Data security is an important component of data communication and transmission systems. Its main role is to keep sensitive information safe and integrated from the sender to the receiver. The proposed system aims to secure text messages through two security principles encryption and steganography. The system produced a novel method for encryption using graph theory properties; it formed a graph from a password to generate an encryption key as a weight matrix of that graph and invested the Least Significant Bit (LSB) method for hiding the encrypted message in a colored image within a green component. Practical experiments of (perceptibility, capacity, and robustness) were calculated using similarity measures like PSNR, MSE, and

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%

The composites were manufactured and study the effect of addition of filler (nanoparticles SiO2 treated with silane) at different weight ratios (1, 2, 3, 4 and 5) %, on electrical, mechanical and thermal properties. Materials were mixed with each other using an ultrasound, and then pour the mixture into the molds to suit all measurements. The electrical characteristics were studied within a range of frequencies (50-1M) Hz at room temperature, where the best results were shown at the fill ratio (1%), and thermal properties at (X=3 %), the mechanical properties at the filler ratio (2%).

Pilots are trained using computerized flight simulators. A flight simulator is a training system where pilots can acquire flying skills without need to practice on a real airplane. Simulators are used by professional pilots to practice flying strategies under emergency or hazardous conditions, or to train on new aircraft types. In this study a framework for flight simulation is presented and the layout of an implemented program is described. The calculations were based on simple theoretical approach. The implementation was based on utilizing some of utilities supported by ActiveX, DirectX and OpenGL written in Visual C++. The main design consideration is to build a simple flight simulation program can operate without need to high computer e

This paper deals with a method called Statistical Energy Analysis that can be applied to the mechanical and acoustical systems like buildings, bridges and aircrafts …etc. S.E.A as a tool can be applied to the resonant systems in the circumstances of high frequency or/and complex structure». The parameters of S.E.A such as coupling loss factor, internal loss factor, modal density and input power are clarified in this work ; coupled plate sub-systems and explanations are presented for these parameters. The developed system is assumed to be resonant, conservative, linear and there is an equipartition of energy between all the resonant modes within a given frequency band in a given sub-system. The aim of th

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri