Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
53
datasets available to search
ShareScore release 0.9.0
Dataset results
53 results for “Modal analysis”
Data supporting: Improved Tangential Interpolation-based Multi-input Multi-output Modal Analysis of a Full Aircraft
Open the record for dataset details and reuse information.
Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images
<p>In cancer research, multiplexed imaging has enabled the in-depth characterization of the tumor microenvironment (TME) and how it relates to patient prognosis. However, standardized, multi-modal data from large numbers of patients to identify robust biomarkers is missing. To provide such data across five cancer indications, the IMMUcan consortium performs broad molecular and cellular spatial profiling of thousands of cancer samples. Two reproducible and scalable workflows have been developed for whole slide multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) to overcome challenges of reproducibility and scalability. For mIF we developed IFQuant, a web-based tool optimized for user-friendliness and reproducibility. This Zenodo record contains the mIF images and IFQuant settings to reproduce the results presented in the referenced publication. The companion IMC dataset is available as a joint Zenodo record.</p>
Cross-modal (text and figures) Analysis of a Scientific Corpus from Semantic Scholar - model weights
<p>In the related <a href="https://github.com/HybridNLP2018/tutorial">notebook </a>we show the application of cross-modal techniques to improve the categorization of scientific papers through content related to figures, using both the textual part (captions) and the visual part (figures, diagrams, images) jointly. To this purpose, we use several CNN models and execute some experiments, illustrating our approach. This deposit contains the model weights trained on such large corpora.</p>
Cross-modal (text and figures) Analysis of a Scientific Corpus from Semantic Scholar - images
<p>In this notebook we show the application of cross-modal techniques to improve the categorization of scientific papers through content related to figures, using both the textual part (captions) and the visual part (figures, diagrams, images) jointly. To this purpose, we use several CNN models and execute some experiments, illustrating our approach. This deposit contains high quality versions of the images used in the analysis.</p>
Modal analysis of thick-walled cylinders
<p><strong>FRF (Frequency Response Function): </strong>This measures how a system responds to dynamic forces at various frequencies. It is used in modal analysis to study vibrations and dynamic behavior of structures. The FRF helps understand how thick-walled cylinders respond to different vibrational modes and frequencies.</p> <div> <div> <div> <div> </div> </div> </div> </div> <div> <div> <div> <div> <div> <div> <p>A <code>.uff</code> file is a Universal File Format (UFF) used in the field of structural analysis, modal analysis, and vibration testing. To read and process <code>.uff</code> files in Python, you can use the <strong>pyuff</strong> library, which is specifically designed for handling UFF files.</p> </div> </div> </div> </div> </div> </div>
Datasets for Material Modal Composite Analysis results in Duanjiapo loess section
<p>The dataset is affilicated to the manuscript titled "Genesis of Loess Particles on the Chinese Loess Plateau" that is submitted for publication in the journal of Geochemistry, Geophysics, Geosystems. The original instrumental data packages were provided in the excel files (Data1, Data2, Data3, and Data4).</p>
Analysis of Human Tissue Temperature After Application of Therapeutic Modalities.
ClinicalTrials.gov study NCT03601715. IPD Sharing: YES. Countries: 1. Publications: 8.
Single-cell multi-modal analysis of tumor microenvironment in human non-small cell lung cancer tissues
Open the record for dataset details and reuse information.
