Disease prevention and control

Globally, the main contributors to morbidity and mortality are chronic diseases, including cardiovascular disease and diabetes. Chronic diseases are costly and partially avoidable, with around sixty percent of deaths and nearly fifty percent of the global disease burden attributable to these conditions. By 2020, chronic illnesses will likely be the leading cause of disability worldwide. Existing health care systems, both national and international, that focus on acute episodic health conditions, cannot address the worldwide transition to chronic illness; nor are they appropriate for the ongoing care and management of those already afflicted with chronic diseases. International and Australian strategic planning documents articulate similar elements to manage chronic disease; including the need for aligning sectoral policies for health, forming partnerships and engaging communities in decision-making. The Australian National Chronic Disease Strategy focuses on four core areas for managing chronic disease; prevention across the continuum, early detection and treatment, integrated and coordinated care, and self-management. Such a comprehensive approach incorporates the entire population continuum, from the ‘healthy’, to those with risk factors, through to people suffering from chronic conditions and their sequelae. This chapter examines comprehensive approach to the prevention, management and care of the population with non-communicable, chronic diseases and communicable diseases. It analyses models of care in the context of need, service delivery options and the potential to prevent or manage early intervention for chronic and communicable diseases. Approaches to chronic diseases require integrated approaches that incorporate interventions targeted at both individuals and populations, and emphasise the shared risk factors of different conditions. Communicable diseases are a common and significant contributor to ill health throughout the world. In many countries, this impact has been minimised by the combined efforts of preventative health measures and improved treatment of infectious diseases. However in underdeveloped nations, communicable diseases continue to contribute significantly to the burden of disease. The aim of this chapter is to outline the impact that chronic and communicable diseases have on the health of the community, the public health strategies that are used to reduce the burden of those diseases and the old and emerging risks to public health from infectious diseases.

GPS fault detection with IMU and aircraft dynamics

Approaches with Vertical Guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection requirements. Aircraft Based Augmentation Systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality MEMS IMU and Aircraft Dynamic Model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of Extended Kalman Filters (EKF) with the Normalized Solution Separation (NSS) fault detection scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated showing a performance improvement over a GPS-only “snapshot” implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF where a small improvement in protection levels is shown.

Osteoarthritis Index delivered by mobile phone (m-WOMAC) is valid, reliable, and responsive

Objectives: To evaluate the validity, reliability and responsiveness of EDC using the WOMAC® NRS 3.1 Index on Motorola V3 mobile phones. ---------- Methods: Patients with osteoarthritis (OA) undergoing primary unilateral hip or knee joint replacement surgery were assessed pre-operatively and 3-4 months post-operatively. Patients completed the WOMAC® Index in paper (p-WOMAC®) and electronic (m-WOMAC®) format in random order. ---------- Results: 24 men and 38 women with hip and knee OA participated and successfully completed the m-WOMAC® questionnaire. Pearson correlations between the summated total index scores for the p-WOMAC® and m-WOMAC® pre- and post-surgery were 0.98 and 0.99 (p<0.0001). There was no clinically important or statistically significant between-method difference in the adjusted total summated scores, pre- and post-surgery (adjusted mean difference = 4.44, p = 0.474 and 1.73, p = 0.781). Internal consistency estimates of m-WOMAC® reliability were 0.87 – 0.98. The m-WOMAC® detected clinically important, statistically significant (p<0.0001) improvements in pain, stiffness, function and total index score. ---------- Conclusions: Sixty-two patients with hip and knee OA successfully completed EDC by Motorola V3 mobile phone using the m-WOMAC® NRS3.1 Index; completion times averaging only 1-1.5 minutes longer than the p-WOMAC® Index. Data were successfully and securely transmitted from patients in Australia to a server in the USA. There was close agreement and no significant differences between m-WOMAC® and p-WOMAC® scores. This study confirms the validity, reliability and responsiveness of the Exco InTouch engineered, Java-based m-WOMAC® Index application. EDC with the m-WOMAC® Index provides unique opportunities for using quantitative measurement in clinical research and practice.

Exploring visual features through Gabor representations for facial expression detection

Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.

Cascading appearance-based features for visual voice activity detection

The detection of voice activity is a challenging problem, especially when the level of acoustic noise is high. Most current approaches only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to overcome this is to use the visual modality. The current state-of-the-art visual feature extraction technique is one that uses a cascade of visual features (i.e. 2D-DCT, feature mean normalisation, interstep LDA). In this paper, we investigate the effectiveness of this technique for the task of visual voice activity detection (VAD), and analyse each stage of the cascade and quantify the relative improvement in performance gained by each successive stage. The experiments were conducted on the CUAVE database and our results highlight that the dynamics of the visual modality can be used to good effect to improve visual voice activity detection performance.

Improved correlation-based modal strain energy method for global damage detection of truss bridge structures

The previous investigations have shown that the modal strain energy correlation method, MSEC, could successfully identify the damage of truss bridge structures. However, it has to incorporate the sensitivity matrix to estimate damage and is not reliable in certain damage detection cases. This paper presents an improved MSEC method where the prediction of modal strain energy change vector is differently obtained by running the eigensolutions on-line in optimisation iterations. The particular trail damage treatment group maximising the fitness function close to unity is identified as the detected damage location. This improvement is then compared with the original MSEC method along with other typical correlation-based methods on the finite element model of a simple truss bridge. The contributions to damage detection accuracy of each considered mode is also weighed and discussed. The iterative searching process is operated by using genetic algorithm. The results demonstrate that the improved MSEC method suffices the demand in detecting the damage of truss bridge structures, even when noised measurement is considered.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Efficient clustering approach for intrusion detection in adhoc networks

Mobile ad-hoc networks (MANETs) are temporary wireless networks useful in emergency rescue services, battlefields operations, mobile conferencing and a variety of other useful applications. Due to dynamic nature and lack of centralized monitoring points, these networks are highly vulnerable to attacks. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. We take benefit of the clustering concept in MANETs for the effective communication between nodes, where each cluster involves a number of member nodes and is managed by a cluster-head. It can be taken as an advantage in these battery and memory constrained networks for the purpose of intrusion detection, by separating tasks for the head and member nodes, at the same time providing opportunity for launching collaborative detection approach. The clustering schemes are generally used for the routing purposes to enhance the route efficiency. However, the effect of change of a cluster tends to change the route; thus degrades the performance. This paper presents a low overhead clustering algorithm for the benefit of detecting intrusion rather than efficient routing. It also discusses the intrusion detection techniques with the help of this simplified clustering scheme.

Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

Detection and prevention of distributed denial of services attacks by collaborative effort of software agents, first prototype implementation

Distributed Denial of Services DDoS, attacks has become one of the biggest threats for resources over Internet. Purpose of these attacks is to make servers deny from providing services to legitimate users. These attacks are also used for occupying media bandwidth. Currently intrusion detection systems can just detect the attacks but cannot prevent / track the location of intruders. Some schemes also prevent the attacks by simply discarding attack packets, which saves victim from attack, but still network bandwidth is wasted. In our opinion, DDoS requires a distributed solution to save wastage of resources. The paper, presents a system that helps us not only in detecting such attacks but also helps in tracing and blocking (to save the bandwidth as well) the multiple intruders using Intelligent Software Agents. The system gives dynamic response and can be integrated with the existing network defense systems without disturbing existing Internet model. We have implemented an agent based networking monitoring system in this regard.

A secure architecture for Australia’s index based e-health environment

This paper proposes a security architecture for the basic cross indexing systems emerging as foundational structures in current health information systems. In these systems unique identifiers are issued to healthcare providers and consumers. In most cases, such numbering schemes are national in scope and must therefore necessarily be used via an indexing system to identify records contained in pre-existing local, regional or national health information systems. Most large scale electronic health record systems envisage that such correlation between national healthcare identifiers and pre-existing identifiers will be performed by some centrally administered cross referencing, or index system. This paper is concerned with the security architecture for such indexing servers and the manner in which they interface with pre-existing health systems (including both workstations and servers). The paper proposes two required structures to achieve the goal of a national scale, and secure exchange of electronic health information, including: (a) the employment of high trust computer systems to perform an indexing function, and (b) the development and deployment of an appropriate high trust interface module, a Healthcare Interface Processor (HIP), to be integrated into the connected workstations or servers of healthcare service providers. This proposed architecture is specifically oriented toward requirements identified in the Connectivity Architecture for Australia’s e-health scheme as outlined by NEHTA and the national e-health strategy released by the Australian Health Ministers.

Damage detection for truss bridge structures using correlation-based structural modal strain energy

This paper presents the feasibility of using structural modal strain energy as a parameter employed in correlation- based damage detection method for truss bridge structures. It is an extension of the damage detection method adopting multiple damage location assurance criterion. In this paper, the sensitivity of modal strain energy to damage obtained from the analytical model is incorporated into the correlation objective function. Firstly, the sensitivity matrix of modal strain energy to damage is conducted offline, and for an arbitrary damage case, the correlation coefficient (objective function) is calculated by multiplying the sensitivity matrix and damage vector. Then, a genetic algorithm is used to iteratively search the damage vector maximising the correlation between the corresponding modal strain energy change (hypothesised) and its counterpart in measurement. The proposed method is simulated and compared with the conventional methods, e.g. frequency-error method, coordinate modal assurance criterion and multiple damage location assurance criterion using mode shapes on a numerical truss bridge structure. The result demonstrates the modal strain energy correlation method is able to yield acceptable damage detection outcomes with less computing efforts, even in a noise contaminated condition.

Optimising figure of merit for phonetic spoken term detection

This paper introduces a novel technique to directly optimise the Figure of Merit (FOM) for phonetic spoken term detection. The FOM is a popular measure of sTD accuracy, making it an ideal candiate for use as an objective function. A simple linear model is introduced to transform the phone log-posterior probabilities output by a phe classifier to produce enhanced log-posterior features that are more suitable for the STD task. Direct optimisation of the FOM is then performed by training the parameters of this model using a non-linear gradient descent algorithm. Substantial FOM improvements of 11% relative are achieved on held-out evaluation data, demonstrating the generalisability of the approach.

Some aspects of calcium phosphate chemistry in sugarcane clarification

This paper reviews some aspects of calcium phosphate chemistry since phosphate in juice is an important parameter in all sugar juice clarification systems. It uses basic concepts to try and explain the observed differences in clarification performance obtained with various liming techniques. The paper also examines the current colorimetric method used for the determination of phosphate in sugar juice. In this method, a phosphomolybdate blue complex formed due to the addition of a dye is measured at 660 nm. Unfortunately, at this wavelength there is interference of the colour arising from within the juice and results in the underestimation of the amount of soluble inorganic phosphate content of juice. It is suggested that phosphate analysis be conducted at the higher wavelength of 875 nm where the interference of the juice colour is minimised.

Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.