The importance of this topic may not be overlooked by many of the specialists, because it is one the sciences of the Arabic language, but it is an important method in the field of influencing the recipient and his aesthetic ability to create influential images as well.
The talking about Semantic (Badi'iyah)is as old as the Arabic age, so it may be talking about it not the new thing because the people who specialized have preceded us and exhausted all the talk .

Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement,

The research seeks to identify the impact of fraud detection skills in the settlement of compensatory claims for the fire and accident insurance portfolio and the reflection of these skills in preventing and reducing the payment of undue compensation to some who seek profit and enrichment at the expense of the insurance contract. And compensatory claims in the portfolio of fire and accident insurance in the two research companies, which show the effect and positive return of the detection skills and settlement of the compensation on the amount of actual compensation against the claims inflated by some of the insured, The research sample consisted of (70) respondents from a community size (85) individuals between the director and assistan

The new Hexadentate complexes type [M(H3L3)]K were prepared from the condensation reaction of Diphenylmonoxime and KOH with (Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II)) in methanol with 3:1 ligand : metal ratio to give a series of new complexes of the general formula [M(H3L3)]K (where: M(II) = Mn ,Co ,N ,Cu ,Zn and Hg).All compounds have been Characterized by spectroscopic methods [I.R, U.v-Vis, atomic absorption and microanalysis (C.H.N) along with conductivity measurements. The stability constant K and Gibbs free energy ∆G were calculated for [Co (H3L3)] K, [Ni (H3L3)] K and [Cu (H3L3)] K and complexes using spectrophotometer method. The obtained values indicate that these complexes stable in their solution. From the above data

Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The res

Due to its association with hepatocellular carcinoma and being one of the ten most common malignancies worldwide, hepatitis C viral infection has become a severe public health concern. Therefore, establishing an accurate, reliable and sensitive diagnostic test for this infection is strongly advised. Real-time polymerase chain reaction (PCR) has been created to achieve this purpose. The current study was established to investigate the hepatitis C virus among Iraqi patients with chronic renal failure and to detect the virus immunologically by the fourth generation enzyme-linked immunosorbent assay technique and molecularly by real-time PCR. As a result, out of 50 patients with chronic renal failure undergoing dialysis, 39 patients tes

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat