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2,045 results for “Plan S”
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>
Data from: Gradual assembly of avian body plan culminated in rapid rates of evolution across dinosaur-bird transition
[No abstract entered]
Figure 2 from: Canhos D (2017) Data Management Plan: Brazil's Virtual Herbarium. Research Ideas and Outcomes 3: e14675. https://doi.org/10.3897/rio.3.e14675
Figure 2 - Information and data flows in the BVH system.
Figure 1 from: Canhos D (2017) Data Management Plan: Brazil's Virtual Herbarium. Research Ideas and Outcomes 3: e14675. https://doi.org/10.3897/rio.3.e14675
Figure 1 - System architecture of the BVH and supporting systems.
D7.1 Plan for Exploitation and Dissemination of Results
<p>Deliverable of dissemination and exploitation of results</p>
Supplementary Material to the Manuscript "On How to Transform Refueling Station Networks: Planning Framework, Model, and Exact Solution Approach"
<p>This dataset consists of two .xlsx files containing the supplementary material to the manuscript "On How to Transform Refueling Station Networks: Planning Framework, Model, and Exact Solution Approach".</p> <p>The file "supplementary_parameter.xlsx" contains the parameters used in the experiments. </p> <p>The file "supplementary_random_networks.xlsx" contains the random networks used in the numerical experiments.</p>
Figure 3 from: Underwood E, Taylor K, Tucker G (2018) The use of biodiversity data in spatial planning and impact assessment in Europe. Research Ideas and Outcomes 4: e28045. https://doi.org/10.3897/rio.4.e28045
Figure 3 Steps in the Environmental Impact Assessment Process.
Figure 2 from: Underwood E, Taylor K, Tucker G (2018) The use of biodiversity data in spatial planning and impact assessment in Europe. Research Ideas and Outcomes 4: e28045. https://doi.org/10.3897/rio.4.e28045
Figure 2 Steps in the Strategic Environmental Assessment Process.
Figure 1 from: Irawan D, Rachmi C (2018) Promoting data sharing among Indonesian scientists: A proposal of generic university-level Research Data Management Plan (RDMP). Research Ideas and Outcomes 4: e28163. https://doi.org/10.3897/rio.4.e28163
Figure 1 Current situation of data lifecycle (Irawan 2018).
Example DICOM plan, dose, and log files
<p>A demo dataset for use on https://app.pymedphys.com to demonstrate mapping a log file to a DICOM file, calculating the dose, and taking a gamma and mudensity analysis of the results.</p>
Improving Route Development Using Convergent Retrosynthesis Planning
Open the record for dataset details and reuse information.
Data from: Framing advance care planning in Parkinson disease: patient and care partner perspectives
Objective: Advance care planning (ACP) is a core quality measure in caring for individuals with Parkinson's disease (PD) and there are no best practice standards for how to incorporate ACP into PD care. This study describes patient and care partner perspectives on ACP to inform a patient and care partner-centered framework for clinical care. Methods: Qualitative descriptive study of 30 patients and 30 care partners affected by PD within a multi-site, randomized clinical trial of neuropalliative care compared to standard care. Participants were individually interviewed about perspectives on ACP, including prior and current experiences, barriers to ACP, and suggestions for integration into care. Interviews were analyzed using theme analysis to identify key themes. Results: Four themes illustrate how patients and care partners perceive ACP as part of clinical care: 1) personal definitions of ACP vary in the context of PD; 2) patient, relationship, and healthcare system barriers exist to engaging in ACP; 3) care partners play an active role in ACP; 4) a palliative care approach positively influences ACP. Taken together, the themes support clinician initiation of ACP discussions and interdisciplinary approaches to help patients and care partners overcome barriers to ACP. Conclusions: ACP in PD may be influenced by patient and care partner perceptions and misperceptions, symptoms of PD (e.g. apathy, cognitive dysfunction, disease severity), and models of clinical care. Optimal engagement of PD patients and care partners in ACP should proactively address misperceptions of ACP and utilize clinic teams and workflow routines to incorporate ACP into regular care.
How do users interact with Virtual Geographic Environments? Users' behavior evaluation in urban participatory planning [Dataset]
<p>VGEs used in the experimental study.</p>
Plan des 12. Bezirkes Meidling der Bundeshauptstadt Wien (1925-30)
<ul> <li>Quelle: Wiener Stadt- und Landesarchiv.</li> <li>Signatur im Wiener Archivinformationssystem (<a href="https://www.wien.gv.at/actaproweb2/benutzung/index.xhtml">WAIS</a>): 3.2.1.1.P4.317./2</li> <li>Anmerkung: Am Digitalisat wurden keine Änderungen vorgenommen.</li> </ul>
Nicosia, Bedestan. Plan of the complex prepared in 1980-81 combined with resistivity tomography at a depth of 1.25m below the current surface.
<p>Nicosia, Bedestan. Plan of the complex prepared in 1980-81 combined with resistivity tomography at a depth of 1.25m below the current surface.</p>
Nicosia, Bedestan. Plan of the east end showing Byzantine and Venetian-period phases, prepared 1980-81.
<p>Nicosia, Bedestan. Plan of the east end showing Byzantine and Venetian-period phases of construction, prepared 1980-81.</p>
National Plan and Provider Enumeration System (NPPES) Data Dissemination
<p>National Plan and Provider Enumeration System (NPPES) Data Dissemination, January 8, 2023 Version.</p>
Experimental Results for the AAAI 2023 Paper "Towards Automated Modeling Assistance: An Efficient Approach for Repairing Flawed Planning Domains"
<p>This is the collection of all experimental outputs described in the paper "Towards Automated Modeling Assistance: An Efficient Approach for Repairing Flawed Planning Domains" by Songtuan Lin, Alban Grastien, and Pascal Bercher, accepted by AAAI 2023. A detailed explanation about the contents can be found in the README.md file.</p>
Planning Poker MDPI 2023
<p>Dataset associated with the paper </p> <p><strong>Scaling-up Social Learning in Small Groups with Robot Supported Collaborative Learning (RSCL)</strong><strong>:</strong><strong> Effects of Learners’ Prior Experience in the Case Study of Planning Poker with the Robot NAO</strong></p>
Scalable Micro-planned Generation of Discourse from Structured Data
<p>Dataset created </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.