The paper presents a framework that through structured analysis of accident reports explores the differences between practice and academic literature as well amongst organizations regarding their views on human error. The framework is based on the hypothesis that the wording of accident reports reflects the safety thinking and models that have been applied during the investigation, and includes 10 aspects identified in the state-of-the-art literature. The framework was applied to 52 air accident reports published by the Dutch Safety Board (DSB) and 45 ones issued by the Australian Transport Safety Bureau (ATSB) from 1999 to 2014. Frequency analysis and statistical tests showed that the presence of the aspects in the accident reports varied from 32.6% to 81.7%, and revealed differences between the ATSB and the DSB approaches to human error. However, in overall safety thinking have not changed over time, thus, suggesting that academic propositions might have not yet affected practice dramatically.
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Background To gain insight into the role of plantar intrinsic foot muscles in fall-related gait parameters in older adults, it is fundamental to assess foot muscles separately. Ultrasonography is considered a promising instrument to quantify the strength capacity of individual muscles by assessing their morphology. The main goal of this study was to investigate the intra-assessor reliability and measurement error for ultrasound measures for the morphology of selected foot muscles and the plantar fascia in older adults using a tablet-based device. The secondary aim was to compare the measurement error between older and younger adults and between two different ultrasound machines. Methods Ultrasound images of selected foot muscles and the plantar fascia were collected in younger and older adults by a single operator, intensively trained in scanning the foot muscles, on two occasions, 1–8 days apart, using a tablet-based and a mainframe system. The intra-assessor reliability and standard error of measurement for the cross-sectional area and/or thickness were assessed by analysis of variance. The error variance was statistically compared across age groups and machines. Results Eighteen physically active older adults (mean age 73.8 (SD: 4.9) years) and ten younger adults (mean age 21.9 (SD: 1.8) years) participated in the study. In older adults, the standard error of measurement ranged from 2.8 to 11.9%. The ICC ranged from 0.57 to 0.97, but was excellent in most cases. The error variance for six morphology measures was statistically smaller in younger adults, but was small in older adults as well. When different error variances were observed across machines, overall, the tablet-based device showed superior repeatability. Conclusions This intra-assessor reliability study showed that a tablet-based ultrasound machine can be reliably used to assess the morphology of selected foot muscles in older adults, with the exception of plantar fascia thickness. Although the measurement errors were sometimes smaller in younger adults, they seem adequate in older adults to detect group mean hypertrophy as a response to training. A tablet-based ultrasound device seems to be a reliable alternative to a mainframe system. This advocates its use when foot muscle morphology in older adults is of interest.
MULTIFILE
This paper aims to describe how we change our mind. As any human knows from his or her own experience, this does not always come naturally to us. This dissertation therefore aims to find fault in Seneca’s assertion: not only to err is human, but it is also human to persist in this mistake despite evidence to the contrary.In this paper I will argue that changing one’s mind is regulated through emotions, building on Damasio’s thoughts that emotions are not a luxury, but essential to rational thinking and normal behavior. His landmark book “Descarte’s Error“ (Damasio and Sutherland 1996) inspired the title of the current work. This research has been triggered by my experience in industry, where I have been lucky enough to have collaborated with many talented, friendly and rather stubborn people for over 20 years.Referentiede Boer, R.J. (2011), Seneca's Error: The Intervening Effect of Emotions on Mental Model Preservation , Symposium on Human Factors for Future Aviation, Schiphol Oost, The Netherlands
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Renewable energy, particularly offshore wind turbines, plays a crucial role in the Netherlands' and EU energy-transition-strategies under the EU Green Deal. The Dutch government aims to establish 75GW offshore wind capacity by 2050. However, the sector faces human and technological challenges, including a shortage of maintenance personnel, limited operational windows due to weather, and complex, costly logistics with minimal error tolerance. Cutting-edge robotic technologies, especially intelligent drones, offer solutions to these challenges. Smaller drones have gained prominence through applications identifying, detecting, or applying tools to various issues. Interest is growing in collaborative drones with high adaptability, safety, and cost-effectiveness. The central practical question from network partners and other stakeholders is: “How can we deploy multiple cooperative drones for maintenance of wind turbines, enhancing productivity and supporting a viable business model for related services?” This is reflected in the main research question: "Which drone technologies need to be developed to enable collaborative maintenance of offshore wind turbines using multiple smaller drones, and how can an innovative business model be established for these services? In collaboration with public and private partners, Saxion, Hanze, and RUG will research the development of these collaborative drones and investigate the technology’s potential. The research follows a Design Science Research methodology, emphasizing solution-oriented applied research, iterative development, and rigorous evaluation. Key technological building blocks to be developed: • Morphing drones, • Intelligent mechatronic tools, • Learning-based adaptive interaction controllers and collaborations. To facilitate the sustainable industrial uptake of the developed technologies, appropriate sustainable business models for these technologies and services will be explored. The project will benefit partners by enhancing their operations and business. It will contribute to renewing higher professional education and may lead to the creation of spin-offs/spinouts which bring this innovative technology to the society, reinforcing the Netherlands' position as a leading knowledge economy.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
Het lopende Bird’s Eye Perspective onderzoek ontwikkelen we door naar een leeromgeving 3.0 waarin wij de mogelijkheden van conversatie analyse en algoritmes toepassen op sociale media berichten. De leeromgeving tracht communicatieprofessionals te trainen in het opmerken van opkomende issues in het online gesprek.
