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检索条件"机构=dept. Science and Technology on Complex System Control"

共 76 条记录，以下是1-10 订阅

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

引用

1st International Conference on Robotics, Engineering, science, and technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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Optimization Scheduling of Multi-Energy Microgrid Based on the QUBO Quantum Computing Model 19th

Optimization Scheduling of Multi-Energy Microgrid Based on t...

引用

19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Baonan Wang, Hui Zhang, Dan College of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9789819608966

Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization scheduling method for multi-energy microgrids based on the QUBO (Quadratic Unconstrained Binary Optimization) quantum computing model is proposed in this paper, alongside a discretization approach based on a grid partitioning strategy. To validate the feasibility of addressing microgrid optimization scheduling problems in a quantum computing environment, a QUBO model is constructed and simulation studies are conducted in the qbsolv environment provided by D-Wave. The results indicate that operational costs are significantly reduced with an increase in the number of grids, particularly a reduction of 4.52% when the number of grids increases from five to ten. This method not only effectively enhances the precision of electricity supply and energy utilization efficiency but also reduces unnecessary electrical waste and economic costs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Microgrids

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A Review of Rotation Mechanical Fault Diagnosis Research Based on Deep Domain Adaptation 9

A Review of Rotation Mechanical Fault Diagnosis Research Bas...

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9th IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2023

作者： Zhang, Shun Xie, Gang Tian, Juan Shi, Hui Zhang, Xiaohong Nie, Xiaoyin Xie, Xinlin Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China Taiyuan University of Science and Technology Dept. of Electronic and Information Engineering Taiyuan China Division of Industrial and System Engineering Taiyuan China

ISBN: (纸本)9798350333794

With the rapid development of computer technology and the Internet of Things (IoT), a large amount of data containing both healthy and faulty states can be collected from existing devices in factories. However, the usable faulty state data is scarce. Transfer learning makes it possible to train efficient and reliable neural networks with a small number of samples. Domain adaptation, as a branch of transfer learning, can effectively realize knowledge transfer between small sample data. Starting from three subcategories of deep learning-based domain adaptation methods, this article summarizes the latest research achievements and provides insights into future research directions. © 2023 IEEE.

关键词： Failure analysis

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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Robotics, Engineering, science, and technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

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A GAN-LSTM Architecture for ECG Anomaly Detection

A GAN-LSTM Architecture for ECG Anomaly Detection

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Electrical, Computer, Telecommunication and Energy Technologies (ECTE-Tech), International Conference on

作者： Soumia OUBADI Naçima MELLAL Rachida BOUCHOUAREB Soumia ZERTAL dept. Computer science Research Laboratory on Computer Science's and Complex System University of Oum El Bouaghi Algeria dept. Networks and telecommunication Research Laboratory of Artificial Intelligence and Autonomous Objects Institute of Applied Science & Technology University of Oum El Bouaghi Algeria dept. Computer science Research Laboratory of Artificial Intelligence and Autonomous Objects University of Oum El Bouaghi Algeria

ISBN: (数字)9798350388480

ISBN: (纸本)9798350388497

Cardiovascular diseases (CVDs) continue to be a primary cause of global mortality, requiring prompt detection and care to avert serious consequences. Electrocardiograms (ECGs) are vital diagnostic instruments for cardiovascular disorders, yet traditional diagnostic methods encounter considerable obstacles, such as class imbalance and substantial heterogeneity in the available data. This study introduces a novel ECG classification technique utilizing GAN and LSTM. Generative Adversarial Networks (GANs) are employed to produce additional synthetic ECG samples, addressing class imbalance in the training dataset. The suggested design integrates LSTM units into the GAN generator to collect and maintain temporal signal patterns, while anomaly detection is performed using a CNN-LSTM model. Experimental findings indicate a significant enhancement in classification performance, achieving an accuracy of up to 94.74%. The findings indicate that the proposed GAN-LSTM model significantly improves ECG anomaly detection and classification, offering substantial potential for the rapid and precise identification of arrhythmias.

关键词： Training Instruments Mortality Computer architecture Electrocardiography Generative adversarial networks Real-time systems Convolutional neural networks Anomaly detection Long short term memory

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Applying Predictive Machine Learning Algorithms to Petroleum Refining Processes as Part of Intelligent Automation 23

Applying Predictive Machine Learning Algorithms to Petroleum...

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23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

作者： Nekrasov, Ivan S. Tynchenko, Vadim S. Bukhtoyarov, Vladimir B. Kachaeva, Vera A. Bashmur, Kirill A. Sinitskaya, Aleksandra E. Siberian Federal Univercity Laboratory of Biofuel Composition Krasnoyarsk Russia Siberian Federal Univercity Dept. of Technological Machines and Equipment of Oil and Gas Complex Krasnoyarsk Russia Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Information-Control Systems Department Krasnoyarsk Russia

ISBN: (纸本)9781665498043

Intelligent automation is a term that can be applied to the more complex field of workflow automation, consisting of robotic workplace automation, robotic process automation, machine learning, and artificial intelligence. Depending on the type of business, companies often use one or more types of automation to improve efficiency or effectiveness. As you move from process-driven automation to more flexible data-driven automation, additional costs arise in the form of training datasets, technical development, infrastructure, and expertise. But the potential benefits in terms of new ideas and financial development can increase significantly. The development of mechanized oil production in recent years has been accompanied by significant achievements in the field of digitalization. Machine learning, as an important element of digitalization, can successfully solve many production problems. The paper describes the application of some machine learning algorithms for solving the problem of classifying and predicting failures of hydrocracking process equipment that occur during oil refining and diesel fuel production. The application of random forest, principal component analysis and hyperparameter tuning methods is considered. The effectiveness of their application is compared. © 2022 IEEE.

