Innovative Projects Realized

The translation and research of a sanskrit manuscript:Vajravali

My research is focused on the proofreading and translation of the sanskrit manuscripture Vajr?v?li,a ritual compendium compiled by the famous abbot of Vikrama?ila monastery, Abhay?karagupta. Vajr?v?li has mainly introduced the process of drawing a mandala.The so-called “mandala” is a pantheon of tantric buddhism,which can be classified into the “drawn mandala”(lekhyamandala) and “envisaged mandala”(bhavyamandala). The objective of my project is to make a critical edition of the sanskrit version of Sutranavidhi and Rajahpatanavidhi with the help of three sanskrit manuscripts and then translate them into Chinese. The outcome of my research will be a critical sanskrit version with its Tibetan version and my Chinese translation.

Optizing/Maximizing HPV Vaccine Strategies to Minimize HPVInfections for Canadians

The human papillomavirus (HPV) infects 75% of Canadians today and causes ailments such as warts

and cancers. The newly approved vaccine, Gardasil, is being used across Canada to prevent

infection of HPV and therefore stop the development of genital warts and cancers. Each province is

given the responsibility of developing a vaccine program and implementing it. When the programs

were first introduced in 2007, they differed across provinces by the age of children who were receiving

the vaccine, how many doses were given and the proportion of children in each province vaccinated.

Since Health Canada approved the vaccine for males in 2010, the program component of which

gender(s) to vaccinate can now be added. We use mathematical modeling techniques to consider

these factors to develop the most effective vaccine program to minimize the number of infections for

each province and territory. The partner organization, the Public Health Agency of Canada, will benefit from this research by (i)

gaining knowledge of….

Nanocomposites as Multifunctional Structure for Space Radiation Shielding

During interplanetary travels, space radiations are always crucial to spacecraft design due to their extreme hazards to human beings and electronics. Conventional materials, such as aluminum and other heavy metals, have been widely used on spacecraft. The cost of launching overweighed items to space is still high even reusable rockets are available now. Reducing weight of shielding structures on spacecraft will largely benefit future space missions. Nanocomposites with extreme low density but high radiation shielding properties are proposed in this project. Their porous structure is suitable to craft functions from other nanomaterials into the nanocomposite by advanced technologies. High radiation shielding effectiveness, mechanical strength, thermal properties and low outgassing will be achieved by this innovative nanocomposite. The prototype of this state-of-art space radiation shielding material will lead the company to be more competitive and further height in value.

Developing effective eDNA tools for environmental monitoring at MOWI salmon aquaculture sites in Atlantic Canada

This project addresses a major challenge in ensuring the sustainability of the salmon aquaculture industry: how to reliably monitor the effects of organic waste (excess feed and feces) on the surrounding marine environment, in an environmentally-friendly way.

Synthesis of Thiol-PEG-PBS-grafted gold nanoparticles for the treatment of head-and-neck cancers

Cancer represents a major public health problem, representing about 13% of deaths worldwide, accounting for more than seven million deaths a year. Surgical excision, chemotherapy, and radiotherapy encompass the forefront of antineoplastic therapy; however, it is well known the numerous adverse effects related to these therapeutic modalities. Some treatments have enough potential to help or replace conventional treatments, such as Magneto hyperthermia and Photodynamic therapy. These require the development of new materials at the nanoscale, that can carry out the loading of its components and that present the characteristics of biocompatibility necessary for biomedical applications. In this context, the objective of the work is to develop a release mechanism based on gold nanoparticles coated with HS-PEG-PBS to enhance the treatment of head and neck cancer. The system consists of the synthesis of gold nanoparticles that will be coated with the HS-PEG-PBS copolymer. Subsequently, three experimental groups will be produced: Group 1 consists of the incorporation of perillyl alcohol, which will function as a chemotherapeutic agent, to the coated gold particle; The second group consists of the incorporation of the photosensitizing agent into the particle; In the third group will be encapsulation of both drugs to the particle.

D2K+: Deep Learning of System Crash and Failure Reports for DevOps

The objective of this project is to develop techniques and tools that leverage artificial intelligence to automate the process of handling system crashes at Ericsson, one of the largest telecom and software companies in the world, and where the handling of crash reports (CRs) and continuous monitoring of key infrastructures tend to be particularly complex due to the large client base the company serves. In this project, we will explore the use of deep learning algorithms to classify CRs based on a variety of features including crash traces, CR descriptions, and a combination of both. Crashes in the same group can be processed in a similar way, reducing the time to process each crash separately. In addition, we will conduct qualitative studies in order to understand the relationship between CRs and faults, providing Ericsson teams with the ability to prioritize problems, collect statistics, and gain actionable insights into their deployed systems. Furthermore, this project will be essential in conducting root cause analysis of faults and crashes, developing organizational guidelines for CR reporting, and setting the ground work for powerful operational intelligence capabilities.

Conservation Planning for the Wells Barkerville Community Forest

The Wells-Barkerville Community Forest (WBCF) is a small, 4300 ha forest in the BC interior wet-belt forest with important value economically and ecologically, and for contributing to the quality of life and the continued ability to attract tourists to the region. The purpose of this project is to work with the WBCF to conduct conservation planning activities to help:
1) identify locations of critical value;
2) examine ecological connectivity within the Forest and ecoregionally; and
3) build capacity within the Forest communities, to inform planning and management as well as initiatives to improve connectivity and resiliency within the region.

Restoration Opportunities for the Lost Creeks of South Etobicoke

Extensive development in south Etobicoke resulted in creeks historically viewed as a nuisance being buried, culverted or piped underground. However, creeks don’t just disappear, during large rainfall or snowmelt events. These buried creeks have been found to be a catalyst for flooding and reduce water quality because of reductions in storage and absorption of stormwater run-off over vegetated surfaces resulting in a ‘flashy’ response to stormwater. This project will investigate restoration options for the remnant portions of the lost creeks and investigate green infrastructure (i.e. stormwater ponds, or rain gardens) alternatives to stormwater management for areas contributing runoff to the lost creek network. The overall goal of this research project is to identify potential solutions to reduce negative impacts on water quality and quantity, while improving the ecological and societal value of the lost creeks.

Correction du biais de la sous-captation des précipitations et séparation des précipitations et séparation des précipitations solides et liquides

La prévision des apports en eau dans les bassins versants du parc de production d’Hydro-Québec est très importante car elle permet de quantifier la production hydro-électrique. Pour faire ces prévisions, on utilise des modèles hydrologiques qui sont alimentés par plusieurs données climatiques dont les plus importantes sont les précipitations. Une meilleure prévision repose sur la qualité de ces données. De nombreuses travaux scientifiques et notamment le dernier rapport produit par l’Organisation Météorologique Mondiale, indiquent une sous-captation des précipitations en hiver par les appareils de mesure que sont les précipitomètres. Il est aussi démontré qu’il est très difficile de discriminer les phases solides et liquides des précipitations quand les températures sont proches de zéro. Grâce à ce projet, on va arriver à résoudre ces deux problématiques en développant des techniques automatiques de correction qui seront appliquées à tous les précipitomètres repartis sur les bassins versants. On disposera alors de données de qualités qui seront utilisés par les modèles hydrologiques pour une meilleure prévision des apports en eaux mais aussi une meilleure planification de la production et d’assurer la sécurité des installations et de minimiser les déversements non productibles.

Towards Developing Trust in Online Third-Party Reporting Systems for Survivors of Sexual Assault

Over 600,000 sexual assault happen in Canada every year, however, 95% of sexual assault go unreported. We are working towards building a research-based online third-party reporting system that will aid the reporting of sexual assault. Survivors will now have the opportunity to document their evidence and experiences and submit the report at their own convenience. VESTA is committed to building research backed technology that draws on the principles of building technology for good. In all development of technology, we will consider the broader social context of our products and services, and make this consideration part of our ethos. This means, among other considerations, taking into account the privacy concerns of potential users. VESTA will benefit from the research by incorporating the findings in our product development.

Health Records over Blockchains – Year Two

It is hard to understate the critical role access to a patient’s comprehensive medical history plays in diagnosing (and treating) patient illness. For a doctor, knowing the latest prescribed drugs of his patient might, for example, point directly to the cause of an illness — which might be just a drug side effect. Yet patients often do not know the names of the drugs they take or even the dates of surgeries and other medical procedures.

A Health register covers the entire log of patient medical treatments, from surgeries through periodic health check-ups and other medical interventions. These records are commonly paper registers, smart cards or online private databases, often owned by hospitals, and not always available on need. Publicly sharing these databases could address the problem — but it would create a new one by violating personal privacy (and Canadian privacy laws).

This project intends to employ blockchain technology to develop a platform that can integrate health registers and enable hospitals and other medical service providers to access health registers securely and promptly. Notwithstanding, the technology we are going to develop is applicable in various research fields.

Automated malware detection using supervised machine learning

Malware is one of today’s biggest computer security problems. Traditionally, malware is detected by inspecting its signature, which is a unique identifier of the software’s binary. Signature-based malware

detection is becoming less effective as cyber criminals mutate the malware they design, where the malware is programed in such a way that simply comparing its signature to known malware signatures

will not identify it as being malicious. Thus, new detection techniques inspect the behavior of the software instead, where an algorithm is used to learn the patterns of malware activities. Usually, this

is achieved by using supervised machine learning, where the malware detection system, called the classifier, is trained using already identified malware samples. In this research project, we propose to

design, implement and diagnose a supervised machine learning architecture for automating malware detection at Sophos Inc., one of the leading anti-malware software vendors.