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Creating the engineer of 2020: Innovation at Eindhoven University of Technology

Eindhoven University of Technology has implemented significant reforms in its engineering education, introducing a three-course series that teaches patents and standards to improve students' critical thinking skills. The changes resulted in a significant increase in student intake, with over 1,900 students enrolled by 2015.

SourceUniversity of South Florida·JournalJournal of Technology and Innovation·DateOct 27, 2017

Straining the memory: Prototype strain engineered materials are the future of data storage

Researchers at Singapore University of Technology and Design have created prototype strain engineered materials that enable fast switching in data storage, outperforming current phase change memory technologies. The new material's energy efficiency and reduced switching time could impact new 3D memory architectures.

University of Sydney charges ahead on zinc-air batteries

Researchers at the University of Sydney have made a breakthrough in rechargeable zinc-air batteries by developing a new three-stage method that produces low-cost and high-performance catalysts. The new catalysts can be used to build rechargeable zinc-air batteries, overcoming one of the biggest hurdles preventing their widespread use.

SourceUniversity of Sydney·JournalAdvanced Materials·DateAug 14, 2017

Printed sensors monitor tire wear in real time

Researchers have developed an inexpensive printed sensor that can track millimeter-scale changes in tire tread depth with high accuracy. The technology has the potential to increase safety, improve vehicle performance, and reduce fuel consumption by detecting sub-millimeter resolution of tire wear.

SourceDuke University·JournalIEEE Sensors Journal·DateJun 14, 2017

Microhotplates for a smart gas sensor

Researchers at Toyohashi University of Technology developed a microhotplate using SU-8 polymer material, achieving good thermal isolation and mechanical stability. The device displayed high temperature resistance up to 550 °C and low power consumption, making it suitable for miniature smart gas sensor chips.

SourceToyohashi University of Technology (TUT)·JournalJournal of Micromechanics and Microengineering·DateFeb 22, 2017

A new spin on electronics

Researchers at TUM and Kyoto University demonstrated the transport of spin information in a unique boundary layer between lanthanum-aluminate and strontium-titanate materials. This breakthrough enables the potential for novel functionality in spin electronic components, overcoming limitations in traditional semiconductor technology.

SourceTechnical University of Munich (TUM)·JournalNature Materials·DateFeb 15, 2017

Virtual renaissance

University Jena researchers have launched a project to create 3D representations of cultural objects from museums and collections, including historical globes and other unique artifacts. The goal is to make these treasures accessible to the public and enable scientific investigation through accurate replicas created via 3D printing.

Technology communication: Worries through information?

A recent study by KIT researchers found that communication of risks related to mobile phones can have unintended consequences. Information on efficient precautions was found to lead to an increased risk perception by recipients, highlighting the need for a better understanding of how messages about precautions affect public perception.

SourceKarlsruher Institut für Technologie (KIT)·JournalInternational Journal of Environmental Research and Public Health·DateDec 14, 2016

EEG reveals information essential to users

A study by Aalto University and the Helsinki Institute for Information Technology used EEG to model user interest in Wikipedia articles, predicting search intentions and recommending relevant documents. This technology has potential to assist humans by automatically monitoring and gathering information through wearable EEG sensors.

SourceAalto University·JournalScientific Reports·DateDec 8, 2016

Using a patient's own words, machine learning automatically identifies suicidal behavior

A new study uses machine learning algorithms to classify patients into one of three groups: suicidal, mentally ill but not suicidal, or neither. The tool achieved up to 93% accuracy in identifying suicidal behavior and has the potential to support clinicians and caregivers in suicide prevention.

SourceCincinnati Children's Hospital Medical Center·JournalSuicide and Life-Threatening Behavior·DateNov 7, 2016

Can you teach koalas new tricks?

A team from Griffith University monitored 130 koala crossings using retrofitted eco-passages and pinpointed individual koalas with RFID tags, camera traps, and audio radio transmitters. The study provides comprehensive insights into koala behavior and movements.

SourceGriffith University·JournalWildlife Research·DateAug 3, 2016