One of the major problems facing the road construction engineer is the collapsible granular soil which may be used for embankment construction. Problems appears when such compacted soil come in touch with water, it exhibits cracking and uncontrolled settlement. Collapsible soils are defined as any unsaturated soil that goes through a radical rearrangement of practice and great loss of volume upon wetting, with or without additional loading. An attempt has been made in this investigation to stabilize the collapsible soil of Nasiriya with asphalt emulsion. Specimens of pure and asphalt emulsion stabilized soil have been prepared using optimum fluid content and tested. The first group of specimens of (60x60x20) cm have been tested for direct s

Background: Automobile spray painting is considered an occupation with a high risk of respiratory impairment and asthma. Exposure to organic solvents used for spraying might be of high risk for development of dysfunction in other organs.
Objective: The study was designed to evaluate the pulmonary and hepatic toxicity due to exposure of automobile painters to organic solvents in work places within the Baghdad governorate area.
Methods: Thirty cross sectional selected male workers employed in automobile body paint shops in two industrial areas within Baghdad city (Al-Sheikh Omar and Al-Rasheed camp regions) were recruited to the study during the period from March to May 2012. Thirty non-exposed students and employees in the college o

The typical test for diagnosis of severe acute respiratory syndrome coronavirus 2 is a reverse transcription-polymerase chain reaction (RT-PCR) technique, but the chest CT scan might play a complementary role at the first detection of Coronavirus Disease 2019 (COVID-19) pneumonia. Objectives: To determine the sensitivity of CT scan on patients with COVID-19 in Al-Najaf, Iraq, and to compare the accuracy of CT scan with that of RT-PCR technique. Material and Method: This is a prospective study. The patients suspicious of having COVID-19 infection and respiratory symptoms were registered. All patients were diagnosed by RT-PCR and chest CT. Diagnostic performance of CT was intended using RT-PCR as the reference sta

Objectives:
To evaluate mothers’ attitudes toward readiness for discharge care at home for a premature baby in Intensive Care Unit at teaching hospitals in Medical City Complex and to find out the relationship between mothers’ attitudes and their socio-demographic characteristics.
Methodology: A quasi-experimental study design was carried out through the period of 6th January 2020 to 2021 to 11th March 2021, to evaluate mother’s attitude toward discharge care plan for premature babies. The study carried out in Welfare Teaching Hospital, Nursing Home Hospital and Baghdad Teaching Hospital at Medical City Complex in Baghdad City on 30 mother of premature babies in neonatal intensive care units using the nonprobability sampling

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Background: Nutrition can affect the development and integrity of the oral cavity as well as the progression of oral diseases such as dental caries which was the most predominant and wide spread not life threatening human diseases especially in developing countries as in Iraq. This study was conducted to assess the occurrence, prevalence and severity of dental caries condition and their relations to nutritional status among intermediate schools females in Al-Najaf city in Iraq. Materials and methods: This study was conducted among intermediate schools females aged 13, 14 and15 years old and the total sample consisted of 754 students. The assessment of nutritional status was performed using body mass index (BMI) following Centers for Diseas

Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give