[{"_id":"45484","project":[{"grant_number":"289287267","_id":"104","name":"INGRID: INGRID: Informationssystem Graffiti in Deutschland"}],"department":[{"_id":"574"},{"_id":"115"}],"user_id":"6593","article_number":"318","type":"journal_article","status":"public","date_updated":"2023-06-06T09:17:10Z","volume":10,"author":[{"full_name":"Sherif, Mohamed Ahmed","last_name":"Sherif","first_name":"Mohamed Ahmed"},{"first_name":"Ana Alexandra Morim","full_name":"da Silva, Ana Alexandra Morim","last_name":"da Silva"},{"full_name":"Pestryakova, Svetlana","last_name":"Pestryakova","first_name":"Svetlana"},{"full_name":"Ahmed, Abdullah Fathi","last_name":"Ahmed","first_name":"Abdullah Fathi"},{"first_name":"Sven","full_name":"Niemann, Sven","last_name":"Niemann"},{"first_name":"Axel-Cyrille Ngonga","last_name":"Ngomo","full_name":"Ngomo, Axel-Cyrille Ngonga"}],"doi":"10.1038/s41597-023-02199-8","publication_identifier":{"issn":["2052-4463"]},"publication_status":"published","intvolume":"        10","citation":{"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).","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} }","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>","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>","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>."},"keyword":["Library and Information Sciences","Statistics","Probability and Uncertainty","Computer Science Applications","Education","Information Systems","Statistics and Probability"],"language":[{"iso":"eng"}],"publication":"Scientific Data","abstract":[{"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>","lang":"eng"}],"publisher":"Springer Science and Business Media LLC","date_created":"2023-06-06T09:12:39Z","title":"IngridKG: A FAIR Knowledge Graph of Graffiti","issue":"1","year":"2023"},{"doi":"10.52041/serj.v21i2.46","title":"A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING","author":[{"first_name":"SUSANNE","last_name":"PODWORNY","full_name":"PODWORNY, SUSANNE"},{"last_name":"Hüsing","full_name":"Hüsing, Sven","id":"58465","first_name":"Sven"},{"full_name":"SCHULTE, CARSTEN","last_name":"SCHULTE","first_name":"CARSTEN"}],"date_created":"2022-07-08T12:06:48Z","volume":21,"date_updated":"2022-07-08T12:07:46Z","publisher":"International Association for Statistical Education","citation":{"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).","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} }","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>","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>.","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>"},"intvolume":"        21","year":"2022","issue":"2","publication_status":"published","publication_identifier":{"issn":["1570-1824"]},"language":[{"iso":"eng"}],"article_number":"6","keyword":["Education","Statistics and Probability"],"user_id":"58465","department":[{"_id":"67"}],"_id":"32335","status":"public","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."}],"type":"journal_article","publication":"STATISTICS EDUCATION RESEARCH JOURNAL"},{"publication":"Zeitschrift für Evaluation","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>"}],"keyword":["Strategy and Management","Applied Psychology","Social Sciences (miscellaneous)","Education","Communication","Statistics and Probability"],"language":[{"iso":"ger"}],"quality_controlled":"1","issue":"02","year":"2022","publisher":"Waxmann","date_created":"2022-12-05T13:25:58Z","title":"Rekonstruktive Evaluationsforschung im Kontext praxeologischer Kompetenzdiskurse. Kritische Reflexionen und konzeptionelle Überlegungen zur Dokumentarischen Evaluationsforschung","type":"journal_article","status":"public","_id":"34200","user_id":"69383","department":[{"_id":"4"}],"publication_status":"published","publication_identifier":{"issn":["1619-5515","2699-5506"]},"citation":{"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} }","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.","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>","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>","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>."},"page":"193-215","intvolume":"      2022","date_updated":"2022-12-05T13:26:35Z","author":[{"first_name":"Thiemo","last_name":"Bloh","full_name":"Bloh, Thiemo"}],"volume":2022,"doi":"10.31244/zfe.2022.02.02"},{"user_id":"30619","_id":"48108","keyword":["Education","Statistics and Probability"],"article_number":"6","publication":"STATISTICS EDUCATION RESEARCH JOURNAL","type":"journal_article","status":"public","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>"}],"volume":21,"author":[{"first_name":"SUSANNE","last_name":"PODWORNY","full_name":"PODWORNY, SUSANNE"},{"first_name":"SVEN","last_name":"HÜSING","full_name":"HÜSING, SVEN"},{"first_name":"CARSTEN","full_name":"SCHULTE, CARSTEN","last_name":"SCHULTE"}],"date_created":"2023-10-17T05:59:38Z","publisher":"International Association for Statistical Education","date_updated":"2023-10-17T06:01:58Z","doi":"10.52041/serj.v21i2.46","title":"A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING","issue":"2","publication_identifier":{"issn":["1570-1824"]},"publication_status":"published","intvolume":"        21","citation":{"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>.","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>","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).","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} }","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>"},"year":"2022"},{"year":"2022","citation":{"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>.","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>.","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>","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} }","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).","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>"},"intvolume":"        83","publication_status":"published","publication_identifier":{"issn":["0038-0121"]},"title":"A private sustainable partner selection model for green public-private partnerships and regional economic development","doi":"10.1016/j.seps.2021.101189","publisher":"Elsevier BV","date_updated":"2024-04-15T13:16:33Z","author":[{"last_name":"Tavana","id":"31858","full_name":"Tavana, Madjid","first_name":"Madjid"},{"first_name":"Arash","full_name":"Khalili Nasr, Arash","last_name":"Khalili Nasr"},{"full_name":"Mina, Hassan","last_name":"Mina","first_name":"Hassan"},{"first_name":"Jerzy","last_name":"Michnik","full_name":"Michnik, Jerzy"}],"date_created":"2024-04-04T15:50:16Z","volume":83,"status":"public","type":"journal_article","publication":"Socio-Economic Planning Sciences","article_number":"101189","keyword":["Management Science and Operations Research","Statistics","Probability and Uncertainty","Strategy and Management","Economics and Econometrics","Geography","Planning and Development"],"language":[{"iso":"eng"}],"_id":"53238","user_id":"51811","department":[{"_id":"277"}]},{"department":[{"_id":"363"}],"user_id":"37888","_id":"34920","language":[{"iso":"eng"}],"keyword":["Education","Statistics and Probability"],"article_number":"1","publication":"Statistics Education Research Journal","type":"journal_article","status":"public","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>"}],"volume":21,"author":[{"first_name":"Rolf","id":"16274","full_name":"Biehler, Rolf","last_name":"Biehler"},{"full_name":"De Veaux, Richard","last_name":"De Veaux","first_name":"Richard"},{"first_name":"Joachim","full_name":"Engel, Joachim","last_name":"Engel"},{"first_name":"Sibel","full_name":"Kazak, Sibel","last_name":"Kazak"},{"last_name":"Frischemeier","full_name":"Frischemeier, Daniel","first_name":"Daniel"}],"date_created":"2022-12-23T11:20:39Z","publisher":"International Association for Statistical Education","date_updated":"2024-04-18T09:45:53Z","doi":"10.52041/serj.v21i2.606","title":"Editorial: Research on Data Science Education","issue":"2","publication_identifier":{"issn":["1570-1824"]},"publication_status":"published","intvolume":"        21","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>","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>.","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>.","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>.","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} }","short":"R. Biehler, R. De Veaux, J. Engel, S. Kazak, D. Frischemeier, Statistics Education Research Journal 21 (2022).","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>"},"year":"2022"},{"volume":14,"date_created":"2023-12-21T12:09:31Z","author":[{"last_name":"Feng","full_name":"Feng, Yuanhua","first_name":"Yuanhua"},{"full_name":"Gries, Thomas","last_name":"Gries","first_name":"Thomas"},{"first_name":"Sebastian","last_name":"Letmathe","full_name":"Letmathe, Sebastian"},{"full_name":"Schulz, Dominik","last_name":"Schulz","first_name":"Dominik"}],"publisher":"The R Foundation","date_updated":"2024-06-12T12:57:13Z","doi":"10.32614/rj-2022-017","title":"The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series","issue":"1","publication_identifier":{"issn":["2073-4859"]},"publication_status":"published","intvolume":"        14","page":"182-195","citation":{"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} }","short":"Y. Feng, T. Gries, S. Letmathe, D. Schulz, The R Journal 14 (2022) 182–195.","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>.","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>","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>.","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>"},"year":"2022","department":[{"_id":"475"},{"_id":"19"},{"_id":"200"}],"user_id":"186","_id":"50024","language":[{"iso":"eng"}],"keyword":["Statistics","Probability and Uncertainty","Numerical Analysis","Statistics and Probability"],"publication":"The R Journal","type":"journal_article","status":"public"},{"publication":"Statistics Education Research Journal","type":"journal_article","abstract":[{"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>","lang":"eng"}],"status":"public","_id":"35672","department":[{"_id":"363"},{"_id":"67"}],"user_id":"37888","keyword":["Education","Statistics and Probability"],"article_number":"7","language":[{"iso":"eng"}],"publication_identifier":{"issn":["1570-1824"]},"publication_status":"published","issue":"2","year":"2022","intvolume":"        21","citation":{"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} }","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).","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>","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>","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>."