---
_id: '45484'
abstract:
- lang: eng
  text: <jats:title>Abstract</jats:title><jats:p>Graffiti is an urban phenomenon that
    is increasingly attracting the interest of the sciences. To the best of our knowledge,
    no suitable data corpora are available for systematic research until now. The
    Information System Graffiti in Germany project (<jats:sc>Ingrid</jats:sc>) closes
    this gap by dealing with graffiti image collections that have been made available
    to the project for public use. Within <jats:sc>Ingrid</jats:sc>, the graffiti
    images are collected, digitized and annotated. With this work, we aim to support
    the rapid access to a comprehensive data source on <jats:sc>Ingrid</jats:sc> targeted
    especially by researchers. In particular, we present <jats:sc>Ingrid</jats:sc>KG,
    an RDF knowledge graph of annotated graffiti, abides by the Linked Data and FAIR
    principles. We weekly update <jats:sc>Ingrid</jats:sc>KG by augmenting the new
    annotated graffiti to our knowledge graph. Our generation pipeline applies RDF
    data conversion, link discovery and data fusion approaches to the original data.
    The current version of <jats:sc>Ingrid</jats:sc>KG contains 460,640,154 triples
    and is linked to 3 other knowledge graphs by over 200,000 links. In our use case
    studies, we demonstrate the usefulness of our knowledge graph for different applications.</jats:p>
article_number: '318'
author:
- first_name: Mohamed Ahmed
  full_name: Sherif, Mohamed Ahmed
  last_name: Sherif
- first_name: Ana Alexandra Morim
  full_name: da Silva, Ana Alexandra Morim
  last_name: da Silva
- first_name: Svetlana
  full_name: Pestryakova, Svetlana
  last_name: Pestryakova
- first_name: Abdullah Fathi
  full_name: Ahmed, Abdullah Fathi
  last_name: Ahmed
- first_name: Sven
  full_name: Niemann, Sven
  last_name: Niemann
- first_name: Axel-Cyrille Ngonga
  full_name: Ngomo, Axel-Cyrille Ngonga
  last_name: Ngomo
citation:
  ama: 'Sherif MA, da Silva AAM, Pestryakova S, Ahmed AF, Niemann S, Ngomo A-CN. IngridKG:
    A FAIR Knowledge Graph of Graffiti. <i>Scientific Data</i>. 2023;10(1). doi:<a
    href="https://doi.org/10.1038/s41597-023-02199-8">10.1038/s41597-023-02199-8</a>'
  apa: 'Sherif, M. A., da Silva, A. A. M., Pestryakova, S., Ahmed, A. F., Niemann,
    S., &#38; Ngomo, A.-C. N. (2023). IngridKG: A FAIR Knowledge Graph of Graffiti.
    <i>Scientific Data</i>, <i>10</i>(1), Article 318. <a href="https://doi.org/10.1038/s41597-023-02199-8">https://doi.org/10.1038/s41597-023-02199-8</a>'
  bibtex: '@article{Sherif_da Silva_Pestryakova_Ahmed_Niemann_Ngomo_2023, title={IngridKG:
    A FAIR Knowledge Graph of Graffiti}, volume={10}, DOI={<a href="https://doi.org/10.1038/s41597-023-02199-8">10.1038/s41597-023-02199-8</a>},
    number={1318}, journal={Scientific Data}, publisher={Springer Science and Business
    Media LLC}, author={Sherif, Mohamed Ahmed and da Silva, Ana Alexandra Morim and
    Pestryakova, Svetlana and Ahmed, Abdullah Fathi and Niemann, Sven and Ngomo, Axel-Cyrille
    Ngonga}, year={2023} }'
  chicago: 'Sherif, Mohamed Ahmed, Ana Alexandra Morim da Silva, Svetlana Pestryakova,
    Abdullah Fathi Ahmed, Sven Niemann, and Axel-Cyrille Ngonga Ngomo. “IngridKG:
    A FAIR Knowledge Graph of Graffiti.” <i>Scientific Data</i> 10, no. 1 (2023).
    <a href="https://doi.org/10.1038/s41597-023-02199-8">https://doi.org/10.1038/s41597-023-02199-8</a>.'
  ieee: 'M. A. Sherif, A. A. M. da Silva, S. Pestryakova, A. F. Ahmed, S. Niemann,
    and A.-C. N. Ngomo, “IngridKG: A FAIR Knowledge Graph of Graffiti,” <i>Scientific
    Data</i>, vol. 10, no. 1, Art. no. 318, 2023, doi: <a href="https://doi.org/10.1038/s41597-023-02199-8">10.1038/s41597-023-02199-8</a>.'
  mla: 'Sherif, Mohamed Ahmed, et al. “IngridKG: A FAIR Knowledge Graph of Graffiti.”
    <i>Scientific Data</i>, vol. 10, no. 1, 318, Springer Science and Business Media
    LLC, 2023, doi:<a href="https://doi.org/10.1038/s41597-023-02199-8">10.1038/s41597-023-02199-8</a>.'
  short: M.A. Sherif, A.A.M. da Silva, S. Pestryakova, A.F. Ahmed, S. Niemann, A.-C.N.
    Ngomo, Scientific Data 10 (2023).
date_created: 2023-06-06T09:12:39Z
date_updated: 2023-06-06T09:17:10Z
department:
- _id: '574'
- _id: '115'
doi: 10.1038/s41597-023-02199-8
intvolume: '        10'
issue: '1'
keyword:
- Library and Information Sciences
- Statistics
- Probability and Uncertainty
- Computer Science Applications
- Education
- Information Systems
- Statistics and Probability
language:
- iso: eng
project:
- _id: '104'
  grant_number: '289287267'
  name: 'INGRID: INGRID: Informationssystem Graffiti in Deutschland'
publication: Scientific Data
publication_identifier:
  issn:
  - 2052-4463
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: 'IngridKG: A FAIR Knowledge Graph of Graffiti'
type: journal_article
user_id: '6593'
volume: 10
year: '2023'
...
---
_id: '32335'
abstract:
- lang: eng
  text: Aspects of data science surround us in many contexts, for example regarding
    climate change, air pollution, and other environmental issues. To open the “data-science-black-box”
    for lower secondary school students we developed a data science project focussing
    on the analysis of self-collected environmental data. We embed this project in
    computer science education, which enables us to use a new knowledge-based programming
    approach for the data analysis within Jupyter Notebooks and the programming language
    Python. In this paper, we evaluate the second cycle of this project which took
    place in a ninth-grade computer science class. In particular, we present how the
    students coped with the professional tool of Jupyter Notebooks for doing statistical
    investigations and which insights they gained.
article_number: '6'
author:
- first_name: SUSANNE
  full_name: PODWORNY, SUSANNE
  last_name: PODWORNY
- first_name: Sven
  full_name: Hüsing, Sven
  id: '58465'
  last_name: Hüsing
- first_name: CARSTEN
  full_name: SCHULTE, CARSTEN
  last_name: SCHULTE
citation:
  ama: 'PODWORNY S, Hüsing S, SCHULTE C. A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL:
    BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS EDUCATION RESEARCH
    JOURNAL</i>. 2022;21(2). doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>'
  apa: 'PODWORNY, S., Hüsing, S., &#38; SCHULTE, C. (2022). A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i>, <i>21</i>(2), Article 6. <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>'
  bibtex: '@article{PODWORNY_Hüsing_SCHULTE_2022, title={A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}, volume={21},
    DOI={<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>},
    number={26}, journal={STATISTICS EDUCATION RESEARCH JOURNAL}, publisher={International
    Association for Statistical Education}, author={PODWORNY, SUSANNE and Hüsing,
    Sven and SCHULTE, CARSTEN}, year={2022} }'
  chicago: 'PODWORNY, SUSANNE, Sven Hüsing, and CARSTEN SCHULTE. “A PLACE FOR A DATA
    SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>.'
  ieee: 'S. PODWORNY, S. Hüsing, and C. SCHULTE, “A PLACE FOR A DATA SCIENCE PROJECT
    IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING,” <i>STATISTICS EDUCATION
    RESEARCH JOURNAL</i>, vol. 21, no. 2, Art. no. 6, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  mla: 'PODWORNY, SUSANNE, et al. “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN
    STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>,
    vol. 21, no. 2, 6, International Association for Statistical Education, 2022,
    doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  short: S. PODWORNY, S. Hüsing, C. SCHULTE, STATISTICS EDUCATION RESEARCH JOURNAL
    21 (2022).
date_created: 2022-07-08T12:06:48Z
date_updated: 2022-07-08T12:07:46Z
department:
- _id: '67'
doi: 10.52041/serj.v21i2.46
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: STATISTICS EDUCATION RESEARCH JOURNAL
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: 'A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC
  PROGRAMMING'
type: journal_article
user_id: '58465'
volume: 21
year: '2022'
...
---
_id: '34200'
abstract:
- lang: eng
  text: <jats:p>Praxeologische Kompetenzansätze verstehen Kompetenz als sozial erlernt
    und folglich als relativ zum sozialen Kontext. Damit einher geht die Frage, wie
    solche praxeologisch gerahmten Kompetenzen eigentlich unabhängig von der sie hervorbringenden
    Praxis evaluiert werden können – und eben dadurch erst für einen breiteren Kompetenzdiskurs
    fruchtbar sind. Die Dokumentarische Evaluationsforschung bietet hierzu erste Anhaltspunkte,
    offenbart aber auch Grenzen, die mit dem Evaluationsverständnis zusammenhängen,
    sich jedoch in der Forschungspraxis so nicht finden lassen. Aus der Differenz
    zwischen Methode und Praxis dokumentarischer Evaluation lässt sich formulieren,
    wie eine praxeologische Evaluation gestaltet werden könnte. Dabei spielt die Formulierung
    von Referenzrahmen eine zentrale Rolle, welche einerseits der zu evaluierenden
    Praktik external sein, andererseits praktisch formuliert werden müssen, damit
    sie soziale Praktiken jenseits ihrer eigenen Sinnhaftigkeit evaluativ (er-)fassen
    können.</jats:p>
author:
- first_name: Thiemo
  full_name: Bloh, Thiemo
  last_name: Bloh
citation:
  ama: Bloh T. Rekonstruktive Evaluationsforschung im Kontext praxeologischer Kompetenzdiskurse.
    Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen Evaluationsforschung.
    <i>Zeitschrift für Evaluation</i>. 2022;2022(02):193-215. doi:<a href="https://doi.org/10.31244/zfe.2022.02.02">10.31244/zfe.2022.02.02</a>
  apa: Bloh, T. (2022). Rekonstruktive Evaluationsforschung im Kontext praxeologischer
    Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen
    Evaluationsforschung. <i>Zeitschrift für Evaluation</i>, <i>2022</i>(02), 193–215.
    <a href="https://doi.org/10.31244/zfe.2022.02.02">https://doi.org/10.31244/zfe.2022.02.02</a>
  bibtex: '@article{Bloh_2022, title={Rekonstruktive Evaluationsforschung im Kontext
    praxeologischer Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen
    zur Dokumentarischen Evaluationsforschung}, volume={2022}, DOI={<a href="https://doi.org/10.31244/zfe.2022.02.02">10.31244/zfe.2022.02.02</a>},
    number={02}, journal={Zeitschrift für Evaluation}, publisher={Waxmann}, author={Bloh,
    Thiemo}, year={2022}, pages={193–215} }'
  chicago: 'Bloh, Thiemo. “Rekonstruktive Evaluationsforschung im Kontext praxeologischer
    Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen
    Evaluationsforschung.” <i>Zeitschrift für Evaluation</i> 2022, no. 02 (2022):
    193–215. <a href="https://doi.org/10.31244/zfe.2022.02.02">https://doi.org/10.31244/zfe.2022.02.02</a>.'
  ieee: 'T. Bloh, “Rekonstruktive Evaluationsforschung im Kontext praxeologischer
    Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen
    Evaluationsforschung,” <i>Zeitschrift für Evaluation</i>, vol. 2022, no. 02, pp.
    193–215, 2022, doi: <a href="https://doi.org/10.31244/zfe.2022.02.02">10.31244/zfe.2022.02.02</a>.'
  mla: Bloh, Thiemo. “Rekonstruktive Evaluationsforschung im Kontext praxeologischer
    Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen
    Evaluationsforschung.” <i>Zeitschrift für Evaluation</i>, vol. 2022, no. 02, Waxmann,
    2022, pp. 193–215, doi:<a href="https://doi.org/10.31244/zfe.2022.02.02">10.31244/zfe.2022.02.02</a>.
  short: T. Bloh, Zeitschrift für Evaluation 2022 (2022) 193–215.
date_created: 2022-12-05T13:25:58Z
date_updated: 2022-12-05T13:26:35Z
department:
- _id: '4'
doi: 10.31244/zfe.2022.02.02
intvolume: '      2022'
issue: '02'
keyword:
- Strategy and Management
- Applied Psychology
- Social Sciences (miscellaneous)
- Education
- Communication
- Statistics and Probability
language:
- iso: ger
page: 193-215
publication: Zeitschrift für Evaluation
publication_identifier:
  issn:
  - 1619-5515
  - 2699-5506
publication_status: published
publisher: Waxmann
quality_controlled: '1'
status: public
title: Rekonstruktive Evaluationsforschung im Kontext praxeologischer Kompetenzdiskurse.
  Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen Evaluationsforschung
type: journal_article
user_id: '69383'
volume: 2022
year: '2022'
...
---
_id: '48108'
abstract:
- lang: eng
  text: <jats:p>Aspects of data science surround us in many contexts, for example
    regarding climate change, air pollution, and other environmental issues. To open
    the “data-science-black-box” for lower secondary school students we developed
    a data science project focussing on the analysis of self-collected environmental
    data. We embed this project in computer science education, which enables us to
    use a new knowledge-based programming approach for the data analysis within Jupyter
    Notebooks and the programming language Python. In this paper, we evaluate the
    second cycle of this project which took place in a ninth-grade computer science
    class. In particular, we present how the students coped with the professional
    tool of Jupyter Notebooks for doing statistical investigations and which insights
    they gained.</jats:p>
article_number: '6'
author:
- first_name: SUSANNE
  full_name: PODWORNY, SUSANNE
  last_name: PODWORNY
- first_name: SVEN
  full_name: HÜSING, SVEN
  last_name: HÜSING
- first_name: CARSTEN
  full_name: SCHULTE, CARSTEN
  last_name: SCHULTE
citation:
  ama: 'PODWORNY S, HÜSING S, SCHULTE C. A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL:
    BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS EDUCATION RESEARCH
    JOURNAL</i>. 2022;21(2). doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>'
  apa: 'PODWORNY, S., HÜSING, S., &#38; SCHULTE, C. (2022). A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i>, <i>21</i>(2), Article 6. <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>'
  bibtex: '@article{PODWORNY_HÜSING_SCHULTE_2022, title={A PLACE FOR A DATA SCIENCE
    PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}, volume={21},
    DOI={<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>},
    number={26}, journal={STATISTICS EDUCATION RESEARCH JOURNAL}, publisher={International
    Association for Statistical Education}, author={PODWORNY, SUSANNE and HÜSING,
    SVEN and SCHULTE, CARSTEN}, year={2022} }'
  chicago: 'PODWORNY, SUSANNE, SVEN HÜSING, and CARSTEN SCHULTE. “A PLACE FOR A DATA
    SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS
    EDUCATION RESEARCH JOURNAL</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.46">https://doi.org/10.52041/serj.v21i2.46</a>.'
  ieee: 'S. PODWORNY, S. HÜSING, and C. SCHULTE, “A PLACE FOR A DATA SCIENCE PROJECT
    IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING,” <i>STATISTICS EDUCATION
    RESEARCH JOURNAL</i>, vol. 21, no. 2, Art. no. 6, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  mla: 'PODWORNY, SUSANNE, et al. “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN
    STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>,
    vol. 21, no. 2, 6, International Association for Statistical Education, 2022,
    doi:<a href="https://doi.org/10.52041/serj.v21i2.46">10.52041/serj.v21i2.46</a>.'
  short: S. PODWORNY, S. HÜSING, C. SCHULTE, STATISTICS EDUCATION RESEARCH JOURNAL
    21 (2022).
date_created: 2023-10-17T05:59:38Z
date_updated: 2023-10-17T06:01:58Z
doi: 10.52041/serj.v21i2.46
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
publication: STATISTICS EDUCATION RESEARCH JOURNAL
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: 'A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC
  PROGRAMMING'
type: journal_article
user_id: '30619'
volume: 21
year: '2022'
...
---
_id: '53238'
article_number: '101189'
author:
- first_name: Madjid
  full_name: Tavana, Madjid
  id: '31858'
  last_name: Tavana
- first_name: Arash
  full_name: Khalili Nasr, Arash
  last_name: Khalili Nasr
- first_name: Hassan
  full_name: Mina, Hassan
  last_name: Mina
- first_name: Jerzy
  full_name: Michnik, Jerzy
  last_name: Michnik
citation:
  ama: Tavana M, Khalili Nasr A, Mina H, Michnik J. A private sustainable partner
    selection model for green public-private partnerships and regional economic development.
    <i>Socio-Economic Planning Sciences</i>. 2022;83. doi:<a href="https://doi.org/10.1016/j.seps.2021.101189">10.1016/j.seps.2021.101189</a>
  apa: Tavana, M., Khalili Nasr, A., Mina, H., &#38; Michnik, J. (2022). A private
    sustainable partner selection model for green public-private partnerships and
    regional economic development. <i>Socio-Economic Planning Sciences</i>, <i>83</i>,
    Article 101189. <a href="https://doi.org/10.1016/j.seps.2021.101189">https://doi.org/10.1016/j.seps.2021.101189</a>
  bibtex: '@article{Tavana_Khalili Nasr_Mina_Michnik_2022, title={A private sustainable
    partner selection model for green public-private partnerships and regional economic
    development}, volume={83}, DOI={<a href="https://doi.org/10.1016/j.seps.2021.101189">10.1016/j.seps.2021.101189</a>},
    number={101189}, journal={Socio-Economic Planning Sciences}, publisher={Elsevier
    BV}, author={Tavana, Madjid and Khalili Nasr, Arash and Mina, Hassan and Michnik,
    Jerzy}, year={2022} }'
  chicago: Tavana, Madjid, Arash Khalili Nasr, Hassan Mina, and Jerzy Michnik. “A
    Private Sustainable Partner Selection Model for Green Public-Private Partnerships
    and Regional Economic Development.” <i>Socio-Economic Planning Sciences</i> 83
    (2022). <a href="https://doi.org/10.1016/j.seps.2021.101189">https://doi.org/10.1016/j.seps.2021.101189</a>.
  ieee: 'M. Tavana, A. Khalili Nasr, H. Mina, and J. Michnik, “A private sustainable
    partner selection model for green public-private partnerships and regional economic
    development,” <i>Socio-Economic Planning Sciences</i>, vol. 83, Art. no. 101189,
    2022, doi: <a href="https://doi.org/10.1016/j.seps.2021.101189">10.1016/j.seps.2021.101189</a>.'
  mla: Tavana, Madjid, et al. “A Private Sustainable Partner Selection Model for Green
    Public-Private Partnerships and Regional Economic Development.” <i>Socio-Economic
    Planning Sciences</i>, vol. 83, 101189, Elsevier BV, 2022, doi:<a href="https://doi.org/10.1016/j.seps.2021.101189">10.1016/j.seps.2021.101189</a>.
  short: M. Tavana, A. Khalili Nasr, H. Mina, J. Michnik, Socio-Economic Planning
    Sciences 83 (2022).
date_created: 2024-04-04T15:50:16Z
date_updated: 2024-04-15T13:16:33Z
department:
- _id: '277'
doi: 10.1016/j.seps.2021.101189
intvolume: '        83'
keyword:
- Management Science and Operations Research
- Statistics
- Probability and Uncertainty
- Strategy and Management
- Economics and Econometrics
- Geography
- Planning and Development
language:
- iso: eng
publication: Socio-Economic Planning Sciences
publication_identifier:
  issn:
  - 0038-0121
publication_status: published
publisher: Elsevier BV
status: public
title: A private sustainable partner selection model for green public-private partnerships
  and regional economic development
type: journal_article
user_id: '51811'
volume: 83
year: '2022'
...
---
_id: '34920'
abstract:
- lang: eng
  text: <jats:p>A very warm welcome to this Special Issue of the Statistics Education
    Research Journal (SERJ) on data science education. Our hope is to give an overview
    of selected theoretical thoughts and empirical studies on data science education
    from a statistics education research perspective. Data science education is rapidly
    developing but research into data science education is still in its infancy. The
    current issue presents a snapshot of this developing field.</jats:p>
article_number: '1'
author:
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
- first_name: Richard
  full_name: De Veaux, Richard
  last_name: De Veaux
- first_name: Joachim
  full_name: Engel, Joachim
  last_name: Engel
- first_name: Sibel
  full_name: Kazak, Sibel
  last_name: Kazak
- first_name: Daniel
  full_name: Frischemeier, Daniel
  last_name: Frischemeier
citation:
  ama: 'Biehler R, De Veaux R, Engel J, Kazak S, Frischemeier D. Editorial: Research
    on Data Science Education. <i>Statistics Education Research Journal</i>. 2022;21(2).
    doi:<a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>'
  apa: 'Biehler, R., De Veaux, R., Engel, J., Kazak, S., &#38; Frischemeier, D. (2022).
    Editorial: Research on Data Science Education. <i>Statistics Education Research
    Journal</i>, <i>21</i>(2), Article 1. <a href="https://doi.org/10.52041/serj.v21i2.606">https://doi.org/10.52041/serj.v21i2.606</a>'
  bibtex: '@article{Biehler_De Veaux_Engel_Kazak_Frischemeier_2022, title={Editorial:
    Research on Data Science Education}, volume={21}, DOI={<a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>},
    number={21}, journal={Statistics Education Research Journal}, publisher={International
    Association for Statistical Education}, author={Biehler, Rolf and De Veaux, Richard
    and Engel, Joachim and Kazak, Sibel and Frischemeier, Daniel}, year={2022} }'
  chicago: 'Biehler, Rolf, Richard De Veaux, Joachim Engel, Sibel Kazak, and Daniel
    Frischemeier. “Editorial: Research on Data Science Education.” <i>Statistics Education
    Research Journal</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.606">https://doi.org/10.52041/serj.v21i2.606</a>.'
  ieee: 'R. Biehler, R. De Veaux, J. Engel, S. Kazak, and D. Frischemeier, “Editorial:
    Research on Data Science Education,” <i>Statistics Education Research Journal</i>,
    vol. 21, no. 2, Art. no. 1, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>.'
  mla: 'Biehler, Rolf, et al. “Editorial: Research on Data Science Education.” <i>Statistics
    Education Research Journal</i>, vol. 21, no. 2, 1, International Association for
    Statistical Education, 2022, doi:<a href="https://doi.org/10.52041/serj.v21i2.606">10.52041/serj.v21i2.606</a>.'
  short: R. Biehler, R. De Veaux, J. Engel, S. Kazak, D. Frischemeier, Statistics
    Education Research Journal 21 (2022).
date_created: 2022-12-23T11:20:39Z
date_updated: 2024-04-18T09:45:53Z
department:
- _id: '363'
doi: 10.52041/serj.v21i2.606
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: Statistics Education Research Journal
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: 'Editorial: Research on Data Science Education'
type: journal_article
user_id: '37888'
volume: 21
year: '2022'
...
---
_id: '50024'
author:
- first_name: Yuanhua
  full_name: Feng, Yuanhua
  last_name: Feng
- first_name: Thomas
  full_name: Gries, Thomas
  last_name: Gries
- first_name: Sebastian
  full_name: Letmathe, Sebastian
  last_name: Letmathe
- first_name: Dominik
  full_name: Schulz, Dominik
  last_name: Schulz
citation:
  ama: Feng Y, Gries T, Letmathe S, Schulz D. The smoots Package in R for Semiparametric
    Modeling of Trend Stationary Time Series. <i>The R Journal</i>. 2022;14(1):182-195.
    doi:<a href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>
  apa: Feng, Y., Gries, T., Letmathe, S., &#38; Schulz, D. (2022). The smoots Package
    in R for Semiparametric Modeling of Trend Stationary Time Series. <i>The R Journal</i>,
    <i>14</i>(1), 182–195. <a href="https://doi.org/10.32614/rj-2022-017">https://doi.org/10.32614/rj-2022-017</a>
  bibtex: '@article{Feng_Gries_Letmathe_Schulz_2022, title={The smoots Package in
    R for Semiparametric Modeling of Trend Stationary Time Series}, volume={14}, DOI={<a
    href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>}, number={1},
    journal={The R Journal}, publisher={The R Foundation}, author={Feng, Yuanhua and
    Gries, Thomas and Letmathe, Sebastian and Schulz, Dominik}, year={2022}, pages={182–195}
    }'
  chicago: 'Feng, Yuanhua, Thomas Gries, Sebastian Letmathe, and Dominik Schulz. “The
    Smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series.”
    <i>The R Journal</i> 14, no. 1 (2022): 182–95. <a href="https://doi.org/10.32614/rj-2022-017">https://doi.org/10.32614/rj-2022-017</a>.'
  ieee: 'Y. Feng, T. Gries, S. Letmathe, and D. Schulz, “The smoots Package in R for
    Semiparametric Modeling of Trend Stationary Time Series,” <i>The R Journal</i>,
    vol. 14, no. 1, pp. 182–195, 2022, doi: <a href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>.'
  mla: Feng, Yuanhua, et al. “The Smoots Package in R for Semiparametric Modeling
    of Trend Stationary Time Series.” <i>The R Journal</i>, vol. 14, no. 1, The R
    Foundation, 2022, pp. 182–95, doi:<a href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>.
  short: Y. Feng, T. Gries, S. Letmathe, D. Schulz, The R Journal 14 (2022) 182–195.
date_created: 2023-12-21T12:09:31Z
date_updated: 2024-06-12T12:57:13Z
department:
- _id: '475'
- _id: '19'
- _id: '200'
doi: 10.32614/rj-2022-017
intvolume: '        14'
issue: '1'
keyword:
- Statistics
- Probability and Uncertainty
- Numerical Analysis
- Statistics and Probability
language:
- iso: eng
page: 182-195
publication: The R Journal
publication_identifier:
  issn:
  - 2073-4859
publication_status: published
publisher: The R Foundation
status: public
title: The smoots Package in R for Semiparametric Modeling of Trend Stationary Time
  Series
type: journal_article
user_id: '186'
volume: 14
year: '2022'
...
---
_id: '35672'
abstract:
- lang: eng
  text: <jats:p>This study examines modelling with machine learning. In the context
    of a yearlong data science course, the study explores how upper secondary students
    apply machine learning with Jupyter Notebooks and document the modelling process
    as a computational essay incorporating the different steps of the CRISP-DM cycle.
    The students’ work is based on a teaching module about decision trees in machine
    learning and a worked example of such a modelling process. The study outlines
    the students’ performance in carrying out the machine learning technically and
    reasoning about bias in the data, different data preparation steps, the application
    context, and the resulting decision model. Furthermore, the context of the study
    and the theoretical backgrounds are presented.</jats:p>
article_number: '7'
author:
- first_name: Franz Yannik
  full_name: Fleischer, Franz Yannik
  id: '42660'
  last_name: Fleischer
  orcid: https://orcid.org/0000-0003-0318-0329
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
- first_name: Carsten
  full_name: Schulte, Carsten
  id: '60311'
  last_name: Schulte
citation:
  ama: Fleischer FY, Biehler R, Schulte C. Teaching and Learning Data-Driven Machine
    Learning with Educationally Designed Jupyter Notebooks. <i>Statistics Education
    Research Journal</i>. 2022;21(2). doi:<a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>
  apa: Fleischer, F. Y., Biehler, R., &#38; Schulte, C. (2022). Teaching and Learning
    Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks. <i>Statistics
    Education Research Journal</i>, <i>21</i>(2), Article 7. <a href="https://doi.org/10.52041/serj.v21i2.61">https://doi.org/10.52041/serj.v21i2.61</a>
  bibtex: '@article{Fleischer_Biehler_Schulte_2022, title={Teaching and Learning Data-Driven
    Machine Learning with Educationally Designed Jupyter Notebooks}, volume={21},
    DOI={<a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>},
    number={27}, journal={Statistics Education Research Journal}, publisher={International
    Association for Statistical Education}, author={Fleischer, Franz Yannik and Biehler,
    Rolf and Schulte, Carsten}, year={2022} }'
  chicago: Fleischer, Franz Yannik, Rolf Biehler, and Carsten Schulte. “Teaching and
    Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks.”
    <i>Statistics Education Research Journal</i> 21, no. 2 (2022). <a href="https://doi.org/10.52041/serj.v21i2.61">https://doi.org/10.52041/serj.v21i2.61</a>.
  ieee: 'F. Y. Fleischer, R. Biehler, and C. Schulte, “Teaching and Learning Data-Driven
    Machine Learning with Educationally Designed Jupyter Notebooks,” <i>Statistics
    Education Research Journal</i>, vol. 21, no. 2, Art. no. 7, 2022, doi: <a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>.'
  mla: Fleischer, Franz Yannik, et al. “Teaching and Learning Data-Driven Machine
    Learning with Educationally Designed Jupyter Notebooks.” <i>Statistics Education
    Research Journal</i>, vol. 21, no. 2, 7, International Association for Statistical
    Education, 2022, doi:<a href="https://doi.org/10.52041/serj.v21i2.61">10.52041/serj.v21i2.61</a>.
  short: F.Y. Fleischer, R. Biehler, C. Schulte, Statistics Education Research Journal
    21 (2022).
date_created: 2023-01-10T08:48:23Z
date_updated: 2024-08-21T10:04:41Z
department:
- _id: '363'
- _id: '67'
doi: 10.52041/serj.v21i2.61
intvolume: '        21'
issue: '2'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: Statistics Education Research Journal
publication_identifier:
  issn:
  - 1570-1824
publication_status: published
publisher: International Association for Statistical Education
status: public
title: Teaching and Learning Data-Driven Machine Learning with Educationally Designed
  Jupyter Notebooks
type: journal_article
user_id: '37888'
volume: 21
year: '2022'
...
---
_id: '50025'
author:
- first_name: Yuanhua
  full_name: Feng, Yuanhua
  id: '20760'
  last_name: Feng
- first_name: Thomas
  full_name: Gries, Thomas
  id: '186'
  last_name: Gries
- first_name: Sebastian
  full_name: Letmathe, Sebastian
  last_name: Letmathe
- first_name: Dominik
  full_name: Schulz, Dominik
  last_name: Schulz
citation:
  ama: Feng Y, Gries T, Letmathe S, Schulz D. The smoots Package in R for Semiparametric
    Modeling of Trend Stationary Time Series. <i>The R Journal</i>. 2022;14(1):182-195.
    doi:<a href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>
  apa: Feng, Y., Gries, T., Letmathe, S., &#38; Schulz, D. (2022). The smoots Package
    in R for Semiparametric Modeling of Trend Stationary Time Series. <i>The R Journal</i>,
    <i>14</i>(1), 182–195. <a href="https://doi.org/10.32614/rj-2022-017">https://doi.org/10.32614/rj-2022-017</a>
  bibtex: '@article{Feng_Gries_Letmathe_Schulz_2022, title={The smoots Package in
    R for Semiparametric Modeling of Trend Stationary Time Series}, volume={14}, DOI={<a
    href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>}, number={1},
    journal={The R Journal}, publisher={The R Foundation}, author={Feng, Yuanhua and
    Gries, Thomas and Letmathe, Sebastian and Schulz, Dominik}, year={2022}, pages={182–195}
    }'
  chicago: 'Feng, Yuanhua, Thomas Gries, Sebastian Letmathe, and Dominik Schulz. “The
    Smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series.”
    <i>The R Journal</i> 14, no. 1 (2022): 182–95. <a href="https://doi.org/10.32614/rj-2022-017">https://doi.org/10.32614/rj-2022-017</a>.'
  ieee: 'Y. Feng, T. Gries, S. Letmathe, and D. Schulz, “The smoots Package in R for
    Semiparametric Modeling of Trend Stationary Time Series,” <i>The R Journal</i>,
    vol. 14, no. 1, pp. 182–195, 2022, doi: <a href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>.'
  mla: Feng, Yuanhua, et al. “The Smoots Package in R for Semiparametric Modeling
    of Trend Stationary Time Series.” <i>The R Journal</i>, vol. 14, no. 1, The R
    Foundation, 2022, pp. 182–95, doi:<a href="https://doi.org/10.32614/rj-2022-017">10.32614/rj-2022-017</a>.
  short: Y. Feng, T. Gries, S. Letmathe, D. Schulz, The R Journal 14 (2022) 182–195.
date_created: 2023-12-21T12:09:53Z
date_updated: 2025-11-10T09:32:36Z
doi: 10.32614/rj-2022-017
intvolume: '        14'
issue: '1'
keyword:
- Statistics
- Probability and Uncertainty
- Numerical Analysis
- Statistics and Probability
language:
- iso: eng
page: 182-195
publication: The R Journal
publication_identifier:
  issn:
  - 2073-4859
publication_status: published
publisher: The R Foundation
status: public
title: The smoots Package in R for Semiparametric Modeling of Trend Stationary Time
  Series
type: journal_article
user_id: '186'
volume: 14
year: '2022'
...
---
_id: '32243'
abstract:
- lang: eng
  text: "<jats:title>Abstract</jats:title>\r\n               <jats:p>The defining
    feature of active particles is that they constantly propel themselves by locally
    converting chemical energy into directed motion. This active self-propulsion prevents
    them from equilibrating with their thermal environment (e.g. an aqueous solution),
    thus keeping them permanently out of equilibrium. Nevertheless, the spatial dynamics
    of active particles might share certain equilibrium features, in particular in
    the steady state. We here focus on the time-reversal symmetry of individual spatial
    trajectories as a distinct equilibrium characteristic. We investigate to what
    extent the steady-state trajectories of a trapped active particle obey or break
    this time-reversal symmetry. Within the framework of active Ornstein–Uhlenbeck
    particles we find that the steady-state trajectories in a harmonic potential fulfill
    path-wise time-reversal symmetry exactly, while this symmetry is typically broken
    in anharmonic potentials.</jats:p>"
article_number: '033216'
author:
- first_name: Lennart
  full_name: Dabelow, Lennart
  last_name: Dabelow
- first_name: Stefano
  full_name: Bo, Stefano
  last_name: Bo
- first_name: Ralf
  full_name: Eichhorn, Ralf
  last_name: Eichhorn
citation:
  ama: 'Dabelow L, Bo S, Eichhorn R. How irreversible are steady-state trajectories
    of a trapped active particle? <i>Journal of Statistical Mechanics: Theory and
    Experiment</i>. 2021;2021(3). doi:<a href="https://doi.org/10.1088/1742-5468/abe6fd">10.1088/1742-5468/abe6fd</a>'
  apa: 'Dabelow, L., Bo, S., &#38; Eichhorn, R. (2021). How irreversible are steady-state
    trajectories of a trapped active particle? <i>Journal of Statistical Mechanics:
    Theory and Experiment</i>, <i>2021</i>(3), Article 033216. <a href="https://doi.org/10.1088/1742-5468/abe6fd">https://doi.org/10.1088/1742-5468/abe6fd</a>'
  bibtex: '@article{Dabelow_Bo_Eichhorn_2021, title={How irreversible are steady-state
    trajectories of a trapped active particle?}, volume={2021}, DOI={<a href="https://doi.org/10.1088/1742-5468/abe6fd">10.1088/1742-5468/abe6fd</a>},
    number={3033216}, journal={Journal of Statistical Mechanics: Theory and Experiment},
    publisher={IOP Publishing}, author={Dabelow, Lennart and Bo, Stefano and Eichhorn,
    Ralf}, year={2021} }'
  chicago: 'Dabelow, Lennart, Stefano Bo, and Ralf Eichhorn. “How Irreversible Are
    Steady-State Trajectories of a Trapped Active Particle?” <i>Journal of Statistical
    Mechanics: Theory and Experiment</i> 2021, no. 3 (2021). <a href="https://doi.org/10.1088/1742-5468/abe6fd">https://doi.org/10.1088/1742-5468/abe6fd</a>.'
  ieee: 'L. Dabelow, S. Bo, and R. Eichhorn, “How irreversible are steady-state trajectories
    of a trapped active particle?,” <i>Journal of Statistical Mechanics: Theory and
    Experiment</i>, vol. 2021, no. 3, Art. no. 033216, 2021, doi: <a href="https://doi.org/10.1088/1742-5468/abe6fd">10.1088/1742-5468/abe6fd</a>.'
  mla: 'Dabelow, Lennart, et al. “How Irreversible Are Steady-State Trajectories of
    a Trapped Active Particle?” <i>Journal of Statistical Mechanics: Theory and Experiment</i>,
    vol. 2021, no. 3, 033216, IOP Publishing, 2021, doi:<a href="https://doi.org/10.1088/1742-5468/abe6fd">10.1088/1742-5468/abe6fd</a>.'
  short: 'L. Dabelow, S. Bo, R. Eichhorn, Journal of Statistical Mechanics: Theory
    and Experiment 2021 (2021).'
date_created: 2022-06-28T07:27:41Z
date_updated: 2022-06-28T07:28:14Z
department:
- _id: '27'
doi: 10.1088/1742-5468/abe6fd
intvolume: '      2021'
issue: '3'
keyword:
- Statistics
- Probability and Uncertainty
- Statistics and Probability
- Statistical and Nonlinear Physics
language:
- iso: eng
project:
- _id: '52'
  name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 'Journal of Statistical Mechanics: Theory and Experiment'
publication_identifier:
  issn:
  - 1742-5468
publication_status: published
publisher: IOP Publishing
status: public
title: How irreversible are steady-state trajectories of a trapped active particle?
type: journal_article
user_id: '15278'
volume: 2021
year: '2021'
...
---
_id: '33649'
article_number: '2000269'
author:
- first_name: Jan
  full_name: Kessler, Jan
  id: '65425'
  last_name: Kessler
  orcid: 0000-0002-8705-6992
- first_name: Francesco
  full_name: Calcavecchia, Francesco
  last_name: Calcavecchia
- first_name: Thomas
  full_name: Kühne, Thomas
  id: '49079'
  last_name: Kühne
citation:
  ama: Kessler J, Calcavecchia F, Kühne T. Artificial Neural Networks as Trial Wave
    Functions for Quantum Monte Carlo. <i>Advanced Theory and Simulations</i>. 2021;4(4).
    doi:<a href="https://doi.org/10.1002/adts.202000269">10.1002/adts.202000269</a>
  apa: Kessler, J., Calcavecchia, F., &#38; Kühne, T. (2021). Artificial Neural Networks
    as Trial Wave Functions for Quantum Monte Carlo. <i>Advanced Theory and Simulations</i>,
    <i>4</i>(4), Article 2000269. <a href="https://doi.org/10.1002/adts.202000269">https://doi.org/10.1002/adts.202000269</a>
  bibtex: '@article{Kessler_Calcavecchia_Kühne_2021, title={Artificial Neural Networks
    as Trial Wave Functions for Quantum Monte Carlo}, volume={4}, DOI={<a href="https://doi.org/10.1002/adts.202000269">10.1002/adts.202000269</a>},
    number={42000269}, journal={Advanced Theory and Simulations}, publisher={Wiley},
    author={Kessler, Jan and Calcavecchia, Francesco and Kühne, Thomas}, year={2021}
    }'
  chicago: Kessler, Jan, Francesco Calcavecchia, and Thomas Kühne. “Artificial Neural
    Networks as Trial Wave Functions for Quantum Monte Carlo.” <i>Advanced Theory
    and Simulations</i> 4, no. 4 (2021). <a href="https://doi.org/10.1002/adts.202000269">https://doi.org/10.1002/adts.202000269</a>.
  ieee: 'J. Kessler, F. Calcavecchia, and T. Kühne, “Artificial Neural Networks as
    Trial Wave Functions for Quantum Monte Carlo,” <i>Advanced Theory and Simulations</i>,
    vol. 4, no. 4, Art. no. 2000269, 2021, doi: <a href="https://doi.org/10.1002/adts.202000269">10.1002/adts.202000269</a>.'
  mla: Kessler, Jan, et al. “Artificial Neural Networks as Trial Wave Functions for
    Quantum Monte Carlo.” <i>Advanced Theory and Simulations</i>, vol. 4, no. 4, 2000269,
    Wiley, 2021, doi:<a href="https://doi.org/10.1002/adts.202000269">10.1002/adts.202000269</a>.
  short: J. Kessler, F. Calcavecchia, T. Kühne, Advanced Theory and Simulations 4
    (2021).
date_created: 2022-10-10T08:15:23Z
date_updated: 2022-10-10T08:15:37Z
department:
- _id: '613'
doi: 10.1002/adts.202000269
intvolume: '         4'
issue: '4'
keyword:
- Multidisciplinary
- Modeling and Simulation
- Numerical Analysis
- Statistics and Probability
language:
- iso: eng
publication: Advanced Theory and Simulations
publication_identifier:
  issn:
  - 2513-0390
  - 2513-0390
publication_status: published
publisher: Wiley
status: public
title: Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo
type: journal_article
user_id: '71051'
volume: 4
year: '2021'
...
---
_id: '48109'
abstract:
- lang: eng
  text: <jats:title>Abstract</jats:title><jats:p>In this paper, we will describe an
    introduction to Data Science for secondary school students. We will report on
    the design and implementation of an introductory unit on “Data and data detectives
    with CODAP” in which secondary school students used the online tool CODAP to explore
    real and meaningful survey data on leisure time activities and media use (so‐called
    JIM‐PB data) in a statistical project setting as a starting point for data science.
    The JIM‐PB data set served as a valuable data set that offered meaningful and
    exciting opportunities for data exploration for secondary school students, and
    CODAP proved to be a valuable tool for the first explorations of this data.</jats:p>
author:
- first_name: Daniel
  full_name: Frischemeier, Daniel
  last_name: Frischemeier
- first_name: Rolf
  full_name: Biehler, Rolf
  last_name: Biehler
- first_name: Susanne
  full_name: Podworny, Susanne
  last_name: Podworny
- first_name: Lea
  full_name: Budde, Lea
  last_name: Budde
citation:
  ama: 'Frischemeier D, Biehler R, Podworny S, Budde L. A first introduction to data
    science education in secondary schools: Teaching and learning about data exploration
    with &#60;scp&#62;CODAP&#60;/scp&#62; using survey data. <i>Teaching Statistics</i>.
    2021;43(S1). doi:<a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>'
  apa: 'Frischemeier, D., Biehler, R., Podworny, S., &#38; Budde, L. (2021). A first
    introduction to data science education in secondary schools: Teaching and learning
    about data exploration with &#60;scp&#62;CODAP&#60;/scp&#62; using survey data.
    <i>Teaching Statistics</i>, <i>43</i>(S1). <a href="https://doi.org/10.1111/test.12283">https://doi.org/10.1111/test.12283</a>'
  bibtex: '@article{Frischemeier_Biehler_Podworny_Budde_2021, title={A first introduction
    to data science education in secondary schools: Teaching and learning about data
    exploration with &#60;scp&#62;CODAP&#60;/scp&#62; using survey data}, volume={43},
    DOI={<a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>}, number={S1},
    journal={Teaching Statistics}, publisher={Wiley}, author={Frischemeier, Daniel
    and Biehler, Rolf and Podworny, Susanne and Budde, Lea}, year={2021} }'
  chicago: 'Frischemeier, Daniel, Rolf Biehler, Susanne Podworny, and Lea Budde. “A
    First Introduction to Data Science Education in Secondary Schools: Teaching and
    Learning about Data Exploration with &#60;scp&#62;CODAP&#60;/Scp&#62; Using Survey
    Data.” <i>Teaching Statistics</i> 43, no. S1 (2021). <a href="https://doi.org/10.1111/test.12283">https://doi.org/10.1111/test.12283</a>.'
  ieee: 'D. Frischemeier, R. Biehler, S. Podworny, and L. Budde, “A first introduction
    to data science education in secondary schools: Teaching and learning about data
    exploration with &#60;scp&#62;CODAP&#60;/scp&#62; using survey data,” <i>Teaching
    Statistics</i>, vol. 43, no. S1, 2021, doi: <a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>.'
  mla: 'Frischemeier, Daniel, et al. “A First Introduction to Data Science Education
    in Secondary Schools: Teaching and Learning about Data Exploration with &#60;scp&#62;CODAP&#60;/Scp&#62;
    Using Survey Data.” <i>Teaching Statistics</i>, vol. 43, no. S1, Wiley, 2021,
    doi:<a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>.'
  short: D. Frischemeier, R. Biehler, S. Podworny, L. Budde, Teaching Statistics 43
    (2021).
date_created: 2023-10-17T06:06:02Z
date_updated: 2023-10-17T06:13:03Z
doi: 10.1111/test.12283
intvolume: '        43'
issue: S1
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
publication: Teaching Statistics
publication_identifier:
  issn:
  - 0141-982X
  - 1467-9639
publication_status: published
publisher: Wiley
status: public
title: 'A first introduction to data science education in secondary schools: Teaching
  and learning about data exploration with <scp>CODAP</scp> using survey data'
type: journal_article
user_id: '30619'
volume: 43
year: '2021'
...
---
_id: '35751'
author:
- first_name: Daniel
  full_name: Frischemeier, Daniel
  last_name: Frischemeier
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
- first_name: Susanne
  full_name: Podworny, Susanne
  id: '30619'
  last_name: Podworny
  orcid: 0000-0002-6313-5987
- first_name: Lea
  full_name: Budde, Lea
  id: '32443'
  last_name: Budde
citation:
  ama: 'Frischemeier D, Biehler R, Podworny S, Budde L. A first introduction to data
    science education in secondary schools: Teaching and learning about data exploration
    with&#60;scp&#62;CODAP&#60;/scp&#62;using survey data. <i>Teaching Statistics</i>.
    2021;43(S1):S182-S189. doi:<a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>'
  apa: 'Frischemeier, D., Biehler, R., Podworny, S., &#38; Budde, L. (2021). A first
    introduction to data science education in secondary schools: Teaching and learning
    about data exploration with&#60;scp&#62;CODAP&#60;/scp&#62;using survey data.
    <i>Teaching Statistics</i>, <i>43</i>(S1), S182–S189. <a href="https://doi.org/10.1111/test.12283">https://doi.org/10.1111/test.12283</a>'
  bibtex: '@article{Frischemeier_Biehler_Podworny_Budde_2021, title={A first introduction
    to data science education in secondary schools: Teaching and learning about data
    exploration with&#60;scp&#62;CODAP&#60;/scp&#62;using survey data}, volume={43},
    DOI={<a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>}, number={S1},
    journal={Teaching Statistics}, publisher={Wiley}, author={Frischemeier, Daniel
    and Biehler, Rolf and Podworny, Susanne and Budde, Lea}, year={2021}, pages={S182–S189}
    }'
  chicago: 'Frischemeier, Daniel, Rolf Biehler, Susanne Podworny, and Lea Budde. “A
    First Introduction to Data Science Education in Secondary Schools: Teaching and
    Learning about Data Exploration With&#60;scp&#62;CODAP&#60;/Scp&#62;using Survey
    Data.” <i>Teaching Statistics</i> 43, no. S1 (2021): S182–89. <a href="https://doi.org/10.1111/test.12283">https://doi.org/10.1111/test.12283</a>.'
  ieee: 'D. Frischemeier, R. Biehler, S. Podworny, and L. Budde, “A first introduction
    to data science education in secondary schools: Teaching and learning about data
    exploration with&#60;scp&#62;CODAP&#60;/scp&#62;using survey data,” <i>Teaching
    Statistics</i>, vol. 43, no. S1, pp. S182–S189, 2021, doi: <a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>.'
  mla: 'Frischemeier, Daniel, et al. “A First Introduction to Data Science Education
    in Secondary Schools: Teaching and Learning about Data Exploration With&#60;scp&#62;CODAP&#60;/Scp&#62;using
    Survey Data.” <i>Teaching Statistics</i>, vol. 43, no. S1, Wiley, 2021, pp. S182–89,
    doi:<a href="https://doi.org/10.1111/test.12283">10.1111/test.12283</a>.'
  short: D. Frischemeier, R. Biehler, S. Podworny, L. Budde, Teaching Statistics 43
    (2021) S182–S189.
date_created: 2023-01-10T10:16:44Z
date_updated: 2024-04-18T10:12:44Z
department:
- _id: '363'
doi: 10.1111/test.12283
intvolume: '        43'
issue: S1
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
page: S182-S189
publication: Teaching Statistics
publication_identifier:
  issn:
  - 0141-982X
  - 1467-9639
publication_status: published
publisher: Wiley
status: public
title: 'A first introduction to data science education in secondary schools: Teaching
  and learning about data exploration with<scp>CODAP</scp>using survey data'
type: journal_article
user_id: '37888'
volume: 43
year: '2021'
...
---
_id: '35737'
author:
- first_name: Rolf
  full_name: Biehler, Rolf
  id: '16274'
  last_name: Biehler
- first_name: Franz Yannik
  full_name: Fleischer, Franz Yannik
  id: '42660'
  last_name: Fleischer
  orcid: https://orcid.org/0000-0003-0318-0329
citation:
  ama: Biehler R, Fleischer FY. Introducing students to machine learning with decision
    trees using CODAP and Jupyter Notebooks. <i>Teaching Statistics</i>. 2021;43:S133-S142.
    doi:<a href="https://doi.org/10.1111/test.12279">10.1111/test.12279</a>
  apa: Biehler, R., &#38; Fleischer, F. Y. (2021). Introducing students to machine
    learning with decision trees using CODAP and Jupyter Notebooks. <i>Teaching Statistics</i>,
    <i>43</i>, S133–S142. <a href="https://doi.org/10.1111/test.12279">https://doi.org/10.1111/test.12279</a>
  bibtex: '@article{Biehler_Fleischer_2021, title={Introducing students to machine
    learning with decision trees using CODAP and Jupyter Notebooks}, volume={43},
    DOI={<a href="https://doi.org/10.1111/test.12279">10.1111/test.12279</a>}, journal={Teaching
    Statistics}, publisher={Wiley}, author={Biehler, Rolf and Fleischer, Franz Yannik},
    year={2021}, pages={S133–S142} }'
  chicago: 'Biehler, Rolf, and Franz Yannik Fleischer. “Introducing Students to Machine
    Learning with Decision Trees Using CODAP and Jupyter Notebooks.” <i>Teaching Statistics</i>
    43 (2021): S133–42. <a href="https://doi.org/10.1111/test.12279">https://doi.org/10.1111/test.12279</a>.'
  ieee: 'R. Biehler and F. Y. Fleischer, “Introducing students to machine learning
    with decision trees using CODAP and Jupyter Notebooks,” <i>Teaching Statistics</i>,
    vol. 43, pp. S133–S142, 2021, doi: <a href="https://doi.org/10.1111/test.12279">10.1111/test.12279</a>.'
  mla: Biehler, Rolf, and Franz Yannik Fleischer. “Introducing Students to Machine
    Learning with Decision Trees Using CODAP and Jupyter Notebooks.” <i>Teaching Statistics</i>,
    vol. 43, Wiley, 2021, pp. S133–42, doi:<a href="https://doi.org/10.1111/test.12279">10.1111/test.12279</a>.
  short: R. Biehler, F.Y. Fleischer, Teaching Statistics 43 (2021) S133–S142.
date_created: 2023-01-10T10:08:32Z
date_updated: 2024-08-21T10:05:05Z
department:
- _id: '363'
doi: 10.1111/test.12279
intvolume: '        43'
keyword:
- Education
- Statistics and Probability
language:
- iso: eng
page: S133-S142
publication: Teaching Statistics
publication_identifier:
  issn:
  - 0141-982X
  - 1467-9639
publication_status: published
publisher: Wiley
status: public
title: Introducing students to machine learning with decision trees using CODAP and
  Jupyter Notebooks
type: journal_article
user_id: '37888'
volume: 43
year: '2021'
...
---
_id: '45561'
abstract:
- lang: eng
  text: <jats:p>The purpose of this study is to experimentally test Trockel’s game,
    which is a modelling of the classical Chain Store Game (CSG), and determine whether
    one of the two theories of Equality and Deterrence may better account for the
    observed behavior. The CSG is an example of a simple game in extensive form where
    the actual behavior of well-informed players cannot be expected to agree with
    the clear results of game theoretical reasoning. To explain the disagreement between
    the theory and the expected behavior, Trockel’s game is proposed as an alternative
    modelling of the scenario. The existence of more than one equilibrium in Trockel’s
    game opens a door for reputation building. This study is the first attempt to
    experimentally test this alternative game with the same purpose. According to
    my data, there is some evidence in favor of both Equality and Deterrence Hypotheses.
    However, since the strategies compatible with the Equality Hypothesis are played
    more frequently, I observe some patterns which share the same intuition with the
    Deterrence Hypothesis.</jats:p>
article_number: '9'
author:
- first_name: Papatya
  full_name: Duman, Papatya
  id: '72752'
  last_name: Duman
citation:
  ama: Duman P. Does Informational Equivalence Preserve Strategic Behavior? Experimental
    Results on Trockel’s Model of Selten’s Chain Store Story. <i>Games</i>. 2020;11(1).
    doi:<a href="https://doi.org/10.3390/g11010009">10.3390/g11010009</a>
  apa: Duman, P. (2020). Does Informational Equivalence Preserve Strategic Behavior?
    Experimental Results on Trockel’s Model of Selten’s Chain Store Story. <i>Games</i>,
    <i>11</i>(1), Article 9. <a href="https://doi.org/10.3390/g11010009">https://doi.org/10.3390/g11010009</a>
  bibtex: '@article{Duman_2020, title={Does Informational Equivalence Preserve Strategic
    Behavior? Experimental Results on Trockel’s Model of Selten’s Chain Store Story},
    volume={11}, DOI={<a href="https://doi.org/10.3390/g11010009">10.3390/g11010009</a>},
    number={19}, journal={Games}, publisher={MDPI AG}, author={Duman, Papatya}, year={2020}
    }'
  chicago: Duman, Papatya. “Does Informational Equivalence Preserve Strategic Behavior?
    Experimental Results on Trockel’s Model of Selten’s Chain Store Story.” <i>Games</i>
    11, no. 1 (2020). <a href="https://doi.org/10.3390/g11010009">https://doi.org/10.3390/g11010009</a>.
  ieee: 'P. Duman, “Does Informational Equivalence Preserve Strategic Behavior? Experimental
    Results on Trockel’s Model of Selten’s Chain Store Story,” <i>Games</i>, vol.
    11, no. 1, Art. no. 9, 2020, doi: <a href="https://doi.org/10.3390/g11010009">10.3390/g11010009</a>.'
  mla: Duman, Papatya. “Does Informational Equivalence Preserve Strategic Behavior?
