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49 results for “performance variability”
Experimental data for the motor learning study performed: "Promoting Motor Variability During Robotic Assistance Enhances Motor Learning of Dynamic Tasks"
<p>The dataset contains the kinematic data and the questionnaire responses for a robot-assisted motor learning study performed in the Motor Learning and Neurorehabilitation Laboratory at University of Bern. The details of the study are described in [doi: 10.3389/fnins.2020.600059]. The kinematic data for each participant is stored as a data frame inside a “pickle” (serialized python object) file. The questionnaire responses are stored as a “csv” file. The variables inside the files are explained in “DataframeVariableDescription.rtf”. For questions, please contact oezhan.oezen@artorg.unibe.ch or L.MarchalCrespo@tudelft.nl.</p>
Spain's marginal electricity mix and its relevance for assessing the environmental performance of installations with variable load or power
<p>This upload contains the Supplementary Information file and the underlying data as Excel-file for the Journal article with the same name. More specifically, it provides time series of the Spanish electricity generation mix for the years 2015-2020 for energy system analysis and the life cycle inventory data for import into openLCA and re-use in combination with the ecoinvent databse (Version 3.7.1). Further details are available on request.</p>
Potential Metabolic Activity, Catalase Activity, Performance traits and Morphological variables of 94 individuals belonging to Podarcis muralis species used in the analysis
<p>Potential Metabolic Activity (ETS26_P, ETS31_P, ETS36_P), Catalase Activity (CAT_P), Performance traits (BITE, SPRINT,CLIMB, MANO) and Morphological variables (snout-vent length (SVL), trunk length (TRL), pileus length (PL), head length (HL), head width (HW), head height (HH), fore limb length (FLL) and hind limb length (HLL) of 94 individuals belonging to <em>Podarcis muralis</em> species. The data was used in the analysis of the paper entitled: Is It Function or Fashion? An Integrative Analysis of Morphology, Performance, and Metabolism in a Colour Polymorphic Lizard, by authors Verónica Gomes, Anamarija Žagar, Guillem Pérez i de Lanuza, Tatjana Simčič and Miguel A. Carretero, published in the journal Diversity 2022, 14, 116. <a href="https://doi.org/10.3390/d14020116">https://doi.org/10.3390/d14020116</a></p>
Data for publication "The ZiCOS-M CO2 sensor network: measurement performance and CO2 variability across Zürich"
<p>Please see README.md for a description of this package. </p> <p>This work was funded by the European Union's Horizon 2020 research and innovation programme, grant agreement number 101037319, named Pilot Applications in Urban Landscapes - towards integrated city observatories for greenhouse gases (PAUL) and is known as ICOS Cities.</p> <p> </p>
Data and analysis scripts for the OSDI 2018 paper "Taming Performance Variability"
<p>This repository contains our raw datasets and notebooks for analyzing performance results of benchmarks executed on CloudLab machines.</p> <p>File organization:</p> <ul> <li><code>notebooks/</code> - Various Jupyter notebooks containing our analysis. Contains analysis on our main dataset as well as some analysis on one-off collections. <ul> <li><code>bench-lib/common.py</code> - Common python utilities that are shared by the notebooks.</li> <li><code>disk-process.ipynb</code> - Main notebook for analysis of disk performance (both HDDs and SSDs).</li> <li><code>e-vs-cov.ipynb</code> - Analysis of E vs CoV for selected configurations.</li> <li><code>env-test.ipynb</code> - Version information for Python and installed packages.</li> <li><code>kernel-testing-Nd.ipynb</code> - Analysis of data using kernel two-sample testing in one and multiple dimensions..</li> <li><code>mem-process.ipynb</code> - Main notebook for analysis of memory performance.</li> <li><code>network-process.ipynb</code> - Main notebook for analysis of network performance.</li> <li><code>normality.ipynb</code> - Notebook for the high-level analysis of normality (or lack of it) in the collected data.</li> <li><code>quantile-regression.ipynb</code> - Notebook for Quantile Regression analysis for both disk and memory data.</li> <li><code>temporal-analysis.ipynb</code> - Notebook to search for/analyze any temporal aspects to our dataset.</li> <li><code>testbed-coverage.ipynb</code> - Analysis of the extent to which we were able to cover all of the test hardware.</li> <li><code>variability.ipynb</code> - Notebook for the high-level analysis of variability.</li> <li><code>wisc-disktests.ipynb</code> - <strong>ONE-OFF RUN</strong>: Analyzing variation in fio results on Wisconsin SSDs over repeated runs.</li> <li><code>wisc-memtests.ipynb</code> - <strong>ONE-OFF RUN</strong>: Analysis of benchmark order for various Wisconsin hardware/memory configurations.</li> </ul> </li> <li><code>data/</code>. Contains a dump of the dataset (as of 04/04/2018). This dataset is generated by running the code contained in the <a href="https://gitlab.flux.utah.edu/emulab/cloudlab-orchestration">https://gitlab.flux.utah.edu/emulab/cloudlab-orchestration</a> repository. Some additional one-off collections are contained here as well. <ul> <li><code>CoV-Summary/</code> - Data derived from our raw dataset for use by <code>notebooks/e-vs-cov.ipynb</code>.</li> <li><code>nodes/</code> - Simple list of all nodeids for each hardware type for use in <code>notebooks/testbed-coverage.ipynb</code>.</li> <li><code>raw-data/</code> - Raw .sql (and .csv files made from it) file containing a dump of our primary dataset through April 4th, 2018, used for the majority of the notebooks. Filtering is done in our notebooks to exclude data past April 1st, 2018 (as well as remove runs that appear to contain impossible execution conditions).</li> <li><code>wisc-disktests/</code> - <strong>ONE-OFF RUN</strong>: Results from successive runs of fio on Wisconsin SSDs. Used in <code>notebooks/wisc-disktests.ipynb</code>.</li> <li><code>wisc-memtests/</code> - <strong>ONE-OFF RUN</strong>: Results from memory benchmarks run with specific orderings on various Wisconsin machines. Used in <code>notebooks/wisc-memtests.ipynb</code>.</li> <li><code>wisc-pagemaps/</code> - <strong>ONE-OFF RUN</strong>: Virtual-to-Physical memory address mappings for tests run in <code>wisc-memtests/</code>. Used in <code>notebooks/wisc-memtests.ipynb</code>.</li> </ul> </li> </ul>
Performance of Cities in IDL 2019 Variables
<p>These pictures show the performance of cities in IDL 2019 variables. More about IDL see: https://idl.institutomongeralaegon.org/</p>
Recording and analysing physical control variables used in clarinet playing: A Musical Instrument Performance Capture and Analysis Toolbox (MIPCAT)
<p>Measuring fine-grained physical interaction between the human player and the musical instrument can significantly improve our understanding of music performance. This article presents a Musical Instrument Performance Capture and Analysis Toolbox (MIPCAT) that can be used to capture and to process the physical control variables used by a clarinettist while performing music. This includes both a measurement apparatus with sensors and a software toolbox for analysis. Several of the components used here can also be applied in other musical contexts. Applied to the clarinet, the instrument sensors record blowing pressure, reed position, tongue contact and sound pressures in the mouth, mouthpiece and barrel. Radiated sound and multiple videos are also recorded to allow details of the embouchure and the instrument’s motion to be determined. The software toolbox can synchronise measurements from different devices, extract time-variable descriptors, segment by notes and excerpts, and summarise descriptors per note, phrase or excerpt. An example of its application is given showing how to compare performances from different musicians.Measuring fine-grained physical interaction between the human player and the musical instrument can significantly improve our understanding of music performance. This article presents a Musical Instrument Performance Capture and Analysis Toolbox (MIPCAT) that can be used to capture and to process the physical control variables used by a clarinettist while performing music. This includes both a measurement apparatus with sensors and a software toolbox for analysis. Several of the components used here can also be applied in other musical contexts. Applied to the clarinet, the instrument sensors record blowing pressure, reed position, tongue contact and sound pressures in the mouth, mouthpiece and barrel. Radiated sound and multiple videos are also recorded to allow details of the embouchure and the instrument’s motion to be determined. The software toolbox can synchronise measurements from different devices, extract time-variable descriptors, segment by notes and excerpts, and summarise descriptors per note, phrase or excerpt. An example of its application is given showing how to compare performances from different musicians.Measuring fine-grained physical interaction between the human player and the musical instrument can significantly improve our understanding of music performance. This article presents a Musical Instrument Performance Capture and Analysis Toolbox (MIPCAT) that can be used to capture and to process the physical control variables used by a clarinettist while performing music. This includes both a measurement apparatus with sensors and a software toolbox for analysis. Several of the components used here can also be applied in other musical contexts. Applied to the clarinet, the instrument sensors record blowing pressure, reed position, tongue contact and sound pressures in the mouth, mouthpiece and barrel. Radiated sound and multiple videos are also recorded to allow details of the embouchure and the instrument’s motion to be determined. The software toolbox can synchronise measurements from different devices, extract time-variable descriptors, segment by notes and excerpts, and summarise descriptors per note, phrase or excerpt. An example of its application is given showing how to compare performances from different musicians.</p>
Exascale Potholes for HPC: Execution Performance and Variability Analysis of the Flagship Application Code HemeLB
<p>Performance measurement and analysis of parallel applications is often challenging, despite many excellent commercial and open-source tools being available. Currently envisaged exascale computer systems exacerbate matters by requiring extremely high scalability to effectively exploit millions of processor cores. Unfortunately, significant application execution performance variability arising from increasingly complex interactions between hardware and system software makes this situation much more difficult for application developers and performance analysts alike.<br> </p> <p>This work considers the performance assessment of the HemeLB exascale flagship application code from the EU HPC Centre of Excellence (CoE) for Computational Biomedicine (CompBioMed) running on the SuperMUC-NG Tier-0 leadership system, using the methodology of the Performance Optimisation and Productivity (POP) CoE. Although 80% scaling efficiency is maintained to over 100,000 MPI processes, disappointing initial performance with more processes and corresponding poor strong scaling was identified to originate from the same few compute nodes in multiple runs, which later system diagnostic checks found had faulty DIMMs and lacklustre performance. Excluding these compute nodes from subsequent runs improved performance of executions with over 300,000 MPI processes by a factor of five, resulting in 190x speed-up compared to 864 MPI processes. While communication efficiency remains very good up to the largest scale, parallel efficiency is primarily limited by load balance found to be largely due to core-to-core and run-to-run variability from excessive stalls for memory accesses, that affect many HPC systems with Intel Xeon Scalable processors. The POP methodology for this performance diagnosis is demonstrated via a detailed exposition with widely deployed `standard' measurement and analysis tools.</p>
BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance
<p>This Zenodo repository contains 100 copies of the model BERT fine-tuned on the MNLI dataset, created for the paper "BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance." Please see the project GitHub page for more details about using these models and how to cite any such usage: https://github.com/tommccoy1/hans/tree/master/berts_of_a_feather</p>
Does external pneumatic compression treatment between bouts of overreaching resistance training sessions exert differential effects on molecular signaling and performance-related variables compared to passive recovery? An exploratory study
<p>Supplemental Information: Data set respective to manuscript published in PLOS ONE titled "<strong>Does external pneumatic compression treatment between bouts of overreaching resistance training sessions exert differential effects on molecular signaling and performance-related variables compared to passive recovery? An exploratory study" </strong></p>
Brain signal variability within individually defined alpha frequency range as a marker of cognitive performance
<p><strong>General description</strong></p> <p>Eight subjects with severe acquired brain injury and fourteen healthy participants took part in the study. EEG was recorded at 19 international standard 10-20 system locations with a sampling frequency of 256 Hz, using an ear-linked reference and the <em>Fpz</em> location as ground.</p> <p>For all participants three-minute baseline recordings were obtained, one with eyes open and one with eyes closed. Both groups participated in the same sustained attention task while EEG data was being collected. Healthy participants underwent 10 blocks of 225 trials while ABI patients were given 7 blocks of 225 trials.</p> <p> </p> <p><strong>Content of the zip files uploaded here</strong></p> <p>Each zip file contains matlab files with raw EEG data plus a channel that contains information of the triggers used in the sustained attention task. In addition, log files contain the latency of the experimental events and responses.</p> <p> </p> <p><strong>Description of the task</strong></p> <p>The Continuous Temporal Expectancy Task (CTET), developed by O’Connell <em>et al.</em> (2009), is a computerized task that measures sustained attention. Participants are required to notice and respond with a click of the mouse when an alternating pattern (Fig. 1) is randomly displayed for a longer interval than the regular interval (800ms). Participants practiced the experiment initially to ensure they obtained 100% accuracy at the end of the training trials. Longer target duration should be easily detected during the training block, but challenging when performed over an extended period of time. The healthy group detected the target difference at 1120ms (duration 40% longer than the standard), whereas the ABI group detected a difference at 1200ms latency (duration 50% longer than the standard). The hand that responded to the longer stimulus with a mouse-click was counterbalanced in each block.</p>
Data for: The climatic variability hypothesis and trade–offs in thermal performance in coastal and inland populations of Mimulus guttatus
<p>Ecologists and evolutionary biologists have long predicted that organisms in more climatically variable environments should be adapted to handle a wider range of conditions. This intuitive idea, known as the Climatic Variability Hypothesis, has gained mixed support from empirical studies. We tested the Climatic Variability Hypothesis in a novel system by comparing the thermal breadth of coastal and inland populations of <em>Mimulus guttatus</em>. To quantify thermal breadth, we performed a thermal performance experiment and built performance curves. Using these performance curves, we also evaluated evidence for a breadth–performance trade–off and the Hotter–is–Better hypothesis. We did not find support for the Climatic Variability Hypothesis; coastal and inland populations did not differ in thermal breadth. However, we found evidence for a breadth performance trade–off and the Hotter–is–Better hypothesis. Surprisingly, the two most inland populations differed the most in the thermal performance traits we evaluated. Our results highlight the importance of explicitly measuring thermal performance to test explanations of species distribution patterns and the need to examine alternative mechanisms by which organisms occupy different climatic regimes.</p>
Population variability in thermal performance of pre-spawning adult Chinook salmon
Open the record for dataset details and reuse information.
Data for: The climatic variability hypothesis and trade–offs in thermal performance in coastal and inland populations of Mimulus guttatus
Open the record for dataset details and reuse information.
Thermal performance under constant temperatures can accurately predict insect development times across naturally variable microclimates
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Data from Climate adaptability in hydrological models: variable storage capacity to improve performance under contrasting climates.
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Fatigability and Physical Performance: Effects of Resistance Training Variables Manipulation
ClinicalTrials.gov study NCT03619070. IPD Sharing: NO. Countries: 1. Publications: 24.
Effects of Ten-Weeks Progressive Resistance Training on Neuromuscular Performance, Mobility, Heart Rate Variability and Sleep Quality in Persons With Multiple Sclerosis
ClinicalTrials.gov study NCT04452760. IPD Sharing: YES. Countries: 1. Publications: 2.
Neuromuscular Variables and Performance in Mexican Weightlifters
ClinicalTrials.gov study NCT07277335. IPD Sharing: NO. Countries: 1. Publications: 3.
Within-crown variability in herbivore performance and leaf traits
<ol> <li>Functional trait variation within individual plants is predicted to have important ecological consequences. However, our understanding of the sources contributing to subindividual<i> </i>trait heterogeneity, and the ramifications thereof, is poor.</li> <li>In a common garden, we sampled multiple genotypes of mature trembling aspen (<i>Populus tremuloides</i>) at different vertical crown levels and quantified the contributions of genetic, spatial and biotic (herbivory) factors to subindividual morphological and chemical leaf trait variance. Bioassays using gypsy moth (<i>Lymantria dispar</i> L.) caterpillars were conducted to study impacts of spatial and genotypic factors on insect performance.</li> <li>Crown position was the primary source of subindividual variation in leaf morphology and explained more of the variance in morphological traits than tree genotype. Effects of spatial, genetic and biotic factors on within-crown chemistry were highly compound-specific. For many compounds, changes in within-crown concentrations differed among genotypes, revealing that genotypic variation not only contributes to phytochemical diversity among individuals of the same population, but also affects subindividual chemical trait heterogeneity. For many defense related compounds, total within-crown variance itself differed among genotypes and was in many cases a heritable trait. Bioassays revealed that effects of crown position on caterpillar performance varied among tree genotypes and caterpillar sexes.</li> <li>We demonstrate that even relatively small trees can express subtle but distinct levels of within-crown leaf-trait variation. In aspen, this variation is shaped not only by spatial factors, but also by genetics and to a lesser degree by herbivory. Within-crown variation in defense chemistry might itself provide a defensive phenotype against herbivores and contribute to the biological diversity of canopy insect communities.</li> </ol>
ScienceDex guides
Understand access before you commit
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.