Groundwater can be assessed by studying water wells. This study was conducted in Al-Wafa District, Anbar Governorate, Iraq. The water samples were collected from 24 different wells in the study area, in January 2021. A laboratory examination of the samples was conducted. Geographical information systems technique was relied on to determine the values of polluting elements in the wells. The chemical elements that were measured were [cadmium, lead, cobalt and chromium]. The output of this research were planned to be spatial maps that show the distribution of the elements with respect to their concentrations. The results show a variation in the heavy elements concentrations at the studied area groundwater. The samples show different values

Seasonal variations of the species composition and abundance of Cladocera were studied in two stations at the end of the Tigris River and one station at the confluence of the Tigris with Euphrates area, at the beginning of the Shatt Al-Arab River in Al-Qurnah North of Basrah Province, from October 2015 to August 2016. Samples of zooplankton were collected by plankton net 100-µm. mesh size. The population density of Cladocera ranged between 1 Ind /m³ during summer and 211 Ind./m³ during winter at station 1 (Al-Jewaber Bridge). A total of 16 species of Cladocera belonging to 12 genera were recorded in the study. The average density of Cladocera ranged from 23.2 ind./m³ at Station 2 (Hamayon Bridge) to 53.7 Ind./m³

The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

Cloud computing (CC) is a fast-growing technology that offers computers, networking, and storage services that can be accessed and used over the internet. Cloud services save users money because they are pay-per-use, and they save time because they are on-demand and elastic, a unique aspect of cloud computing. However, several security issues must be addressed before users store data in the cloud. Because the user will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.), and will not know where the data is stored, the user must ensure that the cloud stores and maintains the outsourced data appropriately. The study's primary goals are to mak

Background: The study of human leukocytes (HLA) alleles, and haplotype frequencies within populations provide an important source of information for anthropological investigation, organ and hematopoietic stem cell transplantation as well as disease association, certain diseases showed association with specific alleles specially those of known or suspected hereditary origin or immunological basis, whether simple renal cyst is congenital or acquired is still unclear and need to be investigated.Objectives: To study the genetic aspect of simple renal cysts by detecting the gene frequency and the haplotype of HLA class I of patients with simple renal cysts, and to find the presence of these cysts in other family members.Method: Thirty patient

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.