine was 245 t/ha when the value of k=8, the radius of HRA was 4km. The estimated mean biomass and mean bias for broadleaved forests were 251 t/ha and -1.6 t/ha, respectively, when the value of k=6, the radius of HRA was 10 km. The estimated total forest biomass by k-NN method was 799,000t and 237 t/ha. The estimated mean biomass by ${\kappa}NN$method was about 1t/ha more than that of filed survey data.

• The Korean Journal of Financial Management
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• v.14 no.1
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• pp.171-205
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• 1997

'80년대 중반 들어 주가지수 예측모형으로 애용되던 시계열 예측모형에 대한 근본적인 의문이 제기되었다. 이것은 기존 예측모형이 선형 데이터 생성과정을 기본가정으로 채택하고 있지만 진정한 데이터 생성과정은 비선형일 수도 있다는 점에서 출발한다. 주가지수의 변동을 유발하는 경제의 기본구조가 비선형임에도 불구하고 이를 선형모형으로 접근한다면 주가의 움직임을 제대로 설명할 수 없을 뿐만 아니라 이러한 설정오류는 모형의 신뢰성을 크게 손상시킨다. 이와 같은 점에 착안하여 본 연구는 업종별 주가지수의 비선형 검정을 통해 주가가 어떠한 형태의 경제구조에서 생성되었는지 여러 가지 방법으로 정정한다. 10개 업종지수의 검정결과 보험업을 제외한 대부분의 업종지수가 카오스 끌개를 보유하고 있다는 증거가 포착되었다. 표본외 예측을 위해서 국지적 가중회귀법을 채택하였는데 예측결과 모형에 따라 $6{\sim}7$개 업종에서 통상최소자승법보다 예측력 우위를 보였다.

• Water for future
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• v.23 no.1
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• pp.79-87
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• 1990

In this study, a regression model, which relates annual flood peak flows collected at stramflow gaging stations in the Han river and Nakdong river basin to both basin characteristics and precipitation data, is developed by using the generalized least squares method which can provide reasonable and unbiased estimator of error variance by separating error variance of the regression model into that due to model error and due to sampling error. This model may be used as a mechanism for transferring hydrologic information from the gaged sites to ungaged sites.

• Journal of IKEEE
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• v.24 no.4
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• pp.1081-1085
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• 2020

Instantaneous frequencies (IF) of the AM-FM signal is estimated based on the inflection point detection (IPD) method. Local maxima/minima are detected using the IPD, and they are exploited to find the IF of AM and FM components, respectively. The envelope of the maxima/minima is obtained to estimate the IF of the AM part. And the distance between neighboring maxima (or minima) is used to estimate the IF of the FM component. Computer simulation shows that the proposed method properly estimates the IF of the AM and FM when the signal has fixed frequencies for both parts. In the case of the time-varying IF of the FM part, the estimated IF shows some deviation from the true IF due to the rough sampling effect of the maximum/minimum points. Thus, the post-processing such as the lowpass filtering of the estimated IF is required to refine the resulting IF estimation.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.29-29
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• 2020

