In their quest to understand the fundamental law governing both the cosmos and interactions between particles, physicists are searching for small deviations from established theories in massive amounts of experimental data. Searches targeting specific signatures have yielded no positive results since the discovery of the Higgs boson, raising the question of whether the right signatures have...
Parkinson’s disease is a neurodegenerative disorder that affects primarily dopaminergic neurons often showing a characteristic tremor or akinesis. While the severity estimation remains a stationary UPDRS scoring, we aim for an additional sensor-driven approach to develop an automated symptom evaluation for a second opinion. Our team collected over 200 million samples of accelerometer data and...
BORGES tackles the handling of the ever-growing climate model data produced. It is a semantic database for the storage, search and retrieval of model data. It serves mainly demands of the up-to-date, competitive Earth system model ICON, developed and used at the MPI-M, Hamburg. BORGES excels for both large ensembles of model experiments as well as very high-res, large volume, „storm-resolving“...
In sheet metal forming, the development cost and complexity of the tool try out is a major challenge. Data-based tool try out focuses on two main areas: the interpretation of die spotting images as indicators of tool quality, and the generation of tool designs based on the parts to be formed. In addition to the part geometry, various physical conditions are taken into account. Limited data...
To analyze events in particle colliders, a comparable amount of events has to bee simulate as events are recorded. The Monte Carlo simulation of the detector needs most of the computing resources. However, the required resources will exceed the available ones soon.
To tackle this problem, we are developing several generative machine learning models in our research group at the Institute for...
Our project's primary focus is to systematically collect legal documents in German from European Union administrative tiers. This effort enables seamless access to German legislation for researchers, lawyers, and citizens alike. Using intuitive Python scripts, we've automated data collection from publicly accessible websites, streamlining the process for users. Furthermore, we employ...
Herbie is an Electronic Lab Notebook (ELN) developed at Helmholtz-Zentrum Hereon. Highly structured, yet flexible protocols for parameters and results of individual manufacturing and characterization processes are described with machine-readable ontologies in RDF using OWL and SHACL. By interlinking the protocols and putting them into context with involved staff, samples, equipment, projects,...
Inflation narratives explain inflation changes and affect expectations. Manually identifying them is cumbersome, prompting the need for scalable algorithms. Narratives comprise events, causal relations, and arguments, represented as graphs with event and argument nodes. Causal relations indicate cause-and-effect relationships between events using directed edges. Our main objective is to...
Radio communication is a central task and safety-critical for international shipping. Despite being based on resilient and robust technology, the quality of transmitted audio signals varies depending on antenna height and prevailing weather conditions. In addition, shipping is characterized by a high degree of crew multi-nationality, so that communications over VHF radio contain a variety of...
Avatar animation is one of the ways to produce sign language content. Using motion capture data allows for fluent avatar movements closer to human signer. However, the generated animation usually cannot adjust grammatical features such as intonation, signing space, and facial expression to match a specific context. This is because all motion data is in a fixed form at the time it is...
A palimpsest is a manuscript page that has been scraped or washed off in preparation for reuse, in the form of another document. When working with palimpsest manuscripts, even with the employment of Multispectral Imaging (MSI), the under-text often remains challenging to read. In some cases, it might not be readable at all. This difficulty arises due to various factors, including parts of the...
In dieser Studie entwickeln wir ein KI-gestütztes System für maritime Such- und Rettungsaktionen. Das System führt in Echtzeit eine Analyse sensorischer Daten und Verhaltensanomalien von Schiffen durch und integriert automatische Objekterkennung zur Identifikation von Personen in Not. Ziel ist eine präzise Vorhersage für Wartungsarbeiten, eine genauere Zustandsüberwachung und effizientere...
In unserem Poster stellen wir das Social Media Observatory (SMO) am Leibniz-Institut für Medienforschung | Hans-Bredow-Institut vor. Das SMO wird seit 2020 als Open-Science-Forschungsinfrastruktur innerhalb des Forschungsinstitut Gesellschaftlicher Zusammenhalt (FGZ) entwickelt. Es konzentriert sich auf die langfristige Beobachtung der öffentlichen Kommunikation auf ausgewählten Plattformen...
The Digital Causality Lab (DCL) is an innovative teaching project at the University of Hamburg which focuses on the topics Causal Inference and Data Literacy. It is one of the teaching projects that have been funded in the DDLitLab Project (Stiftung Innovation in der Hochschullehre). In the Digital Causality Lab, we use interactive apps to complement...
Wordnets are a popular type of lexical resource, used in a variety of computational and linguistic applications. They are appreciated for their sense-based representation of lexical items and their typed relationship network. Wordnets for many different languages exist, but while research has been published toward creating Wordnets for sign languages, our work is the first resulting in a...
Identifying suitable datasets is a common challenge for data scientists working in domains with scarce data. For research on sign languages, this usually involves extensive literature review or word-of-mouth. Information on individual datasets may be distributed across different publications, data repositories and (potentially defunct) project websites. We introduce the Sign Language Dataset...
Patents serve as critical catalysts in drug discovery, assuring legal safeguards to innovations while stimulating investments. By discerning patterns within patent data, researchers glean invaluable insights into pharmaceutical industry trends and priorities. Our study, powered by the Patent Enrichment Tool (PEMT), delves into patent literature concerning rare diseases (RD) and Alzheimer's...
