Guozhu Liu

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In order to extract valid information from video, process video data efficiently, and reduce the transfer stress of network, more and more attention is being paid to the video processing technology. The amount of data in video processing is significantly reduced by using video segmentation and key-frame extraction. So, these two technologies have gradually(More)
In order to understand the message propagation performance in Mobile ad-hoc Networks (MANETs), various methods and models have been proposed in the literature by applying a common pair wise meeting rate between mobile nodes. In this paper, based on this classical meeting rate, we develop an Ordinary Differential Equations (ODEs) based analytical frame-work(More)
High selectively catalytic conversion of lignin-based phenols (m-cresol, p-cresol, and guaiacol) into para-/m-xylene was performed over Pt/HZSM-5 through hydrodeoxygenation and in situ methylation with methanol. It is found that the p-/m-xylene selectivity is uniformly higher than 21%, and even increase up to 33.5% for m-cresol (with phenols/methanol molar(More)
The relational database model (RDM), proposed by Codd, has been proven to be a very useful model in many applications. The inherent of the RDM is effective for precise and unambiguous data. However, real world applications often include imprecise and uncertain information. Therefore, Beaubouef et al. proposed the rough relational database model (RRDM) for(More)
Ensemble techniques have been widely used for improving the classification accuracy, and recent studies show that ensembling classifiers through multi-modal perturbation can further improve the classification performance. In this paper, we propose a novel selective ensemble algorithm (called SE_AROS) based on approximate reducts and optimal sampling. In(More)
Ensemble techniques have been widely used for improving the classification performance, and recent studies show that ensembling classifiers through multi-modal perturbation can further improve the classification performance. In this paper, we propose a selective ensemble algorithm based on multi-modal perturbation (called SE_MP). In SE_MP, we devise a(More)