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Chinese Automation Congress (CAC)

作者： Yumin Lang Jiande Wu Xun Lang Wanke Yu Chuanyan Yang Hongye Su Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) of these RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data.

关键词： Power filters Noise reduction Process control Market research information filters Noise measurement Oscillators Spectral analysis Monitoring Signal to noise ratio

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Quantification of Valve Stiction in control Loops Using Adaptive Differential Evolution Algorithm

Quantification of Valve Stiction in Control Loops Using Adap...

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Chinese Automation Congress (CAC)

作者： Dong Yang Xun Lang Jiande Wu Wanke Yu Songhua Liu Lei Xie Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurately and promptly quantifying stiction is crucial for valve maintenance in industrial settings and ensuring the stability of control loop performance. However, current Hammerstein-based stiction quantification methods overlook valve dynamics, potentially leading to inaccurate quantification. Therefore, this paper proposes a novel stiction quantification method based on an adaptive differential evolution algorithm. In addition to considering the impact of valve dynamics on stiction, the proposed method demonstrates a certain level of robustness against the interference of unknown noise. Finally, the effectiveness of the proposed method is demonstrated through a series of simulations and industrial case studies.

关键词： Adaptation models Heuristic algorithms Noise Interference Valves Stability analysis Robustness Data models Maintenance Classification algorithms

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Effectivenes of the Use of Scientific and Academic information Resourses 13

Effectivenes of the Use of Scientific and Academic Informati...

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13th International Conference Management of Large-Scale System Development, MLSD 2020

作者： Ereshko, Felix Medennikov, Viktor Flerov, Yuri Federal Research Center Computer Science and Control of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (纸本)9781728110943

The methodology for assessing the effectiveness of the use of scientific and academic information resources in the Internet space has been considered in the context of transition to the digital economy and innovative development. The methodology presented has been elaborated on the basis of the analysis of state and volumes of information resources according to the results of the monitoring of websites of agricultural institutions of higher education. © 2020 IEEE.

关键词： information use

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Teeth Segmentation from Bite-Wing X-Ray Images by Integrating Nested Dual UNet with Swin Transformers

Teeth Segmentation from Bite-Wing X-Ray Images by Integratin...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yubo Li Yibin Tian Zhiyuan Zhang Xueyang Zhang Bingran Du Zhi Zeng School of Computer and Information Science Chongqing Normal University Chongqing CN College of Mechatronics and Control Engineering Shenzhen University Shenzhen CN Litemaze Technology Shenzhen CN School of Computing and Information Systems Singapore Management University Singapore SG Department of Stomatology Shunde Hospital Southern Medical University (The First People's Hospital of Shunde) Foshan CN

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In medical practice, the precision of image segmentation is crucial for diagnosis and treatment evaluations. Specifically, in dentistry, accurate teeth segmentation from bite-wing images is important for automatic and objective evaluations of root canal treatments. This study introduces $\text{Swin}-\mathrm{U}^{2} \text{Net}$ , a model merging the nested dual UNet with residual U-block and Swin Transformers. It combines the local feature extraction capability of the former and the global attention and context understanding of the latter. It has been evaluated for tooth root segmentation using 500 bite-wing dental x-ray images obtained from a root canal treatment clinic. It achieved the best segmentation outcome in terms of Intersection over Union (IOU) and the third best result in terms of Dice Similarity Coefficient (DSC) with the second least amount of network parameters among six UNet-like models, thus it is effective and efficient.

关键词： Image segmentation Irrigation Accuracy Merging Teeth Transformers Feature extraction Dentistry X-ray imaging Medical diagnostic imaging

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Reconfigurable Intelligent Surface Enhanced Wireless Localization: Phase Optimization for Malicious Interference Mitigation

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IEEE Transactions on Communications 2025年

作者： Zhang, Yi Xie, Yajing Wang, Lijia Liwang, Minghui Wang, Xianbin Xiamen University Ministry of Education of China Department of Information and Communication Engineering Key Laboratory of Multimedia Trusted Perception and Efficient Computing Xiamen China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai China Western University Department of Electrical and Computer Engineering ON Canada

Recently, unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) have merged as important enabling technologies for localization coverage extension and localization accuracy improvement under signal blockage and malicious interference conditions. However, most existing works assume known locations of jammers, which is generally impractical in real-world networks. To overcome this challenge, we propose a novel RIS-enhanced wireless localization framework against malicious interference with the support of either narrowband or orthogonal frequency division multiplexing (OFDM) pilot signals. A two-stage anti-jamming localization approach is developed to first estimate the unknown channel and signal information of the jammer and then localize the user’s position by eliminating the jamming signal. More importantly, we utilize the full potential of RIS to improve localization accuracy by optimizing the phase shift profile during the iterative process. Extensive simulation results demonstrate the commendable performance of our proposed framework, which can not only mitigate the jamming effect but also achieve better localization accuracy, offering a good reference for future heterogeneous and complex wireless networks. © 1972-2012 IEEE.

关键词： Frequency division multiplexing

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Synthesis of the Decision Support System for controlling the Process of Combined Destruction of Butyl Rubber Vulcanizates 3

Synthesis of the Decision Support System for Controlling the...

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3rd International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Tikhomirov, German Karmanov, Andrey Zhatova, Victoria Popov, Alexey Obraztsov, Nikolay Podvalny, Evgeniy Voronezh State University Department of System Analysis and Management Voronezh Russia Voronezh State Technical University Department of Automated and Computing Systems Voronezh Russia Voronezh State University Department of Geoecology of Environmental Monitoring Voronezh Russia Voronezh State University of Engineering Technologies Department of Information and Control Systems Voronezh Russia Russian Presidental Academy of National Economy and Public Administration Department of Mathematics and Information Technologies in Management Moscow Russia

ISBN: (纸本)9781665439817

the article is devoted to solving the problems of synthesis of algorithmic support of the decision support system for the controlled destruction of resin vulcanizates of butyl rubber. As an object of research, the destruction processes have been selected, which are carried out by combining external destructive factors: ionization irradiation and subsequent thermomechanical treatment. Based on the results of the system analysis of the destruction process stages as control objects, the main and cross system connections between the input, internal parameters of the process and the physical properties of the final product have been revealed. The most preferred channels for controlling the rate of physical and chemical processes occurring during destruction have been selected. Using a combination of control actions, a method and an algorithm for controlling the stages of destruction has been proposed, which allows for programmed control of the operating parameters of the process to obtain reclaimed butyl rubber with target quality indicators. The structural synthesis of the mathematical support of the decision support system, which calculates the optimal values of the process parameters in accordance with the formed search criteria, has been carried out. An algorithm for controlling the destruction process has been developed, which calculates the optimal parameters of the process using the mathematical tools, which includes the Choquet integral, the Sugeno fuzzy measure, and a genetic algorithm for solving optimization problems. © 2021 IEEE.

关键词： Irradiation

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Intelligent Autonomous-Robot control for Medical Applications

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Computers, Materials & Continua 2021年第8期68卷 2189-2203页

作者： Rihem Farkh Haykel Marouani Khaled Al Jaloud Saad Alhuwaimel Mohammad Tabrez Quasim Yasser Fouad College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Laboratory for Analysis Conception and Control of SystemsDepartment of Electrical EngineeringNational Engineering School of TunisTunis El Manar University1002Tunisia King Abdulaziz City for Science and Technology Riyadh12354Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

The COVID-19 pandemic has shown that there is a lack of healthcare facilities to cope with a *** has also underscored the immediate need to rapidly develop hospitals capable of dealing with infectious patients and to rapidly change in supply lines to manufacture the prescription goods(including medicines)that is needed to prevent infection and treatment for infected *** COVID-19 has shown the utility of intelligent autonomous robots that assist human efforts to combat a *** artificial intelligence based on neural networks and deep learning can help to fight COVID-19 in many ways,particularly in the control of autonomous medic *** officials aim to curb the spread of COVID-19 among medical,nursing staff and patients by using intelligent *** propose an advanced controller for a service robot to be used in *** type of robot is deployed to deliver food and dispense medications to individual *** autonomous line-follower robot that can sense and follow a line drawn on the floor and drive through the rooms of patients with control of its *** criteria were met by using two controllers simultaneously:a deep neural network controller to predict the trajectory of movement and a proportional-integral-derivative(PID)controller for automatic steering and speed control.

关键词： Autonomous medic robots PID control neural network control system real-time implementation navigation environment differential drive system

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An Improved Machine Learning Technique with Effective Heart Disease Prediction System

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Computers, Materials & Continua 2021年第12期69卷 4169-4181页

作者： Mohammad Tabrez Quasim Saad Alhuwaimel Asadullah Shaikh Yousef Asiri Khairan Rajab Rihem Farkh Khaled Al Jaloud College of Computing and Information Technology University of BishaBisha67714Saudi Arabia King Abdulaziz City for Science and Technology P.O.Box 6086Riyadh11442Saudi Arabia College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Department of Electrical Engineering Laboratory for AnalysisConception and Control of SystemsLR-11-ES20National Engineering School of TunisTunis El Manar University1002Tunisia

Heart disease is the leading cause of death *** heart disease is challenging because it requires substantial experience and *** research studies have found that the diagnostic accuracy of heart disease is *** coronary heart disorder determines the state that influences the heart valves,causing heart *** indications of coronary heart disorder are strep throat with a red persistent skin rash,and a sore throat covered by tonsils or strep *** work focuses on a hybrid machine learning algorithm that helps predict heart attacks and arterial *** first,we achieved the component perception measured by using a hybrid cuckoo search particle swarm optimization(CSPSO)*** this perception measure,characterization and accuracy were improved,while the execution time of the proposed model was *** CSPSO-deep recurrent neural network algorithm resolved issues that state-of-the-art methods *** proposed method offers an illustrative framework that helps predict heart attacks with high *** proposed technique demonstrates the model accuracy,which reached 0.97 with the applied dataset.

关键词： Machine learning deep recurrent neural network effective heart disease prediction framework

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning 22

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Cao, Weipeng Yao, Xuyang Xu, Zhiwu Pan, Yinghui Sun, Yixuan Li, Dachuan Qiu, Bohua Wei, Muheng Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9798331527471

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model’s capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods. © 2024 IEEE.

关键词： Zero-shot learning

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Classification of information Objects with Fuzzy Parameters in E-Learning systems

Classification of Information Objects with Fuzzy Parameters ...

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IEEE International Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications

作者： Vadym Mukhin Valerii Zavgorodnii Viacheslav Liskin Sergiy Syrota Vasyl Koval Liudmyla Honchar Department of System Design National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kiev Ukraine Department of Information Systems and Technologies National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kiev Ukraine Department of Applied Mathematics National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kiev Ukraine Department of Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine Department of Computer Science West Ukrainian National University Ternopil Ukraine

The paper describes the process of the information objects classification in e-learning systems using the mathematical background of fuzzy logic. This approach can be used to improve the process of searching and organizing information in e-learning systems. As the volume of educational materials grows, it becomes more and more difficult to find and structure information. Fuzzy logic helps to optimize the search, and the use of a neural network can correctly classify materials in e-learning systems, which increases the efficiency and accuracy of search queries.

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