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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Vliv preventivních bezpečnostních opatření na nehodovost v leteckém provozu ČR / Effect of preventive security measures for air traffic accidents in the Czech Republic

Jonáš, Jiří January 2012 (has links)
The thesis objective is considerations of effect safety campaigns, which are issued by CAA CZ, on safety of air traffic in Czech Republic. In thesis are considered categories of aircrafts from 0 to 5700 kg except for Ultralight Aircrafts in period 1993 to 2011. Recognition involves describe given campaigns, assurance of information, processing and final assessment of efficiency published safety campaigns.
2

<b>Safety and mobility improvement of mixed traffic using optimization- And Learning-based methods</b>

Runjia Du (9756128) 11 December 2023 (has links)
<p dir="ltr">Traffic safety and congestion are global concerns. Autonomous vehicles (AVs) are expected to enhance transportation safety and reduce congestion. However, achieving their full potential requires 100% market penetration, a challenging task. This study addresses key issues in mixed traffic environments, where human-driven vehicles (HDVs) and connected autonomous vehicles (CAVs) coexist. A number of critical questions persist: 1) inadequate exploration of human errors (errors originating from non-CAV sources) in mixed traffic; 2): limited focus on information selection and learning efficiency in network-level rerouting, particularly in highly dynamic environments; 3) inadequacy of personalized element driver inputs in motion-planning frameworks; 4) lack of consideration of user privacy concerns.</p><p dir="ltr">With the goal of advancing the existing knowledge in this field and shedding light on these matters, this dissertation introduces multiple frameworks. These frameworks leverage connectivity and automation to improve safety and mobility in mixed traffic, addressing various research levels, including local-level and network-level safety enhancement, as well as network-level and global-level mobility enhancement. With optimization- and learning-based methods implemented (Model Predictive Control, Deep Neural Network, Deep Reinforcement Learning, Transformer model and Federated Learning), frameworks introduced in this dissertation are expected to help highway agencies and vehicle manufacturers improve the safety and efficiency of traffic flow in the mixed-traffic era. Our research findings revealed increased crash-avoidance rates in critical situations, enhanced accuracy in predicting lane changes, improved dynamic rerouting within urban areas, and the implementation of effective data-sharing mechanisms with a focus on user privacy. This research underscores the potential of connectivity and automation to significantly enhance mixed-traffic safety and mobility.</p>
3

Safety management in times of crisis: Lessons learned from a nationwide status-analysis on German intensive care units during the COVID-19 pandemic

Schmidt, Michelle, Lambert, Sophie Isabelle, Klasen, Martin, Sandmeyer, Benedikt, Lazarovici, Marc, Jahns, Franziska, Trefz, Lara Charlott, Hempel, Gunther, Sopka, Sasa 03 May 2024 (has links)
Background: The status of Safety Management is highly relevant to evaluate an organization’s ability to deal with unexpected events or errors, especially in times of crisis. However, it remains unclear to what extent Safety Management was developed and suffciently implemented within the healthcare system during the COVID-19 pandemic. Providing insights of potential for improvement is expected to be directional for ongoing Safety Management efforts, in times of crisis and beyond. Method: A nationwide survey study was conducted among healthcare professionals and auxiliary staff on German Intensive Care Units (ICUs) evaluating their experiences during the first wave of the COVID-19 pandemic. Error Management and Patient Safety Culture (PSC) measures served to operationalize Safety Management. Data were analyzed descriptively and by using quantitative content analysis (QCA). Results: Results for n = 588 participants from 53 hospitals show that there is a gap between errors occurred, reported, documented, and addressed. QCA revealed that low quality of safety culture (27.8%) was the most mentioned reason for errors not being addressed. Overall, ratings of PSC ranged from 26.7 to 57.9% positive response with Staffng being the worst and Teamwork Within Units being the best rated dimension. While assessments showed a similar pattern, medical staff rated PSC on ICUs more positively in comparison to nursing staff. Conclusion: The status-analysis of Safety Management in times of crisis revealed relevant potential for improvement. Human Factor plays a crucial role in the occurrence and the way errors are dealt with on ICUs, but systemic factors should not be underestimated. Further intensified efforts specifically in the fields of staffng and error reporting, documentation and communication are needed to improve Safety Management on ICUs. These findingsmight also be applicable across nations and sectors beyond the medical field.

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