107 resultados para hidden Markov model


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Surveillance in wide-area spatial environments is characterised by complex spatial layouts, large state space, and the use of multiple cameras/sensors. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. This requirement is particularly suited to the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN). In this paper, we propose the use of LDPN as the integrated framework for tracking in wide-area environments. We illustrate, with the help of a synthetic tracking scenario, how the parameters of the LDPN can be estimated from training data, and then used to draw predictions and answer queries about unseen tracks at various levels of detail.

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In this paper, we present our system for online context recognition of multimodal sequences acquired from multiple sensors. The system uses Dynamic Time Warping (DTW) to recognize multimodal sequences of different lengths, embedded in continuous data streams. We evaluate the performance of our system on two real world datasets: 1) accelerometer data acquired from performing two hand gestures and 2) NOKIA's benchmark dataset for context recognition. The results from both datasets demonstrate that the system can perform online context recognition efficiently and achieve high recognition accuracy.

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Currently, most human action recognition systems are trained with feature sets that have no missing data. Unfortunately, the use of human pose estimation models to provide more descriptive features also entails an increased sensitivity to occlusions, meaning that incomplete feature information will be unavoidable for realistic scenarios. To address this, our approach is to shift the responsibility for dealing with occluded pose data away from the pose estimator and onto the action classifier. This allows the use of a simple, real-time pose estimation (stick-figure) that does not estimate the positions of limbs it cannot find quickly. The system tracks people via background subtraction and extracts the (possibly incomplete) pose skeleton from their silhouette. Hidden Markov Models modified to handle missing data are then used to successfully classify several human actions using the incomplete pose features.

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Background : Cardiovascular disease is the leading cause of death worldwide. Like many countries, Australia is currently changing its guidelines for cardiovascular disease prevention from drug treatment for everyone with 'high blood pressure' or 'high cholesterol', to prevention based on a patient's absolute risk. In this research, we model cost-effectiveness of cardiovascular disease prevention with blood pressure and lipid drugs in Australia under three different scenarios: (1) the true current practice in Australia; (2) prevention as intended under the current guidelines; and (3) prevention according to proposed absolute risk levels. We consider the implications of changing to absolute risk-based cardiovascular disease prevention, for the health of the Australian people and for Government health sector expenditure over the long term.

Methods : We evaluate cost-effectiveness of statins, diuretics, ACE inhibitors, calcium channel blockers and beta-blockers, for Australian men and women, aged 35 to 84 years, who have never experienced a heart disease or stroke event. Epidemiological changes and health care costs are simulated by age and sex in a discrete time Markov model, to determine total impacts on population health and health sector costs over the lifetime, from which we derive cost-effectiveness ratios in 2008 Australian dollars per quality-adjusted life year.

Results :
Cardiovascular disease prevention based on absolute risk is more cost-effective than prevention under the current guidelines based on single risk factor thresholds, and is more cost-effective than the current practice, which does not follow current clinical guidelines. Recommending blood pressure-lowering drugs to everyone with at least 5% absolute risk and statin drugs to everyone with at least 10% absolute risk, can achieve current levels of population health, while saving $5.4 billion for the Australian Government over the lifetime of the population. But savings could be as high as $7.1 billion if Australia could match the cheaper price of statin drugs in New Zealand.

Conclusions :
Changing to absolute risk-based cardiovascular disease prevention is highly recommended for reducing health sector spending, but the Australian Government must also consider measures to reduce the cost of statin drugs, over and above the legislated price cuts of November 2010.

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Background
Despite many decades of declining mortality rates in the Western world, cardiovascular disease remains the leading cause of death worldwide. In this research we evaluate the optimal mix of lifestyle, pharmaceutical and population-wide interventions for primary prevention of cardiovascular disease.

Methods and Findings

In a discrete time Markov model we simulate the ischaemic heart disease and stroke outcomes and cost impacts of intervention over the lifetime of all Australian men and women, aged 35 to 84 years, who have never experienced a heart disease or stroke event. Best value for money is achieved by mandating moderate limits on salt in the manufacture of bread, margarine and cereal. A combination of diuretic, calcium channel blocker, ACE inhibitor and low-cost statin, for everyone with at least 5% five-year risk of cardiovascular disease, is also cost-effective, but lifestyle interventions aiming to change risky dietary and exercise behaviours are extremely poor value for money and have little population health benefit.

Conclusions
There is huge potential for improving efficiency in cardiovascular disease prevention in Australia. A tougher approach from Government to mandating limits on salt in processed foods and reducing excessive statin prices, and a shift away from lifestyle counselling to more efficient absolute risk-based prescription of preventive drugs, could cut health care costs while improving population health.


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To update and extend a 2006 report on the clinical effectiveness and cost-effectiveness of adefovir dipivoxil (ADV) and pegylated interferon alpha (PEG-alpha) for the treatment of chronic hepatitis B (CHB). Thirteen bibliographic databases were searched including MEDLINE, EMBASE and the Cochrane Library. Searches were run from the beginning of 2005 to September 2007. For the clinical effectiveness review, randomised controlled trials (RCTs) comparing ADV, PEG-alpha-2a and PEG-alpha-2b with currently licensed treatments for CHB, including non-pegylated interferon alpha (IFN-alpha) and lamivudine (LAM), were included. Outcomes included biochemical, histological and virological response to treatment, drug resistance and adverse effects. A systematic review of economic evaluations of antiviral treatments for CHB was conducted. The economic Markov model used in the 2006 report was updated in terms of utility values, discount rates and costs. `

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Despite global declines in the abundance of marine predators, knowledge of foraging ecology, necessary to predict the ecological consequences of large changes in marine predator abundance, remains enigmatic for many species. Given that populations suffering severe declines are of conservation concern, we examined the foraging ecology of southern sea lions (SSL) (Otaria flavescens)-one of the least studied otariids (fur seal and sea lions)-which have declined by over 90 % at the Falkland Islands since the 1930s. Using a combination of biologging devices and stable isotope analysis of vibrissae, we redress major gaps in the knowledge of SSL ecology and quantify patterns of individual specialization. Specifically, we revealed two discrete foraging strategies, these being inshore (coastal) and offshore (outer Patagonian Shelf). The majority of adult female SSL (72 % or n = 21 of 29 SSL) foraged offshore. Adult female SSL that foraged offshore travelled further (92 ± 20 vs. 10 ± 4 km) and dived deeper (75 ± 23 vs. 21 ± 8 m) when compared to those that foraged inshore. Stable isotope analysis revealed long-term fidelity (years) to these discrete foraging habitats. In addition, we found further specialization within the offshore group, with adult female SSL separated into two clusters on the basis of benthic or mixed (benthic and pelagic) dive behavior (benthic dive proportion was 76 ± 9 vs. 51 ± 8 %, respectively). We suggest that foraging specialization in depleted populations such as SSL breeding at the Falkland Islands, are influenced by foraging site fidelity, and could be independent of intraspecific competition. Finally, the behavioral differences we describe are crucial to understanding population-level dynamics, impediments to population recovery, and threats to population persistence.

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Botnets have become major engines for malicious activities in cyberspace nowadays. To sustain their botnets and disguise their malicious actions, botnet owners are mimicking legitimate cyber behavior to fly under the radar. This poses a critical challenge in anomaly detection. In this paper, we use web browsing on popular web sites as an example to tackle this problem. First of all, we establish a semi-Markov model for browsing behavior. Based on this model, we find that it is impossible to detect mimicking attacks based on statistics if the number of active bots of the attacking botnet is sufficiently large (no less than the number of active legitimate users). However, we also find it is hard for botnet owners to satisfy the condition to carry out a mimicking attack most of the time. With this new finding, we conclude that mimicking attacks can be discriminated from genuine flash crowds using second order statistical metrics. We define a new fine correntropy metrics and show its effectiveness compared to others. Our real world data set experiments and simulations confirm our theoretical claims. Furthermore, the findings can be widely applied to similar situations in other research fields.

