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IEEE/ION Position, Location and Navigation Symposium (PLANS)

作者： Farnoosh, Amirreza Nabian, Mohsen Closas, Pau Ostadabbas, Sarah Northeastern Univ Elect & Comp Engn Dept Boston MA 02115 USA

ISBN: (纸本)9781538616475

In this paper, we aim to enhance the first-person indoor navigation and scene understanding experience by fusing inertial data collected from a smartphone carried by the user with the vision information obtained through the phone's camera. We employed the concept of vanishing directions together with the orthogonality constraints of the man-made environments in an expectation maximization framework to estimate person's orientation with respect to the known indoor coordinates from video frames. This framework allows to include prior information about camera rotation axis for better estimations as well as to select candidate edge-lines for estimation of hallways' depth and width from monocular video frames, and 31) modeling of the scene. Our proposed algorithm concurrently combines the vision-based estimated orientation with the inertial data using a Kalman filter in order to reline estimations and remove substantial measurement drift from inertial sensors. We evaluated the performance of our vision-inertial data fusion method on an IMU-augmented video recorded from a rotary hallway in which a participant completed a full lap. We demonstrated that this fusion provides virtually drift-free instantaneous information about the person's relative orientation. We were able to estimate hallways' depth and width, and generate a closed-path map from the rotary hallway over a roughly 60-meter lap.

关键词： Computer vision Data fusion expectation maximization algorithm In-door navigation Simultaneous localization and mapping (SLAM)

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Direct Learning Coverage Control Based on expectation maximization in Wireless Sensor and Robot Network 1

Direct Learning Coverage Control Based on Expectation Maximi...

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1st Annual IEEE Conference on Control Technology and Applications

作者： Lin, Tsen-Chang Liu, Yen-Chen Natl Cheng Kung Univ Dept Mech Engn Tainan 70101 Taiwan

ISBN: (纸本)9781509021826

This paper proposes a direct learning controller for wireless sensor and robot network to coverage an environment by utilizing expectation maximization algorithm. In addition to sensors, including high-level and low-level sensors, mounted on mobile robots, low-level stationary sensors are considered to provide information for enhance the performance of coverage control. The main objective is to maximize the information quantity of high-level sensors from the sensing density generated by a group of low-level sensors. This direct method uses the parameter of basis function to design controller based on expectation maximization (EM) algorithm. Moreover, the proposed estimation and learning law are also used in indirect method for other coverage controller. Subsequently, this paper proposes a transformation method based on EM algorithm for coverage problem with complicated sensing function such as Gaussian function. Numerical examples are introduced to demonstrate the performance of the proposed direct coverage control in wireless sensor and robot network.

关键词： wireless sensor and robot network coverage control direct density estimation expectation maximization algorithm

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Operational Modal Analysis using expectation maximization algorithm 8

Operational Modal Analysis using Expectation Maximization Al...

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8th International Conference on Structural Dynamics (EURODYN)

作者： Cara, F. J. Carpio, J. Juan, J. Alarcon, E. ETSI Ind UPM Dept Org Engn Business Adm & Stat Madrid 28080 Spain ETSI Ind UPM Dept Struct Mech & Ind Construct Madrid 28080 Spain

ISBN: (纸本)9789076019314

This paper presents a time-domain stochastic system identification method based on Maximum Likelihood Estimation and the expectation maximization algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated applying the proposed identification method to a set of 100 simulated cases. The numerical results show that the proposed method estimates all the modal parameters reasonably well in the presence of 30% measurement noise even. Finally, advantages and disadvantages of the method have been discussed.

关键词： System identification in structures State Space models Kalman filter Operational Modal analysis Maximum likelihood estimation expectation maximization algorithm

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Distributed parameter estimation in wireless sensor networks in the presence of fading channels and unknown noise variance

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第9期14卷 1-14页

作者： Liu, Shoujun Liu, Kezhong Ma, Jie Chen, Wei Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Hubei Peoples R China Wuhan Univ Technol Sch Nav Wuhan Hubei Peoples R China

Parameter estimation is one of the most important research areas in wireless sensor networks. In this study, we consider the problem of estimating a deterministic parameter over fading channels with unknown noise variance. Owing to the bandwidth constraints in wireless sensor networks, sensor observations are quantized and subsequently transmitted to the fusion center. Two types of communication channels are considered, namely, parallel-access channels and multiple-access channels. Based on the knowledge of channel statistics, the power of the received signals at the fusion center can be described by the mode of the exponential mixture distribution. The expectation maximization algorithm is used to determine maximum likelihood solutions for this mixture model. A new estimator based on the expectation maximization algorithm is subsequently proposed. Simulation results show that this estimator exhibits superior performance compared to the method of moments estimator in both parallel- and multiple-access schemes. In addition, we determine that the parallel-access scheme outperforms the multiple-access scheme when the noise variance is small and it loses its superiority when the noise variance is large.

关键词： Distributed parameter estimation wireless sensor networks expectation maximization algorithm parallel-access channels multiple-access channels

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Analysis and probabilistic modeling of wind characteristics of an arch bridge using structural health monitoring data during typhoons

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STRUCTURAL ENGINEERING AND MECHANICS 2017年第6期63卷 809-824页

作者： Ye, X. W. Xi, P. S. Su, Y. H. Chen, B. Zhejiang Univ Dept Civil Engn Hangzhou 310058 Zhejiang Peoples R China

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of R-2 statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

关键词： structural health monitoring wind characteristics typhoon joint distribution function angular-linear approach expectation maximization algorithm

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Moving window adaptive soft sensor for state shifting process based on weighted supervised latent factor analysis

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CONTROL ENGINEERING PRACTICE 2017年 61卷 72-80页

作者： Yao, Le Ge, Zhiqiang Zhejiang Univ Coll Control Sci & Engn Inst Ind Proc Control State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China

Process nonlinearity and state shifting are two of the main factors that cause poor performance of online soft sensors. Adaptive soft sensor is a common practice to ensure high predictive accuracy. In this paper, the moving window method is introduced to the supervised latent factor analysis model to capture the state shifting feature of the process. To make the moving window strategy more efficient, the weighted form of the supervised latent factor analysis approach is applied. In this method, contributions of training samples are expressed through incorporating the similarity index into the noise variance of the process variable, which renders strong adaptability of the method for describing nonlinear relationships and abrupt changes of the process. A numerical example and a real industrial process are provided to demonstrate the effectiveness of the proposed adaptive soft sensor.

关键词： Adaptive soft sensor State shifting Moving window Weighted supervised latent factor analysis expectation maximization algorithm

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Assignment strategies for ground truths in the crowdsourcing of labeling tasks

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JOURNAL OF SYSTEMS AND SOFTWARE 2017年 126卷 113-126页

作者： Kubota, Takuya Aritsugi, Masayoshi Kumamoto Univ Grad Sch Sci & Technol Comp Sci & Elect Engn Chuo Ku 2-39-1 Kurokami Kumamoto 8608555 Japan Kumamoto Univ Fac Adv Sci & Technol Div Environm Sci Big Data Sci & TechnolChuo Ku 2-39-1 Kurokami Kumamoto 8608555 Japan

It is expected that ground truths can result in many good labels in the crowdsourcing of labeling tasks. However, the use of ground truths has so far not been adequately addressed. In this paper, we develop algorithms that determine the number of ground truths that are necessary. We determine this number by iteratively calculating the expected quality of labels for tasks with various sets of ground truths, and then comparing the quality with the limit of the estimated label quality expected to be obtained by crowd sourcing. We assume that each worker has a different unknown labeling ability and performs a different number of tasks. Under this assumption, we develop assignment strategies for ground truths based on the estimated confidence intervals of the workers. Our algorithms can utilize different approaches based on the expectation maximization to estimate good-quality consensus labels. An experimental evaluation demonstrates that our algorithms work well in various situations. (C) 2016 Elsevier Inc. All rights reserved.

关键词： expectation maximization algorithm Human computation Condorcet jury theorem Confidence interval

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QUEUEING SYSTEMS 2017年第3-4期85卷 337-359页

作者： Buchholz, Peter Kriege, Jan TU Dortmund Informat 4 D-44221 Dortmund Germany

In this paper, we consider a queue where the inter-arrival times are correlated and, additionally, service times are also correlated with inter-arrival times. We show that the resulting model can be interpreted as an MMAP[K]/PH[K]/1 queue for which matrix geometric solution algorithms are available. The major result of this paper is the presentation of approaches to fit the parameters of the model, namely the MMAP, the PH distribution and the parameters introducing correlation between inter-arrival and service times, according to some trace of inter-arrival and corresponding service times. Two different algorithms are presented. The first algorithm is based on available methods to compute a MAP from the inter-arrival times and a PH distribution from the service times. Afterward, the correlation between inter-arrival and service times is integrated by solving a quadratic programming problem over some joint moments. The second algorithm is of the expectation maximization type and computes all parameters of the MAP and the PH distribution in an iterative way. It is shown that both algorithms yield sufficiently accurate results with an acceptable effort.

关键词： Markovian arrival process Marked Markovian arrival processes Phase type distributions Multi-class queues expectation maximization algorithm

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Online auto-calibration of triaxial accelerometer with time-variant model structures

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SENSORS AND ACTUATORS A-PHYSICAL 2017年 266卷 294-307页

作者： Ye, L. Argha, A. Celler, B. G. Nguyen, H. T. Su, S. W. Univ Technol Fac Engn & Informat Technol Sydney NSW Australia Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW Australia

In this paper, an online auto-calibration method for MicroElectroMechanical Systems (MEMS) triaxial accelerometer (TA) is proposed, which can simultaneously identify the time-dependent model structure and its parameters during the changes of the operating environment. Firstly, the model as well as its associated cost function is linearized by a new proposed linearization approach. Then, exploiting an online sparse recursive least square (SPARLS) estimation, the unknown parameters are identified. In particular, the online sparse recursive method is based on an L-1-norm penalized expectation-maximum (EM) algorithm, which can amend the model automatically by penalizing the insignificant parameters to zero. Furthermore, this method can reduce computational complexity and be implemented in a low-cost Micro-Controller-Unit (MCU). Based on the numerical analysis, it can be concluded that the proposed recursive algorithm can calculate the unknown parameters reliably and accurately for most MEMS triaxial accelerometers available in the market. Additionally, this method is experimentally validated by comparing the output estimations before and after calibration under various scenarios, which further confirms its feasibility and effectiveness for online TA calibration. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Parameter estimation Tri-axial accelerometer Online calibration Model linearization expectation maximization algorithm

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Enabling multiplexed testing of pooled donor cells through whole-genome sequencing

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GENOME MEDICINE 2018年第1期10卷 31-31页

作者： Chan, Yingleong Chan, Ying Kai Goodman, Daniel B. Guo, Xiaoge Chavez, Alejandro Lim, Elaine T. Church, George M. Harvard Univ Wyss Inst Biol Inspired Engn Boston MA 02115 USA Harvard Med Sch Dept Genet Boston MA 02115 USA Harvard MIT Hlth Sci & Technol Cambridge MA 02139 USA Columbia Univ Coll Phys & Surg Dept Pathol & Cell Biol 630 W 168th St New York NY 10032 USA

We describe a method that enables the multiplex screening of a pool of many different donor cell lines. Our method accurately predicts each donor proportion from the pool without requiring the use of unique DNA barcodes as markers of donor identity. Instead, we take advantage of common single nucleotide polymorphisms, whole-genome sequencing, and an algorithm to calculate the proportions from the sequencing data. By testing using simulated and real data, we showed that our method robustly predicts the individual proportions from a mixed-pool of numerous donors, thus enabling the multiplexed testing of diverse donor cells en masse. More information is available at https://***/poolseq/

关键词： Multiplexed testing Barcode free method Single nucleotide polymorphisms expectation maximization algorithm Next-generation sequencing Personal Genome Project

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