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Three-dimensional tracking and height verification of polystyrene particles with piezo actuator positioning by means of multi-wavelength evanescent fields 20

Three-dimensional tracking and height verification of polyst...

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20th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2020

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Permpatdechakul, Thitipat Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9780995775176

To understand the nanoparticle motion behaviours on a surface, we have studied to investigate the three-dimension tracking of an individual nanoparticle with nanometre localisation accuracy. In three-dimensional nanoparticle moving position, the X and Y coordinates are on the parallel plane to the surface, which their coordinates can be tracked in general microscopy. However, the Z coordinate is the nanoparticle height position perpendicularly to the surface plane, which could not be generally tracked without longitudinal scanning method. In this paper, the polystyrene 100 nm standard particles were used to investigate the three-dimensional tracking. The individual standard nanoparticles were fixed on the tip, which was vertically travelled with the piezo actuator for movement control on the third dimension to verify the actual height Z. Our developed optical microscopy apparatus has been applying multi-wavelength evanescent fields, and obtaining multi scattering light intensities from the observed nanoparticles near to surface. Commonly, the X and Y coordinates of nanoparticle were determined by the centre of mass of each scattering light intensity. The height Z was investigated from the integration of the detected scattering intensities of each wavelength. By using our method, the height Z uncertainty could be measured approximately less than ±20 nm, and the penetration height measurability was approximately 250 nm far from the reference surface. Consequently, we could three-dimensionally track the individual standard nanoparticle in recording speed higher than 50 frames per second. Copyright © Proceedings of the 20th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2020. All rights reserved.

关键词： Nanoparticles

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Context-aware Emotion Recognition Based on Vision-Language Pre-trained Model

Context-aware Emotion Recognition Based on Vision-Language P...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： XingLin Li Xinde Li Chuanfei Hu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Given the difficulty of recognizing ambiguous emotions in facial expression recognition tasks, we propose a visual-language model named CAER-CLIP to address this challenge. The proposed CAER-CLIP standed for Context-Aware Emotion Recognition (CAER), and were incorporated structure of the Contrastive Language–Image Pre-training (CLIP) model as promising alternative to classifier. There are two parts in CAER-CLIP model. In the visual part, facial expressions and contextual information of the image are simultaneously extracted to obtain the final feature embeddings, which are then used as a learnable “class” token for text-image pairing with desired module. In the textual part, we use text labels for emotion recognition classes as input. The outputs were merged to participate the comparative study to generated parameters of the model. The experiments demonstrate the effectiveness of the proposed method and show that our CAER-CLIP outperforms the state-of-the-art results on the CAER benchmark. The ablation experiment verified the effectiveness of both the classifier-based and text-based (ours without classifier) models, demonstrating that our method with the CAER-CLIP structure performed better, and the incorporation of a text encoder in the deep network model architecture effectively enhancing recognition accuracy.

关键词： Training Emotion recognition Visualization Accuracy Text recognition Face recognition Benchmark testing Feature extraction Data mining Context modeling

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A Cyclic Small Phase Theorem

arXiv

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arXiv 2023年

作者： Chen, Chao Chen, Wei Zhao, Di Chen, Jianqi Qiu, Li KU Leuven Leuven3001 Belgium The Department of Mechanics and Engineering Science State Key Laboratory for Turbulence and Complex Systems Peking University Beijing100871 China The Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

This paper introduces a brand-new phase definition called the segmental phase for multi-input multi-output linear time-invariant systems. The underpinning of the definition lies in the matrix segmental phase which, as its name implies, is graphically based on the smallest circular segment covering the matrix normalized numerical range in the unit disk. The matrix segmental phase has the crucial product eigen-phase bound, which makes itself stand out from several existing phase notions in the literature. The proposed bound paves the way for stability analysis of a cyclic feedback system consisting of multiple subsystems. A cyclic small phase theorem is then established as our main result, which requires the loop system phase to lie between −π and π. The proposed theorem complements a cyclic version of the celebrated small gain theorem. In addition, a generalization of the proposed theorem is made via the use of angular scaling techniques for reducing conservatism. Copyright © 2023, The Authors. All rights reserved.

关键词： Linear time-invariant system

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Advance Artificial Intelligence Technique for Designing Double T-Shaped Monopole Antenna

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computers, Materials & Continua 2021年第12期69卷 2983-2995页

作者： El-Sayed M.El-kenawy Hattan F.Abutarboush Ali Wagdy Mohamed Abdelhameed Ibrahim Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina 42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza 12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Machine learning(ML)has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design *** is a massive area within artificial intelligence(AI)that focuses on obtaining valuable information out of data,explaining why ML has often been related to stats and data *** advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture *** algorithm is designed,depending on the hybrid between the Sine Cosine Algorithm(SCA)and the Grey Wolf Optimizer(GWO),to train neural networkbased Multilayer Perceptron(MLP).The proposed optimization algorithm is a practical,versatile,and trustworthy platform to recognize the design parameters in an optimal way for an endorsement double T-shaped monopole *** proposed algorithm likewise shows a comparative and statistical analysis by different curves in addition to the ANOVA and *** offers the superiority and validation stability evaluation of the predicted results to verify the procedures’accuracy.

关键词： Antenna optimization machine learning artificial intelligence multilayer perceptron sine cosine algorithm grey wolf optimizer

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Learning nonlinear feedforward: a Gaussian Process Approach Applied to a Printer with Friction

arXiv

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arXiv 2021年

作者： van Meer, Max Poot, Maurice Portegies, Jim Oomen, Tom The Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands The Delft Center for Systems and Control Delft University of Technology Delft Netherlands The Applied Analysis Group Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands

Feedforward control is essential to achieving good tracking performance in positioning systems. The aim of this paper is to develop an identification strategy for inverse models of systems with nonlinear dynamics of unknown structure using input-output data, which directly delivers feedforward signals for a-priori unknown tasks. To this end, inverse systems are regarded as noncausal nonlinear finite impulse response (NFIR) systems, and modeled as a Gaussian Process with a stationary kernel function that imposes properties such as smoothness and periodicity. The approach is validated experimentally on a consumer printer with friction and shown to lead to improved tracking performance with respect to linear feedforward. Copyright © 2021, The Authors. All rights reserved.

关键词： Friction

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Quantized Distributed Nonconvex Optimization Algorithms with Linear Convergence under the Polyak–Lojasiewicz Condition

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IEEE Transactions on Automatic control 2025年

作者： Xu, Lei Yi, Xinlei Sun, Jiayue Shi, Yang Johansson, Karl H. Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 2Y2 Canada Tongji University Shanghai Institute of Intelligent Science and Technology Shanghai201804 China KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden

This paper considers distributed optimization for minimizing the average of local nonconvex cost functions, by using local information exchange over undirected communication networks. To reduce the required communication capacity, we introduce an encoder–decoder scheme. By integrating it with distributed gradient tracking and proportional integral algorithms, respectively, we then propose two quantized distributed nonconvex optimization algorithms. Assuming the global cost function satisfies the Polyak–Lojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that our proposed algorithms linearly converge to a global optimal point. Moreover, we show that a low data rate is sufficient to guarantee linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical examples. © 1963-2012 IEEE.

关键词： Cost functions

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The New Concept of Guaranteeing Confidence in the E-Voting System

The New Concept of Guaranteeing Confidence in the E-Voting S...

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2020 IEEE International Conference on Problems of Infocommunications Science and technology, PIC S and T 2020

作者： Khlaponin, Yurii Vyshniakov, Volodymyr Prygara, Mykhailo Poltorak, Vadym Kyiv National University of Construction and Architecture Cybersecurity and Computer Engineering Department Kyiv Ukraine National University Machine Industry Technology Department Uzhhorod Uzhhorod Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Technical Systems Automation and Control Kyiv Ukraine

ISBN: (纸本)9781728191775

There is no doubt about the urgency of ensuring trust in e-voting systems since elections without trust cannot be acceptable in a democratic society. To solve this problem, it was proposed to use blockchain technology, however, in voting systems this leads to significant delays in the execution of transactions, and the software solution is accessible only to a narrow circle of specialists, which clearly does not help to show confidence on the part of voters. This paper proposes a different approach, which is based on the widely available verification of all means and processes that may cause distrust in the accuracy of the vote count or in ensuring their confidentiality. We offer a solution to the problem of transparency of all hardware and software that cause distrust. Voting systems that use this approach are implemented in three leading Ukrainian universities for student elections to self-government bodies. The conceptual model of the e-voting system for state elections on the example of Ukraine is presented. Links to Internet resources are provided where you can not only get acquainted with the principles of building the system, but also conduct an experimental vote in Ukrainian, English or Russian. You can also copy and test e-voting server software on your computers. © 2020 IEEE.

