For medical imaging applications, a timely execution of tasks is essential. Hence, running multiple applications on the same system, scheduling with the capability of task preemption and prioritization becomes mandatory. Using GPUs as accelerators in this domain, imposes new challenges since GPU’s common FIFO scheduling does not support task prioritization and preemption. As a remedy, this pape...

Working memory (WM) has limited capacity. This leaves attention with the important role of allowing into storage only the most relevant information. It is increasingly evident that attention is equally crucial for prioritizing representations within WM as the importance of individual items changes. Retrospective prioritization has been proposed to result from a focus of internal attention highl...

Are task-irrelevant stimuli processed to a level enabling individual identification? This question is central both for perceptual processing models and for applied settings (e.g., eye-witness testimony). Lavie's load theory proposes that working memory actively maintains attentional prioritization of relevant over irrelevant information. Loading working memory thus impairs attentional prioritiz...

In this paper we investigate a choice behavior that recognizes the intrinsic value of opportunities for choice. Nonconsequentialism is a choice attitude toward outcomes and opportunities and prioritizes opportunities for choice rather than outcomes. It is possible to define various types of nonconsequentialism in terms of criteria for ranking opportunity sets. We consider the leximax ordering o...

The authors investigated 2 effects of object-based attention: the spread of attention within an attended object and the prioritization of search across possible target locations within an attended object. Participants performed a flanker task in which the location of the task-relevant target was fixed and known to participants. A spreading attention account predicts that object-based attention ...

Motivation and Objectives A major goal in biomedicine is to determine the underlying genetic causes of human diseases in order to better understand them and support their prevention and treatment. However, the genetic bases of many multifactorial diseases are still unclear, and high-throughput technologies typically report hundred or thousands of genes associated to a disease of interest. In th...

Probability distributions are key components of many learning from demonstration (LfD) approaches, with the spaces chosen to represent tasks playing a central role. Although robot configuration is defined by its joint angles, end-effector poses often best explained within several task spaces. In relevant learned independently and only combined at control level. This simplification implies probl...