• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.185-190
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• 2005

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. In order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The six landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The six factors consist of two topographic factors and four geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 86.5% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• Preventive Nutrition and Food Science
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• v.16 no.4
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• pp.364-369
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• 2011

Levels of carbon dioxide gas, a metabolite of microbial growth, have been reported to parallel the onset of microbial spoilage and may be used as a convenient index for a packaged food's shelf life. This study aimed to establish a kinetic model of $CO_2$ production from perishable food for the potential use for shelf life control in the food supply chain. Aerobic bacterial count and package $CO_2$ concentration were measured during the storage of seasoned pork meat at four temperatures (0, 5, 10 and $15^{\circ}C$), and their interrelationship was investigated to establish a mathematical model. The microbial growth at constant temperature was described by using model of Baranyi and Roberts. $CO_2$ production from the stored food could be explained by taking care of its yield and maintenance factors linked to the microbial growth. By establishing the temperature dependence of the microbial growth and $CO_2$ yield factor, $CO_2$ partial pressure or concentration in package headspace could be estimated to a limited extent, which is helpful for controlling the shelf life under constant and dynamic temperature conditions. Application and efficacy of the model needs to be improved with further refinement in the model.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1077-1092
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• 2007

The structural analysis model for estimate of load carrying capacity of railway bridge on service line is important to determine safety of bridges in service, we need to take response of bridge exactly, applying analysis model similar to the real railway bridge most. Track structure which is to distribute loads and decrease vibrations occurred from running train is constructed on the railway bridges. And it is important factor which should be considered to understand exact dynamic and static responses of bridge. But track structure is currently classified as a none structural members in the structural analysis model for estimating load carrying capacity of railway bridge and not considered in analysis model. That's the reason it is difficult to understand exact behavior of bridges. Therefore, the major objective of this study is to develop an analytical track-bridge model which is similar to real railway bridges considering track structure for safety assessment of railway bridge on service line to be effectively done.

• Computers and Concrete
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• v.14 no.1
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• pp.19-40
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• 2014

Reinforced concrete deep beams are structural beams with low shear span-to-depth ratio, and hence in which the strain distribution is significantly nonlinear and the conventional beam theory is not applicable. A strut-and-tie model is considered one of the most rational and simplest methods available for shear strength prediction and design of deep beams. The strut-and-tie model approach describes the shear failure of a deep beam using diagonal strut and truss mechanism: The diagonal strut mechanism represents compression stress fields that develop in the concrete web between diagonal cracks of the concrete while the truss mechanism accounts for the contributions of the horizontal and vertical web reinforcements. Based on a database of 406 experimental observations, this paper proposes a new strut-and-tie-model for accurate prediction of shear strength of reinforced concrete deep beams, and further improves the model by correcting the bias and quantifying the scatter using a Bayesian parameter estimation method. Seven existing deterministic models from design codes and the literature are compared with the proposed method. Finally, a limit-state design formula and the corresponding reduction factor are developed for the proposed strut-andtie model.

• Journal of Distribution Science
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• v.11 no.11
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• pp.77-82
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• 2013

Purpose - This study investigated whether there are differences in advertising effects depending on the type of advertising, divided into public service announcements (PSA) and commercial advertisements, and the form of advertising model. Research Design, Data, and Methodology - By investigating the difference in advertising effects due to the type of advertising and form of advertising model, the study was expected to reveal the optimal advertisements for achieving the desired advertising effects. The subjects were Jangan University students in their first and second year, with 102 copies of the survey questionnaire received for analysis. Results - The findings were different for the celebrities, professionals, and CEOs, except for the PSA; further, they were different among celebrities, professionals and the other types of model, except CEO, in commercial advertising. Simple regression results showed that both the professionals and CEO models had a positive impact on the effect of advertising in the case of the PSA. Conclusion - These results suggested that appropriate selection of the form of advertising model is a very important factor. Conversely, it has been suggested that the celebrity model is the most effective, reflecting the trend for commercial advertisements.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.3
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• pp.315-322
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• 2016

