identifier: Pawar, Yogesh  (2020) A Study on Anomaly Detection Using Mixture Models.  Masters thesis, Concordia University.

abstract:
With the increase in networks capacities and number of online users, threats of different cyber attacks on computer networks also increased significantly, causing the loss of a vast amount of money every year to various organizations. This requires the need to identify and group these threats according to different attack types. Many anomaly detection systems have been introduced over the years based on different machine learning algorithms. More precisely, unsupervised learning algorithms have proven to be very effective. In many research studies, to build an effective ADS system, finite mixture models have been widely accepted as an essential clustering method.
In this thesis, we deploy different non-Gaussian mixture models that have been proven to model well bounded and semi-bounded data. These models are based on the Dirichlet family of distributions. The deployed models are tested with Geometric Area Analysis Technique (GAA) and with an adversarial learning framework.
Moreover, we build an effective hybrid anomaly detection system with finite and in-finite mixture models. In addition, we propose a feature selection approach based on the highest vote obtained. We evaluated the performance of mixture models with Geometric Area Analysis technique based on Trapezoidal Area Estimation (TAE) and the effect of adversarial learning on ADS performance via extensive experiments based on well-known data sets.


identifier: haghighatjoo, mohammadreza  (2020) a numerical investigation of free-fall swirling gas atomization process.  Masters thesis, Concordia University.

type: Thesis NonPeerReviewed

abstract: Gas atomization is a complex multi-physics route in the powder production field. Fine spherical metal powders can be produced using this technique via atomizing superheated molten metals. In the powder production industry, free-fall gas atomizer is often used for the melt atomization. The most significant advantage of using this type of atomizer is that it avoids melt build-up in the vicinity of gas and melt nozzle exits; the problem which is much more pronounced in the close-coupled gas atomizers. Obtaining smaller particle median diameter (d50) and narrower particle size distribution (PSD) have been the major manufacturing challenge. In the present work, a numerical parametric study is carried out on the atomization process variables of a novel layout of free-fall atomizer in order to reduce d50 and narrow down PSD. The used free-fall atomizer features a swirl motion of gas stream which allows the breakup point of the molten jet to be located at a closer distance to the die and benefits the most from the kinetic energy of the gas jets. A two-way coupled Eulerian-Lagrangian approach is utilized. Ideal gas law and k-epsilon turbulence model are employed to simulate the gas flow. In addition, the adaptive mesh refinement (AMR) technique is used to refine the computational domain locally and model the supersonic jet flow more accurately. The number of cells in the domain reaches around 40 million, and five to six shock diamonds are captured using this technique. To model the discrete (particulate) phase, the effects of Reynolds, Mach, and Knudsen numbers on the drag coefficient and Nusselt number on heat transfer are included. Moreover, Kelvin-Helmholtz Rayleigh-Taylor (KHRT) breakup model is used to simulate the molten metal atomization process. It is found that under the same operating condition, the increase in gas to melt ratio (GMR) and number of nozzles result in a smaller d50 and narrower PSD. This numerical analysis also investigates the effect of change in a range of radial and swirl angles. It is observed that increasing the radial angle and decreasing the swirl angle could narrow down the particle size distribution and reduce the particle median diameter.


identifier: Jadhav, Kunal Dhananjay  (2020) Experimental studies of natural convection of carbopol gels in a cavity with differentially heated sidewalls.  Masters thesis, Concordia University.

abstract:
Yield stress fluids resist flow unless an external force greater than their yield stress is applied to them.
The current thesis investigates the behavior of yield stress fluids subjected to a temperature gradient. We use
carbopol gels as a yield stress fluid to perform fluid flow characterization. The experimental setup includes a
cubical acrylic cell with aluminum sidewalls, 2 Thermoelectric units, thermocouples, and thermistors. Rheological
characterization of carbopol gels was performed, and yield stress was calculated by fitting the data
using the Herschel Bulkley equation. PIV (Particle Image velocimetry) technique was used for flow characterization.
Thermochromic liquid crystals (TLC) were used to visualize the temperature isotherms in the
flow field. Our experimental observations suggested an immediate flow onset with extremely slow sub yield
motions. The benchmark motionless experiments were compared with steady flow experiments to reveal
the immediate flow onset dynamics. The flow development curves showed rapid flow acceleration until it
reaches a maximum before decelerating to steady-state. The experiments with no steady flow developments
were compared with benchmark motionless experiments, supporting the presence of subyield motions in
yield stress fluids. The kinetic energy decayed exponentially to rest from the point when the supplied power
turned off during experiments.
iii


identifier: Norouzi, Shahrzad ORCID: https://orcid.org/0000-0002-9185-847X <https://orcid.org/0000-0002-9185-847X>  (2020) Flow Characteristics in Abdominal Aortic Aneurysms: An in vitro Study.  Masters thesis, Concordia University.

abstract:
An abdominal aortic aneurysm (AAA)  is a vascular disorder that emerges when the aortic wall degenerates and the abdominal aorta undergoes a permanent expansion of at least 1.5 times its normal diameter. If an AAA is left undiagnosed and untreated, it can eventually rupture with an associated mortality risk of 81%. Clinically, a maximum diameter exceeding 5 cm is considered the decisive criterion to identify at-risk AAAs. The present work investigates the flow dynamic variations associated with aneurysm experimentally, using compliant AAA models and time-resolved particle image velocimetry (TR-PIV). For this purpose, an in vitro setup is designed and developed to simulate the flow inside 6 idealized phantoms mimicking in vivo physiological properties. The instantaneous flow fields in two orthogonal planes reveal that the flow behavior in the early stages of an aneurysm does not deviate significantly from that of the healthy aorta. An increase in the size and number of bulges triggered the evolution of features such as flow detachment, swirling motion, wall impingement and the collapse of the vortical structures within the aneurysm sac. All these characteristics are more noticeable in the AAA model with a maximal diameter equal to the clinical threshold. Therefore, in the context of fluid dynamics, this perception can provide physical support to the Dmax=5 cm criterion to nominate an AAA patient for elective surgery. It is assumed that the onset and propagation of large vortical structures in the deceleration phase and the formation of stagnant flow regions near the proximal neck of the largest model can lead to unfavorable hemodynamic changes that escalate the weakening, enlargement and rupture of the aortic wall.
Following recent applications of viscous energy dissipation in the severity stratification of cardiovascular diseases, as part of this thesis, the associated energy loss is quantified in order to examine its correlation with changes in the geometry and flow topology of each model. Although the two largest models were identified with the highest energy losses, which can be attributed to their higher shear stresses, this parameter does not follow a clear increase with the aneurysm expansion. In the other four cases, the kinetic energy was almost equally well preserved. The experimental AAA flow data in this work is also inspected from a modal analysis perspective, in particular proper orthogonal decomposition (POD), to identify and extract the dominant structures, which can provide more insights on the disease progression. The Shannon (global) entropy demonstrates that as the aneurysm expands, the modal energy distribution becomes dispersed, meaning that more modes are required to describe and model the flow. This parameter, in turn, can potentially be applied in clinical assessment of the severity of patient-specific AAAs.


identifier: Rouhani Esfahani, AmirReza  (2020) Portable, Stable, and Sensitive Assay to Detect Phosphate in Water with Gold Nanoparticles and Dextran Tablet.  Masters thesis, Concordia University.

abstract:
Phosphate (Pi) is a necessary element for growth and energy transport in humans, animals and plants. However, the excess amount of this element could cause severe problems such as joint pain and skin rash for humans and eutrophication in nature. Eutrophication is the enrichment of nutrients, especially phosphate, in aquatic systems, with harmful effects on surface water bodies, such as lakes and creatures in the water.
This thesis investigated the applicability of gold nanoparticles to detect phosphate using different methods including paper-based and tablet-based sensors. A novel and highly sensitive tablet-based colorimetric sensor is developed to detect phosphate (Pi) in water using mercaptoacetic acid-gold nanoparticles (MA-AuNPs). The principle of this sensor is based on the aggregation (blue colored) and disaggregation (red-colored) mechanism of AuNPs due to surface plasmon resonance, where europium ions (Eu3+) act as an aggregating agent. Herein, dextran tablets encapsulated the Eu3+ ions to make the detection system user friendly. Hence, the sensor just requires dissolving the Eu3+-dextran tablet into the water sample and subsequently adding MA-AuNPs for the colorimetric quantification of phosphate. This assay is very sensitive, with a calculated lower detection limit of 3.779 µg/L and upper detection limit of 0.328 mg/L. The assay does not interfere with common ions in water, thus being Pi-specific, and the display results were stable up to three weeks. Overall, this new approach provides a simple, stable, rapid, low cost and promising device for Pi detection in water.


identifier: Abdelwahab, Ahmed ORCID: https://orcid.org/0000-0001-6079-762X <https://orcid.org/0000-0001-6079-762X>  (2020) Secure Control of Cyber-Physical Systems.  Masters thesis, Concordia University.

abstract:
Cyber-Physical Systems (CPS) are smart co-engineered interacting networks of physical and computational components. They refer to a large class of technologies and infrastructure in almost all life aspects including, for example, smart grids, autonomous vehicles, Internet of Things (IoT), advanced medical devices, and water supply systems. The development of CPS aims to improve the capabilities of traditional engineering systems by introducing advanced computational capacity and communications among system entities. On the other hand, the adoption of such technologies introduces a threat and exposes the system to cyber-attacks. Given the unique properties of CPSs, i.e. physically interacting with its environment, malicious parties might be interested in exploiting the physical properties of the system in the form of a cyber-physical attack. In a large class of CPSs, the physical systems are controlled using a feedback control loop. In this thesis, we investigate, from many angles, how CPSs' control systems can be prone to cyber-physical attacks and how to defend them against such attacks using arguments drawn from control theory.

In our first contribution, by considering Smart Grid applications, we address the problem of designing a Denial of Service (DoS)-resilient controller for recovering the system's transient stability robustly. We propose a Model Predictive Control (MPC) controller based on the set-theoretic (ST) arguments, which is capable of dealing with both model uncertainties, actuator limitations, and DoS. Unlike traditional MPC solutions, the proposed controller has the capability of moving most of the required computations into an offline phase. The online phase requires the solution of a quadratic programming problem, which can be efficiently solved in real-time. Then, stemming from the same ST based MPC controller idea, we propose a novel physical watermarking technique for the active detection of replay attacks in CPSs. The proposed strategy exploits the ST-MPC paradigm to design control inputs that, whenever needed, can be safely and continuously applied to the system for an apriori known number of steps. Such a control scheme enables the design of a physical watermarked control signal. We prove that, in the attack-free case, the generators' transient stability is achieved for all admissible watermarking signals and that the closed-loop system enjoys uniformly ultimately bounded stability.

In our second contribution, we address the attacker's ability to collect useful information about the control system in the reconnaissance phase of a cyber-physical attack. By using existing system identification tools, an attacker who has access to the control loop can identify the dynamics of the underlying control system. We develop a decoy-based moving target defense mechanism by leveraging an auxiliary set of virtual state-based decoy systems. Simulation results show that the provided solution degrades the attacker's ability to identify the underlying state-space model of the considered system from the intercepted control inputs and sensor measurements. It also does not impose any penalty on the control performance of the underlying system.

Finally, in our third contribution, we introduce a covert channel technique, enabling a compromised networked controller to leak information to an eavesdropper who has access to the measurement channel. We show that this can be achieved without establishing any additional explicit communication channels by properly altering the control logic and exploiting robust reachability arguments. A dual-mode receding horizon MPC strategy is used as an illustrative example to show how such an undetectable covert channel can be established.


identifier: Hemmati, Maryam  (2020) A submodular representation for hub networkdesign problems with profits and single assignments.  Masters thesis, Concordia University.

abstract:
Hub network design problems (HNDPs) lie at the heart of network design planning in transportation and telecommunication systems. They constitute a challenging class of optimization problems that focus on the design of a hub network. In this work, we study a class of HNDPs, named hub network design problems with profits and single assignments, which forces each node to be assigned to exactly one hub facility.

We propose three different combinatorial representations for maximizing the total profit defined as the difference between the perceived revenues from routing a set of commodities minus the setup cost for designing a hub network, considering the single allocation assumption. We investigate whether the objective function of each representation satisfies the submodular property or not. One representation satisfies submodularity, and we use it to present an approximation algorithm with polynomial running time. We obtain worst-case bounds on the approximations’ quality and analyze some special cases where these worst-case bounds are sharper.


identifier: Vakacharla, Venkata Ratnam  (2020) Analysis and Design of High Voltage Gain Three-Elements Resonant Soft-Switching Current-fed DC/DC Converters.  PhD thesis, Concordia University.

abstract:
Transportation electrification and distributed generation are proven effective strategies to counter climate change. Modern generation and transportation aim to bring down the carbon footprint by transforming the fossil fuel-driven society with alternate energy sources and electric propulsion, respectively. However, harnessing energy from renewable sources is not straight forward but demands a suitable power electronic interface. Similarly, electric transportation propulsion system demands for specific power conversion stages. These power electronic conversion systems include dc-dc converter and dc-ac inverter. Cost, efficiency, power density, and weight are the major requirements of these converters. To obtain these merits, high-frequency soft-switching converters are selected and designed. Resonant converters with a suitable resonance have been usually explored for voltage-fed switching converters to obtain soft-switching of the semiconductor devices at high-frequency. However, owing to the high voltage gain requirements of the solar/fuel cells/batteries, this thesis explores current-fed topologies with different resonant circuits with natural voltage gain.
In traditional voltage-fed resonant converters, it is observed that the converter characteristics can be fine-tuned to design the requirements by proper selection of resonant tank. In addition, the resonant tank can integrate the transformer non-idealities and circuit/device parasitic in circuit operation thereby suppressing the consequent voltage spikes across the semiconductor devices. Since voltage-fed converters is fundamentally not suitable for high voltage gain and low voltage applications, this thesis attempts to improve current-fed dc/dc converter characteristics with resonant tanks.
In this thesis, a current-fed load resonant DC/DC converter topology is proposed whose characteristics are tuneable with the adopted resonant tank. Further, this thesis proposes a simple technique to ease and improve accuracy of the Fundamental Harmonic Analysis (FHA), which would have been complex otherwise due to capacitive termination of proposed converter. Initially, the characteristics of the proposed converter topology with a parallel resonance derived LCC-T resonant tank is studied to implement zero voltage switching (ZVS) and zero current switching (ZCS) of the semiconductor devices. Three-phase topology of the same has been investigated and analysed. Following the study and a need to further improve the characteristics of resonant dc/dc converter, a series resonance based LCL resonant converter, a dual of the parallel resonance tank is studied and analysed. The load resonant converters are redeemed for integration of PV/fuel cells. Further, for high power applications, suitability of load resonant converters is verified by adopting resonant tank in three-phase topology.  Proof-of-concept hardware prototypes are designed and developed in the laboratory to demonstrate the performance and the merits of the proposed soft-switching resonant converter topologies as well as to prove the proposed theory and the claims.


identifier: Hassan, Abdelmoniem  (2020) High Gain Antenna Array Design for 5G & MIMO Antenna Systems using Microstrip Ridge Gap Waveguide.  PhD thesis, concordia university.

abstract:
The demand for high data rates and the unavailability of low-frequency bands have driven the need to explore and develop millimeter-wave (mm-wave) frequency bands. Indeed, the development of mm-wave frequencies has led to smaller radio frequency (RF) components and more compact profiles, creating more design constraints and challenges. Millimeter-wave technologies are the best-suited candidates that meet the requirements of 5G standards; specifically, for indoor communication, which requires higher gain and more directive beams. Gap waveguide technologies can be used to design high-gain antenna arrays and multiple input multiple output antenna systems (MIMO).
In this thesis, we are mainly focusing on Microstrip Ridge Gap Waveguide (MRGW) to design the antenna array systems for the 60 GHz band. Therefore, it is necessary to facilitate the design procedures and propose new design techniques. Here, we propose new design techniques for a large antenna array system using MRGW. The work of this thesis can be divided into two parts. Firstly, developing an efficient modeling and design tool for the MRGW to facilitate the design process. Recently, the use of MRGW has increased due to the need for self-packaged and low loss structures for millimeter-wave applications. The MRGW consists of a grounded textured surface, which is representing an artificial magnetic conductor (AMC) surface. The AMC surface is loaded with a thin low dielectric constant substrate with a printed strip topped with another air-filled or dielectric-filled substrate in which the wave propagates between the strip and the conducting plate covering such a substrate.
Currently, full-wave and optimization tools are usually used to design the MRGW structure, which makes the design slow and computationally expensive. Thus, an efficient modeling and design tool for the MRGW is proposed.  Empirical expressions are developed for different MRGW parameters to provide the effective dielectric constant, characteristic impedance, and the dispersion effect. The expressions are verified with the full-wave solution. The results show the potential of the proposed approach in modeling and designing the MRGW structure. Secondly, an efficient procedure to design a large finite planar array and its corporate feeding network is presented. The procedure is verified by an 8 × 8 and 16 ×16 array of magneto-electric (ME) dipoles fed by a network of MRGW. The procedure is based on designing the corporate feeding network by replacing the elements ports with the corresponding effective input impedance of each element that accounts for the mutual coupling between the antenna elements. In addition, the far-field characteristics of the array parameters such as the directivity, gain, and radiation patterns are predicted using pattern multiplication, including the mutual coupling effects. The results are verified with the full-wave numerical solution.
The procedure requires limited resources and speed up the design cycle. The use of the MRGW helps in having the feeding network lines to be titer than using the ridge gap technology. Thus, allowing the distance between the radiating elements becomes smaller than one wavelength to avoid grating lobes. In addition, to avoid undesired bends and very tight lines that cause undesired interaction between the lines, unique power dividers are designed. Furthermore, a transition from waveguide WR-15 to the MRGW is proposed to feed two halves of the array antenna perfect out of phase at all frequencies and rotating each half to form a mirrored array that better radiation pattern symmetry and low cross-polarization. Then, this procedure is implemented to design a circularly polarized antenna array with excellent performance. To further enhance the antenna, gain, and reduce the number of elements, a superstrate dielectric lens with the proper parameters is added. Study of a 4 × 4 MIMO system is studied, where each antenna is a sub-array to achieve the high gain requirements.
Finally, A low-profile, compact, and high-efficiency monopulse array antenna has been presented. The monopulse is built based on a hybrid coupler that has a wideband response for the reflection and the transmission coefficients. Then the monopulse system is used to present a multiplexing antenna system for short-range in the near filed region wireless communication. The multiplexing system works as a MIMO system that has four independent channels. The performance of the system is evaluated through the simulation, which shows that it can be a promising candidate for the next wireless communication systems.


identifier: Amin, Turfa Sarah  (2020) Millimeter-wave Contactless Waveguide Joints and Compact OMT Based on Gap Waveguide Technology.  Masters thesis, Concordia University.

abstract:
Amongst the contemporary gap waveguide structures, both ridge gap waveguide (RGW) and groove gap waveguide (GGWG) display low losses and are resistant to signal leakage without the requirement of electrical contacts. In both scenarios, the concept is to allow the wave propagation through the guiding part and eliminating signal leakage in all other directions. Since, at present, millimeter-wave (mm-wave) has gained attention due to its versatile usability at high-frequency applications, it is quite obligatory to develop components with superior electrical features, like high stability, wider bandwidth, as well as high power handling capability at that frequency range. Considering the stated advantages, the proposed devices in this research work emphases on the mm-wave application that are mainly accountable for connecting standard waveguides and feeding antenna systems.
The research work can be summarized in three segments. The first segment aims at designing waveguide adaptors based on the gap waveguide technology that do not necessarily require perfect electrical contact. The contact-free adaptor has been designed for both standard rectangular and circular waveguides covering multiple mm-wave frequency bands within 50- 110 GHz. Additionally, while designing the adaptor, surface roughness has been considered to achieve the response of the structure close enough to the practical case. The same adapter can also be used with different standard waveguide dimensions operating within 50-110 GHz by changing the adapter’s waveguide parameters. The proposed contact-free adaptor exhibits an excellent return loss and insertion loss of better than 20 dB and 0.3 dB, respectively, for both standard circular and rectangular waveguides, regardless of a smooth or uneven surface.
The second segment focuses on a contact-free flangeless pipe connection for both circular and rectangular standard waveguides, covering multiple frequency bands amid 50 and 110 GHz. The contactless, low-loss, flange-free, and pluggable contact aims at joining two slightly modified standard waveguides, along with a 60% downscaling of the recommended structure compared to the traditional UG-387/U waveguide flange, hence demonstrating a reflection coefficient better than -20 dB in each scenario.
In addition, the third segment is introducing microwave devices that can combine and separate two propagating polarizations, such as orthomode transducers (OMT). Aiming for high power applications with compact structure, the proposed configuration introduces a new design procedure of combining the ridge gap and groove gap waveguides for the OMTs, validating an acceptable matching level of better than -18 dB along with isolation higher than 70 dB.
Finally, some valuable recommendations as an extension of this research work are suggested in the final chapter.


identifier: Savehshemshaki, Shima  (2020) Model Predictive Control Strategies For Constrained Unmanned Vehicles.  Masters thesis, Concordia University.

abstract:
This thesis deals with two control problems for unmanned vehicles,  namely battery shortage prevention for electric unmanned vehicles and collision avoidance strategy for constrained multi unmanned vehicle systems.
In the battery shortage prevention problem, we design a novel control architecture, equipped with a battery manager module, capable of avoiding energy shortage by appropriately imposing time-varying upper bounds on the vehicle's maximum acceleration. Here, the dual-mode control paradigm known as set-theoretic model predictive control is applied to couple the reference tracking and the battery shortage problems. First, we offline design a conservative maximum acceleration profile capable of assuring that the electric unmanned vehicle will reach the desired target without incurring into a battery shortage along the given path. Then, online, by following a receding horizon approach, we show that the battery manager can enhance the performance by using the current battery's state-of-charge. Moreover, a simulation example is presented to clarify and show the proposed control framework's potential and features.
In the collision avoidance problem, we deal with vehicles moving in a shared environment where each UV follows a trajectory given by a local planner. We assume that the planners are uncoordinated and each vehicle is subject to different constraints and disturbances.  In this context, we design a new centralized traffic manager that, in conjunction with ad-hoc designed local model predictive controller, can ensure the absence of collisions while minimizing the total vehicle's stops occurrences.  In particular, in a receding horizon fashion, the traffic manager exploits available previews on the successive vehicle's waypoints to speed-up or speed-down the vehicles and minimize the chance of collisions. Moreover,  by exploiting basic set-theoretic arguments, traffic manager can impose a vehicle to stop and safely prevent collisions whenever necessary. Finally, two different simulation examples are presented to better illustrate the capability of the proposed solution.


identifier: Lardier, William  (2020) ASGARDS-H: Enabling Advanced Smart Grid cyber-physical Attacks, Risk and Data Studies with HELICS.  Masters thesis, Concordia University.

abstract: Smart infrastructures are increasingly built with cyber-physical systems that connect physical operational technology (OT) devices, networks and systems over a cyberspace of ubiquitous information technology (IT). A key objective of such interconnection is to offer a data coverage that will enable comprehensive visibility of dynamic environments and events. The arrival of Internet-of-Things, 5G, and beyond in smart infrastructures will enable the collection of unprecedented volumes of data from these various sources for critical visibility of the entire infrastructure with advanced situational awareness. To break the barriers between the different data silos that limit advanced machine learning techniques against cyber-physical attacks and damages and to allow the development of advanced cross-domain awareness models, the thesis tried to develop a modular, complete and scalable co-simulation platform allowing the generation of standardized datasets for research and development of smart distribution grid security. It addresses the lack of realistic training and testing data for machine learning models to enable the development of more advanced techniques. Our contributions are as follows. First, a modular platform for software-based co-simulation testbed generation is developed using the HELICS co-simulation framework. Second, scenarios of instabilities, faults, cyber-physical attacks are built to allow the generation of a realistic and multi-sourced dataset. Third, well-defined datasets are generated from the developed scenarios to enable and empower data-driven approaches toward smart distribution grid security.


identifier: Nourani, Hosein  (2020) A Comprehensive Comparison of Human Activity Recognition using Inertial Sensors.  Masters thesis, Concordia University.

abstract:
Wearables are becoming increasingly popular. Their built-in sensors (e.g., GPS, accelerometer,
gyroscope, light) can provide useful data for Human Activity Recognition (HAR). During the past few years, many HAR models have been introduced with different accuracies and performance. These models have been applied in different areas such as health, fitness tracking, entertainment, or advertisement. Given that these HAR models run on wearables, which are resource-constrained, factors like
inadequate preprocessing can negatively impact the overall HAR performance. While high accuracy is essential in some applications, the device’s battery life is highly critical to the end-user. Prior studies contain a plethora of activity recognition models and pre-processing techniques
that show a very high recognition performance of these models. These results are mostly reported under a specified study setup different from others, making a fair comparison among them nearly impossible. Nevertheless, to date, very few studies have conducted a side-by-side performance analysis in HAR. Therefore, in this dissertation, we investigate some of the most used HAR techniques to understand their impact when developing an end-to-end HAR model to recognize gym exercises (e.g., ”treadmill, ”bicep-curl,” ”Russian-twist”). This study allows us to examine the accuracy performance yielding from 5 state-of-the-art featuresets in HAR models. Additionally, we focus on feature selection methods and experiment on data reduction to understand trade-offs between accuracy levels and data size.
We find that histogram bins are a valid alternative featureset in HAR, with a significant positive
impact on classification performance and classifier learning rate. Moreover, our finding shows that the data reduction techniques in the feature selection phase can decrease the data size by 93% (from 119 features to 8 features) with minimal impact on model performance, resulting in a large computation saving for the model.


identifier: Nellikulam Davis, Alen  (2020) Digital Microfluidics Chips for Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions.  Masters thesis, Concordia University.

abstract:
Microfluidics is a technology that facilitates the automation and miniaturization of biochemical experiments on platforms of small footprints. Among the different types of microfluidics platforms, digital microfluidics (DMF) devices execute an experiment by manipulating droplets of small volume (usually between 10-6 and 10-9 L) on an array of electrodes using the principles of electrowetting. These DMF chips provide control over individual droplets which enables users to perform multi-step or entirely different experiments without the need for any chip reconfiguration. DMF platforms can also be reused multiple times and can be integrated with other devices like a plate reader to monitor the progress of reactions in real-time. These advantages of DMF devices make them an ideal choice to automate end-end biochemical experiments.
	In this work, we describe the design and performance of two digital microfluidics (DMF) chips capable of executing multiple ribozymatic reactions, with proper controls, in response to short single-stranded DNA inducers. Since the fluorescence output of a reaction is measurable directly from the chip, without the need for gel electrophoresis, a complete experiment, involving up to eight reactions (per chip) can be carried out reliably, relatively quickly and efficiently. The ribozymes can also be used as biosensors of the concentration of oligonucleotide inputs, with high sensitivity, low limits of quantification and of detection, and excellent signal-to-noise ratio. The presented chips are readily usable devices that can be used to automate, speed-up and reduce the costs of ribozymatic reaction experiments.


identifier: Nanda, Neha  (2020) Frobenius Distributions in Short Intervals for Non-CM Elliptic Curves.  Masters thesis, Concordia University.

abstract:
Let E be an elliptic curve defined over Q. An extremal prime for E is a prime p of good reduction such that the number of rational points on E modulo p is minimal or maximal in relation to the Hasse bound, i.e.  In the first case, we say that p is a trailing
prime. In the second case, we say that p is a champion prime. The notion of extremal primes was generalized to primes such that ap(E)/2√p lie in a short interval around c ∈ (0,1] in [AHJ+18], who considered the case of curves with complex multiplication.
In this thesis, assuming E does not have complex multiplication, we study the distribution in short intervals for
	(a_p (E))/(2√p)∈(c-f(p),c) 	(1)
where c ∈ (−1,1] and f(x) = x^δ such that −1/2 ≤ δ < 0. The distribution is different if c = 1 or
c ≠ 1, influenced by the Sato-Tate distribution (see Conjecture 1.1). We use the techniques
of David, Gafni, Malik, Prabhu, and Turnage-Butterbaugh [DGM+19], who considered the extremal primes for elliptic curves without complex multiplication to get an upper bound for the number of primes such that (1) holds, under GRH (Theorem 1.4) and unconditionally (Theorem 1.5).


identifier: Baghdadi, Niloofar  (2020) License Plate Detection Using One-stage Object Detection Algorithms.  Masters thesis, Concordia University.

abstract: Automatic License Plate Detection and Recognition (ALPR) has many practical applications such as traffic control and parking tickets; for this reason, it has been one of the exciting research topics. Environmental factors such as lighting and dust, make automatic license plate detection and recognition challenging, especially for traditional image processing methods. Although much research has been conducted on ALPR systems using image processing and computer vision tools and algorithms, the need for more research on this topic with deep-learning algorithms has not been satisfied yet. Among different and in succession phases of ALPR, the license plate detection phase is of great importance because it is the first phase, and its performance affects the result of other stages. Moreover, due to the advent of technology and artificial intelligence in everyday life, having reliable real-time ALPR systems is necessary. Hence, this work empirically studies the mean Average Precision (mAP) of Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLOv4) on CENPARMI and UFPR-ALPR datasets. Although we achieved good mAP results of 95.47 % (ResNet-SSD) and 95.45 % (InceptionV2-SSD) with the SSD model during this experiment, we have reached the highest mAP of 97.46 % and 97.78 % with the newly released YOLOv4 model on CENPARMI and UFPR-ALPR datasets, respectively. However, in object detection, high precision is not the only essential criterion anymore. Hence, we scrutinized the object-detectors mentioned above to find a model that can balance mAP, speed, and memory. We learned that the higher the number of parameters of a model, the better the detection results. On the other hand, the number of parameters of a model can affect an object detection task’s speed.


identifier: Dodangeh, Ali  (2020) Tackiness characterization of thermoset prepreg materials.  Masters thesis, Concordia University.

abstract:
Defects formation during Automated Fiber Placement (AFP) process is inevitable. So far, various studies have been conducted which look for ways to improve produced sample properties and to limit defects formation. However, there is a lack of comprehensive investigation in this field to provide helpful insight to manufacture a part with the lowest possible defects. The aim of this study is to find a deep understanding of the mechanism during lay-up and how changing individual parameter will affect properties of the layup. In addition, optimum condition for lay-up towpreg, resulting in the lowest possible defects, will be studied. Several parameters are comprehensively investigated in this work namely compaction force, feed-rate, heat-gun temperature, dwell-time and roller materials. Peel-rate is the other parameter that affects the outcome and will be studied. Two in-house set-ups are designed and manufactured. The first one is able to lay-up the towpreg on the substrate surface with different processing conditions (AFP simulator) and the second one is used to measure the peel force which is an indication of the tackiness of the laid-up towpreg. The Taguchi method is used for the design of experiment (DOE), and its prediction is correlated by real tests samples. Results show that for each roller material. The optimum condition is changed. Feed-rate, compaction force and heat gun temperature must be optimized to achieve the tackiest laid-up towpreg.
Key words: AFP, towpreg, tackiness, peel test, Taguchi method.


identifier: Jaunky, Dilan Boodhai  (2020) The Discovery and Characterization of a Novel Family of Anti- Cancer Compounds.  PhD thesis, Concordia University.

abstract: Cancer is amongst the leading causes of death in the world and has plagued humanity for far longer than some would expect. We have come a long way in understanding the physiological changes that correlate with cancer progression, but treatment options remain limited. In this thesis, I developed a high-throughput pipeline to screen thienoisoquinoline derivatives synthesized by Dr. Forgione’s laboratory for their efficacy in reducing cancer cell viability. These derivatives were strategically designed to share a common ¬scaffold and have three functional groups amenable to modifications. From >40 derivatives, we identified our lead compound C75. We characterized the mechanism of action of C75 at a molecular and cellular level to develop a better understanding of its efficacy and selectivity for some cell types over others. Through in vitro assays, we found that C75 prevents microtubule polymerization, destabilizes microtubules, and binds to tubulin at the same site as colchicine (another microtubule-targeting drug). In line with its effects on microtubules, C75 causes mitotic arrest and spindle phenotypes in multiple cancer cell lines in the nanomolar range. However, through comparative studies with colchicine, we found that while colchicine causes a gradual decrease in microtubules and spindle pole collapse in cells, similar concentrations of C75 cause a rapid loss of microtubules and spindle pole fragmentation followed by microtubule re-growth to form multipolar spindles. In addition, C75 and colchicine synergize for reduced viability and spindle phenotypes. Importantly, the phenotypes caused by C75 are similar to those caused by the depletion of ch-TOG, a microtubule polymerase, and tubulin and ch-TOG are displaced and oscillate in C75-treated cells. This suggests that C75 directly causes microtubule depolymerization in cells, or indirectly causes this via inhibiting ch-TOG. We also discovered that C75 has higher efficacy in triple negative breast cancer (TNBC) cells compared to other cell types, suggesting that this could be an ideal group of cancers to explore a potential use for. It will be important to determine if C75 retains its efficacy in TNBCs that are resistant to Taxol, which arises in patients after repeated Taxol use leaving them with few alternative treatment options. We also identified a new derivative that has an even higher efficacy in TNBCs compared to C75, and we are determining if this will be a new lead compound. With a strong understanding of how these compounds work at the molecular and cellular level, we are positioned to carry out in vivo studies to determine their potential for use for treating TNBCs.


identifier: Huard Nicholls, Brandon  (2020) Brand Personality as a Mediator of Visual Complexity Effects on Consumer Responses to Packaging.  Masters thesis, Concordia University.

abstract: Research suggests that the visual complexity of advertisements influences brand attitudes, product attitudes, and purchase intentions. This research seeks to extend findings on the effect of visual complexity to the product package design context. It empirically tests the effect of visual complexity on brand personality dimensions and brand personality appeal, and subsequent effects on brand attitude, product attitude, and purchase intentions. An experimental study manipulates visual complexity of fictitious brand packages in three product categories (ice cream, soda, and dishwashing liquid). A sample of North American consumers rated the brand packages in terms of perceived visual complexity, brand personality dimensions, brand personality appeal, and product attitude, brand attitude and purchase intentions. Overall, visual complexity positively affects consumer responses to brands, although it also negatively influences some brand personality dimensions. Support for a mediating effect of brand personality and brand personality appeal was weak. Many of the observed effects were product-category specific. This study nonetheless adds insights regarding the impact of visual complexity on consumer responses, and provides managerial implications for product design.


identifier: Wang, Yihang  (2020) Effects of Financial and Business Cycles and CEO Characteristics on Firm Risk and Performance.  Masters thesis, Concordia University.

abstract: Using a sample of Chinese A share firms from 1991 to 2019, this thesis extends the literature on how business cycles and financial cycle wavelets relate to firm risks and performance after accounting for CEO demographic characteristics. The thesis documents that higher (lower) firm risks are associated economically and statistically with increases (decreases) during business or financial expansions (recessions). These associations also are more pronounced for business recession periods and financial expansion periods. The findings suggest that firms headed by female CEOs are less risk seeking throughout cycle wavelets compared to firms headed by their male counterparts. However, firm risk is higher for firms headed by a female CEO that has obtained a postgraduate degree. The relation between firm risk and performance during changing macro events is less conclusive. These findings potentially provide important implications for understanding business cycles and financial cycles and their effects on the corporate sector in China.


identifier: Graja, Omar  (2020) spatial and temporal predictions for positive vectors.  Masters thesis, Concordia University.

abstract:
Predicting a given pixel from surrounding neighboring pixels is of great interest for several image processing tasks. To model images, many researchers use Gaussian distributions. However, some data are obviously non-Gaussian, such as the image clutter and texture. In such cases, predictors are hard to derive and to obtain. In this
thesis, we analytically derive a new non-linear predictor based on an inverted Dirichlet mixture. The non-linear combination of the neighbouring pixels and the combination of the mixture parameters demonstrate a good efficiency in predicting pixels. In order
to prove the efficacy of our predictor, we use two challenging tasks, which are; object detection and image restoration.
We also develop a pixel prediction framework based on a finite generalized inverted Dirichlet (GID) mixture model that has proven its efficiency in several machine learning applications. We propose a GID optimal predictor, and we learn its parameters using a likelihood-based approach combined with the Newton-Raphson method. We demonstrate the efficiency of our proposed approach through a challenging application, namely image inpainting, and we compare the experimental results with related-work methods.
Finally, we build a new time series state space model based on inverted Dirichlet distribution. We use the power steady modeling approach and we derive an analytical expression of the model latent variable using the maximum a posteriori technique.
We also approximate the predictive density using local variational inference, and we validate our model on the electricity consumption time series dataset of Germany. A comparison with the Generalized Dirichlet state space model is conducted, and the results demonstrate the merits of our approach in modeling continuous positive vectors.


identifier: Larue, Florent, Tasbih, Tasfia, Lavoie, Kim L., Ribeiro, Paula, Dolan, Emilie and Bacon, Simon L. ORCID: https://orcid.org/0000-0001-7075-0358 <https://orcid.org/0000-0001-7075-0358>  (2020) Physiological Effects of Electronic Cigarette: A Systematic Review and Meta-Analysis.  Masters thesis, Concordia University.

creator:
Larue, Florent
Tasbih, Tasfia
Lavoie, Kim L.
Ribeiro, Paula
Dolan, Emilie
Bacon, Simon L.

abstract:
Importance: Electronic cigarettes (e-cigs) are widely used devices that were initially created to aid in smoking cessation. However, their acute physiological effects are unclear and there have been a number of e-cig and vaping acute lung injury (EVALI) events recently reported.
Objective: To conduct a systematic review and meta-analysis of studies assessing the immediate physiological effects, i.e., cardiovascular, respiratory or blood-based responses, of acute e-cig usage in humans.
Data Sources: PubMed, Web of Science, Cochrane and Scopus databases were searched for published articles until 20th May 2020.
Study Selection: English or French peer-reviewed articles measuring at least one physiological parameter before and after using an e-cig.
Data extraction and synthesis: The study followed PRISMA guidelines and assessed article quality using the Downs and Black checklist. Independent extraction was conducted by two reviewers. Data were pooled using random effect models. Sensitivity analysis and meta-regression was performed to explore heterogeneity.
Main outcomes: Systolic and diastolic blood pressure, heart rate, augmentation index (AIx75), fraction of exhaled nitric oxide (FeNO), and spirometry were the most frequently assessed parameters and were, therefore, chosen for meta-analyses.
Results: Of 17102 articles screened, 37 articles were included for the qualitative synthesis, and 23 articles (800 patients) were included in the meta-analysis. Acute use of nicotine e-cig was associated with increased heart rate (SMD=0.51; 95%CI 0.34-0.68), systolic blood pressure (SMD=0.33; 95%CI 0.13 -0.52), diastolic blood pressure (SMD=0.50; 95%CI 0.26-0.73), and augmentation index AIx75 (SMD=0.580; 95%CI 0.220- 0.941), along with a decrease in FeNO (SMD=-0.327; 95%CI -0.599 – -0.055). E-cig exposure wasn't associated with significant changes in any spirometry measure.
Conclusions and Relevance: Acute use of nicotine e-cigs was associated with significant cardiovascular and respiratory responses. Despite being considered safe, these devices have a physiological impact that needs to be further explored especially in term of its long-term consequences.


