title: Profile extrusion of wood plastic cellular composites and formulation evaluation using compression molding

subject:
WPC
Profile extrusion
Foaming
Compression molding

abstract:
Wood Plastic Composites (WPCs) have experienced a healthy growth during the last decade. However, improvement in properties is necessary to increase their utility for structural applications. The toughness of WPCs can be improved by creating a fine cellular structure while reducing the density. Extrusion processing is one of the most economical methods for profile formation. For our study, rectangular profiles were extruded using a twin-screw extrusion system with different grades of HDPE and with varying wood fibre and lubricant contents together with maleated polyethylene (MAPE) coupling agent to investigate their effects on WPC processing and mechanical properties. Work has been done to redesign the extrusion system setup to achieve smoother and stronger profiles. A guiding shaper, submerged in the water, has been designed to guide the material directly through water immediately after exiting the die; instead of passing it through a water cooled vacuum calibrator and then through water. In this way a skin was formed quickly that facilitated the production of smoother profiles. Later on chemical blowing agent (CBA) was used to generate cellular structure in the profile by the same extrusion system. CBA contents die temperatures, drawdown ratios (DDR) and wood fibre contents (WF) were varied for optimization of mechanical properties and morphology. Cell morphology and fibre alignment was characterized by a scanning electron microscope (SEM).
A new compression molding system was developed to help in quick evaluation of different material formulations. This system forces the materials to flow in one direction to achieve higher net alignment of fibres during sample preparation, which is the case during profile extrusion. Operation parameters were optimized and improvements in WPC properties were observed compared to samples prepared by conventional hot press and profile extrusion.


title: Modeling, design, control and validation of a multiple-input DC-DC converter topology for effective renewable energy management

contributor:
Williamson, Sheldon S.
Sood, Vijay

subject:
DC-DC converter
Multi-input single-output
Renewable energy management
Multiple-input converters
Renewable energy applications

abstract: Multiple-input power converters are receiving significant research attention as they offer several advantages over conventional converters, specifically their ability to interface multiple energy sources of various kinds. Additionally, they have promising features such as less components, higher power density and centralized control. A novel multiple-input single-output DC-DC converter topology is proposed for effective energy management. The topology is designed depending on the conventional structure of boost and buck converters and benefits greatly from this combination. Effective energy management strategy is used and a simple control system is introduced by utilizing voltage and current control. The converter is simulated and implemented in hardware testing as a 300W system to confirm the performance and validation of the topology and it is capable of supplying constant output power through different input sources with any voltage variation. The results show a high performance and all of the operating modes have been investigated.

abstract: University of Ontario Institute of Technology


title: Analysis and feasibility of an evaporative cooling system with sessile droplet evaporation to provide cooling for microprocessors

contributor:
MacDonald, Brendan D.
Rosen, Marc A.

subject:
Evaporative cooling
Sessile droplets
Microprocessors
Evaporation
Thermal management

abstract: The study investigates the cooling requirements for the Intel Xenon Processor and the Intel Core i7-900 Processor using diffusion based evaporation of sessile droplets. An analytical model is developed to determine the capacity of a single layer of droplets to provide sufficient cooling. It is found that a single layer can provide sufficient cooling for the processors with tiny droplets. A numerical model is developed to analyze a tiered system that fits within the space restrictions corresponding to the current heat sinks with larger droplets and fewer of them. The results of the numerical modelling work found that a minimum of 41 posts connecting each of the tiers were required to cool the Xenon Processor and 42 posts for the Core i7-900 Processor. It was also found that a minimum of 3 tiers were required for the Xenon Processor, with a droplet radius of 2 mm, and 4 tiers for the Core i7.


title: Endothelial cell response to bioactive peptides and stiffened extracellular matrices:  an investigation into atherogenic pathways

subject:
Endothelial cell
Atherosclerosis
Bioactive peptides
Stiffened matrices
Immunomodulatory

abstract:
Endothelial dysfunction is the initiating step in atherosclerosis and leads to cardiovascular disease outcomes. This dysfunction can be mitigated by cardioprotective signaling molecules such as nitric oxide (NO) which can be upregulated in the presence of bioactive milk peptides. An investigation into the NO liberating capacity of select bioactive peptides was performed on cultures of Human Umbilical Vein Endothelial Cells (HUVECs) and two tripeptides (VPP and IPP) were found to liberate ~50% more NO. This finding drove a further investigation into whether endothelial cells grown on varying matrix stiffness would experience mechanical forces resulting in cellular responses more indicative of in vivo conditions.
Polyacrylamide (PAC) gels of varying stiffness (2.5, 3, 10 and 30kPa) were prepared, and cell growth characteristics and inflammatory responses were measured over a nine day period. Findings showed that stiffer gels (10 and 30kPa) supported the growth of significantly higher numbers of HUVECs with smaller cell areas; however, gel stiffness did not induce a pro-inflammatory response in this cell line. Therefore, these results support PAC gels as useful in simulating a biologically relevant environment for the purposes of endothelial dysfunction investigations.


title: The meaning of murder: newspaper framing of hate crimes against lesbians.

subject:
Media
Hate crimes
Heterosexism
Framing
Lesbians

abstract: The overall purpose of this study is to assess the representations of lesbians within United States news print media to examine the effect these representations can have on societal level ideologies. Using two separate incidents of hate crimes resulting in death, this study looks at newspaper articles from two distinct locations (North Carolina and Florida). The 1990 murder of Talana Quay Kreeger and the 2010 murder of Courtney Elizabeth Bright are analyzed in order to illustrate the divergence between these crimes based on location and time. Although lesbians have been identified in both government statistics and previous research as being less likely to experience hate crimes than gay men (Jacobs & Henry, 1996; Stotzer, 2012), the news media depictions of these crimes may give insights into the under-representation of lesbians. Findings from this study suggest that hate crimes against lesbians in newspaper reports are more likely to discuss the victim’s sex instead of their sexuality, causing the lesbian as a victim to become invisible. In other words, by failing to properly depict the victim’s sexuality as being a factor in the crime, the rates of hate crimes against lesbians are less likely to be acknowledged by wider society. Results of this study therefore contradict findings presented within official government hate crime statistics, suggesting that current methods of collecting data may be unable to properly account for lesbian victimization due to the dual identities they hold.


title: Design considerations for fixed node assisted multi-hop mobile sensor networks

contributor:
Heydari, Shahram
Liscano, Ramiro

subject:
Mobility
FNA-CTP
Performance analysis

abstract: Node mobility in Wireless Sensor Network poses a challenge to the routing protocol; it causes link breakages and disconnections between the nodes. This instability in the network leads to a drop in the successful transmission of data packets to the main station. In order to understand the key factors in the performance degradation in a mobile network and address them, a simulation based performance sensitivity analysis was done on a Collection Tree Protocol based network. First, the main reasons for packet drops in mobile networks were investigated. Then, the effect of the network size, node density and node speed is studied in more detail in a mixed mobile-static sensor network, as well as the effect of the number and transmission range of the static nodes in the network. Based on the performance sensitivity analysis, a set of criteria and network requirements is proposed, which can be used as network design suggestions for a mixed mobile-static sensor network to enhance the network’s performance.


title: Perpetually playing physics

contributor:
van Veen, Lennaert
Tamblyn, Isaac

subject:
Reinforcement learning
Machine learning
Mathematics
Physics
Chemistry

abstract: Here we discuss ideas of reinforcement learning and the importance of various aspects of it. We show how reinforcement learning methods based on genetic algorithms can be used to reproduce thermodynamic cycles without prior knowledge of physics. To show this, we introduce an environment that models a simple heat engine. With this, we are able to optimize a neural network based policy to maximize the thermal efficiency for different cases. Using a series of restricted action sets in this environment, our policy was able to reproduce three known thermodynamic cycles. We also introduce an irreversible action, creating an unknown thermodynamic cycle that the agent helps discover, showing how reinforcement learning can find solutions to new problems. We also discuss shortcomings of the method used, the importance of understanding the class of problem being handled, and why some methods can only be used for certain classes of problems.


title: Decentralized state-space controller design of a large PHWR

subject:
Decentralized control
Decoupling algorithm
Large PHWR
Spatial control
Liquid zone level control
State-space control
Reactor nodal core model

abstract:
The behaviour of a large nuclear reactor can be described with sufficient accuracy using a nodal model, like the spatial model of a 540 MWe large Pressurized Heavy Water Reactor (PHWR). This model divides the reactor into divisions or nodes to create a spatial model in order to control the xenon induced oscillations that occur in PHWRs. However, being such a large scale system, a 72nd-order model, it makes controller design challenging. Therefore, a reduced order model is much more manageable. A convenient method of model reduction while maintaining the important dynamics characteristics of the process can be done by decoupling. Also, due to the nature of the system, decentralized controllers could serve as a better option because it allows each controller to be localized. This way, any control input to a zone only affects the desired zone and the zones most coupled with, thus not causing a respective change in neutron flux in the other zones.
In this thesis, three decentralized controllers were designed using the spatial model of a 540 MWe large PHWR. A decoupling algorithm was designed to divide the system into three partitions containing 20, 27, and 25 states each. Reduced order sub-systems were thus created to produce optimal decentralized controllers. An optimal centralized controller was created to compare both approaches. The decentralized versus centralized controllers’ system responses were analyzed after a reactivity disturbance. A fail-safe study was done to highlight one of the advantages of decentralized controllers.


title: Identifying lesions in paediatric epilepsy using morphometric and textural analysis of magnetic resonance images

contributor:
Ebrahimi, Mehran
Widjaja, Elysa

subject:
Computer-aided diagnosis
Epilepsy
Focal cortical dysplasia
Morphometric
Textural analysis

abstract: We develop an image processing pipeline on Magnetic Resonance Imaging (MRI) sequences to identify features of Focal Cortical Dysplasia (FCD) in patients with MRIvisible FCD. We aim to use a computer-aided diagnosis system to identify epileptogenic lesions with a combination of established morphometric features and textural analysis using Gray-Level Co-occurrence Matrices (GLCM) on MRI sequences. The model will be validated on paediatric subjects. Preliminary morphometric analysis explored the use of computational models of established MRI features of FCD in aiding identification of subtle FCD on MRI-positive subjects. Following this, classification techniques were considered. The 2-Step Naive Bayes classifier was found to produce 100% subjectwise specificity and 94% subjectwise sensitivity (with 75% lesional specificity, 63% lesional sensitivity). Thus it correctly rejected 13/13 healthy subjects and colocalized lesions in 29/31 of the FCD cases with MRI visible lesions, with 63% coverage of the complete extent of the lesion using supplied lesional labels.


title: Investigating proteomic profiles of skin mucus and blood plasma of rainbow trout (Oncorhynchus mykiss) exposed to low concentrations of waterborne nickel

subject:
Nickel
Non-lethal and non-invasive sampling
Proteomics
Fish

abstract: The Ontario Ring of Fire located in the James Bay Lowlands is a nickel rich ore with ongoing mining proposals. This raises the possibility of nickel contamination in one of Ontario’s most precious freshwater regions and peatlands. However, impacts of nickel exposure on freshwater fish species remain elusive. To study the impacts in fish when they are exposed to low, environmentally relevant concentrations of nickel (1 – 46 ppb), we examined changes in protein profiles of skin mucus and blood plasma of rainbow trout using untargeted proteomics. The use of non-lethal blood sampling and non-invasive mucus sampling is becoming increasingly desirable to study toxicological effects. Findings suggest that the proteome of rainbow trout is sensitive to low doses of nickel. Primarily, proteins involved in neurological development were impacted in both plasma and mucus proteins. We also find an increase in nickel burden in blood plasma of trout at these concentrations.


title: Uncertainty quantification for safety verification applications in nuclear power plants

subject:
Uncertainty quantification
CATHENA
Sensitivity analysis
FSN
LOCA

abstract:
There is an increasing interest in computational reactor safety analysis to systematically replace the conservative calculations by best estimate calculations augmented by quantitative uncertainty analysis methods. This has been necessitated by recent regulatory requirements that have permitted the use of such methods in reactor safety analysis. Stochastic uncertainty quantification methods have shown great promise, as they are better suited to capture the complexities in real engineering problems. This study proposes a framework for performing uncertainty quantification based on the stochastic approach, which can be applied to enhance safety analysis.
Additionally, risk level has increased with the degradation of Nuclear Power Plant (NPP) equipment and instrumentation. In order to achieve NPP safety, it is important to continuously evaluate risk for all potential hazards and fault propagation scenarios and map protection layers to fault / failure / hazard propagation scenarios to be able to evaluate and verify safety level during NPP operation. In this study, the Fault Semantic Network (FSN) methodology is proposed. This involved the development of static and dynamic fault semantic network (FSN) to model possible fault propagation scenarios and the interrelationships among associated process variables. The proposed method was demonstrated by its application to two selected case studies. The use of FSN is essential for fault detection, understanding fault propagation scenarios and to aid in the prevention of catastrophic events.
Two transient scenarios were simulated with a best estimate thermal hydraulic code, CATHENA. Stochastic uncertainty quantification and sensitivity analyses were performed using the OPENCOSSAN software which is based on the Monte Carlo method. The effect of uncertainty in input parameters were investigated by analyzing the probability distribution of output parameters. The first four moments (mean, variance, skewness and kurtosis) of the output parameters were computed and analyzed. The uncertainty in output pressure was 0.61% and 0.57% was found for the mass flow rate in the Edward’s blowdown transient. An uncertainty of 0.087% was obtained for output pressure and 0.048% for fuel pin temperature in the RD-14 test case. These results are expected to be useful for providing insight into safety margins related to safety analysis and verification.


title: “Foids have no soul, they are not human.” A sociological examination of the language used by an online male supremacy group.

subject:
Jock Young
Incel
Misogyny
Involuntary celibate
Vertigo

abstract: The online incel community has seen a rise in participation and mainstream media attention, largely due to recent mass murders targeting women committed by self-identified members. Scholarship has therefore focused on the community’s relationship to violence and its highly misogynistic nature. Jock Young’s theory of human behavior underlying criminality, as described in The Vertigo of Late Modernity, was used to trace the path from globalization to liquid modernity to othering and, finally, to violence. Young’s work is key to understanding how an outgroup, in this case women, evolves from “us and them” to “us versus them” and finally to “threat”, using a dictionary created and maintained by online male supremacy groups. This thesis found that women are presented as sexual commodities, male and female hierarchies of value reflect gender-based criteria, and significant contradictions in worldview may be resolved through the presence of Hopeful and Hopeless pathways.


title: Design and implementation of an automated gamma probe for jet boring uranium mining.

subject:
Gamma probe
Jet boring system
Radiation detection
Cigar Lake mine
Design

abstract:
A proof-of-concept detector prototype capable of collecting and storing radiometric
data in Jet Boring System (JBS) pilot holes at the Cigar Lake uranium mine is
presented. Variant design is used to design, develop, test and implement the detector's
hardware, fi rmware and software. The battery powered detector is attached inside a
JBS drill rod to collect radiometric data through the drilling cycle. A readout box
is used to initiate the detector, recharge the battery and download radiometric data
after a pilot hole drilling cycle is complete.
Functional testing results are presented and comparative test results between the
JBS gamma probe and the AlphaNUCLEAR Hi-Flux probe are evaluated. Field
data collected from three pilot holes is plotted against each pilot hole's driving layout
and jetting recipe. Future work is discussed for use of Monte Carlo modelling and a
high activity source to characterize the JBS gamma probe and achieve conversion of
gamma counts into U3O8 grade.
Cigar Lake is the second highest known grade uranium mine in the world. The mine
is located in northern Saskatchewan, Canada. Project engineers during the 2000 JBS
proof-of-concept tests suggested that jetting parameters for extracting cavities at full
production may be more eff ective if selected based on gamma logs and experience from
adjacent cavities instead of using pre-set recipes and interim surveys during jetting.
Moreover, in-situ pilot hole radiometric data may also be useful for grade control and
grade reconciliation from a cavity-to-cavity basis. At present, there is no method
available to efficiently and  effectively obtain gamma logs from pilot holes, this project
is a major first step to address this issue.


title: Molecular characterization of the binding site of nematode GABA-A receptors

subject:
Haemonchus contortus
GABA
Ligand binding
Mutational analysis
Homology modelling

abstract:
Haemonchus contortus is a parasitic nematode that is controlled in large part by
nematocidal drugs that target receptors of the parasitic nervous system. Hco-UNC-49 is a
nematode GABA receptor that has a relatively low overall sequence homology to
mammalian GABA receptors but is very similar to the UNC-49 receptor found in the free
living nematode Caenorhabditis elegans. However, the nematode receptors do exhibit
different sensitivities to GABA which may be linked to differences in the putative GABA
binding domains. Mutational analysis conducted in this study identified at least one
amino acid, positioned near the GABA binding domain, which may partially account for
differences in nematode GABA sensitivity. In addition, positions reported to be crucial
for GABA sensitivity in mammalian receptors also affect GABA sensitivity in Hco-
UNC-49 suggesting that the GABA binding domains of the mammalian and nematode
GABA receptors share some pharmacological similarities. However, there were some
differences observed. For example, in mammalian GABAA receptors amino acids from
both  and  subunits appear to be important for GABA sensitivity. For residues
examined in this study, only those on the UNC-49B subunit, and not UNC-49C, appear
important for GABA sensitivity.


title: Forward genetic analysis of cellulose biosynthesis inhibitor resistance and wall hydrolysis sensitivity.

subject:
Cellulose
Wall hydrolysis
Plant genetics

abstract:
The functional analysis of components involved in cellulose biosynthesis is central in
understanding cell wall assembly and structure in plants. We conducted screens using the
herbicides, isoxaben and flupoxam which inhibit cellulose biosynthesis in higher plants.
Mutations resulting in a high degree of resistance to isoxaben (ixr) or flupoxam (fxr) were
attributed to single amino acid substitutions in primary wall CESAs. Twelve novel
resistance alleles were isolated and no cross-resistance was observed. Point mutations
were mostly clustered around the C-terminal regions of CESA1 and CESA3, and CESA3
and CESA6 for fxr and ixr respectively. Resistance to isoxaben was also conferred by
modification to the putative catalytic regions of CESA3. This resulted in cellulose
deficient phenotypes characterized by reduced crystallinity and dwarfism. These results
provide genetic evidence supporting CESA1-CESA3, and CESA3-CESA6 association
with flupoxam and isoxaben respectively targeting and disrupting these interactions. The
ixr and fxr mutants also exhibited enhanced saccharification under enzymatic degradation
schemes which is consistent with the observed reduction in cellulose crystallinity.
A second forward genetic screen was performed using mild acid hydrolysis to
isolate mutants with enhanced saccharification. This screen identified sixty-three
responsive to acid hydrolysis (rah) lines. Unconventional strategies to increase sugar
yields from plant biomass where highlighted. These included starch hyper-accumulators
such as starch excess 4 (sex4) loss-of-function mutants and the perturbation of polar
auxin transport. Disruption of the serine/threonine kinase positive regulator of auxin
efflux, PINOID (PID) was found to significantly enhance sugar release in Arabidopsis
and similar effects were observed in the maize orthologue, BARREN INFLORESENCE
2 (BIF2). Furthermore, the application of N-1-naphthylphthalamic acid (NPA) in
Arabidopsis, maize, Miscanthus and switchgrass phenocopied the enhanced wall
saccharification effects of PID. This study attempted to elucidate some of the
interactions of seemingly unrelated pathways in the context of wall biosynthesis and
saccharification enhancement.


