In February 2023, the 4TU.NIRICT centre launched theĀ 4TU.NIRICT callĀ Community Funding 2023Ā to strengthen and support collaboration among researchers and practitioners of the 4TU.NIRICT community, increasing the impact of ICT research in The Netherlands. This call therefore explicitly aims to support all activities that help in strengthening the 4TU.NIRICT community and enable this community to start-up new research ventures by using this funding.
The call is continuous, and applications can be submitted until the budget is depleted.
Read more about the application guidelines and procedureĀ here.
Making sense of sound emitted by electric vehicles
- Dr. P. Bazilinskyy, TU/e
- Dr. R. Merino-Martinez, TU Delft
- Dr.Ā K. Bennin, WUR
- Prof.dr. M. Martens, TU/e
- Prof.dr. B. Tekinerdogan, WUR
Over 270,000 fatal pedestrian traffic accidents occur yearly worldwide, with most happening during road crossing. Causes include misjudging crossing gaps and time, low visibility, and noticeability. Electric vehicles (EVs), due to their lack of combustion engine and quiet nature, pose a challenge for vulnerable road users (VRUs). In this project, they will explore the design of optimal synthetic sound signals for EVs to provide maximum information and noticeability to VRUs while keeping noise pollution to a minimum. In a simultaneous hackathon at the three participating institutions, together with students, will investigate what sounds and EV should be emitting in a V2X (vehicle-to-everything) future scenario, where EVs detect VRUs and emit auditory signals. To address the general issue of high level of annoyance of auditory feedback in automotive quantitatively (in contrast to the prevailing use of subjective measures in the field), they will use SQAT, an open-source sound quality analysis toolbox for MATLAB. This approach enables the evaluation of many audio signals within the design loop, which is unfeasible via subjective assessments, such as psychoacoustic listening experiments. In a workshop, building upon the results of the hackathon, generative AI and ANSYS will assist in signal design, and user evaluations will be compared with AI-generated responses to explore the need for traditional user studies in the era of generative AI. Finally, the results of this initiative will be disseminated in conference(s) focusing on sound design in automotive.
An Integrated Learning Infrastructure to Support Programming EducationĀ
- Dr. Mazyar Seraj, TU/eĀ
- Dr. Lina Ochoa Venegas, TU/eĀ
- Dr. Mauricio Verano Merino, VU AmsterdamĀ
- Prof.dr. Jurgen Vinju, TU/eĀ
- Dr. Fenia Aivaloglou, TU DelftĀ
- Dr. Ayushi Rastogi, RUGĀ
- Ir. Danny M. Groenewegen, TU DelftĀ
- Dr. Ćnder Babur, WURĀ
- Dr. Pavol Jancura, TU/eĀ
- Dr. Sander Stuijk, TU/eĀ
- Dr. Marcus Gerhold, UTĀ
- Dr. Angelika Mader, UTĀ
- Dr. Tom van Dijk, UTĀ
The project addresses challenges in programming education by creating an integrated learning infrastructure across six universities. Recognizing limitations in traditional approaches, the initiative aims to automate the generation of didactic materials and personalized programming exercises. Leveraging existing projects, the collaborative effort seeks to develop a shared educational platform adaptable to diverse programming languages and courses. The 10-month plan involves onboarding, literature review, platform development, experiment design, and evaluation. Lessons learned will contribute to practical, open, and reusable programming education, with a future vision of expanding the platform. The requested NIRICT grant supports an Engineering Doctorate (EngD) candidate's salary and experimentation costs, fostering collaboration and community building among universities. The project's impact extends beyond the 10-month period, with ongoing plans for knowledge dissemination and community engagement.