• Title/Summary/Keyword: Hierarchical Likelihood

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Identifying Copy Number Variants under Selection in Geographically Structured Populations Based on F-statistics

  • Song, Hae-Hiang;Hu, Hae-Jin;Seok, In-Hae;Chung, Yeun-Jun
    • Genomics & Informatics
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    • v.10 no.2
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    • pp.81-87
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    • 2012
  • Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional $F_{ST}$ measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the $F_{ST}$ estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific $F_{ST}$ and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.

A Study on the Theme Park Users' Choice behavior -Application of Constraints-Induced Conjoint Choice Model- (주제공원 이용자들의 선택행동 연구 -Constraints-Induced Conjoint Choice Model의 적용-)

  • 홍성권;이용훈
    • Journal of the Korean Institute of Landscape Architecture
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    • v.28 no.2
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    • pp.18-27
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    • 2000
  • The importance of constraints has been one of major issues in recreation for prediction of choice behavior; however, traditional conjoint choice model did not consider the effects of these variables or fail to integrate them into choice model adequately. The purposes of this research are (a) to estimate the effects of constraints in theme park choice behavior by the constraints-induced conjoint choice model, and (b) to test additional explanatory power of the additional constraints in this suggested model against the more parsimonious traditional model. A leading polling agency was employed to select respondents. Both alternative generating and choice set generating fractional factorial design were conducted to meet the necessary and sufficient conditions for calibration of the constraints-induced conjoint choice model. Th alternative-specific model was calibrated. The log-likelihood ratio test revealed that suggested model was accepted in the favor of the traditional model, and the goodness-of-fit($\rho$$^2$) of suggested and traditional model was 0.48427 and 0.47950, respectively. There was no difference between traditional and suggested model in estimates of attribute levels of car and shuttle bus because alternatives were created to estimate the effects of constraints independently from mode related variables. Most parameters values of constraints had the expected sign and magnitude: the results reflected the characteristics of the theme parks, such as abundance of natural attractions and poor accessibility in Everland, location of major fun rides indoor in Lotte World, city park like characteristics of Dream Land, and traffic jams in Seoul. Instead of the multinomial logit model, the nested logit model is recommended for future researches because this model more reasonably reflects the real decision-making process in park choice. Development of new methodology too integrate this hierarchical decision-making into choice model is anticipated.

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The Risk Assessment and Prediction for the Mixed Deterioration in Cable Bridges Using a Stochastic Bayesian Modeling (확률론적 베이지언 모델링에 의한 케이블 교량의 복합열화 리스크 평가 및 예측시스템)

  • Cho, Tae Jun;Lee, Jeong Bae;Kim, Seong Soo
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.16 no.5
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    • pp.29-39
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    • 2012
  • The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.

The Change of Work Careers in Youth Cohort pre and post-the Economic Crisis- (외환위기 전후 청년 코호트의 노동경력 비교)

  • Moon, Hey Jin
    • Korean Journal of Social Welfare
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    • v.65 no.1
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    • pp.201-226
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    • 2013
  • This study aims to identify changes in early work career of youth cohort entering the labor market pre and post-the economic crisis and compare career pathway types of different cohorts. Labor market experiences of youth cohort were constructed by sequencing the number of organizations, kinds of jobs, the scale of the business, and type of employment. In addition, a holistic sequence was created by including complementary factors. In this sense, the labor market experience in this study was conceptualized as a process involving continuous sequences and hierarchical and orderly changes which differs from a simple job mobility. Sequence analysis involving Optimal Matching method was conducted to examine whether such cohort-differences in labor market experiences were related to differences in distribution of career pathway types. The result showed that the post-economic crisis cohort had a relatively higher likelihood of falling into the non-employment type, unemployment type, non-corporate employment type, irregular employment type, and mobile employment type. These findings provide empirical evidence supporting the hypothesis that the employment precariousness of cohort has exacerbated after the economic crisis.

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Model selection method for categorical data with non-response (무응답을 가지고 있는 범주형 자료에 대한 모형 선택 방법)

  • Yoon, Yong-Hwa;Choi, Bo-Seung
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.627-641
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    • 2012
  • We consider a model estimation and model selection methods for the multi-way contingency table data with non-response or missing values. We also consider hierarchical Bayesian model in order to handle a boundary solution problem that can happen in the maximum likelihood estimation under non-ignorable non-response model and we deal with a model selection method to find the best model for the data. We utilized Bayes factors to handle model selection problem under Bayesian approach. We applied proposed method to the pre-election survey for the 2004 Korean National Assembly race. As a result, we got the non-ignorable non-response model was favored and the variable of voting intention was most suitable.

Human Error Analysis in a Permit to Work System: A Case Study in a Chemical Plant

  • Jahangiri, Mehdi;Hoboubi, Naser;Rostamabadi, Akbar;Keshavarzi, Sareh;Hosseini, Ali Akbar
    • Safety and Health at Work
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    • v.7 no.1
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    • pp.6-11
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    • 2016
  • Background: A permit to work (PTW) is a formal written system to control certain types of work which are identified as potentially hazardous. However, human error in PTW processes can lead to an accident. Methods: This cross-sectional, descriptive study was conducted to estimate the probability of human errors in PTWprocesses in a chemical plant in Iran. In the first stage, through interviewing the personnel and studying the procedure in the plant, the PTW process was analyzed using the hierarchical task analysis technique. In doing so, PTWwas considered as a goal and detailed tasks to achieve the goal were analyzed. In the next step, the standardized plant analysis risk-human (SPAR-H) reliability analysis method was applied for estimation of human error probability. Results: The mean probability of human error in the PTW system was estimated to be 0.11. The highest probability of human error in the PTW process was related to flammable gas testing (50.7%). Conclusion: The SPAR-H method applied in this study could analyze and quantify the potential human errors and extract the required measures for reducing the error probabilities in PTW system. Some suggestions to reduce the likelihood of errors, especially in the field of modifying the performance shaping factors and dependencies among tasks are provided.

Unsupervised Image Classification through Multisensor Fusion using Fuzzy Class Vector (퍼지 클래스 벡터를 이용하는 다중센서 융합에 의한 무감독 영상분류)

  • 이상훈
    • Korean Journal of Remote Sensing
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    • v.19 no.4
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    • pp.329-339
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    • 2003
  • In this study, an approach of image fusion in decision level has been proposed for unsupervised image classification using the images acquired from multiple sensors with different characteristics. The proposed method applies separately for each sensor the unsupervised image classification scheme based on spatial region growing segmentation, which makes use of hierarchical clustering, and computes iteratively the maximum likelihood estimates of fuzzy class vectors for the segmented regions by EM(expected maximization) algorithm. The fuzzy class vector is considered as an indicator vector whose elements represent the probabilities that the region belongs to the classes existed. Then, it combines the classification results of each sensor using the fuzzy class vectors. This approach does not require such a high precision in spatial coregistration between the images of different sensors as the image fusion scheme of pixel level does. In this study, the proposed method has been applied to multispectral SPOT and AIRSAR data observed over north-eastern area of Jeollabuk-do, and the experimental results show that it provides more correct information for the classification than the scheme using an augmented vector technique, which is the most conventional approach of image fusion in pixel level.

Associations Between Conventional Healthy Behaviors and Social Distancing During the COVID-19 Pandemic: Evidence From the 2020 Community Health Survey in Korea

  • Rang Hee, Kwon;Minsoo, Jung
    • Journal of Preventive Medicine and Public Health
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    • v.55 no.6
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    • pp.568-577
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    • 2022
  • Objectives: Many studies have shown that social distancing, as a non-pharmaceutical intervention (NPI) that is one of the various measures against coronavirus disease 2019 (COVID-19), is an effective preventive measure to suppress the spread of infectious diseases. This study explored the relationships between traditional health-related behaviors in Korea and social distancing practices during the COVID-19 pandemic. Methods: Data were obtained from the 2020 Community Health Survey conducted by the Korea Disease Control and Prevention Agency (n=98 149). The dependent variable was the degree of social distancing practice to cope with the COVID-19 epidemic. Independent variables included health-risk behaviors and health-promoting behaviors. The moderators were vaccination and unmet medical needs. Predictors affecting the practice of social distancing were identified through hierarchical multiple logistic regression analysis. Results: Smokers (adjusted odds ratio [aOR], 0.924) and frequent drinkers (aOR, 0.933) were more likely not to practice social distancing. A greater degree of physical activity was associated with a higher likelihood of practicing social distancing (aOR, 1.029). People who were vaccinated against influenza were more likely to practice social distancing than those who were not (aOR, 1.150). However, people with unmet medical needs were less likely to practice social distancing than those who did not experience unmet medical needs (aOR, 0.757). Conclusions: Social distancing practices were related to traditional health behaviors such as smoking, drinking, and physical activity. Their patterns showed a clustering effect of health inequality. Therefore, when establishing a strategy to strengthen social distancing, a strategy to protect the vulnerable should be considered concomitantly.

Genomic partitioning of growth traits using a high-density single nucleotide polymorphism array in Hanwoo (Korean cattle)

  • Park, Mi Na;Seo, Dongwon;Chung, Ki-Yong;Lee, Soo-Hyun;Chung, Yoon-Ji;Lee, Hyo-Jun;Lee, Jun-Heon;Park, Byoungho;Choi, Tae-Jeong;Lee, Seung-Hwan
    • Asian-Australasian Journal of Animal Sciences
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    • v.33 no.10
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    • pp.1558-1565
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    • 2020
  • Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ2g, the third 0.001×σ2g, and the fourth to 0.01×σ2g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

The Associated Factors of Protective Behaviors for Radiation Exposure based on Health Belief Model Honam Province Radiologic Technologists (건강신념모델을 적용한 호남지역 방사선사의 방사선 방어행위 수행도 관련 요인)

  • Yoon, Yo-Sang;Ryu, So-Yeon;Park, Jong;Choi, Seong-Woo;Oh, Hye-Jong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.3
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    • pp.96-107
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    • 2020
  • This study aimed to identify the associated factors of protective behaviors for radiation exposure among some radiology technologists using the Health Belief Model. The subjects of the study were 541 radiology technologists working at hospitals or clinics in Honam Province. Using the SPSS version 18.0 program, data were analyzed using a t-test, ANOVA, Pearson's correlation analysis, and hierarchical multiple logistic regression analysis. To modify the factors, the performance of subjects who had a higher level of education and nuclear medicine rooms were higher than those who worked in simple radiography rooms. The radiation protective behaviors performance of the subjects who had more exercise, medium-level stress, and worked in higher-quality protection facilities was higher. Regarding the personal perceptions, the cues to action (β=.292, p=.0001), and perceived seriousness (β =.075, p=.010) were factors that had effects on the performance of radiation protection behaviors. Regarding the likelihood of action, the benefits (β=.168, p<.0001), self-efficacy (β=.148, p=.007), and the performance of protective behaviors were higher. In conclusion, protection education as a cue to action should be provided to stimulate protective behaviors, and the benefits of protective behaviors should be emphasized. To increase the performance of protection behaviors, self-efficacy should be enhanced, and the subjects are offered appropriate information that helps perceive seriousness.