    Experimental Results on Trockel’s Model of Selten’s Chain Store Story.” <i>Games</i>,
    vol. 11, no. 1, 9, MDPI AG, 2020, doi:<a href="https://doi.org/10.3390/g11010009">10.3390/g11010009</a>.
  short: P. Duman, Games 11 (2020).
date_created: 2023-06-09T15:31:17Z
date_updated: 2023-06-09T15:33:34Z
doi: 10.3390/g11010009
intvolume: '        11'
issue: '1'
keyword:
- Applied Mathematics
- Statistics
- Probability and Uncertainty
- Statistics and Probability
language:
- iso: eng
publication: Games
publication_identifier:
  issn:
  - 2073-4336
publication_status: published
publisher: MDPI AG
status: public
title: Does Informational Equivalence Preserve Strategic Behavior? Experimental Results
  on Trockel’s Model of Selten’s Chain Store Story
type: journal_article
user_id: '72752'
volume: 11
year: '2020'
...
---
_id: '48856'
abstract:
- lang: eng
  text: There exist many optimal or heuristic priority rules for machine scheduling
    problems, which can easily be integrated into single-objective evolutionary algorithms
    via mutation operators. However, in the multi-objective case, simultaneously applying
    different priorities for different objectives may cause severe disruptions in
    the genome and may lead to inferior solutions. In this paper, we combine an existing
    mutation operator concept with new insights from detailed observation of the structure
    of solutions for multi-objective machine scheduling problems. This allows the
    comprehensive integration of priority rules to produce better Pareto-front approximations.
    We evaluate the extended operator concept compared to standard swap mutation and
    the stand-alone components of our hybrid scheme, which performs best in all evaluated
    cases.
author:
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Christian
  full_name: Grimme, Christian
  last_name: Grimme
citation:
  ama: 'Bossek J, Grimme C. An Extended Mutation-Based Priority-Rule Integration Concept
    for Multi-Objective Machine Scheduling. In: <i>2017 IEEE Symposium Series on Computational
    Intelligence (SSCI)</i>. ; 2017:1–8. doi:<a href="https://doi.org/10.1109/SSCI.2017.8285224">10.1109/SSCI.2017.8285224</a>'
  apa: Bossek, J., &#38; Grimme, C. (2017). An Extended Mutation-Based Priority-Rule
    Integration Concept for Multi-Objective Machine Scheduling. <i>2017 IEEE Symposium
    Series on Computational Intelligence (SSCI)</i>, 1–8. <a href="https://doi.org/10.1109/SSCI.2017.8285224">https://doi.org/10.1109/SSCI.2017.8285224</a>
  bibtex: '@inproceedings{Bossek_Grimme_2017, title={An Extended Mutation-Based Priority-Rule
    Integration Concept for Multi-Objective Machine Scheduling}, DOI={<a href="https://doi.org/10.1109/SSCI.2017.8285224">10.1109/SSCI.2017.8285224</a>},
    booktitle={2017 IEEE Symposium Series on Computational Intelligence (SSCI)}, author={Bossek,
    Jakob and Grimme, Christian}, year={2017}, pages={1–8} }'
  chicago: Bossek, Jakob, and Christian Grimme. “An Extended Mutation-Based Priority-Rule
    Integration Concept for Multi-Objective Machine Scheduling.” In <i>2017 IEEE Symposium
    Series on Computational Intelligence (SSCI)</i>, 1–8, 2017. <a href="https://doi.org/10.1109/SSCI.2017.8285224">https://doi.org/10.1109/SSCI.2017.8285224</a>.
  ieee: 'J. Bossek and C. Grimme, “An Extended Mutation-Based Priority-Rule Integration
    Concept for Multi-Objective Machine Scheduling,” in <i>2017 IEEE Symposium Series
    on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi: <a href="https://doi.org/10.1109/SSCI.2017.8285224">10.1109/SSCI.2017.8285224</a>.'
  mla: Bossek, Jakob, and Christian Grimme. “An Extended Mutation-Based Priority-Rule
    Integration Concept for Multi-Objective Machine Scheduling.” <i>2017 IEEE Symposium
    Series on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi:<a href="https://doi.org/10.1109/SSCI.2017.8285224">10.1109/SSCI.2017.8285224</a>.
  short: 'J. Bossek, C. Grimme, in: 2017 IEEE Symposium Series on Computational Intelligence
    (SSCI), 2017, pp. 1–8.'
date_created: 2023-11-14T15:58:54Z
date_updated: 2023-12-13T10:44:36Z
department:
- _id: '819'
doi: 10.1109/SSCI.2017.8285224
extern: '1'
keyword:
- Evolutionary computation
- Processor scheduling
- Schedules
- Scheduling
- Sociology
- Standards
- Statistics
language:
- iso: eng
page: 1–8
publication: 2017 IEEE Symposium Series on Computational Intelligence (SSCI)
publication_status: published
status: public
title: An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective
  Machine Scheduling
type: conference
user_id: '102979'
year: '2017'
...
---
_id: '11753'
abstract:
- lang: eng
  text: This contribution describes a step-wise source counting algorithm to determine
    the number of speakers in an offline scenario. Each speaker is identified by a
    variational expectation maximization (VEM) algorithm for complex Watson mixture
    models and therefore directly yields beamforming vectors for a subsequent speech
    separation process. An observation selection criterion is proposed which improves
    the robustness of the source counting in noise. The algorithm is compared to an
    alternative VEM approach with Gaussian mixture models based on directions of arrival
    and shown to deliver improved source counting accuracy. The article concludes
    by extending the offline algorithm towards a low-latency online estimation of
    the number of active sources from the streaming input data.
author:
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Aleksej
  full_name: Chinaev, Aleksej
  last_name: Chinaev
- first_name: Dang Hai
  full_name: Tran Vu, Dang Hai
  last_name: Tran Vu
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Drude L, Chinaev A, Tran Vu DH, Haeb-Umbach R. Towards Online Source Counting
    in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models.
    In: <i>14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)</i>.
    ; 2014:213-217.'
  apa: Drude, L., Chinaev, A., Tran Vu, D. H., &#38; Haeb-Umbach, R. (2014). Towards
    Online Source Counting in Speech Mixtures Applying a Variational EM for Complex
    Watson Mixture Models. In <i>14th International Workshop on Acoustic Signal Enhancement
    (IWAENC 2014)</i> (pp. 213–217).
  bibtex: '@inproceedings{Drude_Chinaev_Tran Vu_Haeb-Umbach_2014, title={Towards Online
    Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson
    Mixture Models}, booktitle={14th International Workshop on Acoustic Signal Enhancement
    (IWAENC 2014)}, author={Drude, Lukas and Chinaev, Aleksej and Tran Vu, Dang Hai
    and Haeb-Umbach, Reinhold}, year={2014}, pages={213–217} }'
  chicago: Drude, Lukas, Aleksej Chinaev, Dang Hai Tran Vu, and Reinhold Haeb-Umbach.
    “Towards Online Source Counting in Speech Mixtures Applying a Variational EM for
    Complex Watson Mixture Models.” In <i>14th International Workshop on Acoustic
    Signal Enhancement (IWAENC 2014)</i>, 213–17, 2014.
  ieee: L. Drude, A. Chinaev, D. H. Tran Vu, and R. Haeb-Umbach, “Towards Online Source
    Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture
    Models,” in <i>14th International Workshop on Acoustic Signal Enhancement (IWAENC
    2014)</i>, 2014, pp. 213–217.
  mla: Drude, Lukas, et al. “Towards Online Source Counting in Speech Mixtures Applying
    a Variational EM for Complex Watson Mixture Models.” <i>14th International Workshop
    on Acoustic Signal Enhancement (IWAENC 2014)</i>, 2014, pp. 213–17.
  short: 'L. Drude, A. Chinaev, D.H. Tran Vu, R. Haeb-Umbach, in: 14th International
    Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–217.'
date_created: 2019-07-12T05:27:35Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
keyword:
- Accuracy
- Acoustics
- Estimation
- Mathematical model
- Soruce separation
- Speech
- Vectors
- Bayes methods
- Blind source separation
- Directional statistics
- Number of speakers
- Speaker diarization
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2014/DrChTrHaeb14.pdf
oa: '1'
page: 213-217
publication: 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2014/DrChTrHaeb14_Poster.pdf
status: public
title: Towards Online Source Counting in Speech Mixtures Applying a Variational EM
  for Complex Watson Mixture Models
type: conference
user_id: '44006'
year: '2014'
...
---
_id: '11862'
abstract:
- lang: eng
  text: In this contribution we extend a previously proposed Bayesian approach for
    the enhancement of reverberant logarithmic mel power spectral coefficients for
    robust automatic speech recognition to the additional compensation of background
    noise. A recently proposed observation model is employed whose time-variant observation
    error statistics are obtained as a side product of the inference of the a posteriori
    probability density function of the clean speech feature vectors. Further a reduction
    of the computational effort and the memory requirements are achieved by using
    a recursive formulation of the observation model. The performance of the proposed
    algorithms is first experimentally studied on a connected digits recognition task
    with artificially created noisy reverberant data. It is shown that the use of
    the time-variant observation error model leads to a significant error rate reduction
    at low signal-to-noise ratios compared to a time-invariant model. Further experiments
    were conducted on a 5000 word task recorded in a reverberant and noisy environment.