关键词： Decision trees

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A Review of Rotation Mechanical Fault Diagnosis Research Based on Deep Domain Adaptation

A Review of Rotation Mechanical Fault Diagnosis Research Bas...

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IEEE International Conference on Big Data Computing Service and Applications (BigDataService)

作者： Shun Zhang Gang Xie Juan Tian Hui Shi Xiaohong Zhang Xiaoyin Nie Xinlin Xie Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China dept. of Electronic and Information Engineering Taiyuan University of Science and Technology Taiyuan China Division of Industrial and System Engineering Taiyuan China

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Design and implementation of a global smart box for quadcopter delivery system 3

Design and implementation of a global smart box for quadcopt...

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3rd International Conference on Intelligent Sustainable systems, ICISS 2020

作者： Abdulkareem Alawsi, Ahmed Abdulmahdi Jasim, Basil H Raafat, Safanah Mudheher University of Wasit College of Science Physics Dept. Iraq University of Basra Electrical Engineering Dept. Iraq University of Technology Control and System Engineering Dept. Iraq

ISBN: (纸本)9781728170893

Recently, delivery by quadcopter has become an increasingly popular application. Nevertheless, there are some problems and constraints. The Last Mile Problem (LMP), which involves several challenges, represents a serious problem and limitation to use the quadcopter in the delivery process. LMP which addresses several challenges is the main limitation in the delivery by quadrotor. This problem is exacerbated in densely populated cities, especially in residential complexes with multi levels buildings where there is no private and safe area for the customer to receive his parcels. To our knowledge, only partial solution has been addressed to solve this problem in literature. A new global smart box (GSB) is proposed in this paper to solve LMP. The GSBs can be networked with central controller via internet to manage them by multi simple delivery services offices distributed near from or inside trading complexes. The results got in this paper show that the GSB is reliable and solve most LMP sub problems like saving parcel, saving quadcopter, double maximum delivery distance, calculate best delivery paths, easy to perform optimal management algorithms, and decrease the cost of delivery. © 2020 IEEE.

关键词： Autonomous flight Delivery by Quadcopter Double delivery distance and Delivery cost by quadcopter Last Mile Problem

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On the role of shape features in metaphor generation for abstract images

On the role of shape features in metaphor generation for abs...

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International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Asuka Terai Natsuki Yamamura Junichi Chikazoe Takaaki Yoshimoto Norihiro Sadato Koji Jimura Dept. of Complex and Intelligent Systems Future University Hakodate Hokkaido Japan Research and Development Dept Araya Inc Tokyo Japan Res. Org. of Science and Technology Ritsumeikan University Kyoto Japan Dept. of System Neuroscience National Institute for Physiological Sciences Aichi Japan Dept. of Informatics Gunma University Gunma Japan

In this study, we examined the role of shape features on metaphor generation for abstract images based on a simulation with a retrained convolutional neural network (CNN), which is in turn based on a pretrained CNN model (AlexNet). A computational experiment was conducted using three types of object recognition models, including a pretrained object recognition model (AlexNet) and recognition models that were retrained to recognize more or fewer shape features using edge-detected or blurred images from the ILSVRC-2012 dataset. A psychological experiment was conducted to collect metaphors that were used to explain the abstract images. The simulation results of the models for the abstract images were compared to examine how well they predicted the concepts used in the metaphors generated for the abstract images. The results of the computational experiment suggest that the model retrained to recognize fewer shape features performed best at predicting the generated metaphors. However, for some abstract images, the model retrained to recognize more shape features performed better. These results suggest that the role of shape features on metaphor generation differs depending on the types of abstract images.

关键词： Shape Image color analysis Image edge detection Computational modeling Simulation Psychology Predictive models

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Economic Equilibrium with Random Transactions 2

Economic Equilibrium with Random Transactions

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2nd International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2020

作者： Zhukova, Aleksandra Pospelov, Igor G. Moscow Institue of Physics and Technology Federal Research Center Computer Science and Control of Ras Dept. of Mathematical Modelling of Economic Systems Dept. of Mathematical Modelling of Complex Systems and Optimization Dept of Theoretical Economics Moscow Russia

ISBN: (纸本)9781728188409

This paper presents the advances in modelling the system of agents under the conditions of random transactions between them. We face certain challenges in this project which we would like to highlight in this presentation. The agents in the modelled system are a large number of consumers, a large number of producers and the bank as the intermediary. Consumers take loans from the bank to spend on consumption goods and producers borrow to make investment at random moments of time. The moments of time the agents deal form the Poisson flow. We present the approach to agents' optimal control problems by the Lagrange method instead of dynamic programming. This enables us obtaining the expressions for the optimal feedback control which appear to be linear in state variables. The solution to the optimal control problems are obtained using asymptotic methods assuming large frequency of transactions. Using the linearity of the agents' optimal control, we may aggregate description of agents, stock-flow consistent on the average. Instead of an ensemble of independent random transactions by agents, the description of the aggregate dynamics is deterministic. The system of equations for the aggregate dynamics is reduced to one equation. There are two cases of this equation, depending on the description of the bank. The equation has a specific form, its numerical analysis is challenging. We provide numerical results and discuss further directions of research. © 2020 IEEE.

关键词： Random processes

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