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A case study of a "Dragon-King": The 1999 Venezuelan catastrophe

EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS 2012年第1期205卷 131-146页

作者： Sueveges, M. Davison, A. C. Univ Geneva ISDC Data Ctr Astrophys CH-1290 Versoix Switzerland Ecole Polytech Fed Lausanne EPFL FSB MATHAA STAT CH-1015 Lausanne Switzerland

We describe a failure of standard extremal models to account for a catastrophic rainfall event in the coastal regions of Venezuela on 14-16 December 1999, due both to inaccurate tail modelling and to an inadequate treatment of clusters of rare events. We investigate this failure, using a Dirichlet mixture model to approximate a form of moving maximum process that should provide accurate models for wide classes of extremal behaviour. This so-called M3-Dirichlet model may be fitted using an EM algorithm, and provides a reasonable explanation for the properties of the data, in terms of a seasonally-varying mixture of types of extreme rainfall clusters.

关键词： Venezuelan Dragon-King catastrophe catastrophes Venezuelan expectation-maximisation algorithm extremum values Venezuela Clusters Case studies Mixture models

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Broadband Field Directionality Mapping with Spatially-Aliased Arrays

Broadband Field Directionality Mapping with Spatially-Aliase...

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IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM)

作者： Odom, Jonathan L. Krolik, Jeffrey L. Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

ISBN: (纸本)9781467310710

This paper addresses the problem of broadband spatial spectrum estimation using multiple spatially-aliased arrays. Unlike previous approaches using sparse arrays, the signals here are assumed to be uncorrelated between multiple arrays which, in fact, may be receiving the same source during different time intervals. This paper presents an approach which jointly exploits spatial-orientation and broadband temporal diversity in order to estimate the spatial spectrum even when the inter-element spacing within each array is greater than a half-wavelength. A dynamical model for the spatial spectrum is employed to formulate a maximum likelihood estimate, which is computed via a recursive version of the expectation-maximization algorithm using data from different arrays. Simulation results are presented to demonstrate the ability of the method to suppress spatial grating lobes and increase low SNR target detection in an interference dominated environment.

关键词： maximum likelihood estimation arrays Spectrum Analysis broadband expectation-maximisation algorithm time diversity Time intervals

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Impact of tracer distribution, count level, iterations and post-smoothing on PET quantification using a variously weighted least squares algorithm

Impact of tracer distribution, count level, iterations and p...

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IEEE Nuclear Science Symposium / Medical Imaging Conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Letourneau, Etienne Verhaeghe, Jeroen Reader, Andrew J.

ISBN: (纸本)9781467320306;9781467320283

This work is a task-oriented quantitative analysis to assess the best range of reconstruction algorithms parameters which are most suited for quantitative PET imaging of the brain. Starting from a general iterative weighted-least squares objective function, well-known methods such as the Maximum Likelihood expectation Maximization (MLEM), the Image Space Reconstruction algorithm (ISRA) and related techniques are obtained. A detailed analysis was done for single-frame imaging as well as a comprehensive study on the impact of post-smoothing by applying a Gaussian convolution kernel at each and every possible post-reconstruction iteration number in order to achieve the lowest mean absolute error (MAE). It has been clearly demonstrated that an appropriate choice of iteration number and post-smoothing level makes most algorithms deliver similar MAE within an interval of 5%, with a considerable reduction of the MAE in comparison to non-optimized reconstructions. Also, reconstruction method performance was influenced by the total number of counts and the activity distribution, meaning that each radiopharmaceutical is not always best reconstructed by the same method. Broadly speaking, MLEM with a point spread function (PSF), ISRA PSF with smoothed expected data as weighting factors and filtered backprojection (FBP), when applied with a suitable level of post-smoothing, were the methods offering the best quantitative images and from these three methods, FBP offered the most robust performance for a broad range of post-smoothing levels. An appropriate choice of iteration number and post-smoothing level for a task-oriented analysis significantly lowered the MAE in comparison with the standard practice of using default fixed numbers of iterations and/or post-smoothing.

关键词： Gaussian distribution brain convolution expectation-maximisation algorithm image reconstruction iterative methods least squares approximations medical image processing positron emission tomography radioactive tracers

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Impact of Truncation to the Reconstruction with a Small Number of Projections

Impact of Truncation to the Reconstruction with a Small Numb...

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IEEE Nuclear Science Symposium / Medical Imaging Conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Mao, Yanfei Zeng, Gengsheng L. Univ Utah Utah Ctr Adv Imaging Res UCAIR Salt Lake City UT 84112 USA Univ Utah Utah Ctr Adv Imaging Res UCAIR Dept Radiol Salt Lake City UT 84108 USA

ISBN: (纸本)9781467320306;9781467320283

Dedicated cardiac SPECT systems have the advantage of high speed and sensitivity at no loss or even a gain in resolution. T he purpose of this paper is to investigate segmented parallel-hole collimation, develop a tailored Maximum-Likelihood expectation-Maximization (ML-EM) algorithm for reconstructing truncated projections, and find the minimal number of view-angles required. We simulated and compared three image configurations, including two segmented-parallel-hole detectors based on the conventional and large detectors, and one small multi-detector. To study the effects of truncation and the number of angular sampling, the number of view-angles was varied from 10 to 60 and the truncation degree increased from 91% to 95%. For each view-angle, the root-mean-square error (RMSE) between the reconstructed image and the phantom was calculated and used to give a measure of the accuracy of the reconstructions. Distortion was observed from the shape difference maps of the heart. A tailored ML-EM algorithm was used in the reconstruction, wherein the true-projection to forward-projection ratios outside of FOV were set to one instead of zero before backprojection. Finally, an NCAT phantom and GAT E Monte Carlo simulation tool were used to verify the conclusions. Computer simulation results show that truncation has little effect on the reconstructed images when sufficient view angles are provided, while it affects the reconstruction with few number of views in terms of reducing contrast and introducing bias to the reconstructions. Based on visual inspection only, 10 view-angles is sufficient to reconstruct the image without shape distortion. To reconstruct both value and shape correctly, 20 view-angles is the minimum requirement for truncated projections. Two segmented conventional detectors are sufficient to reconstruct the image without distortion. Uniform angular sampling gives a considerable improvement in the image quality, but a small rotation is required.

关键词： Monte Carlo methods cardiology expectation-maximisation algorithm image reconstruction image sampling image segmentation mean square error methods medical image processing phantoms single photon emission computed tomography

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Reconstruction of Dose Distribution in In-beam PET for Carbon Therapy

Reconstruction of Dose Distribution in In-beam PET for Carbo...

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IEEE Nuclear Science Symposium / Medical Imaging Conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Kim, Kwangdon Bae, Seungbin Lee, Kisung Chung, Yonghyun An, Sujung Joung, Jinhun Korea Univ Dept Radiol Sci Seoul 136793 South Korea Yonsei Univ Dept Radiol Sci Wonju 220-710 South Korea Nucare Med Syst Inc Seoul 136693 South Korea

ISBN: (纸本)9781467320306;9781467320283

There are two main artifacts in reconstructed images from in-beam positron emission tomography(PET). Unlike generic PET, in-beam PET uses the annihilation photons which occur during heavy ion therapy. Therefore, the geometry of in-beam PET is not a full ring, but a partial ring in order for the hardrons to arrive the tumor without penetration of detector blocks. The partial ring, however, causes truncation in projection data, due to an absence of detector modules in the openings. The other is ring artifact caused by the gaps between detector modules which can be also founded in generic PET. In this study, we aim to investigate the effect of gaps in reconstructed images and propose possible solutions to compensate the artifacts. We acquired the data by GATE v6.1 with initial ion energies 170,290, 350AMeV of carbon beams. Each detector module consists of a 13 by 13 LYSO crystal array. The dimension of a crystal was 4mm * 4mm * 20 mm and the radius of inner circle of the gantry was 15cm. In case of truncation error, we proposed to get prior knowledge of the location where annihilations occur. Similar to time-of-flight PET reconstruction, we applied a Gaussian distribution to system matrix, through the width of hardron beams in our back-projection routine. Then expectation maximization(EM) updates were performed iteratively. In case of the latter, to fill the gaps, we used the iterative discrete-cosine transform(DCT) domain method proposed by Uygar Tuna, Sari Peltonen, and Ulla Ruotsalainen. The results show that the proposed method can compensate to some extent the error caused by insufficient angle coverage and we can see the path of hardron beam by proposed method. However, we found other artifacts induced beyond the Bragg peak positions the number of iterations increased. We will improve the proposed algorithm to get more accurate dose distribution.

关键词： Gaussian distribution carbon discrete cosine transforms dosimetry expectation-maximisation algorithm image reconstruction ion beam applications medical image processing positron emission tomography radiation therapy tumours

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Data-Driven Quality Monitoring and Fault Detection for Multimode Nonlinear Processes

Data-Driven Quality Monitoring and Fault Detection for Multi...

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51st IEEE Annual Conference on Decision and Control (CDC)

作者： Haghani, Adel Ding, Steven X. Esch, Jonas Hao, Haiyang Univ Duisburg Essen Inst Automat Control & Complex Syst AKS D-47057 Duisburg Germany

ISBN: (纸本)9781467320665

This paper addresses the problem of quality monitoring and fault detection in nonlinear processes which are working in different operating points. For such processes the statistical model which is obtained from process data is different from one operating point to another, due to nonlinearities and set-point changes. Therefore the classical methods for quality monitoring and fault detection, e. g. partial least squares (PLS), may not be suitable. To this end, a new approach is proposed based on the modeling of nonlinear process as a piecewise linear parameter varying system, considering the behavior of the plant in each operating point as linear time invariant with different parameters in each operating point. The expectation-maximization (EM) algorithm is used to model the process as a finite mixture of Gaussian components and based on the identified model a Bayesian inference strategy is developed to detect the faults which influence the product quality. Finally, the usefulness of the proposed method is demonstrated on a laboratory continuous stirred tank heater (CSTH) setup.

关键词： Gaussian processes belief networks control nonlinearities expectation-maximisation algorithm fault diagnosis heating elements industrial plants inference mechanisms least squares approximations nonlinear control systems piecewise linear techniques product quality quality control statistical analysis tanks (containers) variable structure systems

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Estimating the number of Active Flows from Sampled Packets

Estimating the number of Active Flows from Sampled Packets

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13th IEEE/IFIP Network Operations and Management Symposium

作者： Cheng, Guang Southeast Univ Sch Comp Sci & Engn Nanjing 210096 Peoples R China

ISBN: (纸本)9781467302685

A flow is active during a measurement period if it sends at least one packet. It is essential to control resource consumption in network monitoring by traffic sampling, so most high-end routers provide sampling network traffic function. The number of original flow is an important metrics to many network applications such as congestion control and network security. In this paper, we present a EUF algorithm that can accurately infer the number of original flow from the sampled packet traffic. Using the EUF algorithm, the number of unsampled flows can be estimated by an iteration method based on random sampling, and then the number of original flows can be precisely estimated according to both the number of the sampled flows and the unsampled flow. The EUF algorithm is also compared with the EM algorithm using multiple traffic traces collected from a Tier-1 ISP backbone networks. The result shows that the EUF algorithm is superior to EM and can provide highly accurate estimation on the number of the original flow.

关键词： Packet Traffic expectation-maximisation algorithm network applications Flow Network security Resource utilization highly accurate Random sampling sampling network

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Median Solution and Noise Sorting, a Reconstruction algorithm for Emission Tomography with Large Hole Collimator

Median Solution and Noise Sorting, a Reconstruction Algorith...

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IEEE Nuclear Science Symposium / Medical Imaging Conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Jeanguillaume, Christian Bouali, Ines Maros, Istvan Faurie, Julia Univ Angers LISA Rue Notre Dame Lac F-49000 Angers France Univ Pannonia H-8200 Veszprem Hungary

ISBN: (纸本)9781467320306;9781467320283

SPECT (Single Photon Emission Computerized Tomography) presents poor performances in term of sensitivity and spatial resolution. The bottleneck of the process is due to the use of thin hole collimators. Collimators with large and long holes have been proposed (CACAO), but they involve a difficult inverse problem. OSEM (Ordered Subset expectation Maximization) has been extensively used with success in conventional Thin Hole Collimator SPECT (THC-SPECT). Unfortunately this algorithm presents some limitations, when applied to the CACAO problem. We developed an algorithm based on the search for a median solution. The first publication describing this algorithm was limited to unrealistic small size problems (6x6 pixels). We present here a dualisation approach, which allows us to solve larger problems. Results on simulations for a 64x64 pixels size problem are given. Comparisons of the same problems treated by the OSEM approach are given.

关键词： collimators expectation-maximisation algorithm image denoising image reconstruction image resolution inverse problems medical image processing single photon emission computed tomography

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Compressed sensing with sparse, structured matrices

Compressed sensing with sparse, structured matrices

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50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

作者： Angelini, Maria Chiara Ricci-Tersenghi, Federico Kabashima, Yoshiyuki Univ Roma La Sapienza Dip Fis Ple Aldo Moro 5 I-00185 Rome Italy Tokyo Inst Technol Dept Comp Intelligence & Syst Sci Yokohama Kanagawa Japan

ISBN: (纸本)9781467345392;9781467345378

In the context of the compressed sensing problem, we propose a new ensemble of sparse random matrices which allow one (i) to acquire and compress a rho(0)-sparse signal of length N in a time linear in N and (ii) to perfectly recover the original signal, compressed at a rate alpha, by using a message passing algorithm (expectation Maximization Belief Propagation) that runs in a time linear in N. In the large N limit, the scheme proposed here closely approaches the theoretical bound rho(0) = alpha, and so it is both optimal and efficient (linear time complexity). More generally, we show that several ensembles of dense random matrices can be converted into ensembles of sparse random matrices, having the same thresholds, but much lower computational complexity.

关键词： computational complexity expectation-maximisation algorithm signal reconstruction sparse matrices

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Implementation of LS, MMSE and SAGE Channel Estimators for Mobile MIMO-OFDM

Implementation of LS, MMSE and SAGE Channel Estimators for M...

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46th Asilomar Conference on Signals, Systems and Computers

作者： Ketonen, Johanna Juntti, Markku Ylioinas, Jari Cavallaro, Joseph R. Univ Oulu Ctr Wireless Commun SF-90100 Oulu Finland Nokia Siemens Networks Oulu Finland Rice Univ Houston TX 77251 USA

ISBN: (纸本)9781467350518

The use of decision directed (DD) channel estimation in a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) downlink receiver is studied in this paper. The 3GPP long term evolution (LTE) based pilot structure is used as a benchmark. The space-alternating generalized expectation-maximization (SAGE) algorithm is used to improve the performance from that of the pilot symbol based least-squares (LS) channel estimator. The DD channel estimation improves the performance with high user velocities, where the pilot symbol density is not sufficient. It can also be used to reduce the pilot overhead without any performance degradation. Minimum mean square error (MMSE) filtering can also be used in estimating the channel in between pilot symbols. The pilot based LS, MMSE and the SAGE channel estimators are implemented and the performance-complexity trade-offs are studied.

关键词： 3G mobile communication Long Term Evolution MIMO communication OFDM modulation channel estimation computational complexity expectation-maximisation algorithm least mean squares methods radio links radio receivers wireless channels

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