Head Tracking Based Avatar Control for Virtual Environment Teamwork Training

Virtual environments (VE) are gaining in popularity and are increasingly used for teamwork training purposes, e.g., for medical teams. One shortcoming of modern VEs is that nonverbal communication channels, essential for teamwork, are not supported well. We address this issue by using an inexpensive webcam to track the user's head. This tracking information is used to control the head movement of the user's avatar, thereby conveying head gestures and adding a nonverbal communication channel. We conducted a user study investigating the influence of head tracking based avatar control on the perceived realism of the VE and on the performance of a surgical teamwork training scenario. Our results show that head tracking positively influences the perceived realism of the VE and the communication, but has no major influence on the training outcome.

Mobile Games for Learning

Today, pupils at the age of 15 have spent their entire life surrounded by and interacting with diverse forms of computers. It is a routine part of their day-to-day life and by now computer-literacy is common at very early age. Over the past five years, technology for teens has become predominantly mobile and ubiquitous within every aspect of their lives. To them, being online is an implicitness. In Germany, 88% of youth aged between 12-19 years own a smartphone and about 20% use the Internet via tablets. Meanwhile, more and more young learners bring their devices into the classroom and pupils increasingly demand for innovative and motivating learning scenarios that strongly respond to their habits of using media. With this development, a shift of paradigm is slowly under way with regard to the use of mobile technology in education. By now, a large body of literature exists, that reports concepts, use-cases and practical studies for effectively using technology in education. Within this field, a steadily growing body of research has developed that especially examines the use of digital games as instructional strategy. The core concern of this thesis is the design of mobile games for learning. The conditions and requirements that are vital in order to make mobile games suitable and effective for learning environments are investigated. The base for exploration is the pattern approach as an established form of templates that provide solutions for recurrent problems. Building on this acknowledged form of exchanging and re-using knowledge, patterns for game design are used to classify the many gameplay rules and mechanisms in existence. This research draws upon pattern descriptions to analyze learning game concepts and to abstract possible relationships between gameplay patterns and learning outcomes. The linkages that surface are the starting bases for a series of game design concepts and their implementations are subsequently evaluated with regard to learning outcomes. The findings and resulting knowledge from this research is made accessible by way of implications and recommendations for future design decisions.

User and Machine Authentication and Authorization Infrastructure for Distributed Wireless Sensor Network Testbeds

The intention of an authentication and authorization infrastructure (AAI) is to simplify and unify access to different web resources. With a single login, a user can access web applications at multiple organizations. The Shibboleth authentication and authorization infrastructure is a standards-based, open source software package for web single sign-on (SSO) across or within organizational boundaries. It allows service providers to make fine-grained authorization decisions for individual access of protected online resources. The Shibboleth system is a widely used AAI, but only supports protection of browser-based web resources. We have implemented a Shibboleth AAI extension to protect web services using Simple Object Access Protocol (SOAP). Besides user authentication for browser-based web resources, this extension also provides user and machine authentication for web service-based resources. Although implemented for a Shibboleth AAI, the architecture can be easily adapted to other AAIs.

Online privacy concerns and legal assurance: a user perspective

Since the emergence of the Internet and Social Media, privacy concerns and need for regulation in this area have been a frequent subject on the agenda of numerous stakeholders and policy-makers worldwide. Contributing to this debate, this paper builds on the responses of 553 Internet users to uncover users’ current privacy concerns and their attitudes towards legal assurances in this context. Our findings suggest that users have a complex attitude towards these issues. While they express strong concerns about privacy when asked directly, they often have difficulties formulating the exact nature of these concerns. In the Facebook context, Facebook itself is often mentioned as the primary source of threat, closely followed by marketing organizations. Users feel ill-protected by existing legal framework, especially when using Social Networking Sites. Reasons include common beliefs that the law is unable to address complexities of the Internet; local character of laws; possibilities to disregard the law, particularly since enforcement is difficult. Overall, positive changes in legal framework are desirable, with many respondents willing to pay more in taxes to ensure progress in this area.

I like it because I (‘m) like You – measuring user attitudes towards information on Facebook

Limited in motivation and cognitive ability to process the increasing amount of information on their Newsfeed, users apply heuristic processing to form their attitudes. Rather than extensively analysing the content, they increasingly rely on heuristic cues – such as the amount of comments and likes as well as the level of relationship with the “poster” – to process the incoming information. In the paper we explore what impact these heuristic cues have on the affective and cognitive attitude of users towards the posts on their Newsfeed. We conduct a survey on based on a Facebook application that allows users to evaluate Newsfeed posts in real time. Applying two distinct panel-regression methods we report robust results that indicate that there is a certain relationship primacy effect when users are processing information: only if the level of relationship with the “poster” is low, the impact of comments and likes on the attitude is considered, whereby likes trigger positive, whereas comments – negative evaluations.

Towards End-User Driven Power Saving Control in Android devices

Abstract. During the last decade mobile communications increasingly became part of people's daily routine. Such usage raises new challenges regarding devices' battery lifetime management when using most popular wireless access technologies, such as IEEE 802.11. This paper investigates the energy/delay trade-off of using an end-user driven power saving approach, when compared with the standard IEEE 802.11 power saving algorithms. The assessment was conducted in a real testbed using an Android mobile phone and high-precision energy measurement hardware. The results show clear energy benefits of employing user-driven power saving techniques, when compared with other standard approaches.

Combined aerobic/inspiratory muscle training vs. aerobic training in patients with chronic heart failure: The Vent-HeFT trial: a European prospective multicentre randomized trial

AIMS Vent-HeFT is a multicentre randomized trial designed to investigate the potential additive benefits of inspiratory muscle training (IMT) on aerobic training (AT) in patients with chronic heart failure (CHF). METHODS AND RESULTS Forty-three CHF patients with a mean age of 58 ± 12 years, peak oxygen consumption (peak VO2 ) 17.9 ± 5 mL/kg/min, and LVEF 29.5 ± 5% were randomized to an AT/IMT group (n = 21) or to an AT/SHAM group (n = 22) in a 12-week exercise programme. AT involved 45 min of ergometer training at 70-80% of maximum heart rate, three times a week for both groups. In the AT/IMT group, IMT was performed at 60% of sustained maximal inspiratory pressure (SPImax ) while in the AT/SHAM group it was performed at 10% of SPImax , using a computer biofeedback trainer for 30 min, three times a week. At baseline and at 3 months, patients were evaluated for exercise capacity, lung function, inspiratory muscle strength (PImax ) and work capacity (SPImax ), quality of life (QoL), LVEF and LV diameter, dyspnoea, C-reactive protein (CRP), and NT-proBNP. IMT resulted in a significantly higher benefit in SPImax (P = 0.02), QoL (P = 0.002), dyspnoea (P = 0.004), CRP (P = 0.03), and NT-proBNP (P = 0.004). In both AT/IMT and AT/SHAM groups PImax (P < 0.001, P = 0.02), peak VO2 (P = 0.008, P = 0.04), and LVEF (P = 0.005, P = 0.002) improved significantly; however, without an additional benefit for either of the groups. CONCLUSION This randomized multicentre study demonstrates that IMT combined with aerobic training provides additional benefits in functional and serum biomarkers in patients with moderate CHF. These findings advocate for application of IMT in cardiac rehabilitation programmes.

Impacts of a word-picture training on reading in youth with mixed intellectual disabilities. A waiting-list control group comparison

