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Full-Text Articles in Physical Sciences and Mathematics

Fabrication And Modification Of Titania Nanotube Arrays For Harvesting Solar Energy And Drug Delivery Applications, Ahmed El Ruby Abdel Rahman Mohamed Dec 2017

Fabrication And Modification Of Titania Nanotube Arrays For Harvesting Solar Energy And Drug Delivery Applications, Ahmed El Ruby Abdel Rahman Mohamed

Electronic Thesis and Dissertation Repository

The fast diminishing of fossil fuels in the near future, as well as the global warming caused by increasing greenhouse gases have motivated the urgent quest to develop advanced materials as cost-effective photoanodes for solar light harvesting and many other photocatalytic applications. Recently, titania nanotube arrays (TNTAs) fabricated by anodization process has attracted great interest due to their excellent properties such as: high surface area, vertically oriented, highly organized, one-dimensional, nanotubular structure, photoactivity, chemical stability and biocompatibility. This unique combination of excellent properties makes TNTAs an excellent photoanode for solar light harvesting. However, the relatively wide band gap energy of …


Gamma-Radiation Induced Corrosion Of Alloy 800, Mojtaba Momeni Nov 2017

Gamma-Radiation Induced Corrosion Of Alloy 800, Mojtaba Momeni

Electronic Thesis and Dissertation Repository

This thesis presents a newly developed mechanism and predictive model for the corrosion of Alloy 800. The Fe-Cr-Ni Alloy (Incoloy 800) is mainly used for steam generator (SG) tubing in CANDU and PWR reactors and is a candidate material for the proposed Canadian Supercritical Water Reactor (SCWR) in which it will be exposed to extreme conditions of high radiation flux and large temperature gradients. The influence of gamma radiation and water chemistry conditions on the corrosion behaviour of Alloy 800 are studied in this work. Ionizing radiation creates reducing (•eaq, •H, •O2-) and oxidizing …


Secure Integer Comparisons Using The Homomorphic Properties Of Prime Power Subgroups, Rhys A. Carlton Aug 2017

Secure Integer Comparisons Using The Homomorphic Properties Of Prime Power Subgroups, Rhys A. Carlton

Electronic Thesis and Dissertation Repository

Secure multi party computation allows two or more parties to jointly compute a function under encryption without leaking information about their private inputs. These secure computations are vital in many fields including law enforcement, secure voting and bioinformatics because the privacy of the information is of paramount importance.

One common reference problem for secure multi party computation is the Millionaires' problem which was first introduced by Turing Award winner Yao in his paper "Protocols for secure computation". The Millionaires' problem considers two millionaires who want to know who is richer without disclosing their actual worth.

There are public-key cryptosystems that …


Crystal Engineering Of Active Pharmaceutical Ingredients With Low Aqueous Solubility And Bioavailability, Jenna M. Skieneh Aug 2017

Crystal Engineering Of Active Pharmaceutical Ingredients With Low Aqueous Solubility And Bioavailability, Jenna M. Skieneh

Electronic Thesis and Dissertation Repository

Approximately 75% of new molecular entities approved by the Food and Drug Administration (FDA) for use in the pharmaceutical industry are found to have poor aqueous solubility. This undesirable attribute leads to consequences such as higher doses required to reach therapeutic levels, greater vulnerability to food effects, lesser fraction absorbed in the small intestine and damage to the environment due to increased quantity of excretion. The addition of an excipient (i.e. a FDA approved inactive ingredient) to the molecular structure of an active pharmaceutical ingredient (API) through intermolecular bonding is of growing interest because the properties of the API can …


Machs: Mitigating The Achilles Heel Of The Cloud Through High Availability And Performance-Aware Solutions, Manar Jammal Apr 2017

Machs: Mitigating The Achilles Heel Of The Cloud Through High Availability And Performance-Aware Solutions, Manar Jammal

Electronic Thesis and Dissertation Repository

Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their …


Metafork: A Compilation Framework For Concurrency Models Targeting Hardware Accelerators, Xiaohui Chen Mar 2017

Metafork: A Compilation Framework For Concurrency Models Targeting Hardware Accelerators, Xiaohui Chen

Electronic Thesis and Dissertation Repository

Parallel programming is gaining ground in various domains due to the tremendous computational power that it brings; however, it also requires a substantial code crafting effort to achieve performance improvement. Unfortunately, in most cases, performance tuning has to be accomplished manually by programmers. We argue that automated tuning is necessary due to the combination of the following factors. First, code optimization is machine-dependent. That is, optimization preferred on one machine may be not suitable for another machine. Second, as the possible optimization search space increases, manually finding an optimized configuration is hard. Therefore, developing new compiler techniques for optimizing applications …