title: An unmanned aerial vehicle-based assessment method for quantifying computer vision models

contributor:
El-Khatib, Khalil
Pazzi, Richard
Almehmadi, Abdulaziz

subject:
CNN
Computer vision
Spatial evaluation
UAV

abstract:
Computer vision is a growing field in computer science. Since the advancement of Machine learning, Computer vision solutions have been trending. As a result of the growing number of solutions and performance increases in Machine learning, machine learning solutions are now being utilized in the field of robotics. A problem propagates when the evaluation methods that were used previously are used for robotic vision solutions. The accuracy metric although valuable from a data driven perspective lends no benefit to the use in robotics.
The accuracy calculated by the performance of the Convolutional neural network on the evaluation dataset is only a relevant metric to the evaluation dataset. The accuracy metric does not define the distance at which the accuracy of the Convolutional Neural Network (CNN) begins to decrease below the required threshold. The accuracy metric does not depict the strengths and weaknesses of the CNN in terms of orientation of the object. The accuracy metric does not show the accuracy of the CNN given a specific orientation and distance.
Orientation and distance are factors when considering a computer vision solution for the use in robotics. A popular example is Tesla. Tesla incorporates a multitude of systems in order to produce their self-driving capabilities. One of the systems used is camera feed that utilizes Machine learning to depict the context of the image. Tesla needs their system to perform in a multitude of distance and orientation of objects [9]. Simply using a single accuracy metric will not be enough to define the limitations of the system.
What this thesis proposes is an evaluative method capable of defining the spatial limitations of a CNN for 3D objects. This approach utilizes Unmanned aerial vehicle (UAV) mobile sensors in order to generate the desired distances and orientation from the object being evaluated. Multiple flight sequences are conducted to provide information that is able to define the exact point in which the accuracy starts to decrease and the orientations that are the most weak. This approach was tested using a two class CNN that depicted if a Ford Ranger was in the image or if it was not. The experimental results using an Unmanned Aerial Vehicle (UAV) was able to depict the CNN's dependencies such as: the distance from the object, the altitude, the orientation of the object and the impact these dependencies have on accuracy. An UAV was used due to their innate capability as mobile sensors capable of producing any perspective and distance required.


title: Investigation of sub-cell homogenization for PHWR lattice cells using superhomogenization factors

subject:
Applied reactor physics
Superhomogenization
PHWR
SPH factors

abstract: To avoid the computational effort associated with full-core neutron transport calculations, full-core neutronics calculations for Pressurized Heavy-Water Reactors (PHWRs) are usually performed in diffusion theory using an approximate core model, whereby only two energy groups are utilized and two-group neutronic properties (i.e. macroscopic cross sections and diffusion coefficients) are homogenized in two dimensions over large sub-domains, each corresponding to a 28.6 cm x 28.6 cm lattice cell. The lattice cell is the elementary geometrical unit describing the rectangular array of fuel channels comprising the PHWR core. The use of lattice-cell homogenization introduces some computational errors. One possible way to reduce such homogenization errors is to sub-divide the lattice cell into sub-cells and perform sub-cell-level homogenization. In this study, the PHWR lattice cell is divided into 3 x 3 sub-cells. Full-cell-averaged, as well as sub-cell-averaged two-group cross-sections, are generated for subsequent use in an equivalent two group two-dimensional diffusion model. Cross sections with Superhomogenization (SPH) [Hebert, 2009] factors are also utilised in an attempt to improve accuracy. The effect of using different homogenization models (full cell, partial cell, partial-cell with SPH-corrected cross sections) is tested on a two-dimensional partial-core model consisting of 3 x 3 lattice cells (bundles). Results from reference transport model with detailed geometry 69-group are compared with cell-homogenized two-group diffusion results obtained using full-cell homogenization and sub-cell homogenization with and without SPH correction factors. The application of sub-cell homogenization, as well as the use of SPH correction factors, is found to have only a minimal effect on computational accuracy.


title: The policing of terrorism: a comparative analysis of Turkish and Canadian counter-terrorism responses

subject:
Terrorism
Counter-terrorism
Turkish National Police
Royal Canadian Mounted Police
Comparative analysis

abstract: Police agencies assume a significant role in the creation and enforcement of government counter-terrorism strategies. Modern police organizations are tasked with preventing and responding to terrorism, in addition to their traditional policing duties of crime prevention, criminal investigation and order maintenance. However, despite the increment and spending on police counter-terrorism efforts, very little is known about the exact nature and effectiveness of police counter-terrorism strategies. Studying the policing of terrorism for a detailed understanding of what police are doing regarding counter-terrorism is a major requisite for terrorism researchers. Additionally, explaining why police agencies differ in their responses to terrorism is also critical in analyzing police counter-terrorism tactics. Although there exist studies that compare and contrast countries’ responses, there is not much comparative research on police organizations’ responses to terrorism. The current research develops a comparative analysis of the Turkish and Canadian police organizations’ responses to terrorism. Using data obtained on the Turkish National Police (TNP) and the Royal Canadian Mounted Police (RCMP), the main purpose of the current study is to explore and compare how international police organizations respond to terrorism. This thesis aims to advance the knowledge and practice of the police role in countering terrorism.


title: Development and validation of a driver distraction alert system for highway driving using a truck driving simulator

subject:
Driver vigilance
Driver distraction
Vigilance monitoring techniques
Driver alert systems
Crash avoidance

abstract: Driver distraction is one of the major causes of vehicle accidents, injuries, fatalities and economical losses in Canada and across the world. The main objective of this thesis is to develop a real time driver distraction alert system that can generate early warning signals and prevent vehicle accidents. The proposed system is applied to a truck driving simulator by monitoring the driver response through the steering wheel and accelerator pedal during different driving experiments. In order to ensure an accurate prediction of the driver distraction, the simulation output of the truck driving simulator is compared to that of the commercial TruckSim® software using identical parameters of a given tractor semitrailer during similar driving conditions. Consequently, the driving speed and steering angle profiles for both simulation environments are then compared during standard test maneuvers and found to be in good agreement. Several distraction indicators are proposed in order to predict the driver distraction namely; the jerk profile, spikiness index and the rate of change for both the steering wheel angle and the accelerator pedal position. Several driving experiments are performed considering both the offline and real time assessment of a driver subjected to different types of distraction. The major finding of the thesis emphasizes the effectiveness of using steering wheel rate to estimate driver distraction. Moreover, in comparison to other techniques for predicting driver vigilance, the presented work requires low computational power and has a great potential for developing a real time simple system that can be affordable and reliable.

abstract: University of Ontario Institute of Technology


title: Study of radio frequency inductively coupled thermal plasma torch (RF ICPT) for radioactive waste treatment: thermoplastics - polyethylene and polyvinyl chloride (PVC)

subject: Inductively coupled plasma torch (ICPT)

subject: Radioactive waste (RW)

subject: COMSOL multiphysics simulation

subject: ICPT design

subject: Polyvinyl chloride (PVC) and Polyethylene (PE)

abstract: Despite advancements in technology and many progresses made in effort for radioactive waste (RW) treatment and overall management, there is still no final and ever lasting solution. Among the many RW materials originating from nuclear power plants (NPPs), thermoplastics such as polyvinyl chloride (PVC) and polyethylene (PE) contribute significant amount to the overall volume of RW. The presence of radioactive nuclides in PVC and PE waste originating from NPPs and their plastic nature (non-bio-degradable characteristics) present two challenges at once. To solve the challenges presented by such plastic RW, a thermal plasma waste treatment approach was considered. A radiofrequency (RF) inductively coupled plasma torch (ICPT) was designed in SOLIDWORKS and simulated using COMSOL Multiphysics software, and its thermal behavior was studied. Its applicability including advantages and shortcomings for such use was studied.


title: Design, analysis and validation of electrode-less plasma generator

subject:
Magneto-hydro-dynamics
Plasma
Control
Coupling methodologies

abstract: The current work investigates a method for generating plasmas without damaging electrodes. The primary objective is the creation of an electrode-less potential region (virtual cathode) through the use of electron emission and active feed of radio frequency (RF) signal. The reason for pursuing this was to make plasma devices that are compact, efficient, resilient, and low maintenance. The foundational scientific theory, model, and the simulation were applied in Elmer multi-physics software and validated by experiments. The experiments were conducted with electrode based plasma generator, ionization setup, and RF assisted configuration, and compared with respect to their operational parameters. It has been determined that it is possible to create a plasma generator with a virtual cathode that receives substantial electromagnetic energy from RF and competes with a direct arc discharge method in performance, and longevity, albeit requiring a more refined control.


title: A cross-sectional analysis of student fruit and vegetable consumption at the University of Ontario Institute of Technology

subject:
Fruit and vegetable consumption
Cross-sectional
University students
Canada’s Food Guide

abstract: Access to nutritious food is imperative for maintaining overall health. Fruits and vegetables are foods that are nutrient rich, and consumption of these foods is related to positive health outcomes. The purpose of this study was to determine fruit and vegetable consumption for students in the Faculty of Health Sciences at the University of Ontario Institute of Technology and what food retailers they frequent. The study found that students reported a daily fruit and vegetable consumption lower than the minimum daily amount recommended by Canada’s Food Guide. Students were also shown to frequent sit-down food retailers that offered diverse dietary options (low-sodium, gluten-free, and vegetarian). There was an association between students who visited stores that offered fewer options and increased consumption of potatoes. Low consumption of fruit and vegetables can lead to health complications, such as increased risk for cardiovascular disease and cancer, and should be addressed to reduce risk.


title: Exergy and exergoeconomic analyses and optimization of thermal management systems in electric and hybrid electric vehicles

contributor:
Dincer, Ibrahim
Naterer, Greg F.

subject:
Exergy
Exergoeconomic analysis
Thermal management system
Electric vehicle
Hybrid electric vehicle

abstract:
With the recent improvements in battery technologies, in terms of energy density, cost and size,
the electric (EV) and hybrid electric vehicle (HEV) technologies have shown that they can
compete with conventional vehicles in many areas. Although EVs and HEVs offer potential
solutions for many key issues related to conventional vehicles, they still face considerable
challenges that prevent the widespread commercialization of these technologies, such as thermal
management of batteries and electrification.
In this PhD thesis, a liquid thermal management system (TMS) for hybrid electric vehicles is
investigated and evaluated against alternative thermal management systems, and optimal
parameters are selected to maximize the system efficiency. In order to achieve this goal, a model
of the liquid thermal management system is established to determine the irreversibilities and
second-law efficiencies associated with the overall system and its components. Furthermore, the
effects of different configurations, refrigerants and operating conditions are analyzed with
respect to conventional exergy analyses. In addition, advanced exergy analyses are also
conducted in order to better identify critical relationships between the TMS components and
determine where the system improvement efforts should be concentrated. Moreover, investment
costs are calculated and cost formation of the system is developed in order to evaluate the TMS
with respect to exergoeconomic principles and provide corresponding recommendations.
Environmental impact correlations are developed, along with a cradle-to-grave life cycle
assessment (LCA), to highlight components causing significant environmental impact, and to
suggest trends and possibilities for improvement based on the exergoenvironmental variables.
Finally, the TMS is optimized using multi-objective evolutionary algorithm which considers
exergetic and exergoeconomic as well as exergetic and exergoenvironmental objectives
simultaneously with respect to the decision variables and constraints.
Based on the conducted research for the studied system under the baseline conditions, the exergy
efficiency, total cost rate and environmental impact rate are determined to be 0.29, ¢28/h and
77.3 mPts/h, respectively. The exergy destruction associated with each component is split into
endogenous/exogenous and avoidable/unavoidable parts, where the exogenous exergy
destruction is determined to be relatively small but significant portion of the total exergy
destruction in each component (up to 40%), indicating a moderate level of interdependencies
among the components of the TMS. Furthermore, it is determined that up to 70% of the exergy
destruction calculated within the components could potentially be avoided.
According to the analyses, electric battery is determined to have the highest exergoeconomic and
exergoenvironmental importance in the system, with cost rate of ¢3.5/h and environmental
impact value of 37.72 mPts/h, due to the high production cost of lithium ion batteries and the use
of copper and gold in the battery pack. From an exergoeconomic viewpoint, it is determined that
the investment costs of the condenser and evaporator should be reduced to improve the costeffectiveness
of the system. On the other hand, from an exergoenvironmental viewpoint, all the
component efficiencies (except for the battery) should be improved in order to reduce the total
environmental impact even if it increases the environmental impact during production of the
components. In addition, it is determined that the coolant pump and the thermal expansion valve
before the chiller are relatively insignificant from exergoeconomic and exergoenvironmental
perspectives.
Subsequently, objective functions are defined and decision variables are selected, along with
their respective system constraints, in order to conduct single and multiple objective
optimizations for the system. Based on the single objective optimizations, it is determined that
the exergy efficiency could be increased by up to 27% using exergy-based optimization, the cost
can be reduced by up to 10% using cost-based optimization and the environmental impact can be
reduced by up to 19% using environmental impact-based optimization, at the expense of the nonoptimized
objectives.
Moreover, multi-objective optimizations are conducted in order to provide the respective Pareto
optimal curve for the system and to identify the necessary trade-offs within the optimized
objectives. Based on the exergoeconomic optimization, it is concluded that 14% higher exergy
efficiency and 5% lower cost can be achieved, compared to baseline parameters at an expense of
14% increase in the environmental impact. Furthermore, based on the exergoenvironmental
optimization, 13% higher exergy efficiency and 5% lower environmental impact can be achieved
at the expense of 27% increase in the total cost.


title: Pilot study on Nordic pole walking and individuals with cancer: effects on physical function and health-related quality of life

contributor:
Nonoyama, Mika
Weaver, Robert

subject:
Cancer
Neoplasms
Nordic pole walking
Excercise/physiology
Walking

abstract:
Individuals diagnosed with cancer experience a high symptom burden that has a significant impact on their quality of life and an individualized, community-based Nordic pole walking (NPW) program may help to alleviate this.
The primary objective of this eight-week multi-centred randomized controlled pilot study was to assess the feasibility of a NPW program for individuals with stage I-IV nonsmall cell lung cancer (NSCLC), prostate cancer, colorectal cancer, and endometrial cancer. The secondary objective was to determine the effects of NPW on physical function and health-related quality of life (HRQoL). Participants were randomly assigned to either the NPW group (one supervised NPW session and up to three independent NPW sessions) or the control group (usual daily routine).
The pilot study suggests that examining the effects of NPW on individuals diagnosed with cancer is feasible with modifications. Recommendations include: 1) Recruit participants at hospital cancer centres; 2) Individualize NPW and integrate behavioural change techniques into the program; 3) Use pedometers or accelerometers to increase the accuracy of measured physical activity levels; and 4) Organize NPW programs for individuals with NSCLC alongside programs for individuals with other chronic respiratory diseases. Results indicate trends of improved overall physical activity levels and HRQoL measures. The NPW group experienced a significant decrease in thigh circumference measurements from the baseline assessment (Right Thigh: median 49.4 cm (range 8.7); Left Thigh: median 49.0 cm (range 6.0)) to the final assessment (Right Thigh: median 48.5 cm (range 6.5); Left Thigh: median 46.3 (range 4.0)) (p<0.05). Significant improvement was also found in the NPW group 30-s chair stand test (Baseline: median SD) 10.5 (3.7); Final: median 14.3 (4.2)) (p<0.05). Further research with larger sample sizes should be completed to more conclusively determine the impact of NPW.


title: Study of the effect of molten CuCl immersion test on alloys  with high Ni-content with and without surface coatings

contributor:
Rizvi, Ghaus
Ikeda, Brian

subject:
Surface
Corrosion
Molten CuCl
Immersion

abstract:
The demand for hydrogen as a clean energy carrier has increased greatly. The Cu-Cl cycle is a promising thermochemical cycle that is currently being developed to be the large-scale method of hydrogen production. The lifetime of materials for the pipes transporting molten CuCl is an important parameter for an economic design of a commercial thermochemical Cu-Cl hydrogen plant. This research is an examination of candidate materials following an immersion test in molten CuCl at 500 °C for 100 h. Two alloys, Ni based super-alloy (Inconel 625) and super austenitic stainless steel (AL6XN) were selected as the base metal. There were two types of coating applied to improve the corrosion resistance of the base metals during molten CuCl exposure. A metallic of Diamalloy 4006 and two ceramic of yttria stabilized zirconia and alumina coatings were applied to the base metal using thermal spray methods.
An immersion apparatus was designed and constructed to perform an immersion test that has a condition similar to those in a hydrogen plant. After the immersion test, the materials were evaluated using an electrochemical method in combination with ex-situ surface analysis. The surface condition including elemental composition, film structure and resistivity of the materials were examined and compared. The majority of the coatings were damaged and fell off. Cracks were found in the original coated specimens indicating the sample geometry may have affected the integrity of the sprayed coating. When the coating cracked, it provided a pathway for the molten CuCl to go under the coating and react with the surface underneath the coating. Copper deposits and iron chloride that were found on the sample surfaces suggest that there were corrosion reactions that involved the metal dissolution and reduction of copper during immersion test. The results also suggest that Inconel 625 performed better than stainless steel AL6XN. Both Diamalloy 4006 and YSZ (ZrO2 18TiO2 10Y2O3) coatings seemed to provide better protection to the underlying base metal than alumina (Al2O3 3TiO2) coating.


title: Faulty node repair and dynamically spawned black hole search in clouds

subject:
Faulty node repair
Black hole search
Agent
Whiteboard

abstract:
The reality of the constant emergence of new threats justifies the necessity to protect
network assets and mitigate the risks associated with attacks. In this context, eliminating faulty network entities in the distributed environment such as cloud of the
clouds and smart grids catches the attention of the researchers. Among all threats,
black hole is a severe and pervasive one which models a network site that disposes
any incoming data without leaving any trace of such distraction. Black hole search
is the process that leverages mobile agents to locate black holes in a fully distributed
way.
In this paper, we first review the state-of-the-art research in this area by categorizing the research results based on the adopted network models, being either
synchronous or asynchronous. Most of the existing works focus on locating a single
black hole. As for multiple black holes, the problem becomes even more complex.
For the study of multiple black hole search, we introduce a new attack model
that involves not only multiple faulty nodes in the network (a type of black hole),
but also a gray virus that can again infect a previously repaired faulty node. Under
such a model, the multiple faulty node search problem becomes more complex and
realistic. We analyze the proposal model and identify key observations about the
multiple faulty node search/location problem. We introduce one-stop and multi-stop
gray virus and study the faulty node repair and black hole search problem.
We first propose solutions that use a token model to solve the problem caused by
a multi-stop gray virus in an asynchronous arbitrary network topology. Also under
the token model, we then present solutions for the problem caused by this one-stop
gray virus in an asynchronous ring network. Apart from the token model, we continue
to study the problem caused by the one-stop virus using a whiteboard model, more
particularly, with only one whiteboard in the homebase node in an asynchronous ring
network.
After proposing the new model and our algorithms, we conclude some future work
on both single and multiple black holes search. We also highlight some open problems
on the one-stop and multi-stop gray virus.


