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739 results for “prints”
Machine Learning based scratches on printed paper detection, in high-speed printing systems [Dataset]
<p>Printing industry rapidly is adopting digital technologies and the requirements in terms of speed and print quality are also becoming more demanding. The is a wide range of possible quality defects in printed paper. This makes it impossible to have humans inspect the printed paper for such a big amount of possible quality defects at the high-speeds the printouts are produced.</p> <p>Printing industry is not taking advantage of the Artificial Intelligence to detect defects in printed paper at speed without human intervention. It is possible to generate millions of images (captures) with printed content from a printing system every day. Most of these images will not have any defect but some other will and can be used to generate a data set to be used in a machine learning system.</p> <p>The intention of this research work is to find ways artificial intelligence can help on automatically detecting defects on printed paper in a printing system and classifying them, without human intervention. Focusing on scratches, I’ve explored what are the actual proposals and solutions, and how machine learning can help improving them by using datasets with different techniques, implementing possible solutions and comparing the obtained results.</p>
Comparative analysis of Printed Circuit Boards with Surface and Embedded Components under Natural and Forced Convection
<p>Figures of heat distribution on PCB depending on the installation method (surface and embedded) and the speed of forced airflow.</p>
Supplementary material for 'In-situ full-field measurements for 3D printed polymers during mode I interface failure'
<p>Additional raw data and correlation analysis output for 'In-situ full- field measurements for 3D printed polymers during mode I interface failure'. We provide the patterned images acquired by the stereo microscopic Correlated Solution system (tiff format) and the VIC3D analysis results (csv format) for one representative specimen with 0°- 0° stacking undergoing mode I interlayer failure.</p>
Optimizing parametric factors in CIELAB and CIEDE2000 color-difference formulas for 3D printed spherical objects
<p>Forty-five spherical samples were printed using a Stratasys J750 3D color printer, and 82 pairs of 3D samples were produced to investigate the human color perception of the lightness, chroma and hue differences of 3D spherical objects, and to optimize the current CIELAB and CIEDE2000 color-difference formulas. This file contains the CIELAB values of the 45 spherical samples and the calculated colour differences as well as visual colour-difference data of 82 pairs of 3D samples. Optimizations of parametric factors in CIELAB and CIEDE2000 colour-difference formulas were performed based on the colour-difference data provided.</p>
Dataset for 'Experimental Quantification of Gas Dispersion in 3D-Printed Logpile Structures Using a Noninvasive Infrared Transmission Technique'
<p>This dataset contains the infrared images of tracer flow that were taken in the investigations of transverse dispersion in 3D-printed logpile structures. Accompanying the files (which are labelled according to the convention of the camera software) is a Python script which can be used to link the images to the operating conditions at which they were obtained. Documentation of this script can be found in the file at the very top. <br> This dataset was used as basis for the journal article 'Experimental Quantification of Gas Dispersion in 3D-Printed Logpile Structures Using a Noninvasive Infrared Transmission Technique', published in ACS Engineering Au under DOI:<a href="https://doi.org/10.1021/acsengineeringau.1c00040">10.1021/acsengineeringau.1c00040</a>. This paper can also be found in this repository at https://zenodo.org/record/6517082</p> <p> </p>
Use of waste materials for 3D printing of cement-based materials
<p>Experimental results:</p> <p>PSD = Particle Size Distribution</p> <p>XRF = X-Ray Fluorescence - chemical composition</p> <p> </p>
Predicting Respone: 3d printed biopolymer block dataset
<p>Dataset consisting of 87 edge shrinkage recording of 87 3d printed biopolymer components printed with inhouse receipe 10.5281/zenodo.5557218</p> <p> </p> <p>This dataset is reported in the paper</p> <p>Rossi G., Chiujdea R., Hochegger L., LHarchi A., Harding J., Nicholas P., Tamke M., Ramsgaard Thomsen M. (forthcomming 2022) Statistically modelling the curing of cellulose-based 3d printed components: Methods for material dataset composition, augmentation and encoding. In Design Modelling Symposium Berlin: Towards Radical Regeneration. 26-28 September 2022. University of the Arts Berlin, Germany</p>
ChapbooksScotland-KG: A Knowlege Graph for representing the "Chapbooks Printed In Scotland" (1671 - 1893)
<p>This Knowlege Graph represents the information of the "<strong>Chapbooks Printed In Scotland"</strong> (years: 1671 - 1893) collection in RDF (ttl format). This dataset comprises more than 3,000 chapbooks printed in Scotland from the 17th to 19th century. They form part of the Lauriston Castle Collection, which was bequeathed to the Library in 1926. It includes some 500 chapbook volumes containing around 5,500 individual items, more than half of which were printed in Scotland. The raw dataset is provided by the NLS in this <a href="https://data.nls.uk/data/digitised-collections/chapbooks-printed-in-scotland/">link</a>. As other NLS data collections, they are originally provided using two XMLs schemas: METS for descriptive, structural, technical and administrative metadata (Title, Author, Publisher, etc); and ALTO for encoding the OCR text of a page.</p> <p>In this work, we have extracted the information from METS and ALTO XMLS using <a href="https://github.com/francesNLP/defoe">defoe</a> tool and developed a <a href="https://github.com/francesNLP/defoe/blob/master/defoe/nls/queries/write_metadata_pages_yml.py">new information extraction defoe query</a> , and created a new Knowlege Graph called ChapbooksScotland-KG. The ChapbooksScotland-KG uses the <a href="https://francesnlp.github.io/NLS-ontology/doc/index-en.html">NLS Ontology </a>to represent the information extracted. Furthermore, during the information extraction phase, we have employed several techniques to mitigate two common OCR errors: long-S and the line-break hyphenation.</p> <p>The ChapbooksScotland-KG contains 352,270 RDF triples. It has information from 2728 series and 3080 volumes. Each serie can have several Volumes, Suplements, references to Books; it also has an Editor and a Publisher, which can be a Person or an Organization. A Volume has several Pages, with text in them. The data model of the ChapbooksScotland-KG can be found <a href="https://francesnlp.github.io/NLS-ontology/doc/dataModel.png">here</a>.</p>
YALTAi: Segmonto Manuscript and Early Printed Book Dataset
<p>This dataset has been built to train a segmentation model. It contains ALTO and YOLOv5 formats</p> <p>This dataset is derived from:</p> <ul> <li>CREMMA Medieval ( Pinche, A. (2022). Cremma Medieval (Version Bicerin 1.1.0) [Data set]. https://github.com/HTR-United/cremma-medieval )</li> <li>CREMMA Medieval Lat (Clérice, T. and Vlachou-Efstathiou, M. (2022). Cremma Medieval Latin [Data set]. https://github.com/HTR-United/cremma-medieval-lat )</li> <li>Eutyches. (Vlachou-Efstathiou, M. Voss.Lat.O.41 - Eutyches "de uerbo" glossed [Data set]. https://github.com/malamatenia/Eutyches)</li> <li>Gallicorpora HTR-Incunable-15e-Siecle ( Pinche, A., Gabay, S., Leroy, N., & Christensen, K. Données HTR incunable du 15e siècle [Computer software]. https://github.com/Gallicorpora/HTR-incunable-15e-siecle )</li> <li>Gallicorpora HTR-MSS-15e-Siecle ( Pinche, A., Gabay, S., Leroy, N., & Christensen, K. Données HTR manuscrits du 15e siècle [Computer software]. https://github.com/Gallicorpora/HTR-MSS-15e-Siecle )</li> <li>Gallicorpora HTR-imprime-gothique-16e-siecle ( Pinche, A., Gabay, S., Vlachou-Efstathiou, M., & Christensen, K. HTR-imprime-gothique-16e-siecle [Computer software]. https://github.com/Gallicorpora/HTR-imprime-gothique-16e-siecle )</li> </ul> <p>+ a few hundred newly annotated data, specifically the test set which is completely novel and based on early prints and manuscripts.</p> <p> </p> <table> <tbody> <tr> <td>Dataset</td> <td>Number of images</td> </tr> <tr> <td>Train</td> <td>854</td> </tr> <tr> <td>Dev</td> <td>154</td> </tr> <tr> <td>Test</td> <td>139</td> </tr> </tbody> </table> <p> </p>
2D MoS2/carbon/polylactic acid filament for 3D printing: Photo and electrochemical energy conversion and storage
<p>Raw data of published journal article "2D MoS2/carbon/polylactic acid filament for 3D printing: Photo and electrochemical energy conversion and storage", DOI: 10.1016/j.apmt.2021.101301</p>
Free-standing electrochemically coated MoSx based 3D-printed nanocarbon electrode for solid-state supercapacitor application
<p>Raw data of journal article "Free-standing electrochemically coated MoSx based 3D-printed nanocarbon electrode for solid-state supercapacitor application" DOI: 10.1039/d0nr06479c</p>
