University of Waterloo

About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.

Opposition-Based Differential Evolution

Abstract: Evolutionary algorithms (EAs) are well-known optimization approaches to deal with nonlinear and complex problems. However, these population-based algorithms are computationally expensive due to the slow nature of the evolutionary process. This paper presents a novel algorithm to accelerate the differential evolution (DE). The proposed opposition-based DE (ODE) employs opposition-based learning (OBL) for population initialization and also for generation jumping. In this work, opposite numbers have been utilized to improve the convergence rate of DE. A comprehensive set of 58 complex benchmark functions including a wide range of dimensions is employed for experimental verification. The influence of dimensionality, population size, jumping rate, and various mutation strategies are also investigated. Additionally, the contribution of opposite numbers is empirically verified. We also provide a comparison of ODE to fuzzy adaptive DE (FADE). Experimental results confirm that the ODE outperforms the original DE and FADE in terms of convergence speed and solution accuracy.

Stiffness Control of Balance in Quiet Standing

Abstract: Winter, David A., Aftab E. Patla, Francois Prince, Milad Ishac, and Krystyna Gielo-Perczak. Stiffness control of balance in quiet standing. J. Neurophysiol. 80: 1211–1221, 1998. Our goal was to pro...

Working memory and language comprehension: A meta-analysis.

Abstract: This paper presents a meta-analysis of the data from 6,179 participants in 77 studies that investigated the association between working-memory capacity and language comprehension ability. A primary goal of the meta-analysis was to compare the predictive power of the measures of working memory developed by Daneman and Carpenter (1980) with the predictive power of other measures of working memory. The results of the meta-analysis support Daneman and Carpenter’s (1980) claim that measures that tap the combined processing and storage capacity of working memory (e.g., reading span, listening span) are better predictors of comprehension than are measures that tap only the storage capacity (e.g., word span, digit span). The meta-analysis also showed that math process plus storage measures of working memory are good predictors of comprehension. Thus, the superior predictive power of the process plus storage measures is not limited to measures that involve the manipulation of words and sentences.