关键词： Transparency

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Robust Data-Driven Predictive control of Unknown Nonlinear systems using Reachability Analysis

arXiv

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arXiv 2022年

作者： Farjadnia, Mahsa Alanwar, Amr Niazi, Muhammad Umar B. Molinari, Marco Johansson, Karl Henrik Department of Energy Technology School of Industrial Engineering and Management KTH Royal Institute of Technology Stockholm Sweden School of Computer Science and Engineering Constructor University Bremen Germany Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge United States

This work proposes a robust data-driven predictive control approach for unknown nonlinear systems in the presence of bounded process and measurement noise. Data-driven reachable sets are employed for the controller design instead of using an explicit nonlinear system model. Although the process and measurement noise are bounded, the statistical properties of the noise are not required to be known. By using the past noisy input-output data in the learning phase, we propose a novel method to over-approximate exact reachable sets of an unknown nonlinear system. Then, we propose a data-driven predictive control approach to compute safe and robust control policies from noisy online data. The constraints are guaranteed in the control phase with robust safety margins by effectively using the predicted output reachable set obtained in the learning phase. Finally, a numerical example validates the efficacy of the proposed approach and demonstrates comparable performance with a model-based predictive control approach. Copyright © 2022, The Authors. All rights reserved.

关键词： Nonlinear systems

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AR Intelligent Real-time Method for Cultural Heritage Object Recognition

AR Intelligent Real-time Method for Cultural Heritage Object...

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International Conference on Advanced Information and Communication Technologies (AICT)

作者： Oleh Pisnyi Ivan Kit Khrystyna Lipianina-Honcharenko Jürgen Sieck Anatoliy Sachenko Maciej Dobrowolski Grygoriy Sapozhnyk Master's degree in Computer Science West Ukrainian National University Ternopil Ukraine Department for Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine Hochschule für Technik und Wirtschaft Berlin Berlin Germany Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland

In a world of rapid technological changes and growing interest in cultural heritage, the development of innovative tools for travelers and history enthusiasts becomes incredibly important. Even in the digital age, interactive ways of exploring historical landmarks remain relevant and attractive. In this research, an AR Intelligent Real-time Method for Cultural Heritage Object Recognition has been developed. The method is implemented through a chatbot, which, when using a smartphone's camera, recognizes objects of cultural heritage and provides descriptions of these objects. The chatbot opens up new possibilities for travelers, allowing them to enjoy history and cultural heritage using intelligent tools and augmented reality.

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Plate Shape Prediction Based on Data-Driven in Roll Quenching Process

Plate Shape Prediction Based on Data-Driven in Roll Quenchin...

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Chinese Automation Congress (CAC)

作者： Liu Hu Luefeng Chen Jie Hu Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and the Engineering Research Center of Intelligent Technology for Geo-Exploration School of Automation Ministry of Education China University of Geosciences Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland The Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey Tokyo Institute of Technology Yokohama Japan The Tokyo Institute of Technology Tokyo Japan

In the process of steel plate production, predicting the plate shape is of great significance for producing high-quality and consistently stable plate shapes. This paper presents a model that predicts both the defect types and flatness of the plate, providing theoretical support for setting process parameters in roller quenching production. First, the parameters of the quenching process are analyzed to identify their characteristics. Then, the K-Means clustering algorithm and correlation analysis are employed to process the quenching process parameters. A gradient boosting decision tree (GBDT) model is used to predict the defect types and flatness of the steel plates. Finally, industrial production data is utilized for experimental validation. The obtained experimental results verify the reliability of the proposed method.

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