A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Molecular markers of obesity and diabetes

Recently it has been shown that the consumption of a diet high in saturated fat is associated with impaired insulin sensitivity and increased incidence of type 2 diabetes. In contrast, diets that are high in monounsaturated fatty acids (MUFAs) or polyunsaturated fatty acids (PUFAs), especially very long chain n-3 fatty acids (FAs), are protective against disease. However, the molecular mechanisms by which saturated FAs induce the insulin resistance and hyperglycaemia associated with metabolic syndrome and type 2 diabetes are not clearly defined. It is possible that saturated FAs may act through alternative mechanisms compared to MUFA and PUFA to regulate of hepatic gene expression and metabolism. It is proposed that, like MUFA and PUFA, saturated FAs regulate the transcription of target genes. To test this hypothesis, hepatic gene expression analysis was undertaken in a human hepatoma cell line, Huh-7, after exposure to the saturated FA, palmitate. These experiments showed that palmitate is an effective regulator of gene expression for a wide variety of genes. A total of 162 genes were differentially expressed in response to palmitate. These changes not only affected the expression of genes related to nutrient transport and metabolism, they also extend to other cellular functions including, cytoskeletal architecture, cell growth, protein synthesis and oxidative stress response. In addition, this thesis has shown that palmitate exposure altered the expression patterns of several genes that have previously been identified in the literature as markers of risk of disease development, including CVD, hypertension, obesity and type 2 diabetes. The altered gene expression patterns associated with an increased risk of disease include apolipoprotein-B100 (apo-B100), apo-CIII, plasminogen activator inhibitor 1, insulin-like growth factor-I and insulin-like growth factor binding protein 3. This thesis reports the first observation that palmitate directly signals in cultured human hepatocytes to regulate expression of genes involved in energy metabolism as well as other important genes. Prolonged exposure to long-chain saturated FAs reduces glucose phosphorylation and glycogen synthesis in the liver. Decreased glucose metabolism leads to elevated rates of lipolysis, resulting in increased release of free FAs. Free FAs have a negative effect on insulin action on the liver, which in turn results in increased gluconeogenesis and systemic dyslipidaemia. It has been postulated that disruption of glucose transport and insulin secretion by prolonged excessive FA availability might be a non-genetic factor that has contributed to the staggering rise in prevalence of type 2 diabetes. As glucokinase (GK) is a key regulatory enzyme of hepatic glucose metabolism, changes in its activity may alter flux through the glycolytic and de novo lipogenic pathways and result in hyperglycaemia and ultimately insulin resistance. This thesis investigated the effects of saturated FA on the promoter activity of the glycolytic enzyme, GK, and various transcription factors that may influence the regulation of GK gene expression. These experiments have shown that the saturated FA, palmitate, is capable of decreasing GK promoter activity. In addition, quantitative real-time PCR has shown that palmitate incubation may also regulate GK gene expression through a known FA sensitive transcription factor, sterol regulatory element binding protein-1c (SREBP-1c), which upregulates GK transcription. To parallel the investigations into the mechanisms of FA molecular signalling, further studies of the effect of FAs on metabolic pathway flux were performed. Although certain FAs reduce SREBP-1c transcription in vitro, it is unclear whether this will result in decreased GK activity in vivo where positive effectors of SREBP-1c such as insulin are also present. Under these conditions, it is uncertain if the inhibitory effects of FAs would be overcome by insulin. The effects of a combination of FAs, insulin and glucose on glucose phosphorylation and metabolism in cultured primary rat hepatocytes at concentrations that mimic those in the portal circulation after a meal was examined. It was found that total GK activity was unaffected by an increased concentration of insulin, but palmitate and eicosapentaenoic acid significantly lowered total GK activity in the presence of insulin. Despite the fact that total GK enzyme activity was reduced in response to FA incubation, GK enzyme translocation from the inactive, nuclear bound, to active, cytoplasmic state was unaffected. Interestingly, none of the FAs tested inhibited glucose phosphorylation or the rate of glycolysis when insulin is present. These results suggest that in the presence of insulin the levels of the active, unbound cytoplasmic GK are sufficient to buffer a slight decrease in GK enzyme activity and decreased promoter activity caused by FA exposure. Although a high fat diet has been associated with impaired hepatic glucose metabolism, there is no evidence from this thesis that FAs themselves directly modulate flux through the glycolytic pathway in isolated primary hepatocytes when insulin is also present. Therefore, although FA affected expression of a wide range of genes, including GK, this did not affect glycolytic flux in the presence of insulin. However, it may be possible that a saturated FA-induced decrease in GK enzyme activity when combined with the onset of insulin resistance may promote the dys-regulation of glucose homeostasis and the subsequent development of hyperglycaemia, metabolic syndrome and type 2 diabetes.

Human preadipocyte proliferation and differentiation

Obesity represents a major health, social and economic burden to many developing and Westernized communities, with the prevalence increasing at a rate exceeding almost all other medical conditions. Despite major recent advances in our understanding of adipose tissue metabolism and dynamics, we still have limited insight into the regulation of adipose tissue mass in humans. Any significant increase in adipose tissue mass requires proliferation and differentiation of precursor cells (preadipocytes) present in the stromo-vascular compartment of adipose tissue. These processes are very complex and an increasing number of growth factors and hormones have been shown to modulate the expression of genes involved in preadipocyte proliferation and differentiation. A number of transcription factors, including the C/EBP family and PP ARy, have been identified as integral to adipose tissue development and preadipocyte differentiation. Together PP ARy and C/EBPa regulate important events in the activation and maintenance of the terminally differentiated phenotype. The ability of PP ARy to increase transcription through its DNA recognition site is dependent on the binding of ligands. This suggests that an endogenous PP ARy ligand may be an important regulator of adipogenesis. Adipose tissue functions as both the major site of energy storage in the body and as an endocrine organ synthesizing and secreting a number of important molecules involved in regulation of energy balance. For optimum functioning therefore, adipose tissue requires extensive vascularization and previous studies have shown that growth of adipose tissue is preceded by development of a microvascular network. This suggests that paracrine interactions between constituent cells in adipose tissue may be involved in both new capillary formation and fat cell growth. To address this hypothesis the work in this project was aimed at (a) further development of a method for inducing preadipocyte differentiation in subcultured human cells; (b) establishing a method for simultaneous isolation and separate culture of both preadipocytes and microvascular endothelial cells from the same adipose tissue biopsies; (c) to determine, using conditioned medium and co-culture techniques, if endothelial cell-derived factors influence the proliferation and/or differentiation of human preadipocytes; and (d) commence characterization of factors that may be responsible for any observed paracrine effects on aspects of human adipogenesis. Major findings of these studies were as follows: (A) Inclusion of either linoleic acid (a long-chain fatty acid reported to be a naturally occurring ligand for PP ARy) or Rosiglitazone (a member of the thiazolidinedione class of insulin-sensitizing drugs and a synthetic PPARy ligand) in differentiation medium had markedly different effects on preadipocyte differentiation. These studies showed that human preadipocytes have the potential to accumulate triacylglycerol irrespective of their stage of biochemical differentiation, and that thiazolidinediones and fatty acids may exert their adipogenic and lipogenic effects via different biochemical pathways. It was concluded that Rosiglitazone is a more potent inducer of human preadipocyte differentiation than linoleic acid. (B) A method for isolation and culture of both endothelial cells and preadipocytes from the same adipose tissue biopsy was developed. Adipose-derived microvascular endothelial cells were found to produce factor/s, which enhance both proliferation and differentiation of human preadipocytes. (C) The adipogenic effects of microvascular endothelial cells can be mimicked by exposure of preadipocytes to members of the Fibroblast Growth Factor family, specifically ~-ECGF and FGF-1. (D) Co-culture of human preadipocytes with endothelial cells or exposure of preadipocytes to either ~-ECGF or FGF-1 were found to 'prime' human preadipocytes, during their proliferative phase of growth, for thiazolidinedione-induced differentiation. (E) FGF -1 was not found to be acting as a ligand for PP ARy in this system. Findings from this project represent a significant step forward in our understanding of factors involved in growth of human adipose tissue and may lead to the development of therapeutic strategies aimed at modifying the process. Such strategies would have potential clinical utility in the treatment of obesity and obesity related disorders such as Type II Diabetes.

Safety-restraint use rate as function of law enforcement and other factors : preliminary analysis

Persistent use of safety restraints prevents deaths and reduces the severity and number of injuries resulting from motor vehicle crashes. However, safety-restraint use rates in the United States have been below those of other nations with safety-restraint enforcement laws. With a better understanding of the relationship between safety-restraint law enforcement and safety-restraint use, programs can be implemented to decrease the number of deaths and injuries resulting from motor vehicle crashes. Does safety-restraint use increase as enforcement increases? Do motorists increase their safety-restraint use in response to the general presence of law enforcement or to targeted law enforcement efforts? Does a relationship between enforcement and restraint use exist at the countywide level? A logistic regression model was estimated by using county-level safety-restraint use data and traffic citation statistics collected in 13 counties within the state of Florida in 1997. The model results suggest that safety-restraint use is positively correlated with enforcement intensity, is negatively correlated with safety-restraint enforcement coverage (in lanemiles of enforcement coverage), and is greater in urban than rural areas. The quantification of these relationships may assist Florida and other law enforcement agencies in raising safety-restraint use rates by allocating limited funds more efficiently either by allocating additional time for enforcement activities of the existing force or by increasing enforcement staff. In addition, the research supports a commonsense notion that enforcement activities do result in behavioral response.

Nitrogen fertilizer rate management as a nitrous oxide mitigation strategy: Development of a nitrous oxide emission reduction protocol (NERP)

Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.

Prevalence of upper-body symptoms following breast cancer and its relationship with upper-body function and lymphoedema

This investigation describes the prevalence of upper-body symptoms in a population-based sample of women with breast cancer (BC) and examines their relationships with upper-body function (UBF) and lymphoedema, as two clinically important sequelae. Australian women (n=287) with unilateral BC were assessed at three-monthly intervals, from six to 18 months post-surgery (PS). Participants reported the presence and intensity of upper-body symptoms on the treated side. Objective and self-reported UBF and lymphoedema (bioimpedance spectroscopy) were also assessed. Approximately 50% of women reported at least one moderate-to-extreme symptom at 6- and at 18-months PS. There was a significant relationship between symptoms and function (p<0.01), whereby perceived and objective function declined with increasing number of symptoms present. Those with lymphoedema were more likely to report multiple symptoms and presence of symptoms at baseline increased risk of lymphoedema (ORs>1.3, p=0.02). Although, presence of symptoms explained only 5.5% of the variation in the odds of lymphoedema. Upper-body symptoms are common and persistent following breast cancer and are associated with clinical ramifications, including reduced UBF and increased risk of developing lymphoedema. However, using the presence of symptoms as a diagnostic indicator of lymphoedema is limited.

Unraveling the complexity of driving while intoxicated: a study into the prevalence of psychiatric and substance abuse comorbidity

Objective Research is beginning to provide an indication of the co-occurring substance abuse and mental health needs for the driving under the influence (DUI) population. This study aimed to examine the extent of such psychiatric problems among a large sample size of DUI offenders entering treatment in Texas. Methods This is a study of 36,373 past year DUI clients and 308,714 non-past year DUI clients admitted to Texas treatment programs between 2005 and 2008. Data were obtained from the State's administrative dataset. Results Analysis indicated that non-past year DUI clients were more likely to present with more severe illicit substance use problems, while past year DUI clients were more likely to have a primary problem with alcohol. Nevertheless, a cannabis use problem was also found to be significantly associated with DUI recidivism in the last year. In regards to mental health status, a major finding was that depression was the most common psychiatric condition reported by DUI clients, including those with more than one DUI offence in the past year. This cohort also reported elevated levels of Bipolar Disorder compared to the general population, and such a diagnosis was also associated with an increased likelihood of not completing treatment. Additionally, female clients were more likely to be diagnosed with mental health problems than males, as well as more likely to be placed on medications at admission and more likely to have problems with methamphetamine, cocaine, and opiates. Conclusions DUI offenders are at an increased risk of experiencing comorbid psychiatric disorders, and thus, corresponding treatment programs need to cater for a range of mental health concerns that are likely to affect recidivism rates.

Indentation size effect and strain rate sensitivity of nanocrystalline Mg-Al alloys

Deformation Behaviour of microcrystalline (mc) and nanocrystalline (nc) Mg-5%Al alloys produced by hot extrusion of ball-milled powders were investigated using instrumented indentation tests. The hardness values of the mc and nc metals exhibited indentation size effect (ISE), with nc alloys showing weaker ISE. The highly localized dislocation activities resulted in a small activation volume, hence enhanced strain rate sensitivity. Relative higher strain rate sensitivity and the negative Hall-Petch Relationship suggested the increasingly important role of grain boundary mediated mechanisms when the grain size decreased to nanometer region.

A study of the generalised max–min fair rate allocation for ABR control in ATM

In the rate-based flow control for ATM Available Bit Rate service, fairness is an important requirement, i.e. each flow should be allocated a fair share of the available bandwidth in the network. Max–min fairness, which is widely adopted in ATM, is appropriate only when the minimum cell rates (MCRs) of the flows are zero or neglected. Generalised max–min (GMM) fairness extends the principle of the max–min fairness to accommodate MCR. In this paper, we will discuss the formulation of the GMM fair rate allocation, propose a centralised algorithm, analyse its bottleneck structure and develop an efficient distributed explicit rate allocation algorithm to achieve the GMM fairness in an ATM network. The study in this paper addresses certain theoretical and practical issues of the GMM fair rate allocation.

Weighted fairness with MCR guarantee and a general-purpose explicit rate allocation algorithm for ATM ABR service

In this paper, weighted fair rate allocation for ATM available bit rate (ABR) service is discussed with the concern of the minimum cell rate (MCR). Weighted fairness with MCR guarantee has been discussed recently in the literature. In those studies, each ABR virtual connection (VC) is first allocated its MCR, then the remaining available bandwidth is further shared among ABR VCs according to their weights. For the weighted fairness defined in this paper, the bandwidth is first allocated according to each VC's weight; if a VC's weighted share is less than its MCR, it should be allocated its MCR instead of the weighted share. This weighted fairness with MCR guarantee is referred to as extended weighted (EXW) fairness. Certain theoretical issues related to EXW, such as its global solution and bottleneck structure, are first discussed in the paper. A distributed explicit rate allocation algorithm is then proposed to achieve EXW fairness in ATM networks. The algorithm is a general-purpose explicit rate algorithm in the sense that it can realise almost all the fairness principles proposed for ABR so far whilst only minor modifications may be needed.

An enhanced explicit rate algorithm for ABR traffic control in ATM networks

A high performance, low computational complexity rate-based flow control algorithm which can avoid congestion and achieve fairness is important to ATM available bit rate service. The explicit rate allocation algorithm proposed by Kalampoukas et al. is designed to achieve max–min fairness in ATM networks. It has several attractive features, such as a fixed computational complexity of O(1) and the guaranteed convergence to max–min fairness. In this paper, certain drawbacks of the algorithm, such as the severe overload of an outgoing link during transient period and the non-conforming use of the current cell rate field in a resource management cell, have been identified and analysed; a new algorithm which overcomes these drawbacks is proposed. The proposed algorithm simplifies the rate computation as well. Compared with Kalampoukas's algorithm, it has better performance in terms of congestion avoidance and smoothness of rate allocation.

Effect of cabin ventilation rate on ultrafine particle exposure inside automobiles

We alternately measured on-road and in-vehicle ultrafine (<100 nm) particle (UFP) concentration for 5 passenger vehicles that comprised an age range of 18 years. A range of cabin ventilation settings were assessed during 301 trips through a 4 km road tunnel in Sydney, Australia. Outdoor airflow(ventilation) rates under these settings were quantified on open roads using tracer gas techniques. Significant variability in tunnel trip average median in-cabin/on-road (I/O) UFP ratios was observed (0.08 to ∼1.0). Based on data spanning all test automobiles and ventilation settings, a positive linear relationship was found between outdoor air flow rate and I/O ratio, with the former accounting for a substantial proportion of variation in the latter (R2 ) 0.81). UFP concentrations recorded in cabin during tunnel travel were significantly higher than those reported by comparable studies performed on open roadways. A simple mathematical model afforded the ability to predict tunnel trip average in-cabin UFP concentrations with good accuracy. Our data indicate that under certain conditions, in-cabin UFP exposures incurred during tunnel travel may contribute significantly to daily exposure. The UFP exposure of automobile occupants appears strongly related to their choice of ventilation setting and vehicle.