identifier: Kumar, Pramod and Ganesan, Rajamohan  (2020) Dynamic Response of Doubly-Tapered Laminated Composite Beams under Periodic and Non-Periodic Loadings.  Masters thesis, Concordia University.

creator:
Kumar, Pramod
Ganesan, Rajamohan

abstract: Doubly-tapered laminated composite beams provide a great opportunity to enhance capabilities such as high strength-to-weight ratio, high modulus-to-weight ratio, and design flexibility. Due to design tailoring capabilities, the use of doubly-tapered composite beams has increased in the automobile industry and aerospace industry. In the present thesis, the free and forced vibration analyses of the width-and-thickness-tapered, called herein as doubly-tapered, laminated composite beams are conducted considering different boundary conditions, taper configurations, and loadings. The exact and closed-form solutions for the mode shapes and natural frequencies of doubly-tapered composite beams could not be acquired because of the complexity of the corresponding partial differential equations. Therefore, the classical laminate theory and the one-dimensional laminated beam theory in combination with the Ritz method are used in evaluating the stiffness and mass matrices of the composite beam. The natural frequencies and the corresponding mode shapes are determined by solving the eigenvalue problem obtained using the Ritz method. The forced vibration analysis of the doubly-tapered composite beams subjected to the transverse periodic and non-periodic loadings is carried out by representing the periodic loading as the superposition of the harmonic components of various frequencies using the Fourier series expansion and by expressing the non-periodic pulse excitation as the superposition of two or more simpler functions for which solutions are easier to determine. The maximum deflection of the doubly-tapered composite beam in spatial and time coordinates is determined. Numerical and symbolic computations have been performed using MATLAB® software. The solutions to the free and forced vibration analyses of the composite beams are compared, with the solution available in the literature and with the solution based on the Finite Element Method obtained using ANSYS®, to demonstrate solution accuracy. The Rayleigh damping is considered to model the viscous damping of the composite beam. A detailed parametric study is carried out to investigate the influences of the loading components in the Fourier series expansion, loading type, period of the periodic loading, the rise and fall times of the non-periodic loadings, taper angle, width ratio, thickness ratio, laminate length, stacking sequence, and taper configuration on the forced response of the doubly-tapered composite beam considering different boundary conditions.


identifier: Mohammadjavad, Arabpour Roghabadi ORCID: https://orcid.org/0000-0002-3924-8375 <https://orcid.org/0000-0002-3924-8375>  (2020) Risk-based Framework for Management of Construction Projects.  PhD thesis, Concordia University.

abstract: Well-developed risk management tools provide critical support for successful delivery of construction projects. Considerable research has been conducted towards integration of risk management in front-end planning and in execution phases of this class of projects. The accuracy of these tools relies heavily on their respective assumptions and on the data used in their application. Consideration of risk in these tools utilizes two types of data: actual past records and estimated future data related to completion of projects under consideration.  The literature reveals that most published work in this area utilized these data either in bidding phase or in one of individual project execution phases to minimize the negative impact of risk on project cost and duration at completion. However, there is a lack of a comprehensive framework that employs both types of data in different phases of construction projects. This prevents construction practitioners from implementing an efficient risk management program. In this research, a new risk-based framework is developed, addressing limitations of existing models for different management functions over project lifecycle. The developed framework employs past performance data of construction organizations and projects in the bidding phase for risk maturity evaluation, contingency estimation, markup estimation, planning and scheduling, and progress reporting. The framework has five developed models. The first introduces a decision support model for risk maturity evaluation of construction organizations to identify their strengths and weaknesses in risk management processes, employing the Analytic Network Process (ANP) and fuzzy set theory. It enables construction organizations to assess and continuously improve their risk management capabilities. The second model introduces a new cost contingency estimation model considering correlations among project cost items, subjectively and objectively. It is also capable of modeling project cost contingency with and without the use of Monte Carlo simulation, which is deemed particularly useful when using subjective correlations. The third model introduces new pattern recognition techniques for estimating project markup. It utilizes Multiple Regression (MR), Artificial Neural Network (ANN) and Adaptive Nero-Fuzzy Inference System (ANFIS) techniques for that purpose, considering five factors: need for work, job uncertainty, job complexity, market condition, and owner capability. The fourth model introduces a newly developed multi-objective optimization model for scheduling of repetitive projects under uncertainty. The model considers the estimated cost contingency and the project markup in the total project cost and conducts, simultaneously, trade-offs between project duration, project cost, crew work interruptions, and interruption costs. It safeguards against assignment of unnecessary costly resources and provides a reliable project baseline. The fifth model presents a newly developed risk-based earned duration management model (RBEDM) that utilizes the generated project baseline in forecasting project duration at completion, considering critical activities only and their associated risk factors. It introduces a new risk adjustment factor (RAFcr) that quantifies the impact of future uncertainties associated with critical activities in estimating project duration at completion. This unique aspect of the developed model addresses the main drawback of earned duration management (EDM) its reliance on past performance data only. It also assists project managers in estimating more accurate and realistic required time to project completion.


identifier: Azad, Mehdi  (2020) Autonomous and Connected Vehicles Canadian Market Comprehensive Readiness Assessment.  Masters thesis, Concordia University.

abstract:
The arrival of the automobile changed the shape of 20th-century cities around the world, now in 21st-century, autonomous vehicles (AVs) and connected vehicles (CVs) will change the shape and culture of the world’s cities once more. AVs and CVs are being deployed all around the world; the reason for this rapid development is that AVs and CVs enrich societies and industries with substantial benefits such as environmental effects, reducing Urbain’s noise and air pollution, safety, mobility for everyone, transportation as-a-service, smart transportation, etc. A market readiness assessment is a way to evaluate and identify that the market is prepared for launching technology and also whether the market will respond positively to that technology or not.
The objectives of this research are to enhance Canadian society and policymakers’ knowledge and understanding of AVs and CVs technologies and examine the maturity of the Canadian market for obtaining the most benefits from these technologies. The four main pillars include policy and legislation, technology and innovation, infrastructure, and customer acceptance. A readiness score model was provided to calculate the four main pillars readiness score regarding AVs and CVs technologies state in Canada.
The results of this study show that the Canadian government has not taken specific actions to enhance public awareness about AVs and CVs technologies, road quality and EVs charging stations should be considered the main challenges in the infrastructure pillar, the absence of OEMs headquarters, low investment of companies, and absence of R&D cores were obstacles and challenges for the technology and innovation sector regarding AVs and CVs technologies.

Keywords: Autonomous Vehicles, Connected Vehicles, Market readiness assessment.


identifier: Ghaderian, Niloufar  (2020) The association between amount and distribution of protein intake with body composition, resting energy expenditure, substrate oxidation, and muscle function in bariatric surgery candidates: a preliminary study.  Masters thesis, Concordia University.

abstract: Background: Obesity is associated with disrupted energy metabolism and skeletal muscle dysfunction. Dietary protein is important for the preservation of skeletal muscle mass and strength. Objectives: The objectives of this preliminary study were: 1) to assess the association of dietary protein intake with body composition, and muscle function; 2) to examine weather protein distribution pattern throughout the day are associated with body composition and substrate oxidation; and 3) to explore the association between body composition with substrate oxidation and energy expenditure in males and females with severe obesity. Methods: This cross-sectional study included 17 male and female bariatric surgery candidates. Dietary data, including protein intake was collected using a 3-day food journal and 24-hour food recall. Body composition was assessed using dual-energy X-ray absorptiometry. Substrate oxidation and resting energy expenditure were measured by indirect calorimetry. Muscle function was assessed by handgrip strength and 6-minute walk test. Results: Mean age and BMI were 43.9 ± 7.8 y and 46.9 ± 4.9 kg/m2, respectively. Daily protein distribution was uneven and had a skewness toward dinner. Males who ate ≥ 20 g protein at each meal had greater ALM in comparison to those who did not (38.0 ± 0.9 vs 35.2 ± 0.7, P = 0.03). ALM was an independent predictor of REE and fat oxidation rate. Females had altered substrate metabolism and decreased rates of fat oxidation. Conclusion: This study provided preliminary results that will help improve study design and considerations in the continued recruitment of participants.


identifier: Sarafrazi, Mehrdad  (2020) Fracture Mechanics Fatigue Life Assessment of Welded Joints Under Ultrasonic Impact Treatment.  Masters thesis, Concordia University.

abstract:
Welding joints are the most used joining method to fabricate engineering structures due to their low cost, structural strength, and geometric flexibility. Irregular geometries, micro cracks, defects, high stress concentration and tensile residual stresses are some of the results of a highly metallurgical process considered as welding. Thus, an important subject of growing concern in product design is to consider some of the critical factors caused from the weld process including high tensile residual stresses and stress concentrations to properly evaluate the fatigue life of the structures. Lightweight design of welded steel and aluminum structures in cyclic service requires the use of post-treatment approaches like Ultrasonic Impact Treatment (UIT). In this thesis, an evaluation of fatigue tests carried out recently on welded specimens exposed to UIT under the effect of the constant amplitude (CA) loading on the fatigue strength is described.
First, the effects of the various fatigue damage parameters on the as-welded (AW) condition and the impact treated welds are described in the literature review. Furthermore, fatigue test data have been taken from literature for both conditions under CA loading for several different stress ranges for each material. Following the tests, residual stress distributions below the weld toe surface have been specified by x-ray diffraction of untested specimens. More importantly, the test data obtained from the literature were analyzed through out the thesis and were used to define input parameter values for fracture mechanics analyses of the welded joint specimens. After that, the crack growth assessment of welded structures is provided. For comparison purposes, both Walker and Forman fatigue crack growth models are thoroughly reviewed and their advantages as invaluable tools for predicting the effects of UIT on fatigue performance for welded joints are examined. Subsequently, the benefit of the models in predicting fatigue crack growth behaviors for nine distinct materials are examined and the effects of the various material strength parameters on the impact treatment performance are assessed. Then, fatigue crack propagation life of the materials is displayed. In the end, the crack shape evolution of the materials is depicted. In conclusion, the outcomes of this investigation accompanied by proposed future work are mentioned.


identifier: Atashi, Mohammadamin ORCID: https://orcid.org/0000-0002-0041-4823 <https://orcid.org/0000-0002-0041-4823>  (2020) Multiple Model-based Indoor Localization via Bluetooth Low Energy and Inertial Measurement Unit Sensors.  Masters thesis, Concordia University.

abstract: Ubiquitous presence of smart connected devices coupled with evolution of Artificial Intelligence (AI) within the field of Internet of Things (IoT) have resulted in emergence of innovative ambience awareness concepts such as smart homes and smart cities. In particular, IoT-based indoor localization has gained significant popularity, given the expected widespread implementation of 5G network, to satisfy the ever increasing requirements of Location-based Services (LBS) and Proximity Based Services (PBS). LBSs and PBSs have found several applications under different circumstances such as localization profiling for human resource management; navigation assistant applications in smart buildings/hospitals, and; proximity based advertisement and marketing. The focus of this thesis is, therefore, on design and implementation of efficient and accurate indoor localization processing and learning techniques. In particular, the thesis focuses on the following three positioning frameworks: (i) \textit{Bluetooth Low Energy (BLE)-based Indoor Localization}, which uses the pathloss model to estimate the user's location; (ii) \textit{Inertial Measurement Unit (IMU)-based Indoor Positioning}, where smart phone's $3$ axis inertial sensors are utilized to iteratively estimate the headings and steps of the target, and; (iii) \textit{Pattern Recognition-based Indoor Localization}, which uses Deep Neural Networks (DNNs) to estimate the performed actions and  find the user's location. With regards to Item (i), the thesis evaluates effects of the orientation of target's phone, Line of Sight (LOS) / Non Line of Sight (NLOS) signal propagation, and presence of obstacles in the environment on the BLE-based distance estimates. Additionally, a fusion framework, combining Particle Filtering with K-Nearest Neighbors (K-NN) algorithm, is proposed and evaluated based on real datasets collected through an implemented LBS platform. With regards to Item (ii), an orientation detection and multiple-modeling framework is proposed to refine Received Signal Strength Indicator (RSSI) fluctuations by compensating negative orientation effects. The proposed data-driven and orientation-free modeling framework provides improved localization results. With regards to Item (iii), the focus is on classifying actions performed by a user using Long Short Term Memory (LSTM) architectures. To address issues related to cumulative error of Pedestrian Dead Reckoning (PDR) solutions, three Online Dynamic Window (ODW) assisted  LSTM  positioning frameworks are proposed. The first model, uses a Natural Language Processing (NLP)-inspired Dynamic Window (DW) approach, which significantly reduces the computation time required for Real Time Localization Systems (RTLS). The second framework is developed based on a Signal Processing Dynamic Window (SP-DW) approach to further reduce the required processing time of the two stage LSTM based indoor localization. The third model, referred to as the SP-NLP, combines the first two models to further improve the overall achieved accuracy.


identifier: Shine, Laura ORCID: https://orcid.org/0000-0001-6033-4246 <https://orcid.org/0000-0001-6033-4246>  (2020) From Foe to Food: Entomophagy and the adoption of edible insects.  PhD thesis, Concordia University.

abstract:
By 2050, the planet’s population could reach 10 billion. To address potential food insecurity, entomophagy – eating insects – has been promoted as a promising alternative to livestock rearing. In many cultures of the world, small invertebrates are already an important part of the human diet. European, Canadian and American populations, however, generally express an extremely strong negative reaction to the idea of eating insects.

To overcome this, advocates have developed a rational-based argumentation hinging on insects’ purported sustainability, nutritional profile, or potential role in assuring food security. Such approaches have achieved fairly limited success among the general public. Consequently, some proponents now focus chiefly on sensory appreciation to increase insects’ appeal. Problematically, both strategies overlook the diversity of social and environmental pressures that contribute to driving food choice.

Using an interdisciplinary developmentalist theoretical framework that incorporates conceptual and methodological tools from Food Anthropology, Food Marketing, and Sensory Studies, I map out the emergent industry in Québec and analyze the different strategies mobilized to mitigate avoidance behaviour. Based on participant observation and interviews with producers, promoters, researchers and consumers, I investigate how culturally-constructed negative reactions to unusual foods can evolve and adapt. I first examine some of the cultural tropes that portray insects as dangerous, dirty and disgusting, and how this correlates with notions of risk in food consumption, disgust, and the perceived “alien-ness” of insects. I then critique some of the prevailing discourses around edible insect promotion, both from rational- and sensory-based perspectives, showing how both coalesce around the concept of acceptability. Finally, I analyze some of the current directions within the Québec edible insect industry and examine some of the prevalent challenges and opportunities within the field, before providing implementable takeaways for firms. I ensconce these localized findings within the larger cultural context of the development of entomophagy among European-derived populations with little or no recent history of consumption, shedding light on wider dynamics of food acceptance and reject, on matters of acceptability, and on the general mechanisms that allow these to evolve and adapt over time.


identifier: Al Hajj, Raghid  (2020) Breaking Down or Breaking Through: The Role of Appraisals in the Challenge-Hindrance Stressors’ Effect on Work Engagement and Performance.  PhD thesis, Concordia University.

abstract: This thesis investigates the effects of work-related stressors on in-role performance and work engagement. First, it explores whether stressors that have long been categorized as challenging or hindering are appraised commensurately as challenging and hindering, respectively, or whether they are appraised as both challenging and hindering simultaneously. Second, it attempts to better explain the contradictory findings surrounding the relationships between stress and in-role performance and work engagement by including stress appraisals as a mechanism driving these relationships. Finally, this thesis also looks at whether one’s beliefs about the debilitating and enhancing characteristics of stress could help to explain not only how stressors are appraised, but also how appraisals eventually influence performance and engagement. On five consecutive work days, 487 Canadian and American full-time employees were asked to report on their stress mindset and to appraise a set of eight stressors destined to capture a wide array of challenging and hindering work stressors, after which they then evaluated their performance and engagement at work. Results showed that employees rarely appraised stress as uniquely challenging or hindering and, in fact, most stressors were appraised as being both at the same time. In addition, challenge and hindrance stressors were evaluated as being less hindering and hindrance stressors were evaluated as being more challenging when employees had increasingly positive views about stress. Stress mindset was thus shown to be an important boundary condition that appears to modulate the genesis of stress appraisals. In addition, including stress appraisals was shown to be beneficial in explaining the stressors’ relationship to performance and engagement, with challenge and hindrance stressors boosting and hampering these outcomes, respectively. Although stress mindset was less effective in explaining the appraisal-to-outcome links, it nevertheless played a buffering role by reducing the negative influence of hindrance appraisals on work engagement. This research is important in clarifying some misconceptions about how workplace stressors are evaluated and in providing novel evidence that stress mindset is a key variable in the study of stress at work, in general, and that of stress appraisals, in particular.


identifier: Huang, Yusheng  (2020) Providing Proximity Safety and Speeding Alerts to Workers on Construction Sites Using Bluetooth Low Energy RTLS.  Masters thesis, Concordia University.

abstract: The construction sector is one of the most dangerous industrial sectors. Struck-by object or equipment is one of the main causes of fatal accidents on construction sites. Although many regulations have been designed for struck-by accidents, these accidents are still causing many injuries and fatalities.  According to the U.S. Bureau of Labor Statistic, the struck-by accidents has led to 112 deaths on construction site in 2018. The application of real-time location systems (RTLS) on construction sites provides new possibilities in construction safety management.  Previous researchers have proposed using RTLS to track the location of workers and equipment on construction sites to improve construction safety. However, the previous methods have some limitations (e.g. cabling problems, positioning quality). Furthermore, providing effective safety alerts to workers within dangerous proximity to equipment has not been addressed in previous research. This research aims to develop a method for providing near real-time proximity alerts to workers on construction sites using Bluetooth Low Energy (BLE) RTLS based on angle of arrival (AOA).  This RTLS can provide acceptable accuracy coupled with large coverage without the need of timing cables. Also, with the support of two-way communications between the tags and sensors, it is possible to provide vibro-tactile alerts to the workers using wristbands. In addition, alerts representing different cases of proximities and speeding were defined. The prototype system has the following features: (1) less cabling by using wireless technologies for data transmission, (2) less false alerts by generating the alerts to specific entities based on the micro-schedule of activities, (3) easily perceived alerts. Tests were conducted on a construction site of an electric substation to test the accuracy of the RTLS and the performance of the prototype system. The test results indicated that the prototype system is capable of detecting proximities and generating timely alerts to the involved entities.


identifier: Gu, FangFang  (2020) Modeling and Simulation of Mudflows Impacting Railway Infrastructure Using Smoothed Particle Hydrodynamics.  Masters thesis, Concordia University.

abstract:
In the Canadian context, it is common that railway tracks transverse a mountainous area prone to natural disaster like mudflows. In the geographical areas where Champlain clays of the Ottawa Valley and St. Lawrence Lowlands in Canada are prone to mudflows, which results in further safety implications when a freight train is passing through this area, further threatening human lives in addition to public properties. Therefore, the investigation of the interaction of flow with trains, the parameters affecting mudflows’ destructive force and the train derailment potential is important to determine the amount of potential damage.
The aim of this research was to study the feasibility of modeling mudflows utilizing the smoothed particle hydrodynamics method based on the available data in the literature and model the scenario of mudflows impacting railway cars on top of a railway embankment and quantitatively investigate the interaction of mudflow with trains. The parametric studies were performed including the identification of key factors, such as geometric characteristics of the natural hillslope and the railway embankment, mudflows’ properties and freight train loading. To calibrate the simulation tool for reproducing the mudflow flowing on hillslope as in the real-world, a series of flume tests were modeled based on the physical large-scale experiment carried out by Bugnion et al. (2010), paved the way for implementation of the case studies' environment and properties of mudflow in the simulation tool in order to be modeled. The control variable method was introduced in numerical model studies to individually study each parameter and its effect on the impact force exerted by mudflows on railway cars. As a contribution, this study provides the information of critical case resulting train derailment with geometric terrain parameters and mudflows' quantities, which could be used as a reference for guidelines used in railway industry.


identifier: Iravani, Rezvan  (2020) Experimental and Modeling Studies of the Effects of Nanoclay on the Oil Behaviors in A Water-Sand System.  Masters thesis, Concordia University.

abstract: When oil is spilled into the marine environment, a certain amount of spilled oil may finally reach the shoreline. This study comprehensively explored the effects of bentonite nanoclay on the oil behaviours in water-sand media from both experimental and modeling perspectives. Four factors including nanoclay  concentration, temperature, salinity and pH have been studied. The increasing nanoclay concentration resulted in the decrease in remaining oil on sand. Higher temperature and salinity were associated with less residual oil on sand in the presence of nanoclay. The lower residudual oil on sand with coexisitng nanoclay was found to be at pH 7. The factorial analysis results indicated that the nanoclay concentration showed the most significant impact among these factors. Miscibility modeling resutls showed an increasing temperature was favorable to the nanoclay miscibility. Moreover, the effect of nanoclay on oil behaviro was further revealed through the dynamic simulation, in which it can be seen the nanoclay could penetrate into oil droplets and promote the detachment of oil from the solid substrate. The results of this study can help understand the role of fine particles in the fate and transport of oil on shoreline, and support the risk assessment and response planning after oil spill.


identifier: baadi, ashkan  (2020) Laser Remelting of Yttria Stabilized Zirconia Coatings Deposited by Suspension Plasma Spraying.  Masters thesis, Concordia University.

abstract:
ABSTRACT
Laser Remelting of Yttria Stabilized Zirconia Coatings Deposited by
Suspension Plasma Spraying
ASHKAN BAADI
CONCORDIA UNIVERSITY, 2020
Thermal barrier coatings (TBCs) are applied as a protective layer in a range of applications,
mainly in the aero-engine and power generation industries to protect the metallic parts from high
operating temperatures, especially in gas turbine-engines. One way to improve the efficiency of
the engines is to increase the combustion temperature; in order to reduce potential damage to the
metallic parts, TBCs are commonly applied to these components. The TBC comprises a bond coat
and a top coat. Since Yttria Stabilize Zirconia (YSZ) has the best combination of properties among
the various options, this material is most commonly used as the top coat on commercial TBCs.
The top coat in TBCs can be applied by different methods, including Electron Beam -
Physical Vapour Deposition (EB-PVD), Atmospheric Plasma Spraying (APS) and the recently
developed Suspension Plasma Spraying (SPS) which is one of the newest methods in applying top
coat layers. SPS has the potential to generate columnar microstructures with a beneficial range of
porosity: these columns reduce thermal stresses in the TBCs and at the same time provide an
acceptable range of porosity which reduces the thermal conductivity of the coated layers. The
columnar structure of this type of coating, despite having a potential to increase the life cycle of
the top coat in terms of thermal stresses, can be a way of penetration for calcium–magnesium–
aluminosilicates (CMAS) into the TBC structure, which will result in deterioration of the TBC.IV
In this thesis, the formation of a variety of top coats using Suspension Plasma Spraying SPS
method is used in order to obtain the desired columnar microstructure. Subsequently, these layers
are laser treated to study the possibility of creating a remelted layer across the TBC surface which
should reduce the CMAS penetration. In this regard, advantages and disadvantages of the major
laser parameters such as scanning speed, output power, power density and energy density were
observed. Based on the experimental tests on columnar structures, it was found that increasing
scanning speed and power does not have a linear relation and that increasing the laser travel speed
above 2 m/min will cause nonuniform melting and create different phases on the surface of the
substrate. At the same time, decreasing power below a certain amount will not cause significant
changes to the substrate. A specific range of energy and power density need to be considered in
order to obtain a uniform melted layer over the substrate.


identifier: Tessier, Jeremy  (2020) Contextualizing Food Systems Planning in Ciudad Juárez, Mexico: Prospects for Alternative and Transborder Coordination.  Masters thesis, Concordia University.

abstract: The Paso Del Norte transborder region is home to one of the world’s largest manufacturing complexes.  Along with industrial and trade policies, agricultural and food policies have shaped economic and demographic shifts in Mexico. The policies that have created conditions favourable for the emergence of this industrial hub have also created negative effects on both sides of the US/Mexico border, markedly in Ciudad Juarez. The focus of this thesis is a historical analysis of agricultural/food systems policy in Mexico to provide in-depth context, followed by an analysis of the performance of various alternative food system planning initiatives in Juárez. Food Regime theory is deployed to describe the state’s historical relationship with food system actors. Narrowing the scope from the national to the regional level, the analysis shifts to assessment of projects by stakeholders seeking to develop alternative food system initiatives. The primary objective is to gain insight as to what types of supports may be beneficial to the continued development and expansion of alternative initiatives in the context of a field of practice that is heavily intermediated by a range of other interests. Potential for collaborations between actors in other jurisdictions in the Paso Del Norte is also considered.


identifier: Haratiannejadi, Kianoush ORCID: https://orcid.org/0000-0001-9925-7890 <https://orcid.org/0000-0001-9925-7890>  (2020) Smart Glove and Hand Gesture-Based Control Interface for Multi-Rotor Aerial Vehicles.  Masters thesis, Concordia University.

abstract:
This thesis introduces two types of adaptable human–computer interaction methods in single-subject and multi-subject unsupervised environments.

In a single-subject environment, a single shot multi-box detector (SSD) is used to detect the hand's regions of interest (RoI) in the input frame.
The RoI detected by the SSD model is fed to a convolutional neural network (CNN) to classify the right-hand gesture.
In a crowded environment, a region-based convolutional neural network (R-CNN) detects subjects in the frame and the RoI of their faces. These regions of interest are then fed to a facial recognition module to find the main subject in the frame.
After the main subject is found, the R-CNN model feeds the right-hand RoI of the main subject to the CNN to classify the right-hand gesture.
In both single-subject and multi-subject environments, a fixed number of gestures is used to describe specific commands from the right-hand gestures to the vehicle (take off, land, hover, etc.).

A smart glove on the left hand is used for more precise vehicular control.
A motion-processing unit (MPU) and a set of four flex sensors are used in the smart glove to produce discrete and continuous signals based on the bending value of each finger and the roll angle of the left hand.
The generated discrete signals with the flex sensors are fed to a support vector machine (SVM) to classify the left-hand gesture, and the generated continuous signals with the flex sensors and the MPU module are used to determine some characteristics of the gesture command such as throttle and angle of the vehicle.

Three simultaneous validation layers have been implemented, including (1) Human-Based Validation, where the main subject can reject the robot’s behavior by sending a command through the smart glove, (2) Classification Validation, where the main subject can retrain the classifier classes at will, and (3) System Validation, which is responsible for finding the error's source when the main subject performs a specific command through the smart glove.

The proposed algorithm is applied to groups consisting of one, two, three, and four subjects including the main subject to validate and investigate the behavior of the algorithm in various desirable and undesirable situations.
The proposed algorithm is implemented on an Nvidia Jetson AGX Xavier GPU.


identifier: Alaghbandrad, Ali  (2020) Economic Analysis and Information Modeling of Smart Multi-purpose Utility Tunnels.  PhD thesis, Concordia University.

abstract:
The traditional method of buried utilities (i.e. water, sewer and gas pipes, and electrical and telecommunication cables) has been used for many decades particularly in urban areas. Repeated excavations are needed to access these underground utilities for maintenance, repair, and renewal activities. Urban areas have been experiencing many street closures and traffic disruptions because of excavation for maintaining underground utilities. These construction works have imposed major costs on public and private utility companies as well as on citizens and local businesses (social cost). Multi-purpose Utility Tunnels (MUTs) have been built since the 19th century as a solution and alternative way that not only avoids these excavations but also facilitates inspection and protects utilities. However, MUTs are not widely used in most of the countries because of the high initial investment, safety and security issues, complicated design and construction, and complex coordination of utility companies. Despite the higher design and construction cost of MUTs, operational cost-savings can justify the investment from the project point of view. From the organization's point of view and based on cost-sharing, MUT should be more economical as well and the MUT benefits should be distributed fairly to convince utility companies to participate in the MUT project. Lifecycle Cost (LCC) analysis of the MUT and the buried utilities method is complicated because of various factors that influence the LCC. Also, there is a gap in defining the concept of fairness and applying mathematical methods for a fair cost-sharing. On the other hand, to facilitate the complicated design and construction, and complex coordination of utility companies in MUT projects, Building Information Modeling (BIM) tools are very helpful. However, BIM is mainly developed for buildings and there are efforts to extend it to civil structures (e.g. bridges, tunnels). Although using BIM for MUTs has progressed in recent years, there is still lack of a comprehensive framework covering MUT components and information requirements for all use cases, as well as its integration with Geographic Information System (GIS) and other technologies.
This research aims to: (1) improve the decision-making related to MUT selection process by developing a comprehensive and systematic approach for MUT and buried utilities LCC analysis. In addition, this research investigates the influence of factors of utility specifications, location conditions, and construction methods. The output of this model determines the LCC of MUT and buried utilities, and the design and construction cost of MUT at the breakeven point to ensure the project decision-makers that MUT is the economic method; (2) improve the fairness of MUT cost-sharing by developing a fair model that considers fairness based on (a) balance of risk, (b) balance of benefit and cost, and (c) balance of contributed benefit and gained benefit. This model makes MUT the economical method for utility companies and distributes the benefits and costs of MUT fairly among the utility companies; and (3) improve the coordination among the MUT stakeholders by developing a framework integrating BIM and 3D GIS for Smart Multi-purpose Utility Tunnel Information Modeling (SMUTIM). The framework defines MUT information requirements, identifies SMUTIM use cases, and extends Industry Foundation Classes (IFC) to MUT.
The contributions of this research are: (1) developing a comprehensive and systematic approach for MUT and buried utilities LCC analysis by considering the factors of utility specifications, location conditions, and construction/maintenance methods. The output of this model estimates the LCC of MUT and buried utilities. The proposed model can justify whether an MUT project is an economic alternative method for buried utilities; (2) developing an MUT cost-sharing method to ensure the decision-makers of utility companies that MUT is the economic method for their company and also the benefits and costs of MUT are distributed fairly among the utility companies. The fairness is defined based on three principals: balance of risk, balanced benefit-cost ratio, and balance in contributed benefit and gained benefit; (3) categorizing and integrating smart MUT physical and functional components and their relationships in a systematic way; (4) completing, integrating, and organizing the available knowledge about SMUTIM use cases within a framework. Then, using the case study to show the capabilities and gaps of current BIM applications, GIS, databases, and facility management tools for MUT lifecycle management; and (5) partially extending IFC to MUT by proposing Model View Definition (MVD), new entities and relationships, and taking advantage of reusable IFC entities, properties, and relationships.
It is expected that the proposed model promotes using MUT by (1) facilitating economic analysis and cost-sharing for MUT projects from project and organization points of view; and (2) facilitating the design, construction, and operation of MUTs, and the coordination of utility companies.


identifier: Tremblay, Andrée  (2020) mind.heart.mouth Care and Community through Collective Gardening.  Masters thesis, concordia university.

abstract: Over two years, from 2018 to 2020, I ran a sequence of workshops and initiated a collective garden on the Loyola campus of Concordia University in Montréal. Using research-creation, in the form of a garden, I explored how embodied knowledge can inform experiential learning, care, and sensory experiences. This garden was a site of intergenerational knowledge exchange involving seniors and students. This thesis addresses the interconnected areas of environmental education, embodied cultural experience, and food security. The central claim of this work is that gardening pedagogy providing sensory experiences, hands-on practices, and related prompts can stir reflections, challenge individual and cultural assumptions, and provide a space to foster and transform our sense of care and community. Furthermore, this project contributes to the field of environmental communication by moving away from traditional visual media to consider natural elements, such as dirt, seeds, seedlings, and vermicompost as devices of mediation that call upon all the senses to promote conscious engagement. It is also a small but creative intervention in the field of food security by offering a model of a university garden and companion workshop series that foster skills and build awareness.


identifier: Larios, Lindsay Gayle ORCID: https://orcid.org/0000-0002-8756-8453 <https://orcid.org/0000-0002-8756-8453>  (2020) Pregnant and Precarious: Canadian Immigration through the Lens of Reproductive Justice.  PhD thesis, Concordia University.

abstract:
In a context where migration has become a contentious global and national issue, and maternal health and reproductive rights continue to be leading priorities for the Canadian state, there is a disconnect between the ideals of Canadian exceptionalism and the discourses and policies surrounding reproductive rights for non-citizens. While legal rights protections for non-citizens have generally been expansive in many liberal democratic states, the politics governing reproductive rights, however, present a unique tension. In countries like Canada with jus soli citizenship, supporting a non-citizen who is giving birth is not simply about providing services, it’s also about formal membership. Given this, the reproductive rights of migrants are positioned against national sovereignty. A fuller account of reproductive citizenship as it intersects with immigration status is needed. In particular, there is a need for analysis that resists this positioning and takes seriously the realization of sexual and reproductive autonomy as a global human right.

Using reproductive justice as an analytic lens, this dissertation contributes to our empirical and theoretical knowledge of how reproductive citizenship is experienced by pregnant people with precarious immigration status. Drawing on 24 narrative interviews with temporary status and non-status women living in Montreal, Canada, 13 key informant interviews with service providers, and a review of relevant policies, this dissertation situates the lived experiences of pregnant precarious status migrants within Canadian immigration and reproductive politics. This analysis reveals how neoliberal notions of choice and the racialized and gendered practices of nation-building intersect in the lives of migrant pregnant people and argues that immigration status is barrier to reproductive justice. In particular, narrative interviews showed how immigration and reproduction strategies are often co-produced; however, who can access these strategies and how they are received when they do is shaped by nationality and highly racialized. Precarious immigration programs are not amenable to the needs of pregnant people, such that migration management on the part of the state is experienced as reproductive management in the lives of precarious status migrants. Specifically, they face challenges maintaining their status and accessing basic public services and protections as they navigate pregnancy, childbirth, and motherhood.


identifier: Katal, Ali ORCID: https://orcid.org/0000-0002-7893-8053 <https://orcid.org/0000-0002-7893-8053>  (2020) Development of Multi-Scale City Building Energy Model for Urban Climate Resilience.  PhD thesis, Concordia university.

abstract:
In the past decades, the world has experienced rapid urbanization that caused increasing climate change challenges, pollution, energy consumption, and greenhouse gas (GHG) emission. More frequent and more prolonged extreme weather events such as heatwave and cold-wave and urban heat island phenomena are some negative impacts of climate change. The building sector is an essential source of urban energy consumption, GHG emission, and Urban Heat Island (UHI) formation. Different energy efficiency measures can be implemented to reduce building energy consumption, such as retrofitting existing building stock and deploying new technologies. These scenarios will also contribute to the mitigation of UHI, heatwaves, and climate change. Urban building energy models are simulation tools developed to study these kinds of problems. There are several challenges with existing Urban Building Energy Modelling (UBEM) tools, including creating a 3D model of buildings, estimating buildings’ properties, and using urban microclimate data for simulation.
On the other hand, accurate building energy simulation and fluxes from buildings to the atmosphere can impact forecasting accuracy by numerical weather prediction tools. Therefore, developing a multi-scale integrated urban building energy and climate simulation tool is essential for modeling both buildings’ energy performance and atmospheric fields. In this work, a new urban building energy model called City Building Energy Model (CityBEM) is developed to solve UBEMs' current challenges. First, a building-scale energy and airflow simulation model is developed for modeling a single building. It is based on a coupled thermal/airflow multi-zone network model. The multi-zone network model is then modified for calculation of urban scale buildings’ energy performance. A new method is developed to create the 3D model of buildings by integrating buildings’ footprint data obtained from OpenStreetMap and Microsoft and building height information by Google Earth Application Programming Interface (API). An archetype library is developed for the estimation of buildings’ non-geometrical properties. Buildings are classified based on usage type and age obtained from city shapefile datasets. The geometrical and non-geometrical datasets are joined using the QGIS tool and Mapbox platform.
To use local microclimate data for buildings’ energy performance, CityBEM is integrated with different microclimate simulation tools. First, CityBEM is fully integrated with the CityFFD tool to model the two-way interaction between buildings and microclimate. In the second method, a multi-scale urban climate and buildings energy simulation tool is developed by one-way integration of CityBEM with 3D Global Environmental Multiscale Model (GEM) and Surface Prediction System (SPS) developed by Environment and Climate Change Canada (ECCC). The one-way multi-scale model cannot capture the impact of CityBEM on the atmospheric fields; therefore, to model this impact, the CityBEM is added as a new module to the SPS model. SPS includes a Town Energy Balance (TEB) scheme for modeling the urban surface. In this thesis, CityBEM is added to the TEB for modeling the buildings. Using the developed TEB-CityBEM model in GEM simulations, near-surface forecasting accuracy can be improved, and buildings’ energy simulation is added as a new feature to the GEM model. The multi-scale model can be used to study different mitigation strategies such as retrofitting existing buildings, modeling natural ventilation and its impact on reducing energy consumption, model new technologies to reduce energy consumption, etc. The TEB-CityBEM model can also be added to the air quality model of ECCC called GEM-MACH to study the impact of urban building modeling on air quality in urban areas.
Finally, due to the importance of aerosol transmission of covid-19 in indoor spaces, it is essential to develop a model to study the impact of different mitigation strategies on reducing the risk of infection in the rooms and their corresponding energy consumption effects. In this thesis, a city-scale model (CityRPI) is developed to estimate airborne transmission of COVID-19 in indoor spaces. The CityRPI model is integrated with the CityBEM. The integrated model is applied to Montreal, and the impact of mitigation strategies on the infection risk and energy consumption is studied for different types of buildings.