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At least 91 records · Page 5

File Comparison Sampler

The file Comparison Sampler console application compares two or more files (typically in separate folders) to check whether the start of the files match, the end of the files match, and selected sections inside the files also match. It is useful for comparing large files without reading the entire file. Alternatively, you can provide two folder paths and the program will compare all of the files in the first folder to the identically named files in the second folder.

Monroe, Matthew↗

Extracting the Data From the LCM vk4 Formatted Output File

These are slides about extracting the data from the LCM vk4 formatted output file. The following is covered: vk4 file produced by Keyence VK Software, custom analysis, no off the shelf way to read the file, reading the binary data in a vk4 file, various offsets in decimal lines, finding the height image data, directly in MATLAB, binary output beginning of height image data, color image information, color image binary data, color image decimal and binary data, MATLAB code to read vk4 file (choose a file, read the file, compute offsets, read optical image, laser optical image, read and compute laser intensity image, read height image, timing, display height image, display laser intensity image, display RGB laser optical images, display RGB optical images, display beginning data and save images to workspace, gamma correction subroutine), reading intensity form the vk4 file, linear in the low range, linear in the high range, gamma correction for vk4 files, computing the gamma intensity correction, observations.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Permanent-File-Validation Utility Computer Program

Errors in files detected and corrected during operation. Permanent File Validation (PFVAL) utility computer program provides CDC CYBER NOS sites with mechanism to verify integrity of permanent file base. Locates and identifies permanent file errors in Mass Storage Table (MST) and Track Reservation Table (TRT), in permanent file catalog entries (PFC's) in permit sectors, and in disk sector linkage. All detected errors written to listing file and system and job day files. Program operates by reading system tables , catalog track, permit sectors, and disk linkage bytes to vaidate expected and actual file linkages. Used extensively to identify and locate errors in permanent files and enable online correction, reducing computer-system downtime.

Derry, Stephen D.↗

Smartfiles: An OO approach to data file interoperability

Data files for scientific and engineering codes typically consist of a series of raw data values whose descriptions are buried in the programs that interact with these files. In this situation, making even minor changes in the file structure or sharing files between programs (interoperability) can only be done after careful examination of the data file and the I/O statement of the programs interacting with this file. In short, scientific data files lack self-description, and other self-describing data techniques are not always appropriate or useful for scientific data files. By applying an object-oriented methodology to data files, we can add the intelligence required to improve data interoperability and provide an elegant mechanism for supporting complex, evolving, or multidisciplinary applications, while still supporting legacy codes. As a result, scientists and engineers should be able to share datasets with far greater ease, simplifying multidisciplinary applications and greatly facilitating remote collaboration between scientists.

Haines, Matthew↗

DMFS: A Data Migration File System for NetBSD

I have recently developed DMFS, a Data Migration File System, for NetBSD. This file system provides kernel support for the data migration system being developed by my research group at NASA/Ames. The file system utilizes an underlying file store to provide the file backing, and coordinates user and system access to the files. It stores its internal metadata in a flat file, which resides on a separate file system. This paper will first describe our data migration system to provide a context for DMFS, then it will describe DMFS. It also will describe the changes to NetBSD needed to make DMFS work. Then it will give an overview of the file archival and restoration procedures, and describe how some typical user actions are modified by DMFS. Lastly, the paper will present simple performance measurements which indicate that there is little performance loss due to the use of the DMFS layer.

Studenmund, William↗

Conversion of Environment Files from ORDEM 3 & MEM 3 to STENVI

To perform Micrometeoroid and Orbital Debris (MMOD) analyses, NASA describes the orbital debris particle environment using the ORDEM 3 tool and the micrometeoroid environment using the MEM 3 tool. Both output files that detail the flux of particles as a function of several parameters. European MMOD analyses use different tools to perform similar functions, including the Meteoroid And Space debris Terrestrial Environment Reference (MASTER) environment model, which outputs flux data in the Standard Environment Interface (STENVI) format. The NASA Johnson Space Center Hypervelocity Impact Technology Group was asked to create a converter to translate flux data from the output file formats used by ORDEM 3.x and MEM 3 into the STENVI file format. Validation was performed to ensure that the converter was reproducing the input data correctly. The Bumper 3 MMOD risk assessment tool has a capability for reading ORDEM 3.x, MEM 3, and STENVI environment file formats and was used to compare MMOD risk results generated using the converter’s output STENVI files to the risk results generated using the input ORDEM 3.x and MEM 3 igloo files. Specific point comparisons validated that the converter translated the environment data correctly, producing the intended output. However, realistic risk assessments showed that the bin methodology employed by Bumper for determining particle flux as a function of particle size when reading files in STENVI format produces much higher MMOD risk than the point-interpolation methodology used in Bumper risk assessments using ORDEM and MEM. Modifications to how Bumper 3 reads STENVI files during analyses are considered to improve Bumper’s ability to perform useful analyses with environment files in this format.

