• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9643-9647
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• 2014

Background: Several studies have been performed to investigate the association of the HER2 Ile655Val polymorphism and breast cancer risk. However, the results were inconsistent. To understand the precise relationship, a meta-analysis was here conducted. Materials and Methods: A search of PubMed conducted to investigate links between the HER2 Ile655Val polymorphism and breast cancer, identified a total of 32 studies, of which 29, including 14,926 cases and 15,768 controls, with odds ratios (ORs) with 95% confidence intervals were used to assess any association. Results: In the overall analysis, the HER2 Ile655Val polymorphism was associated with breast cancer in an additive genetic model (OR=1.136, 95% CI 1.043-1.239, p=0.004) and in a dominant genetic (OR=1.118, 95% CI 1.020-1.227, p=0.018), while no association was found in a recessive genetic model. On subgroup analysis, an association with breast cancer was noted in the additive genetic model (OR=1.111, 95% CI: 1.004-1.230, p=0.042) for the Caucasian subgroup. No significant associations were observed in Asians and Africans in any of the genetic models. Conclusions: In summary, our meta-analysis findings suggest that the HER2 Ile655Val polymorphism is marginally associated with breast cancer susceptibility in worldwide populations with additive and dominant models, but not a recessive model.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2605-2610
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• 2012

Background: Studies investigating the association of 2R/3R polymorphism in the thymidylate synthase 5'-untranslated enhanced region (TSER) and colorectal cancer (CRC) risk have reported conflicting results. Thus, a meta-analysis was performed to summarize the data on the potential association. Methods: Pubmed, Embase and CBM databases were searched for all available studies. Links between the TSER 2R/3R polymorphism and CRC risk were estimated by odds ratios (ORs) with 95% confidence intervals (CIs). Results: Seven case-control studies with a total of 2723 cases and 4030 controls were included in this meta-analysis. The results showed that the 3R variant of TSER 2R/3R polymorphism contributes to CRC risk in two comparison models (OR 3R vs. 2R =1.10, 95%CI 1.02-1.18, P = 0.015; OR Homozygote comparison model = 1.22 1.04-1.43, 95%CI 1.04-1.43, P = 0.012). Subgroup analyses by ethnicity further demonstrated a contribution in Caucasians with three comparison models (OR 3R vs. 2R = 1.10, 95%CI 1.02-1.19, P = 0.015; OR Homozygote comparison model = 1.21, 95%CI 1.03-1.41, P = 0.019; OR Recessive comparison model = 1.18, 95%CI 1.05-1.33, P = 0.008). However, the association in the Asian population was still uncertain due to the limited data (all P values were more than 0.05). Conclusions: Our meta-analysis suggests that the 3R variant of Thymidylate synthase 5'-untranslated enhanced region 2R/3R polymorphism contributes to gastric cancer risk in the Caucasian population, while any association in Asian populations needs further study.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6767-6772
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• 2014

Several studies have suggested associations between MDM2 (mouse double minute 2 homolog) polymorphisms and leukemia risk, but they reported contradictory results. For better understanding of the effect of MDM2 T309G polymorphism on leukemia risk, we performed a meta-analysis. All eligible studies were identified through a search of PubMed, Web of Science, EMBASE, and Chinese Biomedical Literature (CBM) databases before May 2014. Assessment of associations between the MDM2 T309G polymorphism and leukemia risk was conducted by odds ratios (ORs) and 95% confidence intervals (95% CIs). Finally, a total of 11 publications covering 12 case-control studies with 2, 362 cases and 5, 562 controls concerning MDM2 T309G polymorphism with respect to leukemia were included in the meta-analysis. Significant associations were found between MDM2 T309G polymorphism and leukemia risk in four models in overall populations (G vs T: OR=1.29, 95% CI=1.11-1.49, p=0.001; GG vs TT: OR=1.67, 95% CI=1.21-2.30, p=0.002; GG vs TG/TT: OR=1.56, 95% CI=1.21-2.00, p=0.001; GG/TG vs TT: OR=1.28, 95% CI=1.05-1.57, p=0.015). In the sub-group analysis according to ethnicity, increased leukemia risks were observed in three genetic models among Asians but not Caucasians. In conclusion, the results of our meta-analysis suggest that the MDM2 T309G polymorphism can increase the risk of leukemia, especially among Asian populations.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1263-1267
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• 2014

Background: Matrix metalloproteinases (MMPs) play important roles in pathogenesis and development of cancer. Recently, many studies have show associations between polymorphisms in the promoter regions of MMPs and risk of gastric cancer. The present meta-analysis was conducted in order to investigate the potential association between four polymorphisms in the MMP gene and gastric cancer risk. Methods: A computerized literature search was conducted in databases of Med-line, Embase, Science Citation Index and PubMed till June 2013 for any MMP genetic association study of gastric cancer. Odds ratios (ORs) and 95 % confidence intervals (CIs) were estimated for each gene under dominant and recessive models, and heterogeneity between studies was assessed using the Q test and $I^2$ value. Overall and subgroup analyses according to ethnicity were carried out with Stata 12.0. Results: 14 reports covering 8,146 patients (2,980 in the case group and 5,166 in the control group) were included in the present meta-analysis. We found that the MMP-7 (-181A>G) polymorphism increased the gastric cancer risk in therecessive model (GG vs. AA/AG, OR=1.768, 95% CI =1.153-2.712). For MMP2 -1306 C>T, MMP1-1607 1G/2G, and MMP9-1 562 C>T, there were no associations between these polymorphisms and the risk of gastric cancer under dominant or recessive models. Conclusion: This meta-analysis suggested that the MMP7-181 A>G polymorphism may contribute to gastric cancer susceptibility. More studies are needed, especially in Europeans, in the future.

• Journal of Preventive Medicine and Public Health
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• v.33 no.1
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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.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.109-117
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• 2021

In this paper, the meta-model based approximate optimization was carried out for the structure design of an ocean automatic salt collector in order to minimize the structure weight. The structural analysis was performed by using the finite element method to evaluate the strength performance of the ocean automatic salt collector in its initial design. In the structural analysis, it was evaluated the strength performance of the design load conditions. The optimum design problem was formulated so that design variables of main structure thickness would be determined by minimizing the structure weight subject to strength performance constraints. The meta-models used in the approximate optimization were the response surface method, Kriging model, and Chebyshev orthogonal polynomials. Regarding to the numerical characteristics, the solution results from approximate optimization techniques were compared to the results of non-approximate optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the ocean automatic salt collector.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.12
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• pp.4823-4827
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• 2014

Background: Since inconsistent results have been reported regarding the relation between the matrix metalloproteinase-2 (MMP-2) -1306C>T polymorphism and susceptibility for breast cancer, we performed a meta-analysis to investigate the issue. Materials and Methods: An internet search of PubMed and EMBASE was performed to identify eligible studies. Pooled odds ratios (ORs) with their corresponding confidence intervals (CIs) were calculated to evaluate any association between MMP-2 -1306C>T polymorphism and breast cancer susceptibility. Results: Nine case-control studies were included in the meta-analysis, involving 9,858 cases and 10,871 controls. Overall, there was no evidence of any association between the MMP-2 -1306C>T polymorphism and breast cancer susceptibility in different genetic models (T-allele vs C-allele: OR=0.95, 95%CI, 0.82-1.10, p=0.49; TT vs CC: OR=1.03, 95%CI, 0.90-1.19, p=0.66; TT+TC vs CC: OR=0.93, 95%CI, 0.78-1.10, p=0.38; TT vs TC+CC: OR=1.02, 95%CI, 0.89-1.17, p=0.77). In the subgroup analysis by ethnicity, CC was associated with a significant increase in breast susceptibility among Latin-Americans in the dominant model (OR=0.61, 95%CI, 0.40-0.93, p=0.02), but the association disappeared in other models. No significant association was observed among Europeans, East Asians and others in different genetic models. In the subgroup analysis by their source of controls, no significant association between MMP-2 -1306C>T polymorphism and breast cancer susceptibility was noted among population-based studies and hospital-based studies in different genetic models. Conclusions: The results of this meta-analysis suggest that MMP-2 -1306C>T polymorphism is not associated with breast cancer susceptibility, although the association among Latin-Americans in the dominant model was significant.

• Journal of the Korea Society for Simulation
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• v.15 no.2
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• pp.59-69
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• 2006

Component-based software development is introduced as a new development paradigm in software development method. This approach is different from existing software development approach because it is based on reusable and autonomous unit, component. Therefore, component-based development(CBD)is divided into two stages; component development process and component assembly process; application development process. Component development process is the core of CBD because component has a key for good software. Currently many methodologies or tools have been introduced by various academies or industries. However, those don't suggest systematic and flexible modeling techniques adaptable easily into component development project. Existing approaches have a unique orarbitrary modeling technique or provide heuristic guidelines for component modeling. As a result, many component developers are faced with a difficult problems; how to developcomponent models, when develop which diagrams, and so on. In order to address this problem, we suggest a meta-model driven approach for component development in this paper. We provide meta-models according to both layer and development phase. We expect that suggested meta-models allow component developers to develop appropriate models of the time.