100+ datasets found
  1. F

    Employed full time: Wage and salary workers: Writers and authors...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
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    (2025). Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over: Women [Dataset]. https://fred.stlouisfed.org/series/LEU0254700000A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over: Women (LEU0254700000A) from 2000 to 2024 about occupation, full-time, females, salaries, workers, 16 years +, wages, employment, and USA.

  2. i

    Grant Giving Statistics for Writers Matter

    • instrumentl.com
    Updated Jun 22, 2024
    + more versions
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    (2024). Grant Giving Statistics for Writers Matter [Dataset]. https://www.instrumentl.com/990-report/writers-matter
    Explore at:
    Dataset updated
    Jun 22, 2024
    Variables measured
    Total Assets, Total Giving
    Description

    Financial overview and grant giving statistics of Writers Matter

  3. Z

    TriGraphSlant - benchmark set for writer identification - writers were asked...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jan 24, 2020
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    L.R.B. Schomaker (2020). TriGraphSlant - benchmark set for writer identification - writers were asked to write in unnatural slant [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_1195798
    Explore at:
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    C.E. van den Heuvel
    R.A. van Batenburg
    A.A. Brink
    R.M.J. Niels
    L.R.B. Schomaker
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Disclaimer and terms of use:

    /*****************************************************************************
    * * * * * This is the TrigraphSlant (Img version) Distribution, release 18/3/2011 * * * * * This distribution contains 188 images of scanned handwritten text, * * scanned at resolution 300dpi Canon LiDE 25, grey scale, * * by 47 Dutch writers, four pages per writer, from four * * writing conditions, one condition per page. The conditions are: * * 1. [AN] Copy text A in your natural handwriting. * * 2. [BN] Copy text B in your natural handwriting. * * 3. [BL] Copy text B and slant your handwriting to the * * left as much as possible. * * 4. [BR] Copy text B and slant your handwriting to the * * right as much as possible. * * The codes AN, BN, BL and BR refer to subsets into which the collected * * pages of the writers were subdivided. AN represents a collection of * * authentic documents; BN, BL and BR can be seen as collections of * * questioned documents. To avoid structural effects of fatigue, the order * * of item 3 and 4 was randomized at each collection: half of the subjects * * wrote the BR page before the BL page. The data were collected at three * * sites, in three cities: The Hague: NFI (N...), Donders Institute for * * Brain, Cognition and Behaviour, Radboud University Nijmegen (D...) * * and the Artificial Intelligence Dept. of University of Groningen (R...) * * * * Copyright The International Unipen Foundation, 2010, All rights reserved *

    • *
    • *
    • DISCLAIMER AND COPYRIGHT NOTICE FOR ALL DATA CONTAINED ON THIS CARRIER: *
    • *
    • *
    • 1) PERMISSION IS HEREBY GRANTED TO USE THE DATA FOR RESEARCH *
    • PURPOSES. IT IS NOT ALLOWED TO DISTRIBUTE THIS DATA FOR COMMERCIAL *
    • PURPOSES. *
    • *
    • *
    • 2) PROVIDER GIVES NO EXPRESS OR IMPLIED WARRANTY OF ANY KIND AND ANY *
    • IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR PURPOSE ARE *
    • DISCLAIMED. *
    • *
    • 3) PROVIDER SHALL NOT BE LIABLE FOR ANY DIRECT, INDIRECT, SPECIAL, *
    • INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF ANY USE OF THIS *
    • DATA. *
    • *
    • 4) THE USER SHOULD REFER TO THE FOLLOWING ARTICLE ON THIS DATA SET: *
    • *
    • A.A. Brink, R.M.J. Niels, R.A. van Batenburg, C.E. van den Heuvel, *
    • L.R.B. Schomaker, Towards robust writer verification by correcting *
    • unnatural slant, Pattern Recognition Letters, Volume 32, Issue 3, *
    • 1 February 2011, Pages 449-457, ISSN 0167-8655, *
    • DOI: 10.1016/j.patrec.2010.10.010. *
    • *
    • 5) THE RECIPIENT SHOULD REFRAIN FROM PROLIFERATING THE DATA SET TO THIRD *
    • PARTIES EXTERNAL TO HIS/HER LOCAL RESEARCH GROUP. PLEASE REFER INTERESTED *
    • RESEARCHERS TO HTTP://UNIPEN.ORG FOR OBTAINING THEIR OWN COPY. * *****************************************************************************/

