Relief of spatiotemporal accessibility overloading with optimal resource placement

Chien Wei Chang, Hao Yi Chih, Dean Chou, Yu-Chen Shu, Kun-Ta Chuang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the effects of global warming, some epidemic diseases via mosquito (e.g. mosquito-borne diseases) become more serious, such as dengue fever and zika virus. It is reported that the epidemic disease may cause many challenges to the hospital management due to the unexpected burst with uncertain reasons. Furthermore, the imperfect cares during the propagation of epidemic diseases, such as dengue fever (so far the appropriate treatment is not well established), may lead to the increasing mortality rate which should be avoided. In this paper, a novel paradigm for optimizing the placement of medical resource is proposed in pursuit of reducing the overloading cases in hospitals during the epidemic outbreak in the urban area. In this paper we explore the first paper to explore two important issues, including the strategy to evaluate the service quality and the solution to dynamically dispatch the medical resource, along with the spatial variation of epidemic outbreak. As validated in our experimental results in real data of dengue outbreak happening in Tainan (2015), we present the feasibility of our framework to deploy a dynamic placement strategy for medical resource assignment.

Original languageEnglish
Title of host publicationProceedings - 16th IEEE International Conference on Data Mining, ICDM 2016
EditorsFrancesco Bonchi, Xindong Wu, Ricardo Baeza-Yates, Josep Domingo-Ferrer, Zhi-Hua Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages61-70
Number of pages10
ISBN (Electronic)9781509054725
DOIs
Publication statusPublished - 2017 Jan 31
Event16th IEEE International Conference on Data Mining, ICDM 2016 - Barcelona, Catalonia, Spain
Duration: 2016 Dec 122016 Dec 15

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other16th IEEE International Conference on Data Mining, ICDM 2016
CountrySpain
CityBarcelona, Catalonia
Period16-12-1216-12-15

Fingerprint

Global warming
Viruses

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Chang, C. W., Chih, H. Y., Chou, D., Shu, Y-C., & Chuang, K-T. (2017). Relief of spatiotemporal accessibility overloading with optimal resource placement. In F. Bonchi, X. Wu, R. Baeza-Yates, J. Domingo-Ferrer, & Z-H. Zhou (Eds.), Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016 (pp. 61-70). [7837830] (Proceedings - IEEE International Conference on Data Mining, ICDM). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDM.2016.181
Chang, Chien Wei ; Chih, Hao Yi ; Chou, Dean ; Shu, Yu-Chen ; Chuang, Kun-Ta. / Relief of spatiotemporal accessibility overloading with optimal resource placement. Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. editor / Francesco Bonchi ; Xindong Wu ; Ricardo Baeza-Yates ; Josep Domingo-Ferrer ; Zhi-Hua Zhou. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 61-70 (Proceedings - IEEE International Conference on Data Mining, ICDM).
@inproceedings{6a1d57017f314baa9f913ad6165df749,
title = "Relief of spatiotemporal accessibility overloading with optimal resource placement",
abstract = "With the effects of global warming, some epidemic diseases via mosquito (e.g. mosquito-borne diseases) become more serious, such as dengue fever and zika virus. It is reported that the epidemic disease may cause many challenges to the hospital management due to the unexpected burst with uncertain reasons. Furthermore, the imperfect cares during the propagation of epidemic diseases, such as dengue fever (so far the appropriate treatment is not well established), may lead to the increasing mortality rate which should be avoided. In this paper, a novel paradigm for optimizing the placement of medical resource is proposed in pursuit of reducing the overloading cases in hospitals during the epidemic outbreak in the urban area. In this paper we explore the first paper to explore two important issues, including the strategy to evaluate the service quality and the solution to dynamically dispatch the medical resource, along with the spatial variation of epidemic outbreak. As validated in our experimental results in real data of dengue outbreak happening in Tainan (2015), we present the feasibility of our framework to deploy a dynamic placement strategy for medical resource assignment.",
author = "Chang, {Chien Wei} and Chih, {Hao Yi} and Dean Chou and Yu-Chen Shu and Kun-Ta Chuang",
year = "2017",
month = "1",
day = "31",
doi = "10.1109/ICDM.2016.181",
language = "English",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "61--70",
editor = "Francesco Bonchi and Xindong Wu and Ricardo Baeza-Yates and Josep Domingo-Ferrer and Zhi-Hua Zhou",
booktitle = "Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016",
address = "United States",

}

Chang, CW, Chih, HY, Chou, D, Shu, Y-C & Chuang, K-T 2017, Relief of spatiotemporal accessibility overloading with optimal resource placement. in F Bonchi, X Wu, R Baeza-Yates, J Domingo-Ferrer & Z-H Zhou (eds), Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016., 7837830, Proceedings - IEEE International Conference on Data Mining, ICDM, Institute of Electrical and Electronics Engineers Inc., pp. 61-70, 16th IEEE International Conference on Data Mining, ICDM 2016, Barcelona, Catalonia, Spain, 16-12-12. https://doi.org/10.1109/ICDM.2016.181

Relief of spatiotemporal accessibility overloading with optimal resource placement. / Chang, Chien Wei; Chih, Hao Yi; Chou, Dean; Shu, Yu-Chen; Chuang, Kun-Ta.

Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. ed. / Francesco Bonchi; Xindong Wu; Ricardo Baeza-Yates; Josep Domingo-Ferrer; Zhi-Hua Zhou. Institute of Electrical and Electronics Engineers Inc., 2017. p. 61-70 7837830 (Proceedings - IEEE International Conference on Data Mining, ICDM).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Relief of spatiotemporal accessibility overloading with optimal resource placement

AU - Chang, Chien Wei

AU - Chih, Hao Yi

AU - Chou, Dean

AU - Shu, Yu-Chen

AU - Chuang, Kun-Ta

PY - 2017/1/31

Y1 - 2017/1/31

N2 - With the effects of global warming, some epidemic diseases via mosquito (e.g. mosquito-borne diseases) become more serious, such as dengue fever and zika virus. It is reported that the epidemic disease may cause many challenges to the hospital management due to the unexpected burst with uncertain reasons. Furthermore, the imperfect cares during the propagation of epidemic diseases, such as dengue fever (so far the appropriate treatment is not well established), may lead to the increasing mortality rate which should be avoided. In this paper, a novel paradigm for optimizing the placement of medical resource is proposed in pursuit of reducing the overloading cases in hospitals during the epidemic outbreak in the urban area. In this paper we explore the first paper to explore two important issues, including the strategy to evaluate the service quality and the solution to dynamically dispatch the medical resource, along with the spatial variation of epidemic outbreak. As validated in our experimental results in real data of dengue outbreak happening in Tainan (2015), we present the feasibility of our framework to deploy a dynamic placement strategy for medical resource assignment.

AB - With the effects of global warming, some epidemic diseases via mosquito (e.g. mosquito-borne diseases) become more serious, such as dengue fever and zika virus. It is reported that the epidemic disease may cause many challenges to the hospital management due to the unexpected burst with uncertain reasons. Furthermore, the imperfect cares during the propagation of epidemic diseases, such as dengue fever (so far the appropriate treatment is not well established), may lead to the increasing mortality rate which should be avoided. In this paper, a novel paradigm for optimizing the placement of medical resource is proposed in pursuit of reducing the overloading cases in hospitals during the epidemic outbreak in the urban area. In this paper we explore the first paper to explore two important issues, including the strategy to evaluate the service quality and the solution to dynamically dispatch the medical resource, along with the spatial variation of epidemic outbreak. As validated in our experimental results in real data of dengue outbreak happening in Tainan (2015), we present the feasibility of our framework to deploy a dynamic placement strategy for medical resource assignment.

UR - http://www.scopus.com/inward/record.url?scp=85014555738&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85014555738&partnerID=8YFLogxK

U2 - 10.1109/ICDM.2016.181

DO - 10.1109/ICDM.2016.181

M3 - Conference contribution

T3 - Proceedings - IEEE International Conference on Data Mining, ICDM

SP - 61

EP - 70

BT - Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016

A2 - Bonchi, Francesco

A2 - Wu, Xindong

A2 - Baeza-Yates, Ricardo

A2 - Domingo-Ferrer, Josep

A2 - Zhou, Zhi-Hua

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Chang CW, Chih HY, Chou D, Shu Y-C, Chuang K-T. Relief of spatiotemporal accessibility overloading with optimal resource placement. In Bonchi F, Wu X, Baeza-Yates R, Domingo-Ferrer J, Zhou Z-H, editors, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 61-70. 7837830. (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2016.181