• Journal of the Korean Society of Costume
• /
• v.62 no.1
• /
• pp.1-13
• /
• 2012

This study is aimed at finding out the self-perception and value of clothing they wear to today's businessmen who work in a fast-growing global network society and for developing a suitable image consulting program for businessmen. The purpose of this study is to categorize businessmen into personality types, and then analyzing purchase behaviors for clothing and image perception, self-image satisfaction among categorized groups. The participants of this study are 320 businessmen who are from 20's to 50's and working in Seoul. A total of 302 questionnaires were used for the survey of this study. The questionnaire is composed of 3 different parts as follows: 1) personality types, 2) purchase behaviors for clothing and image perception, 3) self-image satisfaction. The methods of this study are frequency analysis, descriptive analysis, factor analysis, variance analysis, cluster analysis, t-test and reliability analysis. In conclusion, an image consulting education program for businessmen has to be based on one's own personality type, current fashion style and image perception. Each person has to be provided a unique direction to increase his self satisfaction, which will result in improvements in both personal image satisfaction and social satisfaction. These changes will ultimately become the driving force of career life.

• Journal of Digital Convergence
• /
• v.19 no.12
• /
• pp.397-404
• /
• 2021

Product image location in search engine advertising plays an important role in consumer perception when the product is relatively low involved and has functional value. The purpose of this research is to investigate the interaction effects of product image location and product type on advertising effectiveness. Building on the literature of location effects, we show that for products for which heaviness is considered a positive attribute, product image placed on the right are preferred. To test hypotheses, a 2(product image location: left vs. right) × 2(product type: single vs. bundle) experiment is conducted and a total of 144 paricipants took part in the experiment. The results revealed that respondents show higher brand attitude and purchse intention toward a bundle product's advertising with product image place on the right. The results provide implications and suggestions for improving search engine advertising and marketing strategies.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 1997.11a
• /
• pp.321-339
• /
• 1997

인터넷의 활용과 컴퓨터 기술환경의 새로운 패러다임 변화는 디지털도서관의 등장을 가져오게 하였으며, 동시에 이미 온라인 서비스를 실시해오던 여러 분야의 정보센터들로 하여금 어떠한 유형의 데이터도 저장, 관리, 제공하며 정보라는 상품을 생산해 내는 정보시장(Information Marketplace)의 역할 자로서 요구하고 있다. 본 논문에서는 1980년대부터 진행되어온 도서관 서지자료의 Database화 작업과 병행하여 도서관 이용자에게 보다 광범위하고 효용성 있는 정보를 제공하기 위한 디지털도서관의 이론적 배경에 대하여 기술하고, 디지털도서관의 주요 소장정보인 원문이미지정보의 처리기술에 대한 이론을 정리하며, 현재국내에서 추진중인 원문이미지정보시스템의 분석을 통하여 향후 디지털도서관 구축시 비교분석 모델을 제시해보고자 한다.

• Journal of the Korean School Mathematics Society
• /
• v.23 no.1
• /
• pp.129-158
• /
• 2020

In this study, we presented two geometric tasks to three 11th grade students to identify the characteristics of the images that the students had at the beginning of problem-solving in the problem situations and investigated how their images changed during problem-solving and effected their problem-solving behaviors. In the first task, student A had a static image (type 1) at the beginning of his problem-solving process, but later developed into a dynamic image of type 3 and recognized the invariant relationship between the quantities in the problem situation. Student B and student C were observed as type 3 students throughout their problem-solving process. No differences were found in student B's and student C's images of the problem context in the first task, but apparent differences appeared in the second task. In the second task, both student B and student C demonstrated a dynamic image of the problem context. However, student B did not recognize the invariant relationship between the related quantities. In contrast, student C constructed a robust quantitative structure, which seemed to support him to perceive the invariant relationship. The results of this study also show that the success of solving the task 1 was determined by whether the students had reached the level of theoretical generalization with a dynamic image of the related quantities in the problem situation. In the case of task 2, the level of covariational reasoning with the two varying quantities in the problem situation was brought forth differences between the two students.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.06b
• /
• pp.346-348
• /
• 2006

기존의 웹 이미지 검색 시스템들은 웹 페이지에 포함된 텍스트들의 출현빈도, 태그유형 등을 고려해 각 키워드들의 중요도를 평가하고 이를 이용해 이미지의 캡션을 결정한다. 하지만 텍스트 정보만으로 캡션을 결정할 경우, 키워드와 이미지 사이의 관련성을 평가할 수 없어 부적절한 캡션의 배제가 어렵고, 사람의 인지와 맞지 않는 캡션이 추출되는 문제점이 있다. 본 논문에서는 기존의 웹 이미지 마이닝 방법을 통해 웹 페이지로부터 캡션 후보 키워드를 추출하고, 자동 이미지 주석 방법을 통해 이미지의 개념 부류 키워드를 결정한 후, 두 종류의 키워드를 결할하여 캡션을 선택한다. 가능한 결합 방법으로는 키워드 병합 방법, 공통 키워드 추출 방법, 개념 부류 필터링 방범 캡션 후보 필터링 방법 등이 있다. 실험에 의하면 키워드 병합 방법은 높은 재현율을 가져 이미지에 대한 다양한 주석이 가능하고 공통 키워드 추출 방법과 개넘 부류 키워드 필터링 방법은 정확률이 높아 이미지에 대한 정확한 기술이 가능하다. 특히, 캡션 후보 키워드 필터링 방법은 기존의 방법에 비해 우수한 재현율과 정확률을 가지므로 기존의 방법에 비해 적은 개수의 캡션으로도 이미지를 정확하게 기술할 수 있으며 일반적인 웹 이미지 검색 시스템에 적용할 경우 효과적인 방법이다.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.191-203
• /
• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.

• Journal of IKEEE
• /
• v.23 no.4
• /
• pp.1302-1308
• /
• 2019

This paper presents an approach for classifying image made by acquired position data from a 2D Lidar sensor with a convolutional neural network (CNN). Lidar sensor has been widely used for unmanned devices owing to advantages in term of data accuracy, robustness against geometry distortion and light variations. A CNN algorithm consists of one or more convolutional and pooling layers and has shown a satisfactory performance for image classification. In this paper, different types of CNN architectures based on training methods, Gradient Descent(GD) and Levenberg-arquardt(LM), are implemented. The LM method has two types based on the frequency of approximating Hessian matrix, one of the factors to update training parameters. Simulation results of the LM algorithms show better classification performance of the image data than that of the GD algorithm. In addition, the LM algorithm with more frequent Hessian matrix approximation shows a smaller error than the other type of LM algorithm.

• Proceedings of KHEA Conference
• /
• 2005.04a
• /
• pp.86-86
• /
• 2005

• Journal of the Korean Society of Clothing and Textiles
• /
• v.34 no.5
• /
• pp.784-796
• /
• 2010

Consumers focus on information about the symbolic meaning of a product for highly involved and emotional products (such as cosmetic products). This study examines the effectiveness of the congruence between cosmetics advertising image and self-image on consumer attitudes. In addition, this study examines two additional moderating effects, which are 'product type' and 'message type'. For the experiment, four advertizing type factorial designs were performed. A total of 320 undergraduate female students in Korea participated in the experiment. This study captured the subjective judgments of consumers on these three comparisons in terms of advertizing attitude, brand attitude, and purchase intention. The results are as follows: First, the greater the self-congruity on cosmetic advertising, then the greater the effectiveness on advertizing attitude. Second, the increased self-congruity on cosmetic advertising did not create greater effectiveness on brand attitude. Third, increased advertizing attitudes on the congruence between cosmetics advertising image and self-image increased the effectiveness on brand attitude. Fourth, increased advertizing attitudes on the congruence between cosmetics advertising image and self-image improved the effectiveness on purchase intention. Fifth, the greater the brand attitude (on the congruence between the cosmetics advertising image and the self-image produced)increased the effectiveness for purchase intention. The results show a significant moderating role of the product type. Marketers can use the results of this study to understand the market of cosmetic products for promotion.

• Journal of Digital Contents Society
• /
• v.15 no.1
• /
• pp.61-68
• /
• 2014

In the past, to stimulate customers' rationality were used as a marketing methods but the storytelling marketing is appealing to consumers by showing product or brand value. Storytelling marketing attracts clients favorable attitude. In this research, I tried to figure out how emotional storytelling and humor advertising affects to brand attitude a quality of products according to advertising types, brand image, trust, interest, message, advertising model, intension of purchase and recommendation requisite to impact on brand attitude. As a result emotional storytelling was more effective than the humor advertising method when forming the brand attitude and brand image. Also, among the types of advertisement, emotional storytelling tended to bring a significant difference between men and women. Emotional storytelling advertisement are increasing and being competitive. Therefore, we need notable advertisement. It is a significant research to understand how advertising type affects to consumers.