Towards objective human performance measurement for maritime safety: A new psychophysiological data-driven machine learning method

Human errors significantly contribute to transport accidents. Human performance measurement (HPM) is crucial to ensure human reliability and reduce human errors. However, how to address and reduce the subjective bias introduced by assessors in HPM and seafarer certification remains a key research challenge. This paper aims to develop a new psychophysiological data-driven machine learning method to realize the effective HPM in the maritime sector. It conducts experiments using a functional Near-Infrared Spectroscopy (fNIRS) technology and compares the performance of two groups in a maritime case (i.e. experienced and inexperienced seafarers in terms of different qualifications by certificates), via an Artificial Neural Network (ANN) model. The results have generated insightful implications and new contributions, including (1) the introduction of an objective criterion for assessors to monitor, assess, and support seafarer training and certification for maritime authorities; (2) the quantification of human response under specific missions, which serves as an index for a shipping company to evaluate seafarer reliability; (3) a supportive tool to evaluate human performance in complex emerging systems (e.g. Maritime Autonomous Surface Ship (MASS)) design for ship manufactures and shipbuilders

Assessing Continuous Operator Workload with a Hybrid Scaffolded Neuroergonomic Modeling Approach

Excerpt: We aimed to predict operator workload from neurological data using statistical learning methods to fit neurological-to-state-assessment models. Adaptive systems require real-time mental workload assessment to perform dynamic task allocations or operator augmentation as workload issues arise. Neuroergonomic measures have great potential for informing adaptive systems, and we combine these measures with models of task demand as well as information about critical events and performance to clarify the inherent ambiguity of interpretation

2018 Faculty Excellence Showcase, AFIT Graduate School of Engineering & Management

Excerpt: As an academic institution, we strive to meet and exceed the expectations for graduate programs and laud our values and contributions to the academic community. At the same time, we must recognize, appreciate, and promote the unique non-academic values and accomplishments that our faculty team brings to the national defense, which is a priority of the Federal Government. In this respect, through our diverse and multi-faceted contributions, our faculty, as a whole, excel, not only along the metrics of civilian academic expectations, but also along the metrics of military requirements, and national priorities

Academic Year 2019-2020 Faculty Excellence Showcase, AFIT Graduate School of Engineering & Management

An excerpt from the Dean\u27s Message: There is no place like the Air Force Institute of Technology (AFIT). There is no academic group like AFIT’s Graduate School of Engineering and Management. Although we run an educational institution similar to many other institutions of higher learning, we are different and unique because of our defense-focused graduate-research-based academic programs. Our programs are designed to be relevant and responsive to national defense needs. Our programs are aligned with the prevailing priorities of the US Air Force and the US Department of Defense. Our faculty team has the requisite critical mass of service-tested faculty members. The unique composition of pure civilian faculty, military faculty, and service-retired civilian faculty makes AFIT truly unique, unlike any other academic institution anywhere

Air Force Institute of Technology Research Report 2017

This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Proposta de uma equação matemática para a integração quantitativa do fator humano em projetos de simulação a eventos discretos

