A multi-modal approach is proposed to evaluate the usability of Adaptive Visual Stimuli for User Interface (AVS4UI) of remote operation systems. This study focuses on the evaluation of AVS4UI for forklift work because the operation complexity includes driving and cargo handling, which typically requires multiple salient attention. Presenting this amount of information simultaneously on a User Interface (UI) tends to cause confusions to operators and reduces operation efficiency. AVS4UI can therefore be one of the promising solutions where the optimal visual stimuli are autonomously presented for different work conditions. However, evaluation of AVS4UI is challenging because operators may be disoriented by adaptive information and worked without safety considerations. Therefore, novel gaze metrics are proposed to evaluate responses of forklift operators to AVS4UI so that undesired behavior can be evaluated. The proposed metrics implicitly represent gaze pattern in terms of transition and distribution between UI elements, operation safety, and familiarity with the adaptive system. The ideal AVS4UI is expected to minimize the proposed gaze metrics and outperform the non-adaptive UI. More importantly, the results of these metrics are consistent with those of perceived workload defined by NASA-Task Load Index. We also propose a correlation model using stepwise linear regression that provides reasonable estimation of perceived workload. Such novel metrics and correlation model enable objective and online evaluation to minimize biases of subjective response. Therefore, online work support system can be developed to support workers. 相似文献
In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers’ locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency. The most significant impact lies in the data center distance and the speed of the communication channel. Moreover, the communication protocol also has impact on the latency. The feasibility of controlling each level of RAMI 4.0 through cloud services was investigated. Experimental results showed that control is possible in many solutions, but these solutions mostly cannot depend just on cloud services. The intelligence on the edge of the network will play a significant role. The main contribution is a thorough evaluation of different cloud providers, locations, and communication protocols to provide recommendations sufficient for different levels of the RAMI 4.0 architecture. 相似文献
This article proposes a complex network methodology for the process of Environmental Impact Assessment (EIA) that limits subjectivity and reduces uncertainty by incorporating elements of complex systems theory in the stages of identification and assessment of the significance of environmental impacts. The proposed methodology reduces the sources of uncertainty, which emerge from the use of simplified models that analyse the environment-activity interactions in a unidirectional fashion. This proposal determines the significance of environmental impacts through multidirectional or complex causal relationships. Likewise, it limits the subjectivity of the evaluator by using these causality relationships instead of criteria based on the impacts’ attributes. The application of the proposed methodology demonstrates the advantages of (i) prioritizing the impacts according to their capacity to interact with other impacts, and (ii) the possibility to redirect the environmental management plans towards the prevention of impacts of higher complexity and to reduce the importance of derived impacts.
The application of the proposed methodology reveals that the percentage of irrelevant and moderate impacts is reduced, whereas the percentage of severe and critical impacts increase, in comparison to the conventional methodologies. 相似文献
Collaboration with artificial intelligence (AI) is a growing trend even in the field of creativity. This paper examines which quantitative metrics can be used to comparatively analyse human-computer co-creativity with children. To study this question, 24 schoolchildren of age 10–11 wrote a poem with three co-creative poetry writing processes: a human-computer, a human-human, and a human-human-computer process. The computational participant in the processes was an AI-based application called the Poetry Machine. The children were asked to evaluate their user experience with a 5-point Likert-type questionnaire after each writing process and a comparative questionnaire after finishing all processes. The metrics used in the evaluation were immediate fun, long-term enjoyment, creativity, self-expression, outcome satisfaction, ease of starting and finishing writing, quality of ideas and support from others, and ownership.
Significant differences were found in fun, long-term enjoyment, quality of ideas, support, and ownership. The high number of statistically relevant results was enabled by exposing all participants to all writing processes, and the comparative questionnaire. The human-human-computer process was evaluated the best in long-term enjoyment and the human-computer process the weakest in support and idea quality. Creativity and ease of finishing writing turned out to be outlining metrics for the co-creative processes. 相似文献