Um-Al-Naaj region in Al-Hawiezah Marsh, Southern Iraq was chosen to study the environmental variations of some water characteristics during 2008, seasonally. The results showed clear seasonal changes in values of some environmental variables (temperature, depth, light penetration, turbidity, total suspended solids, pH, dissolved oxygen, reactive phosphate, reactive nitrite, and reactive nitrate), while there were no clear seasonal changes in electrical conductivity and salinity values. In addition, high nutrients concentrations and light penetration were noted. Statistical analysis showed significant positive relationship between air and water temperature; electrical conductivity and salinity. Water turbidity was significantly affecte

Background; paraphilias were studied in the sex
clinic, at Al-Rashad teaching mental hospital, in the
years 2009-2010, a subject never touched before in the
field of psychiatry in Iraq.
Aims of the study :
1-to identify the prevalence of types and number of
paraphilias in those patients.
2-to study the relationship of paraphilias with
sociodemographic factors of the patients.
Patients and methods; using the diagnostic criteria of
DSM IV TR, 52 patients from the outpatient sex clinic
at Al-Rashad mental hospital, collected and studied (41
males and 11 females).
Results; the ratio of men to women was 3.7 : 1, the
majority of our sample was in the age range of 21-30
years (36.35%), with a limited

This study is directed at investigating the liquefaction potential within earth dams using numerical modelling by two-dimensional finite element analyses method for considering the Makhool earth dam on the Tigris River in Iraq. The effect of peak ground acceleration of 0.02g, 0.04g, 0.06g, and 0.08g is viewed for a shell, and the crest is presented for all scaled earthquake duration 25 s, 50 s, 75 s, and 100 s. The current study program comprises selecting a representative history point within the Makhool earth dam as a case study. Many points were allocated at different locations within the shell and crest to observe the fluctuation in the factor of safety against liquefaction. The seepage analysis results viewed graphically for the operat

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have