The purpose of this study is to design a content-based medical image retrieval system and provide a new method to reduce semantic gap between visual features and semantic concepts. Generally performance of the retrieval systems based on only visual contents decrease because these features often fail to describe the high level semantic concepts in user’s mind. In this paper this problem is solved using a new approach based on projection of relevant and irrelevant images in to a new space with low dimensionality and less overlapping in relevance feedback level. For this purpose, first we change the feature space using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques and then classify the feedback images applying Support Vector Machine (SVM) classifier. The proposed framework has been evaluated on a database consisting of 10,000 medical X-ray images of 57 semantic classes. The obtained results show that the proposed approach significantly improves the accuracy of retrieval system.

Designing a two-phase brushless direct current motor (BLDC) and analyzing effects of stator slots structure on the motor operation are main objectives of this paper. At first BLDC motor with three different structures for stator slots is designed by using RMxprt software and efficiency of BLDC motor for different structures in full-load condition has been presented, then the BLDC motor in different conditions by using Maxwell 3D software is designed and with finite element method is analyzed electromagnetically. The results of simulations show that by varying stator slots structure efficieny and operation of motor have changed significantly therefore with correct choosing of stator slots structure intersted operation can be found.