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Blood Glucose Regulation Modelling and Intelligent Control
No full textA Master of Science thesis in Mechatronics Engineering by Nabeel Nasar entitled, “Blood Glucose Regulation Modelling and Intelligent Control”, submitted in December 2024. Thesis advisor is Dr. Lotfi Romdhane and thesis co-advisor is Dr. Mohammad Jaradat. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).In this thesis, the Reinforcement Learning - Proportional Integral Derivative (RL-PID) and the Particle Swarm Optimization based Reinforcement Learning – Adaptive Proportional Integral Derivative (PSO-RL-PID) Controllers are used to regulate the blood glucose regulation process. The proposed reinforcement learning algorithm used to train the system is called Twin Delayed Deep Deterministic (TD3) Policy Gradient method. The advantages include delayed policy updates, dual critic function evaluation and consideration of noise, which accounts for measurement noise from the blood glucose sensor. The Bergman Minimal (BM) Model, which is considered a Low Complexity (LC) model and the Li & Kuang (LK) Two Delay Diabetic Patient Model, which is of Medium Complexity (MC) model, are used for the regulation process. The Reinforcement Learning Agent is used to tune the PID parameters. After training, the controller’s performance is analyzed by adding external disturbances simulating meal intakes and a constant band-limited white noise. The results indicate that the proposed controllers are able to regulate the blood glucose level while ensuring that the blood glucose level remains within safe limits. Additionally, performance comparison between the proposed controller and other control techniques is analyzed. The results indicate increased performance and lower error between the desired blood glucose reference and the measured blood glucose reference values in comparison to other AI- based controllers.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR
Blockchain for Sustainability in the Shared Economy: A Platform for Shared Last-Mile Delivery
No full textA Master of Science thesis in Engineering Systems Management by Omar Soubhi Abdulkarim entitled, “Blockchain for Sustainability in the Shared Economy: A Platform for Shared Last-Mile Delivery”, submitted in May 2024. Thesis advisor is Dr. Malick Ndiaye. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The shared economy, which originated in communal resource sharing, evolved with digital platforms like Airbnb and Uber in the early 21st century, transforming various industries. However, literature suggests that while many modern shared economy models have proven to be commercially successful, few of them focus on the prospect of improving sustainability as a primary driver. The purpose of this thesis is to demonstrate the applicability of leveraging blockchain technology to track and improve sustainability in a shared economy scenario, while also contributing to an organization’s financial profit. A use case of shared last-mile delivery is proposed with the help of Ethereum Smart Contracts that will facilitate these instances of sharing on the blockchain, providing trust and transparency between parties. The smart contract was developed and tested on Remix IDE; a development environment commonly used for such purposes. Functionality of the entire smart contract is introduced and explored, including trial runs of each function in the system. Cost analysis shows that the shared delivery model is more cost-effective compared to independent company deliveries, with a 21.7% reduction in total travel distance. Hashgraph is also explored as a potential avenue for reduced processing costs, showcasing significantly reduced costs at the expense of increased novelty and complexity. Finally, a thorough security analysis using several Remix plugins revealed no vulnerabilities and acceptable gas cost efficiency. Five types of security checks, totalling over 200 iterations, showed 100% effectiveness in preventing integer overflow/underflow, blocking unauthorized access, correcting uninitialized storage pointers, optimizing gas usage, and handling exceptions. By providing this platform for shared delivery, the total amount of isolated deliveries, and therefore carbon emissions, will be reduced. This study contributes to the growing body of knowledge in this field and lays the groundwork for future developments and implementations of blockchain-based solutions in shared economies and last-mile delivery.College of EngineeringMultidisciplinary ProgramsMaster of Science in Engineering Systems Management (MSESM
Environmental Sustainability Assessments on Water Distribution Networks: A Life-Cycle Approach
