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Analyzing hydrodynamic changes in the Dubai Creek: a pre- and post-extension study
No full textA Master of Science thesis in Civil Engineering by Khaled Elkersh entitled, “Analyzing hydrodynamic changes in the Dubai Creek: a pre- and post-extension study”, submitted in November 2023. Thesis advisor is Dr. Serter Atabay and thesis co-advisor Dr. Tarig Ali. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This thesis presents a comparative study that examines the effects of the Dubai Creek extension on its hydrodynamics and water flushing dynamics. Dubai Creek (Khor Dubai) is a 24km artificial seawater stream located in the emirate of Dubai, separating Deira and Bur Dubai. The creek has experienced rapid urbanization with a major 13km extension project, which connected the creek with the Arabian Gulf from the other side. This increase in human activities and rapid development in the Dubai Creek area affects the water quality and the aquatic ecosystem and causes the creek’s water quality degradation. In this project, two-dimensional hydrodynamic and flushing models were created to investigate the water circulation and water quality of the creek before and after the extension. The Old and Existing Creek models were developed using Delft3D Flexible Mesh Suit. The hydrodynamic models were calibrated and validated to accurately simulate water levels and currents with correlation values close to 1 and very small RMSE and Bias. With the output of the hydrodynamic models, flushing models were created to simulate water renewal along the creek. The results of the flushing models showed a significant improvement in the flushing capabilities in terms of residence times of the Existing Creek model compared to the Old Creek model. This improvement emphasized the positive impact of the creek extension project on the local aquatic ecosystem and the overall water quality. Consequently, the created models will serve as a valuable tool for long-term simulations from the past to the present and for future scenarios, which will help the local authorities in decision-making.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Corporate Diversification, Earnings Management, and Financial Statement Readability
No full textA Master of Science thesis in Finance by Hajar El Mouttaqui entitled, “Corporate Diversification, Earnings Management, and Financial Statement Readability”, submitted in November 2023. Thesis advisor is Dr. Feras Salama and thesis co-advisor is Dr. Kimberly Gleason. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).I examine the implications of corporate diversification on the quality of financial reporting measured as earnings management and financial statement readability. The results reveal that diversified firms have a lower degree of earnings management than comparable portfolios of stand-alone firms and that the magnitude of reduction in earnings management increases with higher levels of diversification. Using path analysis, I find evidence that diversification decreases earnings management by reducing both earnings volatility and the need for external financing, and by increasing the propensity to pay dividends. The results are robust to using different measures of diversification and earnings management and continue to hold when I attempt to account for endogeneity using two different methods: the Heckman two-stage model and a propensity score matching analysis. To investigate the effect of diversification on financial statement readability, I use a widely utilized measure of financial statement readability, namely, the Bog Index. The analyses reveal interesting results. First, I document a negative association between diversification and financial statement readability, indicating that diversified firms have less readable annual reports. Second, the negative impact of diversification on readability is attenuated for firms with high ability managers, consistent with the notion that managerial ability is associated with better disclosure quality. These results are robust to using several measures of managerial ability and diversification. In addition, my results do not change when I estimate a Heckman two-stage model to account and correct for any protentional selection bias resulting from the decision to diversify.School of Business AdministrationDepartment of FinanceMaster of Science in Finance (MSF
Breast Density Estimation in Mammograms Using Unsupervised Image Segmentation
No full textA Master of Science thesis in Computer Engineering by Khaldoon Alhusari entitled, “Breast Density Estimation in Mammograms Using Unsupervised Image Segmentation”, submitted in November 2023. Thesis advisor is Dr. Salam Dhou. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Breast cancer, the most prevalent cancer in women as of 2020, poses significant health risks. Early detection is crucial for effective management, and mammography serves as a key screening method. Mammograms, produced through mammography, are x-ray images which allow radiologists to assess mammographic density—a measure of non-fatty tissue in the breast. The Breast Imaging-Reporting and Data System (BI-RADS) is the current standard for density measurement, and it categorizes density into four classes. The importance of studying breast density is twofold. First, high breast density can be a factor in lowering the mammogram sensitivity as dense tissue, which looks bright on a mammogram, can mask cancers in mammograms. Second, higher breast density is associated with an increased risk of breast cancer, making accurate assessments vital. However, challenges arise in interpreting mammograms, particularly regarding inter-observer variability, especially with dense breasts. This work addresses the need for accurate and objective breast density assessments. It proposes a label-noise-tolerant unsupervised-learning-based method for quantitative breast density estimation. The study begins with a comprehensive review of existing literature and state-of-the-art techniques. A framework for breast density estimation is then introduced, involving mammogram preprocessing, unsupervised segmentation, and percentage density estimation. A convolutional neural network (CNN) with a loss function combining similarity and continuity is adapted for segmentation. The framework is tested on two public datasets (DDSM and INbreast), and its segmentation quality, classification capability, and unsupervised labeling ability are evaluated. Silhouette scores exceed 0.92 for subsets of both datasets, demonstrating strong segmentation performance. Per-patient agreements of 71.43% and 79.28% are achieved for DDSM and INbreast datasets, respectively, comparable to state-of-the-art techniques. The clustering quality assessment confirms reasonable unsupervised labeling, with Silhouette scores averaging around 0.57 for DDSM and 0.50 for INbreast. The proposed framework provides a non-subjective model for quantitative breast density estimation. Its potential benefits extend to clinical settings, where it can aid radiologists in assessing breast density.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
INScription: Department of International Studies (INS) Issue #15 (August 31, 2023, Issue 1)
No full textCollege of Arts and SciencesDepartment of International Studie
Blockchain Technology in UAE Construction Projects - Benefits, Applications, And Challenges
No full textA Master of Science thesis in Construction Management by Dania Jamal Abuhalimeh entitled, “Blockchain Technology in UAE Construction Projects - Benefits, Applications, And Challenges”, submitted in April 2023. Thesis advisor is Dr. Sameh El-Sayegh and thesis co-advisor is Dr. Abdulrahim Shamayleh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Construction Management (MSCM
Impact of Ionic Strength and Charge Density on Donnan Potential in the NaCl-Cation Exchange Membrane System
No full textThis work aims to theoretically investigate the effect of both the fixed charge density of ion exchange membranes and the ionic strength of the treated aqueous NaCl solution on the generated Donnan potential at thermodynamic equilibrium conditions. The direct objective of our work is to calculate the equilibrium concentration of the Cl⁻ co-ion inside a swelled cation-exchange membrane equilibrated with a water/NaCl system. Two activity coefficient models are employed, i.e., the Debye–Huckel (DH) model (as a reference model) and the Meissner model, which is known for its applicability in treating concentrated solutions. Experimental data available in the literature for Donnan potential are used to verify model predictions. Our study confirms that a high fixed charge density is required to counterbalance the deterioration in membrane selectivity encountered in high-salinity systems. The DH model can be safely used to predict the Donnan potential for feed compositions up to 0.1 M. At higher compositions, the DH model significantly overestimates the predicted (absolute) Donnan potential compared to the Meissner model. The osmotic pressure resulting from the difference in ionic concentration between the membrane phase and the feed phase is found to have insignificant effects on the Donnan potential. The equilibrium computations and methodology are presented in a general way that enables handling multivalent electrolyte systems such as CaCl₂.American University of Sharja
The Integration of Circular Economy Strategies in the UAE Construction Industry
No full textA Master of Science thesis in Construction Management by Maryam Ali Al Ahimer entitled, “The Integration of Circular Economy Strategies in the UAE Construction Industry”, submitted in November 2023. Thesis advisor is Dr. Salwa Beheiry. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Construction Management (MSCM
Behavior of RC Beams Strengthened with Galvanized Steel Mesh Using U-Wraps and Splay Anchors
No full textA Master of Science thesis in Civil Engineering by Ahmed Hazem Selim entitled, “Behavior of RC Beams Strengthened with Galvanized Steel Mesh Using U-Wraps and Splay Anchors”, submitted in June 2023. Thesis advisor is Dr. Jamal Abdalla and thesis co-advisor is Dr. Rami Hawileh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Stock Return Prediction In Emerging Markets Using Machine Learning
No full textA Master of Science thesis in Engineering Systems Management by Mohamed Shezan Rizny entitled, “Stock Return Prediction in Emerging Markets Using Machine Learning”, submitted in November 2023. Thesis advisor is Dr. Zied Bahroun and thesis co-advisors are Dr. Hussam Alshraideh and Dr. Anis Samet. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Engineering Systems Management (MSESM
Transferrin-Targeted Liposomes in Glioblastoma Therapy: A Review
No full textGlioblastoma (GBM) is a highly aggressive brain tumor, and its treatment is further complicated by the high selectivity of the blood–brain barrier (BBB). The scientific community is urgently seeking innovative and effective therapeutic solutions. Liposomes are a promising new tool that has shown potential in addressing the limitations of chemotherapy, such as poor bioavailability and toxicity to healthy cells. However, passive targeting strategies based solely on the physicochemical properties of liposomes have proven ineffective due to a lack of tissue specificity. Accordingly, the upregulation of transferrin receptors (TfRs) in brain tissue has led to the development of TfR-targeted anticancer therapeutics. Currently, one of the most widely adopted methods for improving drug delivery in the treatment of GBM and other neurological disorders is the utilization of active targeting strategies that specifically target this receptor. In this review, we discuss the role of Tf-conjugated liposomes in GBM therapy and present some recent studies investigating the drug delivery efficiency of Tf-liposomes; in addition, we address some challenges currently facing this approach to treatment and present some potential improvement possibilities.American University of SharjahAl-Jalila FoundationAl Qasimi FoundationPatient's Friends Committee of SharjahBiosciences and Bioengineering Research InstituteGCC Co-Fund ProgramTakamul programTechnology Innovation Pioneer (TIP) Healthcare AwardsSheikh Hamdan Award for Medical SciencesFriends of Cancer Patients (FoCP)Dana Gas Endowed Chair for Chemical Engineerin