A distributed memory for networked livecoding performance

The symbolic and improvisational nature of Livecoding requires a shared networking framework to be flexible and extensible, while at the same time providing support for synchronisation, persistence and redundancy. Above all the framework should be robust and available across a range of platforms. This paper proposes tuple space as a suitable framework for network communication in ensemble livecoding contexts. The role of tuple space as a concurrency framework and the associated timing aspects of the tuple space model are explored through Spaces, an implementation of tuple space for the Impromptu environment.

Research report : computer surfaces and cross-infection

The computer is fast becoming part of the furniture in many hospital settings. Increasing reliance on the computer for documentation and dissemination of information in patient-care areas has increased the need to consider this equipment as a potential environmental reservoir for microorganisms. This paper reports on a small experimental study which investigated the potential role of computers in cross-infection. The results indicate that computer surfaces are similar to other environmental surfaces and carry the same risks for cross-infection.

Eat Cook Grow : Mixing Human-Computer Interactions with Human-Food Interactions

Food has been a major agenda in political, socio-cultural, and environmental domains throughout history. The significance of food has been particularly highlighted in recent years with the growing public awareness of the unfolding impacts of climate change, challenging our understanding, practice, and expectations of our relationship with food. Parallel to this development has been the rise of web applications such as blogs, wikis, video and photo sharing sites, and social networking systems that are arguably more open, collaborative, and personalisable. These so-called ‘Web 2.0’ technologies have contributed to a more participatory Internet experience than what had previously been possible. An increasing number of these social applications are now available on mobile technologies where they take advantage of device-specific features such as sensors, location and context awareness, further expanding potential for the culture of participation and creativity. This international volume assembles a diverse collection of book chapters that contribute towards exploring and better understanding the opportunities and challenges provided by tools, interfaces, methods, and practices of social and mobile technology to enable engagement with people and creativity in the domain of food in contemporary society. It brings together an international group of academics and practitioners from a diverse range of disciplines such as computing and engineering, social sciences, digital media and human-computer interaction to critically examine a range of applications of social and mobile technology, such as social networking, mobile interaction, wikis, twitter, blogging, mapping, shared displays and urban screens, and their impact to foster a better understanding and practice of environmentally, socio-culturally, economically, and health-wise sustainable food culture.

A qualitative think aloud study of the early Neo-Piagetian stages of reasoning in novice programmers

Recent research indicates that some of the difficulties faced by novice programmers are manifested very early in their learning. In this paper, we present data from think aloud studies that demonstrate the nature of those difficulties. In the think alouds, novices were required to complete short programming tasks which involved either hand executing ("tracing") a short piece of code, or writing a single sentence describing the purpose of the code. We interpret our think aloud data within a neo-Piagetian framework, demonstrating that some novices reason at the sensorimotor and preoperational stages, not at the higher concrete operational stage at which most instruction is implicitly targeted.

A conceptual model for reflecting on expected learning vs. demonstrated student performance

Educators are faced with many challenging questions in designing an effective curriculum. What prerequisite knowledge do students have before commencing a new subject? At what level of mastery? What is the spread of capabilities between bare-passing students vs. the top performing group? How does the intended learning specification compare to student performance at the end of a subject? In this paper we present a conceptual model that helps in answering some of these questions. It has the following main capabilities: capturing the learning specification in terms of syllabus topics and outcomes; capturing mastery levels to model progression; capturing the minimal vs. aspirational learning design; capturing confidence and reliability metrics for each of these mappings; and finally, comparing and reflecting on the learning specification against actual student performance. We present a web-based implementation of the model, and validate it by mapping the final exams from four programming subjects against the ACM/IEEE CS2013 topics and outcomes, using Bloom's Taxonomy as the mastery scale. We then import the itemised exam grades from 632 students across the four subjects and compare the demonstrated student performance against the expected learning for each of these. Key contributions of this work are the validated conceptual model for capturing and comparing expected learning vs. demonstrated performance, and a web-based implementation of this model, which is made freely available online as a community resource.

On the statistical determination of optimal camera configurations in large scale surveillance networks

The selection of optimal camera configurations (camera locations, orientations etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we introduce a statistical formulation of the optimal selection of camera configurations as well as propose a Trans-Dimensional Simulated Annealing (TDSA) algorithm to effectively solve the problem. We compare our approach with a state-of-the-art method based on Binary Integer Programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than 2 alternative heuristics designed to deal with the scalability issue of BIP.