MacEwan University

About: MacEwan University is a education organization based out in Edmonton, Alberta, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 818 authors who have published 1493 publications receiving 20228 citations. The organization is also known as: Grant MacEwan University.

On arithmetic progressions in model sets

Abstract: In this project we show the existence of arbitrary length arithmetic progressions in model sets and Meyer sets in the Euclidean $d$-space. We prove a van der Waerden type theorem for Meyer sets. We show that pure point subsets of Meyer sets with positive density and pure point diffraction contain arithmetic progressions of arbitrary length.

Barriers to the Recognition of Geriatric Depression in Residential Care Facilities in Alberta.

Abstract: This study explored the barriers that regulated nurse professionals encountered in recognizing and assessing geriatric depression in residential care facilities in the Canadian province of Alberta....

Preferences for achromatic horizontal, vertical, and square patterns in zebrafish (Danio rerio)

Abstract: The zebrafish (Danio rerio) is gaining popularity as a laboratory organism and is used to model many human diseases. Many behavioural measures of locomotion and cognition have been developed that involve the processing of visual stimuli. However, the innate preference for vertical and horizontal stripes in zebrafish is unknown. We tested the preference of adult zebrafish for three achromatic patterns (vertical stripes, horizontal stripes, and squares) at three different size conditions (1, 5, and 10 mm). Each animal was tested once in a rectangular arena, which had a different pattern of the same size condition on the walls of either half of the arena. We show that zebrafish have differential preferences for patterned stimuli at each of the three size conditions. These results suggest that zebrafish have naive preferences that should be carefully considered when testing zebrafish in paradigms using visual stimuli.

Simultaneously Searching with Multiple Settings: An Alternative to Parameter Tuning for Suboptimal Single-Agent Search Algorithms.

Abstract: Many search algorithms have parameters that need to be tuned to get the best performance. Typically, the parameters are tuned offline, resulting in a generic setting that is supposed to be effective on all problem instances. For suboptimal single-agent search, problem-instance-specific parameter settings can result in substantially reduced search effort. We consider the use of dovetailing as a way to take advantage of this fact. Dovetailing is a procedure that performs search with multiple parameter settings simultaneously. Dovetailing is shown to improve the search speed of weighted IDA* by several orders of magnitude and to generally enhance the performance of weighted RBFS. This procedure is trivially parallelizable and is shown to be an effective form of parallelization for WA* and BULB. In particular, using WA* with parallel dovetailing yields good speedups in the sliding-tile puzzle domain, and increases the number of problems solved when used in an automated planning system.