This work is a trial to ensure the absolute security in any quantum cryptography (QC) protocol via building an effective hardware for satisfying the single-photon must requirement by controlling the value of mean photon number. This was approximately achieved by building a driving circuit that provide very short pulses (≈ 10 ns) for laser diode -LD- with output power of (0.7-0.99mW) using the available electronic components in local markets. These short pulses enable getting faint laser pulses that were further attenuated to reach mean photon number equal to 0.08 or less.

This study exposed to use the liquid whey (which was produced from of soft cheese processed) partially or completely instead of milk in fatty cake, this whey residue is still not used, instead it is thrown in rivers which effect different environment and economic problems. Different concentrations was used (25% , 50% , 75% , and 100%) of whey in baked cake , Volume , height and other different properties ( panel taste ) was studied too . Sensory evaluation results showed that an improved in all the character of the baked cake was happen by the used of 25% and 50% of the whey in comparison with the control treatment, the 75% replacement showed a decrease in appearance , texture and tenderness , while the degrees of color and fla

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The cinematic medium consists of a group of elements that overlap with each other in balance, giving it its high influential capabilities, and the character is one of the most important of these elements, as it performs a set of important functions, foremost of which is the transmission of the main ideas to the recipient, and since cinema is an art closely related to the intellectual data of the worlds outside it, it is influenced by them and then reproduces them intellectually more deeply and with a higher vitality through its intermediate elements, including the character, to re-broadcast them to society with a retrograde movement, and the character of the prisoner is one of the cinematic characters that achieved this goal, as we can infe

In this paper, a new third kind Chebyshev wavelets operational matrix of derivative is presented, then the operational matrix of derivative is applied for solving optimal control problems using, third kind Chebyshev wavelets expansions. The proposed method consists of reducing the linear system of optimal control problem into a system of algebraic equations, by expanding the state variables, as a series in terms of third kind Chebyshev wavelets with unknown coefficients. Example to illustrate the effectiveness of the method has been presented.

A high Tc superconductor with a nominal composition
(Bi1-xPbx)2(Sr1-yBay)2Ca2Cu3O10+δ for (0 £ x £ 0.5) and (0 £ y £ 0.5) was prepared by
a solid state reaction method. The effect of the substitution of Pb for Bi and Ba for Sr and
quenching temperature on the superconductivity has been investigated to obtain the
optimum conditions for the formation and stabilization of the high Tc phase (2223).
The results showed that the optimum sintering temperature for the pure composition is
equal to 875°C and the sintering time is equal to 240h with heating and cooling rate of
60°C/h . Our results indicated that a small amount of (Ba = 0.1) could raise the transition
temperature (Tc), but enhancing Ba to 0.4 has raised

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes