Dienst van SURF
© 2025 SURF
Background: Due to complex processes of implementation of innovations aimed at persons with intellectual disabilities in healthcare organizations, lifestyle interventions are not used as intended or not used at all. In order to provide insight into determinants influencing this implementation, this study aims to ascertain if the Measurement Instrument for Determinants of Innovations (MIDI) is useful for objectively evaluating implementation.Method: With semi‐structured interviews, data concerning determinants of implementation of lifestyle interventions were aggregated. These data were compared to the determinants questioned in the MIDI. Adaptations to the MIDI were made in consultation with the author of the MIDI.Results: All determinants of the MIDI, except for that concerning legislation and regulations, were represented in the interview data. Determinants not represented in the MIDI were the level of intellectual disabilities, suitability of materials and physical environment, multi‐levelness of interventions and several persons who could be involved in the intervention, such as direct support persons (DSPs), a therapist or family, and the communication between these involved persons.Conclusion: The present authors suggested making adjustments to existing questions of the MIDI in order to improve usability for deployment in organizations that provide care to persons with intellectual disabilities. The adjustments need to be tested with other interventions.
Concerns have been raised over the increased prominence ofgenerative AI in art. Some fear that generative models could replace theviability for humans to create art and oppose developers training generative models on media without the artist's permission. Proponents of AI art point to the potential increase in accessibility. Is there an approach to address the concerns artists raise while still utilizing the potential these models bring? Current models often aim for autonomous music generation. This, however, makes the model a black box that users can't interact with. By utilizing an AI pipeline combining symbolic music generation and a proposed sample creation system trained on Creative Commons data, a musical looping application has been created to provide non-expert music users with a way to start making their own music. The first results show that it assists users in creating musical loops and shows promise for future research into human-AI interaction in art.
The historically developed practice of learning to play a music instrument from notes instead of by imitation or improvisation makes it possible to contrast two types of skilled musicians characterized not only by dissimilar performance practices, but also disparate methods of audiomotor learning. In a recent fMRI study comparing these two groups of musicians while they either imagined playing along with a recording or covertly assessed the quality of the performance, we observed activation of a right-hemisphere network of posterior superior parietal and dorsal premotor cortices in improvising musicians, indicating more efficient audiomotor transformation. In the present study, we investigated the detailed performance characteristics underlying the ability of both groups of musicians to replicate music on the basis of aural perception alone. Twenty-two classically trained improvising and score-dependent musicians listened to short, unfamiliar two-part excerpts presented with headphones. They played along or replicated the excerpts by ear on a digital piano, either with or without aural feedback. In addition, they were asked to harmonize or transpose some of the excerpts either to a different key or to the relative minor. MIDI recordings of their performances were compared with recordings of the aural model. Concordance was expressed in an audiomotor alignment score computed with the help of music information retrieval algorithms. Significantly higher alignment scores were found when contrasting groups, voices, and tasks. The present study demonstrates the superior ability of improvising musicians to replicate both the pitch and rhythm of aurally perceived music at the keyboard, not only in the original key, but also in other tonalities. Taken together with the enhanced activation of the right dorsal frontoparietal network found in our previous fMRI study, these results underscore the conclusion that the practice of improvising music can be associated with enhanced audiomotor transformation in response to aurally perceived music.
LINK
A world where technology is ubiquitous and embedded in our daily lives is becoming increasingly likely. To prepare our students to live and work in such a future, we propose to turn Saxion’s Epy-Drost building into a living lab environment. This will entail setting up and drafting the proper infrastructure and agreements to collect people’s location and building data (e.g. temperature, humidity) in Epy-Drost, and making the data appropriately available to student and research projects within Saxion. With regards to this project’s effect on education, we envision the proposal of several derived student projects which will provide students the opportunity to work with huge amounts of data and state-of-the-art natural interaction interfaces. Through these projects, students will acquire skills and knowledge that are necessary in the current and future labor-market, as well as get experience in working with topics of great importance now and in the near future. This is not only aligned with the Creative Media and Game Technologies (CMGT) study program’s new vision and focus on interactive technology, but also with many other education programs within Saxion. In terms of research, the candidate Postdoc will study if and how the data, together with the building’s infrastructure, can be leveraged to promote healthy behavior through playful strategies. In other words, whether we can persuade people in the building to be more physically active and engage more in social interactions through data-based gamification and building actuation. This fits very well with the Ambient Intelligence (AmI) research group’s agenda in Augmented Interaction, and CMGT’s User Experience line. Overall, this project will help spark and solidify lasting collaboration links between AmI and CMGT, give body to AmI’s new Augmented Interaction line, and increase Saxion’s level of education through the dissemination of knowledge between researchers, teachers and students.
Het HAS lectoraat ‘Precision Livestock Farming’ van Dr. Ir. E. van Erp-van der Kooij richt zich op het tijdig opsporen van afwijkingen van gedrag en fysiologische parameters met sensoren om diergezondheid en welzijn te verbeteren. Het huidige voorstel bouwt hierop voort, waarbij de focus ligt op het vroegtijdig opsporen van hittestress bij melkvee. De laatste jaren is er veel aandacht voor hittestress bij melkkoeien in Nederland. Hittestress treedt op wanneer de warmteproductie van een koe groter is dan haar vermogen om warmte kwijt te raken. Klimaatverandering zorgt in Nederland voor warmere zomers en meer risico op hittestress. Hittestress zorgt voor problemen op het gebied van gedrag, gezondheid en vruchtbaarheid. De kennis die in dit project wordt verzameld kan een bijdrage leveren aan het ontwikkelen van bruikbare indicatoren voor hittestress. Deze indicatoren kunnen ervoor zorgen dat er vroegtijdig maatregelen getroffen worden (op kudde- of koeniveau) om negatieve gevolgen van hittestress te verminderen. Om een sterke verbinding tussen onderzoek en onderwijs te bewerkstelligen wordt het onderzoek uitgevoerd door de postdoc (Dr. Ir. J. Roelofs) én door studenten in diverse studententeams onder begeleiding van de postdoc. Door gebruik van sensoren komen veel gegevens beschikbaar. Voor studenten is het belangrijk dat zij, naast kennis over de biologie en fysiologie van het dier, een gedegen basiskennis hebben van sensoren en van het werken met (big)data en nieuwe analysetechnieken. De postdoc heeft als taak onderwijs te ontwikkelen en verzorgen waarin basiskennis en vaardigheden m.b.t. sensoren in de veehouderij en werken met (big)data aan bod komen. De postdoc is mede verantwoordelijk voor de versterking van de leerlijn ‘Onderzoeksvaardigheden’ bij de opleiding Veehouderij. Daarnaast maakt de postdoc een overzicht waar onderzoeksvaardigheden terugkomen in het curriculum en draagt er zorg voor dat dit voldoende en op consistente wijze gebeurt door begeleiding van studenten én docenten.
The Dutch floriculture is globally leading, and its products, knowledge and skills are important export products. New challenges in the European research agenda include sustainable use of raw materials such as fertilizer, water and energy, and limiting the use of pesticides. Greenhouse growers however have little control over crop growth conditions in the greenhouse at individual plant level. The purpose of this project, ‘HiPerGreen’, is to provide greenhouse owners with new methods to monitor the crop growth conditions in their greenhouse at plant level, compare the measured growth conditions and the measured growth with expected conditions and expected growth, to point out areas with deviations, recommend counter-measures and ultimately to increase their crop yield. The main research question is: How can we gather, process and present greenhouse crop growth parameters over large scale greenhouses in an economical way and ultimately improve crop yield? To provide an answer to this question, a team of university researchers and companies will cooperate in this applied research project to cover several different fields of expertise The application target is floriculture: the production of ornamental pot plants and cut flowers. Participating companies are engaged in the cultivation of pot plans, flowers and suppliers of greenhouse technology. Most of the parties fall in the SME (MKB) category, in line with the RAAK MKB objectives.Finally, the Demokwekerij and Hortipoint (the publisher of the international newsletter on floriculture) are closely involved. The project will develop new knowledge for a smart and rugged data infrastructure for growth monitoring and growth modeling in the greenhouse. In total the project will involve approximately 12 (teacher) researchers from the universities and about 60 students, who will work in the form of internships and undergraduate studies of interesting questions directly from the participating companies.