• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제9권3호
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• pp.301-310
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• 2003

본 논문에서는 고해상도 위성영상의 효과적인 분류를 위한 감독분류 시스템을 설계하고 구현하였다. 구현된 시스템은 분류의 정확도 향상을 위한 훈련데이타의 효율적인 선택을 위해서 다양한 인터페이스와 통계자료를 제공한다. 또한, 다양한 위성영상 포맷의 지원과 새로운 감독분류 알고리즘의 확장을 용이하게 하기 위하여 시스템을 모듈화 하였으며, 분광 특성을 고려한 분류의 적용이 가능하다. 분류 알고리즘으로는 평행육면체 분류, 최소거리 분류, 마하라노비스 거리 분류, 최대우도 분류, 퍼지 분류의 감독분류기법을 이용하여 고해상도 위성영상의 처리를 지원한다. 본 시스템의 적용은 고해상도 IKONOS 위성영상을 입력으로 하고, 그 결과를 분석하여 봄으로써 시스템의 응용 가능성을 보여준다.

• Smart Structures and Systems
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• 제5권1호
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• pp.95-117
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• 2009

In this paper, the time series based damage detection algorithms developed by Nair, et al. (2006) and Nair and Kiremidjian (2007) are applied to the benchmark experimental data from the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan. Both acceleration and strain data are analyzed. The data are modeled as autoregressive (AR) processes, and damage sensitive features (DSF) and feature vectors are defined in terms of the first three AR coefficients. In the first algorithm developed by Nair, et al. (2006), hypothesis tests using the t-statistic are applied to evaluate the damaged state. A damage measure (DM) is defined to measure the damage extent. The results show that the DSF's from the acceleration data can detect damage while the DSF from the strain data can be used to localize the damage. The DM can be used for damage quantification. In the second algorithm developed by Nair and Kiremidjian (2007) a Gaussian Mixture Model (GMM) is used to model the feature vector, and the Mahalanobis distance is defined to measure damage extent. Additional distance measures are defined and applied in this paper to quantify damage. The results show that damage measures can be used to detect, quantify, and localize the damage for the high intensity and the bidirectional loading cases.

• Journal of the Korean Statistical Society
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• 제29권3호
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• pp.361-373
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• 2000

A simple and efficient algorithm is introduced for generalized least squares estimation under nonnegativity constraints in the components of the parameter vector. This algorithm gives the exact solution to the estimation problem within a finite number of pivot operations. Besides an illustrative example, an empirical study is conducted for investigating the performance of the proposed algorithm. This study indicates that most of problems are solved in a few iterations, and the number of iterations required for optimal solution increases linearly to the size of the problem. Finally, we will discuss the applicability of the proposed algorithm extensively to the estimation problem having a more general set of linear inequality constraints.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1992년도 학술논문발표회 논문집 제11권 1호
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• pp.71-75
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• 1992

This paper proposes algorithm in order to classify Korean consonant phonemes same as polosives, fricatives affricates into la sounds, glottalized sounds, aspirated sounds. This three kinds of sounds are one of distinctive characters of the Korean language which don't eist in language same as English. This is thesis on classfication of 14 Korean consonants(k, t, p, s, c, k', t', p', s', c', kh, ph, ch) as a previous stage for Korean phone recognition. As feature sets for classification, LPC cepstral analysis. The eperiments are two stages. First, using short-time speech signal analysis and Mahalanobis distance, consonant segments are detected from original speech signal, then the consonants are classified by fuzzy inference. As the results of computer simulations, the classification rate of the speech data was come to 93.75%.

