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Dataset results
831 results for “automaticity”
Pseudonymized Raw Data for "Automatic Core-Developer Identification on GitHub: A Validation Study"
<p>Pseudonymized raw data (i.e., commit data and issue data for 25 GitHub projects) that has been used as input for the study published as "Automatic Core-Developer Identification on GitHub: A Validation Study".</p> <p>The pseudonymized raw data has been extracted via the tools <a href="https://github.com/se-sic/codeface/">Codeface</a>, <a href="https://github.com/se-sic/GitHubWrapper/">GitHubWrapper</a>, <a href="https://github.com/mehdigolzadeh/BoDeGHa">BoDeGHa</a>, and <a href="https://github.com/se-sic/codeface-extraction/">codeface-extraction</a> (and additional manual corrections after sanity checks).</p>
Replication Package for Automatically Identifying Relations Between Self-Admitted Technical Debt Across Different Sources
<p>This dataset includes a trained weight file for identifying the relations between self-admitted technical debt items.</p>
Trained CNN for analysis of melanoma whole slide images to automatically assess the infiltration of TILs
<p>The file is the trained convolutional neural network (CNN) developed in "Ugolini F et al.Tumor infiltrating lymphocytes recognition in primary melanoma by deep learning convolutional neural network" submitted to American Journal of Pathology (2023). The CNN is based on a a pre-trained Inception-ResNet-v2 to automatically to recognize areas in the tumor region containing TILs and area without TILs in histopathological digitalized slides of primary melanoma. The file is in a Matlab format (.mat).</p>
Anonymized data for paper "Automatic Bug Fixing in the Era of Large Language Models: Interactive Simulation of Programmer Behavior" submitted to ICSE 2024
<p>The project includes the BFP benchmark used in the submitted ICSE 2024 paper titled "Automatic Bug Fixing in the Era of Large Language Models: Interactive Simulation of Programmer Behavior"</p>
Developing a Method to Automatically Extract Road Boundary and Linear Road Markings from MMS Point Cloud using OBB Collision Detection Techniques
<p>This video demonstrates the application of our method in a software tool for constructing road boundaries and lane marking data.</p>
Supplemental material for: Automatic Debugging of Design Faults in MapReduce applications
<p>This is the supplemental material of the paper titled as “Automatic Debugging of Design Faults in MapReduce applications” published in IEEE Transactions on Software Engineering. <a href="https://doi.org/10.1109/TSE.2024.3369766" target="_blank" rel="noopener">Link</a></p> <p> </p> <p>It contains both the test cases used in the evaluation and the statistical analysis to reproduce the experiments. The supplemental material contains the following files:</p> <ul> <li>1_testCases.zip: all test cases randomly generated for the experiments. The description of the test cases is in ./1_testCases/README.txt</li> <li>2_executionTestCases.zip: the aggregated data obtained after the execution of the test cases in the debugging techniques: fault localization technique (MRDebug-FL), input reduction technique (MRDebug-IR) and the combination of both techniques (MRDebug-IR-FL). The folder contains csv with the results the experimentation unit, and they are detailed in the ./2_executionTestCases/README.pdf file.</li> <li>3_notebook.zip: jupyter notebook that contains the analysis done in the experiments. This notebook allows the interactive execution of statistical test and plots. The instructions to install the notebook are in the file 3_notebook.zip/installation.txt.</li> </ul> <p> </p> <p>To cite this work: </p> <p>J. Morán, A. Bertolino, C. de la Riva and J. Tuya, "Automatic Debugging of Design Faults in MapReduce Applications," in <em>IEEE Transactions on Software Engineering</em>, vol. 50, no. 4, pp. 956-978, April 2024, doi: 10.1109/TSE.2024.3369766</p>
Dataset for "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments"
<p>The dataset contains the data used in the article "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments".</p> <p>A low-cost monitoring system composed of 14 monitoring stations was positioned at the official monitoring station of Torino Rubino in the city of Turin (Italy). The official station is managed by the environmental agency ARPA Piemonte.</p> <p>Each low-cost station contains four low-cost light-scattering PM sensors (Honeywell HPMA115S0-XXX), one temperature and relative humidity sensor (DHT22), and one atmospheric pressure sensor (BME/BMP280).<br>The sampling time of the PM sensors was set to one second, while the other sensors generated measurements every 3-4 seconds.</p> <p>The official monitoring station uses both a gravimetric and a beta attenuation instrument for measuring PM.</p> <p>The data contained in this dataset was collected from October 2020 to November 2021. It contains the PM2.5, relative humidity, and temperature measurements of the low-cost monitoring system and the official measurements of the beta attenuation device.</p> <p>Measurements of low-cost sensors are expressed in UTC, while official measurements are expressed in UTC+1.</p> <p>Official PM measurements can be also found at https://aria.ambiente.piemonte.it/qualita-aria/dati.</p>
Study of Automatic Image Fusion of a CT Volume With Ultrasound During Percutaneous Ablation Treatment of Hepatic Tumors
ClinicalTrials.gov study NCT04420026. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Evaluation of Conventional Non-invasive Mechanical Ventilation (NIV) Versus an Automatic Ventilation Mode.
ClinicalTrials.gov study NCT03872167. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Automatic Recognition of Freezing of Gait Episodes
ClinicalTrials.gov study NCT00738075. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Preoperative Anesthesia Automatic System:a Retrospective Cohort Study
ClinicalTrials.gov study NCT06148701. IPD Sharing: NO. Countries: 1. Publications: 1.
Relisten: Enhancing Care Quality and Saving Time With Automatic Clinical Note Generation in Primary Care
ClinicalTrials.gov study NCT06618092. IPD Sharing: NO. Countries: 1. Publications: 1.
Automatic Chlorination and Child Health in Urban Bangladesh
ClinicalTrials.gov study NCT02606981. IPD Sharing: Not stated. Countries: 1. Publications: 1.
MANual vs. automatIC Local Activation Time Annotation for Guiding Premature Ventricular Complex Ablation
ClinicalTrials.gov study NCT03340922. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Effects of an Automatic Oxygen Titration System in People With Hypoxemia During Exercise Training
ClinicalTrials.gov study NCT06545851. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention
ClinicalTrials.gov study NCT02990377. IPD Sharing: NO. Countries: 1. Publications: 1.
Multicenter Validation Study of an Artificial Intelligence Tool for Automatic Classification of Chest X-rays
ClinicalTrials.gov study NCT04991987. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Effects of Closed-loop Automatic Control of FiO2 in Extremely Preterm Infants
ClinicalTrials.gov study NCT03168516. IPD Sharing: UNDECIDED. Countries: 4. Publications: 2.
Automatic Oxygen Control (SPOC) in Preterm Infants
ClinicalTrials.gov study NCT03785899. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Automatic Stop Orders for Urinary Catheters
ClinicalTrials.gov study NCT00157625. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.