Room acoustic properties of coupled rooms connected by an aperture has been analyzed using statistical acoustic model based on the diffused sound field assumption, which has limitation in dealing with the parameters such an room geometries and non uniform absorptivity of the boundary surfaces. In order to overcome these difficulties the acoustic diffusion model has been introduced, by which distribution of the acoustic energy density can be analyzed for various shapes and wall absorptivity. In this study acoustic properties of coupled rooms connected by an aperture(e.g. door) is analyzed using acoustic diffusion equation, which is solved numerically. The mean energy densities of two rooms obtained by the diffusion model are compared with those from the statistical model. The results show good agreement for various coupling aperture sizes and absorption coefficients. For a limiting case when the partition wall is substituted by an aperture and the two rooms eventually forms a single room, results of coupled room analysis using diffusion model show good agreement with those of a single room.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.170-180
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• 2008

The purpose of this study was to measure the causal relationships between past consumption, health belief, subjective, attitude, intention and purchase of organic foods. Total 326 copies of questionnaire were completed. The structural equation model was used to measure the causal effect among constructs. The results demonstrated that the confirmatory factor analysis model provided a good model fit. The proposed model yielded a significantly better fit to the data than the baseline model and the extended model. The effects of past consumption, health belief and subjective norm on attitude and intention were statistically significant. The effects of attitude on intention and behavior to purchase organic food were statistically significant. As expected, health belief and subjective had significant effects on behavior to purchase organic foods. Moreover, past consumption, health belief and subjective norm had indirect influences on intention through mediated variables. Based on the empirical results and findings, some suggestions are provided to the institutions concerned so as to facilitate this organic sector's on-going expansion in the food industry.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.145-150
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• 2017

This study aims to analyze panel data using OECD Health data of 34 years to examine how significant the inequality of income is to the inequality of health. The data was from OECD's pooled Health data of 32 countries from 1980 to 2013. The process of determining analysis model was as follows; First, through the descriptive statistics, we examined averages and standard deviation of variables. Second, Lagrange multiplier test has done. Third, through the F-test, we compared Least squares method and Fixed effect model. Lastly, by Hausman test, we determined proper model and examined effective factor using the model. As a result, rather than Pooled OLS Model, Fixed Effect Model was shown as effective in order to consider the characteristics of individual in the panel. The results are as follows: First, as relative poverty rate(${\beta}=-19.264$, p<.01) grows, people's life expectancy decreases. Second, as the rate of smoking(${\beta}=-.125$, p<.05) and the rate of unemployment (${\beta}=-.081$, p<.01) grows, people's life expectancy decreases. Third, as health expenditure(${\beta}=.414$, p<.01) shares more amount of GDP and as the number of hospital beds(${\beta}=-.190$, p<.05) grows, people's life expectancy increases.

• Journal of the Korean Society of Food Science and Nutrition
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• v.28 no.1
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• pp.178-190
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• 1999

This study was conducted to develop a simulation model for the growth dynamics of pigs and to describe quantitatively protein deposition depending on the amino acid composition of feed protein. In the model it is assumed that the essential processes that determine the utilization of feed protein in the whole body are protein synthesis, breakdown of protein, and oxidation of amino acid. Besides, it is also assumed that occurrence of protein deposition depends on genetic potential and amino acid composition of feed protein. The genetic potential for the protein deposition is the maximum capacity of protein synthesis, being dependent on the protein mass of the whole body. To describe the effect of amino acid composition of feed on the protein deposition, a factor, which consist of ten amino acid functions and lie between 0 and 1, is introduced. Accordingly a model was developed, which is described with 15 flux equations and 11 differential equations and is composed of two compartments. The model describes non linear structure of the protein utilization system of an organism, which is in non steady state. The objective function for the simulation was protein deposition(g/day) cal culated according to the empirical model, PAF(product of amino acid functions) of Menke. The mean of relative difference between the simulated protein deposition and PAF calculated values, lied in a range of 11.8%. The simulated protein synthesis and breakdown rates(g/day) in the whole body showed a parallel behavior in the course of growth.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.