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Analyzing Sensitivity Measures Using Moment-Matching Technique
No full textSensitivity indices are used to rank the importance of input design variables or components by estimating the degree of uncertainty of output variable influenced by the uncertainty generated from input variables or components. With the advent of highly complex engineering simulation models that describe the relationship between input variables and output response, the need for an efficient and effective sensitivity analysis is more demanding. Traditional importance measures either requires extensive random number generations or unable to measure variables interaction effects. In this article, a generalized approach that can provide efficient and accurate global sensitivity indices is developed. The approach consists of two steps; running an orthogonal array based experiment using moment-matched levels of the input variables followed by a variance contribution analysis. The benefits of the approach are demonstrated through different real life examples
Adaptive Video Streaming Over Cognitive Radio Networks
No full textA Master of Science thesis in Electrical Engineering by Ala Eldin Omer Mohamed entitled, "Adaptive Video Streaming over Cognitive Radio Networks," submitted in January 2017. Thesis advisors are Dr. Mohamed Hassan and Dr. Mohamed El-Tarhuni. Soft and hard copy available.Several challenges face reliable video streaming over wireless networks due to the stringent requirements of high data rate, low error rate, and limited end-to-end delay. Cognitive radio (CR) networks offer a great advantage to unlicensed users (typically called secondary users) by allowing them to exploit the unused spectrum of licensed users (known as primary users) on an opportunistic basis. However, it is more challenging to deliver video services over dynamic CR channels that are available to secondary users not only intermittently but with all the challenges of wireless channels. In this research, several frameworks are proposed to stream different scalable videos from a base station to multiple secondary users over a CR network. The objective of this study is to ensure that end users will enjoy continuous video playback with acceptable perceptual quality. To achieve such a goal, a channel allocation algorithm is introduced to adaptively assign the available radio channels to secondary users while taking into considerations the quality of their assigned channels as well as their buffer occupancies. In addition, different streaming algorithms are devised to ensure the delivery of scalable video frames, with base and enhancement layers, within the delay constraints with priority given to the base-layer frames to guarantee the continuity of video playback. Moreover, adaptive modulation is used based on the importance of transmitted video information and the channel state information (CSI) as fed-back by secondary users. Extensive simulations are performed using SimEvents simulator in MATLAB, the results of which show that the proposed schemes that integrate the devised channel allocation and streaming algorithms with adaptive modulation and scalable source coding techniques react to the variations in the channel conditions and the dynamics of the secondary users’ playback buffers in an acceptable fashion. This in turn resulted in efficient usage of the available CR resources as demonstrated in the achieved peak signal-to-noise ratio (PSNR) of the reconstructed video streams with no interruptions in the playback process. It has also been shown that scalable videos outperform their single-layer counterparts in terms of the achieved video quality. Finally, it is shown that joint adaptive modulation and channel coding results in improved bandwidth utilization, continuous playback and enhanced perceptual video quality at the secondary users end.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Zirconium Phosphate/Ionic Liquid Proton Conductors for High Temperature Fuel Cell Applications
No full textA Master of Science thesis in Chemical Engineering by Hanin Mohammed entitled, "Zirconium Phosphate/Ionic Liquid Proton Conductors for High Temperature Fuel Cell Applications," submitted in November 2017. Thesis advisor is Dr. Amani Al-Othman and thesis co-advisor is Dr. Paul Nancarrow. Soft and hard copy available.High temperature operation (> 120 °C) is preferred in proton exchange membrane (PEM) fuel cells. It enhances the electrode kinetics, improves the catalyst tolerance for impurities and allows the use of lower cost fuels such as hydrocarbons. However, high temperature operation is not possible using the conventional Nafion membranes. Their proton conductivity decreases dramatically beyond 90 °C. Therefore, this work aimed at developing Nafion-free proton conducting material, based on zirconium phosphates (ZrP) and ionic liquids (IL) to allow a high temperate operation. ZrP/IL proton conducting materials were prepared via the reaction of zirconium oxychloride ZrOCl₂ in an aqueous solution with phosphoric acid H₃PO₄ at room temperature. Seven different ionic liquids, were investigated in this work. The ionic liquid component was added to the ZrOCl₂ solution prior to the precipitation reaction with IL contents ranging from 0.4-5% by mass. The modified materials were investigated for their proton conductivity. The results of this work demonstrated that the addition of ionic liquids enhances the proton conductivity of the ZrP material by orders of magnitude. Among all the tested ionic liquids, 1-ethyl-3-methylimidazolium ethyl sulfate, 1-butyl-3-methylimidazolium dicyanamide, and 1-butyl-3- methylimidazolium triflate produced the best results with conductivities of 2.26X 10⁻², 1.61X10⁻² and 1.36X 10⁻² S cm⁻¹, respectively. The proton conductivity of the unmodified ZrP prepared in this work was equal to 9.24X 10⁻⁴ S cm⁻¹. The modified samples were analyzed by thermogravimetric analysis (TGA), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy and scanning electron microscopy (SEM). Results showed the enhancement of water uptake properties by 40-60%, changes in morphology and changes in structure upon the introduction of the IL component. The modified samples were processed at high temperature (200 °C) under completely anhydrous conditions and showed a high anhydrous proton conductivity on the order of 10⁻⁴ S cm⁻¹. In conclusion, it appeared that the ionic liquids have formed hydrogen bonds with the ZrP molecules and hence, provided additional pathways for the proton transfer and effective proton hopping sites. The enhanced conductivity of the ZrP/IL materials make them good candidates as solid proton conductors for fuel cells applications.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE
Spectrum Occupancy Measurements and Cognitive Radio System Implementation
No full textA Master of Science thesis in Electrical Engineering by Firas Ahmed Kiftaro entitled, "Spectrum Occupancy Measurements and Cognitive Radio System Implementation," submitted in January 2017. Thesis advisors are Dr. Mohamed El-Tarhuni and Dr. Khaled Assaleh. Soft and hard copy available.Nowadays, radio spectrum is mostly crowded and occupied by many fixed wireless services. Therefore, there is less opportunity of finding a vacant band (spatially or temporally) for deploying new wireless communication services or enhancing already existing ones. The Telecommunications Regulatory Authority (TRA) allocation chart in UAE shows some overlapping allocation for services given the same band which reinforces the spectrum scarcity concept. Insufficient frequency spectrum allocation and the problem of spectrum scarcity are standing against the will of introducing more services to the wireless communication community. As a result, many measurement campaigns around the world have been conducted in order to investigate more about the spectrum utilization and characterization. Dynamic Spectrum Access (DSA) technologies have been introduced and promised to use the idle spectrum bands and utilize them efficiently. One form of DSA technologies is Cognitive Radio (CR) which is based on allowing an unlicensed (secondary) user to access an unoccupied portion of licensed spectrum and use it without causing interference with the licensed (primary) user in an opportunistic way. This thesis is mainly divided into two parts; in the first part, the occupancy of the frequency spectrum is studied through multiple measurement campaigns. These campaigns lasted for twenty days and conducted at the American University of Sharjah. These measurements were done over the ultra-high frequency (UHF) due its potential to be utilized by cognitive radio systems. The measurements indicated that large portions of the UHF band are not utilized efficiently. A Gaussian mixture model (GMM) analysis was carried out to obtain quantitative observations about the UHF occupancy levels. The second part of this thesis is about implementing a cognitive radio system based on real data collected using a prepared experimental setup consists of Universal Software Radio Peripheral (USRP) devices. An energy detector and polynomial classifier were implemented for spectrum sensing. A comparison between the two approaches shows that polynomial classifier has better performance over the energy detector in terms of the misclassification rate.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Information Literacy: Accreditation, Alignment, and Assessment
No full textPresentation by Alanna Ross entitled "Information Literacy: Accreditation, Alignment, and Assessment," presented at the 23rd Annual Conference & Exhibition SLA (Special Libraries Association) in Bahrain, March 6-9. 2017
Renewable Energy, Coal as a Baseload Power Source, and Greenhouse Gas Emissions: Evidence from U.S. State-Level Data
No full textThis paper examines the relationship between renewable energy production and greenhouse gas emissions (GHG) using U.S. state-level data for 2010. After controlling for other sources of emissions, U.S. states that produce a larger share of renewable energy are found to have lower GHG emissions. It is estimated that a 10% increase in the share of renewable energy could decrease CH4 emissions by about 0.26%. Since the use of renewable energy sources does not release GHG emissions, this effect can be interpreted as stabilizing if renewable energy is added to coal use or as corrective if it replaces coal. After accounting for the role of coal as a baseload power source, an increase in the share of renewable energy is estimated to mitigate N2O emissions at the U.S. state level only if states individually decrease their share of coal use to levels below 41.47%. These findings have significant policy implications for the provision of guidance to policymakers in identifying optimal energy mixes and in pursuing realistic goals to enhance renewable energy penetration and to contribute to the current efforts of tackling climate change
Rapid separation of bacteria from blood – Chemical aspects
No full textTo rapidly diagnose infectious organisms causing blood sepsis, bacteria must be rapidly separated from blood, a very difficult process considering that concentrations of bacteria are many orders of magnitude lower than concentrations of blood cells. We have successfully separated bacteria from red and white blood cells using a sedimentation process in which the separation is driven by differences in density and size. Seven mL of whole human blood spiked with bacteria is placed in a 12-cm hollow disk and spun at 3000 rpm for 1 min. The red and white cells sediment more than 30-fold faster than bacteria, leaving much of the bacteria in the plasma. When the disk is slowly decelerated, the plasma flows to a collection site and the red and white cells are trapped in the disk. Analysis of the recovered plasma shows that about 36% of the bacteria is recovered in the plasma. The plasma is not perfectly clear of red blood cells, but about 94% have been removed. This paper describes the effects of various chemical aspects of this process, including the influence of anticoagulant chemistry on the separation efficiency and the use of wetting agents and platelet aggregators that may influence the bacterial recovery. In a clinical scenario, the recovered bacteria can be subsequently analyzed to determine their species and resistance to various antibiotics
Fault-Tolerant Network Topologies for Datacenters
No full textA Master of Science thesis in Computer Engineering by Heba Mahmoud Helal Attia entitled, "Fault-Tolerant Network Topologies for Datacenters," submitted in May 2017. Thesis advisor is Dr. Rana Ahmed. Soft and hard copy available. Embargo expires February 08, 2018.Data centers are an integral part of cloud computing infrastructure to support various cloud-based services such as web search, email, social networking, distributed file systems and scientific computing. Data centers provide huge computational power and storage, reliability, availability, and cost-effective solutions needed by the cloud applications. A data center network (DCN) topology connects thousands of servers within the datacenter and to the external world. The topology is vulnerable to failures due to the presence of huge number of servers, switches and links. Several data center network topologies have been proposed and implemented; however, most of them lack the ability to recover from failures. One of the biggest challenges in DCN is to provide a graceful degradation in performance in the event of a link or server failure. Fault-tolerance in a DCN topology can be provided by adding extra hardware (switches, links) or by provisioning of multiple redundant routing paths among servers. This thesis proposes two new fault-tolerant DCN topologies derived from the standard topology. The proposed topologies, − and −, are both cost-effective and scalable. In addition, the proposed topologies enhance the overall performance (throughput and latency) of topology, and offer graceful performance degradation in the case of a link or server failure. Furthermore, we propose a new mechanism to select the optimal path between the hosts in the topology using Genetic Algorithm (GA). Performance evaluation of the proposed topologies and techniques is done through a simulation study using realistic intra-datacenter traffic models, and the results are compared with the standard topology. The comparison is done in terms of various metrics such as throughput, latency, diameter, and average shortest path length. The simulation results show that the proposed topologies outperform the standard topology due to the availability of multiple alternate shortest paths between any pair of servers, resulting in an improvement of about 5% in throughput even for a small-size network. GA algorithm for the path selection is applied to the two proposed topologies, and it is found that there is a further improvement of about 2% in the throughput of the topologies.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Target Detection Using Learning Methods
No full textA Master of Science thesis in Electrical Engineering by Mohammad Moufeed Sahnoon entitled, "Target Detection Using Learning Methods," submitted in June 2017. Thesis advisor is Dr. Khaled Assaleh and thesis co-advisors are Dr. Usman Tariq and Dr. Hasan Mir. Soft and hard copy available.Adaptive beamforming is an array processing method that can be used for target detection. In the absence of clutter signals, this method uses a one-dimensional adaptive filter called the space filter in the spatial dimension using a uniformly linear array as a receiver that is made of N-channels separated by a distance d. The N-receiver channels work on collecting target-free data that can be used as training data for the radar along with collecting the target signal with all types of interferences. The training data are then used to build the covariance matrix that is used in determining the adaptive beamformer filter weights. After that, the received data are projected onto these weights to null the jamming signals, minimize noise, and amplify the target signal. Finally, the output, after projection, is compared with a measured threshold value to decide upon the presence of the target. This conventional method suffers from several problems such as target cancellation when the training data collected are not target free. Furthermore, the amount of secondary data required is usually not available in such applications. Thus, different algorithms must be found or developed to overcome or improve the problems of the conventional method. In this report, a target detection system that involves direction of arrival estimation and learning based algorithms is proposed. The proposed system is assumed to overcome the problem of the jamming signal direction of arrival variations between the training and testing stages, signal-to-interference-plus-noise-ratio variations and the necessity for target free secondary data. Another target detection system is also proposed, i.e. the cascade system. This system uses the adaptive beamforming method as an unsupervised dimensionality reduction technique in line with the learning-based method for target detection, and it shows a comparable performance as compared to the original proposed system.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
