Showing papers by "Defence Science and Technology Organisation published in 2020"
TL;DR: A set of features represents EEG indicators for the objective assessment of cognitive workload across subjects that could be used for augmented intelligence in human-autonomy teaming scenarios, and form the basis for the work on designing a closed-loop augmented cognition system for human-swarm teaming.
Abstract: Background: Although many electroencephalographic (EEG) indicators have been proposed in the literature, it is unclear which of the power bands and various indices are best as indicators of mental workload. Spectral powers (Theta, Alpha, and Beta) and ratios (Beta/(Alpha + Theta), Theta/Alpha, Theta/Beta) were identified in the literature as prominent indicators of cognitive workload. Objective: The aim of the present study is to identify a set of EEG indicators that can be used for the objective assessment of cognitive workload in a multitasking setting and as a foundational step toward a human-autonomy augmented cognition system. Methods: The participants' perceived workload was modulated during a teleoperation task involving an unmanned aerial vehicle (UAV) shepherding a swarm of unmanned ground vehicles (UGVs). Three sources of data were recorded from sixteen participants (n = 16): heart rate (HR), EEG, and subjective indicators of the perceived workload using the Air Traffic Workload Input Technique (ATWIT). Results: The HR data predicted the scores from ATWIT. Nineteen common EEG features offered a discriminatory power of the four workload setups with high classification accuracy (82.23%), exhibiting a higher sensitivity than ATWIT and HR. Conclusion: The identified set of features represents EEG indicators for the objective assessment of cognitive workload across subjects. These common indicators could be used for augmented intelligence in human-autonomy teaming scenarios, and form the basis for our work on designing a closed-loop augmented cognition system for human-swarm teaming.
50 citations
TL;DR: Shape memory alloys (SMAs) are a class of functional materials with the ability to regain their original shapes after a large inelastic deformation upon external stimuli as discussed by the authors, and they have been employed in many applications in different fields.
Abstract: Shape memory alloys (SMAs) are a class of functional materials with the ability to regain their original shapes after a large inelastic deformation upon external stimuli. In recent years, SMAs have been employed in many applications in different fields. Nitinol is the most widely used SMA due to its outstanding properties such as shape memory effect, superelasticity, biocompatibility, and corrosion resistance among other types of SMAs. Some efforts are also made to implement SMAs on filtration devices that require deployable structures. This motivates the authors to write a review of the recent developments in the field of SMA based filtration devices as far as the use of SMAs is concerned. The present work provides a brief overview of history and basics of SMAs. This paper then reviews and discusses the recent progress and applications of SMA based filtration devices and the challenges of these filtration devices. It is found that most devices are made of nitinol. The aim of this paper is to introduce SMA based filtration devices and promote future developments of functional filtration applications.
11 citations
19 Apr 2020
TL;DR: In this article, the authors present a method for contaminant removal in splash-lubricated gearboxes, such as some gearboxes are used in helicopters and military vehicles, which are widely used in many industries.
Abstract: Splash-lubricated gearboxes are widely used in many industries. Contaminant removal systems are rarely employed in splash-lubricated gearboxes, such as some gearboxes are used in helicopters and mi...
1 citations