• Journal of the Korean Geotechnical Society
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• v.39 no.2
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• pp.31-42
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• 2023

A study was conducted to use soil color obtained from digital im ages as an indicator of soil water content. Digital images of Jumoonjin standard sand with five different water contents were captured under nine different lighting conditions. Through digital image processing, the soil color of the sample was obtained based on the CIELAB color system, and the effect of lighting conditions and water content on the soil color was analyzed. The results indicated that L^* showed a high correlation with illuminance, whereas a^* and b^* showed a high correlation with color temperature. As the water content increased, L^*, which represents the brightness of the soil color, decreased, and a^* and b^* increased. Therefore, the soil color changed from green and blue to red and yellow. Based on the regression analysis results of lighting conditions, water content, and soil color, a water content predicting method based on the soil color of silica-based sand photographed under irregular light conditions was proposed. The proposed method can predict the water content with a m axim um error of 0.29%.

• ETRI Journal
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• v.27 no.5
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• pp.595-607
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• 2005

The widespread use of the Internet has led to the problem of intellectual property and copyright infringement. Digital rights management (DRM) technologies have been developed to protect digital content items. Digital content can be classified into static content (for example, text or media files) and dynamic content (for example, VOD or multicast streams). This paper deals with the protection of a multicast stream on set-top boxes connected to an IP network. In this paper, we examine the following design and architectural issues to be considered when applying DRM functions to multicast streaming service environments: transparent streaming service and large-scale user environments. To address the transparency issue, we introduce a 'selective encryption scheme'. To address the second issue, a 'key packet insertion scheme' and 'hierarchical key management scheme' are introduced. Based on the above design and architecture, we developed a prototype of a multicasting DRM system. The analysis of our implementation shows that it supports transparent and scalable DRM multicasting service in a large-scale user environment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.129-141
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• 2010

In network service environment, cultures from diversified fields are easily accessible thanks to the convenient digital content services. Unfortunately, unauthorized access and indiscreet misuse behaviors have deprived content owners of their copyrights. This study suggests an integrity-ensured model applicable for forensic evidence of digital content infringement in network service environment. The suggested model is based on MPEG-21 core components for digital content protection and the system is designed in connection with the components of digital content forensics. Also, the present study suggests an efficient technology to protect and manage computer forensic evidence and digital content by authorizing digital content use and catching infringing logs of authorized users without lag in network environment for the benefit of network security and reliability.

• Journal of Information Technology Services
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• v.9 no.4
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• pp.37-55
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• 2010

Digital content piracy has been shown to be an emerging societal problem, However, Studies on digital content piracy are very limited. In this paper, we try to find whether Theory of Planned Behavior(TPB) can explain the online digital content piracy in China. In addition to the finding of TPB's usefulness, We also examine the cross-cultural differences between Korea and China in behavior towards online digital content piracy. we argue that cultural factors moderate the strength of the relationships in the TPB model in online digital content piracy. we use a theoretical model of behavior based on the framework of the TPB( Theory of Planned Behavior) and Hofstede's national cultural dimensions. Our results indicate that the general TPB(Theory of Planned Behavior) model of software piracy is broadly applicable to digital content piracy in China. Our findings also show that most of the hypothesized moderating effects of national cultural factors were found to be significant.

• Asia Marketing Journal
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• v.25 no.4
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• pp.173-193
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• 2024

This study adopts organismic integration theory (OIT) to classify and contrast the predominant roles of five motivations (i.e., economic incentives, self-presentation, information acquisition, altruism, and enjoyment) in fostering three levels of behavioral engagement on brand-related social media content. This study further examines the moderating effect of personality (thinkers vs. feelers) on these relationships. The results of PLS-SEM reveal the greater impact of autonomous motivations on content consumption (enjoyment and information acquisition) and content contribution and creation (altruism and information acquisition), compared with controlled motivations (self-presentation and economic incentives). This study also finds that thinkers mostly engage on brand-related content for information acquisition and economic incentives, whereas feelers are mostly driven by enjoyment for content consumption and by altruism for content contribution and creation. This study addresses the inconsistency in prior research findings and provides practical implications to social media marketers.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.6
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• pp.253-260
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• 2015

When we buy items in online stores, it is common to face recommended items that meet our interest. These recommendation system help users not only to find out related items, but also find new things that may interest users. Recommendation system has been widely studied and various models has been suggested such as, collaborative filtering and content-based filtering. Though collaborative filtering shows good performance for predicting users preference, there are some conditions where collaborative filtering cannot be applied. Sparsity in user data causes problems in comparing users. Systems which are newly starting or companies having small number of users are also hard to apply collaborative filtering. Content-based filtering should be used to support this conditions, but content-based filtering has some drawbacks and weakness which are tendency of recommending similar items, and keeping history of a user makes recommendation simple and not able to follow up users preference changes. To overcome this drawbacks and limitations, we suggest weighted window assisted user history based recommendation system, which captures user's purchase patterns and applies them to window weight adjustment. The system is capable of following current preference of a user, removing useless recommendation and suggesting items which cannot be simply found by users. To examine the performance under user and data sparsity environment, we applied data from start-up trading company. Through the experiments, we evaluate the operation of the proposed recommendation system.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.39-48
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• 2009

This study reviews the limit of image search by considering on the image search methods related to content-based image retrieval and suggests a user interface for more efficient content-based image retrieval and the ways to utilize image properties. For now, most studies on image search are being performed focusing on content-based image retrieval; they try to search based on the image's colors, texture, shapes, and the overall form of the image. However, the results are not satisfactory because there are various technological limits. Accordingly, this study suggests a new retrieval system which adapts content-based image retrieval and the conventional keyword search method. This is about a way to attribute properties to images using texts and a fast way to search images by expressing the attribute of images as keywords and utilizing them to search images. Also, the study focuses on a simulation for a user interface to make query language on the Internet and a search for clothes in an online shopping mall as an application of the retrieval system based on image attribute. This study will contribute to adding a new purchase pattern in online shopping malls and to the development of the area of similar image search.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.42-45
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• 2002

A novel characteristic value extraction method based on morphological spatial frequency is proposed. Morphological spatial frequency defined by morphological pattern distribution function is introduced. Superiority of the method was proved for various images by experiment. Furthermore the fact that the proposed method does not need threshold to obtain binary image provides its applicability to content-based image retrieval.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.541-544
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• 2003

This paper proposes a new color feature and a corresponding distance measure for content-based retrieval of design images such as trade marks, pattens, logos, textile images, and icons. Simulation results with textile images show that the proposed method outperforms the traditional color-based retrieval methods which was originally proposed fer content-based retrieval of natural images.