Evaluating automatic road detection across a large aerial imagery collection

The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features.

Raising awareness of traffic pollution: the potential benefits and problems of using a warning smell

Exposure to traffic pollution is increasing worldwide as people move to cities, and as more vehicles join the roads, creating longer journeys and more traffic jams. Most traffic pollutants are odourless and invisible, which hides exposure from the public. If traffic pollution had a distinctive smell it would enable people to avoid exposure, and increase the political will for difficult policy changes. A smell may also instigate longer-term changes, such as switching to active transport for school pick-ups. A smell could be added using a fuel additive or a temporary device attached to vehicle exhausts.

Acoustic hazard detection for pedestrians with obscured hearing

Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease

Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.

A Bayesian approach for estimating detection times in horses : exploring the pharmacokinetics of a urinary acepromazine metabolite

We describe the population pharmacokinetics of an acepromazine (ACP) metabolite (2-(1-hydroxyethyl)promazine) (HEPS) in horses for the estimation of likely detection times in plasma and urine. Acepromazine (30 mg) was administered to 12 horses, and blood and urine samples were taken at frequent intervals for chemical analysis. A Bayesian hierarchical model was fitted to describe concentration-time data and cumulative urine amounts for HEPS. The metabolite HEPS was modelled separately from the parent ACP as the half-life of the parent was considerably less than that of the metabolite. The clearance ($Cl/F_{PM}$) and volume of distribution ($V/F_{PM}$), scaled by the fraction of parent converted to metabolite, were estimated as 769 L/h and 6874 L, respectively. For a typical horse in the study, after receiving 30 mg of ACP, the upper limit of the detection time was 35 hours in plasma and 100 hours in urine, assuming an arbitrary limit of detection of 1 $\mu$g/L, and a small ($\approx 0.01$) probability of detection. The model derived allowed the probability of detection to be estimated at the population level. This analysis was conducted on data collected from only 12 horses, but we assume that this is representative of the wider population.

Technology transfer evaluation in the high technology industry : an interdisciplinary perspective

The underlying objective of this study was to develop a novel approach to evaluate the potential for commercialisation of a new technology. More specifically, this study examined the 'ex-ante'. evaluation of the technology transfer process. For this purpose, a technology originating from the high technology sector was used. The technology relates to the application of software for the detection of weak signals from space, which is an established method of signal processing in the field of radio astronomy. This technology has the potential to be used in commercial and industrial areas other than astronomy, such as detecting water leakages in pipes. Its applicability to detecting water leakage was chosen owing to several problems with detection in the industry as well as the impact it can have on saving water in the environment. This study, therefore, will demonstrate the importance of interdisciplinary technology transfer. The study employed both technical and business evaluation methods including laboratory experiments and the Delphi technique to address the research questions. There are several findings from this study. Firstly, scientific experiments were conducted and these resulted in a proof of concept stage of the chosen technology. Secondly, validation as well as refinement of criteria from literature that can be used for „ex-ante. evaluation of technology transfer has been undertaken. Additionally, after testing the chosen technology.s overall transfer potential using the modified set of criteria, it was found that the technology is still in its early stages and will require further development for it to be commercialised. Furthermore, a final evaluation framework was developed encompassing all the criteria found to be important. This framework can help in assessing the overall readiness of the technology for transfer as well as in recommending a viable mechanism for commercialisation. On the whole, the commercial potential of the chosen technology was tested through expert opinion, thereby focusing on the impact of a new technology and the feasibility of alternate applications and potential future applications.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Immunohistochemical detection of survivin in canine lymphoma

Survivin is a member of the family of proteins known as 'inhibitors of apoptosis proteins'. Survivin has a role in cellular decisions concerning division and survival and is frequently expressed in neoplastic cells. The aim of the present study was to investigate immunohistochemically the expression of survivin in normal canine tissues and in canine lymphoma. A representative range of fetal and adult normal tissues as well as biopsy samples from dogs with lymphoma were assembled in tissue arrays. The lymphomas were classified according to the revised Kiel and to the Revised European American Lymphoma - World Health Organization (REAL-WHO) schemes. Polyclonal and monoclonal antisera cross-reactive with canine survivin identified cytoplasmic expression of the molecule in a broad range of normal canine cells. The same reagents demonstrated cytoplasmic labelling of more than 5% of cells in all 83 lymphoma samples tested with polyclonal antiserum and in 67 of 82 (82%) of samples tested with monoclonal antiserum. Survivin was expressed by a wide range of canine lymphoma subtypes, but the expression of this molecule in normal canine tissues must be considered if novel therapies targeting survivin are applied to the management of canine lymphoma. © 2010 Elsevier Ltd.

A longitudinal assessment of chronic wound fluid to detect biochemical indicators of healing

Chronic venous leg ulcers are a detrimental health issue plaguing our society, resulting in long term pain, immobility and decreased quality of life for a large proportion of sufferers. The frequency of these chronic wounds has led current research to focus on the wound environment to provide important information regarding the prolonged, fluctuated or static healing patterns of these wounds. Disruption to the normal wound healing process results in release of multiple factors in the wound environment that could correlate to wound chronicity. These biochemical factors can often be detected through non-invasively sampling chronic wound fluid (CWF) from the site of injury. Of note, whilst there are numerous studies comparing acute and chronic wound fluids, there have not been any reports in the literature employing a longitudinal study in order to track biochemical changes in wound fluid as patients transition from a non-healing to healed state. Initially the objective of this study was to identify biochemical changes in CWF associated with wound healing using a proteomic approach. The proteomic approach incorporated a multi-dimensional liquid chromatography fractionation technique coupled with mass spectrometry (MS) to enable identification of proteins present in lower concentrations in CWF. Not surprisingly, many of the proteins identified in wound fluid were acute phase proteins normally expressed during the inflammatory phase of healing. However, the number of proteins positively identified by MS was quite low. This was attributed to the diverse range in concentration of protein species in CWF making it challenging to detect the diagnostically relevant low molecular weight proteins. In view of this, SELDI-TOF MS was also explored as a means to target low molecular weight proteins in sequential patient CWF samples during the course of healing. Unfortunately, the results generated did not yield any peaks of interest that were altered as wounds transitioned to a healed state. During the course of proteomic assessment of CWF, it became evident that a fraction of non-proteinaceous compounds strongly absorbed at 280 nm. Subsequent analyses confirmed that most of these compounds were in fact part of the purine catabolic pathway, possessing distinctive aromatic rings and which results in high absorbance at 254 nm. The accumulation of these purinogenic compounds in CWF suggests that the wound bed is poorly oxygenated resulting in a switch to anaerobic metabolism and consequently ATP breakdown. In addition, the presence of the terminal purine catabolite, uric acid (UA), indicates that the enzyme xanthine oxidoreductase (XOR) catalyses the reaction of hypoxanthine to xanthine and finally to UA. More importantly, the studies provide evidence for the first time of the exogenous presence of XOR in CWF. XOR is the only enzyme in humans capable of catalysing the production of UA in conjunction with a burst of the highly reactive superoxide radical and other oxidants like H2O2. Excessive release of these free radicals in the wound environment can cause cellular damage disrupting the normal wound healing process. In view of this, a sensitive and specific assay was established for monitoring low concentrations of these catabolites in CWF. This procedure involved combining high performance liquid chromatography (HPLC) with tandem mass spectrometry and multiple reaction monitoring (MRM). This application was selective, using specific MRM transitions and HPLC separations for each analyte, making it ideal for the detection and quantitation of purine catabolites in CWF. The results demonstrated that elevated levels of UA were detected in wound fluid obtained from patients with clinically worse ulcers. This suggests that XOR is active in the wound site generating significant amounts of reactive oxygen species (ROS). In addition, analysis of the amount of purine precursors in wound fluid revealed elevated levels of purine precursors in wound fluid from patients with less severe ulcers. Taken together, the results generated in this thesis suggest that monitoring changes of purine catabolites in CWF is likely to provide valuable information regarding the healing patterns of chronic venous leg ulcers. XOR catalysis of purine precursors not only provides a method for monitoring the onset, prognosis and progress of chronic venous leg ulcers, but also provides a potential therapeutic target by inhibiting XOR, thus blocking UA and ROS production. Targeting a combination of these purinogenic compounds and XOR could lead to the development of novel point of care diagnostic tests. Therefore, further investigation of these processes during wound healing will be worthwhile and may assist in elucidating the pathogenesis of this disease state, which in turn may lead to the development of new diagnostics and therapies that target these processes.

A fragment of the LG3 peptide of endorepellin is present in the urine of physically active mining workers : a potential marker of physical activity

Biomarker analysis has been implemented in sports research in an attempt to monitor the effects of exertion and fatigue in athletes. This study proposed that while such biomarkers may be useful for monitoring injury risk in workers, proteomic approaches might also be utilised to identify novel exertion or injury markers. We found that urinary urea and cortisol levels were significantly elevated in mining workers following a 12 hour overnight shift. These levels failed to return to baseline over 24h in the more active maintenance crew compared to truck drivers (operators) suggesting a lack of recovery between shifts. Use of a SELDI-TOF MS approach to detect novel exertion or injury markers revealed a spectral feature which was associated with workers in both work categories who were engaged in higher levels of physical activity. This feature was identified as the LG3 peptide, a C-terminal fragment of the anti-angiogenic / anti-tumourigenic protein endorepellin. This finding suggests that urinary LG3 peptide may be a biomarker of physical activity. It is also possible that the activity mediated release of LG3 / endorepellin into the circulation may represent a biological mechanism for the known inverse association between physical activity and cancer risk / survival.

Development of a high-speed sensing and detection system for automatic removal of packages with leaky seals from a high-speed food processing and packaging line

Contamination of packaged foods due to micro-organisms entering through air leaks can cause serious public health issues and cost companies large amounts of money due to product recalls, consumer impact and subsequent loss of market share. The main source of contamination is leaks in packaging which allow air, moisture and microorganisms to enter the package. In the food processing and packaging industry worldwide, there is an increasing demand for cost effective state of the art inspection technologies that are capable of reliably detecting leaky seals and delivering products at six-sigma. The new technology will develop non-destructive testing technology using digital imaging and sensing combined with a differential vacuum technique to assess seal integrity of food packages on a high-speed production line. The cost of leaky packages in Australian food industries is estimated close to AUD $35 Million per year. Contamination of packaged foods due to micro-organisms entering through air leaks can cause serious public health issues and cost companies large sums of money due to product recalls, compensation claims and loss of market share. The main source of contamination is leaks in packaging which allow air, moisture and micro-organisms to enter the package. Flexible plastic packages are widely used, and are the least expensive form of retaining the quality of the product. These packets can be used to seal, and therefore maximise, the shelf life of both dry and moist products. The seals of food packages need to be airtight so that the food content is not contaminated due to contact with microorganisms that enter as a result of air leakage. Airtight seals also extend the shelf life of packaged foods, and manufacturers attempt to prevent food products with leaky seals being sold to consumers. There are many current NDT (non-destructive testing) methods of testing the seal of flexible packages best suited to random sampling, and for laboratory purposes. The three most commonly used methods are vacuum/pressure decay, bubble test, and helium leak detection. Although these methods can detect very fine leaks, they are limited by their high processing time and are not viable in a production line. Two nondestructive in-line packaging inspection machines are currently available and are discussed in the literature review. The detailed design and development of the High-Speed Sensing and Detection System (HSDS) is the fundamental requirement of this project and the future prototype and production unit. Successful laboratory testing was completed and a methodical design procedure was needed for a successful concept. The Mechanical tests confirmed the vacuum hypothesis and seal integrity with good consistent results. Electrically, the testing also provided solid results to enable the researcher to move the project forward with a certain amount of confidence. The laboratory design testing allowed the researcher to confirm theoretical assumptions before moving into the detailed design phase. Discussion on the development of the alternative concepts in both mechanical and electrical disciplines enables the researcher to make an informed decision. Each major mechanical and electrical component is detailed through the research and design process. The design procedure methodically works through the various major functions both from a mechanical and electrical perspective. It opens up alternative ideas for the major components that although are sometimes not practical in this application, show that the researcher has exhausted all engineering and functionality thoughts. Further concepts were then designed and developed for the entire HSDS unit based on previous practice and theory. In the future, it would be envisaged that both the Prototype and Production version of the HSDS would utilise standard industry available components, manufactured and distributed locally. Future research and testing of the prototype unit could result in a successful trial unit being incorporated in a working food processing production environment. Recommendations and future works are discussed, along with options in other food processing and packaging disciplines, and other areas in the non-food processing industry.

Screening to identify large truck potential blackspots : methodological issues and concerns

1. Overview of hotspot identification (HSID)methods 2. Challenges with HSID 3. Bringing crash severity into the ‘mix’ 4. Case Study: Truck Involved Crashes in Arizona 5. Conclusions • Heavy duty trucks have different performance envelopes than passenger cars and have more difficulty weaving, accelerating, and braking • Passenger vehicles have extremely limited sight distance around trucks • Lane and shoulder widths affect truck crash risk more than passenger cars • Using PDOEs to model truck crashes results in a different set of locations to examine for possible engineering and behavioral problems • PDOE models point to higher societal cost locations, whereas frequency models point to higher crash frequency locations • PDOE models are less sensitive to unreported crashes • PDOE models are a great complement to existing practice

The expression, regulation and function of kallikrein 4 in prostate cancer

Prostate cancer is a significant health problem faced by aging men. Currently, diagnostic strategies for the detection of prostate cancer are either unreliable, yielding high numbers of false positive results, or too invasive to be used widely as screening tests. Furthermore, the current therapeutic strategies for the treatment of the disease carry considerable side effects. Although organ confined prostate cancer can be curable, most detectable clinical symptoms occur in advanced disease when primary tumour cells have metastasised to distant sites - usually lymph nodes and bone. Many growth factors and steroids assist the continued growth and maintenance of prostatic tumour cells. Of these mitogens, androgens are important in the development of the normal prostate but are also required to sustain the growth of prostate cancer cells in the early stage of the disease. Not only are androgens required in the early stage of disease, but also many other growth factors and hormones interact to cause uncontrolled proliferation of malignant cells. The early, androgen sensitive phase of disease is followed by an androgen insensitive phase, whereby androgens are no longer required to stimulate the growth of the tumour cells. Growth factors such as transforming growth factor  and  (TGF/), epidermal growth factor (EGF), basic fibroblast growth factor (bFGF), insulin-like growth factors (IGFs), Vitamin D and thyroid hormone have been suggested to be important at this stage of disease. Interestingly, some of the kallikrein family of genes, including prostate specific antigen (PSA), the current serum diagnostic marker for prostate cancer, are regulated by androgens and many of the aforementioned growth factors. The kallikrein gene family is a group of serine proteases that are involved in a diverse range of physiological processes: regulation of local blood flow, angiogenesis, tissue invasion and mitogenesis. The earliest members of the kallikrein gene family (KLK1-KLK3) have been strongly associated with general disease states, such as hypertension, inflammation, pancreatitis and renal disease, but are also linked to various cancers. Recently, this family was extended to include 15 genes (KLK1-15). Several newer members of the kallikrein family have been implicated in the carcinogenesis and tumour metastasis of hormone-dependent cancers such as prostate, breast, endometrial and ovarian cancer. The aims of this project were to investigate the expression of the newly identified kallikrein, KLK4, in benign and malignant prostate tissues, and prostate cancer cell lines. This thesis has demonstrated the elevated expression of KLK4 mRNA transcripts in malignant prostate tissue compared to benign prostates. Additionally, expression of the full length KLK4 transcript was detected in the androgen dependent prostate cancer cell line, LNCaP. Based on the above finding, the LNCaP cell line was chosen to assess the potential regulation of full length KLK4 by androgen, thyroid hormone and epidermal growth factor. KLK4 mRNA and protein was found to be up-regulated by androgen and a combination of androgen and thyroid hormone. Thyroid hormone alone produced no significant change in KLK4 mRNA or protein over the control. Epidermal growth factor treatment also resulted in elevated expression levels of KLK4 mRNA and protein. To assess the potential functional role(s) of KLK4/hK4 in processes associated with tumour progression, full length KLK4 was transfected into PC-3 cells - a prostate cancer cell line originally derived from a secondary bone lesion. The KLK4/hK4 over-expressing cells were assessed for their proliferation, migration, invasion and attachment properties. The KLK4 over-expressing clones exhibited a marked change in morphology, indicative of a more aggressive phenotype. The KLK4 clones were irregularly shaped with compromised adhesion to the growth surface. In contrast, the control cell lines (parent PC-3 and empty vector clones) retained a rounded morphology with obvious cell to cell adhesion, as well as significant adhesion to their growth surface. The KLK4 clones exhibited significantly greater attachment to Collagen I and IV than native PC-3s and empty vector controls. Over a 12 hour period, in comparison to the control cells, the KLK4 clones displayed an increase in migration towards PC-3 native conditioned media, a 3 fold increase towards conditioned media from an osteoblastic cell line (Saos-2) and no change in migration towards conditioned media from neonatal foreskin fibroblast cells or 20% foetal bovine serum. Furthermore, the increase in migration exhibited by the KLK4 clones was partially blocked by the serine protease inhibitor, aprotinin. The data presented in this thesis suggests that KLK4/hK4 is important in prostate carcinogenesis due to its over-expression in malignant prostate tissues, its regulation by hormones and growth factors associated with prostate disease and the functional consequences of over-expression of KLK4/hK4 in the PC-3 cell line. These results indicate that KLK4/hK4 may play an important role in tumour invasion and bone metastasis via increased attachment to the bone matrix protein, Collagen I, and enhanced migration due to soluble factors produced by osteoblast cells. This suggestion is further supported by the morphological changes displayed by the KLK4 over-expressing cells. Overall, this data suggests that KLK4/hK4 should be further studied to more fully investigate the potential value of KLK4/hK4 as a diagnostic/prognostic biomarker or in therapeutic applications.

Binocular summation improves performance to defocus-induced blur

PURPOSE. To assess whether there are any advantages of binocular over monocular vision under blur conditions. METHODS. We measured the effect of defocus, induced by positive lenses, on the pattern reversal Visual Evoked Potential (VEP) and on visual acuity (VA). Monocular (dominant eye) and binocular VEPs were recorded from thirteen volunteers (average age: 28±5 years, average spherical equivalent: -0.25±0.73 D) for defocus up to 2.00 D using positive powered lenses. VEPs were elicited using reversing 10 arcmin checks at a rate of 4 reversals/second. The stimulus subtended a circular field of 7 degrees with 100% contrast and mean luminance 30 cd/m2. VA was measured under the same conditions using ETDRS charts. All measurements were performed at 1m viewing distance with best spectacle sphero-cylindrical correction and natural pupils. RESULTS. With binocular stimulation, amplitudes and implicit times of the P100 component of the VEPs were greater and shorter, respectively, in all cases than for monocular stimulation. Mean binocular enhancement ratio in the P100 amplitude was 2.1 in-focus, increasing linearly with defocus to be 3.1 at +2.00 D defocus. Mean peak latency was 2.9 ms shorter in-focus with binocular than for monocular stimulation, with the difference increasing with defocus to 8.8 ms at +2.00 D. As for the VEP amplitude, VA was always better with binocular than with monocular vision, with the difference being greater for higher retinal blur. CONCLUSIONS. Both subjective and electrophysiological results show that binocular vision ameliorates the effect of defocus. The increased binocular facilitation observed with retinal blur may be due to the activation of a larger population of neurons at close-to-threshold detection under binocular stimulation.