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Trojan Detection Software Challenge - nlp-summary-jan2022-train
Data provided by National Institute of Standards and Technology
Round 9 Train Dataset
Modified:
Source: https://drive.google.com/drive/folders/13OAOIabpF-iHdIC9G5LxGOl7IL0UBcIL?usp=drive_link
Data for Modeling OFDM Communication Signals with Generative Adversarial Networks
Data provided by National Institute of Standards and Technology
This repository contains results for experiments on generative modeling of synthetic Orthogonal-Frequency Division Multiplexing (OFDM) communication signals. (This record supersedes Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks, formerly at https://doi.org/10.18434/mds2-2428)
Modified:
Source: https://doi.org/10.18434/mds2-2532
C++ implementation of enthalpy-entropy flash calculations with superancillary equations
Data provided by National Institute of Standards and Technology
This repository implements the code to accompany the paper "Accelerating Enthalpy-Entropy Iterative Calculations With Superancillary Phase Boundaries" in the Energy journal by Ian Bell.
The code uses superancillary equations (Chebyshev expansions) to speed up the phase-boundary determination and two-phase iterative calculations by a factor of approximately 500 without a loss in precision.
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Serum proteomics of coronavirus shedding in vampire bats (Desmodus rotundus)
Data provided by National Institute of Standards and Technology
Bats can harbor many pathogens without showing disease. However, the mechanisms by which bats resolve these infections or limit pathology remain unclear. To illuminate the bat immune response to coronaviruses, viruses with high public health significance, we will use serum proteomics to assess broad differences in immune proteins of uninfected and infected vampire bats (Desmodus rotundus).
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Simantha: Simulation for Manufacturing
Data provided by National Institute of Standards and Technology
Simantha is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it focuses on asynchronous production lines with finite buffers. It also provides functionality for modeling the degradation and maintenance of machines in these systems. Classes for five basic manufacturing objects are included: source, machine, buffer, sink, and maintainer. These objects can be defined by the user and configured in different ways to model various real-world manufacturing systems.
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Source: https://github.com/usnistgov/simantha
Asynchronous AM Bench 2022 Challenge Data: Real-time, simultaneous absorptance and high-speed Xray imaging
Data provided by National Institute of Standards and Technology
The absolute laser absorption was measured simultaneously with X-ray imaging during laser melting of Ti-6Al-4V solid metal. The data included here are the time-resolved absolute absorbed power and the Xray images acquired at the same time, along with timing data for synchronization. Also included is information about the experimental configuration including applied laser power, laser beam spatial profile, and the experimental setup. A text document is included that describes all files.
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Code used to produce terms list in the work "NLP-Driven Electron Microscopy Ontology Development"
Data provided by National Institute of Standards and Technology
This is a collection of code written by Maurice Curran that was used to process the Microscopy and Microanalysis conference proceeding corpus into word products described in the publication "NLP-Driven Electron Microscopy Ontology Development". The scripts are written in Python, to be used in the following order:
1. SettingUpTextFiles.py and CopyingText.py to get the raw text files;
2. SentenceConversion.py;
3. reference_remover.py;
4. testing.py and testingavg.py;
5. SentenceCreator.py;
6. matscholar_model.py to get matscholar tags;
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GIAB Benchmarking of HG002 Assemblies from HPRC Year 1 Bakeoff
Data provided by National Institute of Standards and Technology
The Human Pangenome Reference Consortium (HPRC) tested which combination of current genome sequencing and automated assembly approaches yields the most complete, accurate, and cost-effective diploid genome assemblies with minimal manual curation. Assemblies were generated for GIAB HG002. Variant calls from twenty-nine assemblies were evaluated by NIST using dipcall v0.3 (https://github.com/lh3/dipcall) to produce variant calls when aligned to GRCh38.
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KAIROS Evaluation Software
Data provided by National Institute of Standards and Technology
The KAIROS Evaluation Software Suite was developed by NIST in support of evaluation of DARPA's Program on Knowledge Directed Artificial Intelligence Reasoning Over Schemas (KAIROS). Some of the capabilities of this software include:
* calculating a variety of metrics and scores indicative of performance of individual KAIROS systems
* processing and format conversion of KAIROS system output, data annotations, and human assessment results
* analyzing metrics, scores, and assessment results
* generating statistics and charts summarizing these results
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Data set for "Evaluating fit-for-purpose cell viability assays that are sensitive to proliferative capacity"
Data provided by National Institute of Standards and Technology
This dataset is associated with the manuscript "Evaluating fit-for-purpose cell viability assays that are sensitive to proliferative capacity". This dataset consists of 12 individual studies containing Jurkat cell proliferation data and viability assay data. A README file describes the data sets.
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