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检索条件"任意字段=3rd IFAC Symposium on Modelling and Control in Biomedical Systems"

共 215 条记录，以下是1-10 订阅

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Dynamic Multiscale Hybrid modelling of a CHO cell system for Recombinant Protein Production 12

Dynamic Multiscale Hybrid Modelling of a CHO cell system for...

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12th ifac symposium on Advanced control of Chemical Processes (ADCHEM)

作者： Pennington, Oliver Rios, Sebastian Espinel Sebastian, Mauro Torres Dickson, Alan Zhang, Dongda Univ Manchester Oxford Rd Manchester M1 3AL Lancs England Princeton Univ Princeton NJ 08544 USA

Multiscale hybrid modelling of biosystems utilises advantageous aspects of several modelling approaches, from the physical interpretations of kinetic modelling to the power of a data-driven Artificial Neural Network (ANN). This study implements multiscale modelling to gain insight into the production of Trastuzumab (Herceptin) from Chinese Hamster Ovary (CHO) cells under challenging dynamics A reduced metabolic network is subject to enzyme constraints with a Dynamic Metabolic Flux Analysis (ecDMFA) approach and integrated within a macro-scale hybrid kinetic model. The model can simulate fed-batch processes with optimized feed control, as well as providing insight into the control gained by alteration to the cell culture media. On the intracellular level, the influence from extracellular perturbations can be observed, in addition to giving an estimated production rate of unmeasured by-products. Overall, this model can be used as a reliable digital twin to estimate the underlying fed-batch process dynamics for future model predictive control and process optimisation. Copyright (C)2024 The Authors. This is an open access article under the CC BY-NC-ND license (htips://***/licenses/by-nc-nd/4.0/)

关键词： Machine Learning Assisted modelling Optimal control Experiment Design

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Dam seepage defect area estimation method based on UAV 3D scene reconstruction 24

Dam seepage defect area estimation method based on UAV 3D sc...

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3rd International symposium on Intelligent Unmanned systems and Artificial Intelligence (SIUSAI)

作者： Gao, Shuhua Gao, Sheng Yang, Yujie Du, Bo Wang, Wenying Yu, Yanfei Wang, Jing Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Beijing Hangzheng Instrument Equipment Co Ltd Beijing Peoples R China

ISBN: (纸本)9798400710025

Due to the complex geometric structure of the dam, it is challenging to directly calculate seepage areas from the infrared images captured by unmanned aerial vehicles ( UAVs). To address this issue, this paper proposes a seepage area calculation method based on three-dimensional (3D) scene reconstruction. The method first optimizes the modelling process to achieve fast 3D scene reconstruction of the dam according to the requirements. By utilizing the projection model established during point cloud modelling, the seepage scale features are projected onto the surface of the model, restoring their spatial relationships in the real dam scene. Finally, the seepage area calculation is accomplished using the principles of lens imaging. Experimental validation confirms the effectiveness of the proposed method for calculating seepage areas.

关键词： Dam seepage 3D scene reconstruction UAV inspection Intelligent recognition

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Deep Learning-Based Three-dimensional Reconstruction and Spatial Position Mapping of Tunnel Defect Zones 24

Deep Learning-Based Three-dimensional Reconstruction and Spa...

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3rd International symposium on Intelligent Unmanned systems and Artificial Intelligence (SIUSAI)

作者： Wang, Jing Wang, Wenying Xu, Ping Wang, Chuan Zhang, Ning Gao, Sheng Xiao, Ganghua Wang, Zhengfang Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Shandong Jiekong Elect Technol Co Ltd Jinan Peoples R China Shandong Hispeed Grp Co Ltd Jinan Peoples R China Shandong Univ Jinan Peoples R China

ISBN: (纸本)9798400710025

Timely detection and discovery of the spatial location, dimensions and categories of surface defects in tunnels are of great significance to ensure the safe operation of tunnels. This study proposes a 3D reconstruction and spatial location mapping method for tunnel defect areas. The local geometry is reconstructed directly in the 3D spatial body, and then the global modelling of the critical areas in the tunnel and the accurate mapping of the surface defects are achieved from coarse to fine. Finally, the MVS-Texturing feature mapping algorithm is used to map the results of the surface defect identification onto the 3D model to achieve the 3D reconstruction and visualization of the surface defects. This method overcomes the problem of low modelling efficiency of existing tunnel 3D reconstruction methods. Experiments were conducted on an indoor tunnel model and a highway tunnel in Jinan, which proved the effectiveness of this method for 3D reconstruction, defect location mapping and dimensioning of tunnels.

关键词： Tunnel surface defect 3D reconstruction Deep learning

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Using Redistribution Index to Identify an Outdated Detail Prior in the DCT-based 3D EIT Algorithm 12

Using Redistribution Index to Identify an Outdated Detail Pr...

