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.

Alginate is one of the natural biopolymers that is widely used for drug formulations, combination of alginate with other polymers, such as gum acacia, pectin, and carrageenan can increase mechanical strength, therefore, can reduce leakage of the encapsulated active pharmaceutical ingredient from the polymer matrix. Interaction of alginate and these polymers can occur via intermolecular hydrogen bonds causing synergism, which is determined from the viscosity of polymer mixture.

Alginate was combined with gum acacia/pectin/carrageenan in different blending ratios (100:0, 75:25, 50:50, 25:75, and 0:100) with and without addition of CaCl₂. The synergism effect is obtained from the design of experimental (DoE), and calculati

Six species of aquatic snails were sorted from three sites, the irrigation canal of Baghdad University campus (S1), River Tigris at Al-Za'afaraniah district / Baghdad(S2) , and River Euphrates at Al-Haideriah district Al-Najaf province(S2). The species included Melanopsis nodosa ;Melanoides tuberculata ; Thaiodaxsas jordani ; Lymnaea auricularia ; Physa acuta and Bellamya bengalensis. The first specis recorded the highest total number and was found in high density in the R. Euphrates site (S3), while the last species was the most widely distributed species, and found in all study sites. The last three species were found in Tigris river (S2) , while the first and last species were collected from the irrigation canal (S1).The result reveal

The study is concerned with the problem of the earthly identity of kindergarten children by verifying its aims in identifying the earthly identity of the first level of kindergarten children and the earthly identity of both levels of the kindergarten. The research also aims to identify the earthly identity of male and female kindergarten children. The study population is represented in public and private kindergartens on both sides of Baghdad city, Karkh & Rusafa for the academic year (2022-2023). The earthly identity test in its final form consisted of (10) items. The test was administered to a sample of (400) children in public and private kindergartens, who were selected randomly. The results showed that kindergarten children have

Applications of nonlinear, time variant, and variable parameters represent a big challenge in a conventional control systems, the control strategy of the fuzzy systems may be represents a simple, a robust and an intelligent solution for such applications.

This paper presents a design of fuzzy control system that consists of three sub controllers; a fuzzy temperature controller (FC_T), a fuzzy humidity controller (FC_H) and a ventilation control system; to control the complicate environment of the greenhouse (GH) using a proposed multi-choice control system approach. However, to reduce the cost of the crop production in the GH, the first choice is using the ventilation system to control the temperature and humidit

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima