There’s a lot to deal with when students start a new degree programme; for instance, familiarising with a new place and meeting lots of new people. The way students learn in higher education might also be different than what they are used to. Research group Study Success created tips for a great start in the first 100 days. These tips are based on the results of various studies conducted by the research group, but also on advice from current students who were asked for their input.
This study introduces a novel methodology for the post-analysis of operational predictability by leveraging timestamps collected through the Airport Collaborative Decision Making (A-CDM) framework. Focusing on the start-up and departure phases, the analysis highlights the importance of accurately planning and managing key timestamps, such as the Target Off-Block Time (TOBT) and Target Start-Up Approval Time (TSAT), which are critical for operational efficiency. Using one week of sample data from Schiphol Airport, this research demonstrates the potential benefits of the proposed framework in improving predictability during the start-up phase, particularly by identifying and analyzing outliers and anomalies. The start-up phase, a critical component of the outbound process, was broken down into subphases to allow for a more detailed assessment. The findings suggest that while 96% of flights maintain TOBT accuracy within ±20 minutes, 68% of flights miss their TOBT by 2 to 17.5 minutes, with 364 notable outliers. These deviations highlight areas for further investigation, with future work aiming to explore the impact of influencing factors such as weather, resource availability, and support tools. The proposed framework serves as a foundation for improving operational predictability and efficiency at airports.
This report analysis the geography of the tech sector in Amsterdam, with a focus on scaleups. After a literature review, it contains a quantitative analysis, showing and mapping the spatial clustering of various types of tech companies cluster in the Amsterdam region. Then, based on interviews, we analyse the growth dynamics, location preferences and geographical dynamics of tech scale-ups. Also, we identify which push and pull factors affect Amsterdam based tech scale-up companies in their locational decision making, on the neighborhood and building level.
Betonprinten biedt veel nieuwe mogelijkheden op het gebied van productie en materiaal, maar vraagt van het MKB en startups flinke investeringen in kennis en middelen om er mee aan de slag te gaan. Met name slicer software, dat 3D modellen omzet naar printercode, vormt een bottleneck omdat deze alleen commercieel en printer-specifiek verkrijgbaar zijn. Saxion, Vertico en White Lioness willen in dit project de haalbaarheid van gratis open source slicer software die als cloud dienst wordt aangeboden onderzoeken. Deze oplossing maakt betonprinten bereikbaar voor meer innovatieve toepassingen vanuit MKB en startups, en vormt een platform voor het verzamelen en delen van kennis op het gebied van betonprinten.
Carboxylated cellulose is an important product on the market, and one of the most well-known examples is carboxymethylcellulose (CMC). However, CMC is prepared by modification of cellulose with the extremely hazardous compound monochloracetic acid. In this project, we want to make a carboxylated cellulose that is a functional equivalent for CMC using a greener process with renewable raw materials derived from levulinic acid. Processes to achieve cellulose with a low and a high carboxylation degree will be designed.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
