• Nutrition Research and Practice
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• v.17 no.1
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• pp.62-72
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• 2023

BACKGROUND/OBJECTIVES: Many studies have revealed an association between fat mass and the obesity-related gene (FTO) and obesity. On the other hand, no meta-analysis was conducted with data from only Koreans. Therefore, this study performed a meta-analysis using Korean data to provide evidence for the association between FTO single nucleotide polymorphisms (SNPs) and the risk of obesity among Korean adults. SUBJECT/METHODS: Meta-analysis was finally conducted with data extracted from seven datasets of four studies performed on Korean adults after the screening passed. Five kinds of FTO SNPs (rs9939609, rs7193144, rs9940128, rs8050136, and rs9926289) were included, and the relationship between FTO SNPs and body mass index (BMI) was investigated using linear regression with an additive model adjusted for covariants, such as age, sex, and area. RESULTS: The minor alleles of FTO SNPs were associated with increased BMI (odds ratio [OR], 1.31; 95% confidence interval [CI], 1.21-1.42). In sub-group analysis, FTO rs9939609 T>A was significantly associated with BMI (OR, 1.23; 95% CI, 1.06-1.42). The other FTO SNPs together were significantly associated with BMI (OR, 1.37; 95% CI, 1.25-1.49). The publication bias was not observed based on Egger's test. CONCLUSIONS: This meta-analysis showed that minor alleles in the FTO SNPs were significantly associated with an increased BMI among Korean adults. This meta-analysis is the first to demonstrate that minor alleles in the FTO SNPs contribute significantly to the increased risk of obesity among Korean adults using data from a Korean population.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.52-57
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• 2023

This study is a basic research for the development of high performance flexible electrode material. To enhance its electrochemical property, CuO nanoparticles (CuO NPs) were introduced and dispersed on surface of CNT fiber through electrochemical deposition method. The CNT fiber/CuO NPs electrode was fabricated and applied to electrochemical non-enzymatic glucose sensor. Surface morphology and elemental composition of the CNT fiber/CuO NPs electrode was characterized by scanning electron microscope (SEM) with energy dispersive X-ray spectrometry (EDS). And its electrochemical characteristics were investigated by cyclic voltammetry, electrochemical impedance spectroscopy and chronoamperometry. The CNT fiber/CuO NPs electrode exhibited the good sensing performance for glucose detection such as high sensitivity, wide linear range, low detection limit and good selectivity due to synergetic effect of CNT fiber and CuO NPs. Based on the unique property of CNT fiber, CuO NPs were provide large surface area, enhanced electrocatalytic activity, efficient electron transport property. Therefore, it is expected to develop high performance flexible electrode materials using various nanomaterials.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.75.2-76
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• 2021

MESSIER is a science satellite project to observe the Low Surface Brightness (LSB) sky at UV and optical wavelengths. The wide-field, optical system of MESSIER is optimized minimizing optical aberrations through the use of a Linear Astigmatism Free - Three Mirror System (LAF-TMS) combined with freeform mirrors. One of the key factors in observations of the LSB is the shape and spatial variability of the Point Spread Function (PSF) produced by scatterings and diffraction effects within the optical system and beyond (baffle). To assess the various factors affecting the PSF in this design, we use PhoSim, the Photon simulator, which is a fast photon Monte Carlo code designed to include all these effects, and also atmospheric effects (for ground-based telescopes) and phenomena occurring inside of the sensor. PhoSim provides very realistic simulations results and is suitable for simulations of very weak signals. Before the application to the MESSIER optics system, PhoSim had not been validated for confocal off-axis reflective optics (LAF-TMS). As a verification study for the LAF-TMS design, we apply Phosim sequentially. First, we use a single parabolic mirror system and compare the PSF results of the central field with the results from Zemax, CODE V, and the theoretical Airy pattern. We then test a confocal off-axis Cassegrain system and check PhoSim through cross-validation with CODE V. At the same time, we describe the shapes of the freeform mirrors with XY and Zernike polynomials. Finally, we will analyze the LAF-TMS design for the MESSIER optical system.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.489-499
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• 2023

As sharing of analyst reports became widely available, reports generated by analysts have become a useful tool to reduce difference in financial information between market participants. The quantitative information of analyst reports has been used in many ways to predict stock returns. However, there are relatively few domestic studies on the prediction power of text information in analyst reports to predict stock returns. We test stock return predictability of text in analyst reports by creating variables representing the TONE from the text. To overcome the limitation of the linear-model-assumption-based approach, we use the random-forest-based F-test.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.39-52
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• 2023

In this study, project information of government-funded research institute in the food field was collected and analyzed to systematically identify the factors affecting the process of transferring technological achievements of public research institute to the private sector. This study hypothesized that human resources, financial resources, and technological characteristics as input factors of R&D projects affect output factors, such as research papers or patents produced by R&D projects. Moreover, these outputs would serve as drivers of the technology transfer as one of the R&D outcomes. Linear Regression Analysis and Poisson Regression Analysis were conducted to empirically and sequentially investigate the relationship between input factors and output and outcome of R&D projects and the results are as follows: First, the principle investigator's career and participating researcher's size as human resource factors have an influence on both the number of SCI (science citation index) papers and patent registration. Second, the research duration and research expenses for the current year have an influence on the number of SCI papers and patent registrations, which are the main outputs of R&D projects. Third, the technology life cycle affects the number of SCI papers and patent registrations. Lastly, the higher the number of SCI papers and patent registrations, the more it affected the number of technology transfers and the amount of technology transfer contract.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.677-683
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• 2023

The purpose of the study was to estimate the trajectories of elementary school adjustment in grades 1 through 4. For the purpose, the Korean Children's Panel data were analyzed using potential growth model and the growth mixture model. As the result, the linear model was selected as the optimal model. The four potential groups were derived as trajectories: high-level maintenance, low-level maintenance, low-level increase, and high-level decrease. In terms of group distribution, the most children were in high-level maintenance group and then low-level maintenance, low-level increase, and high-level decrease in order. Based on the findings that trajectories of elementary school adjustment changes as children growth, we suggest that schools and families need to carefully investigate and support their school adjustment in individual levels.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.581-587
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• 2023

The purpose of this study was to analyze the change trajectory and latent class types of self-esteem in first to fourth grade elementary school students. For the purpose, the Korean Children's Panel data were analyzed using potential growth model and the growth mixture model. As the results, the linear change model was selected as the most appropriate model. The change trajectory was found to increase slightly as the grade increased. In addition, four latent class groups were derived through: 'high level-maintenance,' 'low level-increase,' 'high level-decrease,' and 'low level-maintenance.' Most children were in the 'high level-maintenance' group, followed by 'high level-decrease,' 'low level-increase,' and 'low level-maintenance' groups. Therefore, based on the results of the study, we suggest that educational institutions and local communities pay attention to trends in elementary school students' self-esteem and provide appropriate support for students in each class.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.361-369
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• 2023

Achieving realistic visual quality while maintaining optimal real-time rendering performance is a major challenge in evolving computer graphics and interactive 3D applications. Normal mapping, as a core technology in 3D, has matured through continuous optimization and iteration. Hybrid normal mapping as a new mapping model has also made significant progress and has been applied in the 3D asset production pipeline. This study comprehensively explores the hybrid normal techniques, analyzing Linear Blending, Overlay Blending, Whiteout Blending, UDN Blending, and Reoriented Normal Mapping, and focuses on how the various hybrid normal techniques can be used to achieve rendering performance and visual fidelity. performance and visual fidelity. Under the consideration of computational efficiency, visual coherence, and adaptability in different 3D production scenes, we design comparative experiments to explore the optimal solutions of the hybrid normal techniques by analyzing and researching the code, the performance of different hybrid normal mapping in the engine, and analyzing and comparing the data. The purpose of the research and summary of the hybrid normal technology is to find out the most suitable choice for the mainstream workflow based on the objective reality. Provide an understanding of the hybrid normal mapping technique, so that practitioners can choose how to apply different hybrid normal techniques to the corresponding projects. The purpose of our research and summary of mixed normal technology is to find the most suitable choice for mainstream workflows based on objective reality. We summarized the hybrid normal mapping technology and experimentally obtained the advantages and disadvantages of different technologies, so that practitioners can choose to apply different hybrid normal mapping technologies to corresponding projects in a reasonable manner.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.37-50
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• 2024

This study explored the link between reproductive health knowledge, attitudes, and self-efficacy in young women from Uganda's Luwero district. A survey was conducted on 82 women in the Luwero region from May to July 2016, and the predictive power of knowledge and attitudes toward self-efficacy was evaluated through multiple linear regression analysis. Results showed positive correlations among these factors, with knowledge and attitude predicting self-efficacy. Specifically, understanding healthy puberty habits and valuing women's roles positively influenced self-efficacy for healthy behaviors. These findings emphasize the need to target these aspects in reproductive health education programs, crucial for addressing adolescent pregnancy and related issues in Uganda's rural areas.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.603-608
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• 2024

Nonresponse and missing values are caused by sample dropouts and avoidance of answers to surveys. In this case, problems with the possibility of information loss and biased reasoning arise, and a replacement of missing values with appropriate values is required. In this paper, as an alternative to missing values imputation, we compare several replacement methods, which use mean, linear regression, random forest, K-nearest neighbor, autoencoder and denoising autoencoder based on deep learning. These methods of imputing missing values are explained, and each method is compared by using continuous simulation data and real data. The comparison results confirm that in most cases, the performance of the random forest imputation method and the denoising autoencoder imputation method are better than the others.