Improving spoken term detection using complementary information

This research has made contributions to the area of spoken term detection (STD), defined as the process of finding all occurrences of a specified search term in a large collection of speech segments. The use of visual information in the form of lip movements of the speaker in addition to audio and the use of topic of the speech segments, and the expected frequency of words in the target speech domain, are proposed. By using these complementary information, improvement in the performance of STD has been achieved which enables efficient search of key words in large collection of multimedia documents.

Sri Lankan entrepreneurs in Australia: Chance or choice?

Purpose Ethnic entrepreneurship is, and always has been, a means of survival. However, there is limited literature on ethnic entrepreneurship in Australia and therefore, an understanding of ethnic entrepreneurs’ motivations to become self-employed. The purpose of this paper is to report the influential factors in the decision to engage in self-employment through case studies of members of Melbourne’s Sri Lankan community informed by the mixed embeddedness approach. Design/methodology/approach The mixed embeddedness approach frames the study where the authors examine the motivations for business of five Sri Lankan entrepreneurs. Narratives are used to construct individual case studies, which are then analyzed in terms of the motivations for, resources used and challenges faced on the entrepreneurial journey. Findings For these ethnic entrepreneurs, their entrepreneurial activity results from a dynamic match between local market opportunities and the specific ethnic resources available to them at the time of founding. The self-employment decision was not prompted by a lack of human capital but an inability to use that human capital in alternative means of employment at specific points in time. Moreover the authors highlight the importance of social and cultural capital as resources used to overcome challenges on the entrepreneurial journey. Originality/value In this community, entrepreneurship was not a result of a lack of human capital but how it was utilized in combination with social and cultural capitals in the given opportunity structure. The mixed embeddedness approach enables the uncovering of how ethnic network ties were used in light of the opportunities available to build entrepreneurial activity.

Improved estimation of size-transition matrices using tag-recapture data

We derive a new method for determining size-transition matrices (STMs) that eliminates probabilities of negative growth and accounts for individual variability. STMs are an important part of size-structured models, which are used in the stock assessment of aquatic species. The elements of STMs represent the probability of growth from one size class to another, given a time step. The growth increment over this time step can be modelled with a variety of methods, but when a population construct is assumed for the underlying growth model, the resulting STM may contain entries that predict negative growth. To solve this problem, we use a maximum likelihood method that incorporates individual variability in the asymptotic length, relative age at tagging, and measurement error to obtain von Bertalanffy growth model parameter estimates. The statistical moments for the future length given an individual's previous length measurement and time at liberty are then derived. We moment match the true conditional distributions with skewed-normal distributions and use these to accurately estimate the elements of the STMs. The method is investigated with simulated tag-recapture data and tag-recapture data gathered from the Australian eastern king prawn (Melicertus plebejus).

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Validation of a 4DOF manoeuvring model of a high-speed vehicle-passenger trimaran

This paper presents the validation of a manoeuvring model for a novel 127m-vehicle-passenger trimaran via full scale trials. The adopted structure of the model is based on a model previously proposed in the literature with some simplifications. The structure of the model is discussed. Then initial parameter estimates are computed, and the final set of parameters are obtained via adjustments based on engineering judgement and application of a genetic algorithm so as to match the data of the trials. The validity of the model is also assessed with data from a trial different from the one use for the parameter adjustment. The model shows good agreement with the trial data.

Unsupervised Domain Adaptation by Domain Invariant Projection

Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset

Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model

Background: Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model. Results: The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF. Conclusions: Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

Australian pharmacists' self-perceptions in relation to the 'Advanced Pharmacy Practice Framework'

Background The Australian Pharmacy Practice Framework was developed by the Advanced Pharmacy Practice Steering Committee and endorsed by the Pharmacy Board of Australia in October 2012. The Steering Committee conducted a study that found practice portfolios to be the preferred method to assess and credential Advanced Pharmacy Practitioner, which is currently being piloted by the Australian Pharmacy Council. Credentialing is predicted to open to all pharmacists practising in Australia by November 2015. Objective To explore how Australian pharmacists self-perceived being advanced in practice and how they related their level of practice to the Australian Advanced Pharmacy Practice Framework. Method This was an explorative, cross-sectional study with mixed methods analysis. Advanced Pharmacy Practice Framework, a review of the recent explorative study on Advanced Practice conducted by the Advanced Pharmacy Practice Framework Steering Committee and semi-structured interviews (n = 10) were utilized to create, refine and pilot the questionnaire. The questionnaire was advertised across pharmacy-organizational websites via a purposive sampling method. The target population were pharmacists currently registered in Australia. Results Seventy-two participants responded to the questionnaire. The participants were mostly female (56.9%) and in the 30–40 age group (26.4%). The pharmacists self-perceived their levels of practice as either entry, transition, consolidation or advanced, with the majority selecting the consolidation level (38.9%). Although nearly half (43.1%) of the participants had not seen the Framework beforehand, they defined Advanced Pharmacy Practice similarly to the definition outlined in the Framework, but also added specialization as a requirement. Pharmacists explained why they were practising at their level of practice, stating that not having more years of practice, lacking experience, or postgraduate/post-registration qualifications, and more involvement and recognition in practice were the main reasons for not considering themselves as an Advanced Pharmacy Practitioner. To be considered advanced by the Framework, pharmacists would need to fulfill at least 70% of the Advanced Practice competency standards at an advanced level. More than half of the pharmacists (64.7%) that self-perceived as being advanced managed to fulfill 70% or more of these Advanced Practice competency standards at the advanced level. However, none of the self-perceived entry level pharmacists managed to match at least 70% of the competencies at the entry level. Conclusion Participants' self-perception of the term Advanced Practice was similar to the definition in the Advanced Pharmacy Practice Framework. Pharmacists working at an advanced level were largely able to demonstrate and justify their reasons for being advanced practitioners. However, pharmacists practising at the other levels of practice (entry, transition, consolidation) require further guidance regarding their advancement in practice.

A comparison of self-nominated and actual speeds in work zones

Despite significant research on drivers’ speeding behavior in work zones, little is known about how well drivers’ judgments of appropriate speeds match their actual speeds and what factors influence their judgments. This study aims to fill these two important gaps in the literature by comparing observed speeds in two work zones with drivers’ self-nominated speeds for the same work zones. In an online survey, drivers nominated speeds for the two work zones based on photographs in which the actual posted speed limits were not revealed. A simultaneous equation modelling approach was employed to examine the effects of driver characteristics on their self-nominated speeds. The results showed that survey participants nominated lower speeds (corresponding to higher compliance rates) than those which were observed. Higher speeds were nominated by males than females, young and middle aged drivers than older drivers, and drivers with truck driving experience than those who drive only cars. Larger differences between nominated and observed speeds were found among car drivers than truck drivers. These differences suggest that self-nominated speeds might not be valid indicators of the observed work zone speeds and therefore should not be used as an alternative to observed speed data.

A network forensics tool for precise data packet capture and replay in cyber-physical systems

Network data packet capture and replay capabilities are basic requirements for forensic analysis of faults and security-related anomalies, as well as for testing and development. Cyber-physical networks, in which data packets are used to monitor and control physical devices, must operate within strict timing constraints, in order to match the hardware devices' characteristics. Standard network monitoring tools are unsuitable for such systems because they cannot guarantee to capture all data packets, may introduce their own traffic into the network, and cannot reliably reproduce the original timing of data packets. Here we present a high-speed network forensics tool specifically designed for capturing and replaying data traffic in Supervisory Control and Data Acquisition systems. Unlike general-purpose "packet capture" tools it does not affect the observed network's data traffic and guarantees that the original packet ordering is preserved. Most importantly, it allows replay of network traffic precisely matching its original timing. The tool was implemented by developing novel user interface and back-end software for a special-purpose network interface card. Experimental results show a clear improvement in data capture and replay capabilities over standard network monitoring methods and general-purpose forensics solutions.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

What kind of sick person would see a Foot Doctor! The Foot Disease in Inpatients Study (FDIS)

Background Many different guidelines recommend people with foot complications, or those at risk, should attend multiple health professionals for foot care each year. However, few studies have investigated the characteristics of those attending health professionals for foot care and if those characteristics match those requiring foot care as per guideline recommendations. The aim of this paper was to determine the associated characteristics of people who attended a health professional for foot care in the year prior to their hospitalisation. Methods Eligible participants were all adults admitted overnight, for any reason, into five diverse hospitals on one day; excluding maternity, mental health and cognitively impaired patients. Participants underwent a foot examination to clinically diagnose different foot complications; including wounds, infections, deformity, peripheral arterial disease and peripheral neuropathy. They were also surveyed on social determinant, medical history, self-care, foot complication history, and, past health professional attendance for foot care in the year prior to hospitalisation. Results Overall, 733 participants consented; mean(±SD) age 62(±19) years, 408 (55.8%) male, 172 (23.5%) diabetes. Two hundred and fifty-six (34.9% (95% CI) (31.6-38.4)) participants had attended a health professional for foot care; including attending podiatrists 180 (24.5%), GPs 93 (24.6%), and surgeons 36 (4.9%). In backwards stepwise multivariate analyses attending any health professional for foot care was independently associated (OR (95% CI)) with diabetes (3.0 (2.1-4.5)), arthritis (1.8 (1.3-2.6)), mobility impairment (2.0 (1.4-2.9)) and previous foot ulcer (5.4 (2.9-10.0)). Attending a podiatrist was independently associated with female gender (2.6 (1.7-3.9)), increasing years of age (1.06 (1.04-1.08), diabetes (5.0 (3.2-7.9)), arthritis (2.0 (1.3-3.0)), hypertension (1.7 (1.1-2.6) and previous foot ulcer (4.5 (2.4-8.1). While attending a GP was independently associated with having a foot ulcer (10.4 (5.6-19.2). Conclusions Promisingly these findings indicate that people with a diagnosis of diabetes and arthritis are more likely to attend health professionals for foot care. However, it also appears those with active foot complications, or significant risk factors, may not be more likely to receive the multi-disciplinary foot care recommended by guidelines. More concerted efforts are required to ensure all people with foot complications are receiving recommended foot care.

Modeling transport through an environment crowded by a mixture of obstacles of different shapes and sizes

Many biological environments are crowded by macromolecules, organelles and cells which can impede the transport of other cells and molecules. Previous studies have sought to describe these effects using either random walk models or fractional order diffusion equations. Here we examine the transport of both a single agent and a population of agents through an environment containing obstacles of varying size and shape, whose relative densities are drawn from a specified distribution. Our simulation results for a single agent indicate that smaller obstacles are more effective at retarding transport than larger obstacles; these findings are consistent with our simulations of the collective motion of populations of agents. In an attempt to explore whether these kinds of stochastic random walk simulations can be described using a fractional order diffusion equation framework, we calibrate the solution of such a differential equation to our averaged agent density information. Our approach suggests that these kinds of commonly used differential equation models ought to be used with care since we are unable to match the solution of a fractional order diffusion equation to our data in a consistent fashion over a finite time period.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

Nickel(II) meso-hydroxyporphyrin complexes revisited: Palladium-catalysed synthesis, electronic structures of derived oxy radicals, and oxidative coupling to a dioxoporphodimethene dyad

We report the synthesis and characterisation of new examples of meso-hydroxynickel(II) porphyrins with 5,15-diphenyl and 10-phenyl-5,15-diphenyl/diaryl substitu- tion. The OH group was introduced by using carbonate or hydroxide as nucleophile by using palladium/phosphine cat- alysis. The NiPor OHs exist in solution in equilibrium with the corresponding oxy radicals NiPor OC. The 15-phenyl group stabilises the radicals, so that the 1H NMR spectra of {NiPor OH} are extremely broad due to chemical exchange with the paramagnetic species. The radical concentration for the diphenylporphyrin analogue is only 1%, and its NMR line-broadening was able to be studied by variable-tempera- ture NMR spectroscopy. The EPR signals of NiPor OC are con- sistent with somewhat delocalised porphyrinyloxy radicals, and the spin distributions calculated by using density func- tional theory match the EPR and NMR spectroscopic obser- vations. Nickel(II) meso-hydroxy-10,20-diphenylporphyrin was oxidatively coupled to a dioxo-terminated porphodimethene dyad, the strongly red-shifted electronic spectrum of which was successfully modelled by using time-dependent DFT calculations.