• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.335-344
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• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.143-149
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• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.277-286
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• 2010

In this paper amplitude and phase distortion of the received signal through a fading channel results in a severe performance degradation of the communication system, Therefore we consider the variance of the maximum a posteriori phase estimate of sinusoidal signal by the Cramer-Rao bound in wireless fading channel. To find the Cramer-Rao lower bound for the variance of the phase, We use the derived probability density function(pdf) of the phase in Nakagami fading channel. We analyze the error performance of modulation signals using order statistics on generalized combining reception and find adequate diversity branch number.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.49-69
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• 2010

In this paper, we propose a class of spectrum sensing schemes for cognitive radio with receive diversity. By considering the generalized likelihood ratio test detector in each branch and exploiting non-linear diversity combining strategy, the proposed scheme exhibits reasonable performance for spectrum sensing even in the environment of heavier-tailed noise. From the results of analysis and computer simulations, it is observed that the proposed scheme provides significant performance gain and performance stability over the conventional schemes, especially in impulsive noise environment.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.146-156
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• 1989

This paper discusses how to choose speech parameters and decision logics to improve the performance of speaker recognition systems. It also considers the influence of the reference patterns on the speaker recognition. It is observed from the performance analysis based on LPSs, PARCOR coefficients and LPC-cepstrum coefficients that LPC-cepstrum coefficients are superior to the others in speaker recognition without regard to the reference patterns. In order to improve the recognition performance, a new decision logic is proposed based on a generalized-distance concept. It differs from the existing methods in that it considers the statistics of customer and impostors at the same time. It turns out from a speaker verification test that the proposed decision logic ferforms better than the existing ones.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.339-344
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• 2015

NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, infinite failures NHPP models that repairing software failure point in time reflects the situation, was presented for comparing property. Commonly used in the field of software reliability based on Weibull extension distribution software reliability of infinite failures was presented for comparison problem. The result is that a relatively large shape parameter was effectively. The parameters estimation using maximum likelihood estimation was conducted and Model selection was performed using the mean square error and the coefficient of determination. In this research, software developers to identify software failure property follows shape parameter, some extent be able to help is considered.

• Journal of Korean Society on Water Environment
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• v.29 no.5
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.213-222
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• 2008

The goal of this research was to search for an optimum training program that increases archery performance skills in order to develop a performance training and support. For this research, by examining the existing sports statistics program, information management system, and other related documents, we were able to derive an athlete management realm as well as find archer factors. Also through a council we categorized the factors that constituted the training general management. The archery training general management system consists of six realms. First is the log-in and main screen realm. Second is the athlete information category. Third, the point of impact information category. Fourth, the shift-in-frequency analysis realm. Fifth, in the detailed analysis realm. Thus, the developed archery training general management system allows for a more generalized and scientific athlete management and support system. and it has turned out to be an adequate system for archer's performance.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.587-598
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• 2016

In predicting an outcome of election using a variety of methods ahead of the election, non-response is one of the major issues. Therefore, to address the non-response issue, a variety of methods of non-response imputation may be employed, but the result of forecasting tend to vary according to methods. In this study, in order to improve electoral forecasts, we studied a model based method of non-response imputation attempting to apply the Monte Carlo Expectation Maximization (MCEM) algorithm, introduced by Wei and Tanner (1990). The MCEM algorithm using maximum likelihood estimates (MLEs) is applied to solve the boundary solution problem under the non-ignorable non-response mechanism. We performed the simulation studies to compare estimation performance among MCEM, maximum likelihood estimation, and Bayesian estimation method. The results of simulation studies showed that MCEM method can be a reasonable candidate for non-response model estimation. We also applied MCEM method to the Korean presidential election exit poll data of 2012 and investigated prediction performance using modified within precinct error (MWPE) criterion (Bautista et al., 2007).

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.27-39
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• 2024

Purpose : Smoking is a major factor in chronic obstructive pulmonary disease (COPD), but the effect of electrical cigarette smoking on COPD development is still uncertain. This study aimed to compare the functions of airways and lungs exposed to combustible cigarettes and electrical cigarettes based on the pulmonary function test (PFT) results from the Korean National Health and Nutrition Examination Survey (NHANES). Methods : This study used data from 8,942 participants with PFT results out of 47,309 total subjects from the 6th to 8th Korean NHANES (2014-2015, 2016-2018, and 2019, respectively). Individuals with diseases such as cancer, ex-smokers, and dual tobacco users were excluded. The PFT results were analyzed according to the COPD diagnostic criteria. After adjusting for confounding variables, a complex sample generalized linear model ANOVA test was performed to investigate the association between PFT results and combustible smoker or electrical cigarette user groups. Results : In an analysis based on the obstructive ventilatory disorders (forced expiratory volume in 1 second[FEV₁]/forced vital capacity[FVC]<.7), combustible cigarette smokers showed a 3.46 times higher risk of COPD compared to non-smokers, while electrical cigarette smokers exhibited no significant difference in terms of COPD-related risks compared to non-smokers. FEV₁ showed a negative relation with combustible cigarette smokers as reported elsewhere (B=-.07, p<.001). FEV₁/FVC was negatively related to both combustible cigarette smokers (B=-.03, p<.001) and electrical cigarette smokers (B=-.02, p<.001). Conclusion : FEV₁/FVC decreases were observed in the long-term exposure to both combustible and electrical cigarettes. The lower FEV₁ in the combustible cigarette group implies the worsening of the severity of COPD, suggesting more damage to the airways and lungs in the short term. Therefore, the temporary electrical cigarettes use for the transition period in order to smoking cessation potentially aids to reduce the harmful effect of combustible cigarettes in COPD development.