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A Comprehensive Framework for Optimizing and Integrating Electric Bus Service with Smart Grids for Sustainable Public Transportation
No full textA Master of Science thesis in Electrical Engineering by Aisha Abdalla AlAli entitled, “A Comprehensive Framework for Optimizing and Integrating Electric Bus Service with Smart Grids for Sustainable Public Transportationl”, submitted in May 2025. Thesis advisor is Dr. Mostafa Shaaban and thesis co-advisor is Dr. Abdelfatah Mohamed. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The electrification of public transportation plays a pivotal role in the global transition toward cleaner energy and carbon neutrality, aligning with the Net Zero 2050 strategy. However, large-scale deployment of electric bus (EB) fleets introduces complex challenges in infrastructure and resource planning. This research supports the roadmap for public transit electrification by presenting a comprehensive optimization framework for EB operations and associated infrastructure. It focuses on the strategic deployment of EB fleets, the implementation of advanced charging technologies, and the optimization of service assignments and charging schedules. Furthermore, the research integrates electric bus chargers into smart grid, addressing the optimal allocation of distributed generation (DG) units and assessing the need for line upgrades. This work combines genetic algorithms (GA) for resource optimization with mathematical optimization techniques for scheduling (e.g., GAMS). This hybrid framework leverages the strengths of GA in solving large, nonlinear problems and the reliability of mathematical optimization in enforcing system constraints, ensuring applicability to real-world, large-scale systems. The proposed approach has been studied with different types of EB charging technologies and is evaluated under various scenarios, considering variations in operational strategy and energy demand. An electric 38‐bus network and a representative multi-route bus service are used to simulate and validate the framework. Results showed that the Genetic Algorithm reliably produced cost-efficient solutions by effectively positioning distributed generation units, selectively upgrading the transmission lines, and optimizing the charger types for multi-routes. The results demonstrate the effectiveness of the framework in minimizing costs while successfully meeting the operational requirements of the bus service and the technical limitations of the electric grid, contributing to the development of efficient and resilient electric transit systems.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Beyond Oil and Through Change: The Evolution of the Social Contract in the UAE
No full textA Master of Arts thesis in International Studies by Azza Sultan Al-Nuaimi entitled, “Beyond Oil and Through Change: The Evolution of the Social Contract in the UAE”, submitted in June 2025. Thesis advisor is Dr. Bethany Shockley. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This study explores the evolution of the social contract in the United Arab Emirates (UAE), situating the analysis within the country’s ongoing evolution of state–society relations in the context of diversification efforts and post-rentier adjustments. Historically, the UAE’s governance model has been characterized by the distributive logic of the rentier state, in which expansive welfare provision secured citizen loyalty and political acquiescence. However, fiscal constraints, regional instability, and global disruptions have led the state to reform its welfare policies, which may have had an impact on state–society relations by introducing targeted benefits instead of the traditional universal benefits, thereby altering longstanding expectations around state responsibility and citizen entitlement. While existing scholarship remains largely topdown in orientation, focusing on government strategies and institutional design, this research focuses on citizen perspectives and aims to address three core questions: how Emirati citizens interpret recent changes to the social contract, particularly those related to welfare reform and employment policy, and state expectations of civic responsibility; the extent to which these interpretations vary across generational, gendered, and regional lines; and how citizens perceive the evolving relationship between entitlement, loyalty, and national belonging. Through content analysis of recent initiatives including the Nafis program, the 2015 energy subsidy reform, and the 2018 introduction of Value-Added Tax (VAT)—alongside semi-structured interviews, the study investigates how state–citizen relations in the UAE are being impacted in the context of economic diversification and post-rentier adjustments, as experienced and interpreted by citizens themselves.College of Arts and SciencesDepartment of International StudiesMaster of Arts in International Studies (MAIS
Design and Implementation of a Hybrid Model Reference Adaptive Control System for a Quadrotor UAV
No full textA Master of Science thesis in Mechatronics Engineering by Abdelrahman Ahmed Alblooshi entitled, “Design and Implementation of a Hybrid Model Reference Adaptive Control System for a Quadrotor UAV”, submitted in May 2025. Thesis advisor is Dr. Rached Dhaouadi. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR
Dynamic Adaptive Video Streaming Over HTTP using Deep Learning Techniques
No full textA Doctor of Philosophy Dissertation in Engineering Systems Management by Maram Wahed Rashad Amin Helmy entitled, “Dynamic Adaptive Video Streaming Over HTTP using Deep Learning Techniques”, submitted in May 2025. Dissertation advisor is Dr. Mohamed S. Hassan and dissertation co-advisors are Dr. Usman Tariq and Dr. Mahmoud H. Ismail Ibrahim. Soft copy is available (Dissertation, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Maintaining a high Quality of Experience (QoE) in adaptive video streaming remains a significant challenge in the presence of dynamic and heterogeneous network environments. Traditional Adaptive Bitrate (ABR) algorithms in Dynamic Adaptive Streaming over HTTP (DASH) often rely on basic throughput estimation methods that struggle to adapt to rapid network fluctuations caused by mobility and handoff events. These limitations lead to frequent playback interruptions, abrupt quality changes, and overall QoE degradation. This dissertation proposes a novel deep learning-based framework to enhance ABR decision-making by predicting future throughput with greater accuracy and responsiveness. A transformer-based throughput prediction model is developed to capture the complex temporal dependencies in network dynamics. The predicted throughput feeds into two novel intelligent modules: a mobility-aware throughput prediction system (MATH-P) that combines mobility classification with dynamic bandwidth forecasting, and a handoff-aware prediction engine (HATH-P) that anticipates transitions between access networks (e.g., 4G and 5G) to ensure seamless adaptation during handoff events. In addition, three novel ABR algorithms are introduced using deep reinforcement learning (DRL): a throughput-aware algorithm (THA-P) that directly incorporates predicted throughput into the decision process, a mobility-aware algorithm (MATH-P ABR) that adapts to user movement patterns, and a handoff-aware algorithm (HATH-P ABR) that optimizes decisions during access network transitions. These DRL-based agents are trained and evaluated in realistic mobility and network scenarios.Extensive experiments demonstrate that the proposed methods significantly outperform both heuristic and learning-based ABR algorithms across key QoE metrics, achieving higher bitrate utility, reduced rebuffering durations, smoother bitrate transitions, and improved overall playback quality. The contributions of this work offer a robust and intelligent approach to ABR in mobile and heterogeneous environments, paving the way for next-generation adaptive streaming solutions.College of EngineeringDepartment of Industrial EngineeringPhD in Engineering - Engineering Systems Management (PhD-ESM
Behavior Of Reinforced Concrete Columns Embedded with PET Bottles Under Concentric Axial Compression
No full textA Master of Science thesis in Civil Engineering by Sadiq Duraid Al Bayati entitled, “Behavior of Reinforced Concrete Columns Embedded with PET Bottles Under Concentric Axial Compression”, submitted in June 2025. Thesis advisor is Dr. Sami Tabsh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This research deals with the implementation of Polyethylene Terephthalate (PET) Bottles as void makers in reinforced concrete columns under purely axial compression. Utilization of PET bottles in reinforced concrete structures reduces the amount of concrete used. Moreover, for the same amount of concrete used in a solid and equivalent voided column, the voided column will have greater flexural capacity than the solid one due to the increased moment arm of the steel reinforcement. This proposed construction scheme greatly reduces the pollution that comes with the disposal of PET bottles and amount of concrete. The experimental component of the study consists of testing 16 reinforced concrete columns divided into two groups. One group contained eight 9m long columns having small cross-sections (200mm² solid and 220mm² voided) and another group contained eight 1.1m long columns having large cross-sections (250mm² solid and 350mm² voided). The diameter of the void within the small cross-section group was 100mm while the diameter of the void within the large cross-section group was 265mm. Each category contains 4 solid columns and 4 corresponding voided columns having the same amount of concrete and steel. The experimental program considers variations in the size of the longitudinal steel reinforcement, tie spacing, and concrete compressive strength. The tests are conducted using a UTM machine under displacement-controlled loading condition with help of strain gauges and LVDTs. Analysis of the test results showed that the small columns were slightly impacted by the presence of the void, as the ultimate capacity was reduced by 9%, initial stiffness by 14%, ductility by 20%, and residual strength by 1%. With regards to the large columns, the presence of the void significantly affected structural performance by reducing the ultimate capacity by 24%, initial stiffness by 34%, and ductility by 26%, although the residual strength was increased by 5%. Modelling and analysis by the finite element software ABAQUS showed good agreement with the experimental results. In general, findings from the study demonstrated that reinforced concrete columns containing small voids made with PET bottles that do not take more than 50% of the core can perform fairly well under the action of pure axial compressive loads.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Audit Quality and the Health of the Health Industry
No full textA Master of Business Administration (MBA) thesis by Nour Kousa entitled, “Audit Quality and the Health of the Health Industry”, submitted in May 2025. Thesis advisor is Dr. Feras M. Salama. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Audit quality plays a key role in shaping corporate financial stability, especially in heavily regulated sectors such as pharmaceuticals. While past research has examined the general effects of audit quality on companies, its specific impact on the financial stability of pharmaceutical firms remains underexplored. This study addresses this gap by comparing the United States and European markets, focusing on firms audited by the largest global audit networks (Big Four) versus those audited by smaller audit firms. Using a comprehensive dataset, the analysis reveals that firms audited by the largest global audit networks exhibit lower financial volatility and more stable returns, likely due to enhanced transparency and reduced information asymmetry. In contrast, firms audited by smaller audit firms demonstrate higher average returns but greater instability, suggesting a risk-return trade-off that may appeal to risk-tolerant investors. Notably, the largest global audit networks deliver consistent financial stability in both the United States and Europe, underscoring the robustness of their standardized practices. However, smaller audit firms in Europe show significantly higher volatility than their United States counterparts, implying that regulatory compliance alone does not ensure audit quality. The study also challenges the assumption that frequent auditor rotation improves outcomes; instead, longer auditor relationships, coupled with rigorous standards, may enhance financial oversight, particularly in complex industries like pharmaceuticals. These findings advocate for reconsidering mandatory auditor rotation policies and strengthening oversight of smaller audit firms to improve reporting quality and investor confidence.School of Business AdministrationDepartment of Management, Strategy and EntrepreneurshipMaster of Business Administration (MBA
Artificial Intelligence Driven Electric Vehicle Traction System for Sustainable Transportation
No full textA Master of Science thesis in Electrical Engineering by Shoaib Ahmed entitled, “Optimizing the Performance of a Microwave Tomography System for Biomedical Applications”, submitted in April 2025. Thesis advisor is Dr. Habib ur Rehman and thesis co-advisors are Dr. Usman Tariq and Dr. Ammar Hasan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Increased dependency on fossil fuels as a source of energy has contributed significantly to environmental pollution and rising global temperatures. The automotive industry is making a transition from internal combustion engine (ICE) vehicles that use Gasoline, diesel, or other fossil fuel-dependent energy sources towards battery electric vehicles (BEV) that use an electric motor that can be powered by cleaner modes of energy. However, a significant impediment of BEVs is that lithium-ion batteries have about 100 times less energy density than fossil fuels such as gasoline in terms of both weight and volume. Therefore, a need exists to optimize the performance of lithium-ion batteries to elongate their lifetime. In BEVs, commonly lithium-ion batteries power a field-oriented induction motor drive system that propels the vehicle. The objective of this work is to improve the performance of an indirect field-oriented (IFO) induction motor drive system using three different control approaches and compare their performance in terms of efficient speed regulation and battery energy consumption. The indirect field-oriented control (IFOC) comprises of three control loops: two inner loops control currents while one outer loop regulates the motor speed. The speed control loop is the focus of this study. Firstly, a baseline is developed using a PI controller, which is then replaced by a fuzzy logic controller (FLC) and a reinforcement learning (RL) agent. The FLC and RL above fall under the umbrella of artificial intelligence (AI). Thus, the study aims to investigate and validate that AI can be used to improve the performance of electric vehicles by improving speed regulation, reducing battery energy consumption, and thus increasing the driving range and, hence, the battery lifetime. Also, this study investigates the effect of different control techniques on the battery temperature.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Formal Verification of a Security Protocol in Vehicular Communication
No full textA Master of Science thesis in Computer Engineering by Mohamed Adel Almaazmi entitled, “Formal Verification of a Security Protocol in Vehicular Communication”, submitted in April 2025. Thesis advisor is Dr. Dana Dghaym. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Vehicular communication systems enable vehicles to exchange critical information with other traffic participants, infrastructure, and networks, offering significant benefits for road safety and transportation efficiency. However, designing secure Vehicle-to-Everything (V2X) protocols presents unique challenges as they must simultaneously ensure message authenticity, protect user privacy, prevent attacks, and maintain low computational overhead for time-sensitive applications. Formal verification of these protocols is essential but traditionally complex, as it requires reasoning about both cryptographic mechanisms and system-level properties.
This thesis presents a novel complementary verification approach that combines two formal verification tools, Tamarin Prover for cryptographic analysis with Event-B for system refinement to comprehensively verify V2X security protocols. Using the Anonymous and Efficient (AEE) protocol as a case study, we develop a systematic methodology for translating between formal models, leveraging Tamarin's strength in adversarial reasoning and Event-B's structured refinement capabilities. Our refinement-based approach moves from abstract communication to concrete protocol mechanisms, with Tamarin serving as a cryptographic extension of the most concrete Event-B level. Through this methodology, we verify the AEE protocol's anonymity, traceability, event linkability, and unlinkability properties, while identifying critical requirements not explicit in the original protocol specification, including token-event binding constraints and authority separation mechanisms. The dual-method verification reveals structural insights that would be difficult to obtain using either method alone, providing implementation guidance for secure V2X deployments and establishing a generalized approach for verifying security protocols with complex system interactions. Our results demonstrate that complementary formal methods can provide stronger verification assurance than single-method approaches for safety-critical V2X security protocols.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
A Deep Learning–Blockchain Approach for Cyber-Attack Detection and Prevention in Protection Relays
No full textA Master of Science thesis in Electrical Engineering by Yazan Hisham Barbar entitled, “A Deep Learning–Blockchain Approach for Cyber-Attack Detection and Prevention in Protection Relays”, submitted in April 2025. Thesis advisor is Dr. Ahmed Osman and thesis co-advisor is Dr. Mohamed Hassan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Queuing-Based Optimization of EV Charging Stations: A Case Study of Manama City, Bahrain
No full textA Master of Science thesis in Engineering Systems Management by Hamad A. Rahman Albinali entitled, “Queuing-Based Optimization of EV Charging Stations: A Case Study of Manama City, Bahrain”, submitted in April 2025. Thesis advisor is Dr. Moncer Hariga and thesis co-advisor is Dr. Rami As'ad. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form). Embargo expires July 08, 2026.The transition to electric mobility necessitates proper strategic planning of charging infrastructure to ensure efficiency, accessibility, and user satisfaction. Today, Electric vehicle (EV) charging stations (CSs) must be strategically located to maximize user satisfaction, enhance accessibility, and balance costs for both charging station owners (CSOs) and electric vehicle users (EVUs). However, most existing mathematical models overlook real-world service constraints, often assuming unlimited waiting capacity at CSs. Another often-overlooked aspect in planning EV charging infrastructure is the blocking cost incurred when EVUs arrive at a station that has neither available charging slots nor waiting space. This situation can lead to inefficient and suboptimal infrastructure planning decisions. Additionally, research on the Charging Station Location Problem (CSLP) remains limited in the Middle East, where countries such as the Kingdom of Bahrain (KoB) face significant barriers to EV adoption, such as inadequate charging infrastructure, range anxiety, and policy uncertainty. To address these gaps, this study develops an optimization model for CS deployment considering CSOs and EVUs costs while explicitly accounting for a queuing behavior having a finite queue length. The problem is formulated as a highly complex Mixed-Integer Nonlinear Programming (MINLP) model. To effectively solve this problem, we propose an iterative solution procedure that initially optimizes CSs without considering queuing aspects, including only CSO related and access costs in the objective function. The resulting relaxed problem is formulated as a Mixed Integer Linear Programming (MILP) model and solved through CPLEX optimizer. Subsequently, the results of this MILP model are iteratively refined to incorporate queuing effects, and the process is terminated once no further cost improvements are attained. A case study of Manama City, the capital of the KoB, was conducted to test the model’s ability in identifying the optimal locations for establishing CSs. The results offer practical insights for policy makers and industry stakeholders to develop sustainable and effective EV charging networks in the KoB.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM