• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.1
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• pp.83-92
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• 2019

Advertising signboards are designed for the visibility to affects recall and recognition of costumers. It is well know that the visibility from images is created by the value difference among colors. The research defines whether the background color combination of outdoor signboards is configured to maximize visibility, by a series of color value variation in complex commercial facilities. The subject of study is to examine how the visibility is made by the color combination since visibility cannot be obtained independently. Two steps of analysis were performed to confirm that the color composition of signboards was based on the color value difference. The first is to analyze that the entire colors of signboards are clearly categorized as different value groups. All components of colors, hue, value and chroma had been analyzed by color aesthetic measures to prove that the value variation has the only regularity and the principle of composition. The second step is a further verification with an ample amount of samples to determine whether series of signboards create a value altering pattern. The data for analysis is gained by colorimetric survey and the color data are used for exponentializing the degree of combining, which shows selective affinity between each pair colors.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.267-276
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• 2004

Much of previous attention on researches of the decision tree focuses on the splitting criteria and optimization of tree size. Nowadays the quantity of the data increase and relation of variables becomes very complex. And hence, this comes to have plenty number of unnecessary node and leaf. Consequently the confidence of the explanation and forecasting of the decision tree falls off. In this research report, we propose some decision tree algorithms considering the interaction of predictor variables. A generic algorithm, the k-1 Algorithm, dealing with the interaction with a combination of all predictor variable is presented. And then, the extended version k-k Algorithm which considers with the interaction every k-depth with a combination of some predictor variables. Also, we present an improved algorithm by introducing control parameter to the algorithms. The algorithms are tested by real field credit card data, census data, bank data, etc.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.265-274
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• 2003

Time series data are influenced by the external events such as holiday, strike, oil shock, and political change, so the external events cause a sudden change to the time series data. We regard the observation as outlier that occurred as a result of external events. In general, it is called intervention if we know the period and the reason of external events, and it makes an analyst difficult to establish a time series model. Therefore, it is important that we analyze the styles and effects of intervention. In this paper, we considered the linear time series model with invention and compared with nonlinear time series models such as ARCH, GARCH model and also we compared with the combination prediction method that Tong(1990) introduced. In the practical case study, we compared prediction power with RMSE among linear, nonlinear time series model with intervention and combination prediction method.

• KIEAE Journal
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• v.13 no.2
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• pp.77-84
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• 2013

Schools are one of favorable public buildings for Renewable Energy(RE) systems due to site conditions and their energy demand profiles(e.g. daytime-based use of hot water and heating/cooling). Although the government encourages schools to be equipped with RE systems, the adoption of RE systems in existing energy supply systems faces technical and financial barriers. For example, when installing a RE-based combination system(RECS) to meet the energy demand at various school scales, identifying cost effective combination of capacities of the RECS is not trivial since it usually requires technically intensive work including detailed simulation and demand/supply analysis with extensive data. This kind of simulation-based approaches is hardly implementable in practice. To address this, a simpler and applicable decision-supporting method is suggested in this study. This paper presents a simplified model in support of decision-making for optimal capacities of RECS within given budget scales and schools sizes. The proposed model was derived from detailed simulation results and statistical data. Using this model, the optimal capacities of RECS can be induced from the number of classes in a school.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.11a
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• pp.189-190
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• 2005

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.219-226
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• 2018

Collaborative filtering has been most popular approach to recommend items in online recommender systems. However, collaborative filtering is known to suffer from data sparsity problem. As a simple way to overcome this problem in literature, Jaccard index has been adopted to combine with the existing similarity measures. We analyze performance of such combination in various data environments. We also find optimal weights of factors in the combination using a genetic algorithm to formulate a similarity measure. Furthermore, optimal weights are searched for each user independently, in order to reflect each user's different rating behavior. Performance of the resulting personalized similarity measure is examined using two datasets with different data characteristics. It presents overall superiority to previous measures in terms of recommendation and prediction qualities regardless of the characteristics of the data environment.

• Science of Emotion and Sensibility
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• v.13 no.2
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• pp.301-308
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• 2010

The sensibility effects of color combinations was studied utilizing tone on tone combination and tone in tone combination. A total of 24 color combinations were rated by 10 college students using Semantic Differential Method. The data was analyzed by using Excel statistics program 2004. Analysis method was factor analysis. Theresults of this study were as follow. Color combinations utilizing tone on tone and color combinations utilizing tone in tone was evaluated a very different impression. Thus these were found to have an influence on sensibility effects of color combinations. In comparison with appearance of color combination using colored paper and that of product to apply to color combination using colored paper, it was showed to be evaluated mostly similar impression. However By characteristic with product, shape, size and texture, appearance of color combination is likely to be evaluated very difference impression. The results of these studies will serve as a basis of color combination image or color design.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.221-229
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• 2021

This study aims to forecast the exchange rate of the Chinese Yuan against the US Dollar by a combination of different models as proposed by Poon and Granger (2003) during the Covid-19 pandemic. For this purpose, we include three uni-variate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Chinese Yuan against the US dollar by two combination criteria i.e. var-cor and equal weightage. After finding out the individual accuracy, the models are then assessed through equal weightage and var-cor methods. Our results suggest that Naïve outperforms all individual & combination of time series models. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models except the Naïve model, with the lowest MAPE value of 0764. The results suggesting that the Chinese Yuan exchange rate against the US Dollar is dependent upon the recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting which commensurate with the literature.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.4
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• pp.563-574
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• 2002

Purpose : This study was designed to compare importance of the types of leadership-followership combination in the nursing organization. Method : The subjects of this study were nurses working in the hospital. They were recruited 490 from three medical centers. Data were collected by using self-reported questionnaires from April 8th to 18th, 2002. Result : The results were as follows; 1) It appeared that the most important type of leadership-followership combination for job satisfaction in the nursing organization was the transformational leadership-effective follower, however the most important type of leadership-followership combination for organizational commitment was the transformational leadership-the conformist. 2) According to analysis of partial correlational coefficient to compare the importance of variables, the leadership-followership combination type was the more important than other variables: education, age, duration of job, religion, marriage. Conclusion : With these findings, it was found that the most proper type of leadership-followership combination in nursing organization was the transformational leadership-effective follower for job satisfaction and the transformational leadership-the conformist for organizational commitment. So these results will be used to develop a more effective staffing management strategies to improve the effectiveness of nursing organization.

• The Research Journal of the Costume Culture
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• v.22 no.3
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• pp.399-410
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• 2014

The purpose of this study was to investigate emotional images and preference of knitwear by tone on tone combination. The subjects were 357 university students in Daejeon and Chungnam province, and the measuring instruments were 6 stimuli manipulated by color and tone combination type of background and pattern in the tone and tone combination, and self-administrated questionnaires consisted of emotional images items, preference items, and subjects' demographics attributions. The data were analyzed by Cronbach's ${\alpha}$, factor analysis, t-test, MANOVA and Duncan's multiple range test, using SPSS program. The results were as follows. First, four factors (attractiveness, conspicuity, mildness, and activity) are emerged on emotional images of knitwear. Second, color had main effects on emotional images and preference. Gray color was perceived as most attractive image and more preferred than others. Third, tone combination type had some effects on emotional images. Vivid tone background/light tone pattern was perceived more attractive image but less conspicuous and mild than light tone background/vivid tone pattern. Forth, subjects' gender had an effects on conspicuous image. Male was perceived more conspicuous image on knitwear stimuli than female. Fifth, color and subjects' gender had interaction effects on attractiveness image and preference. Male perceived that blue is more attractive and preferred than female.