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Absolute longitudinal distance measurement verification of a standard polystyrene nanoparticle near a surface in water by means of multi-wavelength evanescent field 22

Absolute longitudinal distance measurement verification of a...

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22nd International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2022

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Baba, Akiyoshi Goto, Daiki Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan Center of Microelectronic System Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

In the wet semiconductor process, abrasive nanoparticles are widely used in the chemical mechanical polishing (CMP) process to polish wafer surfaces for high planarization. During polishing, nanoparticles move with a high-speed three-dimensional (3D) position in the solution. In the 3D particles's moving positions, Z is a perpendicular longitudinal distance between the surface to the nanoparticle that plays a significant role in polishing, which could not be measured by general microscopy without longitudinal scanning. To understand nanoparticle phenomena near-surface, we have proposed and developed the apparatus with real-time fastmotion tracking on optical multi-wavelength evanescent fields microscopy to measure the 3D motion of the nanoparticle in water without scanning. In euspen's 2020, we could verify the relative distance ?Z of nanoparticles in water, but the absolute distance Z is unknown yet. In this manuscript, we have therefore developed an invisible nano-step height in water to verify the absolute height Z of an individual nanoparticle. The invisible nano-step height in water is made from an optical resin with a refractive index of 1.35 that is close to a refractive index of water to avoid unnecessary light during experimental verification. The nano-step height was less than 100 nm on a glass surface, fabricated using nanoimprint lithography. Polystyrene f100 nm standard particles in water were used to verify the height Z. The results of height Z of nanoparticles could be measured less than 100 nm with the measurement uncertainty ±10 nm (2s), which is related to the interferometer result of the nano-step height. © European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Nanoparticles

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Improved Prediction of Metamaterial Antenna Bandwidth Using Adaptive Optimization of LSTM

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computers, Materials & Continua 2022年第10期73卷 865-881页

作者： Doaa Sami Khafaga Amel Ali Alhussan El-Sayed M.El-kenawy Abdelhameed Ibrahim Said H.Abd Elkhalik Shady Y.El-Mashad Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Systems Engineering Faculty of Engineering at ShoubraBenha UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended *** this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial *** proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep *** optimized network is used to retrieve the metamaterial bandwidth given a set of *** addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.

关键词： Metamaterial antenna long short term memory(LSTM) guided whale optimization algorithm(Guided WOA) adaptive dynamic particle swarm algorithm(AD-PSO)

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Human-Robot Collaboration using Monte Carlo Tree Search

Human-Robot Collaboration using Monte Carlo Tree Search

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2022 International Conference on Automation, Robotics and computer Engineering, ICARCE 2022

作者： Yao, Feng Zhao, Huailin Liu, Huaping Shanghai Institute of Technology University Graduate School of Control Science and Engineering Shanghai China Tsinghua University Department of Computer Department Beijing China

ISBN: (纸本)9781665475488

Human-Robot collaboration as a challenging task has received great attention in the academic research field. Many existing search models are aimed at single agent or multi-agent, but there are some defects in the search efficiency of their task targets. Therefore, we propose a human-computer cooperative search algorithm in the indoor scene, where people and agents cooperate to complete the search of related objects. We have developed a platform for human-robot collaboration, and designed a set of algorithms for agent to integrate scene prior knowledge, target recognition, and path planning. The experimental results that the H-R cooperative search model proposed by us shows good efficiency in target search tasks. © 2022 IEEE.

关键词： Motion planning

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PSRMER: Proactive Services Recommendation Driven-by Multimodal Emotion Recognition

PSRMER: Proactive Services Recommendation Driven-by Multimod...

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IEEE International Conference on Web Services (ICWS)

作者： Zhizhong Liu Guangyu Huang Dianhui Chu Yuhang Sun School of Computer and Control Engineering Yantai University Yantai China School of Computer Science and Technology Harbin Institute of Technology Weihai China

In the past three years, global COVID-19 pandemic not only impacted people’s physical health but also significantly affected their mental health, which resulting in rapid increase of psychological problems. Emotions are a common manifestation of psychological changes, and some services (such as music, video, or psychological counseling services) can help users to adjust their emotions in a timely manner, thus to avoid bringing extreme events (e.g., running away from home or committing suicide). Therefore, how to perceive users’ real-time emotions and then recommend the most appropriate services to users has become a challenge. To address this issue, this work proposes an approach for proactive services recommendation driven-by multimodal emotion recognition (named as PSRMER). Specifically, PSRMER first actively identifies a user’s emotion with a multimodal emotion recognition model based on BiGRU and Transformer; Then, considering the user’s emotion and preferences, PSRMER selects the optimal services based on an index-graph linking different emotions and various services; Finally, PSRMER proactively recommends the selected optimal service to the user. Extensive experiments have been conducted and the effectiveness of our proposed method have been proved. Moreover, the proposed method can also be used in smart education, smart transportation, smart elderly care and other modern industry fields.

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Named Entity Recognition for Safety Risks in Electrical Work

Named Entity Recognition for Safety Risks in Electrical Work

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2024 IEEE International Conference on Imaging Systems and Techniques, IST 2024

作者： Liu, Peng Fan, Shanshan Cao, Xiaofan Jia, Yujiao Yang, Jianing Institute of Energy and Electrical Engineering Changchun University of Science and Technology Changchun China School of Control and Computer Engineering North China Electric Power University Beijing China School of Electrical Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798350378214

The texts of safety risks in eletrical work describe the safety risks involved and management measures. The text records information on potential risks, risk levels, and preventive measures within the electrical work, which is crucial for extracting and mining safety risks. Named Entity Recognition for Safety Risks in Electrical Work (EWSR-NER) is a key technique for information extraction and knowledge discovery. It identifies objects related to safety risks in electrical work, such as risk level, risk factors, risk categories and protective measures, which convey critical meanings within the text. Current Named Entity Recognition (NER) is used to identify generic entities. However, their accuracy is limited by inherent linguistic irregularities in natural language texts, such as nested entities, lengthy entities, and the scarcity of domain-specific annotated corpora. To address this issue, the established standards and principles of safety risk texts in electrical work were followed to analyze the structure and characteristics of the text, developing a dataset of safety risk in electrical work. A new model, RoBERTa-BiLSTM-Efficient GlobalPointer (RoBEGP), was proposed in this paper. It uses the Robertly Optimized Bidirectional Encoder Representation from Transformers Pretraining Approach(RoBERTa) pretraining model to learn the characteristics of electrical work content and generate representation vectors. These representation vectors are input into a dynamic fusion layer, which adjusts the weights of each layer's representation vectors based on the specific requirements of the task, reducing the dimensionality from 1024 to 512. The fused vectors are input into a Bidirectional Long Short-Term Memory(BiLSTM) network to generate feature representations. Efficient GlobalPointer decodes these representations to identify nested entities within the text. Experimental results show that the proposed model achieves an F1 score of 92.38% on a self-constructed dataset of safe

关键词： Risk assessment

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Observer-Based control of Second-Order Multi-vehicle Systems in Bearing-Persistently Exciting Formations 63

Observer-Based Control of Second-Order Multi-vehicle Systems...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Tang, Zhiqi Fidan, Baris Johansson, Karl H. Martensson, Jonas Hamel, Tarek Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-10044 Sweden University of Waterloo Mechanical and Mechatronics Engineering Department ON Canada I3S-UCA Cnrs France

ISBN: (纸本)9798350316339

This paper proposes an observer-based formation tracking control approach for multi-vehicle systems with second-order motion dynamics, assuming that vehicles' relative or global position and velocity measurements are unavailable. It is assumed that all vehicles are equipped with sensors capable of sensing the bearings relative to neighboring vehicles and only one leader vehicle has access to its global position. Each vehicle estimates its absolute position and velocity using relative bearing measurements and the estimates of neighboring vehicles received over a communication network. A distributed observer-based controller is designed, relying only on bearing and acceleration measurements. This work further explores the concept of the Bearing Persistently Exciting (BPE) formation by proposing new algorithms for bearing-based localization and state estimation of second-order systems in centralized and decentralized manners. It also examines conditions on the desired formation to guarantee the exponential stability of distributed observer-based formation tracking controllers. In support of our theoretical results, some simulation results are presented to illustrate the performance of the proposed observers as well as the observer-based tracking controllers. © 2024 IEEE.

