Computer Engineering Commons^™

Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal

Dissertations

Artificial intelligence (AI) has achieved remarkable performances across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures; Graph Neural Networks (GNNs) for relational mining and Large Language Models (LLMs) for sequential understanding. Despite their success, these models face challenges in security, robustness, and interpretability. GNNs excel in relational reasoning but are vulnerable to adversarial manipulation and lack interpretability, while LLMs are strong in linguistic reasoning and generalization yet struggle with relational data and …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Codelympics: An Educational Game, Shreyas Raghunath, Riley Guioguio

Computer Science and Engineering Senior Theses

This thesis addresses the growth of Computer Science and the increasing demand for resources that educate people about programming. The central problem is that existing resources either fall short in engaging the user, or are ineffective at communicating the basics of programming. Through a year of development and testing, we developed an application to serve as a bridge between games and educational content, making programming skills fun and accessible for younger students with no prior experience.

This thesis details the development of Codelympics, an educational game designed to teach the basics of computer programming, including control flow, functions, variables, and …

Are Cycles Of Neural Activity The Algorithm Of The Brain?, Edwin Omondi Onyango

Computer Science Senior Theses

We propose that precisely timed neural activity cycles can serve as structural primitives for memory and computation in a system that exhibits associative learning like the brain. Inspired by biologically grounded mechanisms such as calcium-dependent plasticity, spike-timing-dependent learning, and phase-sensitive excitability, we construct a spiking neural network model in which repeated temporal coincidences drive the formation of self-sustaining activity loops. These cycles, once formed, persist as dynamic memory traces: not stored as static weights, but as reverberating patterns that replay in time when these loops are restarted. We show that noise alone fails to induce stable structure, but even sparse, …

True-Bsg: A True Random Bit-Stream Generator For Fast And Efficient Stochastic Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi

Faculty Scholarship

Stochastic computing (SC) leverages random bitstreams to perform arithmetic operations, offering ultra-lowcost, fault-tolerant, and highly parallelizable computations. The quality of these bit-streams is crucial for the accuracy and reliability of SC. This paper introduces TRUE-BSG, a novel true random bit-stream generator designed for fast and energyefficient SC. Unlike state-of-the-art (SoTA) pseudo-random and quasi-random bit-stream generators, TRUE-BSG utilizes a highquality true random number generator (TRNG), capable of producing random bits at a rate of 1 Gigabit per second. Our TRNG ensures high entropy and minimal correlation. TRUE-BSG shows comparable accuracy to software-based generators and better energy efficiency than SoTA bit-stream generators, …

Ams-Hd: Acute Mountain Sickness Detection With Hyperdimensional Computing, M. Hassan Najafi, Mehran Shoushtari Moghadam

Faculty Scholarship

Acute mountain sickness (AMS) is a potentially life-threatening condition that affects many individuals traveling to high altitudes. Early diagnosis is crucial, especially for travelers who may not have immediate access to medical resources. While traditional machine learning (ML) methods have been used to detect AMS using biomedical data (e.g., heart rate, blood oxygen saturation, respiration rate, blood pressure, and body temperature), hyperdimensional computing (HDC) has yet to be explored for this purpose using the few of biomedical data. Previous classification methods fall short of balancing accuracy with low hardware complexity, but HDC offers a promising solution. HDC provides a hardware-efficient …

Endo Almost 3–Absorbing Sub-Modules (Modules) And Related Concepts, Wafaa H. Hanoon, Mahmood S. Fiadh, Marwah W. Allami

Iraqi Journal for Computer Science and Mathematics

The concept of Endo Almost 3-Absorbing sub-modules (modules) is presented in this study, along with observations and the connections between Endo 2-Absorbing sub-modules (modules), Endo Approximately 2-Absorbing sub-modules (modules), Endo quasi-prime sub-modules (modules), and Endo prime sub-modules (modules). The study provides a range of attributes, illustrations, and justifications for these concepts. We aim to utilize the ramifications of this research to develop new ideas based on Endo Almost 3-Absorbing sub-modules (modules). Along with observations and an exploration of the relationships between Endo 2-Absorbing sub-modules (modules), Endo Approximately 2-Absorbing sub-modules (modules), Endo quasi-prime sub-modules (modules), and Endo prime sub-modules (modules), the …

Retracted: A Group Decision-Making For Selecting Multi-Deep Face Recognition Models, Abdulbasit Alazzawi, Qahtan M. Yas, Burhan Albayati

Iraqi Journal for Computer Science and Mathematics

Deep face recognition is a significant area of biometric authentication that addresses challenges such as low resolution, varying facial expressions, and inconsistent lighting. This paper presents a robust deep-learning approach to tackle these challenges. The study aims to employ multi-criteria decision-making techniques and verify the influence of individual and group expert opinions in decision-making. However, balancing criteria such as accuracy, sensitivity, specificity, precision, and recall remain challenging across different models. To fill this gap, the study utilized a decision-support framework that included the fuzzy analytical hierarchical process to set criteria weights based on expert input and the Technique for Order …

Ecg-Based Biometric Key Generation Using Principal Component Analysis And Machine Learning, Ahmad Abadleh

Iraqi Journal for Computer Science and Mathematics

Biometric authentication techniques are fast becoming imperative methods for secure identifications in a wide range of applications, while most of the traditional systems are easily spoofed or forged. In this paper a new approach of deriving a unique biometric key from an electrocardiogram signal is presented owing to physiological uniqueness of heart activity. In this respect, by focusing on RR intervals extracted from ECG signals, the PCA is applied in order to reduce its dimensionality and then form a compact and distinctive biometric key. Thereafter, a Random Forest classifier was used in evaluating the effectiveness of features, where a high …

Retracted: Robust Security System: A Novel Facial Recognition Optimization Using Coronavirus-Inspired Algorithm And Machine Learning, Saif Mohanad Kadhim, Johnny Koh Siaw Paw, Yaw Chong Tak, Shahad Thamear Abd Al-Latief

Iraqi Journal for Computer Science and Mathematics

Facial recognition has become an invaluable and rapidly advancing technology that plays a crucial role in various daily applications. From identity authentication to video surveillance, mobile payment, and even law enforcement and security measures. Despite the remarkable progress, facial recognition is still a dynamic research field and confronts several challenges. One of the main challenges is the high variability in facial images due to factors like facial expressions, lighting conditions, aging, and the presence of accessories. Additionally, the computational complexity and the time concerns surrounding face recognition systems have raised considerations that need to be addressed. This research presents a …

Retracted: Accurate Electrocardiogram Classification Of Heart Disease Using Deep Learning Network, Hadeel M. Saleh, Sahar Hamad Ahmed, Akeel Sh. Mahmoud

Iraqi Journal for Computer Science and Mathematics

Long short-term memory networks can effectively process complex temporal patterns in electrocardiogram data. These sequential models excel at classifying heart disease from the rich signals captured by electrocardiograms. However, traditional algorithms struggle with the intricate waveforms encoded in each heartbeat. Deeper architectures such as LSTM are better equipped to untangle the subtle variations between healthy sinus rhythms and lethal arrhythmias. In this study, an LSTM model was developed to diagnose disease from the PTB dataset. The network was trained using a fusion of deep learning schemes for sequential data. The model underwent several evaluations, from a confusion matrix mapping predictions …

Retracted: Intrusion Detection System For Iot Based On Modified Random Forest Algorithm, Omar Z. Akif, Sura Mazin Ali, Ann F. Sabih, Ahmed T. Sadiq, S. K. Subramaniam

Iraqi Journal for Computer Science and Mathematics

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used …

Retracted: Cipher Text To Secure Li-Fi System Using Hybrid Encryption Algorithm, Mohammed M. Ahmed, Satea H. Alnajjar

Iraqi Journal for Computer Science and Mathematics

It is important to pay attention to develop our security systems, due to the increase in cyberattacks and the development of their methods and the work to develop quantum computers capable of penetrating the solution of complex equations of encryption algorithms. The need to develop protection methods has emerged in line with the development of hackers to ensure the security and safety of users' data. In this research, work was done on the modern Li-Fi technology based on comparing the values with Kim's model and a distance of more than 13 km was reached in the fresh air. This technology …

A New Class Of Endo-R.B Module And Its Relationship With Modules, Mohammed Salman Murad, Buthyna Najad Shihab

Iraqi Journal for Computer Science and Mathematics

This paper gives a definition of a new class of T-module and T-submodule called an Endo-Restricted Bounded module (submodule) written shortly by Endo-R.B. module (submodule) and present some different approaches to connect this class of module with other types of modules such as: compressible modules, monoform modules, critically compressible modules, retractable modules, and quasi-Dedekind modules. One of the main purpose of this work is to introduce a few new conditions and reveal some properties and corollaries. This paper considered to be another solution or answer for Zelmanowitz’s problem. In fact, an Endo-R.B. T-module plays an important role to this problem …

Detection And Mitigation Of Out-Of-Band Channel Wormhole Attack In Wireless Network Using Propagation Delay, Harry May

Doctoral Dissertations

Wireless networks, susceptible to a range of attacks due to their simplicity and ease of evasion, face a significant threat from control data attacks, notably the elusive wormhole attack. Detecting and mitigating such attacks poses challenges, particularly in the absence of a digital signature. This dissertation introduces an innovative approach that utilizes the propagation delay associated with malicious nodes’ timing characteristics for detection, employing the Ad-hoc On-Demand Distance Vector (AODV) algorithm as its foundation. The inherent propagation delay in the AODV protocol is calculated for each node link along the entire communication path, offering a distinctive timing method that provides …

Bronconest, Jake Esperson, Andrew Collins, Anish Katragadda

Computer Science and Engineering Senior Theses

Selecting suitable housing is a critical yet often overwhelming aspect of the college experience, particularly for incoming students who lack access to transparent and meaningful information about residential life. Existing platforms, such as official university housing portals or external real estate websites, fail to capture the nuanced, day-to-day experiences that influence student well-being, including cleanliness, social atmosphere, and sense of community. This issue is further compounded by the growing prevalence of remote decision-making and scattered, unverified sources of housing feedback.

To address this challenge, we developed BroncoNest, a scalable, cross-platform mobile application designed to centralize and personalize the student housing …

Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed

Turkish Journal of Electrical Engineering and Computer Sciences

This work describes a microstrip log-periodic dipole array (MLPDA) antenna that uses metamaterials and operates across the whole Ka-band. The suggested MLPDA antenna layout provides a wide bandwidth with fewer dipole elements than traditional MLPDA antennas while maintaining the same resonance frequencies. To reduce size while covering a wide operational spectrum, the antenna design includes bending dipoles as radiating elements, as well as an incomplete ground plane. Furthermore, the proposed MLPDA antenna’s energy loss has been reduced while boosting its signal strength (gain) by inserting a metamaterial-based structure in front of it at a certain distance and on the same …

A Data-Driven Approach To Smart Shopping: Optimizing Grocery Trips Using Geolocation And Store Inventory Data, Kien T. Giang

Honors Theses

This project presents a data-driven web-based application, Smart Shopping, designed to help customers optimize their grocery purchases based on location and store inventory information. The application allows users to add items to a shopping list and either enter an address or use their browser’s location services to identify nearby stores. It then retrieves product availability and prices from a mock database representing stores at user’s selected locations. The program compares prices across stores to provide users with two optimized options: the cheapest shopping bill from a single store, and the lowest individual item prices across multiple stores. Additionally, the …

Selected Artificial Intelligence Provisions In U.S. Fiscal Year 2025 National Defense Authorization Act, Bert Chapman

Libraries Faculty and Staff Presentations

The 2025 Fiscal Year National Defense Authorization Act contains multiple provisions relating to artificial intelligence (AI). These congressionally mandated provisions direct various sections of the Department of Defense (DOD) and individual U.S. armed service branches to execute congressional intent for AI policymaking. Examples of such intent include identifying and planning DOD's AI workforce, demonstrating AI biotechnology applications for national security, improving the human usability of AI systems, and establishing an AI security center. This presentation will note that reports on these initiatives must be prepared for relevant congressional oversight committees, and, in many cases, are in many cases, publicly released …

Sharc: Simulator For Hardware Architecture And Real-Time Control, Paul K. Wintz, Yasin Sonmez, Paul Griffioen, Mingsheng Xu, Surim Oh, Heiner Litz, Ricardo G. Sanfelice, Murat Arcak

Faculty Work Comprehensive List

Tight coupling between computation, communication, and control pervades the design and application of cyber-physical systems (CPSs). Due to the complexity of these systems, advanced design procedures that account for these tight interconnections are paramount to ensure the safe and reliable operation of control algorithms under computational constraints. This paper presents the Simulator for Hardware Architecture and Real-time Control (Sharc) to assist in the co-design of control algorithms and the computational hardware on which they are run. Sharc simulates the execution of a user-specified control algorithm on a given processor microarchitecture configuration, evaluating how computational constraints affect the dynamical properties of …