Journal of Al-Qadisiyah for computer science and mathematics <h3><strong>Journal of &nbsp; Al-Qadisiyah &nbsp;for computer science and mathematics (JQCM) is scientific journal issued by College of computer Science and Information Technology /University of &nbsp;Al-Qadisiyah&nbsp; since 2009&nbsp;&nbsp;periodically 2 times per year and 4 times per year since 2019, number of issues published sincece journal launched is 15 issues.The date of submission and acceptance of the article has been installed on articles published in Vol( 5)&nbsp; upwards, and the date of&nbsp;</strong><strong>available online&nbsp;</strong><strong>of the&nbsp;article has been installed on articles published in&nbsp;Voll(10)&nbsp;upwards.</strong></h3> <h3><strong><span lang="EN-US">ISSN 2521-3504 (Online), ISSN 2074-0204 (Print)</span></strong></h3> en-US (Assist .Prof .Dr. Ali Mohsin Al-Juboori , Editor- in –chief) (Dr. Rana Jumaa Surayh aljanabi, Editor- in –Charge) Sun, 25 Jul 2021 19:14:25 +0000 OJS 60 Cubic B-splines Method for Solving Singularly Perturbed Delay Partial Differential Equations <p>In this paper, we use the cubic B-splines method to solve the singular perturbed delay partial differential equations where the propagation term is multiplied by a small perturbation coefficient. In general, solutions to this type of problem have a boundary layer. The accuracy of the method was tested with two numerical examples and the results were compared with exact solutions and other methods.</p> Zahraa Salman Bloshi, Bushra A. Taha ##submission.copyrightStatement## Sun, 25 Jul 2021 19:16:23 +0000 On topological spaces generated by graphs and vice versa <p>The relationship between Graph Theory and Topological Space has recently &nbsp;developed greatly , &nbsp;&nbsp;as researchers have &nbsp;been &nbsp;able to &nbsp;find</p> <p>solutions to some problems in daily life by transforming the problem</p> <p>into a graph and then generating a topological space and thus facilita-</p> <p>ting reading the problem and solving it. The researchers also studied</p> <p>the generation of graph from topological spaces.In this article we will present two types of relations on the edges set that generate topolog-</p> <p>ical spaces, and we will discuss some properties of this &nbsp;topology, and</p> <p>we will &nbsp;study &nbsp;discuss the method of &nbsp;returning from &nbsp;the &nbsp;topological</p> <p>space to the graphs through using previous relationships.</p> Tabark Q. Ibraheem, Alaa A. Nagim ##submission.copyrightStatement## Sun, 08 Aug 2021 19:31:01 +0000 Trigonometrically Fitted Runge-Kutta Methods for the Numerical Solution of the Oscillatory Problems <p>In this paper, two trigonometrically methods were established based on classical Runge-Kutta methods of the fourth and fifth-order respectively. The new methods will be applied for the numerical integration of oscillatory problems and have high effectiveness as the results demonstrate. Numerical results show the robustness and competence of the new methods compared to the well-known Runge-Kutta methods in the scientific literature.</p> Zainab Khaled Ghazal, Kasim Abbas Hussain ##submission.copyrightStatement## Mon, 16 Aug 2021 17:26:28 +0000 Numerical Study of the System of Nonlinear Volterra Integral Equations by Using Spline Method <p>The second order non-polynomial spline function for solving system of two nonlinear Volterra integral equations is proposed in this paper. An algorithm introduced as well to numerical examples to illustrate carry out of this method. Also, we compare the absolute error of quadratic non-polynomial spline method with absolute error of linear non-polynomial spline method and the exact solution.</p> Atyaf Jamal Khalaf, Bushra A. Taha ##submission.copyrightStatement## Mon, 16 Aug 2021 18:11:47 +0000 On The λ-Statistically Convergent for Quadruple Sequence Spaces Characterized by The Triple Orlicz Functions by Using Matrix Transformation <p><img src="/journalcm/public/site/images/admin/abstract.jpg" width="659" height="101"></p> AQEEL MOHAMMED HUSSEIN ##submission.copyrightStatement## Fri, 03 Sep 2021 00:00:00 +0000 Numerical Solving of Nonlinear Equation Using Iterative Algorithms <p>In the given algorithm, we propose a development to the evaluations of Newton's numerical algorithm. Derivation of the standard method (Newton Raphson method) involves first derivative of the function. It is shown that the number of iterations of the new method is six and determined results support this technique. The results obtained show that the new proposed method is more accurate, easy to use, and efficient than other numerical methods are indicated.</p> Mohammed RASHEED, Ahmed Rashid, Taha Rashid, Saad Hussein Abed Hamed, Noghanian Toroghi Manoochehr ##submission.copyrightStatement## Fri, 10 Sep 2021 20:44:10 +0000 On Solving Nonlinear Equation Via Numerical Analysis for Photovoltaic Cell <p>Several numerical formulas have been introduced and analyzed in this paper. Based on the initial value x_0 used with each methods; these methods is used for solving the nonlinear equation of PV cell (single-diode). Several experiments are employed in order to examine these methods.&nbsp; Comparison of the results acquired in terms of number of evaluations reveal promising application of the proposed new method for nonlinear examples.</p> Mohammed RASHEED, Ahmed Rashid, Ahmed Rashid, Taha Rashid, Saad Hussein Abed Hamed, Mohammed Hussein Jasim AL-Kinani ##submission.copyrightStatement## Fri, 10 Sep 2021 00:00:00 +0000 Application of Numerical Analysis for Solving Nonlinear Equation <p>For the last years, the various of Newton's formula have become common iterative numerical techniques to realize approximate solutions to the zeros of nonlinear equations of PV cell (single diode) model foe electronic applications. These techniques do not necessitate the computation of second derivative of the functions but it need only first derivative of it's functions. In this paper, we introduce a new proposed method Dekker's Formula with five evaluations per iterations based on Accelerated Predictor-Corrector Halley's method. Numerical experiments produce that the new algorithm can determine with the standard Newton's algorithm.</p> Mohammed RASHEED, Ahmed Rashid, Ahmed Rashid, Taha Rashid, Saad Hussein Abed Hamed, Ola Abdulelah Abed AL-Farttoosi ##submission.copyrightStatement## Sat, 11 Sep 2021 17:00:50 +0000 Analysis of Non-Linear Device by means of Numerical Algorithms <p>In this paper, an efficient new fashion is suggested to improve two-step iterative method. A new three step iterative method for solving nonlinear equations of a photovoltaic cell based on Newton's method has been introduced. The accuracy and efficiency of the proposed method has been carried out using numerical experiments. The absolute error of the proposed and standard ones has been analyzed too. per iterations; the suggested method have lesser number of evaluations than the standard one.</p> Mohammed RASHEED, Ahmed Rashid, Taha Rashid, Saad Hussein Abed Hamed, Anwar AbdulJabbar Sabri ##submission.copyrightStatement## Sat, 11 Sep 2021 17:40:15 +0000 Various Numerical Methods for Solving Nonlinear Equation <p>In this work, two iterative methods is proposed and described here for solving nonlinear equation of PV cell device. The type of solar cell is single diode model based on its equivalent circuit with various values of load resistance R. These methods do not require second order of derivative and easy to use. The convergence of the proposed method do not discussed here. In order to found the accuracy and efficiency of the proposed and other method, the absolute error value have been calculated and compared. The advantages of the new proposed method can be investigated by comparing with the Improved Hornor-Newton method; and the results obtained indicate that the propose method is more accurate, efficient and easy to use than the second method.</p> Mohammed RASHEED, Ahmed Rashid, Taha Rashid, Saad Hussein Abed Hamed, Noghanian Toroghi Manoochehr ##submission.copyrightStatement## Sat, 11 Sep 2021 18:03:31 +0000 Finding the Critical Path Method for Fuzzy Network with Development Ranking Function <p>We propose a development ranking function (RF) to solve project - scheduling problems (PSP) in a foggy environment. The development command works on fuzzy numbers (FN) and this is done by converting the fuzzy parameters to an explicit value and applying the critical path method (CPM) to obtain the solution described in the proposed algorithm. A clear definition of the time limit will aid in the successful implementation of CPM, there is often confusion regarding the length of the process leading to the development of a critical path method (CPM) system. The example and approach strongly suggest that the proposed method is efficient and gives us the critical path (CP) and identifies sensitive activities as well. The results show that the use of the development ranking function (DRF) is better, more efficient, and accurate than the other ranking function (RF) by calculating the hours of the project completion.</p> Rasha Jalal Mitlif, Rasha Jalal Mitlif, Fatema Ahmad Sadiq ##submission.copyrightStatement## Sat, 25 Sep 2021 17:26:29 +0000 Palm vein recognition based on convolution neural network <p>This paper presents a new validation method using a convolutional neural network for palm vein recognition.&nbsp; Unlike fingerprint and face.&nbsp; Vein patterns are endogenous biometric features that do not change over time and that make them difficult to identify and replicate in people.&nbsp; The proposed paper aims to provide a new way to identify people through their veins. This paper used the CASIA dataset, which consists of several wavelengths, in this research used the 850nm wavelength, which is clear in the veins, In addition, we divided the data into 3 cases. The first case is when the training and testing ratio is 50/50, the second case when it is 70/30, and the last case when it is 90/10. Obtained an accuracy of 98% in the case 90/10. In addition, to the proposed network, and used a well-known global network, the AlexNet network, where did the same work on it to compare the results of our proposed network with it.&nbsp; As proposed network outperformed it in terms of accuracy and speed, where the accuracy was 96% in the case 90/10.</p> Ali Salam Al-jaberi, Ali Mohsin Al-juboori ##submission.copyrightStatement## Sun, 25 Jul 2021 19:52:08 +0000 ReliefF and Association Rule Mining to Determine Cervical Cancer Causes <p><strong>Cancer patients till this day suffer from the inability of science to predict the causes of the disease before it occurs.&nbsp; One of the cancers that occupy the minds of many women is the cervical cancer because of the delay in its diagnosis as a result of its multiple and unclear causes, so scientists and researchers need to search for the most causative factors. Machine learning approaches have become one of the best and fastest ways to find associations between symptoms and causes of disease. The use of association rule mining (AR) is very effective if diagnostic features are set up. In this work, feature selection (FS) algorithm named ReliefF is used to reach the most correlated factor, then the Apriori algorithm has been updated to reduce the time and space used, and detects features that are closely related to the class attribute to access most factors that cause cervical cancer. The experimental results of the proposed work indicate a number of cervical cancer risk factors that when combined, indicate a woman's likelihood of developing cervical cancer, which is: the number of years of hormonal contraception is greater than or equal to 15, having any type of cancer or HPV or syphilis or HIV, the number of IUD insertion years exceeded 10, First sexual intercourse smaller than 13 and Number of sexual partners greater than 5. The outcomes of this work help both doctors and women to prevent cancer.</strong></p> Zahraa Naser Shah weli ##submission.copyrightStatement## Tue, 27 Jul 2021 20:19:20 +0000 SECURE RSA CRYPTOSYSTEM BASED ON MULTIPLE KEYS <p>Information and communication technology are spreading very rapidly in terms of information exchange over the Internet, and this information is vulnerable to threats by hackers. Information security is mainly achieved by using encryption techniques to protect it when it is transmitted over an unsecured channel. In this paper, a modified encryption system for the RSA algorithm is presented using a fixed encryption key size and divide that key into specific sections, to encrypt and decrypt blocks using multiple public and private keys. The encryption process can be done for each block by choosing different keys according to the random generator key (seed key) and encrypt each block with these different keys. Through the random arrangement of blocks and the properties of a modified cipher block in the RSA algorithm within the proposed model, to increase security at the expense of time, the use of large keys in the RSA algorithm is very slow since small RSA keys are vulnerable to factorization attacks. To overcome that problem, we increase complexity and use larger block sizes without sacrificing speed, and compare them with the original RSA algorithm. As a result, this method is more efficient, secured, and not easily breakable.</p> Ali Najam Mahawash Al-Jubouri, Dr. Rana Jumaa Surayh Al-Janabi ##submission.copyrightStatement## Wed, 04 Aug 2021 00:00:00 +0000 Review Optimized Artificial Neural Network by Meta-Heuristic Algorithm and its Applications <p>A Meta-Heuristic Algorithms Optimization (MAHO)&nbsp;is inspired by nature. The Artificial neural network (ANN) has been shown to be successful in a variety of applications, including machine learning. ANNs were optimized using meta-optimization methods to enhance classification performance and predictions. The fundamental objective of combining a meta-heuristic algorithm (MHAO) with an artificial neural network (ANN) is to train the network to update the weights. The training would be speedier than with a standard ANN since it will use a meta-heuristic method with global optimal searching capability to avoid local minimum&nbsp;and will also optimize difficult problems. will discuss&nbsp;some of these meta-heuristic algorithms using ANN as they are applied to common data sets, as well as real-time specific classification and prediction experiences. In order to give researchers motivational insights into their own fields of application.</p> Noor Hassan Kadhim, Dr. Qusay Mosa ##submission.copyrightStatement## Sat, 07 Aug 2021 19:39:46 +0000 Survey of Iris Recognition using Deep Learning Techniques <p>Deep learning is an effective data mining method that is used to analyze complex, and large quantities of data accurately and efficiently. In the last few years, the world has gone through an revolutionary change in the way of how data produced and how data are processed not similar to any time before.&nbsp; The data produced must be handled accurately using intelligent methods to get accurate results. For example, iris recognition is one of the applications that needs sophisticated algorithms capable to identify one person from the other via the iris data analysis. In the recent few year, it was clear how deep learning has been used in different areas of life. One of those areas is the pattern recognition area. In this review paper, we focus on the investigation of using the deep learning technologies for these purposes. The research methodology followed in this paper is based on reviewing, analyzing the academic papers published in the last couple of years in terms of the proposed paradigm used on the iris data, and the accuracy results obtained from using that paradigm as well as mentioning the datasets used in these paper. The outcomes of this paper showed that using the deep learning method, in particular, the Convolutional neural networks, has promising future due to its success in this domain.</p> Zahra Rahim Sami, Huda Kadhim Tayyeh, Mohammed Salih Mahdi ##submission.copyrightStatement## Sun, 08 Aug 2021 18:23:32 +0000 EEG Signals Classification based on mathematical selection and cosine similarity <p>This paper presents a new electroencephalogram (EEG) signal classification using a fractal-cosine similarity approach for diagnosing epilepsy patients. The proposed system provides two designed models with PSO as an optimization technique and without optimization. A full classification design is achieved, including prepressing data by normalization, Particle Swarm Optimization (PSO) as optimization technique to reduce the features of EEG signals, Fractal metric computations, metric mapping, and cosine similarity for the final decision. This paper used the BONN university EEG dataset, which consists of five categories. The dataset was divided into four groups based on training set size and testing set size. First, we are used to the training and testing ratio of 90/10. The second case is 80/20, the third case is 70/30, and the final case is 60/40 respectively. The proposed model achieves high rates of accuracy up to 100%.</p> Safaa S. Al-fraiji, Dhiah Al-Shammary ##submission.copyrightStatement## Mon, 30 Aug 2021 17:23:35 +0000 Detection of Human Faces Covered with disguise and Makeup <p>Face detection is kind of the identification. When we look at someone's face, we can get information like his or her gender and age. Face detection research has exploded in popularity during the last few decades. Starting with algorithms that can detect faces in constrained environments, today's face detection systems can attain extremely great accuracies at the large scale unconstrained facial datasets. While new algorithms continue to increase performance, the majority of face detection systems are vulnerable to failure when subjected to disguise and cosmetics alterations, which is one of the most difficult covariates to overcome. In this article, the database of disguised and makeup faces (DMFD) is employed. In order to address this issue, we detected the location and size of the facial in the image by using Histogram of Oriented Gradients (HOG) + Linear SVM Machine Learning detector on the Disguise and makeup face database (DMFD).This approach is effective and can detect any disguise and makeup faces in the complex background and illumination variation. The results shows the effectiveness of the face detection system on a database (DMFD) and it provided better results of (99.3%).</p> Farah Jawad Al-ghanim, Ali mohsin Al-juboori ##submission.copyrightStatement## Thu, 02 Sep 2021 18:10:23 +0000 A MULTI-AGENT SYSTEM FRAMEWORK FOR CLOUD RESOURCES ALLOCATION <p>As cloud computing becomes increasingly attractive to entrepreneurs and resource consumers, researchers have recognized that an integrated infrastructure is needed to explore the potential of the cloud and enhance its efficiency and features. The primary people involved in cloud system operations are usually those who use the cloud, search the cloud provider's website, and make the purchase. This challenge is caused by the lack of a mechanism to provide negotiation interfaces through cloud providers to deal with them dynamically. In addition, one of the most common obstacles that consumers face is choosing resources based on their requirements at an affordable cost. Therefore, the goal of the proposed system is to simplify the process of allocating cloud computing resources to the consumer by choosing the most appropriate offer based on the cloud computing architecture and its integration with the Multi-Agent System (MAS) framework. Accordingly, the resulting system is more efficient and responsive, and negotiations can be conducted easily. In order to find mutually appropriate solutions in terms of service quality and price. The proposed system is applicable to all types of cloud deployments. It has been built using Java programming language and uses CloudSim and JADE as the two types of emulators used in the design and implementation of the system.</p> Fouad Jowda, Muntasir Al-Asfoor ##submission.copyrightStatement## Mon, 20 Sep 2021 17:58:01 +0000 Unusual Activity Detection in Surveillance Video Scene: Review <p>Abnormal activity may indicate threats and risks to others. An anomaly can be defined as something that deviates from what is expected, common, or normal. Because it is difficult to continuously monitor public spaces, intelligent video surveillance is necessary, which can monitor human actions in real-time and categorize them as ordinary or exceptional, as well as create an alarm. Human activities in public and sensitive regions such as bus stations, airports, railway stations, malls, banks, universities, car parks, roads, and other regions can be monitored using visual surveillance to prevent crime, theft, terrorism, vandalism, accidents, and other suspicious activities. ​This makes video surveillance a key to increasing public security. The main objective of event discovery is to discover the occurrence of events and categorize them into normal or abnormal actions. This discovery requires identifying and tracking objects and then learning what is going around those tracked objects. Recent research is based on one of two technologies: handcrafted features and deep learning models. Handmade features are based on extracting low-level features, and their strength is based on selecting the best features, that produce the best results. After the success of deep learning techniques for classifying images, the researchers examined the ability of deep learning techniques to detect, which bypasses the manual step of feature extraction and works directly with images. This paper presents a survey of both handmade and deep learning models to detect abnormal events.</p> Muthana S. Mahdi, Amer Jelwy Mohammed, Mohamed M. Jafer ##submission.copyrightStatement## Wed, 22 Sep 2021 16:20:48 +0000 Feature Level Combination for Face Recognition Based on Convolutional Neural Networks <p>Face detection and recognition systems have recently achieved encouraging results using deep learning, especially Convolutional Neural Network (CNN). Face Recognition (FR) systems have many challenges in unconstrained environments that decrease the accuracy; for overcoming these challenges, a deep learning-based features combination has been proposed. The scheme performs feature-level combination by applying two pre-trained GoogLeNet and VggNet-16 models as deep feature extractors. First, faces are detected and aligned using the Multi-Task Convolutional Neural Networks (MTCNN) face detector. The deep features are extracted from a face image using each individually pre-trained CNN. Second, features obtained from GoogLeNet and VggNet-16 models are combined using the serial-feature combination method. Finally, a classification task is performed using a multiclass Support Vector Machine (SVM) classifier. Experiments on the following datasets: VggFace2, LFW, Essex, and ORL, indicate the efficacy of the proposed system as the combination of the two pre-trained CNN models improves performance. The combination strategy, in particular, yields an accuracy of 95.33% to 99.29% on all datasets. The proposed system was compared to existing models in terms of the LFW, and ORL datasets, the findings showed that the proposed system outperformed most current models in terms of accuracy.</p> Jamal M. Alrikabi, Kadhim H. Alibraheemi ##submission.copyrightStatement## Thu, 23 Sep 2021 18:07:28 +0000