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A Machine Learning Approach on Chest X-Rays for Pediatric Pneumonia Detection
No full textA Master of Science thesis in Engineering Systems Management by Natali Imad Barakat entitled, “A Machine Learning Approach on Chest X-Rays for Pediatric Pneumonia Detection”, submitted in June 2022. Thesis advisor is Dr. Mahmoud Awad and thesis co-advisor is Dr. Bassam Abu-Nabah. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Pneumonia is a highly infectious respiratory disease that can be fatal if left untreated. According to the World Health Organization (WHO), pneumonia is the leading infectious cause of death in children younger than 5 years old. Hence, the early detection of pediatric pneumonia is crucial to reduce its morbidity and mortality rate. Even though chest radiography is the most commonly employed modality for pneumonia detection, recent studies highlight the existence of poor interobserver agreement in the chest x-ray interpretation of healthcare practitioners when it comes to diagnosing pediatric pneumonia. Hence, there is a significant need for automating the detection process to minimize the potential human error. Since Artificial Intelligence (AI) tools such as Deep Learning (DL) and Machine Learning (ML) have the potential to automate disease detection, many researchers explored how such tools can be implemented to detect pneumonia in chest x-rays. Notably, the majority of efforts tackled this problem from a DL point of view. However, DL models can be impractical as they possess low medical interpretability. In contrast, ML has been shown to possess a higher potential for medical interpretability while being less computationally demanding than DL. Thus, the objective of this research is to investigate the interpretability of several ML models trained using features extracted from either full or cropped x-rays in order to aid medical practitioners in accurately and reliably diagnosing pediatric pneumonia in chest x-ray images. The performance of these models is compared to a Transfer Learning (TL) benchmark to assess their candidacy. Notably, the results demonstrate that the Logistic Regression (LR) model performs best on cropped images in terms of interpretability while yielding a recall value of 94.07%, which is around 4% less than that of the TL benchmark. However, the added interpretability of the LR model compensates for the slight decrease in model performance when compared to the TL benchmark.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
The Assessment and Allocation of Public Private Partnership Risks in the UAE
No full textA Master of Science thesis in Construction Management by Mazhd Shaban entitled, “The Assessment and Allocation of Public Private Partnership Risks in the UAE”, submitted in April 2022. Thesis advisor is Dr. Irtishad Ahmad and thesis co-advisor is Dr. Sameh El-Sayegh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Public Private Partnerships (PPP) is a project delivery method used primarily for large civil infrastructure projects. It is an effective way to mitigate financial burdens on public sector entities. PPP arrangements have been extensively used by many developed and developing countries over the last few decades. Even developed countries are adopting this method to mitigate exorbitant financial demands of infrastructure projects. Yet, some countries such as the United Arab Emirates (UAE) have not embraced PPPs extensively. The UAE government is currently promoting the use of PPPs with the aim of attaining economic diversification and attracting foreign investment. However, risk management, which is an essential process in the development of PPP projects, is not properly understood and practiced in UAE. This lack of understanding diminishes chances of achieving success in a PPP project. Therefore, in order to satisfy the increasing need for PPP projects this thesis aims at identifying, assessing, and allocating the critical PPP risks in the UAE. Initially 55 PPP risks were identified and categorized through an extensive literature survey. These identified risks were then assessed based on the opinions of professionals experienced in PPP projects in the UAE. A survey was distributed, and the opinions of 53 respondents were obtained. The survey results were then used to assess and rank the identified risks using the Weighted Average (WA) and Monte Carlo Simulation (MCS) techniques. The outcome of the WA approach found no risks to be critical, while the more effective MCS approach found 23 critical risks. Lastly, the 23 critical risks were allocated using a machine learning technique, the Artificial Neural Networks (ANN) algorithm. At first, 25 risk allocation input parameters were identified through the literature review. Then a survey, to identify projects, was distributed globally. A sample size of 74 projects was collected. The survey responses were used to build and train a ‘classification ANN model’ for each risk. Most of the ANN models showed testing accuracies within the 65% -100% range. The models were then tested on two PPP projects in the UAE. Most of the models were capable of successfully predicting the risk allocation among the stakeholders.College of EngineeringMultidisciplinary ProgramsMaster of Science in Construction Management (MSCM
A Study and Assessment of the Status of Energy Efficiency and Conservation at School Buildings
No full textThe building sector consumes a significant portion of global energy use. In this regard, this work was undertaken to study the status of energy efficiency and conservation at a large school building in the northern part of United Arab Emirates (UAE). The annual electrical consumption at the school was analyzed and an awareness survey among the students and teachers was conducted to measure the level of awareness as well as to assess the current energy consumption practices. In order to identify energy saving opportunities, an energy audit was carried out wherein the school energy consuming systems, particularly the lighting and air-conditioning systems, were assessed. Furthermore, thermography scanning of the school building envelope was conducted to examine the building insulation and identify air leakage locations. The building electricity supply and distribution systems were assessed using power analyzer and thermography devices. The energy conservation measures identified include removing the extra lighting, installing motion sensors in classrooms and labs, as well as integrating a Networked Optimization Software with the current HVAC (heating, ventilating and air conditioning) system. The methodology consists of seven fundamental steps: (1) case study data collection (analysis of buildings and utility data); (2) survey of real operation conditions; (3) understanding of building behavior; (4) analysis of energy conservation measures; (5) estimation of energy-saving potential; (6) economic assessment; and (7) proposing Energy Conservation Measures (ECMs). In this regard, the school energy consuming systems (lighting, building envelope, and air conditioning (AC)) were examined to identify possible ways to reduce the school energy consumption. The results indicate that the cost of installing motion sensors in classrooms, and labs is approximately AED 20,000 (United Arab Emirates Dirham), which yields an annual energy saving of AED 93,691. Furthermore, with all energy saving measures, a total annual saving of AED 364,000 is anticipated, which is approximately 16% of the annual electricity bill.American University of Sharja
Hydrodynamic Modelling of Sharjah lagoons (UAE) under Climate Changes
No full textA Master of Science thesis in Civil Engineering by Mohamed Nashaat Singer entitled, “Hydrodynamic Modelling of Sharjah lagoons (UAE) under Climate Changes”, submitted in April 2022. Thesis advisor is Dr. Serter Atabay and thesis co-advisor is Dr Georgenes Cavalcante. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Global warming has become a growing issue, especially because it is causing a rise in sea level which in turn has contributed to increased inundation areas and flooding risks. More specifically, the sea level in the Arabian Gulf is predicted to continue rising during the 21st century, which will certainly intensify coastal hazards in lagoons located in the United Arab Emirates. Such a combination of natural and anthropogenic stressors is expected to affect the internal hydrodynamics of the system, modifying its efficiency in exchanging water and altering the spatial residency time; this may result in a noticeable degradation of the water quality of lagoons. In the Emirate of Sharjah, the lagoons of Al Khalid, Al Khan and Al Mamzar are among the most important natural assets because they play an essential role in the coastal socioeconomic environment and, more importantly, because the hydrodynamics of these lagoons in the context of climate change has never been studied. This thesis, therefore, focuses on developing a hydrodynamic model using the Delft 3-D FM (Flexible mesh) on Sharjah Lagoons to determine the water circulation and residence time variability under present and future projected 1 m sea level rise in the next 100 years. The results from the model show that a 1 m sea level rise increased the tidal range by around 35% and the current velocity inside the lagoon from 0.31 m/s (present) to 0.43 m/s (future), with maximum currents of 1.4 m/s occurring near the tidal inlet during the flood tide and 0.8 m/s during ebb tide. The increase in the water speed improves the water circulation, reducing the residence time significantly inside the lagoons. The inner areas of the lagoon experienced increased residence times compared to the outer regions of the lagoon which may impact water quality status for inner regions. Overall, the residence time was reduced from 27 days (present) to 14 days (future), reflecting a 50% reduction. In that sense, considering a 1m sea level rise in the new hydrodynamics will be more efficient in dispersing materials out of the lagoons.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Energy assessment of an integrated hydrogen production systemEnergy assessment of an integrated hydrogen production system
No full textHydrogen is believed to be the future energy carrier that will reduce environmental pollution and solve the current energy crisis, especially when produced from a renewable energy source. Solar energy is a renewable source that has been commonly utilized in the production process of hydrogen for years because it is inexhaustible, clean, and free. Generally, hydrogen is produced by means of a water splitting process, mainly electrolysis, which requires energy input provided by harvesting solar energy. The proposed model integrates the solar harvesting system into a conventional Rankine cycle, producing electrical and thermal power used in domestic applications, and hydrogen by high temperature electrolysis (HTE) using a solid oxide steam electrolyzer (SOSE). The model is divided into three subsystems: the solar collector(s), the steam cycle, and an electrolysis subsystem, where the performance of each subsystem and their effect on the overall efficiency is evaluated thermodynamically using first and second laws. A parametric study investigating the hydrogen production rate upon varying system operating conditions (e.g. solar flux and area of solar collector) is conducted on both parabolic troughs and heliostat fields as potential solar energy harvesters. Results have shown that, heliostat-based systems were able to attain optimum performance with an overall thermal efficiency of 27% and a hydrogen production rate of 0.411 kg/s, whereas, parabolic trough-based systems attained an overall thermal efficiency of 25.35% and produced 0.332 kg/s of hydrogen
Applying Thematic Analysis to Psychological Cultural Research
No full textPresented for International Association for Cross-Cultural Psychology (IACCP) Culture & Psychology Summer School, July 4-6, 2022.In this workshop, students will be asked to bring qualitative data that they have collected for one of their own research projects. We will read and discuss Braun and Clarke’s (2006) classic article, Using Thematic Analysis in Psychology. After this foundational discussion, students will develop a coding scheme for their data and work to code their data. They will then work in pairs to achieve reliability in each partner’s data coding. After this, with time remaining, students will begin to draft a findings/results section for a publishable manuscript based on their data coding. Students who wish to participate in the workshop but who do not have their own data to analyze will be paired with a student who have data; in this way, even students without data will gain important experience in qualitative analysis
Modeling of In vitro Release Kinetics of Ultrasound-triggered Targeted Liposomes
No full textA Master of Science thesis in Biomedical Engineering by Zeyad Mohamed Almajed entitled, “Modeling of In vitro Release Kinetics of Ultrasound-triggered Targeted Liposomes”, submitted in April 2022. Thesis advisor is Dr. Ghaleb Husseini. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Ultrasound-triggered, targeted liposomes are a promising drug delivery system as they potentially improve the clinical outcomes of chemotherapy while reducing associated side effects. However, the common drug release models used in pharmaceutical studies do not accurately fit the in-vitro release profiles found in stimuli-responsive or externally-activated drug delivery systems. This presents a challenge for these drug delivery systems, as predictable and stable release profiles are necessary for clinical work. Ideally, the design process of targeted nanoparticles should predict the release behavior of the nanoparticles, at least in-vitro and, eventually, in vivo. This requires models that incorporate properties that influence sonosensitivity of the drug delivery particles. In this work, we perform a comprehensive model fitting of a large data set of liposomal release data with 7 targeting moieties in addition to the control (Albumin, cRGD, Estrone, Hyaluronic acid, Herceptin, Lactobionic acid, and Transferrin) under ultrasound release protocols using low frequency (20 kHz) ultrasound at 6.2, 9 and 10 mW/cm² as well as high frequencies (1.07 MHz and 3 MHz) at power densities of 10.5 (1 MHz), 50 (1 MHz), and 173 W/cm² (3 MHz). The release models we use are Zero-order, First-order, Higuchi, Korsmeyer Peppas, Weibull, Hixon Crowell, Baker Lonsdale, Gompertz, Hopfenberg, the novel Lu Hagen model and a third-order polynomial fit. We then establish the models that fit best under varying conditions of ultrasound release frequencies and power densities. Additionally, we show an empirical mathematical relationship between the molecular weight and pKa value (negative log of the acid dissociation constant) of the moieties and the release coefficients for two single coefficient models, the zero-order model and a fixed power Korsmeyer Peppas model. This is an important step in modeling the responsiveness of targeted liposomes and enables better prediction of in vitro liposomal release performance.College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
A one-dimensional flux-based thermography for thermal diffusivity estimation in metallic alloys
No full textA Master of Science thesis in Mechanical Engineering by Ahmed Elsheikh entitled, “A one-dimensional flux-based thermography for thermal diffusivity estimation in metallic alloys”, submitted in October 2022. Thesis advisor is Dr. Bassam A. Abu-Nabah and thesis co-advisor is Dr. Mohamed O. Hamdan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This work proposes a simple one-dimensional (1D) thermography technique to estimate a metallic alloy thermal diffusivity by employing a uniform flux-based heating source. A theoretical model is developed and validated to account for the sample dimensions, material thermal properties and the sample initial and boundary conditions. These conditions include the sample initial temperature, the effective convection heat transfer coefficient with the surrounding environment and the uniform heat flux supplied to the sample. The adopted theoretical model is tested against simulated thermal measurements to retrieve a sample unknown boundary conditions along with the material thermal diffusivity of interest following the Nelder-Mead optimization approach, which offers a high flexibility to the proposed technique. This technique is experimentally validated over a tempered aluminum alloy (Al-2024 T4) of relatively high thermal diffusivity and a one-order of magnitude lower thermal diffusivity annealed stainless-steel alloy (SS-304) delivering an uncertainty lower than 2% in material thermal diffusivity estimation.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Multi-Objective Co-optimization of Power and Gas under Uncertainties with P2H embedded
No full textA Master of Science thesis in Electrical Engineering by Rawan Yousef Ali Abdallah entitled, “Multi-Objective Co-optimization of Power and Gas under Uncertainties with P2H embedded”, submitted in April 2022. Thesis advisors are Dr. Mostafa Shaaban and Dr. Ahmed Osman-Ahmed. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The need for developing planning studies that detect new requirements and explore the threats and doubts associated with the long-term and large-scale investments is a hot topic in research areas. Designing new models, techniques, and simulation tools is on the rise as the interdependence between electric and natural gas systems is growing all around the world. The rapid growth in natural gas consumption by gas-fired generators and the new emerging power-to-hydrogen technology have increased the interdependency of natural gas and power systems. New challenges have been brought up to the energy system operators for the safe and economic operation of the coupled power and gas systems due to the interdependency, alongside heterogeneous uncertainties of the power system and the gas systems, including power loads, renewables, and gas loads. Uncertainties in one infrastructure could easily affect and spread to the other, increasing vulnerability and eventually resulting in cascading outages for both networks. P2H technology is the most valuable and capable solution to the vital need for large-scale energy storage systems because of the erratic nature of RES. Renewable electricity and Natural gas are widely accepted as the main technologies to transit to economic, clean, and secure energy systems worldwide. To deliver this vision; these technologies need to be investigated to work in an integrated system. This thesis proposes new approaches for the planning and operation process to co-optimize the gas and electric power systems. The proposed model aims to minimize the total operating costs of both systems considering the primary constraints, thus optimizing the operation process without jeopardizing the gas and energy supplied to customers. Further, an MINLP model is proposed for the optimal day-ahead operation of the two integrated systems. The simulation results were tested on IEEE 24-bus power system and a 20-node natural gas system. On the other hand, the proposed approach in the planning phase aims to minimize the total costs and allocate resources in the system. The proposed approach utilizes a genetic algorithm to address the uncertainty associated with each network. Simulation results show the effectiveness of the proposed approach model in minimizing the total costs.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Effect of flange geometry on the shear capacity of RC T-beams
No full textIn reinforced concrete (RC) beams, shear failure is sudden and brittle without prior indication of failure. As a result, extensive research has been conducted over the past century to develop design equations and models that combine the variables contributing to the shear resistance in RC members. Despite that, this essential phenomenon is still the least understood problem in reinforced concrete. In most current design codes, the nominal shear capacity of RC beams comes from superposition of concrete and steel reinforcement. The contribution of concrete in slender beams comes from three sources: shear resisted by concrete in the uncracked compression zone, shear transfer by aggregate interlocking at the edge of the diagonal crack, and dowel action from the longitudinal reinforcement. In most shear design equations, the shear is assumed to be resisted only by the web of the beams by aggregate interlock at the shear crack. The contribution of shear resisted by flanges of T-sections is usually ignored in the shear strength models even though it was proven by many experimental studies that the shear capacity of T-beams is higher than that of equivalent rectangular cross-sections. Ignoring such a contribution result in a very conservative and uneconomical design. Therefore, the aim of this research is to evaluate and compare the shear capacity of RC T-beams using shear strength models available in the design guidelines and the literature. Some of the chosen design models included the flange contribution to the shear capacity, while other models neglected this phenomenon. The models were evaluated against an experimental data base that included slender RC T-beams with different geometry, flexural and shear reinforcement ratios, compressive strength of concrete, and shear span-to-depth ratios. In addition, the effect of the ratio of flange width to the web width and flange thickness to the total height of the member on the shear capacity of the T-beams were assessed. The analytical results showed that the shear capacity is underestimated by most of the current shear strength models. However, the models that were developed in the recent literature to include flange geometry resulted in safe and accurate predictions of the shear capacity of RC T-beams. As a result, it is recommended that the effect of flange is included in the design equations to aid in a more economical design that is consistent with the true capacity of the member