Innovative Projects Realized

A Comparative Analysis on Two Asset Condition Assessment Protocols Used in Canada; PACP and City of Edmonton’s SPCCM

Water and sewer research centers have developed protocols to examine and grade assets and infrastructure already in use. These protocols are widely accepted across the world and municipalities have been using them for assessing their pipeline conditions, which is the foundation of pipeline rehabilitation projects and a key factor for their success. The Water Research Centre in UK has developed a protocol called WRc, and the National Association for Sewer Service Companies used the same protocol to develop an American version of it, which is called PACP. Both – and particularly the latter – are the main protocols used to code pipeline defects and to grade them for rehabilitation decision making in most major cities in Canada. The City of Edmonton developed its own protocol called SPCCM in 1996, requiring its contractors to learn another protocol in addition to the two aforementioned standards. The same contractors are doing many projects for other clients using the PACP or the WRc protocols on a daily basis. The major aim of this study is to address the needs for a unified, national asset condition assessment protocol in Canada, by comparing PACP which is used in many Canadian cities and SPCCM, and by providing advantages and disadvantages of each system from the owner’s and contractors’ points of view. The anticipated results of this research include optimization and increased overall efficiency, while reducing project costs.

Using LSA for Automatically Assessing Free Texts

To evaluate the content of free texts is a challenging task for human. Latent Semantic Analysis (LSA) can be used to automate this process. The main idea behind the LSA technology is to extract the close relationship between the meaning of a text and the words that are present in that text. ShirWin Knowledge and Learning Systems Inc. is currently considering two instances of “free texts” assessment problems, one is automatic essay grading (where student written essays will be graded automatically given course materials and a set of human graded essays as training data) and the other is fact verification in a virtual learning environment (where a student plays the role of a occupational therapist needing to discover necessary facts from the patient file (or given information) in order to declare a diagnosis decision). Both problems involve understanding the inner meaning of the free texts which can be successfully accomplished by using the LSA technique. The main objective of the proposed project is to verify the effectiveness of the LSA technology and conduct extensive experiments to provide solutions for the two problems. The performance of the LSA models will be evaluated by measuring their correlation with the human-graded essays where better correlation will denote better effectiveness of the LSA technology.

Subjective Study of Visual Dynamic Range Limits using High Dynamic Range Video Materials

Development of an environmental impact assessment tool for sports events

Although there is growing awareness of the need for sports events to take account of their environmental impacts and be “greener”, few sports organizations comprehensively assess their environmental performance due to the lack of tailored methods and tools. Small events in particular have limited resources and would benefit from a simplified assessment approach that allows them to rapidly estimate impacts. Through this study, Quantis aims to develop a new tool and method, using a life cycle assessment approach, to be applied to the sport event sector. Sport events at the University of British Columbia (UBC) will be analysed as examples of typical small sports events. By estimating impacts grouped into major event sectors such as travel, food, accommodation, materials and waste, and venue operation and infrastructure – Quantis can use this information to help event organizers prioritize impact reduction initiatives.

Comprehensive Evaluation of Animal Manure Composts and Fumigation to Improve Potato Yield in Manitoba

This project addresses two major needs of the agriculture sector in Manitoba. The shift from nitrogen based- to phosphorus-based manure management regulations has resulted in implementing liquid hog manure separation techniques as a phosphorus (P) balance strategy but it is uncertain as to how best to utilize the solid material with its very high P content. A second major need is to reduce Verticillium wilt and common scab of potato to improve potato yields. To address these identified needs, the proposed project is organized into eight objectives: 1) Determine if hog manure compost material can improve yield and tuber size of potato?, 2) Determine what rates of manure compost increase yields?, 3) Determine by what mechanisms manure composts improve marketable yields?, 4) Determine if reducing Verticillium levels in soil using Vapam fumigation increases marketable yield?, 5) Determine if there is an optimal rate of Vapam fumigation?, 6) Determine if there are relations between Verticillium numbers in soil and plant to disease incidence and yield?, 7) With our non-financial organization supervisor, develop a molecular diagnostic PCR assay to determine the occurrence of the common scab pathogen, Streptomyces, in Manitoba, and 8) Conduct outreach activities to convey the results of the project such as the benefit of composts, awareness of Verticillium wilt and Early Dying of Potato, importance of soil sampling for Verticillium, benefit of fumigation and role of common scab of potato in affecting potato yields and quality. 

Optimization of Blow Heat Recovery

Online Risk-Driven Management Framework for Territorial Security in Wireless Sensor and Robot Networks

Small teams of mobile robots provide nowadays the ability to assist wireless sensor networks in many threatening scenarios that unexpectedly arise during their operational lifetime. The perceived risk or vulnerability that the network is exposed to triggers an immediate, corporate action from the robotic agents (actuators). We focus on a sort of robots which are able to carry static sensors and deploy them all over the field. Our goal is to improve an existing riskdriven collaboration framework between stationary sensors and mobile carrier robots by incorporating an online clustering architecture to better visualize the spatial structure of the sensing nodes in the risk feature space. In this way, we can promptly react to the perceived irregularities in the system's functioning. The proposed framework will be empirically validated in the context of a territorial security application.

Distributed collaborative recommendation engine for Asset Store

In this project we attempt to research and develop from ground up a scalable distributed computing based recommendation engine using machine learning. A computer science student from the University of Toronto will work with Side Effects Software at their Toronto office to implement the research intensive recommendation engine algorithm and integrate it in the smart asset online store. We expect and hope that this will result in high quality recommendation, is scalable and has a strong foundation in statistical machine learning based algorithm approach.

Examining Vocational Opportunities and Supports for Adults with ASD

The project addresses the under-studied area of vocational service for adults with ASD. The study will implement a mixed method research design consisting of: (1) an environmental scan examining vocational services in Alberta, (2) interviews and/or focus groups with adults with ASD and their caregivers examining their experiences and needs related to vocational supports, and (3) interviews and/or focus groups with employers or service agency personnel reviewing their processes and needs related to supporting adults with ASD. It is anticipated that the study will result in a greater understanding of needs, barriers and opportunities related to vocational success specific to ASD. Community practice and policy implications and recommendations will be provided, along with an extensive knowledge translation strategy.

Restoring native grassland function in urban environment; implications for soil-plant relations

Fescue prairie has reduced in Western Canada, because of human activities including housing development and land clearing. Urban development can impact natural ecosystems by eliminating the majority of native species, thus changing the richness and composition of the species. Strategic restoration efforts may reduce the effects of urban expansion on native ecosystem by protecting natural habitat and re-establishing modified habitat. Larch Park is an Edmonton residential development area, to which land reclamation and restoration ecology have been applied to rebuild native ecosystems (grassland) instead of turf grasses to reduce the impacts of urbanization. By rebuilding soils and planting native communities in Larch Park we believe that ecosystem function and wildlife habitat will improve to something more similar to natural grassland with less maintenance costs including watering, fertilization and weed invasion resistance. 

Technical-economic cost modeling for scaled production of printable, organic solar cells

Traditional silicon-based solar cells are harmful to the environment and costly to manufacture. Polymer-based (organic) solar cells on the other hand are thinner and more flexible electronic devices that are economically sustainable and have high cost saving potential due to the printable nature of their manufacturing process. This project involves cost estimation and analysis of different processing steps that the partnering company may pursue for low to medium volume manufacture of its organic solar cells. The intern will familiarize with the solar power market in order to assist the partnering company in identifying and liaising with potential key suppliers and business partners. The outcome of this project will contribute to both short term and long term business development plans implemented by the partnering organization including: sales and revenue forecast, pricing strategy, operational strategy, etc. 

A low complexity face recognition for consumer devices

Due to the rapid growth of consumer grade devices and corresponding application market, the incorporation of vision capabilities into embedded systems has gained significant attention from researchers lately. Similarly to the human visual system, embedded computer vision systems analyze and extract information from visual content in a wide variety of products. Face recognition has been one of the most successful applications in this field. A cost effective implementation of reliable face recognition (FR) solutions can be useful for a wide range of applications, such as identity authentication, entertainment, and content based retrieval system. However, embedded system based face recognition solutions often suffer from not only common problems such as variation in illumination (pose variation does not appear to be a problem for face recognition at a short distance), but also relatively low quality input face images, and limited computational resources. Although many researchers have attempted to develop robust FR algorithms, relatively few initiatives have been undertaken to adapt FR solutions to mobile/smart-phone market. It is believed that the research results obtained by this work will strengthen our industrial partners’ technological leadership and competitiveness.