Main Subjects : Computer Science


Quality of Service and Load Balancing in Cloud Computing: A Review

Muna M.T. Jawhar; Hanaa Mohammed Osman

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 15-22
DOI: 10.33899/csmj.2022.174391

Cloud computing provides facilities. These facilities increased demand for its using as institutions and individuals moved to the cloud service. Therefore, cloud service providers must provide services to users based on the expected quality. One of the main challenges presented by the cloud computing is the Quality of Service management. QoS management is defined as allocating resources to applications to ensure service based on reliability, performance and availability. It is necessary to allocate resources based on load balancing that allows avoiding overloading or low loading in virtual machines, and this is a challenge for researchers in the field of cloud computing. This research highlights the importance of cloud computing, its types and importance, It also reviews some researches in the field of quality assurance of service in computing.

An overview of Cuckoo Optimization Algorithm based Image Processing

Baydaa sulaiman

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 31-36
DOI: 10.33899/csmj.2022.174393

The Cuckoo Search (CS) algorithm is an effective swarm intelligence optimization algorithm whose important developments were presented by Yang and Deb in 2009. The CS algorithm has been used in many applications to solve optimization problems. This paper describes an overview of the applications of CS in the scope of image processing to solve optimization problems for the image during the years 2015-2021. The main categories reviewed that used CS in the field of image processing are: image segmentation, image optimization, image noise removal, image classification, feature extraction in images, image clustering and edge detection. The aim of this paper is to provide an overview and summarize the literature review of applying CS algorithm in these categories in order to extract which categories that applied this algorithm more than others. From this review we conclude that CS was mostly applied in the image segmentation category to optimize the threshold search.

Managing Bank Loans By Using Neural Networks

ramadan al-Brahimi; Nima Abdullah AL-Fakhry AL-Fakhry

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 149-155
DOI: 10.33899/csmj.2022.174419

This study aims at recognizing the role of neural networks in deciding administrative decisions in banks. To achieve the aims, the study developed a suggested model that depends on artificial neural networks as a stabilization tool to support loans management decisions. The Descent Conjugate Gradient algorithm is adopted to build the suggested model through checking loan demands according to the various banking instructions. The results showed that using such techniques in administrative business was a success through evaluating loan demands and deciding the most appropriate ones, with the possibility of refusing or accepting the agent’s demand, and also the possibility of deciding the loans which were demanded more than the other types.

EMV Electronic Payment System and its Attacks: A Review

Ahmed ِAlqassab; Yassin Hikmat Ismael

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 23-29
DOI: 10.33899/csmj.2022.174392

 Recently,The Automated Teller Machines (ATM) and Point of Sale (POS) are based on the Europay, MasterCard and VisaCard (EMV) protocol. The goal of the EMV protocol is to enhance and improve the level of transaction security at both ATMs and Points of Sale. Despite the high performance of electronic payment systems, they suffer from attacks that can lead to unauthorized disclosure of cardholder data. This paper describes the EMV protocol and its features, and common attacks that threaten EMV card users in transactions at both ATMs and Points of Sale. The study will document the vulnerabilities that threaten EMV card holders and provide countermeasures against various potential attacks. It also describes the proposed methods that have been introduced in recent years to overcome these attacks and enhance the security level of the EMV protocol. The results of the comparison showed that biometrics has the highest performance in card security based on the EMV protocol with additional improvements in the encryption phase against all types of attacks.

Disease Diagnosis Systems Using Machine Learning and Deep learning Techniques Based on TensorFlow Toolkit: A review

Firdews A.Alsalman; Shler Farhad Khorshid; Amira Bibo Sallow

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 111-120
DOI: 10.33899/csmj.2022.174415

Machine learning and deep learning algorithms have become increasingly important in the medical field, especially for diagnosing disease using medical databases. Techniques developed within these two fields are now used to classify different diseases. Although the number of Machine Learning algorithms is vast and increasing, the number of frameworks and libraries that implement them is also vast and growing.  TensorFlow is a well-known machine learning library that has been used by several researchers in the field of disease classification. With the help of TensorFlow (Google's framework), a complex calculation can be addressed effectively by modeling it as a graph and properly mapping the graph segments to the machine in the form of a cluster. In this review paper, the role of the TensorFlow-Python framework- for disease classification is discussed.

Using Socket.io Approach for Many-to-Many Bi-Directional Video Conferencing

Sameer Jasim Karam; Bikhtiyar Friyad Abdulrahman

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 81-86
DOI: 10.33899/csmj.2022.174411

Video conferencing has become a critical need in today’s world due to its importance in education and business to mention a few; also, recent years have witnessed a great revolution in communication technologies. However, there still exist limitations in these technologies in terms of the quality of communication established between two peers. Therefore, many solutions have been suggested for a variety of video conferencing applications. One of these technologies is Web Real-Time Communication technology (WebRTC). WebRTC provides the ability to efficiently perform peer-to-peer communication, which improves the quality of the communication. This work tries to propose a WebRTC bi-directional video conferencing for many-to-many (mesh topology) peers. In this work, signaling was obtained using Socket.io Library. The performance evaluation of the proposed approach was performed in terms of CPU performance, and Quality of Experience (QoE). Moreover, to validate the simulations results, a real implementation was achieved based on the following scenarios a) involving several peers, b) at the same time, opening several video rooms, c) a session will still be active even when the room initiator leaves, and d) new users can be shared with currently involved participants.

Multilevel Database Security for Android Using Fast Encryption Methods

Najla Badie AI Dabagh; Mahmood S. Mahmood

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 87-96
DOI: 10.33899/csmj.2022.174412

Multilevel Security (MLS) is one of the ways that protects the stored information in the computer and mobile devices. It classifies users and information into levels of security; thus, the user can access information within its level or less.
A smartphone is used in managing some of businesses, controlling the home and car devices within the smart city environment by using a set of data stored in the database. The database is used by more than one authorized user some of this data is confidential and important that requires protection from un authorized users.
In this research a proposed system to implement the MLS principle within three levels of security is presented. The first level gives the user its own security level. The second level transfers users through the system parts according to their security level (system administrator or regular user). The third level allows users to manipulate the stored encrypted data in SQLite database by using a simple and quick cryptographic algorithm.
The proposed system is implemented in the smart mobile devices which are supported by the Android operating system. The experimental result showed that the proposed system has the ability to protect the data in the database and prevents users to view the data at upper levels. Also, the inability of users to change the security level of data that prevents the leak of data from the upper security levels to the lower level. Moreover, the proposed system works quickly and needs a little storage space.

Using The Hybrid GA-Ant Algorithm To Find The Optimal Path In Computer Networks

Ibtisam Kareem Turki

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 121-129
DOI: 10.33899/csmj.2022.174416

Cost management is one of the performance standards in computer networks and routing strategies through which we can get effective paths in the computer network, reach the target and perform highly in the network by improving the routing table (jumps). This paper is an attempt to propose a new H design mixed algorithm (ACO-GA) that includes the best features of both ACO and GA with a new application that combines both previous algorithms called( H- Hybrid (ACO-GA) hybrid algorithm technology, which differs in its parameters. In order to research and find the optimal path, the improved ant algorithm was used to explore the network, using smart beams, getting the paths generated by ants and then using them as inputs into the genetic algorithm in the form of arranged pairs of chromosomes.
Experimental results through extensive simulations showed that H (ACO-GA) improves the routing schedule, represented by the pheromone values that ants leave when following their path in the network. The values given in the table( 3.2) vary according to the quality of the pheromone concentration. In this case, it is possible to give the greatest opportunity to choose the best quality according to the concentration of the pheromone. For this purpose, a network consisting of four nodes (1), (2), (3), (4) was used starting with node (1) which is the source node and the destination node (2), by calling the selection technique to update the pheromone table by choosing the path to node (1 ). For this case and for selecting the destination node (2), the pheromone table for the nodes visited by the ant is updated. We calculated the final destination )2) by dividing the ratio. Thus, we get to reduce the search area, speed up search time, and improve the quality of the solution by obtaining the optimum set of paths.

Non-Complex Statistics-Driven Algorithm for Enhancement of Grayscale and Color Images

Ahmed Waad Mohammed; Zohair Al-Ameen

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 71-80
DOI: 10.33899/csmj.2022.174410

 Low-contrast images are viewed with obscured details and are unfavorable to the observer. Hence, it is a necessity to process such an effect efficiently to get images with lucid details as the need for clear images become a global demand. Therefore, a statistics-based algorithm of simple complexity is introduced in this research to process color and grayscale images with low contrast. The proposed algorithm consists of five stages, where the first and second stages include the use of two different statistical s-curve transformations, the third stage combines the outputs of the aforesaid stage, the fourth stage improves the brightness, and the fifth stage reallocates the pixels to the natural interval. The proposed algorithm is compared with six modern algorithms, and the outputs are evaluated using two no-reference methods. The obtained results show that the proposed algorithm performed the best, providing the highest image evaluation readings and it was the fastest among the comparison methods.

Performance Evaluation of Vehicle Ad hoc Networks Under Wi-Fi-6 Technology

Ahmed Salih Hasan; Basim Mohammed Mahmood

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 103-109
DOI: 10.33899/csmj.2022.174414

Vehicle ad hoc networks are considered mobile networks where the nodes are mobile objects and can change their positions within an environment over time. These objects can be connected at any time according to a predefined strategy. Simulating this kind of network needs high attention to many details. Moreover, the literature lacks works that describe the requirements of simulating such networks. Therefore, this work tries to describe the requirements of simulating vehicle networks (VANETs). Moreover, the goal is to determine what is needed to simulate vehicle networks in terms of the distribution of vehicles, the movement patterns, and the routing protocols used. The simulation results show interesting facts about the VANET networks and the best strategies to minimize the consumption of network resources. Finally, this work considers two communication technologies among network nodes; Wi-Fi 5 and Wi-Fi 6.

Honey Encryption Security Techniques: A Review Paper

Ammar Abdul Majed Gharbi; Ahmed Sami Nori

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 1-14
DOI: 10.33899/csmj.2022.174390

From time to time, we hear in the news about a breach or attack on some well-known companies as just news, but it is a serious problem because it is the privacy of citizens, their money in trade and managing their businesses and projects. In this paper, we offer a review of the honey encryption planner. Honey Encryption is the encryption system that ensures flexibility versus the brute-force attack through the provision of plain reasonable text, but false for each key is invalid utilized by a trespasser to decrypt a message, two key areas are open it is difficult to create a compelling message trap that's perfect enough to deceive the striker even when he believes that he has the message in its original form.
 The next problem, the typo issue, where a valid phony plain text seem to a lawful user when he accidentally enters the wrong key. Our goal is to have more satisfaction disguised tricks that are perfect enough to prevent a trespasser from getting the original message, We also need new security methods because the attackers are looking for new ways to attack the systems, so we proposed a new way to protect messages and passwords well and difficult to break and take all the possibilities of attack, including the brute-force, and then the data is hidden in an image with a public secret key.

Adapted Single Scale Retinex Algorithm for Nighttime Image Enhancement

Mohammad Khalil Ismail; Zohair Al-Ameen

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 59-69
DOI: 10.33899/csmj.2022.174407

 Images captured at night with low-light conditions frequently have a loss of visible details, inadequate contrast, low brightness, and noise. Therefore, it is difficult to perceive, extract, and analyze important visual information from these images, unless they were properly processed. Different algorithms exist to process nighttime images, yet most of these algorithms are highly complex, generate processing artifacts, over-smooth the images, or do not improve the illumination adequately. Thus, the single scale retinex (SSR) algorithm is adopted in this study to provide better processing for nighttime images. The proposed algorithm starts by converting the color image from the RGB model to the HSV model and enhancing the V channel only while preserving the H and S channels. Then, it determined the image’s illuminated version somewhat like the SSR, computes the logarithms of the illuminated and original images, then subtracts these two images by utilizing an altered procedure. Next, a modified gamma-adjusted Rayleigh distribution function is applied, and its outcome is processed once more by an automatic linear contrast stretching approach to produce the processed V channel that will be utilized with the preserved H and S channels to generate the output RGB image. The developed algorithm is assessed using a real dataset of nighttime images, evaluated using three dedicated image evaluation methods, and compared to ten dissimilar contemporary algorithms. The obtained results demonstrated that the proposed algorithm can significantly improve the perceptual quality of nighttime images and suppress artifact generation rapidly and efficiently, in addition to showing the ability to surpass the performance of different existing algorithms subjectively and objectively.

Diagnosis Retinal Disease by using Deep Learning Models

attallh salih; Manar Y. Kashmoola

AL-Rafidain Journal of Computer Sciences and Mathematics, 2022, Volume 16, Issue 1, Pages 51-58
DOI: 10.33899/csmj.2022.174403

Deep learning approaches have shown to be useful in assisting physicians in making decisions about cancer, heart disease, degenerative brain disorders, and eye disease. In this work, a deep learning model was proposed for the diagnosis of retinal diseases utilizing optical coherence tomography X-ray pictures (OCT) to identify four states of retina disease. The proposed model consists of three different convolutional neural network (CNN) models to be used in this approach and compare the results of each one with others. The models were named respectively as 1FE1C, 2FE2C, and 3FE3C according to the design complexity. The concept uses deep CNN to learn a feature hierarchy from pixels to layers of classification retinal diseases. On the test set, the classifier accuracy is 65.60 % for a (1FE1C) Model, 86.81% for (2FE2C) Model, 96.00% for (3FE3C) Model, and 88.62% for (VGG16) Pre-Train Model. The third model (3FE3C) achieves the best accuracy, although the VGG16 model comes close. Also, this model improves the results of previous works and paves the way for the use of state-of-the-art technology of neural network in retinal disease diagnoses. The suggested strategy may have a bearing on the development of a tool for automatically identifying retinal disease.

Detection of Plants Leaf Diseases using Swarm Optimization Algorithms

Saud M. Abdul Razzaq; Baydaa I. Khaleel

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 193-212
DOI: 10.33899/csmj.2021.170021

Classification is widely and largely used in data analysis, and pattern recognition. The data analysis aims to discover similarities between them and group them based on similarity into multiple classes. Artificial intelligence techniques are characterized by their great ability to classify objects and classify images. In this research, some artificial intelligence algorithms, represented by swarm optimization algorithms, were used to detect and classify plant diseases to healthy and unhealthy through images of different leaves of plants. Where plants are considered one of the most important organisms on this planet because of their important and fundamental role in the continuation of life and in achieving environmental balance, as well as in the economic side in many countries, and other benefits of high importance. These plants are apt to many different diseases. As a result of the technological development that the world witnessed in various areas of life, it was necessary to make use of it in the field of plant disease diagnosis, as many artificial intelligence techniques were employed in the discovery and diagnosis of plant diseases. In this paper, a new method is proposed to classify and distinguish a group of eight different plants to healthy and unhealthy based on the leaf images of these plants They are apples, cherries, grapes, peaches, peppers, potatoes, strawberries, and tomatoes using a hybrid optimization algorithm. In the first stage, the plant leaf images were collected and pre-processed to remove noise and improve contrast. In the second stage, the features were extracted based on the statistical feature extraction method, while in the third stage, the particle swarm (PSO) and chicken swarm optimization(CSO) algorithms were used to diagnose and classify plant diseases. Then these two algorithms were combined to produce a proposed hybrid algorithm called (PSO-CSO) hybrid method. The results obtained from these three algorithms were compared and the proposed method (PSO-CSO) obtained the best results compared to the two methods. Where the proposed method obtained in the first and second tests a diagnostic rate of (96.9%) and (98.18%), respectively.
 

Data Mining Between Classical and Modern Applications: A Review

Ammar Thaher Yaseen Abd Alazeez

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 171-191
DOI: 10.33899/csmj.2021.170020

Data mining (DM) is an incredible innovation with extraordinary potential to help organizations centre around the main data in the information they have gathered about the conduct of their clients and likely clients. It finds data inside the information that inquiries and reports can't viably uncover. Overall, DM (to a great extent called information or data revelation) is the route toward analysing data according to substitute perspectives and summarizing it into significant information - information that can be used to assemble pay, diminishes costs, or both. DM writing computer programs is one of different logical gadgets for separating data. It grants customers to separate data from a wide scope of estimations or focuses, organize it, and summarize the associations perceived. In reality, DM is the path toward finding associations or models among numerous fields in enormous social datasets. Procedures used in DM measure come from a mix of computational strategies including Artificial Intelligence (AI), Statistics, Machine Learning (ML), and Database (DB) Systems. Aside from the centre techniques used to do the investigation, the cycle of DM can include different pre-handling ventures preceding executing the mining method. Also, a post-preparing stage is normally utilized to picture the aftereffects of the investigation (for example perceived examples or recovered data) in an instinctive and simple to-impart way. From a wide perspective, there are two significant standards of methods: expectation and information disclosure. It includes four sub-groups: a) Classification, Prediction and Regression, b) Clustering, c) Association Rule and Sequence Pattern Mining, and d) Outliers and Anomaly Detection. What's more, there are some generally new and energizing zones of information investigation, for example, spatial DM and graph DM that have been made conceivable through the structure squares of DM techniques. This survey not just advantages analyst to create solid examination subjects and distinguish gaps in the research areas yet additionally helps experts for data mining and Big Data (BD) software framework advancement.

Real-Time Based Big Data and E-Learning: A Survey and Open Research Issues

Wael W. Hadeed; Dhuha Basheer Abdullah

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 225-243
DOI: 10.33899/csmj.2021.170044

Big data is considered a remarkable aspect of development communication and information systems. In terms of delivery, retrieval, and storage, a vast volume of complex data exceeds the capability of conventional software and device capabilities. As a result, advanced alternative solutions that allow their control flow is becoming more prevalent. One of the most difficult fields of information management and technology is the real-time management, analysis, and processing of big data. These issues can be seen in a large amount of everyday produced data in a variety of places, including online social networks and the method of logging cell phone data. This survey looks at several studies that use a range of methods to handle, interpret, and process big data in real-time. Hence, the objective of this survey is to provide a comprehensive overview of the integration between real-time and big data fields of study with the field of E-learning. Finally, this survey also presents the colorful aspects of big data and their relationship to E-learning domains such that e-learning platforms, big data frameworks, and datasets used.
 

Image Coding Based on Contourlet Transformation

Sahlah Abd Ali Al-hamdanee; Eman Abd Elaziz; Khalil I. Alsaif

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 149-163
DOI: 10.33899/csmj.2021.170018

The interest in coding was very high because it is widely relied on in the security of correspondence and in the security of information in addition to the need to rely on it in the storage of data because it leads to a pressure in the volume of information when storing it. In this research, image transformation was used to encode gray or color images by adopting parameters elected from contourlet transformations for image. The color images are acquired into the algorithm, to be converted into three slices (the main colors of the image), to be disassembled into their coefficients through contourlet transformations and then some high frequencies in addition to the low frequency are elected in order to reconstruct the image again. The election of low frequencies with a small portion of the high frequencies has led to bury some unnecessary information from the image components.
The performance efficiency of the proposed method was measured by MSE and PSNR criteria to see the extent of the discrepancy between the original image and the recovered image when adopting different degrees of disassembly level, in addition, the extent to which the image type affects the performance efficiency of the approved method has been studied. When the practical application of the method show that the level of disassembly is directly proportional to the amount of the error square MSE and also has a great effect on the extent of correlation where the recovered image away from the original image in direct proportional with the increased degree of disassembly of the image. It also shows the extent to which it is affected by the image of different types and varieties, where was the highest value of the PSNR (58.0393) in the natural images and the less valuable in x-ray images (56.9295) as shown in table 4.

In-Door Surveillance Module Based on an Associative Memory

Ghassan A. Mubarak; Emad I. Abdul Kareem

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 13-26
DOI: 10.33899/csmj.2021.170005

Most recent studies have focused on using modern intelligent techniques especially those developed In-Door surveillance systems. Such techniques have been built depending on modern Artificial intelligence-based modules. Those modules act like a human brain, they learn and recognize what they learned. The importance of developing such systems came after the requests of customers and establishments to defend their properties and avoid Intruders' damages. This would be provided by an intelligent module that ensure the correct alarm for correct non-secured state, Thus, an Indoor surveillance module depending on Multi-Connect Architecture Associative Memory (MMCA) has been proposed. This proposed system can be trained for more than to shoot. Thus the module can recognize more than one true state that might be secured or non-secured states in real-time. The current study found an accepted accuracy level between (62.778.8%) at first training cycle with two images. While the final result were between (97-100%) at the fifth training cycle with (10) images. It considered a high performance and very excellent results.

Design A Smart Reservation for Parking System

Noora A. Salim; Manar Y. Kashmoola

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 103-113
DOI: 10.33899/csmj.2021.170014

Nowadays, the smartphone device has become the most used device for the convenience of the user, smart parking is one such application that helps the consumer to find car parking space in an urban area. Mosul University, in particular, is one of these places. Common problems are the lack of information about vacant parking spaces and there is no way to search for them online. The goal of this work is to produce an Android and iOS app that uses ultrasonic sensors connected to the Arduino MEGA 2560 microcontroller to send parking occupancy values ​​to cloud, in an online database executed using Google Firebase. Finally, this application can book and pay online.

Embedded Descriptor Generation in Faster R-CNN for Multi-Object Tracking

Younis A. Younis; Khalil I. Alsaif

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 91-102
DOI: 10.33899/csmj.2021.170013

With the rapid growth of computer usage to extract the required knowledge from a huge amount of information, such as a video file, significant attention has been brought towards multi-object detection and tracking. Artificial Neural Networks (ANNs) have shown outstanding performance in multi-object detection, especially the Faster R-CNN network. In this study, a new method is proposed for multi-object tracking based on descriptors generated by a neural network that is embedded in the Faster R-CNN. This embedding allows the proposed method to directly output a descriptor for each object detected by the Faster R-CNN, based on the features detected by the Faster R-CNN to detect the object. The use of these features allows the proposed method to output accurate values rapidly, as these features are already computed for the detection and have been able to provide outstanding performance in the detection stage. The descriptors that are collected from the proposed method are then clustered into a number of clusters equal to the number of objects detected in the first frame of the video. Then, for further frames, the number of clusters is increased until the distance between the centroid of the newly created cluster and the nearest centroid is less than the average distance among the centroids. Newly added clusters are considered for new objects, whereas older ones are kept in case the object reappears in the video. The proposed method is evaluated using the UA-DETRAC (University at Albany Detection and Tracking) dataset and has been able to achieve 64.8% MOTA and 83.6% MOTP, with a processing speed of 127.3 frames per second.

Rapid Contrast Enhancement Algorithm for Natural Contrast- Distorted Color Images

Asmaa Y. Albakri; Zohair Al-Ameen

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 73-90
DOI: 10.33899/csmj.2021.170012

Digital images are often obtained with contrast distortions due to different factors that cannot be avoided on many occasions. Various research works have been introduced on this topic, yet no conclusive findings have been made. Therefore, a low-intricacy multi-step algorithm is developed in this study for rapid contrast enhancement of color images. The developed algorithm consists of four steps, in that the first two steps include separate processing of the input image by the probability density function of the standard normal distribution and the softplus function. In the third step, the output of these two approaches is combined using a modified logarithmic image processing approach. In the fourth step, a gamma-controlled normalization function is applied to fully stretch the image intensities to the standard interval and correct its gamma. The results obtained by the developed algorithm have an improved contrast with preserved brightness and natural colors. The developed algorithm is evaluated with a dataset of various natural contrast degraded color images, compared against six different techniques, and assessed using three specialized image evaluation methods, in that the proposed algorithm performed the best among the comparators according to the used image evaluation methods, processing speed and perceived quality.

Bresenham's Line and Circle Drawing Algorithm using FPGA

Areej H. Ali; Riyadh Z. Mahmood

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 39-53
DOI: 10.33899/csmj.2021.170007

In Bresenham's line drawing algorithm, the points of an n-dimensional raster that have to be selected are determined forming a close approximation to a straight line existed between two points. It is widely used for drawing line primitives in a bitmap image (for example: on a computer screen), since only integer addition, subtraction and bit shifting are used. These three operations are cheap concerning standard computer architectures. In addition, it is an incremental error algorithm. It is among the oldest algorithms that have been developed in computer graphics. An extension to the original algorithm may lead to draw circles. This research deals with the Bresenham’s line and circle drawing algorithm based on FPGA hardware platform.  The shapes on the VGA screen are displayed via internal VGA port that is built in the device.

Remote Farm Monitoring and Irrigation System

Zena N. Faysal; Ghassan J. Mohammed

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 123-138
DOI: 10.33899/csmj.2021.170016

The research deals with the intelligent irrigation system using the Internet of Things (IoT) via Low cost and low power system on chip microcontrollers including integrated Wi-Fi with dual-mode Bluetooth ESP32. The objectives of this project are to investigate the concept of an intelligent irrigation system using the Internet of Things, to develop a system using the aforementioned controller that processes data from the soil sensor that automatically irrigates the plant and analyzes the soil status of the plants. In real-time via the smartphone connected to the Internet. The study scope focuses on cropping and horticulture. Sensors had to be installed for each plant as it was necessary to know the condition of the soil. A water pump must also be added to each plant to save water. This project requires the Blynk application which is a platform with IOS and Android apps to control Arduino, Raspberry Pi and the likes over the Internet. It’s a digital dashboard where you can build a graphic interface for your project by simply dragging and dropping widgets.  Software on smartphone and hardware implementation which can detect environment condition using (DHT22: Temperature and Humidity sensor) sensor and soil moisture sensor. The results of this paper are based on the experiments performed.

User Centric Android Application Permission Manager

Belal Mohammed Amro; Zaid Abu Znaid

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 213-223
DOI: 10.33899/csmj.2021.170043

Mobile malware has become a very hot research topic in the last few years, and this was due to the widespread usage of mobile devices all over the world. Like other systems, mobile devices are prune to different attacks that might invade user’s privacy and lead to private data leakage. Millions of Mobile application have been developed and used Worldwide, most of them are requiring permissions to work properly. The permission management problem is more apparent on Android systems rather than other mobile systems such as iOS. Some of these permissions might lead to successful security attacks on Android systems and hence lead to privacy leakage. To reduce the possibility of such attacks, many researchers have proposed mobile applications that help users to manage access permissions for their mobile applications. Most of the proposed systems lack the ability to profile users according to their preferences and do not provide automatic follow up with temporary granted permissions. In this research, we propose a User Centric Android Application Permission Manager tool called (UCAAPM), that provides an efficient and flexible way for managing permissions and profiling these permissions for each user, these profiles can be used on any Android device. UCAAPM will automatically follow up users permissions and grant/deny the permission on a scheduling basis defined by the user’s profile and according to his preferences. Experimental results showed that the tool works efficiently in terms of CPU, RAM, and power consumption, furthermore users are highly satisfied with using it.

Image Enhancement Based on Fan Filter Parameters Adjustment

Huda S. Mustafa

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 2, Pages 27-38
DOI: 10.33899/csmj.2021.170006

In the field of image processing, there is an urgent need to adopt image transformations. In this paper, work is done on image coefficients after decomposing them through Curvelet transformations obtained through the fan filter.
The research deals with two stages: the first is to study the effect of the Fan filter by adopting angles (8, 16, 32) on the image (Lina.jpg) of size (256*256) after being analyzed using Curvelet transformations at scales (2,3,4)  through comparing a set of measurements (Contrast, Energy, Correlation, MSE, and PSNR) for both the original and reconstructed images. It can be found that Contrast and Energy criteria remain the same for the original and reconstructed images according to different levels of analysis or directions, so the value of the Correlation measure is 1. The value of the MSE criterion is very small and is almost not affected by the change of the number of angles in one scale, but it is slightly affected by increasing the scale analysis. What was mentioned above applies to the PSNR criterion as well.
As for the second stage of the research, which included decomposing the image to its coefficients, canceling the effect of one of these coefficients, and then reconstructing it. The results proved that the two criteria (Contrast and Energy) were not affected with falling Correlation criteria from 1 to values ​​ranging from (0.9987_0.9997) depending on the number of scales used in the Curvelet analysis and the number of angles used in  Fan filter (8,16,32). The results also showed an increase in the MSE value when dropping some frequencies, and a corresponding decrease in the PSNR value. Whereas, the decrease in the MSE scale was demonstrated at a specific scale with the increase in the number of angles in the Fan filter, in contrast to the PSNR scale.

Study on Turning Arabic Text into Spoken Words

Abdulwahhab F. Shareef; Riyadh Z. Mahmoud

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 197-209
DOI: 10.33899/csmj.2021.168269

Language was a means of communication between members of a single community, so that some of them would express to each other their ideas and thoughts, and a common characteristic of that society was defined, and the origin of the word was derived from (rhetoric, idle), if he repealed the matter and spoke about it, and the ancients knew it that language: (It is what expresses It contains all the people for their belongings). The ancients went in their definition of a language to the characteristics of their language with which they communicate, without referring to the Arabic language as a language among the living languages ​​that are circulating among them. Arabs and Arabs (whoever inhabited the country and its island, or uttered the language of its people), and to it returns the percentage of the Arabic language, which is one of the Semitic languages. Which spread in the Arabian Peninsula, and the writing came to denote what is in the minds of notables.
This research presents a computer application that depends on human input to pronounce the Arabic letters
The system consists of two phases, the first stage is the axis of creating a database for Arabic language characters and their storage locations, as well as the type of formulas for those letters when the initial processing was performed.
The second stage is the process of comparing the entered letter from the text with the corresponding sound and placing it in a storage so that we can then process it. In the practical part of the research, we used a comparison between the results of four methods to obtain the least possible execution time with the least pauses in speech, which are the combinative method, the smoothing method, the method of nesting speech, and a hybrid method between smoothing and interfering together.
We start by entering in the input text box and using the SpellLetter function, which we use for the purpose of processing and pronunciation, where the input is of three types, either it is a char, or it is an array of characters (String), or it is numbers between zero and nine Num), and in the case that the entry was not For these three types, the entry is wrong, for example, non-Arabic letters or special symbols, for example.,And if the entry was correct, each letter is taken with its accent. This means that we take two positions each time.
Using Matlab (R 2018a) to build the proposed system and it was implemented using a computer. Portable running under the environment of the operating system (Microsoft Windows 10).
 

Analyzing Crime Networks: A Complex Network-Based Approach

Husam B. Sultan; Basim Mohammed Mahmood

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 57-73
DOI: 10.33899/csmj.2021.168261

This article analyzed the crime network of Nineveh province based on the concepts of Complex Networks. To this end, two networks were created; the first represented the crimes that were committed in Nineveh province, while the second was the network of crime regions. These two networks were visualized and then analyzed using network centrality measurements. The results showed that several pairs of crimes had strong relations to each other. Moreover, it was found that some crime regions were considered as the core of crimes in the province. The results also showed that few regions were considered as the most dangerous parts of the province and they had strong tendencies to replicate their behaviour to other regions. Finally, the authors believe this is the first kind of works that take the crime network of Nineveh province as a case study

Using Ant Algorithm to Find the Optimal Critical Path of a Projects Network

Ziyad A. Mohammed; Sama T. Al_Obaidy

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 115-130
DOI: 10.33899/csmj.2021.168264

Intelligent techniques to solve the problem of decision-making in project management, apart from the methods of operations research, the choice was made on one of the algorithms of crowd intelligence represented by the Ant Colony Optimization  algorithm (ACO)to solve the matter of finding the optimal critical path for the enterprise business network because the business network is more Networks tradition the behavior of the ant colony system to find the optimal critical path for the Critical Path Network(CPN) as. You own a project beginning contract (the first event) equivalent to an ant hill.The project end contract (the last event) is equivalent to the food site.The matter of finding the optimal critical path for the project is equivalent to the search process to find an optimal (the shortest) path between the nest and the food site.
The program ANTOCPN, written in Matlab language on a virtual business network. The program is featuring by its efficiency, accuracy of results, and the possibility of applying it to any business network, regard of the degree of complexity in terms of the number of paths (activities), whether real or imaginary, smoothly and easily. Also, the results of the ANTOCPN algorithm program were compared with the results of the genetic algorithm program for the same question GAOCPN for previous research, and the ant algorithm proved its worth in terms of speed in obtaining the optimal solution.
 

Comparison Study for Three Compression Techniques (Wavelet, Contourlet and Curvelet Transformation)

Shahad M. Sulaiman; Hadia Saleh Abdullah

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 101-114
DOI: 10.33899/csmj.2021.168263

Researches and studies on compressing digital images are aiming to make it easier to deal with networks, communications and Internet by reducing the size of the multimedia files transferred, and reducing the execution time and transmission time. In this research, the lossy compression method was adopted as one of the solutions that reduce the size of the data required to compress the image, through the process of compression of digital image data using Discrete Wavelet Transform algorithms using Haar filter, and Contourlet. Using Laplace and Directional Filter, Curvelet transformation using FDCT- Wrapping Technology .The performance of the algorithms used in the proposed research is also evaluated using a Ratio Compression (RC) scale, As well as the Peak signal to noise ratio (PSNR) scale, the mean sequence error (MSE) scale, the signal to noise ratio (SNR) scale, and finally, the Normalization correlation (NC) scale. Correspondence between the original image and the recovered image after compression, in order to choose the best algorithm that achieves the best compression ratio of the image and maintains the parameters of the recovered image based on the standards (MSE, PSNR, SNR, COR and CR) used with the three algorithms, and the results showed that the Curvelet transformation algorithm achieved : best compression ratio, but at the expense of image quality.
 

