• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.187-196
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• 2021

The paper deals with comparative study for characteristics of approximation of design space according to various approximate models and sensitivity analysis using orthogonal array experiments in structure design of active type DSF which was developed for float-over installation of offshore plant. This study aims to propose the orthogonal array experiments based design methodology which is able to efficiently explore an optimum design case and to generate the accurate approximate model. Thickness sizes of main structure member were applied to the design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experiment. Best design case was also identified to improve the structure design with weight minimization. From the orthogonal array experiment results, various approximate models such as response surface model, Kriging model, Chebyshev orthogonal polynomial model, and radial basis function based neural network model were generated. The experiment results from orthogonal array method were validated by the approximate modeling results. It was found that the radial basis function based neural network model among the approximate models was able to approximate the design space of the active type DSF with the highest accuracy.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.487-500
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• 2020

This research analyzed articles about the disability under the 「The Disabled Person Welfare Law」 in a major daily newspaper. A total of 7,684 articles on disability were collected from homepages of the three newspapers , , and . Through network text analysis and content analysis, we considered about "The perspective of Disability" based on "Multiple Disability Model". As a result of this research, when comparing individual models versus social models, individual models have a higher rate 64.31% than social models 35.69%. According to the newspapers, the major perception of Disability is a traditional individual model, which means disability must be solved by individuals. In addition, due to low social and institutional supports, the public's attention and consideration required for the disabled, socially weak people. This research implied that despite the changing times of looking at disability, three newspapers are still staying in the traditional paradigm. Therefore, It is required that viewing a disability from the perspective on disabled people, and a mature awareness that recognizes the diversity of individual needs. The significance of this study can be found in the fact that no attempt has been made to treat the disability perspectivec in newspaper articles as quantitative and qualitative data.

• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Steel and Composite Structures
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• v.46 no.1
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• pp.53-73
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• 2023

Man-made structure materials like concrete usually contain inclusions. These inclusions affect the mechanical properties of concrete. In this investigation, the influence of inclusion length and inclination angle on three-dimensional failure mechanism of concrete under uniaxial compression were performed using experimental test and numerical simulation. Approach of acoustic emission were jointly used to analyze the damage and fracture process. Besides, by combining the stress-strain behavior, quantitative determination of the thresholds of crack stress were done. concrete specimens with dimensions of 120 mm × 150 mm × 100 mm were provided. One and two holes filled by gypsum are incorporated in concrete samples. To build the inclusion, firstly cylinder steel tube was pre-inserting into the concrete and removing them after the initial hardening of the specimen. Secondly, the gypsum was poured into the holes. Tensile strengths of concrete and gypsum were 2.45 MPa and 1.5 MPa, respectively. The angle bertween inclusions and axial loadind ary from 0 to 90 with increases of 30. The length of inclusion vary from 25 mm to 100 mm with increases of 25 mm. Diameter of the hole was 20 mm. Entirely 20 various models were examined under uniaxial test. Simultaneous with experimental tests, numerical simulation (Particle flow code in two dimension) were carried out on the numerical models containing the inclusions. The numerical model were calibrated firstly by experimental outputs and then failure behavior of models containing inclusions have been investigated. The angle bertween inclusions and axial loadind vary from 0 to 90 with increases of 15. The length of inclusion vary from 25 mm to 100 mm with increases of 25 mm. Entirely 32 various models were examined under uniaxial test. Loading rate was 0.05 mm/sec. The results indicated that when inclusion has occupied 100% of sample thickness, two tensile cracks originated from boundaries of sample and spread parallel to the loading direction until being integrated together. When inclusion has occupied 75% of sample thickness, four tensile cracks originated from boundaries of sample and spread parallel to the loading direction until being integrated together. When inclusions have occupied 50% and 25% of sample thickness, four tensile cracks originated from boundaries of sample and spread parallel to the loading direction until being integrated together. Also the inclusion was failed by one tensile crack. The compressive strength of samples decease with the decreases of the inclusions length, and inclusion angle had some effects on that. Failure of concrete is mostly due to the tensile crack. The behavior of crack, was affected by the inclusion length and inclusion number.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Journal of Korean Society of Steel Construction
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• v.17 no.5 s.78
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• pp.511-518
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• 2005

The behavior of steel curved bridges is more complicated than straight bridges, thus the analysis, design and construction process of curved bridges require much more attention. In design of curved bridges, the grillage analysis using general structural analysis program or special program is mainly used. Comparative study in coherence between these analytical results and actual behavior of curved bridges has been rarely conducted. To study the behaviour of curved bridges and verify the current design method, field measurements and analyses using general structural analysis program and 3-D refined analysis program were carried out for simple and continuous bridges in this study. The study focused on the behavior of curved steel bridges during construction. Measured and analytical results had quantitative difference mutually, but there were qualitatively similar. Stress variations in transverse direction of flange were observed and grillage analysis models yielded more conservative values than 3-D refined analysis models.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.12
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• pp.1651-1659
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• 2011

This study was conducted to detect quantitative trait loci (QTL) for thirteen growth and meat quality traits in pigs by combing QTL experimental populations. Two F2 reference populations that were sired by Korea native pig (KNP) and dammed by Landrace (LN) or Yorkshire (YK) were generated to construct linkage maps using 123 genetic markers (mostly microsatellites) and to perform QTL analysis on porcine chromosomes (SSCs) 1, 2, 3, 6, 7, 8, 9, 11, 13, 14, and 15. A set of line-cross models was applied to detect QTL, and a series of lack-of-fit tests between the models was used to characterize inheritance mode of QTL. A total of 23, 11 and 19 QTL were detected at 5% chromosome-wise level for the data sets of KNP${\times}$LN, KNP${\times}$YK cross and joint sets of the two cross populations, respectively. With the joint data, two Mendelian expressed QTL for live weight and cooking loss were detected on SSC3 and SSC15 at 1% chromosome-wise level, respectively. Another Mendelian expressed QTL was detected for CIE a on SSC7 at 5% genome-wise level. Our results suggest that QTL analysis by combining data from two QTL populations increase power for QTL detection, which could provide more accurate genetic information in subsequent marker-assisted selection.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.13 no.1
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• pp.15-18
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• 2003

High purity single crystalline calcium fluoride ($CaF_2$) has excellent optical transmission characteristics down to deep UV and is therefore selected as the main optical material for the next generation of lithography apparatus operating at wavelength of 157 nm. The growth of large sized $CaF_2$ single crystals with the required properties for this optical application can be achieved only by optimizing the crystal growth process by the aid of numerical simulation. This needs especially a precise calculation of the heat transport and temperature distribution in the solid and liquid $CaF_2$ under crystal growth conditions. As $CaF_2$ is considered to be semitransparent, the internal radiative heat transfer in $CaF_2$ plays an decisive role in the simulation of the heat transport. On the other hand it is very difficult to obtain quantitative experimental data for evaluating numerical models as $CaF_2$ is extremely corrosive at high temperatures. In this work we present a newly developed experimental technique to perform temperature measurements in $CaF_2$-crystal as well as in the melt under conditions of crystal growth process. These experimental results are compared to calculated temperature data, which were obtained by using different numerical models concerning the internal heat transfer in semitransparent $CaF_2$. It will be shown, that an advanced model, which was developed by the authors, gives a much better agreement with experimental data as a standard model, which was taken from the literature.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5_2
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• pp.194-205
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• 2010

To predict urban growth according to changes in landcover, probability factors werecal culated and mapped. Topographic, geographic and social and political factors were used as prediction variables for constructing probability maps of urban growth. Urban growth-related factors included elevation, slope, aspect, distance from road,road ratio, distance from the main city, land cover, environmental rating and legislative rating. Accounting for these factors, probability maps of urban growth were constr uctedusing frequency ratio (FR) and logistic regression (LR) methods and the effectiveness of the results was verified by the relative operating characteristic (ROC). ROC values of the urban growth probability index (UGPI) maps by the FR and LR models were 0.937 and 0.940, respectively. The LR map had a slightly higher ROC value than the FR map, but the numerical difference was slight, with both models showing similar results. The FR model is the simplest tool for probability analysis of urban growth, providing a faster and easier calculation process than other available tools. Additionally, the results can be easily interpreted. In contrast, for the LR model, only a limited amount of input data can be processed by the statistical program and a separate conversion process for input and output data is necessary. In conclusion, although the FR model is the simplest way to analyze the probability of urban growth, the LR model is more appropriate because it allows for quantitative analysis.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.151-155
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• 2005

Recently, systems biology has been increasingly applied to gain insights into the complexity of living organisms. Many inaccessible biological information and hidden evidences fur example flux distribution of the metabolites are simply revealed by investigation of artificial cell behaviors. Most bio-models are models of single cell organisms that cannot handle the multi-cellular organisms like plants. Herein, a structured and multi-cellular model of potato was developed to comprehend the root starch biosynthesis. On the basis of simplest plant cell biology, a potato structured model on the platform of Berkley Madonna was divided into three parts: photosynthetic (leaf), non-photosynthetic (tuber) and transportation (phloem) cells. The model of starch biosynthesis begins with the fixation of CO$_2$ from atmosphere to the Calvin cycle. Passing through a series of reactions, triose phosphate from Calvin cycle is converted to sucrose which is transported to sink cells and is eventually formed the amylose and amylopectin (starch constituents). After validating the model with data from a number of literatures, the results show that the structured model is a good representative of the studied system. The result of triose phosphate (DHAP and GAP) elevation due to lessening the aldolase activity is an illustration of the validation. Furthermore, the representative model was used to gain more understanding of starch production process such as the effect of CO$_2$ uptake on qualitative and quantitative aspects of starch biosynthesis.