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Odontogenic Keratocyst

Purpose: to review in detail various aspects of odontogenic keratocyst, emphasizing recent nomenclature, clinical, histopathological, recurrence, and management of odontogenic keratocyst.

Methods: To achieve the objective of this review, a manual search was done in hard copy books of oral and maxillofacial pathology, and an electronic search was done in the google website, oral and maxillofacial pathology E-books, virtual database sites, such as PubMed, Research Gate, Academia, and Google scholar using the descriptors: odontogenic cyst, kerato odontogenic tumor, odontogenic keratocyst, and jaws cystic lesion. The eligibility criteria for selecting articles were: to be in the English language, studies published in journals, or indexed in these databases until 2021. Exclusion criteria were: articles in any languages other than English, studies presented in duplicate between the bases, whose theme did not contemplate the objective proposed in this review, or those not available in the digital environment. Data collection occurred from October to December 2020, followed by a thorough evaluation of the studies found, including an exploratory, selective, analytical, and interpretative reading.

Summary and conclusions: the odontogenic keratocyst is noteworthy because of its unusual growth pattern, the tendency to recur, and association with an inherited syndrome. The renaming of odontogenic keratocysts as keratocystic odontogenic tumors has been one of the most debatable changes in the terminology of odontogenic lesions in recent years. Early diagnose of this lesion is important to perform the more conservative treatment. A wait-and-see policy, with yearly follow-up for the first five years and every two years after that, is strongly advocated.

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Taxonomical and Anatomical Study of the Species Nonea echioides (L.) Roem. & Sehult (Boraginceae) in Northern Iraq

The present study deals with some morphological and anatomical characteristics of the Nonea echioides(L.) Roem. & Sehult species belonging to Boraginaceae, which is recorded to have spread recently in Kurdistan region of Iraq.

This research focused on some of the important morphological characteristics of the stems, leaves, flowers, and fruits and comparing them with other studies of neighboring countries to Iraq. These morphological characteristics were found to be important in isolating the species of the filed. The anatomical features of the epidermis, stomata, and trichomes were also investigated. The study shows that Nonea echioides belongs to C3 plants based on the anatomical featur

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Publication Date
Sun Jan 26 2020
Journal Name
Iraqi Journal Of Science
New Updated Classification of Shallow Earthquakes Based on Faulting Style

Earthquakes occur on faults and create new faults. They also occur on  normal, reverse and strike-slip faults. The aim of this work is to suggest a new unified classification of Shallow depth earthquakes based on the faulting styles, and to characterize each class. The characterization criteria include the maximum magnitude, focal depth, b-constant value, return period and relations between magnitude, focal depth and dip of fault plane. Global Centroid Moment Tensor (GCMT) catalog is the source of the used data. This catalog covers the period from Jan.1976 to Dec. 2017. We selected only the shallow (depth less than 70kms) pure, normal, strike-slip and reverse earthquakes (magnitude ≥ 5) and excluded the oblique earthquakes. Th

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Feature Extraction Using Remote Sensing Images

Feature extraction provide a quick process for extracting object from remote sensing data (images) saving time to urban planner or GIS user from digitizing hundreds of time by hand. In the present work manual, rule based, and classification methods have been applied. And using an object- based approach to classify imagery. From the result, we obtained that each method is suitable for extraction depending on the properties of the object, for example, manual method is convenient for object, which is clear, and have sufficient area, also choosing scale and merge level have significant effect on the classification process and the accuracy of object extraction. Also from the results the rule-based method is more suitable method for extracting

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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.

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
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Satellite image classification using proposed singular value decomposition method

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
A Proposed Background Modeling Algorithm for Moving Object Detection Using Statistical Measures

Extracting moving object from video sequence is one of the most important steps
in the video-based analysis. Background subtraction is the most commonly used
moving object detection methods in video, in which the extracted object will be
feed to a higher-level process ( i.e. object localization, object tracking ).
The main requirement of background subtraction method is to construct a
stationary background model and then to compare every new coming frame with it
in order to detect the moving object.
Relied on the supposition that the background occurs with the higher appearance
frequency, a proposed background reconstruction algorithm has been presented
based on pixel intensity classification ( PIC ) approach.

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Satellite Images Classification in Rural Areas Based on Fractal Dimension

Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Obese Women and Choosing Ready-made Clothes: Difficulties and Choices

Thisstudy aims to determine the specifications of obese women accordingto the heightand type of obesity. It also aimstoidentify the significance of differences in choosing ready-made clothes for the research sample. Finally, the significance of differences in choosing ready-made clothes according to the variable of binaryclassification ofobesity is also identified.The study sample includes obese women: employees, non-employees and students with the age group (18-50) years.The weights and lengths of the sample have been taken to suit the group of obese women.Aquestionnaire in the form of an open question was distributed among (50) obese womenso as to extract the items of the questionnaire. After that, the questionnaire was distributed amo

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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

     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
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Monitoring Vegetation Area in Baghdad Using Normalized Difference Vegetation Index

       Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a low v

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