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39 results for “automated support”
Raw images, annotations, and vvipr code archive to support 'Evaluating thermal and color sensors for automating detection of penguins and pinnipeds in images collected with an unoccupied aerial system''
<p>Images, annotations, and code archived here were used in the paper "Evaluating a machine learning approach to detect penguins and pinnipeds in thermal and color images collected with an unoccupied aerial system" submitted for publication in Drones. The files contain raw thermal and color images of aggregations of gentoo (<em>Pygoscelis papua</em>) and chinstrap (<em>P. antarcticus</em>) penguins and Antarctic fur seals (<em>Arctocephalus gazella</em>). All images were collected with the Flir DuoPro R camera (Teledyne FLIR LLC, Wilsonville, OR, U.S.A.), carried into flight under an APH-28 hexacopter (Aerial Imaging Solutions, LLC, Old Lyme, CT, U<strong>.</strong>S<strong>.</strong>A<strong>.)</strong> at Cape Shirreff, Livingston Island, Antarctica (60.79 °W, 62.46 °S), during the austral summer of 2019-20. All aerial surveys occurred under the Marine Mammal Protection Act Permit No. 20599 granted by the Office of Protected Resources/National Marine Fisheries Service, the Antarctic Conservation Act Permit No. 2017-012, NMFS-SWFSC Institutional Animal Care and Use Committee Permit No. SWPI 2014-03R, and all domestic and international UAS flight regulations. The annotations of the images were conducted using VIAME desktop software (v 0.16.1 or later;<a href="https://github.com/VIAME/VIAME">https://github.com/VIAME</a>) or the online using the DIVE interface (https://viame.kitware.com/). Model results were assessed with the vvipr code (v.0.3.2), archived here and available online (https://github.com/us-amlr/vvipr/releases/tag/v0.3.2).</p> <p> </p>
Automated Support for Searching and Selecting Evidence in Software Engineering: A Cross-domain Systematic Mapping
<p>Dataset -- Brief summary of the automated approaches for searching and selecting studies for secondary studies in software engineering </p>
Automated Support for Searching and SelectingEvidence in Software Engineering: A Cross-domainSystematic Mapping
<p>Data from the studies that adrress search and selection approaches. </p>
Supplementary material 1 from: Scaccia N, Günther T, Lopez de Abechuco E, Filter M (2021) The Glossaryfication Web Service: an automated glossary creation tool to support the One Health community. Research Ideas and Outcomes 7: e70183. https://doi.org/10.3897/rio.7.e70183
The Glossaryfication Web Service: an automated glossary creation tool to support the One Health community
MORE-PC: A 30-day Automated SMS Program to Support Post-discharge Transitions of Care
ClinicalTrials.gov study NCT05245773. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Automated Adjustment of Inspired Oxygen to Maintaining Regional Cerebral Oxygenation in Preterm Infants on Respiratory Support
ClinicalTrials.gov study NCT02748447. IPD Sharing: Not stated. Countries: 1. Publications: 4.
The Use of a Fully Automated Pulsating Support System (CuroCell® A4 CX20) in Pressure Ulcer Prevention and Treatment
ClinicalTrials.gov study NCT04890678. IPD Sharing: NO. Countries: 1. Publications: 1.
Hospice and End-of-life Symptom Monitoring & Support Using an Automated System Designed for Family Caregivers
ClinicalTrials.gov study NCT02112461. IPD Sharing: NO. Countries: 1. Publications: 1.
Automated Versus Manual Oxygen Control in Preterm Babies on Respiratory Support
ClinicalTrials.gov study NCT06622161. IPD Sharing: NO. Countries: 1. Publications: 16.
