Automatic analysis of eye surgery

In many cases, modern ophthalmic surgery involves the video recording of surgical proceedings. The video material is either used for training purposes or for the subsequent reconstruction of operation sequences. Klaus Schöffmann has assembled a research team to work on the automatic recognition of relevant sequences within the scope of an FWF-funded project. Natalia Sokolova, a doctoral candidate at the Department of Information Technology, is a member of the project team and her work focuses on improving the search for particularly “relevant” surgical phases.

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Innovation boost for “learning factory”: European research project “SemI40” generates path-breaking findings

Scientists and researchers have been conducting intensive research into the further development of autonomous factories in the framework of the European “SemI40” project (Power Semiconductor and Electronics Manufacturing 4.0). Under the leadership of Infineon Austria, 37 partners from science and industry have made decisive progress in the development of processes and methods for Industry 4.0 applications over the past three project years. The result: a unique security concept for networked communication of factories, a quality leap in the production process, plus significant improvements in energy efficiency.

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Does smell sell? Overview study provides evidence of ambient scent effects in consumer settings

Within the scope of a detailed meta-analysis, Holger Roschk has examined 64 studies with 71 samples and a total of 15,000 test persons to find out to what extent ambient scents have an effect on experiences and activities in shopping and service environments. Results show: Under ideal conditions, scents can have a positive influence on customer behaviour. 

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Are we seeing genuine progress with recommender systems?

Recommender systems represent a key technology for e-commerce providers such as Google, Amazon, Netflix, Booking.com and Spotify. It is therefore with a certain urgency that researchers are working intensively on making ever more accurate predictions about the products and services users might want to consume next. However, in a paper published recently, Maurizio Ferrari Dacrema, Paolo Cremonesi and Dietmar Jannach were able to show that several critical issues concerning the research methodology are hindering progress in the development of recommender systems. In recognition of their work, they received the Best Full Paper Award at the renowned ACM Conference on Recommender Systems in Copenhagen in September.

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