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• We extend our tool focusing on the evaluation of depth perception to include the evaluation of shape perception. • We extend the generation of task-based experiments based on vascular surface models to arbitrary surfaces models. • We provide an automatic preparation of web-based studies to evaluate depth and shape perception in visualization techniques. User studies are indispensable for visualization application papers in order to assess the value and limitations of the presented approach. Important aspects are how well depth and shape information can be perceived, as coding of these aspects is essential to enable an understandable representation of complex 3D data. In practice, there is usually little time to perform such studies, and the establishment and conduction of user studies can be labour-intensive. In addition, it can be difficult to reach enough participants to obtain expressive results regarding the quality of different visualization techniques. In this paper, we propose a framework that allows visualization researchers to quickly create task-based user studies on depth and shape perception for different surface visualizations and perform the resulting tasks via a web interface. With our approach, the effort for generating user studies is reduced and at the same time the web-based component allows researchers to attract more participants to their study. We demonstrate our framework by applying shape and depth evaluation tasks to visualizations of various surface representations used in many technical and biomedical applications. [ABSTRACT FROM AUTHOR]

Task switching refers to the effortful mental process of shifting attention between different tasks. While it is well-established that task switching usually comes with an objective performance cost, recent studies have shown that people also subjectively evaluate task switching as negative. An open question is whether this affective evaluation of task switching is also related to actual decision making. In this pre-registered study, we therefore examined whether individual differences in the negative evaluation of task switch cues are related to less voluntary task switching. To this end, participants first performed a cued task switching paradigm where abstract cues signaled task transitions (repetition or alternation). In a second phase, these transition cues were used as prime stimuli in an affective priming procedure to assess participants' affective evaluation of task switching. In a third phase, participants were allowed to freely choose whether to switch or repeat tasks. We found that a more negative evaluation of task switching cues was related to lower switch rates in the voluntary task switching phase. This finding supports neuroeconomic theories of value-based decision making which suggest that people use their subjective value of control to decide whether to engage in (different) tasks. [ABSTRACT FROM AUTHOR]

Response time analysis of adaptive variable-rate tasks (AVR tasks) is a challenging problem in automotive real-time systems. While in periodic event-triggered systems, the worst-case response time is easy to determine, the analysis of AVR tasks has to deal with an exponentially growing number of combinations of execution paths. Each execution path has a specific dynamic behavior. In this paper, we present a new approach for reducing the number of potential worst-case combinations by introducing an intuitive view on the relation of start and end speeds given by speed-phase diagram. Here we propose a minimal inter-arrival time algorithm (MIAT) which is built on time constant lines (isochrones) in a speed-phase diagram first introduced in this work. Compared with previous work, the MIAT algorithm is more accurate and shows a significant improvement in runtime. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Floor layers have high rates of musculoskeletal disorders yet few studies have examined their work exposures. This study used observational methods to describe physical exposures within floor laying tasks. Methods: We analyzed 45 videos from 32 floor layers using Multimedia-Video Task Analysis software to determine the time in task, forces, postures, and repetitive hand movements for installation of four common flooring materials. We used the WISHA checklists to define exposure thresholds. Results: Most workers (91%) met the caution threshold for one or more exposures. Workers showed high exposures in multiple body parts with variability in exposures across tasks and for different materials. Prolonged exposures were seen for kneeling, poor neck and low back postures, and intermittent but frequent hand grip forces. Conclusions: Floor layers experience prolonged awkward postures and high force physical exposures in multiple body parts, which probably contribute to their high rates of musculoskeletal disorders. [Copyright &y& Elsevier]

Abstract: This study investigated the electrophysiological correlates of the processes involved in task switching. A pair-wise task-switching paradigm was used where each trial comprised two tasks that were either the same (task repeat) or different (task switch). In the paradigm, task-switch and repeat trials are compared in conditions of foreknowledge and non-foreknowledge of the forthcoming task type and during different response–stimulus intervals (RSIs). The results of this study show that, before the second task began in a task-pair trial, i.e., during the RSI, there was a CNV-like negativity for all trials. This indicates a general anticipatory effect. In foreknowledge conditions, there is an additional switch-specific reconfiguration process followed by a task-specific (including both switch- and repeat-related) preparatory process. During the post-task 2 stage, P3b was found to be smaller in switch trials than in repeat trials. Such differential P3b between switch and repeat trials appeared earlier and larger in foreknowledge than in non-foreknowledge conditions. The results of this study support the existence of advance preparation and uphold the role of carryover effects in task switching. [Copyright &y& Elsevier]

Network-on-Chips (NoC) are widely used in industrial applications since they provide communication parallelism and reduce energy consumption. The use of NoC has been recently extended to real-time systems, whose execution has to meet temporal constraints. Communication delays introduced by the network make the scheduling analysis challenging. In this article, we propose a new NoC communication model called ECTM. The main goal of this model is to assess the schedulability of dependent periodic tasks exchanging messages on a NoC. ECTM is a model allowing schedulability analysis of messages and tasks of the NoC. To achieve schedulability, ECTM produces an analysis model by transforming NoC messages to tasks in order to take into account communication delays during the scheduling analysis. Schedulability of the system is assessed using simulation over the feasibility interval with a list scheduling, ECTM supports Store-And-Forward and Wormhole NoC. In this article, we have demonstrated the correctness of the transformations of ECTM. ECTM has been implemented in a real-time scheduling analysis tool called Cheddar and we performed experiments to assess its efficiency. ECTM is more efficient than existing solutions with an improvement of 30% for Store-And-Forward NoCs and up to 100% for Wormhole NoCs, while the proposed model requires a larger computation time about 17% for Store-And-Forward NoCs. [ABSTRACT FROM AUTHOR]

Edge computing is a new technology for completing real-time and complex tasks with low latency. However, due to limited storage, computing and communication capabilities of edge nodes, it is often necessary for multiple edge nodes to share a task's related work load to decrease its overall execution time. To solve the problem, this paper proposes a task distribution method based on the analysis of task requirements and time delay in an edge computing environment. First, the related data is received by a proxy server to obtain the running states of edge nodes. Then, a task-based edge node selection algorithm is designed to select appropriate target edge nodes. It can meet task requirements by using a Bloom filter to filter malicious nodes. Finally, based on the above selected nodes, optimized target edge nodes are selected to achieve the minimum time delay. Based on the selected optimized target edge nodes, this paper proposes an algorithm to optimize task distribution for meeting task requirements and achieve the minimum delay in an edge computing environment. Because the method considers both task requirements and time delay, it can distribute tasks to target nodes at low cost. The experimental results show that the method is feasible and effective and outperforms two commonly-used methods [ABSTRACT FROM AUTHOR]