The TARDIS project aims to build a scenario-based serious-game simulation platform for NEETs and job-inclusion associations that supports social training and coaching in the context of job interviews. This paper presents the general architecture of the TARDIS job interview simulator, and the serious game paradigm that we are developing. 1 NEET is a government acronym for young people not in employment, education or training. 2 ec.europa.eu/eurostat 3

We present a novel multi-lingual database of natural dyadic noviceexpert interactions, named NoXi, featuring screen-mediated dyadic human interactions in the context of information exchange and retrieval. NoXi is designed to provide spontaneous interactions with emphasis on adaptive behaviors and unexpected situations (e.g. conversational interruptions). A rich set of audio-visual data, as well as continuous and discrete annotations are publicly available through a web interface. Descriptors include low level social signals (e.g. gestures, smiles), functional descriptors (e.g. turn-taking, dialogue acts) and interaction descriptors (e.g. engagement, interest, and uidity). CCS CONCEPTS•Information systems → Database design and models; Semistructured data; Data streams; •Human-centered computing → Systems and tools for interaction design; KEYWORDS A ective computing, multimodal corpora, multimedia databases ACM Reference format:

When looking at Socially Interactive Robots, adaptation to the user's preferences plays an important role in today's Human-Robot Interaction to keep interaction interesting and engaging over a long period of time. Findings indicate an increase in user engagement for robots with adaptive behavior and personality, but also that it depends on the task context whether a similar or opposing robot personality is preferred. We present an approach based on Reinforcement Learning, which gets its reward directly from social signals in real-time during the interaction, to quickly learn about and dynamically address individual human preferences. Our scenario involves a Reeti robot in the role of a story teller talking about the main characters in the novel "Alice's Adventures in Wonderland" by generating descriptions with varying degree of introversion/extraversion. After initial simulation results, an interactive prototype is presented which allows to explore the learning process adapting to the human interaction partner's engagement.Paper accepted for 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Background: For percutaneously tracheostomized patients with prolonged weaning and persisting respiratory failure, the adequate time point for safe decannulation and switch to noninvasive ventilation is an important clinical issue. Objectives: We aimed to evaluate the usefulness of a tracheostomy retainer (TR) and the predictors of successful decannulation. Methods: We studied 166 of 384 patients with prolonged weaning in whom a TR was inserted into a tracheostoma. Patients were analyzed with regard to successful decannulation and characterized by blood gas values, the duration of previous spontaneous breathing, Simplified Acute Physiology Score (SAPS) and laboratory parameters. Results: In 47 patients (28.3%) recannulation was necessary, mostly due to respiratory decompensation and aspiration. Overall, 80.6% of the patients could be liberated from a tracheostomy with the help of a TR. The need for recannulation was associated with a shorter duration of spontaneous breathing within the last 24/48 h (p < 0.01 each), lower arterial oxygen tension (p = 0.025), greater age (p = 0.025), and a higher creatinine level (p = 0.003) and SAPS (p < 0.001). The risk for recannulation was 9.5% when patients breathed spontaneously for 19–24 h within the 24 h prior to decannulation, but 75.0% when patients breathed for only 0–6 h without ventilatory support (p < 0.001). According to ROC analysis, the SAPS best predicted successful decannulation [AUC 0.725 (95% CI: 0.634–0.815), p < 0.001]. Recannulated patients had longer durations of intubation (p = 0.046), tracheostomy (p = 0.003) and hospital stay (p < 0.001). Conclusion: In percutaneously tracheostomized patients with prolonged weaning, the use of a TR seems to facilitate and improve the weaning process considerably. The duration of spontaneous breathing prior to decannulation, age and oxygenation describe the risk for recannulation in these patients.

This paper presents an approach that makes use of a virtual character and social signal processing techniques to create an immersive job interview simulation environment. In this environment, the virtual character plays the role of a recruiter which reacts and adapts to the user's behavior thanks to a component for the automatic recognition of social cues (conscious or unconscious behavioral patterns). The social cues pertinent to job interviews have been identified using a knowledge elicitation study with real job seekers. Finally, we present two user studies to investigate the feasibility of the proposed approach as well as the impact of such a system on users.