Fuzzy-associative-memory-based knowledge construction with an application to a human-machine interface

1999 ◽  
Vol 46 (4) ◽  
pp. 851-860 ◽  
Author(s):  
H. Ushida ◽  
T. Yamaguchi ◽  
T. Takagi
Keyword(s):  
Associative Memory ◽  
Knowledge Construction ◽  
Human Machine Interface ◽  
Fuzzy Associative Memory ◽  
Machine Interface

Designing the human machine interface in the ATIS domain

1990 ◽  
Author(s):  
B. Bly ◽  
P. J. Price ◽  
S. Park ◽  
S. Tepper ◽  
E. Jackson ◽  
...  
Keyword(s):  
Human Machine Interface ◽  
Machine Interface

scholarly journals Evaluation of Multimodal External Human–Machine Interface for Driverless Vehicles in Virtual Reality

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 687
Author(s):  
Jinzhen Dou ◽  
Shanguang Chen ◽  
Zhi Tang ◽  
Chang Xu ◽  
Chengqi Xue
Keyword(s):  
New Technology ◽  
Pedestrian Safety ◽  
Human Machine Interface ◽  
Visual Features ◽  
Visual Modality ◽  
Human Voice ◽  
Road Users ◽  
Machine Interface ◽  
Interaction Efficiency ◽  
Physical Features

With the development and promotion of driverless technology, researchers are focusing on designing varied types of external interfaces to induce trust in road users towards this new technology. In this paper, we investigated the effectiveness of a multimodal external human–machine interface (eHMI) for driverless vehicles in virtual environment, focusing on a two-way road scenario. Three phases of identifying, decelerating, and parking were taken into account in the driverless vehicles to pedestrian interaction process. Twelve eHMIs are proposed, which consist of three visual features (smile, arrow and none), three audible features (human voice, warning sound and none) and two physical features (yielding and not yielding). We conducted a study to gain a more efficient and safer eHMI for driverless vehicles when they interact with pedestrians. Based on study outcomes, in the case of yielding, the interaction efficiency and pedestrian safety in multimodal eHMI design was satisfactory compared to the single-modal system. The visual modality in the eHMI of driverless vehicles has the greatest impact on pedestrian safety. In addition, the “arrow” was more intuitive to identify than the “smile” in terms of visual modality.

SOLI: A Tiny Device for a New Human Machine Interface

2021 ◽  
Author(s):  
Saverio Trotta ◽  
Dave Weber ◽  
Reinhard W. Jungmaier ◽  
Ashutosh Baheti ◽  
Jaime Lien ◽  
...  
Keyword(s):  
Human Machine Interface ◽  
Machine Interface

scholarly journals Cobots in maxillofacial surgery – challenges for workplace design and the human-machine-interface

Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 488-493
Author(s):  
Florian Beuss ◽  
Frederik Schmatz ◽  
Marten Stepputat ◽  
Fabian Nokodian ◽  
Wilko Fluegge ◽  
...  
Keyword(s):  
Maxillofacial Surgery ◽  
Human Machine Interface ◽  
Workplace Design ◽  
Machine Interface

Co@N-CNT/MXene in situ grown on carbon nanotube film for multifunctional sensors and flexible supercapacitor

Nanoscale ◽  
2021 ◽  
Author(s):  
Qiufan Wang ◽  
Jiaheng Liu ◽  
Guofu Tian ◽  
Daohong Zhang
Keyword(s):  
Artificial Intelligence ◽  
Carbon Nanotube ◽  
Energy Storage ◽  
Storage Systems ◽  
Rapid Development ◽  
Human Machine Interface ◽  
Key Factors ◽  
Flexible Supercapacitor ◽  
Machine Interface

The rapid development of human-machine interface and artificial intelligence is dependent on flexible and wearable soft devices such as sensors and energy storage systems. One of the key factors for...

scholarly journals Improving Human Ground Control Performance in Unmanned Aerial Systems

2021 ◽  
Vol 13 (8) ◽  
pp. 188
Author(s):  
Marianna Di Gregorio ◽  
Marco Romano ◽  
Monica Sebillo ◽  
Giuliana Vitiello ◽  
Angela Vozella
Keyword(s):  
Situation Awareness ◽  
Interface Design ◽  
Human Machine Interface ◽  
Ground Control ◽  
Entire Group ◽  
Unmanned Aerial Systems ◽  
Ground Control Station ◽  
Machine Interface ◽  
Team Situation Awareness ◽  
Aerial Systems

The use of Unmanned Aerial Systems, commonly called drones, is growing enormously today. Applications that can benefit from the use of fleets of drones and a related human–machine interface are emerging to ensure better performance and reliability. In particular, a fleet of drones can become a valuable tool for monitoring a wide area and transmitting relevant information to the ground control station. We present a human–machine interface for a Ground Control Station used to remotely operate a fleet of drones, in a collaborative setting, by a team of multiple operators. In such a collaborative setting, a major interface design challenge has been to maximize the Team Situation Awareness, shifting the focus from the individual operator to the entire group decision-makers. We were especially interested in testing the hypothesis that shared displays may improve the team situation awareness and hence the overall performance. The experimental study we present shows that there is no difference in performance between shared and non-shared displays. However, in trials when unexpected events occurred, teams using shared displays-maintained good performance whereas in teams using non-shared displays performance reduced. In particular, in case of unexpected situations, operators are able to safely bring more drones home, maintaining a higher level of team situational awareness.

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