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SCEJ 54th Autumn Meeting (Fukuoka, 2023)

Program search result : 予測 : 33 programs

The preprints(abstracts) are now open (Aug. 28). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants and invited persons are required.

Title (J) field includes “予測”; 33 programs are found. (“Poster with Flash” presentations are double-counted.)
The search results are sorted by the start time.

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
Day 1
8:409:00
A100Development of an estimation model for condensate water composition in EGR of internal combustion engines
(Tokyo Tech) *(Reg)Kodama S., (Reg)Mori S., (AIST) Abe Y., Takeda Y., Oguma M., Kinoshita K., (Ibaraki U.) Ohmori Y., Sakaida S., Konno M., Tanaka K.
EGR
condensate water
pH
ST-22441
Day 1
9:009:20
H101Development of machine learning model for CO2 absorption performance of blended amine solutions
(AIST) *(Reg)Fujii Tatsuya, (Reg)Kohno Yuki, (Reg)Makino Takashi, (Tokyo Tech) Sako Masami, Ishihama Keisuke, Yasuo Nobuaki, Kawauchi Susumu
CO2 absorption
machine learning
amine
ST-21445
Day 1
9:0010:40
PA117Machine learning model for predicting jet fuel fraction yield in catalytic cracking of vegetable oils
(Shinshu U.) *(Stu)Katayama Yuzuki, (Reg)Shimada Iori
catalytic cracking
sustainable aviation fuel
machine learning
SY-62563
Day 1
9:0010:40
PA120Construction of yield prediction model in catalytic cracking of vegetable oils using transfer learning between different catalysts
(Shinshu U.) *(Stu)Sekikawa Nozomi, (Reg)Shimada Iori
catalytic cracking
transfer learning
vegetable oil
SY-62647
Day 1
9:0010:40
PA123Construction of the prediction model for graphene domain size synthesized by chemical vapor deposition
(Fukuoka U.) *(Stu)Tahara Yuya, (Reg)Yoshihara Naoki, (Reg)Noda Masaru
Machine Learning
chemical vapor deposition
graphene
SY-62527
Day 1
9:209:40
H102Predicting Physical Properties of Structurally Unknown Polymers Using Spectroscopy Data
(Resonac) (Cor)Nagai Yuuki
Machine Learning
Predict
Descriptor
ST-21353
Day 1
10:0010:20
H104[Featured presentation] Multimodal Deep Learning for Predictions of Various Properties of Composite Materials
(AIST) *(Reg·PCEF)Muroga Shun, Miki Yasuaki, Hata Kenji
multimodal deep learning
materials informatics
generative deep learning
ST-21602
Day 1
10:0010:20
Y104[Invited lecture] Prediction of the interaction parameters between CO2 and organic solvent for the PR EoS using an ANN
(Tokyo U. Sci.) *(Reg)Matsukawa H., (Reg)Otake K.
Peng-Robinson Equation of State
Artificial Neural Network
ST-26197
Day 1
10:4011:00
K106Performance prediction for OARO concentration of Li brine with CTA hollow fiber membrane modules
(Toyobo MC) *(Reg)Matsude Akihiro, (Cor)Goda Shohei, (Reg)Yasukawa Masahiro, (Reg)Nakao Takahito, Kohno Daiki, Abe Yoji
cellulose triacetate
hollow fiber
brine concentration
SY-61749
Day 1
12:4013:40
PA117Machine learning model for predicting jet fuel fraction yield in catalytic cracking of vegetable oils
(Shinshu U.) *(Stu)Katayama Yuzuki, (Reg)Shimada Iori
catalytic cracking
sustainable aviation fuel
machine learning
SY-62563
Day 1
12:4013:40
PA123Construction of the prediction model for graphene domain size synthesized by chemical vapor deposition
(Fukuoka U.) *(Stu)Tahara Yuya, (Reg)Yoshihara Naoki, (Reg)Noda Masaru
Machine Learning
chemical vapor deposition
graphene
SY-62527
Day 1
13:4014:20
H115[Invited lecture] Prediction and control of bacterial evolution through high-throughput automated experiments using robots
(RIKEN) *Shibai Atsushi, Furusawa Chikara
Laboratory automation
Laboratory evolution
Escherichia coli
ST-21805
Day 1
13:4014:40
PA120Construction of yield prediction model in catalytic cracking of vegetable oils using transfer learning between different catalysts
(Shinshu U.) *(Stu)Sekikawa Nozomi, (Reg)Shimada Iori
catalytic cracking
transfer learning
vegetable oil
SY-62647
Day 1
14:2014:40
H117Deep learning model for predicting all protein-protein interactions from sequence data
(Kyutech) *(Reg)Kurata Hiroyuki, Tsukiyama Sho
Cross attention
deep learning
prediction
ST-2133
Day 1
16:0016:20
H122High accuracy prediction of edible oil oxidation stability by multivariate analysis incorporating chemiluminescence information
(Tohoku U.) *(Stu·PCEF)Yoshida Yuta, (Reg)Hiromori Kousuke, (Reg)Shibasaki-Kitakawa Naomi, (Reg)Takahashi Atsushi
multivariate analysis
oxidative stability
edible oil
ST-21686
Day 1
16:0016:20
J122Prediction of evaporation phenomena for microwave heating using dimensionless numbers
(U. Hyogo) Yakata Ryohei, *(Reg)Asakuma Yusuke, (Curtin U.) Anita Hyde, Chi Phan
microwave
evaporation
dimensionless number
SY-57171
Day 1
17:2017:40
A126Mixing prediction based on Poincaré map in an oscillatory baffled reactor at low oscillatory Reynolds number
(Osaka Metro. U.) *(Stu)Murotani Ryosuke, (Reg)Horie Takafumi, (Keio U.) (Reg)Fujioka Satoko, (Osaka Metro. U.) (Reg)Okita Erika, (Reg)Yasuda Masahiro
Oscillatory flow
Laminar mixing
Poincare map
ST-22852
Day 2
9:009:20
H201Elucidation of appropriate data acquisition conditions for API concentration prediction by NIR
(Kyoto U.) *(Stu)Fukuoka Norihiko, (Powrex/TUAT) (Reg)Oishi Takuya, (Powrex) (Reg)Nagato Takuya, (TUAT) (Reg·APCE)Kim Sanghong, (Kyoto U.) (Reg)Sotowa Ken-Ichiro
NIR Spectrum
diffuse reflectance measurement
API concentration prediction
ST-21741
Day 2
9:209:40
E202Temperature and pH Dependent Prediction Method for Generated Silica Scale Based on Computational Chemistry
(Fuji Electric) *(Int)Jiang Tianlong, Wada Azusa, Ui Shinya, (JMC Geothermal Eng.) Watanabe Masato, Maeto Kotaro, Fukuda Daisuke
silica scale
prediction method
computational chemistry
SY-83151
Day 2
9:3011:00
PA203Prediction of the polymer gel-solvent interaction parameter χ using support vector regression
(TUAT) *(Stu·PCEF)Kamikawa Yuna, (Reg)Kitajima Teiji, (Reg)Tokuyama Hideaki
polymer gel
interaction parameter
machine learning
SY-79178
Day 2
9:3011:00
PA249Prediction Model for Polymorphs of Coated Glycine in Particle Composites Using a Taylor Continuous Crystallizer
(Doshisha U.) *(Stu)Nakamura Takumi, (Reg)Yoshida Mikio, (Reg)Shirakawa Yoshiyuki
Crystal Polymorph
Continuous Crystallization
Machine Learning
SY-79893
Day 2
9:4010:00
H203Novel encoding method for high dimensional power consumption data in distributed energy system for short-term electricity demand forecasting
(TokyoTech) *(Stu)Lee Hyojae, (Stu)Tsuda Shunsaku, (Stu)Iijima Taiki, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu
electricity demand prediction
distributed energy system
big data
ST-21550
Day 2
10:2010:40
H205Gaussian Process Regression Approaches for Process Optimization: A Case Study of Interface State Density Prediction between Insulator and Semiconductor
(NAIST) *(Stu)Matsunaga K., (AIST) Uenuma M., (NAIST) Sato A., Uraoka Y., Miyao T.
Gaussian process regression
length-scale
Metal-oxide-semiconductor
ST-21204
Day 2
10:3012:00
PA246Energy prediction by neural network with self-supervised learning for catalyst
(Fujitsu) *(Reg)Sakai Yasufumi, Dang Thang, (Tokyo Tech) Ishikawa Atsushi, (Fujitsu) Shirahata Koichi
Neural networks
self-supervised learning
catalyst energy prediction
SY-79559
Day 2
11:2011:40
E208Hydrological simulation for the prediction of algal growth in the Murou Dam Reservoir
(Eikei U. Hiroshima) *(Reg)Sagehashi Masaki, (Tohoku U.) Sano Daisuke, Nishimura Osamu, (Nat. Inst. Public Health) Asada Yasuhiro, Akiba Michihiro
Hydrological simulation
Murou Dam Reservoir
SWAT
SY-83601
Day 2
13:0013:40
Y213[Review lecture] Proposal of Molecular Representation and Inference Methods for Biodegradability Prediction QSAR System
(Shizuoka U.) *(Reg)Takeda Kazuhiro, (NITE) Takeuchi Kensuke, Sakuratani Yuki, (Shizuoka U.) (Reg)Kimbara Kazuhide
Decision support system
biodegradation
chemical descriptors
SY-51182
Day 2
14:0014:20
S216Improvement of COSMO-SAC method for estimating vapor pressure of metal complex
(U. Tokyo) *(Reg)Sato Noboru, (Reg)Momose Takeshi, (Reg)Shimogaki Yukihiro
COSMO-SAC
metal complex
vapor pressure
ST-24824
Day 2
14:2014:40
E217Prediction of the CO2 gas flow quantity of the CCU reproduction tower by AI technology
(Toshiba ESS) *(Cor)Shirota Takahiro, (Cor)Muraoka Daigo, (Cor)Fujita Koshito, (Cor)Miura Takahiro, (Cor)Iwasa Kiyohiko
CCU
CO2
AI technology
SY-83748
Day 2
15:4016:00
D221Prediction of power number and flow pattern in a horizontal cylindrical mixing tank by CFD
(Fukuoka U.) *(Stu)Matsukubo S., Kai Y., (Reg)Yoshizuru Y., (Reg)Kanai Y., (Reg)Suzukawa K.
Horizontal cylindrical tank
CFD
VOF
SY-56630
Day 3
9:009:20
Z301Prediction of densities of homogeneous phase fluid mixtures for a CO2/organic solvent system using an Artificial Neural Network
(Tokyo U. Sci.) *(Stu)Imagaki Takaya, (Reg)Matsukawa Hiroaki, (Reg)Murakami Yuya, (Reg)Shono Atsushi, (Reg)Otake Katsuto
Artificial Neural Network
carbon dioxide
density
SY-51377
Day 3
10:2010:40
H305Simulation of crosslinked network structure formation and prediction of physical properties of bifunctional monomers using a lattice model
(Kanazawa U.) Nishimura Yuki, *(Reg)Taki Kentaro
lattice model
cross-link
photopolymerization
SY-82159
Day 3
11:0011:20
E307[Invited lecture] Dependence of strain on the radical degradation rate of fluororubber sealant - Prediction of O-ring degradation using Finite Elements Methods -
(Mitsubishi Cable Industries) Hiyaji Kota
Radical attack
Fluororubber
SY-841066
Day 3
15:0015:20
S319Prediction of aerobic fermentation behavior of waste mushroom bed in a fed-batch reactor
(Shinshu U.) *(Stu)Kondo Yuki, (Reg)Shimada Iori, (Reg)Osada Mitsumasa, (Reg)Fukunaga Hiroshi, (Reg)Takahashi Nobuhide
microbial kinetics
waste biomass utilization
CO2 and heat supply
ST-29988

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SCEJ 54th Autumn Meeting (Fukuoka, 2023)


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