How eye tracking data can enhance human performance in tomorrow's cockpit

How eye tracking data can enhance human performance in tomorrow’s cockpit. Results from a flight simulation study in FUTURE SKY SAFETY

What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling (ASMM) project of NASA s Aviation Safety and Security Program was to develop technologies that will enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. This presents a particular challenge in the aviation system where people are key components and human error is frequently cited as a major contributing factor or cause of incidents and accidents. In the aviation "world", information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. This report describes a conceptual model and an approach to automated analyses of textual data sources for the subjective perspective of the reporter of the incident to aid in understanding why an incident occurred. It explores a first-generation process for routinely searching large databases of textual reports of aviation incident or accidents, and reliably analyzing them for causal factors of human behavior (the why of an incident). We have defined a generic structure of information that is postulated to be a sound basis for defining similarities between aviation incidents. Based on this structure, we have introduced the simplifying structure, which we call the Scenario as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. We believe that it will be possible to design an automated analysis process guided by the structure of the Scenario that will aid aviation-safety experts to understand the systemic issues that are conducive to human error

Charting the edges of human performance

In the Horizon 2020 funded Future Sky Safety programme, the Human Performance Envelope project pushed airline pilots to the edges of their performance in real-time cockpit simulations, by increasing stress and workload, and decreasing situation awareness. The aim was to find out how such factors interact, and to detect the edges of human performance where some form of automation support should be employed to ensure safe continued flight. A battery of measures was used, from behavioural to physiological (e.g. heart rate, eye tracking and pupil dilation), to monitoring pilot performance in real time. Several measures – e.g. heart rate, heart rate variability, eye tracking, cognitive walkthrough, and Human Machine Interface (HMI) usability analysis – proved to be useful and relatively robust in detecting performance degradation, and determining where changes in information presentation are required to better support pilot performance in challenging situations. These results led to proposed changes in a prototype future cockpit human-machine interface, which were subsequently validated in a final simulation. The results also informed the development of a ‘Smart-Vest’ that can be worn by pilots to monitor a range of signals linked to performance

Interpersonal trust to enhance cyber crisis management

International audienceIn the field of cyber-security, software performance optimization is a major focus of research to better prevent cyber threats. However, once threats are detected, they have to be managed by a human operator or more often by human operators' joint actions. The purpose of this study is to show that in these collaborative situations, the interpersonal trust level between these actors shapes their handling of the threat. Forty-five participants performed, with twenty-eight different fictive teammates, a collaborative counting task that included aleatory phases of jamming. Each fictive teammate was described through two adjectives selected to induce a predefined level of interpersonal trust (low or high). The subject and his collaborator worked on different systems with different objects to count and different jamming phases. Nevertheless, each participant had the possibility of supervising his teammate's work by checking out his task and modifying his answers (number of targets and jamming events reported) if required. The subject was responsible for validating the team's final result. The experimental data show that, in this type of collaborative task, the interpersonal trust level has indeed an influence on the supervision strategy used and the team performance

Ecological and Specific Evidence-Based Safe Return To Play After Anterior Cruciate Ligament Reconstruction In Soccer Players: A New International Paradigm

Existing return to play (RTP) assessments have not demonstrated the ability to decrease risk of subsequent anterior cruciate ligament (ACL) injury after reconstruction (ACLR). RTP criteria are standardized and do not simulate the physical and cognitive activity required by the practice of sport. Most RTP criteria do not include an ecological approach. There are scientific algorithms as the "5 factor maximum model" that can identify risk profiles and help reduce the risk of a second anterior cruciate ligament injury. Nevertheless, these algorithms remain too standardized and do not include the situations experienced in games by soccer players. This is why it is important to integrate ecological situations specific to the environment of soccer players in order to evaluate players under conditions closest to their sporting activity, especially with high cognitive load. One should identify high risk players under two conditions: Clinical analyses commonly include assessments such as isokinetic testing, functional tests (hop tests, vertical force-velocity, profile), running, clinical assessments (range of motion and graft laxity), proprioception and balance (Star Excursion Balance Test modified, Y-Balance, stabilometry) and psychological parameters (kinesophobia, quality of life and fear of re-injury). Field testing usually includes game simulation, evaluation under dual-task conditions, fatigue and workload analysis, deceleration, timed-agility-test and horizontal force-velocity profiles. Although it seems important to evaluate strength, psychological variables and aerobic and anaerobic capacities, evaluation of neuromotor control in standard and ecological situations may be helpful for reducing the risk of injury after ACLR. This proposal for RTP testing after ACLR is supported by the scientific literature and attempts to approximate the physical and cognitive loads during a soccer match. Future scientific investigation will be required to demonstrate the validity of this approach. # Level of Evidence

1st Order Logic Formal Concept Analysis: From Logic Programming to Theory

In this paper, we analyze and define the introduction of 1st order logic in Formal Concept Analysis (FCA); the aims are both theoretical (as a complete model is needed) and applied (so as to improve expression power of FCA as a knowledge mining tool and the relevance of its results).   Our contribution consists in: i) the implementation of classical FCA in logic programming and the analysis of real cases, ii) the design of a complete 1st order FCA model, iii) the implementation of this 1st order FCA

A propos d'une mutation du récepteur CKIT dans le cas d'un GIST

AIX-MARSEILLE2-BU Méd/Odontol. (130552103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

1st Order Logic Formal Concept Analysis: from logic programming to theory

In this paper, we analyze and define the introduction of 1st order logic in Formal Concept Analysis (FCA); the aims are both theoretical (as a complete model is needed) and applied (so as to improve expression power of FCA as a knowledge mining tool and the relevance of its results).   Our contribution consists in: i) the implementation of classical FCA in logic programming and the analysis of real cases, ii) the design of a complete 1st order FCA model, iii) the implementation of this 1st order FCA