Innovative Projects Realized

WP 1.1.8 – Metro Reach Silicon Photonic Integrated Transceiver

Driven by cloud based applications and services, there are substantial worldwide research and commercialization efforts that are being directed toward improving the capacity of intra- and inter-data center networks. Intra-data center networks operate in the O-band (1260-1360 nm) over distances ranging from 0.5 m to 20 km, and inter-data center networks operate in the C-band (1530-1565 nm) over distances ranging from 20 km to 160 km. While these two systems share similar constraints in terms of power consumption, footprint, and cost of the employed optical transceivers, they are distinct because of the differing operating wavelengths (e.g., the dispersive properties of fibers in the C-band). Enabled by original silicon photonic circuit designs and innovative packaging, the proposed research will address key challenges in data center networks, namely increasing the capacity whilst decreasing the power consumption, size, and cost of optical transceivers deployed in these networks.

Fault detection and severity assessment for gearboxes

The gearbox is a classical mechanical unit and has been widely used in modern power transmission systems. Fault detection and severity assessment of gearboxes prior to their failure can prevent the sudden failure of gearboxes, as well as enable condition-based maintenance and thus reduce maintenance costs. However, the fault detection and severity assessment are challenging when the gearbox operates under time-varying rotational speed (TVRS) conditions. Unlike the constant speed condition, the condition monitoring data, e.g., vibration, becomes non-stationary due to amplitude and frequency modulations induced from TVRS. Conventional signal processing and analysis tools are no longer applicable. Advanced signal analytic algorithms are in demand. This project aims at proposing an advanced statistical time series model to globally represent the gearbox vibration signal under TVRS. Fault detection and severity assessment objectives are subsequently achieved. The hypothesis is that the time series model-based method will have an improved fault detection rate and severity assessment accuracy compared with existing methods. The result of this project will fundamentally benefit the safety, maintenance and operation of power transmission systems.

Data Analysis and Consolidation for Aircraft Parts Manufacturing

Avcorp Industries provides the world’s leading aircraft manufacturers with supply chain solutions and repair support. Yield optimization, predictive maintenance, and equipment calibration are needs that are widespread throughout the manufacturing industry. The root cause of failures in product testing is often difficult to determine particularly when the failure signals are sparse relative to the available background data. Compounding the problem, the process must meet a variety of specifications for multiple customers simultaneously. This project aims to create a digital twin of the metal finishing line to leverage predictive analytics to analyze data (chemical, temperature, voltage) captured from the process line and provide new insights for an optimized manufacturing process. Leveraging the research capabilities in data analytics at Simon Fraser University, and partnership with D-Wave and SolidStateAI, Avcorp will move manufacturing fault detection processes from reactive to predictive-based. TO BE CONT’D

Compressed Supersymmetric Spectra at the Large Hadron Collider (LHC)

With the discovery of the Higgs boson, the Standard Model (SM) is complete. Experimental results, even precision tests involving higher order perturbative quantum chromodynamics (QCD) calculations, appear to confirm SM results. However, SM cannot be the final theory, and the quest for physics beyond the SM is very much alive. Of the beyond the SM scenarios, supersymmetry (SUSY) appears to be the most popular. Unfortunately, no signals of any new model, and in particular of supersymmetry, have been observed at the Large Hadron Collider (LHC). Given that no supersymmetry signals have been observed at the LHC, and the fact that constrained theories which can explain dark matter predict no visible signals at the LHC, it would appear useful to study extended versions of minimal supersymmetric standard model (MSSM). Supersymmetric secluded U(1)’ model with 3 additional scalars and neutralinos, in addition to the usual supersymmetric U(1)’ model spectrum gives rise to many more possibilities for compressed spectrum. That is, charginos, neutralinos and sleptons and sneutrinos would be light and close by, while the rest of the particles would be heavy. TO BE CON’T

Machine-Learning-Based Artistic Photo Manipulation and Stylization on Mobile Devices

Recent advances in using machine learning for object recognition and image manipulation have resulted in a new and emerging market for mobile applications that use machine learning for creating a variety of new artistic expressions. This research will develop a framework for performing machine-learning-based photo and video manipulation on mobile devices with the goal of integrating it with the Generate Toolkit. This proposal follows previous MITACS internships between the same partners and further extends our objectives. In the previous iterations of this project, we developed a fast, on-device style transfer library for both iOS and Android systems and started developing a user-interface to train machine learning models for style transfer, facilitating the exploration of the parameter space of the models within a computer-assisted creativity paradigm. Our main objectives for this internship term involves three tasks. TO BE CONT’D

Brain Imaging Biomarkers Type 2 Diabetes and Stroke

Adult onset diabetes, or type 2 diabetes, is becoming more common in Canada and across

the world. And it is a risk factor for stroke. For example, silent strokes lesions are common in

adults with type 2 diabetes. Despite this knowledge, we do not have a very good

understanding as to how type 2 diabetes affects the brain. We are proposing 2 internships

that will make use of magnetic resonance imaging to specifically address type 2 diabetes

effects in the brain. And we are also proposing new software tools that can be used to look at

brain connections, which is applicable to studying type 2 diabetes and stroke. Intern 1 will

focus on grey matter structure and blood vessels in the brain. Intern 2 will focus on grey

matter connections in the brain. Both internships involve developing software that will

facilitate clinical translation. In so doing we will foster collaboration between the intership site

(Baycrest) and the academic site (Sunnybrook)…….TBC

At-a-station measurement and prediction of flow and sediment fluxes in rivers

This project will make a major contribution to improve channel rehabilitation projects, which are reconstructing streams to imitate the natural form of the stream. These projects are very costly and their failure can cause high financial losses. The results of this project will lead to a decrease or elimination of the financial losses by improving the design of restored channels. In addition, this project will improve protection of the species-at-risk “Redside Dace” by improving the accuracy of monitoring the deleterious sediments entering their habitat.

High-throughput design and synthesis of novel nanomaterials for Li-ion batteries

This research project seeks to develop new low-cost and abundant materials for energy storage, like batteries, with an improved performance. The work will include the design, synthesis and characterization of the new materials, and, ultimately, will use them in fully functional devices. The project will focus in novel ways of combining elements and alloys with high conductivity in order to eliminate the expensive materials used nowadays in commercial batteries.
Based on the previous work done at the Toronto facilities, combinations known of metals such as Iron, Cobalt, Nickel and Tungsten will be put to the test so that the battery can attain higher voltage than the ones conceived presently.
The student will participate in computational materials design, building the machine learning models to describe the obtain data, materials synthesis in a high-throughput robotic system, materials characterization and battery testing. All experimental training on material fabrication and characterization will be provided in place.

Advancing biological phosphorus removal from wastewater using applied genomics

Wastewater can be damaging to the environment if left untreated. Microorganisms play important roles in removing harmful pollutants, such as organics and nutrients, within wastewater treatment plants. For instance, certain wastewater bioreactor designs promote the growth of specialized microbes that sequester phosphorus into their cells, which prevents harmful algal blooms in natural waters and enables sustainable nutrient recovery as fertilizer. Yet, we currently understand little about the types of microorganisms within these treatment processes, and what types of metabolisms they are performing. Such information is direly needed to develop engineering solutions that recover resources from waste and improve environmental water quality. This research will employ new genomics-based techniques to study the microorganisms that are active within a novel wastewater treatment process that AECOM is developing in partnership with the City of Penticton (British Columbia). TO BE CONT’D

Operational complexity in accounting research : measurement(s) and impacts

This project aims to find a better way to measure operational complexity for multi-segments firms, under an accounting perspective. Complexity is an important matter for accounting as many studies have documented how complex firms are harder to analyze for many stakeholders (financial analysts, auditors, regulators). Basically, operational complexity is currently proxied by the number of business segments in which a firm operates. This measure is incomplete because it does not account for the distance between segments – how they are related to each other – and their respective weight – what proportion of firm’s total sales they represent. Overall, this research project aims to find a better way to measure operational complexity in order to better the impact of complex firms on the main users of financial statements.

Inhibition du virus de l’hépatite B

L’hépatite B est un virus. Un virus utilise le matériel biologique de son hôte pour exister. L’hépatite B affecte chroniquement environ 240 millions de personnes à travers le monde. C’est conséquemment une pathologie de premier l’ordre lorsque l’on évoque la santé publique.
Ce virus affecte sans précédent la qualité de vie des gens qu’il parasite. Ce dernier affecte le foie d’où son nom « hépatite ». Contrairement à l’hépatite C, l’hépatite B ne requiert que 4 gènes virales pour se répliquer. Trouver un remède est alors difficile dû à sa dépendance biologique discrète dû à son mode de réplication. Autrement dit, ses interactions avec les cellules sont faiblement notoires. De plus, lors de la conception d’un remède, il faut penser aux effets secondaires de celui-ci. TO BE CONT’D

The Epidemiology of Fabry Disease and Metabolic Acidosis in Manitoba

The proposed project is for the postdoctoral fellow to access healthcare data for individual adults in the province of Manitoba in order to: 1) determine the rates of metabolic acidosis in Manitoba along with associated outcomes and risk factor profiles and 2) identify patients in Manitoba who are at high risk of Fabry disease but currently undiagnosed in order to facilitate disease screening and improve patient care. The postdoctoral fellow will use their statistical and programming expertise to link various datasets of physician visits, hospitalizations, laboratory results and drug prescriptions via a scrambled patient health number that is tied to a unique patient but unidentifiable to any researcher so to protect privacy. The postdoctoral fellow will conduct statistical analyses and then will compile their results into several reports complete with text, tables and figures to be presented to our clients. They will also create manuscripts based on their reports that will be suitable for publication in an academic medical journal. This project will help the partner (CDIC) understand the epidemiology of important chronic diseases, provide synergies with ongoing clinical trials conducted at CDIC, and will help establish CDIC as a capable research partner within the pharmaceutical industry.