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Numerical Modeling of Nanoparticle-Assisted Laser Thermal Ablation of Tumors
No full textA Master of Science thesis in Mechanical Engineering by Yaqeen Abdulaziz Alyamani entitled, “Numerical Modeling of Nanoparticle-Assisted Laser Thermal Ablation of Tumors”, submitted in December 2021. Thesis advisor is Dr. Mohamed Abdelgawad. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The field of thermal ablation of cancer is growing rapidly in the technical and clinical sectors. Image-guided non-invasive techniques in particular have shown high potential for cancer therapy. Many types of cancer are diagnosed by imaging techniques such as magnetic resonance imaging (MRI), ultrasound, or computed tomography (CT) scan. When cancer is detected, usually open surgery resection is the preferred procedure in most cases of focal tumors. Thermal ablation of tumors appeared recently as a less invasive cancer treatment technique. It offers many advantages over traditional resection surgery including less pain and shorter recovery time. To increase the selectivity of thermal ablation, photothermal therapy was recently introduced as a way to ablate tumors without affecting surrounding healthy tissue. In photothermal therapy, photothermal agents such as nanoparticles (NPs) are introduced into tumors to increase their energy absorption capacity significantly compared to surrounding tissue. In this thesis, a numerical model of laser ablation was built to investigate the effect of changing optical and physical properties of the tumor and surrounding tissue, as a result of adding photothermal agents. The effect of changing both the absorption and scattering coefficients of the tumor and tissue on the resulting temperature was investigated. In addition, properties of laser source such as laser intensity, beam radius, number of applied beams, and total power were investigated. It was found that laser intensity has the most significant effect on the resulting temperature. Controlling the radius of the laser beam and the number of applied beams can help greatly adjust the uniformity of the generated temperature inside the tumor. Moreover, the absorption coefficient had a more significant effect than the scattering coefficient on the temperature distribution. By controlling the location of injecting the NPs inside the tumor (e.g. in the core or the periphery of the tumor) a more localized temperature rise inside the tumor was achievable. The effect of anisotropic thermal conductivity of biological tissue was also considered and results showed that it can considerably change the anticipated temperature distribution inside the tumor and tissue.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
A Review of the Impact of Artificial Intelligence on the Healthcare Industry: A United Arab Emirates Perspective
No full textThe last few decades have seen an unprecedented scope and intensity of disruptors to key industries globally. Among the most impactful of these disruptors is artificial intelligence (AI), which has manifested in numerous ways across a very wide-ranging and diverse set of industries. This review article aims to provide a broad overview of global disruption and a brief history of AI as a key disruptor. The current and future impacts of AI are outlined, with a particular focus on its use in the healthcare industry, broadly defined. From this base, the article discusses specific implications of the application of AI in hospitals, using some recent examples from the United Arab Emirates. With this review article, we aim to contribute to current knowledge on the distribution of AI across the healthcare industry, and the future implications for hospitals and their immediate stakeholders
Flex Behavior of Green SNFRC Circ Beams with Double-Layers of Spirals and Uniformly Distributed Reinf
No full textA Master of Science thesis in Civil Engineering by Nour Mohamad Ghazal Aswad entitled, “Flex Behavior of Green SNFRC Circ Beams with Double-Layers of Spirals and Uniformly Distributed Reinf”, submitted in December 2021. Thesis advisor is Dr. Mohammad AlHamaydeh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Green Concrete has emerged as a promising sustainable alternative to Ordinary Portland Cement (OPC)-based concrete. Partial OPC replacement by Ground Granulated Blast-Furnace Slag (GGBS) promotes enhanced sustainability without adversely impacting mechanical characteristics. Macro-synthetic fibers can radically improve concrete’s post-cracking behavior. Combining the two creates Synthetic Fiber-Reinforced Green Concrete (SNFRGC). Moreover, Glass Fiber-Reinforced Polymer (GFRP) rebars address the steel reinforcement corrosion potential. This research experimentally investigated the flexural behavior of circular beams made from SNFRGC reinforced with GFRP and hybrid steel-GFRP uniformly distributed rebars in single-layer and double-layer configurations. An experimental program consisting of 18 large-scale beams of a 1,760 mm clear-span length and 260 mm cross-sectional diameter was executed. Moreover, the clear shear span-to-overall depth was 2.1 for the test beams. The average concrete compressive strength was 32 MPa reinforced with 1% by volume macro-synthetic fibers. The displacement-controlled flexural testing was conducted via a four-point loading setup. The influence of varying the following parameters was observed: (a) the reinforcement configuration (single layer vs. double layers), (b) reinforcement material (all-steel, all-GFRP, and hybrid), (c) number of longitudinal rebars (6, 12, 16, and 20), (d) spiral rebar diameter (10 and 12 mm), and (e) spiral pitch (45, 60, 65, 75, 80, 85, and 95 mm). Ductile elastoplastic behavior manifested with pure flexural and mixed flexural-shear cracks was observed for all tested specimens. Steel-reinforced beams exhibited concrete crushing failure modes subsequent to observable steel reinforcement yielding. In the GFRP-reinforced specimens, the failure mechanisms were initiated through compression concrete crushing and cover spalling followed by GFRP tension rebar rupture. The failure mechanism in the hybrid-reinforced specimens was associated with steel yielding, followed by concrete crushing and cover spalling, then GFRP tension rebar rupture. The double-layered hybrid-reinforced beams exhibited up to 33% higher load-carrying capacity than their all-GFRP reinforced counterparts. Moreover, double-layered hybrid-reinforced beams outperformed their all-GFRP reinforced counterparts in ductility; the difference ranged between 27 and 254%. The improved ductile behavior is a direct outcome of the steel rebars within the hybrid reinforcement. Hence, hybrid-reinforced beams can be regarded as a promising substitute for traditional steel-reinforced beams. This is especially important in harsh environments where such hybrid reinforcement configurations substantially enhance the infrastructure sustainability.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
No full textA Master of Science thesis in Ccomputer Engineering by Muhammad Arbab Arshad entitled, “Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data”, submitted in August 2021. Thesis advisor is Dr. Imran Zualkernan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Analysis and understanding of bat behaviors have taken on an increased importance post-Covid 19. Manual analysis of echolocation calls in bats to deduce behavior is cumbersome, time-consuming and costly. Previous attempts to automate this process have relied on labeled data which is expensive and difficult to collect. This thesis explored the use of state-of-the-art unsupervised learning algorithms like IMSAT, IIC, SCAN, JULE and DeepCluster to determine if interesting bat behaviors can be automatically determined based on unlabeled bat echolocation data which is readily available. The algorithms originally developed for image classification were adapted to work with audio data. One small labeled echolocation data set from the UAE Al-Hajar mountains and a large unlabeled dataset from an urban space in Dubai from the Emirates Nature - World Wildlife Foundation (WWF) were utilized. A coding scheme for interpreting bats' behavior was also developed. The results are that different algorithms capture different behavior. For example, IIC and IMSAT identified the presence of multiple bats, DeepCluster was better able to identify prey capture attempts, SCAN could distinguish bat calls in a close habitat and JULE could capture different species types. Based on Mutual Information (MI) the most similar pairs of algorithms were IIC and IMSAT (0.429), IIC and DeepCluster (0.374), and IMSAT and DeepCluster (0.266). On the small labeled data set, IIC performed the best with an accuracy of 48.28% followed by IMSAT (43.59%), JULE (43.13%), DeepCluster (39.84%) and SCAN (29.38%). A baseline K-Medoid algorithm only had an accuracy of 23.75%. For future work, better audio augmentation techniques can be explored and other unsupervised learning algorithms like DAC, DEC and K-Autoencoders can be investigated as well.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
A Subspace Identification Technique for Real Time Stability Assessment of Droop Based Microgrids
No full textReal time detection of the microgrid stability is crucial for determining and adjusting the power-sharing droop controllers' gains to maintain a sufficient stability margin. Maintaining minimum relative stability should be ensured at different operating conditions to accommodate any sudden system changes. This paper develops a novel subspace-based identification technique to assess microgrid stability real time without relying on offline analytical small or large-signal models. Unlike conventional system identification techniques that require the introduction of external excitation signals, the proposed method employs a simple routine through small and short-duration perturbations in the active power droop gain of inverter-based distributed generation (IBDG). The use of subspace identification does not require pre-defining the system’s order and avoids the exhaustive computations associated with iterative identification methods. The proposed stability assessment method has been tested on an IBDG microgrid considering different operating conditions in MATLAB/Simulink. The accuracy of the proposed real time stability assessment tool is determined by comparing the results to the analytically-derived small-signal model.Deputyship for Research & Innovation, Ministry of Education in Saudi Arabi
An Intelligent System Approach for RF Energy Harvesting
No full textA Master of Science thesis in Computer Engineering by Raviha W. Khan entitled, “An Intelligent System Approach for RF Energy Harvesting”, submitted in August 2021. Thesis advisor is Dr. Michel Bernard Pasquier and thesis co-advisor id Dr. Hicham Hallal. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).RF energy harvesting has emerged as a viable energy source for low-powered devices in wireless sensor networks. It also acts as a replacement for conventional power sources such as batteries. RF energy harvest uses an unlimited source and makes efficient use of the existing energy in the surrounding environment. The use of machine learning techniques to predict the suitability of RF energy harvest under specific conditions further enhances the performance of energy harvesters. Such a prediction depends on several parameters, such as the time of the day, the temperature, the distance from source, the water density in the air, etc. These have a direct effect on the quality of the received signal at the harvesting node and thus, the harvested energy. In this thesis, a simulation of an RF energy harvesting network using MATLAB to collect relevant data is proposed. This data is used to train different machine learning models: Logistic Regression, Classification Trees, Support Vector Machines and Naïve Bayes in RStudio. The outcomes of the machine learning models are used to enhance the energy harvesting modules’ performance by scheduling them to be on or off with a given set of parametric values. The most suitable model for the dataset being used is chosen based on accuracy, F-Measure and Area Under the Curve. All the models evaluated in this thesis show a performance of 95% and above when tested.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations
No full textA Master of Science thesis in Electrical Engineering by Mohamed Mostafa Abdelazim Elmeligy entitled, “Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations”, submitted in April 2021. Thesis advisor is Dr. Mostafa Shaaban. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).s transportation electrification increases globally, new technologies emerged in the past few years to meet the growth of the electricity demand. A mobile energy storage system (MESS) could provide several services to the distribution systems such as reactive power support, renewable energy integration, peak shaving, and load leveling. In addition, an MESS can be utilized to support electric vehicles (EVs) charging in different parking lots (PLs), which is the main focus of this thesis. The task of multiple stationary storage units can be achieved using a single MESS with a relatively lower cost. In this thesis, a new dynamic optimal dispatch strategy for MESS is proposed to support several charging stations sharing the same geographical area. The objective of the proposed approach is to optimally dispatch the MESS in conjunction with optimal EVs charging to minimize the total operation cost and address the extra demand of PLs. Different case studies are provided on the IEEE 38-bus system and a real radial feeder in Ontario, Canada to test the proposed approach. In the second phase of this research, a new approach is proposed for the optimal resource allocation for an MESS fleet owned by multiple PLs sharing the same geographical area and sharing its capital and operational cost. The aim is to optimally decide on the number of MESSs and their battery bank capacities that should be used in order to serve charging stations participated in the project. The optimization includes practical constraints for battery dynamics. Comparative case studies showed the effectiveness of the proposed algorithms.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Polyaniline-based flexible implantable electrodes for neural sensing/stimulation applications
No full textA Master of Science thesis in Biomedical Engineering by Nader Lutfi Almufleh entitled, “Polyaniline-based flexible implantable electrodes for neural sensing/stimulation applications”, submitted in March 2021. Thesis advisor is Dr. Amani Al-Othman and thesis co-advisors are Dr. Hasan Awad Moh’d Al Nashash and Dr. Mohammed Hussein Al-Sayah. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Implantable bioelectrodes have the potential to advance neural sensing and muscle stimulation, mainly in patients with peripheral nerve injuries. The current emerging prostheses rely on the use of conductive and capacitive materials to assist the nerve recovery process, which is often slow. Therefore, implantable electrodes are used to stimulate and restore muscle function after injury. The function of implantable electrodes is to work as an interface between the damaged nerve and the muscle which is controlled by that nerve. There are conventional implantable electrodes that are fabricated from precious metals, such as platinum and gold. Aside from the cost, they have many disadvantages such as high impedance, toughness, and they make damage to the soft tissue. This thesis discusses the fabrication and characterization of novel, low-cost, flexible bioelectrodes based on silicone, and polyaniline (PANI), and polymethyl methacrylate (PMMA) in addition to their combinations. Implantable electrodes were fabricated from variant combinations of these polymers and their electrochemical and mechanical properties were evaluated. PANI was used as the main conducting components for fabrication. The characterization methods included conductivity, capacitive behaviour, cost, long term impedance, and their mechanical properties. The results of the fabricated PANI-silicone based samples displayed a bulk impedance of 600 Ω with an impedance of 1.6 kΩ at the frequency of 1 kHz and a modulus of elasticity of 75.312 MPa. The charge storage capacity of the fabricated sample was equal to 138.14 C/ Cm² which is the highest compared to the literature materials. The samples did not have any peaks so they were considered as stable samples. The mechanical test results of the fabricated batches were compared to those found in the literature such as PEDOT: PSS (poly 3,4-ethylenedioxythiophene): polystyrene sulfonate) and skin tissue. The young modulus of the fabricated samples (sample 1 and sample 9) were 0.1468 MPa and 75.312 MPa respectively, while the young modulus from the literature were 1.8 ± 0.2 GPa and 83.33 ± 4.9 MPa respectively. The results for the silicone with PANI showed promising electrochemical and mechanical characteristics with flexible and ductile properties.College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
Assessing the Impact of Reactive Power Droop on Inverter Based Microgrid Stability
Get PDFDroop control is the most common approach for controlling inverter-based micro-grids. The active power droop gain has always been considered as the main parameter for identifying the micro-grid stability margin. Increasing this margin improves the transient performance and provides robustness to the micro-grid for a wide range of operations. Previous work on droop control focused on the active power droop gain, which is required for accurate power sharing as well as for micro-grid stability assessment. This paper utilizes small-signal stability analysis to analyze the impact of the reactive power droop gain on micro-grid stability, which is ignored in previous work. Consequently, a micro-grid domain of stability chart is proposed and defined in the mp max -nq plane, which represents the zone within which the micro-grid will maintain stable operation. The proposed domain of stability chart is utilized to assess and compare the impact of the conventional and proportional derivative (PD) reactive power droop controller on the micro-grid stability margin. The results show that there exists a reactive power droop gain at which the stability margin is minimum. Furthermore, it has been shown, through the domain of stability chart, that the PD reactive power droop controller is capable and sufficient to significantly increase the micro-grid stability margin while maintaining equal load sharing. Further, the domain of stability chart can serve as a useful tool for defining the micro-grid droop gain operational boundaries and for assessing and comparing inverter-based micro-grid control schemes.American University of Sharja
Transient high thyroid stimulating hormone and hypothyroidism incidence during follow up of subclinical hypothyroidism
No full textObjectives. Given the high prevalence of subclinical hypothyroidism (SCH), defined as high thyroid stimulating hormone (TSH) and normal free thyroxine (FT4), and uncertainty on treatment, one of the major challenges in clinical practice is whether to initiate the treatment for SCH or to keep the patients under surveillance. There is no published study that has identified predictors of short-term changes in thyroid status amongst patients with mild elevation of TSH (4.5-10 mIU/L). Subjects and Results. A cohort study was conducted on patients with SCH detected through a general population screening program, who were followed for six months. This project identified factors predicting progression to hypothyroid status, persistent SCH and transient cases. A total of 656 participants joined the study (431 controls and 225 were patients with SCH). A part of participants (12.2%) developed biochemical hypothyroidism during the follow-up, while 73.8% of the subjects became euthyroid and the remained ones (13.4%) stayed in the SCH status. The incidence of overt hypothyroidism for participants with TSH above 6.9 mIU/L was 36.7%, with incidence of 42.3% for females. Anti-thyroid peroxidase antibodies (TPO) positivity is an important predictor of development of hypothyroidism; however, it could be also positive due to transient thyroiditis. Conclusions. It can be concluded that females with TSH above 6.9 mIU/L, particularly those with free triiodothyronine (FT3) and FT4 in the lower half of the reference range, are more likely to develop biochemical hypothyroidism. Therefore, it is recommended to give them a trial of levothyroxine replacement. It is also recommended to repeat TSH after six months for male subjects and participants with baseline TSH equal or less than 6.9 mIU/L.Mutah Universit