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Religiosity, neglected risk and asset returns: theory and evidence from Islamic finance industry
No full textThis paper studies the sociological influence of religion on the risk and return in the financial markets with particular context of Islamic finance, a rapidly emerging and expanding financial industry. The paper builds a theoretical model to show how intermediaries serve their customers’ religious needs by creating innovative Islamic financial instruments. The customer's emphasis on religiosity exposes the industry to a theological risk, which can increase the financial fragility of the system. In our model, the theological risk emerges as a neglected component, which can be realized in the event of a bad news challenging the religious legitimacy of (Islamic) finance structures. To corroborate our theoretical findings, we present two sets of results. First, using stock prices data for 104 Islamic bond (Sukuk) issuers, we show that Sukuk issuers experienced a significant decline in their stock prices, following multiple formal and informal announcements in 2008, which challenged the religious legitimacy of Islamic bond structures. Second, using data from 1360 newly issued Malaysian Sukuk from 2006 to 2016, we find that following the regulatory changes the Sukuk margins have increased significantly. This suggests that there may be a significant difference between what Islamic and conventional customers may be willing to pay for Sukuk, exposing the industry to a unique form of religious risk
Mechanical perturbation control of cardiac alternans
No full textCardiac alternans is a disturbance in heart rhythm that is linked to the onset of lethal cardiac arrhythmias. Mechanical perturbation control has been recently used to suppress alternans in cardiac tissue of relevant size. In this control strategy, cardiac tissue mechanics are perturbed via active tension generated by the heart’s electrical activity, which alters the tissue’s electric wave profile through mechanoelectric coupling. We analyze the effects of mechanical perturbation on the dynamics of amap model that couples themembrane voltage and active tension systems at the cellular level. Therefore, a two-dimensional iterative map of the heart beat-to-beat dynamics is introduced, and a stability analysis of the system of coupled maps is performed in the presence of a mechanical perturbation algorithm. To this end, a bidirectional coupling between the membrane voltage and active tension systems in a single cardiac cell is provided, and a discrete form of the proposed control algorithm, that can be incorporated in the coupled maps, is derived. In addition, a realistic electromechanical model of cardiac tissue is employed to explore the feasibility of suppressing alternans at cellular and tissue levels. Electrical activity is represented in two detailed ionic models, the Luo-Rudy 1 and the Fox models, while two active contractile tension models, namely a smooth variant of the Nash-Panfilov model and the Niederer-Hunter-Smith model, are used to represent mechanical activity in the heart. The Mooney-Rivlin passive elasticity model is employed to describe passive mechanical behavior of the myocardium
Nonlinear Analysis of Electrically-coupled Microbeams under Mechanical Shock
No full textA Master of Science thesis in Mechanical Engineering by Moustafa Adel Sayed Ahmed entitled, “Nonlinear Analysis of Electrically-coupled Microbeams under Mechanical Shock”, submitted in April 2018. Thesis advisor is Dr. Mehdi Ghommem. Soft and hard copy available.This work presents a theoretical investigation of the dynamic response of electrically-coupled microcantilever beams under the combined effect of squeeze-film damping and mechanical shock for MEMS applications. Several research studies have reported and analyzed the failure of MEMS devices deploying electrically-actuated vibrating beams, such as inertial, bio-mass, and gas sensors, when undergoing mechanical shocks due to the inherent pull-in instability. The sensitivity of the vibrating beams to mechanical shock can also be exploited to design microswitches that are intended to trigger a signal once receiving a mechanical shock to activate safety functionalities, such as airbag systems. We consider two different microsystem designs, namely: single and dual beams, operating at varying conditions. The single-beam system is actuated via a fixed electrode (uncoupled actuation) while the electric actuation of the dual-beam system, comprising two movable microbeams, is achieved by applying a DC and AC voltages among them (coupled actuation). We develop a mathematical model to simulate the dynamic response of the single and dual microbeams while accounting for the Fringing field effect, the squeeze-film damping, and the mechanical shock. The simulation results are in good qualitative and quantitative agreement with those reported in the literature. A parametric study is conducted to investigate the effect of the electric actuation, the initial gap distance, the fluid viscosity, and the beam geometry on the shock response of the microsystem. We observe a significant reduction of 29-36% in the pull-in voltage when considering the dual-beam system in comparison with the single-beam case. The frequency response curves show expanded dynamic pull-in bandwidth when operating the symmetric dual-beam system near the primary resonance. We notice that the dual-beam systems are more robust in terms of resistance to mechanical shock. This shows the suitability of such design for the operation and reliability of MEMS devices in harsh environments characterized by high mechanical shock levels. Breaking the symmetry of the dual beam system in terms of the beams’ geometry is found to significantly reduce the resistance to shocks. Given their high sensitivity to mechanical shock, single-beam systems are observed to be more attractive for deployment as microswitches.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Combinations of absorptive capacity metaroutines: the role of organizational disruptions and time constraints
