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Any of six different data formats at any of five different data rates from phase-shift-key (PSK) modulated input signal extracted by digital radio receiver. Subcarrier Demodulator is Costas loop with hard limiter in inphase arm. There are six low-pass filters, each selectable for rate and format of data to be processed.
Fatigue testing campaigns are a common feature in the design and operation of advanced engineering systems in the aerospace and power generation sectors. The resulting data are typically of a high inherent technical and financial value. Presently, these data are typically transferred between departments and companies by way of ad-hoc solutions reliant on obsolete or proprietary technologies, including CSV files, MS Excel® files, and PDFs. In these circumstances there is significant potential for data loss, inconsistency, and error. To address these shortcomings, there is a need for a systematic means of transferring data between different digital systems. With this in mind, a series of CEN Workshops on engineering materials data have taken place with a view to developing technologies for representing and exchanging engineering materials data. Most recently, a CEN Workshop on the topic of fatigue test data has delivered data formats derived from the ISO 12106 standard for axial strain-controlled fatigue testing. This paper describes the methodology for developing the data formats and demonstrates their use in the scope of the INCEFA PLUS project on increasing safety in nuclear power plants by covering gaps in environmental fatigue assessment.
This manual for use of the magnetograph program describes: (1) black box use of the programs; (2) the magtape data formats used; (3) the adjustable control parameters in the program; and (4) the algorithms. With no adjustments on the control parameters this program may be used purely as a black box. For optimal use, however, the control parameters may be varied. The magtape data formats are of use in adopting other programs to look at raw data or final magnetograph data.
The Physics programmes of LHC Run III and HL-LHC challenge the HEP community. The volume of data to be handled is unprecedented at every step of the data processing chain: analysis is no exception. Physicists must be provided with first-class analysis tools which are easy to use, exploit bleeding edge hardware technologies and allow to seamlessly express parallelism. This document discusses the declarative analysis engine of ROOT, RDataFrame, and gives details about how it allows to profitably exploit commodity hardware as well as high-end servers and manycore accelerators thanks to the synergy with the existing parallelised ROOT components. Real-life analyses of LHC experiments’ data expressed in terms of RDataFrame are presented, highlighting the programming model provided to express them in a concise and powerful way. The recent developments which make RDataFrame a lightweight data processing framework are described, such as callbacks and I/O capabilities. Finally, the flexibility of RDataFrame and its ability to read data formats other than ROOT’s are characterised, as an example it is discussed how RDataFrame can directly read and analyse LHCb’s raw data format MDF.
ObjectiveLANL has built software that automatically collects global notifiable disease data, synthesizes the data, and makes it available to humans and computers within the Biosurveillance Ecosystem (BSVE) as a novel data stream. These data have many applications including improving the prediction and early warning of disease events.IntroductionMost countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health.While most nations likely store incident data in a machine-readable format, governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues1.A survey conducted by LANL of notifiable disease data reporting in over fifty countries identified only a few websites that report data in a machine-readable format. The majority (>70%) produce reports as PDF files on a regular basis. The bulk of the PDF reports present data in a structured tabular format, while some report in natural language.The structure and format of PDF reports change often; this adds to the complexity of identifying and parsing the desired data. Not all websites publish in English, and it is common to find typos and clerical errors.LANL has developed a tool, Epi Archive, to collect global notifiable disease data automatically and continuously and make it uniform and readily accessible.MethodsWe conducted a survey of the national notifiable disease reporting systems notating how the data are reported and in what formats. We determined the minimal metadata that is required to contextualize incident counts properly, as well as optional metadata that is commonly found.The development of software to regularly ingest notifiable disease data and make it available involves three or four main steps: scraping, detecting, parsing and persisting.Scraping: we examine website design and determine reporting mechanisms for each country/website, as well as what varies across the reporting mechanisms. We then designed and wrote code to automate the downloading of the data for each country. We store all artifacts presented as files (PDF, XLSX, etc.) in their original form, along with appropriate metadata for parsing and data provenance.Detecting: This step is required when parsing structured non-machine-readable data such as tabular data in PDF files. We combined the Nurminen methodology of PDF table detection with in-house heuristics to find the desired data within PDF reports2.Parsing: We determined what to extract from each dataset and parsed these data into uniform data structures, correctly accommodating the variations in metadata (e.g., time interval definitions) and the various human languages.Persisting: We store the data in the Epi Archive database and make it available on the internet and through the BSVE. The data is persisted into a structured and normalized SQL database.ResultsThe Epi Archive tool currently contains national and/or subnational notifiable disease data from twenty nations. When a user accesses the Epi Archive site, they are prompted with four fields: country, subregion, disease of interest, and date duration. Upon form submission, a time series is generated from the users’ specifications. The generated graph can then be downloaded into a CSV file if a user is interested in performing personal analysis. Additionally, the data from Epi Archive can be reached through a REST API (Representational State Transfer Application Programming Interface).ConclusionsLANL, as part of a currently funded DTRA effort, is automatically and continually collecting global notifiable disease data. While 20 nations are in production, more are being brought online in the near future. These data are already being utilized and will have many applications including improving the prediction and early warning of disease events.References[1] van Panhuis WG, Paul P, Emerson C, et al. A systematic review of barriers to data sharing in public health. BMC Public Health. 2014. 14:1144. doi:10.1186/1471-2458-14-1144[2] Nurminen, Anssi. "Algorithmic extraction of data in tables in PDF documents." (2013).
NJOY has a long history of nuclear data processing. NJOY began as a successor to MINX (Multigroup Interpretation of Nuclear X-Sections), a Los Alamos code and was first publicly released in the summer of 1977. The initial version included modules such as RECONR for resonance reconstruction on a union energy grid, BROADR for Doppler broadening plus a new Multigroup averaging program, GROUPR and an associated output module, DTR. Soon thereafter the HEATR, ERRORR, and THERMR modules were added to NJOY. By the mid 1980's, NJOY had a worldwide user community. The current version of NJOY2012 was released in December 2012. NJOY2012 builds on the success of more than 45 years of nuclear data processing at Los Alamos National Laboratory. NJOY2012 was rewritten using Fortran 90/95, utilizing among other things the concepts of public and private variables, eliminating common blocks in lieu of Fortran modules and taking advantage of allocatable arrays. A new version of NJOY is being developed at Los Alamos National Laboratory; NJOY21: NJOY for the 21. Century. NJOY21 uses modern programming standards of quality, reliability, and maintainability. It is being designed from the ground up to utilize modern methods of interacting with computer codes by providing an interactive and scripting (e.g., Python) interface. This will allow scientists the ability to more easily work with the results of the various steps in the processing of nuclear data. NJOY21 will continue the legacy of NJOY by providing a trusted and verified processing code that is fast, flexible, easy to use and customize and capable of handling both modern and established nuclear data formats. This paper introduces NJOY21 by first relating the history of NJOY; the majority of the paper will discuss NJOY21. NJOY21 will take advantage of the many decades of nuclear data processing experience that is contained in NJOY2012 and previous versions of NJOY and extend the capabilities and convenience of processing nuclear data. We will discuss how NJOY21 will remain backwards compatible with NJOY2012 - i.e., how current NJOY2012 input decks will continue to work with NJOY21. We will also discuss the verification and validation of the NJOY21 code base. Finally we will discuss new features in NJOY21 that do not exist in NJOY2012. These features include changes in how a scientist can interact with NJOY to process and verify and validate nuclear data; and the ability to read and write new nuclear data formats. (authors)
A standard data format for the archival and transport of x-ray events generated by ray trace models is described. Upon review and acceptance by the Advanced X-ray Astrophysics Facility (AXAF) Software Systems Working Group (SSWG), this standard shall become the official AXAF data format for ray trace events. The Flexible Image Transport System (FITS) is well suited for the purposes of the standard and was selected to be the basis of the standard. FITS is both flexible and efficient and is also widely used within the astronomical community for storage and transfer of data. In addition, software to read and write FITS format files are widely available. In selecting quantities to be included within the ray trace standard, the AXAF Mission Support team, Science Instruments team, and the other contractor teams were surveyed. From the results of this survey, the following requirements were established: (1) for the scientific needs, each photon should have associated with it: position, direction, energy, and statistical weight; the standard must also accommodate path length (relative phase), and polarization. (2) a unique photon identifier is necessary for bookkeeping purposes; (3) a log of individuals, organizations, and software packages that have modified the data must be maintained in order to create an audit trail; (4) a mechanism for extensions to the basic kernel should be provided; and (5) the ray trace standard should integrate with future AXAF data product standards.
There are a large number of astronomical archives and catalogs on-line for network access, with many different user interfaces and features. Some systems are moving towards distributed access, supplying users with client software for their home sites which connects to servers at the archive site. Many of the issues involved in defining a standard framework of services that archive/catalog suppliers can use to achieve a basic level of interoperability are described. Such a framework would simplify the development of client and server programs to access the wide variety of astronomical archive systems. The primary services that are supplied by current systems include: catalog browsing, dataset retrieval, name resolution, and data analysis. The following issues (and probably more) need to be considered in establishing a standard set of client/server interfaces and protocols: Archive Access - dataset retrieval, delivery, file formats, data browsing, analysis, etc.; Catalog Access - database management systems, query languages, data formats, synchronous/asynchronous mode of operation, etc.; Interoperability - transaction/message protocols, distributed processing mechanisms (DCE, ONC/SunRPC, etc), networking protocols, etc.; Security - user registration, authorization/authentication mechanisms, etc.; Service Directory - service registration, lookup, port/task mapping, parameters, etc.; Software - public vs proprietary, client/server software, standard interfaces to client/server functions, software distribution, operating system portability, data portability, etc. Several archive/catalog groups, notably the Astrophysics Data System (ADS), are already working in many of these areas. In the process of developing StarView, which is the user interface to the Space Telescope Data Archive and Distribution Service (ST-DADS), these issues and the work of others were analyzed. A framework of standard interfaces for accessing services on any archive system which would benefit archive user and supplier alike is proposed.
The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts (“branches”) that are really used in a given analysis need to be read from storage. Its unique feature is the seamless C++ integration, which allows users to directly store their event classes without explicitly defining data schemas. In this contribution, we present the status and plans of the future ROOT 7 event I/O. Along with the ROOT 7 interface modernization, we aim for robust, where possible compile-time safe C++ interfaces to read and write event data. On the performance side, we show first benchmarks using ROOT’s new experimental I/O subsystem that combines the best of TTrees with recent advances in columnar data formats. A core ingredient is a strong separation of the high-level logical data layout (C++ classes) from the low-level physical data layout (storage backed nested vectors of simple types). We show how the new, optimized physical data layout speeds up serialization and deserialization and facilitates parallel, vectorized and bulk operations. This lets ROOT I/O run optimally on the upcoming ultra-fast NVRAM storage devices, as well as file-less storage systems such as object stores.
LANL has built a software program that automatically collects global notifiable disease data—particularly data stored in files—and makes it available and shareable within the Biosurveillance Ecosystem(BSVE) as a new data source. This will improve the prediction and early warning of disease events and other applications. Most countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health as exemplified by the Biosurveillance Ecosystem(BSVE).While most nations do likely store their data in a machine-readable format, the governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues. For example, an attempt by LANL to obtain a weekly version of openly available monthly data, reported by the Australian government, resulted in an onerous bureaucratic reply. The obstacles to obtaining data included: paperwork to request data from each of the Australian states and territories, a long delay to obtain data (up to 3 months) and extensive limitations on the data’s use that prohibit collaboration and sharing. This type of experience when attempting to contact public health departments or ministries of health for data is not uncommon. A survey conducted by LANL of notifiable disease data reporting in 52 countries identified only 10 as being machine-readable and 42 being reported in pdf files on a regular basis. Within the 42 nations that report in pdf files, 32 report in a structured, tabular format and10 in a non-structured way. As a result, LANL has developed a tool-Epi Archive (formerly known as EPIC)-to automatically and continuously collect global notifiable disease data and make it readily accessible. We conducted a survey of the national notifiable disease reporting systems notating how the data is reported in two important dimensions: date standards and case definitions. The development of software to regularly ingests notifiable disease data frand makes this data available involved four main steps scraping, extracting, parsing and persisting. For scraping: we would examine website designs and determine reporting mechanisms for each country/website as well as what varies across the reporting mechanisms. We then designed and wrote code to automate the downloading of report pdf files, for each country. We stored report pdfs along with appropriate metadata for extracting and parsing. For extracting: we developed software that can extract notifiable disease data presented in tabular form from a pdf file. We combined the methodology of figure placement detection with the in-house developed table extraction and annotation heuristics. For parsing: we determined what to extract from each pdf dataset from the survey conducted. We then parsed the extracted data into uniform data structures correctly accommodating the dimensions surveyed and the various human languages. This task involved ingesting notifiable disease data in many disparate formats extracted from pdf files and coalescing the data into a standardized format. For persisting: We then store the data in the Epi Archive PostgreSQL database and make it available through the BSVE. The EpiArchive tool currently contains subnational notifiable disease data from 10 nations. When a user accesses the EpiArchive site, they are prompted with four fields: country, region, disease, and date duration. These fields allow the user to specify the location(down to the state level), the disease of interest, and the duration of interest. Upon form submission, a time series is generated from the users’ specifications. The generated time series can then be downloaded into a csv file if a user is interested in performing personal analysis. Additionally, the data from EpiArchive can be reached through an API. LANL as part of a currently funded DTRA effort so that it will automatically and continuously collect global notifiable disease data—particularly data stored in pdf files—and make it available and shareable within the Biosurveillance Ecosystem (BSVE) as a new data source. This will provide data to analytics and users that will improve the prediction and early warning of disease events and other applications.
The objective of this project has been to complete the archiving of energetic (10 eV/epsilon - 18 keV/epsilon) ion composition data from the Lockheed Plasma Composition Experiment on the International Sun-Earth Explorer One (ISEE 1) satellite, using a particular data format that had previously been approved by NASA and the NSSDC. That same format, a combination of ion velocity moments and differential flux spectra, had been used in 1991 to archive, at the NSSDC, the first 28 months (the "Prime" period of ISEE investigations) of data from the Lockheed instrument under NASA Contract NAS5-33047. With the completion of this project, the almost 4 1/2-year time span of these unique data is now covered by a very compact set, approximately 1 gigabyte in total, of electronic files with physical quantities, all in ASCII. The files are organized by data type and time of data acquisition, in Universal Time, and named according to year and day of year. Each calendar day has five separate files (five types of data), the lengths of which vary from day to day, depending on the instrument mode of operation. The data format and file structure are described in detail in appendices 1 and 2. The physical medium consists of high-density (6250 cpi) 9-track magnetic tapes, complemented by a set of hardcopy line plots of certain plasma parameters. In this case there are five tapes, to be added to the six previous ones from 1991, and 25 booklets of plots, one per month, to be added to the previous 28. The tapes, including an extra standard-density (1600 cpi) tape with electronic versions of the Data User's Guide and self-guiding VAX/VMS command files, and the hardcopy plots are being boxed for shipment to the NSSDC.
The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets.
The Univac 1108 computer tape data formats are documented for the ephermeris tape generated by the Jet Propulsion Laboratory and the ephemeris tape used by the Quick Response Targeting Program (QRTP). Ephermeris tapes are used as the data source for the position and velocity components of those celestial bodies being considered in an integrated trajectory simulation program. The QRTP ephemeris tape has data only for lunar mission simulations. The JPL ephemeris tape has data for the moon and the nine planets. The ephemeris tapes, the data formats, the coordinate systems, and units are defined. The transformation from the mean-of-1950 coordinate system to the nearest mean Besselian year is given.
The ‘kazrcfrcorge’ dataset is created by the KAZRCFRCOR VAP, which operates on ingested KAZR cfRadial-formatted data in conjunction with interpolated soundings to create significant detection masks, correct KAZR reflectivities for gaseous attenuation, and dealias mean Doppler velocities. This dataset serves as an input to the KAZR-ARSCL VAP.
The ‘kazrcfrcormd’ dataset is created by the KAZRCFRCOR VAP, which operates on ingested KAZR cfRadial-formatted data in conjunction with interpolated soundings to create significant detection masks, correct KAZR reflectivities for gaseous attenuation, and dealias mean Doppler velocities. This dataset serves as an input to the KAZR-ARSCL VAP.
In an effort to construct an optical transceiver for supporting multi-point communication, researchers developed large field-of-view FSO transceivers with wide apertures for facilitating rapid acquisition and optical signal tracking. The design is constructed from fiber-bundle(s) intelligently arranged to provide multiple optical pathways within a single transceiver, with each pathway limited to a particular optical directionality. Because designs with wide apertures are susceptible to receiving several optical signals simultaneously from multiple transmitters, accurately decoding individual signals and achieving true multi-user communication can be difficult. The work detailed in this paper investigated the use of blind source separation techniques, mainly independent component analysis (ICA), to estimate transmitted signals from their observed, combined mixtures sans information. Effects of signal power, format, data rate, wavelength, and turbulence severity on signal separation, as well as signal demodulation accuracy was also analyzed using experimental optical signals and corresponding mixtures. Signal generators, laser sources, turbulence emulator, beam profiler, photodiodes, and oscilloscopes comprised the experiment setup. Optical signals with varying power, format, and wavelength were generated and propagated through turbulence with varying degree severity, and finally received by the fiber-bundle-based optical transceiver. Results demonstrate that an ICA technique can accurately process the combined signals into corresponding individual components. The investigation further identified signal characteristics (e.g., power levels, format, data rate) and turbulence severity under which ICA is unable to accurately perform signal separations.
OurOcean Portal 2.0 (http:// ourocean.jpl.nasa.gov) is a software system designed to enable users to easily gain access to ocean observation data, both remote-sensing and in-situ, configure and run an Ocean Model with observation data assimilated on a remote computer, and visualize both the observation data and the model outputs. At present, the observation data and models focus on the California coastal regions and Prince William Sound in Alaska. This system can be used to perform both real-time and retrospective analyses of remote-sensing data and model outputs. OurOcean Portal 2.0 incorporates state-of-the-art information technologies (IT) such as MySQL database, Java Web Server (Apache/Tomcat), Live Access Server (LAS), interactive graphics with Java Applet at the Client site and MatLab/GMT at the server site, and distributed computing. OurOcean currently serves over 20 real-time or historical ocean data products. The data are served in pre-generated plots or their native data format. For some of the datasets, users can choose different plotting parameters and produce customized graphics. OurOcean also serves 3D Ocean Model outputs generated by ROMS (Regional Ocean Model System) using LAS. The Live Access Server (LAS) software, developed by the Pacific Marine Environmental Laboratory (PMEL) of the National Oceanic and Atmospheric Administration (NOAA), is a configurable Web-server program designed to provide flexible access to geo-referenced scientific data. The model output can be views as plots in horizontal slices, depth profiles or time sequences, or can be downloaded as raw data in different data formats, such as NetCDF, ASCII, Binary, etc. The interactive visualization is provided by graphic software, Ferret, also developed by PMEL. In addition, OurOcean allows users with minimal computing resources to configure and run an Ocean Model with data assimilation on a remote computer. Users may select the forcing input, the data to be assimilated, the simulation period, and the output variables and submit the model to run on a backend parallel computer. When the run is complete, the output will be added to the LAS server for
SGRAPH program is considered one of the seismological programs that maintain seismic data. SGRAPH is considered unique for being able to read a wide range of data formats and manipulate complementary tools in different seismological subjects in a stand-alone Windows-based application. SGRAPH efficiently performs the basic waveform analysis and solves advanced seismological problems. The graphical user interface (GUI) utilities and the Windows facilities such as, dialog boxes, menus, and toolbars simplified the user interaction with data. SGRAPH supported the common data formats like, SAC, SEED, GSE, ASCII, and Nanometrics Y-format, and others. It provides the facilities to solve many seismological problems with the built-in inversion and modeling tools. In this paper, I discuss some of the inversion tools built-in SGRAPH related to source parameters and hypocentral location estimation. Firstly, a description of the SGRAPH program is given discussing some of its features. Secondly, the inversion tools are applied to some selected events of the Dahshour earthquakes as an example of estimating the spectral and source parameters of local earthquakes. In addition, the hypocentral location of these events are estimated using the Hypoinverse 2000 program operated by SGRAPH.