    Abstract

    Towards robust writer verification by correcting unnatural slant

    A.A. Brink, , R.M.J. Niels, R.A. van Batenburg, C.E. van den Heuvel,
    and L.R.B. Schomaker,

    a Institute of Artificial Intelligence and Cognitive Engineering (ALICE),
    University of Groningen, P.O. Box 407, 9700 AK Groningen, The Netherlands

    b Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen,
    P.O. Box 9104, 6500 HE Nijmegen, The Netherlands

    c Netherlands Forensic Institute, P.O. Box 24044, 2490 AA Den Haag, The Netherlands

    Received 11 September 2009. Available online 30 October 2010.

    Slant is a salient feature of Western handwriting and it is considered to be an important writer-specific feature. In disguised handwriting however, slant is often modified. It was tested whether slant is indeed an important factor and it was tested whether the distorting effect of deliberate slant change can be countered by a simple shear transform. This was done in two off-line writer verification experiments in image processing conditions of slant elimination and slant correction. The experiments were performed using three features based on statistical pattern recognition, including the state-of-the-art features Fraglets and Hinge. A new public dataset was created and used, containing natural and slanted handwriting by 47 writers. A striking result is that the average natural slant value is much less important for biometric systems than is usually assumed: eliminating slant yields just a 1-5% performance loss. A second result is that the effects of deliberate slant change cannot be fully countered by a simple shear transform: it raises performance on the distorted handwriting from 53-68% to 64-90%, but this is still lower than normal operation on natural handwriting: 97-100%.

    Research highlights - The value of slant as a writer identification feature has been overrated.
    - Deliberate slant change can be partly countered by the shear transform.
    - Deliberate slant change introduces non-affine distortions to the handwriting.
    - A new dataset of deliberately slanted handwriting was introduced.

    Keywords: Handwriting biometrics; Writer verification; Slant; Disguise; Statistical pattern recognition

  4. F

    Employed full time: Wage and salary workers: Writers and authors...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
    + more versions
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    (2025). Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over [Dataset]. https://fred.stlouisfed.org/series/LEU0254486400A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over (LEU0254486400A) from 2000 to 2024 about occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

  5. Female writers on late night shows in the U.S. 2019

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Female writers on late night shows in the U.S. 2019 [Dataset]. https://www.statista.com/statistics/1016152/female-writers-late-night-shows-us/
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    This statistic presents the share of writers on selected late night shows that are women in the United States in 2019. The findings show that despite The Late Late Show with James Corden and Jimmy Kimmel Live having female co-head writers, and The Tonight Show Starring Jimmy Fallon having a female head writer, none of these shows had a cohort of writing staff that was more than ** percent female. For Full Frontal With Samantha Bee, the share of writers that were women amounted to ** percent, making the show the most evenly split in terms of writer gender.

  6. i

    Grant Giving Statistics for Writers and Books Inc.

    • instrumentl.com
    Updated Mar 7, 2021
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    (2021). Grant Giving Statistics for Writers and Books Inc. [Dataset]. https://www.instrumentl.com/990-report/writers-and-books-inc
    Explore at:
    Dataset updated
    Mar 7, 2021
    Variables measured
    Total Assets, Total Giving
    Description

    Financial overview and grant giving statistics of Writers and Books Inc.

