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Outdoor Scene Classification Using Multiple SVM
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This paper presents a hierarchical two-stage outdoor scene classification method using multi-classes of Support Vector Machine (SVM). In this proposed method, the gist feature of all the images in the database is extracted first to obtain the feature vectors. The image of database is classified into eight outdoor scenes classes, four manmade scenes and four natural scenes. Second, a hierarchical classification is applied, where the first stage classifies all manmade scene classes against all natural scene classes, while the second stage of a hierarchical classification classifies the outputs of first stage into either one of the four manmade scene classes or natural scene classes. Binary SVM and multi-classes SVMs are employed in the first and second stage of a hierarchical classification respectively. The proposed method is designed also to compare and find the most suitable multi-classes SVMs approach and the kernel function for classification task, where their performances are analyzed based on experimental results. The multi-classes SVMs used in this paper are One-versus-All (OvA) and One-versus-One (OvO), while the kernel functions used are linear kernel, Radius Basis Function (RBF) kernel and Polynomial kernel. Experimental results indicate that OvO classifier provides better performance than OvA classifier. The results, also show that the Polynomial kernel function is superior to others kernel function.

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Header-Words Based for Printed Arabic Document Images Retrieval System
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Printed Arabic document image retrieval is a very important and needed system for many companies, governments and various users. In this paper, a printed Arabic document images retrieval system based on spotting the header words of official Arabic documents is proposed. The proposed system uses an efficient segmentation, preprocessing methods and an accurate proposed feature extraction method in order to prepare the document for classification process. Besides that, Support Vector Machine (SVM) is used for classification. The experiments show the system achieved best results of accuracy that is 96.8% by using polynomial kernel of SVM classifier.

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Publication Date
Fri Sep 15 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Determine, Predict and Map Soil pH Level by Fiber Optic Sensor
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Abstract<p>Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.</p> ... Show More
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Scopus (7)
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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Detour Polynomial of Theta Graph
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     Let  be any connected graph with vertices set  and edges set .  For any two distinct vertices  and , the detour distance between  and  which is denoted by  is a longest path between  and  in a graph . The detour polynomial of a connected graph  is denoted by ;  and is defined by . In this paper, the detour polynomial of the theta graph and the uniform theta graph will be computed.

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Approximation of Functions in Lp, α (I) (0 < p < 1)
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   In this paper we show that the function , () p fLI α ∈ ,0<p<1 where I=[-1,1] can be approximated by an algebraic polynomial with an error not exceeding , 1 ( , , ) kp ft n Ï• αω      where
,
1 ( , , ) kp ft n ϕ αω is the Ditizian–Totik modules of smoothness of unbounded function in , () p LI

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Modeling the Contamination of Soil Adjacent to Mohammed AL-Qassim Highway in Baghdad
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The aim of this paper is to estimate the concentrations of some heavy metals in Mohammed AL-Qassim Highway in Baghdad city for different distances by using the polynomial interpolation method for functions passing from the data, which is proposed by using the MATLAB software. The sample soil in this paper was taken from the surface layer (0-25 cm depth) at the two sides of the road with four distances (1.5, 10, 25 and 60 m) in each  side of the road. Using this method, we can find the concentrations of heavy metals in the soil at any depth and time without using the laboratory, so this method reduces the time, effort and costs of conducting laboratory analyzes.

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Crossref (2)
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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
The Use of Predictive Analyzes for University Dropout Cases
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We will also derive practical solutions using predictive analytics. And this would include application making predictions with real world example from University of Faculty of Chariaa of Fez. As soon as student enrolled to the university, they will certainly encounter many difficulties and problems which discourage their motivation towards their courses and which pushes them to leave their university.
The aim of our article is to manage an investigation of the issue of dropping out their studies. This investigation actively integrates the benefits ofmachine learning. Hence, we will concentrate on two fundamental strategies which are KNN, which depends on the idea of likeness among data; and the famous strategy SVM, which can break the

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Arabic Handwriting Word Recognition Based on Scale Invariant Feature Transform and Support Vector Machine
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Offline Arabic handwritten recognition lies in a major field of challenge due to the changing styles of writing from one individual to another. It is difficult to recognize the Arabic handwritten because of the same appearance of the different characters.  In this paper a proposed method for Offline Arabic handwritten recognition. The   proposed method for recognition hand-written Arabic word without segmentation to sub letters based on feature extraction scale invariant feature transform (SIFT) and   support vector machines (SVMs) to enhance the recognition accuracy. The proposed method  experimented using (AHDB) database. The experiment result  show  (99.08) recognition  rate.

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Some Topological and Polynomial Indices (Hosoya and Schultz) for the Intersection Graph of the Subgroup of〖 Z〗_(r^n )
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         Let  be any group with identity element (e) . A subgroup intersection graph of  a subset  is the Graph with V ( ) =  - e and two separate peaks c and d contiguous for c and d if and only if      , Where  is a Periodic subset of resulting from  . We find some topological indicators in this paper and Multi-border (Hosoya and Schultz) of   , where    ,  is aprime number.

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
M_n – Polynomials of Some Special Graphs
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 Let  be a connected graph with vertices set  and edges set . The ordinary distance between any two vertices of  is a mapping  from  into a nonnegative integer number such that  is the length of a shortest  path. The maximum distance between two subsets  and  of   is the maximum distance between any two vertices  and  such that  belong to  and  belong to . In this paper, we take a special case of maximum distance when  consists of one vertex and  consists of  vertices, . This distance is defined by: where  is the order of  a graph .

     In this paper, we defined  – polynomials based on

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Scopus (5)
Crossref (1)
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Publication Date
Wed Mar 28 2018
Journal Name
Iraqi Journal Of Science
Linear Polynomial Coding with Midtread Adaptive Quantizer
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In this paper, a hybrid image compression technique is introduced that integrates discrete wavelet transform (DWT) and linear polynomial coding. In addition, the proposed technique improved the midtread quantizer scheme once by utilizing the block based and the selected factor value. The compression system performance showed the superiority in quality and compression ratio compared to traditional polynomial coding techniques.

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