• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.571-578
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• 2002

In this paper, we propose a video sequence coding scheme called AMV (Auxiliary Motion Vector) to minimize error propagation caused by transmission errors over the Internet. Unlike the conventional coding schemes the AMY coder, for a macroblock in a frame, selects two best matching blocks among several preceding frames. The best matching block, called a primary block, is used for motion compensation of the destination macroblock. The other block, called an auxiliary block, replaces the primary block in case of its loss at the decoder. When a primary block is corrupted or lost during transmission, the decoder can efficiently and simply suppress error propagation to the subsequent frames by replacing the block with an auxiliary block. This scheme has an advantage of reducing both the number and the impact of error propagations. We implemented the proposed coder by modifying H.263 standard coding and evaluated the performance of our proposed scheme in the simulation. The simulation results show that AMV coder is more efficient than the H.263 baseline coder at the high packet loss rate.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.9-16
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• 2009

While the broadband network and multimedia technology are being developed, the commercial market of digital contents as well as using IPTV has been widely spreading. In this background, Time-Shift system is developed for requirement of multimedia. This system is independent of Time but is not independent of Place and Occasion. For solving these problems, in this paper, we propose the TPO(Time, Place, Occasion)-Shift system for mobile multimedia devices. The profile that can be applied to the mobile multimedia devices is much different from that of the setter-box. And general mobile multimedia devices could not have such large memories that is for multimedia data. So it is important to continuously store and manage those multimedia data in limited capacity with mobile device's profile. Therefore we compose the basket in a way using defined time unit and manage these baskets for effective buffer management. In addition. since the file name of basket is made up to include a basket's time information, we can make use of this time information as DTS(Decoding Time Stamp). When some multimedia content is converted to be available for portable multimedia devices, we are able to compose new formatted contents using such DTS information. Using basket based buffer systems, we can compose the contents by real time in mobile multimedia devices and save some memory. In order to see the system's real-time operation and performance, we implemented the proposed TPO-Shift system on the basis of mobile device, MS340. And setter-box are desisted by using directshow player under Windows Vista environment. As a result, we can find the usefulness and real-time operation of the proposed systems.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.