The present study involves experimental analysis of the modified Closed Wet Cooling Tower (CWCT) based on first and second law of thermodynamics, to gain a deeper knowledge in this important field of engineering in Iraq. For this purpose, a prototype of CWCT optimized by added packing under a heat exchanger was designed, manufactured and tested for cooling capacity of 9 kW. Experiments are conducted to explore the effects of various operational and conformational parameters on the towers thermal performance. In the test section, spray water temperature and both dry bulb temperature and relative humidity of air measured at intermediate points of the heat exchanger and packing. Exergy of water and air were calculated by applying the exergy

    The environmental contamination by the polycyclic aromatic hydrocarbons (PAHs) and heavy metals (Pb, Cu, Ni, Cr, and Cd) concentrations in the leaves of plant Eucalyptus camaldulensis were determined at the city of Kirkuk in 15 selected locations using GPS. The pickings up of samples were carried out in two periods October 2010 and March 2011. Compared with results of other studies, the concentration levels of determined heavy metals show values within these studies results. The average total concentration of polycyclic aromatic hydrocarbons (PAHs) in the leaves of Plant Eucalyptus camaldulensis indicated 37.1 ppb in October, while in March 165.2 ppb.

    The mode

This thesis aims to show the effects of the development of the traditional manual system of the tax accounting process to the electronic system by the activation of the tax identification numbers (TINs) mechanism. The impact of this development is facilitating the tax accounting process, tax fraudand thus increasing the tax outcome.To prove the research hypothesis, an electronic system was designed based on income tax report, estimation note of individuals, in additional to using Adobe Dreamweaver application to write PHP, HTML, Javascript, and CSS web languages to implement  the proposed system. The research reached a set of conclusions, the most important of which is; not enough the communication methods between the Genera

In this article, performing and deriving te probability density function for Rayleigh distribution is done by using ordinary least squares estimator method and Rank set estimator method. Then creating interval for scale parameter of Rayleigh distribution. Anew method using   is used for fuzzy scale parameter. After that creating the survival and hazard functions for two ranking functions are conducted to show which one is beast.

Various of 2,5- disubstituted 1,3,4-oxadiazole (Schiff base, ?- lactam and azo) were synthesized from 2,5-di (4,4?-amino-1,3,4-oxadiazole which usequently synth-esized from mixture of 4- amino benzoic acid and hydrazine arch of polyphosphorus acid. The synthesized compounds were cherecterized by using some spectral data (UV, FT-IR , and 1H-NMR)

Four new copolymers were synthesized from reaction of bis acid monomer 3-((4-carboxyphenyl) diazenyl)-5-chloro-2-hydroxybenzoic acid with five diacidhydrazide in presence of poly phosphoric acid. The resulted monomers and copolymers have been characterized by FT-IR, 1H-NMR, 13C-NMR spectroscopy as well as EIMs technique. The number averages of molecular weights of the copolymers are between 4822 and 9144, and their polydispersity indexes are between 1.02 and 2.15. All the copolymers show good thermal stability with the temperatures higher than 305.86 C when losing 10% weight under nitrogen. The cyclic voltammetry (CV) measurement and the electrochemical band gaps (Eg) of these copolymers are found below 2.00 ev.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial