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SCEJ 87th Annual Meeting (Kobe, 2022)

Last modified: 2022-03-04 12:00:00

Hall and day program : Hall M

Program of CS-2 is updated.
The preprints are now open (Mar. 2nd). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants in Period I/II and invited persons are required. (The participants registered in Period III will get the ID/PW on Mar. 15th.)
The yellow back on the Technical sessions page denotes streaming-live session. (HQ-21 is changed to online.)

Hall M(online)

Hall M, Day 2 | Hall M, Day 3
6

TimePaper
ID		Title / AuthorsKeywordsTopic codeAck.
number
Hall M(online), Day 2(Mar. 17)
6. Systems, information, and simulation technologies
(13:00–14:40) (Chair: Takatsuka Kayoko)
13:00– 13:20M213Multiscale design of cryopreservation processes for human induced pluripotent stem cells
(U. Tokyo) *(Stu)Hayashi Yusuke, (Reg)Sugiyama Hirokazu
Modeling
Simulation
Regenerative medicine
6-b65
13:20– 13:40M214Superstructure-based process design for injectable manufacturing
(U. Tokyo) *(Stu)Yamada Masahiro, (Int)A. Udugama Isuru, (Reg)Badr Sara, (Shionogi pharma) (Cor)Zenitani Kenichi, (Cor)Kubota Kokichi, (Reg)Nakanishi Hayao, (U. Tokyo) (Reg)Sugiyama Hirokazu
Pharmaceutical manufacturing
Decision making
Process modeling
6-b336
13:40– 14:00M215Transport Phenomenological Modeling on Packed Column Distillation Process
(Kansai Chem. Eng.) *(Reg)Kataoka Kunio, (Reg)Nishimura Goro, (Reg)Noda Hideo
Packed Column Distillation
Heat and Mass Transfer
Control Volume Approach
6-c4
14:00– 14:20M216Local analytical study of mass transfer in a packed distillation column of a binary mixture
(Kansai Chem. Eng.) *(Reg)Nishimura Goro, (Reg)Kataoka Kunio, (Reg)Noda Hideo, (Kobe U.) (Reg)Ohmura Naoto
Mass transfer
Packed distillation column
Two film theory
6-c38
14:20– 14:40M217[Featured presentation] Soft sensors using physical model and learning-based system identification
(AIST/NEC) *(Reg)Kubosawa Shumpei, Onishi Takashi, (AIST/U. Tokyo) Tsuruoka Yoshimasa
soft sensors
dynamic simulation
reinforcement learning
6-c62
(15:00–16:20) (Chair: Kawai Hideki, Nishimura Goro)
15:00– 15:20M219Selecting optimal CO2 capture technology for combustion processes in power and industrial sectors
(Tohoku U.) *(Stu)Yagihara Koki, (Reg)Ohno Hajime, (Reg)Fukushima Yasuhiro
Carbon capture
CO2 emissions reduction
Optimization
6-e663
15:20– 15:40M220Towards automatic physical model building. Part 1: Development of variable annotation tool
(Kyoto U.) *(Stu)Kato Shota, Numoto Masaki, (Reg)Kano Manabu
Physical model
Automatic physical model building
Information extraction
6-f44
15:40– 16:00M221[Featured presentation] Towards automatic physical model building. Part 2: ProcessBERT: a pre-trained language model for chemical engineering
(Kyoto U.) Kanegami Kazuki, *(Stu)Kato Shota, (Reg)Kano Manabu
Physical model
Automatic physical model building
Pre-trained language model
6-f45
16:00– 16:20M222Inherent digital readiness: The challenges facing data-driven applications in the pharmaceutical industry
(UTokyo) *(Reg)Badr Sara, (Reg)Udugama Isuru, (Reg)Sugiyama Hirokazu
Digital twins
Pharma 4.0
Data standardization
6-f365
Hall M(online), Day 3(Mar. 18)
(9:00–10:40) (Chair: Matsuo Seiji)
9:00– 9:20M301Formulation of Integrated KPI Dashboard for Fertilizer Plant
(TUAT) *(Stu)Kobayashi Yasunori, (Reg)Yamashita Yoshiyuki
KPI
Energy Conservation
Optimization
6-a178
9:20– 9:40M302Improvement of MPC Performance and Maintenance Scheme Utilizing Cyber Physical System for the Raw Mix Proportioning in Cement Industry
(Taiheiyo Cement) *(Cor)Sudo Kota, (Cor)Katsuki Takeshi, (ADAPTEX) (Reg)Obika Masanobu, Ohnishi Ryo
Model predictive control
Cyber physical system
Cement
6-d56
9:40– 10:00M303Future prospects in AI technologies for process control
(AIST/NEC) *(Reg)Kubosawa Shumpei, Onishi Takashi, (AIST/U. Tokyo) Tsuruoka Yoshimasa
process control
artificial intelligence
machine learning
6-d63
10:00– 10:20M304Stiction compensation for industrial process control valves
(TUAT) *(Stu)Daiguji Masaharu, (Reg)Yamashita Yoshiyuki
process control
process models
optimization
6-d125
10:20– 10:40M305Automatic Detection of Self-excited Oscillatory Response and Re-Tuning of Poor Controller
(TUAT) *(Stu)Otakara Shigeki, (Reg)Yamashita Yoshiyuki
Process Control
PID Control
Oscillation Detection
6-d368
(11:00–12:00) (Chair: Sotowa Ken-Ichiro)
11:00– 11:20M307Automatic annotation method for growth diagnosis using image analysis by AI in smart agriculture
(U. Tokyo) *(Reg)Matsuo S., (Reg)Tokoro C., (NARO) Isozaki M.
Smart agriculture
object detection
automatic annotation
6-g21
11:20– 11:40M308Study of systems to support risk management of time, cost, and quality for projects
(U. Miyazaki) *(Reg)Takatsuka Kayoko, Kawabata Kaisei, Yorisada Shota, (JGC) (Reg)Sato Tomoichi, (U. Miyazaki) Aburada Kentaro, Okazaki Naonobu
QCD (quality, cost and development)
risk due to the work delay
schedule network
6-g358
11:40– 12:00M309Cost-effectiveness modelling and analysis of companion diagnostics
(UTokyo) *(Stu)Okamura K., (U. Tokyo) (Stu)Hamada R., (UTokyo) Tsuchiya H., (Reg)Ohta S., (Reg)Sugiyama H.
Medical costs
DALY
Antibody drugs
6-g381

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SCEJ 87th Annual Meeting (Kobe, 2022)

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