This study is attempt to improve thermal isolation through measuring thermal conductivity composite of on polyester resin with fillers of (TiO2, ZnO, Acrylonitril, wood flour Coconut (Wf). The grain size of the fillers is 200 µm. The number of samples is (16) in addition to the virgin sample; these samples are prepared by cast molding method for polyester with filler volume fractions (5%, 10%, 15% and 20%). Shore hardness tests were used to measure the hardness and Lee disk method for thermal conductivity. The experimental results showed that the (20% ZnO) sample has the maximum value of thermal conductivity where (20% w.f) has minimum thermal conductivity .on the other hand (15% ZnO) sample give the maximum value of hardness where (20% w

The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods. 

The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Hyperthyroidism refers to overactive of thyroid gland leading to excessive synthesis of thyroid hormones and accelerated metabolism in the peripheral tissue. Objective: The aim of this study is to evaluate a new member of the IL-1 super family of cytokines interleukin-33(IL-33) levels in serum .in order to evaluate its utility as clinical bio marker of autoimmune disease (i.e. hyperthyroidism) Methods: The present study was conducted on 30 patients from the Iraqi female patients with hyperthyroidism attending Baghdad teaching hospital, in addition to 30 healthy controls. All subjects were (35-65) years old. Parameters measured in the sera of patients and healthy groups, were interleukin -33 (IL-33), Thyroxin (T4), Thyroxin (T3)

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Abstract

Anaerobic digestion process of organic materials is biochemical decomposition process done by two types of digestion bacteria in the absence of oxygen resulting in the biogas production, which is produced as a waste product of digestion. The first type of bacteria is known as acidogenic which converts organic waste to fatty acids. The second type of bacteria is called methane creators or methanogenic which transforms the fatty acids to biogas (CH₄ and CO₂). The considerable amounts of biodegradable constitutes such as carbohydrates, lipids and proteins present in the microalgae biomass make it a suitable substrate for the anaerobic digestion or even c

Anew Schiff base (NaHL) has been prepared from the reaction between the salt of amino acid glycine with 2-hydroxy naphthaldehyde. By tridentate Schiff base of (ONO), donors were characterized by using U.V and spectrophotometer techniques. Complexes of Co(II) Ni(II) Cu(II) and Zn(II) ion with the ligand have been prepared, these complexes were identified by infrared, electronic spectral data, elemental analysis, magnetic moments, and molar conductivity measurements. It is concluded from the elemental analysis that all the complexes have (1:2) [metal:ligand] molar ratios, octahedral, with the exception to Zn(II) complex which have (1:1)[metal:ligand] molar ratio.