Yaşar University

About: Yaşar University is a education organization based out in Izmir, Turkey. It is known for research contribution in the topics: Exergy & Job shop scheduling. The organization has 760 authors who have published 1436 publications receiving 20813 citations. The organization is also known as: Yaşar Üniversitesi.

Hue, saturation, lightness, and building exterior preference: An empirical study in Turkey comparing architects' and nonarchitects' evaluative and cognitive judgments

Abstract: This study investigated architects' and nonarchitects' evaluative and cognitive judgments of color on building exteriors. Thirty architects and 30 high school teachers living in Izmir, Turkey participated in the study. The experiment had two phases. First, participants viewed eight images, in which the color of a building exterior was manipulated with hues selected from HSB (hue, saturation, and brightness) color space. Participants were then asked to rate each image on 7-point semantic differential scales measuring preference (like–dislike), arousal (arousing–sleepy), naturalness (natural–artificial), and relaxation (relaxing–distressing). Second, participants viewed the same building in nine saturation and lightness levels for each hue and picked the most preferred lightness and saturation level for each hue. Findings showed that for a building exterior: (1) yellow and blue were the most liked colors, (2) some hues were rated as more arousing, more natural, and more relaxing over the others, (3) gender had an effect on color preference and semantic ratings of naturalness and relaxation, (4) architects and nonarchitects differed in their color preference and semantic ratings of arousal and naturalness, and (5) full bright and moderate to low saturated colors and full saturated and moderate to high bright colors were preferred more. The results have practical implications for architects and urban designers. A successful coloration of a building exterior may increase its use frequency and economical value. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 395–405, 2008

Frontoparietal tDCS Benefits Visual Working Memory in Older Adults With Low Working Memory Capacity.

Abstract: Working memory (WM) permits maintenance of information over brief delays and is an essential executive function. Unfortunately, WM is subject to age-related decline. Some evidence supports the use of transcranial direct current stimulation (tDCS) to improve visual WM. A gap in knowledge is an understanding of the mechanism characterizing these tDCS linked effects. To address this gap, we compared the effects of two tDCS montages designed on visual working memory (VWM) performance. The bifrontal montage was designed to stimulate the heightened bilateral frontal activity observed in aging adults. The unilateral frontoparietal montage was designed to stimulate activation patterns observed in young adults. Participants completed three sessions (bilateral frontal, right frontoparietal, sham) of anodal tDCS (20 min, 2 mA). During stimulation, participants performed a visual long-term memory (LTM) control task and a visual WM task. There was no effect of tDCS on the LTM task. Participants receiving right unilateral tDCS showed a WM benefit. This pattern was most robust in older adults with low WM capacity. To address the concern that the key difference between the two tDCS montages could be tDCS over the posterior parietal cortex (PPC), we included new analyses from a previous study applying tDCS targeting the PPC paired with a recognition VWM task. No significant main effects were found. A subsequent experiment in young adults found no significant effect of either tDCS montage on either task. These data indicate that tDCS montage, age and WM capacity should be considered when designing tDCS protocols. We interpret these findings as suggestive that protocols designed to restore more youthful patterns of brain activity are superior to those that compensate for age-related changes.

Optimal any-angle pathfinding in practice

Abstract: Any-angle pathfinding is a fundamental problem in robotics and computer games. The goal is to find a shortest path between a pair of points on a grid map such that the path is not artificially constrained to the points of the grid. Prior research has focused on approximate online solutions. A number of exact methods exist but they all require super-linear space and pre-processing time. In this study, we describe Anya: a new and optimal any-angle pathfinding algorithm. Where other works find approximate any-angle paths by searching over individual points from the grid, Anya finds optimal paths by searching over sets of states represented as intervals. Each interval is identified on-the-fly. From each interval Anya selects a single representative point that it uses to compute an admissible cost estimate for the entire set. Anya always returns an optimal path if one exists. Moreover it does so without any offine pre-processing or the introduction of additional memory overheads. In a range of empirical comparisons we show that Anya is competitive with several recent (sub-optimal) online and pre-processing based techniques and is up to an order of magnitude faster than the most common benchmark algorithm, a grid-based implementation of A.