959 resultados para pretest probability
Resumo:
In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.
Resumo:
The article focuses on how the information seeker makes decisions about relevance. It will employ a novel decision theory based on quantum probabilities. This direction derives from mounting research within the field of cognitive science showing that decision theory based on quantum probabilities is superior to modelling human judgements than standard probability models [2, 1]. By quantum probabilities, we mean decision event space is modelled as vector space rather than the usual Boolean algebra of sets. In this way,incompatible perspectives around a decision can be modelled leading to an interference term which modifies the law of total probability. The interference term is crucial in modifying the probability judgements made by current probabilistic systems so they align better with human judgement. The goal of this article is thus to model the information seeker user as a decision maker. For this purpose, signal detection models will be sketched which are in principle applicable in a wide variety of information seeking scenarios.
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At NTCIR-10 we participated in the cross-lingual link discovery (CrossLink-2) task. In this paper we describe our systems for discovering cross-lingual links between the Chinese, Japanese, and Korean (CJK) Wikipedia and the English Wikipedia. The evaluation results show that our implementation of the cross-lingual linking method achieved promising results.
Resumo:
Asthma is an incapacitating disease of the respiratory system, which causes extensive morbidity and mortality worldwide. Asthma affects more than 300 million people globally(Masoli et al. 2004). In Australia, it affects 10.2% of the population (Masoli et al. 2004) and causes 60,000 people to be hospitalised annually. Health care expenditure due to asthma in Australia was $606 million in 2004–2005. There are four primary biological factors that function in the initiation and exacerbation of asthma. Airway inflammation is important as it is often the first response to an airway insult, initiating the three other components: bronchoconstriction, mucus hyper-secretion and hyper-reactivity. The mediators involved in asthma are still not well understood, and current anti-inflammatory corticosteroid treatments are not effective with all asthmatics. As there is currently no cure for asthma, and airway inflammation is the primary component of the disease, it is important that we understand and investigate the mediators of airway inflammation to look for a potential cure and to produce better therapeutics to treat the inflammation. Trefoil factors (TFFs) and secretoglobins (SCGBs) are small secreted proteins involved in the mediation of inflammation and epithelial restitution. TFFs are pro-inflammatory and SCGBs anti-inflammatory by nature. The hypothesis of this study is that in response to induced acute airway inflammation, the expression of TFF1 and TFF3 will increase and expression of SCGB1A1 and SCGB3A2 will decrease in non-asthmatics (N-A), asthmatics medicating with bronchodilators (A-BD) and asthmatics medicating with corticosteroids (A-ST). When comparing the three groups, we expect to see higher expression of the TFFs in the A-BD group compared to the N-A and A-ST groups, indicating that inflammation is mediated by TFFs in asthma and that corticosteroid medication controls their expression as part of the control of inflammation. We expect to see the opposite with SCGBs, with a greater decrease in the A-BD group compared to the other two groups, suggesting that the A-BD group has the least anti-inflammatory activity in response to inflammatory insult. Epigenetic modification plays a role in the regulation of genes that initiate disease states such as inflammatory conditions and cancers. Histone acetylation is one such modification, which involves the acetylation of histones in chromatin by histone acetyltransferases (HATs). This increases the transcription of genes involved with inflammation or enrols histone deacetylases (HDACs) to down-regulate the transcription of inflammatory genes. These HATs and HDACs work in a homeostatic fashion; however, in the event of inflammation, increased HAT activity can stimulate further inflammation, which is believed to be the mechanism involved in some inflammatory diseases. This study hypothesises that in response to inflammation, the expression of HDACs (HDAC1-5) will decrease and the expression of HATs (NCOA1-3, HAT-1 and CREBBP) will increase in all groups. When comparing the expression between the groups, it was expected that a greater decrease in HDACs and a greater increase in HATs will be seen in the A-BD group compared to the other two groups. This would identify histone acetylation as a mechanism involved in the inflammatory condition of asthma and indicate that corticosteroids may treat the inflammation in asthma at least in part by controlling histone acetylation. The aim of the project was to compare