URDU Dataset for Multi-modal Sentiment Analysis
<p>The "Multi-modal Sentiment Analysis Dataset for Urdu Language Opinion Videos" is a valuable resource aimed at advancing research in sentiment analysis, natural language processing, and multimedia content understanding. This dataset is specifically curated to cater to the unique context of Urdu language opinion videos, a dynamic and influential content category in the digital landscape.</p> <p><strong>Dataset Description:</strong></p> <ul> <li><strong>Size and Diversity:</strong> This dataset comprises an extensive collection of Urdu language opinion videos, encompassing a wide spectrum of topics and sentiments. It consists of a total of 214 videos, each of varying lengths, offering a diverse and comprehensive representation of the Urdu language content landscape.</li> <li><strong>Sentiment Annotations:</strong> The dataset is meticulously annotated with sentiment labels, providing information on the emotional tone expressed in each video. The sentiment labels include "positive," "negative," and "neutral," offering a nuanced understanding of the sentiment conveyed in these multimedia opinion pieces.</li> <li><strong>Multi-modal Approach:</strong> A unique feature of this dataset is its multi-modal approach. It combines text, audio, and visual data to enable researchers to delve into the various dimensions of sentiment analysis within the context of opinion videos. The multi-modal annotations encompass the textual content of spoken words, the auditory characteristics of the videos, and the visual cues from the video frames.</li> </ul> <p><strong>Significance and Applications:</strong></p> <p>This dataset holds significant value for both the research community and practical applications:</p> <ul> <li><strong>Research Advancement:</strong> Researchers can employ this dataset to investigate the complex landscape of sentiment analysis within the context of opinion videos. It facilitates inquiries into sentiment trends, the development of sentiment analysis models, and the creation of sentiment-aware multimedia content analysis tools.</li> <li><strong>Content Recommendation:</strong> The dataset can play a pivotal role in the development of content recommendation systems that cater to viewers' emotional preferences. Understanding sentiment in opinion videos is crucial for improving content engagement and user experience.</li> <li><strong>User Engagement Analysis:</strong> The dataset can empower studies on user engagement and interaction with multimedia content. It is an essential resource for researchers aiming to decode the factors influencing viewer reactions and engagement in multimedia.</li> </ul> <p> </p> <p>Researchers are encouraged to explore and utilize this dataset for various academic and commercial purposes, fostering innovation in sentiment analysis and multimedia understanding. The dataset is made available with open access to facilitate collaborative research and to contribute to the broader knowledge in the field.</p>
Dataset and statistical analysis related to "Amphibian studies to investigate the endocrine disrupting properties of chemicals through the Thyroid modality: a comparison of their statistical power"
Open the record for dataset details and reuse information.
EMA (Experimental Modal Analysis) of Concept Car Frame
<p>Result file of EMA measurement of Concept Car frame.</p>
Using Multi-Modal Path-Specific Transit Trips in Transportation Social Sustainability Analysis: Case Study in Atlanta, GA
Open the record for dataset details and reuse information.
Data from: Creating a multi-track classical music performance dataset for multi-modal music analysis: challenges, insights, and applications
We introduce a dataset for facilitating audio-visual analysis of musical performances. The dataset comprises 44 simple multi-instrument classical music pieces assembled from coordinated but separately recorded performances of individual tracks. For each piece, we provide the musical score in MIDI format, the audio recordings of the individual tracks, the audio and video recording of the assembled mixture, and ground- truth annotation files including frame-level and note-level tran- scriptions. We describe our methodology for the creation of the dataset, particularly highlighting our approaches for addressing the challenges involved in maintaining synchronization and ex- pressiveness. We demonstrate the high quality of synchronization achieved with our proposed approach by comparing the dataset against existing widely-used music audio datasets. We anticipate that the dataset will be useful for the devel- opment and evaluation of existing music information retrieval (MIR) tasks, as well as for novel multi-modal tasks. We bench- mark two existing MIR tasks (multi-pitch analysis and score- informed source separation) on the dataset and compare against other existing music audio datasets. Additionally, we consider two novel multi-modal MIR tasks (visually informed multi-pitch analysis and polyphonic vibrato analysis) enabled by the dataset and provide evaluation measures and baseline systems for future comparisons (from our recent work). Finally, we propose several emerging research directions that the dataset enables.
DravidianMultiModality: A Dataset for Multi-modal Sentiment Analysis in Tamil and Malayalam
<p>@article{dravidian_multimodality,<br> title={DravidianMultiModality: A Dataset for Multi-modal Sentiment Analysis in Tamil and Malayalam},<br> author={Bharathi Raja Chakravarthi, Jishnu Parameswaran P.K, Premjith B, K.P Soman, Rahul Ponnusamy, Prasanna Kumar Kumaresan, Kingston Pal Thamburaj, John P. McCrae},<br> journal={arXiv.org},<br> publisher={2021}<br> }</p>
Estimating Modal Mineralogy using Raman Spectroscopy: Multivariate Analysis Models and Raman Cross-Section Proxies - Chapter 4 Data
<p>I provide supplementary data for Chapter 4 of my dissertation including electron microprobe analysis data as well as the Raman spectra and associated metadata of the mineral end-members, the mineral-mineral mixtures, and the diamond-mineral mixtures.</p>
Analysis of the Effects on Human Tissues After Application of Therapeutic Modalities.
ClinicalTrials.gov study NCT03414346. IPD Sharing: NO. Countries: 1. Publications: 10.
Data from: Creating a multi-track classical music performance dataset for multi-modal music analysis: challenges, insights, and applications
Open the record for dataset details and reuse information.
Multi-modal analysis of the aging mouse lung at cellular resolution
GEO Series GSE124872. Mus musculus. 41 samples. Type: Expression profiling by high throughput sequencing.
Multi-modal analysis of human Plasma-cells
GEO Series GSE189953. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing; Other.
Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model.
GEO Series GSE160628. Mus musculus. 13 samples. Type: Other.
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.