Figure 2 from: Scaccia N, Günther T, Lopez de Abechuco E, Filter M (2021) The Glossaryfication Web Service: an automated glossary creation tool to support the One Health community. Research Ideas and Outcomes 7: e70183. https://doi.org/10.3897/rio.7.e70183
Figure 2 A, a screenshot of the GWS KNIME workflow. There are 5 steps within the data processing workflow, which are described in the text. The first and the last green boxes of the workflow, designed with KNIME WebPortal extension, contain so-called "Components" that provide a workflow-specific web user interface that can also be triggered by the KNIME Server. In this way, the GWS KNIME workflow becomes available as a fully functional web service in the KNIME WebPortal. B, a screenshot of the KNIME's Text Processing extension nodes wrapped up into a metanode.
Figure 1 from: Scaccia N, Günther T, Lopez de Abechuco E, Filter M (2021) The Glossaryfication Web Service: an automated glossary creation tool to support the One Health community. Research Ideas and Outcomes 7: e70183. https://doi.org/10.3897/rio.7.e70183
Figure 1 A, a screenshot of the GWS start page. B and C, output sections of the service. Specifically, B, number of exact terms and associated definitions found and, a tag cloud outcome; C, downloadable table of identified terms and definitions with term frequency, sector classification and reference. Through the GWS, end-users can upload their own file (2, A) and select which of the supported glossary(ies) should be searched through (1, A). Clicking "Next" (3, A), the GWS displays the results in an interactive table within the dashboard providing also the number of occurrences for each term in the user's document next to the identified definitions (4, B) and the tag cloud (5, B). The different colours for the terms in the tag cloud refer to different types of matches: exact matches in green, inexact matches in yellow and non-matching terms in grey. Afterwards, scrolling down the dashboard view (image C), the user has the possibility to download directly different tables (6, C) in Excel format. These options are: i) download the table with all the matches found, ii) download the exact-matches table or iii) download the inexact-matches table (6, C). Furthermore, if only a few terms with appropriate definitions are needed, the end-user can download those specific terms checking the corresponding checkboxes (7, C) and then clicking "Next" at the bottom of the dashboard page (8, C).
Supporting Information for the Journal Article "High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference treatment"
<p>This dataset contains the supporting information for the journal article "High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference treatment". It consists of two files:</p> <ul> <li>"structures.json", containing 3335 unique structures found in the exploration, and</li> <li>"energies.json", containing 2227 elementary steps and its energies found in the exploration</li> </ul> <p>In the file "structures.json", the following keys are used to characterize a structure:</p> <ul> <li> _id: the ID of the structure</li> <li>nAtoms: the total number of atoms in the structure</li> <li>atoms: the XYZ coordinates of the atoms in atomic units</li> <li>charge: the total charge of the structure</li> <li>multiplicity: the spin multiplicity 2S+1 of the structure</li> <li>label: the position of the structure on the minimum energy pathway</li> </ul> <p>In the file "energies.json", there are two major fields: structures and reactions.</p> <p>In the field "structures", the keys are:</p> <ul> <li>id: the ID of structure (can be linked to XYZ coordinates in "structures.json")</li> <li>label: the position of the structure on the minimum energy pathway</li> <li>energy_dft: PBE-D3BJ/def2-SVP total energy in atomic units</li> <li>energy_hf: HF/cc-pVDZ total energy in atomic units</li> <li>energy_ccsd: CCSD/cc-pVDZ total energy in atomic units</li> <li>energy_ccsd_t: CCSD(T)/cc-pVDZ total energy in atomic units</li> <li>energy_gibbs_correction: PBE-D3BJ/def2-SVP Gibbs free energy correction in atomic units</li> </ul> <p>In the field "reactions", the keys are:</p> <ul> <li>id: the ID of the elementary step</li> <li>lhs: the structure IDs on the left-hand side of the reaction</li> <li>rhs: the structure IDs on the right-hand side of the reaction</li> <li>type: regular or barrierless</li> <li>barrierless: binary key to indicate whether the elementary step has a barrier</li> <li>ts: ID of the transition state structure</li> <li>reaction: the ID of the reaction to which the elementary step belongs</li> </ul> <p>Due to the nature of exploration, certain structures can be explored from multiple elementary steps. Therefore, duplicated structures are common in the reaction exploration. In "structures.json", we de-duplicated the structures and only list the unique ones. The coordinates (in bohr) and global attributes like spin multiplicity and charge are provided. </p> <p>In "energies.json", each "step" represents an elementary step. 1260 of the steps are barrierless, while 967 of the steps have a barrier. The structures keys cited in "lhs", "rhs", and "ts" are before de-duplication. The "id" in each structure key points to the unique, de-duplicated structure in "structures.json".</p> <p>The main catalytical pathways (figure 9) can be found in the dataset with the following elementary_step IDs:</p> <ul> <li>62066d2fb8e290f3afb607e2</li> <li>6206704db8e290f3afb607e3</li> <li>62067db7b8e290f3afb607e4</li> <li>620a6d49b8e290f3afb607e5</li> <li>620a6dbeb8e290f3afb607e6</li> <li>620a6e2fb8e290f3afb607e7</li> <li>620a6e78b8e290f3afb607e8</li> <li>620a7f01b8e290f3afb607e9</li> <li>620a7f54b8e290f3afb607ea</li> </ul>
Scalable Non-Volatile Tuning of Photonic Computational Memories by Automated Silicon Ion Implantation - Supporting Information
<p>Photonic integrated circuits (PICs) are revolutionizing the realm of information technology, promising unprecedented speeds and efficiency in data processing and optical communication. However, the nanoscale precision required to fabricate these circuits at scale presents significant challenges, due to the need to maintain consistency across wavelength-selective components, which necessitates individualized adjustments after fabrication. Harnessing spectral alignment by automated silicon ion implantation, in this work scalable and non-volatile photonic computational memories are demonstrated in high-quality resonant devices. Precise spectral trimming of large-scale photonic ensembles from a few picometers to several nanometres is achieved with long-term stability and marginal loss penalty. Based on this approach, spectrally aligned photonic memory and computing systems for general matrix multiplication are demonstrated, enabling wavelength multiplexed integrated architectures at large scales.</p>
Supporting Data for Integrating Human Factors Expertise into Development of Automated Vehicles
<p>This dataset provides the questionnaires utilized during various stages of data collection for our manuscript titled "Integrating Human Factors Expertise into Development of Automated Vehicles".</p> <p>In addition to the questionnaires, we offer scripts and survey data essential for replicating and evaluating the methodology outlined in our manuscript</p> <p>The dataset includes the following files:</p> <ol> <li>Questionnaire used during Stage 1 of the data collection process.</li> <li>Questionnaire employed in Stage 2 of the data collection.</li> <li>Survey questionnaire used in Stage 3.</li> <li>Zip file providing the dataset and scripts used for quantitative analysis.</li> </ol> <p>For any inquiries or further clarification, please contact <a target="_new" rel="noreferrer">amnap@chalmers.se. </a></p>
Discontinuation of Automated Engagement Support
ClinicalTrials.gov study NCT02578628. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Automated Telephone Nutrition Support
ClinicalTrials.gov study NCT01040676. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Conventional Versus Automated Bag-based Mechanical Ventilator to Support ARDS Patients
ClinicalTrials.gov study NCT06667375. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Supporting Data for Integrating Human Factors Expertise into Development of Automated Vehicles
<p>This dataset provides the questionnaires utilized during various stages of data collection for our manuscript titled "Integrating Human Factors Expertise into Development of Automated Vehicles".</p> <p>In addition to the questionnaires, we offer scripts and survey data essential for replicating and evaluating the methodology outlined in our manuscript</p> <p>The dataset includes the following files:</p> <ol> <li>Questionnaire used during Stage 1 of the data collection process.</li> <li>Questionnaire employed in Stage 2 of the data collection.</li> <li>Survey questionnaire used in Stage 3.</li> <li>Zip file providing the dataset and scripts used for quantitative analysis. data</li> </ol> <p>For any inquiries or further clarification, please contact <a target="_new" rel="noreferrer">amnap@chalmers.se</a>.</p> <p> </p>
Supporting Data for Integrating Human Factors Expertise into Development of Automated Vehicles
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