• Genomics & Informatics
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• 제20권2호
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• pp.16.1-16.12
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• 2022

Various methodologies for the genetic analysis of longitudinal data have been proposed and applied to data from large-scale genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with traits of interest and to detect SNP-time interactions. We recently proposed a grid-based Bayesian mixed model for longitudinal genetic data and showed that our Bayesian method increased the statistical power compared to the corresponding univariate method and well detected SNP-time interactions. In this paper, we further analyze longitudinal obesity-related traits such as body mass index, hip circumference, waist circumference, and waist-hip ratio from Korea Association Resource data to evaluate the proposed Bayesian method. We first conducted GWAS analyses of cross-sectional traits and combined the results of GWAS analyses through a meta-analysis based on a trajectory model and a random-effects model. We then applied our Bayesian method to a subset of SNPs selected by meta-analysis to further discover SNPs associated with traits of interest and SNP-time interactions. The proposed Bayesian method identified several novel SNPs associated with longitudinal obesity-related traits, and almost 25% of the identified SNPs had significant p-values for SNP-time interactions.

• 천문학회지
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• 제29권spc1호
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• pp.125-126
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• 1996

Beijing-Arizona-Taipei-Connecticut (BATC) survey is a long term project to map the spectral energy distribution of various objects using 15 intermediate band filters and aims to cover about 450 sq degrees of northern sky. The SED information, combined with image structure information, is used to classify objects into several stellar and galaxy categories as well as QSO candidates. In this paper, we present a preliminary setup of robust data reduction procedure recently developed at NCU and also briefly discuss general classification scheme: redshift estimate, and automatic detection of variable objects.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 제4회 압출 및 인발가공 심포지엄
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• pp.45-53
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• 2001

Copper bus-bar is made by drawing process and used in many part of industry. When design drawing die for copper bus-bar, design factor is focused on the deformation of die-land by drawing force and shrink fit. In this paper, to determine shrink fit value is analyzed by automatic shrink fit analysis program, APDL/UIDL language in a commercial FEM package, ANSYS, has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process and by using DEFORM software for drawing process analysis. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the drawing die design. The stress analysis of the dies is used to determine optimized dimension of die-land.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.166-171
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• 2001

Copper bus-bar is made by drawing process and used in many part of industry. When design drawing die for copper bus-bar, design factor is focused on the deformation of die-land by drawing force and shrink fit. In this paper, to determine shrink fit value is analyzed by automatic shrink fit analysis program, APDL/UIDL language in a commercial FEM package, ANSYS, has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process and by using DEFORM software for drawing process analysis. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the drawing die design. The stress analysis of the dies is used to determine optimized dimension of die-land.

• 터널과지하공간
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• 제8권2호
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• pp.139-145
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• 1998

The reliable estimation of the system parameters and the accurate prediction of the system behavior are important to design underground structures safely and economically. Especially, the elastic modulus and the in-situ stresses are very important parameters in predicting the behavior of the underground structure. Therefore, the back analysis using the field measurement data is developed to determine accurately the elastic modulus and the in-situ stresses of the underground structural system in this study. A back analysis using the combined finite and boundary element is developed. It can consider the far field boundary condition and is efficient in computation. In this study, a back analysis is performed to predict behaviors of underground structures for the real construction site. The comparison between the results of the back analysis with field measurement data and the obtained material properties from the field test shows good agreement for the real construction site.

• Food Science and Biotechnology
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• 제15권4호
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• pp.494-498
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• 2006

An increase in variance (overdispersion) can occur when a binomial statistical analysis is applied to sensory difference test data in which replicate sensory evaluations (tastings) and multiple evaluators (judges) are combined to increase the sample size. Such a practice can cause extensive Type I errors, leading to serious misinterpretations of the data, especially when traditional simple binomial analysis is applied. Alternatively, the use of beta binomial analysis will circumvent the problem of overdispersion. This brief review discusses the uses and computation methodology of beta binomial analysis and in practice evidence for the occurrence of overdispersion.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• 한국의류학회지
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• 제19권6호
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• pp.924-932
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• 1995

Concept of the comfort and fitness has become a major concern in the basic function of the ready.made clothes. Until now ready-made clothes were not made by on the basis of the bodytype, but by the body size only This research was performed to classify and characterize the bodytypes of Korean adult males. Sample size was 1290 subjects and their age range was from 19 to 54 years old. 25 variables from the photographic data were applied to analyze the bodytype of trunk. Data were analyzed by the multivariate method, especially factor and cluster analysis. The groups forming a cluster can be subdivided into 5 sets by crosstabulation extracted by the hierarchical cluster analysis. 5 bodytypes classified by the photographic sources could be combined with the anthropometric data and were demonstrated with 5 silhouette. Type 3 and 4 in trunk were dominant and were composed of the majority of 55.6% of the subjects. Bodytypes of Korean males were influenced by the degree of posture erectness and of curvature of the front side of the body in waist and abdomen.

• 산업기술연구
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• 제28권B호
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• pp.101-109
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• 2008

In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.

• Journal of Preventive Medicine and Public Health
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• 제33권1호
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• pp.125-133
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• 2000

Objectives : This study uses meta-analysis methodology to examine the statistical consistency and importance of random variation among results of epidemiologic studies of occupational electromagnetic field exposure and leukemia. Methods : Studies for this meta-analysis were identified from previous reviews and by asking researcher active in this field for recommendations. Overall, 27 studies of occupational electromagnetic field exposures and leukemia were reviewed. A variety of meta-analysis statistical methods have been used to assess combined effects, to identify heterogeneity, and to provide a single summary risk estimate based on a set of simiar epidemiologic studies. In this study, classification of exposure metircs on occupational epidemiologic studies are reported for (1) job classification (20 individual studies); (2) leukemia subtypes (13 individual studies); and (3) country (27 individual studies). Results : Results of this study, an inverse-variance weighted pooling of all the data leads to a small but significant elevation in risk of f 1% (OR=1.11, 95% CI : $1.06\sim1.16$) among 27 occupational epidemiologic studies. Publication bias was assessed by the 'fail-safe n' that may be not influence for all combined results exception a few categories, ie, 'power station operators' and 'electric utility workers' by job classification on occupational study. And ail combined odds ratio results were similar for fixed-effects models and random-effects models, with slightly higher risk estimates for the random-effects model in situations where there was significant heterogeneity, ie, Q-statistic significant (p<.05). Conclusions : We found a small elevation in risk of leukemia, but the ubiquitous nature of exposure to electromagnetic fields from workplace makes even a weak association a public health issue of substantial power to influence the present overall conclusion about relationship between electromagnetic fields exposure and leukemia.