2 Search Results for "Chen, Jun"


Document
Invited Talk
How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk)

Authors: Sudeepa Roy, Amir Gilad, Yihao Hu, Hanze Meng, Zhengjie Miao, Kristin Stephens-Martinez, and Jun Yang

Published in: LIPIcs, Volume 290, 27th International Conference on Database Theory (ICDT 2024)


Abstract
Data analytics skills have become an indispensable part of any education that seeks to prepare its students for the modern workforce. Essential in this skill set is the ability to work with structured relational data. Relational queries are based on logic and may be declarative in nature, posing new challenges to novices and students. Manual teaching resources being limited and enrollment growing rapidly, automated tools that help students debug queries and explain errors are potential game-changers in database education. We present a suite of tools built on the foundations of database theory that has been used by over 1600 students in database classes at Duke University, showcasing a high-impact application of database theory in database education.

Cite as

Sudeepa Roy, Amir Gilad, Yihao Hu, Hanze Meng, Zhengjie Miao, Kristin Stephens-Martinez, and Jun Yang. How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk). In 27th International Conference on Database Theory (ICDT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 290, pp. 2:1-2:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{roy_et_al:LIPIcs.ICDT.2024.2,
  author =	{Roy, Sudeepa and Gilad, Amir and Hu, Yihao and Meng, Hanze and Miao, Zhengjie and Stephens-Martinez, Kristin and Yang, Jun},
  title =	{{How Database Theory Helps Teach Relational Queries in Database Education}},
  booktitle =	{27th International Conference on Database Theory (ICDT 2024)},
  pages =	{2:1--2:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-312-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{290},
  editor =	{Cormode, Graham and Shekelyan, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2024.2},
  URN =		{urn:nbn:de:0030-drops-197841},
  doi =		{10.4230/LIPIcs.ICDT.2024.2},
  annote =	{Keywords: Query Debugging, SQL, Relational Algebra, Relational Calculus, Database Education, Boolean Provenance}
}
Document
On the Utilisation of Fuzzy Rule-Based Systems for Taxi Time Estimations at Airports

Authors: Jun Chen, Stefan Ravizza, Jason A. D. Atkin, and Paul Stewart

Published in: OASIcs, Volume 20, 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2011)


Abstract
The primary objective of this paper is to introduce Fuzzy Rule-Based Systems (FRBSs) as a relatively new technology into airport transportation research, with a special emphasis on ground movement operations. Hence, a Mamdani FRBS with the capability to learn from data has been adopted for taxi time estimations at Zurich Airport (ZRH). Linear regression is currently the dominating technique for such an estimation task due to its established nature, proven mathematical characteristics and straightforward explanatory ability. In this study, we demonstrate that FRBSs, although having a more complex structure, can offer more accurate estimations due to their proven properties as nonlinear universal approximators. Furthermore, such improvements in accuracy do not come at the cost of the model's interpretability. FRBSs can offer more explanations of the underlying behavior in different regions. Preliminary results on data for ZRH suggest that FRBSs are a valuable alternative to already established linear regression methods. FRBSs have great potential to be further seamlessly integrated into the taxiway routing and scheduling process due to the fact that more information is now available in the explanatory variable space.

Cite as

Jun Chen, Stefan Ravizza, Jason A. D. Atkin, and Paul Stewart. On the Utilisation of Fuzzy Rule-Based Systems for Taxi Time Estimations at Airports. In 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 20, pp. 134-145, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


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@InProceedings{chen_et_al:OASIcs.ATMOS.2011.134,
  author =	{Chen, Jun and Ravizza, Stefan and Atkin, Jason A. D. and Stewart, Paul},
  title =	{{On the Utilisation of Fuzzy Rule-Based Systems for Taxi Time Estimations at Airports}},
  booktitle =	{11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{134--145},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-33-0},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{20},
  editor =	{Caprara, Alberto and Kontogiannis, Spyros},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2011.134},
  URN =		{urn:nbn:de:0030-drops-32736},
  doi =		{10.4230/OASIcs.ATMOS.2011.134},
  annote =	{Keywords: Fuzzy rule-based system, Taxi time estimation, Airport ground movement}
}
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