Applied Mechanics and Materials
Vol. 792
Vol. 792
Applied Mechanics and Materials
Vol. 791
Vol. 791
Applied Mechanics and Materials
Vols. 789-790
Vols. 789-790
Applied Mechanics and Materials
Vol. 788
Vol. 788
Applied Mechanics and Materials
Vol. 787
Vol. 787
Applied Mechanics and Materials
Vol. 786
Vol. 786
Applied Mechanics and Materials
Vol. 785
Vol. 785
Applied Mechanics and Materials
Vol. 784
Vol. 784
Applied Mechanics and Materials
Vol. 783
Vol. 783
Applied Mechanics and Materials
Vol. 782
Vol. 782
Applied Mechanics and Materials
Vol. 781
Vol. 781
Applied Mechanics and Materials
Vol. 780
Vol. 780
Applied Mechanics and Materials
Vol. 779
Vol. 779
Applied Mechanics and Materials Vol. 785
Paper Title Page
Abstract: Attitude determination system (ADS) is a process to control the orientation of the satellite to make sure that the orientation is relative to inertial references frame such as Earth. ADS is consists of mathematical algorithm and sensor as a references measurement to determine attitude of satellite. Since RazakSAT in the orbit, the sensor such as sun sensor, magnetometer and gyroscopes are used to control angular rotation and prevent high spin rates that can damage the satellite. This paper presents the analysis on sensor of attitude determination system based on RazakSAT data. Matlab was used to analyze the X,Y and Z axis of the sensor to determine the condition of the satellite.
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Abstract: In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.
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