18661216
A stabilized bandwidth selection method for kernel smoothing of the periodogram
One popular method for nonparametric spectral density estimation is to perform kernel smoothing on the periodogram, and one important component of this method is the choice of the bandwidth (or span) for smoothing. This paper proposes a new bandwidth selection method that is based on a coupling of the so-called plug-in and the unbiased risk estimation ideas. This new method is easy to describe, simple to implement, and does not impose severe conditions on the unknown spectrum. Numerical results suggest that this new method often outperforms some other commonly used bandwidth selection methods. The new methodology is also applied to choose the bandwidth for log-periodogram smoothing.
16239260
Hybrid local polynomial wavelet shrinkage: wavelet regression with automatic boundary adjustment
An usual assumption underlying the use of wavelet shrinkage is that the regression function is assumed to be either periodic or symmetric. However, such an assumption is not always realistic. This paper proposes an effective method for correcting the boundary bias introduced by the inappropriateness of such periodic or symmetric assumption. The idea is to combine wavelet shrinkage with local polynomial regression, where the latter regression technique is known to possess excellent boundary properties. Simulation results from both the univariate and bivariate settings provide strong evidence that the proposed method is extremely effective in terms of correcting boundary bias.
41225454
Segmenting images corrupted by correlated noise
Image segmentation is fundamental to many image analysis problems. It aims to partition a digital image into a set of non-overlapping homogeneous regions. This paper describes a new segmentation procedure which is designed to segment images corrupted by correlated noise. This procedure is based on Rissanen's (1989) minimum description length principle.
14075649
Nonparametric log spectrum estimation using disconnected regression splines and genetic algorithms
This article proposes a new nonparametric procedure for estimating log spectra. This procedure consists of three major components: (1) a novel statistical model for modelling the unknown target log spectrum, (2) an AIC-based model selection criterion for choosing a 'best' fitting model, and (3) a genetic algorithm for effectively searching the 'best' fitting model. Numerical experiments are conducted to evaluate and compare the practical performance of the proposed procedure with some other common log spectral estimation procedures appearing in the literature. These other procedures include wavelet techniques, kernel smoothing and regression spline fitting. Empirical results suggest that the proposed procedure compares favourably against all these procedures, especially when the unknown log spectrum contains inhomogeneous structures.
20836735
Kernel smoothing of periodograms under Kullback-Leibler discrepancy
Kernel smoothing on the periodogram is a popular nonparametric method for spectral density estimation. Most important in the implementation of this method is the choice of the bandwidth, or span, for smoothing. One idealized way of choosing the bandwidth is to choose it as the one that minimizes the Kullback-Leibler (KL) discrepancy between the smoothed estimate and the true spectrum. However, this method fails in practice, as the KL discrepancy is an unknown quantity. This paper introduces an estimator for this discrepancy, so that the bandwidth that minimizes the unknown discrepancy can be empirically approximated via the minimization of it. It is shown that this discrepancy estimator is consistent. Numerical results also suggest that this empirical choice of bandwidth often outperforms some other commonly used bandwidth choices. The same idea is also applied to choose the bandwidth for log-periodogram smoothing.
21281832
Progressive mesh metamorphosis
This paper describes a new integrated scheme for metamorphosis between two closed manifold genus-0 polyhedral models. Spherical parameterizations of the source and target models are created first. To control the morphing, any number of feature vertex pairs is specified and a fold-over free warping method is used to align two spherical embeddings. Our method does not create a merged meta-mesh or execute re-meshing to construct a common connectivity for morphs. Alternatively, a scheme for the progressive connectivity transformation of two spherical parameterizations is employed to generate the intermediate meshes. A novel semi-overlay with a geomorph scheme is proposed to reduce the popping effects caused by the connectivity transformation. We demonstrate several examples of aesthetically pleasing morphing sequences using the proposed scheme. Copyright © 2005 John Wiley & Sons, Ltd.
3114143
Interactive Execution Monitoring of Agent Teams
There is an increasing need for automated support for humans monitoring the activity of distributed teams of cooperating agents, both human and machine. We characterize the domain-independent challenges posed by this problem, and describe how properties of domains influence the challenges and their solutions. We will concentrate on dynamic, data-rich domains where humans are ultimately responsible for team behavior. Thus, the automated aid should interactively support effective and timely decision making by the human. We present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We describe a monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload. 
 
We use this framework to describe an execution monitoring approach we have used to implement Execution Assistants (EAs) in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior. One domain (Army small unit operations) has hundreds of mobile, geographically distributed agents, a combination of humans, robots, and vehicles. The other domain (teams of unmanned ground and air vehicles) has a handful of cooperating robots. Both domains involve unpredictable adversaries in the vicinity. Our approach customizes monitoring behavior for each specific task, plan, and situation, as well as for user preferences. Our EAs alert the human controller when reported events threaten plan execution or physically threaten team members. Alerts were generated in a timely manner without inundating the user with too many alerts (less than 10% of alerts are unwanted, as judged by domain experts).
11717164
Source Attribution for Querying Against Semi-structured Documents
Mediation architectures like the Context Interchange research project, from which this work stems, integrate disparate information sources, hiding distribution and reconciling heterogeneity. As a result of transparent access, the notion of distinct sources often disappears from queries and results. However, there are situations where users or applications do need to know the sources from which a particular datum is drawn: for example, enforcement of intellectual property, evaluation of data quality or measurement of the timeliness of data. In this paper, we define attribution as the association of a value in the result of a query with the sources either from which the data was extracted or which contributed to the selection. Motivated by multisource querying, attribution has particular applicability in the context of the World Wide Web. After beginning with an example that both describes and motivates the need for attribution within the semi-structured environment of the Web, we offer a general attribution framework and algebra and discuss the implementation of a prototype.
1878850
Information Brokering on the World Wide Web
Information Brokering is the process of collecting and re-distributing information. As the rich but unstructured sea of data that comprises the World Wide Web continues to grow, so too will the demand for information brokering services. This paper outlines a methodology and an architecture to support information brokering on the Web. Specifically, the two innovations which are described facilitate the construction and distribution of customized views that integrate data from a number of Web sources. An original technique is presented for the extraction of data from the Web and a solution based on JavaScript and HTML is presented to support the embedding of SQL queries within Web documents.
767826
The Spectral Independent Components of Natural Scenes
We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was able to find basis functions that had a broadband spectrum similar to natural daylight, as well as basis functions that coincided with the human cone sensitivity response functions. When applied to small image patches, the algorithm found homogeneous basis functions, achromatic basis functions, and basis functions with overall chromatic variation along lines in color space. Our findings suggest that ICAm ay be used to reveal the structure of color information in natural images.