Project Details

Řízení peristaltického čerpadla s využitím kombinace neuronových sítí, experimentálních měření a numerických simulací

Project Period: 1. 3. 2022 - 31. 12. 2022

Project Type: grant

Code: FIT/FSI-J-22-7952

Agency: Brno University of Technology

Program: Vnitřní projekty VUT

English title

Peristaltic pump control using a combination of neural networks, experimental measurements and numerical simulations

Type

grant

Keywords

physiological flow

Abstract

Simulating physiological flow is currently a major challenge, especially in medical methods (eg veno-arterial extracorporeal membrane oxygenation), where cardiac function is represented by a pump. This pulsating wave occurs in many in vitro phantom studies, but none of them assess the degree of hemolysis in the pump, as this is not of interest in these applications. The aim of the project is to develop a peristaltic pump that produces physiological wool and at the same time reduces the rate of hemolysis.

Team members

Kohút Jan, Ing. (UPGM FIT VUT) , research leader
Smrž Pavel, doc. RNDr., Ph.D. (UPGM FIT VUT)

Publications

2022

BURDISSO Sergio, FAJČÍK Martin, SMRŽ Pavel and MOTLÍČEK Petr et al. IDIAPers @ Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach. In: Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022). Abu Dhabi: Association for Computational Linguistics, 2022, pp. 61-69. ISBN 978-1-959429-05-0. Detail
FAJČÍK Martin, SMRŽ Pavel, MOTLÍČEK Petr and BURDISSO Sergio et al. IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model. In: Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022). Abu Dhabi: Association for Computational Linguistics, 2022, pp. 70-78. ISBN 978-1-959429-05-0. Detail