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ShareScore release 0.9.0
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92 results for “Autonomy”
Expandable Variable-Autonomy Architecture Project
<p>Effective multi-level autonomous piloting systems require integration with safety-critical functions. The Expandable Variable-Autonomy Architecture&nbsp;(EVAA)&nbsp;project seeks to develop a hierarchal autonomous system framework that will depend on deterministic systems with higher authority to protect against catastrophic piloting faults and allow a lower level certification for the machine learning sub-systems. The multi-layered approach provides the framework for analytical systems that can learn, predict, and adapt to both routine and emergency situations.&nbsp;</p><p>The objective of the project is to develop an autonomous piloting system based on analytical and learning algorithms that are capable of making effective decisions, in both nominal and potentially catastrophic situations. This will develop a safety critical framework for certification of complex autonomous systems where a small but sufficient number of levels. The system will be integrated with a certified safety critical decision makers (such as vehicle health monitoring, collision avoidance, loss of control avoidance and restricts commands of higher level critical decision makers not certified to level A software. The project will integrate these systems onto a quad-rotor micro-UAV for inexpensive and quick flight testing of concepts and develop customized, low power hardware to house the control and decision making algorithms.</p><p>ASSUMPTIONS AND LIMITATIONS: The purpose of this CIF project is not to develop a full scale aircraft capable of these types of advancements, but only to develop a piloting system which make them possible. Initially, decisions associated with &ldquo;where to fly&rdquo; will be focused on and integrated into the algorithms. For this slice of the pie, the system will be required to navigate a potentially changing dense urban landscape. Routes will be planned based on time, distance, and potential risk. Additionally, terrain and obstacle avoidance algorithms will restrict these activities based on preloaded obstacle and terrain maps. Additionally, off nominal conditions such as loss of motor or other non-pre-programmed events will cause the aircraft to select landing or crashing locations based on population density maps, location of buildings, and other information. A hangar or small area will be turned into the urban city-center mockup with maps created of the mockup to facilitate flight test of concepts.</p><p><strong>Work to date: </strong>The hierarchical decision chain and framework, hardware, and embedded processing related to ground collision avoidance is in place for a sub-scale platform. Flight tests on a quad-rotor model helicopter demonstrated successful limitation of flight decisions when facing imminent ground collision.&nbsp;</p><p><strong>Looking ahead: </strong>The team is developing a full set of safety-critical functions for the sub-scale platforms and working to scale up to larger UAVs.&nbsp;</p><p><strong>Partners: </strong>University of California at Berkeley and Stanford University are developing algorithms, and the FAA is participating in the certification process.&nbsp;</p><p><strong>Benefits&nbsp;</strong></p><ul><li><strong>Increases safety: </strong>Integration of safety-critical functions improves outcomes in emergency situations.&nbsp;</li><li><strong>Certifiable: </strong>Removal of safety-critical functions from the autonomous control enables adaptable processes to be certified to a lower level.&nbsp;</li></ul><p><strong>Applications&nbsp;</strong></p><ul><li>UAVs and unmanned submersibles&nbsp;</li><li>Autonomous rail transport&nbsp;</li><li>Deep space exploration&nbsp;</li><li&g
Enabling Nanosat Mobility and Autonomy for Small Bodies Exploration Project
<p>Develop control and planning algorithms for a science-driven spacecraft/rover hybrid, such that the rover is able to autonomously reach designated targets and point instruments traverse performance meets science objectives of 20-30% of traverse distance.</p>
Effect of iodine on early stage thyroid autonomy
GEO Series GSE22118. Rattus norvegicus. 8 samples. Type: Expression profiling by array.
Targeted Escalation of Acetylated HOXB13 Regulated Super-Enhancers Promotes Prostate Tumor Autonomy
GEO Series GSE169134. Homo sapiens. 17 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Targeted Escalation of an Acetylated HOXB13-dependent Tyrosine Kinase Super-Enhancer Network Promotes Prostate Tumor Autonomy
GEO Series GSE169133. Homo sapiens. 7 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Growth Signaling Autonomy in Circulating Tumor Cells Aids Metastatic Seeding
GEO Series GSE215822. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Motorized Platform and Autonomy Among the Frail and Pre-frail Older Adult (PLATAUTONOMIE)
ClinicalTrials.gov study NCT02850731. IPD Sharing: NO. Countries: 0. Publications: 0.
"Patient Autonomie" in People With Cancer
ClinicalTrials.gov study NCT04517773. IPD Sharing: NO. Countries: 0. Publications: 0.
Muscle Strength and Functional Autonomy of Elderly Women
ClinicalTrials.gov study NCT01553396. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Bulk RNAseq analysis of CD4 CD8 double negative 3 (DN3) and CD4 CD8 double positive (DP) thymocytes in thymus autonomy and turnover
GEO Series GSE159218. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Single cell RNAseq coupled with TCR repertoire analysis of thymocytes in thymus autonomy and turnover
GEO Series GSE160135. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
Parental autonomy and control and bullying victimization
<p>Data set for <em>Parental autonomy and control and bullying victimization.</em></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.