the expression of inflammatory genes TFF1, TFF3, SCGB1A1 and SCGB3A2, as well as to compare the gene expression of HDAC1-5, NCOA1-3, HAT-1 and CREBBP within and between N-A (n=15), A-BD (n=15) and A-ST (n=15) groups in response to inflammation. This was performed by collecting airway cells and proteins by sputum induction in three sessions. The sessions were coordinated into an initial baseline collection (SI-1), followed by a second session at least one week later (SI-2) and a third session, six hours after SI-2 to collect a sample containing the resultant acute inflammation caused in SI-2 (SI-3). Analysis of the SI-1 and SI-2 samples in all three groups had high amounts of variability between samples. The samples were taken at least one weak apart and the environmental stimuli on each participant outside of the testing sessions could not be controlled. For this reason, the SI-1 samples were not used for analysis; instead SI-2 and SI-3 samples were compared as they were same-day collections, reducing the probability of differences being due to anything other than the sputum induction. The gene expressions of the TFFs, SCGBs, HDACs and HATs were analysed using real-time PCR. Western blot analysis was performed to analyse the protein concentrations of the TFFs and SCGBs in secreted fractions of the sputum collection. Both the secreted and intracellular protein fractions collected from the sputum inductions for pre- and post-inflammation (SI-2, SI-3) samples of the N-A and A-BD groups were analysed using a proteomic method called iTRAQ. This allowed the comparison of the change in protein expression as a result of airway inflammation in each group. This technique was used as a discovery method to identify novel proteins that are modulated by induced acute airway inflammation. Any proteins of interest would then be further validated and used for future research. Inflammation was achieved in the SI-3 samples of the N-A group with a 21% unit increase in % neutrophils compared to SI-2 (p=0.01). The N-A group had a marked 5.5-fold decrease in HDAC1 gene expression in SI-3 compared to SI-2 (p=0.03). No differences were seen in any of the TFFs, SCGBs or any of the rest of the HDACs and HATs. Western blot data did not display any significant changes in the protein levels of the TFFs and SCGBs analysed. However, non-significant analysis of the data displayed increases in TFF1 and TFF3, and decreases in SCGB1A1 and SCGB3A2 for the majority of SI-3 samples compared to SI-2. The A-BD group also presented a marked increase in neutrophils in the SI-3 samples compared to SI-2 (27% unit increase, p=0.04). The A-BD group had a significant increase in TFF3 and SCGB1A1 gene expression concomitant with induced acute airway inflammation. A 7.3-fold increase in TFF3 (p=0.05) in SI-3 indicated that TFF3 is linked to inflammation in asthmatics. A 2.8-fold increase in SCGB1A1 (p=0.03) indicated that this gene is also up-regulated, suggesting that this SCGB is expressed to try to combat induced acute airway inflammation. No significant changes were seen in any of the other genes analysed. Western blot data did not display any significant changes in the protein levels of the TFFs and SCGBs analysed. However, non-significant analysis of the data displayed an increase in TFF1 and TFF3, and a decrease in SCGB1A1 and SCGB3A2 in SI-3, similar to that seen in the N-A group. The A-ST group was different from the A-BD group, characterised by the use of inhaled corticosteroid medication to treat asthma symptoms. Inhaled corticosteroids are known to treat asthma symptoms through the control of inflammation. Therefore, it was expected that corticosteroid medication would also control the expression of TFFs, SCGBs, HATs and HDACs. Gene expression results only identified a 7.6-fold decrease in HDAC2 expression in SI-3 (p=0.001), which is proposed to be due to the up-regulation of HDAC2 protein that is known to be a function of corticosteroid use. Western blot data did not display any significant changes in the protein levels of the TFFs and SCGBs analysed. The gene expression in SI-2 and SI-3 in each group was compared. When comparing the A-BD group to the N-A group, a 9-fold increase in TFF3 (p=0.008) and a 34-fold increase in SCGB1A1 (p=0.03) were seen in the SI-3 samples. Comparisons of the A-ST group to the N-A group had an increased expression in SI-2 samples for HDAC5 (3.6-fold, p=0.04), NCOA2 (8.5-fold, p=0.04), NCOA3 (17-fold, p=0.01), HAT-1 (36-fold, p=0.003) and CREBBP (13-fold, p=0.001). The SI-3 samples in the A-ST group compared to the N-A group had increased expression for HDAC1 (6.4-fold, p=0.04), HDAC5 (5.2-fold, p=0.008), NCOA2 (9.6-fold, p=0.03), NCOA3 (16-fold, p=0.06), HAT-1 (41-fold, p<0.001) and CREBBP (31-fold, p=0.001). Comparisons of the A-ST group to the A-BD group had SI-2 increases in HDAC1 (3.8-fold, p=0.03), NCOA3 (4.5-fold, p=0.03), HAT-1 (5.3-fold, p=0.01) and CREBBP (23-fold, p=0.001), while SI-3 comparisons saw a decrease in HDAC2 (41-fold, p=0.008) and increases in HAT-1 (4.3-fold, p=0.003) and CREBBP (40-fold, p=0.001). Results showed that TFF3 and SCGB1A1 expression is higher in asthmatics than non-asthmatics and that histone acetylation is more active in the A-ST group than either the N-A or A-BD group, which suggests that histone acetylation activity may be positively correlated with asthma severity. The iTRAQ proteomic analysis of the secreted protein samples identified the SCGB1A1 protein and found it to be decreased in both the N-A and A-BD groups post-inflammation, but significantly so only in the A-BD group. Although no significant results were obtained from the western blot data, both groups displayed a decrease in SCGB1A1 concentration in SI-3 samples, suggesting a correlation with the proteomic data. Only 31 peptides were identified from the secreted samples. The intracellular iTRAQ analysis successfully identified 664 peptides, eight of which had differential expression in association with induced acute airway inflammation. Significant increases were seen in the A-BD group in SI-3 compared to SI-2 than in the N-A group in chloride intracellular channel protein 1, keratin-19, eosinophil cationic protein, calnexin, peroxiredoxin-5, and ATP-synthase delta subunit, while decreases were seen in cystatin-A and mucin-5AC. The iTRAQ analysis was only a discovery measure and further validation must be performed. In summary, the expression of TFFs and SCGBs differed between non-asthmatics and asthmatics. It is clear that TFF3 is active in the airway inflammation associated with asthma as indicated by an increase associated with inflammation in the A-BD group compared to the N-A group. Results for HDAC and HAT genes showed high HAT expression in the A-ST group compared to the N-A and A-BD groups, suggesting that histone acetyltransferases may be responsible for the characteristic unregulated inflammatory symptoms of asthmatics taking corticosteroids. Interestingly, corticosteroid medication did not seem to silence the expression of the analysed HAT genes, which indicates that corticosteroids may not control inflammation by direct regulation of HATs, but instead by competition, most probably with HDAC2 protein. As a discovery tool, iTRAQ is a potent method to both identify and compare the concentration of proteins between samples. The method is a powerful first step into the identification of novel proteins that are regulated in response to different treatments.
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In this article, we investigate experimentally whether people search optimally and how price promotions influence search behaviour. We implement a sequential search task with exogenous price dispersion in a baseline treatment and introduce discounts in two experimental treatments. We find that search behaviour is roughly consistent with optimal search but also observe some discount biases. If subjects do not know in advance where discounts are offered, the purchase probability is increased by 19 percentage points in shops with discounts, even after controlling for the benefit of the discount and for risk preferences. If consumers know in advance where discounts are given, then the bias is only weakly significant and much smaller (7 percentage points).
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The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.
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This paper details the processes and challenges involved in collecting inventory data from smallholder and community woodlots on Leyte Island, Philippines. Over the period from 2005 through to 2012, 253 woodlots at 170 sites were sampled as part of a large multidisciplinary project, resulting in a substantial timber inventory database. The inventory was undertaken to provide information for three separate but interrelated studies, namely (1) tree growth, performance and timber availability from private smallholder woodlots on Leyte Island; (2) tree growth and performance of mixed-species plantings of native species; and (3) the assessment of reforestation outcomes from various forms of reforestation. A common procedure for establishing plots within each site was developed and applied in each study, although the basis of site selection varied. A two-stage probability proportion to size sampling framework was developed to select smallholder woodlots for inclusion in the inventory. In contrast, community-based forestry woodlots were selected using stratified random sampling. Challenges encountered in undertaking the inventory were mostly associated with the need to consult widely before the commencement of the inventory and problems in identifying woodlots for inclusion. Most smallholder woodlots were only capable of producing merchantable volumes of less than 44 % of the site potential due to a lack of appropriate silviculture. There was a clear bimodal distribution of proportion that the woodlots comprised of the total smallholding area. This bimodality reflects two major motivations for smallholders to establish woodlots, namely timber production and to secure land tenure.
