Stochastic Non-Linear Pseudo-Random Sequence Generator

Many of the key stream generators which are used in practice are LFSR-based in the sense that they produce the key stream according to a rule y = C(L(x)), where L(x) denotes an internal linear bit stream, produced by small number of parallel linear feedback shift registers (LFSRs), and C denotes some nonlinear compression function. In this paper we combine between the output sequences from the linear feedback shift registers with the sequences out from non linear key generator to get the final very strong key sequenc

Modified Weighted Pareto Distribution Type I (MWPDTI)

           في هذا البحث استخدمنا طريقة Azzallini لإيجاد توزيع موزون مشتق من توزيع  باريتو القياسي النوع الاول((SPDTI عن طريق إدخال معلمة الشكل ( ) الناتجة عن الطريقة المذكورة أعلاه لتغطية الفترة (0 ، 1[ التي أهملها التوزيع القياسي.وبالتالي ، فإن التوزيع المقترح هو تعديل لتوزيع باريتو من النوع الأول ، حيث تكون القيم الاحتمالية للمتغير العشوائي خلال الفترة تم ايجاد الخصائص الاحصائية لتوزيع باريتو المعدل الموزون من النوع الاول (  (MWPDTIكدالة كثافة الاحتمالة ودالة التوزيع  ودالة البقاء والعزوم والدوال الاحصائية الاخرى .In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period  The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and  the hazard function are found. The behaviour of probability density function for MWPDTI distribution by representing the values of    This means, the probability density function of this distribution treats the period (0,1] which is ignore in SPDTI

The Modified Quadrature Method for solving Volterra Linear Integral Equations

In this paper the modified trapezoidal rule is presented for solving Volterra linear Integral Equations (V.I.E) of the second kind and we noticed that this procedure is effective in solving the equations. Two examples are given with their comparison tables to answer the validity of the procedure

Comparison between Modified Weighted Pareto Distribution and Many other Distributions

  In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in different initial values for each Pareto distribution family being used in the research. A comparison was done by using Akaike Information Criteria, Corrected Akaike Information Criteria, and Bayesian Information Criteri