In discrete event simulation (DES) projects, generally, some computational validation criteria are not defined assertively and human factors are not integrated and considered in the input data modeling phase. An erroneous assumption made during the input data modeling step is that workers operate at an unchanging rate. This ends up being a problem for the modeling of production systems, especially if the process to be modeled involves a large amount of manual work. In this context, the objective of this thesis is to propose a mathematical equation to integrate three human factors in an DES project. And the innovation of this research is based on the proposed mathematical equation, which intends to model and integrate human factors, circadian rhythm, performance and learning and apply them through the equation in three different DES projects. The adherence of the proposed equation was verified with the help of validation tests, used in order to validate the developed computational model. Therefore, the aforementioned equation was conceived in this research to represent the human factor from the processing times of each activity considered in each object of study. In the methodological stage, the system conceived in this thesis was presented, and six scenarios were planned, CIA, CIB and CIC that do not consider human factors, circadian rhythm, performance and learning. And the CIIA, CIIB and CIIC scenarios that consider, through the proposed equation, these three human factors. Finally, a quantitative validation was performed using the two-sample t test and a qualitative validation using the Turing Test on the results from the computational model. As a conclusion, it was found that the validation of the computational model conducted through the two techniques mentioned above did not occur for the CIA, CIB and CIC scenarios and, therefore, only occurred partially or in full, for the CIIA, CIIB and CIIC. Therefore, it was found that the computational validation in an DES project is influenced when these three human factors are considered and the proposed mathematical equation is a novelty for researchers in the field of discrete-event simulation.Em projetos de simulação a eventos discretos (SED), geralmente, alguns critérios de validação computacional não são definidos de forma assertiva e os fatores humanos não são integrados e considerados na fase de modelagem dos dados de entrada. Uma suposição errônea, assumida durante a etapa da modelagem dos dados de entrada é que os trabalhadores operam a uma taxa imutável. Isso acaba sendo um problema para a modelagem de sistemas produtivos, principalmente, se o processo a ser modelado envolver uma ampla parcela de trabalho manual. Neste contexto, o objetivo desta tese é propor uma equação matemática para integrar três fatores humanos em um projeto de SED. E a inovação desta pesquisa baseia-se na equação matemática proposta, que pretende modelar e integrar os fatores humanos, ritmo circadiano, performance e aprendizagem e aplicá-los por meio da equação em três projetos distintos de SED. A aderência da equação proposta foi verificada com o auxílio de testes de validação, utilizados, de modo a validar o modelo computacional desenvolvido. Portanto, a supracitada equação foi concebida nesta pesquisa para representar o fator humano a partir dos tempos de processamento de cada atividade considerada em cada objeto de estudo. Na etapa metodológica foi apresentada a sistemática concebida na presente tese, e foram planejados seis cenários, CIA, CIB e CIC que não consideram os fatores humanos, ritmo circadiano, performance e aprendizagem. E os cenários CIIA, CIIB e CIIC que consideram, por meio da equação proposta, esses três fatores humanos. Finalmente, foi realizado uma validação quantitativa por meio do teste two-sample t test e uma validação qualitativa usando o Teste de Turing nos resultados provenientes do modelo computacional. Como conclusão, ficou constatado que a validação do modelo computacional conduzida por meio das duas técnicas, citadas acima, não ocorreu para os cenários CIA, CIB e CIC e, logo, somente ocorreu de forma parcial ou integral, para os cenários CIIA, CIIB e CIIC. Por conseguinte, verificou-se que a validação computacional em um projeto de SED é influenciada quando esses três fatores humanos são considerados e a equação matemática proposta é uma novidade para os pesquisadores da área de simulação a eventos discretos

Topological Changes in the Functional Brain Networks Induced by Isometric Force Exertions Using a Graph Theoretical Approach: An EEG-based Neuroergonomics Study

Neuroergonomics, the application of neuroscience to human factors and ergonomics, is an emerging science focusing on the human brain concerning performance at work and in everyday settings. The advent of portable neurophysiological methods, including electroencephalography (EEG), has enabled measurements of real-time brain activity during physical tasks without restricting body movements. However, the EEG signatures of different physical exertion activity levels that involve the musculoskeletal system in everyday settings remain poorly understood. Furthermore, the assessment of functional connectivity among different brain regions during different force exertion levels remains unclear. One approach to investigating the brain connectome is to model the underlying mechanism of the brain as a complex network. This study applied employed a graph-theoretical approach to characterize the topological properties of the functional brain network induced by predefined force exertion levels, namely extremely light (EL), light (L), somewhat hard (SWH), hard (H), and extremely hard (EH) in two frequency bands, i.e., alpha and beta. Twelve female participants performed an isometric force exertion task and rated their perception of physical comfort at different physical exertion levels. A CGX-Mobile-64 EEG was used for recording spontaneous brain electrical activity. After preprocessing the EEG data, a source localization method was applied to study the functional brain connectivity at the source level. Subsequently, the alpha and beta networks were constructed by calculating the coherence between all pairs of 84 brain regions of interests that were selected using Brodmann Areas. Graph -theoretical measures were then employed to quantify the topological properties of the functional brain networks at different levels of force exertions at each frequency band. During an \u27extremely hard\u27 exertion level, a small-world network was observed for the alpha coherence network, whereas an ordered network was observed for the beta coherence network. The results suggest that high-level force exertions are associated with brain networks characterized by a more significant clustering coefficient, more global and local efficiency, and shorter characteristic path length under alpha coherence. The above suggests that brain regions are communicating and cooperating to a more considerable degree when the muscle force exertions increase to meet physically challenging tasks. The exploration of the present study extends the current understanding of the neurophysiological basis of physical efforts with different force levels of human physical exertion to reduce work-related musculoskeletal disorders