Abstract: Arthritis is the most common inflammation in bone-joints and this progressive disease often leads to early disability and joint deformities. By the early diagnosis and treatment of the Arthritis, the damage to the joins can be reduced. A number of therapeutic approaches are now widely available for the diagnosis of this disease. Imaging of the affected joints plays a vital role in the diagnosis. In this paper, a novel classification system for the classification of OA in knee x-ray images based on Local Binary Pattern (LBP) and Local ternary pattern(LTP) is presented. The classification is achieved by extracting the histograms of LBP and LTP of the knee x-ray image. Then classifier system based on K Nearest Neighbor (KNN) is constructed. This system classifies the knee x-ray images into normal or abnormal, and the abnormal severity into medium or worst cases. 50 knee x-ray images are used to evaluate the proposed system. The classification rate achieved is very satisfied.

• Publication Date: 07-Apr-2013
• DOI: 10.15224/978-981-07-5939-1-14
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Abstract: This paper presents the dynamic model of Permanent Magnet Synchronous Generator (PMSG) based on Wind Energy Conversion System (WECS). The models of WECS consist of a wind turbine, pitch angle control, drive train, PMSG and power converter. Wind turbine model with controller for generator protection in high wind speed is also presented in this paper. The PMSG and converter model are established in the d-q model. The presented model, dynamic simulation and simulation results are tested in MATLAB/SIMULINK

• Publication Date: 07-Apr-2013
• DOI: 10.15224/978-981-07-5939-1-15
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