British Columbia Institute of Technology

About: British Columbia Institute of Technology is a education organization based out in Burnaby, British Columbia, Canada. It is known for research contribution in the topics: Smart grid & Belief revision. The organization has 458 authors who have published 785 publications receiving 16140 citations.

Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring

Abstract: Understanding how appliances in a house consume power is important when making intelligent and informed decisions about conserving energy. Appliances can turn ON and OFF either by the actions of occupants or by automatic sensing and actuation (e.g., thermostat). It is also difficult to understand how much a load consumes at any given operational state. Occupants could buy sensors that would help, but this comes at a high financial cost. Power utility companies around the world are now replacing old electro-mechanical meters with digital meters (smart meters) that have enhanced communication capabilities. These smart meters are essentially free sensors that offer an opportunity to use computation to infer what loads are running and how much each load is consuming (i.e., load disaggregation). We present a new load disaggregation algorithm that uses a super-state hidden Markov model and a new Viterbi algorithm variant which preserves dependencies between loads and can disaggregate multi-state loads, all while performing computationally efficient exact inference. Our sparse Viterbi algorithm can efficiently compute sparse matrices with a large number of super-states. Additionally, our disaggregator can run in real-time on an inexpensive embedded processor using low sampling rates.

AMPds: A public dataset for load disaggregation and eco-feedback research

Abstract: A home-based intelligent energy conservation system needs to know what appliances (or loads) are being used in the home and when they are being used in order to provide intelligent feedback or to make intelligent decisions. This analysis task is known as load disaggregation or non-intrusive load monitoring (NILM). The datasets used for NILM research generally contain real power readings, with the data often being too coarse for more sophisticated analysis algorithms, and often covering too short a time period. We present the Almanac of Minutely Power dataset (AMPds) for load disaggregation research; it contains one year of data that includes 11 measurements at one minute intervals for 21 sub-meters. AMPds also includes natural gas and water consumption data. Finally, we use AMPds to present findings from our own load disaggregation algorithm to show that current, rather than real power, is a more effective measure for NILM.

A new method to support UMTS/WLAN vertical handover using SCTP

Abstract: This article proposes a new method to facilitate seamless vertical handover between wide area cellular data networks such as UMTS and WLANs using the stream control transmission protocol (SCTP). The multihoming capability and dynamic address configuration extension of SCTP are applied in UMTS/WLAN overlay architecture to decrease handover delay and improve throughput performance. Unlike techniques based on mobile IP or session initiation protocol, the SCTP-based vertical handover scheme does not require the addition of components such as home/foreign agents or a SIP server to existing networks. Therefore, the proposed scheme provides a network-independent solution preferred by service providers. Performance evaluations are presented to demonstrate the effectiveness of the proposed scheme.

Cardiovascular disease and spinal cord injury: Results from a national population health survey

Abstract: Objective: To evaluate the association between cardiovascular disease (CVD) and spinal cord injury (SCI) in a large representative sample. Methods: Data were compiled from more than 60,000 individuals from the 2010 cycle of the cross-sectional Canadian Community Health Survey (CCHS). Multivariable logistic regression analysis was conducted to examine this relationship, adjusting for confounders and using probability weighting to account for the CCHS sampling method. Results: After adjusting for age and sex, SCI was associated with a significant increased odds of heart disease (adjusted odds ratio [OR] = 2.72, 95% confidence interval [CI] 1.94–3.82) and stroke (adjusted OR = 3.72, 95% CI 2.22–6.23). Conclusions: These remarkably heightened odds highlight the exigent need for targeted interventions and prevention strategies addressing modifiable risk factors for CVD in individuals with SCI.

Digital Learners in Higher Education: Generation is Not the Issue

Abstract: Generation is often used to explain and rationalize the use of information and communication technologies (ICTs) in higher education. However, a comprehensive review of the research and popular literature on the topic and an empirical study at one postsecondary institution in Canada suggest there are no meaningful generational differences in how learners say they use ICTs or their perceived behavioural characteristics. The study also concluded that the post-secondary students at the institution in question use a limited set of ICTs and their use is driven by three key issues: familiarity, cost, and immediacy. The findings are based on focus group interviews with 69 students and survey responses from a random sample of 438 second year students in 14 different programs in five schools in the institution. The results of this investigation add to a growing body of research that questions the popular view that generation can be used to explain the use of ICTs in higher education.