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We enhance a tourist trip planning framework based on orienteering with category constraints by adding social sensing. This allows us to customize a user's experience without putting the burden of preference elicitation on the user. We identify the interests of a user by analyzing their Tweets and then match these interests to descriptions of points of interests. For this analysis we adapt different schemes for social sensing to the needs of our orienteering context and compare them to find the most suitable approach. We show that our technique is fast enough for use in real-time dynamic settings and also has a higher accuracy compared to previous approaches. Additionally, we integrate a more efficient algorithm for solving the orienteering problem, boosting the overall performance and utility of our framework further, as demonstrated by the positive user satisfaction received by real users.

Our goal is to improve and extend our earlier, prototypical work on event-detection platforms, which was able to take immediate action by means of a robotic platform, when a potentially dangerous event was detected. Here we go further by enhancing and extending the system in order to not only detect instances of potentially dangerous events, but to try to predict them before they actually occur. This allows the robot to carry out specific preventive actions to stop them happening in the first place.

The aim of our work is to integrate a previously developed framework for high-level surveillance event detection with a smart robot to enhance the monitoring process. More specifically, the robot is able to improve the quality of a video stream, which in our earlier work was recorded from a static camera position, by providing a mobile camera, enabling us to get footage from different angles. Furthermore, a robot platform is able to go beyond just contacting security or the police by taking immediate action when a potentially dangerous event is detected: for instance, picking up an unattended package.

BACKGROUND: Communication between health care provider and patients in oncology presents challenges. Communication skills training have been frequently developed to address those. Given the complexity of communication training, the choice of outcomes and outcome measures to assess its effectiveness is important. The aim of this paper is to 1) perform a systematic review on outcomes and outcome measures used in evaluations of communication training, 2) discuss specific challenges and 3) provide recommendations for the selection of outcomes in future studies. METHODS: To identify studies and reviews reporting on the evaluation of communication training for health care professionals in oncology, we searched seven databases (Ovid MEDLINE, CENTRAL, CINAHL, EMBASE, PsychINFO, PsychARTICLES and Web of Science). We extracted outcomes assessed and the respective assessment methods. We held a two-day workshop with experts (n = 16) in communication theory, development and evaluation of generic or cancer-specific communication training and/or outcome measure development to identify and address challenges in the evaluation of communication training in oncology. After the workshop, participants contributed to the development of recommendations addressing those challenges. RESULTS: Out of 2181 references, we included 96 publications (33 RCTs, 2 RCT protocols, 4 controlled trials, 36 uncontrolled studies, 21 reviews) in the review. Most frequently used outcomes were participants' training evaluation, their communication confidence, observed communication skills and patients' overall satisfaction and anxiety. Outcomes were assessed using questionnaires for participants (57.3%), patients (36.0%) and observations of real (34.7%) and simulated (30.7%) patient encounters. Outcomes and outcome measures varied widely across studies. Experts agreed that outcomes need to be precisely defined and linked with explicit learning objectives of the training. Furthermore, outcomes should be assess

The charging of electric vehicles is a new market that is emerging, partially from existing markets. The emergence of such new markets requires the definition of new roles and responsibilities. Such a ‘market model’ describes the market roles (e.g. owner, operator etc) in terms of responsibilities and interactions between roles (processes). However, the development of an abstract market model for a future market is complicated since the dynamics of future markets are difficult to imagine, let alone understand. The use of simulation games is a proven method to deal with such complexities but is never applied on market model design. Here we report the complexity of and challenges to market model design based on expert interviews. Second, the novel E-CITY 2020 simulation game was developed to examine the contribution of gaming simulation to market model design for Dutch energy related markets. The game simulates a preferred market model for the charging infrastructure in a fictive city in 2020. E-CITY 2020 resulted in an increased insight in the dynamics and interactions in a new market from different perspectives (operator, customer, etc) for both designers and participants of the intervention. Second, we found that a gaming simulation creates a shared understanding of the future market model. Finally, we identified requirements for success for implementing the market model. In conclusion we find that simulation games are an effective tool to overcome complexities in market model development. Also recommendations for developing gaming simulations for market models are made., SEPAM, Systems Engineering, Technology, Policy and Management