Quantitative assessment of pilot-endured workloads during helicopter flying emergencies: an analysis of physiological parameters during an autorotation.

The procedures to be performed after sudden engine failure of a single-engine helicopter impose high workload on pilots. The maneuver to regain aircraft control and safe landing is called autorotation. The safety limits to conduct this maneuver are based on the aircraft height versus speed diagram, which is also known as "Dead Man's Curve". Flight-test pilots often use subjective methods to assess the difficulty to conduct maneuvers in the vicinity of this curve. We carried out an extensive flight test campaign to verify the feasibility of establishing quantitative physiological parameters to better assess the workload endured by pilots undergoing those piloting conditions. Eleven pilots were fully instrumented with sensors and had their physiological reactions collected during autorotation maneuvers. Our analyses suggested that physiological measurements (heart rate and electrodermal activity) can be successfully recorded and useful to capture the most effort-demanding effects during the maneuvers. Additionally, the helicopter's flight controls displacements were also recorded, as well as the pilots' subjective responses evaluated by the Handling Qualities Rate scale. Our results revealed that the degree of cognitive workload was associated with the helicopter's flight profile concerning the Height-Speed diagram and that the strain intensity showed a correlation with measurable physiological responses. Recording flight controls displacement and quantifying the pilot's subjective responses show themselves as natural effective candidates to evaluate the intensity of cognitive workload in such maneuvers.

Return on Scientific Investment - RoSI: a PMO dynamical index proposal for scientific projects performance evaluation and management.

OBJECTIVE: To propose a measure (index) of expected risks to evaluate and follow up the performance analysis of research projects involving financial and adequate structure parameters for its development. METHODS: A ranking of acceptable results regarding research projects with complex variables was used as an index to gauge a project performance. In order to implement this method the ulcer index as the basic model to accommodate the following variables was applied: costs, high impact publication, fund raising, and patent registry. The proposed structured analysis, named here as RoSI (Return on Scientific Investment) comprises a pipeline of analysis to characterize the risk based on a modeling tool that comprises multiple variables interacting in semi-quantitatively environments. RESULTS: This method was tested with data from three different projects in our Institution (projects A, B and C). Different curves reflected the ulcer indexes identifying the project that may have a minor risk (project C) related to development and expected results according to initial or full investment. CONCLUSION: The results showed that this model contributes significantly to the analysis of risk and planning as well as to the definition of necessary investments that consider contingency actions with benefits to the different stakeholders: the investor or donor, the project manager and the researchers.

Return on Scientific Investment - RoSI: a PMO dynamical index proposal for scientific projects performance evaluation and management / Retorno sobre o Investimento Científico - RoSI: uma proposta de índice dinâmico PMO para avaliação de desempenho e gestão de projetos científicos

Objective: To propose a measure (index) of expected risks to evaluate and follow up the performance analysis of research projects involving financial and adequate structure parameters for its development. Methods: A ranking of acceptable results regarding research projects with complex variables was used as an index to gauge a project performance. In order to implement this method the ulcer index as the basic model to accommodate the following variables was applied: costs, high impact publication, fund raising, and patent registry. The proposed structured analysis, named here as RoSI (Return on Scientific Investment) comprises a pipeline of analysis to characterize the risk based on a modeling tool that comprises multiple variables interacting in semi-quantitatively environments. Results: This method was tested with data from three different projects in our Institution (projects A, B and C). Different curves reflected the ulcer indexes identifying the project that may have a minor risk (project C) related to development and expected results according to initial or full investment. Conclusion: The results showed that this model contributes significantly to the analysis of risk and planning as well as to the definition of necessary investments that consider contingency actions with benefits to the different stakeholders: the investor or donor, the project manager and the researchers.

Objetivos: Propor um novo índice adaptado de riscos esperados para avaliar, planejar e acompanhar projetos de pesquisa que dependem de financiamento e estrutura adequada para o seu desenvolvimento. Métodos: Uma grade de resultados aceitáveis em relação aos projetos de pesquisa com variáveis complexas foi aplicada como índice para mensurar o desempenho dos projetos. Para sua implementação foram utilizados o índice de ulcer como medida básica para acomodar as seguintes variáveis: custos, fator de impacto de publicação, levantamento de fundos e registro de patentes. Obteve-se uma ferramenta de modelagem aqui denominada "Retorno sobre Investimento Científico" (RoSI) que permitiu mensurar e acompanhar projetos de modo analítico, levando-se em conta o conjunto dos resultados esperados, as respectivas variáveis e suas interações analisadas num ambiente virtual semi-quantitativo. Resultados: O modelo foi testado para avaliação de três projetos da Instituição (projetos A, B, e C). Diferentes curvas refletem os índices de ulcer identificando o projeto de menor risco (projeto C) relacionado ao desenvolvimento e resultados esperados de acordo com o investimento inicial ou total considerado. Conclusão: O modelo contribuiu tanto para a quantificação dos riscos e planejamento, quanto para a definição de investimentos necessários que contemplem ações de contingência, beneficiando os diferentes stakeholders envolvidos: o financiador (investidor ou doador), o gestor e os pesquisadores.