• Journal of Smart Tourism
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• v.2 no.3
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• pp.5-15
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• 2022

As the utilization of technology in the tourism field becomes familiar, it greatly impacts people's tourism activities. These changes could also affect the behavior of tourists during the pandemic. To investigate consumers' adaptation to the self-service technology (SST) environment during the coronavirus disease of 2019 (COVID-19) pandemic, we adopted a model of absorptive capacity as the main framework for empirical research. To track the social effects of COVID-19, consumers' behavioral intentions for four different points in time are collected. The analysis was conducted using latent growth and structural equation modeling. We set the organizational and environmental characteristics as the first step of the model, with assimilation and trust as a middle step. Intention to use a kiosk is placed at the final step as an exploit. Findings indicate that organizational characteristics and environmental characteristics positively influenced assimilation and trust, except for environmental characteristics. Consumers' assimilation in SST encourages immediate intention to use a kiosk. Consumers' trust in kiosks positively impacts both immediate and continuance intention to use a kiosk during COVID-19.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.157-161
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• 2023

Reliability is one of the computable quality features of the software. To assess the reliability the software reliability growth models(SRGMS) are used at different test times based on statistical learning models. In all situations, Tradational time-based SRGMS may not be enough, and such models cannot recognize errors in small and medium sized applications.Numerous traditional reliability measures are used to test software errors during application development and testing. In the software testing and maintenance phase, however, new errors are taken into consideration in real time in order to decide the reliability estimate. In this article, we suggest using the Weibull model as a computational approach to eradicate the problem of software reliability modeling. In the suggested model, a new distribution model is suggested to improve the reliability estimation method. We compute the model developed and stabilize its efficiency with other popular software reliability growth models from the research publication. Our assessment results show that the proposed Model is worthier to S-shaped Yamada, Generalized Poisson, NHPP.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.6
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• pp.894-902
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• 2003

Prebiotics (peptides, N-acetyglucoamine, fructo-oligosaccharides, isomalto-oligosaccharides and galactooligosaccharides) were added to skim milk in order to improve the growth rate of contained Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium longum and Bifidobacterium bifidum. The purpose of this research was to study the potential synergy between probiotics and prebiotics when present in milk, and to apply modern optimization techniques to obtain optimal design and performance for the growth rate of the probiotics using a response surface-modeling technique. To carry out response surface modeling, the regression method was performed on experimental results to build mathematical models. The models were then formulated as an objective function in an optimization problem that was consequently optimized using a genetic algorithm and sequential quadratic programming approach to obtain the maximum growth rate of the probiotics. The results showed that the quadratic models appeared to have the most accurate response surface fit. Both SQP and GA were able to identify the optimal combination of prebiotics to stimulate the growth of probiotics in milk. Comparing both methods, SQP appeared to be more efficient than GA at such a task.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.11 no.2
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• pp.45-50
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• 2015

In many cases, the field fracture mechanism of the thermoplastic pipe is considered as either brittle or environmental fractures. Thus the estimation of the lifetime by modeling slow crack growth considering such fracture mechanisms is required. In comparison of the some conventional and empirical equations to explain the slow crack growth rate such as the Paris' law, the crack layer theory can be used to simulate the crack and process zone growth behaviors precisely, so the lifetime of thermoplastic pipe can also be accurately estimated. In this study, the modified crack layer theory for the stress corrosion cracking (SCC) of high density polyethylene is introduced with detailed algorithm. The oxidation induction time of the HDPE is also considered for the reduction of specific fracture energy during exposed to chemical environments. Furthermore, the parametric study for an important SCC parameter is conducted to understand the slow crack growth behavior of SCC.

• Microbiology and Biotechnology Letters
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• v.19 no.5
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• pp.521-535
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• 1991

A kinetic model incorporating cell morphology in cephalosporin C biosynthesis by Cephalosporium amemoniurn was developed. The double-substrate Double-substrate kinetic model was used to describe cell growth. Methionine controlled the rate of growth while glucose ultimately controlled the extent of growth. The changes in specific product formation rate were associated with morphologenesis, especially cell differentiation. To increase the productivity of cephalosporin C, the proposed model equations were applied to a fed-batch culture. The algorithm to optimize the fed-batch culture consists of two steps; cell growth was maximized in the growth phase and then cephalosporin C production was maximized in the production phase. The increase of about 33% in the cephalosporin C titre was obtained by the optimal feeding scheduling in comparison with that of batch culture.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.648-650
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• 1998

This paper proposes a constructive algorithm for generating the Takagi-Sugeno type fuzzy model through the sequential learning from training data set. The proposed algorithm has a two-stage learning scheme that performs both structure and parameter learning simultaneously. The structure learning constructs fuzzy model using two growth criteria to assign new fuzzy rules for given observation data. The parameter learning adjusts the parameters of existing fuzzy rules using the LMS rule. To evaluate the performance of the proposed fuzzy modeling approach, well-known benchmark is used in simulation and compares it with other modeling approaches.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.5
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• pp.395-404
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• 2017

Cultivating soybeans in rice paddy field reduces labor costs and increases the yield. Soybeans, however, are highly susceptible to excessive soil water in paddy field. Controlled drainage system can adjust groundwater level (GWL) and control soil moisture content, resulting in improvement soil environments for optimum crop growth. The objective of this study was to fit the soybean growth data (canopy height and stem diameter) using Gompertz model and Logistic model at different GWL and validate those models. The soybean, Daewon cultivar, was grown on the lysimeters controlled GWL (20cm and 40cm). The soil textures were silt loam and sandy loam. The canopy height and stem diameter were measured from the 20th days after seeding until harvest. The Gompertz and Logistic models were fitted with the growth data and each growth rate and maximum growth value was estimated. At the canopy height, the $R_2$ and RMSE were 0.99 and 1.58 in Gompertz model and 0.99 and 1.33 in Logistic model, respectively. The large discrepancy was shown in full maturity stage (R8), where plants have shed substantial amount of leaves. Regardless of soil texture, the maximum growth values at 40cm GWL were greater than the value at 20cm GWL. The growth rates were larger at silt loam. At the stem diameter, the $R_2$ and RMSE were 0.96 and 0.27 in Gompertz model and 0.96 and 0.26 in Logistic model, respectively. Unlike the canopy height, the stem diameter in R8 stage didn't decrease significantly. At both GWLs, the maximum growth values and the growth rates at silt loam were all larger than the values at sandy loam. In conclusion, Gompertz model and Logistic model both well fit the canopy heights and stem diameters of soybeans. These growth models can provide invaluable information for the development of precision water management system.

• Journal of Ecology and Environment
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• v.31 no.3
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• pp.177-181
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• 2008

Recently, the evolutionary study of human psychology and behavior has undergone rapid growth, diversifying into a few distinct sub-disciplines. One fundamental issue over which researchers in Human Behavioral Ecology and Evolutionary Psychology (EP) have different views is the role of formal optimality modeling for making hypotheses and deriving predictions about human adaptations. The study of EP typically rests on informal inferences and rarely uses optimality modeling, a strategy which human behavioral ecologists have severely criticized. Here I argue that EP researchers have every reason to make extensive use of optimality modeling as its research method. I show that optimality modeling can play an integral role in identifying the functional organization of human psychological adaptations.

• Journal of Powder Materials
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• v.18 no.2
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• pp.168-171
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• 2011

We investigate grain growth behavior of poly-crystalline Mg sheet having strong basal fiber texture using phase field model for grain growth and micro-elasticity. Strong initial basal texture was maintained when external load was not imposed, but was weaken when external biaxial strain was imposed. Elastic interaction between elastic anisotropy of Mg grain and external load is the reason why texture evolution occurs.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.26 no.1
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• pp.8-13
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• 2016

A top-seeded solution growth (TSSG) is a method of growing SiC single crystal from the Si melt dissolved the carbon. In this study, multiphysics modeling was conducted using COMSOL Multiphysics, a commercialized finite element analysis package, to get analytic results about electromagnetic analysis, heat transfer and fluid flow in the Si melt. Experimental results showed good agreements with simulation data, which supports the validity of the simulation model. Based on the understanding about solution growth of SiC and our set-up, crystal growth was conducted on off-axis 4H-SiC seed crystal in the temperature range of $1600{\sim}1800^{\circ}C$. The grown layer showed good crystal quality confirmed with optical microscopy and high resolution X-ray diffraction, which also demonstrates the effectiveness of the multiphysics model to find a process condition of solution growth of SiC single crystal.