  7. Time spent on writing tasks among U.S. professionals 2023

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Time spent on writing tasks among U.S. professionals 2023 [Dataset]. https://www.statista.com/statistics/1493349/time-spent-writing-tasks-us-employees/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 29, 2023 - Oct 3, 2023
    Area covered
    United States
    Description

    According to a survey conducted between September and October 2023, among professionals and business leaders in the United States, writing tasks required approximately ***** hours per week. Written communications to others were the most common writing task, occupying U.S. professionals for almost **** hours per week.

  8. Favorite contemporary French writers in France 2016

    • statista.com
    Updated Oct 29, 2016
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    Statista (2016). Favorite contemporary French writers in France 2016 [Dataset]. https://www.statista.com/statistics/747702/favorite-contemporary-french-writers-france/
    Explore at:
    Dataset updated
    Oct 29, 2016
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 20, 2016 - Oct 21, 2016
    Area covered
    France
    Description

    This statistic shows a ranking of the favorite contemporary French writers in France in 2016. ** percent of respondents stated that Jean d'Ormesson was their favorite contemporary French writer, compared to Amélie Nothomb who obtained ** percent.

  9. g

    NEWW Women Writers

    • datasearch.gesis.org
    • ssh.datastations.nl
    • +1more
    Updated Jan 23, 2020
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    Dijk, Dr. S. van (Huygens ING) DAI=info:eu-repo/dai/nl/304848379, ProjectLeader (2020). NEWW Women Writers [Dataset]. http://doi.org/10.17026/dans-x4u-2vha
    Explore at:
    Dataset updated
    Jan 23, 2020
    Dataset provided by
    DANS (Data Archiving and Networked Services)
    Authors
    Dijk, Dr. S. van (Huygens ING) DAI=info:eu-repo/dai/nl/304848379, ProjectLeader
    Description

    Description of the NEWW Women Writers VRE

    1. History

    First steps for preparing this tool were made at the end of the 1990s.

    Designated then as the “Database WomenWriters” it was created in order to allow, for pre-1900 Europe, the study of women’s writing in their international reception context. Such a study was not possible given the evident lack of large-scale information about women's writing being received by contemporaries. Large scale and transcending of boundaries was considered a necessity because of women's frequent role as translators, and also because of women's reputations abroad not always being recognized in the home country.

    The initiative was taken within the context of my research and teaching about French 18th and 19th-century women’s writing, as received in the Netherlands (Huizinga Institute and French department of University of Amsterdam). A number of colleagues of the “Werkverband Genderstudies Neerlandistiek Literatuur-geschiedschrijving (see also here) participated in the preliminary discussions which were also reflected in the volume “I have heard about you”. Foreign women’s writing crossing the Dutch border: from Sappho to Selma Lagerlöf (edited by Suzan van Dijk, Petra Broomans, Janet F. van der Meulen and Pim van Oostrum. Hilversum: Verloren, 2004).

    Starting 2001, the database was included in the Roquade project of the Utrecht University Library, and further developed under the direction of Ben Brandenburg. Thanks to different NWO grants (digitizing and “internationalizing” projects), data were entered by assistants, and an international network started being created, whose members used the database for their research. It was elected for the "International Innovation Award 2005" on the occasion of the XVIth International Conference of the Association for History and Computing (Amsterdam).

    In 2009 we were granted a COST Action (IS0901 Women Writers in History), and the headquarters moved to Huygens Institute (KNAW) in The Hague. The meetings and training schools organized in the COST context were extremely useful for defining common approaches, and discussing research. They resulted in features listed as requirements for the tool. In part these could be realized by the Institute’s IT department, thanks to the HERA Project Travelling TexTs 1790-1914. The Transnational Reception of Women’s Writing at the Fringes of Europe (2013–2016). This project involved colleagues from five countries, but maintained the collaboration with colleagues of some 15 other countries. These are now, together, the DARIAH Working Group Women Writers in History.

    1. Content description

    The NEWW VRE contains information on the production of women authors from the Middle Ages up to the early 20th century, and on the reception of their works by contemporaries as well as early literary historians (both men and women). It comprises women who were active as authors, in the sense that they published their writings, either through publishing houses or in the periodical press.

