Speaker: Annalu Waller, University of Dundee

Abstract:

Augmentative and alternative communication (AAC) attempts to augment natural speech, or to provide alternative ways to communicate for people with limited or no speech. Technology has played an increasing role in AAC. At the most simplest level, people with complex communication needs (CCN) can cause a prestored message to be spoken by activating a single switch. At the most sophisticated level, literate users can generate novel text. Although some individuals with CCN become effective communicators, most do not – they tend to be passive communicators, responding mainly to questions or prompts at a one or two word level. Conversational skills such as initiation, elaboration and story telling are seldom observed.
One reason for the reduced levels of communicative ability is that AAC technology provides the user with a purely physical link to speech output. The user is required to have sufficient language abilities and physical stamina to translate what they want to say into the code sequence of operations needed to produce the desired output. Instead of placing all the cognitive load on the user, AAC devices can be designed to support the cognitive and language needs of individuals with CCN, taking into account the need to scaffold communication as children develop into adulthood. A range of research projects, including systems to support personal narrative and language play, will be used to illustrate the application of Human Computer Interaction (HCI) and Natural Language Generation (NLG) in the design and implementation of electronic AAC devices.

About Annalu:
Dr Annalu Waller is a Senior Lecturer in the School of Computing at the University of Dundee. She has worked in the field of Augmentative and Alternate Communication (AAC) since 1985, designing communication systems for and with nonspeaking individuals. She established the first AAC assessment and training centre in South Africa in 1987 before coming to Dundee in 1989. Her PhD developed narrative technology support for adults with acquired dysphasia following stroke. Her primary research areas are human computer interaction, natural language generation, personal narrative and assistive technology. In particular, she focuses on empowering end users, including disabled adults and children, by involving them in the design and use of technology. She manages a number of interdisciplinary research projects with industry and practitioners from rehabilitation engineering, special education, speech and language therapy, nursing and dentistry. She is on the editorial boards of several academic journals and sits on the boards of a number of national and international organisations representing disabled people.

Speaker: Aaron Quigley, SACHI University of St Andrews

Abstract:

Our bodies shape our experience of the world, and our bodies influence what we design. How important are the physical differences between people? Can we model the physiological differences and use the models to adapt and personalize designs, user interfaces and artifacts? Within many disciplines Digital Human Models and Standard Observer Models are widely used and have proven to be very useful for modeling users and simulating humans. In this paper, we create personalized digital human models of perception (Individual Observer Models), particularly focused on how humans see. Individual Observer Models capture how our bodies shape our perceptions. Individual Observer Models are useful for adapting and personalizing user interfaces and artifacts to suit individual users’ bodies and perceptions. We introduce and demonstrate an Individual Observer Model of human eyesight, which we use to simulate 3600 biologically valid human eyes. An evaluation of the simulated eyes finds that they see eye charts the same as humans. Also demonstrated is the Individual Observer Model successfully making predictions about how easy or hard it is to see visual information and visual designs. The ability to predict and adapt visual information to maximize how effective it is is an important problem in visual design and analytics.

About Aaron:

In this talk Professor Aaron Quigley will present a talk for a paper he is presenting at the User Modeling, Adaptation and Personalization (UMAP) conference 2011 on July 12th in Barcelona Spain. This work on Creating Personalized Digital Human Models of Perception for Visual Analytics is the work with and of his former PhD student Dr. Mike Bennett and now postdoctoral fellow in the Department of Psychology in Stanford University.

Professor Aaron Quigley is the Chair of Human Computer Interaction in the School of Computer Science at the University of St Andrews. He is the director of SACHI and his appointment is part of SICSA, the Scottish Informatics and Computer Science Alliance. Aaron’s research interests include surface and multi-display computing, human computer interaction, pervasive and ubiquitous computing and information visualisation.

Speaker: Sean Lynch, Innovis group/Interactions lab, University of Calgary, Canada

Abstract:

Information visualization and new paradigms of interaction are generally applied to productive processes (i.e., at work) or for personal and entertainment purposes. In my work, I have looked instead at how to apply new technologies and visualization techniques to art. I will present mainly two projects that focus on multi-touch music composition and performance, and the visual analysis of the history and visual features of fine paintings.

About Sean:

Sean Lynch is a Master’s Student in Computer Science at the Interactions Lab at the University of Calgary. Sean’s research interests span interactive technologies (e.g., multi-touch), interactive art, and information visualization.

Speaker: Peterri Nurmi,  Helsinki Institute for Information Technology HIIT
Abstract:
Contemporary mobile phones readily support different positioning techniques. In addition to integrated GPS receivers, GSM and WiFi can be used for position estimation, and other sensors such as accelerometers and digital compasses can be used to support positioning, e.g., through dead reckoning or the detection of stationary periods. Selecting which sensor technologies to use for positioning is, however, a non-trivial task as available sensor technologies vary considerably in terms of their energy demand and the accuracy of location estimates. To improve the energy-efficiency of mobile devices and to provide as accurate position estimates as possible, novel on-device positioning technologies together with techniques that select optimal sensor modalities based on positioning accuracy requirements are required. In this talk we first introduce novel GSM and WiFi fingerprinting algorithms that run directly on mobile devices with minimal energy consumption [1]. We also introduce our recent work on minimizing the power consumption of continuous location and trajectory tracking on mobile devices [2].
[1] P. Nurmi, S. Bhattacharya, J. Kukkonen: “A grid-based algorithm for on-device GSM positioning.” Proc. 12th ACM International Conference on Ubiquitous Computing (Ubicomp, Copenhagen, Denmark, September 2010). ACM Press, 2010, 227-236.
[2] M. B. Kjaergaard, S. Bhattacharya, H. Blunck, P. Nurmi, “Energy-efficient Trajectory Tracking for Mobile Devices”, Proc. 9th International Conference on Mobile Systems, Applications and Services (MobiSys, June-July, 2011).

About Petteri:
Dr. Petteri Nurmi is a Senior Researcher at the Helsinki Institute for Information Technology HIIT. He received a PhD in Computer Science from the University of Helsinki in 2009. He is currently co-leading the Adaptive Computing research group at HIIT together with Doc. Patrik Floréen. His research focuses on ubiquitous computing, user modeling and interaction with a view of making the life of ordinary people easier through easy-to-use mobile services. He regularly serves as Program Committee Member and reviewer for numerous leading conferences and journals. More information about his research can be found from the webpage of the research group: http://www.hiit.fi/adapc/

Speaker: Mirco Musolesi, Computer Science, University of St Andrews

Abstract:

Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, that can be used to sense and interpret people behaviour in real-time. Novel user-centered sensing applications can be built by exploiting the availability of such technologies in these devices that are part of our everyday experience. Moreover, data extracted from the sensors can also be used to model people behaviour and movement patterns providing a very rich set of multi-dimensional data, which can be extremely useful for social science, marketing and epidemiological studies.

In this talk I will present some of my recent work in this area including the design and implementation of the CenceMe platform, a system that supports the inference of activities and other presence information of individuals using off-the-shelf sensor-enabled phones and of EmotionSense, a system for supporting social psychology research. Finally, I will discuss the issues related to the design of energy-efficient social sensing systems.

About Mirco:

Dr. Mirco Musolesi is a SICSA Lecturer at the School of Computer Science at the University of St. Andrews. He received a PhD in Computer Science from University College London in 2007 and a Master in Electronic Engineering from the University of Bologna in 2002. From October 2005 to August 2007 he was a Research Fellow at the Department of Computer Science, University College London. Then, from September 2007 to August 2008 he was an ISTS Postdoctoral Research Fellow at Dartmouth College, NH, USA, and from September 2008 to October 2009 a Postdoctoral Research Associate at the Computer Laboratory, University of Cambridge. His research interests lie in the broad area of mobile systems and networking with a current focus on intelligent mobile systems, online social networks, application of complex network theory to networked systems design, mobility modelling and sensing systems based on mobile phones. More information about his research profile can be found at the following URL: http://www.cs.st-andrews.ac.uk/~mirco