No full textThis paper explores absorptive capacity metaroutines in a financial organization that experienced a large-scale misappropriation episode. We selected an instrumental case and collected individual semi-structured interviews, on-site nonparticipant observations, and documents to better understand the combination of absorptive capacity in organizational contexts. Findings revealed that the magnitude of organizational disruptions and time constraints influenced absorptive capacity metaroutines. The magnitude of organizational disruptions related to the intensity of required change for innovation adoption and the persistence of outcomes, while time constraints influenced the degree of involvement and cohesiveness of organizational members. In addition, findings showed that the combination of absorptive capacity metaroutines experienced asymmetries and had incremental and cumulative features. This work extends current theorizations of absorptive capacity conceptualized from a micro-foundation perspective as a collection of external and internal metaroutines and provides a means to start understanding potential factors that influence the combination of absorptive capacity metaroutines. Implications for theory and practice are discussed, and suggestions for future research are offered
Residential Area Energy Consumption Big Data Analytics and Visualization
No full textA Master of Science thesis in Computer Engineering by Ragini Gupta entitled, “Residential Area Energy Consumption Big Data Analytics and Visualization”, submitted in June 2018. Thesis advisor is Dr. Abdulrehman Al-Ali and thesis co-advisor is Dr. Imran Zualkernan. Soft and hard copy available.As Internet of Things (IoT) technology and open source file distributed system applications are evolving, home appliances can be monitored and controlled via an IoT-based home gateway. These gateways collect energy consumption from home appliances and hence create a large amount of data. Due to the large amount of data being generated, utility companies require platforms that enable them to store, process, analyze, visualize, and monetize the energy consumption data, and to gain meaningful insights into load profiles. This thesis proposes a residential area smart energy management system that enables home owners and utilities to monitor consumption patterns of each home, community, state, and country. Using an open source file distributed file system tools, home owners can monitor their home appliances energy consumption on a periodic basis. Additionally, utilities can also monitor the neighborhoods, communities, states, and country’s consumption. The architecture was tested to process data from one million smart meters. This data was synthetically generated based on one year of real consumption data from a home. The big data was stored in a Hadoop cluster of four nodes. Dimensional modeling was used to develop benchmarking queries to create a real time dashboard consisting of charts, graphs, and reports for home owners and utilities. Both Spark and Hive were used to implement the benchmarking queries and it was found that Spark outperformed Hive in terms of latency and processor throughput. Spark’s average latency was fifteen minutes with an average throughput of 2400 MBps while Hive’s average latency was thirty-four minutes with an average throughput of 2200 MBps for processing one million smart meters in a four nodes cluster. To validate the proposed system outcomes, the results were compared with existing proprietary tools such as IBM’s TimeSeries and relational database management systems. Spark and Hive have an intermediate performance in comparison to IBM’s proprietary tool and relational database management system. The results demonstrate that the proposed solution can be utilized to provide energy data consumption visualization for consumer and utility provider stakeholders, while implementing Spark as the backend processing engine for low latency, performance gain, and a high throughput.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Effects of Autonomous Vehicles on Freeway Traffic Performance
No full textA Master of Science thesis in Civil Engineering by Osama Mohamed ElSahly entitled, “Effects of Autonomous Vehicles on Freeway Traffic Performance”, submitted in October 2018. Thesis advisor is Dr. Akmal Abdelfatah. Soft and hard copy available.Autonomous vehicles (AVs) are smart transportation technologies that have drawn significant attention recently due to their rapid development and promising future. Dubai is trying to promote the use of AVs on its road network as it announced its future strategy to make 25% of its transportation automated by 2030. One of the major challenges that are expected to happen is the interaction between AVs and Regular vehicles (RVs) as the mode share, for AVs (percentage of AVs) would not be 100% in the early stages of adoption, and this interaction is not well-researched so far. The purpose of this study is to evaluate the impact of AVs on freeway traffic performance. The study considers a segment of E311 (Sheikh Mohamed Bin Zayed Road) freeway in Dubai as the test corridor for the study. A microsimulation software (VISSIM) is used to model and evaluate different scenarios. Different traffic demand to capacity ratios are evaluated by considering demand to capacity ratios. The results show that increasing AVs mode share increases the average speed and reduces average travel time and delay. Also, the impact of AVs on freeway performance is higher when the demand to capacity ratio is higher. The minimum effect is achieved when there is a 5% AVs and the demand to capacity ratio is 0.6 while the ultimate case is for 100% AVs and demand to capacity ratio of 1.2. In this case, the increase in speed is about 115%, the reduction in the average travel time is about 1.5%, and the average delay is lower by about 87%. The results obtained in this thesis represent a lower bound of what can actually be obtained, as the considered simulations assumed the lane width and capacity to remain the same. In real applications, more improvements can be achieved by designating some of the road lanes for AVs use only, at high mode shares of AVs. Such lanes have smaller width than regular lanes, which will increase the number of the lanes and road capacity.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Behavioral Modeling of RF Power Amplifiers Using Reduced Sampling Rate
No full textA Master of Science thesis in Electrical Engineering by Moustafa Farag Abdelnaby entitled, “Behavioral Modeling of RF Power Amplifiers Using Reduced Sampling Rate”, submitted in November 2018. Thesis advisor is Dr. Oualid Hammi. Soft and hard copy available.The increasing demands for high data rates on wireless communication systems necessitate the enhancement of those systems in terms of software and hardware requirements. This creates real complications in designing power amplifiers (PA) that simultaneously meet the efficiency and linearity specifications of the modern wireless communication systems. Consequently, digital predistortion (DPD) is often used to compensate for the nonlinearity of the PA when operated at high efficiency. However, the increasing growth of the data rates and bandwidth requirements of the transmitter’s architectures are setting new burdens on the use of some of its hardware components, such as the analog-to-digital converters (ADCs) of the feedback path that is used to capture the PA’s output signal needed to derive the predistortion function. This thesis explores a technique suitable for extending the correction bandwidth of DPD systems for a given hardware specification. This approach is based on DPD model extraction from narrow-band measurements using under-sampling ADCs. The DPD is implemented using a two-box architecture which consists of the cascade of dynamic nonlinearity function followed by a static nonlinearity. The proposed method is validated in the presence of a 20-MHz long term evolution-advanced (LTE-A), which requires an ADC with a sampling rate of 100-Msps to capture the output of the PA due to the spectral regrowth behavior of the nonlinear amplifier. The output signal in this work is captured using an ADC with several under-sampling speeds that are reduced up to 75% of the full-rate requirements (i.e. 50-Msps, 40-Msps, 30-Msps, 25-Msps). Furthermore, the proposed approach also aims to reduce the software computational complexity of the typical DPD systems that involve high resolution delay alignment to be able to successfully extract the DPD coefficients. This is done by extracting the dynamic nonlinearity function in the two-box model using various delay mis-alignment conditions, that vary from -1 to +1 samples in steps of 0.1. Successful PA linearizations were achieved using the under-sampled signals from the ADC and dynamic nonlinearity predistorters that are extracted under delay mis-alignment conditions.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Measuring the Acoustic Release of a Chemotherapeutic Agent from Folate-Targeted Polymeric Micelles
No full textIn this paper, we compare the use of Bayesian filters for the estimation of release and reencapsulation rates of a chemotherapeutic agent (namely Doxorubicin) from nanocarriers in an acoustically activated drug release system. The study is implemented using an advanced kinetic model that takes into account cavitation events causing the antineoplastic agent’s release from polymeric micelles upon exposure to ultrasound. This model is an improvement over the previous representations of acoustic release that used simple zero-, first- and second-order release and reencapsulation kinetics to study acoustically triggered drug release from polymeric micelles. The new model incorporates drug release and micellar reassembly events caused by cavitation allowing for the controlled release of chemotherapeutics specially and temporally. Different Bayesian estimators are tested for this purpose including Kalman filters (KF), Extended Kalman filters (EKF), Particle filters (PF), and multi-model KF and EKF. Simulated and experimental results are used to verify the performance of the above-mentioned estimators. The proposed methods demonstrate the utility and high-accuracy of using estimation methods in modeling this drug delivery technique. The results show that, in both cases (linear and non-linear dynamics), the modeling errors are expensive but can be minimized using a multi-model approach. In addition, particle filters are more flexible filters that perform reasonably well compared to the other two filters. The study improved the accuracy of the kinetic models used to capture acoustically activated drug release from polymeric micelles, which may in turn help in designing hardware and software capable of precisely controlling the delivered amount of chemotherapeutics to cancerous tissue
