• Journal of Distribution Research
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• v.6 no.1
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• pp.77-101
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• 2001

Recently, the role of Internet becomes wide so that it could provide the information among users as well as the opportunity to make commercial transactions in the cyberspace. Now, the virtual storefronts are the virtual space where anyone makes a profit on Internet by selling and buying goods/services. Therefore, it is important to develop the good image for cyberconsumers so that virtual storefronts can attract many browser to buy goods. The study reported examines how combination of specific elements in the internet environment influence cyberconsumers' inferences about the virtual storefront and discusses the extent to which these inferences mediate the virtual storefront loyalty. Results show that the virtual storefront elements were posited to be antecedents of virtual storefront image rather than components of virtual storefront image. In addition, the virtual storefront image mediators the satisfaction and loyalty of cyberconsumer on virtual storefront.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.141-146
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• 2002

Chlorophyll-a concentration maps of Yongdam reservoir in September and October, 2001 were produced using Landsat ETM imagery and the in-situ water quality measurement data. In-situ water samples were collected on 16th September and 18th October during the satellite overpass. The correlations between the DN values of the imagery and the values of chlorophyll-a concentration were analyzed. The visible bands(band 1, 2, 3) and the near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed correlation coefficient values of about 0.7 due to the low variations of chlorophyll-a concentration. Regression models between the DN values of the Landsat ETM image and the chlorophyll-a concentration have been developed for each image. The developed regression models were then applied to each image, and finally the chlorophyll-a distribution maps of Yongdam reservoir were produced. The produced maps showed the spatial distribution of the chlorophyll-a in Yongdam reservoir in a synoptic way so that the tropic state could be easily monitored and analysed in the spatial domain.

• Journal of Magnetics
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• v.18 no.3
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• pp.311-316
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• 2013

Digital image processing has increasingly been implemented in nanostructural analysis and would be an ideal tool to characterize the morphology and position of self-assembled magnetic nanoparticles for high density recording. In this work, magnetic nanoparticles were synthesized by the modified polyol process using $Fe(acac)_3$ and $Pt(acac)_2$ as starting materials. Transmission electron microscope (TEM) images of as-synthesized products were inspected using an image processing procedure. Grayscale images ($800{\times}800$ pixels, 72 dot per inch) were converted to binary images by using Otsu's thresholding. Each particle was then detected by using the closing algorithm with disk structuring elements of 2 pixels, the Canny edge detection, and edge linking algorithm. Their centroid, diameter and area were subsequently evaluated. The degree of polydispersity of magnetic nanoparticles can then be compared using the size distribution from this image processing procedure.

• Current Optics and Photonics
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• v.5 no.4
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• pp.421-430
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• 2021

The multifocal multiphoton microscopy (MMM) enables high-speed imaging by the concurrent scanning and detection of multiple foci generated by lenslet array or diffractive optical element. The MMM system mainly suffers from crosstalk generated by scattered emission photons that form ghost images among adjacent channels. The ghost image which is a duplicate of the image acquired in sub-images significantly degrades overall image quality. To eliminate the ghost image, the photon reassignment method was established using maximum likelihood estimation. However, this post-processing method generally takes a longer time than image acquisition. In this regard, we propose a novel strategy for rapid noise reduction in the MMM system based upon Monte-Carlo (MC) simulation. Ballistic signal, scattering signal, and scattering noise of each channel are quantified in terms of photon distribution launched in tissue model based on MC simulation. From the analysis of photon distribution, we successfully eliminated the ghost images in the MMM sub-images. If the priori MC simulation under a certain optical condition is established at once, our simple, but robust post-processing technique will continuously provide the noise-reduced images, while significantly reducing the computational cost.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.49-59
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• 2019

Generative adversarial networks(GANs) have received great attention in the machine learning field for their capacity to model high-dimensional and complex data distribution implicitly and generate new data samples from the model distribution. This paper investigates the model training methodology, architecture, and various applications of generative adversarial networks. Experimental evaluation is also conducted for generating synthetic image dataset for defense using two types of GANs. The first one is for military image generation utilizing the deep convolutional generative adversarial networks(DCGAN). The other is for visible-to-infrared image translation utilizing the cycle-consistent generative adversarial networks(CycleGAN). Each model can yield a great diversity of high-fidelity synthetic images compared to training ones. This result opens up the possibility of using inexpensive synthetic images for training neural networks while avoiding the enormous expense of collecting large amounts of hand-annotated real dataset.

