A New Scheme For Wireless Network Authentication System
In this paper we use the independent component analysis (ICA) and Factorial Face Code as an additional user identity checking method to strengthen the solidity of the wireless application system authentication security. The basic theory of ICA and factorial face code are presented firstly and then the main works of this method are detailed. After that an experiment based on this method is given. According to this experiment, we know that this method can confirm user’s identity and can be an additional method to check wireless application system user identity. In order to improve the affectivity of this method, we should increase the mount of image data in the face database, getting more ICs and enlarging the size of the basic images set. All this will increase the length of the factorial face code, and subsequently will differentiate one person from another more easily.

title: An Advanced Scheme For Wireless Network Authentication System
abstract: In this paper we use the independent component analysis (ICA) and Factorial Face Code as an additional user identity checking method to strengthen the solidity of the wireless application system authentication security. The basic theory of ICA and factorial face code are presented firstly and then the main works of this method are detailed. After that an experiment based on this method is given. According to this experiment, we know that this method can confirm user’s identity and can be an additional method to check wireless application system user identity. In order to improve the affectivity of this method, we should increase the mount of image data in the face database, getting more ICs and enlarging the size of the basic images set. All this will increase the length of the factorial face code, and subsequently will differentiate one person from another more easily.

title: Comparative knowledge management: A pilot study of Chinese and American universities
abstract: Comparative study of knowledge management (KM) promises to lead to more effective knowledge use in all cultural environments. This pilot study compares KM priorities, needs, tools, and administrative structure components in large Chinese and American universities. General KM theory and literature related to KM in higher education are analyzed to develop the four components of the study. Comparative differences in KM practice at large Chinese and American universities are analyzed for each component. A correlation matrix reveals statistically significant co-variation among all but one of the study components. Four conclusions related to comparative KM and suggestions for future research are presented.

title: Replicators: transformations to address model scalability
abstract: In Model Integrated Computing, it is desirable to evaluate different design alternatives as they relate to issues of scalability. A typical approach to address scalability is to create a base model that captures the key interactions of various components (i.e., the essential properties and connections among modeling entities). A collection of base models can be adorned with necessary information to characterize their replication. In current practice, replication is accomplished by scaling the base model manually. This is a time-consuming process that represents a source of error, especially when there are deep interactions between model components. As an alternative to the manual process, this paper presents the idea of a replicator, which is a model transformation that expands the number of elements from the base model and makes the correct connections among the generated modeling elements. The paper motivates the need for replicators through case studies taken from models supporting different domains.

title: Camera Calibration from a Single Frame of Planar Pattern
abstract: A method to calibrate camera from a single frame of planar pattern is presented in this paper. For a camera model with four intrinsic parameters and visible lens distortion, the principal point and distortion coefficients are firstly determined through analysis of the distortion in an image. The distortion is then removed. Finally, the other intrinsic and extrinsic parameters of the camera are obtained through direct linear transform followed by bundle adjustment. Theoretically, the method makes it possible to analyze the calibration result at the level of a single frame. Practically, such a method provides a easy way to calibrate a camera used in industrial vision system on line and used in desktop vision system. Experimental results of both simulated data and real images validate the method.

title: Motion segmentation of multiple translating objects using line correspondences
abstract: We present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. We show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. The individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). Given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. The limitations of the proposed algorithm are also discussed. Experimental results on synthetic and real dynamic scenes are presented.

title: Application of multisensor data fusion based on RBF neural networks for fault diagnosis of SAMS
abstract: The idea of multisensor integration is to use multiple sensors for measuring the same variables, where each sensor has its own accuracy, reliability and drawbacks. The sensor information is integrated by some data integration algorithms. In this paper, Radial Basis Function (RBF) neural networks and multisensor data fusion technology are combined and used in the fault detection and diagnosis of sensors hardware faults in the Satellite Attitude Measurement System (SAMS). The fusion method of the RBF neural networks is adopted. By using the combination method the outputs of the system are more accurate and reliable than each individual sensor. Research results show that this method for the detection and diagnosis of the sensors hardware faults in the SAMS is feasible and more effective, and for the sensors which measure the same attitude angle, using the method of firstly integration, then faults diagnosis, finally connection with the measurement system, the systematic measurement precision and performance-price-ratio can be improved.