During the period 1970-2006 the Marshes-land region was exposed to several change into many sides of vanishing steeling and growth as follow :
1- Drying this region after 1991,and re-flooded again during 2003. Many other large Marsh-land, like al-Hawaisa was dried by cutting off inlet-water fed from Iran sources .As asqunance there are transferred to different kinds of swamps ,followed by major change in the structure of the region as the rural settlement concerned. Rural settlement in this area starts new push of migration. The research did not take that in consideration in this thesis because some others took it in details in some thesis and researches. The situation of Marsh-land is getting anew face after those major changes which need an urgent action to over-come this issue . In this thesis the researcher focus on finding the relative important of variable affect those changes of rural settlement in the study area . Settlement this region was a parted tow kind :First settlement flooded big Marsh-land water while the second group of settlements found on the off shore of marsh-land .Beside that a remarkable change in (the second group).
Socio economic and environmental factors distinguished between the two groups which attract rural settlement of in the flooded area of Marsh-land were translated gradually to the second group ( on the off shore side ) . Both of those group were utile the advantage of the second group of settlement (off shore group ) were attracting the other sectored in the floodedarea for many reason :ie : Saw shore economic and environmental condition plus the high precipitins of all kind of serves, social and technical infrastructure . Researcher adept descriptive and quantities analysis for all variable collected by questioner for selective sample of household with personal interview and inventory. The thesis found very remarkable circulation and recommendation relatively given to
This research aims to identify the cognitive distortion of kindergarten children and its relationship to their parenting reinforcement. The researcher used the descriptive approach, being the closest to reaching the study objectives, To measure the relationship between the research variables, the researcher prepared two questionnaire tools for this purpose, the first for measuring "cognitive distortion", And the second is to measure "parental reinforcement", and each tool consisted of (20) items.
After ensuring the validity and reliability of the two research tools and their suitabi
... Show MoreThe possibility of using zero-valent iron as permeable reactive barrier in removing lead from a contaminated groundwater was investigated. In the batch tests, the effects of many parameters such as contact time between adsorbate and adsorbent (0-240 min), initial pH of the solution (4-8), sorbent dosage (1-12 g/100 mL), initial metal concentration (50-250 mg/L), and agitation speed
(0-250 rpm) were studied. The results proved that the best values of these parameters achieve the maximum removal efficiency of Pb+2 (=97%) were 2 hr, 5, 5 g/100 mL, 50 mg/L and 200 rpm respectively. The sorption data of Pb+2 ions on the zero-valent iron have been performed well by Langmuir isotherm model in compared with Freundlich model under the studied
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The aim of this research work is to study the effect of stabilizing gypseous soil, which covers
vast areas in the middle, west and south parts of Iraq, using liquid asphalt on its strength properties
to be used as a base course layer replacing the traditional materials of coarse aggregate and broken
stones which are scarce at economical prices and hauling distances.
Gypseous soil brought from Al-Ramadi City, west of Iraq, with gypsum content of 66.65%,
medium curing cutback asphalt (MC-30), and hydrated lime are used in this study.
The conducted tests on untreated and treated gypseous soil with different percentages of medium
curing cutback asphalt (MC-30), water, and lime were: unconfined compression strength, and o
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In this work Nano crystalline (Cu2S) thin films pure and doped 3% Al with a thickness of 400±20 nm was precipitated by thermic steaming technicality on glass substrate beneath a vacuum of ~ 2 × 10− 6 mbar at R.T to survey the influence of doping and annealing after doping at 573 K for one hour on its structural, electrical and visual properties. Structural properties of these movies are attainment using X-ray variation (XRD) which showed Cu2S phase with polycrystalline in nature and forming hexagonal temple ,with the distinguish trend along the (220) grade, varying crystallites size from (42.1-62.06) nm after doping and annealing. AFM investigations of these films show that increase average grain size from 105.05 nm to 146.54 nm
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FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6
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Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area. The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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