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54 results for “information flow”
MOTIVE - tiMe-OpTimized contextual Information flow on unmanned VEhicles project experimental results
<p>The experimentation data were collected during the 6th Fed4FIRE+ Open Call (https://www.fed4fire.eu/) using the mobile nodes of the w-iLab.t (link) testbed. During this Open Call we proposed to evaluate the performance of an optimization model for temporal control of the transmission of messages from an IoT mobile device. This mechanism is based on a network condition model that transits from favourable to adverse conditions and vice versa. All these transitions are monitored and validated through our system (change detection and optimal stopping). If a network is performing properly then the transmission control can be relaxed to exploit available resources.The main contribution of MOTIVE is to apply a sequential decision-making process (DMP) on IoT devices that leverages the on-line derived network statistics to efficiently control their telemetry measurements transmission.</p> <p>Our data collected from the experimentation using the testbed's devices consists of network related information, packet error rate and latency. We collected data from a completely functional mobile node that operates in a saturated network and five mobile nodes in the same circumstances. Saturated conditions were generated by data produced by twenty static sensors for the duration of the each experiment. On each run we collected more than 2 * 105 samples. The comparative assessment we did was based on five different policies of decision making: i) no-policy model, ii) the heuristic threshold based model in which the transmission of the messages is paused when a specific threshold of quality network is below a threshold, iii) TOCP model which overviews the quality of network in normal mode and gets in pausing mode when a change is detected; the pausing period lasts for a specific threshold and then it is activated again, iv) TOCP-DRP and the v) fair TOCP-DRP which enters in pausing mode if a change is indicated by TOCP decision making model.</p> <p>The datasets include the packet error rate and the latency of each device, for each experiment, and the critical areas found during the experiments (most saturated areas).</p> <p>The datatset includes for each scenario(experiment) the participating devices and the Latency and Packet Error Rate(PER) per policy( NoPolicy, Heuristic, TOCP, TOCPDRP, TOCPDRPFAIR), apart from scenarioA(single node) where only four policies are present, since the TOCPDRPFAIR applies with more that one participating nodes.</p>
Figure 4 in Optimizing biodiversity informatics to improve information flow, data quality, and utility for science and society
Figure 4. Graphical representation of original and recently modified pathways for feedback regarding Primary Biodiversity Data, showing information transfer among users, providers, and aggregators. Such feedback consists of suggested improvements or additions to data fields, for example a change in species identification or a newly determined georeference. The diagrams contrast two complementary mechanisms: (a) the original feedback loop (currently dominant); and (b) the emerging feedback pendulum (proposed for expansion). In a: (1) the user sends feedback to the provider (e.g., a given natural history museum); (2) if the provider makes a corresponding change to its database, the updated information is sent to the aggregator; and (3) that information becomes available for query by all users. In practice, because many providers do not consistently make such changes (denoted by an X), users do have access to updated information (dashed line). In b: (1) the user sends feedback to the aggregator; (2) the aggregator simultaneously both annotates the record (visible to all users) and sends the suggested information to the provider; (3) if the provider makes a corresponding change to its database, the updated information is sent to the aggregator; and (4) the aggregator makes the updated information available for query by all users. Note that even if a provider takes no action regarding the suggested information, the annotations placed by the aggregator are nevertheless available to users. Additionally, because the quantifications of data quality and use described in the text allow for benchmarks that can be tracked over time, we anticipate that the feedback pendulum will help providers become more successful in justifying and securing funding to make data improvements based on feedback from users.
Dataset for a physics informed deep learning method with adaptively weighted loss for modeling soil water flows
<p>The data for the 11 scenarios generated by Hydrus-1D is located in data.zip</p> <p>The code for the physics-informed neural networks with adaptively weighted loss used to simulate water flow in loam soils is located at PINN_adaptively_weighted_loss_loam.zip</p>
The flow of axonal information among hippocampal subregions: 2. Patterned stimulation sharpens routing of information transmission
<p>The subregions of the hippocampal formation are essential for episodic learning and memory formation, yet the spike dynamics of each region contributing to this function are poorly understood, in part because of a lack of access to the inter-regional communicating axons. Here we reconstructed hippocampal networks confined to four subcompartments in 2D cultures on a multi-electrode array that monitors individual communicating axons. In our novel device, somal and axonal activity were measured simultaneously with the ability to ascertain the direction and speed of information transmission. Each subregion and inter-regional axons had unique power-law spiking dynamics, indicating differences in computational functions. After stimulation, spiking and burst rates decreased in all subregions, spikes per burst generally decreased, intraburst spike rates increased, and burst duration decreased, which were specific for each subregion. These changes in spiking dynamics post-stimulation were found to occupy a narrow range, consistent with the maintenance of the network at a critical state. Functional connections between the subregion neurons and communicating axons in our device revealed homeostatic network routing strategies post-stimulation in which spontaneous feedback activity was selectively decreased and balanced by decreased feed-forward activity. Post-stimulation, the number of functional connections per array decreased, but the reliability of those connections increased. The networks maintained a balance in spiking and bursting dynamics in response to stimulation and sharpened network routing. These plastic characteristics of the network revealed the dynamic architecture of hippocampal computations in response to stimulation by selective routing on a spatiotemporal scale in single axons.</p>
Data for paper "Information flow between motor cortex and striatum reverses during skill learning"
<p>Simultaneous spiking activity and local field potential (LFP) recordings from motor cortex (M1) and dorsolateral striatum (DLS) during learning of a reach-to grasp task.<br>Deposited data include spiking activity and LFP recordings, reaching trajectories, andi single-trial success data for the 8 animals included in the paper "Information flow between motor cortex and striatum reverses during skill learning".</p>
Information Flow in the Old Tibetan Annals-I
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The dataset of "Characteristics of Urban Interaction Network in Shandong Province from the Perspective of Traffic Flow and Information Flow"
<p>There are the datasets of the research named "Characteristics of Urban Interaction Network in Shandong Province from the Perspective of Traffic Flow and Information Flow".</p>
Checking Secure Information Flow of CoCoME using UPPAAL
<p>Model of the CoCoME case study for the UPPAAL model checker. Also includes auto-generated verification models for checking the information flow security of CoCoME, and the corresponding verification properties.</p>
Data Set of Publication on Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams
<p>This data set contains the evaluation data of our publication on "<a href="https://doi.org/10.1016/j.jss.2021.111138">Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams</a>". The data set contains an overview on our implementation, description of the evaluation cases, and the evaluation results.</p> <p>The application to produce this data is available in another data set, which is linked to this data set.</p>
BIOnTop project components and information flow
<p>The project components pictured in a diagram. BIOnTOP project will deliver recyclable-by-design cost competitive packaging solutions that can be mechanically recycled, industrially/home composted or even suitable for anaerobic digestion.</p>
Modeling water flow and solute transport in unsaturated soils using physics-informed neural networks trained with geoelectrical data
<p>Numerical codes and results for the article: Modeling water flow and solute transport in unsaturated soils using physics-informed neural networks trained with geoelectrical data</p>
On the Correspondence between Information Flow, Noninterference, and Symbolic Execution - Benchmark Set
<p>The benchmark set the paper ``On the Correspondence between Information Flow, Noninterference, and Symbolic Execution'' evaluates.</p>
On the Correspondence between Information Flow, Noninterference, and Symbolic Execution - Benchmark Set
<p>The benchmark set the paper ``On the Correspondence between Information Flow, Noninterference, and Symbolic Execution'' evaluates.</p>
The flow of axonal information among hippocampal subregions: 2. Patterned stimulation sharpens routing of information transmission
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Data from: Occipital alpha activity during stimulus processing gates the information flow to object-selective cortex
Given the limited processing capabilities of the sensory system, it is essential that attended information is gated to downstream areas, whereas unattended information is blocked. While it has been proposed that alpha band (8–13 Hz) activity serves to route information to downstream regions by inhibiting neuronal processing in task-irrelevant regions, this hypothesis remains untested. Here we investigate how neuronal oscillations detected by electroencephalography in visual areas during working memory encoding serve to gate information reflected in the simultaneously recorded blood-oxygenation-level-dependent (BOLD) signals recorded by functional magnetic resonance imaging in downstream ventral regions. We used a paradigm in which 16 participants were presented with faces and landscapes in the right and left hemifields; one hemifield was attended and the other unattended. We observed that decreased alpha power contralateral to the attended object predicted the BOLD signal representing the attended object in ventral object-selective regions. Furthermore, increased alpha power ipsilateral to the attended object predicted a decrease in the BOLD signal representing the unattended object. We also found that the BOLD signal in the dorsal attention network inversely correlated with visual alpha power. This is the first demonstration, to our knowledge, that oscillations in the alpha band are implicated in the gating of information from the visual cortex to the ventral stream, as reflected in the representationally specific BOLD signal. This link of sensory alpha to downstream activity provides a neurophysiological substrate for the mechanism of selective attention during stimulus processing, which not only boosts the attended information but also suppresses distraction. Although previous studies have shown a relation between the BOLD signal from the dorsal attention network and the alpha band at rest, we demonstrate such a relation during a visuospatial task, indicating that the dorsal attention network exercises top-down control of visual alpha activity.
Supplementary Information for "Deciphering controls of pore-pressure evolution on sediment bed erosion by debris flows"
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Original data and code for Kang, Mooshagian, and Snyder (2024) Functional organization of posterior parietal cortex circuitry based on inferred information flow
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Efficiently characterizing quantum information flow, loss and recovery in the central spin system
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Raw Data for Data Set of Publication on Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams
<p>This data set contains the build script, software and intermedia results that we used to create the result data set for the publication "<a href="https://doi.org/10.1016/j.jss.2021.111138">Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams</a>".</p>
Supplementary information to "Actual sources of life cycle impacts: elementary processes and flows causing environmental impacts for a typical Brazilian building"
<p>Electronic Supplementary Material with the underlying data of the manuscript entitled "Actual sources of life cycle impacts: elementary processes and flows causing environmental impacts for a typical Brazilian building", including:</p> <p>- A spreadsheet containing all the data used in the LCA of the analyzed building</p> <p>- A PDF file with an explanation of the process contribution function used in the analysis</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.