• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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• pp.135-146
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• 2017

This paper considers redundancy optimization problems of multi-level systems and reviews existing papers which proposed various optimization models and used different algorithms in this research area. Three different mathematical models are studied: Multi-level redundancy allocation (MRAP), multiple multi-level redundancy allocation, and availability-based MRAP models. Many meta-heuristics are applied to find optimal solutions in the several optimization problems. We summarized key idea of meta-heuristics applied to the existing MARP problems. Two extended models (MRAP with interval reliability of units and an integrated optimization problem of MRAP and preventive maintenance) are studied and further research ideas are discussed.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2033-2036
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• 2013

Many studies have suggested that the XRCC1 Arg280His gene polymorphism might be involved in the development of hepatocellular carcinoma (HCC). However, the results have been inconsistent. In this study, the authors performed a meta-analysis to assess the association between XRCC1 Arg280His and HCC susceptibility. Published literature from PubMed, EMBASE and CNKI Data was searched. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using fixed- or random-effects models when appropriate. Begg's test was used to measure publication bias. A total of 7 case-control studies covering 1,448 HCC cases and 1,544 controls were included. No significant variation in HCC risk was detected in any of the genetic models overall. In the stratified analysis, four studies with sample sizes over 300 produced similar results. The corresponding pooled ORs were not substantially altered after the exclusion of three studies deviating from Hardy-Weinberg equilibrium in the control group, which indicated reliability for our meta-analysis results.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.1
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• pp.45-61
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• 2008

Meta-analysis refers to the analysis of analysis. It is the statistical analysis of a large collection of analysis results from individual studies for the purpose of summarizing, integrating and interpreting the inconsistent findings. However, no meta-analysis study has been conducted in Library and Information Science in Korea. This Study introduced the characteristics, basic principles, analysis procesure, and major models of meta-analysis, reviewed meta-analysis studies in Library and Information Science, and discussed major problems in conducting meta-analysis in Library and Information Science especially in Korea.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5663-5667
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• 2015

Background: Earlier studies on the association between p53 codon 72 Arg>Pro polymorphism and cancer risk were inconclusive and conflicting for the Saudi population. Therefore, we performed a meta-analysis to investigate the relationship between the codon 72 Arg>Pro polymorphism and overall cancer risk in Saudi Arabia. Materials and Methods: We searched all eligible published studies and data were pooled together to perform the meta-analysis. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for homozygous, heterozygous, dominant and recessive genetic models. Results: A total of five eligible published studies covering 502 cancer cases and 784 healthy controls were included in the meta-analysis. No publication bias was detected in this study. The results suggested that the variant (Pro vs Arg: p=0.960; OR=1.004, 95% CI=0.852-1.183), homozygous (Pro.Pro vs Arg.Arg: p=0.970; OR=1.006, 95% CI=0.729-1.390), heterozygous (Arg.Pro vs Arg.Arg: p=0.473; OR=0.783, 95% CI=0.402-1.527) carriers were not associated with overall cancer risk. Similarly, dominant (Pro.Pro+Pro.Arg vs Arg.Arg: p=0.632; OR=0.886, 95% CI=0.540-1.454) and recessive (Pro.Pro vs Pro.Arg+Arg.Arg: p=0.269; OR=1.163, 95%CI=0.890-1.521) models also did not indicate increased risk of cancer. Conclusions: The current meta-analysis suggests that the codon 72 Arg>Pro polymorphism of the p53 gene might not contribute to cancer susceptibility in Saudi population. Future well designed large case control studies are needed to validate our findings.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.125-139
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• 2017

In this paper, we developed a framework to detect and predict insider information leakage by collecting and restoring network traffic. For automated behavior analysis, many meta information and behavior information obtained using network traffic collection are used as machine learning features. By these features, we created and learned behavior model, network model and protocol-specific models. In addition, the ensemble model was developed by digitizing and summing the results of various models. We developed a function to present information leakage candidates and view meta information and behavior information from various perspectives using the visual analysis. This supports to rule-based threat detection and machine learning based threat detection. In the future, we plan to make an ensemble model that applies a regression model to the results of the models, and plan to develop a model with deep learning technology.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.425-448
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• 2003

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution proposed originally by Chen et al. (1999) and Branco and Dey (2001). These rich classes of models combine the information of independent studies, allowing investigation of variability both between and within studies, and incorporate weight function. Here, the testing for the skewness parameter is discussed. The score test statistic for such a test can be shown to be expressed as the posterior expectations. Also, we consider the detail computational scheme under skewed normal and skewed Student-t distribution using MCMC method. Finally, we introduce one example from Johnson (1993)'s real data and apply our proposed methodology. We investigate sensitivity of our results under different skewed errors and under different prior distributions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.308-313
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• 2016

Modern systems have become more and more complex due to the ever-increasing user requirements and rapid advance of technology. As such, the frequency of accidents due to system design errors or failure has been increasing. When the damage incurred by accidents to human beings or property is serious, the underlying systems are referred to as safety-critical systems. The development of such systems requires special efforts to ensure the safety of the human beings operating them. To cope with such a requirement, in this paper an approach is employed in which we consider safety starting from the conceptual design phase of the systems. Specifically, a systems design method that can detect functional failure is proposed by utilizing meta-models and M&S methods. To accomplish this, the safety design data from international safety standards are first extracted and also a meta-model is generated using SysML (systems modeling language). Then, a SysML-based system design method is proposed based on the use of the developed meta-model. We also discuss how the safety requirements can be created and verified using a simulation method. Finally, through a case study in automotive design, it is demonstrated that the detection of a functional failure and the verification of a safety requirement can be accomplished using the SysML-based M&S method. This study indicates that the use of meta-models can be useful for collecting and managing safety data and that the meta-model based M&S method can make it possible to satisfy the system requirements by reducing the design errors.

• Korea Trade Review
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• v.41 no.3
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• pp.27-42
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• 2016

This study is to investigate seaport clustering by using meta-frontier and cross-efficiency models. Data covers the 13 Asian ports during 2009, 2010 and 2013 with 3 inputs(depth, total area, and number of cranes) and 1 output(TEU). Correlations coefficient from cross-efficiency matrix are used for measuring clustering dendrogram. After that, meta-frontier analysis for investigating whether the clustering using cross-efficiency method increases the meta-efficiency. Empirical main results are as follows: First, group efficiencies of Busan, Incheon, and Gwangyang ports are increased. Second, meta and group efficiencies of China ports are greater than those of Korean ports. Third, distortion of technology gap of Gwangyang is lower than that of Busan and Incheon. Fourth, Gwangyang, clustering with Ningbo, Chingtao, Tokyo and Caosung ports in 2009 and with Dubai port in 2013 can increase the efficiency. Fifth, to enhance the efficiency, Busan port should be clustered to group 2 in 2010 and group 1 in 2013, and Incheon port clustered to group 2 in 2010 and 2013. Fifth, it is empirically investigated that Busan, Incheon and Gwangyang ports can increase the efficiency by using Cross-efficiency and Meta-frontier models. Port policy planner should promote the clustering policy for Busan with Hong Kong, Shanghai, and Singapore, Incheon and Gwangyang with Chingtao, Nagoya, Ningbo, Tokyo, and Kaoshung ports.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.425-431
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• 2005

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.5
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• pp.501-507
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• 2010

Structural optimization is performed to minimize the weight of a RC building structure, which has eight floors above ground and three underground, under gravity, wind, and seismic loads. Design optimization problem is formulated to find the values of the design variables that minimize the volume while satisfying various design and side constraints. To solved the optimization problem posed, several design techniques equipped in PIAnO, a commercial PIDO tool, are used. DOE is used to generate training points and structural analysis is performed using MIADS Gen, a general-purpose structural analysis CAE tool. Then, meta-models are generated from structural analysis results and accuracies of meta-models are evaluated. Next, design optimization is performed by using the verified meta-models and optimization technique equipped in PIAnO. Finally, we obtained optimal results, which could demonstrate the effectiveness of our design method.