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Background Human papillomavirus (HPV) vaccines and their widespread adoption have the potential to relieve a large part of the burden of cervical cancer morbidity and mortality, particularly in countries that have low screening rates or, like Japan, lack a cohesive universal screening program. An economic evaluation was conducted to assess the cost-effectiveness of introducing a bivalent HPV vaccination program in Japan from a healthcare perspective. METHODS: A Markov model of the natural history of HPV infection that incorporates both vaccination and screening was developed for Japan. The modelled intervention, a bivalent HPV vaccine with a 100% lifetime vaccine efficacy and 80% vaccine coverage, given to a cohort of 12-year-old Japanese girls in conjunction with the current screening program, was compared with screening alone in terms of costs and effectiveness. A discount rate of 5% was applied to both costs and utilities where relevant. RESULTS: Vaccination alongside screening compared with screening alone is associated with an incremental cost-effectiveness ratio (ICER) of US$20315 per quality-adjusted-life-year gained if 80% coverage is assumed. The ICER at 5% coverage with the vaccine plus screening, compared with screening alone, is US$1158. CONCLUSION: The cost-effectiveness results suggest that the addition of a HPV vaccination program to Japan's cervical cancer screening program is highly likely to prove a cost-effective way to reduce the burden of cervical cancer, precancerous lesions and HPV16/18-related diseases.

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AIMS: School-based psychological interventions encompass: universal interventions targeting youth in the general population; and indicated interventions targeting youth with subthreshold depression. This study aimed to: (1) examine the population cost-effectiveness of delivering universal and indicated prevention interventions to youth in the population aged 11-17 years via primary and secondary schools in Australia; and (2) compare the comparative cost-effectiveness of delivering these interventions using face-to-face and internet-based delivery mechanisms. METHODS: We reviewed literature on the prevention of depression to identify all interventions targeting youth that would be suitable for implementation in Australia and had evidence of efficacy to support analysis. From this, we found evidence of effectiveness for the following intervention types: universal prevention involving group-based psychological interventions delivered to all participating school students; and indicated prevention involving group-based psychological interventions delivered to students with subthreshold depression. We constructed a Markov model to assess the cost-effectiveness of delivering universal and indicated interventions in the population relative to a 'no intervention' comparator over a 10-year time horizon. A disease model was used to simulate epidemiological transitions between three health states (i.e., healthy, diseased and dead). Intervention effect sizes were based on meta-analyses of randomised control trial data identified in the aforementioned review; while health benefits were measured as Disability-adjusted Life Years (DALYs) averted attributable to reductions in depression incidence. Net costs of delivering interventions were calculated using relevant Australian data. Uncertainty and sensitivity analyses were conducted to test model assumptions. Incremental cost-effectiveness ratios (ICERs) were measured in 2013 Australian dollars per DALY averted; with costs and benefits discounted at 3%. RESULTS: Universal and indicated psychological interventions delivered through face-to-face modalities had ICERs below a threshold of $50 000 per DALY averted. That is, $7350 per DALY averted (95% uncertainty interval (UI): dominates - 23 070) for universal prevention, and $19 550 per DALY averted (95% UI: 3081-56 713) for indicated prevention. Baseline ICERs were generally robust to changes in model assumptions. We conducted a sensitivity analysis which found that internet-delivered prevention interventions were highly cost-effective when assuming intervention effect sizes of 100 and 50% relative to effect sizes observed for face-to-face delivered interventions. These results should, however, be interpreted with caution due to the paucity of data. CONCLUSIONS: School-based psychological interventions appear to be cost-effective. However, realising efficiency gains in the population is ultimately dependent on ensuring successful system-level implementation.

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In this paper, we consider daily financial data from various sources (stock market indices, foreign exchange rates and bonds) and analyze their multiscaling properties by estimating the parameters of a Markov-switching multifractal (MSM) model with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the empirical data, we estimate and compare (generalized) Hurst exponents for both empirical data and simulated MSM models. In general, the Lognormal MSM models generate "apparent" long memory in good agreement with empirical scaling provided that one uses sufficiently many volatility components. In comparison with a Binomial MSM specification [11], results are almost identical. This suggests that a parsimonious discrete specification is flexible enough and the gain from adopting the continuous Lognormal distribution is very limited.

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In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal (MSM) model. In order to see how well the estimated model captures the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q=1,2) for both empirical data and simulated data of the MSM model. In most cases the multifractal model appears to generate ‘apparent’ long memory in agreement with the empirical scaling laws.

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The work presented in this paper focuses on fitting of a neural mass model to EEG data. Neurophysiology inspired mathematical models were developed for simulating brain's electrical activity imaged through Electroencephalography (EEG) more than three decades ago. At the present well informative models which even describe the functional integration of cortical regions also exists. However, a very limited amount of work is reported in literature on the subject of model fitting to actual EEG data. Here, we present a Bayesian approach for parameter estimation of the EEG model via a marginalized Markov Chain Monte Carlo (MCMC) approach.