• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.419-428
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• 2006

The method of Reverse Ranked Ordering-Set Sampling(RROSS) as an opposed Ranked Ordering-Set Sampling(ROSS) and Ranked-Set Sampling(RSS) is discussed. We propose the test statistic using sign test on RROSS. This method is effective when observations are expensive and measurement is perhaps destructive or invasive. This method obtains more informations than ROSS and RSS. The asymptotic relative efficiencies of RROSS with respect to ROSS and RSS are always greater than 1 for all sample sizes. We consider a simple model to describe the effect of imperfect judgment errors.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.1
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• pp.138-143
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• 2011

In spite of abundant clinical resources of stroke patients, the objective and logical data analyses or diagnostic systems were not established in oriental medicine. As a part of researches for standardization and objectification of differentiation of syndromes for stroke, in this present study, we tried to develop the statistical diagnostic tool discriminating the 4 subtypes of syndrome differentiation using the essential indices considering the sex. Discriminant analysis was carried out using clinical data collected from 1,448 stroke patients who was identically diagnosed for the syndrome differentiation subtypes diagnosed by two clinical experts with more than 3 year experiences. Empirical discriminant model(V) for different sex was constructed using 61 significant symptoms and sign indices selected by stepwise selection. We comparison. We make comparison a between discriminant model(V) and discriminant model(IV) using 33 significant symptoms and sign indices selected by stepwise selection. Development of statistical diagnostic tool discriminating 4 subtypes by sex : The discriminant model with the 24 significant indices in women and the 19 significant indices in men was developed for discriminating the 4 subtypes of syndrome differentiation including phlegm-dampness, qi-deficiency, yin-deficiency and fire-heat. Diagnostic accuracy and prediction rate of syndrome differentiation by sex : The overall diagnostic accuracy and prediction rate of 4 syndrome differentiation subtypes using 24 symptom and sign indices was 74.63%(403/540) and 68.46%(89/130) in women, 19 symptom and sign indices was 72.05%(446/619) and 70.44%(112/159) in men. These results are almost same as those of that the overall diagnostic accuracy(73.68%) and prediction rate(70.59%) are analyzed by the discriminant model(IV) using 33 symptom and sign indices selected by stepwise selection. Considering sex, the statistical discriminant model(V) with significant 24 symptom and sign indices in women and 19 symptom and sign indices in men, instead of 33 indices would be used in the field of oriental medicine contributing to the objectification of syndrome differentiation with parsimony rule.

• International Journal of Reliability and Applications
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• v.3 no.4
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• pp.173-184
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• 2002

This paper introduces the joint structural importance of two components in a coherent system. Some relationships between joint structural importance and marginal structural importance are presented. It is shown that the sign of Joint structural importance can be determined, in advance, without computation in some special structures. The joint structural importance of two components in some series-parallel and parallel-series systems are established. Some practical examples are presented to elucidate some of the derived results.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.573-581
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• 2015

We study problems of sample size determination for one-sample location tests. A simulation study shows that sample size calculations based on approximated distribution do not achieve the nominal level of power. We investigate sample size determinations based on exact distribution and with a power that attains the nominal level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.5
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• pp.445-448
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• 1991

The two-sample locally optimum rank detection scheme is obtained which uses rank and sign statistics for detection of random signals in additive noise. It is shown that the detector is similar in structure to the locally optimum detector for random signals and to the one-sample locally optimum rank detector for random signals. It is also shown that the detector is a generalization of the two-sample locally optimum rank detector for known signals. In addition , the problem of two-sample locally optimum rank detection of random signals in multiple input case is considered briefly.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.293-301
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• 1995

Sums of independent random variables $S_n = X_1 + \cdots + X_n$ are considered, where the $X_n$ are chosen according to a stationary process of distributions. For $c > 0$, let $t_c$ be the smallest positive integer n such that $$\mid$S_n$\mid$ > cn^{\frac{1}{2}}$. In this set up we are concerned with finiteness of expectation of $t_c$ and we have some results of sign-invariant process as applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.379-383
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• 2003

A simpler nonparametric detector test statistic based on reference observation in addition to the rank statistics of regular observations is suggested in this letter. Using reference observations instead of sign statistics helps us a simpler detector structure especially for random signals buried in multiplicative noise.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.20-32
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• 2018

Purpose: The purpose of this study is to set up an anomaly detection criteria for sensor data coming from a motorcycle. Methods: Five sensor values for accelerator pedal, engine rpm, transmission rpm, gear and speed are obtained every 0.02 second from a motorcycle. Exploratory data analysis is used to find any pattern in the data. Traditional process control methods such as X control chart and time series models are fitted to find any anomaly behavior in the data. Finally unsupervised learning algorithm such as k-means clustering is used to find any anomaly spot in the sensor data. Results: According to exploratory data analysis, the distribution of accelerator pedal sensor values is very much skewed to the left. The motorcycle seemed to have been driven in a city at speed less than 45 kilometers per hour. Traditional process control charts such as X control chart fail due to severe autocorrelation in each sensor data. However, ARIMA model found three abnormal points where they are beyond 2 sigma limits in the control chart. We applied a copula based Markov chain to perform statistical process control for correlated observations. Copula based Markov model found anomaly behavior in the similar places as ARIMA model. In an unsupervised learning algorithm, large sensor values get subdivided into two, three, and four disjoint regions. So extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior in the sensor values. Conclusion: Exploratory data analysis is useful to find any pattern in the sensor data. Process control chart using ARIMA and Joe's copula based Markov model also give warnings near similar places in the data. Unsupervised learning algorithm shows us that the extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior.

• Journal of Korean Biological Nursing Science
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• v.22 no.4
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• pp.297-307
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• 2020

Purpose: The purpose of this research was to identify the relationships between stroke knowledge, health perception, exercise self-efficacy and stroke prevention behaviour and the factors influencing stroke prevention behaviour in middle-aged adults. Methods: A cross-sectional survey was conducted in 2 cities of Korea from May to July 2020, using structured questionnaire. The participants were 168 middle-aged adults without a history of stroke. Collected data were analyzed using descriptive statistics, independent t-test, one-way ANOVA, Pearson correlation coefficients, and multiple regression with SPSS/WIN 25.0. Results: There was significant correlations among degree of stroke prevention behaviour, stroke knowledge about warning sign (r= .20, p= .010), health perception (r= .35, p< .001) and exercise self-efficacy (r= .43, p< .001). The most important factor influencing stroke prevention behaviour was exercise self-efficacy (β= 0.38, p< .001), followed by health perception (β= 0.18, p= .008), body mass index (β= -0.17, p= .011), stroke knowledge about warning sign (β= 0.13, p= .045) in that order. These factors explained 37.7% of total variance in stroke prevention behaviour (F= 11.09, p< .001). Conclusion: The results of this study suggest that the development of nursing intervention for stroke prevention behaviour improvement is needed considering exercise self-efficacy and stroke knowledge.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.35-44
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• 1998

Road guide sign is one of important traffic facility, which guides a driver a direction to go. A road is being newly built and/or an existing road can be temporarily closed very often at metropolitan area. Such information has to be linked to a road guide sign and to be updated in time. Otherwise, it might cause not only confusion to a driver but also traffic accident and/or traffic congestion. However, road guide signs are not properly managed at this time since the amounts of information are huge and they are being managed through paper maps manually. A decision-making framework has been developed to manage a variety of information of road guide signs based on the concept of GIS(Geographic Information Systems). Especially, it is designed on the fact that the existing national digital base maps under the NGIS(National Geographic Information Systems) program can be utilized. This framework has several functions such as the manipulation of statistics, landmark linkages along the selected traffic corridor and automatic design of signboard's content. This system is applied to the Kangnam district in Seoul Metropolitan area (SMA) for a case study.