Skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. If they detected at an early stage, treatment can become simple and economically. Accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. The aim of this study is to provide an effective approach to detect the skin lesion border on a purposed image. A novel method is proposed that combines the edge detection and the thresholding technique for skin lesions detection from skin region in an image. The distributions of edge and the proposed thresholding method provide a good discrimination of skin lesions. The evaluation of the proposed method was based on the comparison with the Otsu and Rosin segmentation results. The performance of the designed system is evaluated with 30 test images, and the experimental results demonstrate the effectiveness of the proposed mole localization scheme. Manuscript profile

In this paper, we propose a new optimized PID controller to stabilize the synchronous machine connected to an infinite bus. The model for the synchronous machine is 4-ordered linear Philips-Heffron synchronous machine. In this research, the parameters of the PID controller are optimally achieved by minimizing a definite fitness function to removes the unstable Eigen-value to the left side of imaginary axis. The considered parameters for the controller are achieved by employing a new defined, World Cup Optimization algorithm. After applying the proposed controller, it is compared by the particle swarm optimization as a popular and high performance algorithm. Here, controller is obtained for all operating points. Final results show that the using World Cup Optimization algorithm has a better performance toward the compared particle swarm optimization. Manuscript profile