Application of neuro-fuzzy control for satellite AOCS
The attitude control of a future satellite is facing the challenge of its uncertain model because of flexural bodies coupling to the center body. This paper proposes a neuro-fuzzy approach to control the uncertain dynamics and disturbance. The flexible model of solar array is extended to the satellite attitude equation. To overcome the variation of internal parameters and external disturbances, three adaptive neuro-fuzzy controllers are applied to realize the attitude and orbit control system (AOCS) on the base of Proportional-Integral-Differential (PID) controllers. A least square estimation method is combined with gradient descent learning in order to optimize the learning error universally during train procedure. Simulation results show the neuro-fuzzy controllers have good performance to abate influence from disturbance, fadeless vibration and the change of the satellite's inertia parameters.

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.

title: High Dependability Design Framework in Real-Time Embedded Control Software
abstract: This paper introduces an abstract high dependability framework for the implementation of embedded control software with hard real-time constraints. The framework specifies time-triggered sensor readings, atomic component invocations, actuator updates, and pattern switches independent of any implementation platform. In order to leverage model continuity, XML-based description of composite component informal description is required, which supports reuse of components and model information interoperability. By separating the platform-independent from the platform-dependent concerns, Consider a quality process control system in steel industry on a distributed real-time embedded environment, we implement a simplified high dependability design framework to prove the feasibility in the validation and synthesis of embedded control component execution.

title: Building XML Data Warehouse Based on Frequent Patterns in User Queries
abstract: With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources.

title: Enabling Safe Dynamic Component-Based Software Adaptation
abstract: Recomposable software enables a system to change its structure and behavior during execution, in response to a dynamic execution environment. This paper proposes an approach to ensure that such adaptations are safe with respect to system consistency. The proposed method takes into consideration dependency analysis for target components, specifically determining viable sequences of adaptive actions and those states in which an adaptive action may be applied safely. We demonstrate that the technique ensures safe adaptation (insertion, removal, and replacement of components) in response to changing external conditions in a wireless multicast video application.

title: Exploiting Frame-to-Frame Coherence for Rendering Terrain Using Continuous LOD
abstract: It is the key issue of the terrain real-time rendering to reduce the time-spending for the level-of-detail. The concept of triangle live frame is introduced in this paper. Using this live frame, the algorithm reuses per-vertex visibility computation from previously displayed frames efficiently during continuous view-dependent level-of-detail visualizations. This algorithm decreases to a certain extent computing the distance from the viewpoint to vertex at each frame. Experimental results show that the algorithm reduces the time effectively to produce the LOD terrain.

title: ArnetMiner: An Expertise Oriented Search System for Web Community
abstract: Expertise Oriented Search aims at providing comprehensive analysis and mining for people from distributed sources. In this paper, we give an overview of the expertise oriented search system (ArnetMiner). The system addresses several key research issues in extraction and mining of a researcher social network. The system is in operation on the internet for more than one year and receives accesses from about 1,500 users per month. Feedbacks from users and system logs indicate that users consider the system can really help people to find and share information in the web community.