Abstract

Abstract
Fleet tracking technology collects real-time information about geolocation of vehicles as well as driving-related data. This information is typically used for location monitoring as well as for analysis of routes, vehicles and drivers. From an operational point of view, the geolocation simply identifies the state of a vehicle in terms of positioning and navigation. From a management point of view, the geolocation may be used to infer the state of a vehicle in terms of process (e.g., driving, fueling, maintenance, or lunch break). Meaningful information may be extracted from these inferred states using process mining. An innovative methodology for inferring process states from geolocation data is proposed in this paper. Also, it is presented the potential of applying process mining techniques on geolocation data for process discovery. © 2020 The Authors. Published by Elsevier B.V.

Abstract
Serious Pervasive Games extend themagic circle (Huizinga, 1938) to the players’ context and surrounding environment. The blend of both physical and fictive game worlds provides a push in player engagement and promotes situated learning approaches. Space and time, as well as social context, acquire a more meaningful impact on the gameplay. From pervasive learning towards science communication with location-based games, this article presents research and case studies that exemplify their benefits and related problems. Pervasive learning can be defined as “learning at the speed of need through formal, informal and social learning modalities” (Pontefract, 2013). The first case study—the BEACONING project—aims to contextualize the teaching and learning process, connecting it with problem-based game mechanics within STEM. The main goal of this project is to provide the missing connection between STEM subjects and real-world interactions and applications. The pedagogical foundation is supported on problem-based learning (PBL), in which active learning is in the center, and learners have to work with different tools and resources in order to solve problems (quests). Teachers create, facilitate, and assess pervasive and gamified learning activities (missions). Furthermore, these quests are gamified in order to provide non-linear game plots. In a second case study, we demonstrate and evaluate how natural heritage can benefit from pervasive games. This study is based on a set of location-based games for an existing natural park, which have been developed in order to provide enhanced experiences, as well as additional information about some species that are more difficult to observe or that are seasonal. Throughout the research and development of these projects, we have encountered and identified several problems, of different nature, present in pervasive games.

Abstract
Interactive tabletops offer unique collaborative features, particularly their size, geometry, orientation and, more importantly, the ability to support multi-user interaction. Although previous efforts were made to make interactive tabletops accessible to blind people, the potential to use them in collaborative activities remains unexplored. In this paper, we present the design and implementation of a multi-user auditory display for interactive tabletops, supporting three feedback modes that vary on how much information about the partners' actions is conveyed. We conducted a user study with ten blind people to assess the effect of feedback modes on workspace awareness and task performance. Furthermore, we analyze the type of awareness information exchanged and the emergent collaboration strategies. Finally, we provide implications for the design of future tabletop collaborative tools for blind users. © 2020 ACM.

Abstract
An approach to analyzing Streaming Big Data as it comes in while maintaining the proper context of past events is to employ contiguous visualizations with an increasingly aggressive aggregation degree. This allows for the most recent data to be displayed in detail, while older data is shown in an aggregated form according to how long ago it was received. However, the transitions applied between visualizations with different aggregations must not compromise the understandability of the data flow. Particularly, new data should be perceived considering the context established by older data, and the visualizations should not be perceived as independent or unconnected. In this paper, we present the first study on transitions between two contiguous visualizations, focusing on time series data. We developed several animated transitions between a scatter plot, where all data points are individually represented as they arrive, and other visualizations where data is displayed in an aggregated form. We then conducted a user evaluation to assess the most appealing and effective transitions that allow for the best comprehension of the displayed data for each visualization pair.

Abstract
Health literacy affects how people understand health information and, therefore, should be considered by search engines in health searches. In this work, we analyze how the level of health literacy is related to the eye movements of users searching the web for health information. We performed a user study with 30 participants that were asked to search online in the context of three work task situations defined by the authors. Their eye interactions with the Search Results Page and the Result Pages were logged using an eye-tracker and later analyzed. When searching online for health information, people with adequate health literacy spend more time and have more fixations on Search Result Pages. In this type of page, they also pay more attention to the results' hyperlink and snippet and click in more results too. In Result Pages, adequate health literacy users spend more time analyzing textual content than people with lower health literacy. We found statistical differences in terms of clicks, fixations, and time spent that could be used as a starting point for further research. That we know of, this is the first work to use an eye-tracker to explore how users with different health literacy search online for health-related information. As traditional instruments are too intrusive to be used by search engines, an automatic prediction of health literacy would be very useful for this type of system.