• Genomics & Informatics
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• 제1권2호
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• pp.94-100
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• 2003

Motivation: Many have observed a nonlinear relationship between the signal intensity and the transcript abundance in microarray data. The first step in analyzing the data is to normalize it properly, and this should include a correction for the nonlinearity. The commonly used linear normalization schemes do not address this problem. Results: Nonlinearity is present in both cDNA and oligonucleotide arrays, but we concentrate on the latter in this paper. Across a set of chips, we identify those genes whose within-chip ranks are relatively constant compared to other genes of similar intensity. For each gene, we compute the sum of the squares of the differences in its within-chip ranks between every pair of chips as our statistic and we select a small fraction of the genes with the minimal changes in ranks at each intensity level. These genes are most likely to be non-differentially expressed and are subsequently used in the normalization procedure. This method is a generalization of the rank-invariant normalization (Li and Wong, 2001), using all available chips rather than two at a time to gather more information, while using the chip that is least likely to be affected by nonlinear effects as the reference chip. The assumption in our method is that there are at least a small number of non­differentially expressed genes across the intensity range. The normalized expression values can be substantially different from the unnormalized values and may result in altered down-stream analysis.

• 응용통계연구
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• 제29권1호
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• pp.75-83
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• 2016

본 연구에서는 금융시장 통합화에 따른 금융 시장 전염을 생물학적 전염개념에 기초하여 분석하는 검정 방법론을 제시하였다. 금융 시장 통합화를 측정하기 위하여 U-통계량을 사용하였고, 금융 시장 전염 검정을 위하여 단일방정식 오차수정 모형을 중심으로 잠재 요인모형, 분위수 회귀모형과 런검정을 사용하였다. 시뮬레이션결과 단일방정식 오차수정 모형이 자기상관을 갖는 오차항을 포함한 선형 회귀모형에서 비교적 높은 수준의 적합도를 일관성 있게 보여 주고 있다.

• ETRI Journal
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• 제33권2호
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• pp.219-229
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• 2011

In this paper, we propose a transformation scheme used to analyze online gaming traffic properties and develop a traffic model. We analyze the packet size and the inter departure time distributions of a popular first-person shooter game (Left 4 Dead) and a massively multiplayer online role-playing game (World of Warcraft) in order to compare them to the existing scheme. Recent online gaming traffic is erratically distributed, so it is very difficult to analyze. Therefore, our research focuses on a transformation scheme to obtain new smooth patterns from a messy dataset. It extracts relatively heavy-weighted density data and then transforms them into a corresponding dataset domain to obtain a simplified graph. We compare the analytical model histogram, the chi-square statistic, and the quantile-quantile plot of the proposed scheme to an existing scheme. The results show that the proposed scheme demonstrates a good fit in all parts. The chi-square statistic of our scheme for the Left 4 Dead packet size distribution is less than one ninth of the existing one when dealing with erratic traffic.

• 한국지진공학회논문집
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• 제10권3호
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• pp.35-45
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• 2006

지진해일 위험재해도의 작성과 재해경감대책 수립을 위해서는 연안역의 상세한 수심 및 지형을 이용한 시뮬레이션이 요구되고 있다. 본 연구에서는 Beowulf 병렬계산을 통해 동해 전 영역에서 정밀산정이 가능한 병렬유한요소모형을 이용하여 1993년 7월 12일 동해안에 내습한 지진해일에 대한 시뮬레이션을 수행하고, 그 계산 결과와 관측치와의 비교결과를 제시한다. 또한, 해안에서의 지진 해일고의 통계적 분포에 대해 논하며, 해안에서의 지진해일고의 파고분포가 전반적으로 대수정규분포를 따르는 경향을 제시하였다.

• 응용통계연구
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• 제17권1호
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• pp.89-103
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• 2004

2차원 분할표 형태의 자료에 대해 두 범주형 변수들간의 독립성을 검정함에 있어, 만일 두 변수 각각의 모분포가 이미 완전히 알려진 경우라면 이 알려진 정보를 충족할 수 있도록 분할표 자료를 보정한 후 보정된 분할표 자료에 대해 전통적인 카이제곱 검정법을 적용하는 것이 더 타당함을 논증한다 그리고 이에 근거한 제약상황 카이제곱 독립성 검정법을 유도하고 모의실험을 통해 전통적인 무보정 카이제곱 검정법과 비교한다.

• Perspectives in Nursing Science
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• 제10권2호
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• pp.97-110
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• 2013

Purpose: This study sought to identify how initiating breastfeeding soon after birth affected breastfeeding practice. Methods: The subjects were mothers and newborns in Seoul's S. University Hospital maternity unit who elected to breastfeed. They were divided into an experimental group, which practiced an "early latching-on program" (latching-on within 30 minutes after birth), and a control group, which did not. Both groups' daily frequencies of breastfeeding and supplementary-glucose or bottle feeding were recorded. Results: The correlation between socio-demographic and medical characteristics and the breastfeeding rate was examined; 3 variables showed statistical significance: neonatal health anomaly, Apgar score after 1 minute, and Apgar score after 5 minutes. The difference in breastfeeding rates between the two groups was clear: the experimental group's rate was 1.93, while the control group's was 3.76 (t-statistic difference: 14.865), with the experimental group's rate during hospitalization being twice that of the control group (73.3% and 32.6%, respectively). Multiple regression analysis assessing the influence of the latching-on program yielded a t-statistic of -4.735 and a p-value of .000, indicating statistical significance. Conclusion: An early latching-on program's positive effect on the breastfeeding practice of mother's of newborns was demonstrated. Therefore, an early latching-on program could be a practical and effective nursing intervention for after mothers give birth.

• 한국지능시스템학회논문지
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• 제21권6호
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• pp.786-791
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• 2011

An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.

• 한국항해항만학회지
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• 제26권2호
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• pp.183-188
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• 2002

컨테이너 물동량 예측은 항만과 항만의 개발에 있어서 매우 중요하다. 일반적으로 이동평균법, 지수평활법, 회귀분석과 같은 통계적인 방법들은 물동량 예측에서 많이 사용되어졌다. 하지만, 컨테이너 물동량 예측에 영향을 주는 여러 가지 요소들을 고려해 보면 다중병렬처리시스템인 신경망을 이용하는 것이 효과적이다. 본 연구는 신경망의 역전파학습알고리즘을 이용하여 컨테이너 활동량을 예측하였다. 신경망을 이용하여 영향력 있는 요소들을 선별하였으며, 선별된 요소들을 이용하여 물동량 예측을 하였다. 또한 제안된 신경망 알고리즘과 통계적인 방법의 예측들을 비교하였다.

• 유통과학연구
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• 제14권1호
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• pp.93-102
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• 2016

Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.

• 디지털융복합연구
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• 제13권10호
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• pp.279-285
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• 2015

본 논문은 DNS를 이용한 보안 위협에 대응하기 위한 웹 기반의 실시간 질의 분석 및 제어 시스템을 제안한다. 제안 시스템은 DMZ로 유입되는 DNS 질의를 미러링하여 데이터를 수집하고 분석한다. 그 결과로 DNS 보안 위협을 발견하면 방화벽 필터링 정보로 사용하며 DNS 질의의 통계정보를 실시간으로 웹 서비스한다. DNS특정 문제만을 해결하기 위한 기존의 시스템에 비해 제안 시스템은 DNS 스푸핑, DNS 플러딩 공격, DNS 증폭 공격 등 다양한 공격에 대응하며, 불법적인 DNS의 사용을 미리 차단함으로써 내부로부터 발생할 수 있는 불법적인 침해 사고를 예방한다. 웹으로 실시간 DNS 통계 정보를 제공하고 GeoIP를 이용한 위치정보와 Google API의 지도를 이용하여 DNS 질의 발생과 관련하여 위치 정보를 제공한다. 현재까지의 DNS 공격에 대한 경험과 지식이 부족하기 때문에 웹 서비스와의 보안 융합 시스템을 이용하여 구축한 데이터베이스는 DNS 관련 보안 침해 공격에 대한 연구에 있어 향후 중요한 자료로 사용될 수 있다.