TY - GEN
T1 - Building the vector-control collaborative strategy in Dengue Fever
T2 - Case surabaya, Kuala Lumpur, Bangkok
AU - Sesulihatien, Wahjoe Tjatur
AU - Kiyoki, Yasushi
AU - Sasaki, Shiori
AU - Safie, Azis
AU - Yotopranoto, Subagyo
AU - Sornlertlamvanich, Virach
AU - Hansuebai, Aran
AU - Chawakitchareon, Petchporn
N1 - Publisher Copyright:
© 2017 The authors and IOS Press.
PY - 2017
Y1 - 2017
N2 - Dengue fever is a communicable disease that attacks more than 120 countries in the world during 50 years. Therefore, it is to make sense to say that collaboration among the countries, especially neighborhood countries, is one important key to combat the dengue. Currently, except a serological collaboration, collaboration in dengue is sporadic and temporal. This paper addresses the initiative to build vector-control strategy collaborative among Surabaya (Indonesia), Kuala Lumpur (Malaysia), and Bangkok (Thailand). Deriving the global policy from World Health Organization (WHO), we build the system that (1) extracting global feature from the local feature, (2) selecting the significant features, to determine ranking of importance of a feature, by weighting a feature, and (3) matching the pattern of data to the suitable strategy by measuring the similarity. We built the system from the real data of the Surabaya, Kuala Lumpur and Bangkok in 2012. We verified reliability of the system by comparing the data with the actual action in January 2012 The result shows that the system is system feasible to be implemented, however we still need more preparation to implement the system.
AB - Dengue fever is a communicable disease that attacks more than 120 countries in the world during 50 years. Therefore, it is to make sense to say that collaboration among the countries, especially neighborhood countries, is one important key to combat the dengue. Currently, except a serological collaboration, collaboration in dengue is sporadic and temporal. This paper addresses the initiative to build vector-control strategy collaborative among Surabaya (Indonesia), Kuala Lumpur (Malaysia), and Bangkok (Thailand). Deriving the global policy from World Health Organization (WHO), we build the system that (1) extracting global feature from the local feature, (2) selecting the significant features, to determine ranking of importance of a feature, by weighting a feature, and (3) matching the pattern of data to the suitable strategy by measuring the similarity. We built the system from the real data of the Surabaya, Kuala Lumpur and Bangkok in 2012. We verified reliability of the system by comparing the data with the actual action in January 2012 The result shows that the system is system feasible to be implemented, however we still need more preparation to implement the system.
KW - Bangkok
KW - Collaborative
KW - Kuala Lumpur
KW - Surabaya
KW - global policy
KW - similarity
KW - vector-control strategy
UR - http://www.scopus.com/inward/record.url?scp=85003022740&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85003022740&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-720-7-94
DO - 10.3233/978-1-61499-720-7-94
M3 - Conference contribution
AN - SCOPUS:85003022740
T3 - Frontiers in Artificial Intelligence and Applications
SP - 94
EP - 105
BT - Information Modelling and Knowledge Bases XXVIII
A2 - Thalheim, Bernhard
A2 - Jaakkola, Hannu
A2 - Kiyoki, Yasushi
A2 - Yoshida, Naofumi
PB - IOS Press
ER -
