• Korean Journal of Microbiology
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• v.54 no.3
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• pp.254-265
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• 2018

Avian influenza recently damaged the poultry industry, which suffered a huge economic loss reaching billions of U.S. dollars in South Korea. Transmission routes of the pathogens would help plan to control and limit the spread of the devastating biological tragedy. Phylogenetic analyses of pathogen's DNA sequences could sketch transmission trees relating hosts with directed edges. The last decade has seen the methodological development of inferring transmission trees using epidemiological as well as genetic data. Here, I reanalyzed the DNA sequence data that had originated in the highly pathogenic avian influenza H5N8 outbreak of South Korea in 2014. The H5N8 viruses spread geographically contiguously from the origin of the outbreak, Jeonbuk. The Jeonbuk origin viruses were known to spread to four provinces neighboring Jeonbuk. I estimated the transmission tree of the host domestic and migratory wild birds after combining multiple runs of Markov chain Monte Carlo using a Bayesian method for inferring transmission trees. The estimated transmission tree, albeit with a rather large uncertainty in the directed edges, showed that the viruses spread from Jeonbuk through Chungnam to Gyeonggi. Domestic birds of breeder or broiler ducks were estimated to appear to be at the terminal nodes of the transmission tree. This observation confirmed that migratory wild birds played an important role as one of the main infection mediators in the avian influenza H5N8 outbreak of South Korea in 2014.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.174-179
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• 1998

This research explores the application of the bootstrap methods to the construction of control limits for the x charts and the EWMA charts based on single observations with stationary autoregressive processes. The subsample means-based control chars in the presence autocorrelation are also considered. We use a technique for inferring confidence intervals using bootstrap, the percentile method. Simulation studies are conducted to compare the performance of the bootstrap method and that of standard method for constructing control charts under several conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.719-724
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• 1998

This paper presents a systematic developement of a formal approach to inference in approximate reasoning. We introduce some measures of similarity and discuss their properties. Using the concept of similarity index we formulate two methods for inferring from vague knowledge. In order to illustrate the effectiveness of the proposed technique we use it to develop a vowel recognition system.

• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.1-13
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• 1994

Deep reasoning procedures are model-based, inferring single or multiple causes and/or timing relations from the knowledge of behavior of component models and their causal structure. The overall goal of this paper is to develop an automated deep reasoning methodology that exploits deep knowledge of structure and behavior of a system. We have proceeded by building a software environment that uses such knowledge to reason from advanced symbolic simulation techniques introduced by Chi and Zeigler. Such reasoning system has been implemented and tested on several examples in the domain of performance evaluation, and event-based control.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.397-410
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• 2007

For the two groups data from multivariate binomial distribution, we consider a bootstrap approach to inferring the simultaneous confidence level and its standard error of a collection of the dependent confidence intervals for the difference of proportions with an experimentwise error rate at the a level are presented. The bootstrap method is used to estimate the simultaneous confidence probability for the difference of proportions.

• Bioinformatics and Biosystems
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• v.2 no.1
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• pp.24-27
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• 2007

Human cell regulatory mechanism is one of suspicious problems among biologists. Here we tried to uncover the human breast cancer cell regulatory mechanism from gene expression data (Marc J. Van de vijver, et. al., 2002) using a module network algorithm which is suggested by Segal, et. al.(2003) Finally, we derived a module network which consists of 50 modules and 10 tree depths. Moreover, to validate this candidate network, we applied a GO enrichment test and known transcription factor-target relationships from Transfac(R) (V. Matys, et. al, 2006) and HPRD database (Peri, S. et al., 2003).

• Management Science and Financial Engineering
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• v.9 no.2
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• pp.13-20
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• 2003

For inferring criteria in a performance appraisal. linear programming (LP) has been utilized as an alternative to policy capturing (PC). Previous policy capturing LP (PCLP) studies were limited to the criteria of exact numerical ratings. However. under certain evaluation circumstances, a ranged rating with a lower and upper bound may be preferred over an exact numerical value. Therefore, this study introduces a new LP model that allows ranged ratings. A simple example is given to illustrate our model.

• Review of KIISC
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• v.7 no.2
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• pp.85-94
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• 1997

This paper describes the notion of a Multilevel Secure Knowledge Base Management System(MLS/KBMS). It states a security policy and security constraints. A design for query operation introduced cover story in a MLS/KBMS is discussed. Query processing approach is to provide cover stories that lead to alternative explanations for readily available information. Therefore such cover stories prevent an unauthorized user from inferring high-level information from low-level data.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.323-333
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• 2005

In this paper, we develop a MCMC method for estimating the skew normal distributions. The method utilizing the data augmentation technique gives a simple way of inferring the distribution where fully parametric frequentist approaches are not available for small to moderate sample cases. Necessary theories involved in the method and computation are provided. Two numerical examples are given to demonstrate the performance of the method.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.163-164
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• 2020

When measuring fine dust at a large-scale site such as complex construction, the change in the value of fine dust measurement is large due to the influence of the time, location, wind speed, wind direction, and humidity. This study aims to find out the results of measuring fine dust in an actual construction site and inferring the changes.