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171 results for “performance prediction”
PREDICTING THE PERFORMANCE OF GREEN STORMWATER INFRASTRUCTURE USING MULTIVARIATE LONG SHORT-TERM MEMORY (LSTM) NEURAL NETWORK
<p>The expected performance of Green Stormwater Infrastructure (GSI) is typically quantified through numerical models based on hydrologic parameters and physics-based equations. With numerical models, the choice of a spatio-temporal discretization scheme for the computational domain is a strenuous task that requires extensive calibration and potentially lab-based parameters and experimentation. The performance of GSI has high temporal dynamics due to natural, anthropogenic, and climatic processes that are not well represented by the traditional physics-based hydrologic models, which are calibrated against only a few historical observations and have a user-defined and constrained set of computational outcomes. Deep learning-based predictive models, such as Long Short-Term Memory (LSTM) neural networks, offer an exciting opportunity to quantify GSI performance, accounting for its highly dynamic and constantly evolving nature by leveraging advancements in observational data. A LSTM regression can overcome some of the limitations associated with traditional hydrological models to aid the development of a fully data-informed GSI performance predictor. To demonstrate the LSTM and traditional model outcomes, both methods were applied to a rain garden in Villanova, PA, USA. Specifically, a LSTM model was used to predict the recession of ponded water depth in the rain garden using five years of observed data.</p>
Dataset for the article: Evaluating the Predictive Performance of Quick Methods for Estimating Task Difficulty and Student Ability in Automated Computer Programming Assessment
<p>This open access repository houses the dataset utilized in the research article:</p><p>Pankiewicz, M. (2023). Evaluating the Predictive Performance of Quick Methods for Estimating Task Difficulty and Student Ability in Automated Computer Programming Assessment. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 1413-1418). Vienna, Austria: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/primary/p/222666</p><p>The repository includes these files:</p><p>"submissions.csv": This data file captures the evaluation results of programming assignments. It is organized by the following columns:</p><p> </p><ul><li>"user_id": The unique identifier for each student who submitted the assignment.</li><li>"task_id": The unique identifier for each task that received submissions.</li><li>"submission_seconds": The number of seconds since the first user accessed the initial task's description within the system.</li><li>"correct": The outcome of the evaluation (1 denotes correct; 0 denotes incorrect).</li><li>"subject": The specific subject matter that the task addresses.</li></ul><p> </p><p>"subjects.csv": This data file comprises the roster of subjects for which tasks have been assigned within the system. It includes these columns:</p><p> </p><ul><li>"subject_id": The unique identifier for each subject.</li><li>"subject": The actual name of the subject.</li></ul><p> </p>
Virtual Flight Trajectory Prediction and Performance Optimization
<p>Data sets collected from running test flights using Prepar-3D flight simulator; extracted using FS-Flight Control software </p>
Metal halide thermoelectrics: prediction of high-performance CsCu2I3
<p>Optimized crystal structures of CsCu<sub>2</sub>I<sub>3</sub> (<em>Cmcm</em> and <em>Amm</em>2); force constant sets of <em>Amm</em>2 structure; and raw AMSET input/output files.</p>
Functional traits of young seedlings predict trade-offs in seedling performance in three neotropical forests
<ol> <li>Understanding the mechanisms that promote the coexistence of hundreds of species over small areas in tropical forest remains a challenge. Many tropical tree species are presumed to be functionally equivalent shade-tolerant species that differ in performance trade-offs between survival in shade and the ability to quickly grow in sunlight.</li> <li>Variation in plant functional traits related to resource acquisition is thought to predict variation in performance among species, perhaps explaining community assembly across habitats with gradients in resource availability. Many studies have found low predictive power, however, when linking trait measurements to species demographic rates.</li> <li>Seedlings face different challenges recruiting on the forest floor and may exhibit different traits and/or performance trade-offs than older individuals face in the eventual adult niche. Seed mass is the typical proxy for seedling success, but species also differ in cotyledon strategy (reserve vs photosynthetic) or other seedling traits. These can cause species with the same average seed mass to have divergent performance in the same habitat.</li> <li>We combined long-term studies of seedling dynamics with functional trait data collected at a standard developmental stage in three diverse neotropical forests to ask whether variation in coordinated suites of traits predicts variation among species in demographic performance.</li> <li>Across hundreds of species in Ecuador, Panama, and Puerto Rico, we found seedlings displayed correlated suites of leaf, stem, and root traits, which strongly correlated with seed mass and cotyledon strategy. Variation among species in seedling functional traits, seed mass, and cotyledon strategy were strong predictors of trade-offs in seedling growth and survival.</li> <li>Our findings highlight the importance of cotyledon strategy in addition to seed mass as a key component of seed and seedling biology. These results also underscore the importance of matching the ontogenetic stage of the trait measurement to the stage of demographic dynamics.</li> <li> <em>Synthesis</em>: With strikingly consistent patterns across three tropical forests, we find strong evidence for the promise of functional traits to provide mechanistic links between seedling form and demographic performance. </li> </ol>
Reproduction package for the paper "The Impact of Hard and Easy Negative Training Data on Vulnerability Prediction Performance"
<p>This Reproduction package contains the datasets, code and results for the paper "The Impact of Hard and Easy Negative Training Data on Vulnerability Prediction Performance" for other researchers to use for reproducing or improving our work. </p>
Functional traits of young seedlings predict trade-offs in seedling performance in three neotropical forests
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Modelling heterogeneity in the classification process in multi-species distribution models can improve predictive performance
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Data for: Predictable local adaptation in butterfly photoperiodism but not thermal performance along a latitudinal cline
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Assessing predictive performance of supervised machine learning algorithms for a diamond pricing model
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Mean body size predicts colony performance in the common eastern bumble bee (Bombus impatiens)
Prior studies suggest that both the mean and variation of worker size predict the performance of bumble bee colonies. The 'variation hypothesis' posits that colony performance increases with variation of worker body size due to more efficient division of labour within colonies. The 'mean size hypothesis' posits that colony performance increases with mean bumble bee size, as each individual’s efficiency tends to increase with body size. The present study tested these non-mutually exclusive hypotheses by establishing 62 Bombus impatiens Cresson (Hymenoptera, Apidae) nest boxes in 32 semi-natural savanna fragments within large-scale experimental landscapes in South Carolina (U.S.A.). Based on measurements of > 24 000 individuals and on colony growth over ca. 7 weeks, our results support the mean size hypothesis, not the variation hypothesis.
Using psychophysical performance to predict short-term ocular dominance plasticity in human adults
<p>This is the dataset reported in the manuscript "Using psychophysical performance to predict short-term ocular dominance plasticity in human adults" published in the Journal of Vision 2020;20(7):6. doi: <a href="https://doi.org/10.1167/jov.20.7.6">https://doi.org/10.1167/jov.20.7.6</a></p> <p> </p>
Establishing diversity in synthetic time series for prediction performance evaluation
<p>This dataset enables practitioners to evaluate their time series prediction algorithms on various types of time series</p>
WESSBAS: Extraction of Probabilistic Workload Specifications for Load Testing and Performance Prediction - A Model-Driven Approach for Session-Based Application Systems.
<p>Supplementary material for the paper: "WESSBAS: Extraction of Probabilistic Workload Specifications for Load Testing and Performance Prediction".</p> <p>Included in the supplementary material are the evaluation results.</p> <p>The WESSBAS software relevant to the paper is available via https://github.com/Wessbas/</p> <p>The WESSBAS UI is available as a password-protected (password: wessbasui) ZIP file:</p> <p>https://dl.dropboxusercontent.com/u/81621779/wessbas.ui.zip (--- WESSBAS GUI (license confirmation pending, i.e., not on GitHub, yet))</p>
Data from "Spontaneous alpha power lateralization predicts detection performance in an un-cued signal detection task", PlosOne2016
<p>32-channel(+6) data (Biosemi Active two, 10-20, 2048Hz) unfiltered from the 2016 Plos ONE paper "Spontaneous alpha power lateralization predicts detection performance in an un-cued signal detection task"</p>
Data from: Does the number of functional olfactory receptor genes predict olfactory sensitivity and discrimination performance in mammals?
<p>The number of functional genes coding for olfactory receptors differs markedly between species and has repeatedly been suggested to be predictive of a species' olfactory capabilities. To test this assumption, we compiled a database of all published olfactory detection threshold values in mammals and used three sets of data on olfactory discrimination performance that employed the same structurally related monomolecular odor pairs with different mammal species. We extracted the number of functional olfactory receptor genes of the 20 mammal species for which we found data on olfactory sensitivity and/or olfactory discrimination performance from the Chordata Olfactory Receptor Database. We found that the overall olfactory detection thresholds significantly correlates with the number of functional olfactory receptor genes. Similarly, the overall proportion of successfully discriminated monomolecular odor pairs significantly correlates with the number of functional olfactory receptor genes. These results provide the first statistically robust evidence for the relation between olfactory capabilities and their genomics correlates. However, when analysed individually, of the 44 monomolecular odorants for which data on olfactory sensitivity from at least five mammal species are available, only five yielded a significant correlation between olfactory detection thresholds and the number of functional olfactory receptors genes. Also, for the olfactory discrimination performance, no significant correlation was found for any of the 74 relationships between the proportion of successfully discriminated monomolecular odor pairs and the number of functional olfactory receptor genes. While only a rather limited amount of data on olfactory detection thresholds and olfactory discrimination scores in a rather limited number of mammal species is available so far, we conclude that the number of functional olfactory receptor genes may be a predictor of olfactory sensitivity and discrimination performance in mammals.</p>
Craniodental traits predict feeding performance and dietary hardness in a community of Neotropical free-tailed bats (Chiroptera: Molossidae)
<p>Form-function studies have established a strong link between dental morphology and the mechanical properties of food items, with animals evolving tooth shapes theoretically ideal for their diets. However, information on how teeth perform under natural conditions is rare, which limits our understanding of how dental morphology influences dietary ecology and niche partitioning within animal communities.</p> <p>Free-tailed bats (Chiroptera: Molossidae) are a diverse clade of aerial insectivorous mammals that exhibit an outstanding variation in size and craniodental traits, which have been directly related to ecological segregation among sympatric species.</p> <p>We investigate the mechanisms that allow functional dietary specialization and trophic segregation among sympatric free-tailed bat species inhabiting a Neotropical forest. To do so, we coupled data on 3D dental topographic metrics, head and skull dimensions, field-collected feeding performance and dietary hardness measurements.</p> <p>We found that evolved differences in molar topography and skull size vary in tandem with the mechanical demands of prey items naturally consumed by sympatric molossid species. This may be explained by feeding performance capabilities resulting from both molar shape and the overall size of the feeding apparatus, which seem to allow efficient processing of prey items with specific mechanical properties. For instance, smaller bats with higher molar topographic values (sharper, more complex molars) and more gracile heads mainly feed on softer insects, whereas bigger bats with lower molar topographic values (blunter, less complex molars) and more robust heads mostly feed on tougher insects. Species with a broader range of sizes, craniodental morphologies, and insect hardness are also present in the community.</p> <p>Our results illustrate how the morphology and size of feeding structures, and how they perform, may facilitate trophic segregation among sympatric insectivorous bats. Similar mechanisms may help structure other communities of insectivorous mammals, therefore the approaches presented here could be used to generate a better understanding of the ecomorphological traits and processes that underlie their diversity.</p>
Towards understanding the importance of time-series features in automated algorithm performance prediction
<p><strong>merged_feature_importance.csv</strong> - CSV with feature importance values with different meta-models, forecasting algorithms, and feature importance methods computed on 30 different train/test splits.</p> <p><strong>Catch22.csv</strong> - Catch22 features (raw time-series)</p> <p><strong>Catch22Log.csv</strong> - Catch22 features (log time-series)</p> <p><strong>Catch22Diff.csv</strong> - Catch22 features (differenced time-series)</p> <p><strong>TSFresh.csv</strong> - TSFresh features (raw time-series)</p> <p><strong>TSFreshLog.csv</strong> - TSFresh features (log time-series)</p> <p><strong>TSFreshDiff.csv</strong> - TSFresh features (differenced time-series)</p> <p><strong>mape.csv</strong> - sMAPE performance for all forecasting algoirthms</p>
PredictION: A predictive model to establish the performance of Oxford sequencing reads of SARS-CoV-2
<p>Dataset (1) that included 1461 samples and a dataset (2) with 471 samples that was a subset of dataset 1 that included Number of sequenced reads per genome, CT (Cycle threshold) value [N2 target gene], mean coverage depth, coverage genome (percentage), and quantification cDNA (ng/µl).</p>
Habitat structural complexity predicts cognitive performance and behavior in western mosquitofish
<p>Urbanization and stream order alter freshwater habitat complexity (defined as the degree of variation in physical habitat structure). More complex habitats have more variation in habitat structure. Habitat complexity affects species composition and shapes animal ecology, behavior, and cognition. We used a delayed detour test to measure whether motor self-regulation and behavior of Western mosquitofish, <em>Gambusia affinis, </em>varied with habitat structural complexity that was quantified for nine populations. We predicted that motor self-regulation, motivation, and risk-taking behavior would increase with increasing habitat complexity, yet we found the opposite relationship. Lower complexity habitats offer less refuge which could increase predation pressure and select for greater risk-taking by fish with greater motor self-regulation. Our findings provide insight into how habitat complexity is related to cognitive processes and behavioral outcomes, and provide an explanation for why some species have a higher tolerance for urbanized environments.</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.