Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Kok Hen Chong"'
Autor:
Tarek Abedin, Chong Tak Yaw, Siaw Paw Koh, M.A. Hannan, Sieh Kiong Tiong, Kok Hen Chong, Ahmed N Abdalla, Kharudin Ali
Publikováno v:
Engineering and Technology Journal, Vol 41, Iss 8, Pp 1034-1057 (2023)
The smart street-lighting system (SSLS) is a leading candidate in the smart city. By the time of the last 15 cycles, many meaningful improvements have been executed in the SSLS with the impact of the internet of things technologies and universal netw
Externí odkaz:
https://doaj.org/article/b20ee0484f524103a42c833155fed09c
Publikováno v:
IEEE Access, Vol 10, Pp 86127-86180 (2022)
Nowadays, advanced communication technologies are being utilized to develop intelligent transportation management and driving assistance. Through the ability to exchange traffic and infotainment information between road infrastructure and vehicles, v
Externí odkaz:
https://doaj.org/article/9a197a46e8464275968b7898be1b6404
Autor:
Chong Tak Yaw, Siaw Paw Koh, Madderla Sandhya, Devarajan Ramasamy, Kumaran Kadirgama, Foo Benedict, Kharuddin Ali, Sieh Kiong Tiong, Ahmed N. Abdalla, Kok Hen Chong
Publikováno v:
Nanomaterials, Vol 13, Iss 10, p 1596 (2023)
Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graph
Externí odkaz:
https://doaj.org/article/20cb7969cd0e4af284e6e91b725b780b
Publikováno v:
Journal of Physics: Conference Series. 2319:012017
Wind energies are one of the most used resources worldwide and favours the economy by not emitting harmful gases that could lead to global warming. It is a cost-efficient method and environmentally friendly. Hence, explains the popularity of wind ene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::501ff4b9d521fa30446a19a84faeb06b
https://doi.org/10.1088/1742-6596/2319/1/012017
https://doi.org/10.1088/1742-6596/2319/1/012017
Fault Diagnosis in Wind Energy Management System using Extreme Learning Machine: A Systematic Review
Publikováno v:
Journal of Physics: Conference Series. 2319:012014
Fault diagnosis is increasingly important given the worldwide demand on wind energy as one of the promising renewable energy sources. This systematic review aimed to summarize the fault diagnosis using Extreme Learning Machine (ELM) on wind energy. F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59505c7858e215dbc5cc4416c25212ed
https://doi.org/10.1088/1742-6596/2319/1/012014
https://doi.org/10.1088/1742-6596/2319/1/012014
Publikováno v:
2010 IEEE Conference on Sustainable Utilization & Development in Engineering & Technology (STUDENT); 2010, p123-126, 4p
Publikováno v:
2009 IEEE Student Conference on Research & Development (SCOReD); 2009, p520-522, 3p