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SCEJ 89th Annual Meeting (Sakai, 2024)
Program search result : Machine learning : 22 programs
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Keywords field exact matches “Machine learning”; 22 programs are found.
The search results are sorted by the start time.
| Time | Paper ID | Title / Authors | Keywords | Topic code | Ack. number |
|---|---|---|---|---|---|
| Day 1 | PA130 | Machine-learning-assisted molecular evolution for the analysis of sequence-structure-function relationships | Protein Machine learning Molecular evolution | 7-a | 547 |
| Day 1 | K115 | Quality prediction in a small data environment for batch processes | Machine Learning Quality Prediction Small data | 6-a | 286 |
| Day 1 | K119 | Data-driven approach to automated reaction process analysis | Mechanistic model Machine learning Neural network | 6-b | 235 |
| Day 1 | F122 | Development of Hybrid Kinetic Model Applying Machine Learning for Liquid Phase Photocatalytic Reaction | Photocatalyst Kinetics Machine learning | 5-a | 693 |
| Day 1 | F123 | Machine Learning-assisted analysis of NO adsorption and dissociation on PdRuIr ternary nanoparticle alloy | machine learning nanoparticle alloy catalysis | 5-a | 285 |
| Day 1 | K124 | Dynamic Process Simulation for Green Ammonia Synthesis Considering Wind and Solar Condition | Dynamic simulation Green ammonia Machine learning | 6-c | 695 |
| Day 2 | PB221 | Real time monitoring of polymer properties and design of polymerization process with machine learning | machine learning polymer Online sensing | 6-d | 66 |
| Day 2 | PB226 | Vapor pressure prediction of amines using molecular descriptors | Machine Learning Physical Property Prediction amine | 6-g | 12 |
| Day 2 | PB280 | Application of US-EC system oxidation PPCPs and using machine learning to predict hydraulic retention time in continuous processes | Machine learning Sonoelectrochemical Continuous stirred-tank reactor | 13-b | 16 |
| Day 2 | PB286 | Prediction of CO2 desorption performance of amine-based absorbents in vacuum flash desorption using porous hollow fiber membranes | CO2 chemical absorption CO2 stripping machine learning | 13-g | 690 |
| Day 2 | F204 | Exploring the large-area graphene CVD conditions by machine learning assisted image analysis | Graphene Chemical vapor deposition Machine learning | 5-i | 302 |
| Day 2 | PC216 | Determination of Molecular Descriptor in Pharmaceutical Cocrystal Prediction | Molecular Descriptor Machine learning Cocrystal | 8-b | 370 |
| Day 2 | K217 | Coarse-Grained Force Field Parametrization for Polymers Using Machine Learning | Coarse-Grained Force Field Machine Learning | 6-g | 220 |
| Day 2 | F219 | Polymer immobilization catalysts using machine learning methods | Polymer Immobilized Catalyst Machine Learning Pd | 5-f | 717 |
| Day 2 | H219 | Understanding the stability of features for AI cardiotoxicity prediction models using in vitro cardiomyocyte beating data. | cardiotoxicity iPS-derived cardiomyocytes Machine learning | 7-e | 195 |
| Day 3 | H302 | Improving the performance of fluorescence immunosensor by predicting single mutation effects using protein language model | immunosensor yeast surface display machine learning | 7-a | 13 |
| Day 3 | PD367 | Machine Learning Models for Predicting Gaseous Adsorption in Metal-Organic Frameworks by Employing Sigma Profiles of Organic Linkers | metal-organic frameworks adsorption machine learning | 4-e | 362 |
| Day 3 | I304 | Dispersion prediction of surface modified nanoparticles using machine learning model with various molecular descriptors | machine learning dispersion prediction surface modified nanoparticles | 1-b | 242 |
| Day 3 | J304 | Machine learning compared with conventional statistic model: Design of permeable reactive barrier for groundwater remediation | Groundwater Permeable reactive barrier Machine learning | 13-a | 19 |
| Day 3 | PE335 | Establishment of machine learning model for ultrasonic combined catalyst degradation of organic pollutants: focus on prediction of kinetic constants | Ultrasonics catalyst machine learning | 5-b | 319 |
| Day 3 | I316 | Physics-informed neural networks for flow in a bubble column | Bubble column OpenFOAM Machine learning | 2-d | 635 |
| Day 3 | K316 | Machine-Learning-Aided Understanding of Protein Adsorption onto Zwitterionic Polymer Brushes | Zwitterionic polymer Antifouling Machine learning | 12-a | 554 |
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SCEJ 89th Annual Meeting (Sakai, 2024)
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