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Identification and Prediction of Microvascular Invasion in Hepatocellular Carcinoma Based on Multiple Sequence Fusion Images 43

Identification and Prediction of Microvascular Invasion in H...

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43rd Chinese control conference, CCC 2024

作者： Lu, Mingguang Zhu, Yuan China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

Hepatocellular carcinoma (HCC) is one of the most difficult diseases to be treated fundamentally in the medical field in today's world, and the recurrence rate of HCC has been increasing year by year in recent years. The study on the identification and prediction of microvascular invasion phenomenon (MVI) in hepatocellular carcinoma is beneficial to the postoperative prevention of hepatocellular carcinoma patients, which can greatly improve the survival probability of patients after surgery. In this study, a new MVI prediction method (MSF-GWO-GPR) was proposed, which combines the multi-sequence image features of imaging histology, sifts out the unimportant features through the T-test method and the dimensionality reduction of Lasso regression, and establishes the multi-sequence Gaussian process regression (GPR) prediction model for data fusion, and combined with the Gray Wolf Optimization (GWO) algorithm to design a suitable optimization objective function to optimize the hyper-parameters in the GPR, in order to get better prediction results. Compared with the existing methods, the data from different sequences of MRI images are selected for fusion in this study, which makes the feature data richer and more complete, and the model applicability is better;moreover, by optimizing the hyperparameters in the model through the GWO, the model can be made more accurate, reduce the risk of misidentified prediction, and improve the accuracy rate. The experimental results show that MSF-GWO-GPR outperforms widely used machine learning methods in terms of accuracy, F1 score, precision, recall and AUC metrics. This may provide a new idea for the identification and prediction of MVI in hepatocellular carcinoma. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Dimensionality reduction

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Path Planning using Multiple Random Trees Algorithm Based on Adaptive Step Adjustment 6

Path Planning using Multiple Random Trees Algorithm Based on...

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6th World Robot conference (WRC) / Symposium on advanced Robotics and automation (SARA)

作者： Li, Zhengzheng Zhou, Lelai Dai, Xiaomeng Shen, Zhen Zhang, Wenhe Li, Yibin Shandong Univ Ctr Robot Sch Control Sci & Engn Jinan 250061 Shandong Peoples R China Minist Educ Engn Res Ctr Intelligernt Unmanned Syst Jinan 250061 Shandong Peoples R China Construct Assemble Technol Corp Bridge Engn Bur Grp China Railway Construct Corp Tianjin 300300 Peoples R China China Railway Construct Bridge Engn Bur Grp Tianjin 300300 Peoples R China Natl Innovat Ctr High Speed Rail Technol Qingdao Qingdao 266000 Peoples R China

ISBN: (纸本)9798331506100

This paper presents a path planning method using multiple random trees algorithm based on adaptive step adjustment(ASM-RRT). The method introduces a strategy for generating random trees, enabling the placement of root nodes at optimal locations within the environment. An adaptive step adjustment approach is employed to accelerate the exploration process. Additionally, a local search strategy for adjacent points is proposed, defining the search range around the center of each newly generated node to identify more optimal paths. The effectiveness of the method is validated through simulation experiments in two-dimensional and manipulator path planning environments. In comparison to the RRT and RRT-Connect algorithms, the proposed method exhibites superior performance. The manipulator experiment is carried out in physical scenarios to assess the feasibility of the presented method.

关键词： adaptive step adjustment multiple trees root node generation robot obstacle avoidance path planning

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Optimal control Methods for Fuzzy Optimal control Problem

Optimal Control Methods for Fuzzy Optimal Control Problem

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2023 International conference on advanced Mechatronics, Intelligent Manufacture and Industrial automation, ICAMIMIA 2023

作者： Soemarsono, Annisa R. Mardlijah Yazid, Edwar Mathematics Department Surabaya Indonesia Research Centre for Electrical Power and Mechatronics Bandung Indonesia

ISBN: (纸本)9798350309225

We have made several adjustmentsto fulfill the necessary requirements for optimal control problems based on fuzzy concepts for the LQR method by implementing the horizontal membership function (HMF) concept and also utilizing the definition of differentiation with a granular approach. We then construct an illustrative example of fuzzy optimal control problems for PMP and LQR methods by determining fuzzy control in the description of a Gaussian membership function. The fuzzy control, which is declared as a membership function, is expected to facilitate the optimal control process applied to the fuzzification process of a fuzzy model, such as the Takagi-Sugeno (or Takagi-Sugeno-Kang) fuzzy *** models of the Takagi-Sugeno (or Takagi-Sugeno-Kang) type aim to represent systems or plants that are non-linear. Therefore, we have PMP for optimal control problems with a fuzzy approach and LQR for optimal control problems with a fuzzy approach. Both optimal control methods involve many variational calculus (variational problems) that require an approach relevant with the idea of Euler-Lagrange. Hereafter, we find a solution to the fuzzy optimal control problems for PMP and LQR analytically. We obtain optimal fuzzy state and optimal fuzzy control. Finally, we apply Simulink (Matlab) to show graphics of the optimal fuzzy state and optimal fuzzy control. © 2023 IEEE.

关键词： Fuzzy control

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Self-triggered control for linear systems based on hierarchical reinforcement learning with RNNs 24

Self-triggered control for linear systems based on hierarchi...

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3rd International conference on Computer, Artificial Intelligence and control Engineering, CAICE 2024

作者： Chen, Wei Wan, Haiying Luan, Xiaoli Liu, Fei Key Laboratory of Advanced Process Control for Light Industry Institute of Automation Jiangnan University Wuxi China

ISBN: (纸本)9798400716942

In this research, we introduce a novel model-free self-triggered control strategy for linear systems, employing a hierarchical reinforcement learning approach. This strategy establishes a dual-Actor Critic hierarchical architecture, utilizing two neural networks that guide each other's decision-making to simulate the triggering and control strategies in self-triggered control. The triggering strategy, serving as the top-level policy, aims to find the maximum triggering interval that maintains system stability based on the initial control strategy. The control strategy, as the bottom-level policy, under the guidance of the triggering strategy, takes the optimization of control performance considering the impact of triggering intervals as a sub-goal. This approach reduces the exploration space of the bottom-level policy and accelerates the reinforcement learning process. In the implementation of the dual-Actor Critic algorithm, the Critic network employs recurrent neural networks to capture the temporal dependencies of expected rewards, thereby enhancing the efficiency and accuracy in approximating the Q-function. The efficacy of our proposed method is demonstrated through a series of numerical simulations. Theory of computation∼Theory and algorithms for application domains∼Machine learning theory∼Reinforcement learning∼Sequential decision making. © 2024 ACM.

关键词： Federated learning

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A Norm Optimal Iterative Learning control Approach with Efficient Computation 13

A Norm Optimal Iterative Learning Control Approach with Effi...

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13th IEEE Data Driven control and Learning Systems conference, DDCLS 2024

作者： Gao, Luyuan Zhuang, Zhihe Tao, Hongfeng Chen, Yiyang Paszke, Wojciech Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Institute of Automation University of Zielona Gora Zielona Gora Poland

ISBN: (纸本)9798350361674

Iterative learning control (ILC) is excellently applied to output tracking for systems that perform repetitive tasks. Classical norm optimal ILC (NOILC) approach yields optimal control inputs by minimizing a quadratic cost function. However, this approach requires the introduction of supervectors, i.e., lifting technique, for system description, which raises a high computational load problem. The contribution of this paper is to propose a non-lifted NOILC (N-NOILC) approach by redesigning a cost function that does not involve the lifting technique, achieving the goal of efficient computation. Therefore, the proposed approach is particularly suitable for large tracking tasks with long trial duration and high sampling frequency. Moreover, considering the model uncertainty in practice, robust convergence is analyzed. Numerical simulations are shown to demonstrate the properties and advantages of the proposed approach. © 2024 IEEE.

关键词： Adversarial machine learning

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Garbage classification system design 6

Garbage classification system design

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6th IEEE advanced Information Technology, Electronic and automation control conference (IEEE IAEAC)

作者： Zhou, Jie He, JingYan Tao, JiaYu Nantong Inst Technol Coll Mech Engn Nantong Jiangsu Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

An intelligent garbage automatic classification device based on single chip microcomputer STC89C52 is designed. The device is equipped with various modules on the basis of ordinary garbage cans to realize the functions of identifying garbage types, automatically classifying garbage after putting it in, and detecting the remaining space in the garbage cans, which improves the intelligence of the system and the market development value of the device. In the design process, the mechanical structure part of itself is analyzed by SolidWorks 3D modeling. After garbage management and classification, the recyclable utilization rate of resources can be maximized, and the amount of garbage treatment can be reduced. Garbage can be classified and treated before manual treatment to convert it into new energy.

关键词： Smart trash can refuse classification Single chip microcomputer control Visual recognition WiFi module data transmission

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Model Predictive control of a wastewater treatment process using neural networks 28

Model Predictive Control of a wastewater treatment process u...

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28th IEEE International conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Vasiliev, Iulian Luca, Irina Condrachi, Larisa Luca, Laurentiu Barbu, Marian Vilanova, Ramon Caraman, Sergiu Dunǎrea de Jos University of Galati Department of Automation and Electrical Engineering Galati Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain

ISBN: (纸本)9798350339918

This paper deals with the increasing of the operation efficiency of a wastewater treatment plant by reducing the level of pollutant concentration in the effluent. In essence, the main goal is the reduction of the concentration of organic substrate, Model Predictive control algorithm being used for this, considering as a model of the wastewater treatment process a neural network model based on a simplified mathematical model of the 4th order. For the implementation of the control algorithm, two neural networks were trained. In the first version of the neural network, it was considered that all 4 state variables are measurable and in the second version, only the organic substrate was considered measurable. Regarding the training of the two neural networks, good results were obtained in the case of both versions. Instead, the control algorithm gave better results when the second neural network was used (lower values of the substrate, lower variations of the aeration rate, which means a lower cost of operation). © 2023 IEEE.

关键词： Neural networks

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Study on Water-Entry Projectile control Based on ALE Method 6

Study on Water-Entry Projectile control Based on ALE Method

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6th IEEE advanced Information Technology, Electronic and automation control conference (IEEE IAEAC)

作者： Liu, Xi Jiangsu Automat Res Inst Lianyungang Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

The penetration of a high-velocity water-entry projectile into the target plate is investigated using the arbitrary Lagrange-Euler (ALE) method. First, the profiles of the cavities formed during the water entry of a projectile are calculated and compared to verify the rationality and accuracy of the proposed computational model and method adopted. Then the characteristics of the high-velocity water-entry projectile penetrating a target plate under three typical cases are simulated to analyze cavity evolution, acceleration and velocity variation of the projectile during water entry process. The effect of penetration angles is analyzed and an increased angle between the target plate and the free surface of the liquid is found to cause a significantly increased peak load of penetration and prolonged penetration time. Simulation results show that in actual penetration of water-entry projectiles into target plates, it is of great necessity to comprehensively evaluate the effects of warhead strength and target attitude on the penetration, so as to provide insights into the research on high-velocity projectile penetration into underwater targets.

关键词： Arbitrary Lagrangian-Eulerian method Trans-media Penetration water-entry

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Integrating Sensor Fusion for Teleoperation control of Anthropomorphic Dual-Arm Robots∗ 5

Integrating Sensor Fusion for Teleoperation Control of Anthr...

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5th World Robot conference Symposium on advanced Robotics and automation, WRC SARA 2023

作者： Wang, Feilong Chen, Furong Yang, Xiaolong Yong, Qi Dong, Yanling Zhang, Xinming Zheng, Long Su, Hang Changchun University of Science and Technology College of Mechanical and Electrical Engineering Changchun130022 China Esiee Paris Noisy-le-Grand93160 France Shandong University School of Foreign Languages Jinan250100 China Jilin University Weihai Institute for Bionics Weihai264402 China Guangdong Univerisity of Technology School of Automation Guangzhou China

ISBN: (纸本)9798350307320

In order to achieve accurate control of anthropo-morphic two-arm robots, a novel teleoperation control system is proposed. The system uses sensor fusion technology to analyze and process the position and attitude information of the human arm, so as to realize the real-time control of the humanoid two-arm robot and its bionic hand. The system ensures stable and reliable remote operation, enabling users to control the robot freely. In order to verify the effectiveness of the system in different users, we invited several operators to participate in the experiment. The experimental results show that the system not only enhances the human-robot interaction experience, but also is effective for different users. © 2023 IEEE.

关键词： Remote control

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The System of Electric Drive of the Dragging Camp During the automation of the Technological process of Drawing Steel Wire 5

The System of Electric Drive of the Dragging Camp During the...

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5th IEEE KhPI Week on advanced Technology, KhPIWeek 2024

作者： Khrebtova, Oksana Shapoval, Oleksandr Khrebtov, Oleg Rudych, Mykhailo Babaryka, Maryna Kozlovs'ka, Tatyana Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department of Mechanical Engineering Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department of Jurisprudence Sciences Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Central Ukrainian National Technical University Kropyvnytskyi Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Kremenchuk Flight College of Kharkiv National University of Internal Affairs Kremenchuk Ukraine

ISBN: (纸本)9798350384499

The study involved an analysis of methods and electromechanical equipment during the production of metal products using wire drawing machines. For manufacturing wires with a medium diameter (1.8 ... 3.0 mm), the most promising approach is the use of wire drawing machines with a non-impact technological process, which has the potential for significant efficiency improvement through the optimization of power parameters and increasing the drawing speed. Increasing the efficiency of the wire drawing process is achievable through the modernization of existing electric drive systems, leading to a substantial increase in the overall drawing process efficiency. As for increasing the drawing speed, it can be accomplished by employing a more advanced electric drive control system. It has been proven that the electric drive based on the frequency converter - asynchronous motor is economically beneficial for use as the main electric drive in the wire drawing machine. An analysis of the operating modes of the wire drawing machine's electric drive using a mathematical model confirmed that the developed control principle provides speed regulation of wire drawing with an error that does not exceed the specified criteria. Thus, the technological process requirements are met in all operating modes. ©2024 IEEE.

关键词： Speed regulators

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