No full textA Master of Science thesis in Construction Management by Abdulaziz Salah Alshaikh entitled, “Environmental Sustainability Assessments on Water Distribution Networks: A Life-Cycle Approach”, submitted in May 2024. Thesis advisor is Dr. Md. Maruf Mortula. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Water Distribution Networks (WDNs) are considered one of the vital aspects in an infrastructure. Their significance in supplying good quality water to the end user is undeniable. Nevertheless, the processes, methods, and materials used to create WDNs are contributing towards increased environmental impacts, threatening the sustainability of the entire water supply system. Depending on its operation and maintenance throughout the life cycle, the environmental impact can be quite significant, threating its functionality, and shortening its service life. The thesis proposes a holistic approach to quantify the environmental sustainability of four different WDNs which are the Grid, Ring, Radial, and Tree WDNs using a life-cycle assessment (LCA) approach. The LCA was done using Simapro 8. The LCA is aimed at quantifying seven different environmental sustainability indicators in the form of Global Warming Potential (GWP), Ozone Layer Depletion (OLD), Cumulative Energy Demand (CED), Air Pollution and Water Pollution, Eutrophication Potential (EP), and Acidification Potential (AP) of each WDN. This will be assessed against each of the material extraction, manufacturing, transportation, and disposal life-cycle phases. The above-mentioned parameters were used to formulate the Environmental Sustainability Model and rank the four WDNs. The model was created to function beyond the reach of the study to investigate the environmental sustainability of any piping material relative to those examined. The results portrayed that the material extraction phase has the greatest influence and emissions in the LCA for each WDN. In addition, the Grid WDN is the most sustainable with an Environmental Sustainability Index (ESI) of 23.9 compared to 24.9 for Tree, 25.0 for Ring, and 25.1 for Radial.College of EngineeringMultidisciplinary ProgramsMaster of Science in Construction Management (MSCM
A Machine Learning Model Based Schedule of Photovoltaic Solar Plant Dust Cleaning
No full textA Doctor of Philosophy Dissertation in Engineering Systems Management by Haneen Mohammad Faleh Abuzaid entitled, “A Machine Learning Model Based Schedule of Photovoltaic Solar Plant Dust Cleaning”, submitted in March 2024. Dissertation advisor is Dr. Mahmoud Awad and dissertation co-advisor is Dr. Abdulrahim Shamayleh. Soft copy is available (Dissertation, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Photovoltaic (PV) systems are widely utilized renewable energy resources, playing a vital role in sustainable energy generation worldwide. Nonetheless, their performance is significantly reduced by dust accumulation, emphasizing the importance of effective cleaning strategies. This research aims to enhance the overall performance of PV systems by improving maintenance practices, particularly focusing on the methods and schedules for PV cleaning. To achieve this, a comprehensive literature review spanning from 2010 to 2024 is conducted, concerning factors influencing PV performance, and current PV cleaning methods, with ongoing discussion and validation from PV experts, actively engaged in the PV field, to bridge theory and practice. The most influential factors include meteorological variables, PV specifications, system design, dust characteristics, sustainability considerations, and operational factors. Using a Multi-Criteria Decision-Making (MCDM) model, specifically the Analytic Network Process (ANP), the study proposes an optimal PV cleaning method, identifying partially automated cleaning as the most suitable for utility-scale PV projects in MENA. Additionally, the research offers a robust cleaning schedule by predicting the PV Performance Ratio (PR), a standardized metric that is widely used in performance-guaranteed contracts, utilizing machine learning algorithms. Two prediction models are proposed: time-series prediction models using LSTM, ARIMA, and SARIMAX algorithms for predicting the PR, and a threshold-based ensemble voting classifier using RF, Log, and GBM for predicting the cleaning process, with three large and distinct datasets validation. Results indicate the efficacy of SARIMAX in PR prediction, with high R2 values and low errors across case studies. The ensemble voting classification model achieves satisfactory performance accuracy in predicting cleaning processes. Notably, PR predictive models outperform cleaning process classification models. Moreover, varying features’ importance outcomes across case studies highlight the necessity of including location-specific conditions for optimal PV cleaning strategy. The findings provide robust guidelines for PV system stakeholders, aiding informed decision-making and enhancing the sustainability of PV cleaning processes.College of EngineeringMultidisciplinary ProgramsPhD in Engineering - Engineering Systems Management (PhD-ESM
The Effect of Terrorism on Consumer Confidence in Europe
No full textA Master of Business Administration (MBA) thesis by Maria Gulzar Sharifullah entitled, “The Effect of Terrorism on Consumer Confidence in Europe”, submitted in December 2024. Thesis advisor is Dr. Khusrav Gaibulloev. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Terrorism studies tend to focus on the macro-economic effects, which seem to be significant in the short-run but insignificant in the long-run, emphasizing the need to develop a deeper understanding of micro-level effects. In particular, the impact of terrorism on the driving force of our economy – consumers – has been underresearched. Using monthly panel data from 23 European countries from 1973-2019, this study examines the effect of terrorism on consumer confidence in Europe. To test this micro-level relationship, we use a unique identification strategy, where we exploit the inherent randomness in the success or failure of an attack in order to overcome endogeneity issues and establish a direct causal relationship. We, therefore, directly compare the effect of successful attacks to failed attacks on consumer confidence. Our results reveal that compared to failed attacks, successful attacks lead to a significant and persistent negative impact on consumer confidence.School of Business AdministrationDepartment of Management, Strategy and EntrepreneurshipMaster of Business Administration (MBA
A Framework for Peer-to-Peer (P2p) Electricity Trading in Distribution Networks
No full textA Doctor of Philosophy Dissertation in Engineering Systems Management by Ahmed Hassan Al Marzooqi entitled, “A Framework for Peer-to-Peer (P2p) Electricity Trading in Distribution Networks”, submitted in May 2024. Dissertation advisor is Dr. Ahmed Osman-Ahmed and dissertation co-advisor is Dr. Mostafa Shaaban. Soft copy is available (Dissertation, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The introduction of the Smart Grid has resulted in many applications that have been developed and followed the concept of bidirectional flow of electricity and data. One of the pillars of smart grids is the distributed generation (DG) technologies, where the customers turn to be prosumers with power generation capability. Another pillar is demand side management (DSM), which helps in controlling the energy consumption by changing the power usage slots among other peers. DG and DSM have facilitated the sharing of excess power by customers to the grid, and then to their peers through the grid as a trading agent. Although the concept of peer-to-peer (P2P) energy trading integrated with DSM has been explored by scholars and relative trading frameworks have been established, there is very limited research on the impact of power quality (PQ) and supply reliability (SR) on electricity transactions. The aim of this study is to explore the perception of P2P electricity trading within the Power Distribution Network in the United Arab Emirates and to build a Peer-to-Peer energy trading framework considering power quality and supply reliability. The proposed study will encounter the reliability performance of the participants, minimize the power quality impact, and manage the energy management system using game theory. The customer perception and satisfaction level with the quality of supply evolving energy trading have been explored and results were discussed in the study. The proposed P2P framework resulted in reduction of the trading cost through applying a profit sharing scheme and using reliability pricing scheme, and provides a foundation base to the utilities as well as individuals to the changes in the electricity market structure with new business opportunities for the utilities.College of EngineeringMultidisciplinary ProgramsPhD in Engineering - Engineering Systems Management (PhD-ESM
Waste Separation Behavior Among UAE Students: An Exploratory Study
No full textA Master of Business Administration (MBA) thesis by Aaliya Ahammed entitled, “Waste Separation Behavior Among UAE Students: An Exploratory Study”, submitted in November 2024. Thesis advisor is Dr. Marie- France Waxin. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).The rapid increase in waste generation has become a significant challenge for many countries, including the UAE, driven by urbanization, economic growth, and changing consumption patterns. Waste Separation Behavior, a key component of effective waste management, involves the sorting of discarded materials for recycling and composting. Despite the growing importance of sustainable waste practices, there remains a substantial gap in understanding the determinants of Waste Separation Behavior, particularly among university students in the UAE. This study aims to bridge this gap by quantitatively exploring the factors influencing Waste Separation Behavior through the lens of the Theory of Planned Behavior. The research examines the role of psychological constructs—attitude, subjective norms, and perceived behavioral control—alongside personal and factors that shape students’ intentions and behaviors related to waste separation. We used a quantitative, self-administered questionnaire to collect data from 66 students at the American University of Sharjah, in the United Arab Emirates, and we analysed the data using descriptive statistics. The descriptive findings reveal positive attitudes toward Waste Separation Behavior among students but highlight a gap between their intentions and actual behaviors. This discrepancy underscores the presence of psychological barriers that hinder consistent engagement in waste separation.The study contributes to the existing literature by offering a quantitative exploratory description of Waste Separation Intention, Waste Separation Behavior, and their key antecedents within the unique cultural context of the UAE. Practical implications include actionable recommendations for policymakers and educational institutions aimed at enhancing sustainable waste practices through targeted interventions. Ultimately, this research provides valuable insights into the psychological and contextual factors influencing Waste Separation Behavior among university students, laying the foundation for future studies and effective policy initiatives in the UAE.School of Business AdministrationDepartment of Management, Strategy and EntrepreneurshipMaster of Business Administration (MBA
Effect of Strain Fields on Frequency Band Gaps of Periodic Lattice-Based Metamaterials
No full textLattice-based metamaterials, known for their ability to deliver unique acoustic properties such as wave band gaps and direction-dependent phase velocities, are considered promising for noise filtering and acoustic sensor applications. Lattice-based metamaterials’ unique acoustic abilities arise from their periodic porous structures, allowing them to be realized even when the lattices are made from isotropic materials. The properties of lattice metamaterials are primarily determined by their inner microstructure (i.e., topology and morphology). Consequently, by designing their inner microstructure, it is possible to tune their properties to filter or detect specific frequencies. Varying the topology of lattice metamaterials has been shown to affect their acoustic properties significantly. However, this work focuses on the effect of morphological changes, particularly stretching, on their acoustic properties. Stretching can be achieved by mechanically deforming lattice metamaterials using external forces or by constructing them from active constituents such as piezoelectric materials. The overall goal of this work is to assist in developing lattice metamaterial that can deliver deformation-tunable acoustic properties. This work computationally investigates the effect of stretching strain fields on a hexagonal lattice-based metamaterial. In particular, it examines the effects of small and large strain fields on the frequency band gaps between 100kHz and 1000kHz. Different strain levels are used to determine the sensitivity of frequency band gaps to stretching strains. The results show that the frequency band gaps are insensitive to small strains at low frequencies (~100kHz) but are sensitive to small strains at higher frequencies (~1000kHz). Conversely, large strains significantly affect the frequency band gaps, resulting in the shift, creation, or cancelation of band gaps. The findings demonstrate that actuating lattice-based metamaterial can effectively tune their frequency band gaps
Polymer-Coated Metal Organic Framework for Drug Delivery
No full textA Master of Science thesis in Chemical Engineering by Tasneem Jassim Aljassim entitled, “Polymer-Coated Metal Organic Framework for Drug Delivery”, submitted in May 2024. Thesis advisor is Dr. Rana Sabouni. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).In this Thesis, a nanocarrier has been designed to deliver an anticancer drug with a good loading capacity and release efficiency. The Doxorubicin hydrochloride drug (DOX) was loaded into MIL-53(Al) MOF and two different polymers were used to coat the loaded MOFs separately, Sodium alginate (SA) and Polyvinyl alcohol (PVA) polymers to ensure the drug is protected from leaking out through the delivery process. Both 7.4 and 5.3 pH environments were used to test the DOX release from the nanocarrier. In addition, UV light was employed as an external stimulus to test the drug release. For Sodium alginate polymer coated nanocarriers (DOX@ MIL-53(Al)@SA), the average release of the drug was observed to be 27.27% and 30.92% at 5.3 and 7.4 pH, respectively, when exposed to UV light. However, under a controlled environment (water bath of 37 C°), it was observed to be 8.30% and 7.34% at 5.3 and 7.4 pH, respectively. When exposed to UV light, the average drug release for Polyvinyl alcohol polymer coated nanocarriers (DOX@ MIL-53(Al)@PVA) was 26.4% and 5.54% at 5.3 and 7.4 pH, correspondingly. In a controlled environment (water bath of 37 C°), it was observed to be 8.02% and 5.31% at 5.3 and 7.4 pH, respectively. A shaking experiment was also done on DOX@MIL-53(Al)@SA, DOX@MIL-53(Al)@PVA, and DOX@MIL-53(Al) to test the drug release at pH 7.4. We observed that PVA-coated nanoparticles showed the least release indicating that PVA polymer is pH and Light responsive polymer. Different characterization tests were performed, XRD, TGA, BET, EDX, SEM, and FTIR on (DOX@MIL-53(Al)@SA) and (DOX@MIL-53(Al)@PVA) samples before and after coating to confirm the efficiency of the delivery process of the guest molecule (DOX). Each advancement in drug delivery technology makes cancer treatment more targeted and less invasive. As a result of our commitment to improve drug delivery methods, our goal is to increase the effectiveness of anticancer therapies.College of EngineeringDepartment of Chemical and Biological EngineeringMaster of Science in Chemical Engineering (MSChE
A mixed finite element method for nonlinear radiation–conduction equations in optically thick anisotropic media
No full textWe propose a new mixed finite element formulation for solving radiation–conduction heat transfer in optically thick anisotropic media. At this optical regime, the integro-differential equations for radiative transfer can be replaced by the simplified Pɴ approximations using an asymptotic analysis. The conductivity is assumed to be nonlinear depending on the temperature along with anisotropic absorption and scattering depending on both the direction and location variables. The simplified Pɴ approximations are enhanced by considering a diffusion tensor capable of describing anisotropic radiative heat transfer. In the present study, we investigate the performance of the unified and mixed formulations combining cubic P₃, quadratic P₂, and linear P₁ finite elements to approximate the temperature in the simplified P₃ model. To demonstrate the performance of the proposed methodology, three-dimensional examples of nonlinear radiation–conduction equations in optically thick anisotropic media are presented. The obtained numerical results demonstrate the accuracy and efficiency of the proposed mixed finite element formulation over the conventional unified finite element formulation to accurately solve the simplified P₃ equations in anisotropic media.Royal Society, UKAmerican University of Sharja