1,944 research outputs found
Data for: A tutorial on uncertainty modeling for machine reasoning
No full textMATLAB routines for all numerical examples in the manuscript
A note on the reward function for PHD filters with sensor control
No full textThe context is sensor control for multi-object Bayes filtering in the framework of partially observed Markov decision processes (POMDPs). The current information state is represented by the multi-object probability density function (pdf), while the reward function associated with each sensor control (action) is the information gain measured by the alpha or Rényi divergence. Assuming that both the predicted and updated state can be represented by independent identically distributed (IID) cluster random finite sets (RFSs) or, as a special case, the Poisson RFSs, this work derives the analytic expressions of the corresponding Rényi divergence based information gains. The implementation of Rényi divergence via the sequential Monte Carlo method is presented. The performance of the proposed reward function is demonstrated by a numerical example, where a moving range-only sensor is controlled to estimate the number and the states of several moving objects using the PHD filter. © 2006 IEEE.</p
Modification of PLA-based films by grafting or coating
No full textRecently, the demand for the use of natural polymers in the cosmetic, biomedical, and sanitary sectors has been increasing. In order to meet specific functional properties of the products, usually, the incorporation of the active component is required. One of the main problems is enabling compatibility between hydrophobic and hydrophilic surfaces. Therefore, surface modification is necessary. Poly(lactide) (PLA) is a natural polymer that has attracted a lot ofattention in recent years. It is bio-based, can be produced from carbohydrate sources like corn, and it is biodegradable. The main goal of this work was the functionalization of PLA, inserting antiseptic and anti-inflammatory nanostructured systems based on chitin nanofibrils–nanolignin complexes ready to be used in the biomedical, cosmetics, and sanitary sectors. The specific challenge of this investigation was to increase the interaction between the hydrophobic PLA matrix with hydrophilic chitin–lignin nanoparticle complexes. First, chemical modification via the “grafting from” method using lactide oligomers was performed. Then, active coatings with modified and unmodified chitin–lignin nanoparticle complexes were prepared and applied on extruded PLA-based sheets. The chemical, thermal, and mechanical characterization of prepared samples was carried out and the obtained results were discussed
Adaptive target birth intensity for PHD and CPHD filters
No full textThe standard formulation of the probability hypothesis density (PHD) and cardinalised PHD (CPHD) filters assumes that the target birth intensity is known a priori. In situations where the targets can appear anywhere in the surveillance volume this is clearly inefficient, since the target birth intensity needs to cover the entire state space. This paper presents a new extension of the PHD and CPHD filters, which distinguishes between the persistent and the newborn targets. This extension enables us to adaptively design the target birth intensity at each scan using the received measurements. Sequential Monte-Carlo (SMC) implementations of the resulting PHD and CPHD filters are presented and their performance studied numerically. The proposed measurement-driven birth intensity improves the estimation accuracy of both the number of targets and their spatial distribution
A Metric for Performance Evaluation of Multi-Target Tracking Algorithms
No full textPerformance evaluation of multi-target tracking algorithms is of great practical importance in the design, parameter optimization and comparison of tracking systems. The goal of performance evaluation is to measure the distance between two sets of tracks: the ground truth tracks and the set of estimated tracks. This paper proposes a mathematically rigorous metric for this purpose. The basis of the proposed distance measure is the recently formulated consistent metric for performance evaluation of multi-target filters, referred to as the OSPA metric. Multi-target filters sequentially estimate the number of targets and their position in the state space. The OSPA metric is therefore defined on the space of finite sets of vectors. The distinction between filtering and tracking is that tracking algorithms output tracks and a track represents a labeled temporal sequence of state estimates, associated with the same target. The metric proposed in this paper is therefore defined on the space of finite sets of tracks and incorporates the labeling error. Numerical examples demonstrate that the proposed metric behaves in a manner consistent with our expectations.</p
Bernoulli Forward-Backward Smoothing for Joint Target Detection and Tracking
No full textIn this correspondence, we derive a forward-backward smoother for joint target detection and estimation and propose a sequential Monte Carlo implementation. We model the target by a Bernoulli random finite set since the target can be in one of two "present" or "absent" modes. Finite set statistics is used to derive the smoothing recursion. Our results indicate that smoothing has two distinct advantages over just using filtering: First, we are able to more accurately identify the appearance and disappearance of a target in the scene, and second, we can provide improved state estimates when the target exists.</p
DFIG-Based WECS With Partial-Scale Converter: Efficiency, Cost, and Volume Comparison of SiC-Based and IGBT-Based Converter Solution
No full textThe green goals imposed by many countries and the increasing application of renewable energy systems are bringing power electronics to the center of attention. Of particular interest are the wide band-gap devices, as they offer important benefits when considering the efficiency increase and volume reduction. Consequently, they can be viably adopted in renewable energy sources. In this paper, a 2 MW Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion System (WECS) with a bidirectional partial-scale frequency converter composed of two back-to-back converters is considered. The main contribution of the paper is a result of comprehensive comparisons conducted for the two systems: DFIG WECS based on a Si-IGBT converter and DFIG WECS based on a SiC-MOSFET converter in terms of efficiency, volume, and cost. The performed comparison is also a fair comparison, being the selected modules are of the same power ratings. In this way, the previously unspecified but valuable decision-making process regarding the selection of power electronic modules suitable for DFIGs is facilitated. The thermal analysis has been implemented in PLECS, together with the converter control. The realistic libraries obtained from the manufacturers have been included for different power modules. The findings highlight the advantages of employing the Silicon Carbide-based converter in terms of minimizing the size and cost of passive components. They also offer insights on what is needed in order to make the Silicon Carbide solution the absolute best candidate
Bernoulli Particle/Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty
No full textThis work presents sequential Bayesian detection and estimation methods for nonlinear dynamic stochastic systems using measurements affected by three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. Following Mahler’s framework for information fusion, the paper develops the optimal Bayes filter for this problem in the form of the Bernoulli filter for interval measurements. Two numerical implementations of the optimal filter are developed. The first is the Bernoulli particle filter (PF), which turns out to require a large number of particles in order to achieve a satisfactory performance. For the sake of reduction in the number of particles, the paper also develops an implementation based on box particles, referred to as the Bernoulli Box-PF. A box particle is a random sample that occupies a small and controllable rectangular region of non-zero volume in the target state space. Manipulation of boxes utilizes the methods of interval analysis. The two implementations are compared numerically and found to perform remarkably well: the target is reliably detected and the posterior probability density function of the target state is estimated accurately. The Bernoulli Box-PF, however, when designed carefully, is computationally more efficient
Gender differences in clinical features and quality of life of patients with axial spondyloarthritis and psoriatic arthritis
No full textObjective: The aim of the current study was to compare the clinical and treatment characteristics and dimensions of health-related quality of life between female and male patients with axial spondyloarthritis (SpA) and psoriatic arthritis (PsA). Methods: The present study is cross-sectional and comprises 119 patients with axial SpA and 198 patients with PsA. Clinical data were collected by standardized and self-reported instruments. Disease activity was evaluated by the Ankylosing Spondylitis Disease Activity Score with C-reactive protein and the Disease Activity in PSoriatic Arthritis (for SpA and PsA, respectively). Health-related quality of life was assessed with the Medical Outcomes Study 36-item Short Form Survey. Patients were stratified by gender, and the socio-demographic, clinical, and quality-of-life data were compared. Results: Women with axial SpA and PsA had significantly lower education (p<0.001, p=0.004, respectively) and higher disease activity (p<0.001, p=0.003, respectively). Female patients with axial SpA were more frequently under second-line therapy (p=0.026) and glucocorticoid treatment (p=0.005), while women with PsA had more radiographic progression (p=0.006). Female patients with axial SpA and PsA had worse scores in the dimensions of quality of life regarding physical role, bodily pain, vitality, and mental health. Women with axial SpA had lower scores in general health, while women with PsA had lower scores in physical and social functioning. Conclusions: Women with axial SpA and PsA had worse scores than men in most clinical and treatment characteristics and health-related quality of life dimensions
A Box Particle Filter for Stochastic and Set-theoretic Measurements with Association Uncertainty
No full textThis work develops a novel estimation approach for nonlinear dynamic stochastic systems by combining the sequential Monte Carlo method with interval analysis. Unlike the common pointwise measurements, the proposed solution is for problems with interval measurements with association uncertainty. The optimal theoretical solution can be formulated in the framework of random set theory as the Bernoulli filter for interval measurements. The straightforward particle filter implementation of the Bernoulli filter typically requires a huge number of particles since the posterior probability density function occupies a significant portion of the state space. In order to reduce the number of particles, without necessarily sacrificing estimation accuracy, the paper investigates an implementation based on box particles. A box particle occupies a small and controllable rectangular region of non-zero volume in the target state space. The numerical results demonstrate that the filter performs remarkably well: both target state and target presence are estimated reliably using a very small number of box particles
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