154 resultados para Detection and segmentation


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Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

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This paper presents the flight trials of an electro-optical (EO) sense-and-avoid system onboard a Cessna host aircraft (camera aircraft). We focus on the autonomous collision avoidance capability of the sense-and-avoid system; that is, closed-loop integration with the onboard aircraft autopilot. We also discuss the system’s approach to target detection and avoidance control, as well as the methodology of the flight trials. The results demonstrate the ability of the sense-and-avoid system to automatically detect potential conflicting aircraft and engage the host Cessna autopilot to perform an avoidance manoeuvre, all without any human intervention

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Modelling activities in crowded scenes is very challenging as object tracking is not robust in complicated scenes and optical flow does not capture long range motion. We propose a novel approach to analyse activities in crowded scenes using a “bag of particle trajectories”. Particle trajectories are extracted from foreground regions within short video clips using particle video, which estimates long range motion in contrast to optical flow which is only concerned with inter-frame motion. Our applications include temporal video segmentation and anomaly detection, and we perform our evaluation on several real-world datasets containing complicated scenes. We show that our approaches achieve state-of-the-art performance for both tasks.

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Prostate cancer is the second most common cause of cancer related deaths in Western men. Despite the significant improvements in current treatment techniques, there is no cure for advanced metastatic, castrate-resistant disease. Early detection and prevention of progression to a castrate-resistant state may provide new strategies to improve survival. A number of growth factors have been shown to act in an autocrine/paracrine manner to modulate prostate cancer tumour growth. Our laboratory has previously shown that ghrelin and its receptors (the functional GHS-R1a and the non-functional GHS-R1b) are expressed in prostate cancer specimens and cell lines. We have shown that ghrelin increases cell proliferation in the PC3 and LNCaP prostate cancer cell lines through activation of ERK1/2, suggesting that ghrelin could regulate prostate cancer cell growth and play a role in the progression of the disease. Ghrelin is a 28 amino-acid peptide hormone, identified to be the natural ligand of the growth hormone secretagogue receptor (GHS-R1a). It is well characterised as a growth hormone releasing and as an orexigenic peptide that stimulates appetite and feeding and regulates energy expenditure and bodyweight. In addition to its orexigenic properties, ghrelin has been shown to play a regulatory role in a number of systems, including the reproductive, immune and cardiovascular systems and may play a role in a number of pathological conditions such as chronic heart failure, anorexia, cachexia, obesity, diabetes and cancer. In cancer, ghrelin and its receptor are expressed in a range of tumours and cancer cell lines and ghrelin has been demonstrated to modulate cell proliferation, apoptosis, migration and invasion in some cell types. The ghrelin gene (GHRL) encodes preproghrelin peptide, which is processed to produce three currently known functional peptides - ghrelin, desacyl ghrelin and obestatin. Prohormone convertases (PCs) have been shown to cleave the preproghrelin peptide into two primary products - the 28 amino acid peptide, ghrelin, and the remaining 117 amino acid C-terminal peptide, C-ghrelin. C-ghrelin can then be further processed to produce the 23 amino acid peptide, obestatin. Ghrelin circulates in two different forms - an octanoylated form (known as ghrelin) and a non-octanoylated form, desacyl ghrelin. The unique post-translational addition of octanoic acid to the serine 3 residue of the propeptide chain to form acylated ghrelin is catalysed by ghrelin O-acyltransferase (GOAT). This modification is necessary for binding of ghrelin to its only known functional receptor, the GHS-R1a. As desacyl ghrelin cannot bind and activate the GHS-R1a, it was initially thought to be an inactive peptide, despite the fact that it circulates at much higher levels than ghrelin. Further research has demonstrated that desacyl ghrelin is biologically active and shares some of the actions of ghrelin, as well as having some opposing and distinct roles. Interestingly, both ghrelin and desacyl ghrelin have been shown to modulate apoptosis, cell differentiation and proliferation in some cell types, and to stimulate cell proliferation through activation of ERK1/2 and PI3K/Akt pathways. The third known peptide product of the ghrelin preprohormone, obestatin, was initially thought to oppose the actions of ghrelin in appetite regulation and food intake and to mediate its effects through the G protein-coupled receptor 39 (GPR39). Subsequent research failed to reproduce the initial findings, however, and the possible anorexigenic effects of obestatin, as well as the identity of its receptor, remain unclear. Obestatin plays some important physiological roles, including roles in improving memory, the inhibition of thirst and anxiety, increased secretion of pancreatic juice, and regulation of cell proliferation, survival, apoptosis and differentiation. Preliminary studies have also shown that obestatin stimulates cell proliferation in some cell types through activation of ERK1/2, Akt and PKC pathways. Overall, however, at the commencement of this PhD project, relatively little was known regarding the functions and mechanisms of action of the preproghrelin-derived functional peptides in modulating prostate cancer cell proliferation. The roles of obestatin, and desacyl ghrelin as potential growth factors had not previously been investigated, and the potential expression and regulation of the preproghrelin processing enzymes, GOAT and prohormone convertases was unknown in prostate cancer cell lines. Therefore, the overall objectives of this study were to: 1. investigate the effects of obestatin on cell proliferation and signaling in prostate cancer cell lines 2. compare the effects of desacyl ghrelin and ghrelin on cell proliferation and signaling in prostate cancer cell lines 3. investigate whether prostate cancer cell lines possess the necessary enzymatic machinery to produce ghrelin and desacyl ghrelin and if these peptides can regulate GOAT expression Our laboratory has previously shown that ghrelin stimulates cell proliferation in the PC3 and LNCaP prostate cancer cell line through activation of the ERK1/2 pathway. In this study it has been demonstrated that treatments with either ghrelin, desacyl ghrelin or obestatin over 72 hours significantly increased cell proliferation in the PC3 prostate cancer cell line but had no significant effect in the RWPE-1 transformed normal prostate cell line. Ghrelin (1000nM) stimulated cell proliferation in the PC3 prostate cancer cell line by 31.66 6.68% (p<0.01) with the WST-1 method, and 13.55 5.68% (p<0.05) with the CyQUANT assay. Desacyl ghrelin (1000nM) increased cell proliferation in PC3 cells by 21.73 2.62% (p<0.01) (WST-1), and 15.46 7.05% (p<0.05) (CyQUANT) above untreated control. Obestatin (1000nM) induced a 28.37 7.47% (p<0.01) (WST-1) and 12.14 7.47% (p<0.05) (CyQUANT) significant increase in cell proliferation in the PC3 prostate cancer cell line. Ghrelin and desacyl ghrelin treatments stimulated Akt and ERK phosphorylation across a range of concentrations (p<0.01). Obestatin treatment significantly stimulated Akt, ERK and PKC phosphorylation (p<0.05). Through the use of specific inhibitors, the MAPK inhibitor U0126 and the Akt1/2 kinase inhibitor, it was demonstrated that ghrelin- and obestatin-induced cell proliferation in the PC3 prostate cancer cell line is mediated through activation of ERK1/2 and Akt pathways. Although desacyl ghrelin significantly stimulated Akt and ERK phosphorylation, U0126 failed to prevent desacyl ghrelin-induced cell proliferation suggesting ghrelin and desacyl ghrelin might act through different mechanisms to increase cell proliferation. Ghrelin and desacyl ghrelin have shown a proliferative effect in osteoblasts, pancreatic -cells and cardiomyocytes through activation of ERK1/2 and PI3K/Akt pathways. Here it has been shown that ghrelin and its non-acylated form exert the same function and stimulate cell proliferation in the PC3 prostate cancer cell line through activation of the Akt pathway. Ghrelin-induced proliferation was also mediated through activation of the ERK1/2 pathway, however, desacyl ghrelin seems to stimulate cell proliferation in an ERK1/2-independent manner. As desacyl ghrelin does not bind and activate GHSR1a, the only known functional ghrelin receptor, the finding that both ghrelin and desacyl ghrelin stimulate cell proliferation in the PC3 cell line suggests that these peptides could be acting through the yet unidentified alternative ghrelin receptor in this cell type. Obestatin treatment also stimulated PKC phosphorylation, however, a direct role for this pathway in stimulating cell proliferation could not be proven using available PKC pathway inhibitors, as they caused significant cell death over the extended timeframe of the cell proliferation assays. Obestatin has been shown to stimulate cell proliferation through activation of PKC isoforms in human retinal epithelial cells and in the human gastric cancer cell line KATO-III. We have demonstrated that all of the prostate-derived cell lines examined (PC3, LNCaP, DU145, 22Rv1, RWPE-1 and RWPE-2) expressed GOAT and at least one of the prohormone convertases, which are known to cleave the proghrelin peptide, PC1/3, PC2 and furin, at the mRNA level. These cells, therefore, are likely to possess the necessary machinery to cleave the preproghrelin protein and to produce the mature ghrelin and desacyl ghrelin peptides. In addition to prohormone convertases, the presence of octanoic acid is essential for acylated ghrelin production. In this study octanoic acid supplementation significantly increased cell proliferation in the PC3 prostate cancer cell line by over 20% compared to untreated controls (p<0.01), but surprisingly, not in the DU145, LNCaP or 22Rv1 prostate cancer cell lines or in the RWPE-1 and RWPE-2 prostate-derived cell lines. In addition, we demonstrated that exogenous ghrelin induced a statistically significant two-fold decrease in GOAT mRNA expression in the PC3 cell line (p<0.05), suggesting that ghrelin could pontentially downregulate its own acylation and, therefore, regulate the balance between ghrelin and desacyl ghrelin. This was not observed, however, in the DU145 and LNCaP prostate cancer cell lines. The GOAT-ghrelin system represents a direct link between ingested nutrients and regulation of ghrelin production and the ghrelin/desacyl ghrelin ratio. Regulation of ghrelin acylation is a potentially attractive and desirable tool for the development of better therapies for a number of pathological conditions where ghrelin has been shown to play a key role. The finding that desacyl ghrelin stimulates cell proliferation in the PC3 prostate cancer cell line, and responds to ghrelin in the same way, suggests that this cell line expresses an alternative ghrelin receptor. Although all the cell lines examined expressed both GHS-R1a and GHS-R1b mRNA, it remains uncertain whether these cell lines express the unidentified alternative ghrelin receptor. It is possible that the varied responses seen could be due to the expression of different ghrelin receptors in different cell lines. In addition to GOAT, prohormone convertases and octanoic acid availability may regulate the production of different peptides from the ghrelin preprohormone. The studies presented in this thesis provide significant new information regarding the roles and mechanisms of action of the preproghrelin-derived peptides, ghrelin, desacyl ghrelin and obestatin, in modulating prostate cancer cell line proliferation. A number of key questions remain to be resolved, however, including the identification of the alternative ghrelin/desacyl ghrelin receptor, the identification of the obestatin receptor, a clarification of the signaling mechanisms which mediate cell proliferation in response to obestatin treatment and a better understanding of the regulation at both the gene and post-translational levels of functional peptide generation. Further studies investigating the role of the ghrelin axis using in vivo prostate cancer models may be warranted. Until these issues are determined, the potential for the ghrelin axis, to be recognised as a novel useful target for therapy for cancer or other pathologies will be uncertain.

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Child abuse and neglect is prevalent and entails significant costs to children, families and society. Teachers are responsible for significant proportions of official notifications to statutory child protection agencies. Hence, their accurate and appropriate reporting is crucial for well-functioning child protection systems. Approximately one-quarter of Australian teachers indicate never detecting a case of child maltreatment across their careers, while a further 13-15% admit to not reporting suspected cases in some circumstances. The detection and reporting of child abuse and neglect are complex decision-making behaviors, influenced by: the nature of the maltreatment itself; the characteristics of the teacher; the school environment; and the broader legislative and policy environment. In this chapter, the authors provide a background to teachers’ involvement in detecting and reporting child abuse and neglect, and an overview of the role of teachers is provided. Results are presented from three Australian studies that examine the unique contributions of: case; teacher; and contextual characteristics to detection and reporting behaviors. The authors conclude by highlighting the key implications for enhancing teacher training in child abuse and neglect, and outline future research directions.

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and sexual violence on the social adjustment of Grade 8 and 9 school children in the state of Tripura, India. The study participants, 160 boys and 160 girls, were randomly selected from classes in eight English and Bengali medium schools in Agartala city, Tripura. Data were collected using a self-administered Semi-structured Questionnaire for Children/Students and a Social Adjustment Inventory which were custom-made for the study based on measures in the extant research adapted for the Indian context. Findings revealed that students experienced physical (21.9%), psychological (20.9%), and sexual (18.1%) violence at home, and 29.7% of the children had witnessed family violence. Boys were more often victims of physical and psychological violence while girls were more often victims of sexual violence. The social adjustment scores of school children who experienced violence, regardless of the nature of the violence, was significantly lower when compared with scores of those who had not experienced violence (p<0.001). Social adjustment was poorer for girls than boys (p<0.001). The study speaks in favour of early detection and intervention for all child maltreatment subtypes and for children exposed to interparental violence, and highlights the crucial role of schools and school psychology in addressing the problem.

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Exceeding the speed limit and driving too fast for the conditions are regularly cited as significant contributing factors in traffic crashes, particularly fatal and serious injury crashes. Despite an extensive body of research highlighting the relationship between increased vehicle speeds and crash risk and severity, speeding remains a pervasive behaviour on Australian roads. The development of effective countermeasures designed to reduce the prevalence of speeding behaviour requires that this behaviour is well understood. The primary aim of this program of research was to develop a better understanding of the influence of drivers’ perceptions and attitudes toward police speed enforcement on speeding behaviour. Study 1 employed focus group discussions with 39 licensed drivers to explore the influence of perceptions relating to specific characteristics of speed enforcement policies and practices on drivers’ attitudes towards speed enforcement. Three primary factors were identified as being most influential: site selection; visibility; and automaticity (i.e., whether the enforcement approach is automated/camera-based or manually operated). Perceptions regarding these enforcement characteristics were found to influence attitudes regarding the perceived legitimacy and transparency of speed enforcement. Moreover, misperceptions regarding speed enforcement policies and practices appeared to also have a substantial impact on attitudes toward speed enforcement, typically in a negative direction. These findings have important implications for road safety given that prior research has suggested that the effectiveness of speed enforcement approaches may be reduced if efforts are perceived by drivers as being illegitimate, such that they do little to encourage voluntary compliance. Study 1 also examined the impact of speed enforcement approaches varying in the degree of visibility and automaticity on self-reported willingness to comply with speed limits. These discussions suggested that all of the examined speed enforcement approaches (see Section 1.5 for more details) generally showed potential to reduce vehicle speeds and encourage compliance with posted speed limits. Nonetheless, participant responses suggested a greater willingness to comply with approaches operated in a highly visible manner, irrespective of the corresponding level of automaticity of the approach. While less visible approaches were typically associated with poorer rates of driver acceptance (e.g., perceived as “sneaky” and “unfair”), participants reported that such approaches would likely encourage long-term and network-wide impacts on their own speeding behaviour, as a function of the increased unpredictability of operations and increased direct (specific deterrence) and vicarious (general deterrence) experiences with punishment. Participants in Study 1 suggested that automated approaches, particularly when operated in a highly visible manner, do little to encourage compliance with speed limits except in the immediate vicinity of the enforcement location. While speed cameras have been criticised on such grounds in the past, such approaches can still have substantial road safety benefits if implemented in high-risk settings. Moreover, site-learning effects associated with automated approaches can also be argued to be a beneficial by-product of enforcement, such that behavioural modifications are achieved even in the absence of actual enforcement. Conversely, manually operated approaches were reported to be associated with more network-wide impacts on behaviour. In addition, the reported acceptance of such methods was high, due to the increased swiftness of punishment, ability for additional illegal driving behaviours to be policed and the salutary influence associated with increased face-to-face contact with authority. Study 2 involved a quantitative survey conducted with 718 licensed Queensland drivers from metropolitan and regional areas. The survey sought to further examine the influence of the visibility and automaticity of operations on self-reported likelihood and duration of compliance. Overall, the results from Study 2 corroborated those of Study 1. All examined approaches were again found to encourage compliance with speed limits, such that all approaches could be considered to be “effective”. Nonetheless, significantly greater self-reported likelihood and duration of compliance was associated with visibly operated approaches, irrespective of the corresponding automaticity of the approach. In addition, the impact of automaticity was influenced by visibility; such that significantly greater self-reported likelihood of compliance was associated with manually operated approaches, but only when they are operated in a less visible fashion. Conversely, manually operated approaches were associated with significantly greater durations of self-reported compliance, but only when they are operated in a highly visible manner. Taken together, the findings from Studies 1 and 2 suggest that enforcement efforts, irrespective of their visibility or automaticity, generally encourage compliance with speed limits. However, the duration of these effects on behaviour upon removal of the enforcement efforts remains questionable and represents an area where current speed enforcement practices could possibly be improved. Overall, it appears that identifying the optimal mix of enforcement operations, implementing them at a sufficient intensity and increasing the unpredictability of enforcement efforts (e.g., greater use of less visible approaches, random scheduling) are critical elements of success. Hierarchical multiple regression analyses were also performed in Study 2 to investigate the punishment-related and attitudinal constructs that influence self-reported frequency of speeding behaviour. The research was based on the theoretical framework of expanded deterrence theory, augmented with three particular attitudinal constructs. Specifically, previous research examining the influence of attitudes on speeding behaviour has typically focussed on attitudes toward speeding behaviour in general only. This research sought to more comprehensively explore the influence of attitudes by also individually measuring and analysing attitudes toward speed enforcement and attitudes toward the appropriateness of speed limits on speeding behaviour. Consistent with previous research, a number of classical and expanded deterrence theory variables were found to significantly predict self-reported frequency of speeding behaviour. Significantly greater speeding behaviour was typically reported by those participants who perceived punishment associated with speeding to be less certain, who reported more frequent use of punishment avoidance strategies and who reported greater direct experiences with punishment. A number of interesting differences in the significant predictors among males and females, as well as younger and older drivers, were reported. Specifically, classical deterrence theory variables appeared most influential on the speeding behaviour of males and younger drivers, while expanded deterrence theory constructs appeared more influential for females. These findings have important implications for the development and implementation of speeding countermeasures. Of the attitudinal factors, significantly greater self-reported frequency of speeding behaviour was reported among participants who held more favourable attitudes toward speeding and who perceived speed limits to be set inappropriately low. Disappointingly, attitudes toward speed enforcement were found to have little influence on reported speeding behaviour, over and above the other deterrence theory and attitudinal constructs. Indeed, the relationship between attitudes toward speed enforcement and self-reported speeding behaviour was completely accounted for by attitudes toward speeding. Nonetheless, the complexity of attitudes toward speed enforcement are not yet fully understood and future research should more comprehensively explore the measurement of this construct. Finally, given the wealth of evidence (both in general and emerging from this program of research) highlighting the association between punishment avoidance and speeding behaviour, Study 2 also sought to investigate the factors that influence the self-reported propensity to use punishment avoidance strategies. A standard multiple regression analysis was conducted for exploratory purposes only. The results revealed that punishment-related and attitudinal factors significantly predicted approximately one fifth of the variance in the dependent variable. The perceived ability to avoid punishment, vicarious punishment experience, vicarious punishment avoidance and attitudes toward speeding were all significant predictors. Future research should examine these relationships more thoroughly and identify additional influential factors. In summary, the current program of research has a number of implications for road safety and speed enforcement policy and practice decision-making. The research highlights a number of potential avenues for the improvement of public education regarding enforcement efforts and provides a number of insights into punishment avoidance behaviours. In addition, the research adds strength to the argument that enforcement approaches should not only demonstrate effectiveness in achieving key road safety objectives, such as reduced vehicle speeds and associated crashes, but also strive to be transparent and legitimate, such that voluntary compliance is encouraged. A number of potential strategies are discussed (e.g., point-to-point speed cameras, intelligent speed adaptation. The correct mix and intensity of enforcement approaches appears critical for achieving optimum effectiveness from enforcement efforts, as well as enhancements in the unpredictability of operations and swiftness of punishment. Achievement of these goals should increase both the general and specific deterrent effects associated with enforcement through an increased perceived risk of detection and a more balanced exposure to punishment and punishment avoidance experiences.

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The standard approach to tax compliance applies the economics-of-crime methodology pioneered by Becker (1968): in its first application, due to Allingham and Sandmo (1972) it models the behaviour of agents as a decision involving a choice of the extent of their income to report to tax authorities, given a certain institutional environment, represented by parameters such as the probability of detection and penalties in the event the agent is caught. While this basic framework yields important insights on tax compliance behavior, it has some critical limitations. Specifically, it indicates a level of compliance that is significantly below what is observed in the data. This thesis revisits the original framework with a view towards addressing this issue, and examining the political economy implications of tax evasion for progressivity in the tax structure. The approach followed involves building a macroeconomic, dynamic equilibrium model for the purpose of examining these issues, by using a step-wise model building procedure starting with some very simple variations of the basic Allingham and Sandmo construct, which are eventually integrated to a dynamic general equilibrium overlapping generations framework with heterogeneous agents. One of the variations involves incorporating the Allingham and Sandmo construct into a two-period model of a small open economy of the type originally attributed to Fisher (1930). A further variation of this simple construct involves allowing agents to initially decide whether to evade taxes or not. In the event they decide to evade, the agents then have to decide the extent of income or wealth they wish to under-report. We find that the ‘evade or not’ assumption has strikingly different and more realistic implications for the extent of evasion, and demonstrate that it is a more appropriate modeling strategy in the context of macroeconomic models, which are essentially dynamic in nature, and involve consumption smoothing across time and across various states of nature. Specifically, since deciding to undertake tax evasion impacts on the consumption smoothing ability of the agent by creating two states of nature in which the agent is ‘caught’ or ‘not caught’, there is a possibility that their utility under certainty, when they choose not to evade, is higher than the expected utility obtained when they choose to evade. Furthermore, the simple two-period model incorporating an ‘evade or not’ choice can be used to demonstrate some strikingly different political economy implications relative to its Allingham and Sandmo counterpart. In variations of the two models that allow for voting on the tax parameter, we find that agents typically choose to vote for a high degree of progressivity by choosing the highest available tax rate from the menu of choices available to them. There is, however, a small range of inequality levels for which agents in the ‘evade or not’ model vote for a relatively low value of the tax rate. The final steps in the model building procedure involve grafting the two-period models with a political economy choice into a dynamic overlapping generations setting with more general, non-linear tax schedules and a ‘cost-of evasion’ function that is increasing in the extent of evasion. Results based on numerical simulations of these models show further improvement in the model’s ability to match empirically plausible levels of tax evasion. In addition, the differences between the political economy implications of the ‘evade or not’ version of the model and its Allingham and Sandmo counterpart are now very striking; there is now a large range of values of the inequality parameter for which agents in the ‘evade or not’ model vote for a low degree of progressivity. This is because, in the ‘evade or not’ version of the model, low values of the tax rate encourages a large number of agents to choose the ‘not-evade’ option, so that the redistributive mechanism is more ‘efficient’ relative to the situations in which tax rates are high. Some further implications of the models of this thesis relate to whether variations in the level of inequality, and parameters such as the probability of detection and penalties for tax evasion matter for the political economy results. We find that (i) the political economy outcomes for the tax rate are quite insensitive to changes in inequality, and (ii) the voting outcomes change in non-monotonic ways in response to changes in the probability of detection and penalty rates. Specifically, the model suggests that changes in inequality should not matter, although the political outcome for the tax rate for a given level of inequality is conditional on whether there is a large or small or large extent of evasion in the economy. We conclude that further theoretical research into macroeconomic models of tax evasion is required to identify the structural relationships underpinning the link between inequality and redistribution in the presence of tax evasion. The models of this thesis provide a necessary first step in that direction.

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Prostate cancer (CaP) is the second leading cause of cancer-related deaths in North American males and the most common newly diagnosed cancer in men world wide. Biomarkers are widely used for both early detection and prognostic tests for cancer. The current, commonly used biomarker for CaP is serum prostate specific antigen (PSA). However, the specificity of this biomarker is low as its serum level is not only increased in CaP but also in various other diseases, with age and even body mass index. Human body fluids provide an excellent resource for the discovery of biomarkers, with the advantage over tissue/biopsy samples of their ease of access, due to the less invasive nature of collection. However, their analysis presents challenges in terms of variability and validation. Blood and urine are two human body fluids commonly used for CaP research, but their proteomic analyses are limited both by the large dynamic range of protein abundance making detection of low abundance proteins difficult and in the case of urine, by the high salt concentration. To overcome these challenges, different techniques for removal of high abundance proteins and enrichment of low abundance proteins are used. Their applications and limitations are discussed in this review. A number of innovative proteomic techniques have improved detection of biomarkers. They include two dimensional differential gel electrophoresis (2D-DIGE), quantitative mass spectrometry (MS) and functional proteomic studies, i.e., investigating the association of post translational modifications (PTMs) such as phosphorylation, glycosylation and protein degradation. The recent development of quantitative MS techniques such as stable isotope labeling with amino acids in cell culture (SILAC), isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM) have allowed proteomic researchers to quantitatively compare data from different samples. 2D-DIGE has greatly improved the statistical power of classical 2D gel analysis by introducing an internal control. This chapter aims to review novel CaP biomarkers as well as to discuss current trends in biomarker research from two angles: the source of biomarkers (particularly human body fluids such as blood and urine), and emerging proteomic approaches for biomarker research.

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Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

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Circulating tumour cells (CTCs) have attracted much recent interest in cancer research as a potential biomarker and as a means of studying the process of metastasis. It has long been understood that metastasis is a hallmark of malignancy, and conceptual theories on the basis of metastasis from the nineteenth century foretold the existence of a tumour "seed" which is capable of establishing discrete tumours in the "soil" of distant organs. This prescient "seed and soil" hypothesis accurately predicted the existence of CTCs; microscopic tumour fragments in the blood, at least some of which are capable of forming metastases. However, it is only in recent years that reliable, reproducible methods of CTC detection and analysis have been developed. To date, the majority of studies have employed the CellSearch™ system (Veridex LLC), which is an immunomagnetic purification method. Other promising techniques include microfluidic filters, isolation of tumour cells by size using microporous polycarbonate filters and flow cytometry-based approaches. While many challenges still exist, the detection of CTCs in blood is becoming increasingly feasible, giving rise to some tantalizing questions about the use of CTCs as a potential biomarker. CTC enumeration has been used to guide prognosis in patients with metastatic disease, and to act as a surrogate marker for disease response during therapy. Other possible uses for CTC detection include prognostication in early stage patients, identifying patients requiring adjuvant therapy, or in surveillance, for the detection of relapsing disease. Another exciting possible use for CTC detection assays is the molecular and genetic characterization of CTCs to act as a "liquid biopsy" representative of the primary tumour. Indeed it has already been demonstrated that it is possible to detect HER2, KRAS and EGFR mutation status in breast, colon and lung cancer CTCs respectively. In the course of this review, we shall discuss the biology of CTCs and their role in metastagenesis, the most commonly used techniques for their detection and the evidence to date of their clinical utility, with particular reference to lung cancer.

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Threats against computer networks evolve very fast and require more and more complex measures. We argue that teams respectively groups with a common purpose for intrusion detection and prevention improve the measures against rapid propagating attacks similar to the concept of teams solving complex tasks known from field of work sociology. Collaboration in this sense is not easy task especially for heterarchical environments. We propose CIMD (collaborative intrusion and malware detection) as a security overlay framework to enable cooperative intrusion detection approaches. Objectives and associated interests are used to create detection groups for exchange of security-related data. In this work, we contribute a tree-oriented data model for device representation in the scope of security. We introduce an algorithm for the formation of detection groups, show realization strategies for the system and conduct vulnerability analysis. We evaluate the benefit of CIMD by simulation and probabilistic analysis.

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Computer worms represent a serious threat for modern communication infrastructures. These epidemics can cause great damage such as financial losses or interruption of critical services which support lives of citizens. These worms can spread with a speed which prevents instant human intervention. Therefore automatic detection and mitigation techniques need to be developed. However, if these techniques are not designed and intensively tested in realistic environments, they may cause even more harm as they heavily interfere with high volume communication flows. We present a simulation model which allows studies of worm spread and counter measures in large scale multi-AS topologies with millions of IP addresses.

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We propose CIMD (Collaborative Intrusion and Malware Detection), a scheme for the realization of collaborative intrusion detection approaches. We argue that teams, respectively detection groups with a common purpose for intrusion detection and response, improve the measures against malware. CIMD provides a collaboration model, a decentralized group formation and an anonymous communication scheme. Participating agents can convey intrusion detection related objectives and associated interests for collaboration partners. These interests are based on intrusion objectives and associated interests for collaboration partners. These interests are based on intrusion detection related ontology, incorporating network and hardware configurations and detection capabilities. Anonymous Communication provided by CIMD allows communication beyond suspicion, i.e. the adversary can not perform better than guessing an IDS to be the source of a message at random. The evaluation takes place with the help of NeSSi² (www.nessi2.de), the Network Security Simulator, a dedicated environment for analysis of attacks and countermeasures in mid-scale and large-scale networks. A CIMD prototype is being built based on the JIAC agent framework(www.jiac.de).

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Anomaly detection compensates shortcomings of signature-based detection such as protecting against Zero-Day exploits. However, Anomaly Detection can be resource-intensive and is plagued by a high false-positive rate. In this work, we address these problems by presenting a Cooperative Intrusion Detection approach for the AIS, the Artificial Immune System, as an example for an anomaly detection approach. In particular we show, how the cooperative approach reduces the false-positive rate of the detection and how the overall detection process can be organized to account for the resource constraints of the participating devices. Evaluations are carried out with the novel network simulation environment NeSSi as well as formally with an extension to the epidemic spread model SIR