Fabrication and characterization of a multimodal 3D printed mouse phantom for ionoacoustic quality assurance in image-guided pre-clinical proton radiation research
<p>Dataset related to the publication: "Fabrication and characterization of a multimodal 3D printed mouse phantom for ionoacoustic quality assurance in image-guided pre-clinical proton radiation research"</p>
Text-fig. 4. Type specimens of Magnolia allasoniae MARTINETTO sp. nov. from the Pliocene locality Ca' Viettone. a1–a4: Holotype (MGPT-PU141081) in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 5) in a black and white print (a1), in a new digital photograph in basal view (a2), ventral view (a3) and dorsal view (a4); b1–b4: Paratype MGPT-PU141082 in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 4) in a black and white print (b1), in a new digital photograph in basal view (b2), ventral view (b3) and dorsal view (b4); c1–c4: Paratype MGPT-PU141083 in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 6) in a black and white print (c1), in a new digital photograph in basal view (c2), ventral view (c3) and dorsal view (c4); d1–d4: Paratype MGPT-PU141084 in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 7) in a black and white print (d1), in a new digital photograph in basal view (d2), ventral view (d3) and internal view (d4). Scale bars 1 mm. in Late Messinian Flora From The Post-Evaporitic Deposits Of The Piedmont Basin (Northwest Italy)
Text-fig. 4. Type specimens of Magnolia allasoniae MARTINETTO sp. nov. from the Pliocene locality Ca' Viettone. a1–a4: Holotype (MGPT-PU141081) in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 5) in a black and white print (a1), in a new digital photograph in basal view (a2), ventral view (a3) and dorsal view (a4); b1–b4: Paratype MGPT-PU141082 in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 4) in a black and white print (b1), in a new digital photograph in basal view (b2), ventral view (b3) and dorsal view (b4); c1–c4: Paratype MGPT-PU141083 in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 6) in a black and white print (c1), in a new digital photograph in basal view (c2), ventral view (c3) and dorsal view (c4); d1–d4: Paratype MGPT-PU141084 in different views, i.e., as originally figured in Martinetto (1995: pl. 1, fig. 7) in a black and white print (d1), in a new digital photograph in basal view (d2), ventral view (d3) and internal view (d4). Scale bars 1 mm.
Fig. 3 in Theodor Kotschy in Iran, 1841-1843. Botanical collections and an early printed vegetation profile
Fig. 3. – Theodor Kotschy's Pflanzen Vertheilung [notes on distribution of duplicates] intended for Ludwig von KÖchel, 12 April 1842.
Fig. 1 in Theodor Kotschy in Iran, 1841-1843. Botanical collections and an early printed vegetation profile
Fig. 1. – Order of the government of Mohammad Shah to support the work of Theodor Kotschy in Iran issued by the scribe Al-Seyed Osman, servant of the helm, c. 1843.
Fig. 6 in Theodor Kotschy in Iran, 1841-1843. Botanical collections and an early printed vegetation profile
Fig. 6. – Lectotype of Aegilops kotschyi Boiss. (G-BOIS). Specimen collected in Iran, near Sabst-Buschom [Kuh-e Sabz Pushan] in May 1842 by Theodor Kotschy.
Fig. 4 in Theodor Kotschy in Iran, 1841-1843. Botanical collections and an early printed vegetation profile
Fig. 4. – Theodor Kotschy's passport, issued 29 December 1835. [recto; © Archiv, Naturhistorisches Museum, Vienna]
Fig. 7 in Theodor Kotschy in Iran, 1841-1843. Botanical collections and an early printed vegetation profile
Fig. 7. – Rudolf Friedrich Hohenacker, HÖhenprofil und Kärtchen des südwestlichen Theiles von Persien. Esslingen, 1846. (Annotation in unknown hand). Detail of the HÖhenprofil is shown below.
X-ray scattering Datasets of gold and silver nanoparticle composites, relating to the publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup"
<p>Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology). </p> <p> </p>
Reference data used in pufferfish pre-print experiments
<p>This holds the reference data used in the pufferfish pre-print. This includes a specific version of the human transcriptome, the human genome, and a collection of microbial genomes. These references are also available from different public repositories, but these versions are uploaded here to ease reproducibility of the manuscript's tests, and because the references were pre-processed to replace ambiguous nucleotides with valid ones.</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.