Digital places: location-based digital practices in higher education using Bluetooth Beacons

The physical campus is a shared space that enables staff and students, industry and the public, to collaborate in the acquisition, construction and consolidation of knowledge. However, its position as the primary place for learning is being challenged by blended modes of study that range from learning experiences from fully online to more traditional campus-based approaches. Bluetooth beacons offer the potential to combine the strengths of both the digital world and the traditional university campus by augmenting physical spaces to enhance learning opportunities, and the student experience more generally. This simple technology offers new possibilities to extend and enrich opportunities for learning by exploiting the near-ubiquitous nature of personal technology. This paper provides a high-level overview of Bluetooth beacon technology, along with an indication of some of the ways in which it is developing, and ways that it could be used to support learning in higher education

A comparison of score, rank and probability-based fusion methods for video shot retrieval

It is now accepted that the most effective video shot retrieval is based on indexing and retrieving clips using multiple, parallel modalities such as text-matching, image-matching and feature matching and then combining or fusing these parallel retrieval streams in some way. In this paper we investigate a range of fusion methods for combining based on multiple visual features (colour, edge and texture), for combining based on multiple visual examples in the query and for combining multiple modalities (text and visual). Using three TRECVid collections and the TRECVid search task, we specifically compare fusion methods based on normalised score and rank that use either the average, weighted average or maximum of retrieval results from a discrete Jelinek-Mercer smoothed language model. We also compare these results with a simple probability-based combination of the language model results that assumes all features and visual examples are fully independent

Dublin City University at CLEF 2005: Experiments with the ImageCLEF St Andrew’s collection

The aim of the Dublin City University participation in the CLEF 2005 ImageCLEF St Andrew’s Collection task was to explore an alternative approach to exploiting text annotation and content-based retrieval in a novel combined way for pseudo relevance feedback (PRF). This method combines evidence from retrieved lists generated using text and content-based retrieval to determine which documents will be assumed relevant for the PRF process. Unfortunately the results show that while standard textbased PRF improves upon a no feedback text baseline, at present our new approach to combining evidence from text and content-based retrieval does not give further improve improvement

Discrete language models for video retrieval

Finding relevant video content is important for producers of television news, documentanes and commercials. As digital video collections become more widely available, content-based video retrieval tools will likely grow in importance for an even wider group of users. In this thesis we investigate language modelling approaches, that have been the focus of recent attention within the text information retrieval community, for the video search task. Language models are smoothed discrete generative probability distributions generally of text and provide a neat information retrieval formalism that we believe is equally applicable to traditional visual features as to text. We propose to model colour, edge and texture histogrambased features directly with discrete language models and this approach is compatible with further traditional visual feature representations. We provide a comprehensive and robust empirical study of smoothing methods, hierarchical semantic and physical structures, and fusion methods for this language modelling approach to video retrieval. The advantage of our approach is that it provides a consistent, effective and relatively efficient model for video retrieval

Exploring the transformative potential of Bluetooth beacons in higher education

The growing ubiquity of smartphones and tablet devices integrated into personal, social and professional life, facilitated by expansive communication networks globally, has the potential to disrupt higher education. Academics and students are considering the future possibilities of exploiting these tools and utilising networks to consolidate and expand knowledge, enhancing learning gain. Bluetooth beacon technology has been developed by both Apple and Google as a way to situate digital information within physical spaces, and this paper reflects on a beacon intervention in a contemporary art school in higher education conducted by the authors intended to develop a situated community of practice in Art & Design. The paper describes the project, including relevant theoretical foundations and background to the beacon technology, with regards to the potential of using these devices to create a connected learning community by enhancing learning and facilitating knowledge creation in a borderless learning space

Use of the Físchlár video library system

Físchlár is a shared video retrieval system that lets users record, browse and watch television programmes using their web browser. In Físchlár, the programmes users can watch and record are organised by channel, by theme and by personal recommendation as provided by the ChangingWorlds’ ClixSmart personalisation engine. Our initial results from user trials illustrate the usage of each of these features

Online television library: organization and content browsing for general users

This paper describes the organisational and playback features of Físchlár, a digital video library that allows users to record, browse and watch television programmes online. Programmes that can be watched and recorded are organised by personal recommendations, genre classifications, name and other attributes for access by general television users. Motivations and interactions of users with online television libraries are outlined and they are also supported by personalised library access, categorised programmes, a combined player browser with content viewing history and content marks. The combined player browser supports a user who watches a programme on different occasions in a non-sequential order

Improving the quality of the personalized electronic program guide

As Digital TV subscribers are offered more and more channels, it is becoming increasingly difficult for them to locate the right programme information at the right time. The personalized Electronic Programme Guide (pEPG) is one solution to this problem; it leverages artificial intelligence and user profiling techniques to learn about the viewing preferences of individual users in order to compile personalized viewing guides that fit their individual preferences. Very often the limited availability of profiling information is a key limiting factor in such personalized recommender systems. For example, it is well known that collaborative filtering approaches suffer significantly from the sparsity problem, which exists because the expected item-overlap between profiles is usually very low. In this article we address the sparsity problem in the Digital TV domain. We propose the use of data mining techniques as a way of supplementing meagre ratings-based profile knowledge with additional item-similarity knowledge that can be automatically discovered by mining user profiles. We argue that this new similarity knowledge can significantly enhance the performance of a recommender system in even the sparsest of profile spaces. Moreover, we provide an extensive evaluation of our approach using two large-scale, state-of-the-art online systems—PTVPlus, a personalized TV listings portal and Físchlár, an online digital video library system

Dublin City University video track experiments for TREC 2001

Dublin City University participated in the interactive search task and Shot Boundary Detection task* of the TREC Video Track. In the interactive search task experiment thirty people used three different digital video browsers to find video segments matching the given topics. Each user was under a time constraint of six minutes for each topic assigned to them. The purpose of this experiment was to compare video browsers and so a method was developed for combining independent users’ results for a topic into one set of results. Collated results based on thirty users are available herein though individual users’ and browsers’ results are currently unavailable for comparison. Our purpose in participating in this TREC track was to create the ground truth within the TREC framework, which will allow us to do direct browser performance comparisons

Net-Zero Design Education. Transition to “Better States” in Understanding Carbon and the Design Process

Design education must adapt to the changing attitudes of student designers, and industry immediately. The consequence of how we design shapes the attitudes, values, and decisions student designers make across a professional career. Design education must be responsible for how they facilitate a course and the projects they deploy. Decision-making in the process of designing subsequently develops values and impacts that transcend beyond a design course. The research adopted a mixed-methods approach comprising of semi-structured interviews, questionnaires, and data tracking of an undergraduate visual communication cohort. Activity data enabled understanding of the cultural, leadership and transitioning challenges associated with the design process. The project surfaced gaps in the organisation, knowledge, process, skills, tools and technologies embedded into the design process. This research situates a critical pivot in design education demanding a cultural shift for a Net-Zero world