The Experts below are selected from a list of 115320 Experts worldwide ranked by ideXlab platform
Mrv Michel Chaudron - One of the best experts on this subject based on the ideXlab platform.
-
prediction of run time resource consumption in multi Task Component based software systems
Component-Based Software Engineering, 2004Co-Authors: J Muskens, Mrv Michel ChaudronAbstract:Embedded systems must be cost-effective. This imposesstrict requirements on the resource consumption of their applications. It is therefore desirable to be able to determine the resource consumption of applications as early as possible in its development. Only then, a designer is able to guarantee that an application will fit on a target device.
-
prediction of run time resource consumption in multi Task Component based software systems
Lecture Notes in Computer Science, 2004Co-Authors: J Muskens, Mrv Michel ChaudronAbstract:Embedded systems must be cost-effective. This imposes strict requirements on the resource consumption of their applications. It is therefore desirable to be able to determine the resource consumption of applications as early as possible in its development. Only then, a designer is able to guarantee that an application will fit on a target device. In this paper we will present a method for predicting run-time resource resource consumption in multi-Task Component based systems based on a design of an application. In [5] we describe a scenario based resource prediction technique and show that it can be applied to non-pre-emptive non-processing resources, like memory. In this paper we extend this technique, which enables us to handle pre-emptive processing resources and their scheduling policies. Examples of these class of resources are CPU and network. For Component based software engineering the challenge is to express resource consumption characteristics per Component, and to combine them to do predictions over compositions of Components. To this end, we propose a model and tools, for combining individual resource estimations of Components. These composed resource estimations are then used in scenarios (which model run-time behavior) to predict resource consumption.
J Muskens - One of the best experts on this subject based on the ideXlab platform.
-
prediction of run time resource consumption in multi Task Component based software systems
Component-Based Software Engineering, 2004Co-Authors: J Muskens, Mrv Michel ChaudronAbstract:Embedded systems must be cost-effective. This imposesstrict requirements on the resource consumption of their applications. It is therefore desirable to be able to determine the resource consumption of applications as early as possible in its development. Only then, a designer is able to guarantee that an application will fit on a target device.
-
prediction of run time resource consumption in multi Task Component based software systems
Lecture Notes in Computer Science, 2004Co-Authors: J Muskens, Mrv Michel ChaudronAbstract:Embedded systems must be cost-effective. This imposes strict requirements on the resource consumption of their applications. It is therefore desirable to be able to determine the resource consumption of applications as early as possible in its development. Only then, a designer is able to guarantee that an application will fit on a target device. In this paper we will present a method for predicting run-time resource resource consumption in multi-Task Component based systems based on a design of an application. In [5] we describe a scenario based resource prediction technique and show that it can be applied to non-pre-emptive non-processing resources, like memory. In this paper we extend this technique, which enables us to handle pre-emptive processing resources and their scheduling policies. Examples of these class of resources are CPU and network. For Component based software engineering the challenge is to express resource consumption characteristics per Component, and to combine them to do predictions over compositions of Components. To this end, we propose a model and tools, for combining individual resource estimations of Components. These composed resource estimations are then used in scenarios (which model run-time behavior) to predict resource consumption.
Laurie R Weingart - One of the best experts on this subject based on the ideXlab platform.
-
impact of group goals Task Component complexity effort and planning on group performance
Journal of Applied Psychology, 1992Co-Authors: Laurie R WeingartAbstract:This study tested a model asserting that goal difficulty and Task Component complexity influence group performance by affecting the effort exerted by group members, the amount and quality of their planning, and the timing of their planning(preplanning versus in-process planning). Hypotheses derived from this model were tested in a 2×2 experimental design. Fifty-six groups of 4 students each worked for 15 min building Tinkertoy structures. Results showed that group-goal difficulty influenced group performance through effort; Task Component complexity influenced performance through the amount of planning performed by group members and the level of effort invested in their work; and the quality of the group's planning process also influenced group performance
Nima Toosizadeh - One of the best experts on this subject based on the ideXlab platform.
-
the association between cognition and dual Tasking among older adults the effect of motor function type and cognition Task difficulty
Clinical Interventions in Aging, 2019Co-Authors: Hossein Ehsani, Martha Jane Mohler, Kathy Oconnor, Edward Zamrini, Coco Victoria Gomez Tirambulo, Nima ToosizadehAbstract:Background Dual-Task actions challenge cognitive processing. The usefulness of objective methods based on dual-Task actions to identify the cognitive status of older adults has been previously demonstrated. However, the properties of select motor and cognitive Tasks are still debatable. We investigated the effect of cognitive Task difficulty and motor Task type (walking versus an upper-extremity function [UEF]) in identifying cognitive impairment in older adults. Methods Older adults (≥65 years) were recruited, and cognitive ability was measured using the Montreal Cognitive Assessment (MoCA). Participants performed repetitive elbow flexion under three conditions: 1) at maximum pace alone (Single-Task); and 2) while counting backward by ones (Dual-Task 1); and 3) threes (Dual-Task 2). Similar single- and dual-Task gait were performed at normal speed. Three-dimensional kinematics were measured for both motor functions using wearable sensors. Results One-hundred older adults participated in this study. Based on MoCA score 0.26). Conclusion This study demonstrated that counting backward by threes within a UEF dual-Task experiment was a pertinent and challenging enough Task to detect cognitive impairment in older adults. Additionally, UEF was superior to gait as the motor Task Component of the dual-Task. The UEF dual-Task could be applied as a quick memory screen in a clinical setting.
Roman Liepelt - One of the best experts on this subject based on the ideXlab platform.
-
dual Tasking in the near hand space effects of stimulus hand proximity on between Task shifts in the psychological refractory period paradigm
Frontiers in Psychology, 2018Co-Authors: Rico Fischer, Thomas Hosang, Jennifer Pomp, Roman LiepeltAbstract:Two decades of research indicate that visual processing is typically enhanced for items that are in the space near the hands (near-hand space). Enhanced attention and cognitive control have been thought to be responsible for the observed effects, amongst others. As accumulating experimental evidence and recent theories of dual-Tasking suggest an involvement of cognitive control and attentional processes during dual Tasking, dual-Task performance may be modulated in the near-hand space. Therefore, we performed a series of three experiments that aimed to test if the near-hand space affects the shift between Task-Component processing in two visual-manual Tasks. We applied a Psychological Refractory Period Paradigm (PRP) with varying stimulus-onset asynchrony (SOA) and manipulated stimulus-hand proximity by placing hands either on the side of a computer screen (near-hand condition) or on the lap (far-hand condition). In Experiment 1, Task 1 was a number categorization Task (odd vs. even) and Task 2 was a letter categorization Task (vowel vs. consonant). Stimulus presentation was spatially segregated with Stimulus 1 presented on the right side of the screen, appearing first and then Stimulus 2, presented on the left side of the screen, appearing second. In Experiment 2, we replaced Task 2 with a color categorization Task (orange vs. blue). In Experiment 3, Stimulus 1 and Stimulus 2 were centrally presented as a single bivalent stimulus. The classic PRP effect was shown in all three experiments, with Task 2 performance declining at short SOA while Task 1 performance being relatively unaffected by Task-overlap. In none of the three experiments did stimulus-hand proximity affect the size of the PRP effect. Our results indicate that the switching operation between two Tasks in the PRP paradigm is neither optimized nor disturbed by being processed in near-hand space.
