Cross database training of audio-visual hidden Markov models for phone recognition

Speech recognition can be improved by using visual information in the form of lip movements of the speaker in addition to audio information. To date, state-of-the-art techniques for audio-visual speech recognition continue to use audio and visual data of the same database for training their models. In this paper, we present a new approach to make use of one modality of an external dataset in addition to a given audio-visual dataset. By so doing, it is possible to create more powerful models from other extensive audio-only databases and adapt them on our comparatively smaller multi-stream databases. Results show that the presented approach outperforms the widely adopted synchronous hidden Markov models (HMM) trained jointly on audio and visual data of a given audio-visual database for phone recognition by 29% relative. It also outperforms the external audio models trained on extensive external audio datasets and also internal audio models by 5.5% and 46% relative respectively. We also show that the proposed approach is beneficial in noisy environments where the audio source is affected by the environmental noise.

The use of embodiments in distributed collaborative business process modelling

Remote networked collaboration with business model documentation has many communication problems. The aim of this project is to solve some of these communication problems by using digital 3D representations of human visual cues. Results from this project increased our understanding of the role and effects of visual cues in remote collaboration, specifically for validating business process models. Technology designs to support such cues across a distance have been proposed in this thesis with qualitative and quantitative methods of analysis being combined to analyse the impact of these cues on the communication, coordination and performance of a team collaborating remotely.

The importance of connexin hemichannels during chondroprogenitor cell differentiation in hydrogel versus microtissue culture models

Appropriate selection of scaffold architecture is a key challenge in cartilage tissue engineering. Gap junction-mediated intercellular contacts play important roles in precartilage condensation of mesenchymal cells. However, scaffold architecture could potentially restrict cell-cell communication and differentiation. This is particularly important when choosing the appropriate culture platform as well as scaffold-based strategy for clinical translation, that is, hydrogel or microtissues, for investigating differentiation of chondroprogenitor cells in cartilage tissue engineering. We, therefore, studied the influence of gap junction-mediated cell-cell communication on chondrogenesis of bone marrow-derived mesenchymal stromal cells (BM-MSCs) and articular chondrocytes. Expanded human chondrocytes and BM-MSCs were either (re-) differentiated in micromass cell pellets or encapsulated as isolated cells in alginate hydrogels. Samples were treated with and without the gap junction inhibitor 18-α glycyrrhetinic acid (18αGCA). DNA and glycosaminoglycan (GAG) content and gene expression levels (collagen I/II/X, aggrecan, and connexin 43) were quantified at various time points. Protein localization was determined using immunofluorescence, and adenosine-5'-triphosphate (ATP) was measured in conditioned media. While GAG/DNA was higher in alginate compared with pellets for chondrocytes, there were no differences in chondrogenic gene expression between culture models. Gap junction blocking reduced collagen II and extracellular ATP in all chondrocyte cultures and in BM-MSC hydrogels. However, differentiation capacity was not abolished completely by 18αGCA. Connexin 43 levels were high throughout chondrocyte cultures and peaked only later during BM-MSC differentiation, consistent with the delayed response of BM-MSCs to 18αGCA. Alginate hydrogels and microtissues are equally suited culture platforms for the chondrogenic (re-)differentiation of expanded human articular chondrocytes and BM-MSCs. Therefore, reducing direct cell-cell contacts does not affect in vitro chondrogenesis. However, blocking gap junctions compromises cell differentiation, pointing to a prominent role for hemichannel function in this process. Therefore, scaffold design strategies that promote an increasing distance between single chondroprogenitor cells do not restrict their differentiation potential in tissue-engineered constructs.

Tracking the neoliberal juggernaut: A virtual edition

This is an editorial introduction for a virtual edition focused on neoliberalism in educational sectors for the journal, "Critical Studies in Education". The introduction outlines the nature and progress of neoliberalism, then reviews the selected articles from the journal's archives.

An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III

This study compares Value-at-Risk (VaR) measures for Australian banks over a period that includes the Global Financial Crisis (GFC) to determine whether the methodology and parameter selection are important for capital adequacy holdings that will ultimately support a bank in a crisis period. VaR methodology promoted under Basel II was largely criticised during the GFC for its failure to capture downside risk. However, results from this study indicate that 1-year parametric and historical models produce better measures of VaR than models with longer time frames. VaR estimates produced using Monte Carlo simulations show a high percentage of violations but with lower average magnitude of a violation when they occur. VaR estimates produced by the ARMA GARCH model also show a relatively high percentage of violations, however, the average magnitude of a violation is quite low. Our findings support the design of the revised Basel II VaR methodology which has also been adopted under Basel III.

Endogenous and exogenous effects in self-exciting process models of terrorist activity

A model based on the cluster process representation of the self-exciting process model in White and Porter 2013 and Ruggeri and Soyer 2008is derived to allow for variation in the excitation effects for terrorist events in a self-exciting or cluster process model. The details of the model derivation and implementation are given and applied to data from the Global Terrorism Database from 2000–2012. Results are discussed in terms of practical interpretation along with implications for a theoretical model paralleling existing criminological theory.

Virtual countries: Internet domain names and geographical terms

This paper examines the dispute between the Seattle company Virtual Countries Inc. and the Republic of South Africa over the ownership of the domain name address southafrica.com. The first part of the paper deals with the pre-emptive litigation taken by Virtual Countries Inc. in a District Court of the United States. The second part considers the possible arbitration of the dispute under the Uniform Domain Name Dispute Resolution Process of the Internet Corporation for Assigned Names and Numbers (ICANN) and examines the wider implications of this dispute for the jurisdiction and the governance of ICANN. The final section of the paper evaluates the Final Report of the Second WIPO Internet Domain Name Process.

Mathematical models for collective cell spreading

Collective cell spreading is frequently observed in development, tissue repair and disease progression. Mathematical modelling used in conjunction with experimental investigation can provide key insights into the mechanisms driving the spread of cell populations. In this study, we investigated how experimental and modelling frameworks can be used to identify several key features underlying collective cell spreading. In particular, we were able to independently quantify the roles of cell motility and cell proliferation in a spreading cell population, and investigate how these roles are influenced by factors such as the initial cell density, type of cell population and the assay geometry.

Bayesian parametric bootstrap for models with intractable likelihoods

In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the semi-automatic approximate Bayesian computation (ABC) summary statistics are selected. After a pilot run of ABC, the likelihood-free parametric bootstrap approach requires very few model simulations to produce an approximate posterior, which can be a useful approximation in its own right. An alternative is to use this approximation as a proposal distribution in ABC algorithms to make them more efficient. In this paper, the parametric bootstrap approximation is used to form the initial importance distribution for the sequential Monte Carlo and the ABC importance and rejection sampling algorithms. The new approach is illustrated through a simulation study of the univariate g-and- k quantile distribution, and is used to infer parameter values of a stochastic model describing expanding melanoma cell colonies.

Assessing testamentary and decision-making capacity: Approaches and models

The need for better and more accurate assessments of testamentary and decision-making capacity grows as Australian society ages and incidences of mentally disabling conditions increase. Capacity is a legal determination, but one on which medical opinion is increasingly being sought. The difficulties inherent within capacity assessments are exacerbated by the ad hoc approaches adopted by legal and medical professionals based on individual knowledge and skill, as well as the numerous assessment paradigms that exist. This can negatively affect the quality of assessments, and results in confusion as to the best way to assess capacity. This article begins by assessing the nature of capacity. The most common general assessment models used in Australia are then discussed, as are the practical challenges associated with capacity assessment. The article concludes by suggesting a way forward to satisfactorily assess legal capacity given the significant ramifications of getting it wrong.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

Cultural adaptation and resilience: Controversies, issues and emerging models

What enables people to bounce back from stressful experiences? How do certain individuals maintain a sense of purpose and direction over the long term, even in the face of adversity? This is the first book to move beyond childhood and adolescence to explore resilience across the lifespan. Coverage ranges from genetic and physiological factors through personal, family, organizational, and community processes. Contributors examine how resilience contributes to health and well-being across the adult life cycle; why—and what happens when—resilience processes fail; ethnic and cultural dimensions of resilience; and ways to enhance adult resilience, including reviews of exemplary programs.

A virtual radiation therapy workflow training simulation

Aim Simulation forms an increasingly vital component of clinical skills development in a wide range of professional disciplines. Simulation of clinical techniques and equipment is designed to better prepare students for placement by providing an opportunity to learn technical skills in a “safe” academic environment. In radiotherapy training over the last decade or so this has predominantly comprised treatment planning software and small ancillary equipment such as mould room apparatus. Recent virtual reality developments have dramatically changed this approach. Innovative new simulation applications and file processing and interrogation software have helped to fill in the gaps to provide a streamlined virtual workflow solution. This paper outlines the innovations that have enabled this, along with an evaluation of the impact on students and educators. Method Virtual reality software and workflow applications have been developed to enable the following steps of radiation therapy to be simulated in an academic environment: CT scanning using a 3D virtual CT scanner simulation; batch CT duplication; treatment planning; 3D plan evaluation using a virtual linear accelerator; quantitative plan assessment, patient setup with lasers; and image guided radiotherapy software. Results Evaluation of the impact of the virtual reality workflow system highlighted substantial time saving for academic staff as well as positive feedback from students relating to preparation for clinical placements. Students valued practice in the “safe” environment and the opportunity to understand the clinical workflow ahead of clinical department experience. Conclusion Simulation of most of the radiation therapy workflow and tasks is feasible using a raft of virtual reality simulation applications and supporting software. Benefits of this approach include time-saving, embedding of a case-study based approach, increased student confidence, and optimal use of the clinical environment. Ongoing work seeks to determine the impact of simulation on clinical skills.

A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers

In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.