Figure 1. The presence of an audience impacts the user's behavior in front of a public display. High audience cardinality, glances towards the user and close physical distance between the audience and the display, contribute to increasing user-display distance, decreasing interaction time and discouraging interaction in general.

Public displays have lately become ubiquitous thanks to the decreasing cost of such technology and public policies supporting the future development of smart cities. Depending on form factor, those displays might use touchless gestural interfaces that therefore are becoming more often the object of public and private research. In this paper, we focus on touchless interactions with situated public displays, and introduce a pilot study on comparing two interfaces: an interface based on the Microsoft Human Interface Guidelines (HIG), a de facto standard in the field, and a novel interface, designed by us. Differently from the HIG, our interface displays an avatar, which does not require an activation gesture to trigger actions. Our aim is to study how the two interfaces address the so-called interaction blindness -the inability of the users to recognize the interactive capabilities of those displays. According to our pilot study, although providing a different approach, both interfaces proven effective in the proposed scenario: a public display in a campus building's hall. CCS Concepts• Human-centered computing → Interaction design → Interaction design process and methods → User interface design.

Public displays, typically equipped with touchscreens, are used for interactions in public spaces, such as streets or fairs. Currently low-cost visual sensing technologies, such as Kinect-like devices and high quality cameras, allow to easily implement touchless interfaces. Nevertheless, the arising interactions have not yet been fully investigated for public displays in-the-wild (i.e. in appropriate social contexts where public displays are typically deployed). Different audiences, cultures and social settings strongly affect users and their interactions. Besides gestures for public displays must be guessable to be easy to use for a wide audience. Issues like these could be solved with user-centered design: gestures must be chosen by users in different social settings, and then selected to be resilient to cultural bias and provide a good level of guessability. Therefore the main challenge is to define touchless gestures in-the-wild by using novel UCD methods applied out of controlled environments, and evaluating their effectiveness

In recent years, touchless-enabling technologies have been more and more adopted for providing public displays with gestural interactivity. This has led to the need for novel visual interfaces aimed at solving issues such as communicating interactivity to users, as well as supporting immediate usability and "natural" interactions. In this paper, we focus our investigation on a visual interface based only on the use of in-air direct manipulations. Our study aims at evaluating whether and how the presence of an Avatar that replays user's movements may decrease the perceived cognitive workload during interactions. Moreover, we conducted a brief evaluation of the relationship between the presence of the Avatar and the use of one or two hands during the interactions. To this end, we compared two versions of the same interface, differing only for the presence/absence of the user's Avatar. Our results showed that the Avatar contributes to lower the perceived cognitive workload during the interactions.

the conference committee reflected on SIGUCCS conferences, what they mean to us individually, and what we hope to achieve this year. Our conference theme Connect | Discover was developed as a result of our discussions. We are confident that over the next several days, you will connect with amazing colleagues from other institutions across the US and the world, and discover new ideas and solutions to bring back to your home institution.

The aim of the study is to show whether it is possible to predict infectious disease outbreaks early, by using machine learning. This study was carried out following the guidelines of the Cochrane Collaboration and the meta-analysis of observational studies in epidemiology and the preferred reporting items for systematic reviews and meta-analyses. The suitable bibliography on PubMed/Medline and Scopus was searched by combining text, words, and titles on medical topics. At the end of the search, this systematic review contained 75 records. The studies analyzed in this systematic review demonstrate that it is possible to predict the incidence and trends of some infectious diseases; by combining several techniques and types of machine learning, it is possible to obtain accurate and plausible results.

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Abstract-The palmprint recognition has become a focus in biological recognition and image processing fields. In this process, the features extraction (with particular attention to palmprint principal line extraction) is especially important. Although a lot of work has been reported, the representation of palmprint is still an open issue. In this paper we propose a simple, efficient, and accurate palmprint principal lines extraction method. Our approach consists of six simple steps: normalization, median filtering, average filters along four prefixed directions, grayscale bottom-hat filtering, combination of bottom-hat filtering, binarization and post processing. The contribution of our work is a new method for palmprint principal lines detection and a new dataset of hand labeled principal lines images (that we use as ground truth in the experiments). Preliminary experimental results showed good performance in terms of accuracy with respect to three methods of the state of the art.