• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.168-170
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• 2003

In this paper, we discuss the concept of Spatio-Temporal Data Warehouse and analyze the organization model of spatio-temporal data. Based on the above, we found the framework of Spatio-Temporal Data Warehouse composed of data source, processing tools and application, which covers the whole process from building warehouse to supplying services.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3341-3355
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• 2016

Background: A recent WHO data report on mortality attributable to tobacco use including cigarette smoking indicated a very high burden of deaths in Asia and that people often initiate smoking as early as young adolescents. The objectives of this study were to systematically review peer-reviewed articles on cigarette smoking initiation among Asian adolescents and to develop a conceptual model of factors influencing smoking initiation by integrating all relevant factors based on existing data. Materials and Methods: Following a PRISMA guideline, a systematic review of articles published between 2005 and June 2015 was conducted using 5 databases on cigarette smoking initiation among adolescents (aged 10-19 years) living in Asia. We summarized the main findings of each study according to our research questions and data that emerged during the data extraction process. Analysis and categorization were based on the TTI and TPB models and classification of factors extracted from the study, were as follows: personal factors, social factors, broader environmental factors, mediators, and intention to initiate smoking and smoking behavior. Results: Of 1,227 identified studies, only 20 were included in this review. Our findings found that the mean age of cigarette smoking initiation ranged from 10 to 14 years and those who are more likely to initiate smoking are male, older adolescents, adolescents with low parental SES, individuals with low parental monitoring, low parental education level and having no discussion on smoking at home, those living in public housing and those exhibiting health-risk behavior. Our study also revealed that the risk of smoking initiation increased when they are exposed to smokers, influenced by peers, exposed to tobacco advertisements, receive pocket money, have lack of knowledge about smoking, have poor school performance, have a family conflict and have psychological problems. The conceptual model developed demonstrated complex networks of factors influencing initiation. Conclusions: This systematic review presents various factors influencing smoking initiation of the Asian adolescents and provides a conceptual framework to further analyze factors. Future studies should have a standard measure of smoking initiation, should analyze interactions and the intensity of relationships between different factors or variables in the conceptual model. This will in turn consolidate the understanding of the different factors affecting smoking initiation and will help to improve interventions in this area.

• Korean Journal of Cognitive Science
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• v.17 no.1
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• pp.53-74
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• 2006

Similarity has been considered as one of basic concepts of cognitive psychology which is useful for explaining cognitive structure and process. MDS models(Shepard, 1964; Nosofsky, 1991) and Contrast model(Tversky, 1977) were proposed as early models of similarity comparison process. But, there have been a lot of theoretical doubts about the conceptual validity of similarity as a result of empirical findings which could not be explained by early models. Goldstone(1994) assumed that similarity could be defined by alignment processes, and suggested structural alignment as a prospective alternative for solving conceptual controversies so far. In this study, basic assumption and algorithms of MDS models(Shepard, 1944; Nosofsky, 1991) and Contrast model(Tversky, 1977) were described shortly and some theoretical limitations such as arbitrariness of selective attention and correlated structures were discussed as well. The conceptual characteristics and algorithms of SIAM(Goldstone, 1994) were described and how it has been applied to cognitive psychology areas such as categorization, conceptual combination, and analogical reasoning were reviewed. Finally, some theoretical limitations related with data-driven processing and alternative processing and possible directions for structural alignment were discussed.

• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.91-99
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• 2006

The purpose of this study is propose an Artificial Neural Network(ANN) model for the construction estimate of the public educational facility at conceptual stage. The current method for the preliminary cost estimate of the public educational facility uses a single-parameter which is based on basic criteria such as a gross floor area. However, its accuracy is low due to the nature of the method. When the difference between the conceptual estimate and detailed estimate is huge, the project has to be modified to meet the established budget. Thus, the ANN model is developed by using multi-parameters in order to estimate the project budget cost more accurately. The result of the research shows 6.82% of the testing error rates when the developed model was tested. The error rates and the error range of the developed model are smaller than those of the general preliminary estimating model at conceptual stage. Since the proposed ANN model was trained using the detailed estimate information of the past 5 years' school construction data, it is expected to forecast the school project cost accurately.

• Journal of The Korean Association For Science Education
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• v.27 no.5
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• pp.379-393
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• 2007

The purpose of this article is to analyze the conceptual change of nine 11th graders after implementing the model-based instruction of blood circulation by multidimensional framework, and to find some implications about teaching strategies for improving conceptual understanding. The model-based instruction consisted of 4 periods: (1) introduction for inducing students' interests using an episode in the science history of blood circulation, (2) vivisectional experiment on rats, (3) visual-linguistic model instruction using the videotape of heartbeat, and (4) modeling activity on the path of blood flow. Based on the data from pre-test, post-test and interviews, we classified students' models on the path of blood flow, and investigated their ontological features and the conceptual status of blood circulation. Most students could describe the path of blood flow and the changes of substances in blood precisely after the instructions. However, the modeling activity were not sufficient to improve students' understanding of the mechanisms of the blood distribution throughout various organs and the material exchanges between blood and tissues. From the interview of 9 students, we acquired informative results about conceptual status elements that were helpful to, preventing from, or not used for students' understanding. It was also found that conceptual status of students depended on the ontological categories into which students' conceptions of blood circulation fell. The results of this study can help design the effective teaching strategy for the understanding of concept of the equilibrium category.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.910
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• pp.1253-1264
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• 2004

The purpose of this study is to develop clothing shopping orientation[CSO] scale reflecting the conceptual structure of CSO. For this purpose, a questionnaire composed of comprehensive 85 CSO items was developed through 2-step preliminary tests. Data was collected from two samples. One sample(n=559) was for scale development and the other sample(n=235) was for cross validity test. Descriptive analysis, correlation analysis, exploratory factor analysis, regression analysis, ANOVA, and confirmatory factor analysis were used for data analysis. For each lower-dimension within the CSO conceptual structure model, 1-2 items were selected based on the quantitative and the qualitative standards. As a result, a CSO scale composed of 31 items was developed, and reliability, construct validity, cross validity, convergent validity, discriminant validity, and criterion validity of the scale were verified. This study has significance in offering the standardized scale to both the academic and the practical fields.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.781-790
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• 2013

This research focuses on development of the conceptual cost estimation models for I.L.M box girder bridge. The current conceptual cost estimation for public construction projects is dependent on governmental average unit price references which has been regarded as inaccurate and unreliable by many experts. Therefore, there have been strong demands for developing a better way of conceptual cost estimating methods. This research has proposed three different conceptual cost estimating method for a P.S.C. girder bridge built with the I.L.M method. Model (I) attempts to seek the proper breakdown of standard works that are accountable for more than 95 percentage in total cost and calculates the amount of standard work's materials from the standard section and volume of I.L.M box girder bridge. Model (II) utilizes a correlation analysis (coefficient over 0.6 or more) between breakdown of standard works and input data that would be considered available information in preliminary design phase. Model(III) obtains conceptual estimating through multiple-regression analysis between the breakdown of standard works and all of input data related to them. In order to validate the clustering of coverage in the preliminary design phase, the variation of I.L.M cost coverage from multiple-regression analysis[model(III)] has been investigated which result in between -3.76% and 11.79%, comparing with AACE(Association for the Advancement of Cost Engineering) which informs its variation between -5% and +15% in the design phase. The model proposed from this research are envisioned to be improved to a great distinct if reliable cost date for P.S.C. girder bridges can be continually collected with reasonable accuracies.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.217-225
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• 2009

In case of sketching a conceptual model in 3D space, it's not easy for designer to recognize the depth cue accurately and to draw a model correctly in short time. In this paper, multi-strokes based sketch is adopted not only to reduce the error of input point but to substantiate the shape o) the conceptual design effectively. The designer can see the drawing result immediately after stroking some curves. The shape can also be modified by stroking curves repeatedly and be confirmed the modified shape in real time. However, the multi-strokes based sketch needs to manage the great amount of input data. Therefore, the drawing space is divided into the limited spatial cubical grids and the movable infernal vertex in each spatial grid is implemented and used to define the surface by the multi-strokes. We implemented the spatial sketching system which allows the concept designer's intention to 3D model data efficiently.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

• Journal of Soil and Groundwater Environment
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• v.28 no.2
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• pp.12-29
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• 2023

Conceptual site model (CSM) development and enhancement for contaminated sites assists in identifying data gaps during the site investigation process. In this study, CSM was developed and enhanced for a contaminated site in Korea as a case study. Site Y was scrutinized four times previously. The site profiles for each scrutiny were reorganized based on the scrutiny reports, and the relevant data was utilized to develop and enhance CSMs. CSM for the first investigation was developed in various forms including table, flowchart, diagram, and narrative formats. CSM was enhanced in a stepwise manner by incorporating the updated profile information obtained in next investigation to existing CSM. The hypothetical data gap analysis between each investigation step was established to meet the purpose of the follow-up investigation. This case study showed that CSM is a useful tool to identify the history and current status of contaminated sites and thereby help in planning supplementary investigations for better site characterization.