Safety Aspects of Supporting Apron Controllers with Automatic Speech Recognition and Understanding Integrated into an Advanced Surface Movement Guidance and Control System

The information air traffic controllers (ATCos) communicate via radio telephony is valuable for digital assistants to provide additional safety. Yet, ATCos have to enter this information manually. Assistant-based speech recognition (ABSR) has proven to be a lightweight technology that automatically extracts and successfully feeds the content of ATC communication into digital systems without additional human effort. This article explains how ABSR can be integrated into an advanced surface movement guidance and control system (A-SMGCS). The described validations were performed in the complex apron simulation training environment of Frankfurt Airport with 14 apron controllers in a human-in-the-loop simulation in summer 2022. The integration significantly reduces the workload of controllers and increases safety as well as overall performance. Based on a word error rate of 3.1%, the command recognition rate was 91.8% with a callsign recognition rate of 97.4%. This performance was enabled by the integration of A-SMGCS and ABSR: the command recognition rate improves by more than 15% absolute by considering A-SMGCS data in ABSR

The HAAWAII Framework for Automatic Speech Understanding of Air Traffic Communication

During the last decade many successful applications combining Automatic Speech Recognition and Understanding (ASRU) for Air Traffic Management applications have been proposed and demonstrated. The HAAWAII project developed a generic architecture and framework, which was validated for, e.g., callsign highlighting, pre-filling radar labels and readback error detection. It supports recognizing and understanding pilot and air traffic controller (ATCo) transmissions. Contextual information extracted from available surveillance data, from flight plan data and from previous transmissions can be exploited to significantly improve ASRU performance. Different design decisions have been taken, depending on concrete scenarios. This paper evaluates the effect of the design decisions integrated in the HAAWAII framework on overall performance for speech understanding based on eight hypotheses, of which seven are validated. Using all framework elements enables command recognition rates for ATCos of 90% for real-time applications and 93% for offline applications, respectively. The most significant impact is achieved, when callsign information from surveillance data is available: the command recognition rate improves by more than 20% absolute. Knowing apriori, whether ATCo or pilot is speaking, can provide additional improvement in command recognition rate up to 16% absolute. The reported results are based on commands from apron, approach, and enroute recorded both in laboratory and in ops room environment

Diel Growth Cycle of Isolated Leaf Discs Analyzed with a Novel, High-Throughput Three-Dimensional Imaging Method Is Identical to That of Intact Leaves1[W]

Dicot leaves grow with pronounced diel (24-h) cycles that are controlled by a complex network of factors. It is an open question to what extent leaf growth dynamics are controlled by long-range or by local signals. To address this question, we established a stereoscopic imaging system, GROWSCREEN 3D, which quantifies surface growth of isolated leaf discs floating on nutrient solution in wells of microtiter plates. A total of 458 leaf discs of tobacco (Nicotiana tabacum) were cut at different developmental stages, incubated, and analyzed for their relative growth rates. The camera system was automatically displaced across the array of leaf discs; visualization and camera displacement took about 12 s for each leaf disc, resulting in a time interval of 1.5 h for consecutive size analyses. Leaf discs showed a comparable diel leaf growth cycle as intact leaves but weaker peak growth activity. Hence, it can be concluded that the timing of leaf growth is regulated by local rather than by systemic control processes. This conclusion was supported by results from leaf discs of Arabidopsis (Arabidopsis thaliana) Landsberg erecta wild-type plants and starch-free1 mutants. At night, utilization of transitory starch leads to increased growth of Landsberg erecta wild-type discs compared with starch-free1 discs. Moreover, the decrease of leaf disc growth when exposed to different concentrations of glyphosate showed an immediate dose-dependent response. Our results demonstrate that a dynamic leaf disc growth analysis as we present it here is a promising approach to uncover the effects of internal and external cues on dicot leaf development

Apron Controller Support by Integration of Automatic Speech Recognition with an Advanced Surface Movement Guidance and Control System

Digital assistants in air traffic control today have access to a large number of sensors that allow monitoring of traffic in the air and on the ground. Voice communication between air traffic controller and pilot, however, is not used by these assistants. Whenever the information from voice communication has to be digitized, controllers are burdened to enter the information manually. Research shows that up to one third of controllers working time is spent on these manual inputs. Assistant Based Speech Recognition (ABSR) has already shown that it can reduce the amount of manual inputs from controllers. This paper presents how a modern digital assistant, a so-called A-SMGCS, can utilize the outputs of ABSR. The combined application is installed in the complex apron simulation training environment of the Frankfurt airport. This allows on the one hand the integration of recognized controller commands into the A-SMGCS planning process. On the other hand, ABSR performance is improved through the usage of A-SMGCS information. The implemented ABSR system alone reaches Word Error Rates of 3.1% for the text recognition process, which results in a callsign recognition rate of 97.4% and a command recognition rate of 91.8%. The integration of ABSR in the A-SMGCS brings a reduction of workload for controllers, which increases the overall performance and safety

Dynamics of seedling growth acclimation towards altered light conditions can be quantified via GROWSCREEN: a setup and procedure designed for rapid optical phenotyping of different plant species

Using a novel setup, we assessed how fast growth of Nicotiana tabacum seedlings responds to alterations in the light regime and investigated whether starch-free mutants of Arabidopsis thaliana show decreased growth potential at an early developmental stage. Leaf area and relative growth rate were measured based on pictures from a camera automatically placed above an array of 120 seedlings. Detection of total seedling leaf area was performed via global segmentation of colour images for preset thresholds of the parameters hue, saturation and value. Dynamic acclimation of relative growth rate towards altered light conditions occurred within 1 d in N. tabacum exposed to high nutrient availability, but not in plants exposed to low nutrient availability. Increased leaf area was correlated with an increase in shoot fresh and dry weight as well as root growth in N. tabacum. Relative growth rate was shown to be a more appropriate parameter than leaf area for detection of dynamic growth acclimation. Clear differences in leaf growth activity were also observed for A. thaliana. As growth responses are generally most flexible in early developmental stages, the procedure described here is an important step towards standardized protocols for rapid detection of the effects of changes in internal (genetic) and external (environmental) parameters regulating plant growth

Common variants at SCN5A-SCN10A and HEY2 are associated with Brugada syndrome, a rare disease with high risk of sudden cardiac death

Brugada syndrome is a rare cardiac arrhythmia disorder, causally related to SCN5A mutations in around 20% of cases. Through a genome-wide association study of 312 individuals with Brugada syndrome and 1,115 controls, we detected 2 significant association signals at the SCN10A locus (rs10428132) and near the HEY2 gene (rs9388451). Independent replication confirmed both signals (meta-analyses: rs10428132, P = 1.0 × 10(-68); rs9388451, P = 5.1 × 10(-17)) and identified one additional signal in SCN5A (at 3p21; rs11708996, P = 1.0 × 10(-14)). The cumulative effect of the three loci on disease susceptibility was unexpectedly large (Ptrend = 6.1 × 10(-81)). The association signals at SCN5A-SCN10A demonstrate that genetic polymorphisms modulating cardiac conduction can also influence susceptibility to cardiac arrhythmia. The implication of association with HEY2, supported by new evidence that Hey2 regulates cardiac electrical activity, shows that Brugada syndrome may originate from altered transcriptional programming during cardiac development. Altogether, our findings indicate that common genetic variation can have a strong impact on the predisposition to rare disease