    The structure of the VRE connects between authors and between publications: it can show both Jane Austen (for instance) influencing Isabelle de Montolieu, and Sense and Sensibility being translated into Raison et Sensibilité. Data are entered when any proof of reception is found: in other words, when it becomes clear through comments in press, private letters, translations, adaptations etc. that a woman writer and/or her works were received and read. Though the main focus lies on European women authors, the VRE also includes information on works and reception created in European colonies, Canada and the United States, due to the mutual cultural exchanges between these regions and Europe.

    The data in the VRE are information data (metadata in fact): short biographical data and categorization of the authors; titles and other bibliographical information, as well as categorization of the publications (both primary works and reception documents). If available, records for authors and publications refer through hyperlinks to relevant online information and digitized texts.

    1. The Dutch part available at DANS

    As work on this tool started in the Netherlands and had the benefit of initial NWO funding, the amount of data for this country is more considerable than for the other countries. This is why we considered important to archive this bulk of information at DANS in EASY.

    The three “layers” contain at this moment: 1. 850 Dutch female authors (from Hadewych to Anne Frank, who through Cissy van Marxveldt was linked to Nellie van Kol), as well as 370 male authors, who were related to the women, receivers of the women’s writings (critics, journalists, anthologizers, etc.) or inspired their writing activities (from Erasmus to Heinz Polzer, grandson of Nellie van Kol) 2. 3700 publications by these women; 3. and: • 2800 reception documents (of the women’s works) • 2000 reception documents (concerning the authors)

    The very most of this cou

  10. i

    Grant Giving Statistics for Writers Of Southern Nevada

    • instrumentl.com
    Updated Sep 22, 2021
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    (2021). Grant Giving Statistics for Writers Of Southern Nevada [Dataset]. https://www.instrumentl.com/990-report/writers-of-southern-nevada
    Explore at:
    Dataset updated
    Sep 22, 2021
    Area covered
    Southern Nevada, Nevada
    Description

    Financial overview and grant giving statistics of Writers Of Southern Nevada

  11. Top ways for using AI-assisted writing for marketing worldwide 2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Top ways for using AI-assisted writing for marketing worldwide 2023 [Dataset]. https://www.statista.com/statistics/1425269/ai-assisted-writing-uses-marketers-worldwide/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2023
    Area covered
    Worldwide
    Description

    During a March 2023 survey among marketers worldwide, ** percent of respondents who used artificial intelligence (AI) as an assistant in writing said that before publishing, they only make minor edits to the AI-generated text. Another ** percent made major edits before going online, while **percent changed the text altogether.

  12. Distribution of movie writers in the U.S. 2011-2022, by ethnicity

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Distribution of movie writers in the U.S. 2011-2022, by ethnicity [Dataset]. https://www.statista.com/statistics/696893/movie-writer-ethnicity/
    Explore at:
    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, **** percent of film writers in the United States were part of ethnic minorities, whereas the remaining **** percent were white, according to the source. A decade earlier, the shares stood at *** and **** percent, respectively. More than ** percent of movie directors in the U.S. were white in 2022.

  13. Share of people writing poems, haiku, and novels in Japan 1996-2021

    • statista.com
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    Statista, Share of people writing poems, haiku, and novels in Japan 1996-2021 [Dataset]. https://www.statista.com/statistics/1338893/japan-novel-poem-writing-participation-rate/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2021
    Area covered
    Japan
    Description

    According to a survey conducted in October 2021 in Japan, *** percent of people practiced penmanship, by writing poems, haiku, or novels. This was the lowest result during the surveyed period.

  14. Popularity of writing as a hobby in the U.S. 2022-2024

    • statista.com
    Updated Jun 18, 2024
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    Statista (2024). Popularity of writing as a hobby in the U.S. 2022-2024 [Dataset]. https://www.statista.com/forecasts/1466876/popularity-of-writing-as-a-hobby-in-the-us
    Explore at:
    Dataset updated
    Jun 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    There are so many hobbies to choose from. How has the popularity of writing as a hobby in the U.S. changed over time? There is only a slight increase from 2023 Q1 to the current value. What do you do in your free time? Would you consider yourself one of the writers? Hobbies cater to different needs like creativity, self-expression, or relaxation. Rather than a pastime we look forward to our hobbies and cut out time for them regularly. If you are looking for hobby inspiration, this ranking of the most popular hobbies in the U.S. might just spark a new interest for you. The survey was conducted online among 15040 to 60327 respondents per quarter in the United States, between 2022 and 2024. Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than 2,000,000 interviews.

  15. H

    Data from: Normative data for email writing

    • dataverse.harvard.edu
    Updated Dec 19, 2014
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    Lindsey Thiel; Karen Sage; Paul Conroy (2014). Normative data for email writing [Dataset]. http://doi.org/10.7910/DVN/28204
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 19, 2014
    Dataset provided by
    Harvard Dataverse
    Authors
    Lindsey Thiel; Karen Sage; Paul Conroy
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/28204https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/28204

    Time period covered
    2011 - 2014
    Area covered
    United Kingdom
    Description

    This data set includes emails from forty two healthy control participants ranging from 16 to 88 years of age (mean = 45.64) and 9 to 24 years of education (mean = 13.36). Three emails were produced by each participant, each within a time limit of three minutes. Emails were anonymised by replacing names, addresses and professions with different names, addresses and professions consisting of the same number of letters. Otherwise, the emails appear exactly as they were written, with no changes to layout, spaces, words, letter case or punctuation. It is expected that this normative data will be useful to clinicians and researchers working with adults with acquired language disorders in assessing email writing.

  16. o

    Writers Circle Cross Street Data in Brentwood, TN

    • ownerly.com
    Updated Mar 23, 2022
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    Ownerly (2022). Writers Circle Cross Street Data in Brentwood, TN [Dataset]. https://www.ownerly.com/tn/brentwood/writers-cir-home-details
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    Dataset updated
    Mar 23, 2022
    Dataset authored and provided by
    Ownerly
    Area covered
    Brentwood, Tennessee, Writers Circle
    Description

    This dataset provides information about the number of properties, residents, and average property values for Writers Circle cross streets in Brentwood, TN.

  17. i

    Grant Giving Statistics for Mountain Writers Series

    • instrumentl.com
    Updated Jul 31, 2025
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    (2025). Grant Giving Statistics for Mountain Writers Series [Dataset]. https://www.instrumentl.com/990-report/mountain-writers-series
    Explore at:
    Dataset updated
    Jul 31, 2025
    Variables measured
    Total Assets
    Description

    Financial overview and grant giving statistics of Mountain Writers Series

  18. f

    Data from: Developing Students’ Statistical Expertise Through Writing in the...

    • tandf.figshare.com
    pdf
    Updated Jun 30, 2025
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    Laura S. DeLuca; Alex Reinhart; Gordon Weinberg; Michael Laudenbach; Sydney Miller; David West Brown (2025). Developing Students’ Statistical Expertise Through Writing in the Age of AI [Dataset]. http://doi.org/10.6084/m9.figshare.28883205.v2
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset provided by
    Taylor & Francis
    Authors
    Laura S. DeLuca; Alex Reinhart; Gordon Weinberg; Michael Laudenbach; Sydney Miller; David West Brown
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    As large language models (LLMs) such as GPT have become more accessible, concerns about their potential effects on students’ learning have grown. In data science education, the specter of students’ turning to LLMs raises multiple issues, as writing is a means not just of conveying information but of developing their statistical reasoning. In our study, we engage with questions surrounding LLMs and their pedagogical impact by: (a) quantitatively and qualitatively describing how select LLMs write report introductions and complete data analysis reports; and (b) comparing patterns in texts authored by LLMs to those authored by students and by published researchers. Our results show distinct differences between machine-generated and human-generated writing, as well as between novice and expert writing. Those differences are evident in how writers manage information, modulate confidence, signal importance, and report statistics. The findings can help inform classroom instruction, whether that instruction is aimed at dissuading the use of LLMs or at guiding their use as a productivity tool. It also has implications for students’ development as statistical thinkers and writers. What happens when they offload the work of data science to a model that doesn’t write quite like a data scientist? Supplementary materials for this article are available online.

  19. Z

    Firemaker image collection for benchmarking forensic writer identification...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jan 24, 2020
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    Vuurpijl, Louis (2020). Firemaker image collection for benchmarking forensic writer identification using image-based pattern recognition [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_1194611
    Explore at:
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Schomaker, Lambert
    Vuurpijl, Louis
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Disclaimer and terms of use:

    /*****************************************************************************
    * * * * * This is the Firemaker NFI-images Distribution * * * * This distribution contains 1000 images of scanned handwritten text, * * scanned at resolution 300dpi grey scale, containing pages of * * handwritten text by 250 writers, four pages per writer, from four * * writing conditions, one condition per page. The conditions are: * * p1: copied, natural style, p2: copied, UPPER case, p3: copied and forged, * * i.e.,"try to write in a different style than your natural style", and p4, * * self generated, i.e., text produced to describe a given cartoon. * * * * * * * * Copyright The International Unipen Foundation, 2000, All rights reserved *

    • *
    • *
    • DISCLAIMER AND COPYRIGHT NOTICE FOR ALL DATA CONTAINED ON THIS CDROM: *
    • *
    • *
    • 1) PERMISSION IS HEREBY GRANTED TO USE THE DATA FOR RESEARCH *
    • PURPOSES. IT IS NOT ALLOWED TO DISTRIBUTE THIS DATA FOR COMMERCIAL *
    • PURPOSES. *
    • *
    • *
    • 2) PROVIDER GIVES NO EXPRESS OR IMPLIED WARRANTY OF ANY KIND AND ANY *
    • IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR PURPOSE ARE *
    • DISCLAIMED. *
    • *
    • 3) PROVIDER SHALL NOT BE LIABLE FOR ANY DIRECT, INDIRECT, SPECIAL, *
    • INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF ANY USE OF THIS *
    • DATA. *
    • *
    • 4) THE USER SHOULD REFER TO THE FIRST PUBLIC ARTICLE ON THIS DATA SET: *
    • *
    • M. Bulacu, L. Schomaker & L. Vuurpijl (2003). *
    • Writer identification using edge-based directional features. *
    • ICDAR '03: Proceedings of the 7th International Conference on Document *
    • Analysis and Recognition, pp. 937-941. *
    • Piscataway: IEEE Computer, ISBN 0-7695-1960-1 *
    • *
    • 5) THE RECIPIENT SHOULD REFRAIN FROM PROLIFERATING THE DATA SET TO THIRD *
    • PARTIES EXTERNAL TO HIS/HER LOCAL RESEARCH GROUP. PLEASE REFER INTERESTED *
    • RESEARCHERS TO HTTP://UNIPEN.ORG FOR OBTAINING THEIR OWN COPY. * *****************************************************************************/

    BibTeX entry:

    @inproceedings{Firemaker,
    author = {Bulacu, M. and Schomaker, L.R.B. and Vuurpijl, L.},
    title = {Writer Identification Using Edge-Based Directional Features}, booktitle = {ICDAR '03: Proceedings of the 7th International Conference on Document Analysis and Recognition}, year = {2003}, isbn = {0-7695-1960-1}, pages = {937-941}, publisher = {IEEE Computer Society}, address = {Washington, DC, USA}, }

    In the project "Vergelijk", a grant obtained from the Dutch Forensic Science Institute, two existing professional writer-identification systems have been compared regarding usability studies and in particular recognition performance (Schomaker & Vuurpijl, 2000). The results of this comparison are contained in a confidential report:

    L.R.B. Schomaker and L.G. Vuurpijl (2000). Forensic writer identification: A benchmark data set and a comparison of two systems. Technical report, Nijmegen Institute for Cognition and Information (NICI), University of Nijmegen, The Netherlands.

    Informative and non-confidential details from this report are given in the accompanying file: 'firemaker-dbase.pdf'

    To compare both systems, a carefully designed experiment was conducted to record handwritten samples from male and female writers in several conditions:

    Condition 1: Normal constrained handwriting

    Below, the Dutch text writers had to produce in normal handwriting is given.

    --- start text ---- Zij bezochten veilingen en reisden met de KLM. Voor korte afstanden huurden ze een auto, meestal een VW of een Ford.

    De veilingen waren van 7-4-1993 tot 3-5-1993 in New York, Tokyo, Québec, Rome, Parijs, Zürich en Oslo.

    Omdat de veilingen steeds begonnen om 12 uur en je gemiddeld 200 tot 300 kilometer moest rijden, stonden zij steeds om 6.30 uur op en vertrokken om 8 uur uit het hotel.

    Elke dag hadden ze vijfhonderd (f 500,-) gulden nodig. Daarvoor gebruikten ze elke keer een cheque van tweehonderd (f 200,-) en een cheque van driehonderd (f 300,-) gulden. Aan geschenken gaven ze ongeveer honderd gulden (f 100,-) uit. --- end text ----

    Condition 2: Production of constrained block capital handwriting

    In this condition, the writers had to produce the following text in block-capital handwriting:

    --- start text ---- NADAT ZE IN NEW YORK, TOKYO, QUÉBEC, PARIJS, ZÜRICH EN OSLO WAREN GEWEEST, VLOGEN ZE UIT DE USA TERUG MET VLUCHT KL 658 OM 12 UUR.

    ZE KWAMEN AAN IN DUBLIN OM 7 UUR EN IN AMSTERDAM OM 9.40 UUR 'S AVONDS. DE FIAT VAN BOB EN DE VW VAN DAVID STONDEN IN R3 VAN HET PARKEERTERREIN. HIERVOOR MOESTEN ZE HONDERD GULDEN (F 100,-) BETALEN. --- end text ----

    Condition 3: Production of free-forged handwriting

    Below, the text writers had to produce in the free-forged handwriting condition is given. No example of handwriting is given which they have to mimick (forge), the condition concerns a self-conceived distorted handwriting style.

    --- start text ---- Nog dezelfde avond reden ze naar hun vrienden Chris, Emile, Jan, Irene en Henk, nadat ze hun vriendinnen Greta en Maria hadden opgehaald.

    Samen hadden ze vijfhonderd (500) zeldzame postzegels gekocht, Bob driehonderd (300) en David tweehonderd (200).

    De reis was de moeite waard geweest. --- end text ----

    Condition 4: Production of unconstrained handwriting

    The final text writers had to produce is unconstrained handwriting. The cartoon, a series of pictures concerning a 'UFO' landing had to be described in their own words, in at least six lines of text. See image file "space.gif".

    Thruth labels and writer identifications

    Each writer has a unique id, specified as:

    id: {num}{set} num: a three-digit number set: either 01, 02, 03 or 04, identifying one of the 4 experiments

    The vast majority of the writers producing sets 01, 02 and 03 mimicked the content and layout (empty lines) of the constrained texts they had to copy sufficiently accurately, such that the example texts are a good indication of the contents. However, as set 04 ("describe cartoon story") contains unconstrained self-generated handwriting, the corresponding thruth labels had to be extracted manually. The resulting label files are contained in the directory ./300dpi/p4-self-natural/labels/

    Note: no letter, word, line or paragraph segmentation is provided with this data set. The main text can be cropped easily. Since the orientation is horizontal, projection techniques can be used to extract lines, using a line-spacing parameter (~94 pixels line height) as an additional check.

