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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 Sep 30 2022
Journal Name
Iraqi Journal Of Science
Survey of Some Heavy Metals and Radioactivity in the Dust in A Selected Area in Kirkuk Governorate- Northern Iraq
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      Air pollution means the release of pollutants into the atmosphere, which are harmful to human health and the planet as a whole. Almost all air pollutants come from production and energy use. In the present work, an assessment of some heavy metals, natural radioactivity and the quantity of dust fallen in three sites (Tessen, Rahemawa, and Laylan) in Kirkuk Governorate, northern Iraq. Three dust samples were collected from three locations (residential, commercial and industrial areas). The collected samples were analyzed for Cd, Cr, Cu, Ni, Pb, Zn, and radioactivity (Gamma rays). The studied heavy metals (Fe, Ni, Pb, and Zn) exceeded their limits in the atmosphere due to the increase in the number of automobiles, which

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Publication Date
Tue Jan 10 2017
Journal Name
Assiut J. Agric. Sci.
The response of white eggplant plants to foliar application with boron and potassium silicate
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Publication Date
Thu Aug 30 2018
Journal Name
Iraqi Journal Of Science
Study the Effect of Some Methanolic and Aqueous Traditional Plants Extracts on Probiotic Bacteria
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Probiotics mean live microorganisms that have beneficial effects on their host’s health. The purpose of this study was to compare aqueous, methanolic of some traditional plant extracts on the viability of dietary probiotic supplementation [a dietary probiotic (Protexin)]. Also, this study was conducted to evaluate the antibacterial effect of various extracts concentrations from 1.25 to 100 mg/ml of Rosmarinus officinal, Glycyrchiza glabra, Hibiscus sabdriffo, Curcuma longa, Citrus auratifolia swingle, Cinnamomum zeylancium, Urtica dioica, Thymus vulgaris, Punica grantum and Zingiber officinal on activities of probiotic bacteria Lactobacillus, Bifidobacterium, Streptococcus thermophillus by determining the minimum inhibitory co

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Science
Classification of Iraqi Anber Rice by Using Image Processing and KNN Algorithm
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Image classification takes a large area in computer vision in term of quality or type or data sharing and so on Iraqi Anber Rice in they need this kind of work, where few in the field of computer science that deal with the types of Iraqi Anber rice, and because of the Anber Rice are grown and produced in Iraq only, and because of the importance of rice around the world and especially in Iraq. In this paper a proposed system distinguishes between the classes of Iraqi Anber Rice that Grown in different parts of Iraq, and have their own specifications for each class by using moment invariant and KNN algorithm. Iraqi Anber Rice that is more than Fiftieth class Cultivated and irrigated in different parts of Iraq, and because of the different

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Publication Date
Tue May 16 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets
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Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Diagnosis and Classification of Type II Diabetes based on Multilayer Neural Network
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     Diabetes is considered by the World Health Organization (WHO) as a main health problem globally. In recent years, the incidence of Type II diabetes mellitus was increased significantly due to metabolic disorders caused by malfunction in insulin secretion. It might result in various diseases, such as kidney failure, stroke, heart attacks, nerve damage, and damage in eye retina. Therefore, early diagnosis and classification of Type II diabetes is significant to help physician assessments.

The proposed model is based on Multilayer Neural Network using a dataset of Iraqi diabetes patients obtained from the Specialized Center for Endocrine Glands and Diabetes Diseases. The investigation includes 282 samples, o

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
An Automated Classification of Mammals and Reptiles Animal Classes Using Deep Learning
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Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

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Publication Date
Mon Apr 10 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Evaluation of Antibacterial Activity of Ethanolic Extracts for Three Local Plants
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There is an increasing interest in the use of plant extracts as therapeutic agents, particularly their capacity to inhibit the growth of pathogenic microorganisms. In this study antibacterial effect of Malva sylvestris, Anastatica hierochuntica and Vitis vinifera leaves extracts were evaluated against Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus and Proteus mirabilis. The in vitro antibacterial activity was performed using agar well diffusion method and the minimum inhibitory concentration (MIC) was determined by microtitration technique. The result indicated that the extract of V. vinifera leaves inhibited with the growth of gram-positive bacteria, as well as gram-negative bacteria while the extract

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
The Use of Aquatic Plants in Sewage Treatment/ Using Lily of the Nile in the City of Mosul
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The sewage water is the main sources of pollution for the Tigris river for that reason this study was done,The ability of nature treatment were examined along the path of alkarazi valley which was covered with reed plant also the phytoremidation were examined at the establish unit(surface flow system) which was vegetative with the plant Eichhornia crassipes .The result shows that elements which can be removed by precipitation efficiency removal like turbidity where its removal percentage at the unit of treatment reached 95.2 %where the percentage of removal through the Alkarazi was 50.4%.The removal percentage of E.coli at the unit was 90.2% where the percentage of removal through the Alkarazi was 52%.The biological oxygen demand removal

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