5 research outputs found
Reduced Separation during Final Approach: A procedural time based separation solution to optimize landing delivery
No full textAerospace EngineeringControl & OperationsAerospace Transport & Operation
Optimizing the energy and charging infrastructure costs for regional electric aircraft operations: A case study in the Dutch Caribbean
No full textCommercial electric aircraft operations are foreseen in the coming five to ten years. For an airport to be ready for this introduction, energy infrastructure requirements have already been subject to various research topics. Most research in this field only focused on cost minimization of the number of chargers given a fixed flight schedule. This research however implements flexibility into the flight schedule and incorporates the energy provision in terms of renewable energy sources in combination with battery storage. Considering energy infrastructure costs as well as operational costs, the goal of the newly proposed Mixed-Integer Linear Programming model remains cost minimization. Besides a daily operational model, an additional energy balance focused optimization has been applied for data of an entire year. In this second model, energy from the local grid may be drawn and returned to come to a cost optimized solution. Both models have been run for a case-study on Bonaire International Airport whereinter-island flights to and from its two neighboring islands were electrified. A combination of solar panels and battery energy storage was found to be most cost efficient while sensitivity analysis showed many insights into possible energy business cases for airports.Aerospace Engineering | Air Transport and Operation
Statistical signature of subtle behavioural changes in large-scale behavioural assays
No full textPosted May 05, 2024 on bioRxiv.International audienceThe central nervous system can generate various behaviours, including motor responses, which we can observe through video recordings. Recent advancements in genetics, automated behavioural acquisition at scale, and machine learning enable us to link behaviours to their underlying neural mechanisms causally. Moreover, in some animals, such as the Drosophila larva, this mapping is possible at unprecedented scales of millions of animals and single neurons, allowing us to identify the neural circuits generating particular behaviours. These high-throughput screening efforts are invaluable, linking the activation or suppression of specific neurons to behavioural patterns in millions of animals. This provides a rich dataset to explore how diverse nervous system responses can be to the same stimuli. However, challenges remain in identifying subtle behaviours from these large datasets, including immediate and delayed responses to neural activation or suppression, and understanding these behaviours on a large scale. We introduce several statistically robust methods for analyzing behavioural data in response to these challenges: 1) A generative physical model that regularizes the inference of larval shapes across the entire dataset. 2) An unsupervised kernel-based method for statistical testing in learned behavioural spaces aimed at detecting subtle deviations in behaviour. 3) A generative model for larval behavioural sequences, providing a benchmark for identifying complex behavioural changes. 4) A comprehensive analysis technique using suffix trees to categorize genetic lines into clusters based on common action sequences. We showcase these methodologies through a behavioural screen focused on responses to an air puff, analyzing data from 280,716 larvae across 568 genetic lines. Author Summary There is a significant gap in understanding between the architecture of neural circuits and the mechanisms of action selection and behaviour generation. Drosophila larvae have emerged as an ideal platform for simultaneously probing behaviour and the underlying neuronal computation [1]. Modern genetic tools allow efficient activation or silencing of individual and small groups of neurons. Combining these techniques with standardized stimuli over thousands of individuals makes it possible to relate neurons to behaviour causally. However, extracting these relationships from massive and noisy recordings requires the development of new statistically robust approaches. We introduce a suite of statistical methods that utilize individual behavioural data and the overarching structure of the behavioural screen to deduce subtle behavioural changes from raw data. Given our study’s extensive number of larvae, addressing and preempting potential challenges in body shape recognition is critical for enhancing behaviour detection. To this end, we have adopted a physics-informed inference model. Our first group of techniques enables robust statistical analysis within a learned continuous behaviour latent space, facilitating the detection of subtle behavioural shifts relative to reference genetic lines. A second array of methods probes for subtle variations in action sequences by comparing them to a bespoke generative model. Together, these strategies have enabled us to construct representations of behavioural patterns specific to a lineage and identify a roster of ”hit” neurons with the potential to influence behaviour subtly
Evaluation of Educational Quality Under a Six Sigma Approach to Engineering Degrees in Colombia
No full textIn this research, a methodology is developed to measure the quality of the Colombian educational system by analyzing universities and their academic programs. For the above, a Six Sigma approach is used as a tool for educational management in order to classify, evaluate and analyze the educational system having two approaches: universities and academic programs. Consequently, this article is divided into 5 sections: In the first section, a review of research carried out on quality and HEIs is carried out. The second section presents the research methodology, describes the study population and variables. The third section shows the results derived from the application of the Six Sigma methodology. The fourth section presents the discussion and recommendations. Finally, the fifth section presents the conclusions. Now, within the most significant findings, it is found that the sigma level of the Colombian educational system is found at Z = 2.17 and Y = 75% and is considered, according to what is established in the methodology of this work, as an acceptable level. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG
