Transactions on Computational Science XXXII

Many studies have shown that most maritime accidents are attributed to human error as the initiating cause, resulting in a need for study of human factors to improve safety in maritime transportation. Among the various techniques, Electroencephalography (EEG) has the key advantage of high time resolution, with the possibility to continuously monitor brain states including human mental workload, emotions, stress levels, etc. In this paper, we proposed a novel mental workload recognition algorithm using deep learning techniques that outperformed the state-of art algorithms and successfully applied it to monitor crew members’ brain states in a maritime simulator. We designed and carried out an experiment to collect the EEG data, which was used to study stress and distribution of mental workload among crew members during collaborative tasks in the ship’s bridge simulator. The experiment consisted of two parts. In part 1, 3 maritime trainees fulfilled the tasks with and without an experienced captain. The results of EEG analyses showed that 2 out of 3 trainees had less workload and stress when the experienced captain was present. In part 2, 4 maritime trainees collaborated with each other in the simulator. Our findings showed that the trainee who acted as the captain had the highest stress and workload levels while the other three trainees experienced low workload and stress due to the shared work and responsibility. These results suggest that EEG is a promising evaluation tool applicable in human factors study for the maritime domain.

Synchronising state between multiple connected clients can be a challenging task. However, the need to carry this out is becoming much greater as a larger number of software packages are becoming collaborative across a network. Online multiplayer games in particular are already extremely popular but the synchronisation methods and architecture have largely remained the same. OpenGL|Distributed, presented here, aims to provide not only an alternative to this architecture allowing for a greatly simplified development pipeline, but also the opportunity for a number of additional features and design patterns. The architecture provided by OpenGL|D is such that no state information needs to be transferred between clients. Instead, the OpenGL API has been utilised as a platform agnostic protocol. This means that graphical calls can be streamed to each client rather than relying on manual synchronisation of application domain specific data. Initial test results are discussed, including performance evaluation using data from a number of small prototypes developed within a constrained 48-h timeframe. These results are compared and evaluated against a more traditional approach to network multiplayer by id Software’s QuakeWorld client. It should be noted that this article is an extended version of the work we published in the proceedings of the Cyberworlds 2017 conference [1].