The ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· of Augsburg is delighted to have received the highest rating for five of its bachelor¡¯s degree programmes in the CHE ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· Ranking 2024. The five degree programmes to receive a top rating were geography, computer science, mathematics, physics, and social sciences, with the general study conditions and supervision by teaching staff highly commended. Conducted by the Centre for Higher Education (CHE), the ranking provides a nationwide comparison of degree programmes and study conditions. It was published in May. Applications to the ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· of Augsburg for the winter semester 2024/25 are possible until the 15th of July.

Over the next three years, the Bavarian research alliance ¡°Intelligent Manufacturing Processes & Closed-Loop Production¡± (FORinFPRO) will be researching fundamental concepts for process-specific sensor and condition monitoring, as well as the data-based modelling, control, and optimisation of manufacturing processes. The project has been funded by the Bayerische Forschungsstiftung to the tune of around €2 million. Tobias Gotthardt, Bavarian State Secretary for Economic Affairs, Regional Development, and Energy, handed over the confirmation of funding today.

In an initial study, researchers from the AI Production Network at the ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· of Augsburg investigated the behavioral patterns of neurotypical employees and employees with autism spectrum disorder in direct collaboration with cobots in an industrial context. Several Italian partners were involved, such as the Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA-CNR), the ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· of Milan, the ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· of Bologna and the scientific institute Eugenio MEDEA project. The results show the advantages of a workplace adapted to the respective needs and are intended to be the starting point for greater attention to physical and mental health in Industry 4.0. They were published in the international journal "Frontiers in Psychology".

Self-learning computer programmes can do a great deal today: predict the weather, discover tumours in X-rays, play chess better than any human being. How the algorithms draw their conclusions, however, is often not even known by those who programmed them. Researchers at the ΰµÂ¹ú¼Ê_ΰµÂ¹ú¼Ê1946$ÓéÀÖappÓÎÏ· of Augsburg and the Israel Institute of Technology (Technion) have now compared two approaches to shed some light on this "black box".

Can a COVID-19 infection be detected based on your voice and sounds? This is what the speech and audio analysis app developed by Prof. Dr. Bj?rn W. Schuller, Professor of Artificial Intelligence and Digital Health is developed for. It estimates the probability of being infected with the corona virus based on prolonged vowels or a text that has been read aloud or free speech. First results are highly promising, but the app is still being improved and tested, in particular by collecting more data.