• Journal of Digital Contents Society
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• v.18 no.1
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• pp.71-77
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• 2017

Virtual advertisement is an advertising technique that using computer graphic in a media production such as a sports image for inserting product image, logo, advertising slogan, etc. Recently, the image insertion of virtual advertisement is actively spreading due to the satisfaction of technical element for the image insertion of virtual advertisement in sports advertisement by increasing of the image processing technology and the computing performance. In addition, image processing technology for automatic insertion has become an important research field in the virtual advertisement field. In this paper, we propose the method of extracting less-informative region by using image processing technique and machine learning to insert a virtual advertisement automatically in sports image. The proposed method analyzes the brightness level of image through the histogram and extracts the less-informative region using the machine learning method.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.38-42
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• 2007

Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of functional information from a large corpus of gene expression data is still a time-consuming task. In this paper, we propose an efficient method for identifying functional categories of differentially expressed genes from a micro-array experiment by using Gene Ontology (GO). Our method is as follows: (1) The expression data set is first filtered to include only genes with mean expression values that differ by at least 3-fold between the two groups. (2) The genes are then ranked based on the t-statistics. The 100 most highly ranked genes are selected as informative genes. (3) The t-value of each informative gene is imposed as a score on the associated GO terms. High-scoring GO terms are then listed with their associated genes and represent the functional category information of the micro-array experiment. A system called HMDA (Hallym Micro-array Data analysis) is implemented on publicly available micro-array data sets and validated. Our results were also compared with the original analysis.

• Korean Institute of Interior Design Journal
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• v.25 no.1
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• pp.172-180
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• 2016

This study aimed to evaluate how universal design principles are embodied in the Public Service Center. It will be used for planning the basic materials of the interior environmental design for Public Service Center facilities and for developing ways to improve interior environments in order for them to be conveniently used. In studying a method, we conducted an Universal Design check list to evaluate interior environment, targeting five Public Service Center facilities located in Gwangju Metropolitan city. This study investigated the Universal Design suitability of center interior Public Service Center on the basis of the tools for Universal Design check list which was composed of supportive design, adaptable design, communicability, safety-oriented design, and accessible design. Through theoretically considering the services of Gwangju's old city hall public service center, which got divided into common space, public service space, waiting space and informative material space. Evaluation on universal design application level showed that those with best universal design application are supportiveness and safety in public service space, communication efficacy and safety in waiting space and safety and accessibility in informative material space and acceptability in waiting space had the lowest application level.

• The Journal of Industrial Distribution & Business
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• v.10 no.8
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• pp.7-15
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• 2019

Purpose - This study aims to examine the influence of social network service (SNS) on the brand image of infant food products; highlight the effects of brand image on the purchasing and word-of-mouth intention; and explore the effects of the purchasing intention on the word-of-mouth intention. Research design, data, and methodology - Based on previous studies, it was found that the fundamental SNS characteristics for infant food products are reliability, interactivity, and informative. Using AMOS 22.0 and structural equation modeling (SEM), 288 questionnaires were surveyed as a statistical method for examining the proposed hypotheses. Results - The analysis shows that reliability and informative have significant impacts on brand image, whereas interactivity does not. Again, the effect of brand image of infant food products on the purchase and word-of-mouth intention is statistically significant. However, the results differ across the "working housewife" and the "full-time housewife" groups. The connection between reliability and brand image was found to be statistically significant in this study. Conclusions - This study analyzes the effects of SNS characteristics on the brand image of infant food products and the effect of the brand image on purchase and word-of-mouth intentions, and provides practical implications for the same.

• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.4
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• pp.559-566
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• 2016

Purpose: This study aimed to examine the communication styles and nursing service satisfaction of clinical research nurses perceived by clinical subjects. Methods: The data were collected with self-administrated questionnaires after receiving consents from 200 clinical trial subjects. The data were analysed with descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients and stepwise multiple regression analysis using SPSS 21.0 statistic program. Result: Clinical subjects perceived that clinical research nurses used the informative, affective, and non-authoritative communication styles. The study identified factors influencing the nursing service satisfaction, and they were the informative communication styles (${\beta}$=.34, p<.001) and affective communication styles (${\beta}$=.35, p<.001, $R^2$=37%) by multiple linear regression. Conclusion: If educational programs on communication are developed to help clinical research nurses use the informative and affective communication styles according to the characteristics of subjects and applied to the field of practice, they will be able to increase the nursing service satisfaction and contribute to the higher quality of clinical trials.

• Fashion & Textile Research Journal
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• v.9 no.2
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• pp.229-236
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• 2007

Many researchers have focused on consumers' clothes purchase behavior, These researches could not reflect the characteristics of the single consumers' clothes purchase behavior. In addition, little has been written on the single consumer. The purposes of this study are to identify the concept and psychologic characteristics of single consumer and investigate the effects of single consumers' psychologic characteristic and susceptibility to interpersonal influence on clothes shopping pursuing value. Also, It was analyzed how single consumer' pursuing values are different based on the type of single motivation. To test research problems, Data were collected by means of a survey questionnaire, which was sent to 300 single in Pusan and Ulsan. In total, 274 were returned and 14 were unusable because of unacceptable levels of missing data. The Results were summarized as follows: First, self-efficacy, informative and normative influence were positively related to utilitarian pursuing value employee satisfaction. Also, self-efficacy, variety seeking, innovativeness and informative influence had a positive effect on hedonic pursuing value. Second, voluntary single and nonvoluntary single group had different perceptions about self-efficacy, variety seeking, innovativeness, informative influence, and hedonic pursuing value.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.8
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• pp.918-932
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• 2011

This research examines shopping motives, information search of e-fashion consumers and their behavioral intentions (word of mouth, repurchase and site switching intentions). The survey was conducted from December $17^{th}$ 2010 to January $5^{th}$ 2011 and all respondents had previous experiences with on-line purchase of fashion items. The study finds that an information search has three dimensions, recreational search, informative search, and rational search. The effects of both hedonic and utilitarian shopping motives on information search and behavioral intentions are significant. In addition, recreational and informative search have a positive impact on word of mouth and site switching intentions, while repurchase intention is influenced by an informative search. Rational search has a positive effect on switching intention only. Finally, there are significant differences by gender in shopping motives, information search and behavioral intentions.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.707-711
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• 2007

Microarray gene expression data is believed to show the functions of living organism through the gene expression values. We have studied a method to get the informative genes from the microarray gene expression data. There are several ways for this. In recent researches to get more sophisticated and detailed results, it has used the intelligence information theory like fuzzy theory. Some methods are to add fudge factors to the significance test for more refined results. In this paper, we suggest a method to get informative genes from microarray gene expression data. We combined the difference of means between two groups and the fuzzy membership degree which reflects the variance of the gene expression data. We have called our significance test the Fuzzy Information method for Gene Expression data(FIGER). The FIGER calculates FIGER variation ratio and FIGER membership degree to show how strongly each object belongs to the each group and then it results in the significance degree of each gene. The FIGER is focused on the variation and distribution of the data set to adjust the significance level. Out simulation shows that the FIGER-test is an effective and useful significance test.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.439-448
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• 1996

Extraction and selection of the informative features play a central role in pattern recognition. This paper describes a modified back-propagation algorithm that performs selection of the informative features and trains a neural network simultaneously. The algorithm is mainly composed of three repetitive steps : training, connection pruning, and input unit elimination. Afer initial training, the connections that have small magnitude are first pruned. Any unit that has a small number of connections to the hidden units is deleted,which is equivalent to excluding the feature corresponding to that unit.If the error increases,the network is retraned,again followed by connection pruning and input unit elimination.As a result,the algorithm selects the most im-portant features in the measurement space without a transformation to another space.Also,the selected features are the most-informative ones for the classification,because feature selection is tightly coupled with the classifi-cation performance.This algorithm helps avoid measurement of redundant or less informative features,which may be expensive.Furthermore,the final network does not include redundant parameters,i.e.,weights and biases,that may cause degradation of classification performance.In applications,the algorithm preserves the most informative features and significantly reduces the dimension of the feature vectors whiout performance degradation.

• The Pure and Applied Mathematics
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• v.9 no.1
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• pp.81-90
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• 2002

The least informative (favorable) distributions, minimizing Fisher information for a multivariate location parameter, are derived in the parametric class of the exponential-power spherically symmetric distributions under the following characterizing restrictions; (i) a bounded variance, (ii) a bounded value of a density at the center of symmetry, and (iii) the intersection of these restrictions. In the first two cases, (i) and (ii) respectively, the least informative distributions are the Gaussian and Laplace, respectively. In the latter case (iii) the optimal solution has three branches, with relatively small variances it is the Gaussian, them with intermediate variances. The corresponding robust minimax M-estimators of location are given by the $L_2$-norm, the $L_1$-norm and the $L_{p}$ -norm methods. The properties of the proposed estimators and their adaptive versions ar studied in asymptotics and on finite samples by Monte Carlo.