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12th ifac symposium on Biological and Medical systems (BMS)

作者： Chen, Rongqing Krueger-Ziolek, Sabine Battistel, Alberto Rupitsch, Stefan J. Moeller, Knut Hsch Furtwangen Inst Tech Med ITeM Jakob Kienzle Str 17 Villingen Schwenningen Germany Univ Freiburg Fac Engn Georges Kohler Allee 101 Freiburg Germany

The integration of detailed prior information obtained from morphological images into the discrete cosine transformation (DCT) based 3D electrical impedance tomography (EIT) algorithm significantly enhances the interpretability of the obtained results. However, the presence of outdated detail priors may introduce inaccuracies, thereby compromising the accuracy of clinical decisions. Consequently, detecting outdated detail priors in an EIT algorithm is essential for ensuring the reliability of the reconstruction results. To address this concern, we propose the redistribution index to assess and quantify potential errors associated with detailed priors. Simulations covering various atelectasis scales were conducted to evaluate the redistribution index behavior. An increase is observed in the redistribution index, escalating from 0.02 at 64% atelectasis to 0.50 at 0% atelectasis when the detail prior is outdated. The redistribution index from the accurate detail prior remains small and stable. This finding demonstrates that the redistribution index effectively detects outdated detail priors, but consideration of specific application requirements and tolerances in the clinical setting is necessary. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： biomedical imaging systems biomedical system modeling simulation and visualization model formulation decision support systems for the control of physiological and clinical variables

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Towards targeted exploration for non-stochastic disturbances 20

Towards targeted exploration for non-stochastic disturbances

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20th ifac symposium on System Identification (SYSID)

作者： Venkatasubramanian, Janani Kohler, Johannes Cannon, Mark Allgoewer, Frank Univ Stuttgart Inst Syst Theory & Automat Control D-70550 Stuttgart Germany Swiss Fed Inst Technol Inst Dynam Syst & Control CH-80092 Zurich Switzerland Univ Oxford Control Grp Parks Rd Oxford OX1 3PJ England

We present a novel targeted exploration strategy for linear time-invariant systems without stochastic assumptions on the noise, i.e., without requiring independence or zero mean, allowing for deterministic model misspecifications. This work utilizes classical data-dependent uncertainty bounds on the least-squares parameter estimates in the presence of energy-bounded noise. We provide a sufficient condition on the exploration data that ensures a desired error bound on the estimated parameter. Using common approximations, we derive a semidefinite program to compute the optimal sinusoidal input excitation. Finally, we highlight the differences and commonalities between the developed non-stochastic targeted exploration strategy and conventional exploration strategies based on classical identification bounds through a numerical example. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licneses/by-nc-nd/4.0/)

关键词： Experiment Design Identification for control Uncertainty Quantification

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A Medical Sample Collection Robot Based on Improved YOLO Algorithm 24

A Medical Sample Collection Robot Based on Improved YOLO Alg...

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3rd International symposium on Intelligent Unmanned systems and Artificial Intelligence (SIUSAI)

作者： Xiao, Qun Wu, Chuanyan Wang, Xinli Song, Rui Shandong Management Univ Sch Intelligent Engn Jinan Shandong Peoples R China Shandong Univ Sch Control Sci & Engn Jinan Shandong Peoples R China

ISBN: (纸本)9798400710025

Medical sample collection is a crucial foundation for clinical diagnosis and biomedical research. With the Healthy China initiative, the importance of health medical big data is increasingly recognized, and the demand for medical sample collection in China continues to grow. The development of high-precision medical testing technologies like gene testing has heightened the quality requirements for sample collection. Therefore, developing a more efficient and safer automated medical sample collection robot is of significant importance. Traditional medical sample collection methods, which rely on direct operation by medical staff, present certain risks and challenges. These include the risk of cross-infection, insufficient standardization in sampling, and low efficiency when dealing with large-scale sample collection needs. To address these issues, we have designed a medical sample collection robot that enhances sampling efficiency and safety while reducing the risk of infection for healthcare workers. The design is divided into hardware and software components. The software part utilizes an improved YOLO v5 algorithm with an enhanced attention mechanism layer for better target area recognition. The hardware part features a 6-axis robotic arm, 3D-printed for precision, controlled by an Arduino and STM32 microcontroller system, with a force feedback device at the gripper for safety. Our medical sample collection robot, equipped with the improved YOLOv5 model, has demonstrated robust performance in accurately identifying target sampling locations. The 6-DOF robotic arm, mimicking the actions of medical staff, successfully collects medical samples. Experimental validation confirms the robot's capability to effectively collect medical sample information.

关键词： Medical sample collection 6-DOF robotic arm Target recognition

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Third International Scientific and Practical symposium on Materials Science and Technology, MST 2023

Third International Scientific and Practical Symposium on Ma...

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3rd International Scientific and Practical symposium on Materials Science and Technology, MST 2023

ISBN: (纸本)9781510672901

The proceedings contain 45 papers. The topics discussed include: promising synthetic auxins from alkylphenols: a DFT study;installation and technology for the synthesis of magnetorheological polyurethane elastomer;impregnation modelling of the pultruded continuous fiber reinforced UD-prepregs;generalized susceptibility and small oscillations of edge dislocation in the Peierls relief when interacting with point defects;internal friction due to radiation drag of edge dislocation bending vibrations in the Peierls relief when interacting with point defects;application of the method of acoustic emission in assessing the resistance of coatings;synthesis of n-heterocycles based on chalcones and their antioxidant properties;influence of polyalkenyl succinimides on the stability of petroleum dispersed systems;kinetics of the strength of slag-alkaline concrete under conditions of solar thermal treatment;and critical control loop in pulp and paper production technology and control valves.

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On the Use of MPC Techniques to Decide Intervention Policies against COVID-19 3rd

On the Use of MPC Techniques to Decide Intervention Policies...

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3rd ifac Conference on modelling, Identification and control of Nonlinear systems (MiCNON)

作者： Liu, Zonglin Stursberg, Olaf Univ Kassel Dept Elect Engn & Comp Sci Control & Syst Theory Kassel Germany

This paper aims at demonstrating how and that model predictive control (MPC) strategies can be used to determine optimal intervention policies against the COVID-19 pandemic. Especially for the time after a first wave of infection and before a vaccine can be safely distributed to a sufficient extent, the intervention experience from the first outbreak can be utilized to guide the policy decision in this period. The MPC problem in this paper takes the pandemic in different regions of a country and its neighboring countries into account, while policies such as wearing masks or social distancing are selected as inputs to be optimized. This optimized policy balances the risk of a second outbreak and socio-economic costs, while considering that the measure should not be too severe to be rejected by the population. Effectiveness of this policy compared to standard intervention policies is compared through numerical simulations. Copyright (C) 2021 The Authors.

关键词： Nonlinear Model Predictive control biomedical systems Networked systems

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Interdisciplinary K-12 control Education in biomedical and Public Health Applications 13

Interdisciplinary K-12 Control Education in Biomedical and P...

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13th ifac symposium on Advances in control Education (ACE)

作者： Duncan, Dominique Garner, Rachael Bennett, Alexis Sinclair, Michael Ramirez-de la Cruz, Glendy Pasik-Duncan, Bozenna Univ Southern Calif Keck Sch Med USC Stevens Neuroimaging & Informat Inst Lab Neuro ImagingUSC Los Angeles CA 90033 USA Francisco Bravo Med Magnet High Sch Los Angeles CA 90033 USA Univ Kansas Dept Math Lawrence KS 66045 USA

There is a lack of control education at the K-12 level, and introducing high school students to the wide range of control applications and methods needed for these problems will increase the number of students who later plan to pursue science, technology, engineering, and mathematics (STEM) education and control research or careers. Through our established partnerships with schools in California and Kansas, we have developed educational tools to positively influence the learning and career paths of young high school (HS) students from underserved districts and underrepresented minority (URM) groups. Through the development of new curricula, teaching modules, and shared resources that are made broadly available to other school districts, this work has the potential to impact a large number of K-12 teachers and students. We have been working to train HS teachers to create connections between the STEM subjects they teach students with advanced topics, such as artificial intelligence (AI), that are often taught only post-HS. It creates a context where students can see how their STEM skills can be applied and a pathway of continuing STEM education from secondary to post-secondary. As a result, there is the potential to improve student interest and self-efficacy in STEM and to encourage them to pursue STEM careers. Furthermore, AI is key to understanding and making use of data and solving many control problems. We aim to help students learn the fundamentals of how AI algorithms are applied in contemporary neuroscience. Copyright (C) 2022 The Authors.

关键词： control education biomedical control systems stochastic control machine learning artificial intelligence databases medical applications

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Distribution Grid modelling and Particle Swarm Optimization for Electric Vehicles Flexibility 3

Distribution Grid Modelling and Particle Swarm Optimization ...

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3rd International Conference on Power, Energy, control and Transmission systems, ICPECTS 2022

作者： Kumar, Sairam Sampath Asthana, Alankrita Katikireddy, Avinash Mohanta, Prodyumna Kumar TUM School of Engineering and Design Technical University of Munich Munich Germany TUM School of Management Technical University of Munich Munich Germany

ISBN: (纸本)9781665462754

Electrical vehicles and renewable energy resources have increased penetration in the market. Consumers have redefined themselves as 'prosumers' because they are no longer consuming energy but also are producing energy. This creates problems like congestion and rebound effects on the distribution grid. However, controlling them with appropriate frameworks helps the distribution grid by providing services like voltage control, congestion management or compensating losses. These parameters are restructuring or creating new markets at the distribution level such that prosumers can participate and aid the distribution grid operators. This paper aims to perform a literature review on flexibility concepts at the distribution grid. Various types of flexibility, market formulation and methods to solve operational problems are summarized in this paper. Furthermore, a distribution grid with G2V (Grid-to-Vehicle) flexibility is modelled to demonstrate local electric vehicle flexi-bility and analyze the impacts on the distribution grid. A meta-heuristic algorithm called Particle Swarm Optimization is used to optimize the electric vehicle schedule and minimize the impacts on electricity grid. This coordination between the real-time grid loads and energy needs for electric vehicles directly affects the charging and discharging patterns of electric vehicles. The results from the simulations show a great reduction in impacts on the voltage of the grid and reduction in loads for grids. © 2022 IEEE.

关键词： Vehicle-to-grid

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