The research amid to find out the extent of Iraqi oil companies commitment to implement internal control procedures in accordance with the updated COSO framework. As the research problem was represented in the fact that many of the internal control procedures applied in the Iraqi oil companies are incompatible with most modern international frameworks for internal control, including the integrated COSO framework, issued by the Committee of Sponsoring Organizations of the Tradeway Committee. The research followed the quantitative approach to handling and analysing data by designing a checklist to represent the research tool for collecting data. The study population was represented in the Iraqi oil companies, while the study sample

       Iraq is one of the most important countries in the world that has received its share of terrorist acts by the terrorist organization the Islamic State of Iraq and al-Sham (ISIS), which has caused instability, especially during the period of ISIS's control of seven Iraqi provinces (2014-2017). This stage has caused a decline in the levels of human and economic development and its inconsistency with the capabilities and needs of the Iraqi population. Therefore, this study aims to investigate the hypothesis that there is a close relationship between the decline in development in Iraq and the brutal practices of ISIS that it committed during his period of control over many Iraqi cities and regions. This study used several method

Background: Large amounts of oily wastewater and its derivatives are discharged annually from several industries to the environment. Objective: The present study aims to investigate the ability to remove oil content and turbidity from real oily wastewater discharged from the wet oil's unit (West Qurna 1-Crude Oil Location/ Basra-Iraq) by using an innovated electrocoagulation reactor containing concentric aluminum tubes in a monopolar mode. Methods: The influences of the operational variables (current density (1.77-7.07 mA/cm2) and electrolysis time (10-40 min)) were studied using response surface methodology (RSM) and Minitab-17 statistical program. The agitation speed was taken as 200 rpm. Energy and electrodes consumption had been studi

Rapid increase in the use of smart mobile phones and the proliferation of social media networking programs such as facebook, tweeter, whatsapp and viber etc. affects the learning attitude of second language. This research aims to investigate the effects of emoticons provided by Viber application on Iraqi students in context of vocabulary acquisition. 60 Iraqi students are randomly selected from X international school with the average of age 7 to 9 years. All the subjects are given 50 English words for five weeks, 25 English words were written on papers and the rest Viber stickers laden with English words. The results show that students recognize the vocabularies given by Viber stickers better than the written vocabulary. In general, student

African-American writers during the 19th century wrote in the shadow of the prominent romance, sentimental, and domestic fiction. Harriet Wilson’s Our Nig (1859) reflects an “alternative social character”, for the female protagonist suffers racism in the free North, because she is a mulatto child. Through depicting the life of free blacks, who supposedly lives a better life than Southern slaves, Wilson exposes how she has actually lived and sensed life in antebellum America. According to Raymond Williams (2011), there are two kinds of literary writings. The first represents the general tendency of the age, and he calls it “dominant social character”; representing the majority content of both the public writing and speaking. But, a

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

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Jurisprudence of Imam women through Susan Book of blood money