Standard programming tools use a system of error messages and warnings to help programmers in finding syntax and logical errors in their programs. Generative programming differentiates the level of generator from the level of generated application. The source code is synthesized at the level of generator from a set of code templates according to application specification and rules defined by ge...

Time, data and memory trade off attack is one of the most important threats against pseudorandom generators and resisting against it, is considered as a main criteria of designing such generators. In this research, the pseudo-random GMGK generator will be addressed and analyzed in details. Having indicated various weaknesses of this generator, we performed three different versions of structural...

‎‎a natural generalization of two dimensional cyclic code ($t{tdc}$) is two dimensional skew cyclic code‎. ‎it is well-known that there is a correspondence between two dimensional skew cyclic codes and left ideals of the quotient ring $r_n:=f[x,y;rho,theta]/_l$‎. ‎in this paper we characterize the left ideals of the ring $r_n$ with two methods and find the generator matrix for two dimensional s...

A stream cipher generator can not be considered as suitable for stream ciphers applications unless its output sequences have large periods, large linear complexities and possess certain randomness properties. The use of clock-controlled shift registers in keystream generators appears to be a good way of achieving sequences with these properties. In this thesis we look at clock-controlled genera...

Introduction Medical data is often stored in the form of two dimensional images, detailed slices of sections of the body. Images representing the interior can be obtained using a number of technologies such as magnetic resonance imaging (MRI), computer aided topography (CAT) and ultrasound. Many forms of 3D images are sampled from two dimensional slices. Medical data stored as sets of slices ca...

We consider the problem of training generative models with deep neural networks as generators, i.e. to map latent codes to data points. Whereas the dominant paradigm combines simple priors over codes with complex deterministic models, we propose instead to use more flexible code distributions. These distributions are estimated non-parametrically by reversing the generator map during training. T...

In the last lecture, we discussed a recursive construction of a pseudorandom generator that is based on expanders: the INW generator. In this lecture we will show that the INW-generator with a suitable instantiation of an expander family produces pseudorandomness for machines that run in logarithmic space. We also introduce Nisan’s generator, which is a pseudorandom generator that has a recursi...

This article presents an information retrieval system (IRS) using genetic algorithm to increase the performance and efficiency of Text to Matrix Generator (TMG).This paper presents an extension in previous work of Text to Matrix Generator (TMG). In this paper, we proposed a genetic algorithm approach in Text to Matrix Generator for information retrieval. This experimental result shows an improv...