본 연구는 현재 공주대학교 포장에 보존되어 있는 식용, 약용, 관상용 등의 매실나무 유전자원에 대한 외부 형태적 특성평가를 통하여 향후 우수한 종자원 확보와 양묘생산의 토대 및 육종을 위한 소재로 활용할 수 있는 기초 정보를 제공하기 위하여 실시하였다. 매실나무의 엽형은 난형에 가까웠는데, 엽장은 평균 76.9±9.7mm (최소 52.0mm, 최대 102.0mm)이었으며, 엽폭은 평균 41.9±6.4mm (최소 27.0mm, 최대 60.0mm)이었고, 엽병장은 평균 9.5±2.6mm (최소 4.0mm, 최대 24.0mm)이었다. 이들 형질의 변이계수는 엽병장이 27.7%로서 가장 높아 엽장과 엽폭에 비해 진폭이 컸으며, 다음으로 엽폭 (15.3%), 엽장 (12.6%) 순이었다. 매실나무 엽장은 71~80mm에서 가장 높은 비율 (50.3%)을 나타내었으며, 다음으로 81~90mm (21.9%), 61~70mm (12.4%), 91mm 이상 (8.0%), 60mm 이하 (7.4%) 순이었다. 엽폭은 41~50mm에서 가장 높은 비율 (45.8%)을 나타내었으며, 다음으로 31~40mm (41.8%), 51mm 이상 (7.4%), 30mm 이하 (5.0%) 순이었다. 엽병장은 6~10mm에서 가장 높은 비율 (72.6%)을 나타내었으며, 다음으로 11~15mm (22.4%), 16mm 이상 (3.0%), 5mm 이하 (2.0%) 순이었다. 엽형 형질 간의 상관계수는 모두가 0.2 이하로 상관관계가 약하였으나 표본수가 많아 유의한 값을 나타내었으며, 엽장과 엽폭이 0.242로 가장 높았고, 다음으로 엽장과 엽병장 (0.173), 엽폭과 엽병장 (0.001) 순이었다.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.15-34
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• 2006

This paper introduces an empirical modeling technique. This technique uses a set of sample results which are collected from a few small scale simulations. Empirical models are developed by applying a couple of statistical estimation techniques to these samples. We built two types of models for cache miss rates in Symmetric Multiprocessor systems. One is for the changes of input data set size while the specification of target system is fixed. The other is for the changes of the number of processors in target system while the input data set size is fixed. To develop accurate models, we built individual model for every kind of cache misses for each shared data structure in a program. The final model is then obtained by integrating them. Besides, combined use of Least Mean Squares and Robust Estimations enhances the quality of models by minimizing the distortion due to outliers. Empirical modeling technique produces extremely accurate models without analysis on sample data. In addition, since only snail scale simulations are necessary, once a set of samples can be collected, empirical method can be adopted in any research areas. In 17 cases among 24 trials, empirical models present extremely low prediction errors below $1\%$. In the remaining cases, the accuracy is excellent, as well. The models sustain high quality even when the behavioral characteristics of programs are irregular and the number of samples are barely enough.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.625-636
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• 2011

This paper proposes two parametric entropy estimators, the minimum variance unbiased estimator and the maximum likelihood estimator, for the lognormal distribution for a comparison of the properties of the two estimators. The variances of both estimators are derived. The influence of the bias of the maximum likelihood estimator on estimation is analytically revealed. The distributions of the proposed estimators obtained by the delta approximation method are also presented. Performance comparisons are made with the two estimators. The following observations are made from the results. The MSE efficacy of the minimum variance unbiased estimator appears consistently high and increases rapidly as the sample size and variance, n and ${\sigma}^2$, become simultaneously small. To conclude, the minimum variance unbiased estimator outperforms the maximum likelihood estimator.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.75-88
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• 2004

The Support Vector Machine(SVM) algorithm has paid attention on maximizing the shortest distance between sample points and discrimination hyperplane. This paper suggests the total margin algorithm which considers the distance between all data points and the separating hyperplane. The method extends existing support vector machine algorithm. In addition, this newly proposed method improves the generalization error bound. Numerical experiments show that the total margin algorithm provides good performance, comparing with the previous methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.986-991
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• 2002

This paper presents off-line handwritten numeral recognition method by using Eigen-Vectors. In this method, numeral features are extracted statistically by using Eigen-Vectors through KL transform and input numeral is recognized in the feature space by the nearest-neighbor classifier. In our feature extraction method, basis vectors which express best the property of each numeral type within the extensive database of sample numeral images are calculated, and the numeral features are obtained by using this basis vectors. Through the experiments with the unconstrained handwritten numeral database of Concordia University, we have achieved a recognition rate of 96.2%.