• Journal of the Korean GEO-environmental Society
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• v.19 no.6
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• pp.5-12
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• 2018

Domestic design manuals provide various empirical relationships of design parameters of soils with N values from the Standard Penetration Test (SPT), which can be widely used in the basic design process as well as during the construction process. However, the currently used empirical relationships are based on the data from foreign countries and are rarely evaluated with domestic data with currently used site investigation techniques. Therefore, in this study, those empirical relationships and conversion tables are evaluated with the geotechnical information in the Integrated DB Center of National Geotechnical Information and new empirical relationships are newly proposed with the consideration of domestic geotechnical conditions.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.374-383
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• 2020

At ship design stage, the maneuverability is generally estimated based on the empirical formula or the computational fluid dynamic (CFD), which is one of the numerical simulation methods. Using the hydrodynamic derivatives derived through these methods can quantitatively estimate the maneuverability of target vessels and evaluate indirect maneuverability. Nevertheless, research on estimating maneuverability is insufficient for ships not subject to IMO maneuverability standard, especially fishing vessels, and even at the design stage, the empirical formula developed for merchant ships is applied without modification. An estimation error may occur due to the empirical formula derived from the regression analysis results of a model test if the empirical formula developed for merchant ships with different hull shapes is applied to fishing vessels without any modification. In this study, the modified empirical formula that can more accurately estimate the fishing vessel's maneuverability was derived by including the hull shape parameter of target fishing trawlers in the regression analysis process that derives Kijima et al. (1990) formula. As a result, the modified empirical formula showed an average estimation error of 6%, and the result improved the average error of 49% of Kijima et al. (1990) formula developed for merchant ships.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.10
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• pp.1671-1686
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• 2010

This research presents a fashion adoption process model based on collective selection theory and examines the differences in the consumer adoption process of merchandising types at each stage of the fashion cycle. A questionnaire survey of 472 adult women was conducted for the purpose of empirical analysis of the fashion adoption process. The results show that fashionability and popularity (the primary attributes of fashion goods) have direct effects on resistance and adoption as well as indirectly through social compatibility and personal compatibility in the evaluation stage. In conclusion, on the theoretical side, this study verified the fashion process model according to consumer participation in the adoption process of fashion goods existing at different stage of the fashion cycle, internally through negotiating with individual tastes, and externally through interacting with others. On the practical side, this study presented an empirical result that can apply to merchandizing strategy centered on merchandizing type by connecting consumer adoption for the fashion goods released by actual companies.

• Journal of Industrial Convergence
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• v.20 no.1
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• pp.23-33
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• 2022

The study was conducted to develop an implementation model for digital transformation (DX) of manufacturing companies. To this end, previous studies on the process of management innovation and digital transformation were reviewed. The DX process model was derived based on the NEBIC theory and innovation theory applied in the innovation process of the Internet business. In addition, a research model including the factors of the will of the top management class (TMT) was constructed and confirmed through empirical data. The research hypothesis were verified based on data collected from members of mid-sized manufacturing companies promoting digital transformation. Through regression analysis, the influence relationship of each stage of the research model (technical knowledge, TK → opportunity perception, OR → performace expectation, PE and → Intention to execute, IE) was confirmed. Hierarchical regression analysis was conducted to understand the mediating effect of the members' perception of the top management's willingness to promote DX in the process. As a result of checking the Sobel test, it was confirmed that the management's perception of DX promotion partially mediated the relationship at each stage. This study is meaningful in that it presented a model applicable to the digital transformation of the mid-sized manufacturing industry. It is also valuable in providing an empirical basis for innovative research and NEBIC expansion. Longitudinal studies are required to overcome the limitations of empirical data for process models with dynamic characteristics whereas extended empirical studies are required in various fields other than manufacturing to generalize research results.

