Structural, optical, and electrical properties of thin films of CdS : Zn prepared by the solution – growth technique are reported as a function of zinc concentration. CdS are window layers influencing the photovoltaic response of CIS solar cells. The zinc doping concentration was varied from 0.05 to 0.5 wt %, zinc doping apparently increase the band gap and lowers the resistivity. All beneficial optical properties of chemically deposited CdS thin films for application as window material in heterojunction optoelectronic devices are retained. Heat treatment in air at 400 °C for 1h modify crystalline structure, optical, and electrical properties of solution growth deposited CdS : Zn films.

The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

In this research , design and study a (beam expander) for the Nd – YAG laser with (1.06 ?m) Wavelength has been studied at 5X zoom with narrow diversion in the room temperature. by using (ZEMAX) to study the system. Evaluate its performance via (ZEMAX) outputs, as bright Spot Diagram via (RMS), Ray Fan Plot, Geometric Encircled Energy and the value of Focal shift. Then study the effect of field of view on the outputs in the room temperature.

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

Two samples of (Ag NPs-zeolite) nanocomposite thin films have been prepared by easy hydrothermal method for 4 hours and 8 hours inside the hydrothermal autoclave at temperatures of 100°C. The two samples were used in a photoelectrochemical cell as a photocatalyst inside a cell consisting of three electrodes: the working electrode photoanode (AgNPs-zeolite), platinum as a cathode electrode, and Ag/AgCl as a reference electrode, to study the performance of AgNPs-zeolite under dark current and 473 nm laser light for water splitting. The results show the high performance of an eight-hour sample with high crystallinity compared with a four-hour sample as a reliable photocatalyst to generate hydrogen for renewable energies.

Free Space Optical (FSO) technology offers highly directional, high bandwidth communication channels. This technology can provide fiber-like data rate over short distances. In order to improve security associated with data transmission in FSO networks, a secure communication method based on chaotic technique is presented. In this paper, we have turned our focus on a specific class of piece wise linear one-dimensional chaotic maps. Simulation results indicate that this approach has the advantage of possessing excellent correlation property. In this paper we examine the security vulnerabilities of single FSO links and propose a solution to this problem by implementing the chaotic signal generator “reconfigurable tent map”. As synchronizat

Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

The Jeribe Formation, the Jambour oil field, is the major carbonate reservoir from the tertiary reservoirs of the Jambour field in northern Iraq, including faults. Engineers have difficulty organizing carbonate reserves since they are commonly tight and heterogeneous. This research presents a geological model of the Jeribe reservoir based on its facies and reservoir characterization data (Permeability, Porosity, Water Saturation, and Net to Gross). This research studied four wells. The geological model was constructed with the Petrel 2020.3 software. The structural maps were developed using a structural contour map of the top of the Jeribe Formation. A pillar grid model with horizons and layering was designed for each zone. Followin

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina