Crew Resource Management Doctrine Applicability to Human-Machine Interaction in Commercial Aircraft

2017 ◽  
pp. 564-570
Author(s):  
Aysen K. Taylor
Keyword(s):  
Resource Management ◽  
Crew Resource Management ◽  
Commercial Aircraft ◽  
Human Machine Interaction ◽  
Machine Interaction

Integrating Safety and Crew Resource Management (CRM) Aspects in the Recurrent Training of Cabin Crew Members

2011 ◽  
Vol 1 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Sandrina Ritzmann ◽  
Annette Kluge ◽  
Vera Hagemann ◽  
Margot Tanner
Keyword(s):  
Resource Management ◽  
Integrated Design ◽  
Crew Resource Management ◽  
Training Module ◽  
Cabin Crew ◽  
Training Cycle ◽  
Aviation Training ◽  
Training Format ◽  
Instructional Design Principles ◽  
Practical Instruction

Recurrent training of cabin crew should include theoretical and practical instruction on safety as well as crew resource management (CRM) issues. The endeavors of Swiss International Air Lines Ltd. and Swiss Aviation Training Ltd. to integrate CRM and safety aspects into a single training module were evaluated. The objective of the integration was to make CRM more tangible and ease acquisition of competencies and transfer of CRM training content to practice by showing its relevance in relation to safety tasks. It was of interest whether the integrated design would be mirrored in a more favorable perception by the trainees as measured with a questionnaire. Participants reacted more positively to the integrated training than to stand-alone CRM training, although the integrated training was judged as being slightly more difficult and less oriented toward instructional design principles. In a range of forced-choice questions, the majority of participants opted for an integrated training format because it was seen as livelier and more interesting and also more practically relevant. For the forthcoming training cycle, a better alignment of training with instructional principles and an even higher degree of training integration by using simulator scenarios are striven for.

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

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