The WayHome: Long-term Motion Prediction on Dynamically Scaled

One of the key challenges for autonomous vehicles is the ability to accurately predict the motion of other objects in the surrounding environment, such as pedestrians or other vehicles. In this contribution, a novel motion forecasting approach for autonomous vehicles is developed, inspired by the work of Gilles et al. [1]. We predict multiple heatmaps with a neuralnetwork-based model for every traffic participant in the vicinity of the autonomous vehicle; with one heatmap per timestep. The heatmaps are used as input to a novel sampling algorithm that extracts coordinates corresponding to the most likely future positions. We experiment with different encoders and decoders, as well as a comparison of two loss functions. Additionally, a new grid-scaling technique is introduced, showing further improved performance. Overall, our approach improves stateof-the-art miss rate performance for the function-relevant prediction interval of 3 seconds while being competitive in longer prediction intervals (up to eight seconds). The evaluation is done on the public 2022 Waymo motion challenge

Die Analyse von Leitfadengesprächen mit Lehrern über ihre Erziehungsauffassungen: ein Beispiel für die Anwendung der hermeneutisch-klassifikatorischen Inhaltsanalyse

'Ziel dieses Beitrags ist, am Beispiel von Leitfadengesprächen mit Lehrern, die über ihre Auffassungen von Erziehung (Aurin 1993; Eckert 1993) durchgeführt wurden, Anwendungs- und Weiterentwicklungsmöglichkeiten der hermeneutisch-klassifikatorischen Inhaltsanalyse zu demonstrieren. Besonderes Gewicht wird dabei auf die Kombination verschiedener Analysestrategien gelegt.' (Autorenreferat)'It is the goal of this contribution to demonstrate possibilities of use and development of the hermeneutic-classificatory content analysis through the example of structured interviews with teachers about their opinions on education. The combination of different analysis strategies is thought to be especially important.' (author's abstract)

User Provisioning Processes in Identity Management addressing SAP Campus Management

This document is the report of the work of an ISWA working team on a WUSKAR case study. This study tackles on the desire of meta directory synchronisation with a proprietary SAP R/3 system in the context of an identity management system. Early tasks concern identifying exact desires and scenarios, modelling the synchronisation process, identifying what relevant data is to be processed, as well as proposing templates for the matching and transformation process. Intermediate tasks are related to the technical aspects of the case study, as well as problem task division and progress management, regular review of strategic and technical choices

Analysis of Cotton Quality on the High Plains of Texas.

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Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews

These are the data we generated in our evaluation of the graphical user interface. Please see our publication on Wellcome Open Research for information about the evaluations.These are the data we generated in our evaluation of the graphical user interface. Please see our publication on Wellcome Open Research for information about the evaluations

Fine Particulate Matter Constituents Associated with Cardiovascular Hospitalizations and Mortality in New York City

Bac k g r o u n d: Recent time-series studies have indicated that both cardiovascular disease (CVD) mortality and hospitalizations are associated with particulate matter (PM). However, seasonal patterns of PM associations with these outcomes are not consistent, and PM components responsible for these associations have not been determined. We investigated this issue in New York City (NYC), where PM originates from regional and local combustion sources. Obj e c t i v e: In this study, we examined the role of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) and its key chemical components on both CVD hospitalizations and on mortality in NYC. Met h o d s: We analyzed daily deaths and emergency hospitalizations for CVDs among persons ≥ 40 years of age for associations with PM2.5, its chemical components, nitrogen dioxide (NO2), carbon monoxide, and sulfur dioxide for the years 2000–2006 using a Poisson time-series model adjusting for temporal and seasonal trends, temperature effects, and day of the week. We estimated excess risks per interquartile-range increases at lags 0 through 3 days for warm (April through September) and cold (October through March) seasons. Re s u l t s: The CVD mortality series exhibit strong seasonal trends, whereas the CVD hospitalization series show a strong day-of-week pattern. These outcome series were not correlated with each othe

Limits from the FUNK experiment on the mixing strength of hidden-photon dark matter in the visible and near-ultraviolet wavelength range

We present results from the FUNK experiment in the search for hidden-photon dark matter. Near the surface of a mirror, hidden photons may be converted into ordinary photons. These photons are emitted perpendicularly to the surface and have an energy equal to the mass of the dark matter hidden photon. Our experimental setup consists of a large, spherical mirror with an area of more than 14  m2, which concentrates the emitted photons into its central point. Using a detector sensitive to visible and near-UV photons, we can exclude a kinetic-mixing coupling of stronger than χ≈10−12 in the mass range of 2.5 to 7 eV, assuming hidden photons comprise all of the dark matter. The experimental setup and analysis used to obtain this limit are discussed in detai

The Association of Tree Pollen Concentration Peaks and Allergy Medication Sales in New York City: 2003–2008

The impact of pollen exposure on population allergic illness is poorly characterized. We explore the association of tree pollen and over-the-counter daily allergy medication sales in the New York City metropolitan area. Dates of peak tree pollen (maple, oak, and birch) concentrations were identified from 2003 to 2008. Daily allergy medication sales reported to the city health department were analyzed as a function of the same-day and lagged tree pollen peak indicators, adjusting for season, year, temperature, and day of week. Significant associations were found between tree pollen peaks and allergy medication sales, with the strongest association at 2-day lag (excess sales of 28.7% (95% CI: 17.4–41.2) over the average sales during the study period). The cumulative effect over the 7-day period on and after the tree pollen peak dates was estimated to be 141.1% (95% CI: 79.4–224.1). In conclusion, tree pollen concentration peaks were followed by large increases in over-the-counter allergy medication sales