• Journal of Korean Society of Steel Construction
• /
• v.29 no.4
• /
• pp.311-321
• /
• 2017

This paper deals with the flexural performance of a composite girder system designed to readily form a composite section without a formwork and to easily realize multistage preflexing and prestressing. After a 3-Dimensional finite element modeling for construction stage analysis, the parametric numerical analysis was performed to analyse the stress distribution on the composite girder sections and the prestressing effects along with concrete pouring method and strand tensioning method. Based on the stress distribution analysis, a favorable construction stage model has been rationally chosen and then the ultimate flexural strengths were evaluated to conduct a comparative study, which exceed the nominal flexural strength suggested by the current design specification(ASD). It can be concluded that the proposed composite girder and fabrication procedure should have a sufficient structural performance.

• 한국데이터정보과학회:학술대회논문집
• /
• 2006.04a
• /
• pp.109-120
• /
• 2006

Huge information has been made due to the current computing environment and could not be acceptable. People want the information which they can understand and accept easily. They may want not only simple information but also knowledge. That is why data mining becomes a center of information. We use RFM analysis in order to create customer score. Customers are classified into five groups(most oxcellenrexcellenycommoflowerilowest) for a various marketing activities. We can found the significant patterns in each group, and classify customers from loyal customers to leaving customers in the near future by the indirect data mining(e.g. association analysis) and the direct data mining(e.g. decision tree, logistic regression analysis, etc.), which are named in this study. Our research focuses on the advanced models by applying the association rules in data mining. Our results indicate that the indirect data mining and the direct data mining seem to have same outputs, but the former shows more clear pattern then the latter one.

• Journal of Korean Society of Steel Construction
• /
• v.9 no.4 s.33
• /
• pp.649-658
• /
• 1997

When steel tube as a column is filled with concrete, it is common that the load-bearing capacities of CFST(Concrete Filled Steel Tube) column are increased substantially, And the CFST column can obtain a capacity of fire resistance without any additional detail on the surface of the steel tube for fire protection. In order to clarify the behavior of CFST column during fire occurrence, a theoretical study is performed, that is, a thermal analysis is used to find temperature gradient dependent on the time on the steel tube and the infilled concrete. N-M (axial force-moment) interaction curves are summarized under the consideration for time dependent variation. The material properties of concrete and steel in accordance with a temperature variation are referred to the existing general data. Thermal transient analyses are performed by finite element method through ANSYS and then these results are verified by comparing with the existing test results. On the basis of analytical results, load-carrying capacities (N-M interaction curves) are calculated by numerical analysis method.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.39 no.5
• /
• pp.433-441
• /
• 2011

The optimization of a centrifugal compressor was conducted. The ANN (Artificial Neural Network) was adopted as an optimization algorithm, and it was learned and trained with the DOE (Design of Experiment). In the DOE, it was predicted the main effect and the interaction effect of design variables to the objective function. The ANN was improved in the optimization process using the GA (Genetic Algorithm). When any output at each generation was reached a standard level, it was re-calculated by the CFD (Computational Fluid Dynamics) and it was applied to develop a new ANN. After 6th generation, the prediction difference between ANN and CFD was less than 1%. A pareto of the efficiency versus the pressure ratio was obtained through the 21th generation. Using this method, the computational time for the optimization was equivalent to the time consumed by the gradient method, and the optimized results of multi-objective function were obtained.

• Korean Business Review
• /
• v.11
• /
• pp.149-171
• /
• 1998

The most important thing in the Tourist Market Segmentation is to find descriptive variables which can describe the changes of tourist demand properly. There are many descriptive variables. Among them, vital statistical variables were proved to be effective. The strongest variable but which was studied much less is the Family Life Cycle. This study will focus on the relation between Family Life Cycle and Travel Behavior of Destination Choice. In this study, I will verify the validity of Family Life Cycle as a descriptive variable of Tourist Market Segmentation, and try to find the meaningful variable at each steps. Therefore, The purpose of this study is to explain the relation between Family Life Cycle and Travel Behavior of Destination Choice, to verify the validity of Family Life Cycle as descriptive variable and to find the strategy to respond to the increase in quantity and diversity of quality of Tourist Market. The studies on the Family Life Cycle should be updated continuously according to the change of family structure and it should be understood as standard for Tourist Market Segmentation in the public and private sphere.

• The Journal of Society for e-Business Studies
• /
• v.19 no.4
• /
• pp.21-30
• /
• 2014

Personalized data of users at social network service can be used as a new resource for providing personalized nutrition information. Although providing personalized information for nutrition using social data, there are a few studies on providing personalized nutrition information with customized user preference based on social network service. The purpose of this study is to implement the clustering of data analysis with collected personal data of Facebook users. To find out the method for providing personalized information, this study described an effective method for providing nutrition information by analyzing web posting on Facebook that can be called a typical social network service. According to the result from clustering, sodium and sugars were important variables from diet of user. Furthermore, the importance of elements of user's diet has some differences according to vendor/manufactures.

• Korean Journal of Remote Sensing
• /
• v.21 no.2
• /
• pp.163-171
• /
• 2005

I have developed a processor for synthetic aperture radar (SAR) raw data compression using range-doppler algorithm for educational purpose. The program realized a generic SAR focusing algorithm so that it can deal with any SAR system if the specification is known. It can run efficiently on a low-cost computer by selecting minimum size out of a whole dataset, and can produce intermediate images during the process. Especially, the program is designed for educational purpose in such a way that Doppler centroid and azimuth ambiguity can be determined graphically by the user. By distributing the source code and the algorithm to public, I intend to maximize the educational effect on understanding and utilizing SAR data. This paper introduces the principle of SAR focusing algorithm embedded on the eSAR processor and shows an example of data processing using ERS-1 raw data.

• Journal of Korea Port Economic Association
• /
• v.38 no.2
• /
• pp.49-67
• /
• 2022

This study applied the method of Diebold and Yilmaz (2012, 2014, 2016) to analyze the connectedness between the Freight Index (BDI, BDTI, BCTI), energy price(oil, natural gas, coal), and grain price(soybean, corn, wheat) from July 19, 2007 to March 31, 2022. The main analysis results of this paper are as follows. First, according to the network analysis results, the total connectedness was measured to be 20.43% for the entire analysis period, indicating that there was a low correlation between the freight index and the commodity price. In addition, looking at the directional results, the variable with the greatest effects was corn, and conversely, the variable with the lowest effects BDI. When classified by events, BCTI was found to play a major role only during the COVID-19 period. Second, according to the results of the rolling-sample analysis, the total connectedness be found to be highly correlated with changes in economic conditions such as the financial crisis, trade war, and COVID-19 when specific events occurred.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.12
• /
• pp.7224-7230
• /
• 2014

This study attempted to identify the health-related quality of life and its related factors in urban elderly women. This study used the data of the 2011 Community Health Survey. The subjects of this study were 704 elderly women. Based on the literature review, this study examined variables with health-related quality of life and construct integrated conceptual framework of the study. For data analysis, SPSS 18.0 and LISREL 8.8. were used to calculate the percentage, mean, standard deviation, Spearman correlation, and path analysis parameter. The total mean EQ-5D index score was $0.81({\pm}0.20)$ and the major problems were pain/discomfort (62.5%) and mobility (53.9%) and normal activity (38.9%). The model showed a goodness of fit to the empirical data. Age, income, health promotion behavior, social support, physical health and mental health had significant direct effects on EQ-5D and age, income, health promotion behavior and social support had indirect effects on EQ-5D. These variables explained 28% of the variance of EQ-5D. To improve the quality of life in urban elderly women, it is essential to have a comprehensive program for elderly women.

• Korean Journal of Social Welfare
• /
• v.68 no.4
• /
• pp.53-74
• /
• 2016

In this study, to verify influence that economic situations of a household unit have on donation behavior, after economic situations of a household unit were measured with income and assets by type and income to assets, effect which each variable has on secular giving was verified. This study used 3-year panel data of a total of 4,938 households based on the fifth to seventh year data as investigation data from 2012 to 2014 among data of financial panel investigation of Korea Institute of Public Finance of National Survey of Tax and Benefit. As an analysis method, a random effect tobit model was used. At the analysis result, it appeared that as scales of financial assets, earned income, property income, and transfer income become larger, the amount of donation increased. Also, it was represented that rates of income to assets had negative influence on secular giving. In case of demographic variables, education levels of householders and sizes of houses had relation of a positive direction. In case of ages, it appeared that they had inverted U-type relation. This study has meanings in that understanding of donation behavior of a household unit can be increased and expanded more and also implications related to intervention strategies of a household unit to expand sharing culture can be extracted by verifying influence which economic factors of a household unit have on donation behavior based on panel data.