Translation is a vital process that needs much more understanding and mutual background knowledge on the part of ESL or EFL learners in terms of grammar , meaning and context of both the SL and TL . Thus , the main aim of the current research paper is to identify and figure out the techniques used by ESL or EFL learners when translating English barnyard verbs into Arabic . The main problem of this study is attributed to the fact that ESL or EFL learners may not be able to identify and understand the connotative meaning of barnyard verbs since these verbs are onomatopoeic (i.e,) a word that phonetically imitates, or suggests the source of sound that it describes. Therefore they may be unable to translate these verbs appropriately and accura

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

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

Background: Ultrasonography has been used to examine the thickness of the lower uterine segment in women with previous cesarean sections in an attempt to predict the risk of scar dehiscence during subsequent pregnancy. The predictive value of such measurement has not been adequately assessed. Objectives: To correlate lower uterine segment thickness measured by trans abdominal ultrasound in pregnant women with previous cesarean section with that measured during cesarean section by caliper and to find out minimum lower uterine segment thickness indicative of integrity of the scar.Methods: A prospective observational study at Elwyia Maternity Teaching Hospital, from January 2011 to January 2012. A total of 143 women were enrolled in the stu

Background: Strangles is a highly contagious equine respiratory disease caused by Streptococcus equi subsp. equi. It is a globally significant pathogen and one of the most common infectious agents in horses. In Iraq, no sequencing data on this pathogen are available, and only two molecular studies have been published to date. This study provides preliminary insights into strain diversity and provides a foundation for future large-scale investigations. Aim: This study aimed to investigate the molecular characteristics, identify SeM gene alleles, and perform a phylogenetic analysis of S. equi isolates from horses in Baghdad, Iraq. Methods: We analyzed 59 Streptococcus spp. isolates previously obtained from equine clinical sample

The gas sensing properties of Co3O4and Co3O4:Y nano structures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for Co3O4and Co3O4:Y thin films. XRD analysis shows that all films are polycrystalline in nature, having a cubic structure, and the crystallite size is (11.7)nm for cobalt oxide and (9.3)nm for the Co3O4:10%Y. The SEM analysis of thin films obviously indicates that Co3O4possesses a nanosphere-like structure and a flower-like structure for Co3O4:Y.The sensitivity, response time and recovery time to a H2S reducing gas were tested at different operating