Computer Engineering Commons^™

Secure Healthcare Systems And Big Data: A Bibliometrics Analysis, Rasha Talal Hameed, Saad Ahmed Dheyab, Saba Abdulbaqi Salman, Ahmed Hussein Ali, Omar Abdulwahabe Mohamad

Iraqi Journal for Computer Science and Mathematics

This study conducts a bibliometrics analysis of research on secure healthcare systems and big data, aiming to identify trends, key contributors, and thematic areas within the field. By examining a comprehensive database of academic publications, we highlight the evolution of research from foundational concepts to contemporary innovations in data security and privacy management in healthcare. Key metrics such as publication volume, citation impact, and co-authorship networks are analyzed to uncover the most influential authors and institutions. Additionally, we explore the integration of big data analytics in enhancing healthcare delivery while addressing security challenges. The findings provide valuable insights for researchers …

Integrating Image Data Fusion And Resnet Method For Accurate Fish Freshness Classification, Yahya Layth Khaleel, Mustafa Abdulfattah Habeeb, Ghadeer Ghazi Shayea

Iraqi Journal for Computer Science and Mathematics

Fish freshness classification is critical for protecting public health and ensuring efficient economic, regulatory and environmental sustainability. Classifying accurately reduces the risk of foodborne illness, protects product quality, builds consumer trust and supports sustainable resource conservation through waste minimization. However, the traditional methods for determining fish freshness are variable, time consuming and subjective, precluding practical use. This research presents an improved framework that integrates image data fusion and a deep learning ResNet model to differentiate fresh and nonfresh fish. From multiple sources, a comprehensive dataset including 16,640 samples was curated, and data fusion was used to increase the diversity and …

Develop Secure Software Specifications For Android App Concealing The Information And Safeguarding Data, Huda Abdulaali Abdulbaqi, Ahmmad Mohamad Ghandour, Thekrayat Abbas Jawad

Iraqi Journal for Computer Science and Mathematics

In the current landscape of technological advancement, data holds a pivotal role, shaping societal interactions and daily routines. The rapid escalation in digital data volume, driven by technological strides, has underscored the critical necessity for robust protective measures to safeguard its sensitive nature. This study aims to develop a secure software specification for Android application ensuring effective data protection through a specialized Android application tailored explicitly for data concealment, assuring utmost confidentiality and secure transmission. In this paper we revolve around the integration of multifaceted security and privacy protocols, employing advanced information concealment techniques, encryption mechanisms, secure key management, and …

Unveiling The Shadows: The Influence Of Anonymity And Fake Accounts On Cyberbully Intention In Social Media, Muzdalini Malik, Hapini Awang, Nur Suhaili Mansor, Mohamad Fadli Zolkipli, Khuzairi Mohd Zaini, Abdulrazak F. Shahatha Al-Mashhadani

Iraqi Journal for Computer Science and Mathematics

Cyberbullying has arisen as a prevalent and worrying issue in the digital age, substantially influencing the well-being and mental health of social media users. Previous studies have identified several factors and theories of cyberbullying. Still more in-depth research is required to understand the key factors influencing cyberbullying intention in social media. This study aims to identify the factors influencing cyberbullying intention in social media and examine the moderating effect of fake accounts on cyberbullying intention. An extensive literature review has been conducted to examine the gaps in existing studies on cyberbullying intention. As a result, this study uses the Theory …

Energy Optimization In Wireless Sensor Networks: A Review, Zahraa Hammodi, Ahmed Al Hilli, Mohanad Al-Ibadi

Iraqi Journal for Computer Science and Mathematics

The use of wireless sensor networks (WSNs) has become an inevitably necessary for a smart world, such as smart cities and environmental fields. WSN consists of hundreds or even thousands of sensor nodes that have the ability to sense physical conditions from the target field, and also consists of a device that acts as a link between the sensor nodes and the base station (BS) called cluster head (CH). In the recent years, researchers have become interested in optimizing the energy efficiency of the WSNs due to the limited and non-replenish energy sources of their sensor nodes. In this paper, …

E-Learning Management Technology Integration For Laboratory Usage, Mohammed Khaleel Hussein, Mohammed Ahmed Subhi, Saleh Mahdi Mohammed, Mayasah Al-Khateeb

Iraqi Journal for Computer Science and Mathematics

E-learning systems have transformed educational sectors and more interestingly, the use of these educational platforms for laboratory-based practices has been trending in the last couple of years. Laboratory-usage e-learning system has various tremendous benefits such as the skill of accessibility utilization and practical experimentation simulation. Several intelligent tasks still need to be tackled to make the most of it. One of the biggest problems is how to recreate hands-on experience in a virtual or remote environment. Some e-learning systems offer simulations and virtual experiments but may also require additional tactile feedback through interaction with physical equipment for this challenge, it …

The Significance Of Cannibalism, Panic, And Sanctuary In The Interactions Between Prey And Predator With A Stage Structure, Ahmed Sami Abdulghafour, Raid Kamel Naji

Iraqi Journal for Computer Science and Mathematics

This paper analyzes a novel prey-predator model that takes into account the predator's stage structure, cannibalism within the predator population, panicky behavior, and the existence of a sanctuary where the prey might hide from the predator. The Holling type II functional response is used in the predation process. The behavior of the identified fixed points of the proposed system has been closely analyzed. The analysis focuses on the local stability and potential bifurcations that could happen close to the system's fixed points. The Lyapunov function approach is used to investigate the fixed-point stability zone globally. Numerical simulations were run to …

Secure Blind Medical Image Watermarking Using Hybrid Feature Extraction Techniques, Sawsan D. Mahmood, Yassine Aribi, Fadoua Drira, Adel M. Alimi

Iraqi Journal for Computer Science and Mathematics

Watermarking offers great potential for medical images by embedding identifiable information that ensures secure and authenticated sharing of patient data while maintaining both integrity and diagnostic quality. In this paper, we present an innovative framework for blind medical image watermarking that harnesses advanced feature extraction techniques, including K-Means clustering, BRISK (Binary Robust Invariant Scalable Key-points), GFTT (Good Features to Track), and chaotic systems algorithms.

We conducted extensive experiments on the Ocular Disease Intelligent Recognition (ODIR) dataset, focusing specifically on Retinal Optical Coherence Tomography (OCT) images. The results highlight the framework's ability to preserve image quality and diagnostic utility, with minimal …

Convolutional Neural Networks For Dementia Severity Classification: Ordinal Versus Regular Methods, Ambresh Bhadrashetty, P. Sandhya

Iraqi Journal for Computer Science and Mathematics

Dementia, a chronic neurodegenerative disorder, progressively impairs cognitive functions such as memory, reasoning, learning, and recall, placing a significant burden on patients and healthcare systems. Early and accurate classification of dementia severity is crucial for personalized care and intervention. This study introduces a novel Convolutional Neural Network (CNN) designed to classify dementia into four ordinal severity levels (None, Very Mild, Mild, and Moderate) based on MRI brain scans. Utilizing the extensive Open Access Series of Imaging Studies (OASIS) dataset, which includes 86,437 MRI scans (67,222 ‘none,’ 13,725 ‘very mild,’ 5,002 ‘mild,’ and 488 ‘moderate’), our model addresses severe class imbalance …

New Three-Parameter Exponentiated Benini Distribution: Properties And Applications, Elif Yıldırım, Gamze Özel, Christophe Chesneaul, Farrukh Jamal, Ahmed M. Gemeay

Iraqi Journal for Computer Science and Mathematics

Modeling of some rarely occurring environmental events, obtaining and analyzing accurate predictions is quite important in determining the nature of such events and taking measures accordingly. Modeling these rarely occurring environmental events with the statistical distributions in the literature may cause some problems. For this reason, different statistical distributions are needed for modeling this type of rare data. In this paper, a new three-parameter exponentiated Benini distribution based on the exponential family is proposed as a new lifetime distribution. It is called the three-parameter exponentiated Benini distribution. Although new distributions are derived by different methods in the literature, there is …

Investigating Intrusion Detection System Using Federated Learning For Iot Security Challenges, Mohammed Q. Mohammed, Zena Abd Alrahman, Aouf R. Shehab

Iraqi Journal for Computer Science and Mathematics

The Internet of Things (IoT) is a decentralized and ever-changing network, which poses challenges in terms of security. The input highlights the need for robust security measures to protect IoT devices and their data from potential threats. The study focuses on Federated Learning (FL) technology as a potential solution to enhance IoT security. FL models are designed to protect sensitive data while allowing its exchange with other systems, making it a promising approach for securing IoT environments. Additionally, the input suggests the implementation of intrusion detection systems (IDS) as an additional strategy to enhance overall IoT security. By combining FL …

Explainable Machine Learning Approach Enables Computer-Aided Identification System For Children Autism Spectrum Disorder (C-Asd), Karrar Hameed Abdulkareem, Zainab Hussein Arif, Mazin Abed Mohammed

Iraqi Journal for Computer Science and Mathematics

Neurodevelopmental disorders like autism spectrum disorder (ASD) cause significant cognitive, linguistic, object identification, communication, and social skills deficits. Although there is currently no cure for autism spectrum disorder (ASD), early detection can aid in diagnosis and implementing effective preventative measures. Artificial intelligence (AI) tools allow for an earlier diagnosis of ASD than was previously possible. Furthermore, many clinical and not clinical attributes can be used for identification of ASD but select the most proper ones still challenge. Therefore, in this study we propose a Computer-Aided Identification System based on machine learning concept and feature selection methods to diagnosis Children Autism …

Stable Heterogeneous Traffic Flow With Effective Localization And Path Planning In Wireless Network Connected And Automated Vehicles In~Internet Of Vehicular Things (Iovt), Ahmed N. Rashid, Ahmed Mahdi Jubair

Iraqi Journal for Computer Science and Mathematics

The increasing complexity of networks comprising both Connected Autonomous Vehicles (CAVs) and Human-Driven Vehicles (HDVs) presents substantial challenges in achieving accurate positioning, efficient communication, and optimal route planning. Current methodologies fall short in enhancing vehicular network efficiency and reliability due to noise interference, inefficient data transmission, and unstable data transfer. This study aims to improve localization accuracy, reduce communication noise, and enhance path planning efficiency in mixed CAV and HDV environments through the Stable Heterogeneous Traffic Flow using Deep Reinforcement Learning and Effective Path Planning (SHTDR-EPP) approach. The primary goals are to ensure dependable localization, efficient communication, and reliable route …

A Comprehensive Analysis Of Partition Dimensions In Efavirenz Abacavir Lamivudine Doravirine Of Anti-Hiv Drug Structures, R. Nithya Raj, R. Sundara Rajan, Hijaz Ahmad

Iraqi Journal for Computer Science and Mathematics

The partition dimension of a graph in chemical graph theory refers to a graph invariant used to analyze the structural properties of molecules. It represents the minimum number of clusters or resolving partition set required to uniquely identify each vertex in the graph based on the neighborhoods within their respective clusters. In the context of chemical graph theory, the vertices of the graph correspond to atoms, and edges represent bonds between these atoms in a molecular structure. Determining the partition dimension of a chemical graph helps in understanding the relationships between molecular components and their spatial arrangements. It assists in …

Embedded Schemes Of The Runge-Kutta Type For The Direct Solution Of Fourth-Order Ordinary Differential Equations, F. A. Fawzi, Nizam G. Ghawadri

