Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand

Granular carbon can be used after conventional filtration of suspended matter or, as a combination of filtration - adsorption medium. The choice of equipment depends on the severity of the organic removal problem, the availability of existing equipment, and the desired improvement of adsorption condition.
Design calculations on dechlorination by granular - carbon filters considering the effects of flow rate, pH , contact time, head loss and bed expansion in backwashing , particle size, and physical characteristics were considered assuming the absence of bacteria or any organic interface .

publishing has become a large space in the field of interactive education and modern pages have become dedicated to the service of the educational effort in this area as the research in this context of the urgent scientific necessities, especially as we consider in Iraq from the new countries in the exploitation of these new technologies and investment possibilities of the information network And the contents of different in the framework of so-called distance education Here lies the problem of research in the possibility of finding scientific solutions for the design of interactive inter active website for students of the preparatory stage in Iraq and to find out the scientific ways to find design The study, which included the problem of

Abstract

          The research aims to identify tax exemptions, their objectives and types, as well as to shed light on the concept of sustainable development, its objectives, dimensions and indicators (economic, social and environmental), as well as to analyze the relationship between tax exemptions and economic development, in addition to measuring and analyzing the impact of tax exemptions on economic development in Iraq for the period ( 2015 - 2021) using the NARDL model. The research problem centers on the fact that failure to employ financial policy tools correctly led to a weakness in achieving economic justice, which leads to a failure to improve social welfar

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme