The paper summarizes two models for engineering education, as discussed in earlier papers. The first model (Corporate Curriculum) aims to bring Industry into the school, while the second model (I3) intends to bring the school into Industry. The contribution of the presented models to the Bologna Declaration and to the Renaissance Engineer idea are discussed.
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The swift enhancement of technology has affected the business environment as higher education alone no longer plays a definitive role in the employment process. To meet the emerging requirements of employers, individuals, specifically students, need to gain more entrepreneurial tendencies. The aim of this study is to investigate the factors affecting the entrepreneurial intention (EI) of university students. In order to do so, five constructs (EI, individual entrepreneurial orientation (IEO), self-efficacy, environmental support, and knowledge sharing) and their items taken from existing literature were used within the proposed model, and the constructed hypotheses were evaluated using structural equation modelling (SEM). Based on the model, a survey was distributed to 332 students of various universities.Self-efficacy and IEO are expected to be the prime factors affecting EI, whereas environmental support and knowledge sharing are expected to have more of an indirect effect on EI. Overall, this study will help establish the influencers of EI among university students.
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Background: The present study investigates the suitability of various treatment outcome indicators to evaluate performance of mental health institutions that provide care to patients with severe mental illness. Several categorical approaches are compared to a reference indicator (continuous outcome) using pretest-posttest data of the Health of Nation Outcome Scales (HoNOS). Methods: Data from 10 institutions and 3189 patients were used, comprising outcomes of the first year of treatment by teams providing long-term care. Results: Findings revealed differences between continuous indicators (standardized pre-post difference score ES and ΔT) and categorical indicators (SEM, JTRCI, JTCS, JTRCI&CS, JTrevised) on their ranking of institutions, as well as substantial differences among categorical indicators; the outcome according to the traditional JT approach was most concordant with the continuous outcome indicators. Conclusions: For research comparing group averages, a continuous outcome indicator such as ES or ΔT is preferred, as this best preserves information from the original variable. Categorical outcomes can be used to illustrate what is accomplished in clinical terms. For categorical outcome, the classical Jacobson-Truax approach is preferred over the more complex method of Parabiaghi et al. with eight outcome categories. The latter may be valuable in clinical practice as it allows for a more detailed characterization of individual patients.
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Entangled Machines is a project by Mariana Fernández Mora that interrogates the colonial and extractive legacies underpinning artificial intelligence (AI). By introducing slowness and digital kinship as critical frameworks, the project reconceptualises AI as embedded within intricate social and ecological networks, thereby contesting dominant narratives of efficiency and optimisation. Through participatory, practice-based methodologies such as the Material Playground, the project integrates feminist and non-Western epistemologies to articulate alternative models for ethical, sustainable, and equitable AI practices. Over a four-year period, Entangled Machines develops theory, engages diverse communities, and produces artistic outputs to reimagine human-AI interactions. In collaboration with partners including ARIAS Amsterdam, Archival Consciousness, and the Sandberg Institute, the research seeks to foster decolonial and interdisciplinary approaches to AI. Its culmination will be an “Anarchive” – a curated assemblage of artistic, theoretical, and archival outputs – that serves as a resource for rethinking AI’s socio-political and ecological impacts.
Het RaakPRO project INTRALOG (1/9/2015-31/8/2019) heeft inzicht opgeleverd in de toepassing van autonoom rijden op distributiecentra (DCs). Het project heeft door de samenwerking van hogescholen en universiteiten met bedrijven, kenniscentra en branchevertegenwoordigers, op de thema’s businessmodellen en technologische innovatie in de ontwikkeling van autonoom rijden, een uniek resultaat bereikt. Een autonoom rijdende Yard Truck, gestuurd door Multi Agent System voor het beheer van de logistieke infrastructuur op een distributiecentrum. De aansturing en organisatie van de externe logistiek op een distributiecentrum (DC) door een Multi Agent Systeem (MAS), borgt een optimale inzet van autonoom rijdende Yard Trucks. In de ontwikkeling van het MAS is onderzoek uitgevoerd bij de logistieke partners van INTRALOG. Doel was inzicht in de logistieke eisen en randvoorwaarden vervoersbewegingen op DCs en deze te vertalen in kritische prestatie indicatoren (KPIs) voor de autonome Yard Trucks. De realisatie van een autonoom rijdende Yard Truck op modelschaal is gedaan door de ontwikkeling van een rij-robot (controller) die in staat is om los van de infrastructuur een Yard Truck autonoom over en binnen een bestaande infrastructuur te dirigeren. De randvoorwaarden voor het uitvoeren van de voertuigbewegingen van de Yard Truck, zijn voortgekomen uit de KPIs die bepaald zijn aan de hand van de onderzochte businessmodellen. Centraal in de Top-Up staan twee aspecten: 1) de ontwikkeling van een video waarin het autonoom dokken centraal staat dat gestuurd wordt door een MAS-applicatie en 2) een seminar gericht op de toepassing van het resultaat van INTRALOG op distributiecentrums. De doelstelling van de Top-up is primair het verspreiden van het gedachtegoed van INTRALOG, maar ook het: o Vergroten van het netwerk van het consortium van INTRALOG; en o Demonstreren om versneld tot een real life product te komen.
This proposal aims to explore a radically different path towards a more sustainable fashion future through technology. Most research on fashion and technology focuses on high tech innovation and, as a result, overlooks knowledge that is already available and has been used, tested and improved for centuries. The proposed research project, however, looks backward to move forward. It aims to investigate ‘the blindingly obvious’ and asks the question how historical technologies could be used to solve contemporary environmental issues in fashion. It thus argues that technology from the past could inspire both designers and technologists to come up with new and exciting solutions to make the future of fashion more sustainable. The current fast fashion system has changed the relationship consumers have with their clothing. Clothing has become a throwaway object and this has severe environmental implications. This research project aims to find a solution by exploring historical technologies - such as folding, mending and reassembling-, because in the past a ‘sustainable’ attitude towards fashion was the norm simply because cloth and garments were expensive. It wants to examine what happens when consumers, fashion designers and technologists are confronted with these techniques. What would, for example, materialize when an aeronautical engineer takes the technique of folding as a starting point and aims to create clothes that can grow with babies and toddlers? The answer is the signature suit of the brand Petit Pli: a special folding technique allows their signature suit to grow with children from 3 months to 3 years. Much like the age-old folding techniques applied in traditional Dutch dress, which allowed the size women’s jackets to be altered, by simply adjusting the pleats. Similarly, this project aims to investigate how high tech solutions, can be initiated through historical techniques.