STENVI↗

Conversion of ORDEM 3.X & MEM 3 Into STENVI File Format

To perform Micrometeoroid and Orbital Debris (MMOD) analyses, NASA describes the orbital debris particle environment using the ORDEM 3 tool and the micrometeoroid environment using the MEM 3 tool. Both output files that detail the flux of particles as a function of several parameters. European MMOD analyses use different tools to perform similar functions, including the Meteoroid And Space debris Terrestrial Environment Reference (MASTER) environment model, which outputs flux data in the Standard Environment Interface (STENVI) format. The NASA Johnson Space Center Hypervelocity Impact Technology Group was asked to create a converter to translate flux data from the output file formats used by ORDEM 3.x and MEM 3 into the STENVI file format. Validation was performed to ensure that the converter was reproducing the input data correctly. The Bumper 3 MMOD risk assessment tool has a capability for reading ORDEM 3.x, MEM 3, and STENVI environment file formats and was used to compare MMOD risk results generated using the converter’s output STENVI files to the risk results generated using the input ORDEM 3.x and MEM 3 igloo files. Specific point comparisons validated that the converter translated the environment data correctly, producing the intended output. However, realistic risk assessments showed that the bin methodology employed by Bumper for determining particle flux as a function of particle size when reading files in STENVI format produces much higher MMOD risk than the point-interpolation methodology used in Bumper risk assessments using ORDEM and MEM. Modifications to how Bumper 3 reads STENVI files during analyses are considered to improve Bumper’s ability to perform useful analyses with environment files in this format.

STENVI↗

Single Integrated Flux Files to Account for Spacecraft Attitude Motion in Meteoroid Risk Assessments Using the NASA MEM3 and Bumper Codes

Spacecraft meteoroid risk assessments can be performed using NASA’s Meteoroid Engineering Model 3 (MEM3) and the Bumper risk assessment code. The MEM3 meteoroid flux is highly directional in heliocentric space. To represent the directionality, MEM3 outputs the flux in commonly used coordinate frames. For example, if a spacecraft attitude is fixed in the orbital tangential frame, a single Bumper run using the MEM3 flux file in the body-fixed frame can be performed. Cases exist in which the spacecraft does not remain fixed in one of these frames during a mission. This could be handled by performing a series of Bumper runs at points along the trajectory. For each trajectory point, the spacecraft has to be rotated into the frame in which the MEM3 flux file is defined. Another option presented here is to generate a single integrated flux (SIF) file. A SIF file is an average over a trajectory of the time varying MEM3 flux files rotated from their native frame into the spacecraft bus frame. A SIF file enables accounting for spacecraft rotation (coupled with flux variation over the trajectory) in a single Bumper run. An example of an application of SIF files is the meteoroid risk assessment for the Mars Sample Return (MSR) campaign Capture Containment and Return System (CCRS). This report discusses how SIF files were generated for the CCRS risk assessment and presents metrics on the accuracy of the impinging fluence that is generated when using the files. The results show a maximum difference per element in a finite element model within 1 percent for seven of the eight examined cases, with the outlier being less than 2 percent. The results also show that the maximum standard deviation of differences across all elements is within 0.275 percent. The maximum difference in the total fluence across all the elements is 0.0463 percent. The maximum difference in the mean fluence across all the elements is 0.0407 percent.

Meteoroids↗

Collective operations in a file system based execution model

A mechanism is provided for group communications using a MULTI-PIPE synthetic file system. A master application creates a multi-pipe synthetic file in the MULTI-PIPE synthetic file system, the master application indicating a multi-pipe operation to be performed. The master application then writes a header-control block of the multi-pipe synthetic file specifying at least one of a multi-pipe synthetic file system name, a message type, a message size, a specific destination, or a specification of the multi-pipe operation. Any other application participating in the group communications then opens the same multi-pipe synthetic file. A MULTI-PIPE file system module then implements the multi-pipe operation as identified by the master application. The master application and the other applications then either read or write operation messages to the multi-pipe synthetic file and the MULTI-PIPE synthetic file system module performs appropriate actions.

