• Culinary science and hospitality research
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• v.19 no.3
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• pp.18-32
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• 2013

This study attempts to 1) identify the dimensions of perceived value in the restaurant industry and 2) assess the effects of these dimensions on overall customer satisfaction and behavioral intent. With a total of 272 samples obtained from empirical research, this study reviews the reliability and fitness of the research model, and verifies a total of 4 hypotheses using the Amos program. The hypothesized relationships in the model were tested simultaneously using a structural equation model(SEM). The proposed model provided an adequate fit to the data:${\chi}^2$ 140.087(df 80), CMIN/df 1.751, RMR .060, GFI .937, AGFI .906, NFI .962, CFI .983, RMSEA .053. As a result of confirmatorical analysis, the quality value, emotional value and economical value were quantified as perceived value in fastfood restaurants. These factors were indicated to have influence on customer satisfaction and re-visit intention. Limitations and future research were also discussed.

• Korean Journal of Health Education and Promotion
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• v.30 no.1
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• pp.27-39
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• 2013

Objectives: The purpose of the study was to test a model of physical activity of elderly living in Korea, determine significant factors contributing the physical activity, and examine significant paths in the model. Methods: A cross-sectional study was conducted using a convenience sample of 207 elderly men and women, aged 60 and older, residing in Busan Metropolitan City. Data were collected from July to August 2009 and analyzed using Predictive Analytics Software (PASW) and Analysis of a Moment Structures (AMOS). Results: The fitness of the modified model was confirmed to be appropriate (${\chi}^2$ = 55.61, ${\chi}^2$/df = 1.32, p = .078, RMSEA = .04, GFI = .96, AGFI = .91, NFI = .90, NNFI = .94, CFI = .97, PNFI = .48). The elder's age, previous exercise behavior, and self-efficacy were significant in explaining the variance in their physical activity. We found that (a) perceived health status, perceived benefits, perceived barriers, and social support directly affected self-efficacy; (b) previous exercise behavior and perceived health status directly affected perceived benefits; (c) previous exercise behavior directly affected perceived barriers; and (d) and education level, extent of pocket money, and economic level directly affected social support. Conclusions: The younger the age, the more previous exercise experience, and the higher the self-efficacy, the more S. Korean elders demonstrated improved physical activity.

• The Korean Journal of Financial Management
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• v.2 no.1
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• pp.21-34
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• 1986

The purpose of this study is to analyse the risk and uncertainty involved in the capital budgeting which is executed in long periods and requires massive capital expenditure. Under risk and uncertainty conditions, the estimates in the capital budgeting are random variables rather than known constants. Two approaches have emerged in performing economic analysis that explicitly incorporate risk and uncertainty conditions in the analysis. One approach is to develop a descriptive model which describes the economic performance of an individual investment alternative. But no recomendation would be forthcoming from the model. Rather, the decision-maker would be furnished descriptive information concerning each alternative; the final choice among the alternatives would required a separate action. The second approach is to develop a normative model which includes an objective function to be maximized or minimized. The output from the model prescribes the course of action to be taken. Owing to the fact that the normative approach considers the fitness of criteria for decision-making its reasonableness looks better. But it is almost imposible that we correctly and easily derive the individuals' utility function. So within we recognize the limits of the descriptive methods, it is more practicle to analyse the investment alternatives by sensitivity analysis.

• Journal of Korea Technology Innovation Society
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• v.9 no.4
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• pp.865-883
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• 2006

This paper explored the development factors influencing the high growth of internet media industry recently in Korea. Both theoretical model and analytic model were formulated and tested by the results of questionnaire analysis. The factors extracted from five fields were as followings: policy, technology, market, firm, and profitability. Factor analysis was used to test the fitness of the given model, and the hypothesized model was found to be useful to explain the development factors of the internet media industry. The results showed that industry's development was explained by 41.3% for firm level, 37.6% for IT technology and policy, and 21.00/0 for market condition and competition.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.411-420
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• 1999

A mixed model production line is a production line where a variety of product models are produced. In U-shaped production lines (called U-lines) used in just-in-time production system, the strategy of mixing product models is often used to provide various types of products to customers in time. Line balancing and model sequencing problems are important for an efficient use of mixed model U-lines. Although the two problems are tightly interrelated with each other, prior researches have considered them separately or sequentially. This paper presents a new method using a coevolutionary algorithm that can solve the two problems at the same time. To promote diversity and search efficiency, in this paper the evolutionary system is based on the localized interactions within and between populations. Methods of selecting environmental individuals and evaluating fitness are developed. Efficient genetic representations and operator schemes are also provided. When designing the schemes, we take into account the features specific to the problems. The experimental results demonstrate that the proposed algorithm is superior to existing approaches.

