• Journal of the Korean Home Economics Association
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• v.34 no.4
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• pp.103-117
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• 1996

This study is a theoretical approach by literature about life style and housing life style. The purpose of this research is making an analysis model of housing life style which can be used as a conceptual framework in empirical study. the theme of‘Life style’was studied mainly in the area of consumerism and housing. Model was made to explore the sub-domain of new analysis model by the microsociological approach. As results, 1) Independent variable of housing life style research model must be selected to be possible of comparison in effect of objective and subjective variable and in effect of predictive function and well-being function of housing life style. 2) Sub-domain of housing life style must be consisted of value orientation of family life, consumption in house, consumer durables, furniture., and propensity to using space. 3) Conceptual model of housing life style must be tested in empirical study to know what is the housing adjustment behavior of individual family, to improve quality of housing life and to suggest housing policy for family as a consumer.

• Journal of The Korean Association For Science Education
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• v.10 no.1
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• pp.47-55
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• 1990

The purposes of this study are to investigate Korean middle school students' conceptions related to electric current, and to analyze their changes in explanations about current after their observations of the related phenomena The subjects of the study were 20 students from one middle school in Seoul The conclusions of the studty are as follows: 1, Korean middle school students have various misconceptions such as current consumption model, sequential model, monopole model, non-various current model, the most students have sequential model' 2. When an evidence is introduced, some students do not perceive the phenomena as the teacher attempts. 3. When an evidence was introduced, after observation of the evidence some of the students who had misconceptions changed their explanatios, which were not always correct explanations, and the others did not change their expanations, which their observations were mostly incorrect.

• Journal of The Korean Association For Science Education
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• v.12 no.1
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• pp.35-46
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• 1992

The purpose of this study was to investigate the most effective teaching model in the study of boiling point elevation. The teaching models were classified into three group-deductive, inductive and analogical teaching models. Learning materials, based on three teaching models respectively, were applied to 11th grade students, and the effect of teaching models were investigated and analyzed. The average achievement score(4.24) of the group treated with the analogical teaching model was higher than those(3.06 respectively) of each group treated with inductive or deductive teaching model(p<0.001). Most students answered that the analogical teaching model was helpful and interesting one for the comprehension of scientific concept.

• Korean Journal of English Language and Linguistics
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• v.4 no.2
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• pp.151-174
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• 2004

A historical investigation reveals that English preposition with underwent a change from OPPOSITION to ASSOCIATION and further to ACCOMPANIMENT, where the first stage shows peculiarity in that the two concepts involved comprise an unusual set to form an extensional chain. Intrigued by this oddity, this paper aims to investigate the semantic structure of English preposition with from a grammaticalization perspective. We review mechanisms and models of semantic change and evaluate their adequacy with the semantic structure and change shown by with. Drawing upon the observed fact that with underwent the apparent antonymic semantic change, it is argued that such semantic change mechanisms as metaphor, metonymy, subjectification, and generalization have difficulties explaining the change, and that only the Frame-of-Focus Variation can effectively account for this peculiar change type. In terms of semantic change models, we argue that the Bleaching Model cannot effectively provide an explanation; that the Loss and Gain Model has problems in explaining the motivation of change directions; that the Metonymic-Metaphoric Model cannot be assessed at the current level of investigation; and that the Overlap Model and the Prototype Extension Model excellently account for the macro-level changes.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1560-1563
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of support vector machine neural networks model (SVM-NNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of SVM-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2004.11a
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• pp.221-232
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• 2004

Paper process is complex and multivariable system. Identification of a paper process model is imperative for the development of predictive control method. 13-level Pseudo-Random Sequence Signals were used to identify the plant model in which the neural network model was considered model as a real paper process. Results of simulations for identification using 13-level PRS signals and Prediction Error Method are compared with plant operation data. From the comparison, we can see that the dynamics of the model show good agreement with those of real plant.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.200-204
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• 2012

In engineering hydrology, an estimation of precipitation loss is one of the most important issues for successful modeling to forecast flooding or evaluate water resources for both surface and subsurface flows in a watershed. An accurate estimation of precipitation loss is required for successful implementation of rainfall-runoff models. Precipitation loss or hydrological abstraction may be defined as the portion of the precipitation that does not contribute to the direct runoff. It may consist of several loss elements or abstractions of precipitation such as infiltration, depression storage, evaporation or evapotranspiration, and interception. A composite loss rate model that combines four loss rates over time is derived as a lumped form of a continuous time function for a storm event. The composite loss rate model developed is an exponential model similar to Horton's infiltration model, but its parameters have different meanings. In this model, the initial loss rate is related to antecedent precipitation amounts prior to a storm event, and the decay factor of the loss rate is a composite decay of four losses.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.557-557
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• 2015

To overcome main drawbacks of parametric models, k-nearest neighbor resampling (KNNR) is suggested for water quality analysis involving geographic information. However, with KNNR nonparametric model, Geographic information is not properly handled. In the current study, to manipulate geographic information properly, we introduce a depth function which is a novel statistical concept in the classical KNNR model for stormwater quality simulation. An application is presented for a case study of the total suspended solids throughout the entire United States. Total suspended solids concentration data of stormwater demonstrated that the proposed model significantly improves the simulation performance rather than the existing KNNR model.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.194-194
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• 2017

Flooding is one of the most serious and frequently occurred natural disaster at many regions around the world. Especially, under the climate change impact, it is more and more increasingly trend. To reduce the flood damage, flood forecast and its accuracy analysis are required. This study is conducted to analyze the accuracy of the real-time flood forecasting of a coupled meteo-hydrological model for the Han River basin, South Korea. The LDAPS (Local Data Assimilation and Prediction System) products with the spatial resolution of 1.5km and lead time of 36 hours are extracted and used as inputs for the SURR (Sejong University Rainfall-Runoff) model. Three statistical criteria consisting of CC (Corelation Coefficient), RMSE (Root Mean Square Error) and ME (Model Efficiency) are used to evaluate the performance of this couple. The results are expected that the accuracy of the flood forecasting reduces following the increase of lead time corresponding to the accuracy reduction of LDAPS rainfall. Further study is planed to improve the accuracy of the real-time flood forecasting.