The city of Karbala is one of the most important holy places for visitors and pilgrims from the Islamic faith, especially through the Arabian visit, when crowds of millions gather to commemorate the martyrdom of Imam Hussein. Offering services and medical treatments during this time is very important, especially when the crowds head to their destination (the holy shrine of Imam Hussein (a.s)). In recent years, the Arba'in visit has witnessed an obvious growth in the number of participants. The biggest challenge is the health risks, and the preventive measures for both organizers and visitors. Researchers identified various challenges and factors to facilitating the Arba'in visit. The purpose of this research is to deal with the religious an

The study aims to examine the estimation of a sample of Palestinian University students in Gaza governorate to the contribution of teaching human sciences in their political education. It further aims to reveal whether there are statistically significant differences at a significance level (α≤ 0.05) between the averages of the sample. Such differences might be attributed to the following variables: sex, residential area, specialization. To achieve this, the researcher used the descriptive approach by applying a tool of (50) items on (618) randomly chosen male and female students from the largest Palestinian universities in the governorates of Gaza. Results have shown that: the overall degree of estimation to the contribution of teachi

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Today, there are large amounts of geospatial data available on the web such as Google Map (GM), OpenStreetMap (OSM), Flickr service, Wikimapia and others. All of these services called open source geospatial data. Geospatial data from different sources often has variable accuracy due to different data collection methods; therefore data accuracy may not meet the user requirement in varying organization. This paper aims to develop a tool to assess the quality of GM data by comparing it with formal data such as spatial data from Mayoralty of Baghdad (MB). This tool developed by Visual Basic language, and validated on two different study areas in Baghdad / Iraq (Al-Karada and Al- Kadhumiyah). The positional accuracy was asses

This study aimed to identify the changes in total protein in saliva and sera samples of patients with oral squamous cell carcinoma in comparison to those of healthy controls. These changes were followed using electrophoresis (PAGE). Meanwhile, determinations of albumin, globulin and albumin to globulin ratio were carried out on sera samples only.Two groups were the participants in the present study, 18 patients with Oral Squamous Cell Carcinoma (OSCC), and 20 ages and gender matched healthy controls.

Giant Cell Fibroma (GCF) is a relatively rare oral mucosal lesion, so named due to the characteristic giant cells present within the fibrous stroma of the lesion, limited number of clinicopathological studies were performed in previously published literature. This study was performed to evaluate the clinicopathological features of Giant cell fibroma in a sample of Iraqi patients. Formalin-fixed paraffin-embedded sections from 22 giant cell fibroma in period between 2010 and 2018 were retrieved from the laboratory of oral pathology of Baghdad University/College of Dentistry, Clinical data and microscopic features were reviewed and analyzed according to the available surgical reports. The mean age of patients at the time of diagnosis was 29.6

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,