},"date_updated":"2024-08-21T10:04:41Z","publisher":"International Association for Statistical Education","volume":21,"author":[{"last_name":"Fleischer","orcid":"https://orcid.org/0000-0003-0318-0329","full_name":"Fleischer, Franz Yannik","id":"42660","first_name":"Franz Yannik"},{"first_name":"Rolf","last_name":"Biehler","full_name":"Biehler, Rolf","id":"16274"},{"first_name":"Carsten","last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten"}],"date_created":"2023-01-10T08:48:23Z","title":"Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks","doi":"10.52041/serj.v21i2.61"},{"status":"public","type":"journal_article","publication":"The R Journal","language":[{"iso":"eng"}],"keyword":["Statistics","Probability and Uncertainty","Numerical Analysis","Statistics and Probability"],"user_id":"186","_id":"50025","citation":{"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} }","short":"Y. Feng, T. Gries, S. Letmathe, D. Schulz, The R Journal 14 (2022) 182–195.","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>.","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>","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>.","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>."},"page":"182-195","intvolume":"        14","year":"2022","issue":"1","publication_status":"published","publication_identifier":{"issn":["2073-4859"]},"doi":"10.32614/rj-2022-017","title":"The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series","author":[{"last_name":"Feng","id":"20760","full_name":"Feng, Yuanhua","first_name":"Yuanhua"},{"id":"186","full_name":"Gries, Thomas","last_name":"Gries","first_name":"Thomas"},{"first_name":"Sebastian","full_name":"Letmathe, Sebastian","last_name":"Letmathe"},{"first_name":"Dominik","last_name":"Schulz","full_name":"Schulz, Dominik"}],"date_created":"2023-12-21T12:09:53Z","volume":14,"date_updated":"2025-11-10T09:32:36Z","publisher":"The R Foundation"},{"intvolume":"      2021","citation":{"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>.","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>","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).","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} }","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>"},"publication_identifier":{"issn":["1742-5468"]},"publication_status":"published","doi":"10.1088/1742-5468/abe6fd","volume":2021,"author":[{"last_name":"Dabelow","full_name":"Dabelow, Lennart","first_name":"Lennart"},{"first_name":"Stefano","last_name":"Bo","full_name":"Bo, Stefano"},{"first_name":"Ralf","full_name":"Eichhorn, Ralf","last_name":"Eichhorn"}],"date_updated":"2022-06-28T07:28:14Z","status":"public","type":"journal_article","article_number":"033216","department":[{"_id":"27"}],"user_id":"15278","_id":"32243","project":[{"name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"year":"2021","issue":"3","title":"How irreversible are steady-state trajectories of a trapped active particle?","date_created":"2022-06-28T07:27:41Z","publisher":"IOP Publishing","abstract":[{"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>","lang":"eng"}],"publication":"Journal of Statistical Mechanics: Theory and Experiment","language":[{"iso":"eng"}],"keyword":["Statistics","Probability and Uncertainty","Statistics and Probability","Statistical and Nonlinear Physics"]},{"date_updated":"2022-10-10T08:15:37Z","volume":4,"author":[{"first_name":"Jan","id":"65425","full_name":"Kessler, Jan","last_name":"Kessler","orcid":"0000-0002-8705-6992"},{"first_name":"Francesco","last_name":"Calcavecchia","full_name":"Calcavecchia, Francesco"},{"first_name":"Thomas","last_name":"Kühne","id":"49079","full_name":"Kühne, Thomas"}],"doi":"10.1002/adts.202000269","publication_identifier":{"issn":["2513-0390","2513-0390"]},"publication_status":"published","intvolume":"         4","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>","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>.","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>.","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>","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>.","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} }","short":"J. Kessler, F. Calcavecchia, T. Kühne, Advanced Theory and Simulations 4 (2021)."},"_id":"33649","department":[{"_id":"613"}],"user_id":"71051","article_number":"2000269","type":"journal_article","status":"public","publisher":"Wiley","date_created":"2022-10-10T08:15:23Z","title":"Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo","issue":"4","year":"2021","keyword":["Multidisciplinary","Modeling and Simulation","Numerical Analysis","Statistics and Probability"],"language":[{"iso":"eng"}],"publication":"Advanced Theory and Simulations"},{"citation":{"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>.","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} }","short":"D. Frischemeier, R. Biehler, S. Podworny, L. Budde, Teaching Statistics 43 (2021).","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>."