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The Knowledge Base Interface for Parametric Grid Information

Description: The parametric grid capability of the Knowledge Base (KBase) provides an efficient robust way to store and access interpolatable information that is needed to monitor the Comprehensive Nuclear Test Ban Treaty. To meet both the accuracy and performance requirements of operational monitoring systems, we use an approach which combines the error estimation of kriging with the speed and robustness of Natural Neighbor Interpolation. The method involves three basic steps: data preparation, data storage, and data access. In past presentations we have discussed in detail the first step. In this paper we focus on the latter two, describing in detail the type of information which must be stored and the interface used to retrieve parametric grid data from the Knowledge Base. Once data have been properly prepared, the information (tessellation and associated value surfaces) needed to support the interface functionality, can be entered into the KBase. The primary types of parametric grid data that must be stored include (1) generic header information; (2) base model, station, and phase names and associated ID's used to construct surface identifiers; (3) surface accounting information; (4) tessellation accounting information; (5) mesh data for each tessellation; (6) correction data defined for each surface at each node of the surfaces owning tessellation (7) mesh refinement calculation set-up and flag information; and (8) kriging calculation set-up and flag information. The eight data components not only represent the results of the data preparation process but also include all required input information for several population tools that would enable the complete regeneration of the data results if that should be necessary.
Date: August 3, 1999
Creator: Hipp, James R.; Simons, Randall W. & Young, Chris J.
Partner: UNT Libraries Government Documents Department

Cluster Analysis for CTBT Seismic Event Monitoring

Description: Mines at regional distances are expected to be continuing sources of small, ambiguous events which must be correctly identified as part of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) monitoring process. Many of these events are small enough that they are only seen by one or two stations, so locating them by traditional methods maybe impossible or at best leads to poorly resolved parameters. To further complicate matters, these events have parametric characteristics (explosive sources, shallow depths) which make them difficult to identify as definite non-nuclear events using traditional discrimination methods. Fortunately, explosions from the same mines tend to have similar waveforms, making it possible to identify an unknown event by comparison with characteristic archived events that have been associated with specific mines. In this study we examine the use of hierarchical cluster methods to identify groups of similar events. These methods produce dendrograms, which are tree-like structures showing the relationships between entities. Hierarchical methods are well-suited to use for event clustering because they are well documented, easy to implement, computationally cheap enough to run multiple times for a given data set, and because these methods produce results which can be readily interpreted. To aid in determining the proper threshold value for defining event families for a given dendrogram, we use cophenetic correlation (which compares a model of the similarity behavior to actual behavior), variance, and a new metric developed for this study. Clustering methods are compared using archived regional and local distance mining blasts recorded at two sites in the western U.S. with different tectonic and instrumentation characteristics: the three-component broadband DSVS station in Pinedale, Wyoming and the short period New Mexico Tech (NMT) network in central New Mexico. Ground truth for the events comes from the mining industry and local network locations, respectively. The clustering techniques prove to be much ...
Date: August 3, 1999
Creator: Carr, Dorthe B.; Young, Chris J.; Aster, Richard C. & Zhang, Xioabing
Partner: UNT Libraries Government Documents Department