Traffic flow prediction plays an indispensable role in the intelligent transportation system. The effectiveness of traffic control and management relies heavily on the prediction accuracy. The authors propose a model ...
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Currently, many works regarded extractive summarization as a binary classification problem. However, the metric of the summary classification is always too singular and cannot fully utilize sentence features. To addre...
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Analysis approaches of reachability decision is fundamental to Petri nets theory;however, the relevant research work in the past cannot always guarantee the correctness of analysis conclusions. This paper firstly reve...
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The real-time traffic parameters are necessary to dynamic traffic light control at intersection due to the serious traffic congestion. In this paper, we describe an approach for the real-time vehicle queue length meas...
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A novel metric for full-reference image quality assessment (IQA) is proposed in this paper. Based on the sparse representation in independent component analysis (ICA) domain, the image basis is generated from natural ...
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A novel metric for full-reference image quality assessment (IQA) is proposed in this paper. Based on the sparse representation in independent component analysis (ICA) domain, the image basis is generated from natural images adaptively, which coincides with the characteristics of human vision system (HVS). In order to extract the feature vector, a hybrid norm optimization strategy is introduced for achieving more stable computational performances. The proposed IQA metric is calculated as a correlation coefficient between the two feature vectors from reference and distorted images, respectively. Experimental results on the LIVE Database Release 2 demonstrate that the proposed metric can achieve competitive performances as compared to the well-known structural similarity (SSIM) metric.
Real-time wireless sensor networks in the industrial settings usually consist of tens of nodes. Seldom do we see a network of over 100 wireless nodes. The smaller size is usually sufficient as a typical plane unit is ...
Web services composition (WSC) is the key techniques in its application. Dynamically selecting reliable Web services (WSs) becomes crucial to users. In fact, most works regard a Web service (WS) as the basic unit and ...
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With the explosive growth of Internet information, it is more and more important to fetch real-time and related information. And it puts forward higher requirement on the speed of webpage classification which is one o...
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Spatial-temporal modeling considering the particularity of traffic data is a crucial part of traffic forecasting. Many methods take efforts into relatively independent time series modeling and spatial mining and then ...
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In high frequency radar, we should avoid noise disturbances in the radar's working-frequency segment. Moreover, the sidelobes of strong targets interfere with the detection of weak targets. A new method based on a...
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In high frequency radar, we should avoid noise disturbances in the radar's working-frequency segment. Moreover, the sidelobes of strong targets interfere with the detection of weak targets. A new method based on an adaptive selecting working-frequency is proposed. Frequency spectrum monitor is designed for selecting quiet frequency segment for the radar. Frequency spectrum monitor and the receiver of the radar are arranged to work according to special time periods respectively. So the radar can work in the frequency segments with lower noise disturbances. Moreover, there is no correlation between the noise and the useful echo signal, though the correlation between noises over very short time periods is strong, the noise data produced by frequency spectrum monitor can be exploited effectively Adjusting system parameters in real-time by adaptive methods can be utilized to reduce noise disturbances. Algorithm based on the properties of crosscorrelation between noise and target is exploited for suppressing sidelobe disturbances of strong targets. Lastly, the feasibility of the methods is verified by processing actual radar data.
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