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Satellite image classification using proposed singular value decomposition method
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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
water and hills are decreased, while vegetation, wet land and barren
land are increased for years 1999 and 2014; comparable with 1990.
The classification accuracy was done by number of random points
chosen on the study area in the field work and geographical data then
compared with the classification results, the classification accuracy for
the proposed SVD method are 92.5%, 84.5% and 90% for years
1990,1999,2014, respectivety, while the classification accuracies for
unsupervised classification method based mean value are 92%, 87%
and 91% for years 1990,1999,2014 respectivety.

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
Illumination - Invariant Facial Components Extraction Using Adaptive Contrast Enhancement Methods
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The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Fri May 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI images using region growing algorithm
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LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2

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Publication Date
Tue Apr 02 2024
Journal Name
Al-iraqia Journal Of Scientific Engineering Research
Prioritise Five Tafseer Translators Using Clustering Technique for Surah Al-Baqarah
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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Accuracy Evaluation of Digital Elevation Model Created Using Handheld Global Positioning System Receivers
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This study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this

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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model
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In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Auto-Regressive Distributed Lag Method in Investigating The Impact of Interest Rate on Foreign Direct Investment in Yemen for the Period 1990-2018
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 Foreign direct investment has seen increasing interest worldwide, especially in developing economies. However, statistics have shown that Yemen received fluctuating FDI inflows during the period under study. Against this background, this research seeks to determine the relationship and impact of interest rates on FDI flows. The study also found other determinants that greatly affected FDI inflows in Yemen for the period 1990-2018. Study data collected from the World Bank and International Monetary Fund databases. It also ensured that the time series were made balanced and interconnected, and then the Auto Regressive Distributed Lag method used in the analysis. The results showed that the interest rates and

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Publication Date
Sun Dec 05 2004
Journal Name
Journal Of Physical Education
The evaluate of usage educational method for jump shooting and it effect on speed strength in basketball for specialized students in College Sport of Dayla University
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The research aim to the usage educational method for jump shooting and it effect on speed strength in basketball for the specialist students in College Sport of Dayla University, which used the following statistic treatment (The T.test for compatible specimens), so after statistic treatment which appears theres a tow moral differences in speed strength and jump shooting tests results to (legs & arms) for the before and after tests, and after that the conclusions we positive and the second the special drills effect immaterial speed strength to legs and arms, so the tow researches recommended to looking after the best for educational methods that used in our sport colleges in Iraq.

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Publication Date
Wed Apr 09 2014
Journal Name
Chemical And Process Engineering Research
Analytical Profile of 4 - (4-Nitro Benzene Azo) - 3 - Amino Benzoic Acid on a Surface of Natural Granulated Calcined Iraqi Montmorillonite Clay Mineral, via Columnar Method
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The adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb of 4-(4-Nitrobenzeneazo) 3-Aminobenzoic Acid from aqueous solutions has been investigated through columnar method. The azo dye adsorption found to be dependent on adsorbent dosage, initial concentration and contact time. All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.), at room temperature (25±2) °C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monolayer adsorption capacity is 6.4066 mg Azo ligand per 1g calcined Montmorillonite. The experiments showed that highest removal rate 90.5 % for azo dye at pH 5.5.The

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