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Distribution and Classification of Medicinal Plants in Zakhikhah Area of Al-Anbar Desert
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This study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in the study area at all stages were recorded. The reasons for the variation in the distribution of medicinal plants in the Zakhikhah area were also presented in this study concerning their distribution sites. The total number of species collected in all stages, according to the findings of this study, was 12. The most abundant plant was the hibiscus, which accounted for 35.40% of the total area and covered 4210.8 acres. The samples were identified, named, and preserved in the University of Anbar’s College of Education for Pure Sciences/Department of Life Sciences herbarium. How to Cite: Fatin H. Al-Dulaimi, 2023. "Distribution and Classification of Medicinal Plants in Zakhikhah Area of Al-Anbar Desert." Journal of Agriculture and Crops, vol. 9, pp. 257-265.

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Publication Date
Fri Oct 22 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
4D Finite element modeling of stress distribution in depleted reservoir of south Iraq oilfield
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Abstract<p>The harvest of hydrocarbon from the depleted reservoir is crucial during field development. Therefore, drilling operations in the depleted reservoir faced several problems like partial and total lost circulation. Continuing production without an active water drive or water injection to support reservoir pressure will decrease the pore and fracture pressure. Moreover, this depletion will affect the distribution of stress and change the mud weight window. This study focused on vertical stress, maximum and minimum horizontal stress redistributions in the depleted reservoirs due to decreases in pore pressure and, consequently, the effect on the mud weight window. 1D and 4D robust geomechanical models are</p> ... Show More
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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
Geographical distribution of the potato crop in the district of Abo – Ghraib, 2005- 2011
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Source of energy and protein Field crops considered an important needed for human
beings Due of this fact increases should appear in the quantities of their production in order to
meet the needs of continuous increasing in the population of the glope year after year ;
otherwise, an increase in the gap between the amount of production and consumption will
occur .
This study aims to reveal the geographical distribution of the potato crop in the district
of Abu – Ghraib. For this purpose, a study conducted about the cultivated areas, production
and crop yields per Dunam for period of 7 years lasted from 2005-2011.
The study shows that potato is one of the most important field crops that are grown in
the Abu –

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Tue Jan 01 2008
Journal Name
University Of Baghdad
The use of remote sensing to study the reflection of the ground cover and its relationship to some soil characteristics in the Abi Gharib area
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Publication Date
Thu Feb 02 2012
Journal Name
Education College Journal/al-mustansiriyah University
On Significance Testimator in Pareto Distribution Via Shrinkage Technique
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In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering
Salt Distribution in a Soil Irrigated by Subsurface Emitter
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The best design of subsurface trickle irrigation systems requires knowledge of water and salt distribution patterns around the emitters that match the root extraction and minimize water losses. The transient distribution of water and salt in a two-dimensional homogeneous Iraqi soil domain under subsurface trickle irrigation with different settings of an emitter is investigated numerically using 2D-HYDRUS software. Three types of Iraqi soil were selected. The effect of altering different values of water application rate and initial soil water content was investigated in the developed model. The coefficient of correlation (R2) and the root-mean-square error (RMSE) was used to validate the predicted numerical res

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Publication Date
Sat Dec 01 2018
Journal Name
Baghdad Science Journal
Seasonal variation and modeling of disinfection by-products (DBPs) in drinking water distribution systems of Wassit Province Southeast Iraq
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Publication Date
Mon Oct 21 2024
Journal Name
Iraqi Statisticians Journal
On Inference of Finite Mixture of Rayleigh Distribution by Gibbs Sampler and Metropolis-Hastings
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Inferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixt

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