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Orthogonal Functions Solving Linear functional Differential EquationsUsing Chebyshev Polynomial

A method for Approximated evaluation of linear functional differential equations is described. where a function approximation as a linear combination of a set of orthogonal basis functions which are chebyshev functions .The coefficients of the approximation are determined by (least square and Galerkin’s) methods. The property of chebyshev polynomials leads to good results , which are demonstrated with examples.

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Early Childhood Special Education (int-jecs)
Study of some visual functions and functional variables of the respiratory and nervous systems and their relationship to the level of achievement of air rifle shooting

The purpose of this paper is to identifying the relationship between some visual functions and the level of achievement of air rifle shooting among young Iraqi female, and identifying the relationship between some functional variables of the respiratory and nervous systems at the level of achievement of air rifle shooting among young Iraqi female. The researchers used the descriptive approach in the correlative relationships style for its suitability and the research problem. The researchers determined the research community by the intentional method represented by (10) young female shooters who represent the national team with air rifle shooting effectiveness, and who represent (100%) of the research community. One of the most important re

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
Stability of Complement Degree Polynomial of Graphs

     A graph is a structure amounting to a set of objects in which some pairs of the objects are in some sense related. The objects correspond to mathematical abstractions called vertices (also called nodes or points) and each of the related pairs of vertices is called an edge (also called link or line). A directed graph is a graph in which edges have orientation. A simple graph is a graph that does not have more than one edge between any two vertices and no edge starts and ends at the same vertex.  For a simple undirected graph G with order n, and let  denotes its complement. Let δ(G), ∆(G) denotes the minimum degree and maximum degree of G respectively. The complement degree polynomial of G is the polynomial CD[G,x]= , where C

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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Image Compression based on Quadtree and Polynomial

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Publication Date
Wed Jul 25 2018
Journal Name
International Journal Of Engineering Trends And Technology
Fixed Predictor Polynomial Coding for Image Compression

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Publication Date
Tue Oct 04 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment

Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Orthogonal Symmetric Higher bi-Derivations on Semiprime Г-Rings

   Let M is a Г-ring. In this paper the concept of orthogonal symmetric higher bi-derivations on semiprime Г-ring is presented and studied and the relations of two symmetric higher bi-derivations on Г-ring are introduced.

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
symmetric analysis of multiple variables classified ranked orthogonal polynomials

MCA has gained a reputation for being a very useful statistical method for determining the association between two or more categorical variables and their graphical description. For performance this method, we must calculate the singular vectors through (SVD). Which is an important primary tool that allows user to construct a low-dimensional space to describe the association between the variables categories. As an alternative procedure to use (SVD), we can use the (BMD) method, which involves using orthogonal polynomials to reflect the structure of ordered categorical responses. When the features of BMD are combined with SVD, the (HD) is formed. The aim of study is to use alternative method of (MCA) that is appropriate with order

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Publication Date
Tue Oct 18 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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Publication Date
Wed Jun 01 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
Lightweight Image Compression Using Polynomial and Transform Coding

Publication Date
Wed Jul 06 2022
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression using Polynomial Coding Techniques: A review