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Information and services personalization is essential for an optimal user experience. Systems have to be able to acquire data about the user's context, process them in order to identify the user's situation and finally, adapt the functionality of the system to that situation, but the development of context-aware systems is complex. Data coming from distributed and heterogeneous sources have to be acquired, processed and managed. Several programming frameworks have been proposed in order to simplify the development of context-aware systems. These frameworks offer high-level application programming interfaces for programmers that complicate the involvement of domain experts in the development life-cycle. The participation of users that do not have programming skills but are experts in the application domain can speed up and improve the development process of these kinds of systems. Apart from that, there is a lack of methodologies to guide the development process. This article presents as main contributions, the implementation and evaluation of a web platform and a methodology to collaboratively develop context-aware systems by programmers and domain experts. [ABSTRACT FROM AUTHOR]

Addressing cyber and privacy risks has never been more critical for organisations. While a number of risk assessment methodologies and software tools are available, it is most often the case that one must, at least, integrate them into a holistic approach that combines several appropriate risk sources as input to risk mitigation tools. In addition, cyber risk assessment primarily investigates cyber risks as the consequence of vulnerabilities and threats that threaten assets of the investigated infrastructure. In fact, cyber risk assessment is decoupled from privacy impact assessment, which aims to detect privacy-specific threats and assess the degree of compliance with data protection legislation. Furthermore, a Privacy Impact Assessment (PIA) is conducted in a proactive manner during the design phase of a system, combining processing activities and their inter-dependencies with assets, vulnerabilities, real-time threats and Personally Identifiable Information (PII) that may occur during the dynamic life-cycle of systems. In this paper, we propose a cyber and privacy risk management toolkit, called AMBIENT (Automated Cyber and Privacy Risk Management Toolkit) that addresses the above challenges by implementing and integrating three distinct software tools. AMBIENT not only assesses cyber and privacy risks in a thorough and automated manner but it also offers decision-support capabilities, to recommend optimal safeguards using the well-known repository of the Center for Internet Security (CIS) Controls. To the best of our knowledge, AMBIENT is the first toolkit in the academic literature that brings together the aforementioned capabilities. To demonstrate its use, we have created a case scenario based on information about cyber attacks we have received from a healthcare organisation, as a reference sector that faces critical cyber and privacy threats. [ABSTRACT FROM AUTHOR]

Currently an increasing number of head mounted displays (HMD) for virtual and augmented reality (VR/AR) are equipped with integrated eye trackers. Use cases of these integrated eye trackers include rendering optimization and gaze-based user interaction. In addition, visual attention in VR and AR is interesting for applied research based on eye tracking in cognitive or educational sciences for example. While some research toolkits for VR already exist, only a few target AR scenarios. In this work, we present an open-source eye tracking toolkit for reliable gaze data acquisition in AR based on Unity 3D and the Microsoft HoloLens 2, as well as an R package for seamless data analysis. Furthermore, we evaluate the spatial accuracy and precision of the integrated eye tracker for fixation targets with different distances and angles to the user ( n = 21 ). On average, we found that gaze estimates are reported with an angular accuracy of 0.83 degrees and a precision of 0.27 degrees while the user is resting, which is on par with state-of-the-art mobile eye trackers. [ABSTRACT FROM AUTHOR]

This paper presents a user-centered methodology to co-design and co-evaluate wearables that has been developed following a research-through design methodology. It has been based on the principles of human–computer interaction and on an empirical case entitled "Design and Development of a Low-Cost Wearable Glove to Track Forces Exerted by Workers in Car Assembly Lines" published in Sensors. Insights from both studies have been used to develop the wearable co-design domino presented in this study. The methodology consists of different design stages composed of an ideation stage, digital service development and test stages, hardware development and test stage, and a final test stage. The main conclusions state that it is necessary to maintain a close relationship between human factors and technical factors when designing wearable. Additionally, through the several studies, it has been concluded that there is need of different field experts that should co-design and co-evaluate wearable iteratively and involving users from the beginning of the process. [ABSTRACT FROM AUTHOR]