SCEJ 55th Autumn Meeting (Sapporo, 2024)
Program search result : モデル : 46 programs
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Title (J) field includes “モデル”; 46 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 | M101 | Machine learning model for predicting three-dimensional flow field inside a face mask obtained from X-ray CT | face mask numerical simulation machine learning | SY-52 | 527 |
| Day 1 | YB128 | Construction of yield prediction model in catalytic cracking of vegetable oils considering fatty acid composition | catalytic cracking vegetable oil machine learning | SY-63 | 697 |
| Day 1 | YB130 | Construction of Prediction Model for the Yield of Suzuki-Miyaura Type Cross-Coupling Reactions Using Polymeric Ni Catalysts and Proposal of Novel Polymeric Ni Catalysts | Machine Learning Polymeric Ni Catalysts Chemical Reactions | SY-63 | 271 |
| Day 1 | YB131 | Extension of chemical reaction neural network for kinetic model construction of heterogeneous catalyst reactions | chemical reaction neural network kinetic model heterogeneous catalyst | SY-63 | 255 |
| Day 1 | YA182 | A prioritization of parameter determinations for constructing a kinetic model of metabolic pathways | Kinetic model Metabolic pathway | SY-68 | 306 |
| Day 1 | Q109 | Development of a graph neural network (GNN) model for predicting the solubility of organic compounds in supercritical CO2 | Supercritical Solubility prediction Machine learning | SY-73 | 851 |
| Day 1 | L113 | Machine learning model estimating blood glucose monitoring from mid-infrared spectra measured by the photothermal monitoring method | mid-infrared spectra noninvasive blood glucose monitoring machine learning | SY-66 | 102 |
| Day 1 | V113 | Modeling of stratified treatment for cost-effectiveness analysis of new drugs and evaluation case studies | Agent-based modeling Stratification strategy New modality | ST-26 | 96 |
| Day 1 | K115 | Study on hydrogen utilization model for decarbonization of factories using mainly thermal energy | hydrogen thermal energy carbon neutrality | SY-74 | 265 |
| Day 1 | L115 | Development of a soft sensor model that takes into account the dynamic characteristics of the process and two similar qualities | machine learning soft sensor time delay | SY-66 | 260 |
| Day 1 | S116 | Construction of a machine learning model for predicting the characteristics from the fuel cell electrode catalyst layer preparation process | Fuel Cell Electrode Machine learning | ST-23 | 489 |
| Day 1 | YA182 | A prioritization of parameter determinations for constructing a kinetic model of metabolic pathways | Kinetic model Metabolic pathway | SY-68 | 306 |
| Day 1 | L121 | A method for estimating the reaction rates by inverse analysis of elementary reaction and transport model simulating a denitrification system | Kinetic model Surface reaction Optimization | SY-66 | 326 |
| Day 1 | S121 | [Featured presentation] A fuel cell catalyst degradation model for the integration to the fuel cell system simulator | fuel cell simulation degradation | ST-23 | 256 |
| Day 1 | YB131 | Extension of chemical reaction neural network for kinetic model construction of heterogeneous catalyst reactions | chemical reaction neural network kinetic model heterogeneous catalyst | SY-63 | 255 |
| Day 1 | S122 | Optimization of operation conditions of fuel cell systems based on material properties using model predictive control | Fuel Cell Systems Model Predictive Control | ST-23 | 696 |
| Day 1 | YB128 | Construction of yield prediction model in catalytic cracking of vegetable oils considering fatty acid composition | catalytic cracking vegetable oil machine learning | SY-63 | 697 |
| Day 1 | YB130 | Construction of Prediction Model for the Yield of Suzuki-Miyaura Type Cross-Coupling Reactions Using Polymeric Ni Catalysts and Proposal of Novel Polymeric Ni Catalysts | Machine Learning Polymeric Ni Catalysts Chemical Reactions | SY-63 | 271 |
| Day 1 | W125 | Calculation of virus filter performance and virus removability using an advanced multilayer membrane model | Virus filter virus reduction multilayer model | SY-69 | 15 |
| Day 2 | YA206 | Constructing model for predicting pesticide activity using scaffolds by machine learning and visualizing the basis for prediction | Machine Learning Quantitative Structure-Activity Relationship Pesticide | SY-78 | 86 |
| Day 2 | YA232 | Construction of predictive model for biodegradability as an alternative to biodegradability test using machine learning | Machine Learning Biodegradation plastic | SY-78 | 90 |
| Day 2 | YA258 | Evaluation of optical properties of light shielding gel using temperature-responsive polymer and construction of a model for predicting transmittance | temperature-responsive polymer light shielding material gel | SY-78 | 659 |
| Day 2 | YA217 | Proposal of a mathematical model describing nanoparticle translocation across cell membrane | Nano particles Cell membrane Mathematical model | SY-78 | 241 |
| Day 2 | YA223 | Research to Improving the Accuracy of Machine Learning Models for Predicting Reorganization Energy | Machine learning Organic semiconductor Graph Convolutional Network | SY-78 | 272 |
| Day 2 | L206 | Design space determination in freezing processes for human iPS cell-derived spheroids using hybrid models | Manufacturing Regenerative medicine Numerical simulation | SY-66 | 567 |
| Day 2 | R209 | Measurement of VOC adsorption equilibria on mesoporous silica in supercritical CO2 and analysis by thermodynamic adsorption model | Supercritical carbon dioxide, Mesoporous silica Adsorption | SY-51 | 620 |
| Day 2 | V209 | Development of model about moisture sorption kinetics based on water transfer properties in freeze-dried sugar matrices | Freeze-drying Moisture sorption Model prediction | SY-70 | 935 |
| Day 2 | L213 | Optimization of property prediction model in dynamic manufacturing process for carbon materials using a genetic algorithm | Machine learning Genetic-algorithm-based process variables and dynamics selection Multi-objective optimization | SY-66 | 273 |
| Day 2 | R213 | [Review lecture] Property prediction with machine learning models and designs of molecules, materials and processes through inverse analysis of models | Machine learning Material design Process design | SY-51 | 431 |
| Day 2 | YB245 | Machine learning model predicting properties from monomer structures of alkyl sulfonated polyimides | alkyl sulfonated polyimide machine learning fuel cell | SY-75 | 82 |
| Day 2 | E214 | Prediction model for real-time power generation of solar cells with shadow simulation based on module structure and irradiance fraction | Solar cell Energy system Prediction model | ST-22 | 865 |
| Day 2 | L214 | Discussion toward the application of mathematical models in controlling cell cultivation and antibody production | Cell Cultivation Antibody production Process Control | SY-66 | 573 |
| Day 2 | V214 | Near-infrared spectroscopic characteristics of saccharides in aqueous solutions with sodium chloride | infrared spectroscopy 2D correlation food model | SY-70 | 1100 |
| Day 2 | R215 | Searching for the optimal machine learning prediction model in carbon dioxide expansion fluid density | machine learning carbon dioxide density | SY-51 | 403 |
| Day 2 | E216 | Molecular design using deep learning and vecror annealing | Deep learning Quantum anealing Generative model | ST-22 | 1099 |
| Day 2 | L216 | Deep Learning Prediction Model for Solubility of Nanoparticles From Perspective of Similarity | Nanoparticle solubility Deep learning | SY-66 | 677 |
| Day 2 | F218 | Development of a reaction kinetic model of hydrothermal synthesis of formic acid from KHCO3 solution. | CCU alkali bicarbonate chemical absorption | SY-64 | 884 |
| Day 2 | L219 | Molecular design with direct inverse analysis of autoencoder-based QSAR/QSPR model | Machine learning Inverse analysis Molecular design | SY-66 | 140 |
| Day 2 | Q219 | Model Analysis for Extraction Behavior of Rice Bran Oil from Rice Bran by Supercritical CO2 | supercritical carbon dioxide extraction rice bran oil group contribution method | SY-73 | 545 |
| Day 2 | E220 | Development of a product composition prediction model for catalytic cracking reactions and its application to the prediction of reactions with unknown feedstocks | physics-informed machine learning catalytic cracking reaction prediction | ST-22 | 1128 |
| Day 3 | N301 | Development of the numerical analysis model for the laminar fluid mixing with practical spatial resolution. | Laminar Fluid Mixing Numerical Simulation | SY-55 | 1102 |
| Day 3 | N302 | CFD Analysis of Fluid Flow and Mixing in a Stirred Tank: The Effect of Turbulence Models | CFD mixing turbulence | SY-55 | 943 |
| Day 3 | J304 | Numerical simulation of particle formation processes based on a population balance model describing nucleation pathways | Population balance Nucleation Numerical simulation | SY-79 | 782 |
| Day 3 | YA331 | Molecular modelling of solvation structures to evaluate the fouling resistance of zwitterionic materials. | betaines biocompatibility molecular dynamics | SY-57 | 662 |
| Day 3 | W305 | Machine learning-based cancer diagnosis using size-dependent blood residence time of nanoparticles | machine learning cancer diagnosis blood residence time | SY-72 | 624 |
| Day 3 | I324 | Constructing a Model for Predicting the Growth of Microalgae | Microalgae Nannochloropsis Growth Simulation | ST-24 | 858 |
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SCEJ 55th Autumn Meeting (Sapporo, 2024)
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