• Journal of the Korean Society of Food Culture
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• v.27 no.1
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• pp.19-29
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• 2012

The purpose of this study was to understand interrelationships among switching costs, customer satisfaction, and switching intent in a family restaurant. Based on a total of 427 customers obtained from empirical research, this study reviewed the reliability and fitness of the research model and verified a total of five hypotheses using the Amos program. The hypothesized relationships in the model were tested simultaneously by using a structural equation model (SEM). The proposed model provided an adequate fit to the data, ${\chi}^2$=137.881 (df=50); p< .001; CMIN/df 2.758; GFI= .947; AGFI= .919, NFI= .965; IFI= .978; TLI= .970; CFI= .978; RMR= .047; RMSEA= .064. The results showed that switching cost (${\beta}$= .123) in a family restaurant had a positive (+) influence upon customer satisfaction. Further, switching cost had a significantly negative (-) effect on switching intent (${\beta}$= -.414). In addition, there were moderating effects related to customer knowledge and variety seeking orientation in terms of the causal relationships between switching costs, customer satisfaction, and switching intent. Limitations and future research directions are also discussed.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2547-2555
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• 2021

The frequency of reactor coolant leakage is expected to increase over the lifetime of a nuclear power plant owing to degradation mechanisms, such as flow-acceleration corrosion and stress corrosion cracking. When loss of coolant accidents (LOCAs) occur, several parameters change rapidly depending on the size and location of the cracks. In this study, leak flow during LOCAs is predicted using a deep fuzzy neural network (DFNN) model. The DFNN model is based on fuzzy neural network (FNN) modules and has a structure where the FNN modules are sequentially connected. Because the DFNN model is based on the FNN modules, the performance factors are the number of FNN modules and the parameters of the FNN module. These parameters are determined by a least-squares method combined with a genetic algorithm; the number of FNN modules is determined automatically by cross checking a fitness function using the verification dataset output to prevent an overfitting problem. To acquire the data of LOCAs, an optimized power reactor-1000 was simulated using a modular accident analysis program code. The predicted results of the DFNN model are found to be superior to those predicted in previous works. The leak flow prediction results obtained in this study will be useful to check the core integrity in nuclear power plant during LOCAs. This information is also expected to reduce the workload of the operators.

• Journal of East-West Nursing Research
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• v.24 no.2
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• pp.101-109
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• 2018

Purpose: The purpose of this study was to construct and test a structural equation model of health behavior compliance among patients with percutaneous coronary intervention based on self-determination theory. Methods: A total of 227 participants who received follow-up care after percutaneous coronary intervention were recruited. A structured questionnaire was used to assess health providers' autonomous support, basic psychological needs, autonomous motivation, controlled motivation, type D personality, and health behavior compliance. Collected data were analyzed using SPSS 21.0 and AMOS 21.0 program. Results: The final hypothetical model showed a good fitness with data: GFI=.94, RMSEA=.07, CFI=.96, NFI=.92, TLI=.94. The results revealed that autonomous support of health care providers, basic psychological needs, and autonomous motivation, and D-type personality accounted for 51.8% of health behavior compliance. Conclusion: The findings of this study indicate that enhanced autonomous support of health care providers is essential to promote patients' basic psychological needs and autonomous motivation. This leads to maximized compliance to the health behaviors among patients who underwent percutaneous coronary intervention. We recommend that health care institutions establish various measures to foster the special environments in which health care providers can actively provide and utilize autonomous support for their patients.

• Journal of Animal Science and Technology
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• v.63 no.3
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• pp.603-613
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• 2021

This research improved the growth potential of Bifidobacterium animalis subsp lactis strain JNU306, a commercial medium that is appropriate for large-scale production, in yeast extract, soy peptone, glucose, L-cysteine, and ferrous sulfate. Response surface methodology (RSM) was used to optimize the components of this medium, using a central composite design and subsequent analyses. A second-order polynomial regression model, which was fitted to the data at first, significantly lacked fitness. Thus, through further analyses, the model with linear and quadratic terms plus two-way, three-way, and four-way interactions was selected as the final model. Through this model, the optimized medium composition was found as 2.8791% yeast extract, 2.8030% peptone soy, 0.6196% glucose, 0.2823% L-cysteine, and 0.0055% ferrous sulfate, w/v. This optimized medium ensured that the maximum biomass was no lower than the biomass from the commonly used blood-liver (BL) medium. The application of RSM improved the biomass production of this strain in a more cost-effective way by creating an optimum medium. This result shows that B. animalis subsp lactis JNU306 may be used as a commercial starter culture in manufacturing probiotics, including dairy products.

• Transactions of Materials Processing
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• v.30 no.3
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• pp.125-133
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• 2021

In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process