Reducing Information Overload in Large Seismic Data Sets

Event catalogs for seismic data can become very large. Furthermore, as researchers collect multiple catalogs and reconcile them into a single catalog that is stored in a relational database, the reconciled set becomes even larger. The sheer number of these events makes searching for relevant events to compare with events of interest problematic. Information overload in this form can lead to the data sets being under-utilized and/or used incorrectly or inconsistently. Thus, efforts have been initiated to research techniques and strategies for helping researchers to make better use of large data sets. In this paper, the authors present their efforts to do so in two ways: (1) the Event Search Engine, which is a waveform correlation tool and (2) some content analysis tools, which area combination of custom-built and commercial off-the-shelf tools for accessing, managing, and querying seismic data stored in a relational database. The current Event Search Engine is based on a hierarchical clustering tool known as the dendrogram tool, which is written as a MatSeis graphical user interface. The dendrogram tool allows the user to build dendrogram diagrams for a set of waveforms by controlling phase windowing, down-sampling, filtering, enveloping, and the clustering method (e.g. single linkage, complete linkage, flexible method). It also allows the clustering to be based on two or more stations simultaneously, which is important to bridge gaps in the sparsely recorded event sets anticipated in such a large reconciled event set. Current efforts are focusing on tools to help the researcher winnow the clusters defined using the dendrogram tool down to the minimum optimal identification set. This will become critical as the number of reference events in the reconciled event set continually grows. The dendrogram tool is part of the MatSeis analysis package, which is available on the Nuclear Explosion Monitoring Research and Engineering Program Web Site. As part of the research into how to winnow the reference events in these large reconciled event sets, additional database query approaches have been developed to provide windows into these datasets. These custom built content analysis tools help identify dataset characteristics that can potentially aid in providing a basis for comparing similar reference events in these large reconciled event sets. Once these characteristics can be identified, algorithms can be developed to create and add to the reduced set of events used by the Event Search Engine. These content analysis tools have already been useful in providing information on station coverage of the referenced events and basic statistical, information on events in the research datasets. The tools can also provide researchers with a quick way to find interesting and useful events within the research datasets. The tools could also be used as a means to review reference event datasets as part of a dataset delivery verification process. There has also been an effort to explore the usefulness of commercially available web-based software to help with this problem. The advantages of using off-the-shelf software applications, such as Oracle's WebDB, to manipulate, customize and manage research data are being investigated. These types of applications are being examined to provide access to large integrated data sets for regional seismic research in Asia. All of these software tools would provide the researcher with unprecedented power without having to learn the intricacies and complexities of relational database systems

Communal Recommendation Based On Liquidiation Online Voting

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MatOFF: A tool for analyzing behaviorally complex neurophysiological experiments

The simple operant conditioning originally used in behavioral neurophysiology 30 years ago has given way to complex and sophisticated behavioral paradigms; so much so, that early general purpose programs for analyzing neurophysiological data are ill-suited for complex experiments. The trend has been to develop custom software for each class of experiment, but custom software can have serious drawbacks. We describe here a general purpose software tool for behavioral and electrophysiological studies, called MatOFF, that is especially suited for processing neurophysiological data gathered during the execution of complex behaviors. Written in the MATLAB programming language, MatOFF solves the problem of handling complex analysis requirements in a unique and powerful way. While other neurophysiological programs are either a loose collection of tools or append MATLAB as a post-processing step, MatOFF is an integrated environment that supports MATLAB scripting within the event search engine safely isolated in a programming sandbox. The results from scripting are stored separately, but in parallel with the raw data, and thus available to all subsequent MatOFF analysis and display processing. An example from a recently published experiment shows how all the features of MatOFF work together to analyze complex experiments and mine neurophysiological data in efficient ways. Published by Elsevier B.V