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Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spent to achieve the best classification accuracy.

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
New Adaptive Satellite Image Classification Technique for Al habbinya Region West of Iraq
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   Developing a new adaptive satellite images classification technique, based on a new way of merging between regression line of best fit and new empirical conditions methods. They are supervised methods to recognize different land cover types on Al habbinya region. These methods should be stand on physical ground that represents the reflection of land surface features.      The first method has separated the arid lands and plants. Empirical thresholds of different TM combination bands; TM3, TM4, and TM5 were studied in the second method, to detect and separate water regions (shallow, bottomless, and very bottomless). The Optimum Index Factor (OIF) is computed for these combination bands, which realized

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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
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Wed May 01 2013
Journal Name
Ieee Journal Of Biomedical And Health Informatics
Classification of Finger Movements for the Dexterous Hand Prosthesis Control With Surface Electromyography
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Publication Date
Sun May 12 2019
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Importance of two-dimensional strain imaging in diagnosis of coronary artery disease
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Background: Strain imaging assessing regional myocardial deformation and can be used to quantify regional myocardial function and differentiate between ischemic and non ischemic myocardium.

Objectives: to assess sensitivity and specificity of strain imaging in detection of coronary artery disease in comparison with coronary angiography.
Patients and Methods:
ninety six patients were referred to Ibn albitar center for cardiac surgery, Baghdad, Iraq with symptoms of coronary artery disease for a period between June 2014 and April 2015, all of whom were evaluated by two dimensional echocardiography and all were found to have good left ventricular systolic function with no regiona

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Three Dimensional MHD Simulationof Comet Hale-Bopp Tail
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The interaction between comet Hale-Bopp tail with the solar wind is investigated in the present paper using magneto-hydrodynamic (MHD) numerical simulation, which accounts for the presence of the interplanetary magnetic field (IMF). The simulation is based on three-dimensional Lax-Wendroff explicit scheme, providing second-order accuracy in space and time. The ions produced from the nucleus of the comet will add considerable effects on the microstructure of the solar wind, thus severely altering its physical properties. The present simulation focuses on careful analysis of these properties by means of simulating the behavior of the comet Hale-Bopp’s tail at 1 AU from the sun. These properties include the changes of the plasma density,

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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
Thu Feb 01 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Performance of composite unprotected steel Beam-deck floor exposed to high temperature (fire flame)
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An experimental program was conducted to determine the residual of composite Steel Beams-Reinforced Concrete (SB-RC) deck floors fabricated from a rolled steel beam topped with a reinforced concrete slab, exposed to high temperatures (fire flame) of 300, 500, and 700ºC for 1 hour, and then allowed to cool down by leaving them in the lab condition to return to the ambient temperature. The burning results showed that, by exposing them to a fire flame of up to 300ºC, no serious permanent deflection occurred. It was also noticed that the specimen recovered 93% of 19.2 mm of the deflection caused by burning. The recovered deflection of burned composite SB-RC deck floor at 500ºC was 40% of 77.9 mm of the deflection caused by burning with a res

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Publication Date
Wed Jan 31 2018
Journal Name
Engineering Journal
Residual Strength of Composite Unprotected Steel-Deck Floor Exposed to High Temperature (Fire Flame)
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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Silica Fume Modified Cement-Based Mortar Exposed to High Temperatures: Residual Strengths and Microstructure
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Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

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