• Molecules and Cells
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• v.25 no.3
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• pp.397-406
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• 2008

Computational modeling of signal transduction is currently attracting much attention as it can promote the understanding of complex signal transduction mechanisms. Although several mathematical models have been used to examine signaling pathways, little attention has been given to crosstalk mechanisms. In this study, an attempt was made to develop a computational model for the pathways involving growth-factor-mediated mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3'-kinase/protein kinase B (PI3K/Akt). In addition, the dynamics of the protein activities were analyzed based on a set of kinetic data. The simulation approach integrates the information on several levels and predicts systems behavior. The in-silico analysis conducted revealed that the Raf and Akt pathways act independently.

• Korean Journal of Computational Design and Engineering
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• v.11 no.4
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• pp.235-245
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• 2006

This paper proposes a CSG-based representation scheme for heterogeneous objects including multi-material objects and Functionally Graded Materials (FGMs). In particular, this scheme focuses on the construction of complicated heterogeneous objects guaranteeing desired material continuities at all the interfaces. In order to create various types of heterogeneous primitives, we first describe methods for specifying material composition functions such as geometry-independent, geometry-dependent functions. Constructive Material Composition (CMC) and corresponding heterogeneous Boolean Operators (e.g. material union, difference, intersection. and partition) are then proposed to illustrate how material continuities are dealt with. Finally, we describe the model hierarchy and data structure for computer representation. Even though the proposed scheme alone is sufficient for modeling all sorts of heterogeneous objects, the proposed scheme adopts a hybrid representation between CSG and decomposition. That is because hybrid representation can avoid the unnecessary growth of binary trees.

• Journal of the Korea Concrete Institute
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• v.11 no.3
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• pp.181-192
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• 1999

The progressive failure following strain localization in concrete can be analyzed effectively using finite element modeling of fracture process zone of concrete with a finite element embedded discontinuity. In this study, a finite element with embedded discontinuous line is utilized for the analysis of progressive failure in concrete. The finite element with embedded discontinuity is a kind of discrete crack element, but the difficulties in discrete crack approach such as remeshing or adding new nodes along with crack growth can be avoided. Using a discontinuous shape function for this element, the displacement discontinuity is embedded within an element and its constitutive equation is modeled from the modeling of fracture process zone. The element stiffness matrix is derived and its dual mapping technique for numerical integration is employed. Then, a finite element analysis program with employed algorithms is developed and failure analysis results using developed finite element program are verified through the comparison with experimental data and other analysis results.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.154-157
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• 2004

With the need of high-speed and mass data transmission, optical communication system requires the growth of optical components. Waveguide photodiodes(WGPDs) are introduced and circuit models of WGPD and submodule are required for the optical receiver application. In this paper, the circuit models of WGPD and submodule are investigated and modeling results are derived by PEEC methodology. The s-parameters are measured for the test structures of WGPD and submodule and the equivalent circuit models are examined. The modeling results agreed well with the measured data and can present a reasonable physical representation.

• Computers and Concrete
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• v.10 no.1
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• pp.49-57
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• 2012

Nano-particle-reinforced cement mortars have been the basis of research in recent years and a significant growth is expected in the future. Therefore, optimization and quantification of the effect of processing parameters and mixture ingredients on the performance of cement mortars are quite important. In this work, the effects of nano-silica, water/binder ratio, sand/binder ratio and aging (curing) time on the compressive strength of cement mortars were modeled by means of artificial neural network (ANN). The developed model can be conveniently used as a rough estimate at the stage of mix design in order to produce high quality and economical cement mortars.

• International Journal of Korean Welding Society
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• v.2 no.1
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• pp.11-14
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• 2002

A metallurgical model for bainite transformation kinetics in the coarse-grained heat affected zone(CGHAZ) on the basis of an Avrami-type equation was studied. Isothermal transformation tests were carried out to obtain the empirical equations for incubation time and Avrami kinetic constants for C-Mn-Mo-Ni steel. The effect of prior austenite grain size(PAGS) on the reaction rate of bainite was also investigated. Compared with experimental transformation behavior of bainite, the predicted behavior was in good agreement. It was also found that a smaller grain size retard the bainite reaction rate, contrary to the classical grain size effect and this is considered to be caused by constraint of grain size to bainite growth.

• Journal of ILASS-Korea
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• v.27 no.1
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• pp.36-41
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• 2022

In this study, the combustion instability characteristics according to the change in the hydrogen ratio in the fuel in the single nozzle system of the hydrogen-natural gas mixed gas turbine for power generation was analyzed using a three-dimensional finite element analysis-based Helmholtz solver. This combustor shows the instability characteristics in which mode transition occurs from a mode having a low amplitude near 70 Hz to a mode having a high amplitude of 250 Hz or higher as the hydrogen fraction in the fuel increases. The current modeling results are found to reasonably predict the main characteristics of the change in measured instability frequency and growth rate with the change in fuel composition.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.977-998
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• 2023

The study is based on the technology-organization-environment (TOE) model which, attempted to determine the factors that are going to influence ICT adoption. The proposed research model evaluates the interplay among technological context (IT infrastructure, system security, and user capacity), organizational context (top management commitment, and innovations strategies), environmental context (quick response to the external agencies, interactive network infrastructure, and competitive pressure) and ICT adoption (productivity growth, organizational change, and competitiveness). Data were collected from 243 senior executives of full member firms of the Bangladesh Garments and Manufacturers Association (BGMEA) of examining the relationships among the constructs in the proposed framework utilizing structural equation modeling (SEM). The analysis of TOE factors revealed that environmental, organizational, and technological factors have a significant impact on the successful implementation of ICT tools. The study also discusses implications for management practitioners.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.378-384
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• 2023

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

• Food Science of Animal Resources
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• v.30 no.1
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• pp.49-54
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• 2010

The aim of this research was to estimate the effect of temperature and develop predictive models for the growth of total viable cells (TVC) and Escherichia coli (EC) on chicken breast under aerobic and various temperature conditions. The primary models were determined by Baranyi model. The secondary models for the specific growth rate (SGR) and lag time (LT), as a function of storage temperature, were developed by the polynomial model. The initial contamination level of chicken breasts was around 4.3 Log CFU/g of TVC and 1.0 Log CFU/g of E. coli. During 216 h of storage, SGR of TVC showed 0.05, 0.15, and 0.54 Log CFU/g/h at 5, 15, and $25^{\circ}C$. Also, the growth tendency of EC was similar to those of TVC. As storage temperature increased, the values of SGR of microorganisms increased dramatically and the values of LT decreased inversely. The predicted growth models with experimental data were evaluated by $B_f$, $A_f$, RMSE, and $R^2$. These values indicated that these developed models were reliable to express the growth of TVC and EC on chicken breasts. The temperature changes of distribution and showcase in markets might affect the growth of microorganisms and spoilage of chicken breast mainly.