Iraqi Journal for Computer Science and Mathematics

This paper introduces an innovative approach for solving fourth-order ordinary differential equations (ODEs) of the form. We present the embedded Runge-Kutta (RK) Direct Explicit (ERKDGF) method, a family of embedded direct explicit RK type methods tailored specifically for this purpose. Through meticulous application of Taylor expansion, we have derived algebraic equations with order conditions up to the sixth order, ensuring the accuracy and reliability of our proposed integrator. We have developed two key variants within this method, namely RKDF5(4) and ERKDGF5(4), with orders five and four, respectively. Our approach is strategically designed, with the higher-order method ensuring exceptional accuracy, and …

Robust-Fragile Watermarking Using Integer Wavelet Transform For Tampered Detection And Copyright Protection, Hendra Budi, Ferda Ernawan, Agit Amrullah

Iraqi Journal for Computer Science and Mathematics

The use of the internet and advanced technologies enables the distribution of information and data through diverse digital images. Nevertheless, this ease of use comes with the potential risk of data misappropriation, encompassing unauthorized alterations, duplications, and reproductions of digital images. Ongoing research is being conducted in the field of watermarking to enhance the capabilities of protecting digital images. The objective of this work is to enhance the strength of copyright protection and the vulnerability of watermarking for authentication in digital images by utilizing the Integer Wavelet Transform (IWT). The watermarking approach involves embedding a durable watermark in the red …

Modelling Security Factors Influencing E-Wallet Adoption In Malaysia, Adi Badiozaman Ruhani, Nur Suhaili Mansor, Hapini Awang, Mohamad Fadli Zolkipli, Khuzairi Mohd Zaini, Abderrahmane Benlahcene

Iraqi Journal for Computer Science and Mathematics

This study aims to develop an effective framework that addresses the security concerns and user behavior related to e-wallet adoption. The research methodology entails quantitative data collection through a literature review and surveys of e-wallet users using convenience sampling, and the proposed model is tested using the Partial Least Squares Structural Equation Modelling (PLS-SEM). The proposed security factors in this study include phone stolen protection, app security performance, secure authentication, data privacy protection, secure online transaction and banking info security. The online survey form was disseminated to Malaysian citizens, and 186 respondents participated in the survey. Using a two-step approach, …

Robust Image Watermarking Based On Schur Decomposition, Ahmad Toha, Ferda Ernawan, Agit Amrullah

Iraqi Journal for Computer Science and Mathematics

The advanced of internet technology allows unauthorized people to distribute multimedia data. Copyright protection for digital images is needed to protect the intellectual properties of the digital image. This study presents a colour image watermarking using schur decomposition for protecting the digital copyright. This study investigates the significant contribution of the orthogonal U of schur decomposition with the size of 8´8 pixels. The proposed scheme embeds a watermark on the (U₂, U₆) of the U matrix to achieve high invisibly and robustness of the embedded watermark. The relationship of each coefficient on the U matrix …

Image Watermarking Using Firefly Algorithm–Iwt-Svd For Copyright Protection, Anjahul Khuluq, Ferda Ernawan, Agit Amrullah, Mohd Arfian Ismail

Iraqi Journal for Computer Science and Mathematics

Image watermarking is a technique used to ensure the legitimacy of ownership by safeguarding images. This research presented the Firefly algorithm–IWT-SVD to enhance resistance and robustness performance against different type of attacks. The cover image is split into blocks of 4×4 pixels, and each block is then computed by IWT-SVD. The Firefly algorithm is used to determine the appropriate scaling factor to incorporate the watermark using a predefined set of principles. The watermarked images have been evaluated under various attacks such as noise addition, filtered image, compressed image and scaled image. The experimental results demonstrate exceptional imperceptibility, with an average …

Robust Image Watermarking Based On Iwt-Dct-Svd For Copyright Protection, Syafiqul Shubuh, Ferda Ernawan, Agit Amrullah, Prajanto Wahyu

