In this research , Aprocess ( LICVD) was used for producing silicon nitride powders with chemical compositon Si3N4 ,by using TEA-Co2 Laser to induc reaction in the gas phase,  NH3 was used as on additive to SiH4. Reactant gases that were vibrationaly heated by absorbing energy emitted from TEA-Co2 Laser decomposes throug coillsion assisted multiple photon dissociation causing Si3N4 powders. By the dependence of the LICVD process  on  varios parameters such as Laser intensity , total gas pressure, partial pressures of SiH4 and NH3 were investigated. Dissociation rate as a function of Laser intensity and pressure was investigated. The powders obtained exhibit various colors from brown which  is rich in Si to white.This

Abstract

   The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search th

Carbon nanospheres (CNSs) were successfully prepared and synthesized by Catalytic Chemical Vapor Deposition (CCVD) by using camphor as carbon source only, over iron Cobalt (Fe-Co) saturated zeolite at temperature between (700 oC and 900 °C), with different concentrations of camphor, and reaction time. The synthesized CNSs were characterized using Scanning Electron Microscopy (SEM), X-ray diffraction spectroscopy (XRD), and Fourier Transform Infrared (FTIR). The carbon spheres in different sizes between 100 nm and 1000 nm were investigated. This work has done by two parts, first preparation of the metallic catalyst and second part formation CNSs by heat treatment.

A simple, precise and accurate spectrophotometric method has been developed for simultaneous estimation of sulfanilamide and furosemide in their mixture by using first and second order derivative method in the ultraviolet region. The method depends on first and second derivative spectrophotometry, with zero-crossing and peak to base line and peak area measurements. The first derivative amplitudes at 214, 238 and 266 nm were selected for the assay of sulfanilamide and 240, 260, 284, 314 and 352 nm for furosemide. Peak area at 201222, 222-251 and 251-281 nm selected for estimation of sulfanilamide and at 229-249, 249270, 270-294, 294-333 and 333-382 nm for furosemide. The second derivative amplitudes at 220, 252 and 274 nm for sulfanilamid

A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

Pseudomonas aeruginosa was isolated from various clinical samples included urine, sputum, stool, ear, wound & burn swabs. Detection of the ability of local isolates to produce staphylolysin enzyme was studied, on Tryptic soya agar + 0.2% (wt./vol.) of heat killed Staphylococcus. aureus at temperature 100oC. medium and the diameters of lysis zone ranged from 5-22mm, then the isolate P16 was chosen to extract staphylolysin A (LasA) and its specific activity reaches 8.59 unit /mg protein, whi1e the isolate P5 was chosen to extract staphylolysin D (LasD) where it's specific activity reaches 0.66 unit /mg protein since the two isolates were the most production of enzyme. Staphylolysin enzyme was extracted by cooling centrifugation and par

Westiellopsis prlifica was exposed to 1, 2, 3, 5, 7 and 10 ppm from both lead & Cadmium, in order to measure their capacity to remove these metals from the polluted aquatic environment and to study its ability to tolerant them. The algae were grown under optimum conditions.
Westiellopsis prlifica had the ability to remove the lead with percentages about 31.57, 54.42, 62.35, 61.8, 57.02 and 68.34% for the concentrations 1, 2, 3, 5, 7 and 10 ppm, respectively, but it was found that these percentages were be better in the last day of the experiment for some of the concentrations 1, 2 and 3 ppm, While the tolerant of it to lead was up to the concentration 10 ppm.
Westiellopsis prlifica appears ability to remove Cadmium with percent

This work explores the designing a system of an automated unmanned aerial vehicles (UAV( for objects detection, labelling, and localization using deep learning. This system takes pictures with a low-cost camera and uses a GPS unit to specify the positions. The data is sent to the base station via Wi-Fi connection.

The proposed system consists of four main parts. First, the drone, which was assembled and installed, while a Raspberry Pi4 was added and the flight path was controlled. Second, various programs that were installed and downloaded to define the parts of the drone and its preparation for flight. In addition, this part included programs for both Raspberry Pi4 and servo, along with protocols for communication, video transmi