• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.45-53
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the $x^2$ reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.309-322
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• 2023

The Hawkes process is a point process with self-exciting characteristics. It has been mainly used to describe seismic phenomena in which aftershocks occur due to the main earthquake. Recently, it has been used to explain various phenomena with self-exciting properties, such as the spread of infectious diseases and the spread of news on SNS. The Hawkes process can be flexibly modified according to the characteristics of events by using various types of excitation functions. Since it is difficult to implement a maximum likelihood estimator numerically, estimation methods have been improved until recently. In this paper, the conditional intensity function and excitation function are explained to describe the Hawkes process. Then, existing examples of Hawkes processes used in seismic, epidemiological, criminal, and financial fields are described and estimation methods are introduced. I analyze earthquakes that occurred in gyeongsang-do, Korea from November 2017 to December 2022, using R package ETAS.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.159-166
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• 2012

There are several ways such as GPS(Global Positioning System) and INS (Inertial Navigation System) to track the location of moving vehicle. The GPS has the advantages of having non-accumulative error even if it brings about errors. In order to obtain the position information, we need to receive at least 3 satellites information. But, the weak point is that GPS is not useful when the 혠 signal is weak or it is in the incommunicable region such as tunnel. In the case of INS, the information of the position and posture of mobile with several Hz~several hundreds Hz data speed is recorded for velocity, direction. INS shows a very precise navigational performance for a short period, but it has the disadvantage of increasing velocity components because of the accumulated error during integration over time. In this paper, sensor fusion algorithm is applied to both of INS and GPS for the position information to overcome the drawbacks. The proposed system gets an accurate position information from experiment using SVD in a non-accessible GPS terrain.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.75-76
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• 2008

본 논문에서는 한국형 에너지 관리 시스템의 계통 해석용 프로그램을 위한 공통 데이터 모델의 구축에 대해 다루었다. 공통 데이터 모델이란 다양한 어플리케이션이 공유하여 사용할 수 있는 계통 모델의 데이터베이스를 가리키며 본 논문에서는 토폴로지 프로세서(topology processor, TP), 상태추정(state estimator, SE), 급전원 조류계산(dispatcher power flow, DPF), 휴전계획(outage scheduler, OS), 부하 분포계수(bus load distribution factor, BLDF), 송전 손실 민감도 계수(transmission loss sensitivity factor, TLSF) 등을 위한 공통 모델에 대해 다루었다. 공통 모델의 구축을 위해 각 어플리케이션에서 필요한 정보를 수집하여 전력계통의 토폴로지 구조과 계통 설비를 모델링 하였다. 최종적으로 계층적(hierarchy) 구조와 비계층적(non-hierarchy) 구조로 나뉘어진 직접(direct) 및 간접(indirect) 인덱스 코드를 사용하여 데이터로의 빠른 접근이 가능한 실시간 데이터베이스 형태를 제시하였다.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.877-888
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• 2017

Spectral analysis is used to determine the frequency of time series data. We first determine the frequency of the series through the power spectrum or the periodogram and then calculate the period of a cycle that may exist in a time series. Estimating the frequency using a Bayesian technique has been developed and proven to be useful; however, the Bayesian estimator for the frequency cannot be analytically solved through mathematical equations and may be handled numerically or computationally. In this paper, we make an inference on the Bayesian frequency through both resampling a parameter by Markov chain Monte Carlo (MCMC) methods and resampling data by bootstrap methods for a time series. We take the Korean real estate price index as an example for Bayesian frequency estimation. We have found a difference in the periods between the sale price index and the long term rental price index, but the difference is not statistically significant.

• Korean Journal of Plant Taxonomy
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• v.47 no.1
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• pp.11-22
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• 2017

Prangos fedtschenkoi (Regel et Schmalh.) Korovin (Apiaceae) is an endemic species for mountainous Middle Asia, which is both a rare and useful plant. Organic extractions from this species are being used in pharmaceutics and cosmetology. In recent years, P. fedtschenkoi distribution area has considerably decreased, presumably, resulting from human activities such as agriculture, construction works, overgrazing and collection from wild for pharmaceutic purposes. Six populations were found in Uzbekistan and their genetic divergence and differentiation were studied with 10 inter-simple sequence repeat (ISSR) markers, selected out of 101. Totally 166 amplified ISSR fragments (loci) were revealed, of which 164 were polymorphic. Relatively moderate level of polymorphism was found at population level with polymorphic bands ranging from 27.71% to 47.59%. Mean P = 39.05%, $N_a=1.40$, $N_e=1.25$, S.I. = 0.21, and $H_e=0.14$ were revealed for all loci across six populations. AMOVA showed higher variation among populations (62%) than within them (38%). The Bayesian model determined 5 clusters, or genetic groups. The posteriori distribution of the Theta II estimator detected full model identifying high inbreeding, intensified by low gene flow (Nm = 0.3954). Mantel test confined population 6 as distinct cluster corresponding to geographic remoteness (R = 0.5137, $p{\leq}0.005$). Results were used as the bases for developing conserve measures to restore populations.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.589-597
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• 2021

In simple and multiple regression, there is a difference in the meaning of regression coefficients, and not only are the estimates of regression coefficients different, but they also have different signs. Understanding the relative contribution of explanatory variables in a regression model is an important part of regression analysis. In a standardized regression model, the regression coefficient can be interpreted as the change in the response variable with respect to the standard deviation when the explanatory variable increases by the standard deviation in a situation where the values of the explanatory variables other than the corresponding explanatory variable are fixed. However, the size of the standardized regression coefficient is not a proper measure of the relative importance of each explanatory variable. In this paper, the estimator of the regression coefficient in multiple regression is expressed as a function of the correlation coefficient and the coefficient of determination. Furthermore, it is considered in terms of the effect of an additional explanatory variable and additional increase in the coefficient of determination. We also explore the relationship between estimates of regression coefficients and correlation coefficients in various plots. These results are specifically applied when there are two explanatory variables.

• Journal of Preventive Medicine and Public Health
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• v.57 no.5
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• pp.499-507
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• 2024

Objectives: This study aimed to compare the Delta, Greenland, and Monte Carlo methods for estimating 95% confidence intervals (CIs) of the population-attributable fraction (PAF). The objectives were to identify the optimal method and to determine the influence of primary parameters on PAF calculations. Methods: A dataset was simulated using hypothetical values for primary parameters (population, relative risk [RR], prevalence, and variance of the beta estimator ) involved in PAF calculations. Three methods (Delta, Greenland, and Monte Carlo) were used to estimate the 95% CIs of the PAFs. Perturbation analysis was performed to assess the sensitivity of the PAF to changes in these parameters. An R Shiny application, the "GDM-PAF CI Explorer," was developed to facilitate the analysis and visualization of these computations. Results: No significant differences were observed among the 3 methods when both the RR and p-value were low. The Delta method performed well under conditions of low prevalence or minimal RR, while Greenland's method was effective in scenarios with high prevalence. Meanwhile, the Monte Carlo method calculated 95% CIs of PAFs that were stable overall, though it required intensive computational resources. In a novel approach that utilized perturbation for sensitivity analysis, was identified as the most influential parameter in the estimation of CIs. Conclusions: This study emphasizes the necessity of a careful approach for comparing 95% CI estimation methods for PAFs and selecting the method that best suits the context. It provides practical guidelines to researchers to increase the reliability and accuracy of epidemiological studies.

• Journal of Preventive Medicine and Public Health
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• v.30 no.1 s.56
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• pp.31-43
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• 1997

Obesity usually is defined as the presence of and abnormally amount of adipose tissue. In many epidemiologic study, obesity as a health risk factor has been estimated by Body Mass Index(BMI) in general. This study was conducted to review of body fat percent measured by Bioelectric impedance analyzer as a estimator of obesity in a rural adult population. The study subjects were 421 men and 664 women who reside in the area on the Juam lake. They were sampled by multistage cluster sampling. Their mean age was 59 years old. Body fat percent increased with age, but BMI decreased with age in this study. Body fat percent was more larger at female and elder on the same BMI. The correlation coefficient between with body fat percent and body mass index was low (r=0.4737). Body fat percent was explained by not only BMI but also sex and age $(r^2=0.63)$. The result suggested that it is inadequate for BMI only to estimate obesity about elderly person who reside in the rural community. The relation of body fat percent and body mass index of this study agreed with the preceding know-ledges and studies in general.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.