Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Crowd counting using group tracking and local features

In public venues, crowd size is a key indicator of crowd safety and stability. In this paper we propose a crowd counting algorithm that uses tracking and local features to count the number of people in each group as represented by a foreground blob segment, so that the total crowd estimate is the sum of the group sizes. Tracking is employed to improve the robustness of the estimate, by analysing the history of each group, including splitting and merging events. A simplified ground truth annotation strategy results in an approach with minimal setup requirements that is highly accurate.

Practical stability of approximating discrete-time filters with respect to model mismatch using relative entropy concepts

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Using local consistency assumption, the practical stability established is in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Significantly, these practical stability results do not require the approximating model to be of the same model type as the true system. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Should athletes return to sport after applying Ice? A systematic review of the effect of local 3 cooling on functional performance

Applying ice or other forms of topical cooling is a popular method of treating sports injuries. It is commonplace for athletes to return to competitive activity, shortly or immediately after the application of a cold treatment. In this article, we examine the effect of local tissue cooling on outcomes relating to functional performance and to discuss their relevance to the sporting environment. A computerized literature search, citation tracking and hand search was performed up to April, 2011. Eligible studies were trials involving healthy human participants, describing the effects of cooling on outcomes relating to functional performance. Two reviewers independently assessed the validity of included trials and calculated effect sizes. Thirty five trials met the inclusion criteria; all had a high risk of bias. The mean sample size was 19. Meta-analyses were not undertaken due to clinical heterogeneity. The majority of studies used cooling durations >20 minutes. Strength (peak torque/force) was reported by 25 studies with approximately 75% recording a decrease in strength immediately following cooling. There was evidence from six studies that cooling adversely affected speed, power and agility-based running tasks; two studies found this was negated with a short rewarming period. There was conflicting evidence on the effect of cooling on isolated muscular endurance. A small number of studies found that cooling decreased upper limb dexterity and accuracy. The current evidence base suggests that athletes will probably be at a performance disadvantage if they return to activity immediately after cooling. This is based on cooling for longer than 20 minutes, which may exceed the durations employed in some sporting environments. In addition, some of the reported changes were clinically small and may only be relevant in elite sport. Until better evidence is available, practitioners should use short cooling applications and/or undertake a progressive warm up prior to returning to play.

Hessian-based affine adaptation of salient local image features

Affine covariant local image features are a powerful tool for many applications, including matching and calibrating wide baseline images. Local feature extractors that use a saliency map to locate features require adaptation processes in order to extract affine covariant features. The most effective extractors make use of the second moment matrix (SMM) to iteratively estimate the affine shape of local image regions. This paper shows that the Hessian matrix can be used to estimate local affine shape in a similar fashion to the SMM. The Hessian matrix requires significantly less computation effort than the SMM, allowing more efficient affine adaptation. Experimental results indicate that using the Hessian matrix in conjunction with a feature extractor that selects features in regions with high second order gradients delivers equivalent quality correspondences in less than 17% of the processing time, compared to the same extractor using the SMM.

Histogram of weighted local directions for gait recognition

In this paper, we explore the effectiveness of patch-based gradient feature extraction methods when applied to appearance-based gait recognition. Extending existing popular feature extraction methods such as HOG and LDP, we propose a novel technique which we term the Histogram of Weighted Local Directions (HWLD). These 3 methods are applied to gait recognition using the GEI feature, with classification performed using SRC. Evaluations on the CASIA and OULP datasets show significant improvements using these patch-based methods over existing implementations, with the proposed method achieving the highest recognition rate for the respective datasets. In addition, the HWLD can easily be extended to 3D, which we demonstrate using the GEV feature on the DGD dataset, observing improvements in performance.

Local inter-session variability modelling for object classification

Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

Self-assembled low-dimensional nanomaterials via low-temperature plasma processing

Examples of successful fabrication of low-dimensional semiconducting nanomaterials in the Integrated Plasma-Aided Nanofabrication Facility are shown. Self-assembled size-uniform ZnO nanoparticles, ultra-high-aspect ratio Si nanowires, vertically aligned cadmium sulfide nanostructures, and quarternary semiconducting SiCAlN nanomaterial have been synthesized using inductively coupled plasma-assisted RF magnetron sputtering deposition. The observed increase in crystallinity and growth rates of the nanostructures are explained by using a model of plasma-enhanced adatom surface diffusion under conditions of local energy exchange between the ion flux and the growth surface. Issues related to plasma-based growth of low-dimensional semiconducting nanomaterials are discussed as well. © 2007 Elsevier B.V. All rights reserved.

Dynamics of contour, object and face processing in the human visual cortex

The neural basis of visual perception can be understood only when the sequence of cortical activity underlying successful recognition is known. The early steps in this processing chain, from retina to the primary visual cortex, are highly local, and the perception of more complex shapes requires integration of the local information. In Study I of this thesis, the progression from local to global visual analysis was assessed by recording cortical magnetoencephalographic (MEG) responses to arrays of elements that either did or did not form global contours. The results demonstrated two spatially and temporally distinct stages of processing: The first, emerging 70 ms after stimulus onset around the calcarine sulcus, was sensitive to local features only, whereas the second, starting at 130 ms across the occipital and posterior parietal cortices, reflected the global configuration. To explore the links between cortical activity and visual recognition, Studies II III presented subjects with recognition tasks of varying levels of difficulty. The occipito-temporal responses from 150 ms onwards were closely linked to recognition performance, in contrast to the 100-ms mid-occipital responses. The averaged responses increased gradually as a function of recognition performance, and further analysis (Study III) showed the single response strengths to be graded as well. Study IV addressed the attention dependence of the different processing stages: Occipito-temporal responses peaking around 150 ms depended on the content of the visual field (faces vs. houses), whereas the later and more sustained activity was strongly modulated by the observers attention. Hemodynamic responses paralleled the pattern of the more sustained electrophysiological responses. Study V assessed the temporal processing capacity of the human object recognition system. Above sufficient luminance, contrast and size of the object, the processing speed was not limited by such low-level factors. Taken together, these studies demonstrate several distinct stages in the cortical activation sequence underlying the object recognition chain, reflecting the level of feature integration, difficulty of recognition, and direction of attention.

Integrated semantic processing of complex pictures and spoken sentences - Evidence from event-related potentials

It has been suggested that semantic information processing is modularized according to the input form (e.g., visual, verbal, non-verbal sound). A great deal of research has concentrated on detecting a separate verbal module. Also, it has traditionally been assumed in linguistics that the meaning of a single clause is computed before integration to a wider context. Recent research has called these views into question. The present study explored whether it is reasonable to assume separate verbal and nonverbal semantic systems in the light of the evidence from event-related potentials (ERPs). The study also provided information on whether the context influences processing of a single clause before the local meaning is computed. The focus was on an ERP called N400. Its amplitude is assumed to reflect the effort required to integrate an item to the preceding context. For instance, if a word is anomalous in its context, it will elicit a larger N400. N400 has been observed in experiments using both verbal and nonverbal stimuli. Contents of a single sentence were not hypothesized to influence the N400 amplitude. Only the combined contents of the sentence and the picture were hypothesized to influence the N400. The subjects (n = 17) viewed pictures on a computer screen while hearing sentences through headphones. Their task was to judge the congruency of the picture and the sentence. There were four conditions: 1) the picture and the sentence were congruent and sensible, 2) the sentence and the picture were congruent, but the sentence ended anomalously, 3) the picture and the sentence were incongruent but sensible, 4) the picture and the sentence were incongruent and anomalous. Stimuli from the four conditions were presented in a semi-randomized sequence. Their electroencephalography was simultaneously recorded. ERPs were computed for the four conditions. The amplitude of the N400 effect was largest in the incongruent sentence-picture -pairs. The anomalously ending sentences did not elicit a larger N400 than the sensible sentences. The results suggest that there is no separate verbal semantic system, and that the meaning of a single clause is not processed independent of the context.

Cocowood processing manual: from coconut wood to quality flooring.

This manual describes best practice for producing high-value flooring products from coconut ‘wood’—or cocowood. It meets international standards for flooring products and accounts for the recognised, specific, local conditions of the Pacific Islands. The information is intended for operators skilled in timber processing, who need to work with the unusual properties of cocowood, and specifies where cocowood processes differ from standard practice for timber. For other processes, refer to the relevant standards set by the importing country. These technical guidelines are based on the research outcomes of the ACIAR project, 'Improving value and marketability of coconut wood'. The manual is divided into three chapters. Each chapter adds to different aspects of primary and secondary processing. Chapter 1 provides an overview of the best practice steps for harvesting and processing cocowood. There is also a glossary of terms specifically associated with processing cocowood and a section on managing processing risks. Chapter 2 covers cocowood’s unique properties and how they relate to critical processing techniques. This is followed by sections that set out the processing methods in more detail, explaining why these practices are essential when working with cocowood. Chapter 3 provides more information, including contacts, current timber standards and some useful publications.

Utilisation of local ingredients in commercial pig feeds

The long-term competitiveness of the both the Vietnamese feed and pig production industries are constrained and under pressure whilst the industry is dependent on the use of imported feed ingredients in diets for animal production. These cost pressures are a result of import taxes, transport costs, currency fluctuations and feed supply limitations. By undertaking studies on available resources which are currently under-utilised and with potential as local feeds, we can prove their suitability for use as feedstuffs in pig diets and as replacements for imported feed ingredients. In undertaking this process we can lower feeding costs for pig production in Vietnam by the use of local feeds which are cheaper, generate new industries in Vietnam harvesting or processing these feeds and increase the incomes of Vietnamese workers who are involved in producing these by-products. Our project has shown that rubber seed, when processed correctly to lower the hydrogen cyanide content, is a safe and suitable protein meal feedstuff for use in pig diets with the potential to replace significant quantities of imported soybean and fishmeal in Vietnamese pig diets as long as diets are balanced for any amino acid shortfalls. Our peanut studies have shown that use of binders can help alleviate pig production problems with aflatoxin content in peanut meals. Further work is needed to characterise the fate of the bound aflatoxin to see if there is any meat residue risk. Cassava residue is a resultant by-product from starch extraction in both large and small cassava processing factories. Sub-samples from these two mill types were collected and evaluated for residue HCN. Analyses has shown that the processing and sun drying results in a product with relatively consistent low HCN content. Chemical analyses also reveal that significant residual starch also remains in this by-product. Digestibility studies and pig performance feeding studies have shown that cassava residue can be included in diets at 30% with no adverse effect, although the higher fibre content of this product means that strategically, cassava residue is more suitably used in finisher and sow diets. Research has examined the digestible energy content of a number of sunflower meal types available in Australia and identified major differences in their energy value based on processing, additionally, amino acid analysis has shown a significantly lower lysine content than previous reported. We also examined the digestible energy content of a number of Australian stylo forage legume harvest batches and identified the differences in their energy value based on age/harvest time of the forage legume. Analysis results of various stylo cuts showed that the early cut stylo has a higher starch content and lower fibre fraction content than observed in late and recut stylo which were allowed to grow longer. As a result the faecal digestible energy content was higher for the early cut stylo than for the subsequent cut stylo material which had been allowed to become woody. The results have shown that feeding of stylo meal does provide some nutritive value to the pig with increased energy and nitrogen supply, with a portion of the nitrogen presented which the pig is able to retain. Based on nutrient and fibre content stylo could have a useful role in sow feeding and satiety under non-stall housing situations. With increasing Vietnamese investment in rubber production seen with larger areas under plantations the amounts of rubber seed available for animal feeding will grow significantly over the next 15 years and the importance of the by-product ie rubber seed meal as a protein source in diets for Vietnamese pigs.

Dual Power Multiple Access with Multipacket Reception using Local CSI

Contention-based multiple access is a crucial component of many wireless systems. Multiple-packet reception (MPR) schemes that use interference cancellation techniques to receive and decode multiple packets that arrive simultaneously are known to be very efficient. However, the MPR schemes proposed in the literature require complex receivers capable of performing advanced signal processing over significant amounts of soft undecodable information received over multiple contention steps. In this paper, we show that local channel knowledge and elementary received signal strength measurements, which are available to many receivers today, can actively facilitate multipacket reception and even simplify the interference canceling receiver¿s design. We introduce two variants of a simple algorithm called Dual Power Multiple Access (DPMA) that use local channel knowledge to limit the receive power levels to two values that facilitate successive interference cancellation. The resulting receiver structure is markedly simpler, as it needs to process only the immediate received signal without having to store and process signals received previously. Remarkably, using a set of three feedback messages, the first variant, DPMA-Lite, achieves a stable throughput of 0.6865 packets per slot. Using four possible feedback messages, the second variant, Turbo-DPMA, achieves a stable throughput of 0.793 packets per slot, which is better than all contention algorithms known to date.