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System Level Evaluation of UE-to-Network Relays in D2D-enabled LTE Networks
Data provided by National Institute of Standards and Technology
The data in this document corresponds to the results presented in the paper entitled "System Level Evaluation of UE-to-Network Relays in D2D-enabled LTE Networks", to appear in the proceeding of the 2019 IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (IEEE CAMAD 2019)
Modified:
MCV QoE End to End Access Time Software Code
Data provided by National Institute of Standards and Technology
This codeset was developed for the QoE MCV end to end access time measurement methodology.
Modified:
Source: https://github.com/usnistgov/accessTime
MCV QoE Microcontroller Firmware
Data provided by National Institute of Standards and Technology
Code for the TI MSP4030F5529LP board for PTT application with MCV QoE software
Modified:
Source: https://doi.org/10.18434/M32086
MCV QoE End to End Access Time Measurement Data
Data provided by National Institute of Standards and Technology
Data collected includes audio device characterization (latency/delay). End to end access time of Land Mobile Radios (LMR) including direct mode operation and trunked mode operation.
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Characterization of zinc carboxylates in an oil paint test panel [dataset]
Data provided by National Institute of Standards and Technology
This dataset contains X-ray EDS (energy dispersive spectroscopy), FTIR (Fourier transform infrared spectroscopy), and DART-MS (Direct analysis in real time mass spectrometry) data and analysis files that
can be used to reproduce the results from the paper:
Modified:
ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models
Data provided by National Institute of Standards and Technology
This software is a Python module for estimating uncertainty in predictions of machine learning models. It is a Python package that calculates uncertainties in machine learning models using bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work.
Modified:
Source: https://pages.nist.gov/ml_uncertainty_py/
Bayesian Hierarchical Models for Service Life Prediction of Polymers Data and Code
Data provided by National Institute of Standards and Technology
The data and code that accompanies the book chapter Bayesian Hierarchical Models for Service Life Prediction of Polymers.
Modified:
Source: https://doi.org/10.18434/M32080
Computation of 3-d matrices of maximal trace over rotations
Data provided by National Institute of Standards and Technology
The programs here compute 3x3 matrices of maximal trace over rotation matrices from input matrices. A dxd matrix M is of maximal trace over rotation matrices if given any dxd rotation matrix U, the trace of UM does not exceed that of M.
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Measurement Data for a Wireless Force Seeking Apparatus
Data provided by National Institute of Standards and Technology
Cyber-physical systems are systems governed by the laws of physics that are tightly controlled by computer-based algorithms and network-based sensing and actuation. Wireless communication technology is envisioned to play a primary role in conducting the information flows within such systems. A practical industrial wireless use case involving a robot manipulator control system, an integrated wireless force-torque sensor, and a remote vision-based observer is constructed and the performance of the cyber-physical system is examined.
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Brignac et al. Marine Debris Polymers on Main Hawaiian Island Beaches, Sea Surface, and Seafloor Supporting Information
Data provided by National Institute of Standards and Technology
Supporting information documents for Brignac et al manuscript entitled, "Marine Debris Polymers on Main Hawaiian Island Beaches, Sea Surface, and Seafloor." Files include raw data tables of each debris item that was categorized and measured as well as additional figures of interpreted data.
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