There are many methods for RNS implementation. The Bajard method is the fastest RNS implementation until now. One of the goals of this paper is to optimize this method to achieve higher performance for hardware implementation of RSA cryptosystem. Higher performance means increase in processing speed and less area. Proper hardware architectures for this method are proposed. For this purpose the number of multiplications is the criterion of the processing speed and the required memory for saving the constant values indicates the area required for this system. The number of multiplications is reduced by 400/(3k+ 11) percent (k is the number of modulus) in the final improved system and the number of constant values reduced by 50 percent.

Microarray technology is a new and powerful tool for concurrent monitoring of large number of genes expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression schemes. In this paper, we offer a new architecture for lossless compression of microarray images. In this architecture, we have used a dedicated hardware for separation of foreground pixels from the background ones. By separating these pixels and using pipeline architecture, a higher lossless compression ratio has been achieved as compared to other existing methods.