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Sex Variations by Linear Measurements of Palatal Bones and Skull Base Using 3D Reconstructed Computed Tomographic Scan among Iraqi Sample
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Background: The skull base and the hard palate contain many anatomical features that make them rich in information which are useful in sex differentiation; in addition to that they have the ability to resist the hardest environmental conditions that support them in making sex differentiation. Three dimensional computed tomographic techniques has important role in differentiation between sex since it offers images with very accurate data and details of all anatomical structures with high resolution. This study was made to study sex variations among Iraqi sample by craniometric linear measurements of the hard palate and the skull base using 3D reconstructed Computed Tomographic scan. Materials and methods: This study composed of 100 Iraqi subjects (50 male and 50 female) aged between 20-59 years. The sample collected from patients attending Al-Shaheed Ghazi hospital in Baghdad city to for spiral CT scanner. The craniometrical linear measurements of the hard palate and the skull base in this study were including: Maxillo-Alveolar Breadth, Maxillo-Alveolar Length, the distance between incisive foramen and greater palatine foramen (right and left), the distance between the incisor foramen and B point (the median point located at the anterior area of the magnum foramen), the distance between the incisor foramen and the anterior root of the mastoid notch on both sides (right and left), Maxillo-Alveolar Index and size of Palate. All these measurements were done by (mm) unit. Results: The statistical analysis of linear measurements of the hard palate and the skull base showed that the mean values of all measurements were significantly higher in males than females except for Maxillo-Alveolar Index was not significant and also showed that the size of the palate was the best indicator for sex variation and making the diagnosis of male with accuracy 93.3%. The age had none significant effect on these measurements. Conclusion: Three dimensional Computed Tomographic scanners is the best diagnostic tool for sex variation by the craniometrical linear measurements for the anatomical landmarks points of the hard palate and the skull base.

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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Heterogeneously Catalyzed Esterification Reaction: Experimental and Modeling Using Langmuir- Hinshelwood Approach
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The esterification reaction of ethyl alcohol and acetic acid catalyzed by the ion exchange resin, Amberlyst 15, was investigated. The experimental study was implemented in an isothermal batch reactor. Catalyst loading, initial molar ratio, mixing time and temperature as being the most effective parameters, were extensively studied and discussed. A maximum final conversion of 75% was obtained at 70°C, acid to ethyl alcohol mole ratio of 1/2 and 10 g catalyst loading. Kinetic of the reaction was correlated with Langmuir-Hanshelwood model (LHM). The total rate constant and the adsorption equilibrium of water as a function of the temperature was calculated. The activation energies were found to be as 113876.9 and -49474.95 KJ per Kmol of ac

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Fri Oct 03 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced TEA Algorithm Performance using Affine Transformation and Chaotic Arnold Map
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In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

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Publication Date
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology &amp; Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Computer And Communications
Pathfinding in Strategy Games and Maze Solving Using A* Search Algorithm
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Publication Date
Wed Dec 12 2018
Journal Name
Iop Conference Series: Materials Science And Engineering
Preparation and characterization DLC thin films using atmospheric pressure plasma Jet
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Diamond-like carbon, amorphous hydrogenated films forms of carbon, were pretreated from cyclohexane (C6H12) liquid using plasma jet which operates with alternating voltage 7.5kv and frequency 28kHz. The plasma Separates molecules of cyclohexane and Transform it into carbon nanoparticles. The effect of argon flow rate (0.5, 1 and 1.5 L/min) on the optical and chemical bonding properties of the films were investigated. These films were characterized by UV-Visible spectrophotometer, X-ray diffractometer (XRD) Raman spectroscopy and scanning electron microscopy (SEM). The main absorption appears around 296, 299 and 309nm at the three flow rate of argon gas. The value of the optical energy gap is 3.37, 3.55 and 3.68 eV at a different flow rate o

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Publication Date
Sat Dec 01 2018
Journal Name
Fuel
Biodiesel from batch and continuous oleic acid esterification using zeolite catalysts
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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