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130
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ShareScore release 0.9.0
Dataset results
130 results for “Power Systems”
Data from: Modularity and rates of evolutionary change in a power-amplified prey capture system
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Data from: Levers and linkages: Mechanical trade-offs in a power-amplified system
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Data from: Muscle tradeoffs in a power-amplified prey capture system
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Supporting data for Loik et al. 2017 Wavelength-Selective Solar Photovoltaic Systems: Powering greenhouses for plant growth at the food-energy-water nexus. Earth's Future
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Data on IEEE and Synthetic Test Power Systems for Oriol Cartiel's PhD
<p>The data used in my PhD thesis comes from internet repositories (see within files). It is based on detailed information from both IEEE n-bus test power systems and synthetic power grid test cases developed by the scientific community. The dataset, stored in spreadsheet format (.xlsx), includes comprehensive technical details such as line impedances, equivalent internal impedances, locations of generators, load demands and their locations, and shunt element specifications. All values are normalized to per-unit (pu), assuming a base power of 100 MVA. Additionally, the reference to the internet repository is available in the same file for potential further consultation.</p>
Data for "Resolving Structures of Paramagnetic Systems in Chemistry and Materials Science by Solid-State NMR: the Revolving Power of Ultra-Fast MAS"
<p>Raw NMR data</p>
Evaluation of a Powered Stapler System on Surgical Interventions Required During Laparoscopic Sleeve Gastrectomy
ClinicalTrials.gov study NCT02358785. IPD Sharing: YES. Countries: 1. Publications: 0.
Interactive POWER Rehabilitation System on Rehabilitation Training for Patients With Parkinson's Disease
ClinicalTrials.gov study NCT05046236. IPD Sharing: NO. Countries: 1. Publications: 0.
To Evaluate the Clinical Impact of the Point Powered System
ClinicalTrials.gov study NCT07135947. IPD Sharing: NO. Countries: 1. Publications: 0.
AI-Powered DIY Screening System for Diabetic Retinopathy
ClinicalTrials.gov study NCT06892353. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparison of a Powered Bone Marrow Biopsy Device With a Manual System
ClinicalTrials.gov study NCT01535313. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Amplitude Vascular Systems (AVS) Lithotripsy POWER PAD 2 Trial
ClinicalTrials.gov study NCT06457685. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of a Mobile AI-powered Decision Support System for Insulin Dosing and Glucose Prediction in Type 1 Diabetes: The glUCModel Clinical Trial Protocol
ClinicalTrials.gov study NCT07304778. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
AI-Powered Scoliosis Auto-Analysis System Multicenter Development and Validations
ClinicalTrials.gov study NCT05146193. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Assessment of a storage system to deliver uninterrupted therapeutic oxygen during power outages in resource-limited settings
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Advanced Space Power Systems (ASPS): Advanced Microelectromechanical (MEMs) Photovoltaic Systems (AMPS) Project
<p>Develop new cell and blanket technologies and manufacturing processes that reduce overall array costs</p><p>&bull;Cells: develop new cell technology comparable to SOA with reduced cost at various production levels</p><p>&bull;Blankets: develop blanket technology compatible with the space environment at costs less than SOA</p><p>&bull;Electrical Interconnects and Cell Protection: develop automated processes for stringing cells and providing protection from the space environment</p><p>&bull;Lab-scale development of technologies with greater power density and cost reduction through multiple programs tested for reliability by thermal cycling and space plasma interactions</p><p>&bull;Flight-sized cell/blanket demonstrators for integration in SOA solar array structures</p>
Integrated systems-biology platform for power-to-gas technology
GEO Series GSE218145. Methanothermobacter thermautotrophicus; Methanothermobacter marburgensis. 12 samples. Type: Expression profiling by high throughput sequencing.
Supplementary Data: The role of hydro power, storage and transmission in the decarbonization of the Chinese power system
<p>This is the supplementary data to the publication:</p> <p>The role of hydro power, storage and transmission in the decarbonization of the Chinese power system</p> <p><a href="https://doi.org/10.1016/j.apenergy.2019.02.009">https://doi.org/10.1016/j.apenergy.2019.02.009</a></p> <p>This dataset includes:</p> <ul> <li>Hourly wind, solar and electricity load time series for 31 Chinese provinces and their calculations</li> <li>Reservoir hydro stations' effective capacity and inflow time series (details are referred to <a href="https://zenodo.org/record/1471322">Daily hydro power time series (1979-2016) for 43 Chinese reservoir hydro stations</a>)</li> <li>Wind and solar power's geographical potential calculations</li> <li>Directory p_nom_min contains existing wind and solar power capacities up to end of 2014</li> <li>Long-range transmission topologies</li> </ul> <p>The bash command scripts initiate three sets of simulations respectively: CO2 emission reduction sweep; 38-year weather input sensitivity; constraining transmission volume.</p> <p>Dependencies:</p> <ul> <li><a href="https://github.com/PyPSA/PyPSA">Pypsa</a></li> <li><a href="https://github.com/FRESNA/vresutils">vresutils</a></li> <li><a href="https://github.com/AUESG/REatlas-client">RE-atlas(optional)</a></li> </ul>
Probabilistic Model-Based Diagnosis for Electrical Power Systems
We present in this article a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. Our probabilistic approach is formally well-founded, and based on Bayesian networks and arithmetic circuits. We pay special attention to meeting two of the main challenges model development and real-time reasoning often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-touse specication language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In experiments with the ADAPT Bayesian network, which contains 503 discrete nodes and 579 edges and produces accurate results, the time taken to compute the most probable explanation using arithmetic circuits has a mean of 0.2625 milliseconds and a standard deviation of 0.2028 milliseconds. In comparative experiments, we found that while the variable elimination and join tree propagation algorithms also perform very well in the ADAPT setting, arithmetic circuit evaluation was an order of magnitude or more faster. **Reference:** O. J. Mengshoel, M. Chavira, K. Cascio, S. Poll, A. Darwiche, and S. Uckun. "Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study”. Accepted to IEEE Transactions on Systems, Man, and Cybernetics, Part A, 2009.
Qualitative Event-based Diagnosis with Possible Conflicts Applied to Spacecraft Power Distribution Systems
Model-based diagnosis enables efficient and safe operation of engineered systems. In this paper, we describe two algorithms based on a qualitative event-based fault isolation framework augmented with model-based fault identification that are applied to spacecraft power distribution systems. Although based on a common framework, the fundamental difference between the two algorithms is that one uses a global model for residual generation, fault isolation, and fault identification; whereas the other uses a set of minimal submodels computed using Possible Conflicts. We describe the implementation of the two algorithms and compare their diagnosis results on a representative spacecraft power distribution system.
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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.