Blockchain is a decentralized and immutable data structure. The information stored on blockchain is tamper-resistant, immutable and transparent. Blockchain is an interesting platform for managing digital certificates without a central authority. Because paper certificates can be easily faked or tampered with modern computer skills. Additionally, using a central authority for issuing distributing certificates is inefficient.
In this project, we will analyze the security and scalability of different approaches to certificate management solutions using blockchain.
Understanding of Earth history involves many approaches. In the case of this project, the focus is understanding the distribution (paleogeography) of ancient shallow-marine and coastal environments of Alberta and Saskatchewan during the Lower Cretaceous. The Grand Rapids Fm represents an important interval that occupies a crucial location for resolving the history of such environments, particularly those relevant to the oil sands-bearing McMurray Fm and the heavy oil-bearing Lloydminster area units.
This project is a collaboration between NORSAT International Inc. and Laboratory for Alternative Energy Conversion (LAEC) at SFU to commercialize novel and efficient cooling solutions for NORSAT ATOM series BUCs and SSPAs. NORSAT amplifiers are typically 15-20% efficient meaning up to 85% of the applied electrical power is dissipated as heat. The heat is removed by means of several ways in the current design e.g. heat sinks, heat pipes, and fans which is about 50% of the amplifier size.
Considerable advances in geological and rock engineering mapping methods using both conventional and remote sensing techniques have occurred over the last decade. The primary objective of the proposed research is to further develop the use Virtual and Mixed Reality (VR/MR), techniques in improving structural geological and rock mass field data acquisition. New uses of MR and Virtual Reality, VR, methods will be explored in combined field and office settings.
Seniors may experience social isolation when they lose the ability to drive their own car due to the loss of access to services and opportunities to socialize. I will examine the role of public transportation in reducing social isolation for seniors in Metro Vancouver. With BC’s aging population, the transportation needs of this demographic will become increasingly important over the coming decade. While many studies focus on how to ensure seniors can continue driving, this project will focus on barriers to other modes of transportation and programs or options to reduce these barriers.
Rethink is Canada's largest, national independent creative agency. As Rethink enters their twentieth year, they would like to formally collect the tips, tools and wisdom 20 years of knowledge and experience and share it with a broader audience interested in the creative industries and the process of creativity in general. Working with a humanities scholar from Simon Fraser University, Rethink will write a book that is accessible to readers both within and outside of the creative industry.
The proposed research work will be a breakthrough in the emerging data engineering field, especially in satellite data management, Machine learning algorithms, quality and quantitative analytics. The machine learning platform quickly scans vast archives of satellite images and delivers usable insights to decision makers.
In well-logging industry, gamma-ray density logging is an indispensable method to determine formations’ lithology and porosity. This research proposal under the support of Mitacs and Rimpac Advanced Technology Development Ltd. aims at developing a high-resolution density well logging tool which is expected to achieve higher precision and better vertical resolution of formation density measurement. This work is based on a previous Mitacs project. In this project, we will study the performance of this novel density logging tool in some complex geologic models.
Machine learning can be used to predict employee events around retention, promotion or movement. This project explores how to generate better predictions by exploring correlations and exploiting them through features that increase predictive strength. Furthermore, the project explores how to reliably fine-tune the predictive model to a particular data set in the presence of interdependence of data points. The results will enable improved Machine learning predictions related to employee events.
Batteries are main storage systems in many applications such as electric vehicles, shipping, transportation, and utility backup power. With the recent breakthrough in the supercapacitor technology, it is predicted that supercapacitors will challenge the batteries in many of these applications since their power delivery is much faster than the batteries. The current chargers are designed based on the requirements of the batteries.