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2,863 results for “Challenge”
Datasets of Indoor UWB Measurements for Ranging and Positioning in Good and Challenging Scenarios
<p>This is a dataset of ranging and positioning measurements collected from an UWB development board. The Real Time Location System based on UWB is set up in a laboratory. Data were captured in the static laboratory environment with different conditions that affects to the positioning performance. In the lab, scenarios with different propagation conditions between the nodes and different geometries were set up. We consider good, challenging, and intermediate scenarios with: Line of Sight (LOS) and Non-LOS propagation conditions as well as easy and challenging geometries. These datasets may be used, for example, for investing and validating ranging and positioning algorithms in different scenarios. A detailed description is provided in the file README.pdf</p>
Supplementary Information – HyDRA challenge
<p>Related Output files for the geometry optimizations (wB97xD/def2-TZVP) of train and blind set of Hydra Challenge.</p>
Challenging a host-pathogen paradigm: Susceptibility to chytridiomycosis is decoupled from genetic erosion
<p>The putatively positive association between host genetic diversity and the ability to defend against pathogens has long attracted the attention of evolutionary biologists. Chytridiomycosis, a disease caused by the chytrid fungus <em>Batrachochytrium dendrobatidis</em> (<em>Bd</em>), has emerged in recent decades as a cause of dramatic declines and extinctions across the amphibian clade. Bd susceptibility can vary widely across populations of the same species, but the relationship between standing genetic diversity and susceptibility has remained notably underexplored so far. Here, we focus on a putatively <em>Bd</em>-naive system of two mainland and two island populations of the common toad (<em>Bufo bufo</em>) at the edge of the species' range, and use controlled infection experiments and dd-RAD sequencing of >10,000 SNPs across 95 individuals to characterise the role of host population identity, genetic variation and individual body mass in mediating host response to the pathogen. We found strong genetic differentiation between populations and marked variation in their susceptibility to Bd. This variation was not, however, governed by isolation-mediated genetic erosion, and individual heterozygosity was even found to be negatively correlated with survival. Individual survival during infection experiments was strongly positively related to body mass, which itself was unrelated to population of origin or heterozygosity. Our findings underscore the general importance of context-dependency when assessing the role of host genetic variation for the ability of defence against pathogens.</p>
The Tensor Brain - Entity Level Visual Relationship Detection Challenge
<p>This dataset contains images and annotations from real-world scenarios. It is aimed at testing a machine's perception performance in terms of object recognition, relationship detection, and instance and semantic memory retrieval.</p>
FaVCI2D Face Verification with Challenging Imposters and Diversified Demographics
<p>Face verification aims to distinguish between genuine and imposter pairs of faces, which include the same or different identities, respectively. The performance reported in recent years gives the impression that the task is practically solved. Here, we revisit the problem and argue that existing evaluation datasets were built using two oversimplifying design choices. First, the usual identity selection to form imposter pairs is not challenging enough because, in practice, verification is needed to detect challenging imposters. Second, the underlying demographics of existing datasets are often insufficient to account for the wide diversity of facial characteristics of people from across the world. To mitigate these limitations, we introduce the FaVCI2D dataset. Imposter pairs are challenging because they include visually similar faces selected from a large pool of demographically diversified identities. The dataset also includes metadata related to gender, country and age to facilitate fine-grained analysis of results. FaVCI2D is generated from freely distributable resources. Experiments with state-of-the-art deep models that provide nearly 100% performance on existing datasets show a significant performance drop for FaVCI2D, confirming our starting hypothesis. Equally important, we analyze legal and ethical challenges which appeared in recent years and hindered the development of face analysis research. We introduce a series of design choices which address these challenges and make the dataset constitution and usage more sustainable and fairer. FaVCI2D is available at https://github.com/AIMultimediaLab/FaVCI2D-Face-Verification-with-Challenging-Imposters-and-Diversified-Demographics</p>
Denoised ECGs from The PhysioNet/Computing in Cardiology Challenge 2020
<p>This dataset is a denoised version of the CPSC dataset presented in <em>Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020<sup>1</sup></em>. This dataset was used as part of the article <em>A Lightweight and Interpretable Model to classify Bundle Branch Blocks from ECG Signals.</em></p> <p>1)Perez Alday, E. A., Gu, A., Shah, A., Liu, C., Sharma, A., Seyedi, S., Bahrami Rad, A., Reyna, M., & Clifford, G. D. (2020). Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 (version 1.0.1). <em>PhysioNet</em>. <a href="https://doi.org/10.13026/f4ab-0814">https://doi.org/10.13026/f4ab-0814</a>.</p>
Exploring traffic safety problems and challenges of older roads' users in Louisiana: Causes and countermeasures
<p>It is well established that older pedestrians and drivers with 65 years and above are among the most vulnerable road users. As the number and proportion of older road users (as drivers and pedestrians) grows in many countries, as well as their share in pedestrians’ and drivers’ crashes and injuries, it behooves transportation researchers to further investigate the safety and mobility challenges of older road users. This study aims mainly to provide a comprehensive investigation of older pedestrians’ and drivers’ safety challenges. To this end, a three-fold research approach is designed to thoroughly examine older road users’ safety challenges as pedestrians and drivers. First, crash data analysis identified significant risk factors causing/leading older drivers’ to be involved in vehicle crashes. Second, a driving simulator experiment was performed to further investigate the identified risky conditions from the crash data analysis and literature review. Third, a self-reported survey was conducted across the country to address pedestrians’ safety challenges, needs, and attitudes toward different pedestrian crossing facilities (i.e., signalized intersections, unsignalized intersections, midblock cross walks with and without flashing lights, and roundabouts). The results of this study provide a better understanding regarding older drivers’ and pedestrian’ needs and challenges that should be accommodated to improve their safety and mobility.</p>
Strategic low-cost energy investment opportunities and challenges towards achieving universal electricity access (SDG7) in forty-eight African nations.
<p>This dataset underpins the study "Strategic low-cost energy investment opportunities and challenges towards achieving universal electricity access (SDG7) in forty-eight African nations".</p> <p>The study provides insights into energy supply and demand, power generation, investments and total system costs, SD7 indicators, job creation as well as carbon dioxide emissions for each African nation (48 in total).</p> <p>An energy systems model enhanced with geospatial data was developed to evaluate energy supply requirements to cover the energy needs of the African continent during the period 2015-2030 and achieve universal access by 2030. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS and the geospatial electrification outlook (GEP). The objective function is to minimise the total energy system costs. </p> <p>The results can be found https://doi.org/10.5281/zenodo.6468262</p>
Strategic low-cost energy investment opportunities and challenges towards achieving universal electricity access (SDG7) in forty-eight African nations
<p>The attached modeling results underpin the study "Strategic low-cost energy investment opportunities and challenges towards achieving universal electricity access (SDG7) in forty-eight African nations".</p> <p>The study provides insights into energy supply and demand, power generation, investments and total system costs, SD7 indicators, job creation as well as carbon dioxide emissions for each African nation (48 in total).</p> <p>An energy systems model enhanced with geospatial data was developed to evaluate energy supply requirements to cover the energy needs of the African continent during the period 2015-2030 and achieve universal access by 2030. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS and the geospatial electrification outlook (GEP). The objective function is to minimise the total energy system costs. </p> <p>The TEMBA model produces aggregate energy, and detailed power system results in each country in the African continent. The power sector results are also reported with power pool aggregation.</p> <p>The OSeMOSYS model and input data used to produce these results can be found at JoPapp/jrc_temba: v1.0.2 [Data set]. Zenodo.https://doi.org/10.5281/zenodo.6468278 (Authors: Ioannis Pappis. (2021)).</p>
Accompanying data for the report data.europa.eu and Citizen-generated Data: Opportunities and challenges associated to the inclusion of citizen-generated data in data.europa.eu
<p>Accompanying data for the report data.europa.eu and Citizen-generated Data: Opportunities and challenges associated to the inclusion of citizen-generated data in data.europa.eu. This includes the catalogue of papers that have been revised in the course of generating this report, as well as a file with the analysis of datasets from different open data portals in Europe, with respect to their inclusion of Citizen-Generated Data.</p>
Understanding challenges of GPU programming by classifying and analyzing Stack Overflow posts
<p>This dataset includes a dataset of posts related to GPU programming and supplemental materials including the complete analyzed results of our paper "Understanding challenges of GPU programming by classifying and analyzing Stack Overflow posts".</p>
Non-Functional Requirements for Machine Learning: Understanding Current Use and Challenges Among Practitioners
<p>This package contains interview data (themes, codes, and quotes) and survey data to identify, define and measure non-functional requirements for ML systems.</p>
Associated data files and scripts for 'Ancestry-inclusive dog genomics challenges popular breed stereotypes'
<p>Behavioral genetics in dogs has focused on modern breeds, isolated subgroups <200 years old with distinctive physical, and, purportedly, behavioral characteristics. We interrogated breed stereotypes by surveying owners of 18,371 purebred and mixed-breed dogs, and densely genotyping (~45 million markers) a subset of 2,155 dogs. Most behavioral traits are heritable (h<sup>2</sup>>25%), and admixture patterns in mixed-breed dogs can reveal breed propensities. However, breed poorly predicts an individual purebred dog's behavioral phenotype, explaining just 9% of variation. Using genome-wide association, we identify 11 loci significantly associated with howling and other behaviors, and show characteristic breed behaviors are genetically complex. Behavior-associated loci are not unusually differentiated in modern breeds, but breed propensities do align, albeit weakly, with ancestral function. We propose behaviors now perceived as characteristic of modern breeds likely derive from thousands of years of polygenic adaptation predating breed formation, with modern breeds distinguished primarily by aesthetic, not behavioral, traits.</p>
Videos from "Postural analysis reveals persistent vigilance in paper wasps after conspecific challenge"
<p>Videos of field assays demonstrating persistent effects of a simulated social challenge on the vigilance behavior of wild northern paper wasp foundresses, <em>Polistes fuscatus</em>. Untracked and tracked ("predictions.cleaned.slp") videos included.</p>
Dataset for "Tackling global challenges with coherent policies producing more researchers and diaspora engagement"
<p>A list of science policies that were published between 2002 and 2021 by the African Union, Southern African Development Community, and the Government of Zimbabwe.</p>
Dataset Validation Images for the MICCAI-2022-Challenge: Airway Tree Modeling (ATM'22)
<p>Dataset for the MICCAI-2022-Challenge: Airway Tree Modeling (ATM'22)</p> <p>This is the Validation Image part. </p> <p>If you use this dataset in your research, you must cite the papers in the References below !!!</p>
Dataset TrainBatch2 for the MICCAI-2022-Challenge: Airway Tree Modeling (ATM'22)
<p>[Attention]: ATM_164_0000.nii.gz has misaligned label to CT image, please discard this case!</p> <p>Dataset for the MICCAI-2022-Challenge: Airway Tree Modeling (ATM'22)</p> <p>This is the TrainBatch2. </p> <p>If you use this dataset in your research, you must cite the papers in the References below !!!</p>
MIDOG challenge npz files for Oneat
<p>MIDOG challenge dataset converted to Oneat compatiable npz files</p> <p> </p> <p>Computational support provided by Jean Zay dynamic access grant: AD011013396, oneat model training and evaluation was performed on Jean Zay compute nodes</p>
Ariel Big Challenge (ABC) Database
<p>This is the database for the publication: ESA-Ariel Data Challenge NeurIPS 2022: Introduction to exo-atmospheric<br> studies and presentation of the Ariel Big Challenge (ABC) Database. </p> <p>The database contains 105,877 realistic Ariel observations in Tier-2 resolutions. All examples are generated with a pre-determined atmospheric assumptions. 26% (26,109) of these observations are complemented with retrieval results produced from Nested Sampling algorithms. </p> <p>Inside you will find Level 1 and Level 2 data. Level 1 data is for general propose and Level 2 data is specifically designed for NeurIPS 2022 data challenge. </p> <p>We have also included a simple tutorial on how to manipulate the files and a introduction tutorial on TauREx3, the software we used to generate these spectra. </p> <p>Abstract:</p> <p>This is an exciting era for exo-planetary exploration. In the past two decades, astronomers have harvested data from all the observatories at their disposal. Those collective efforts allowed us to have a glimpse at the convoluted process of planetary formation and evolution and its connections to atmospheric compositions, but nevertheless remained limited by the low quality and scarcity of exo-atmospheric data. Now, the recently launched JWST, and other upcoming space missions such as Ariel, Twinkle and ELTs are set to anew the landscape, bringing fresh insights to these remote worlds. However, with new opportunities come new challenges. The field of exoplanet atmospheres is already struggling with the incoming volume and quality of data, and machine learning (ML) techniques lands itself as a promising alternative. Developing techniques of this kind is an inter-disciplinary task, one that requires domain knowledge of the field, access to relevant tools and expert insights on the capability and limitations of current ML models. These stringent requirements have so far limited the developments of ML in the field to a few isolated initiatives. As part of the data product of the NeurIPS 2022 Data challenge, we would like to present the Ariel Big Challenge Database (ABC Database), a carefully designed, organised and publicly available database. With 105,887 forward models, 26,109 complementary posterior distributions and an easy-to-understand documentation, this represents an unprecedented effort to invite cross-disciplinary experts to the study of the inverse problem in the context of exoplanetary studies. </p> <p>For more information on the data and how they were generated please refer to our publication (https://arxiv.org/abs/2206.14633). </p> <p>This work utilised resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk).</p>
Data from: Efficacy of negative feedback in the HPA axis predicts recovery from acute challenges.
The glucocorticoid stress response mediates a suite of physiological and behavioral changes that allow vertebrates to cope with transient stressors. Chronically elevated glucocorticoid levels are known to result in a variety of organismal costs, but relatively little is known about the downstream effects of mounting a series of brief, acute spikes in circulating glucocorticoids. Conceptual models of stress suggest that repeated acute stressors might produce 'wear-and-tear' on the stress response system when encountered in sequence. We used a novel technique to experimentally induce acute corticosterone spikes on either three or six consecutive days in incubating tree swallows. Consistent with the 'wear-and-tear' hypothesis, we found that i) a sequence of corticosterone spikes produced cumulative effects on corticosterone regulation, ii) treatment frequency predicted the severity of consequences, and iii) individual variation in the ability to terminate the stress response through negative feedback predicted the duration of physiological disruption in the group that experienced the most frequent challenges. Our results illustrate the importance of assessing multiple aspects of the hormonal stress response and have implications for understanding both individual and population resilience to repeated transient stressors.
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.