• 한국통신학회논문지
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• 제32권2C호
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• pp.150-159
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• 2007

이 논문의 1부에서는, 곱셈꼴 잡음과 일차 마르코프 덧셈꼴 잡음으로 손상된 약한 신호를 검파할 수 있는 검정 통계량을 얻었다. 이제, 이 2부에서는 이를 바탕으로 여러 검파기의 점근 상대 효율 및 유한 표본 크기 성능을 얻고 견준다. 검파 성능을 처음 뜻한 만큼 내려면 간섭끼리의 의존성을 생각해야 함을 보인다.

• Communications for Statistical Applications and Methods
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• 제9권1호
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• pp.13-19
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• 2002

In nonparametric entropy estimation, both mass and mean-preserving maximum entropy distribution (Theil, 1980) and the underlying distribution of the sample entropy (Vasicek, 1976), the most widely used entropy estimator, consist of nb mass-preserving densities based on disjoint Intervals of the simple averages of two adjacent order statistics. In this paper, we notice that those nonparametric density functions do not actually keep the mass-preserving constraint, and propose a modified sample entropy by considering the generalized 0-statistics (Kaigh and Driscoll, 1987) in averaging two adjacent order statistics. We consider the proposed estimator in a goodness of fit test for normality and compare its performance with that of the sample entropy.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.11-14
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• 1996

Performance of the group cumulative sum(CUSUM) control scheme using multiple univariate CUSUM charts is more sensitive to the change of quality control(QC) characteristics than the control chart scheme based on the Hotelling statistics. We examine three group charts for multivariate normal data sets simulated with various correlation structures and shift directions in the mean vector. These group schemes apply the orginal measurement vectors, the scaled residual vectors from the regression of each variable on all others and the principal component vectors respectively to calculating the CUSUM statistics. They are also compared to the multivariate QC charts based on the Hotelling statistic by estimating average run lengths, coefficients of variation of run length and ranks in signaling order. On the basis of simulation results, we suggest a control chart scheme appropriate for specific quality control environment.

• 한국컴퓨터정보학회논문지
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• 제28권11호
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• pp.1-11
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• 2023

유방암은 전 세계적으로 여성들 대다수에게 가장 두려워하는 질환이다. 오늘날 데이터의 증가와 컴퓨팅 기술의 향상으로 머신러닝(machine learning)의 효율성이 증대되어 암 검출 및 진단 등에 중요한 역할을 하고 있다. 딥러닝(deep learning)은 인공신경망(artificial neural network, ANN)을 기반으로 하는 머신러닝 기술의 한 분야로 최근 여러 분야에서 성능이 급속도로 개선되어 활용 범위가 확대되고 있다. 본 연구에서는 유방암 분류를 위해 전이학습(transfer learning) 기반 DNN(Deep Neural Network)과 SVM(support vector machine)의 구조를 결합한 DNN-SVM Hybrid 모형을 제안한다. 전이학습 기반 제안된 모형은 적은 학습 데이터에도 효과적이고, 학습 속도도 빠르며, 단일모형, 즉 DNN과 SVM이 가지는 장점을 모두 활용 가능토록 결합함으로써 모형 성능이 개선되었다. 제안된 DNN-SVM Hybrid 모형의 성능평가를 위해 UCI 머신러닝 저장소에서 제공하는 WOBC와 WDBC 유방암 자료를 가지고 성능실험 결과, 제안된 모형은 여러 가지 성능 척도 면에서 단일모형인 로지스틱회귀 모형, DNN, SVM 그리고 앙상블 모형인 랜덤 포레스트보다 우수함을 보였다.

• Communications for Statistical Applications and Methods
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• 제24권5호
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• 통합자연과학논문집
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• 제10권3호
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• pp.162-170
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• 2017

In this paper, it is aim to implement a wheelchair monitoring system that provides users with customized medical services easily in everyday life, together with mobility guarantee, which is the most basic requirement of the elderly and disabled persons with physical disabilities. The case-based intelligent wheelchair monitoring system proposed in this study is based on a case-based k-NN algorithm, which implements a system for constructing and inferring examples of various biometric and environmental information of wheelchair users as a knowledge database and a monitoring interface for wheelchair users. In order to confirm the usefulness of the case-based k-NN algorithm, the SVM algorithm showed an average accuracy of 84.2% and the average accuracy of the proposed case-based k-NN algorithm was 86.2% And showed higher performance in terms of accuracy. The system implemented in this paper has the advantage of measuring biometric information and data communication regardless of time and place and it can provide customized service of wheelchair user through user friendly interface.

• 대한전자공학회논문지SP
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• 제44권2호
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• pp.37-45
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• 2007

국부통계처리에 근거한 금석문영상의 적응영상향상 기법을 제안한다. 영상의 국부통계처리 값들을 영상향상을 위한 적응실현으로 활용하여 평활화와 상세화의 경로를 조정한다. 미세부분에서는 영상이 향상되고 평활영역에서는 잡음이 억제된다 금석 문영상의 모델링을 위해 한지밀착본(韓紙密着本)디지털영상(HSDI, Hanzi squeezed digital image)의 전처리 과정을 수행하였다. HSDI 분석을 통해 국부통계처리 값들을 산출하고 영상을 모델링한다. 본 기법을 HSDI에 적용하여 에지부분의 미세한 변화를 향상시키고 배경영역을 평활시킴으로 결국 문자영역의 시각적 효과를 증대하였다 실험결과들은 제시한 알고리즘이 기존의 영상향상기법보다 우수함을 보여준다.

• Communications for Statistical Applications and Methods
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• 제16권6호
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• pp.1005-1012
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• 2009

The area under the curve(AUC) is commonly used as a measure of the receiver operating characteristic(ROC) curve which displays the performance of a set of binary classifiers for all feasible ratios of the costs associated with true positive rate(TPR) and false positive rate(FPR). In the bipartite ranking problem where one has to compare two different observations and decide which one is "better", the AUC measures the quantity that ranking score of a randomly chosen sample in one class is larger than that of a randomly chosen sample in the other class and hence, the function which maximizes an AUC of bipartite ranking problem is different to the function which maximizes (minimizes) accuracy (misclassification error rate) of binary classification problem. In this paper, we develop a way to construct the unified framework for AUC maximizer including support vector machines based on maximizing large margin and logistic regression based on estimating posterior probability. Moreover, we develop an efficient algorithm for the proposed unified framework. Numerical results show that the propose unified framework can treat various methodologies successfully.

• Asian Journal of Business Environment
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• 제12권2호
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• pp.43-53
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• 2022

Purpose: This study aims to analyze the performance of local taxes in Indonesia through the estimation of tax capacity and tax effort, as well as classifying provinces based on the estimated value of tax capacity and tax effort. Research design, data and methodology: this study uses panel data of 34 provinces in Indonesia for the period of 2014-2018. The analytical method used in the tax capacity model is panel data regression to explain the factors that influence tax performance. Tax effort is estimated by the ratio of tax to tax capacity. Results: The results of the analysis show that gini ratio and regional expenditures have a significant positive effect on the tax ratio, while the share of GRDP in the manufacturing sector and HDI has a significant negative effect on the tax ratio. Based on the results, there are 19 provinces that have low tax capacity and 16 provinces that have low tax effort. Conclusions: The development of local tax performance tends to fluctuate with an average of 1.24 percent per year. Gini ratio and regional expenditure have a significant positive effect on the tax ratio, while the share of GRDP in the manufacturing sector and HDI have a significant negative effect on the tax ratio.

• 대한전자공학회논문지TC
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• 제44권11호
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• pp.19-24
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• 2007

본 논문은 직교 분할 다중 반송파 다중 접속 방식(OFDMA, Orthogonal Frequency Division Multiple Access)에서 그리디 방법(GA, Greedy Approach)을 사용한 동적 채널 할당 알고리즘의 성능분석에 관한 것이다. GA를 기반으로 한 동적 채널 할당의 경우 사용자간의 다이버시티 효과를 통하여 성능 이득을 얻을 수 있다. 본 논문에서는 동적 채널 할당 알고리즘에서 다중 사용자 다이버시티 계수인 할당 가능한 사용자 수(NAU, Number of Allocable Users)를 모델링하고, 이를 통하여 GA를 기반으로 한 동적 채널 할당 알고리즘의 성능(실패 확률 및 데이터 전송량)을 분석한다. 분석된 결과를 기반으로 GA를 기반으로 한 동적 채널 할당 알고리즘의 성능을 최대화 할 수 있는 조건을 제시할 수 있다.