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14 results for “Fuzzy logic”
Samples of Rectified Transfemoral Sockets with Fuzzy-Logic-Based Decision Support System
<p>This dataset contains sample rectified transfemoral sockets as an output of the fuzzy-logic DSS.</p> <p>This work was supported by the EU Horizon2020 research and innovation project SocketSense, No 825429.</p> <p>Relevant paper DOI: <a href="https://doi.org/10.3390/s21113743">https://doi.org/10.3390/s21113743</a></p>
Fuzzy Logic Control for ABS ESR 8
<p>Results of the Fuzzy Logic Control for ABS from the HIL test rig at TU Ilmenau.</p>
Fuzzy Logic Automated Insulin Regulation
ClinicalTrials.gov study NCT03040414. IPD Sharing: NO. Countries: 4. Publications: 11.
Data from: Using fuzzy logic to determine the vulnerability of marine species to climate change
Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biological and ecological attributes of many marine species, as well as inherent uncertainties in the assessment process, climate change vulnerability assessments in the marine environment frequently focus on a limited number of taxa or geographic ranges. As climate change is already impacting marine biodiversity and fisheries, there is an urgent need to expand vulnerability assessment to cover a large number of species and areas. Here, we develop a modelling approach to synthesize data on species-specific estimates of exposure, and ecological and biological traits to undertake an assessment of vulnerability (sensitivity and adaptive capacity) and risk of impacts (combining exposure to hazards and vulnerability) of climate change (including ocean acidification) for global marine fishes and invertebrates. We use a fuzzy logic approach to accommodate the variability in data availability and uncertainties associated with inferring vulnerability levels from climate projections and species' traits. Applying the approach to estimate the relative vulnerability and risk of impacts of climate change in 1074 exploited marine species globally, we estimated their index of vulnerability and risk of impacts to be on average 52 ± 19 SD and 66 ± 11 SD, scaling from 1 to 100, with 100 being the most vulnerable and highest risk, respectively, under the 'business-as-usual' greenhouse gas emission scenario (Representative Concentration Pathway 8.5). We identified 157 species to be highly vulnerable while 294 species are identified as being at high risk of impacts. Species that are most vulnerable tend to be large-bodied endemic species. This study suggests that the fuzzy logic framework can help estimate climate vulnerabilities and risks of exploited marine species using publicly and readily available information.
Data from: Integrating fuzzy logic and statistics to improve reliabile definition of biogeographic regions and transition zones
The present study uses the amphibian species of the Mediterranean Region to develop a consistent procedure based on fuzzy sets with which biogeographic regions and biotic transition zones can be objectively detected and reliably mapped. Biogeographical regionalizations are abstractions of the geographical organization of life on Earth that provide frameworks for cataloguing species and ecosystems, for answering basic questions in biogeography, evolutionary biology and systematics, and for assessing priorities for conservation. On the other hand, limits between regions may form sharply defined boundaries along some parts of their borders, whereas elsewhere they may consist of broad transition zones. The fuzzy set approach provided a heuristic way to analyze the complexity of the biota within an area; significantly different regions were detected whose mutual limits were sometimes fuzzy, sometimes clearly crisp. Most of the regionalizations described in the literature for the Mediterranean Region present a certain degree of convergence when they are compared within the context of fuzzy interpretation, as many of the differences found between regionalizations are located in transition zones, according to our case study. Compared to other classification procedures based on fuzzy sets, the novelty of our method is that both fuzzy logic and statistics are used together in a synergy in order to avoid arbitrary decisions in the definition of biogeographic regions and transition zones.
Software for control of autonomous robots using fuzzy logic controllers tuned by genetic algorithms
<p>This software implements the autonomous control of a robot by using a fuzzy logic controller tuned by a genetic algorithm. The software was written in C programming language for Windows (SDK). A description of the software can be found in the research publication "Arsene, C.T.C., & Zalzala, A.M.S., "Control of autonomous robots using fuzzy logic controllers tuned by genetic algorithms", In Proc Congress on Evolutionary Computation, Vol. 1, pp. 428-35, Washington DC, 1999, IEEE Computer Science Press, ISBN 0-7803-5536-9". Possibly the software to be used also for simulation of Nano-robots.</p>
Prediction of Compressive Strength of Concrete with Silica, Ash and Fiber Using Fuzzy Logic Method
<p>Prediction of Compressive Strength of Concrete with Silica, Ash and Fiber Using Fuzzy Logic Method</p> <p>References</p>
Data from: Integrating fuzzy logic and statistics to improve reliabile definition of biogeographic regions and transition zones
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Data from: Using fuzzy logic to determine the vulnerability of marine species to climate change
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Software for control of autonomous robots using fuzzy logic controllers tuned by genetic algorithms
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MODELING OF TELECOMMUNICATION NETWORKS BASED ON FUZZY LOGIC TECHNOLOGY
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Songs in Isolation IV: Fuzzy Logic
<p>Text from YouTube description box: "Week three million four hundred and twenty-two of Melbourne lockdown. I've got the brain-fuzz, what've you got? I used a screen recording of the Mind Monitor App for iPad and used the OSC data from my own brain-hole (captured by the Muse EEG device) to "control" the effects and sounds through Max/MSP and Ableton."</p> <p>This piece was written in September 2020 in response to the heightening of my brain fog due to the stress of the second Melbourne COVID-19 lockdown, working on a doctoral project during the pandemic, and the pressures of remaining positive and supportive in my role as an educator while anti-lockdown protests became a regular feature of Melbourne life (McGowan 2020). For my doctoral thesis, This étude was also used to test Muse 2 (a consumer EEG device) as an embodied sound controller and alternative to glove-based gesture control.</p> <p>I use voice and the <em>Muse 2</em> EEG device to control distortion and other effects and generate MIDI (Musical Instrument Digital Interface) notes. Delta, theta, alpha, beta, and gamma brain waves were routed into <em>Max</em> via OSC via iPad and a secondary application to accept <em>Muse 2</em>’s data. Each brain wave type controlled a different sound source. One voice layer sings an “ah” with and without vocal fry (individual pops of air through the vocal folds) and an undertone. The video was created by recording the device output while listening to the final work.</p> <p>The piece is named for the logic theory, its common-purpose use in washing machine advertisements as mundane aspects of life, brain fog (cognitive fuzziness), and the control of distortion (or fuzz) in turning my brain waves into real numbers between 0 and 1.</p>
Fuzzy Logic Selection as a New Reliable Tool to Identify Gene Signatures in Breast Cancer - the INNODIAG Study
GEO Series GSE53958. Homo sapiens. 151 samples. Type: Expression profiling by array.
Assessment of potential bioenergy supply using GIS-based fuzzy logic and network optimization: The Potential for switchgrass-based bioenergy in Missouri
<p>This data package is a supplementary material for the article, named "Assessment of potential bioenergy supply using GIS-based fuzzy logic and network optimization: The Potential for switchgrass-based bioenergy in Missouri."</p> <p> </p>
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
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.