• Journal of Korea Trade
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• 제25권2호
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• pp.22-45
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• 2021

Purpose - This study aims to identify new attributes by analyzing reviews conducted by global automaker customers and to examine the influence of these attributes on satisfaction ratings in the U.S. automobile sales market. The present study used J.D. Power for customer responses, which is the largest online review site in the USA. Design/methodology - Automobile customer reviews are valid data available to analyze the brand personality of the automaker. This study collected 2,998 survey responses from automobile companies in the U.S. automobile sales market. Keyword analysis, topic modeling, and the multiple regression analysis were used to analyze the data. Findings - Using topic modeling, the author analyzed 2,998 responses of the U.S. automobile brands. As a result, Topic 1 (Competence), Topic 5 (Sincerity), and Topic 6 (Prestige) attributes had positive effects, and Topic 2 (Sophistication) had a negative effect on overall customer responses. Topic 4 (Conspicuousness) did not have any statistical effect on this research. Topic 1, Topic 5, and Topic 6 factors also show the importance of buying factors. This present study has contributed to identifying a new attribute, personality. These findings will help global automakers better understand the impacts of Topic 1, Topic 5, and Topic 6 on purchasing a car. Originality/value - Contrary to a traditional approach to brand analysis using questionnaire survey methods, this study analyzed customer reviews using text mining. This study is timely research since a big data analysis is employed in order to identify direct responses to customers in the future.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1132-1142
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• 2001

The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1999년도 추계 학술대회논문집
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• pp.152-157
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• 1999

For the simulation of the blood flow in coronary artery, the system modeling of coronary hemodynamics is combined with CFD technique. The blood flow in coronary artery interacts with the global coronary circulation. Especially in case of the coronary artery with stenosis, the interaction plays an important role in the hemodynamics of the circulation. In this study we present a combined numerical approach using both the CFD technique for flow simulation and the global system model of coronary circulation. We use a lumped parameter model for the global simulation of coronary circulation whereas the finite element method is employed to compute the viscous flow field in stenosed coronary artery, The time variation of the pressure drop due to stenosis is obtained from the proposed numerical method. Numerical results shows that the flow resistance and pressure drop due to stenosis has a relatively large value in systole.

• 한국환경과학회지
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• 제25권7호
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• pp.1029-1042
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• 2016

The initial and boundary conditions are important factors in regional chemical transport modeling systems. The method of generating the chemical boundary conditions for regional air quality models tends to be different from the dynamically varying boundary conditions in global chemical transport models. In this study, the impact of real time Copernicus atmosphere monitoring service (CAMS) re-analysis data from the modeling atmospheric composition and climate project interim implementation (MACC) on the regional air quality in the Korean Peninsula was carried out using the community multi-scale air quality modeling system (CMAQ). A comparison between conventional global data and CAMS for numerical assessments was also conducted. Although the horizontal resolution of the CAMS re-analysis data is not higher than the conventionally provided data, the simulated particulate matter (PM) concentrations with boundary conditions for CAMS re-analysis is more reasonable than any other data, and the estimation accuracy over the entire Korean peninsula, including the Seoul and Daegu metropolitan areas, was improved. Although an inland area such as the Daegu metropolitan area often has large uncertainty in PM prediction, the level of improvement in the prediction for the Daegu metropolitan area is higher than in the coastal area of the western part of the Korean peninsula.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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• pp.136-138
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• 2003

UML cannot meet all the requirements offered in different software system for diverse application domain. GNSS (Global Navigation Satellite System) application domain is an especial environment that requires precise measurement and precision calculation of real-world geographical entities with the help of GPS (Global Position System) in both temporal and spatial factor. Therefore in the paper new extended iconic stereotypes for better modeling GNSS application in the UML Diagram are proposed, and the implementation of a program called StereotypeCreator, which is able to create iconic stereotypes used in one of the most popular visual modeling tools for software development, Rational Rose, will be also proposed.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제42회 동계 정기 학술대회 초록집
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• pp.179-179
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• 2012

Low pressure radio-frequency glow discharges are investigated using theoretical modeling and various experimental diagnostic methods. In the calculations, global models and transformer models are developed to understand the chemical kinetics as well as the electrical properties such as the effective collision frequency, the heating mechanism and the power transferred to the plasma electrons. In addition, Boltzmann equation solver is used to compensate the effect of the electron energy distribution function (EEDF) shape in the global model, and the general expression of energy balance for non-Maxwellian electrons is developed. In the experiments, a number of traditional plasma diagnostic methods are used to compare with calculated results such as Langmuir probe, optical emission spectroscopy (OES), optical absorption spectroscopy (OAS) and two-photon absorption laser-induced fluorescence (TALIF). These theoretical and experimental methods are applied to understand several interesting phenomena in low pressure ICP discharges. The chemical and physical properties of low pressure ICP discharges are described and the applications of these methods are discussed.

• International Journal of CAD/CAM
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• 제7권1호
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• pp.81-89
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• 2007

As the modular production is an important issue in globalized manufacturing industries, sub modules or parts of the final product are provided by many suppliers. Some part suppliers design their own products for themselves. In some cases, part supplier may provide the same type product to multiple 1-tier companies. Because all suppliers and 1-tier companies can not use the same CAD system in general case, the engineering change in the CAD model of one company could not propagate to related CAD models of other companies directly. Although they use the same CAD system, it is hard to share their CAD model with each other because of company security policy. In this paper, the neutral reference model, which consists of the neutral skeleton model and the external reference model, is proposed to apply a global top-down modeling approach to collaborating companies.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.25-30
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• 1997

Genetic Algorithm(GA) is a parallel, global search technique modeled with the Darwinian principle of survival and reproduction of the fittest. Since Holland has proposed GA called the Simple GA, considerable research has focused of improving Simple GA performance. In this paper, I describe some methods of GA's modeling in different field.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2006년도 PARALLEL CFD 2006
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• pp.188-189
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• 2006

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4095-4101
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• 2022

Following the climate-related disasters considered by several efforts, the nuclear capacity needs to double by 2050 compared to 2015. So, it is reasonable to investigate global warming incorporated with the fuzzy set theory for nuclear energy consumption in the aspect of fuzziness and nonlinearity of temperature variations. The complex modeling is proposed for the enhanced assessment of climate change where simulations indicate the degree of influence with the Boolean values between 0.0 and 1.0 in the designed variables. In the case of OIL, there are many 1.0 values between 20^th and 60^th months in the simulations where there are 10 times more for a 1.0 value in influence. Hence, the temperature variable can give the effective time using this study for 100 months. In the analysis, the 1.0 value in NUCLEAR means the highest influence of the modeling as the temperature increases resulting in global warming. In detail, the first influence happens near the 8th month and then there are four times more influences than effects in the early part of the temperature mitigation. Eventually, in the GLOBAL WARMING, the highest peak is around the 20^th month, and then it is stabilized.