Device and context influence on wireless infotainment access: A real world story

Copyright @ 2005 CEPISUser considerations are paramount when it comes to take up of technologies, and even more so in the case of mobile devices, in which the success of a particular device often depends on its novelty appeal. However, relatively little work has been undertaken exploring how day-to-day tasks are affected when mediated by such access devices. This paper reports the results of an empirical study placed in a 'real-world' setting, in which participants undertook typical infotainment - combined information and entertainment access tasks on three different wireless-enabled mobile devices. These were a laptop, a Personal Digital Assistant and a Head Mounted Display device. Our results show that, with the exception of participants' level of self-consciousness when using such devices in public environments, the user wireless infotainment access experience is generally unaffected by device type. Location was shown, though, to be a significant factor when users engage in tasks such as listening to online music or navigation

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500 Computing Tips for Teachers and Lecturers by Phil Race and Steve McDowell, London: Kogan Page, 1996. ISBN: 0–7494–1931–8. 135 pages, paperback. £15.99

Indexing of fictional video content for event detection and summarisation

This paper presents an approach to movie video indexing that utilises audiovisual analysis to detect important and meaningful temporal video segments, that we term events. We consider three event classes, corresponding to dialogues, action sequences, and montages, where the latter also includes musical sequences. These three event classes are intuitive for a viewer to understand and recognise whilst accounting for over 90% of the content of most movies. To detect events we leverage traditional filmmaking principles and map these to a set of computable low-level audiovisual features. Finite state machines (FSMs) are used to detect when temporal sequences of specific features occur. A set of heuristics, again inspired by filmmaking conventions, are then applied to the output of multiple FSMs to detect the required events. A movie search system, named MovieBrowser, built upon this approach is also described. The overall approach is evaluated against a ground truth of over twenty-three hours of movie content drawn from various genres and consistently obtains high precision and recall for all event classes. A user experiment designed to evaluate the usefulness of an event-based structure for both searching and browsing movie archives is also described and the results indicate the usefulness of the proposed approach

An introduction to learning technology in tertiary education in the UK.

Contents: 1. The Learning Technology Arena 2. The Learning Technology Community 3. Learning Technology Tools 4. Key issues and developments in the Learning Technology Field 5. Implementing Learning Technologies 6. Further Resource

Deep Reinforcement Learning for Resource Management in Network Slicing

Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices. In order to provide better-performing and cost-efficient services, network slicing involves challenging technical issues and urgently looks forward to intelligent innovations to make the resource management consistent with users' activities per slice. In that regard, deep reinforcement learning (DRL), which focuses on how to interact with the environment by trying alternative actions and reinforcing the tendency actions producing more rewarding consequences, is assumed to be a promising solution. In this paper, after briefly reviewing the fundamental concepts of DRL, we investigate the application of DRL in solving some typical resource management for network slicing scenarios, which include radio resource slicing and priority-based core network slicing, and demonstrate the advantage of DRL over several competing schemes through extensive simulations. Finally, we also discuss the possible challenges to apply DRL in network slicing from a general perspective.Comment: The manuscript has been accepted by IEEE Access in Nov. 201

Research Methodologies in MIS: An Update

This article presents trends in published MIS research for an 11 year period, 1993-2003. It is an update of a previous article in CAIS (Volume 11, Article 16) that covered the period 1993-1997. All of the articles in seven mainstream MIS journals were examined in terms of subjects researched and methodologies employed to conduct research. Recent trends are presented and compared to those of the earlier study. The results clearly indicate the focus of efforts of researchers on information system usage and information systems resource management. The survey methodology still appeals to many researchers but increases in the use of mathematical models and laboratory experiments is an indication that the field is attaining maturity by using more rigorous research methods

Special issue on soft computing applications to intelligent information retrieval on the Internet

This special issue encompasses eleven papers devoted to the recent developments in the applications of soft computing (SC) techniques to information retrieval (IR), both in the text and Web retrieval areas. The seed of the current issue were some of the presentations made in two special sessions organized by the guest editors in two different conferences: the First Spanish Conference on Evolutionary and Bioinspired Algorithms (AEB’02), that was held in M erida, Spain, February 2002, and the Seventh International ISKO Conference (ISKO’02), held in Granada, Spain, July 2002. The scope of both special sessions was pretty related. In the former conference, the session topic was ‘‘Applications of Evolutionary Computation to Information Retrieval’’ while in the latter the session was entitled ‘‘Artificial Intelligence Applications to Information Retrieval’’