Iraqi Journal for Computer Science and Mathematics

The rapid advancement of technology has resulted in many intellectual works, in the form of images requiring copyright protection to prevent unauthorized use by irresponsible parties. This research examines the hybrid watermarking method that utilises IWT-DCT-SVD domain to enhance the durability of the embedded watermark. The host image is used as the input for the R-Level process, if the watermark logo is small, then the cover image is computed by 3-level of IWT. Whereas, the watermark logo has a large size, the cover image is then computed by 1-level of IWT. The watermark logo is embedded into the singular value …

Automated Fake News Detection System, Saja A. Al-Obaidi, Tuba Çağlıkantar

Iraqi Journal for Computer Science and Mathematics

Online news has been the majority of people’s information source in recent decades. However, a lot of the information that is accessible online is fake and sometimes even designed to mislead. It might be difficult for individuals to distinguish between certain false newspaper items and the real ones since they are so similar. Deep learning (DL) and machine learning (ML) models, among other automated false news detection (FND) techniques, are quickly becoming essential. A comparative study was conducted to analyze the performance of five prominent deep learning models across four distinct datasets, namely ISOT, FakeNewsNet, Dataset1, and Dataset2. Results indicated …

Posinormality Of Operators Treated By Weyl's Theorem On Unbounded Hilbert Space, Abbas G. Rajij, Dalia S. Ali, Huseyin Cakalli, Nadia M. G. Al-Saidi

Iraqi Journal for Computer Science and Mathematics

Hamiltonians, momentum operators, and other quantum-mechanical perceptible take the form of self-adjoint operators when understood in quantized physical schemes. Unbounded and self-adjoint recognition are required in the situation of positive measurements. The selection of the proper Hilbert space(s) and the selection of the self-adjoint extension must be made in order for this to operate. In this effort, we define a new extension positive measure depending on the measurable field of nonzero positive self-adjoint operator in unbounded Hilbert space of analytic functions of complex variables. Consequently, we define an extension norm in the same space. We show several new properties of …

Rad-Quasi-Prime Submodules, Rana Noorimajeed, Ghaleb Ahmed Hammood, Mahmood S. Fiadh, Lemya Abd Alameer Hadi

Iraqi Journal for Computer Science and Mathematics

Consider a left J-module I. The present study introduces the conception of rad-Quasi- Prime submodule, that serves as a dual popularization of both Quasi-Prime submodules and primary submodules. An apposite submodule A of an J-module named as rad- Quasi Prime if for all and with implies that either or . Numerous facts and characterizations that concerning are acquired.

Detecting Data Poisoning Attacks In Federated Learning For Healthcare Applications Using Deep Learning, Mohammed Aljanabi, Sahar Yousif Mohammed, Alaa Hamza Omran

Iraqi Journal for Computer Science and Mathematics

This work introduces a new approach to protecting the data in the healthcare applications of federated learning based on the classification of skin cancer. The recommended solution established and prevents the data poisoning attacks by using deep learning and CNN architectures namely VGG16. In a federated learning system which comprises of ten healthcare facilities, the approach enables the training of models in a collaborative way without compromising the medical data or the patients’ information. Data is meticulously prepared and preprocessed using the Skin Cancer MNIST: According to the HAM10000 dataset. As for the federated learning approach, VGG16’s feature extraction capability …

Embedded Deep Learning To Improve The Performance Of Approaches For Extinct Heritage Images Denoising, Ali Salim Rasheed, Alaa Hamza Omran

Iraqi Journal for Computer Science and Mathematics

Many advanced deep convolutional neural network (DCNN) methods have proven their efficacy in reconstructing the texture of super-resolution images (SR) from low-resolution images (LR). Nevertheless, the objective of achieving super-resolution (SR) reconstruction using Deep Convolutional Neural Networks (DCNN) becomes difficult when the input image is distorted by noise. Photographs captured at the inception of the camera are presently regarded as acultural heritage that chronicles an important periodin human history; however, they are marred by low resolution and noise as a result of obsolescence and the primitive nature of the technology that captured them, in contrast to the technological advances that …

An Integrative Computational Intelligence For Robust Anomaly Detection In Social Networks, Helina Rajini Suresh, K R. Harsavarthini, R Mageswaran, Hirald Dwaraka Praveena, C Gnanaprakasam, C.Sakthi Lakshmi Priya

Iraqi Journal for Computer Science and Mathematics

Anomaly detection is one of the most important tasks for maintaining the integrity, security, and trustworthiness of online communities in a social network. This paper proposes AdaptoDetect, which represents a new framework; it discusses a new anomaly detection approach called Pufferfish Optimization Technique for feature selection, together with a Graph Embedding Autoencoder for identifying anomalies. What makes AdaptoDetect special is that, with the use of POT, it has a distinctive capability in dynamic adaptation against network changes by selecting only the most relevant features in social network data. The technique for optimization underlines the important attributes for anomaly detection so …

Improving Security In The 5g-Based Medicalinternet Of Things Toimprove The Qualityofpatient Services, Israa Ibraheem Al_Barazanchi, Kholood J. Moulood, Muneer Sameer Gheni Mansoor, Jamal Fadhil Tawfeq

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) is like a tech upgrade that benefits patients by reducing healthcare costs, making medical care more accessible, and improving the quality of treatment. To make IoMT devices smart and capable, they need super-fast 5G support. However, there are security concerns when using IoMT devices that can put a patient's data and privacy at risk. For instance, someone could eavesdrop on your medical data due to weak network access management and data encryption.Many systems use encryption methods to protect data, but these methods often fall short when it comes to the high security standards required …

Automatic Temperature Control System Using African Vultures Optimization Algorithm, Mostafa Abdulghafoor Mohammed, Muntadher Khamees, Dina Hassan Abbas

Iraqi Journal for Computer Science and Mathematics

One of the most important tasks in control engineering is tuning a PID controller for maximum efficiency. However, without a great deal of practice, manual adjustment of PID settings might result in erroneous results. Using met heuristic algorithms is one method for tweaking the PID controller. These algorithms, which are inspired bythe laws of nature, can effectively find the sweet spot for the PID settings. Therefore, instead of manually tweaking the PID controller, using met heuristic methods can greatly enhance the system's performance while decreasing the related expenses. A reliable temperature control system is crucial to the production of a …

Resource Allocation And Edge Computing For Dual Hop Communication In Satellite Assisted Uavs Enabled Vanets, Ahmed Adil Nafea, Mustafa Maad Hamdi, Sami Abduljabbar Rashid

Iraqi Journal for Computer Science and Mathematics

VANETs are highly attractive and isused in maximum of the applications of cross-regional communication. To increase the coverage of the vehicular network, Unmanned Arial Vehicles (UAVs) are introduced, and they getconnected with the satellite networks to perform heterogeneous communication. With the help of this connectivity,the communication quality of ground level to air medium is increased.Currently the vehicle usage is highly increased and as aresults of communication link failure, improper resource allocation are arises whither abruptly assumesa stability about a network with that increasesan energy consumption and communication delay in the heterogeneous networks. In these conditions, thus study is idea of …

A Review Of Optimization Techniques: Applications And Comparative Analysis, Ahmed Hasan Alridha, Fouad H. Abd Alsharify, Zahir Al-Khafaji

Iraqi Journal for Computer Science and Mathematics

Optimization algorithms exist to find solutions to various problems and then find out the optimal solutions. These algorithms are designed to reach desired goals with high accuracy and low error, as well as improve performance in various fields, including machine learning, operations research, physics, chemistry, and engineering. As technology continues to advance, optimization algorithms are increasingly needed to address complex real-world challenges and drive innovation across all disciplines. Quantitative leaps have been achieved in improving the efficiency of optimization algorithms through the diversity of sources of information feeding these algorithms according to the type of optimization problem, based on scientific …