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8 results for “RCD”
CaRCC Research Computing and Data (RCD) Workforce Survey Data 2021 - Part 2
<p>Data sets to accompany "Compensation of Academic Research Computing and Data Professionals"</p> <p>Paper citation: Christina Maimone, Carrie Brown, Kimberly Grasch, Chris Reidy, and Ashley Stauffer. 2023. Compensation of Academic Research Computing and Data Professionals. In Proceedings of Practice and Experience in Advanced Research Computing (PEARC23). ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3569951.3593599</p> <p>Survey questions: Maimone, Christina, Yockel, Scott, Middelkoop, Timothy, Alameda, Jay, Stauffer, Ashley, & Neeser, Amy. (2021). CaRCC Research Computing and Data (RCD) Workforce 2021 Census Questions (1.0). Zenodo. https://doi.org/10.5281/zenodo.5914431</p>
CaRCC Research Computing and Data (RCD) Workforce Survey Data 2021 - Part 1
<p>Datasets and analysis to accompany "Characterizing the US Research Computing and Data (RCD) Workforce"</p> <p>Paper: Christina Maimone, Scott Yockel, Timothy Middelkoop, Ashley Stauffer, and Chris Reidy. 2022. Characterizing the US Research<br> Computing and Data (RCD) Workforce. In Practice and Experience in Advanced Research Computing (PEARC ’22), July 10–14, 2022,<br> Boston, MA, USA. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3491418.3530289</p>
Remondis Contamination Dataset (RCD)
<p>The Remondis Contamination Dataset (RCD) is a novel and challenging collection of images designed to facilitate the development and evaluation of computer vision models for the detection of plastic-bag contamination in waste collection scenarios. This dataset was meticulously curated from historical records of Remondis, a waste management company, and open source online resources which provides real-world visuals captured by cameras installed on waste collection trucks. The images cover various scenarios including waste bins, truck hoppers, different camera zooms, angles, and lighting conditions, accurately reflecting the complexities of waste collection environments.</p> <p><strong>Dataset Details:</strong></p> <ul> <li><strong>Format:</strong> JPEG images, RGB color scheme</li> <li><strong>Dimensions:</strong> 640 x 480 pixels</li> <li><strong>Resolution:</strong> 72 pixels-per-inch</li> <li><strong>Annotations:</strong> Bounding box annotations for plastic-bag candidates</li> <li><strong>Annotation Format:</strong> KITTI</li> <li><strong>Contaminant Types:</strong> Plastic bags including coles bags, woolie bags, color bags, white bags, black bags, and packaging material</li> <li><strong>Total Images:</strong> 1125 samples (968 for training, 157 for validation)</li> <li><strong>Total Bounding Box Annotations:</strong> 1851 (1588 for training, 263 for validation)</li> </ul> <p><strong>Key Challenges:</strong> The RCD dataset poses unique challenges due to visual similarities between plastic bags and non-contaminants, such as white paper or dark portions in the image. The diverse range of plastic bag types, along with the intricacies of waste collection environments, make the task of plastic-bag contamination detection particularly demanding.</p> <p><strong>Applications:</strong> The RCD dataset serves as a benchmark for practical waste segregation tasks, including the detection of various waste contaminants, characterization of waste contents, and counting occurrences of specific waste types. The dataset is a valuable resource for researchers, practitioners, and enthusiasts working on computer vision applications in waste management and environmental monitoring.</p> <p><strong>Citation:</strong> If you use the RCD dataset in your research, please consider citing it using the following reference:</p> <p>U. Iqbal, J. Barthelemy, P. Perez, and T. Davies, “Edge-Computing Video Analytics Solution for Automated Plastic-Bag Contamination Detection: A Case from Remondis,” <em>Sensors</em>, vol. 22, no. 20, p. 7821, Oct. 2022, doi: 10.3390/s22207821.</p>
The Comparison of RCD Versus BCD in Newly Diagnosed Waldenström Macroglobulinemia
ClinicalTrials.gov study NCT02844322. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Interferon Gamma-1b Administered Topically for Macular Edema/Intraretinal Schisis Cysts in Rod-Cone Dystrophy (RCD) and Enhanced S-Cone Syndrome (ESCS)
ClinicalTrials.gov study NCT02338973. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Novel type of EATL evolving from mucosal γδ-T-cells in a RCD type I patient
GEO Series GSE56425. Homo sapiens. 1 samples. Type: Genome variation profiling by genome tiling array.
Double-Blind, Multi-Center, Randomized Study to Assess the Efficacy and Safety of Velneperit (S-2367) and Orlistat Administered Individually or Combined With a Reduced Calorie Diet (RCD) in Obese Subj
ClinicalTrials.gov study NCT01126970. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PCD Versus RCD for the Treatment of Patients With Waldenstrom's Macroglobulinemia
ClinicalTrials.gov study NCT02971982. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.