Search
Skip to Search Results- 1Bendrich, Michelle
- 1Bineshmarvasti, Baher
- 1De la Hoz Siegler, Hector Jr
- 1Hartley, Kendra Jade
- 1Kasiri, Sepideh
- 1Li, Chaoqun
- 3Huang, Biao (Chemical and Materials Engineering)
- 1Amos Ben-Zvi (Chemical and Materials Engineering)
- 1Antoniuk, Tim (Industrial Design)
- 1Ben-Zvi, Amos (Chemical and Materials Engineering)
- 1Dr. Arvind Rajendran (Chemical and Materials Engineering)
- 1Forbes, Fraser (Chemical and Materials Engineering)
-
Optimization of the reaction conditions of two enzymes for use in a carbon sequestration process, and investigation into immobilization via encapsulation within polymersomes
DownloadFall 2016
Carbon dioxide emissions from human activities contribute to an increase of greenhouse gases in the atmosphere. In nature, this gas is sequestered through the use of enzymes found in the Calvin-Benson-Bassham cycle, with useful molecules such as sugars being synthesized as products. A biomimetic...
-
Spring 2020
Reinforcement learning (RL) has received wide attention in various fields lately. Model-free RL brings data-driven solutions that learn the control strategy directly from interaction with process data without the need for a process model. This is especially beneficial in the case of nonlinear...
-
Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization
DownloadFall 2015
Availability of large amounts of industrial process data is allowing researchers to explore new data-based modelling methods. In this thesis, Gaussian process (GP) regression, a relatively new Bayesian approach to non-parametric data based modelling is investigated in detail. One of the primary...