F
Fred Popowich
Researcher at Simon Fraser University
Publications - 94
Citations - 2513
Fred Popowich is an academic researcher from Simon Fraser University. The author has contributed to research in topics: Machine translation & Parsing. The author has an hindex of 22, co-authored 94 publications receiving 2138 citations. Previous affiliations of Fred Popowich include University of Alberta & University of British Columbia.
Papers
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Journal ArticleDOI
Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring
TL;DR: 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.
Proceedings ArticleDOI
AMPds: A public dataset for load disaggregation and eco-feedback research
TL;DR: The Almanac of Minutely Power dataset (AMPds) is presented for load disaggregation research; it contains one year of data that includes 11 measurements at one minute intervals for 21 sub-meters, and also includes natural gas and water consumption data.
Journal ArticleDOI
Electricity, water, and natural gas consumption of a residential house in Canada from 2012 to 2014
TL;DR: The Almanac of Minutely Power dataset Version 2 (AMPds2) has been released to help computational sustainability researchers, power and energy engineers, building scientists and technologists, utility companies, and eco-feedback researchers test their models, systems, algorithms, or prototypes on real house data.
Journal ArticleDOI
Nonintrusive load monitoring (NILM) performance evaluation
Stephen Makonin,Fred Popowich +1 more
TL;DR: In this article, the authors present a unified approach that would allow for consistent accuracy testing for nonintrusive load monitoring, which is the process of determining what loads or appliances are running in a house from analysis of the power signal of the whole-house power meter.
Patent
A method and system for describing and identifying concepts in natural language text for information retrieval and processing
Daniel C. Fass,Davide Turcato,Gordon W. Tisher,James Devlan Nicholson,Milan Mosny,Fred Popowich,Janine Toole,Paul McFetridge,Frederick W. Kroon +8 more
TL;DR: In this article, a method for information retrieval that matches occurrences of concepts in natural language text documents against descriptions of concepts described in user queries is proposed. But the method is not suitable for text-based systems.