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33
datasets available to search
ShareScore release 0.9.0
Dataset results
33 results for “state machine”
On the Understandability of Language Constructs to Structure the State and Behavior in Abstract State Machine Specifications: A Controlled Experiment
<p>Data-Set and Artifacts: Documents, Forms, and R Scripts for Reproducibility of the Empirical Study</p>
A Machine Learning Approach for Real-time Cortical State Estimation
<p>Data and code accompanying the following publication: Weiss, D. A., Borsa, A. M., Pala, A., Sederberg, A. J., & Stanley, G. B. (2024). A machine learning approach for real-time cortical state estimation. <em>Journal of neural engineering</em>, <em>21</em>(1), 10.1088/1741-2552/ad1f7b. https://doi.org/10.1088/1741-2552/ad1f7b</p>
Data for "Explainable Machine Learning for Predicting Homicide Clearance in the United States"
<p>These pickle files can be used to replicate the analyses carried out in the paper "Explainable Machine Learning for Predicting Homicide Clearance in the United States", currently under review.</p>
Supporting data and code for the published paper: Machine Learning Nonadiabatic Dynamics: Eliminating Phase Freedom of Nonadiabatic Couplings with the State-Interaction State-Averaged Spin-Restricted Ensemble-Referenced Kohn–Sham Approach
Open the record for dataset details and reuse information.
Power grid attack detection and state estimation with machine learning
<p>Detecting attacks and estimating states of power grids from partial observations with machine learning. A manuscript submitted to PRX Energy.</p>
Dataset of Flow Velocity Prediction in Vegetated Alluvial Channels Comparing Empirical and State-of-the-art Hybrid Machine Learning Models
<p>We compiled 447 datasets from different sources and lab- and field-based measurements. These datasets included Einstein and Banks (1950), Fenzl (1962), Kouwen et al. (1969), Ree and Crow (1977), Murota (1984), Tsujimoto and Kitamura (1990), Tsujimoto (1991), Tsujimoto (1993), Shimizu (1994), Dunn et al. (1996), Ikeda and Kanazawa (1996), Meijer (1998), Jarvela (2002), Rowinski and Kubrak (2002), Stone and Shen (2002), Poggi et al. (2004), Carollo et al. (2005), and Murphy et al. (2007).</p>
An Approach to Identify and Classify State Machine Changes from Code Changes
<p>Vídeo de auxílio para apresentação do artigo: An Approach to Identify and Classify State Machine Changes from Code Changes</p>
Live programming controlled experiment on state machines for robotic behaviors
<p>All the information about the controlled experiment performed on the Live Robot Programming language (LRP) vs SMACH (Python API), both for program comprehension and program writing</p> <ul> <li>Programs for both SMACH and LRP</li> <li>Introductory material for both SMACH and LRP</li> <li>Questionnaires</li> <li>Raw and processed data</li> </ul>
Machine readable code lists for an algorithm to identify incident lung cancer in United States healthcare claims data
<p>Machine readable code lists for an algorithm to identify incident lung cancer in United States healthcare claims data</p>
Novel Multimodal Neural, Physiological, and Behavioral Sensing and Machine Learning for Mental States
ClinicalTrials.gov study NCT07110688. IPD Sharing: YES. Countries: 1. Publications: 0.
Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning
ClinicalTrials.gov study NCT05864976. IPD Sharing: NO. Countries: 1. Publications: 0.
DBSOMA: A Machine Learning Method that Identifies Chemical Modulators of Transcriptional States Uncovers Effectors of Beta-Cell Maturation
GEO Series GSE309159. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Machine Learning approach to Classification of Resting-State EEG Microstates in stroke survivors
<p>Dataset - Machine Learning approach to Classification of Resting-State EEG Microstates in stroke survivors</p> <p>https://docs.google.com/spreadsheets/d/1MeEx9ysEC_tWyohqEmvc8Ey5mc5Z9NV2/edit#gid=160681293</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.