Bayesian dialogue system for the let's go spoken dialogue challenge

This paper describes how Bayesian updates of dialogue state can be used to build a bus information spoken dialogue system. The resulting system was deployed as part of the 2010 Spoken Dialogue Challenge. The purpose of this paper is to describe the system, and provide both simulated and human evaluations of its performance. In control tests by human users, the success rate of the system was 24.5% higher than the baseline Lets Go! system. ©2010 IEEE.

Multiplexed model predictive control

Most academic control schemes for MIMO systems assume all the control variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The multiplexed MPC scheme described in this paper solves the MPC problem for each subsystem sequentially, and updates subsystem controls as soon as the solution is available, thus distributing the control moves over a complete update cycle. The resulting computational speed-up allows faster response to disturbances, and hence improved performance, despite finding sub-optimal solutions to the original problem. The multiplexed MPC scheme is also closer to industrial practice in many cases. This paper presents initial stability results for two variants of multiplexed MPC, and illustrates the performance benefit by an example. Copyright copy; 2005 IFAC. Copyright © 2005 IFAC.

Multiplexed model predictive control

This paper proposes a form of MPC in which the control variables are moved asynchronously. This contrasts with most MIMO control schemes, which assume that all variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The Multiplexed MPC (MMPC) scheme described in this paper solves the MPC problem for each subsystem sequentially, and updates subsystem controls as soon as the solution is available, thus distributing the control moves over a complete update cycle. The resulting computational speed-up allows faster response to disturbances, which may result in improved performance, despite finding sub-optimal solutions to the original problem. This paper describes nominal and robust MMPC, states some stability results, and demonstrates the effectiveness of MMPC through two examples. © 2011 Elsevier Ltd. All rights reserved.

Improving Pothole Recognition through Vision Tracking for Automated Pavement Assessment

Pavement condition assessment is essential when developing road network maintenance programs. In practice, pavement sensing is to a large extent automated when regarding highway networks. Municipal roads, however, are predominantly surveyed manually due to the limited amount of expensive inspection vehicles. As part of a research project that proposes an omnipresent passenger vehicle network for comprehensive and cheap condition surveying of municipal road networks this paper deals with pothole recognition. Existing methods either rely on expensive and high-maintenance range sensors, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In our previous work we created a pothole detection method for pavement images. In this paper we present an improved recognition method for pavement videos that incrementally updates the texture signature for intact pavement regions and uses vision tracking to track detected potholes. The method is tested and results demonstrate its reasonable efficiency.

Robust multiplexed MPC for distributed multi-agent systems

This paper extends the authors' earlier work which adapted robust multiplexed MPC for application to distributed control of multi-agent systems with non-interacting dynamics and coupled constraint sets in the presence of persistent unknown, but bounded disturbances. Specifically, we propose exploiting the single agent update nature of the multiplexed approach, and fix the update sequence to enable input move-blocking and increased discretisation rates. This permits a higher rate of individual policy update to be achieved, whilst incurring no additional computational cost in the corresponding optimal control problems to be solved. A disturbance feedback policy is included between updates to facilitate finding feasible solutions. The new formulation inherits the property of rapid response to disturbances from multiplexing the control and numerical results show that fixing the update sequence does not incur any loss in performance. © 2011 IFAC.

Verification of periodically controlled hybrid systems: Application to an autonomous vehicle

This article introduces Periodically Controlled Hybrid Automata (PCHA) for modular specification of embedded control systems. In a PCHA, control actions that change the control input to the plant occur roughly periodically, while other actions that update the state of the controller may occur in the interim. Such actions could model, for example, sensor updates and information received from higher-level planning modules that change the set point of the controller. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariant properties of PCHAs is presented. For PCHAs with polynomial continuous vector fields, it is possible to check these conditions automatically using, for example, quantifier elimination or sum of squares decomposition. We examine the feasibility of this automatic approach on a small example. The proposed technique is also used to manually verify safety and progress properties of a fairly complex planner-controller subsystem of an autonomous ground vehicle. Geometric properties of planner-generated paths are derived which guarantee that such paths can be safely followed by the controller. © 2012 ACM.

Convex relaxation of mixture regression with efficient algorithms

We develop a convex relaxation of maximum a posteriori estimation of a mixture of regression models. Although our relaxation involves a semidefinite matrix variable, we reformulate the problem to eliminate the need for general semidefinite programming. In particular, we provide two reformulations that admit fast algorithms. The first is a max-min spectral reformulation exploiting quasi-Newton descent. The second is a min-min reformulation consisting of fast alternating steps of closed-form updates. We evaluate the methods against Expectation-Maximization in a real problem of motion segmentation from video data.

From subspace learning to distance learning: A geometrical optimization approach

In this paper, we adopt a differential-geometry viewpoint to tackle the problem of learning a distance online. As this problem can be cast into the estimation of a fixed-rank positive semidefinite (PSD) matrix, we develop algorithms that exploits the rich geometry structure of the set of fixed-rank PSD matrices. We propose a method which separately updates the subspace of the matrix and its projection onto that subspace. A proper weighting of the two iterations enables to continuously interpolate between the problem of learning a subspace and learning a distance when the subspace is fixed. © 2009 IEEE.

Low-rank optimization with trace norm penalty

The paper addresses the problem of low-rank trace norm minimization. We propose an algorithm that alternates between fixed-rank optimization and rank-one updates. The fixed-rank optimization is characterized by an efficient factorization that makes the trace norm differentiable in the search space and the computation of duality gap numerically tractable. The search space is nonlinear but is equipped with a Riemannian structure that leads to efficient computations. We present a second-order trust-region algorithm with a guaranteed quadratic rate of convergence. Overall, the proposed optimization scheme converges superlinearly to the global solution while maintaining complexity that is linear in the number of rows and columns of the matrix. To compute a set of solutions efficiently for a grid of regularization parameters we propose a predictor-corrector approach that outperforms the naive warm-restart approach on the fixed-rank quotient manifold. The performance of the proposed algorithm is illustrated on problems of low-rank matrix completion and multivariate linear regression. © 2013 Society for Industrial and Applied Mathematics.

Calibrating the Gaussian multi-target tracking model

We present novel batch and online (sequential) versions of the expectation-maximisation (EM) algorithm for inferring the static parameters of a multiple target tracking (MTT) model. Online EM is of particular interest as it is a more practical method for long data sets since in batch EM, or a full Bayesian approach, a complete browse of the data is required between successive parameter updates. Online EM is also suited to MTT applications that demand real-time processing of the data. Performance is assessed in numerical examples using simulated data for various scenarios. For batch estimation our method significantly outperforms an existing gradient based maximum likelihood technique, which we show to be significantly biased. © 2014 Springer Science+Business Media New York.

dynamic evolutions based on ontologies

With the continuous changes in application requirements of the enterprises, Web resources must be updated, so do the underlying ontologies that are associated with the Web resources. In the situation, it is very challenging for ontological engineers to specify the changes of ontologies, keep their consistencies and achieve semantic query of Web resources based on the evolving ontologies. We propose a construct called Prioritized Knowledge Base (PKB) based on SHOQ(D) description logic, and discuss some properties of PKB.PKB can be used for describing the evolutions and updates of ontologies with conflicting information. Furthermore, we develop some algorithms for checking conflict rules and performing semantic query based on PKB.

聚类引导搜索的移动机器人路径规划方法

本文提出一种聚类引导搜索（cluster guide searching，CGS）的路径规划方法。采用基于最大最小距离的K均值聚类方法对样本进行离线聚类学习，学习结果以相似环境相似决策的知识形式进行存储。路径规划过程中，机器人在线整理环境信息，获得输入空间样本，通过与知识库匹配，检索到最近的类别，然后在该类别内部采用速度优先策略和方向优先策略交替的方式搜索输出空间。若知识不完备导致检索失败，可重启线性规划算法（linear programming，LP）进行在线路径规划，并更新聚类知识库。仿真结果表明该方法是一种有效的路径规划学习方法。

双聚焦偏移速度估计与可分表示叠前弹性反演

In exploration seismology, the geologic target of oil and gas reservoir in complex medium request the high accuracy image of the structure and lithology of the medium. So the study of the prestack image and the elastic inversion of seismic wave in the complex medium come to the leading edge. The seismic response measured at the surface carries two fundamental pieces of information: the propagation effects of the medium and the reflections from the different layer boundaries in the medium. The propagation represent the low-wavenumber component of the medium, it is so-called the trend or macro layering, whereas the reflections represent the high-wavenumber component of the medium, it is called the detailed or fine layering. The result of migration velocity analysis is the resolution of the low-wavenumber component of the medium, but the prestack elastic inversion provided the resolution of the high-wavvenumber component the medium. In the dissertation, the two aspects about the migration velocity estimation and the elastic inversion have been studied.Firstly, any migration velocity analysis methods must include two basic elements: the criterion that tell us how to know whether the model parameters are correct and the updating that tell us how to update the model parameters when they are incorrect, which are effected on the properties and efficiency of the velocity estimation method. In the dissertation, a migration velocity analysis method based on the CFP technology has been presented in which the strategy of the top-down layer stripping approach are adapted to avoid the difficult of the selecting reduce .The proposed method has a advantage that the travel time errors obtained from the DTS panel are defined directly in time which is the difference with the method based on common image gather in which the residual curvature measured in depth should be converted to travel time errors.In the proposed migration velocity analysis method, the four aspects have been improved as follow:? The new parameterization of velocity model is provided in which the boundaries of layers are interpolated with the cubic spline of the control location and the velocity with a layer may change along with lateral position but the value is calculated as a segmented linear function of the velocity of the lateral control points. The proposed parameterization is suitable to updating procedure.? The analytical formulas to represent the travel time errors and the model parameters updates in the t-p domain are derived under local lateral homogeneous. The velocity estimations are iteratively computed as parametric inversion. The zero differential time shift in the DTS panel for each layer show the convergence of the velocity estimation.? The method of building initial model using the priori information is provided to improve the efficiency of velocity analysis. In the proposed method, Picking interesting events in the stacked section to define the boundaries of the layers and the results of conventional velocity analysis are used to define the velocity value of the layers? An interactive integrate software environment with the migration velocity analysis and prestack migration is built.The proposed method is firstly used to the synthetic data. The results of velocity estimation show both properties and efficiency of the velocity estimation are very good.The proposed method is also used to the field data which is the marine data set. In this example, the prestack and poststack depth migration of the data are completed using the different velocity models built with different method. The comparison between them shows that the model from the proposed method is better and improves obviously the quality of migration.In terms of the theoretical method of expressing a multi-variable function by products of single-variable functions which is suggested by Song Jian (2001), the separable expression of one-way wave operator has been studied. A optimization approximation with separable expression of the one-way wave operator is presented which easily deal with the lateral change of velocity in space and wave number domain respectively and has good approach accuracy. A new prestack depth migration algorithm based on the optimization approximation separable expression is developed and used to testing the results of velocity estimation.Secondly, according to the theory of the seismic wave reflection and transmission, the change of the amplitude via the incident angle is related to the elasticity of medium in the subsurface two-side. In the conventional inversion with poststack datum, only the information of the reflection operator at the zero incident angles can be used. If the more robust resolutions are requested, the amplitudes of all incident angles should be used.A natural separable expression of the reflection/transmission operator is represented, which is the sum of the products of two group functions. One group function vary with phase space whereas other group function is related to elastic parameters of the medium and geological structure.By employing the natural separable expression of the reflection/transmission operator, the method of seismic wave modeling with the one-way wave equation is developed to model the primary reflected waves, it is adapt to a certain extent heterogeneous media and confirms the accuracy of AVA of the reflections when the incident angle is less than 45'. The computational efficiency of the scheme is greatly high.The natural separable expression of the reflection/transmission operator is also used to construct prestack elastic inversion algorithm. Being different from the AVO analysis and inversion in which the angle gathers formed during the prstack migration are used, the proposed algorithm construct a linear equations during the prestack migration by the separable expression of the reflection/transmission operator. The unknowns of the linear equations are related to the elasticity of the medium, so the resolutions of them provided the elastic information of the medium.The proposed method of inversion is the same as AVO inversion in , the difference between them is only the method processing the amplitude via the incident angle and computational domain.

Learning Classes Correlated to a Hierarchy

Trees are a common way of organizing large amounts of information by placing items with similar characteristics near one another in the tree. We introduce a classification problem where a given tree structure gives us information on the best way to label nearby elements. We suggest there are many practical problems that fall under this domain. We propose a way to map the classification problem onto a standard Bayesian inference problem. We also give a fast, specialized inference algorithm that incrementally updates relevant probabilities. We apply this algorithm to web-classification problems and show that our algorithm empirically works well.

Temporal Surface Reconstruction

This thesis investigates the problem of estimating the three-dimensional structure of a scene from a sequence of images. Structure information is recovered from images continuously using shading, motion or other visual mechanisms. A Kalman filter represents structure in a dense depth map. With each new image, the filter first updates the current depth map by a minimum variance estimate that best fits the new image data and the previous estimate. Then the structure estimate is predicted for the next time step by a transformation that accounts for relative camera motion. Experimental evaluation shows the significant improvement in quality and computation time that can be achieved using this technique.