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- 75Adsorption
- 9Artificial intelligence
- 7Biochar
- 5Activated Carbon
- 5Reinforcement learning
- 5Kuznicki, S. M.
- 4Hindle, Abram
- 4Mark A. Lewis
- 4Russell Greiner
- 3Jin, Zhehui
- 3Noonari, Juned (Supervisor)
- 126Graduate and Postdoctoral Studies (GPS), Faculty of
- 126Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8WISEST Summer Research Program
- 8WISEST Summer Research Program/WISEST Research Posters
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- 7Master of Science in Internetworking (MINT)/Capstone Projects & Reports (Master of Science in Internetworking (MINT))
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Energy optimization of a residential building using occupancy prediction via sensor fusion and machine learning algorithms
DownloadFall 2023
Occupancy-based control systems for floor heating can lead to energy saving in a residential building. This study focuses on the energy consumption by space heating system in a half-duplex residential house located in Edmonton, Alberta. In the first part, a sensor fusion model was designed to...
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Spring 2015
Separation of ethane and heavier hydrocarbons from natural gas stream is a major topic in petrochemical industry due to the increase in Natural gas reserves in North America. Natural gas liquids are frequently separated using a cryogenic distillation process, which is able to separate all the C3+...
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Evaluation of machine learning methods for predicting eradication of aquatic invasive species
Download2018-03-27
Yanyu Xiao, Russell Greiner, Mark A. Lewis
In the work, we evaluate the performance of machine learning approaches for predicting successful eradication of aquatic invasive species (AIS) and assess the extent to which eradication of an invasive species depends on the certain specified ecological features of the target ecosystem...
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2021-01-05
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Although ecological models used to make predictions from underlying covariates have a record of success, they also suffer from limitations. They are typically unable to make predictions when the value of one or more covariates is missing during the testing. Missing values can be estimated but...
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Spring 2018
Intrinsically disordered regions (IDRs) in proteins lack stable three dimensional structure under physiological conditions. IDRs are prevalent in nature, functionally important, and difficult to characterize experimentally due to their unstructuredness. As a result, many computational methods...
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Fall 2010
Non-Player Character (NPC) behaviors in today’s computer games are mostly generated from manually written scripts. The high cost of manually creating complex behaviors for each NPC to exhibit intelligence in response to every situation in the game results in NPCs with repetitive and artificial...
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2018
Chowdhury, S., Borle, S., Romansky, S., Hindle, Abram
Software energy consumption is a performance related non-functional requirement that complicates building software on mobile devices today. Energy hogging applications (apps) are a liability to both the end-user and software developer. Measuring software energy consumption is non-trivial,...
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Fall 2023
Self-play is a technique for machine learning in multi-agent systems where a learning algorithm learns by interacting with copies of itself. Self-play is useful for generating large quantities of data for learning, but has the drawback that agents the learner will face post-training may have...