},"intvolume":"        43","year":"2021","issue":"S1","publication_status":"published","publication_identifier":{"issn":["0141-982X","1467-9639"]},"doi":"10.1111/test.12283","title":"A first introduction to data science education in secondary schools: Teaching and learning about data exploration with <scp>CODAP</scp> using survey data","author":[{"first_name":"Daniel","last_name":"Frischemeier","full_name":"Frischemeier, Daniel"},{"last_name":"Biehler","full_name":"Biehler, Rolf","first_name":"Rolf"},{"last_name":"Podworny","full_name":"Podworny, Susanne","first_name":"Susanne"},{"full_name":"Budde, Lea","last_name":"Budde","first_name":"Lea"}],"date_created":"2023-10-17T06:06:02Z","volume":43,"date_updated":"2023-10-17T06:13:03Z","publisher":"Wiley","status":"public","abstract":[{"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>","lang":"eng"}],"type":"journal_article","publication":"Teaching Statistics","language":[{"iso":"eng"}],"keyword":["Education","Statistics and Probability"],"user_id":"30619","_id":"48109"},{"publisher":"Wiley","date_created":"2023-01-10T10:16:44Z","title":"A first introduction to data science education in secondary schools: Teaching and learning about data exploration with<scp>CODAP</scp>using survey data","issue":"S1","year":"2021","keyword":["Education","Statistics and Probability"],"language":[{"iso":"eng"}],"publication":"Teaching Statistics","date_updated":"2024-04-18T10:12:44Z","volume":43,"author":[{"first_name":"Daniel","last_name":"Frischemeier","full_name":"Frischemeier, Daniel"},{"last_name":"Biehler","id":"16274","full_name":"Biehler, Rolf","first_name":"Rolf"},{"orcid":"0000-0002-6313-5987","last_name":"Podworny","id":"30619","full_name":"Podworny, Susanne","first_name":"Susanne"},{"first_name":"Lea","id":"32443","full_name":"Budde, Lea","last_name":"Budde"}],"doi":"10.1111/test.12283","publication_identifier":{"issn":["0141-982X","1467-9639"]},"publication_status":"published","intvolume":"        43","page":"S182-S189","citation":{"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>.","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>.","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>","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} }","short":"D. Frischemeier, R. Biehler, S. Podworny, L. Budde, Teaching Statistics 43 (2021) S182–S189.","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>.","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>"},"_id":"35751","department":[{"_id":"363"}],"user_id":"37888","type":"journal_article","status":"public"},{"volume":43,"date_created":"2023-01-10T10:08:32Z","author":[{"last_name":"Biehler","full_name":"Biehler, Rolf","id":"16274","first_name":"Rolf"},{"full_name":"Fleischer, Franz Yannik","id":"42660","orcid":"https://orcid.org/0000-0003-0318-0329","last_name":"Fleischer","first_name":"Franz Yannik"}],"date_updated":"2024-08-21T10:05:05Z","publisher":"Wiley","doi":"10.1111/test.12279","title":"Introducing students to machine learning with decision trees using CODAP and Jupyter Notebooks","publication_identifier":{"issn":["0141-982X","1467-9639"]},"publication_status":"published","intvolume":"        43","page":"S133-S142","citation":{"short":"R. Biehler, F.Y. Fleischer, Teaching Statistics 43 (2021) S133–S142.","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>.","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} }","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>","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>.","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>.","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>"},"year":"2021","department":[{"_id":"363"}],"user_id":"37888","_id":"35737","language":[{"iso":"eng"}],"keyword":["Education","Statistics and Probability"],"publication":"Teaching Statistics","type":"journal_article","status":"public"},{"user_id":"72752","_id":"45561","language":[{"iso":"eng"}],"keyword":["Applied Mathematics","Statistics","Probability and Uncertainty","Statistics and Probability"],"article_number":"9","publication":"Games","type":"journal_article","status":"public","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>"}],"volume":11,"date_created":"2023-06-09T15:31:17Z","author":[{"first_name":"Papatya","last_name":"Duman","full_name":"Duman, Papatya","id":"72752"}],"publisher":"MDPI AG","date_updated":"2023-06-09T15:33:34Z","doi":"10.3390/g11010009","title":"Does Informational Equivalence Preserve Strategic Behavior? Experimental Results on Trockel’s Model of Selten’s Chain Store Story","issue":"1","publication_identifier":{"issn":["2073-4336"]},"publication_status":"published","intvolume":"        11","citation":{"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>.","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>","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).","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} }"},"year":"2020"},{"date_updated":"2023-12-13T10:44:36Z","date_created":"2023-11-14T15:58:54Z","author":[{"first_name":"Jakob","id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668"},{"full_name":"Grimme, Christian","last_name":"Grimme","first_name":"Christian"}],"title":"An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling","doi":"10.1109/SSCI.2017.8285224","publication_status":"published","year":"2017","citation":{"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>.","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} }","short":"J. Bossek, C. Grimme, in: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1–8.","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>","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>","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>.","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>."},"page":"1–8","_id":"48856","user_id":"102979","department":[{"_id":"819"}],"keyword":["Evolutionary computation","Processor scheduling","Schedules","Scheduling","Sociology","Standards","Statistics"],"extern":"1","language":[{"iso":"eng"}],"type":"conference","publication":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","abstract":[{"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.","lang":"eng"}],"status":"public"},{"year":"2014","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.","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.","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.","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.","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.","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} }","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)."},"page":"213-217","related_material":{"link":[{"relation":"supplementary_material","description":"Poster","url":"https://groups.uni-paderborn.de/nt/pubs/2014/DrChTrHaeb14_Poster.pdf"}]},"title":"Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2014/DrChTrHaeb14.pdf","open_access":"1"}],"oa":"1","date_updated":"2022-01-06T06:51:08Z","author":[{"full_name":"Drude, Lukas","id":"11213","last_name":"Drude","first_name":"Lukas"},{"first_name":"Aleksej","last_name":"Chinaev","full_name":"Chinaev, Aleksej"},{"first_name":"Dang Hai","full_name":"Tran Vu, Dang Hai","last_name":"Tran Vu"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"date_created":"2019-07-12T05:27:35Z","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."}],"status":"public","type":"conference","publication":"14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)","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"}],"_id":"11753","user_id":"44006","department":[{"_id":"54"}]},{"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"}],"_id":"11862","department":[{"_id":"54"}],"user_id":"44006","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."}],"status":"public","publication":"IEEE Transactions on Audio, Speech, and Language Processing","type":"journal_article","title":"Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition","doi":"10.1109/TASL.2013.2258013","date_updated":"2022-01-06T06:51:11Z","volume":21,"date_created":"2019-07-12T05:29:42Z","author":[{"first_name":"Volker","full_name":"Leutnant, Volker","last_name":"Leutnant"},{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach"}],"year":"2013","page":"1640-1652","intvolume":"        21","citation":{"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>.","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} }","short":"V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 21 (2013) 1640–1652.","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>","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.","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>.","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>"},"issue":"8"},{"_id":"11913","department":[{"_id":"54"}],"user_id":"44006","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"}],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)","type":"conference","abstract":[{"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.","lang":"eng"}],"status":"public","date_updated":"2022-01-06T06:51:12Z","oa":"1","date_created":"2019-07-12T05:30:40Z","author":[{"last_name":"Tran Vu","full_name":"Tran Vu, Dang Hai","first_name":"Dang Hai"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"title":"Blind speech separation employing directional statistics in an Expectation Maximization framework","doi":"10.1109/ICASSP.2010.5495994","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf","open_access":"1"}],"year":"2010","page":"241-244","citation":{"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>","short":"D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.","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} }","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>.","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>","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."}},{"status":"public","type":"journal_article","_id":"34886","department":[{"_id":"102"}],"user_id":"93826","intvolume":"       172","page":"2035-2104","citation":{"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} }","short":"É. Fouvry, J. Klüners, Annals of Mathematics 172 (2010) 2035–2104.","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>.","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>.","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>.","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>"},"publication_identifier":{"issn":["0003-486X"]},"publication_status":"published","doi":"10.4007/annals.2010.172.2035","date_updated":"2023-03-06T09:50:37Z","volume":172,"author":[{"last_name":"Fouvry","full_name":"Fouvry, Étienne","first_name":"Étienne"},{"id":"21202","full_name":"Klüners, Jürgen","last_name":"Klüners","first_name":"Jürgen"}],"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."}],"publication":"Annals of Mathematics","keyword":["Statistics","Probability and Uncertainty","Mathematics (miscellaneous)"],"language":[{"iso":"eng"}],"year":"2010","issue":"3","title":"On the negative Pell equation","publisher":"Annals of Mathematics","date_created":"2022-12-23T09:09:02Z"}]