P26. Global Exponential Stabilization On So(3), Soulaimane Berkane Mar 2017

P26. Global Exponential Stabilization On So(3), Soulaimane Berkane

Western Research Forum

Global Exponential Stabilization on SO(3)


Directed Acyclic Graph Continuous Max-Flow Image Segmentation For Unconstrained Label Orderings, John Sh Baxter, Martin Rajchl, A. Jonathan Mcleod, Jing Yuan, Terry M. Peters Feb 2017

Directed Acyclic Graph Continuous Max-Flow Image Segmentation For Unconstrained Label Orderings, John Sh Baxter, Martin Rajchl, A. Jonathan Mcleod, Jing Yuan, Terry M. Peters

Robarts Imaging Publications

Label ordering, the specification of subset–superset relationships for segmentation labels, has been of increasing interest in image segmentation as they allow for complex regions to be represented as a collection of simple parts. Recent advances in continuous max-flow segmentation have widely expanded the possible label orderings from binary background/foreground problems to extendable frameworks in which the label ordering can be specified. This article presents Directed Acyclic Graph Max-Flow image segmentation which is flexible enough to incorporate any label ordering without constraints. This framework uses augmented Lagrangian multipliers and primal–dual optimization to develop a highly parallelized solver implemented using GPGPU. This …


Design Of Radio-Frequency Arrays For Ultra-High Field Mri, Ian R O Connell Jan 2017

Design Of Radio-Frequency Arrays For Ultra-High Field Mri, Ian R O Connell

Electronic Thesis and Dissertation Repository

Magnetic Resonance Imaging (MRI) is an indispensable, non-invasive diagnostic tool for the assessment of disease and function. As an investigational device, MRI has found routine use in both basic science research and medicine for both human and non-human subjects.

Due to the potential increase in spatial resolution, signal-to-noise ratio (SNR), and the ability to exploit novel tissue contrasts, the main magnetic field strength of human MRI scanners has steadily increased since inception. Beginning in the early 1980’s, 0.15 T human MRI scanners have steadily risen in main magnetic field strength with ultra-high field (UHF) 8 T MRI systems deemed to …


An Ensemble Learning Framework For Anomaly Detection In Building Energy Consumption, Daniel B. Araya, Katarina Grolinger, Hany F. Elyamany, Miriam Am Capretz, Girma T. Bitsuamlak Jan 2017

An Ensemble Learning Framework For Anomaly Detection In Building Energy Consumption, Daniel B. Araya, Katarina Grolinger, Hany F. Elyamany, Miriam Am Capretz, Girma T. Bitsuamlak

Electrical and Computer Engineering Publications

During building operation, a significant amount of energy is wasted due to equipment and human-related faults. To reduce waste, today's smart buildings monitor energy usage with the aim of identifying abnormal consumption behaviour and notifying the building manager to implement appropriate energy-saving procedures. To this end, this research proposes a new pattern-based anomaly classifier, the collective contextual anomaly detection using sliding window (CCAD-SW) framework. The CCAD-SW framework identifies anomalous consumption patterns using overlapping sliding windows. To enhance the anomaly detection capacity of the CCAD-SW, this research also proposes the ensemble anomaly detection (EAD) framework. The EAD is a generic framework …


Deep Neural Networks With Confidence Sampling For Electrical Anomaly Detection, Norman L. Tasfi, Wilson A. Higashino, Katarina Grolinger, Miriam A. M. Capretz Jan 2017

Deep Neural Networks With Confidence Sampling For Electrical Anomaly Detection, Norman L. Tasfi, Wilson A. Higashino, Katarina Grolinger, Miriam A. M. Capretz

Electrical and Computer Engineering Publications

The increase in electrical metering has created tremendous quantities of data and, as a result, possibilities for deep insights into energy usage, better energy management, and new ways of energy conservation. As buildings are responsible for a significant portion of overall energy consumption, conservation efforts targeting buildings can provide tremendous effect on energy savings. Building energy monitoring enables identification of anomalous or unexpected behaviors which, when corrected, can lead to energy savings. Although the available data is large, the limited availability of labels makes anomaly detection difficult. This research proposes a deep semi-supervised convolutional neural network with confidence sampling for …


A Gamification Framework For Sensor Data Analytics, Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz Jan 2017

A Gamification Framework For Sensor Data Analytics, Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz

Electrical and Computer Engineering Publications

The Internet of Things (IoT) enables connected objects to capture, communicate, and collect information over the network through a multitude of sensors, setting the foundation for applications such as smart grids, smart cars, and smart cities. In this context, large scale analytics is needed to extract knowledge and value from the data produced by these sensors. The ability to perform analytics on these data, however, is highly limited by the difficulties of collecting labels. Indeed, the machine learning techniques used to perform analytics rely upon data labels to learn and to validate results. Historically, crowdsourcing platforms have been used to …