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EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it is obvious that the number of moments selected by the SP should exceed 30% of the overall EEG samples for accuracy to be over 90%.

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Design a Vegetative Filter Strips Length Using VFSMOD_W Model for Reducing Sediments and Pesticides
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 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
An Approximate Solution of some Variational Problems Using Boubaker Polynomials
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In this paper, an approximate solution of nonlinear two points boundary variational problem is presented. Boubaker polynomials have been utilized to reduce these problems into quadratic programming problem. The convergence of this polynomial has been verified; also different numerical examples were given to show the applicability and validity of this method.

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Publication Date
Sat Dec 01 2012
Journal Name
International Journal Of Contemporary Mathematical Sciences
Approximation by Convex Polynomials in Weighted Spaces
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Here, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity

Publication Date
Thu Nov 15 2018
Journal Name
Journal Of Mathematical Imaging And Vision
A New Hybrid form of Krawtchouk and Tchebichef Polynomials: Design and Application
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Publication Date
Fri May 30 2025
Journal Name
Iraqi Journal Of Science
A Novel Approach for Synthesizing the Pan-chromatic Band to (10 m) of Landsat 9 Based on Sentinel-2 Data to Improve Classification Performance
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This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

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Publication Date
Sat Oct 01 2016
Journal Name
Al–bahith Al–a'alami
From Structure to the Signal (Text and Discourse in the Semiotic Analysis)
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Care and attention to the structure in the sixties of the last century replaced the mark, and if the structure of Ms. pampered in research and studies, it has become the mark is also a spoiled lady .. But the relationship between the structure and the mark was not a break and break, but the relationship of integration, His themes are structural analysis, and these are intellectual themes that can not be surpassed in contemporary research, especially since semiotics have emerged from the linguistic inflection.

We have tried to distinguish between text and speech, which is a daunting task, as it seems that whenever the difference between them is clear and clear, we come back to wonder whether the text is the same discourse, and is

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Publication Date
Sun Jan 01 2023
Journal Name
Ieee Access
Accelerated and Improved Stabilization for High Order Moments of Racah Polynomials
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
TOTAL AND MATRIC SUCTION MEASUREMENT OF UNSATURATED SOILS IN BAGHDAD REGION BY FILTER PAPER METHOD
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Soil suction is one of the most important parameters describing the moisture condition of unsaturated soils. The measurement of soil suction is crucial for applying the theories of the engineering behavior of unsaturated soils.
The filter paper method is one of the soil suction measurement techniques In this paper, five soil samples were collected from five sites within Baghdad city – al-Rasafa region. These soils have different properties and they were prepared at different degrees of saturation. For each sample, the total and matric suction were measured by the filter paper method at different degrees of saturation. Then correlations were made between the soil properties and the total and matric suction. It was concluded that the

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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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