The research aims to release the concept of auditing reporting and its role in the rationalization of economic decisions in the companies listed in the Iraq Stock Exchange from the viewpoint of academics, professionals, investors and lenders. Auditor reporting witnessed the great progress in many areas addressed many of the previous studies compare with Iraqi auditors reporting because there are some defects in these aria .The research problem focused whether the auditor report in Iraq is contains useful information to rationalize investment decisions & lending decisions in the shareholding companies listed on the Iraq Stock Exchange , and under that premise , " There is statistically significant relationship between the reporting au

This study aimed to evaluate oral health (OH) and periodontal diseases (PD) awareness in the Iraqi population.

This review delves deep into the intricate relationship between urban planning and flood risk management, tracing its historical trajectory and the evolution of methodologies over time. Traditionally, urban centers prioritized defensive measures, like dikes and levees, with an emphasis on immediate solutions over long-term resilience. These practices, though effective in the short term, often overlooked broader environmental implications and the necessity for holistic planning. However, as urban areas burgeoned and climate change introduced new challenges, there has been a marked shift in approach. Modern urban planning now emphasizes integrated blue-green infrastructure, aiming to harmonize human habitation with water cycles. Resil

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

The present study investigates deep eutectic solvents (DESs) as potential media for enzymatic hydrolysis. A series of ternary ammonium and phosphonium-based DESs were prepared at different molar ratios by mixing with aqueous glycerol (85%). The physicochemical properties including surface tension, conductivity, density, and viscosity were measured at a temperature range of 298.15 K – 363.15 K. The eutectic points were highly influenced by the variation of temperature. The eutectic point of the choline chloride: glycerol: water (ratio of 1: 2.55: 2.28) and methyltriphenylphosphonium bromide:glycerol:water (ratio of 1: 4.25: 3.75) is 213.4 K and 255.8 K, respectively. The stability of the lipase enzyme isolated from porcine pancreas (PPL) a

The purpose of this study was to examine the role of cortisol, and it is related to BMI in the chronic diseases which may increase early cardiovascular disease (CVD) in old Iraqi. The subjects were 116 adults, aged 51-71 years. Body Mass Index (BMI), Waist Circumferences (WC) and Waist Hip Ratio (WHR) were used as a measure of adiposity. Investigation showed highly significant difference between patients in BMI ranges, most of male were in an obese weight range (48.5%), as well in women. There were no significant correlations between serum cortisol concentration and age both gender groups. While there were highly significant correlations between cortisol level and BMI, waist, and WHR (except in female subjects), also there were highly signi

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a