Homeostatic epistemology : reliability, coherence and coordination in a Bayesian virtue epistemology
Resumo:
How do agents with limited cognitive capacities flourish in informationally impoverished or unexpected circumstances? Aristotle argued that human flourishing emerged from knowing about the world and our place within it. If he is right, then the virtuous processes that produce knowledge, best explain flourishing. Influenced by Aristotle, virtue epistemology defends an analysis of knowledge where beliefs are evaluated for their truth and the intellectual virtue or competences relied on in their creation. However, human flourishing may emerge from how degrees of ignorance are managed in an uncertain world. Perhaps decision-making in the shadow of knowledge best explains human wellbeing—a Bayesian approach? In this dissertation I argue that a hybrid of virtue and Bayesian epistemologies explains human flourishing—what I term homeostatic epistemology. Homeostatic epistemology supposes that an agent has a rational credence p when p is the product of reliable processes aligned with the norms of probability theory; whereas an agent knows that p when a rational credence p is the product of reliable processes such that: 1) p meets some relevant threshold for belief (such that the agent acts as though p were true and indeed p is true), 2) p coheres with a satisficing set of relevant beliefs and, 3) the relevant set of beliefs is coordinated appropriately to meet the integrated aims of the agent. Homeostatic epistemology recognizes that justificatory relationships between beliefs are constantly changing to combat uncertainties and to take advantage of predictable circumstances. Contrary to holism, justification is built up and broken down across limited sets like the anabolic and catabolic processes that maintain homeostasis in the cells, organs and systems of the body. It is the coordination of choristic sets of reliably produced beliefs that create the greatest flourishing given the limitations inherent in the situated agent.
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Bactrocera dorsalis sensu stricto, B. papayae, B. philippinensis and B. carambolae are serious pest fruit fly species of the B. dorsalis complex that predominantly occur in south-east Asia and the Pacific. Identifying molecular diagnostics has proven problematic for these four taxa, a situation that cofounds biosecurity and quarantine efforts and which may be the result of at least some of these taxa representing the same biological species. We therefore conducted a phylogenetic study of these four species (and closely related outgroup taxa) based on the individuals collected from a wide geographic range; sequencing six loci (cox1, nad4-3′, CAD, period, ITS1, ITS2) for approximately 20 individuals from each of 16 sample sites. Data were analysed within maximum likelihood and Bayesian phylogenetic frameworks for individual loci and concatenated data sets for which we applied multiple monophyly and species delimitation tests. Species monophyly was measured by clade support, posterior probability or bootstrap resampling for Bayesian and likelihood analyses respectively, Rosenberg's reciprocal monophyly measure, P(AB), Rodrigo's (P(RD)) and the genealogical sorting index, gsi. We specifically tested whether there was phylogenetic support for the four 'ingroup' pest species using a data set of multiple individuals sampled from a number of populations. Based on our combined data set, Bactrocera carambolae emerges as a distinct monophyletic clade, whereas B. dorsalis s.s., B. papayae and B. philippinensis are unresolved. These data add to the growing body of evidence that B. dorsalis s.s., B. papayae and B. philippinensis are the same biological species, which poses consequences for quarantine, trade and pest management.
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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.
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Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Resumo:
The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.
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A "self-exciting" market is one in which the probability of observing a crash increases in response to the occurrence of a crash. It essentially describes cases where the initial crash serves to weaken the system to some extent, making subsequent crashes more likely. This thesis investigates if equity markets possess this property. A self-exciting extension of the well-known jump-based Bates (1996) model is used as the workhorse model for this thesis, and a particle-filtering algorithm is used to facilitate estimation by means of maximum likelihood. The estimation method is developed so that option prices are easily included in the dataset, leading to higher quality estimates. Equilibrium arguments are used to price the risks associated with the time-varying crash probability, and in turn to motivate a risk-neutral system for use in option pricing. The option pricing function for the model is obtained via the application of widely-used Fourier techniques. An application to S&P500 index returns and a panel of S&P500 index option prices reveals evidence of self excitation.
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The mean action time is the mean of a probability density function that can be interpreted as a critical time, which is a finite estimate of the time taken for the transient solution of a reaction-diffusion equation to effectively reach steady state. For high-variance distributions, the mean action time under-approximates the critical time since it neglects to account for the spread about the mean. We can improve our estimate of the critical time by calculating the higher moments of the probability density function, called the moments of action, which provide additional information regarding the spread about the mean. Existing methods for calculating the nth moment of action require the solution of n nonhomogeneous boundary value problems which can be difficult and tedious to solve exactly. Here we present a simplified approach using Laplace transforms which allows us to calculate the nth moment of action without solving this family of boundary value problems and also without solving for the transient solution of the underlying reaction-diffusion problem. We demonstrate the generality of our method by calculating exact expressions for the moments of action for three problems from the biophysics literature. While the first problem we consider can be solved using existing methods, the second problem, which is readily solved using our approach, is intractable using previous techniques. The third problem illustrates how the Laplace transform approach can be used to study coupled linear reaction-diffusion equations.
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This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.