Abstract
Haze is one of the environmental issues that greatly effects human health, economy and ecology. Particulate matter with aerodynamic size below 10 micrometers PM10 is the major pollutant during haze period. The existing methods are currently focusing on statistical analysis to provide quantitative analysis of PM10. Persistent homology is a tool in topological data analysis (TDA) that provides qualitative information known as topological features of data by detecting birth and death points that persist across multiple scales. One question arises in relating persistent homology and haze. Can persistent homology detect haze? This study addresses this question by providing qualitative structures of PM10 and detecting topological changes during haze episodes from 2000 until 2015 in Klang air quality monitoring station. This paper shows that, there are changes in topological features during haze episodes.
| Original language | English |
|---|---|
| Title of host publication | 2018 UKM FST Postgraduate Colloquium |
| Subtitle of host publication | Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium |
| Editors | Noor Hayati Ahmad Rasol, Kamarulzaman Ibrahim, Siti Aishah Hasbullah, Mohammad Hafizuddin Hj. Jumali, Nazlina Ibrahim, Marlia Mohd Hanafiah, Mohd Talib Latif |
| Publisher | American Institute of Physics Inc. |
| ISBN (Electronic) | 9780735418431 |
| DOIs | |
| Publication status | Published - 27 Jun 2019 |
| Event | 2018 UKM FST Postgraduate Colloquium - Selangor, Malaysia Duration: 4 Apr 2018 → 6 Apr 2018 |
Publication series
| Name | AIP Conference Proceedings |
|---|---|
| Volume | 2111 |
| ISSN (Print) | 0094-243X |
| ISSN (Electronic) | 1551-7616 |
Conference
| Conference | 2018 UKM FST Postgraduate Colloquium |
|---|---|
| Country | Malaysia |
| City | Selangor |
| Period | 4/4/18 → 6/4/18 |
Fingerprint
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Ecology
- Plant Science
- Physics and Astronomy(all)
- Nature and Landscape Conservation
Cite this
Haze detection using persistent homology. / Zulkepli, N. F.S.; Md. Noorani, Mohd. Salmi; Abdul Razak, Fatimah; Ismail, Munira; Alias, M. A.
2018 UKM FST Postgraduate Colloquium: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium. ed. / Noor Hayati Ahmad Rasol; Kamarulzaman Ibrahim; Siti Aishah Hasbullah; Mohammad Hafizuddin Hj. Jumali; Nazlina Ibrahim; Marlia Mohd Hanafiah; Mohd Talib Latif. American Institute of Physics Inc., 2019. 020012 (AIP Conference Proceedings; Vol. 2111).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Haze detection using persistent homology
AU - Zulkepli, N. F.S.
AU - Md. Noorani, Mohd. Salmi
AU - Abdul Razak, Fatimah
AU - Ismail, Munira
AU - Alias, M. A.
PY - 2019/6/27
Y1 - 2019/6/27
N2 - Haze is one of the environmental issues that greatly effects human health, economy and ecology. Particulate matter with aerodynamic size below 10 micrometers PM10 is the major pollutant during haze period. The existing methods are currently focusing on statistical analysis to provide quantitative analysis of PM10. Persistent homology is a tool in topological data analysis (TDA) that provides qualitative information known as topological features of data by detecting birth and death points that persist across multiple scales. One question arises in relating persistent homology and haze. Can persistent homology detect haze? This study addresses this question by providing qualitative structures of PM10 and detecting topological changes during haze episodes from 2000 until 2015 in Klang air quality monitoring station. This paper shows that, there are changes in topological features during haze episodes.
AB - Haze is one of the environmental issues that greatly effects human health, economy and ecology. Particulate matter with aerodynamic size below 10 micrometers PM10 is the major pollutant during haze period. The existing methods are currently focusing on statistical analysis to provide quantitative analysis of PM10. Persistent homology is a tool in topological data analysis (TDA) that provides qualitative information known as topological features of data by detecting birth and death points that persist across multiple scales. One question arises in relating persistent homology and haze. Can persistent homology detect haze? This study addresses this question by providing qualitative structures of PM10 and detecting topological changes during haze episodes from 2000 until 2015 in Klang air quality monitoring station. This paper shows that, there are changes in topological features during haze episodes.
UR - http://www.scopus.com/inward/record.url?scp=85068473133&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068473133&partnerID=8YFLogxK
U2 - 10.1063/1.5111219
DO - 10.1063/1.5111219
M3 - Conference contribution
T3 - AIP Conference Proceedings
BT - 2018 UKM FST Postgraduate Colloquium
A2 - Rasol, Noor Hayati Ahmad
A2 - Ibrahim, Kamarulzaman
A2 - Hasbullah, Siti Aishah
A2 - Jumali, Mohammad Hafizuddin Hj.
A2 - Ibrahim, Nazlina
A2 - Hanafiah, Marlia Mohd
A2 - Latif, Mohd Talib
PB - American Institute of Physics Inc.
ER -