• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.745-749
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• 2006

The appearance of wirelsss internet service made accessing easier than existing mobile devices. Due to the properity of mobile devices, we can easily obtain his/her profile information compared to a wired internet service. It enables to provide a personalized service through mobile devices. In this paper, we propose a recommendation service based on collaborative filtering method and a content push service. Using users' profile information, we recommand a target user's favoriate content. The recommanded contents are stored in mobile device through the push service. When we connect a wireless internet service, our mobile push service starts to cache from user's favorite contents. Especially, when we select a large mobile content, our system can reduce a download time by using our recommandation service. Also, in case of a connectionless, we can use a cached data from pushed content in our mobile device.

• Journal of Information Technology Services
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• v.13 no.1
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• pp.147-159
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• 2014

Recently, the quantity of information that is accessible from the Internet is being dramatically increased. Searching the Web for useful information has therefore become increasingly difficult. Thus, much research has been done on web robots which perform internet information filtering based on user interest. If a web site which users want to visit is found, its content is searched by following the searching list or Web sites links in order. This search process takes a long time according as the number of page or site increases so that its performance need to be improved. In order to minimize unnecessary search with web robots, this paper proposes an efficient information collection system based on compare and merge method. In the proposed system, a web robot initially collects information from web sites which users register. From the next visit to the web sites, the web robot compares what it collected with what the web sites have currently. If they are different, the web robot updates what it collected. Only updated web page information is classified according to subject and provided to users so that users can access the updated information quickly.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.4
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• pp.293-298
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• 2004

To satisfy the requirements for QoS and acceptance ratio of the users using multimedia content service, it is required to control mechanism for QoS assurance and allocation of the stream server' resources based on CoS(Class of Service). To compare performance of the algorithm, we have classified the user by two classes (super class, base class) and control the acceptance ratio of user's requests by user's class information. We have experimented the test of network resources and test of processing time under server/client environment and agent environment. MA-URFA based on agent increases the acceptance ratio of super class and utilization ratio of network resources.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.27-36
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• 2010

In Web registration pages and online polling applications, CAPTCHA(Completely Automated Public Turing Test To Tell Computers and Human Apart) is used for distinguishing human users from automated programs. Text-based CAPTCHAs have been widely used in many popular Web sites in which distorted text is used. However, because the advanced optical character recognition techniques can recognize the distorted texts, the reliability becomes low. Image-based CAPTCHAs have been proposed to improve the reliability of the text-based CAPTCHAs. However, these systems also are known as having some drawbacks. First, some image-based CAPTCHA systems with small number of image files in their image dictionary is not so reliable since attacker can recognize images by repeated executions of machine learning programs. Second, users may feel uncomfortable since they have to try CAPTCHA tests repeatedly when they fail to input a correct keyword. Third, some image-base CAPTCHAs require high communication cost since they should send several image files for one CAPTCHA. To solve these problems of image-based CAPTCHA, this paper proposes a new CAPTCHA based on both image and text. In this system, an image and keywords are integrated into one CAPTCHA image to give user a hint for the answer keyword. The proposed CAPTCHA can help users to input easily the answer keyword with the hint in the fused image. Also, the proposed system can reduce the communication costs since it uses only a fused image file for one CAPTCHA. To improve the reliability of the image-text fusion CAPTCHA, we also propose a dynamic building method of large image dictionary from gathering huge amount of images from theinternet with filtering phase for preserving the correctness of CAPTCHA images. In this paper, we proved that the proposed image-text fusion CAPTCHA provides users more convenience and high reliability than the image-based CAPTCHA through experiments.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.9-20
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• 2005

Recently, the MPEG-7 standard a multimedia content description standard is wide]y used for content based image/video retrieval systems. However, since the descriptors standardized in MPEG-7 are usually multidimensional and the problem called 'Curse of dimensionality', previously proposed indexing methods(for example, multidimensional indexing methods, dimensionality reduction methods, filtering methods, and so on) could not be used to effectively index the multimedia database represented in MPEG-7. This paper proposes an efficient multimedia data indexing mechanism reflecting the characteristics of MPEG-7 visual descriptors. In the proposed indexing mechanism, the descriptor is transformed into a histogram of some attributes. By representing the value of each bin as a binary number, the histogram itself that is a visual descriptor for the object in multimedia database could be represented as a bit string. Bit strings for all objects in multimedia database are collected to form an index file, bitmap index, in the proposed indexing mechanism. By XORing them with the descriptors for query object, the candidate solutions for similarity search could be computed easily and they are checked again with query object to precisely compute the similarity with exact metric such as Ll-norm. These indexing and searching mechanisms are efficient because the filtering process is performed by simple bit-operation and it reduces the search space dramatically. Upon experimental results with more than 100,000 real images, the proposed indexing and searching mechanisms are about IS times faster than the sequential searching with more than 90% accuracy.

• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.242-249
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• 2018

This study was conducted to develop an SNP set that can be useful for marker-assisted breeding (MAB) in watermelon (Citrullus. lanatus L) using Genotyping-by-sequencing (GBS) analysis of 20 commercial elite watermelon inbreds. The result of GBS showed that 77% of approximately 1.1 billion raw reads were mapped on the watermelon genome with an average mapping region of about 4,000 Kb, which indicated genome coverage of 2.3%. After the filtering process, a total of 2,670 SNPs with an average depth of 31.57 and the PIC (Polymorphic Information Content) value of 0.1~0.38 for 20 elite inbreds were obtained. Among those SNPs, 55 SNPs (5 SNPs per chromosome that are equally distributed on each chromosome) were selected. For the understanding genetic relationship of 20 elite inbreds, PCA (Principal Component Analysis) was carried out with 55 SNPs, which resulted in the classification of inbreds into 4 groups based on PC1 (52%) and PC2 (11%), thus causing differentiation between the inbreds. A similar classification pattern for PCA was observed from hierarchical clustering analysis. The SNP set developed in this study has the potential for application to cultivar identification, F1 seed purity test, and marker-assisted backcross (MABC) not only for 20 elite inbreds but also for diverse resources for watermelon breeding.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.355-361
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• 2005

This paper proposed a system collecting image information by agents in multi-threaded environment and then retrieving them with content based image retrieval. This system uses multi threads to retrieve web information effectively, then improves efficiency of CPU cycles to reduce latency time, which is the time requesting queries, executing communication processing 4hat the retrieval agents perform and filtering the retrieval results. Also, the agents for image retrieval use Java language, which is platform independent, to be suitable for distributed environment. Using JDBC to save the retrieved images, the agents are connected to database. The images themselves are stored in distributed agents' databases, and only the image indexes are stored in an index server so that the efficiency of storage and retrieval time can be improved.

• Smart Structures and Systems
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• v.25 no.5
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• pp.531-541
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• 2020

This paper demonstrates the possibility of evaluating the safety of a building right after an earthquake using consumer-grade surveillance cameras installed in the building. Two cameras are used in each story to extract the time history of interstory drift during the earthquake based on camera calibration, stereo triangulation, and image template matching techniques. The interstory drift of several markers on the rigid floor are used to estimate the motion of the geometric center using the least square approach, then the horizontal interstory drift of any location on the floor can be estimated. A shaking table collapse test of a steel building was conducted to verify the proposed approach. The results indicate that the accuracy of the interstory drift measured by the cameras is high enough to estimate the damage state of the building based on the fragility curve of the interstory drift ratio. On the other hand, the interstory drift measured by an accelerometer tends to underestimate the damage state when residual interstory drift occurs because the low frequency content of the displacement signal is eliminated when high-pass filtering is employed for baseline correction.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.93-100
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• 2005

This study is to desist and implement an efficient microbial medical image retrieval system based on knowledge and content of them which can make use of more accurate decision on colony as doll as efficient education for new techicians. For this. re first address overall inference to set up flexible search path using rule-base in order U redure time required original microbial identification by searching the fastest path of microbial identification phase based on heuristics knowledge. Next, we propose a color ffature gfraction mtU, which is able to extract color feature vectors of visual contents from a inn microbial image based on especially bacteria image using HSV color model. In addition, for better retrieval performance based on large microbial databases, we present an integrated indexing technique that combines with B+-tree for indexing simple attributes, inverted file structure for text medical keywords list, and scan-based filtering method for high dimensional color feature vectors. Finally. the implemented system shows the possibility to manage and retrieve the complex microbial images using knowledge and visual contents itself effectively. We expect to decrease rapidly Loaming time for elementary technicians by tell organizing knowledge of clinical fields through proposed system.