    A significant word error rate reduction was obtained demonstrating the effectiveness
    of the approach on real-world data.
author:
- first_name: Volker
  full_name: Leutnant, Volker
  last_name: Leutnant
- first_name: Alexander
  full_name: Krueger, Alexander
  last_name: Krueger
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Leutnant V, Krueger A, Haeb-Umbach R. Bayesian Feature Enhancement for Reverberation
    and Noise Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i>. 2013;21(8):1640-1652. doi:<a href="https://doi.org/10.1109/TASL.2013.2258013">10.1109/TASL.2013.2258013</a>
  apa: Leutnant, V., Krueger, A., &#38; Haeb-Umbach, R. (2013). Bayesian Feature Enhancement
    for Reverberation and Noise Robust Speech Recognition. <i>IEEE Transactions on
    Audio, Speech, and Language Processing</i>, <i>21</i>(8), 1640–1652. <a href="https://doi.org/10.1109/TASL.2013.2258013">https://doi.org/10.1109/TASL.2013.2258013</a>
  bibtex: '@article{Leutnant_Krueger_Haeb-Umbach_2013, title={Bayesian Feature Enhancement
    for Reverberation and Noise Robust Speech Recognition}, volume={21}, DOI={<a href="https://doi.org/10.1109/TASL.2013.2258013">10.1109/TASL.2013.2258013</a>},
    number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
    author={Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2013},
    pages={1640–1652} }'
  chicago: 'Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “Bayesian
    Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” <i>IEEE
    Transactions on Audio, Speech, and Language Processing</i> 21, no. 8 (2013): 1640–52.
    <a href="https://doi.org/10.1109/TASL.2013.2258013">https://doi.org/10.1109/TASL.2013.2258013</a>.'
  ieee: V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Bayesian Feature Enhancement
    for Reverberation and Noise Robust Speech Recognition,” <i>IEEE Transactions on
    Audio, Speech, and Language Processing</i>, vol. 21, no. 8, pp. 1640–1652, 2013.
  mla: Leutnant, Volker, et al. “Bayesian Feature Enhancement for Reverberation and
    Noise Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language
    Processing</i>, vol. 21, no. 8, 2013, pp. 1640–52, doi:<a href="https://doi.org/10.1109/TASL.2013.2258013">10.1109/TASL.2013.2258013</a>.
  short: V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech,
    and Language Processing 21 (2013) 1640–1652.
date_created: 2019-07-12T05:29:42Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2013.2258013
intvolume: '        21'
issue: '8'
keyword:
- Bayes methods
- compensation
- error statistics
- reverberation
- speech recognition
- Bayesian feature enhancement
- background noise
- clean speech feature vectors
- compensation
- connected digits recognition task
- error statistics
- memory requirements
- noisy reverberant data
- posteriori probability density function
- recursive formulation
- reverberant logarithmic mel power spectral coefficients
- robust automatic speech recognition
- signal-to-noise ratios
- time-variant observation
- word error rate reduction
- Robust automatic speech recognition
- model-based Bayesian feature enhancement
- observation model for reverberant and noisy speech
- recursive observation model
language:
- iso: eng
page: 1640-1652
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition
type: journal_article
user_id: '44006'
volume: 21
year: '2013'
...
---
_id: '11913'
abstract:
- lang: eng
  text: In this paper we propose to employ directional statistics in a complex vector
    space to approach the problem of blind speech separation in the presence of spatially
    correlated noise. We interpret the values of the short time Fourier transform
    of the microphone signals to be draws from a mixture of complex Watson distributions,
    a probabilistic model which naturally accounts for spatial aliasing. The parameters
    of the density are related to the a priori source probabilities, the power of
    the sources and the transfer function ratios from sources to sensors. Estimation
    formulas are derived for these parameters by employing the Expectation Maximization
    (EM) algorithm. The E-step corresponds to the estimation of the source presence
    probabilities for each time-frequency bin, while the M-step leads to a maximum
    signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about
    the source activity. Experimental results are reported for an implementation in
    a generalized sidelobe canceller (GSC) like spatial beamforming configuration
    for 3 speech sources with significant coherent noise in reverberant environments,
    demonstrating the usefulness of the novel modeling framework.
author:
- first_name: Dang Hai
  full_name: Tran Vu, Dang Hai
  last_name: Tran Vu
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Tran Vu DH, Haeb-Umbach R. Blind speech separation employing directional statistics
    in an Expectation Maximization framework. In: <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>. ; 2010:241-244.
    doi:<a href="https://doi.org/10.1109/ICASSP.2010.5495994">10.1109/ICASSP.2010.5495994</a>'
  apa: Tran Vu, D. H., &#38; Haeb-Umbach, R. (2010). Blind speech separation employing
    directional statistics in an Expectation Maximization framework. In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i> (pp. 241–244).
    <a href="https://doi.org/10.1109/ICASSP.2010.5495994">https://doi.org/10.1109/ICASSP.2010.5495994</a>
  bibtex: '@inproceedings{Tran Vu_Haeb-Umbach_2010, title={Blind speech separation
    employing directional statistics in an Expectation Maximization framework}, DOI={<a
    href="https://doi.org/10.1109/ICASSP.2010.5495994">10.1109/ICASSP.2010.5495994</a>},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2010)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2010},
    pages={241–244} }'
  chicago: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
    Directional Statistics in an Expectation Maximization Framework.” In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 241–44,
    2010. <a href="https://doi.org/10.1109/ICASSP.2010.5495994">https://doi.org/10.1109/ICASSP.2010.5495994</a>.
  ieee: D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional
    statistics in an Expectation Maximization framework,” in <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 2010,
    pp. 241–244.
  mla: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
    Directional Statistics in an Expectation Maximization Framework.” <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 2010,
    pp. 241–44, doi:<a href="https://doi.org/10.1109/ICASSP.2010.5495994">10.1109/ICASSP.2010.5495994</a>.
  short: 'D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.'
date_created: 2019-07-12T05:30:40Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2010.5495994
keyword:
- array signal processing
- blind source separation
- blind speech separation
- complex vector space
- complex Watson distribution
- directional statistics
- expectation-maximisation algorithm
- expectation maximization algorithm
- Fourier transform
- Fourier transforms
- generalized sidelobe canceller
- interference suppression
- maximum signal-to-noise ratio beamformer
- microphone signal
- probabilistic model
- spatial aliasing
- spatial beamforming configuration
- speech enhancement
- statistical distributions
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf
oa: '1'
page: 241-244
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2010)
status: public
title: Blind speech separation employing directional statistics in an Expectation
  Maximization framework
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '34886'
abstract:
- lang: eng
  text: We give asymptotic upper and lower bounds for the number of squarefree d (0
    < d ≤ X) such that the equation x² − dy²= −1 is solvable. These estimates, as
    usual, can equivalently be interpreted in terms of real quadratic fields with
    a fundamental unit with norm −1 and give strong evidence in the direction of a
    conjecture due to P. Stevenhagen.
author:
- first_name: Étienne
  full_name: Fouvry, Étienne
  last_name: Fouvry
- first_name: Jürgen
  full_name: Klüners, Jürgen
  id: '21202'
  last_name: Klüners
citation:
  ama: Fouvry É, Klüners J. On the negative Pell equation. <i>Annals of Mathematics</i>.
    2010;172(3):2035-2104. doi:<a href="https://doi.org/10.4007/annals.2010.172.2035">10.4007/annals.2010.172.2035</a>
  apa: Fouvry, É., &#38; Klüners, J. (2010). On the negative Pell equation. <i>Annals
    of Mathematics</i>, <i>172</i>(3), 2035–2104. <a href="https://doi.org/10.4007/annals.2010.172.2035">https://doi.org/10.4007/annals.2010.172.2035</a>
  bibtex: '@article{Fouvry_Klüners_2010, title={On the negative Pell equation}, volume={172},
    DOI={<a href="https://doi.org/10.4007/annals.2010.172.2035">10.4007/annals.2010.172.2035</a>},
    number={3}, journal={Annals of Mathematics}, publisher={Annals of Mathematics},
    author={Fouvry, Étienne and Klüners, Jürgen}, year={2010}, pages={2035–2104} }'
  chicago: 'Fouvry, Étienne, and Jürgen Klüners. “On the Negative Pell Equation.”
    <i>Annals of Mathematics</i> 172, no. 3 (2010): 2035–2104. <a href="https://doi.org/10.4007/annals.2010.172.2035">https://doi.org/10.4007/annals.2010.172.2035</a>.'
  ieee: 'É. Fouvry and J. Klüners, “On the negative Pell equation,” <i>Annals of Mathematics</i>,
    vol. 172, no. 3, pp. 2035–2104, 2010, doi: <a href="https://doi.org/10.4007/annals.2010.172.2035">10.4007/annals.2010.172.2035</a>.'
  mla: Fouvry, Étienne, and Jürgen Klüners. “On the Negative Pell Equation.” <i>Annals
    of Mathematics</i>, vol. 172, no. 3, Annals of Mathematics, 2010, pp. 2035–104,
    doi:<a href="https://doi.org/10.4007/annals.2010.172.2035">10.4007/annals.2010.172.2035</a>.
  short: É. Fouvry, J. Klüners, Annals of Mathematics 172 (2010) 2035–2104.
date_created: 2022-12-23T09:09:02Z
date_updated: 2023-03-06T09:50:37Z
department:
- _id: '102'
doi: 10.4007/annals.2010.172.2035
intvolume: '       172'
issue: '3'
keyword:
- Statistics
- Probability and Uncertainty
- Mathematics (miscellaneous)
language:
- iso: eng
page: 2035-2104
publication: Annals of Mathematics
publication_identifier:
  issn:
  - 0003-486X
publication_status: published
publisher: Annals of Mathematics
status: public
title: On the negative Pell equation
type: journal_article
user_id: '93826'
volume: 172
year: '2010'
...