Sensitive information of any multimedia must be encrypted before transmission. The dual chaotic algorithm is a good option to encrypt sensitive information by using different parameters and different initial conditions for two chaotic maps. A dual chaotic framework creates a complex chaotic trajectory to prevent the illegal use of information from eavesdroppers. Limited precisions of a single chaotic map cause a degradation in the dynamical behavior of the communication system. To overcome this degradation issue in, a novel form of dual chaos map algorithm is analyzed. To maintain the stability of the dynamical system, the Lyapunov Exponent (LE) is determined for the single and dual maps. In this paper, the LE of the single and dual maps
... Show MoreThe automatic liquid filling system is used in different applications such as production of detergents, liquid soaps, fruit juices, milk products, bottled water, etc. The automatic bottle filling system is highly expensive. Where, the common filling systems required to complex changes in hardware and software in order to modify volume of liquid. There are many important variables in the filling process such as volume of liquid, the filling time, etc. This paper presents a new approach to develop an automatic liquid filling system. The new proposed system consists of a conveyor subsystem, filling stations, and camera to detect the level of the liquid at any instant during the filling process. The camera can detect accurately the leve
... Show MoreOne of the globalization results is (VAT) , so it is important to consider its results and impact on the tax system.
The Iraqi economy having wittnisd an acute transition period , still in need for a better care in aim to back it, especialy from the tax system.
The research is concerned with the (VAT) and its details –And for five chapters all the problomes connect are displayed .But yet the new system does not comply with the modern development and this is one of the defects of (VAT) in Iraq.
The history of (VAT)was also studied mentiorned and studied.
As a conclusion (VAT) is one of the m
... Show MoreIn the present work, different thicknesses of CdS film were prepared by chemical bath deposition. Z-Scan technique was used to study the nonlinear refractive index and nonlinear absorption coefficients. Linear optical testing were done such as transmission test, and thickness of films were done by the interference fringes (Michelson interferometer). Z-scan experiment was performed at 650nm using CW diode laser and at 532nm wavelength. The results show the effect of self-focusing and defocusing that corresponds with nonlinear refraction n2. The effect of two-photon absorption was also studied, which correspond to the nonlinear absorption coefficient B.
In this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
In this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
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