CIGS nanoink has synthesized from molecular precursors of CuCl, InCl3, GaCl3 and Se metal heat up 240 °C for a half hour in N2-atmosphere to form CIGS nanoink, and then deposited onto substrates of soda-lime glass (SLG). This work focused on CIGS nanocrystals, indicates their synthesis and applications in photovoltaic devices (PVs) as an active light absorber layers. in this work, using spin-coating to deposit CIGS layers (75 mg/ml and 500 nm thickness), without selenization at high temperatures, were obtained up to 1.398 % power conversion efficiency (PCE) at AM 1.5 solar illumination. Structural formations of CIGS chalcopyrite structure were studied by using x ray diffraction XRD. The morphology and composition of CIGS were studied using

In this work gold nanoparticles (AuNPs), were prepared. Chemical method (Seed-Growth) was used to prepare it, then doping AuNPs with porous silicon (PS), used silicon wafer p-type to produce (PS) the processes doping achieved by electrochemical etching, the solution etching consist of HF, ethanol and AuNPs suspension, the result UV-visible absorption for AuNPs suspension showed the single peak located at ~(530 – 521) nm that related to SPR, the single peak is confirmed that the NPs present in the suspension is spherical shape and non-aggregated. X-ray diffraction analysis indicated growth AuNPs with PS. compare the PS layer without AuNPs and with AuNPs doped for electrical properties and sensitivity properties we found AuNPs:PS is more

ABSTRACT:

              Interest rates are one of the important aspects that affect the banking business directly, which is characterized by unstable dynamic dynamics, which must be viewed on a daily and continuous basis through the macroeconomic view, which directly affects the bank’s income realized from loans as interest received or interest paid on its deposits as an expense. Hence the earnings per share. The relationship between interest rates and between net income and earnings per share was measured and a correlation was found between them, and then the effect between them was measured using regression equations and they were applied and th

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

A fast laser texturing technique has been utilized to produce micro/nano surface textures in Silicon by means of UV femtosecond laser. We have prepared good absorber surface for photovoltaic cells. The textured Silicon surface absorbs the incident light greater than the non-textured surface. The results show a photovoltaic current increase about 21.3% for photovoltaic cell with two-dimensional pattern as compared to the same cell without texturing.