Hiding Encryption Text by DNA using Exploiting Modification Direction Algorithm

Mohammad S. Hashim; Melad jader saeed

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 147-158
DOI: 10.33899/csmj.2021.168266

Local networks and the Internet increase day by day, and a large amount of information is transferred across these networks every day resulting in a dramatic increase in the information security threats.
Therefore, it was necessary to use the techniques that ensure the security and the confidentiality of the transferred information. Secret writing is a general term which is used to refer to the protection of information from attackers, and it includes two types of widely used technologies: cryptography and steganography.
The research has presented a security model that fulfils the requirements of confidentiality and safety of the data transferred between the parties of the communication process. This model includes two phases that aim to provide a high level of confidentiality and security for the secret text. New methods have been used to combine cryptography with steganography to attain a high level of secrecy and security where the secret text was encrypted in an innovative and modified way by encoding DNA (Deoxyribo Nucleic Acid( and hiding the resulting encrypted text inside images by means of EMD) Exploiting Modification Direction) method.
This method has been applied on a number of images and texts, and the measurement of PNSR (88.5382, 87.0293, 97.8257), MSE (0.000015, 0.000019, 0.00004), CO (0) and Q-Factor (0.3521,3458,0.3354) values in the resulting hidden images have been yielded good results.
 

Survey on Human Activity Recognition using Smartphone

Adeeba KH; Laheeb M. Ibrahim

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 55-67
DOI: 10.33899/csmj.2021.168253

The field of Human Activity Recognition (HAR) is an active research field in which methods are being developed to understand human behavior by interpreting features obtained from various sources, these activities can be recognized using interactive sensors that are affected by human movement. Sensor can embed elements within Smartphones or Personal Digital Assistants (PDAs). The great increase in smart phone users and the increase in the sensor ability of these smart phones, and users usually carry their smartphones with them. This fact makes HAR more important and accepted.
In this survey, A number of previous studies were studied and analyzed, where we prepared a comparison of the research works conducted over the period 2010-2020 in human activity recognition using Smartphone sensors. Comparison charts highlight their most important aspects such as a type of sensor used, activities, sensor placement, HAR- system type (offline, online), computing device, classifier (type of algorithms) and system accuracy levels.
 

A Multimedia Medical Expert System for Human Diseases Diagnosis

Ahmed Kh. Ameen; Baydaa Ibraheem Khaleel

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 131-146
DOI: 10.33899/csmj.2021.168265

With the great expansion and development of computer science and its systems. Its applications are used in most areas of life, which facilitated the solution of many simple and complex issues, as it was used in multiple fields, including the medical field, where computer applications were designed to help the specialist doctor in his work and reduce the time in diagnosis. In this research, an expert system is built, which is one of the artificial intelligence techniques, using the advanced (forward) sequencing algorithms also called data-directed inference, and the algorithm. Backward (backward) sequence, also called target-directed inference, to diagnose the most common diseases to which a person is exposed. It is supported by multimedia, which includes (text, images, audio, and video) to reach a solution to the problem through dialogue with the user and rely on the stored knowledge as a base on which the inference engine represented by the two algorithms to reach to solutions, instructions and recommendations to diagnose the disease and give the appropriate treatment. These solutions are given to users in several forms using multimedia (text, pictures, audio and video) and this system is used by people who cannot reach a doctor or hospital for any reason. This system consists of major parts, which are the knowledge base that organizes the collection of facts the laws and the inference engine, which in turn include the Forward Chaining and Backward Chaining algorithms.
These diseases in order to reach a diagnosis of the disease with high accuracy, and this leads to reducing medical errors. The proposed system can be used as a substitute for the doctor in diagnosing some diseases in general and some diseases in particular. Which is useful in cases where the doctor is absent due to natural conditions or emergency situations, or when it is difficult for the patient to reach hospitals or health centers.
 

Designing an Electronic Platform for the Distribution and Managing Undergraduate Projects

Osama O. Mohammed; Shayma Mustafa Mohi-Aldeen

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 159-177
DOI: 10.33899/csmj.2021.168267

Our study in this research came as a proposal for an electronic platform to manage projects that graduate the fourth stage through which all tasks were transferred from the traditional system to an electronic system. As the system collects project proposals by the teachers and follows up the process of selecting them by the students, then managing the discussion process and sending the evaluation electronically by the members of the discussion committees and by connecting to the internal network (Router) via mobile or computer to the main database so that the system administrator prints the results The evaluation is processed electronically and submitted to the examination committee. The system was developed structurally according to the principle of the server and the client, and the wireless network was used to connect the system devices to transfer information between the server and the client. The system provided a protection method for system information and a way for users to enter, relying on efficient investigation methods to ensure safe access to all system interfaces. The system was tested on real information for the Computer Science Department, and the system showed its efficiency in achieving the required goals, completing the tasks, and issuing results accurately, quickly and without errors. Programming languages used in the design (C # for design interfaces + SQL Server for distributed database + PHP for web pages)
 

Electronic System for Managing Theses of Computer Science College

Dhafar H. Al-Ali; Auday Hashim Saeed Al Wattar

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 179-195
DOI: 10.33899/csmj.2021.168268

This research paper includes designing and implementing of an Electronic system for  managing theses of  College of Computer Science and Mathematics, University of Mosul, using replication, C # language and MS SQL Server 2008 databases to be a stable work basis that can be relied upon in the departments’ work as it facilitates the higher administrative bodies in the departments and the deanship Obtaining the required results quickly and accurately, which facilitates and contributes to making the right decisions at the appropriate time and required with the ease of preparing special reports for each student, lecturer and thesis and printing them which it will help the departments head and the scientific committee to complete them if requested, as well as provide various statistics, and to improve administrative efficiency for thesis, the problem of losing thesis data and preserving it from human and natural disasters has been overcome by applying the principle of replication.
 

Data Modeling and Design Implementation for CouchDB Database

Shaymaa Ahmed Razoqi

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 39-55
DOI: 10.33899/csmj.2021.168252

In the modern database environment, new non-traditional database types appear that are Not SQL database (NoSQL). This NoSQL database does not rely on the principles of the relational database. Couchdb is one of the NoSQL Document-Oriented databases, in Couchdb the basic element was a document. All types of databases have the same conceptual data model and it was deferent in the logical and physical model, this mean UML class diagram can be used in the  NoSQL design at a conceptual level, that is, it can be used to design a Couchdb database. In this research, we suggest a method to model and implement the conceptual level of the Couchdb database from the UML class diagram in using simple way depending on the association types. Depending on the types of relationships between classes, we can have more than one database model to choose from and find the most suitable for the system to be designed. A medical clinic database was proposed to implement the transfer steps according to the proposed method. Three database models were designed and implemented to study the suitability of the proposed transfer method.

Study the Relationship between the University Student and Teacher using the Principal Component Analysis and Genetic Algorithms

Sahar E. Mahmood

AL-Rafidain Journal of Computer Sciences and Mathematics, 2021, Volume 15, Issue 1, Pages 75-100
DOI: 10.33899/csmj.2021.168262

Multivariate data analysis is one of the popular techniques, and among them is the Principal Component Analysis, or PCA, is a dimensionality-reduction method which is the process of converting a large number of related variables to a smaller number of unrelated factors, that still contains most of the information in the large set. Therefore, any phenomenon that consist of a large group of variables that are difficult to treat with in their initial form. The process of the interpreting these variables become complex process, so reducing these variables to a smaller is easier to deal with which is the aspiration of every researcher working in the field of principal component analysis. In this research, a multivariate data collection process was carried out which are relates to the nature of education and the relationship between the university student and the teacher, then studying and analyzing by Principal component analysis model, which is a technique used to summarize and condense data through the use of bonding software SPSS,2020.
Thus, it will be illustrious that this research will fall into a concept Data Mining, and is also abbreviated, and then it is realized using genetic algorithms procedure, in latest version MATLAB 2019B, Application of Genetic Algorithms using simulation software with latest release MATLAB 2019, using the Multiple linear regression equation method.
Multiple linear regression procedure to find the arrangement of independent variables within each factor of the factors obtained, by calculating the weight of the independent variable (Beta). Overall results were obtained for the eigenvalues of the stored correlation matrix, and the study required a Statistical analysis (PCA) method, and by reducing the number of the variables without losing much information about the original variables. The goal is to simplify their understanding. The disclosure of its structure and interpretation, in addition to reaching a set of conclusions that were discussed in detail, In addition to important recommendation.
 

Nineveh Blood: Android Based Blood Donation Application for Nineveh Governorate in Iraq

Ahmed Mostfa; Aya A. Alabass; Abdel-Nasser Sharkawy

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 85-96
DOI: 10.33899/csmj.2020.167341

Blood donation (BD) is one of the most significant contributions that a person can make towards the society. The growing android technology has made the process of BD easier and hassle-free. The Nineveh blood bank is an android application made for such great and noble cause. The application connects the givers and the requesters of blood who live in the Nineveh province, Iraq. The blood requester can serach from a list of all donors who have the same blood group and directly contact them without any third-party involvement. The Nineveh Blood application creates giver’s/requester’s profile through the Google Firebase Real-time database. In which, a one WebSocket two-way channel can constantly send the data back-and-forth between the server and the clients, and store the data as a JavaScript Object Notation (JSON) file.  
 

Maintainability Prediction for Object-Oriented Software Systems Based on Intelligent Techniques: Literature Review

anfal abd fadhil; Taghreed Riyadh Alreffaee

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 97-111
DOI: 10.33899/csmj.2020.167342

The maintainability of the software is one of the most substantial aspects when assessing software product quality. It is known as the easiness with which the current software can be changed. In the literature, a great number of models have been suggested to predict and measure maintainability during various stages of the Software Development Life Cycle, to conduct a comparative study of the existing suggested models of the prediction, only few attempts have been done. This study hints at the basics about the manner of how to measure maintainability in the object-oriented (OO) design knowing that the maintainability will be measured differently at every level. Also, we will concentrate on the artificial intelligence technologies of these studies.
 

The Impact of Mobility Models on the Consumption of Network Resources in the Internet of Things (IoT)

Rasha J. Al-Jarah; Basim Mohammed Mahmood

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 51-69
DOI: 10.33899/csmj.2020.167346

Nowadays, the field of Internet of Things (IoT) has become a new trend and one of the most attractive areas of research. It has a wide range of applications; starting from smart devices to developing smart cities. The main issue in this kind of applications is the limitation in network resources (e.g., energy, memory, connectivity, etc.). Most of the works in the literature deal with this issue in a traditional way. For instance, developing routing protocols that find the optimal path for data forwarding. This paper looks to this issue from a different angle. In this work, we aim at testing different mobility patterns and then investigate their impact of the consumption of network resources under particular distributions and data routing protocols. The aspect we aim to investigate and measure is the amount of data exchanged, which in turn affects the power and the memory consumption of a network. We also measure two more aspects; performance stability, and data coverage area. The results show that mobility models play a significant role in the overall network performance.
 

A Comparative Study of Methods for Separating Audio Signals

Riham J. Issa; Yusra Mohammad

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 39-49
DOI: 10.33899/csmj.2020.167345

The process of separating signal from a mixture of signals represents an essential task for many applications including sound signal processing and speech processing systems as well as medical signal processing. In this paper, a review of sound source separation problem has been presented, as well as the methods used to extract features from the audio signal, also, we define the Blind source separation problem and comparing between some of the methods used to solve the problem of source separation.
 

Smart Agriculture; Farm Irrigation System Using IoT

Amera Istiqlal Badran; Manar Y. Kashmoola

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 75-83
DOI: 10.33899/csmj.2020.167340

          Due to the increase of development in modern technology which entered in most fields of life including sustainable agriculture; most studies revealed that most lesions result from over irrigation which causes fungi in plant and soil salinity. Recently; some very important terms emerged and changed most agricultural concepts such as the sustainable agriculture, green cities and smart irrigation systems. Most of these systems improved the quality of production and reduced lesions. In this paper a smart irrigation system was designed depending on Field Capacity F.C value, Wilting Point W.P value. In addition to the ranges of moisture that are measured in the field which are important in decision making of irrigation and selecting the best values to rely on such as threshold value in designing for the sake of maintaining moisture in the soil permanently. The best field moisture value was recorded when designing was %24 at threshold value in a clay soil field. Finally; the best types of microcontrollers ESP8266 & ESP-32S and moisture sensors, which are  used to upload the data to Adafruit server. Also, the fast and light Message Queuing Telemetry Transport (MQTT) protocol, was used to transfer the ranges of moisture through the system and cloud computing.
 

The Linguistic Connotations of the Word Light in the Holy Quran (An analytical study of Quranic verses using Artificial intelligent techniques)

Nima A. Al-Fakhry

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 13-24
DOI: 10.33899/csmj.2020.167343

The Holy Quran is a sea of words, articulations, phrases, regulations, laws, and judgments. Therefore, when we dive in the Quran verses we need a large amount of information in various aspects to achieve the required knowledge. The word (Al-Noor) is one of the Quran's vocabularies, which enjoys a special place, and this privacy came from the specificity of the Quran and its sanctity. The word (Al-Noor) has one pronunciation and many meanings and vocabulary.
The research has sought to know God's lights: “the science, the guidance, the kernels, and faith “the closest and most intense and congregated of the verse (35/Al-Noor).  Furthermore, this verse was chosen due to it speaks about the Sultan of Allah Almighty and god's light. Finally, the research has used the algorithm of “subtractive clustering and weighted subtractive clustering” measured and Matlab language (2013) to achieve the practical aspect of the study.
 

Palm Print Features for Personal Authentication Based On Seven Moments

Khaleda B. Ali; Khalil I. Alsaif

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 63-74
DOI: 10.33899/csmj.2020.167339

Biometric images are considered as one of the major coefficients in the field of personal authentication. One of the main approaches for personal identification is based on palm print. So studying the features extracted from palm print image adopted to get high efficient system for any recognition systems. In this research two major phases are hold on, in the first phase a database was built for 100 persons by acquiring four images for both hands (4 for left hand and 4 for right hand), then processed to extract ROI (region of interest) by looking for the palm centroid then a square area is fixed based on that centroid. The pre-process play an important step for stable features. Evaluation of the seven moments for each image (8 images) follow the preprocess then stored in the database file (so each person will have 56 values), this phase called personal database preparation. The second phase is the detection phase, which requires the same steps to get 56 values then go through the database looking for the closest person to the tested one. The system evaluation measured by statistical metrics which show good result goes up to 95.7% when applied on 50 persons with different conditions. Also the effect of ROI dimension with individual hands and integrated both of them studied, and the recommended dimension is 192*192.

Improving Performance of Projector with the Protection of the Eyes while using a Smart Board

Abdulrafa H. Maree

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 2, Pages 53-62
DOI: 10.33899/csmj.2020.167338

One of the most important problems that a teacher faces when using a smart board in the teaching process is the fall of a strong light beam from the projector on their faces and bodies. The focus of this light is harmful to the human eye, which leads to temporary blindness when it falls directly on the eye. It also leads to harmful side effects. The light falling on the presenter body will make the picture on the screen looks unprofessional and unclear and distract the attention of the students. Solving this problem will led to better lectures delivering for both the teachers and the student.
In this study, a system is designed to track the movement of the teacher using an infrared transmitter that is attached to the teacher’s freshness or head cap. Electronic signals directed to an infrared receiver are installed on the front of the projector device in order to send these signals to the computer for analysis according to the proposed algorithms to determine the teacher face position. A black shade square) is placed in the designated and displayed on the smart board where the lighting will decrease on the face and eyes of the teacher, as this shade will be moving with the movement of the transmitter. This method aims to protect the teacher’s eyes from the harmful strong light.
 

Applying Standard JPEG 2000 Part One on Image Compression

Maha Abdul Rahman Hasso; Sahlah Abed Ali

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 13-33
DOI: 10.33899/csmj.2020.164796

In this paper, has been proposed Algorithm for standard JPEG2000 part one for image compression. The proposed Algorithm was executed by  using  MATLAB7.11  environment,  applied  these  algorithm  on  the gray and color images for type of the images natural, medical, Graphics images  and  remote  sensing.  Dependence  on  the  Peak  Signal-to-Noise Ratio  (PSNR)  for  comparing  the  result  of  the  proposed  Algorithm  by using the Daubechies filters 5/3 tap filter and 9/7 tap filter  Biothogonal , Another  comparison  is  held  concerning  the  obtained  results  of   the algorithm    of    ModJPEG  and  Color-SPECK. Proved  the  processing results Efficiency performance of   proposed Algorithm.
 

Medical Image Classification Using Different Machine Learning Algorithms

Sami H. Ismael; Shahab W. Kareem; Firas H. Almukhtar

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 135-147
DOI: 10.33899/csmj.2020.164682

The different types of white blood cells equips us an important data for diagnosing and identifying of many diseases. The automation of this task can save time and avoid errors in the identification process. In this paper, we explore whether using shape features of nucleus is sufficient to classify white blood cells or not. According to this, an automatic system is implemented that is able to identify and analyze White Blood Cells (WBCs) into five categories (Basophil, Eosinophil, Lymphocyte, Monocyte, and Neutrophil). Four steps are required for such a system; the first step represents the segmentation of the cell images and the second step involves the scanning of each segmented image to prepare its dataset. Extracting the shapes and textures from scanned image are performed in the third step. Finally, different machine learning algorithms such as (K* classifier, Additive Regression, Bagging, Input Mapped Classifier, or Decision Table) is separately applied to the extracted (shapes and textures) to obtain the results. Each algorithm results are compared to select the best one according to different criteria’s.
 

Design Simulation System to Simplifying Boolean Equation by using Karnaugh Map

Elham H. Aziz

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 97-115
DOI: 10.33899/csmj.2020.164680

Simulation is one of most important technique used for learning, it makes learning possible without cost and provides best way to improve the practical skills for learners. The purpose of this  research  was to design program  to simulate  processing of simplifying  Boolean expression by using kranaugh- map depending on rules and procedures applied to Boolean equation in order  minimize  it to obtain  final optimal expression with minimum  number of  variables ,and reduction in  equipment  that leads to  reduce cost,  and this research recommend to use modern methods in education which  Simulation programs is one of this method to  improve E-learning  to keep up with universities  which care to use E-learning with traditional education and make student more interactive with education progress. 

Studying the Coefficient Curvelet for Aerial Image Segmentation

Nagham A. Sultan; Khalil I. Alsaif

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 83-95
DOI: 10.33899/csmj.2020.164880

Currently, there are many approaches for image transformations that are developed to cover the new technology in the huge amount of data treatment. In this paper, a study on Curvelet transformation coefficients was performed based on the aerial image to apply segmentation. This paper applies a lot of modifications on cut off frequencies on the filters, which is used to decompose the image on curvelet transformation. Two approaches are proposed and tested to look for the best segmentation result; the first one is based on designing filters manually, while the second evaluates the filter coefficients depending on the selected shape of the filters. The first technique gives acceptable segmentation and the second reaches the optimal result. One of the most important results is that the cut of frequency has a high effect on the segmentation; in addition, choosing filter parameters depended on the coefficients dimension of the curvelet transformation. Finally, the results show that the first approach underperformed the second one.

HPPD: A Hybrid Parallel Framework of Partition-based and Density-based Clustering Algorithms in Data Streams

Ammar Thaher Abd Alazeez

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 67-82
DOI: 10.33899/csmj.2020.164677

Data stream clustering refers to the process of grouping continuously arriving new data chunks into continuously changing groups to enable dynamic analysis of segmentation patterns. However, the main attention of research on clustering methods till now has been concerned with alteration of the methods updated for static datasets and changes of the available modified methods. Such methods presented only one type of final output clusters, i.e. convex or non-convex shape clusters. This paper presents a novel two-phase parallel hybrid clustering (HPPD) algorithm that identify convex and non-convex groups in online stage and mixed groups in offline stage from data stream. In this work, we first receive the data stream and apply pre-processing step to identify convex and non-convex clusters. Secondly, apply modified EINCKM to present online output convex clusters and modified EDDS to present online output non-convex clusters in parallel scheme. Thirdly, apply adaptive merging strategy in offline stage to give last composed output groups. The method is assessed on a synthetic dataset. The output results of the experiments have authenticate the activeness and effectiveness of the method.

The Pandemic COVID-19 Infection Spreading Spatial Aspects: A Network-Based Software Approach

Basim Mohammed Mahmood; Marwah M. Dabdawb

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 159-170
DOI: 10.33899/csmj.2020.164684

Coronavirus or what has been termed COVID-19 is one of the infectious diseases that have been recently classified as a pandemic. Currently, it is considered as the activist and the most dangerous disease that is rapidly spreaded around the world causing thousands of death cases. COVID-19 spreads between people through the contact with the infected ones when they sneeze, cough, or droplets of saliva. In this article, we investigated the impact of the spatial aspects and the movement patterns on COVID-19 infection spreading. We considered three aspects, namely, mobility patterns, curfew (stay-at-home) impact, and the distribution of people within places. The results show that spatial aspects can be considered as one of the factors that play a significant role in spreading the virus.

Using Cohen Sutherland Line Clipping Algorithm to Generate 3D Models from 2D

Marah M. Taha

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 39-49
DOI: 10.33899/csmj.2020.164675

This paper provides an efficient algorithm to generate three dimensional objects from simple uncomplicated 2D environment, lead to reduce processor effort, limit of using complex mathematical operations. Most of the previous researches used the idea of ​​drawing by vanishing point to generate 3D objects from 2D environment, But the algorithm designed in this paper provides an idea of ​​how to draw three-dimensional shapes from two-dimensional drawings when applying Cohen Sutherland Line clipping algorithm, so that a basic two-dimensional shape is inserted from a set of points connected with each other must be within vision borders with a vanishing point outside of vision that is connected with all points of basic shape to consist a group of lines with partial intersections. So that any point has specific limited vision border which represents one of its coordinates of depth vertex, finally 3d object is generated when all clipping processes are completed to obtain other coordinates for all points.

Predicting Bank Loan Risks Using Machine Learning Algorithms

Maan Y. Alsaleem; Safwan O. Hasoon

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 149-158
DOI: 10.33899/csmj.2020.164686

Bank loans play a crucial role in the development of banks investment business. Nowadays, there are many risk-related issues associated with bank loans. With the advent of computerization systems, banks have become able to register borrowers' data according their criteria. In fact, there is a tremendous amount of borrowers’ data, which makes the process of load management a challenging task. Many studies have utilized data mining algorithms for the purpose of loans classification in terms of repayment or when the loans are not based on customers’ financial history. This kind of algorithms can help banks in making grant decisions for their customers. In this paper, the performance of machine learning algorithms has been compared for the purpose of classifying bank loan risks using the standard criteria and then choosing (Multilayer Perceptron) as it has given best accuracy compared to RandomForest, BayesNet, NaiveBayes and DTJ48 algorithms.

Collaboration Networks: University of Mosul Case Study

Basim Mohammed Mahmood; Nagham A. Sultan; Karam H. Thanoon; Dhiya Sh. Khadhim

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 117-133
DOI: 10.33899/csmj.2020.164679

Scientific research is currently considered as one of the key factors in the development of our life. It plays a significant role in managing our business, study, and work in a more flexible and convenient way. The most important aspect when it comes to scientific research is the level of collaboration among scientific researchers. This level should be maximized as much as possible in order to obtain more reliable solutions for our everyday issues. To this end, it is needed to understand the collaboration patterns among researchers and come up with convenient strategies for strengthening the scientific collaboration. The scientific collaboration among the University of Mosul researchers–which is our case in this study–has not yet been investigated or analyzed. In this work, we aim at revealing the patterns of the scientific collaboration of the scientific colleges in the University of Mosul. We generate a co-authorship network for the university; the generated network is based on the data we collected from each individual researcher. The generated co-authorship network reveals many interesting facts regarding the collaboration patterns among the university researchers.

Family GPS Tracking for Android

Mafaz M. Al-Anezi; Hisham D. Zebari; Saad N. Birfkani

AL-Rafidain Journal of Computer Sciences and Mathematics, 2020, Volume 14, Issue 1, Pages 31-38
DOI: 10.33899/csmj.2020.164674

In smart phone field, the security, tracking lost and kidnapping prevention are one of the main areas in current days. Today family members safety is more important when they are outside home. So, there is a need for a tracking system for kids where the parents can monitor their kids at anytime from anywhere.
These security goals are achieved by the Android System, Global System for Mobile (GSM), Global Positioning System (GPS) and Short Message Service (SMS) technologies.
The proposed application must be installed in all family member's smart phones, and these smart phones will use GPS services without need for internet connection, where the GPS is used to locate the child specifically and to track the child whenever he changes his place. The location obtained by only depending on GSM by sending SMS which contain a link of Google map shows the information of the position. The application also has the ability to trigger a help SMS to his parents when the child is in a dangerous situation by using his headphone, and this is considering a help message in real time.

Information Hiding Based on Chan-Vese Algorithm

Samia Sh. Lazar; Nadia M. Mohammed

AL-Rafidain Journal of Computer Sciences and Mathematics, 2011, Volume 8, Issue 2, Pages 99-110
DOI: 10.33899/csmj.2011.7876

The process of data transfer via the Internet becomes an easy process as a result of the great advances in networking technologies, and now many people can communicate with each other easily and quickly through them.Because the online environment is general and open, the unauthorized one can control information were transmitted between any two parts and interception of getting access for it, because of that there is an emergency need for write covered, which is the science of hiding secret information in a digital cover such as an images, so it is impossible for the normal person and others unauthorized to detected or perceives. In this paper, the technology in the field of information hiding in the images is developed, where first, the cover (PNG, BMP) image is segmented using Chan-Vese algorithm, then the text will hide in the segmented image depending on the areas of clipping.The standards (PSNR, BER) are used to measure technical efficiency. In addition the algorithm of this technique is implemented in Matlab.

A Hybrid Ant Colony Optimization Algorithm to Solve Assignment Problem by Hungarian Method

Isra N. Alkallak

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 2, Pages 159-175
DOI: 10.33899/csmj.2009.163805

This research studied ant colony optimization with optimization problem as an assignment model problem by Hungarian method. The proposed heuristic algorithm simulate ant colony optimization algorithm with  Hungarian method for Assignment   problem. The ant colony optimization algorithm simulates  the behavior of  real ant colony, to find the shortest path between many paths for solving the problem. It dependent on the path from the nest (problem of research) to food (optimal solution) by deposited pheromone on the path they take between the nest and food, so that other ants can smell it.
The experiment in this research  shows that the algorithm provides optimal solution. It  has outperforms with computation and it is an effective approach  and the algorithm performs significantly better than the classical method, to  reduce the region of the space considered and computation as compared to the classical methods.
 

Encryption Binary Images by Using Template Matching

Sundus Khaleel Ebraheem

AL-Rafidain Journal of Computer Sciences and Mathematics, 2006, Volume 3, Issue 2, Pages 43-69
DOI: 10.33899/csmj.2006.164058

Text encryption is a very important field in application of data transformation through the digital networks, and the Internet, so it is very necessary to do encryption operation on the text data to get more security in data transformation.
In this paper, we present a method -Template Matching- to encrypt data which is represented in form of image with BMP extension by using Mono Digital Images method with partial compression for the data by using RLE method which increases the security of the method and reduces the file size.
The application results is efficient for the printed or handwritten text in Arabic or English or any other language, and for the maps or sketches images. The method gives a good ability for data encryption. It is suitable for data transformation through the Internet networks.
 

Comparison of Edge Detection Methods in Gray Images

Sobhi H. Hamdoun; Afzal A. Hassan

AL-Rafidain Journal of Computer Sciences and Mathematics, 2006, Volume 3, Issue 2, Pages 11-28
DOI: 10.33899/csmj.2006.164056

The methods of edge detection play an important role in many image processing applications as edge detection is regarded as an important stage in image processing and the extraction of certain information from it.
Therefore, this subject was the focus of many studies performed by many authors. Many new techniques of edge detection which search into the discontinuity in color intensity of the image leading to the features of the image components were suggested.
Despite of the presence of many methods of edge detection which proved their efficiency in certain fields and gave good results on application, the performance of one method differs from one application to another, thus there was a need to carry out an evaluation of performance for each method to show its efficiency. The aim of this research is to evaluate the performance of edge detection by choosing five methods known as (Canny, Laplacian of Gaussian,Prewitt, Scobel, Roberts) and the application of each method on images with grayscale to find out the performance of each of them and writing down computer programs for each. Also, a subjective evaluation to compare the performance of these five methods using Partt Figure of Merit, calculating the increase percent in the detected edges, decrease percent in the edge points and the correct position of the edge in each method.
 

Efficiency of Artificial Neural Networks (Percepton Network) in the Diagnosis of Thyroid Diseases

Suher A. Dawood; Laheeb M. Ibrahim; Nabil D. Kharofa

AL-Rafidain Journal of Computer Sciences and Mathematics, 2006, Volume 3, Issue 1, Pages 11-22
DOI: 10.33899/csmj.2006.164042

Thyroid gland software which was obtained through research is considered an effective system to diagnosed thyroid gland automatically. This is done by a built  complementary database which is flexible and easy at work with data patients concerning those patients under observation at Hazim Al-Hafith Hospital for Oncology & Nuclear  Medicine in Mosul. The activity of Thyroid gland software was tested on information about 200 Patients, and information about them was stred in Thyroid database, after that we diagnosed The Thyroid Gland Disease by using an artificial neural network (Perceptron) that is able to recognize Thyroid Gland Disease in good recognized ratio and with a ratio close to the doctor diagnosis depending on (sign & symptoms) which may enables the doctors in depending on it the right diagnosis for the disease.                                                                 
 

A Modified Heuristic Procedure for NP-Complete Problems Supported by Genetic Algorithms

Najla Akram Al-Saati

AL-Rafidain Journal of Computer Sciences and Mathematics, 2004, Volume 1, Issue 1, Pages 120-137
DOI: 10.33899/csmj.2004.164101

This work is based on the process of modifying an intelligent heuristic rule used in solving NP-Complete problems, where a study and a modification of a Flow Shop assignment heuristic has been carried out to solve a well-known classic Artificial Intelligent problem, which is the traveling Salesman problem. For this modification to be carried out successfully, the problem’s mathematical formulation had to be studied carefully and the possibility of reformulating the problem to be more suitable for the heuristic procedure. This may require some changes in the heuristic procedure itself, these adjustments were due to the noticeable differences like the symmetric property present in the traveling salesman problem environment and some other differences.
Genetic Algorithm is added to improve the results obtained by the used heuristic, where the use of crossover and mutation procedures will provide better chances for the near optimal solution to be improved towards optimal solutions.
The test problem is made on cities that lie on the regular square grid, which simplify the calculations of distance traveled between any two cities. Programs were written using C programming language, and timers were used to measure the elapsed time of calculations in order to assess the efficiency of the program.
 

Fast Backpropagation Neural Network for VQ-Image Compression

Basil S. Mahmood; Omaima N. AL-Allaf

AL-Rafidain Journal of Computer Sciences and Mathematics, 2004, Volume 1, Issue 1, Pages 96-118
DOI: 10.33899/csmj.2004.164100

The problem inherent to any digital image is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop algorithms that compress images to lower data rates with better quality.  Artificial neural networks are becoming very attractive in image processing where high computational performance and parallel architectures are required.
In this work, a three layered backpropagation neural network (BPNN) is designed to compress images using vector quantization technique (VQ).The results coming out from the hidden layer represent the codebook used in vector quantization, therefore this is a new method to generate VQ-codebook. Fast algorithm for backpropagation called

(FBP) is built and tested on the designed BPNN. Results show that for the same compression ratio and signal to noise ratio as compared with the ordinary backpropagation algorithm, FBP can speed up the neural system by more than 50. This system is used for both compression/decompression  of any image. The fast backpropagation (FBP) neural network algorithm was used for  training  the designed BPNN. The efficiency of the designed BPNN comes from reducing the chance of error occurring during the compressed image transmission through analog channel (BPNN can be used for enhancing any noisy compressed image that had already been corrupted during transmission through analog channel). The simulation of the BPNN image compression system is  performed using the Borland C++ Ver 3.5 programming language. The compression system has been applied on the well known images such as Lena, Carena, and Car images, and also deals with BMP graphic format images.

FID Fast Image Display for (.BMP & .PCX) Images

Rawaa P. Qasha; Ahmed S. Nori

AL-Rafidain Journal of Computer Sciences and Mathematics, 2004, Volume 1, Issue 1, Pages 66-87
DOI: 10.33899/csmj.2004.164098

Video display speed constitutes a very important factor in modern software performance. The best way to achieve fastest display is by accessing Video RAM and programming video card directly. In addition to the speed, this method provides flexibility and high performance video display operations. Besides that, dealing with 64K and 16.7 M color mode can be achieved only by this method.
Fast Image Display (FID) software is developed to display two popular types of images (BMP, PCX) using direct access to VRAM method with various SVGA modes differing in resolutions and number of colors. Assembly instructions and C++ language have been used to write Software parts.