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It is well known that the Synthetic Aperture Radar(SAR) images are abundant of directional and texture information, which is very useful for segmentation. Contourlet is a geometric multiscale tool that is based on multiscale filters and directional filter banks. It not only inherits the multiscale characteristics of dimensionality-inseparable wavelets, but also has the flexible multi-directional characteristic. In this paper, we developed a new non-subsampled contourlet transform (NSCT) and gray level co-occurrence matrix (GLCM) based image segmentation method for SAR image segmentation. For the redundant and shift-invariant property of the NSCT, and the statistical texture features extracted by GLCM, the proposed method can present accurate segmentation result for SAR images.

Contourlet is a new geometric multiscale tool that is based on multiscale filters and directional filter banks. It not only inherits the multiscale characteristics of dimensionality-inseparable wavelets, but also has the flexible multi-directional characteristic by changing the directions of transform and sequences. In this paper, we developed a new non-subsampled contourlet transform (NSCT) and gray level co-occurrence matrix (GLCM) based image segmentation method. For the redundant and shift-invariant property of the NSCT, and the statistical texture features extracted by GLCM, the proposed method can present accurate segmentation result.

In the process of decision tree construction, property division standards directly affect the classification results. Aimed at weakness of ID3 in nicety of grading, we provide the concept of degree of rough classification as select criteria of separation of property. The method took into account nicety of grading and dependency between condition attributes and decision attributes. Compared with traditional decision tree based entropy, the experiment proved that the decision tree constructed in our method effectively improves the classification results.

IPv6 will inevitably take the place of IPv4 as the next generation of the Internet Protocol. Despite IPv6 has better security than IPv4, but there still have some security issues. So it is an urgent problem to requirement of IDS for IPv6 networks. Many intelligent information processing methods, data mining technology and so on have been applied to improve detection accuracy for IPv4 network. At first IPv6 security issues has been analysis in this paper, secondly discussed the IPv6 intrusion detection model, then we in accordance with such a model present an intrusion detection model realization for IPv6 network, and we propose a strategy for the system achieve and optimization. The system can work well for intrusion detection for IPv6 network.

A new self-adaptive video watermarking, which is combined the motion characteristics detection with the model of the entropy is proposed. By uniting the human visual masking system (HVS) with the blocking-matching techniques we acquire the motion information of every macro-block in video sequence such as the velocity, the motion angle, and the deformation. The motion information is statistic by using the motion entropy. According to the entropy of motion information in each macro-block and the human visual masking system, a set of non-linear formulas have been used to calculate the maximum of the embedding strength of the every block in the video sequence to improve the imperceptibility of the watermarking. The results of imperceptible experiments indicate that the imperceptibility of the video watermarking has been improved by introducing the motion characteristics detection and the model of motion entropy. In the robust experiments the proposed algorithm could resisted the normal video watermarking attracts and has the excellent robustness and security.

Su Feng presented the modified logical track initiation algorithm in his paper, however, the development of the algorithm has not been proved in theory. In this paper, the track detection probability and false track probability of the algorithm is deduced by statistics methods. The simulation test verifies the results.

Contrast with current WLAN (wireless local area network) security mechanism worked in data link layer. IPSec worked in IP layer is applied in WLAN as a security technology which is used in wired network has his superiorities. But IPSec uses Internet key exchange protocol (IKE) as default that need to a large number of computations is not fit for mobile devices of WLAN. This paper puts forward that using the third party authentication of symmetric algorithms to replace the major mode of the IKE first phase and maintain IKE original process of second phase basically. Doing so not only satisfy the WLAN application background but also maintain the original basic functions of IKE. We rename the improvement IKE to WKE (wireless key exchange). Theory analysis and experiment represent WKE has low calculation. It can improve the execution efficiency of the identity authentication and key negotiation between wireless station and IPSec security gateway.