title: The effectiveness of the Foodbot Factory serious game on increasing nutrition knowledge in children

subject:
Canada’s Food Guide
Serious games
Nutrition knowledge
Elementary school children
Nutrition questionnaire

abstract: Background: The interactive nature of serious games (i.e., video games designed for educational purposes) enable deeper learning and facilitate behavior change; however, there is limited data on their impact on child nutrition knowledge. The objective of this study was to determine if Foodbot Factory effectively improves children’s knowledge of 2019 Canada’s Food Guide. Methods: Study was a single-blinded, parallel randomized controlled trial conducted among children ages 8-10 years attending Ontario Tech University summer day camps. Results: Compared to the control group (n=34), children who used Foodbot Factory (n=39) had significant increases in overall nutrition knowledge (10.3 ± 2.9 to 13.5 ± 3.8 versus 10.2 ± 3.1 to 10.4 ± 3.2, p<0.001), and in Vegetables and Fruits (p<0.001), Protein Foods (p<0.001), and Whole Grain Food (p=0.040) sub-scores. No significant difference in knowledge was observed in Drinks sub-score. Conclusion: Foodbot Factory is an effective educational tool to support children learning about nutrition.


title: Proposing an ensemble-based model using data clustering and machine learning algorithms for effective predictions

contributor:
Rahnamayan, Shahryar
Makrehchi, Masoud

subject:
Data mining
Machine learning
Clustering
Regression
Prediction

abstract: One of the most important tasks in machine learning is prediction. Data scientists use various regression methods to find the most appropriate and accurate model applicable for each type of datasets. This study proposes a meta-model to improve prediction accuracy. In common methods different models are applied to the whole dataset to find the best model with the highest accuracy. This means, a global model is developed for the entire dataset. In the proposed approach, first, we cluster data using different methods and we have used algorithm-based and expert-based clustering. Algorithm-based clustering such as K-means, DBSCAN, agglomerative hierarchical clustering algorithms. For expert-based clustering, we use expert knowledge to group datasets based on the important features which are selected by experts. Then, for each clustering method and for each generated cluster, we apply different machine learning models including linear and polynomial regressions, SVR, neural network, genetic programming and other techniques and select the most accurate prediction model per cluster. In every cluster, the number of samples in each cluster is reduced compared to the number of samples in the original dataset and consequently, by decreasing the number of samples in each cluster, the model is prone to lose its accuracy. On the other hand, customizing a model for each sub-dataset increases the capability of offering more effective prediction, compared to a situation where one model is fitted to the whole dataset. That is why the proposed model can be categorized as in an ensemble-based group due to the fact that the prediction is performed based on the collaboration of various models over clusters of sub-datasets. Moreover, granularity of the proposed method is better for parallelization purposes. This means, it can be parallelized in a more efficient way. As our main case study, we used real-estate data with more than 21,000 instances and 20 features to improve house price prediction. However, this approach is applicable to other large datasets. In order to examine its capability, we applied the proposed method on two other datasets; agricultural dataset with 10 features and more than 7,000 instances and also Facebook comments volume dataset, which contains roughly 41,000 samples with 54 features. For the first dataset, the new approach reduces error value from 0.14 to 0.087 for K-means clustering and 0.086 for grouping based on human knowledge. With respect to our second case study, the water evaporation data did not obtain considerable improvement in accuracy; however, in some sub-datasets there was an improvement in accuracy.


title: TCP congestion control using reinforcement learning

subject:
Reinforcement learning
OpenAI gym
Software-defined networking (SDN)
TCP congestion avoidance
Network congestion

abstract: TCP, a transport layer protocol which ensures the reliable delivery of information on the network, is the basis of Internet connectivity, with 85% of the worlds Internet traffic being TCP based. TCP however, is slow to adapt to changes in the network, drastically reducing the throughput at the first sign of possible congestion, thereby preventing rapid restoration of the throughput. Mitigating this problem has been a very active area of research, as, until recently, the idea of using Artificial Intelligence (AI) in this space was relatively limited. Recently, Reinforcement Learning (RL), a form of AI, has been explored in the networking space, and in enhancing the performance of TCP, this Thesis aims to expand the use of RL for TCP (TCP-CA/RL) in a software-defined data center. We demonstrate that our proposed approach is able to significantly reduce the impact of congestion on the end-to-end network throughput within the data center.


title: I remember, at least I think I do : An investigation into emotional memories and our perception of them over time

contributor:
Mirza-Babaei, Pejman
Kapralos, Bill

subject:
Memory
Sensory emotional design
Emotions
Games user research
Education

abstract: Entertainment and emotions play a large part in the area of education and learning, however there is a lack of understanding in both the implementation of game-based learning and how this information changes over time. Furthermore, there is lack of tools in investigating emotional memories, as many traditional methods focus on immediate feedback which is not appropriate for repeated long-term evaluation. This thesis performs an indepth investigation into emotional memories, identifying and understanding them as well as insight into designing and utilizing games and entertainment as a means of learning. The result of this work can be allocated into three primary categories. i) Designing games for play-learners ii) Identifying memorable information using new and existing methods iii) Understanding emotional memories, how we view, what we recall, and the details we remember with respect to time. The results of this work contribute to the areas of games user research, psychology, memory, digital game-based learning, aiming to improve our understanding of memory, what types of events we are likely to remember accurately and the way our emotions influence it as time passes by.


title: Exploring design alternatives in game development engines using visual programming

subject:
Alternatives
Visual programming
Creativity support
Unreal engine
Game development

abstract: We present BPAlt – a system which allows game developers to create and manage alternatives for Unreal Engine’s Blueprints Visual Scripting System. BPAlt allows the user to create, save, organize and swap Blueprint alternatives for rapid testing and experimentation. We conducted a user study with 10 moderately skilled participants where we compared BPAlt to Unreal Engine alone for prototyping alternatives of game objects and mechanics in four different games. We found evidence that supporting alternatives with BPAlt is beneficial in the game developers’ workflow. In response to the results of the user study we implemented new features for selectively merging parts of one alternative Blueprint to another. We also implemented an interface for alternative scenarios.


title: Towards a concurrent implementation of keyword search over relational databases.

subject:
Relational database
Full-text search
Graph search
Algorithms

abstract: Vast amounts of data are stored in relational databases. Traditionally, querying this data required a deep understanding of the underlying schema in addition to knowledge of a query language such as structured query language (SQL). We present a framework for the automatic, lossless transformation of data from the relational model to the document model. By performing this transformation, users may locate information by using simple keyword queries. We further this by implementing graph search, allowing users to automatically discover related facts of information. The effects of performing graph search concurrently are explored, revealing a substantial reduction in graph search run-time over the serial implementation.


title: The "unique" experiences of domestic violence of immigrant Sikh women through films.

subject:
Domestic violence
Women
Sikhism
Intersectionality
Content analysis

abstract: The larger context in which minority groups such as the Sikh community make sense of domestic violence, and assign meaning to abuse, has seldom been explored in intimate partner violence research. Current literature, regardless of racial background, tends to homogenize the multiple experiences, perceptions and understanding of domestic violence survivors. With South Asians, specifically those of Sikh descent, being one of the largest growing minority groups in Canada, it becomes necessary to understand how this ethnic group experiences, perceives and makes sense of domestic violence. By utilizing a qualitative approach of content analysis, an analysis of two South Asian films, Heaven on Earth and Provoked, is conducted. Moreover, this research uses an intersectional approach of culture, gender, religion, public policy and immigration status to illustrate the multidimensional experience, perception and understanding of domestic violence by the representation of the Sikh community in films.


title: Pushing the limits of performance. is it really mind over matter? an investigation into the effects of menthol mouth rinsing and the capacity for fatigue amelioration in trained adolescent male cyclists under heat stress

subject:
Menthol
Cycling
Variable cycle test
Heat stress
Central fatigue

abstract: This thesis investigated the effects of menthol (MEN) mouth rinsing (MR) on performance responses in trained adolescent male athletes during a modified variable power cycle test (M-VCT). Participants (n=11) cycled for 30-min in hot conditions (31.4±0.9 °C, 23.4±3.7% RH) on two occasions. In a randomized crossover design, (1) menthol MR (0.01%) or (2) placebo (PLA) MR, was administered at 6-min intervals. Power, distance, core temperature, heart rate, surface electromyography, perceptual responses (exertion, thermal stimulation, fatigue, and feeling), and blood lactate were recorded. The MEN MR significantly improved mean power output by 1.81±1.57% relative to PLA (p=<0.001, 95% CI= [1.73-4.46], ES= 1.53). Physiological and perceptual measures did not differ between trials. While individual responses varied to MEN, results demonstrate that a nonthermal cooling agent that acts on the CNS can benefit power regulation during a stochastic cycling task without causing additional decline in perception, as suggested by the central fatigue hypothesis.


title: Automatic trajectory generation for mobile-manipulators using 3D LiDAR scans of unknown surfaces

subject:
Mobile-manipulator
Trajectory generation
Localization
Shotcrete
LiDAR

abstract: An approach to improving worker safety in underground uranium drift mining through automating the radiation scanning and shotcrete application process is presented. Utilizing the Robot Operating System (ROS) framework to achieve autonomous operation, workers can be removed from the most hazardous areas of the mine. Worker knowledge and experience is utilized when instructing the system from a remote location. The current approach to radiation scanning exposes the workers to radiation hazards and employs the use of cumbersome handheld radiation sensors that are difficult to position accurately. Sprayable concrete liner known as shotcrete is applied to all surfaces of the drift to protect workers from hazards, such as rock fall and radon gas. Proper application of shotcrete and visual estimation of its thickness require highly skilled operators. This research presents a trajectory generation algorithm that is capable of autonomously applying shotcrete to unknown surface geometries. The trajectory generation algorithm can also be used to perform radiation scanning with the use of a previously developed tool changer. A novel localization algorithm developed for use in underground mining uses the Point Cloud Library (PCL) to accurately register point cloud scans of the drift from before and after shotcrete application and produces thickness estimates of the entire shotcrete area. Estimating shotcrete thickness allows for verification to ensure worker safety and eliminates the human error present in current thickness estimation methods. The hardware and software systems are highly modular in order to allow components or algorithms to easily be replaced or implemented on other systems. The localization system presented uses fiducial markers that allow the robot to generate 3D point cloud representations of the entire mine. While scanning the drift face, a shielded radiation sensor can be used for more directional measurements, and the locations at which the measurements are taken relative to the drift face can be recorded with great accuracy. Verifying shotcrete thickness, mapping mine drifts, and protecting workers from hazardous environments are three factors which contribute to improved safety and monitoring of underground uranium mines.


title: Single magnetic resonance image super-resolution using generative adversarial network

subject:
Medical image super-resolution
Magnetic Resonance Image
Generative Adversarial Network
Real-ESRGAN

abstract: Super-Resolution is the process of converting given low-resolution images into corresponding high-resolution ones. The resolution enhancement process applied to medical images can potentially improve diagnostic accuracy for a variety of conditions and reduce imaging scan time. Recent improvements in computational tools have made deep learning methods popular for various image processing techniques including resolution enhancement. In this thesis, we consider the image super-resolution problem of the brain and cardiac MRI datasets. To increase the spatial resolution of these medical images, we have adapted a Generative Adversarial Network (GAN) model where the generator has a DenseNet type structure and the discriminator is based on the U-Net model. We have used a combination of loss functions to ensure the generated images are consistent with ground truth. To train and validate the model, we have used four different datasets consisting of brain and cardiac MRI. Promising qualitative and quantitative results are provided.

abstract: University of Ontario Institute of Technology


title: Case management for community-dwelling seniors living with frailty: perspectives of case managers

subject:
Frailty
Community-dwelling seniors
Case management
Case managers

abstract: Frailty is a growing health concern in Canada’s aging population. Community-dwelling seniors living with frailty are at an increased risk of adverse health and wellness outcomes. Case management has emerged as a promising approach to mitigate the burden of frailty. Case managers are responsible for the delivery of case management to community-dwelling seniors living with frailty. This phenomenological study explored case managers’ experiences delivering case management to this population. The Senior Friendly Care Framework guided the core components of this study including the data collection, analysis, and discussion. Interpretative phenomenological analysis of the data resulted in the identification of 13 themes that affect case management. These results provide insight into the current barriers and facilitators of case management practices for community-dwelling seniors living with frailty. The implications of this study’s results provide further evidence that can influence future practice, education, research and policy of case management for community-dwelling seniors living with frailty.


title: Detecting vulnerabilities of broadcast receivers in Android applications

subject:
Android
Broadcast receiver
Taint analysis
Semantic analysis
Vulnerability

abstract: As being a representative mobile operating system in the world, Android OS has been part of users' daily life. Unfortunately, the rapid expansion of Android third-markets introduces malware aiming at Android applications at an alarming rate, which poses great threats to its users. Current research about the privacy leakage in Android mostly focuses on Activity, Service and Content Providers. Little attention has been paid to the vulnerability of Broadcast Receiver, which is expected to assist inter-component collaboration and facilitate component reutilization. In this thesis, we first present a detailed analysis on vulnerabilities of Broadcast Receiver. Then, we design and develop a Broadcast Receiver Vulnerability Detection (BRVD) system that examines such vulnerabilities, using a combination of semantic analysis and taint analysis. Furthermore, we perform experimental evaluation by analyzing 55 applications from Android third-markets using the proposed system; and 132 registered receivers are found with 11 vulnerable receivers being verified.


title: An evaluation of the net breeding capability of heterogeneously-fuelled pressure-tube heavy water reactors with the thorium fuel cycle

subject:
Thorium
PT-HWR
Breeder reactor
SSET
CANDU

abstract:
The thorium fuel cycle is a promising future option for an alternative to uranium. The pressure tube heavy water reactor (PT-HWR) has for decades been considered capable of achieving net breeding on the thorium fuel cycle, but this capability has not been conclusively demonstrated. The goal of this work was to perform reactor physics modelling of the 380-channel, 700 MWe PT-HWR, attempting to achieve a self-sustaining equilibrium thorium cycle with specific focus on operational viability.
The DRAGON neutron transport code was used to model ThO₂/²³³UO₂ fuel lattice cells.
Sensitivity analyses were performed for the fissile nuclide content, specific power, and average fuel temperature. Thorium-based fuels are found to have a strongly negative power coefficient of reactivity, leading to criticality concerns in the event of a prolonged shutdown. Several fuel bundle concepts were modelled in order to determine the most favourable assembly for breeding. The results showed no significant benefit to other concepts, therefore the standard 37-element bundle was selected due to its wealth of operational experience and well-known operating margins. Homogeneous fuelling was found to be impractical for breeding, and heterogeneous fuel bundles were found to not offer significant improvement while increasing complexity. As a result, heterogeneous core configurations using homogeneous bundles were investigated in full core calculations.
The DONJON core physics code was used in conjunction with homogenized cross-sections calculated by DRAGON to model the complete reactor, including reactivity devices and supporting structures. Seven fuelling configurations were simulated and iteratively improved through an empirical process. Ultimately, none of the studied configurations could achieve net breeding. The most favourable configuration was found to be a heterogeneous seed and blanket core where the blanket (composed of 1.4 at% ²³³U) was placed in the central region and the seed (composed of 1.6 at% ²³³U) was placed in the periphery. Two variants of this configuration (differing on the refuelling scheme used in the blanket) were further investigated with instantaneous power simulations with 10 full power days of refuelling. Both variants were found to abide by the existing license limits on maximum bundle and channel power. The variant using 4-bundle shift in both blanket and seed could tolerate an increase in reactor power to 110% FP while maintaining a comfortable margin to safety. A number of postulated misfuelling events were simulated for both variants, and the responses were found to be controllable by the existing reactivity systems.
It is noted that there are significant sources of error in the results of this work. Advances in computational methods as well as better nuclear data for the thorium fuel cycle are required for more accurate predictions. Overall, while the PT-HWR has great potential as a very high converting reactor, based on the results of this work, the existing design cannot operate as a net breeder. From an economic perspective, a gain in power output may be more beneficial than an entirely closed fuel cycle.


title: Sum-rate optimal network beamforming and power allocation for single-carrier asynchronous bidirectional relay network

subject:
Two-way relaying
Bi-directional relay networks
Sum-rate maximization
Asynchronous relay networks

abstract:
We study the problem of sum-rate maximization, under a total transmit power budget,
for an asynchronous single-carrier bidirectional (two-way) network. The network consists
of two single-antenna transceivers which wish to exchange information with the help of
multiple single-antenna amplify-and-forward (AF) relays. We assume that the network
is asynchronous meaning that different transceiver-relay links cause significantly different
propagation delays in the signal they convey. As a result, the end-to-end channel is not
amenable to a frequency flat model, rather a multi-path channel model with multiple taps
appears to be more appropriate. Such a multi-path model for the end-to-end channel raises
the issue of inter-symbol-interference (ISI) at the two transceivers. In a block transmission/
reception scheme, ISI leads to inter-block interference (IBI), which could result in loss
in the sum-rate of the network, if it is not considered in the design of the system. Considering
a block transmission/reception scheme and assuming a total transmit power budget,
we maximize the sum-rate of this ISI end-to-end channel over the relay complex weights
and transceivers’ transmit powers. We rigorously prove that such a sum-rate maximization
problem leads to a relay selection scheme, where only those relays which contribute to one
tap of the end-to-end channel impulse response are turned on and the rest of the relays
are switched off. Indeed, we prove that at the optimum, the end-to-end channel impulse
response (CIR) has only one non-zero tap, rendering the end-to-end channel frequency
flat. We present the optimal value of the vector of the weights of the active relays and the
optimal values of the transceivers’ transmit powers in a semi-closed form.


title: A privacy preservation framework for smart connected toys

subject:
Privacy preservation framework
Toy computing
Security
Context data model
Smart connected toys (SCTs)

abstract: Advances within the toy industry and interconnectedness have resulted in the rapid and pervasive development of Smart Connected Toys (SCTs), built to aid children in learning, socialization, and development. A SCT is a physical embodiment artifact that acts like a child user interface for toy computing services on Cloud. SCTs extend the capability of the traditional toy into a new area of computer research by incorporating the physical component of a traditional toy combined with networking and sensory capabilities of mobile devices using ubiquitous technologies. These SCTs are built as part of the Internet of Things (IoT) with the potential to collect terabytes of personal and play information; introducing ever-increasing privacy, and serious safety concerns for children. SCTs can gather data on the context of the child user’s physical activity state (e.g., walking, standing, running) and store personalized information (e.g., location and activity pattern) through a camera, microphone, Global Positioning System (GPS), and various sensors such as facial recognition or sound detection. Privacy concerns itself with the protection against the intrusion of someone’s defined space without explicit consent, in such a manner that the defined space is protected from intrusion, interference, and information access by a non-authorized entity. In addition to privacy and safety concerns, criminals using a child’s Personal Identifiable Information (PII) can create false identities to engage in a variety of financial frauds and other crimes. The challenge is, with so many SCTs in the market, how to develop a framework and techniques to protect the privacy of children’s data; and in the case where a privacy breach occurs (cybercrime), how to develop a digital forensic framework to analyze data on SCTs. This thesis surveys the cybersecurity and the privacy landscape of state-of-art emerging technology and development in SCTs; investigates technical and legislative related privacy issues in SCTs with functionalities that collect, process, and transmit PII; and presents a privacy preservation framework that will address privacy challenges within SCTs. In addition, this thesis develops a SCT digital forensic processing framework for privacy breach or crime-related investigation. The privacy preservation framework includes a context data model and a privacy-preserving data-modelling framework. The data context model is an abstract model that organizes elements of data and standardizes how they relate to one another and to properties of the related entities in SCTs based on eXtensible Markup Language (XML). The privacy preservation framework is depicted by Petri-Nets and will identify offensive (non-privacy compliant) content intended for storage or transmission, tag, classify, alerts, and secure delete content. The framework consists of four major components, including (1) Systematic Privacy Impact Assessment Table (SPIAT); (2) Privacy-Preserving Context Ontology (PPCO) Model; (3) SCT privacy preservation data model using Petri-Nets; (4) Empirical Study to support Petri-Nets model as one of the most promising tools to support data flow privacy; and (5) Case studies of SCT digital forensic investigation.


title: Reporting unwanted sexual behavior at a post-secondary institution: an examination of campus policy

contributor:
O'Connor, Christopher
Ammar, Nawal
Alvi, Shahid

subject:
Policy
Sexual assault
Campus sexual assault
Canada

abstract: The Ontario government has made recommendations and proposed legislation to mandate all universities and colleges in Ontario, Canada to create a sexual assault policy that involves student input. Using a small commuter university in southwestern Ontario as a case study, this thesis examines student perceptions of the policy. This research includes two parts. The first part consists of online qualitative research with seventeen students using an open-ended inductive exploratory instrument which asks students to read and define aspects of policy. The objective of this instrument was to verify if students adequately comprehended the language of the policy, knew how to report, who to report to, felt safe reporting, and found the reporting process supportive of their needs. The second part uses Allan’s (2008) policy discourse analysis to investigate replicated power and gender inequalities within the policy as well as policy silences and absences. Student recommendations to the policies are discussed.


title: Risk-modeling tools for designing resilient micro energy grids

subject:
Micro energy grid
Fault diagnosis and prognosis
Risk-modelling
Risk analysis

abstract: Micro energy grid (MEG) is widely used to meet the combined electricity, heating, cooling and natural gas demands for numerous customers’ types. Design of MEGs were extensively introduced in numerous articles, however safety analysis methods for MEG design are not existing so far. This study develops a hazard and operability (HAZOP) matrix for MEGs by proposing a resilience matrix. In addition, it proposes two advanced risk-modeling approaches, namely fault tree and layer of resilience analysis (LORA), for risk and resilience analysis of MEG. Selected independent resilience layers (IRLs) were proposed to achieve a resilient MEG by increasing safety integrity level (SIL). IRLs are applied using co-generation and thermal energy storage (TES) technologies to mitigate the hazards of system failure, increase efficiency, and minimize greenhouse gas emissions. The proposed risk assessment approach aims to design a resilient MEG that has the ability to deal with those potentials efficiently. In addition, an energy risk analysis has been applied to each MEG’s physical domains such as electrical, thermal, mechanical and chemical. These concurrent objectives lead to achieving higher resilience, fewer greenhouse gases emissions, and greater sustains economy. A multi-level hierarchical decision making (MLHDM) is one of the IRLs that are proposed in this study. It aims to boost the MEG’s self-healing features on risks uncertainty of the system operation. The structural design of MLHDM consists of three concurrent levels functioning together to achieve a resilient operation. The simulation results of the proposed resilient MEG infrastructure that combine a selected group of IRLs, shows the ability to work with high level of self-healing capability under various hazardous scenarios as well as meeting the on-demand energy requirement. On the other hand, intelligent reasoning algorithms using Bayesian belief network (BBN) are proposed to accurately and instantaneously estimate risks in MEG. This study introduces a hybridsafety assessment approach for MEG diagnosis by using a combination of ANFIS and BBN techniques. Finally, the validation results of the proposed safety analysis tools reveal promising solution for designing resilient MEGs.


title: Interfaces for alternatives, difference visualizations and collaborative authoring of behavior trees

subject:
Behavior tree
Alternatives
Visualization
Collaboration

abstract: A visual behavior authoring framework for exploring and comparing multiple game AI behavior alternatives is presented. A mixed method study revealed participants rated it higher compared to the control framework. Mostly positive feedback was also obtained in a semi-structured interview and a follow-up qualitative longitudinal study. An extension for collaboration using synchronous and asynchronous modes is also presented. A mixed methods study revealed that collaboration provides improvement over the control condition, but no differences were found between the collaboration modes. In a semi-structured interview, the synchronous mode was revealed to be useful for quick prototyping, while the asynchronous mode – for most other situations. Overall, the results suggest that proposed solutions have a potential to improve the exploration and collaboration for behavior tree development, but further research is necessary.


title: Towards molecular reconstruction in Coulomb explosion imaging

subject: Velocity-map Simplex Asymptotic Alignment Reconstruction

abstract:
The interaction of a fast laser with molecules at the femtosecond time scale, leads to the latter losing most of its valence electrons and become positively charged. The molecule which was initially in an equilibrium state, undergoes internal repulsion which leads to fragmentation of the molecule into constituent ions and other neutral fragments. The unidirectional electric field in lens accelerates the charged ions towards a position-sensitive detector, and their arrivals are based on their charge per mass ratio. The ion with the highest ratio of charge per mass arrives first at the detector; its time-of-flight and position of impact on the detector by the ion is recorded. The same information is recorded for subsequent ions that arrive at the detector.
This research attempts to reconstruct the molecular structure prior to a Coulomb explosion of the ionized molecule using only the information available at the detector. There are broadly two components to the approach examined here: the forward and the backward (inverse) problems. In the forward problem, we develop a model using the classical equations of motion to describe the time evolution of the constituent ions immediately after the fragmentation of the parent molecule. The goal being to accurately reproduce a given impact pattern on the target screen, consistent with the ions time of arrival. The inverse problem uses the positions and time-of-flights of the constituent ions to systematically predict the original molecular structure.
The inverse problem is characterized by a shortage of information from the detector due to the fact that not all the atoms of the molecule become ionized during any particular laser-molecule interaction and the electric field is inhomogeneous. Therefore, one way to reconstruct the initial positions of the photo-fragments is to simulate the inhomogeneous field and reverse the paths of detected ions.


title: Examining the experiences of parents and caregivers of children with autism spectrum disorder around aquatic environments

subject:
Autism spectrum disorder (ASD)
Aquatic
Water
Parent
Swimming lessons

abstract: Through transcendental phenomenological qualitative research we investigated the experiences of parents and caregivers of children with ASD when accessing water environments. Semi-structured individual interviews were used to collect data with 12 parents (N=12). Results were grouped into two clusters. Experiences and perspectives on aquatic environment and recreational swimming included the themes: safety is the priority, attraction to water, acceptance of children with ASD in aquatic environments, and therapeutic benefits. Experiences and perspectives on swimming lessons included the themes; making lesson accessible, teaching methods, teach the teacher, and the impact on pride, independence, and normalcy. Findings suggest participation in water activities has a positive effect on children with ASD. Enrollment in swimming lessons can promote safe encounters with water for children with ASD. Parents identified barriers to accessing aquatic programming. Recommendations are provided for improvements to current swim programming and other aquatic environments.


title: Using music to motivate movement in children aged 4-6 years with autism spectrum disorder

subject:
Autism spectrum disorder
Movement
Music
Intervention

abstract: Autism spectrum disorder (ASD) is an umbrella term used to describe a group of disorders of brain development usually diagnosed in early childhood. Children with ASD experience difficulties in social skills, communication and repetitive or restricted behaviors. Additionally, they often have delays and difficulties with movement skills. Improving movement skills in early childhood may have an impact on the core characteristic of ASD. The aim of this study was to investigate the effects of a 6-week music and movement intervention on the movement, social and adaptive skills of children aged 4-6 with ASD. Nine children aged 4-6 with ASD participated in the study, they were randomly divided into either a music and movement intervention (n=6) or movement intervention without music (n=3), the children participated in the interventions for 2, 45 minute sessions per week. The music group experienced significant improvements in BOT-2 body coordination (p=0.01), BOT-2 total raw scores (p=0.04) and a significant reduction in maladaptive behaviors (p=0.04) (Vineland Adaptive Behavior Scales). The movement group demonstrated significant improvements in social skills (p=0.02) and daily living skills (0.03). The results support the use of music during movement interventions to increase body coordination and reduce maladaptive behaviors.


title: A qualitative exploration of the experience of a single mindfulness session with informal caregivers

subject:
Mindfulness
Informal Caregivers
Qualitative Exploration

abstract:
Introduction: The purpose of the pilot study was to explore informal caregivers’ experience who have completed a short, single mindfulness session. There is evidence to support mindfulness as a non-invasive method for improving psychological and physical well-being.
Methods: The participants (N=6) of the study attended a short, single mindfulness practice session. One-on-one semi-structured interviews were conducted to obtain data and a thematic content analysis method was used for data analysis process.
Results: Six main themes emerged from the obtained data. The identified themes were: 1) comparison of mindfulness to other relaxation methods: 2) initial impression on mindfulness; 3) mindfulness as a relaxation technique; 4) mindfulness as a support for sleep hygiene: 5) mindfulness as an anxiety reduction method and; 6) future integration of mindfulness into daily life.
Discussion: The emerged themes of the study highlighted informal caregivers' perceived effectiveness of mindfulness practice in their daily life, which lays a foundation for future research. Participants perceived a single mindfulness session to be an opportunity to learn a relaxation technique.


title: Stability of heroin metabolites and oxycodone in rat hair and liver during decomposition

contributor:
Forbes, Shari L.
Kelly, Tamsin

subject: Hair Soil Oxycodone Heroin Decomposition

abstract: The aim of this study was to investigate the influence of soft tissue decomposition on the stability of drugs incorporated in hair antemortem. Two burial trials were conducted: in the first trial, rats were administered oxycodone over five days; in the second trial, rats were administered heroin over nine days then drug abstinent for another nine days. After each respective treatment the rats were sacrificed and buried in controlled burial microcosms. Concentrations of oxycodone and selected metabolites or the metabolites of heroin; 6-monoacetylmorphine and morphine, incorporated within rat hair and liver were measured before and during the decomposition process. Oxycodone was analysed in hair and liver samples, while morphine and 6-monoacetylmorphine were analysed in hair samples by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Oxycodone concentrations in both hair and liver decreased as the interment period and decomposition of the carcasses progressed. 6-Monoacetylmorphine was not detected in any hair samples collected from the exhumed carcasses.


title: Automated sleep-wake cycling detection in neonates from cerebral function monitor signals.

subject:
Amplitude-integrated EEG
EEG
Cerebral function monitor
Neonates

abstract: This thesis presents a link between a clinical need involving the analysis of high frequency physiological data and the informatics and technology designed to automate these specific clinical rules. An algorithmic design for the automated detection of sleep-wake cycling patterns in neonates aged 29-44 weeks gestational age via cerebral function monitor signal is presented in this thesis. The design also includes the automation of impedance levels and background classification of electrical activity via cerebral function monitor signal. The relevance of these algorithms is demonstrated within the neonatal intensive care unit as this monitor is commonly used at the bedside of critically ill infants. The design composition determines analyzable and clinically relevant data through the assessment of impedance levels associated with the cerebral function monitor signal, then the overall background classification of the infant’s cerebral electrical activity which indicates whether or not sleep-wake cycling can be present in the signal trace. A third output is the detection of sleep-wake cycling. Current practice in an intensive care setting involves the meticulous and time-consuming process of manual interpretation by a health care professional, subsequently the automation of these processes has the potential to reallocate the use of resources in the form of staff, increase the rate at which the current practice takes place, improve the timing of medical intervention to allow for maximal neurological development in patients as well as facilitate comprehensive analysis with other physiological data streams in unison to deliver enhanced decision making. Performance of the algorithms in comparison to expert clinical annotation resulted in concordance values of 95.70% for impedance, 78.49%, 81.25% sensitivity and 75.32% specificity for sleep-wake cycling and finally 76.34% for background classification. Through this retrospective analysis of de-identified patient data it was determined that this can be applicable to a real-time computer software environment enabled by stream computing.


title: Using machine learning methods to aid scientists in laboratory environments

contributor:
Tamblyn, Isaac
van Veen, Lennaert

subject:
Machine learning
Deep learning
Neural networks
Reinforcement learning
Bayesian Modelling

abstract: As machine learning gains popularity as a scientific instrument, we look to create methods to implement it as a laboratory tool for researchers. In the first of two projects, we discuss creating a real-time interference monitor for use at a radio observatory. We show how deep neural networks can be used to assist with the detection of radio-frequency interference around the site, and consider methods of unsupervised learning to identify patterns in the detections. In the second project, we show how a reinforcement learning agent can build an internal hypothesis of its environment, using experience from past measurements, that it can then act on. We demonstrate how our newly developed method can be used to learn the dynamics of physics-based models and exploit the knowledge gained to achieve a given objective with measurable confidence. We also demonstrate how the agent's behaviour changes when the frequency of certain measurements is limited.


title: Evidence-based claims adjudication:  a technology-based learning tool for automobile insurance claims adjusters

subject:
Automobile insurance
Clinical practice guidelines
Instructional design
Pedagogy
Technology-based learning

abstract: My thesis aimed to 1) develop an evidence-based claims adjudication framework for automobile insurance claims adjusters; 2) develop a technology-based learning (TBL) tool to train Aviva Canada claims adjusters about evidence-based claims adjudication and the evidence-based management of neck pain; and 3) evaluate the learning, design and engagement constructs of the tool. I adapted Sackett’s evidence-based medicine framework for claims adjudication. I conducted a systematic review of the literature to determine the effectiveness of TBL tools to improve claims adjusters’ knowledge of clinical practice guidelines. I developed an online, asynchronous, self-directed, module-based curriculum. I evaluated the learner-centered constructs of the TBL tool in a sample of adjusters using a validated questionnaire. Results indicated the majority of participating adjusters agreed with the learning, design and engagement constructs of the TBL tool. My research can be used to inform future development of online tools to educate and train adjusters about clinical evidence.


title: An Online System for Visualizing UOIT Class Schedules

abstract:
The objective of this thesis is to design a system that will enable users to visualize aspects of a schedule so that the information can be interpreted in a meaningful way. The concept of visualizing data has allowed many possible forms such as graphs, time tables, maps, etc. In order to make the results of this thesis more accessible it was decided early on to switch to a web-based implementation. This way a wide audience of faculty or students of the school could have access this information and allow for the project to have a larger scope.
Implementations for displaying data include tables, a week calendar view, a week time table view with classes sized to represent time, and coloured bar graphics to represent capacity and time based on spatial location. In addition to the method of displaying schedule information the data to display has been focused on a few different areas of: courses, rooms, and capacity. Displaying lists of courses as well as being able to connect courses to professors resulted in the calendar view. The need for room schedules resulted in the time table to better display the information and help with the availability visualization at the same time. However the availability of several rooms or several professors was not capable with the calendar or time table view, so this resulted in more abstract methods of attempting to display availability data.  Availability is displayed using generated graphics of coloured bars representing classes with their colour representing capacity.
Another requirement besides the visualization part of each piece of the thesis was the accessibility. Being a web-based program the project to be flexible such as allowing different parameters to customize results, as well as being easy for the average user to navigate. Methods such as connecting different colours for each visualization, breadcrumbs, tooltips, clickable areas to display more information and easy menu selections were included in the thesis webpage.  This project has iterated over several different designs through web pages and visualization to attempt to find the most flexible method of presenting the collected information.


title: Utilization of thermal plasma for conversion of thermoplastic waste to oil products in a pyrolysis reaction

subject:
DC thermal plasma
Pyrolysis
Thermoplastic recycling
Pyrolysis oil

abstract: Chemical recycling of waste plastics has gained attention in last decade with nearly 170 million tonnes of deposited waste plastics annually. A chemical process known as pyrolysis converts thermoplastic waste to oil products. In this research work, direct current thermal plasma is designed and used as a heating source for a pyrolysis reaction with nearly 30 minutes residence time. Diesel range oil is produced with 59 wt % conversion yield including small traces of gasoline. The DC Thermal plasma used has power of 270 W and emits temperature between 625 ℃ and 860 ℃ in pyrolysis reaction. Aspen HYSYS simulation and economic analysis of a 10 tonne per hour pyrolysis chemical plant is illustrated.

abstract: University of Ontario Institute of Technology


title: Adaptive engagement of older adults’ fitness through gamification

contributor:
Mirza-Babaei, Pejman
Nacke, Lennart

subject:
Gamification
Motivation
Motivational affordances
Physical activity
User experience design

abstract:
Older adults are often not physically active because they lack motivation, time, and/or physical ability. Not only does this impact the life of older adults, but it also affects society as a whole, because the cost of healthcare attached to maintaining the health of older adults is continually rising. This thesis addresses the problem by investigating the disenchantment of older adults with physical activity (PA), reasons for their lack of participation in PA, and contributes motivational affordances for PA. This thesis makes three important contributions to human-computer interaction: a) the development of adaptive engagement guidelines for PA technology for older adults. b) the Exercise Motivation Technology Framework (EMFT) - a framework to aid in the design and development of PA technology for older adults, and c) the Kaleidoscope of Effective Gamification (KEG) - a design and analysis tool for helping designers design and develop gamified apps.
These contributions were achieved through a phased investigative approach. The analysis of preliminary studies (Phase 1) resulted in the development of the EMTF for older adults PA technology. A survey study (Phase 2) on the preferences of motivational affordances for PA across different age groups suggested that ‘health pressures’ and ‘ill-health avoidance’ were significant exercise motives for PA in different age groups. Age-differentiated guidelines from Phase 2 were used to develop and evaluate Spirit50 (Phase 3), a gamified technology artifact, specifically developed under my supervision for adults over 50 years of age. Phase 4 was a synchronous, three-condition (gamified, non-gamified, and control groups) experimental study over an eight-week period with a total of 30 participants. Expert evaluation (Phase 5) to review technology facilitation of PA using the Spirit50 app also pointed to the usefulness and the applicability of gamification as a behaviour change technology for delivering PA solutions for older adults.
The findings of this thesis contribute to understanding PA motivation among older adults on a granular level from a technology facilitation standpoint using gamification strategies. The EMTF model helped to design PA technology by combining desirability, customization, and motivational affordances for older adults. Finally, this thesis contributes to tailoring and personalizing of adaptive engagement strategies using specific gamification elements like goals supported by challenges, selection of quests based on ability, progressive feedback, and rewards validating performance and efforts as potential ways to deliver age-centric PA technology for older adults


title: Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI)

subject: Explainable Artificial Intelligence (XAI)

subject: LIME

subject: Multi-scale explanations

subject: Parameter-free weighting framework

abstract: The recent success of deep neural networks has generated a remarkable growth in Artificial Intelligence (AI) research, and it received much interest over the past few years. However, one of the main challenges for the broad adoption of deep learning based models such as Convolutional Neural Networks (CNN) is the lack of understanding of their decisions. Local Interpretable Model-agnostic Explanations (LIME) is an explanation method which produces a coarse heatmap as a visual explanation highlighting the most important superpixels affecting the CNN’s decision. This thesis aims to explore and develop a multi-scale scheme of LIME to explain decisions made by CNN models through heatmaps of coarse to finer scales. More precisely, when LIME highlights large superpixels from the coarse scale, there are some tiny regions in the corresponding superpixel that influenced the model’s prediction at the finer scale. Therefore, we propose a multi-scale scheme of LIME and two weighting approaches based on Gaussian distribution and a parameter-free framework to produce visual explanations observed from different scales. We investigated the proposed multi-scale scheme on Flower Dataset from TensorFlow and a biological dataset, Camelyon 16. The results prove that the explanations are faithful to the underlying model, and our visualizations are reasonably interpretable.