news 2022

Research Award Winner at the University of Paderborn Presents Results In classical music, editions are considered the basis of scholarly study of music. Unlike classical music, however, pop music is not composed on music paper, but in audio data. The substance of pop music is its sound. Rebecca Grotjahn, professor at the Department of Musicology at the University of Paderborn and the Detmold University of Music, is investigating how this can be edited as so-called -phonographic- music.

Unconventional computing combines Brownian computing with reservoir computing / First prototype developed A large percentage of energy used today is consumed in the form of electrical power for processing and storing data and for running the relevant terminal equipment and devices. According to predictions, the level of energy used for these purposes will increase even further in the future.

Artificial intelligence (AI) has become an integral part of our lives. It has given rise to smart assistants that take on tasks that would otherwise take humans a great deal of time and effort - in medicine, business and industry, for example. To do this, smart assistants require vast amounts of data.

Humanitarian protection and support for victims of war and armed violence, that is the goal of the International Committee of the Red Cross (ICRC). The symbol of the Red Cross is intended to protect aid workers from attack during their missions. Can this symbol also be used for the digital world - and what opportunities and risks are associated with it? An international team of researchers investigated this question on behalf of the ICRC.

Scientists at TU Ilmenau have succeeded in improving the accuracy of data evaluations for forecasting weather events, among other things, by up to 80 percent. In the scientific publication ,,Flipped Classroom - Effective Teaching for Time Series Forecasting", which was published in October, Prof. Patrick Mäder, head of the department Data-intensive Systems and Visualization, and Philipp Teutsch, research associate at the same department, present their research results on the training of recurrent neural networks.

INaturalist app users play a significant role in helping researchers create global maps of plant traits <p><strong>Leipzig. Missing knowledge in the global distribution of plant traits could be filled with data from species identification apps. Researchers from Leipzig University, the German Centre for Integrative Biodiversity Research (iDiv) and other institutions were able to demonstrate this based on data from the popular iNaturalist app.

In a pilot project, machine learning is helping to develop materials for hydrogen storage, for example. Artificial intelligence is opening up new possibilities in the development of new materials. Particularly in the search for materials for special applications such as high-entropy alloys, which contain several components in roughly equal proportions, machine learning could support research.

Machine learning improves climate models Accurately modeling extreme precipitation events remains a major challenge for climate models. These models predict how the earth's climate may change over the course of decades and even centuries. To improve them especially with regard to extreme events, researchers now use machine learning methods otherwise applied to image generation.

Scientists develop platform that combines measurements of surface topography in a digital twin Scientists from the University of Freiburg, Germany, and the University of Pittsburgh have developed a software platform that facilitates and standardizes the analysis of surfaces. The platform enables users to create a digital twin of a surface and thus to help predict, for example, how quickly it wears out, how well it conducts heat, or how well it adheres to other materials.

Freiburg computer scientists make an important step towards advancing perception in complex urban environments How can mobile robots perceive and understand the environment correctly, even if parts of the environment are occluded by other objects? This is a key question that must be solved for self-driving vehicles to safely navigate in large crowded cities.

The expectations for autonomous driving are clear: "Cars have to travel safely not only at low speeds, but also in fast-moving traffic," says Jörg Schrepfer, the Head of Driving Advanced Research Germany at Valeo. For example, when objects fall off a truck, the "egocentric" perspective of a car will often be unable to detect the hazardous debris in time.

Researchers led by Göttingen University develop new machine-learning method to understand force chains Granular matter is all around us. Examples include sand, rice, nuts, coffee and even snow. These materials are made of solid particles that are large enough not to experience thermal fluctuations. Instead, their state is determined by mechanical influences: shaking produces -granular gases- whilst by compression one gets -granular solids-.

It could be so simple: producing global maps for vegetation, climate or soil at the touch of a button. Whether in Africa, America or Europe; whether up in the mountains or deep in the forest. No laborious on-site fieldwork would be necessary, nor would days spent evaluating data in a lab. Simply "train" the computer system to provide, as accurately as possible, predictions for any and every environmental variable.

Münster surgeons use new operating method for the first time anywhere in the world / Research at Münster University strengthens medical digitalisation in the operating theatre It is a great success for robotic microsurgery not only in Münster but worldwide - both for medicine and for science: a team led by scientists Dr. Maximilian Kückelhaus and Prof. Tobias Hirsch from the Centre for Musculoskeletal Medicine at the University of Münster has carried out the first completely robot-supported microsurgical operations on humans.

Carl Zeiss Foundation provides five million euros for establishment of CZS Heidelberg Center for Model-Based AI A centre for model-based artificial intelligence has been set up at Heidelberg University to link mathematical modelling methods with information processing in neuronal networks. The Carl Zeiss Foundation (CZS) is funding the CZS Heidelberg Center for Model-Based AI with five million euros over a period of six years.

Cryptographic systems that even quantum computers cannot crack will soon be standard in the USA Whenever you visit a website, send an email, or do your online banking in the future, in many cases algorithms developed with the participation of researchers at the Max Planck Institute for Security and Privacy in Bochum and the Ruhr University Bochum will be used to protect your data.

Linguists and computer scientists collaborate to publish a large global Open Access lexical database Scholars from the Max Planck Institute for Evolutionary Anthropology in Germany and the University of Auckland in New Zealand have created a new global repository of linguistic data. The project is designed to facilitate new insights into the evolution of words and sounds of the languages spoken across the world today.

German Research Foundation approves further four-year funding of the joint Collaborative Research Center/Transregio 146 on Multiscale Simulation Methods for Soft Matter Systems of Mainz University, TU Darmstadt, and the Max Planck Institute for Polymer Research The German Research Foundation (DFG) has agreed to finance another four years of development of soft matter simulation by the Collaborative Research Center/TRR 146.

The cooperation strengthens application-related research on artificial intelligence in Germany Amazon and the Max Planck Society today announced the establishment of the first German Science Hub in Tübingen. The main goal of this science cooperation is to advance research in Germany in subfields of artificial intelligence (AI), in particular causality, computer vision and machine learning, to develop secure and trustworthy concepts for the future and thus to strengthen Germany as a technology location.

Machine learning is playing an ever-increasing role in biomedical research. Scientists at the Technical University of Munich (TUM) have now developed a new method of using molecular data to extract subtypes of illnesses. In the future, this method can help to support the study of larger patient groups.