Engineering Commons^™

Protecting Health Data In A Pandemic: A Systematic Adversarial Threat Analysis Of Contact Tracing Apps, Leah Krehling

Electronic Thesis and Dissertation Repository

In this thesis centralized, decentralized, Bluetooth, and GPS based applications of digital contact tracing were reviewed and assessed. Using privacy principles created by a contingent of security and privacy experts from across Canada, a metric of assessing an application’s privacy was created. An attack tree was built to assess the security of the contact tracing applications. Eighteen attacks were theorized against contact tracing applications currently in use. An application’s vulnerability to the attacks was measured using a scoring system developed for this purpose. The results of the security scores were used to create a metric for assessing the security of …

Modeling And Simulation Of Concentric And Eccentric Tube Continuum Robots, Lexuan Wang

Electronic Thesis and Dissertation Repository

Unlike conventional manipulators where the robot is actuated at discrete joints, continuum robots are actuated continuously in smooth curves. These robots are often dexterous and compact, allowing them to operate in constrained environments during minimally invasive medical interventions. Since the unconventional robot structure often consists of elastic or flexible materials, the corresponding kinematics formulation is significantly more challenging to derive and simulate. This thesis introduces two different but related continuum robot designs: the concentric tube robot (CTR) and the eccentric tube robot (ETR). These designs utilize multiple pre-curved and superelastic nitinol tubes to actuate the robot. This mechanism also leads …

Radiometric Correction Of Multispectral Cameras Using Photosensor Irradiance For Agronomy Applications, Nicholas S. Mitchell

Electronic Thesis and Dissertation Repository

Cloud coverage has a significant impact on the reflectance maps generated by multispectral cameras mounted on UAV's in small farm settings. The current approach is to calibrate the camera once before every flight and use the radiometric calibration map for the entire flight. In this work we have designed and built a downwelling and upwelling photosensor to work in sync with our custom multispectral camera. A dual reflectance panel implementation for the time dependent radiometric calibration of the multispectral camera is completed. The solar spectral irradiance curve is approximated using the current measurements from the downwelling photosensor and the ground …

Intelligent And Low Overhead Network Synchronization Over Large-Scale Industrial Internet Of Things Systems, Pengyi Jia

Electronic Thesis and Dissertation Repository

With the extensive development of information and communication technologies and vertical industry applications, industrial IoT (IIoT) systems are expected to enable a wide variety of applications, including advanced manufacturing, networked control, and smart supply chain, which all exclusively hinge on the efficient cooperation and coordination among the involved IIoT machines and infrastructures. The ubiquitous connection among IIoT entities and the associated exchange of collaborative information necessitate the achievement of accurate network synchronization, which can guarantee the temporal alignment of the critical information. To enhance the temporal correlation of heterogeneous devices in large-scale IIoT systems, this thesis aims at designing industry-oriented …

Efficient Hardware Architectures For Public-Key Cryptosystems, Mohammadamin Saburruhmonfared

Electronic Thesis and Dissertation Repository

Finite field arithmetic plays an essential role in public-key cryptography as all the underlying operations are performed in these fields. The finite fields are either prime fields or binary fields. Binary field elements can mainly be represented on a polynomial basis or a normal basis (NB). NB representation offers a simple squaring operation, especially in hardware. However, multiplication is typically complex, and a particular subset of NB called Gaussian Normal Basis (GNB) features an efficient multiplication operation used in this work. The first part of this thesis has focused on improving finite field arithmetic architectures over GNB. Among different arithmetic …

Towards Efficient And Secure Iiot: Solutions For The Sensing Domain, Elena Uchiteleva

Electronic Thesis and Dissertation Repository

This work explores reduced complexity solutions for the increased efficiency and safety of the industrial Internet of Things (IIoT) sensing domain. Resource virtualization, security, and predictive modeling are the main subjects of these studies.

The first solution is a joint throughput and time-resource allocation scheme for virtualization of IEEE 802.15.4-based wireless sensor networks. Virtualization is realized through the utilization of the guaranteed time slot mechanism for scheduling on the medium access control (MAC) layer. The solution abstracts resources into logical units that are allocated to segregated applications with different service requirements. The problem is formulated in a linear optimization framework …

Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad

Electronic Thesis and Dissertation Repository

Three research projects are presented in this manuscript. Projects one and two describe two waveform relaxation algorithms (WR) with longitudinal partitioning for the time-domain analysis of transmission line circuits. Project three presents theoretical results about the convergence of WR for chains of general circuits.

The first WR algorithm uses a assignment-partition procedure that relies on inserting external series combinations of positive and negative resistances into the circuit to control the speed of convergence of the algorithm. The convergence of the subsequent WR method is examined, and fast convergence is cast as a generic optimization problem in the frequency-domain. An automatic …

Orthogonal Frequency Division Multiplexing System With Index Modulations For Wireless Communication, Ibrahim M Abdalla Aboharba

Electronic Thesis and Dissertation Repository

Orthogonal Frequency Division Multiplexing (OFDM) with Index Modulation (OFDM-IM) system with arbitrary and are suggested and investigated for data transmission over realistic fading and shadowing wireless communication channels. In these OFDM-IM systems, data is conveyed to the receiver using characteristics of signal mapper in the OFDM system and by using indices of active subcarriers dictated by the type of IM employed. Two types of index modulations, arbitrary and Look-Up Table (LUT), are described and examined for selection of active subcarriers in OFDM systems with OOK (ON-OFF Keying), M-QAM (M-ary Quadrature Amplitude Modulation), and M-PSK (M-ary Phase Shift Keying) signal mappers. …

Characterization And Control Of A Woven Biomimetic Actuator For Wearable Neurorehabilitative Devices, Vaughan K. Murphy

Electronic Thesis and Dissertation Repository

Strokes are a major cause of death and disability, with nearly 300,000 Canadians suffering from stroke-related disability. Many survivors suffer from upper limb paresis, which makes ordinary tasks difficult. Availability of care is an issue, with only 43.3% of patients in Ontario receiving proper treatment. Robot-assisted neurorehabilitation has been used to address limited clinician availability, and has been shown to improve patient strength and range of motion faster than or comparable to traditional methods. However, the size and weight of current devices limit their use to within therapists’ offices. Incorporating actuators into clothing would make the devices more comfortable, natural …

Deep Reinforcement Learning In Medical Object Detection And Segmentation, Dong Zhang

Electronic Thesis and Dissertation Repository

Medical object detection and segmentation are crucial pre-processing steps in the clinical workflow for diagnosis and therapy planning. Although deep learning methods have achieved considerable performance in this field, they impose several shortcomings, such as computational limitations, sub-optimal parameter optimization, and weak generalization. Deep reinforcement learning as the newest artificial intelligence algorithm has great potential to address the limitation of traditional deep learning methods, as well as obtaining accurate detection and segmentation results. Deep reinforcement learning has a cognitive-like process to propose the area of desirable objects, thereby facilitating accurate object detection and segmentation. In this thesis, we deploy deep …

Material Evaluation And Structural Monitoring Of Early-Age Masonry Structures, Kyle Dunphy

Electronic Thesis and Dissertation Repository

During the initial construction period, “early-age” masonry walls are susceptible to lateral loads induced by wind or earthquake, which may result in damages or catastrophic failures. To mitigate such consequences at construction sites, temporary bracings are adopted to provide lateral support to masonry walls until they are matured enough to serve as the inherent lateral system of the structure. However, current temporary bracing guidelines provide oversimplified design due to the lack of available information on the material properties of early-age masonry. Moreover, there are no existing techniques for monitoring masonry walls to detect cracks due to construction activities. …

Network Resource And Performance Optimization In Autonomous Systems: A Connected Vehicles And Autonomous Networks Perspective, Ibrahim Shaer

Electronic Thesis and Dissertation Repository

This thesis covers two topics that optimize a network-related problem subject to environment-specific constraints; placing vehicular applications and executing network traffic assignment changes. The first topic introduces an optimization model, Resource and Delay-aware V2X service Placement (RDP), and a baseline approach that only considers the resource requirements of vehicular services. Both are responsible for placing vehicular services used by vehicular applications in an edge computing environment. Under different simulation scenarios, the results obtained by RDP satisfy the delay requirements of vehicular applications as opposed to the baseline approach. The second topic examines the efficient execution of inter-domain traffic changes under …

A New Approach For Homomorphic Encryption With Secure Function Evaluation On Genomic Data, Mounika Pratapa

Electronic Thesis and Dissertation Repository

Additively homomorphic encryption is a public-key primitive allowing a sum to be computed on encrypted values. Although limited in functionality, additive schemes have been an essential tool in the private function evaluation toolbox for decades. They are typically faster and more straightforward to implement relative to their fully homomorphic counterparts, and more efficient than garbled circuits in certain applications. This thesis presents a novel method for extending the functionality of additively homomorphic encryption to allow the private evaluation of functions of restricted domain. Provided the encrypted sum falls within the restricted domain, the function can be homomorphically evaluated “for free” …

Intelligent Security Provisioning And Trust Management For Future Wireless Communications, He Fang

Electronic Thesis and Dissertation Repository

The fifth-generation (5G)-and-beyond networks will provide broadband access to a massive number of heterogeneous devices with complex interconnections to support a wide variety of vertical Internet-of-Things (IoT) applications. Any potential security risk in such complex systems could lead to catastrophic consequences and even system failure of critical infrastructures, particularly for applications relying on tight collaborations among distributed devices and facilities. While security is the cornerstone for such applications, trust among entities and information privacy are becoming increasingly important. To effectively support future IoT systems in vertical industry applications, security, trust and privacy should be dealt with integratively due to their …

An Investigation Of The Interleaved Operation Of A Stacked Ac-Dc Single-Stage Flyback Converter, Mengkai Xiong

Electronic Thesis and Dissertation Repository

Low power AC-DC power conversion is typically done with a two-stage converter that consists of an AC-DC front-end boost converter that also performs input power factor correction and an isolated DC-DC back-end converter that is either a flyback or a forward converter. In applications where cost is an overriding factor, single-stage AC-DC converters that use a single power converter to simultaneously perform input power factor correction and AC-DC conversion can be used. In applications where output filtering and hold-up time are important considerations, single-stage AC-DC converters are implemented with a DC bus capacitor.

The main objective of this thesis is …

Terramechanics And Machine Learning For The Characterization Of Terrain, Bryan W. Southwell

Electronic Thesis and Dissertation Repository

An instrumented rover wheel can collect vast amounts of data about a planetary surface. Planetary surfaces are changed by complex geological processes which can be better understood with an abundance of surface data and the use of terramechanics. Identifying terrain parameters such as cohesion and angle of friction hold importance for both the rover driver and the planetary scientist. Knowledge of terrain characteristics can warn of unsafe terrain and flag potential interesting scientific sites. The instrumented wheel in this research utilizes a pressure pad to sense load and sinkage, a string potentiometer to measure slip, and records motor current draw. …

Performance Evaluation, Comparison And Improvement Of The Hardware Implementations Of The Advanced Encryption Standard S-Box, Doaa Ashmawy

Electronic Thesis and Dissertation Repository

The Advanced Encryption Standard (AES) is the most popular algorithm used in symmetric key cryptography. The efficient computation of AES is essential for many computing platforms. The S-box is the only nonlinear transformation step of the AES algorithm. Efficient implementation of the AES S-box is very crucial for AES hardware. The AES S-box could be implemented by using look-up table method or by using finite field arithmetic. The finite field arithmetic design approach to implement the AES S-box is superior in saving the hardware resources. The main objective of this thesis is to evaluate, compare and improve the hardware implementations …

Analytic Delay Model Of Rlc Interconnects Using Numerical Inversion Of The Laplace Transform, Yu Jiang

Electronic Thesis and Dissertation Repository

Signal integrity analysis for on-chip interconnect becomes increasingly important in high-speed designs. SPICE, a conventional circuit simulator, can provide accurate prediction for interconnects, however, using SPICE is extremely computationally expensive. On the other hand, explicit moment matching technique can produce unstable poles for highly accurate approximations and implicit moment matching technique can obtain more accurate approximations at the expense of computational complexity. This thesis presents an analytic model to efficiently estimate the signal delays of RLC on-chip interconnects. It uses the numerical inversion of Laplace transform (NILT) to obtain time function, suitable for transient analysis. Since the integration formula of …

Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat

Electronic Thesis and Dissertation Repository

The rapid growth of the Internet and related technologies has led to the collection of large amounts of data by individuals, organizations, and society in general [1]. However, this often leads to information overload which occurs when the amount of input (e.g. data) a human is trying to process exceeds their cognitive capacities [2]. Machine learning (ML) has been proposed as one potential methodology capable of extracting useful information from large sets of data [1]. This thesis focuses on two applications. The first is education, namely e-Learning environments. Within this field, this thesis proposes different optimized ML ensemble models to …

Novel Estimation And Detection Techniques For 5g Networks, Anas Saci

Electronic Thesis and Dissertation Repository

The thesis presents several detection and estimation techniques that can be incorporated into the fifth-generation (5G) networks. First, the thesis presents a novel system for orthogonal frequency division multiplexing (OFDM) to estimate the channel blindly. The system is based on modulating particular pairs of subcarriers using amplitude shift keying (ASK) and phase-shift keying (PSK) adjacent in the frequency domain, which enables the realization of a decision-directed (DD) one-shot blind channel estimator (OSBCE). The performance of the proposed estimator is evaluated in terms of the mean squared error (MSE), where an accurate analytical expression is derived and verified using Monte Carlo …

Vehicle Networks: Statistical And Game Theoretic Approaches To Their Evaluation And Design, Gleb Dubosarskii

Electronic Thesis and Dissertation Repository

Vehicle ad hoc networks (VANETs) have become a popular topic in modern research. The main advantages of these networks include: improved security, traffic optimization, and infotainment. However, deploying such networks in practice requires extensive infrastructure. To estimate the network load, one needs to have information about the network, such as the number of clusters, cluster size, etc. Since VANETs are formed by vehicles that rapidly change their location, the network topology is constantly changing, making its analysis by deterministic methods impossible. Therefore, in this dissertation, we use probability theory methods to obtain probability distributions of such fundamental network properties, such …

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh

Electronic Thesis and Dissertation Repository

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …

Hyperspectral Image Classification For Remote Sensing, Hadis Madani

Electronic Thesis and Dissertation Repository

This thesis is focused on deep learning-based, pixel-wise classification of hyperspectral images (HSI) in remote sensing. Although presence of many spectral bands in an HSI provides a valuable source of features, dimensionality reduction is often performed in the pre-processing step to reduce the correlation between bands. Most of the deep learning-based classification algorithms use unsupervised dimensionality reduction methods such as principal component analysis (PCA).

However, in this thesis in order to take advantage of class discriminatory information in the dimensionality reduction step as well as power of deep neural network we propose a new method that combines a supervised dimensionality …

Synchrophasor Based Islanding & Open Phase Fault Protection In Distribution Systems, Mansour Jalali

Electronic Thesis and Dissertation Repository

With the rapid growth of renewable energy resources, energy efficiency initiatives, electric vehicles, energy storage, etc., distribution systems are becoming more complex such that conventional protection, control, and measurement infrastructure – typically concentrated at the main substation, with little to no access to information along the feeder – cannot maintain the reliability of the system without some sort of additional protection, control and measurement functionalities. As an example, a dedicated communication channel for carrying the transfer trip signal from the substation to the Point of Common Coupling (PCC) to prevent islanding operation of alternative resources, has been a requirement for …

Advanced Hardware And Software Approach To Seismic Site Response Investigations, Aleksandar Dimitrov Mihaylov

Electronic Thesis and Dissertation Repository

Vibration measurement is an essential aspect of modern geotechnical engineering. It is particularly vital task for measuring the dynamic soil parameters, estimating seismic hazards and evaluating influence of industrial, traffic and construction vibrations on the surrounding buildings, structures and their elements. Meanwhile, commercial exploration seismic stations and data acquisition systems require significant professional knowledge and training in geophysics or vibration measurement, as well as practical skills and experience in adjusting data acquisition parameters. Furthermore, available seismological investigation and vibrometry sensors are not universally suitable for field applications in geophysical studies, soil-structure interaction investigations or structural vibrations. The frequency range suitable …

Geometric State Observers For Autonomous Navigation Systems, Miaomiao Wang

Electronic Thesis and Dissertation Repository

The development of reliable state estimation algorithms for autonomous navigation systems is of great interest in the control and robotics communities. This thesis studies the state estimation problem for autonomous navigation systems. The first part of this thesis is devoted to the pose estimation on the Special Euclidean group $\SE(3)$. A generic globally exponentially stable hybrid estimation scheme for pose (orientation and position) and velocity-bias estimation on $\SE(3)\times \mathbb{R}^6$ is proposed. Moreover, an explicit hybrid observer, using inertial and landmark position measurements, is provided.

The second part of this thesis is devoted to the problem of simultaneous estimation of the …

Dc-Dc And Ac-Dc Converters Based On Three-Phase Dc-Dc Topologies, Adel Ali Abosnina

Electronic Thesis and Dissertation Repository

Power electronics is the field of electrical engineering that uses power semiconductor devices along with passive elements such as inductors, capacitor and transistors to convert electrical power that can be generated by a source to a form that is suitable for user loads. The main focus of this thesis is on the development of new DC-DC and AC-DC topologies that are based on three-phase DC-DC converters. Three-phase DC-DC converters take an input DC voltage, convert it into a high-frequency AC voltage that is then stepped up or down, then rectify and filter this voltage to produce an output DC voltage. …