ISSN: 1815-4816

Volume 11, Issue 1

Volume 11, Issue 1, Spring 2014, Page 13-201


On SNF-rings , I

Raida D. Mahmood; Akram S. M.

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 13-18
DOI: 10.33899/csmj.2014.163727

A ring  is called right SNF-rings if every simple right R-module is N-flat . In this paper , we give some conditions which are sufficient or equivalent for a right SNF-ring to be n-regular (reduced) .It is shown that
1- If is a GW-ideal of R for every . then ,is reduced if and only if is right SNF-ring.
2- If  is an reversible, then  is regular if and only if  is right GQ-injective and SSNF-ring .
 

Classification of Zero Divisor Graphs of Commutative Rings of Degrees 11,12 and 13

Nazar H. Shuker; Husam Q. Mohammad

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 19-24
DOI: 10.33899/csmj.2014.163728

In 2005  Wang investigated the zero divisor graphs of degrees 5,6,9 and 10. In 2012 Shuker and Mohammad investigated the zero divisor graphs of degrees 7 and 8. In this paper, we consider zero divisor graphs of commutative rings of degrees 11, 12 and 13.
 

A Modified Class of Conjugate Gradient Algorithms Based on Quadratic Model for Nonlinear Unconstrained Optimization

Basim A. Hassan; Hameed M. Sadiq

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 25-37
DOI: 10.33899/csmj.2014.163729

In this paper, we have investigated a new class of conjugate gradient algorithms for unconstrained non-linear optimization which are based on the quadratic model. Some theoretical results are investigated which are sufficient descent and ensure the local convergence of the new proposed algorithms. Numerical results show that the proposed algorithms are effective by comparing with the Polak and Ribiere algorithm.
 
 

Conjugate Gradient Algorithm Based on Aitken's Process for Training Neural Networks

Khalil K. Abbo; Hind H. Mohammed

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 39-51
DOI: 10.33899/csmj.2014.163730

Conjugate gradient methods constitute excellent neural network training methods, because of their simplicity, numerical efficiency and their very low memory requirements. It is well-known that the procedure of training a neural network is highly consistent with unconstrained optimization theory and many attempts have been made to speed up this process. In particular, various algorithms motivated from numerical optimization theory have been applied for accelerating neural network training. In this paper, we propose a conjugate gradient neural network training algorithm by using  Aitken's process which guarantees sufficient descent with Wolfe line search. Moreover, we establish that our proposed method is globally convergent for general functions under the strong Wolfe conditions. In the experimental results, we compared the behavior of our proposed method(NACG) with well- known methods in this field.
 

Measuring Of Data Base Performance Using Oracle

Heba Abdul-Razzak Raoof; Firas Mahmoud Mustafa

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 53-67
DOI: 10.33899/csmj.2014.163731

Due to the tremendous increase in the manufacturing of computer and producing high speed and performance computers, it was very important to find new methods for distinguishing its efficiency, performance and characteristics.
Optimization method can be defined as a process of choosing the most efficient way to execute DML statements such as (select, insert, update and delete).
In this research, performance efficiency of two different computers specifications by using Oracle system (9i) has been measured, in addition to distinguishing the performance between these two computers, on different data sizes (1000, 5000, 80000,300000 and 600000 records). (SQL) as tools for any comparison can be achieved  by the statistical performance parameters (Cpu time , Logical block read ,physical block read, physical block write,  Process Global Area memory, Execution time). Update command  effect on the parameters Cpu-time, logic_read, phy_read, Phy_Write was higher than select command specially at record number (600000) for both computers. Also, Values of these parameters increased by increasing data size (number of records). The parameters (PGA memory in use, exe_time)  gave ununiform results by increasing data size.
The effect of selection and update commands in computer1 on (Cpu_time, logic_read, phy_read, Phy_Write) parameters values were significantly higher compared to computer2 . While, the values of (PGA memory in use, exe_time) parameters in computer2 for both select and update commands were higher compared with computer1, but it was not significant.
 

Numerical Solution of Allen – Cahn Equation by Adomian Decomposition Method

Abdulghafor M. Al-Rozbayani

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 69-79
DOI: 10.33899/csmj.2014.163732

In this paper, Adomian Decomposition Method with Adomian polynomials are applied to solve Allen - Cahn equation with the initial condition only, also DuFort-Frankel method is applied with the initial and boundary conditions. The numerical results that are obtained by the Adomian decomposition method have been compared with the exact solution of  the equation shown that it is more efficient than the DuFort-Frankel method, that is illustrated through the tables and Figures.
 

Studying the Stability of a Non-linear Autoregressive Model (Polynomial with Hyperbolic Cosine Function)

Abdulghafoor Gasim Salim; Anas Salim Youns Abdullah

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 81-91
DOI: 10.33899/csmj.2014.163733

            In this paper we study the statistical properties of one of a non-linear autoregressive model with hyperbolic triangle function(polynomial with hyperbolic cosinefunction)by using the local linearization  approximation method to find the stability of the model  (singular point and its stability conditions and the stability of  limit cycle).Where we started by the model of lower order (first and second and third order) and generalized the idea, and we tried to apply these theory results by using some of examples to explain one of important truth that says (if the model has unstable singular point, then it, maybe, has a stable limit cycle).    
 

On Local Rings

Zubayda M. Ibraheem; Anees A. Fthee

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 93-97
DOI: 10.33899/csmj.2014.163734

A ring R is called local ring if it has exactly one maximal ideal. In this paper, we introduce some characterization and basic properties of this ring. Also, we studied the relation between local rings and Von Neumann regular rings and strongly regular rings.
 

Image Clustering based on Artificial Intelligence Techniques

Baydaa Ibraheem Khaleel

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 99-112
DOI: 10.33899/csmj.2014.163735

Clustering has been widely used in data analysis and pattern recognition and classification. The objective of cluster analysis is the classification of objects according to similarities among them, and organizing of data into groups. There are several algorithms for clustering large data sets or streaming data sets, Their aims are to organize a collection of data items into clusters. These such items are more similar to each other within a cluster, and different than they are in the other clusters. We have take the advantage of classification abilities of Artificial Intelligence Techniques (AITs) to classify images data set into a number of clusters. The Gath-Geva (GG) fuzzy clustering algorithm, Artificial Bee Colony algorithm(ABC), Radial Basis Function Network(RBF), and then combined Gath-Geva algorithm with (RBF) algorithm to produce Fuzzy RBF (FRBF) method were applied using images data set to classify this data set into a number of clusters (classes). Each cluster will contain data set with most similarity in the same cluster and most dissimilarity with the different clusters. We compute the classification rate, and false rate on this data set. Finally we make comparisons between results obtained after applying these algorithms on this images data set.TheFRBF is better than the other three methods that applied in this research such as G-G, ABC, RBF, because the FRBF was obtained higher classification rate in testing state equal (96.8571) and low false alarm equal(3.1429).
 

Using DNA to Encode Text Files

Yassin H. Ismail; Najla B. Ibrahim

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 13-23
DOI: 10.33899/csmj.2014.163736

Modern studies focused on Deoxyribonucleic acid (DNA)  because that DNA have several important features including the random nature of the sequence of nitrogenous bases consisting the acid and large storage capability of the information that led to it’s usage in the field of encryption where the appearance of a new branch which is encryption of DNA . This research provided a new method to encrypt text files using DNA were building a set of coding tables and using them to obtain the cipher text in DNA  form , also used a set of transposition cipher methods for the purpose of increasing the security of the resulted cipher text .
 

Hybridization of a hidden Markov model using Elman neural network with application

Omar Saber Qasim

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 25-42
DOI: 10.33899/csmj.2014.163737

This research aims to improve the performance of the work of hidden Markov model, which is limited to the positive integers as input, and through the use of Elman artificial neural network that have the ability to accept all types of data in the input space. The proposed model has proved that it is highly efficient in the classification of osteoporosis data compared with Elman artificial neural network on the one hand and the hidden Markov model on the other.
 

Incomplete (rq-q+r- ɛ , r)-arcs and minimal {ℓ,t}-Blocking set in PG(2,q)

Nada Yassen Kasm Yahya; Hiba suhil najem

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 43-60
DOI: 10.33899/csmj.2014.163738

We proved that(rq-q+r-ɛ,r)-arcs is incomplete  by using minimal {ℓ,t}-Blocking set in projective plane PG(2,q)and we found a new condition for ɛ is ɛ ≥-A(r-1)2+B(r-1)-C and A,B,C is a constant which is not get previously in studies which is search in finding ɛ  for incomplete (rq-q+r-ɛ,r)-arcs ,for value 2≤r≤ 4  where q is prime for values 11≤q≤ 31  in addition to  q=16.

Building an electronic documentation system for the Graduate Studies Division using Distributed databases

Nather Muhammad Qiddo; Raed A. H. Al-Dabbagh

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 61-80
DOI: 10.33899/csmj.2014.163739

This research aims to build a system for electronic documentation for the unit of graduate studies, which is used for managing electronic documents (official books, attachments, and instructions). The system was characterized by the possibility of participating electronic documents between administrative units and scientific departments in the college through the use of distributed database management system (Oracle), as well as the use of multimedia databases for dealing with images and (pdf) files, which represent the instruction manual for graduate work.
System have been analyzed and identify entities and its attributes as well as the relationships between these entities, this model of entities and relationships was used to represent the database, and then convert the model into standard formats relations. Oracle 10g language was used to design distributed database. Finally, the Proposed model was applied to real data obtained from graduate unit in the college, and showed its efficiency in the management of data and official documents used.
 

Application of Chaotic Neural Network for Authentication using the Database

Ammar Thaher Yaseen Abd Alazeez

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 81-95
DOI: 10.33899/csmj.2014.163740

  In this paper a new algorithm is suggested to encrypt data, since it was to take advantage of properties of the chaotic, so it was entered as a key in encryption and hiding  by entering values to the artificial neural network for training as well as hide in the picture, beside use the database for storage and retrieval information and increase the secret system. Through the overlap between the results of stages encryption and hide and artificial neural network algorithm was obtained exciting new strength from where you can not detect secret text only after obtaining random values of the chaotic algorithm and information about neural network algorithm as well as algorithm of work.
 

Textures Recognition using Elman Neural Network

Fawziya Mahmood Ramo; Alaa Anwr Mohamed

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 97-108
DOI: 10.33899/csmj.2014.163741

         In this research building system to recognition  texture images using artificial neural networks. The system consists of two phases: phase extraction important feature of each texture by using an algorithm Principal Components Analysis (PCA)   and recognition phase which recognize these feature by using  Elman network were trained network on a number of various texture  models down to the steady-state network  and then test the network by input  samples  of textures.  The experiments show that the method achieves high performance and produces 92% recognition rate.
 

Architecture Design of 2-D Discrete Wavelet Transformation Algorithm using Field Programmable Gate Array (FPGA)

Maha A. Hasso; Sahla A. Ali

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 109-123
DOI: 10.33899/csmj.2014.163742

In this paper an architecture has been proposed for the 2-D Discrete Wavelet Transform (DWT) and the Inverse Discrete Wavelet Transform (IDWT) based on  the Convolution method of  the Daubechies 5/3-tap Biorthogonal filter bank in the Algorithm transformto image processing, and implementation it on the FPGA (Field Programmable Gate Array) using VHDL, for benefiting from implementation advantages of these Hardware and save run-time. The processing  results proved speed and Efficiency of the proposed architecture,  where   the employed number of slices is less. So  it result to Frequency higher  and less run-time.The type of the FPGA based in this paper is  Xilinx XC3S500E Spartan-3E using Xilinx ISE 9.2i.
 

Isolated Arabic Digit Recognition Using Genetic Algorithm

Yusra Faisal Al-Irhaim; Ali Insaf Jasim

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 125-142
DOI: 10.33899/csmj.2014.163743

This study aims at constructing an intelligent system for recognizing the single Arabic numbers. It consists of two basic stages: the stage of features extraction and the stage of recognition. In the first stage, the technology of (Mel-Frequency cestrum coefficient (MFCC)) was employed. But in the second stage, the genetic algorithm was used.
The results of the test showed that words recognition percentage was (100%) for the words used with training, and it was (97%) for the words used with no training. The proposed system was constructed using the MatLab version (0.7) program, and the data used in the system are the following numbers: (0, 1, 2, 3, 4, 5, 6, 7, 8 and 9). Also, six speakers (four males and two females) performed the voice recording.
 

Distinguish of Fingerprint Based on Artificial Neural Networks

Zahraa Maen Al-Qattanz

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 143-162
DOI: 10.33899/csmj.2014.163744

In this research use one of artificial intelligence techniques which is artificial neural networks was used to distinguish fingerprint from a range of fingerprints belong to a unified database, based on a set of properties to the texture of image and which are extracted and analyzed using co-occurrence  matrix (Event), These properties are (contrast ,correlation, determined, homogeneity), and after extracting properties, a combination of neural networks (Cascade Neural Network CNN and Radial Basis Functions netwoek RBFN and Elman Neural Network ENN) used to distinguish fingerprint, and the results of training 100%  for the three networks after being trained on the network (18) sample where each person(3)samples.
Network efficiency was measured in recognition by using scale (training rate) and scale (recognition rate RR) for comparison between these networks to see the best network in the recognition.
 

Selection and Prioritization of Test Cases by using Bees Colony

Shahbaa I. Khaleel; Ragad waleed khaled

AL-Rafidain Journal of Computer Sciences and Mathematics, Volume 11, Issue 1, Pages 179-201
DOI: 10.33899/csmj.2014.163746

In this research, the bees swarm intelligence was studied to appointment it to serve software engineering. And that was performed through using Artificial Bees Colony ABC Algorithm in selection of test cases for the software written by C++ language in an automatic way since to enable the corporation which develops the software to save time, effort  and costs that required for testing phase and regression testing activity, which is always evaluated by 50% of the product cost. The proposed work can reduce test cases that are used in the tests of software and in regression testing activity ,also will make prioritization to the test cases, that are produced by the best selection process, by using Greedy Algorithm and Genetic Algorithm. the proposed work was applied practically on some programs – that differ in number of lines of code-.the result that appeared reduce number of test cases and make test cases in certain ordering that assists testing and regression testing for the software in safe mode and short time .