    Overview of directories:

    300dpi/ p1-copy-normal/ Copying task, normal writing style
    p2-copy-upper/ Copying task, UPPER-case p3-copy-forged/ Copying task, instructed to mimic another script style p4-self-natural/ Self-generated text, natural writing condition

    Note: the original raw collection contained writer #155, who has been removed from this data set, as his first condition (p1) was started in upper case and the page was not completed. Deleted files were 15501.tif, 15502.tif, 15503.tif and 15504.tif.

    Note: the name of this data set (Firemaker) is a contraction of the names Vuurpijl and Schomaker.

    Note b: Example of a cutout of essential handwritten text using NetPBM tools:
    tifftopnm 15201.tif | pnmcut -left 50 -right 2400 -top 700 -bottom 3250 > handwriting.pgm

    For an experiment, the upper and lower halves of the resulting image were usually used in the Schomaker & Bulacu studies to obtain two samples of handwriting for a writer.

    http://www.ai.rug.nl/~lambert http://www.ai.rug.nl/~bulacu

    Our features for writer identification:

    Lambert Schomaker

  20. f

    Data from: Initial reading and writing skills in childhood education:...

    • scielo.figshare.com
    jpeg
    Updated Jun 1, 2023
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    Américo Nobre Gonçalves Ferreira Amorim; Natália Martins Dias; Emilia Xavier da Silva Albuquerque; Vanessa Cristina da Silva; Amanda Christina Gomes Pereira Falcão; Vera Gabrielly Rangel Guerra; Maíra Hermínio da Silva; Larissa Laís dos Santos (2023). Initial reading and writing skills in childhood education: achievement sample in the Northeast of Brazil for obtaining specific regional performance standards [Dataset]. http://doi.org/10.6084/m9.figshare.11609493.v1
    Explore at:
    jpegAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELO journals
    Authors
    Américo Nobre Gonçalves Ferreira Amorim; Natália Martins Dias; Emilia Xavier da Silva Albuquerque; Vanessa Cristina da Silva; Amanda Christina Gomes Pereira Falcão; Vera Gabrielly Rangel Guerra; Maíra Hermínio da Silva; Larissa Laís dos Santos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Northeast Region, Brazil
    Description

    ABSTRACT Purpose: the study aims to obtain preliminary normative data for early reading and writing skills of 5-year-old children in a sample from the Northeast of Brazil. It also aims to investigate the effects of the type of school (public vs. private) and the time of assessment (beginning vs. end of the school year), and whether there were significant differences in performance, as compared to those of children from the Southeast of Brazil. Methods: 389 5-year-old children from 17 private and 12 public schools were assessed in the beginning and at the end of the school year, by using the Reading and Writing Test. Each student was individually assessed in the two times of the year. Appropriate statistical tests were applied, adopting a significance level lower than 0.05. Results: the progress in the performance of private school children was stronger than that of their peers from public schools, accentuating the existing learning gap. The comparison with normative data from the Southeast revealed that the public schools in the Northeast outperformed those in all topics of comparison. Private schools in the Southeast had a better performance at the beginning of the year, but were outperformed by those of the Northeast at the end of the year. Conclusion: the differences in performance identified in the samples suggest the need for specific norms by geographical regions of Brazil, and by type of school (public or private). The data presented in this study are preliminary and can be enlarged in future studies.

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(2025). Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over: Women [Dataset]. https://fred.stlouisfed.org/series/LEU0254700000A

Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over: Women

LEU0254700000A

Explore at:
jsonAvailable download formats
Dataset updated
Jan 22, 2025
License

https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

Description

Graph and download economic data for Employed full time: Wage and salary workers: Writers and authors occupations: 16 years and over: Women (LEU0254700000A) from 2000 to 2024 about occupation, full-time, females, salaries, workers, 16 years +, wages, employment, and USA.

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