97 MATHEMATICS AND COMPUTING↗

Collective operations in a file system based execution model

A mechanism is provided for group communications using a MULTI-PIPE synthetic file system. A master application creates a multi-pipe synthetic file in the MULTI-PIPE synthetic file system, the master application indicating a multi-pipe operation to be performed. The master application then writes a header-control block of the multi-pipe synthetic file specifying at least one of a multi-pipe synthetic file system name, a message type, a message size, a specific destination, or a specification of the multi-pipe operation. Any other application participating in the group communications then opens the same multi-pipe synthetic file. A MULTI-PIPE file system module then implements the multi-pipe operation as identified by the master application. The master application and the other applications then either read or write operation messages to the multi-pipe synthetic file and the MULTI-PIPE synthetic file system module performs appropriate actions.

97 MATHEMATICS AND COMPUTING↗

Small file aggregation in a parallel computing system

Techniques are provided for small file aggregation in a parallel computing system. An exemplary method for storing a plurality of files generated by a plurality of processes in a parallel computing system comprises aggregating the plurality of files into a single aggregated file; and generating metadata for the single aggregated file. The metadata comprises an offset and a length of each of the plurality of files in the single aggregated file. The metadata can be used to unpack one or more of the files from the single aggregated file.

97 MATHEMATICS AND COMPUTING↗

Storing files in a parallel computing system based on user or application specification

Techniques are provided for storing files in a parallel computing system based on a user-specification. A plurality of files generated by a distributed application in a parallel computing system are stored by obtaining a specification from the distributed application indicating how the plurality of files should be stored; and storing one or more of the plurality of files in one or more storage nodes of a multi-tier storage system based on the specification. The plurality of files comprise a plurality of complete files and/or a plurality of sub-files. The specification can optionally be processed by a daemon executing on one or more nodes in a multi-tier storage system. The specification indicates how the plurality of files should be stored, for example, identifying one or more storage nodes where the plurality of files should be stored.

97 MATHEMATICS AND COMPUTING↗

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used to reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.

97 MATHEMATICS AND COMPUTING↗

Data-model files associated with the manuscript "Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California"

This package contains the data, simulation setups, notebooks and figures used in “Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California” (Xu et al., 2025). In this study, we selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise on coastal hydrology using the process-based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site-specific data. We designed a novel modeling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modeled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected sea level rise over the next few decades. The low-lying Yampah Marsh, the reference site, is likely to be inundated due to future sea level rise when highest tides arrive; while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.Several files can be found from this data package.1. README.md: This file describes the title, journal, co-authors, abstract, repository structure and model version.2. Simulation_Setups.zip: The file contains the model configuration files (XML format) for ATS. 3. Notebooks.zip: The file contains the Jupyter notebooks for generating the pre- and post-restoration meshes and the meshes of future scenarios. 4. Figures.zip: The file contains the figures used in the manuscript.5. Data.zip: The file contains the data used to drive the model simulations, including watershed and wetlands boundaries, mesh files and references to additional datasets (e.g., meteorological forcing, tidal dataset, DEMs, land cover, soil properties). Also, it contains water level observations at the restored wetland.

54 ENVIRONMENTAL SCIENCES↗

Ad Hoc File Systems for High-Performance Computing

Storage backends of parallel compute clusters are still based mostly on magnetic disks, while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory (NVRAM) are deployed within compute nodes. Including these new storage technologies into scientific workflows is unfortunately today a mostly manual task, and most scientists therefore do not take advantage of the faster storage media. One approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes, which serve as temporary storage systems for single applications or longer-running campaigns. This paper presents results from the Dagstuhl Seminar 17202 “Challenges and Opportunities of User-Level File Systems for HPC” and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage media. The discussion includes open research questions, such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file systems. Also presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device compatibility. Various interfaces and semantics are presented, for example those used by the three ad hoc file systems BeeOND, GekkoFS, and BurstFS. Their presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

97 MATHEMATICS AND COMPUTING↗

diyepw: A Python package for Do-It-Yourself EnergyPlus weather file generation

diyepw allows for quick and easy generation of a set of EnergyPlus weather (EPW) files for a given location over a given historical period. The user can obtain weather files using an open-source, automated workflow by simply specifying the location of interest using the World Meteorological Organization weather station ID number, and specifying a year or set of years for which to generate EPW files. Building energy modelers can use these auto-generated weather files in building performance simulations to represent the actual observed weather conditions in the location(s) of interest, based on meteorological observations obtained from the National Oceanic and Atmospheric Administration's Integrated Surface Database. Because observed weather data are not available for every meteorological variable specified in the EPW format, diyepw starts with a widely-used set of typical meteorological year (TMY) files, using them as the template to generate new EPW files by substituting in the observed values of selected meteorological variables that are known to affect building energy performance. Its output is a weather file or group of weather files that conform to the data standards associated with the EPW format so they can be used with any building performance simulation software employing EnergyPlus as its simulation engine.

97 MATHEMATICS AND COMPUTING↗

Monte Carlo simulation of TrueBeam flattening-filter-free beams using Varian phase-space files: Comparison with experimental data

Purpose: Phase-space files for Monte Carlo simulation of the Varian TrueBeam beams have been made available by Varian. The aim of this study is to evaluate the accuracy of the distributed phase-space files for flattening filter free (FFF) beams, against experimental measurements from ten TrueBeam Linacs. Methods: The phase-space files have been used as input in PRIMO, a recently released Monte Carlo program based on thePENELOPE code. Simulations of 6 and 10 MV FFF were computed in a virtual water phantom for field sizes 3 × 3, 6 × 6, and 10 × 10 cm{sup 2} using 1 × 1 × 1 mm{sup 3} voxels and for 20 × 20 and 40 × 40 cm{sup 2} with 2 × 2 × 2 mm{sup 3} voxels. The particles contained in the initial phase-space files were transported downstream to a plane just above the phantom surface, where a subsequent phase-space file was tallied. Particles were transported downstream this second phase-space file to the water phantom. Experimental data consisted of depth doses and profiles at five different depths acquired at SSD = 100 cm (seven datasets) and SSD = 90 cm (three datasets). Simulations and experimental data were compared in terms of dose difference. Gamma analysis was also performed using 1%, 1 mm and 2%, 2 mm criteria of dose-difference and distance-to-agreement, respectively. Additionally, the parameters characterizing the dose profiles of unflattened beams were evaluated for both measurements and simulations. Results: Analysis of depth dose curves showed that dose differences increased with increasing field size and depth; this effect might be partly motivated due to an underestimation of the primary beam energy used to compute the phase-space files. Average dose differences reached 1% for the largest field size. Lateral profiles presented dose differences well within 1% for fields up to 20 × 20 cm{sup 2}, while the discrepancy increased toward 2% in the 40 × 40 cm{sup 2} cases. Gamma analysis resulted in an agreement of 100% when a 2%, 2 mm criterion was used, with the only exception of the 40 × 40 cm{sup 2} field (∼95% agreement). With the more stringent criteria of 1%, 1 mm, the agreement reduced to almost 95% for field sizes up to 10 × 10 cm{sup 2}, worse for larger fields. Unflatness and slope FFF-specific parameters are in line with the possible energy underestimation of the simulated results relative to experimental data. Conclusions: The agreement between Monte Carlo simulations and experimental data proved that the evaluated Varian phase-space files for FFF beams from TrueBeam can be used as radiation sources for accurate Monte Carlo dose estimation, especially for field sizes up to 10 × 10 cm{sup 2}, that is the range of field sizes mostly used in combination to the FFF, high dose rate beams.

61 RADIATION PROTECTION AND DOSIMETRY↗

SU-E-T-392: Evaluation of Ion Chamber/film and Log File Based QA to Detect Delivery Errors

Purpose: Ion chamber and film (ICAF) is a method used to verify patient dose prior to treatment. More recently, log file based QA has been shown as an alternative for measurement based QA. In this study, we delivered VMAT plans with and without errors to determine if ICAF and/or log file based QA was able to detect the errors. Methods: Using two VMAT patients, the original treatment plan plus 7 additional plans with delivery errors introduced were generated and delivered. The erroneous plans had gantry, collimator, MLC, gantry and collimator, collimator and MLC, MLC and gantry, and gantry, collimator, and MLC errors. The gantry and collimator errors were off by 4{sup 0} for one of the two arcs. The MLC error introduced was one in which the opening aperture didn’t move throughout the delivery of the field. For each delivery, an ICAF measurement was made as well as a dose comparison based upon log files. Passing criteria to evaluate the plans were ion chamber less and 5% and film 90% of pixels pass the 3mm/3% gamma analysis(GA). For log file analysis 90% of voxels pass the 3mm/3% 3D GA and beam parameters match what was in the plan. Results: Two original plans were delivered and passed both ICAF and log file base QA. Both ICAF and log file QA met the dosimetry criteria on 4 of the 12 erroneous cases analyzed (2 cases were not analyzed). For the log file analysis, all 12 erroneous plans alerted a mismatch in delivery versus what was planned. The 8 plans that didn’t meet criteria all had MLC errors. Conclusion: Our study demonstrates that log file based pre-treatment QA was able to detect small errors that may not be detected using an ICAF and both methods of were able to detect larger delivery errors.

60 APPLIED LIFE SCIENCES↗