This CODMAC level 3 data set contains the key parameters of the Inertial Measurement Package. In particular, it provides information on the gyroscope attitude measurements on a global scale and individual. It covers the period from launch in 2004, through the 3 Earth and 1 Mars flyby, plus the hibernation phases, plus the asteroid flybys and finally covers the Prelanding, comet escort & Extension phases of the prime target of the mission. The prime target is comet 67P/Churyumov-Gerasimenko 1 (1969 R1). This version V1.0 is the first version of this dataset.

The Plasma Wave Data were submitted to National Space Science Data Center after the Principal Investigator's death (Scarf) by S. Chang of TRW. For the magnetic field data, the time interval submitted was Sept 9 - 14, 1985 was included. That information, as well as an explanation of the reformatted data is detailed.

This dataset provides RF data from software defined ratio (SDR) measurement results of a few cases: A. one 4G LTE link, B. two LTE links, C. one LTE link and one Wi-Fi link. The LTE links were emulatedby USRP B210 units and an open-source software (srsRAN), and the Wi-Fi link was emulated by a pair ofWi-Fi commercial development boards. This dataset includes metadata and performance results (ina spreadsheet format) and I/Q baseband sample data (in a binary float point format). Though specifictrade names are mentioned, they should not be construed as an endorsement of that product. Other productsmay work as well or better.The spreadsheet files provide the mapping among some system parameters (such as the SDR received powerand SINR) and key performance indicators (KPIs), such as throughput and packet drop rate. The I/Q datafiles provide the digital samples of the received signals at the receivers (LTE or Wi-Fi).This dataset can be used to support research topics such as multi-cell LTE system performance evaluationand optimization, spectrum sensing and signal classification, and AI and machine learning, beside others.

This repo contains open-source channel measurement data for research and development purposes.

Copyright Thomas Choi, University of Southern California. The data may be used for non-commercial purposes only. Redistribution prohibited. If you use this data for results presented in research papers, please cite as follows: Data were obtained from [Choi2021Using], whose data are available at [WiDeS_Choi2021Using].

[Choi2021Using] T. Choi et al., "Using a drone sounder to measure channels for cell-free massive MIMO systems," arXiv preprint arXiv:2106.15276, 2021.

[WiDeS_Choi2021Using] T. Choi et al., “Open-Source Cell-Free Massive MIMO Channel Data 2020”. URL: https://wides.usc.edu/research_matlab.html

To ensure meaningful comparison of test scores across groups or time, measurement invariance (i.e., invariance of the general factor structure and the values of the measurement parameters) across groups or time must be examined. However, many empirical examinations of measurement invariance of psychological/educational questionnaires need to address two issues: Using the appropriate model for ordinal variables (e.g., Likert scale items), and handling missing data. In two Monte Carlo simulations, this study examined the performance of one full-information-maximum-likelihood-based method and five multiple-imputation-based methods to obtain tests of measurement invariance across groups for ordinal variables that have missing data. Our results indicate that the full-information-maximum-likelihood-based method and one of the multiple-imputation-based methods generally have better performance than the other examined methods, though they also have their own limitations.

Data repository for measurements from a wind measurement station with a lidar in Bangladesh. Data will be uploaded in batches, on a monthly basis, and will transmit daily reports on 1 minute average values. Please refer to the country project page for additional outputs and reports, including the installation reports: http://esmap.org/re-mapping/bangladesh. For access to maps and GIS layers, please visit the Global Wind Atlas: https://globalwindatlas.info/

Units of Measurement

Quarterly GDP and its components (1995 constant prices) by type of data, measurement unit, transactions and period. National. Quarterly GDP and its components (1995 constant prices).

Over time, economic statistics are refined. This implies that data measuring recent economic events are typically less reliable than older data. Such time variation in measurement error affects optimal forecasts. Measurement error, and its time variation, are of course unobserved. Our contribution is to show how estimates of these can be recovered from the variance of revisions to data using a behavioural model of the statistics agency. We illustrate the gains in forecasting performance from exploiting these estimates using a real-time dataset on UK aggregate expenditure data.

This dataset includes the position data of a two-dimensional gantry system experiment in which the G-code commands for the gantry were transmitted through a wireless communications link. The testbed is composed of four main components related to the operation of the gantry system. These components are the gantry system, the Wi-Fi network, the RF channel emulator, and the supervisory computer. In the experimental study, we run a scenario in which the gantry tool moves sequentially between four positions and has a preset dwell at each of the positions. The wireless channel impact is produced through the RF channel emulator. First, we consider the benchmark channel with free-space log-distance path loss and ideal channel impulse response (CIR) which has no multi-path. Second, we consider a measured delay profile of an industrial environment where the CIR is experimentally measured and processed to be deployed using the channel emulator and to reflect the industrial environment impact. Moreover, time-varying log-normal shadowing is introduced due to the fluctuations in the signal level because of obstructions. The variance of zero-mean log-normal shadowing is set through the emulator. In order to collect the position information of the gantry system tool, we used a vision tracking system. In this dataset, we attached a meta_data.csv file to map various files to their corresponding parameters. A README.doc file is included to describe the measurement apparatus.

Ground measurement data from 3 solar meteorological stations in Senegal. Data contains 1 minute average values for solar radiation, air temperature, relative humidity, barometric pressure, precipitation, wind speed at 3m, wind speed calculated for 10m, wind direction and cleaning events. For download access to GIS layers, please visit the Global Solar Atlas: http://globalsolaratlas.info/

Data repository for solar measurements from 4 WB funded stations in Armenia. The four solar measuring stations and the associated measurement campaign have been financed by the Scaling-Up Renewable Energy Program (SREP) as part of the preparation activities for the Armenia Utility-Scale Solar Project. This project, which is being jointly supported by SREP and the World Bank, will deliver the first utility-scale solar plant in the country. The locations for the measuring stations were selected by the Renewable Resources and Energy Efficiency Fund, the project’s implementing entity, following the recommendations from Effergy, the expert consultant firm. For download access to GIS layers, please visit the Global Solar Atlas: http://globalsolaratlas.info/

This is a Jupyter notebook that explores the linked Survey of Earned Doctorates (SED)-Universities: Measuring the Impacts of Research on Innovation, Competitiveness, and Science (UMETRICS) data to get a better sense of how these two data sources might be used together. Furthermore, the purpose of this notebook is to allow participants to think critically about what exactly is being measured and how missingness in the data should be interpreted. This notebook was developed for the Fall 2021 Applied Data Analytics training facilitated by the National Center for Science and Engineering Statistics (NCSES) and Coleridge Initiative.

Data repository for measurements from 12 wind masts in Pakistan. Data transmits daily reports for wind speed, wind direction, air pressure, relative humidity and temperature. Please refer to the country project page for additional outputs and reports, including the installation reports: http://esmap.org/node/3058. For access to maps and GIS layers, please visit the Global Wind Atlas: https://globalwindatlas.info/ Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP).

1. Ordination and clustering methods are widely applied to ecological data that are nonnegative, for example species abundances or biomasses. These methods rely on a measure of multivariate proximity that quantifies differences between the sampling units (e.g. individuals, stations, time points), leading to results such as: (i) ordinations of the units, where interpoint distances optimally display the measured differences; (ii) clustering the units into homogeneous clusters; or (iii) assessing differences between pre-specified groups of units (e.g., regions, periods, treatment-control groups). 2. These methods all conceal a fundamental question: To what extent are the differences between the sampling units, computed according to the chosen proximity function, capturing the "size" in the multivariate observations, or their "shape"? "Size" means the overall level of the measurements: for example, some samples contain higher total abundances or more biomass, others less. "Shape" mea...

This file contains the data and minimal working example code for the results underlying the manuscript:
"Direct measurement of darkness using a standard single-photon avalanche photodiode"
JOSA A 42:506/arXiv: 2410.06691
authored by T.H.A. van der Reep, D. Molenaar and W. Löffler

See README in file for instructions.

Simulated computational basis measurement outcomes from the noisy simulation of the sequences in "Application 1: random gate sequences". The simulation was performed using Qiskit with 1000 shots per sequence. After each Clifford gate layer, a gate-independent unitary noise channel was inserted as described in the paper. Additionally, each single- and two-qubit gate is affected by depolarizing noise.

Data repository for measurements from 10 wind masts in Nepal. Data will be uploaded in batches, on a monthly basis, and will transmit daily reports for wind speed, wind direction, air pressure, relative humidity and temperature. Please refer to the country project page for additional outputs and reports, including the installation reports: http://esmap.org/re-mapping/nepal For access to maps and GIS layers, please visit the Global Wind Atlas: https://globalwindatlas.info/ Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP).

State capacity is a core concept in political science research, and it is widely recognized that state institutions exert considerable influence on outcomes such as economic development, civil conflict, democratic consolidation, and international security. Yet, researchers across these fields of inquiry face common problems involved in conceptualizing and measuring state capacity. In this article, we examine these conceptual issues, identify three core dimensions of state capacity, and develop the expectation that they are mutually supporting and interlinked. We then use Bayesian latent variable analysis to estimate state capacity at the conjunction of indicators related to these dimensions. We find strong interrelationships between the three dimensions and produce a new, general-purpose measure of state capacity with demonstrated validity for use in a wide range of empirical inquiries. It is hoped that this project will provide effective guidance and tools for researchers studying the causes and consequences of state capacity.

The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs within industry, with an emphasis on leveraging artificial intelligence, data-driven methodologies, and high-throughput and automated workflows for accelerating x-ray-based structural analysis for materials development and manufacturing. Participants, predominantly from industry, gathered in-person at ICDD headquarters in Newtown Square, Pennsylvania. The data collected during this workshop is published in this data publication. This data is interpreted in the workshop report, which cites this dataset. Certain equipment, instruments, software, or materials, commercial or non-commercial, are identified in this dataset. Such identification does not imply recommendation or endorsement of any product or service by NIST, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.