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Dataset results
28 results for “online experiment”
Code, benchmarks and experiment data for the IPC 2018 entry "Delfi: Online Planner Selection for Cost-Optimal Planning"
<p>This bundle contains code, scripts and benchmarks for reproducing all experiments reported in the paper. It also contains the data generated for the paper.</p> <p>katz-et-al-icp2018-delfi.zip and katz-et-al-icp2018-delf2.zip contain the implementation based on Fast Downward (the two folders only differ in how the planner selection works). It also contains the experiment scripts (hopefully) compatible with Lab 2.1 for reproducing all experiments of the paper, under experiments/ipc2018.</p> <p>katz-et-al-ipc2018-scripts.zip contain all scripts for the learning pipeline used to train the planner selection models.</p> <p>katz-et-al-icp2018-benchmarks.zip contains the benchmarks. It consists of the IPC benchmarks used in all optimal sequential tracks of IPCs up to 2014 (suite optimal from https://github.com/aibasel/downward-benchmarks).</p> <p>katz-et-al-icp2018-lab.zip contains a copy of Lab 2.1 (https://github.com/aibasel/lab).</p> <p>katz-et-al-icp2018-raw-data.zip and katz-et-al-icp2018-parsed-data.zip contain the experimental data. Directories in katz-et-al-icp2018-raw-data.zip (without the "-eval" ending) contain raw data, distributed over a subdirectory for each experiment. Each of these contain a subdirectory tree structure "runs-*" where each planner run has its own directory. For each run, there are symbolic links to the input PDDL files domain.pddl and problem.pddl (can be resolved by putting the benchmarks directory to the right place), the run log file "run.log" (stdout), possibly also a run error file "run.err" (stderr), the run script "run" used to start the experiment, and a "properties" file that contains data parsed from the log file(s). Directories in katz-et-al-icp2018-parsed-data.zip (with the "-eval" ending) contain a "properties" file, which contains a JSON directory with combined data of all runs of the corresponding experiment. In essence, the properties file is the union over all properties files generated for each individual planner run.</p> <p>The image data set used for training can be found online: https://github.com/IBM/IPC-image-data</p> <p>Note on license: we chose GPL v3.0 or later mainly because we consider our implementation based on Fast Downward the main contribution of this package, and Fast Downward comes with GPL v3.0. We only include a copy of Lab and the benchmarks for convenience.</p> <p> </p>
Feasibility, Effectiveness, and Patient Experience of Online Acceptance and Commitment Therapy Plus Exercises for Older People With Chronic Low Back Pain
ClinicalTrials.gov study NCT06576414. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Online Individual Intervention Program to Make Sense of People's Experiences After a Breast Cancer Diagnosis
ClinicalTrials.gov study NCT05963412. IPD Sharing: NO. Countries: 1. Publications: 0.
Online Intervention for Transgender/Nonbinary Young Adults' Experiences With Alcohol and Romantic Relationships
ClinicalTrials.gov study NCT06392542. IPD Sharing: NO. Countries: 1. Publications: 0.
Data Set of an online controlled experiment to study adaptive learning
<p>Online-controlled experiment evaluation - Data Set</p> <p>Digital learning platforms are more and more used in blended classroom scenarios in Germany. However, as learning processes are different among students, adaptive learning platforms can offer personalized learning, e.g. by individual feedback and corrections, task sequencing, or recommendations. As digital learning platforms are already used in classroom settings, we propose the transformation of these plat-forms into adaptive learning environments. To measure the effectiveness and improvements achieved through the adaptions an online-controlled experiment design is created. In our experiment, we therefore investigate the effectiveness of different inter-ventions on a large user group in a four-month online-controlled experiment. For this purpose, the highly frequented German learning platform Orthografietrainer.net was transformed into an adaptive learning platform and users were randomly assigned to different interventions.</p> <p>The experimental design is published here: N. Rzepka, K. Simbeck, H.-G. Müller, and N. Pinkwart An Online Controlled Experiment Design to Support the Transformation of Digital Learning towards Adaptive Learning Platforms Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,, SciTePress, 2022, ISBN 978-989-758-562-3 </p> <p>The architectural concept is published here: Rzepka, N., Simbeck, K., Müller, H.-G. & Pinkwart, N., (2022). Adaptive Learning as a Service – A concept to extend digital learning platforms?. In: Henning, P. A., Striewe, M.-0. 0. & Wölfel, M.-0. 0. (Hrsg.), 20. Fachtagung Bildungstechnologien (DELFI). Bonn: Gesellschaft für Informatik e.V.. (S. 237-238). DOI: 10.18420/delfi2022-049 </p> <p>The findings of this experiment are published here: tba</p> <p>The code to this evaluation can be found on Zenodo: <a href="https://doi.org/10.5281/zenodo.7755546">10.5281/zenodo.7755546</a></p>
Adapting Cultural Probes to an Online-Only Format to Inform the Design of Online Heritage Experiences - Photo Dataset
<p>Screenshots submitted by the participants as part of the photography activity in their Cultural Probe packs.</p>
Adapting Cultural Probes to an Online-Only Format to Inform the Design of Online Heritage Experiences - Open Questions Answers
<p>Answers provided by the participants to the open questions. Responses are separated by type of probe and classified by question.</p>
Detection and Recognition of Fearful Facial Expressions During the Coronavirus Disease (COVID-19) Pandemic in an Italian Sample: An Online Experiment
<p>Dataset associated with the article:</p> <p>Scarpina F. Detection and Recognition of Fearful Facial Expressions During the Coronavirus Disease (COVID-19) Pandemic in an Italian Sample: An Online Experiment. <em>Front Psychol.</em> 2020 Sep 11;11:2252. doi: 10.3389/fpsyg.2020.02252.</p>
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.