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133 results for “self-organization”

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zenodo32/100

Understanding the driver, mechanism, and role of self-organized synchronization of human crowds

<p>Raw data in &quot;Understanding the driver, mechanism, and&nbsp;role of&nbsp;self-organized synchronization of human crowds&quot;</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Data from "Connecting large-scale meteorological patterns to extratropical cyclones in CMIP6 climate models using self-organizing maps"

<p>The following files were used as data and analysis in the article &quot;Connecting large-scale meteorological patterns to extratropical cyclones in CMIP6 climate models using self-organizing maps&quot; (<a href="https://doi.org/10.1029/2022EF003211">https://doi.org/10.1029/2022EF003211</a>).&nbsp;In the study, we applied&nbsp;self-organizing maps (SOMs) as an automated machine-learning approach to characterize the large-scale meteorological patterns (LSMP) and associated frequency and intensity of discrete extratropical cyclone (ETC)&nbsp;events over the northeastern U.S. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during 1980 -&nbsp;2019. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMP&nbsp;and ETC events identified in the SOM. Please see the published paper for more details. Here we have archived:&nbsp;</p> <p>- data pre-processing scripts</p> <p>- code to run the self-organizing map analysis</p> <p>- code to&nbsp;calculate the SOM and ETC statistics</p> <p>- composites of 500-hPa geopotential&nbsp;height for each dataset as organized by the SOM</p> <p>- ETC tracking script&nbsp;and tracking output for each dataset</p> <p>- SOM output for each dataset&nbsp;</p>

openagpl-3.0-or-laterJul 2023View details →
dryad32/100

Redefining floristic zones in the Korean Peninsula using high-resolution georeferenced specimen data and self-organizing maps

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publicAug 2021View details →
dryad32/100

Self-organization and information transfer in Antarctic krill swarms

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publicNov 2021View details →
dryad32/100

Data from: Self-organizing dominance hierarchies in a wild primate population

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publicAug 2015View details →
dryad32/100

Data from: Local interactions and self-organized spatial patterns stabilize microbial cross-feeding against cheaters

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publicFeb 2019View details →
zenodo28/100

Data used for manuscript "High-integrity human intervention in ecosystems: Tracking self-organization modes"

<p>Data used for manuscript &quot;High-integrity human intervention in ecosystems: Tracking self-organization modes&quot;.</p> <p>This includes large aerial images taken from the northern Negev in Israel, extracted areas within them, and metadata on these areas.</p>

opencc-by-4.0Jun 2020View details →
dryad28/100

Data from: Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-efficient Wireless Sensor Networks

Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, the current study proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25 %. The results showed that the performance improved by 13 % in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs.

opencc-zeroDec 2016View details →
dryad28/100

Data from: Modeling the internet of things, self-organizing and other complex adaptive communication networks: a cognitive agent-based computing approach

Background: Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose: It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method: We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results: The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

opencc-zeroDec 2015View details →
zenodo28/100

Supplementary material to "Manipulation of Robustness in Self-Organizing Systems on the the Example of UAV Defense"

<p>Supplementary material to the bachelor thesis &quot;Manipulation of Robustness in Self-Organizing Systems on the the Example of UAV Defense&quot;.</p>

opencc-by-4.0Nov 2021View details →
zenodo28/100

A precise and general FRET-based method for monitoring structural transitions in protein self-organization

<p>Data underlying the figures in the manuscript</p>

opencc-by-4.0Feb 2022View details →
zenodo28/100

Self-Organized Patterns in Predator-Prey Droplets

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opencc-by-4.0May 2024View details →
zenodo28/100

Engineered Self-Organization for Resilient Robot Self-Assembly with Minimal Surprise - Paper Material

<p>Supplementary&nbsp;Videos&nbsp;</p>

opencc-by-4.0Feb 2019View details →
zenodo28/100

THE ROLE OF SELF-ORGANIZATION IN EARLY CHILDHOOD EDUCATION: A MONTESSORI METHOD APPROACH

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opencc-by-4.0Oct 2024View details →
zenodo28/100

Precise and scalable self-organization in mammalian pseudo-embryos (v1)

<p>This is a test of a dataset repository on the Sandbox version of Zenodo with the main immunofluorescence data analyzed in the paper <em>Precise and scalable self-organization in mammalian pseudo-embryos</em> (<a href="https://arxiv.org/abs/2303.17522">https://arxiv.org/abs/2303.17522</a>).<br> Each folder corresponds to an experiment. The name indicates to which figures it was used in in the paper.<br> Each subfolder corresponds to a plate of gastruloids and contain the max projections of each individual gastruloid in .tif. Raw .czi available under request.</p> <p>See&nbsp; <a href="https://gitlab.pasteur.fr/tglab/gastruloids_precisionandscaling">https://gitlab.pasteur.fr/tglab/gastruloids_precisionandscaling</a> for an example of image analysis pipeline.</p>

openJul 2023View details →
dryad28/100

Data from: Density-dependent and species-specific effects on self-organization modulate the resistance of mussel bed ecosystems to hydrodynamic stress

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publicMar 2021View details →
dryad28/100

Data from: Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-efficient Wireless Sensor Networks

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publicNov 2017View details →
dryad28/100

Cellular dialogues that enable self-organization of dynamic spatial patterns

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publicNov 2019View details →
dryad28/100

Data from: Evolution of self-organized task specialization in robot swarms

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publicJul 2015View details →
dryad28/100

Data from: The shaping role of self-organization: linking vegetation patterning, plant traits and ecosystem functioning

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publicMar 2019View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record