This study addresses the burgeoning global shortage of healthcare workers and the consequential overburdening of medical professionals, a challenge that is anticipated to intensify by 2030 [1]. It explores the adoption and perceptions of AI-powered mobile medical applications (MMAs) by physicians in the Netherlands, investigating whether doctors discuss or recommend these applications to patients and the frequency of their use in clinical practice. The research reveals a cautious but growing acceptance of MMAs among healthcare providers. Medical mobile applications, with a substantial part of IA-driven applications, are being recognized for their potential to alleviate workload. The findings suggest an emergent trust in AI-driven health technologies, underscored by recommendations from peers, yet tempered by concerns over data security and patient mental health, indicating a need for ongoing assessment and validation of these applications
DOCUMENT
Highlights•Crime scene investigations are accompanied by cognitive challenges.•Introducing technologies at crime scenes requires research into the human factor.•Mobile technologies can impede the investigation without studying the impact.
DOCUMENT
Als relatief nieuw begrip in de context van e-learning krijgt ‘mobile learning’ steeds meer aandacht, wat ten dele kan worden verklaard door de ontwikkeling en verspreiding van mobiele technologie. Als we de pleitbezorgers van ‘mobile learning’ moeten geloven, dan wordt deze vorm van leren belangrijker en is het denkbaar dat sommige leerprocessen in de toekomst volledig op die wijze vormgegeven zullen worden. Probleem is dat een eenduidige definitie van ‘mobile learning’ nog altijd ontbreekt, dat er meningsverschillen zijn over de technologie die tot het domein van ‘mobile learning’ behoort, en dat er betrekkelijk weinig resultaten zijn van succesvolle inzet van mobiele technologie in leerprocessen. Daarbij wordt onder succesvol verstaan dat het heeft bijgedragen aan de effectiviteit van het leren, en daarmee aan een beter leerresultaat en een efficiënter leerproces, waarbij onder het laatste verstaan wordt dat het maximale leereffect wordt bereikt met een beperkte inzet van mensen en middelen. Deze notitie beoogt enige duidelijkheid te scheppen in de definitiekwestie en in de visies op leren die een rol spelen bij ‘mobile learning’. Vanuit dat perspectief wordt vervolgens ingegaan op kenmerken van mobiele technologie en ontwikkelingen die daarin verwacht worden. Aansluitend wordt er dieper ingegaan op leerprocessen en de rol die mobiele technologie daarin zou kunnen vervullen, waarna de notitie wordt afgesloten met een kijkkader om de mogelijke inzet en betekenis van ‘mobile learning’ in onderwijssituaties te kunnen duiden en beoordelen.
DOCUMENT
Drones have been verified as the camera of 2024 due to the enormous exponential growth in terms of the relevant technologies and applications such as smart agriculture, transportation, inspection, logistics, surveillance and interaction. Therefore, the commercial solutions to deploy drones in different working places have become a crucial demand for companies. Warehouses are one of the most promising industrial domains to utilize drones to automate different operations such as inventory scanning, goods transportation to the delivery lines, area monitoring on demand and so on. On the other hands, deploying drones (or even mobile robots) in such challenging environment needs to enable accurate state estimation in terms of position and orientation to allow autonomous navigation. This is because GPS signals are not available in warehouses due to the obstruction by the closed-sky areas and the signal deflection by structures. Vision-based positioning systems are the most promising techniques to achieve reliable position estimation in indoor environments. This is because of using low-cost sensors (cameras), the utilization of dense environmental features and the possibilities to operate in indoor/outdoor areas. Therefore, this proposal aims to address a crucial question for industrial applications with our industrial partners to explore limitations and develop solutions towards robust state estimation of drones in challenging environments such as warehouses and greenhouses. The results of this project will be used as the baseline to develop other navigation technologies towards full autonomous deployment of drones such as mapping, localization, docking and maneuvering to safely deploy drones in GPS-denied areas.
The maximum capacity of the road infrastructure is being reached due to the number of vehicles that are being introduced on Dutch roads each day. One of the plausible solutions to tackle congestion could be efficient and effective use of road infrastructure using modern technologies such as cooperative mobility. Cooperative mobility relies majorly on big data that is generated potentially by millions of vehicles that are travelling on the road. But how can this data be generated? Modern vehicles already contain a host of sensors that are required for its operation. This data is typically circulated within an automobile via the CAN bus and can in-principle be shared with the outside world considering the privacy aspects of data sharing. The main problem is, however, the difficulty in interpreting this data. This is mainly because the configuration of this data varies between manufacturers and vehicle models and have not been standardized by the manufacturers. Signals from the CAN bus could be manually reverse engineered, but this process is extremely labour-intensive and time-consuming. In this project we investigate if an intelligent tool or specific test procedures could be developed to extract CAN messages and their composition efficiently irrespective of vehicle brand and type. This would lay the foundations that are required to generate big data-sets from in-vehicle data efficiently.
This project addresses the fundamental societal problem that encryption as a technique is available since decades, but has never been widely adopted, mostly because it is too difficult or cumbersome to use for the public at large. PGP illustrates this point well: it is difficult to set-up and use, mainly because of challenges in cryptographic key management. At the same time, the need for encryption has only been growing over the years, and has become an urgent problem with stringent requirements – for instance for electronic communication between doctors and patients – in the General Data Protection Regulation (GDPR) and with systematic mass surveillance activities of internationally operating intelligence agencies. The interdisciplinary project "Encryption for all" addresses this fundamental problem via a combination of cryptographic design and user experience design. On the cryptographic side it develops identity-based and attribute-based encryption on top of the attribute-based infrastructure provided by the existing IRMA-identity platform. Identity-based encryption (IBE) is a scientifically well-established technique, which addresses the key management problem in an elegant manner, but IBE has found limited application so far. In this project it will be developed to a practically usable level, exploiting the existing IRMA platform for identification and retrieval of private keys. Attribute-based encryption (ABE) has not reached the same level of maturity yet as IBE, and will be a topic of further research in this project, since it opens up attractive new applications: like a teacher encrypting for her students only, or a company encrypting for all employees with a certain role in the company. On the user experience design side, efforts will be focused on making these encryption techniques really usable (i.e., easy to use, effective, efficient, error resistant) for everyone (e.g., also for people with disabilities or limited digital skills). To do so, an iterative, human-centred and inclusive design approach will be adopted. On a fundamental level, scientific questions will be addressed, such as how to promote the use of security and privacy-enhancing technologies through design, and whether and how usability and accessibility affect the acceptance and use of encryption tools. Here, theories of nudging and boosting and the unified theory of technology acceptance and use (known as UTAUT) will serve as a theoretical basis. On a more applied level, standards like ISO 9241-11 on usability and ISO 9241-220 on the human-centred design process will serve as a guideline. Amongst others, interface designs will be developed and focus groups, participatory design sessions, expert reviews and usability evaluations with potential users of various ages and backgrounds will be conducted, in a user experience and observation laboratory available at HAN University of Applied Sciences. In addition to meeting usability goals, ensuring that the developed encryption techniques also meet national and international accessibility standards will be a particular point of focus. With respect to usability and accessibility, the project will build on the (limited) usability design experiences with the mobile IRMA application.
