The concept of twisted pair on the cable interconnection can be readily applied to the differential lines on printed circuit board (PCB), which enables enhanced immunity against crosstalk and radiated emission. In thi...
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The concept of twisted pair on the cable interconnection can be readily applied to the differential lines on printed circuit board (PCB), which enables enhanced immunity against crosstalk and radiated emission. In this paper, twisted differential line (TDL) is implemented on PCB and fully characterized. First, the transmission characteristics of TDL including propagation constant and differential impedance are extracted by using 3D full-wave analysis. The potential of TDL for the transmission of over GHz signal and enhanced immunity against crosstalk and radiated emission is clearly shown. Second, the measurement results reconfirm TDL's capability as a good transmission line structure over several GHz. Also, it is modeled by a simple equivalent circuit, based on measurement results. Third, the enhanced immunity of TDL against crosstalk and radiated emission is clearly demonstrated by measurement results. TDL is compared with other transmission line structures showing its superiority. Finally, several ideas to improve TDL's performance are suggested and verified to be useful.
In this paper, we present a real-time method for mining the facial patterns and tracking the facial emotion. We first recognize the facial patterns based on a nonsupervised idea of pattern mining from video. To raise ...
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An abstract multimedia semantic model called the multimedia augmented transition network (MATN) model is proposed to model the RTSP-based (real-time streaming protocol) multimedia presentation systems. RTSP provides a...
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Due to the explosive growth of available information on the World Wide Web (WWW), users have suffered from the information overload. To alleviate this problem, there is a need for an intelligent tool to help the users...
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Due to the explosive growth of available information on the World Wide Web (WWW), users have suffered from the information overload. To alleviate this problem, there is a need for an intelligent tool to help the users screening and filtering for interesting and useful information. In this paper, a method of automatically identifying topics for Web documents via a classification technique is proposed. Topic identification can be applied as a filtering tool for recommender systems to prune down the number of documents to within some particular topics. We adopt the fuzzy association concept as a machine learning technique to classify the documents into some predefined categories or topics. Our approach is compared to the vector space model with the cosine coefficient using the data sets collected from three different Web portals: Yahoo!, Open Directory Project and Excite. The results show that our approach yields higher classification accuracy compared to the vector space model.
Searching for new rules and new knowledge in problem areas, where very little or almost none previous knowledge is present, can be a very long and demanding process. In our research we addressed the problem of finding...
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Searching for new rules and new knowledge in problem areas, where very little or almost none previous knowledge is present, can be a very long and demanding process. In our research we addressed the problem of finding new knowledge in the form of rules in the diabetes database using a combination of decision trees and association rules. The first question we wanted to answer was, if there are significant differences in sets of rules both approaches produce, and how rules, produced by decision trees behave, after being a subject of filtering and reduction, normally used in association rule approaches. In order to accomplish that, we had to make some modifications to both the decision tree approach and association rule approach. From the first results we can conclude, that the sets of rules, built by decision trees are much smaller than the sets created by association rules. We could also establish, that filtering and reduction did not effect the rules derived from decision trees in the same scale as association rules.
Automatic video scene change detection is a challenging task. Using audio or visual information alone often cannot provide a satisfactory solution. However, how to combine audio and visual information efficiently stil...
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Automatic video scene change detection is a challenging task. Using audio or visual information alone often cannot provide a satisfactory solution. However, how to combine audio and visual information efficiently still remains a difficult issue since there are various cases in their relationship due to the versatility of videos. We present an effective scene change detection method that adopts the joint evaluation of the audio and visual features. First, video information is used to find the shot boundaries. Second, the audio features for each video shot can be extracted. Lastly, an audio-video combination schema is proposed to detect the video scene boundaries.
In this paper, a method of automatically classifying web documents into a set of categories using the fuzzy association concept is proposed. Using the same word or vocabulary to describe different entities creates amb...
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In this paper, a method of automatically classifying web documents into a set of categories using the fuzzy association concept is proposed. Using the same word or vocabulary to describe different entities creates ambiguity, especially in the web environment where the user population is large. To solve this problem, fuzzy association is used to capture the relationships among different index terms or keywords in the documents, i.e., each pair of words has an associated value to distinguish itself from the others. Therefore, the ambiguity in word usage is avoided. Experiments using data sets collected from two web portals: Yahoo! and Open Directory Project are conducted. We compare our approach to the vector space model with the cosine coefficient. The results show that our approach yields higher accuracy compared to the vector space model.
Recently, efficient network resource management and quality-of-service (QoS) guarantee become more and more important for multimedia applications and services, especially when considering network delays. An optimal ba...
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Recently, efficient network resource management and quality-of-service (QoS) guarantee become more and more important for multimedia applications and services, especially when considering network delays. An optimal bandwidth allocation scheme is introduced. It achieves maximal utilization of the client buffer and minimal allocation of bandwidth for each client. The proposed scheme allocates bandwidth to multiple clients requesting services from a server by adjusting the transmission rates based on the client buffer occupancy, the playback requirements of the individual client and the network delays. Simulations for the single client and multiple client scenarios are conducted under different network congestion levels. The simulation results show that our approach performs better in comparison with the fixed rate allocation approach and the rate by playback requirement approach, since it avoids underflows and overflows efficiently and provides QoS for more clients with limited available bandwidth in the network.
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