Vacuum properties of nonsymmetric gravity in de Sitter space

We consider quantum effects of a massive antisymmetric tensor field on the dynamics of de Sitter space-time. Our starting point is the most general, stable, linearized Lagrangian arising in nonsymmetric gravitational theories (NGTs), where part of the antisymmetric field mass is generated by the cosmological term. We construct a renormalization group (RG) improved effective action by integrating out one loop vacuum fluctuations of the antisymmetric tensor field and show that, in the limit when the RG scale goes to zero, the Hubble parameter -- and thus the effective cosmological constant -- relaxes rapidly to zero. We thus conclude that quantum loop effects in de Sitter space can dramatically change the infrared sector of the on-shell gravity, making the expansion rate insensitive to the original (bare) cosmological constant.Comment: 32 pages, 2 eps figure

ARTEFACTS: How do we want to deal with the future of our one and only planet?

The European Commission’s Science and Knowledge Service, the Joint Research Centre (JRC), decided to try working hand-in-hand with leading European science centres and museums. Behind this decision was the idea that the JRC could better support EU Institutions in engaging with the European public. The fact that European Union policies are firmly based on scientific evidence is a strong message which the JRC is uniquely able to illustrate. Such a collaboration would not only provide a platform to explain the benefits of EU policies to our daily lives but also provide an opportunity for European citizens to engage by taking a more active part in the EU policy making process for the future. A PILOT PROGRAMME To test the idea, the JRC launched an experimental programme to work with science museums: a perfect partner for three compelling reasons. Firstly, they attract a large and growing number of visitors. Leading science museums in Europe have typically 500 000 visitors per year. Furthermore, they are based in large European cities and attract local visitors as well as tourists from across Europe and beyond. The second reason for working with museums is that they have mastered the art of how to communicate key elements of sophisticated arguments across to the public and making complex topics of public interest readily accessible. That is a high-value added skill and a crucial part of the valorisation of public-funded research, never to be underestimated. Finally museums are, at present, undergoing something of a renaissance. Museums today are vibrant environments offering new techniques and technologies to both inform and entertain, and attract visitors of all demographics.JRC.H.2-Knowledge Management Methodologies, Communities and Disseminatio

Prediction and Extraction of Tower Controller Commands for Speech Recognition Applications

Air traffic controllers' (ATCos) workload often is a limiting factor for air traffic capacity. Thus, electronic support systems intend to reduce ATCos' workload. Automatic speech recognition can extract controller command elements from verbal clearances to deliver automatic input for air traffic control systems, thereby avoiding manual input. Assistant Based Speech Recognition (ABSR) with high command recognition rates and low error rates has proven to dramatically reduce ATCos' workload and increase capacity in approach scenarios. However, ABSR needs accurate hypotheses on expected commands and accurate extractions of command annotations from utterance transcriptions to achieve the required performance. Based on the experience of implementation for approach control, a hypotheses generator and a command extractor have been developed for speech recognition applications regarding tower control communication to face current and future challenges in the aerodrome environment. Three human-in-the-loop multiple remote tower simulation studies were performed with 16 ATCos from Hungary, Lithuania, and Finland at DLR Braunschweig from 2017 to 2019. Roughly 100 h of speech with corresponding radar data were recorded. Around 6000 speech utterances resulting in 16,000 commands have been manually transcribed and annotated. Some parts of the data have been used for training prediction models and command extraction algorithms. Other parts were used for evaluation of command prediction and command extraction. The automatic command extractor achieved a command extraction rate of 96.7%. The hypotheses generator showed operational feasibility with a sufficiently low command prediction error rate of 7.3%

Assistant Based Speech Recognition Support for Air Traffic Controllers in a Multiple Remote Tower Environment

Assistant Based Speech Recognition (ABSR) systems for air traffic control radiotelephony communication have shown their potential to reduce air traffic controllers’ (ATCos) workload. Related research activities mainly focused on utterances for approach and en-route traffic. This is one of the first investigations of how ABSR could support ATCos in a tower environment. Ten ATCos from Lithuania and Austria participated in a human-in-the-loop simulation to validate ABSR support within a prototypic multiple remote tower controller working position. The ABSR supports ATCos by (1) highlighting recognized callsigns, (2) inputting recognized commands from ATCo utterances in electronic flight strips, (3) offering correction of ABSR output, (4) automatically accepting ABSR output, and (5) feeding the digital air traffic control system. This paper assesses human factors such as workload, situation awareness, and usability when ATCos are supported by ABSR. Those assessments result from a system with a relevant command recognition rate of 82.9% and a callsign recognition rate of 94.2%. Workload reductions and usability improvement with p-values below 0.25 are obtained for the case when the ABSR system is compared to the baseline situation without ABSR support. This motivates the technology to be brought to a higher technology readiness level, which is also confirmed by subjective feedback from questionnaires and objective measurement of workload reduction based on a performed secondary task

Understanding Tower Controller Communication for Support in Air Traffic Control Displays

Automatic speech recognition and understanding for air traffic control (ATC) communication has been deeply explored in the approach and en-route environment. Solution 97.2 is one of the first European attempts to analyze recognition rates and human performance of air traffic controllers (ATCos) in simulated tower and ground environments. Three validation exercises with 22 ATCos from four different European air navigation service providers were conducted in Germany, Norway, and Italy. The validated artificial intelligence-based prototypes of Assistant Based Speech Recognition systems (ABSR) supported ATCos fulfilling tasks in a ground and tower environment as well as multiple remote tower environment, respectively. Thus, in any relevant ATC display, (1) recognized callsigns of ATCo utterances have been highlighted, (2) fully recognized commands were shown, and (3) the ATCo was able to manually manipulate the ABSR output if needed or the output was automatically accepted by the ATC system otherwise. This paper evaluates callsign and command type recognition rates as well as ATCo performance. It compares the results for the three validation exercises. A callsign recognition rate of more than 98%, a command recognition rate of more than 91%, and a slight reduction in ATCo workload are achieve