Cancer classification and identification are major areas in medical research. DNA microarrays could provide useful information for cancer classification at the gene expression level. The number of genes in a microarra...
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Cancer classification and identification are major areas in medical research. DNA microarrays could provide useful information for cancer classification at the gene expression level. The number of genes in a microarray is always several thousands while the number of training samples always several dozens. In such case most of the machine learning models suffer from the overfitting and it is necessary to select a handful of most informative genes. An adaptive and iterative gene selection algorithm based on least squares support vector machines is proposed in this paper. The algorithm adopts sequential forward selection search scheme. The number of selected genes can be determined adaptively. The total number of genes processed by the proposed algorithm is smaller than that processed by other algorithms using support vector machines. Results of numerical experiments show that the proposed algorithm trains fast and achieves comparable performance on two well-known benchmark problems.
Moving object segmentation in the compressed domain plays an important role in many real-time applications, e.g. video indexing, video surveillance, etc. H.264/AVC is the up-to-date video coding standard, which employ...
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ISBN:
(纸本)300018726X
Moving object segmentation in the compressed domain plays an important role in many real-time applications, e.g. video indexing, video surveillance, etc. H.264/AVC is the up-to-date video coding standard, which employs several new coding tools and provides a different video format. In this paper, a robust spatio-temporal segmentation approach to extract moving objects in the compressed domain for H.264 video stream is proposed. Coarse moving objects are firstly extracted from the motion vector field through the MRF classification process. Spatial segmentation is based on the HT coefficient, which is used to refine the object boundary of temporal segmentation results. Fusion of spatio-temporal segmentation is based on region projection based labeling technique. Further edge refinement is performed to smooth the object boundaries. The performance of the proposed approach is illustrated by simulation carried on several test sequences. Experimental results show that the proposed approach can provide the visually similar results as by using spatial domain process with much less computational complexity.
To use role-based access control (RBAC) in wireless network is difficult than that in wired network. RBAC needs to search relative tables to get the user's permissions. We present an access control judgment algori...
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To use role-based access control (RBAC) in wireless network is difficult than that in wired network. RBAC needs to search relative tables to get the user's permissions. We present an access control judgment algorithm which bases on artificial neural network (ANN). The algorithm reduces the data transmission using bit string to express roles and permissions. The algorithm employs set theory to represent roles and their inheritance hierarchy, as well as conflicted permissions. It uses selected roles as input vectors and the matching permissions which contain no conflict as the output vectors to train the ANN. Then it uses the trained ANN to compute directly users' permissions when the system is under running condition, instead of searching tables. That improves the efficiency of access control. The algorithm is simple and efficient, which makes it easy to be realized in wireless networks
Tô et al. presented a bilinear-map-based traitor tracing scheme with revocation, but it is a symmetric scheme because it does not provide non-repudiation. An improved Tô scheme was proposed using oblivious p...
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Tô et al. presented a bilinear-map-based traitor tracing scheme with revocation, but it is a symmetric scheme because it does not provide non-repudiation. An improved Tô scheme was proposed using oblivious polynomial evaluation (OPE) protocol and service parameters. Under the precondition of general sameness capabilities of both Tô's and improved Tô's scheme, the new scheme adds some advantages such as providing multi-service capability, user's non-repudiation and data provider's no framing innocent users. Furthermore, it is also proved to be semantically secure under the decisional bilinear Diffie-Hellman problem (DBDH) assumption.
We have developed a portable gas sensor using microfluidic devices (concentration and detection cells) for detecting and identifying gaseous aromatic volatile organic compounds (VOCs), such as benzene, toluene, xylene...
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We have developed a portable gas sensor using microfluidic devices (concentration and detection cells) for detecting and identifying gaseous aromatic volatile organic compounds (VOCs), such as benzene, toluene, xylene, styrene, and ethylbenzene. To improve the sensor's sensitivity, we introduced techniques for the precise control of gas transfer from the concentration cell to the detection cell and optimized the spectrum measurement conditions. We achieved a detection level of 10 ppb for benzene gas as an example of aromatic VOC detection in a sampling time of 50 minutes. The calibration curve showed good linearity in the range of 10-100 ppb of benzene. We also carried out gas-monitoring experiments in a garage. The results show the applicability of our aromatic VOC sensor for field monitoring.
We present a robust disaster recovery system model according to the requests of disaster recovery talent of a key e-government project of China. The model strengthens the safe communication ability and guarantees the ...
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For group-oriented applications, designing secure and efficient group key management schemes is a major problem. We present a group key management scheme for dynamic peer networks, which supports join, leave, merge an...
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ISBN:
(纸本)1424406048
For group-oriented applications, designing secure and efficient group key management schemes is a major problem. We present a group key management scheme for dynamic peer networks, which supports join, leave, merge and partition events. In the scheme, the numbers of rounds and messages are close to the lower bounds of those for dynamic group key management, and the length of messages and computation costs are less than those of the existing schemes. Furthermore, this scheme provides forward secrecy, backward secrecy and key independence
The water quality is the most vital factor in a successfully healthy aquaculture. After investigation by 415 fish disease cases and experiments, it is found that eutrophication and the pollutants of NH3, H2S as well a...
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The water quality is the most vital factor in a successfully healthy aquaculture. After investigation by 415 fish disease cases and experiments, it is found that eutrophication and the pollutants of NH3, H2S as well as heavy metals and organic compounds are the main reasons of inducing fish disease in the north of China. Generally speaking, an early warning system for fish disease based on water management is a cheaper and alternative choice available for the fish farmers to warn the risks and to minimize disease problems. A Web-GIS-based fish disease early-warning system (FDEWS 2.0) based on water quality management has been developed by us. Building a water quality monitoring network in the aquafarm and integrating a series of simulation models with the GIS and the World-Wide-Web (WWW) are the key advantages of this system
In high-speed Internet links, effective and efficient packet sampling technology in traffic measurement becomes more and more indispensable for its benefits of reducing data quantity and saving various resources. We a...
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The study on semantic routing efficiency of DHTP2P networks is a key element to promote the development of P2P networks, it is critical for a P2P routing algorithm to be aware of the network physical topology, which l...
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