Abstract-As the technology available on cars is increasing, a wide range of applications, from safety to entertainment, are becoming factually accessible to passengers. Many of these applications involves a one-to-many transmission model where a single car broadcasts a message that has to be forwarded, even with multiple hops, in a very short time to all the other cars located within a range of few kilometers from the source. Since the high mobility and density of a car network scenario, specific solutions need to be devised to choreograph a fast-delivery multihop broadcast. To this aim, we developed a practical and efficient technique that allows cars to estimate their communication range with the help of a very limited message exchange and exploit this information to reduce the number of transmissions, as well as the hops to be traversed, and hence the time, required by a broadcasted message to reach all the cars following the sender within a certain distance.

Abstract-Inter-vehicle communication (IVC) is emerging in research prominence for the interest that isgenerating in all major car manufacturers and for the benefits that its inception will produce. The specific features of IVC will allow the deployment of a wide set of possible applications which span from road safety to entertainment. Even if, on the one hand, these applications share the common need for fast multi-hop message propagation, on the other hand, they possess distinct characteristics in terms of generated network traffic. The current research state of the art only proposes solutions specifically designed for a single application (or class) that are not directly extendable to a general IVC context. Instead, we claim that a privileged architecture exists, which is able to support the whole spectrum of application classes. To this aim, we propose a novel IVC architecture that adapts its functionalities to efficiently serve applications in quickly propagating their messages over a vehicular network. We conducted an extensive set of experiments that demonstrate the efficacy of our approach. As representative case studies, we considered two application classes that for their network traffic characteristics are at the opposite boundaries of the application spectrum: safety and entertainment.

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Since the expansion of their market and their challenging requirements, Massively Multiplayer Online Games are gaining increasing attention in the scientific community. One of the key factors in this kind of application is represented by the ability to rapidly deliver game events among the various players over the network. Employing in this context Mirrored Game Server architectures and adapting RED (Random Early Detection) techniques borrowed from network queuing management, we are able to show sensible benefits in upholding interactivity and scalability, whilst preserving game state consistency and game evolution fluency at the player's side.Index Terms-Consistency, event delivery service, interactivity, massively multiplayer online game, online entertainment.

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This paper presents a study on urban data crowdsourcing driven by Geo-Zombie, a multimedia mobile application we designed and developed to engage pedestrians in taking note of urban architectural impediments and facilities by documenting them through pictures and multimedia data. Geo-Zombie aims at transforming the civic activity of contributing into a virtual gamified experience where players attempt to escape from horrific situations in which zombies are ready to cannibalize unsuspecting walkers. In some sense, walkers that kill zombies deeply reconnect with the concept of imminent danger which can be fought resorting to appropriate civic actions. To challenge our initial hypotheses we conducted a design process, starting with a concept generation where three different concepts were discussed which gave rise to five different multimedia mobile apps including the one with zombies. Then, focus group, experience prototyping, application design and implementation, and finally field trials were exploited to refine the design and to select the best apps out of the five that better responded to the need of involving common people in collecting urban accessibility data. It is worth noting that the experiences of use with 50 avid walkers have demonstrated that a multimedia mobile app with maps and zombies can be a concrete step towards a social inclusion strategy while inviting new reflections and discussions on the issue of urban data crowdsourcing.

BackgroundData concerning patients originates from a variety of sources on social media.ObjectiveThe aim of this study was to show how methodologies borrowed from different areas including computer science, econometrics, statistics, data mining, and sociology may be used to analyze Facebook data to investigate the patients’ perspectives on a given medical prescription.MethodsTo shed light on patients’ behavior and concerns, we focused on Crohn’s disease, a chronic inflammatory bowel disease, and the specific therapy with the biological drug Infliximab. To gain information from the basin of big data, we analyzed Facebook posts in the time frame from October 2011 to August 2015. We selected posts from patients affected by Crohn’s disease who were experiencing or had previously been treated with the monoclonal antibody drug Infliximab. The selected posts underwent further characterization and sentiment analysis. Finally, an ethnographic review was carried out by experts from different scientific research fields (eg, computer science vs gastroenterology) and by a software system running a sentiment analysis tool. The patient feeling toward the Infliximab treatment was classified as positive, neutral, or negative, and the results from computer science, gastroenterologist, and software tool were compared using the square weighted Cohen’s kappa coefficient method.ResultsThe first automatic selection process returned 56,000 Facebook posts, 261 of which exhibited a patient opinion concerning Infliximab. The ethnographic analysis of these 261 selected posts gave similar results, with an interrater agreement between the computer science and gastroenterology experts amounting to 87.3% (228/261), a substantial agreement according to the square weighted Cohen’s kappa coefficient method (w2K=0.6470). A positive, neutral, and negative feeling was attributed to 36%, 27%, and 37% of posts by the computer science expert and 38%, 30%, and 32% by the gastroenterologist, respectively. Only a slight agreement was found between the experts’ opinion and the software tool.ConclusionsWe show how data posted on Facebook by Crohn’s disease patients are a useful dataset to understand the patient’s perspective on the specific treatment with Infliximab. The genuine, nonmedically influenced patients’ opinion obtained from Facebook pages can be easily reviewed by experts from different research backgrounds, with a substantial agreement on the classification of patients’ sentiment. The described method allows a fast collection of big amounts of data, which can be easily analyzed to gain insight into the patients’ perspective on a specific medical therapy.