Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Some major pollutants of polycyclic aromatic hydrocarbons (PAH) those discharged as water produced (WP) from the AlAhdab oil field (AOF) in the ponds close to it may leak to the water resources around and eventually reaches the marshes which will affect its ecosystem. Thus, this work aims to track the availability of PAH in the water resources and the Main Outfall Drain (MOD) nearby. The determination of PAH was evaluated using “High-Performance Liquid Chromatography (HPLC)”. The mean concentration of sixteen PAH in the produced water within the field was relatively high (0.01 to 10.89 g/ml) with standard deviations of (0.10.9). While, PAH outside the field were gradually diminishes down to (0.01-0.039) x10-2 g/ml which exceeds th

Based on collections made during March to September 2012. A totals of 58 species belong to 33 genera were identified from extra north to extra south of Erbil governorate, among them 30 species are registered as a new record to flora of Iraq. Most attention was paid to the most common and abundant lichens that present almost in most locations, which were Collema cristatum, Diploschistes scruposus, Lecanora dispersa, Lecanora murales, Pertusaria flavicunda, Placidium lacinulatum, Thelomma californicum and Verrucaria Maura.

Bacterial contamination of AL-Habania reservoir was studied during the period from February 2005 to January 2006; samples were collected from four stations (AL-Warrar, AL-Theban regulator, middle of the reservoir and the fourth was towards AL-Razzaza reservoir). Coliform bacteria, faecal Coliforms, Streptococci, and faecal Streptococci were used as parameters of bacterial contamination in waters through calculating the most probable number. Highest count of Coliform bacteria (1500 cell/100ml) was recorded at AL-Razaza during August, and the lowest count was less than (300 cell/100ml) in the rest of the collection stations for all months. Fecal Coliform bacteria ranged between less than 300 cells/100ml in all stations for all months to 700 c

Tax is an important financial resource that the state depends on in all its economic, political, and social fields. Nevertheless, the role of the tax is highlighted in raising tax revenues and influencing economic variables, such as savings, consumption, investment, and employment. The tax was taken as an important tool to stimulate investment in industrial projects because of this activity's important role in raising the efficiency of economic development and reviving the national economy, as many industrial investment laws were enacted and the most important thing included was exempting industrial projects from all taxes and fees (5-10) years, and an exemption Profits from income tax for a period of 5 years starting from the year in which

The purpose of research is highlighting the role of tax expenses in promoting direct foreign investment in Iraq, The main objective of the increase in the field of tax expenses is to manage the competition in the production of goods and services locally, in addition to the various qualities of the economical. As the search contributes to the idea of the role of the policy of the tax expenses in the promotion of foreign companies operating in Iraq. The analytical and transparent transparency used by adoption of cases of the relevant body of the tax body. For each image or form of tax expenses have been reliably related to the promotion of direct foreign investment, the taxpayers highlighted the annual controls, tax cuts as the sample was