• 한국의류산업학회지
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• 제10권4호
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• pp.526-536
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• 2008

This study is to analyze and examine the relations of lifestyle, fashion behavior, and make-up behavior of post digital generation and to provide the basic data which help to establish and perform the distinctive marketing strategies targeting the post digital generation. Subjects were 1,460 male and female undergraduates who attend colleges or universities in Seoul, Busan, and Daegu. Average, standard deviation, MANOVA, and ANOVA were conducted using SPSS 12.0 statistic program. The results were as follows: The higher points the group got in all the subfactors regarding information seeking pursuit and sensation intention fascination pursuit, the higher points the group had in the subfactors of fashion behavior and make-up behavior. The group with higher fashionenjoyment pursuit appeared to seek after more brand price choice behavior, internet shopping purchasing behavior, fashion information source seeking behavior, and impulse buying behavior in the subfactors of fashion behavior as well as more self-satisfaction appearance orientation and fashion information buying orientation in the subfactors of make-up behavior. With the group in pursuit of more multi activities, not only were brand price choice behavior and fashion information source seeking behavior in the subfactors of fashion behavior sought after more, but self-satisfaction appearance orientation and fashion information buying orientation in the subfactors of make-up behavior were pursued more as well. The more interpersonal relations the group had, the more self-satisfaction appearance orientation and fashion information buying orientation in the subfactors of make-up behavior as well as the more brand price choice behavior, fashion information source seeking behavior, impulse buying behavior, other-regarding behavior and independent buying behavior in the subfactors of fashion behavior the group had.

• 복식문화연구
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• 제21권5호
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• pp.671-683
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• 2013

The purpose of this study was to identify middle-school boys' purchase behavior according to their shoes shopping orientation. A self-administered questionnaire was used to collect from 314 subjects. Factor analysis, Chi-square test, and one-way ANOVA were done using SPSS PC (Ver. 18.0). Most middle-school boys selected shoes that were 255~270mm, possessed on to two pairs of school shoes, searched for information for about five days before purchase, had spent 50,000~150,000 won on one to two pairs of shoes during the previous six months, saw design, comfort, and brand as their selection criteria, chose their shoes by themselves, shoes specialty stores, had favorite brands, preferred athletic shoes made of achromatic canvas, and bought new shoes when their old ones wore out. Factors of shoe shopping orientation were fashion and brand, economy, conformity, and comfort, and students were grouped into an active shopping group, an underdeveloped shopping orientation group, and a value pursuit group. The active shopping group bought more shoes, spent more on shoes, selected their shoes themselves, patronized discount shoe stores or specialty stores, and preferred national brand shoes. The underdeveloped shopping orientation group accepted their friends' opinions when selecting shoes and bought cheaper shoes. The value pursuit group accepted their parents' opinions when selecting shoes, patronized internet shopping malls or traditional markets, and selected cheaper shoes. The shoe shopping orientation of middle-school boys was immature, but they showed strong consumption needs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2075-2092
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• 2017

Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권6호
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• pp.2289-2301
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• 2015

Mobile devices are becoming powerful enough to realize augmented reality (AR) application. This paper introduces two AR methods to estimate an environmental illumination distribution of a scene. In the first method, we extract the lighting direction and intensity from input images captured with a front-side camera of a mobile device, using its orientation sensor. The second method extracts shadow regions cast by three dimensional (3D) AR marker of known shape and size. Because previous methods examine per pixel shadow intensity, their performances are much affected by the number of sampling points, positions, and threshold values. By using a simple binary operation between the previously clustered shadow regions and the threshold real shadow regions, we can compute efficiently their relative area proportions according to threshold values. This area-based method can overcome point sampling problem and threshold value selection. Experiment results demonstrate that the proposed methods generate natural image with multiple smooth shadows in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권5호
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• pp.1766-1784
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• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.309-317
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• 2015

Recently many companies began to realize their visions for the sustainable growth with the advent of CSV(Creating Shared Values). Michael E. Porter, a Harvard Professor, claims that placing social value creation at the core of business strategy has the potential to uncover big opportunities for individual companies and that shared value can play a significant role in increasing competitive advantages while fostering social prosperity. In consequence, the various researches have illustrated how to get the opportunity for competitive advantages from building a social value proposition into corporate strategy, and considerable studies have been promoted heavily from the managerial perspective. However, due to the lack of capability converging information technology with business strategy, any research effort to identify technological or Internet-related issues and to link the issues to CSV does not exist. With Korean being a Internet leading country, the demands of researches analyzing core technology, information, and service utilizing Internet are rapidly growing. The study aims to find out Internet-related enablers for CSV. This paper describes the concepts and features of CSV, identifies emerging Internet-related issues toward the opportunity for competitive advantage, and then depicts the rigorous research endeavors in the areas of Internet information, technology, and services. As a result, 11 papers presented and selected as the outstanding papers at APIC-IST 2014 handle the issues to be brought together, which include: Wireless and Sensor Network, Image Processing and HCI, Big Data and Business Intelligence, Security & Privacy in Internet, SNS & Communication, Smart-Learning and e-Learning, and Internet Business Strategy. The study finally recommends indispensible terms for substantially vitalizing CSV.

• 디지털융복합연구
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• 제13권8호
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• pp.483-493
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• 2015

농어촌 지역은 산업화 도시화로 도시보다 건강관리가 미흡하며 이에 따른 지역 간 건강불균형 문제가 중요한 사회적 아젠다가 되었다. 이 연구는 사회적 자본과 건강정보, 의료 커뮤니케이션 요인들이 지역사회의 건강상태에 어떠한 영향을 미치는지를 구조방정식 모델을 통해서 검증하고자 하였다. 먼저 사회적 자본은 의료진과의 의사소통성에 영향을 미치는 것으로 나타났고, 의료진과의 의사소통성은 건강상태에 영향을 미치는 것으로 나타났다. 또한 건강정보추구는 건강행위, 인터넷 건강정보이용에 영향을 미치는 것으로 확인되었으며, 인터넷 건강정보이용을 매개로 건강상태에 영향을 미치는 것으로 나타났다. 마지막으로 인터넷 건강정보이용과 건강행위는 건강상태에 영향을 미치는 것으로 확인되었다. 이 연구는 사회적 요인과 커뮤니케이션 요인이 농어촌 건강상태에 영향을 미치는 선행 경로구조를 형성하고 있다는 점을 검증함으로써 지역사회 건강상태의 결정요인에 대한 설명력을 한층 풍부하게 하는 데 기여하고 있다.

• 한국인터넷방송통신학회논문지
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• 제16권2호
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• pp.137-144
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• 2016

본 연구의 목적은 원격평생교육에서 학습자의 목표지향성, 교수실재감, 학습접근방식, 만족도 및 학업성취도 간의 구조적 관계를 규명하는 것이다. 이를 위해 A, B, C 대학교 부설 원격평생교육원 학습자 235명을 대상으로 온라인 설문조사를 실시하였다. 구조방정식 모델링 분석을 통한 연구 결과, 첫째, 숙달접근목표지향성과 교수실재감은 심층학습접근에 정적 영향을 미쳤으며, 둘째, 숙달접근목표지향성은 피상학습접근에 부적 영향을, 교수실재감에는 영향을 미치지 않는 것으로 확인되었다. 셋째, 심층학습접근은 만족도에 정적영향을 미쳤으며, 넷째, 피상학습접근은 만족도에 부적영향을 미쳤다. 다섯째, 심층학습접근은 학업성취도에 정적영향을 미쳤으며, 여섯째, 피상학습접근은 학업성취도에 부적영향을 미치는 것으로 확인되었다. 위와 같은 연구결과는 학습자의 숙달접근목표지향성과 교수실재감이 학습자들로 하여금 심층학습접근방식을 선택하게 하여 궁극적으로는 학업성취도와 만족도를 높여줌을 시사하였다.

• 한국의류학회지
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• 제32권11호
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• pp.1802-1813
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• 2008

As a very first step for theorizing shopping, this study attempted to diagnose the current of shopping research. Using the keyword of shopping from major academic databases in Korea, the study collected 560 research articles and analyzed patterns of: 1) research by year, journal, and academic area; 2) researchers by academic area; 3) keywords; and 4) research contents. Analyses showed that two thirds of articles in shopping were published after 2000. While the number of journals was the highest in business and engineering, the numbers of articles and researchers were the highest in business and apparel. The most frequently used included internet shopping mall, internet shopping, and shopping orientation. About 66% of shopping research was internet shopping related, and 80% was empirical study using individual consumers. Though shopping was studied as an individual consumer behavior, there were noticeable patterns in research contents by academic field. The study discussed such patterns and provided implications for multidisciplinary approaches for shopping theory and research.