Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.

 

Search Results

Yeomans, J.S. (2017). "A Metaheuristic Procedure for Calculating Optimal Osmotic Dehydration Parameters: A Case Study of Mushrooms", Transactions on Machine Learning and Artificial Intelligence, 5(6), 1-10.

Open Access Download

Abstract The Firefly Algorithm (FA) metaheuristic is employed to determine the optimal parameter settings in a case study of the osmotic dehydration of mushrooms. In the case, the functional form of the dehydration model is established through a response surface technique and the resulting mathematical programming is formulated as a non-linear goal programming model. For optimization purposes, a computationally efficient, FA-driven method is used and the resulting optimal process parameters are shown to be superior to those from previous approaches.

Cao, T. and Yeomans, J.S. (2016). "The Calculation of Optimal Osmotic Dehydration Process Parameters for Mushrooms: A Firefly Algorithm", International Journal of Environmental and Agriculture Research, 2(12), 52-58.

Open Access Download

Abstract The Firefly Algorithm (FA) is employed to determine the optimal parameter settings in a case study of the osmotic dehydration process of mushrooms. In the case, the functional form of the dehydration model is established through a response surface technique and the resulting mathematical programming is formulated as a non-linear goal programming model. For optimization purposes, a computationally efficient, FA-driven method is used and the resulting optimal process parameters are shown to be superior to those from previous approaches.

Yeomans, J.S. (2015). "A Parametric Testing of the Firefly Algorithm in the Determination of the Optimal Osmotic Drying Parameters of Mushrooms", Journal of Artificial Intelligence and Soft Computing Research, 4(4), 257-266.

Open Access Download

Abstract The Firefly Algorithm (FA) is employed to determine the optimal parameter settings in a case study of the osmotic dehydration process of mushrooms. In the case, the functional form of the dehydration model is established through a response surface technique and the resulting mathematical programming is formulated as a non-linear goal programming model. For optimization purposes, a computationally efficient, FA-driven method is used and the resulting optimal process parameters are shown to be superior to those from previous approaches. The final section of this study provides a computational experimentation performed on the FA to analyze its relative sensitivity over a range of the two key parameters that most influence its running time.