• Journal of the Korean Mathematical Society
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• v.38 no.1
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• pp.25-35
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• 2001

In this paper we consider an age dependent branching process whose particles move according to a Markov process with continuous state space. The Markov process is assumed to the stationary with independent increments and positive recurrent. We find some sufficient conditions for he Markov motion process such that the empirical distribution of the positions converges to the limiting distribution of the motion process.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1197-1211
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• 2011

The actual power performance of historical structural change tests are compared under various alternatives. The tests of interest are F, CUSUM, MOSUM, Moving Estimates and empirical distribution function tests with both recursive and ordinary least-squares residuals. Our comparison of the structural tests involves limiting distributions under the hypothesis, the ability to detect the alternative hypotheses under one or double structural change, and smooth change in parameters. Even though no version is uniformly superior to the other, the knowledge about the properties of those tests and connections between these tests can be used in practical structural change tests and in further research on other change tests.

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.271-273
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• 2006

This paper focuses on the developed empirical models for the prediction on top-bead width in GMA(Gas Metal Arc) welding process. Three empirical models have been developed: linear, curvilinear and an intelligent model. Regression analysis was employed fur optimization of the coefficients of linear and curvilinear model, while Genetic Algorithm(GA) was utilized to estimate the coefficients of intelligent model. Not only the fitting of these models were checked, but also the prediction on top-bead width was carried out. ANOVA analysis and contour plots were respectively employed to represent main and interaction effects between process parameters on top-bead width.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.3
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• pp.395-409
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• 1994

Consumers experience various emotional responses to clothing in consumption process. These emotional responses are important in explaining consumer behavior of clothing. The Purpose of the study was to identify the types of emotion that consumers experience in the process of wearing clothes. A questionnaire consisted of 35 words expressing emotion was developed. 110 female college students were surveyed to find out consumption experience of clothing. The empirical study was conducted in two ways. One is that the subjects were asked to respond six-point unipolar scale of emotional adjectives to identify the various emotions that consumers experienced. The other is that four different wearing situations were described for the survey and then the subjects were asked to respond same questionnaire. The data surveyed for research were analyzed by factor analysis. The conclusion of empirical study was as follows. The types of emotion that consumers experienced at various situstions were: pleasure, arousal, unpleasure, aversion, dominance, sandness, security and tension.

• Journal of the korean Society of Automotive Engineers
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• v.10 no.4
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• pp.39-56
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• 1988

In this study, the computer program was developed to predict the engine performances and exhaust emissions of a 4-cylinder 4-stroke cycle ignition engine including intake and exhaust system. The simulation models applied to each process were as follows. For the combustion process, two zone model which requires only one empirical constant was applied, and for the gas exchange process, the method of characteristics that allows the calculations of the time variation and spatial variation of properties along the pipes was used. Constant pressure perfect mixing model was applied to take into account of the interaction at manifold branches. To predict exhaust emissions, twelve chemical species were considered to be present in combustion products. These species were calculated through equilibrium thermodynamics and kinetic theory. The empirical constants reduced to least number as possible were determined through the comparison with the experimental indicator diagram of one particular operating condition and these constants were applied to other operating conditions. The predicted performances and emissions were compared with the experimental results over the wide range of operating conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.395-395
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• 2000

Optimization of existing processes becomes more important than the past as environmental problems and concerns about energy savings stand out. When we can model a process mathematically, we can easily optimize it by using the model as constraints. However, modeling is very difficult for most chemical processes as they include numerous units together with their correlation and we can hardly obtain parameters. Therefore, optimization that is based on the process models is, in turn, hard to perform. Especially, f3r unknown processes, such as bioprocess or microelectronics materials process, optimization using mathematical model (first principle model) is nearly impossible, as we cannot understand the inside mechanism. Consequently, we propose a few optimization method using empirical model evolutionarily instead of mathematical model. In this method, firstly, designing experiments is executed fur removing unecessary experiments. D-optimal DOE is the most developed one among DOEs. It calculates design points so as to minimize the parameters variances of empirical model. Experiments must be performed in order to see the causation between input variables and output variables as only correlation structure can be detected in historical data. And then, using data generated by experiments, empirical model, i.e. response surface is built by PLS or MLR. Now, as process model is constructed, it is used as objective function for optimization. As the optimum point is a local one. above procedures are repeated while moving to a new experiment region fur finding the global optimum point. As a result of application to the pulp digester benchmark model, kappa number that is an indication fur impurity contents decreased to very low value, 3.0394 from 29.7091. From the result, we can see that the proposed methodology has sufficient good performance fur optimization, and is also applicable to real processes.