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No full textCollege of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Edge-Optimized Deep Learning Architectures for Classification of Agricultural Insects with Mobile Deployment
No full textThe deployment of machine learning models on mobile platforms has ushered in a new era of innovation across diverse sectors, including agriculture, where such applications hold immense promise for empowering farmers with cutting-edge technologies. In this context, the threat posed by insects to crop yields during harvest has escalated, fueled by factors such as evolution and climate change-induced shifts in insect behavior. To address this challenge, smart insect monitoring systems and detection models have emerged as crucial tools for farmers and IoT-based systems, enabling interventions to safeguard crops. The primary contribution of this study lies in its systematic investigation of model optimization techniques for edge deployment, including Post-Training Quantization, Quantization-Aware Training, and Data Representative Quantization. As such, we address the crucial need for efficient, on-site pest detection tools in agricultural settings. We provide a detailed analysis of the trade-offs between model size, inference speed, and accuracy across different optimization approaches, ensuring practical applicability in resource-constrained farming environments. Our study explores various methodologies for model development, including the utilization of Mobile-ViT and EfficientNet architectures, coupled with transfer learning and fine-tuning techniques. Using the Dangerous Farm Insects Dataset, we achieve an accuracy of 82.6% and 77.8% on validation and test datasets, respectively, showcasing the efficacy of our approach. Furthermore, we investigate quantization techniques to optimize model performance for on-device inference, ensuring seamless deployment on mobile devices and other edge devices without compromising accuracy. The best quantized model, produced through Post-Training Quantization, was able to maintain a classification accuracy of 77.8% while significantly reducing the model size from 33 MB to 9.6 MB. To validate the generalizability of our solution, we extended our experiments to the larger IP102 dataset. The quantized model produced using Post-Training Quantization was able to maintain a classification accuracy of 59.6% while also reducing the model size from 33 MB to 9.6 MB, thus demonstrating that our solution maintains a competitive performance across a broader range of insect classes.College of EngineeringDepartment of Computer Science and Engineerin
Assessing Key CE Strategies to Advance UAE Construction Circular Economy Practices
No full textA Master of Science thesis in Construction Management by Mark Moheb Wasef entitled, “Exploring the Transformative Potential of Generative AI in Mechanical Engineering Education”, submitted in April 2025. Thesis advisor is Dr. Sameh El-Sayegh and thesis co-advisor is Dr. Sherif Yehia. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Concrete being the most utilized material in the world will face many issues in the future and overcoming them will need the implementation of circular economy strategies. Though research interest in creating Circular Economy (CE) strategies for concrete is growing quickly, much of it has concentrated on technical and environmental problems at the material and product scale. However, there has not been clear strategies identified and their method of implementation in various stages of a construction project. Furthermore, there has not been holistic approaches on how CE will contribute towards achieving the Sustainable Development Goals (SDGs). The main objective of this study is to identify and rate the relative importance of CE strategies, contributing towards achieving CE in the UAE construction sector. This could be achieved by identifying and assessing the CE strategies that shape how these CE strategies can be achieved and integrating them into construction practices. After an extensive literature review, 17 CE strategies were identified that can be utilized by construction leaders to adopt CE in construction projects. Furthermore, a cross-sectional survey was conducted among various local and international construction firms and 60 responses from experienced professionals in the industry were obtained. Relative importance index and principal component factor analysis (PCFA) were adopted to evaluate the obtained data. Key significant CE strategies for construction professionals to propel circular construction were identified such as specification writing for components and materials, designing for multiple-use cycles, and designing for near-zero energy buildings, among others. Three components were extracted from the PCFA which served as guidelines for enhancing the CE strategies of construction professionals, namely, Effective Collaboration and Coordination Techniques, Sustainable Project and Operations Management, and Sustainable Design Practice. In addition, to enhance its practical implications, a competency implementation framework was also developed for construction professionals of developing economies to propel the adoption and evaluation of their competency skills toward circular construction.College of EngineeringDepartment of Civil EngineeringMaster of Science in Construction Management (MSCM
Impact of Digital Transformation on Accounting Systems in the UAE’s Aviation Industry
No full textA Master of Science thesis in Accounting (MSA) by Salama Obaid Khalaf Bin Tooq Almarri entitled, “Impact of Digital Transformation on Accounting Systems in the UAE’s Aviation Industry”, submitted in April 2025. Thesis advisor is Dr. Eid Alotaibi. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).School of Business AdministrationDepartment of AccountingMaster of Science in Accounting (MSA
Electric Vehicle Batteries’ Lifecycle Management
No full textA Master of Science thesis in Mechanical Engineering by AbdulRahman Salem entitled, “Electric Vehicle Batteries’ Lifecycle Management”, submitted in October 2025. Thesis advisor is Dr. Basil Darras and thesis co-advisor is Dr. Mohammad Nazzal. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The global transition toward clean energy caused the automotive industry to embrace electric vehicle (EV) production. EVs using clean renewable energy are expected to have significantly lower environmental impact compared to conventional internal combustion vehicles. However, the recycling of EV batteries causes several environmental issues. For instance, the disposal of leaching solutions used in leaching lithium from Li-ion batteries causes soil and water eutrophication. Furthermore, pyrolysis of battery packaging and Printed Circuit Boards (PCBs) containing polymers releases toxic polybrominated fumes, dioxins and furans to the environment. Moreover, most EV batteries are disposed of without utilizing their full potential. EV batteries become unfit for EV use once they lose 20% of their original capacity, which leaves 80% of their capacity untapped. To address these issues, this research developed three decision making frameworks. The first framework provides a blueprint to identify Key Performance Indicators (KPIs) and the decision making process for the selection of battery State of Health (SOH) estimation models responsible for determining EV batteries’ viability for second use options. The second framework introduces a general EV battery management system presented a sorting mechanism capable of 98% sorting consistency, superior to contemporary machine learning models (85 – 90%) used in EV battery health monitoring and management frameworks. Additionally, the sorting framework utilizes a QR code-based Matlab program to identify battery KPIs and assign them accordingly to their appropriate end destination in either renewable energy applications or refurbishing and recycling centers. Moreover, this framework outlines the line of interaction between users, manufacturers and governments to facilitate handling and retrieval of end-of-life EV batteries. Lastly, a third framework was developed to facilitate battery material selection for future EV applications based on holistic KPIs identified from scientometric analysis and literature review of battery material technology advance ments. Multiple case studies validated the flexibility, robustness, and effectiveness of the proposed frameworks in decision-making and end-of-life battery management. The frameworks can be adopted by government entities for sorting used and spent EV batteriesCollege of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
A Decision Support Tool for Optimizing Carbon Sequestration of Desert Plants- A Sharjah Case Study
No full textA Doctor of Philosophy Dissertation in Engineering Systems Management by Israa Falah Mahdi Al Khaffaf entitled, “A Decision Support Tool for Optimizing Carbon Sequestration of Desert Plants- A Sharjah Case Study”, submitted in October 2025. Dissertation advisor is Dr. Adil Tamimi and dissertation co-advisor is Dr. Abudullah Belhaif AL Nuaimi. Soft copy is available (Dissertation, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Industrial EngineeringPhD in Engineering - Engineering Systems Management (PhD-ESM
Thermal Management System Optimization for Electronics Using Loop Heat Pipe, Guided by Hybrid Heat-Sink Benchmarks, to Enhance Energy Efficiency and Sustainability
No full textA Master of Science thesis in Mechanical Engineering by Kareem Morsi entitled, “Thermal Management System Optimization for Electronics Using Loop Heat Pipe, Guided by Hybrid Heat-Sink Benchmarks, to Enhance Energy Efficiency and Sustainability”, submitted in October 2025. Thesis advisor is Dr. Mohammad O. Hamdan and thesis co-advisor is Dr. Bassam Abu Nabah. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Reliable thermal management remains a critical challenge in compact, moderate-to-high-flux electronic systems, where conventional cooling methods often fail to ensure efficiency and orientation independence. This thesis experimentally investigates two classes of thermal management solutions: (i) Part A: hybrid heat sinks that integrate multiple passive techniques, including fins, phase change materials (PCMs), metal foams, and heat pipes, and (ii) Part B: a flat-evaporator loop heat pipe (LHP).In Part A, eight hybrid sink configurations were tested under heat fluxes of 1000–2000 W/m². PCM-based designs provided effective thermal buffering but suffered from low conductivity. Incorporating metal foam improved melt uniformity, and heat pipes enabled rapid heat spreading. The highest performance was achieved with the combined PCM–foam–heat pipe arrangement, although operating temperatures remained higher than those achieved with the LHP. In Part B, a custom flat-evaporator LHP was fabricated and evaluated up to 23 kW/m² while varying filling ratio, wick pore size, wick material, and orientation. At the lowest flux tested (1000 W/m²), the evaporator stabilized near the expected saturation temperature of water at reduced pressures (~32-36 °C). With increasing heat flux, evaporator temperatures rose significantly, with the evaporator-to-condenser temperature difference of approximately 4 °C at low fluxes and about 25 °C at higher loads. Optimal performance was observed at 55–60% filling ratios and ~5 μm pore size. Polytetrafluoroethylene (PTFE) wicks excelled at low fluxes due to high porosity and wettability, whereas stainless steel wicks performed better at high heat fluxes due to their superior thermal conductivity. Gravity-assisted orientations reduced evaporator-to-condenser temperature difference, whereas adverse orientations-imposed performance penalties but maintained system stability. The findings confirm that, while hybrid heat sinks offer incremental benefits, the LHP provides a superior and scalable solution for high-flux electronics and aerospace applications.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Acetone Sensor Readout Circuit for Noninvasive Diabetes Diagnosis and Monitoring
No full textA Master of Science thesis in Biomedical Engineering by Joel Nabil Georgeous entitled, “Acetone Sensor Readout Circuit for Noninvasive Diabetes Diagnosis and Monitoring”, submitted in May 2025. Thesis advisor is Dr. Lutfi Albasha and thesis co-advisor is Dr. Ghaleb Husseini. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This thesis explores the development of a breath acetone sensor readout method for the non-invasive monitoring and diagnosis of diabetes mellitus (DM). DM is a chronic metabolic disorder characterized by insufficient insulin production or its impaired use in the cells, leading to a high blood glucose level. This disease requires constant monitoring of blood glucose levels. Traditional blood glucose monitoring techniques are invasive and inconvenient, highlighting the need for non-invasive alternatives. Breath acetone, a byproduct of fat metabolism in diabetic patients, has been identified and used as a biomarker for diabetes as it is directly related to blood glucose levels. Its concentration is significantly higher in the breath of diabetic patients, making it an effective indicator of the disease’s progression. This research aims to develop a real-time, precise readout method for a highly selective and sensitive acetone sensor developed previously in the literature. The sensor utilizes a capacitive measurement technique where its dielectric constant varies with acetone concentrations. A capacitive readout circuit processes the sensor’s output, which converts capacitance to a DC output voltage. The capacitance is measured through a series of inverters that output a pure square wave. The phase shift in the square wave is correlated with a change in the sensor’s capacitance. A subtractor op-amp finds the difference between the original square wave and the one with a phase shift. A passive low-pass filter finds the average of the difference output signal, generating a DC signal with a value corresponding to the difference extent. Next, the signal is processed in a microprocessor that displays health information on a graphic user interface (GUI).College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
The Impact of Fintech on Bank Cost Efficiency
No full textA Master of Science thesis in Finance (MSF) by Yasamin Babaei entitled, “The Impact of Fintech on Bank Cost Efficiency”, submitted in May 2025. Thesis advisor is Dr. Ali Mirzaei. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).School of Business AdministrationDepartment of FinanceMaster of Science in Finance (MSF
Adaptive Hybrid Sensor Fusion for Enhanced Outdoor Vehicle Localization in Complex Environments
No full textA Master of Science thesis in Mechatronics Engineering by Mohammad Khaled Abdelazim Rashwan entitled, “Adaptive Hybrid Sensor Fusion for Enhanced Outdoor Vehicle Localization in Complex Environments”, submitted in April 2025. Thesis advisor is Dr. Mamoun Abdel-Hafez and thesis co-advisor is Dr. Mohammad Jaradat. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR