The General Data Protection Regulation (GDPR) requires data controllers to implement end-to-end compliance. Controllers must therefore ensure that the terms agreed with the data subject and their own obligations under GDPR are respected in the data flows from data subject to controllers, processors and sub-processors (i.e. data supply chain).
Continue readingThe assessment of the digital transformation progress is essential to understand and undertake in order to evaluate the level of maturity of data-driven companies in terms of data capabilities and to plan for improvement actions.
Continue readingMaturity models are helpful business tools that refine and develop how organizations conduct their businesses and benchmark their maturity status against a scale or with industry peers. They serve to prioritize the actions for improvement better and control the progress in reaching the target maturity stage.
Continue readingIn this paper, we propose a framework for image classification tasks, named MIC, that takes as input multi-view images, such as RGB-T images for surveillance purposes. We combine auto-encoder and generative adversarial network architectures to ensure the multi-view embedding in a common latent space.
Continue readingFor safety-critical systems involving AI components (such as in planes, cars, or healthcare), safety and associated certification tasks are one of the main challenges, which can become costly and difficult to address.
One key aspect is to ensure that the decisions a machine-learning classifier makes are properly calibrated.
Continue readingMolecular pathway databases represent cellular processes in a structured and standardized way. These databases support the community-wide utilization of pathway information in biological research and the computational analysis of high-throughput biochemical data. We present Padhoc, a pipeline for pathway ad hoc reconstruction.
Continue readingRadiomics is the main approach used to develop predictive models based on 3D Positron Emission Tomography (PET) scans of patients suffering from cancer. We propose a deep learning architecture associating a 2D feature extractor to a 3D CNN predictor.
Continue readingThe popularisation of privacy policies has become an attractive subject of research in recent years, notably after the General Data Protection Regulation came into force in the European Union. While GDPR gives Data Subjects more rights and control over the use of their personal data, length and complexity of privacy policies can still prevent them from exercising those rights. An accepted way to improve the interpretability of privacy policies is…
Continue readingAfter GDPR enforcement in May 2018, the problem of implementing privacy by design and staying compliant with regulations has been more prominent than ever for businesses of all sizes, which is evident from frequent cases against companies and significant fines paid due to non-compliance. Consequently, numerous research works have been emerging in this area….
Continue readingOne of the factors limiting busiest airport’s runway throughput capacity is the spacing to be applied between landing aircraft in order to ensure that the runway is vacated when the follower aircraft reaches the runway threshold. Today, because the Controller is not able to always anticipate the runway occupancy time (ROT) of the leader aircraft, significant spacing buffers are added to the minimum required spacing in order to cover all possible cases, which negatively affects the resulting arrival throughput. The present paper shows how a Machine Learning (ML) analysis can support the development of accurate, yet operational, models for ROT prediction depending on all impact parameters. Based on Gradient Boosting Regressors, those ML models make use of flight plan information (such as aircraft type, airline, flight data) and weather information to model the ROT. This paper shows how it can be used operationally to increase runway capacity while maintaining or reducing the risk of delivery of separations below runway occupancy time. The methodology and related benefits are assessed using three years of field measurements gathered at Zurich airport.
You can find the slide here and the paper here.
Guillaume Stempfel, Victor Brossard, Ivan De Visscher, Antoine Bonnefoy, Mohamed Ellejmi, Vincent Treve ̧ Applying Machine Learning Modeling to Enhance Runway Throughput at A Big European Airport, Proc. of the 10th EASN International Conference on “Innovation in Aviation & Space to the Satisfaction of the European Citizens, Naples, Italy, 2020.