Internet of Things (IoT) is comprised of interacting networks of physical, computational, and human components that coordinate to fulfill time-sensitive functions in their environment. The development of these systems spans all industrial sectors and demands collaborative effort between research and development teams from multiple institutions. Realizing the full potential of IoT requires interoperability between heterogeneous systems and development processes supported by robust platforms for experimentation and testing across domains.

This data set contains the data/information used to plot the graphs published in the 2022 Nat. Comm. article (titled "Amontons-Coulomb-like slip dynamics in acousto-microfluidics") of authors A. Quelennec, J.J. Gorman and D.R. Reyes.

This dataset contains CSV files for the figures in the paper titled "Restricted Domain Compressive Sensing for Antenna Metrology".

Round 9 Test Dataset

Round 9 Holdout Dataset

The American Community Survey (ACS) Public Use Microdata Sample (PUMS) contains a sample of responses to the ACS. The ACS PUMS dataset includes variables for nearly every question on the survey, as well as many new variables that were derived after the fact from multiple survey responses (such as poverty status). Each record in the file represents a single person, or, in the household-level dataset, a single housing unit.

The Public Use Microdata Sample (PUMS) for Puerto Rico (PR) contains a sample of responses to the Puerto Rico Community Survey (PRCS). The PRCS is similar to, but separate from, the American Community Survey (ACS). The PRCS collects data about the population and housing units in Puerto Rico. Puerto Rico data is not included in the national PUMS files. It is published as a state equivalent file and has a State FIPS code of "72".

Round 9 Train Dataset

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)

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.