2 Search Results for "Zhao, Yue"

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.47
Investigating MAUP Effects on Census Data Using Approximately Equal-Population Aggregations (Short Paper)

Authors: Yue Lin and Ningchuan Xiao

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
The modifiable areal unit problem (MAUP) can significantly impact the use of census data as different choices in aggregating geographic zones can lead to varying outcomes. Previous research studied the effects using random aggregations, which, however, may lead to the use of impractical and unrealistic zones that deviate from recommended census geography criteria (e.g., equal population). To address this issue, this study proposes the use of approximately equal-population aggregations (AEPAs) for exploring MAUP effects on various statistical properties of census data, including Moran coefficients, correlation coefficients, and regression statistics. A multistart and recombination algorithm (MSRA) is used to generate multiple sets of high-quality AEPAs for testing MAUP effects. The results of our computational experiments highlight the need for more well-defined census geographies and realistic alternative zones to fully understand MAUP effects on census data.
Cite as

Yue Lin and Ningchuan Xiao. Investigating MAUP Effects on Census Data Using Approximately Equal-Population Aggregations (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 47:1-47:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{lin_et_al:LIPIcs.GIScience.2023.47,
  author =	{Lin, Yue and Xiao, Ningchuan},
  title =	{{Investigating MAUP Effects on Census Data Using Approximately Equal-Population Aggregations}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{47:1--47:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.47},
  URN =		{urn:nbn:de:0030-drops-189428},
  doi =		{10.4230/LIPIcs.GIScience.2023.47},
  annote =	{Keywords: Census, heuristics, modifiable areal unit problem, spatial aggregation, spatial autocorrelation}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2016.26
Towards Ontology-Based Program Analysis

Authors: Yue Zhao, Guoyang Chen, Chunhua Liao, and Xipeng Shen

Published in: LIPIcs, Volume 56, 30th European Conference on Object-Oriented Programming (ECOOP 2016)

Abstract
Program analysis is fundamental for program optimizations, debugging, and many other tasks. But developing program analyses has been a challenging and error-prone process for general users. Declarative program analysis has shown the promise to dramatically improve the productivity in the development of program analyses. Current declarative program analysis is however subject to some major limitations in supporting cooperations among analysis tools, guiding program optimizations, and often requires much effort for repeated program preprocessing. In this work, we advocate the integration of ontology into declarative program analysis. As a way to standardize the definitions of concepts in a domain and the representation of the knowledge in the domain, ontology offers a promising way to address the limitations of current declarative program analysis. We develop a prototype framework named PATO for conducting program analysis upon ontology-based program representation. Experiments on six program analyses confirm the potential of ontology for complementing existing declarative program analysis. It supports multiple analyses without separate program preprocessing, promotes cooperative Liveness analysis between two compilers, and effectively guides a data placement optimization for Graphic Processing Units (GPU).
Cite as

Yue Zhao, Guoyang Chen, Chunhua Liao, and Xipeng Shen. Towards Ontology-Based Program Analysis. In 30th European Conference on Object-Oriented Programming (ECOOP 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 56, pp. 26:1-26:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

Copy BibTex To Clipboard

@InProceedings{zhao_et_al:LIPIcs.ECOOP.2016.26,
  author =	{Zhao, Yue and Chen, Guoyang and Liao, Chunhua and Shen, Xipeng},
  title =	{{Towards Ontology-Based Program Analysis}},
  booktitle =	{30th European Conference on Object-Oriented Programming (ECOOP 2016)},
  pages =	{26:1--26:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-014-9},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{56},
  editor =	{Krishnamurthi, Shriram and Lerner, Benjamin S.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2016.26},
  URN =		{urn:nbn:de:0030-drops-61201},
  doi =		{10.4230/LIPIcs.ECOOP.2016.26},
  annote =	{Keywords: ontology, compiler, program analysis}
}
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