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33 results for “millimeter wave”
Dataset for Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation
<p>Dataset of paper "Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation".</p> <p>The measurement data contains indoor mapping results using millimeter-wave 5G NR signals at 28 GHz. The measurement campaign was conducted in an indoor office environment in Hervanta Campus of Tampere University. Six different sets of measurements contain the range profiles after the proposed radar processing. The shared data contains the IQ data of both transmit and receive signals used during the measurement campaign.</p> <p>The file "main.m" shows how to process and plot the shared data.</p>
Dual-band Reflectarray Antennas Using Integrated Resonant and Non-Resonant Natures of Metallic Waveguide Elements at Millimeter Wave Frequencies
<p>Pure metallic reflectarray antennas have good power efficiency and low fabrication cost, which were limited to single band operation. A dual-band reflectarray antenna is developed for two directional beams by two feeds. The reflecting elements are metal waveguides, and have novel properties of both resonant and non-resonant modes at the two frequency bands. The low and high frequency bands can be easily separated by the cutoff frequency of waveguide modes. The phase changing mechanisms via ray optics and fundamental waveguide modes, respectively provide simple formulations for elemental structure design of directional beams. Radiation characteristics of the linear and circular polarizations are cross-examined with good performance by full-wave simulations using HFSS, FEKO and CST at 28 and 60 GHz bands for 5G front-haul network applications.</p>
Dataset for Radio-based Sensing and Indoor Mapping with Millimeter-Wave 5G NR Signals
<p>Dataset of paper "Radio-based Sensing and Indoor Mapping with Millimeter-Wave 5G NR Signals" presented in International Conference on Localization and GNSS (ICL-GNSS) 2020.</p> <p>The measurement data contains indoor mapping results using millimeter-wave 5G NR signals at 28 GHz. The measurement campaign was conducted at an indoor office environment in Hervanta Campus of Tampere University. Six different sets of measurements contain the range profiles after the proposed radar processing.</p> <p>The file "indoorMapping_processing.m" shows how to process and plot the shared data.</p> <p> </p> <p> </p>
Exploring the impact of varied background on quantification of soil carbon content using microwave and millimeter wave signal reflectance
<p>The quantification of soil carbon content is paramount to the advancement of soil carbon management practices, serving as the bedrock for the development and implementation of various carbon-negative and carbon-neutral technologies. These technologies are crucial in the battle against climate change and in enhancing soil health to boost agricultural productivity. Therefore, we employ an innovative sensor technology comprised of a compact array, including 18 pairs of radar transmitters (TX) and receivers (RX) within a microwave radar array sensor, alongside a configuration of 20 TX and 20 RX pairs in a millimeter wave radar array sensor. For this kind of setup to work, the sensors need to be carefully tested to make sure they can capture changes in the soil's carbon content over time and space.</p> <p>This dataset presents an exhaustive series of raw data aimed at evaluating the efficacy of these two sensor technologies in detecting soil carbon content. A distinctive aspect of this study is the examination of sensor performance across four divergent backgrounds—glass, metal, sponge, and wood surfaces—to ascertain the influence of background material on radar wave reflectance and, consequently, measurement accuracy. Furthermore, the investigation extends to the analysis of sensing distance as a critical parameter for classification accuracy, with the microwave radar array sensor tested across distances ranging from 1 inch to 4 inches and the millimeter wave radar sensor evaluated at intervals of 2.5 inches, 5 inches, 7.5 inches, and 10 inches. By providing a comprehensive dataset on the performance evaluation of cutting-edge sensor technologies, this study aims to facilitate further advancements in the field of soil carbon management, ultimately supporting the global effort to combat climate change through innovative and sustainable agricultural practices.</p>
Exploring the impact of varied background on quantification of soil carbon content using microwave and millimeter wave signal reflectance
Open the record for dataset details and reuse information.
Microwave and millimeter wave signals reflectance of soil carbon content
Open the record for dataset details and reuse information.
Millimeter Wave Point to Multipoint for Affordable High Capacity Backhaul of Dense Cell Networks
<p>This dataset contains the data to reproduce the graphs in the article: Millimeter Wave Point to Multipoint for Affordable High Capacity Backhaul of Dense Cell Networks", 2018 IEEE Wireless Communications and Networking Conference (IEEE WCNC 2018).</p>
Planar slow wave structures for millimeter-wave vacuum electron devices
<p>Underlying data corresponding to the conference paper: G. Ulisse, V. Krozer, "Planar slow wave structures for millimeter-wave vacuum electron devices", 47th European Microwave Conference (EuMC), Nuremberg, Germany, October 2017</p>
Study of Somatosensory Responses During Millimeter Waves Application
ClinicalTrials.gov study NCT04801550. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Millimeter Wave Therapy (MWT) for Analgesia After Total Knee Replacement
ClinicalTrials.gov study NCT00233831. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Millimeter-wave Multi-View Radar (MMVR) Dataset
<p><strong>Introduction</strong></p> <p>The Millimeter-wave Multi-View Radar (MMVR) dataset comprises 345K multi-view radar frames collected from 25 human subjects over 6 different rooms. It includes 446K annotated bounding boxes/segmentation instances, and 7.59 million annotated keypoints to support three perception tasks: object detection, pose estimation, and instance segmentation in the image plane.</p> <p>MMVR consists of 35 data sessions, each stored in a data folder with the format d<em>x</em>sy, where <em>x</em> represents the day and y the session index of that day when the data were collected.</p> <p>Within each data folder, data frames are grouped into 395 non-overlapping one-minute data segments. Each data segment is stored in a folder named using a three-digit, zero-filled convention based on the chronological order. For example, the first one-minute data segment is saved in the folder 000, while the second one-minute data segment is stored in the folder 001.</p> <p>Within each data segment folder, each data frame consists of 5 NPZ files: meta, radar, bounding boxes (bbox), keypoints (pose) and segmentation masks (mask). Each data frame is named using a five-digit, zero-filled convention based on the chronological order within the one-minute data segment.</p> <pre><code>Root/ ├── d1s1/ │ └── ... ├── d1s2/ │ ├── 000/ │ │ ├── 00000_meta.npz ... Meta info │ │ ├── 00000_radar.npz ... Horizontal/Vertical heatmaps │ │ ├── 00000_bbox.npz ... 2D Bounding Boxes │ │ ├── 00000_pose.npz ... 2D keypoints │ │ ├── 00000_mask.npz ... 2D Segmentation masks │ │ ├── 00001_meta.npz │ │ ├── 00001_radar.npz │ │ ├── 00001_bbox.npz │ │ ├── 00001_pose.npz │ │ ├── 00001_mask.npz │ │ . │ │ ├── 00899_meta.npz │ │ ├── 00899_radar.npz │ │ ├── 00899_bbox.npz │ │ ├── 00899_pose.npz │ │ └── 00899_mask.npz │ └── 001/ │ ├── 00000_meta.npz │ ├── 00000_radar.npz │ ├── 00000_bbox.npz │ ├── 00000_pose.npz │ ├── 00000_mask.npz . └── ... ├── d9s5/ │ └── ... └── d9s6/ └── ... </code></pre> <p> </p> <p><strong>At a Glance</strong></p> <ul> <li> <ul> <li>The size of the unzipped dataset is ~81.8 GB</li> <li>The MMVR dataset consists of 345K data frames with each frame including 5 NPZ files: meta, radar, bounding boxes (bbox), keypoints (pose) and segmentation masks (mask).</li> <li>The MMVR dataset is divided into four smaller chunks to facilitate easier downloads: three chunks of approximately 20 GB each and one chunk of 12 GB. <ul> <li>P1.zip (24.2 GB): <ul> <li>README.md and its related figure folder (figs)</li> <li>load_sample.ipynb: a python snippet to load and visualize a data frame</li> <li>data_split.npz: an npz file containing the predefined data splits (S1 or S2) for training, validation, and test sets of data segments under P1 and P2.</li> <li>all data frames under P1 (d1s1, d1s2, d2s2, d3s1, d3s2, d4s1)</li> </ul> </li> <li>P2_00.zip (20.4 GB): all data frames in d5s1 – d5s6 and d6s1 – d6s6</li> <li>P2_01.zip (21.6 GB): all data frames in d7s1 – d7s5 and d8s1 – d8s6</li> <li>P2_02.zip (11.7 GB): all data frames in d9s1 – d9s6</li> </ul> </li> </ul> </li> </ul> <p><strong>Citation</strong></p> <p>If you use the MMVR dataset in your research, please cite our contribution:</p> <pre><code>@inproceedings{MMVR2024, title={MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception}, author={M. Mahbubur Rahman and Ryoma Yataka and Sorachi Kato and Pu Perry Wang and Peizhao Li and Adriano Cardace and Petros Boufounos}, booktitle={Proceedings of European Conference on Computer Vision (ECCV)}, pages={}, year={2024} }</code></pre> <p><strong>License</strong></p> <p>The MMVR dataset is released under <a href="https://creativecommons.org/licenses/by-sa/4.0/">CC-BY-SA-4.0 license</a>.</p> <p>All data:</p> <pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2023 SPDX-License-Identifier: CC-BY-SA-4.0</code></pre>
Evaluation of a Millimeter Wave Emission Bracelet for Improving Parkinson's Disease Symptoms
ClinicalTrials.gov study NCT04648150. IPD Sharing: NO. Countries: 1. Publications: 0.
CAMEX-3 ER-2 Millimeter-wave Imaging Radiometer (MIR)
The CAMEX-3 ER-2 Millimeter-wave Imaging Radiometer (MIR) dataset is a browse-only dataset containing plots of brightness temperature measurements collected by the Millimeter-wave Imaging Radiometer (MIR) in support of the third field campaign in the Convection And Moisture EXperiment (CAMEX) series, CAMEX-3. This field campaign took place from August to September 1998 based out of Patrick Air Force Base in Florida, with the purpose of studying various aspects of tropical cyclones in the region. During CAMEX-3, MIR operated onboard the NASA ER-2 high-altitude research aircraft, collecting brightness temperature measurements of water vapor, clouds, precipitation, and other atmospheric features. The MIR browse image files are available from August 8 through September 8, 1998 in GIF format.
GPM Ground Validation Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) OLYMPEX
The GPM Ground Validation Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) OLYMPEX dataset consists of brightness temperatures from 9 channels as measured by CoSMIR when flown on the NASA DC-8 aircraft during the Global Precipitation Mission (GPM) Olympic Mountains Experiment (OLYMPEX) campaign. CoSMIR is a conical and cross-track scanning radiometer with frequencies centered at 50.3, 52.8, 89.0, 165.5, 183.31+/-1, 183.31+/-3, and 183.31+/-7 GHz. Data files are available from November 5, 2015 thru December 19, 2015 in HDF-5 format, with browse imagery files in PNG format containing brightness temperature time series plots.
GPM GROUND VALIDATION CONICAL SCANNING MILLIMETER-WAVE IMAGING RADIOMETER (COSMIR) IPHEx
The GPM Ground Validation Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) IPHEx dataset consists of brightness temperatures from 9 channels as measured by the CoSMIR instrument onboard the NASA ER-2 aircraft during the Global Precipitation Mission (GPM) Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign in North Carolina. The goal of IPHEx was to evaluate the accuracy of satellite precipitation measurements and use the collected data for hydrology models in the region. CoSMIR is a conical and cross-track scanning radiometer with frequencies centered at 50.3, 52.8, 89.0, 165.5, 183.31 ±1, 183.31±3, and 183.31±7 GHz. Data files are available from May 7, 2014 through June 14, 2014 in ASCII format, with browse images available in the postscript format.
Millimeter-wave Imaging Radiometer Brightness Temperatures, Wakasa Bay, Japan, Version 1
This data set includes calibrated brightness temperatures measured over Wakasa Bay in the Sea of Japan.
Global gene expression analysis reveals importance of thermal effect in cellular response to millimeter wave exposure
GEO Series GSE57135. Homo sapiens. 16 samples. Type: Expression profiling by array.
ADDITIVE EFFECTS OF MILLIMETER WAVES AND 2 DEOXYGLUCOSE CO-EXPOSURE ON THE HUMAN KERATINOCYTE TRANSCRIPTOME
GEO Series GSE83829. Homo sapiens. 16 samples. Type: Expression profiling by array.
Millimeter Wave Radar data of different people walking_part1
<p>The dataset contains complex signals coming from a mmWave FMCW radar system. Signal were acquired during a measurement campaign taken indoor and aimed to assess people’s different ways of walking. </p>
Millimeter Wave Radar data of different people walking_part2
<p>The dataset contains complex signals coming from a mmWave FMCW radar system. Signal were acquired during a measurement campaign taken indoor and aimed to assess people’s different ways of walking. </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.