Filters: Date: "2018" Collection: "ir_uspace"
1 - 25 of 3
| Creator | Title | Description | Subject | Date | ||
|---|---|---|---|---|---|---|
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Malinowski, Nicholas | Improving water heaters for sustainability | Buildings use about 40% of the total U.S. energy demand. Water heaters provide hot water for a variety of building uses including sinks, showers, dishwashers, washing machines, and space heating. Water heaters are the second most energy intensive appliances in a common household. Typically a home... | Water heaters; Energy efficiency; Electricity; Emissions; Natural gas | 2018 |
| 2 |
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Rahman, Aowabin | Predicting heating demand and sizing a stratified thermal storage tank using deep learning algorithms | This paper evaluates the performance of deep recurrent neural networks in predicting heating demand for a commercial building over a medium-to-long term time horizon (≥ 1 week), and proposes a modeling framework to demonstrate how these longer-term predictions can be used to aid design of a strati... | Building Energy Modeling; Machine Learning; Recurrent Neural Networks; Deep Learning; Heating Load Prediction; Thermal Energy Storage | 2018 |
| 3 |
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Marshall, Colleen | Evaluating the impact of an interprofessional education simulation: A methodology | In an effort to improve the quality of health care delivery, training health professional students to work effectively in interprofessional teams has become a high priority of many educational establishments, and the health professional community (Institute of Medicine, 2015; Association of Departme... | Interproffesional teams; Health profession | 2018 |
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