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

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

Petrophysical properties evaluation from well log analysis has always been crucial for the identification and assessment of hydrocarbon bearing zones. East Baghdad field is located 10 km east of Baghdad city, where the southern area includes the two southern portions of the field, Khasib formation is the main reservoir of East Baghdad oil field.

In this paper, well log data of nine wells have been environmentally corrected, where the corrected data used to determine lithology, shale volume, porosity, and water saturation. Lithology identified by two methods; neutron-density and M-N matrix plots, while the shale volume estimated by single shale indicator and dual shale indicator, The porosity is calculated from the three common po

Objective: To evaluate the psychological work environment's effect on the workers’ productivity in Baghdad
City industries at Al-Rusafa and Al-Karkh Sectors.
Methodology: A descriptive evaluation design is employed throughout the present study from May 25th 2012
through January 7
th
, 2014. A purposive (non probability) sample is selected for the study which includes (500)
workers from industries at AL-Russafa and AL-Kerch sectors in Baghdad City. A questionnaire is constructed to
gather data which may assist to achieve the objective of the study. Content validity of the instrument is
determined through eliciting the opinions of a panel of (10) experts and the reliability through a pilot study by
using intern

Sewage sludge samples were collected from Al-rasafa and Al-karkh refinement stations which represent the main stations of Baghdad city. Samples were collected from all treatment stages: before, after, and during refinement processes. The High Purity Germanium Coaxial Detector system with energy resolution 1.8 keV for energy line 1333 keV of Co – 60 radioactive sources was used to measure radioactivity from both natural and artificial sources. GENIE – 2000 analysis the results statistically and qualitatively. The results showed that all sewage sludge samples exhibited natural radioactive level and sometimes less than the international regular standards, but Al–Karkh station showed increment in radioactive levels than Al– Rasa

Back ground: One out of six children in the
world today is involved in child labor, doing
work that is damaging to his or her mental,
physical and emotional development.
Objective: Assessment of some health
problems among the studied working children.
Method; A cross-sectional study was
conducted in Al Amen Primary Health Care
(PHCC) during the period from January to
August 2009, a sample of 6048 children were
selected randomly(3218girls and2866 boys age
between 5-17 years ) and interviewed to collect
information using a structured questionnaire
form, information related to different aspects
of child labor prevention were included in the
form as well as a general medical examination
and lab

Objectives : The study aims to assessing nurses’ knowledge concerning peritonitis- dialysis association at the
peritoneal dialysis units, and to identifying the relationship between some nurses’ knowledge and some of their
demographic characteristic.
Methodology : A descriptive study was carried out at the peritoneal dialysis units in Baghdad Teaching
Hospitals started from November 29th 2004 to August 15th, 2005. A purposive sample of (52) nurses was
selected from Baghdad Teaching Hospitals. The data were collected through the use of constructed
questionnaire, which comprised of (97) items as an interview questionnaire technique as mean of data
collection. The reliability of the instrument was determined through