• 한국멀티미디어학회논문지
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• 제17권2호
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• pp.113-123
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• 2014

Electrophysiological recordings are considered a reliable method of assessing a person's alertness. Sleep medicine is asked to offer objective methods to measure daytime alertness, tiredness and sleepiness. As EEG signals are non-stationary, the conventional method of frequency analysis is not highly successful in recognition of alertness level. In this paper, EEG signals have been analyzed using wavelet transform as well as discrete wavelet transform and classification using statistical classifiers such as euclidean and mahalanobis distance classifiers and a promising method SVM (Support Vector Machine). As a result of simulation, the average values of accuracies for the Linear Discriminant Analysis (LDA)-Quadratic, k-Nearest Neighbors (k-NN)-Euclidean, and Linear SVM were 48%, 34.2%, and 86%, respectively. The experimental results show that SVM classification method offer the better performance for reliable classification of the EEG signal in comparison with the other classification methods.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2001년도 춘계 학술대회 논문집 통권 4호 Proceedings of the 2001 KSRS Spring Meeting
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• pp.62-69
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• 2001

본 연구에서는 해상도가 상이한 시기별 위성영상과 GIS를 이용하여 경남 통영시 한산면 추봉도 지역의 소나무재선충(Bursaphelenchus Xylophilus) 피해지역을 탐지하고 다양한 영상처리를 통하여 이를 효율적으로 추출 할 수 있는 기법을 선정하였다. 연구결과 피해지역의 공간적 범위를 추출하기 위해서는 감독분류의 MHC(Mahalanobis Distance Classification)가 유용하였고 벌채 후의 토지피복 분류로 인한 피해지역 추출을 위해서는 MLC(Maximum Likelihood Classification)가 최적한 기법으로 나타났다. 아울러 이에 관련된 GIS를 구축하여 공간정보를 추출함으로써 피해지역의 공간적 분포특성을 규명하였는데 고도 약 120-160m, 경사 21$^{\circ}$-40$^{\circ}$ 그리고 서쪽 방향 사면에서 소나무재선충이 가장 활발하게 활동하였음이 밝혀졌다.

• Agricultural and Biosystems Engineering
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• 제5권1호
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• pp.25-29
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• 2004

Fluorescence spectroscopy was used to characterize chicken carcass diseases. Spectral signatures of three different disease categories of poultry carcasses (airsacculitis, cadaver and septicemia) were obtained from fluorescence emission measurements in the wavelength range of 360 to 600 nm with 330 nm excitation. Principal Component Analysis (PCA) was used to select the most significant wavelengths for the classification of poultry carcasses. These wavelengths were analyzed for pathologic correlation of poultry diseases. Using a Soft Independent Modeling of Class Analogy (SIMCA) of principal components with a Mahalanobis distance metric, poultry carcasses were individually classified into different classes with $97.9\%$ accuracy.

• 대한산업공학회지
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• 제39권2호
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• pp.82-89
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• 2013

Novelty detection (ND) is an effective technique that can be used to determine whether a future observation is normal or not. In the present study we propose a novelty detection algorithm that can handle a situation where the distributions of target (normal) observations are inhomogeneous. A simulation study and a real case with the TFT-LCD process demonstrated the effectiveness and usefulness of the proposed algorithm.

• Journal of Biosystems Engineering
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• 제23권4호
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• pp.343-350
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• 1998

Spectroscopic analysis of soybean kernels were made in the wavelength range of 400 to 1100 nm to find effective discrimination factors which are required for developing an opitical soybean sorter. Soybean samples used for the test were the sound and five classes of the defective kernels such as the immature, discolored(brown and violet), damaged by insect and diseased. Effective discrimination factors to classify the soybean kernels into the sound and the defective were found to be $R_{640}$, $R_{580}$/ $R_{990}$, $R_{600}$- $R_{820}$ and ( $R_{590}$- $R_{820}$)/ $R_{990}$. with classification error of less than 4%. Mahalanobis distance was used as a criterion to select significant wavelengths involved in the discrimination factors.s.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.971-980
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• 2003

The tree method can be extended to multivariate responses, such as repeated measure and longitudinal data, by modifying the split function so as to accommodate multiple responses. Recently, some decision trees for multiple responses have been constructed by Segal (1992) and Zhang (1998). Segal suggested a tree can analyze continuous longitudinal response using Mahalanobis distance for within node homogeneity measures and Zhang suggested a tree can analyze multiple binary responses using generalized entropy criterion which is proportional to maximum likelihood of joint distribution of multiple binary responses. In this paper, we will modify CART procedure and suggest a new tree-based method that can analyze multiple binary responses using similarity measures.