Design of a tablet sized human-computer interface and its effect on situation awareness

Emergency Response Teams increasingly use interactive technology to help manage information and communications. The challenge is to maintain a high situation awareness for different interactive devices sizes. This research specifically compared a handheld interactive device in the form of an iPad with a large interactive multi-touch tabletop. A search and rescue inspired simulator was designed to test operator situation awareness for the two sized devices. The results show that operators had better situation awareness on the tabletop device when the operation related to detecting of moving targets, searching target locations, distinguishing target types, and comprehending displayed information.

A normal-distribution based rating aggregation method for generating product reputations

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

Brisbane Art Deco: Stories of our Built Heritage

Our built heritage plays an important role in the ongoing story of our city. Modern cities such as Brisbane embraced Art Deco style in its architecture as it swept the world during the interwar period. From inner city landmarks such as the striking McWhirters department store to lesser-known gems further afield like the streamlined Archerfield Airport administration building, Brisbane has a significant range of intriguing and beautiful Art Deco buildings. This publication documents and celebrates a selection of our favourite residential and commercial examples. Written contributions from a range of authors are complemented by stunning modern photography and historic archive imagery, taking readers on a journey through this fascinating era. The articles not only describe the aesthetic and architectural features, but also delve into the associated social history. Brisbane Art Deco: Stories of our Built Heritage is a charming and informative reference, and offers a colourful insight into Brisbane’s built heritage and the life and times of this dynamic city.

Place recognition with ConvNet landmarks: Viewpoint-robust, condition-robust, training-free

Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.

Special Issue: Intuitive Interaction [Edited]

Towards Intuitive Interaction Theory Intuitive interaction, or intuitive use, or even ‘intuitivity’, have long been buzzwords used by designers and marketers but until recently there was no research about what this might entail and how designers could encourage it. This century, work on intuitive interaction has been gaining pace and this special issue showcases the state of the art in intuitive interaction research worldwide. This editorial is intended to introduce readers to the concept and definitions of intuitive interaction, briefly discuss the short history of work in this field and highlight and discuss some of the main issues raised by the papers in the issue.

Left ventricular volume and valve gradient analysis using an Apple Macintosh computer

A description of a computer program to analyse cine angiograms of the heart and pressure waveforms to calculate valve gradients.

A computer-controlled hyperthermia system

Hyperthermia, raised temperature, has been used as a means of treating cancer for centuries. Hippocrates (400 BC) and Galen (200 BC) used red-hot irons to treat small tumours. Much later, after the Renaissance, there are many reports of spontaneous tumour regression in patients with fevers produced by erysipelas, malaria, smallpox, tuberculosis and influenza. These illnesses produce fevers of about 40 °C which last for several days. Temperatures of at least 40 °C were found to be necessary for tumour regression. Towards the end of the nineteenth century pyrogenic bacteria were injected into patients with cancer. In 1896, Coly used a mixture of erysipelas and B. prodigeosus, with some success...

Searching for people using semantic soft biometric descriptions

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

Automation of underground truck haulage

This paper reviews the state-of-the-art in the automation of underground truck haulage. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tramming systems currently being commercialised, that follow rail-type guides placed along the back, cannot match the performance, flexibility and reliability of systems based on modern mobile robotic principles. In addition, the lack of collision detection research in the underground environment is highlighted.

Complete-linkage clustering for voice activity detection in audio and visual speech

We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.

Art museums and the global tourist: Experience centres in experience-scapes

In the experience economy, the role of art museums has evolved so as to cater to global cultural tourists. These institutions were traditionally dedicated to didactic functions, and served cognoscenti with elite cultural tastes that were aligned with the avant-garde’s autonomous stance towards mass culture. In a post-avant-garde era however museums have focused on appealing to a broad clientele that often has little or no knowledge of historical or contemporary art. Many of these tourists want art to provide entertaining and novel experiences, rather than receiving pedagogical ‘training’. In response, art museums are turning into ‘experience venues’ and are being informed by ideas associated with new museology, as well as business approaches like Customer Experience Management. This has led to the provision of populist entertainment modes, such as blockbuster exhibitions, participatory art events, jazz nights, and wine tasting, and reveals that such museums recognize that today’s cultural tourist is part of an increasingly diverse and populous demographic, which shares many languages and value systems. As art museums have shifted attention to global tourists, they have come to play a greater role in gentrification projects and cultural precincts. The art museum now seems ideally suited to tourist-centric environments that offer a variety of immersive sensory experiences and combine museums (often designed by star-architects), international hotels, restaurants, high-end shopping zones, and other leisure forums. These include sites such as Port Maravilha urban waterfront development in Rio de Janiero, the Museum of Old and New Art in Hobart, and the Chateau La Coste winery and hotel complex in Provence. It can be argued that in a global experience economy, art museums have become experience centres in experience-scapes. This paper will examine the nature of the tourist experience in relation to the new art museum, and the latter’s increasingly important role in attracting tourists to urban and regional cultural precincts.

The QUT-NOISE-SRE protocol for the evaluation of noisy speaker recognition

The QUT-NOISE-SRE protocol is designed to mix the large QUT-NOISE database, consisting of over 10 hours of back- ground noise, collected across 10 unique locations covering 5 common noise scenarios, with commonly used speaker recognition datasets such as Switchboard, Mixer and the speaker recognition evaluation (SRE) datasets provided by NIST. By allowing common, clean, speech corpora to be mixed with a wide variety of noise conditions, environmental reverberant responses, and signal-to-noise ratios, this protocol provides a solid basis for the development, evaluation and benchmarking of robust speaker recognition algorithms, and is freely available to download alongside the QUT-NOISE database. In this work, we use the QUT-NOISE-SRE protocol to evaluate a state-of-the-art PLDA i-vector speaker recognition system, demonstrating the importance of designing voice-activity-detection front-ends specifically for speaker recognition, rather than aiming for perfect coherence with the true speech/non-speech boundaries.

Dynamics of reverse salience as technological performance gap: An empirical study of the personal computer technology system

The evolution of technological systems is hindered by systemic components, referred to as reverse salients, which fail to deliver the necessary level of technological performance thereby inhibiting the performance delivery of the system as a whole. This paper develops a performance gap measure of reverse salience and applies this measurement in the study of the PC (personal computer) technological system, focusing on the evolutions of firstly the CPU (central processing unit) and PC game sub-systems, and secondly the GPU (graphics processing unit) and PC game sub-systems. The measurement of the temporal behavior of reverse salience indicates that the PC game sub-system is the reverse salient, continuously trailing behind the technological performance of the CPU and GPU sub-systems from 1996 through 2006. The technological performance of the PC game sub-system as a reverse salient trails that of the CPU sub-system by up to 2300 MHz with a gradually decreasing performance disparity in recent years. In contrast, the dynamics of the PC game sub-system as a reverse salient trails the GPU sub-system with an ever increasing performance gap throughout the timeframe of analysis. In addition, we further discuss the research and managerial implications of our findings.

External knowledge and query strategies in active learning: A study in clinical information extraction

This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.