Kim Sanghong - Program search result - SCEJ 52nd Autumn Meeting (Okayama, 2021)

`SCEJ 52nd Autumn Meeting (Okayama, 2021)`

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Program search result : Kim Sanghong : 3 programs

ST-25,SY-56,SY-64,SY-65,SY-70 are changed from live streaming sessions to online sessions.
The preprints are now open (Sep. 8). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants (excludes free registration) and invited persons are required.

Authors field exact matches “Kim Sanghong”; 3 programs are found. (“Poster with Flash” presentations are double-counted.)
The search results are sorted by the start time.

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Day 1 13:00– 13:40	VE113	[Invited lecture] Role of Process Systems Engineering (TUAT) (Reg·APCE)Kim Sanghong	Process systems engineering Process synthesis Solution synthesis	ST-27	510
Day 1 16:40– 17:00	LD124	Distillation apparatus with agitator for enhancing interfacial mass exchange (Kyoto U.) *(Reg)Sotowa Ken-Ichiro, Yoshikawa Itsuki, (Tokushima U.) (Stu)Uno Yumi, (Reg)Horikawa Toshihide, (Kyoto U.) (Reg)Tonomura Osamu, (TUAT) (Reg)Kim Sanghong	Distillation Continuous operation HETP	SY-65	861
Day 2 13:00– 14:20	Chair: Kim Sanghong, Badr Sara
	LD213	[Featured presentation] [The Outstanding Paper Award] Physical-Principle Based Extended Attributes for Process Fault Detection (TUAT) *(Reg·PCE)Xia Junqing, (Reg)Yamashita Yoshiyuki	Fault Detection Grey-box Process Modeling Process Monitoring	SY-64	101
	LD214	Formulation of the method of Integrated Performance Management in process industry (TUAT) *(Stu)Kobayashi Yasunori, (Reg)Yamashita Yoshiyuki	KPI Performance Management Process Manufacturing	SY-64	100
	LD215	Fault Detection of Chemical process based on Deep Neural Networks with Continuous Wavelet Transform (TUAT) *(Stu)Ukawa Chinatsu, (Reg)Yamashita Yoshiyuki	Fault Detection Neural Network Continuous Wavelet Transform	SY-64	666
	LD216	An approach for estimating the geographical distribution of infectious disease epidemic hazards.　-Use of COVID-19 infection data (U. Miyazaki) *(Reg)Takatsuka Kayoko, Kozakai Yuya, Kuroda Yoshiki, Sekiguchi Satoshi, Aburada Kentaro, Okazaki Naonobu	infectious disease epidemic potential hazards keeling model COVID-19 infection data	SY-64	196

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SCEJ 52nd Autumn Meeting (Okayama, 2021)

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