Individuals with intellectual disabilities (ID) often struggle with learning how to read. Reading difficulties seem to be the most common secondary condition of ID. Only one in five children with mild or moderate ID achieves even minimal literacy skills. However, literacy education for children and adolescents with ID has been largely overlooked by researchers and educators. While there is little research on reading of children with ID, many training studies have been conducted with other populations with reading difficulties. The most common approach of acquiring literacy skills consists of sophisticated programs that train phonological skills and auditory perception. Only few studies investigated the influence of implicit learning on literacy skills. Implicit learning processes seem to be largely independent of age and IQ. Children are sensitive to the statistics of their learning environment. By frequent word reading they acquire implicit knowledge about the frequency of single letters and letter patterns in written words. Additionally, semantic connections not only improve the word understanding, but also facilitate storage of words in memory. Advances in communication technology have introduced new possibilities for remediating literacy skills. Computers can provide training material in attractive ways, for example through animations and immediate feedback .These opportunities can scaffold and support attention processes central to learning. Thus, the aim of this intervention study was to develop and implement a computer based word-picture training, which is based on statistical and semantic learning, and to examine the training effects on reading, spelling and attention in children and adolescents (9-16 years) diagnosed with mental retardation (general IQ  74). Fifty children participated in four to five weekly training sessions of 15-20 minutes over 4 weeks, and completed assessments of attention, reading, spelling, short-term memory and fluid intelligence before and after training. After a first assessment (T1), the entire sample was divided in a training group (group A) and a waiting control group (group B). After 4 weeks of training with group A, a second assessment (T2) was administered with both training groups. Afterwards, group B was trained for 4 weeks, before a last assessment (T3) was carried out in both groups. Overall, the results showed that the word-picture training led to substantial gains on word decoding and attention for both training groups. These effects were preserved six weeks later (group A). There was also a clear tendency of improvement in spelling after training for both groups, although the effect did not reach significance. These findings highlight the fact that an implicit statistical learning training in a playful way by motivating computer programs can not only promote reading development, but also attention in children with intellectual disabilities.

Individual Video Training - Entwicklung einer nationalen Infrastruktur für Video-unterstütztes Lernen

Video-basiertes Lernen ist besonders effektiv, wo es um Fertigkeiten und Verhalten geht. Videoaufzeichnungen von Gesprächen, Unterrichtssituationen oder der Durchführung praktischer Tätigkeiten wie dem Nähen einer Wunde erlauben es den Ausführenden, ihren Peers und ihren Tutoren, die Qualität der Leistung zu beurteilen und Anregungen zur Verbesserung zu formulieren. Wissend um den grossen didaktischen Wert von Videoaufzeichnungen haben sich vier Pädagogische Hochschulen (Zürich, Freiburg, Thurgau, Luzern) und zwei Medizinische Fakultäten (Bern, Lausanne) zusammen getan, um eine nationale Infrastruktur für Video-unterstütztes Lernen anzustossen. Ziel was es, ein System zu entwickeln, das einfach zu bedienen ist, bei dem viele Arbeitsschritte automatisiert sind und das die Videos im Internet bereit stellt. Zusammen mit SWITCH, der nationalen IT-Support-Organisation der Schweizer Hochschulen, wurde basierend auf den vorbestehenden Technologien AAI und SWITCHcast das Programm iVT (Individual Video Training) entwickelt. Die Integration des nationalen Single Logon System AAI (Authentification and Authorization Infrastructure) erlaubt es, die Videos mit dem jeweiligen User eindeutig zu verknüpfen, so dass die Videos nur für diesen User im Internet zugänglich sind. Mit dem Podcast-System SWITCHcast können Videos automatisch ins Internet hochgeladen und bereit gestellt werden. Es wurden je ein Plugin für die Learning Management Systeme ILIAS (PH Zürich, Uni Bern) und Moodle (Uni Lausanne) entwickelt. Dank dieser Plugins werden die Videos in den jeweiligen LMS verfügbar gemacht. Der Einsatz von iVT ist beim Kommunikationstraining unserer Medizinstudierenden in Bern inzwischen Standard. Das Login gilt gleichzeitig als Beleg für das Testat. Studierende, die keine Videoaufzeichnung wünschen, können diese nach dem Login stoppen. Bis anhin ist das Betrachten der Videos freiwillig. Szenarios mit Peer Feedback sind geplant. Eine entsprechende Erweiterung des Systems um gegenseitige Annotationsmöglichkeiten besteht bereits und wird fortlaufend weiterentwickelt.

Adaptable Visualisation Based On User Needs

Software developers often ask questions about software systems and software ecosystems that entail exploration and navigation, such as who uses this component?, and where is this feature implemented?. Software visualisation can be a great aid to understanding and exploring the answers to such questions, but visualisations require expertise to implement effectively, and they do not always scale well to large systems. We propose to automatically generate software visualisations based on software models derived from open source software corpora and from an analysis of the properties of typical developers queries and commonly used visualisations. The key challenges we see are (1) understanding how to match queries to suitable visualisations, and (2) scaling visualisations effectively to very large software systems and corpora. In the paper we motivate the idea of automatic software visualisation, we enumerate the challenges and our proposals to address them, and we describe some very initial results in our attempts to develop scalable visualisations of open source software corpora.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Synergistic User <-> Context Analytics

Various avours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semantically-rich insights from people's low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental (e.g. weather, infrastructure) and application-specific data, to better capture the interactions between users and their context, in addition to those among users. To illustrate our proposed concept of synergistic user <-> context analytics, we first provide some example use cases. Then, we present our ongoing work towards a synergistic analytics platform: a testbed, based on mobile crowdsensing and the Internet of Things (IoT), a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.

Development and Evaluation of a New Tablet Computer Application for the Therapy of Brain-Injured Patients with Aphasia

Introduction Language is the most important mean of communication and plays a central role in our everyday life. Brain damage (e.g. stroke) can lead to acquired disorders of lan- guage affecting the four linguistic modalities (i.e. reading, writing, speech production and comprehension) in different combinations and levels of severity. Every year, more than 5000 people (Aphasie Suisse) are affected by aphasia in Switzerland alone. Since aphasia is highly individual, the level of difficulty and the content of tasks have to be adapted continuously by the speech therapists. Computer-based assignments allow patients to train independently at home and thus increasing the frequency of ther- apy. Recent developments in tablet computers have opened new opportunities to use these devices for rehabilitation purposes. Especially older people, who have no prior experience with computers, can benefit from the new technologies. Methods The aim of this project was to develop an application that enables patients to train language related tasks autonomously and, on the other hand, allows speech therapists to assign exercises to the patients and to track their results online. Seven categories with various types of assignments were implemented. The application has two parts which are separated by a user management system into a patient interface and a therapist interface. Both interfaces were evaluated using the SUS (Subject Usability Scale). The patient interface was tested by 15 healthy controls and 5 patients. For the patients, we also collected tracking data for further analysis. The therapist interface was evaluated by 5 speech therapists. Results The SUS score are xpatients = 98 and xhealthy = 92.7 (median = 95, SD = 7, 95% CI [88.8, 96.6]) in case of the patient interface and xtherapists = 68 in case of the therapist interface. Conclusion Both, the patients and the healthy subjects, attested high SUS scores to the patient interface. These scores are considered as "best imaginable". The therapist interface got a lower SUS score compared to the patient interface, but is still considered as "good" and "usable". The user tracking system and the interviews revealed that there is room for improvements and inspired new ideas for future versions.

Working memory training in children: Effectiveness depends on temperament

Studies revealing transfer effects of working memory (WM) training on non-trained cognitive performance of children hold promising implications for scholastic learning. However, the results of existing training studies are not consistent and provoke debates about the potential and limitations of cognitive enhancement. To examine the influence of individual differences on training outcomes is a promising approach for finding causes for such inconsistencies. In this study, we implemented WM training in an elementary school setting. The aim was to investigate near and far transfer effects on cognitive abilities and academic achievement and to examine the moderating effects of a dispositional and a regulative temperament factor, neuroticism and effortful control. Ninetynine second-graders were randomly assigned to 20 sessions of computer-based adaptiveWMtraining, computer-based reading training, or a no-contact control group. For the WM training group, our analyses reveal near transfer on a visual WM task, far transfer on a vocabulary task as a proxy for crystallized intelligence, and increased academic achievement in reading and math by trend. Considering individual differences in temperament, we found that effortful control predicts larger training mean and gain scores and that there is a moderation effect of both temperament factors on post-training improvement: WM training condition predicted higher post-training gains compared to both control conditions only in children with high effortful control or low neuroticism. Our results suggest that a short but intensive WM training program can enhance cognitive abilities in children, but that sufficient selfregulative abilities and emotional stability are necessary for WM training to be effective.