In this work, a speed controlled, the programmable, low-cost, high-efficiency spin coating system is designed and implemented. The system is built from commercially available hard disk drivers DC motor, vacuum pump, speed sensor, brushless driver circuit carries Toshiba's TB6575FNG IC, PIC18F47J53 Microcontroller and using the interactive user interface to communicate with a user. Three different voltage stages and pulse width modulation techniques were used to guarantee accurate spinning speed and time. This system provides a wide range of precise and stable multi-step speeds rang of 1500 to 8,000 rpm. To evaluate the implemented system, ZnO thin films have been deposited by the sol-gel method on a glass substrate. Homogenous and uniform thickness films were obtained. The outstanding features of this system are the stability, accuracy, low energy consumption and durability, and the simplicity of adjusting multi-step spinning speed and time by using the interactive user interface.
A multilevel compression method, for magnetic resonance imaging (MRI) images, is presented in this paper. First, the image is segmented into frames of equal size. Then, the sparsity of each frame is computed. Based on the sparsity index value, each frame is compressive sensing (CS) compressed/reconstructed at one level of four. Particle swarm optimization (PSO) is used to optimize the amount of information to be used in the CS reconstruction process, and to optimize the sparsity thresholds, that separate the different compression levels. Two-dimensional sigmoid function is suggested as a fitness function for the PSO. Six MRI images are used to evaluate the performance of the proposed method. The results show considerable gain in both peak signal to noise ratio (PSNR) and compression level (CL), when compared to single level compression, which is commonly considered in the literature.
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