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An EM algorithm for dynamic estimation of interfacial boundary in stratified flow of immiscible liquids using EIT

FLOW MEASUREMENT AND INSTRUMENTATION 2011年第6期22卷 517-528页

作者： Khambampati, Anil Kumar Kim, Sin Kim, Kyung Youn Jeju Natl Univ Dept Elect Engn Cheju 690756 South Korea Jeju Natl Univ Appl Radiol Sci Res Inst Cheju 690756 South Korea Jeju Natl Univ Dept Nucl & Energy Engn Cheju 690756 South Korea

Estimation of interfacial boundary between two immiscible liquids in two-phase flows through pipe line provides information about the flow characteristics and thus can aid in design and monitoring of the flow process. The interfacial boundary can be represented in several ways, one such method is the front point approach. Front points describe the location and the shape of the interfacial boundary separating the immiscible liquids. During the flow process, due to fluctuations the interfacial boundary and so the front points which describe the boundary changes with time. The time-varying interfacial boundary can be estimated using dynamic inverse algorithms based on Kalman filter. However, algorithms based on Kalman filter require complete knowledge of model parameters (initial states, state transition matrix, and noise covariance matrices) for implementation. In processes involving complex flow pattern such as two-phase flows, it is difficult to represent the model parameters in a prior form. This uncertainty in model parameters causes suboptimal performance of the Kalman type filters. In this paper, we employ expectation maximization algorithm (EM) to estimate model parameters along with the interfacial boundary using electrical impedance tomography (EIT). The estimation of model parameters reduces the modeling uncertainty and thus results in improving the tracking of interfacial boundary. Numerical and experimental studies are performed to validate the performance of the proposed method. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Electrical impedance tomography Immiscible liquids Dynamic estimation Kalman filter expectation maximization algorithm

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4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening

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JOURNAL OF CHEMINFORMATICS 2011年第1期3卷 1-17页

作者： Jahn, Andreas Rosenbaum, Lars Hinselmann, Georg Zell, Andreas Univ Tubingen Ctr Bioinformat Tubingen ZBIT D-72076 Tubingen Germany

Background: The performance of 3D-based virtual screening similarity functions is affected by the applied conformations of compounds. Therefore, the results of 3D approaches are often less robust than 2D approaches. The application of 3D methods on multiple conformer data sets normally reduces this weakness, but entails a significant computational overhead. Therefore, we developed a special conformational space encoding by means of Gaussian mixture models and a similarity function that operates on these models. The application of a model-based encoding allows an efficient comparison of the conformational space of compounds. Results: Comparisons of our 4D flexible atom-pair approach with over 15 state-of-the-art 2D- and 3D-based virtual screening similarity functions on the 40 data sets of the Directory of Useful Decoys show a robust performance of our approach. Even 3D-based approaches that operate on multiple conformers yield inferior results. The 4D flexible atom-pair method achieves an averaged AUC value of 0.78 on the filtered Directory of Useful Decoys data sets. The best 2D- and 3D-based approaches of this study yield an AUC value of 0.74 and 0.72, respectively. As a result, the 4D flexible atom-pair approach achieves an average rank of 1.25 with respect to 15 other state-of-the-art similarity functions and four different evaluation metrics. Conclusions: Our 4D method yields a robust performance on 40 pharmaceutically relevant targets. The conformational space encoding enables an efficient comparison of the conformational space. Therefore, the weakness of the 3D-based approaches on single conformations is circumvented. With over 100,000 similarity calculations on a single desktop CPU, the utilization of the 4D flexible atom-pair in real-world applications is feasible.

关键词： Virtual Screening expectation maximization algorithm Conformational Space Optimal Assignment Conformational Ensemble

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EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data

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GENOME BIOLOGY 2011年第5期12卷 1-14页

作者： Miller, Christopher S. Baker, Brett J. Thomas, Brian C. Singer, Steven W. Banfield, Jillian F. Univ Calif Berkeley Dept Earth & Planetary Sci Berkeley CA 94720 USA Univ Calif Berkeley Lawrence Berkeley Lab Div Earth Sci Berkeley CA 94720 USA Joint BioEnergy Inst Deconstruct Div Emeryville CA 94660 USA Univ Calif Berkeley Dept Environm Sci Policy & Management Berkeley CA 94720 USA

Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at https://***/csmiller/EMIRGE.

关键词： Microbial Community Reference Sequence Acid Mine Drainage expectation maximization algorithm Short Read

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Doubly selective channel estimation for subband OFDMA using basis expansion models

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Science China(Information Sciences) 2011年第10期54卷 2113-2123页

作者： CHEN DongHua & QIU HongBing School of Telecommunications Engineering,Xidian University,Xi’an 710071,China School of Telecommunications Engineering Xidian University Xi’an China

This letter considers the channel estimation for subband orthogonal frequency division multiple access (OFDMA) operating over highly time-frequency selective (i.e.,doubly selective) *** on general basis expansion model,two expectation maximization-type channel estimation methods are proposed for subband OFDMA in order to overcome channel time-frequency *** proposed method is compared with conventional approach and is shown to be superior to the conventional one.

关键词： orthogonal frequency division multiple access channel estimation basis expansion model expectation maximization algorithm time-frequency selectivity

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A Note on Mixture Bivariate Model

A Note on Mixture Bivariate Model

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International Conference on Graphic and Image Processing (ICGIP)

作者： Cao, Hanwen Tian, Wei Deng, Chengzhi Nanchang Inst Technol Dept Sci Nanchang Peoples R China Nanchang Inst Technol Sch Informat Engn Nanchang Jiangxi Peoples R China

ISBN: (纸本)9780819489326

L. Sendur and I. W. Selesnick suggest four jointly non-Gaussian bivariate models to characterize the dependency between a coefficient and its parent, and respectively derive the corresponding MAP estimators based on noisy wavelet coefficients in detail in [6]. Among the four models, the second is a mixture model and it is quite complicated to evaluate parameters, so L. Sendur and I. W. Selesnick didn't give a concrete method. In this letter, a concrete mixture bivariate model will be described by drawing inspiration from Model 2. expectation maximization (EM) algorithm is employed to find the parameters of new model. The simulation results show that the values of PSNR have a bit improvement compared with Model 1. The results can be viewed as a supplementary of model 2 in [6].

关键词： Image denoising Mixture bivariate model Bayesian estimator expectation maximization algorithm

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Multi-state Travel Time Reliability Model: Impact of Incidents on Travel Time Reliability

Multi-state Travel Time Reliability Model: Impact of Inciden...

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14th International IEEE Conference on Intelligent Transportation Systems (ITSC)

作者： Park, Sangjun Rakha, Hesham Guo, Feng Virginia Tech Transportat Inst Ctr Sustainable Mobil Dept Civil Engn Blacksburg VA 24061 USA Virginia Tech Dept Stat Blacksburg VA 24061 USA

ISBN: (纸本)9781457721977

This paper attempts to quantify the impact of traffic incidents on travel time reliability using a newly proposed multi-state travel time reliability model. Given that the multi-state travel time reliability model provides significantly better fits when compared to using a single-mode density function, it is possible to quantify the incident impacts more accurately. In order to obtain travel times, the study simulates weekday traffic on a section of I-66 over 17 days, once with incidents and once without them, using the INTEGRATION microscopic traffic simulation software. The simulated travel time data sets are then used to fit a three-state travel time reliability model (three normal distributions) to calibrate the parameters of the density function using the expectation maximization (EM) algorithm. The study demonstrates that incidents do not introduce an additional component distribution when congestion has already onset;instead they increase the mean travel time and variability in travel times for the congested conditions. For instance, the 90th percentile travel time of the second component distribution increases by up to 93 percent. Additionally, the study addresses technical issues related to the calibration and interpretation of the model from a practical standpoint.

关键词： Calibration Data models Delay Density functional theory Reliability Road transportation Vehicles calibration density function expectation maximization algorithm expectation-maximisation algorithm integration microscopic traffic simulation multistate trave

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Unsupervised Color Image Segmentation by Clustering into Multivariate Gaussians

Unsupervised Color Image Segmentation by Clustering into Mul...

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5th International Conference on Information Processing (ICIP 2011)

作者： Raj, Jobin Govindan, V. K. Natl Inst Technol Calicut Dept Comp Sci & Engn Calicut Kerala India

ISBN: (纸本)9783642227851

An Unsupervised Color Image Segmentation algorithm by using Finite Gaussian Mixture Model (GMM) is proposed in this paper. The parameters of GMM are estimated using expectation maximization (EM) algorithm. A novel technique for initializing the EM algorithm is presented. The algorithm runs in two stages. The first stage performs an initial segmentation which initializes the EM algorithm. The second stage is the parameter estimation phase using EM algorithm. The scheme is computationally efficient in terms of space and time complexity.

关键词： expectation maximization algorithm Gaussian Mixture Model Image Segmentation Model-based Segmentation Multivariate Gaussian Distribution

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Traffic Speed Forecasting by Mixture of Experts

Traffic Speed Forecasting by Mixture of Experts

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14th International IEEE Conference on Intelligent Transportation Systems (ITSC)

作者： Coric, Vladimir Wang, Zhuang Vucetic, Slobodan Temple Univ Philadelphia PA 19122 USA Siemens Res Corp Princeton NJ 08540 USA

ISBN: (纸本)9781457721977

Traffic speed is one of the most important quantities for travel information systems. Accurate speed forecasting can help in trip planning by allowing travelers to avoid the congested routes, either by choosing the alternative routes or by changing the departure time. It is also helpful for traffic monitoring, control, and planning. An important feature of traffic is that it consists of free flow and congested regimes, which have significantly different properties. Training a single traffic speed predictor for both regimes typically results in suboptimal accuracy. To address this problem, a mixture of experts algorithm which consists of two regime-specific linear predictors and a decision tree gating function was developed. A generalized expectation maximization algorithm was used to train the linear predictors and the decision tree. The proposed algorithm was evaluated on a 5-mile stretch of I35 highway in Minneapolis containing 10 single loop detector stations, with prediction horizons ranging from 5 minutes to one hour ahead. Experimental results showed that mixture of experts approach outperforms several popular benchmark approaches.

关键词： Forecasting Linear regression Markov processes Prediction algorithms Regression tree analysis Road transportation decision tree decision tree gating function decision trees expectation maximization algorithm expectation-maximisation algorithm experts algo

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Fault reconnaissance agent for sensor networks

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MOBILE INFORMATION SYSTEMS 2010年第3期6卷 229-247页

作者： Shakshuki, Elhadi M. Xing, Xinyu Sheltami, Tarek R. Acadia Univ Jodrey Sch Comp Sci Wolfville NS B4P 2R6 Canada Univ Colorado Dept Comp Sci Boulder CO 80309 USA King Fahd Univ Petr & Minerals Dept Comp Engn Dhahran 31261 Saudi Arabia

One of the key prerequisite for a scalable, effective and efficient sensor network is the utilization of low-cost, low-overhead and high-resilient fault-inference techniques. To this end, we propose an intelligent agent system with a problem solving capability to address the issue of fault inference in sensor network environments. The intelligent agent system is designed and implemented at base-station side. The core of the agent system - problem solver - implements a fault-detection inference engine which harnesses expectation maximization (EM) algorithm to estimate fault probabilities of sensor nodes. To validate the correctness and effectiveness of the intelligent agent system, a set of experiments in a wireless sensor testbed are conducted. The experimental results show that our intelligent agent system is able to precisely estimate the fault probability of sensor nodes.

关键词： Management intelligent agents expectation maximization algorithm wireless sensor networks

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Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

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BMC BIOINFORMATICS 2010年第1期11卷 1-12页

作者： Shepherd, Ross K. Meuwissen, Theo H. E. Woolliams, John A. Cent Queensland Univ Sch Informat & Commun Technol Rockhampton Qld 4702 Australia Norwegian Univ Life Sci Inst Anim & Aquacultural Sci N-1432 As Norway Univ Edinburgh Royal Dick Sch Vet Studies Roslin EH25 9PS Midlothian Scotland Univ Edinburgh Roslin Inst Roslin EH25 9PS Midlothian Scotland

Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved. Results: This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. Conclusions: emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time.

关键词： Quantitative Trait Locus Single Nucleotide Polymorphism Lasso Genomic Selection expectation maximization algorithm

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