162,042 research outputs found

    Kinect-based RGB detection for 'smart' costume interaction.

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    This paper is an overview of a Kinect-based RGB detection software developed as part of an ongoing 'Smart' (Smart Textiles and Wearable Technology in Pervasive Computing Environments) Costume project. The project involved a multi-disciplinary team in the domains of textile design, engineering and computer science. In this work we aimed to establish initial studies on how the Microsoft Kinect performs in tracking a "smart" lighting conditions. We explain the computer application capable of detecting, tracking and measuring colour changes (Red, Blue and Green) created using the Microsoft Kinect API

    Which Design Decisions in AI-enabled Mobile Applications Contribute to Greener AI?

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    Background: The construction, evolution and usage of complex artificial intelligence (AI) models demand expensive computational resources. While currently available high-performance computing environments support well this complexity, the deployment of AI models in mobile devices, which is an increasing trend, is challenging. Mobile applications consist of environments with low computational resources and hence imply limitations in the design decisions during the AI-enabled software engineering lifecycle that balance the trade-off between the accuracy and the complexity of the mobile applications. Objective: Our objective is to systematically assess the trade-off between accuracy and complexity when deploying complex AI models (e.g. neural networks) to mobile devices, which have an implicit resource limitation. We aim to cover (i) the impact of the design decisions on the achievement of high-accuracy and low resource-consumption implementations; and (ii) the validation of profiling tools for systematically promoting greener AI. Method: This confirmatory registered report consists of a plan to conduct an empirical study to quantify the implications of the design decisions on AI-enabled applications performance and to report experiences of the end-to-end AI-enabled software engineering lifecycle. Concretely, we will implement both image-based and language-based neural networks in mobile applications to solve multiple image classification and text classification problems on different benchmark datasets. Overall, we plan to model the accuracy and complexity of AI-enabled applications in operation with respect to their design decisions and will provide tools for allowing practitioners to gain consciousness of the quantitative relationship between the design decisions and the green characteristics of study.Comment: Accepted as registered report at ESEM 202

    Agent Assistance: From Problem Solving to Music Teaching

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    We report on our research on agents that act and behave in a web learning environment. This research is part of a general approach to agents acting and behaving in virtual environments where they are involved in providing information, performing transactions, demonstrating products and, more generally, assisting users or visitors of the web environment in doing what they want or have been asked to do. While initially we hardly provided our agents with 'teaching knowledge', we now are in the process of making such knowledge explicit, especially in models that take into account that assisting and teaching takes place in a visualized and information-rich environment. Our main (embodied) tutor-agent is called Jacob; it knows about the Towers of Hanoi, a well-known problem that is offered to CS students to learn about recursion. Other agents we are working on assist a visitor in navigating in a virtual world or help the visitor in getting information. We are now designing a music teacher - using knowledge of software engineering and how to design multi-modal interactions, from previous projects

    Learning from Digital Natives: Bridging Formal and Informal Learning. Final Report

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    Overview This report suggests that students are increasingly making use of a variety of etools (such as mobile phones, email, MSN, digital cameras, games consoles and social networking sites) to support their informal learning within formalised educational settings, and that they use the tools that they have available if none are provided for them. Therefore, higher education institutions should encourage the use of these tools. Aims and background This study aimed to explore how e-tools (such as mobile phones, email, MSN, digital cameras, games consoles and social networking sites) and the processes that underpin their use can support learning within educational institutions and help improve the quality of students’ experiences of learning in higher education (pgs 9-11). Methodology The study entailed: (i) desk research to identify related international research and practice and examples of integration of e-tools and learning processes in formal educational settings; (ii) a survey of 160 engineering and social work students across two contrasting Scottish universities (pre- and post-1992) – the University of Strathclyde and Glasgow Caledonian University – and follow-up interviews with eight students across the two subject areas to explore which technologies students were using for both learning and leisure activities within and outside the formal educational settings and how they would like to use such technologies to support their learning in both formal and informal settings; and (iii) interviews with eight members of staff from across the institutions and two subject areas to identify their perceptions of the educational value of the e-tools. (pgs 24-27). Key findings • Students reported making extensive use of a variety of both e-tools (such as mobile phones, email, MSN, digital cameras) and social networking tools (such as Bebo, MySpace, Wikipedia and YouTube) for informal socialisation, communication, information gathering, content creation and sharing, alongside using the institutionally provided technologies and learning environments. • Most of the students owned their own computer or had access to a sibling or parent’s computer. Many students owned a laptop but preferred not to bring it onto campus due to security concerns and because they found it too heavy to carry about. • Ownership of mobile phones was ubiquitous. • Whilst the students’ information searching literacy seemed adequate, the ability of these students to harness the power of social networking tools and informal processes for their learning was low. Staff reported using a few Web 2.0 and social software tools but they were generally less familiar with how these could be used to support learning and teaching. There were misconceptions surrounding the affordances of the tools and fears expressed about security and invasion of personal space. Considerations of the costs and the time it would take staff to develop their skills meant that there was a reluctance to take up new technologies at an institutional level. • Subject differences emerged in both staff and student perceptions as to which type of tools they would find most useful. Attitudes to Web 2.0 tools were different. Engineers were concerned with reliability, using institutional systems and inter-operability. Social workers were more flexible because they were focused on communication and professional needs. • The study concluded that digital tools, personal devices, social networking software and many of the other tools explored all have a large educational potential to support learning processing and teaching practices. Therefore, use of these tools and processes within institutions, amongst staff and students should be encouraged. • The report goes on to suggest ways in which the use of such technologies can help strengthen the links between informal and formal learning in higher education. The recommendations are grouped under four areas – pedagogical, socio-cultural, organisational and technological
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