• Journal of Distribution Science
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• v.22 no.9
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• pp.97-106
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• 2024

Purpose: In view of increased social awareness of today's consumers, it is very important to understand how retail customers perceive their sense of social responsibility. This study aims to explore the decision processes of university students that affect the patronage of social enterprises in retail sector. Research design, data and methodology: This study proposes and tests whether and how social network traits, firm's image, and perceived trustworthiness serve as predictors of value co-creation behavior specific to two different industries (social enterprises and regular firms) operating in retail sector of South Korea. This study incorporated theoretical premise of value co-creation to verify the structural relationships among the predictors of value co-creation. Results: The result demonstrates that social network and firm's image both significantly influence consumers' value co-creation behavior. The study further found that the firm's image is overall more effective for eliciting consumers' value co-creation behavior than social network traits. Conclusions: As the result of comparing the industry type (social enterprises vs. regular firms), the study confirmed a meaningful difference such that consumers indicated greater impact of firm's image on value co-creation for social enterprises than for regular firms. The findings are expected to provide useful industrial insights for the management of social enterprises.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.4
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• pp.503-514
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• 1998

The purpose of this study was to develop a large representative data base for jeans marketing strategy This study was to survey brand features(launching year, launching company, design concept, sales volume, and price zone) in the current market, and was to examine brand awareness and it's relationship to segmented distribution regions, demo- graphic variables(sex, age, monthly household income, and seasonal clothing expenditure). This study was also to analyze brand image and consumer's seeking image. The 660 questionnaires were distributed and 618 reliable ones were used for statistical analysis. A SAS statistical package including frequency table, Chi-square test, factor analysis, analysis of variance(ANOVA), Duncan's multiple range test and paired-t test was used. The results are as follows: 1. Brand awareness involves "brand recall" based on asking a person to name the brand recalled first, and "brand recognition" based on asking to identify brand name from 30 given brands. The result of recall brand test indicated that Levi's was dominant brand. People recognized about 70.8% of brands on the average. Brand recognition was influenced by segmented distribution region and demographic variables. 2. There was significantly positive relationship between brand recognition and purchasing behavior. 3. National brands were more recognized than Licensed brands. 4. The result showed that "Nix" was best represented for sophisticated brand image, "Strom" for characteristic, "Jambangee" for resonable price, and "Levi's" for classic '||'&'||' comfortable brand image. 5. As a result of factor analysis on consumer's seeking image, six factors(characteristic, young, intelligent/sexy, comfortable, exotic and popular) were found. Several factors had a relationship with preferred design, demographic variables, fashion interest, and brand recognition. variables, fashion interest, and brand recognition.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.173-182
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• 1998

As a result of remarkable developments in multimedia technology, the image database system that can efficiently retrieve image data becomes a core technology of information-oriented society. In this paper, we proposed the 2-phase Image Retrieval System considering both color and shape information as the method of image features extraction for content-based image data retrieval. At the first level, to get color information, with improving and extending the indexing method using color distribution characteristic suggested by Striker et al., i.e. the indexing method considering local color distribution characteristics, the system roughly classifies images through the improved method. At the second level, the system finally retrieves the most similar image from the image queried by the user using the shape information about the image groups classified at the first level. To extract the shape information, we use the Improved Moment Invariants (IMI) that manipulates only the pixels on the edges of objects in order to overcome two main problems of the existing Moment Invariant methods large amount of processing and rotation sensitiveness which can frequently be seen in the Directive Histogram Intersection technique suggested by Jain et al. Experiments have been conducted on 300 automobile images. And we could obtain the more improved results through the comparative test with other methods.

• Fashion & Textile Research Journal
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• v.6 no.5
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• pp.575-584
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• 2004

The purpose of this study was to investigate the differences in recognition of brand and advertisement image according to the advertisement expression forms of domestic make-up cosmetics. This study was conducted by means of a questionnaire survey of female which age from twenties to the thirties. The statistics used for data analysis were frequency distribution, Percentage, mean, factor analysis, and paired t-test by the SPSS program. The results of this study were as follows. The brand and advertisement image of domestic Make-up cosmetics were classified into seven factors. : Of good quality, high-toned, modern, chic, unique, familiar, stimulative brand and advertisement image. The brand image and advertisement image recognition didn't correspond in general except HERCYNA and ETUDE.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.2
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• pp.243-251
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• 2004

This study was interested in examining the image of a co-brand with the case of＇CHIMERIC＇, the co-brand of Daegu city in Korea. The purpose of the study was to investigate the difference in brand image by brand knowledge and the effects of brand image on brand preference, brand purchase, and brand satisfaction. A total of 354 questionnaires collected from the region(Daegu)＇s residents, who were aware of CHIMERIC, were analyzed. Factor analysis extracted 6 factors of brand image including symbolic image, product, ad, price, distribution, and publicity. The results revealed that there were differences in product and publicity images by brand knowledge. Symbolic and publicity images and brand knowledge affected brand preference, which in turn had the strongest effect on brand purchase. Brand knowledge also affected brand purchase while no direct effect of brand image was observed. Brand satisfaction was affected by brand preference, publicity, and ad image.