Inexact uniformization method for computing transient distributions of Markov chains

The uniformization method (also known as randomization) is a numerically stable algorithm for computing transient distributions of a continuous time Markov chain. When the solution is needed after a long run or when the convergence is slow, the uniformization method involves a large number of matrix-vector products. Despite this, the method remains very popular due to its ease of implementation and its reliability in many practical circumstances. Because calculating the matrix-vector product is the most time-consuming part of the method, overall efficiency in solving large-scale problems can be significantly enhanced if the matrix-vector product is made more economical. In this paper, we incorporate a new relaxation strategy into the uniformization method to compute the matrix-vector products only approximately. We analyze the error introduced by these inexact matrix-vector products and discuss strategies for refining the accuracy of the relaxation while reducing the execution cost. Numerical experiments drawn from computer systems and biological systems are given to show that significant computational savings are achieved in practical applications.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

Shape discrimination using invariants defined from higher-order spectra

An approach to pattern recognition using invariant parameters based on higher-order spectra is presented. In particular, bispectral invariants are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale- and amplification-invariant. A minimal set of these invariants is selected as the feature vector for pattern classification. Pattern recognition using higher-order spectral invariants is fast, suited for parallel implementation, and works for signals corrupted by Gaussian noise. The classification technique is shown to distinguish two similar but different bolts given their one-dimensional profiles

The design and development of an undergraduate signal processing laboratory

The School of Electrical and Electronic Systems Engineering of Queensland University of Technology (like many other universities around the world) has recognised the importance of complementing the teaching of signal processing with computer based experiments. A laboratory has been developed to provide a "hands-on" approach to the teaching of signal processing techniques. The motivation for the development of this laboratory was the cliche "What I hear I remember but what I do I understand." The laboratory has been named as the "Signal Computing and Real-time DSP Laboratory" and provides practical training to approximately 150 final year undergraduate students each year. The paper describes the novel features of the laboratory, techniques used in the laboratory based teaching, interesting aspects of the experiments that have been developed and student evaluation of the teaching techniques

Speech recognition in adverse environments using lip information

The performance of automatic speech recognition systems deteriorates in the presence of noise. One known solution is to incorporate video information with an existing acoustic speech recognition system. We investigate the performance of the individual acoustic and visual sub-systems and then examine different ways in which the integration of the two systems may be performed. The system is to be implemented in real time on a Texas Instruments' TMS320C80 DSP.

Postcode segmentation and recognition using projections and bispectral features

A system to segment and recognize Australian 4-digit postcodes from address labels on parcels is described. Images of address labels are preprocessed and adaptively thresholded to reduce noise. Projections are used to segment the line and then the characters comprising the postcode. Individual digits are recognized using bispectral features extracted from their parallel beam projections. These features are insensitive to translation, scaling and rotation, and robust to noise. Results on scanned images are presented. The system is currently being improved and implemented to work on-line.

The use of speech and lip modalities for robust speaker verification under adverse conditions

Investigates the use of lip information, in conjunction with speech information, for robust speaker verification in the presence of background noise. We have previously shown (Int. Conf. on Acoustics, Speech and Signal Proc., vol. 6, pp. 3693-3696, May 1998) that features extracted from a speaker's moving lips hold speaker dependencies which are complementary with speech features. We demonstrate that the fusion of lip and speech information allows for a highly robust speaker verification system which outperforms either subsystem individually. We present a new technique for determining the weighting to be applied to each modality so as to optimize the performance of the fused system. Given a correct weighting, lip information is shown to be highly effective for reducing the false acceptance and false rejection error rates in the presence of background noise

Destination positioning opportunities using personal values : elicited through the Repertory Test with Laddering Analysis

While in many travel situations there is an almost limitless range of available destinations, travellers will usually only actively consider two to six in their decision set. One of the greatest challenges facing destination marketers is positioning their destination, against the myriad of competing places that offer similar features, into consumer decision sets. Since positioning requires a narrow focus, marketing communications must present a succinct and meaningful proposition, the selection of which is often problematic for destination marketing organisations (DMO), which deal with a diverse and often eclectic range of attributes in addition to self-interested and demanding stakeholders who have interests in different market segments. This paper reports the application of two qualitative techniques used to explore the range of cognitive attributes, consequences and personal values that represent potential positioning opportunities in the context of short break holidays. The Repertory Test is an effective technique for understanding the salient attributes used by a traveller to differentiate destinations, and Laddering Analysis enables the researcher to explore the smaller set of consequences and personal values guiding such decision making. A key finding of the research was that while individuals might vary in their repertoire of salient attributes, there was a commonality of shared consequences and values. This has important implications for DMOs, since a brand positioning theme that is based on a value will subsume multiple and diverse attributes. It is posited that such a theme will appeal to a broader range of travellers, as well as appease a greater number of destination stakeholders, than would an attribute based theme.

How can a mentor’s personal attributes and pedagogical knowledge develop a preservice teacher’s behaviour management?

This study presents the importance of a mentor’s (experienced teacher’s) personal attributes and pedagogical knowledge for developing a mentee’s (preservice teacher’s) teaching practices. Specifically, preservice teachers can have difficulties with behaviour management and must learn management strategies that help them to teach more effectively. This paper investigates how mentoring may facilitate the development of a mentee’s behaviour management strategies, in particular what personal attributes and pedagogical knowledge are used in this process.

Computing with motile bio-agents

We describe a model of computation of the parallel type, which we call 'computing with bio-agents', based on the concept that motions of biological objects such as bacteria or protein molecular motors in confined spaces can be regarded as computations. We begin with the observation that the geometric nature of the physical structures in which model biological objects move modulates the motions of the latter. Consequently, by changing the geometry, one can control the characteristic trajectories of the objects; on the basis of this, we argue that such systems are computing devices. We investigate the computing power of mobile bio-agent systems and show that they are computationally universal in the sense that they are capable of computing any Boolean function in parallel. We argue also that using appropriate conditions, bio-agent systems can solve NP-complete problems in probabilistic polynomial time.

Large scale participatory acoustic sensor data analysis : tools and reputation models to enhance effectiveness

Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.

Urban Informatics Research and Insights for Libraries, Cultural Industries and Innovation Systems

Over less than a decade, we have witnessed a seismic shift in the way knowledge is produced and exchanged. This is opening up new opportunities for civic and community engagement, entrepreneurial behaviour, sustainability initiatives and creative practices. It also has the potential to create fresh challenges in areas of privacy, cyber-security and misuse of data and personal information. The field of urban informatics focuses on the use and impacts of digital media technology in urban environments. Urban informatics is a dynamic and cross-disciplinary area of inquiry that encapsulates social media, ubiquitous computing, mobile applications and location-based services. Its insights suggest the emergence of a new economic force with the potential for driving innovation, wealth and prosperity through technological advances, digital media and online networks that affect patterns of both social and economic development. Urban informatics explores the intersections between people, place and technology, and their implications for creativity, innovation and engagement. This paper examines how the key learnings from this field can be used to position creative and cultural institutions such as galleries, libraries, archives and museums (GLAM) to take advantage of the opportunities presented by these changing social and technological developments. This paper introduces the underlying principles, concepts and research areas of urban informatics, against the backdrop of modern knowledge economies. Both theoretical ideas and empirical examples are covered in this paper. The first part discusses three challenges: a. People, and the challenge of creativity: The paper explores the opportunities and challenges of urban informatics that can lead to the design and development of new tools, methods and applications fostering participation, the democratisation of knowledge, and new creative practices. b. Technology, and the challenge of innovation: The paper examines how urban informatics can be applied to support user-led innovation with a view to promoting entrepreneurial ideas and creative industries. c. Place, and the challenge of engagement: The paper discusses the potential to establish place-based applications of urban informatics, using the example of library spaces designed to deliver community and civic engagement strategies. The discussion of these challenges is illustrated by a review of projects as examples drawn from diverse fields such as urban computing, locative media, community activism, and sustainability initiatives. The second part of the paper introduces an empirically grounded case study that responds to these three challenges: The Edge, the Queensland Government’s Digital Culture Centre which is an initiative of the State Library of Queensland to explore the nexus of technology and culture in an urban environment. The paper not only explores the new role of libraries in the knowledge economy, but also how the application of urban informatics in prototype engagement spaces such as The Edge can provide transferable insights that can inform the design and development of responsive and inclusive new library spaces elsewhere. To set the scene and background, the paper begins by drawing the bigger picture and outlining some key characteristics of the knowledge economy and the role that the creative and cultural industries play in it, grasping new opportunities that can contribute to the prosperity of Australia.