The Effect of Ultrasound on the Drug Delivery of RGD-Targeted Liposomes
No full textA Master of Science thesis in Chemical Engineering by Mohamad Mahmoud entitled, “The Effect of Ultrasound on the Drug Delivery of RGD-Targeted Liposomes”, submitted in May 2018. Thesis advisor is Dr. Ghaleb Husseini. Soft and hard copy available.Approaches used to treat cancer, with the most prominent being chemotherapy, have detrimental effects on patients’ health. Doxorubicin, a chemotherapeutic agent, alters normal cellular functions and can cause many fatal side effects, such as cell loss and congestive heart failure. Smart Drug Delivery Systems (DDS), such as liposomes, constitute a novel approach which can deliver a cytotoxic agent to the tumor without affecting healthy cells. A moiety, such as an RGD motif, can be conjugated to the liposome’s surface. This modification increases the efficacy of such liposomes by actively targeting specific receptors which are overexpressed on the surface of cancer cells. Two types of carriers were developed in this study, RGD-positive, and their control counterparts, RGD-negative (NH2 liposomes). The liposomes possessed radii of 88.26 ± 5.55 nm and 79.52 ± 4.81 nm, respectively, which classify them as Large Uni-lamellar Vesicles (LUVs). A 20-kHz ultrasound probe at three power densities, 7.46, 9.85, and 17.31 mW/cm2, equivalent to mechanical index (MI) values of 0.11, 0.12, and 0.16, respectively, was used to trigger the liposomes into releasing their encapsulated fluorescent model-drug, calcein. Both types of liposomes were stable and showed a higher release rate as the power density increased. Nine drug release kinetics models were utilized to model the online release profiles, where the Korsmeyer-Peppas and the Weibull models presented the best fits, predicting diffusion and dissolution driven drug release, respectively. Statistical analysis showed that the release rate constants were significantly affected by changes in power densities and the type of carrier. The calculated average release rate constants were KKP = 5.7291 (s-1.0789) and KW = 5.3734 for NH2 liposomes, and KKP = 9.3574 (s-0.9441) and KW = 6.2857 for RGD liposomes. This thesis presents the preparation of the smart DDS (liposomes), evaluates its stability and storage, and analyzes its drug release and sensitivity to ultrasound. The overall goal is to design a drug delivery system capable of reducing the side effects of conventional chemotherapy and hence improving the quality of life of cancer patients worldwide.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE
Produced water treatment using microbial desalination cells
No full textA Master of Science thesis in Chemical Engineering by Apoorva Goel entitled, “Produced water treatment using microbial desalination cells”, submitted in May 2018. Thesis advisor is Dr. Naif Darwish and thesis co-advisor is Dr. Ahmed Aidan. Soft and hard copy available.Globally, 250 million barrels of produced water is generated daily for extracting 80 million barrels of oil. Having a highly variable composition and no economic value, produced water presents serious environmental problems. While the treatment of produced water is of paramount concern, existing desalination technologies are highly expensive and energy-intensive leading to great investments by oil industries. Microbial desalination cells (MDC) provide a promising alternative through their potential for negligible energy input, use of low-cost resources, low waste production, and electricity generation. However, MDC is a relatively new technology and its application in industries is limited by its low desalination efficiency and pH instability. This research investigates the effect of various factors on the performance of MDC employing Saccharomyces cerevisiae yeast as electron generating microorganisms. Two mediators, methylene blue, and menadione are used as electron promoters to shuttle the electrons from the yeast cells to the anode electrode. In particular, a two-level partial factorial design is implemented where, MDC desalination efficiency is investigated at two (low/high) levels of three input factors: aeration in anolyte (aerobic/ anaerobic), hydrophilic mediator concentration (0.5– 2 mM), and concentration of Total Dissolved Solids (TDS) in produced water (20– 40 g/l). Acquired experimental data are statistically analyzed using single effect and interaction plots. In addition, several other operating parameters and configurations are investigated in order to achieve optimum conditions for best performance. These include aeration rates in the anode and cathode chambers, the concentration of lipophilic and hydrophilic mediators, the pH of the anolyte solution, the use of activated carbon granules, and the repeated batch operation. Moreover, an MDC unit is operated at the optimized conditions where it resulted in 36% desalination after 72 hours. The study revealed that the operation of repeated batch cycles was the most effective among other parameters in improving desalination efficiency of MDCs. Furthermore, the factorial design study concluded that produced water TDS has the highest single effect on MDC performance and that there is a significant interaction between all three input factors employed in the factorial design.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE