Understanding Online Audio-Visual Content: A European Initiative, Media Literacy and the User

Recent debates about media literacy and the internet have begun to acknowledge the importance of active user-engagement and interaction. It is not enough simply to access material online, but also to comment upon it and re-use. Yet how do these new user expectations fit within digital initiatives which increase access to audio-visual-content but which prioritise access and preservation of archives and online research rather than active user-engagement? This article will address these issues of media literacy in relation to audio-visual content. It will consider how these issues are currently being addressed, focusing particularly on the high-profile European initiative EUscreen. EUscreen brings together 20 European television archives into a single searchable database of over 40,000 digital items. Yet creative re-use restrictions and copyright issues prevent users from re-working the material they find on the site. Instead of re-use, EUscreen instead offers access and detailed contextualisation of its collection of material. But if the emphasis for resources within an online environment rests no longer upon access but on user-engagement, what does EUscreen and similar sites offer to different users?

Robust Audio-Visual Speech Recognition under Noisy Audio-Video Conditions

This paper presents the maximum weighted stream posterior (MWSP) model as a robust and efficient stream integration method for audio-visual speech recognition in environments, where the audio or video streams may be subjected to unknown and time-varying corruption. A significant advantage of MWSP is that it does not require any specific measurements of the signal in either stream to calculate appropriate stream weights during recognition, and as such it is modality-independent. This also means that MWSP complements and can be used alongside many of the other approaches that have been proposed in the literature for this problem. For evaluation we used the large XM2VTS database for speaker-independent audio-visual speech recognition. The extensive tests include both clean and corrupted utterances with corruption added in either/both the video and audio streams using a variety of types (e.g., MPEG-4 video compression) and levels of noise. The experiments show that this approach gives excellent performance in comparison to another well-known dynamic stream weighting approach and also compared to any fixed-weighted integration approach in both clean conditions or when noise is added to either stream. Furthermore, our experiments show that the MWSP approach dynamically selects suitable integration weights on a frame-by-frame basis according to the level of noise in the streams and also according to the naturally fluctuating relative reliability of the modalities even in clean conditions. The MWSP approach is shown to maintain robust recognition performance in all tested conditions, while requiring no prior knowledge about the type or level of noise.

How does involvement of a hospice nurse specialist impact on the experience on informal caring in palliative care? Perspectives of middle-aged partners bereaved through cancer

The aim of this study was to retrospectively explore partners' understandings and experiences in relation to caring for a loved one with a terminal illness, with a particular focus on the role of the hospice nurse specialist (HNS). Participants were purposively sampled and recruited through HNS gatekeepers. Seven middle-aged, bereaved partners participated in semi-structured, qualitative interviews. The interviews were audio recorded and transcribed verbatim and data were analysed using thematic content analysis. Five main themes emerged regarding the impact of the HNS on informal caring: ‘the ambivalence of caring’, ‘the HNS as a “confidante” in caring’, ‘the HNS as a “champion” in support’, ‘the work of the HNS – an unseen benefit’ and ‘being prepared for death and bereavement’. Findings from this study offer new insights into how involvement of a HNS impacts on the ability of carers to perform their role as an informal caregiver. Results highlight a crucial need for carers to have a clear understanding of all aspects of the HNS role so that full benefit is derived from their input. Recruitment of experienced and knowledgeable nurses is paramount, but equally important for carers is the supportive aspect of the role for which nurses need to demonstrate excellent communication skills and an intuitive, caring approach.

Processing of short auditory stimuli:The rapid audio sequential presentation paradigm (RASP)

Human listeners seem to be remarkably able to recognise acoustic sound sources based on timbre cues. Here we describe a psychophysical paradigm to estimate the time it takes to recognise a set of complex sounds differing only in timbre cues: both in terms of the minimum duration of the sounds and the inferred neural processing time. Listeners had to respond to the human voice while ignoring a set of distractors. All sounds were recorded from natural sources over the same pitch range and equalised to the same duration and power. In a first experiment, stimuli were gated in time with a raised-cosine window of variable duration and random onset time. A voice/non-voice (yes/no) task was used. Performance, as measured by d', remained above chance for the shortest sounds tested (2 ms); d's above 1 were observed for durations longer than or equal to 8 ms. Then, we constructed sequences of short sounds presented in rapid succession. Listeners were asked to report the presence of a single voice token that could occur at a random position within the sequence. This method is analogous to the "rapid sequential visual presentation" paradigm (RSVP), which has been used to evaluate neural processing time for images. For 500-ms sequences made of 32-ms and 16-ms sounds, d' remained above chance for presentation rates of up to 30 sounds per second. There was no effect of the pitch relation between successive sounds: identical for all sounds in the sequence or random for each sound. This implies that the task was not determined by streaming or forward masking, as both phenomena would predict better performance for the random pitch condition. Overall, the recognition of familiar sound categories such as the voice seems to be surprisingly fast, both in terms of the acoustic duration required and of the underlying neural time constants.

Low-Power Process-Variation Tolerant Arithmetic Units Using Input-Based Elastic Clocking

In this paper we propose a design methodology for low-power high-performance, process-variation tolerant architecture for arithmetic units. The novelty of our approach lies in the fact that possible delay failures due to process variations and/or voltage scaling are predicted in advance and addressed by employing an elastic clocking technique. The prediction mechanism exploits the dependence of delay of arithmetic units upon input data patterns and identifies specific inputs that activate the critical path. Under iso-yield conditions, the proposed design operates at a lower scaled down Vdd without any performance degradation, while it ensures a superlative yield under a design style employing nominal supply and transistor threshold voltage. Simulation results show power savings of upto 29%, energy per computation savings of upto 25.5% and yield enhancement of upto 11.1% compared to the conventional adders and multipliers implemented in the 70nm BPTM technology. We incorporated the proposed modules in the execution unit of a five stage DLX pipeline to measure performance using SPEC2000 benchmarks [9]. Maximum area and throughput penalty obtained were 10% and 3% respectively.

MSC-clustering and forward stepwise regression for virtual metrology in highly correlated input spaces

Increasingly semiconductor manufacturers are exploring opportunities for virtual metrology (VM) enabled process monitoring and control as a means of reducing non-value added metrology and achieving ever more demanding wafer fabrication tolerances. However, developing robust, reliable and interpretable VM models can be very challenging due to the highly correlated input space often associated with the underpinning data sets. A particularly pertinent example is etch rate prediction of plasma etch processes from multichannel optical emission spectroscopy data. This paper proposes a novel input-clustering based forward stepwise regression methodology for VM model building in such highly correlated input spaces. Max Separation Clustering (MSC) is employed as a pre-processing step to identify a reduced srt of well-conditioned, representative variables that can then be used as inputs to state-of-the-art model building techniques such as Forward Selection Regression (FSR), Ridge regression, LASSO and Forward Selection Ridge Regression (FCRR). The methodology is validated on a benchmark semiconductor plasma etch dataset and the results obtained are compared with those achieved when the state-of-art approaches are applied directly to the data without the MSC pre-processing step. Significant performance improvements are observed when MSC is combined with FSR (13%) and FSRR (8.5%), but not with Ridge Regression (-1%) or LASSO (-32%). The optimal VM results are obtained using the MSC-FSR and MSC-FSRR generated models. © 2012 IEEE.

A Coordination and Ligand Replacement Based Three-Input Colorimetric Logic Gate Sensing Platform for Melamine, Mercury Ions, and Cysteine

Discrimination of different species in various target scopes within a single sensing platform can provide many advantages such as simplicity, rapidness, and cost effectiveness. Here we design a three-input colorimetric logic gate based on the aggregation and anti-aggregation of gold nanoparticles (Au NPs) for the sensing of melamine, cysteine, and Hg2+. The concept takes advantages of the highly specific coordination and ligand replacement reactions between melamine, cysteine, Hg2+, and Au NPs. Different outputs are obtained with the combinational inputs in the logic gates, which can serve as a reference to discriminate different analytes within a single sensing platform. Furthermore, besides the intrinsic sensitivity and selectivity of Au NPs to melamine-like compounds, the “INH” gates of melamine/cysteine and melamine/Hg2+ in this logic system can be employed for sensitive and selective detections of cysteine and Hg2+, respectively.

Lanthanide luminescent logic gate mimics in soft matter: [H(+)] and [F(-)] dual-input device in a polymer gel with potential for selective component release

The non-covalent incorporation of responsive luminescent lanthanide, Ln(iii), complexes with orthogonal outputs from Eu(iii) and Tb(iii) in a gel matrix allows for in situ logic operation with colorimetric outputs. Herein, we report an exemplar system with two inputs ([H(+)] and [F(-)]) within a p(HEMA-co-MMA) polymer organogel acting as a dual-responsive device and identify future potential for such systems.

Using Audio-visual Presentation to Teach Global Mindedness in Social Work Education

Direct experience of social work in another country is making an increasingly important contribution to internationalising the social work academic curriculum together with the cultural competency of students. However at present this opportunity is still restricted to a limited number of students. The aim of this paper is to describe and reflect on the production of an audio-visual presentation as representing the experience of three students who participated in an exchange with a social work programme in Pune, India. It describes and assesses the rationale, production and use of video to capture student learning from the Belfast/Pune exchange. We also describe the use of the video in a classroom setting with a year group of 53 students from a younger cohort. This exercise aimed to stimulate students’ curiosity about international dimensions of social work and add to their awareness of poverty, social justice, cultural competence and community social work as global issues. Written classroom feedback informs our discussion of the technical as well as the pedagogical benefits and challenges of this approach. We conclude that some benefit of audio-visual presentation in helping students connect with diverse cultural contexts, but that a complementary discussion challenging stereotyped viewpoints and unconscious professional imperialism is also crucial.

The Use of Audio Podcasts to Enhance the Delivery of a Computer Networks Course

Experience obtained in the support of mobile learning using podcast audio is reported. The paper outlines design, storage and distribution via a web site. An initial evaluation of the uptake of the approach in a final year computing module was undertaken. Audio objects were tailored to meet different pedagogical needs resulting in a repository of persistent glossary terms and disposable audio lectures distributed by podcasting. An aim of our approach is to document the interest from the students, and evaluate the potential of mobile learning for supplementing revision

Robust indoor speaker recognition in a network of audio and video sensors

Situational awareness is achieved naturally by the human senses of sight and hearing in combination. Automatic scene understanding aims at replicating this human ability using microphones and cameras in cooperation. In this paper, audio and video signals are fused and integrated at different levels of semantic abstractions. We detect and track a speaker who is relatively unconstrained, i.e., free to move indoors within an area larger than the comparable reported work, which is usually limited to round table meetings. The system is relatively simple: consisting of just 4 microphone pairs and a single camera. Results show that the overall multimodal tracker is more reliable than single modality systems, tolerating large occlusions and cross-talk. System evaluation is performed on both single and multi-modality tracking. The performance improvement given by the audio–video integration and fusion is quantified in terms of tracking precision and accuracy as well as speaker diarisation error rate and precision–recall (recognition). Improvements vs. the closest works are evaluated: 56% sound source localisation computational cost over an audio only system, 8% speaker diarisation error rate over an audio only speaker recognition unit and 36% on the precision–recall metric over an audio–video dominant speaker recognition method.