关键词： Acceleration measurement

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The Research on Sheet Metal Part Recognition technology Based on Improved Mask R-CNN 5

The Research on Sheet Metal Part Recognition Technology Base...

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5th International Conference on Machine Learning and computer Application, ICMLCA 2024

作者： Liu, Mingfei Liu, Jun Zhou, Kecheng Wang, Jian School of Computer Science and Technology Shenyang University of Chemical Technology Key Laboratory of Industrial Intelligence Technology on Chemical Process Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9798331530334

The visual recognition of sheet metal parts is a crucial component of industrial automation sorting, particularly under complex lighting and background interference conditions. To enhance the accuracy of sheet metal part recognition, this paper curates a dataset of sheet metal parts acquired by an intelligent light field image sensor and proposes a visual recognition model, PA-CBAM, based on an improved Mask R-CNN. By improving the original feature pyramid FPN and introducing the Convolutional Block Attention Module (CBAM), the model enhances multi-scale feature fusion and the focus on key features: (1) Bottom up paths and shortcut connections have been added between different layers of the traditional FPN feature pyramid, thereby improving multi-scale object detection capability. (2) CBAM further optimizes the model's channel and spatial attention mechanisms, effectively enhancing the capture of edge details and the suppression of background noise. Experimental results show that the proposed PA-CBAM model significantly improves detection and segmentation performance compared to traditional methods, particularly in terms of edge recognition accuracy for sheet metal parts under complex lighting conditions. © 2024 IEEE.

关键词： Sheet metal

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Sustainable Mining in the Era of Artificial Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 1-4页

作者： Long Chen Yuting Xie Yutong Wang Shirong Ge Fei-Yue Wang IEEE the State Key Laboratory for Management and Control of Complex Systems at the Institute of Automation Chinese Academy of SciencesBeijing 100190China the National Laboratory of Pattern Recognition at the Institute of Automation and Waytous Ltd.China the School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275GuangdongChina the School of Mechanical Electronic and Information Engineering China University of Mining and Technology BeijingBejing 100083China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread ***-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

关键词： Sustainable mining consequences

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Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach

arXiv

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arXiv 2023年

作者： Ramkannan, Rishi Beintema, Gerben I. Tóth, Roland Schoukens, Maarten Control System Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

The SUBNET neural network architecture has been developed to identify nonlinear state-space models from input-output data. To achieve this, it combines the rolled-out nonlinear state-space equations and a state encoder function, both parameterised as neural networks The encoder function is introduced to reconstruct the current state from past input-output data. Hence, it enables the forward simulation of the rolled-out state-space model. While this approach has shown to provide high-accuracy and consistent model estimation, its convergence can be significantly improved by efficient initialization of the training process. This paper focuses on such an initialisation of the subspace encoder approach using the Best Linear Approximation (BLA). Using the BLA provided state-space matrices and its associated reconstructability map, both the state-transition part of the network and the encoder are initialized. The performance of the improved initialisation scheme is evaluated on a Wiener-Hammerstein simulation example and a benchmark dataset. The results show that for a weakly nonlinear system, the proposed initialisation based on the linear reconstructability map results in a faster convergence and a better model quality. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Finite Dimensional Koopman Form of Polynomial Nonlinear Systems

arXiv

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arXiv 2023年

作者： Iacob, Lucian Cristian Schoukens, Maarten Tóth, Roland Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

The Koopman framework is a popular approach to transform a finite dimensional nonlinear system into an infinite dimensional, but linear model through a lifting process, using so-called observable functions. While there is an extensive theory on infinite dimensional representations in the operator sense, there are few constructive results on how to select the observables to realize them. When it comes to the possibility of finite Koopman representations, which are highly important form a practical point of view, there is no constructive theory. Hence, in practice, often a data-based method and ad-hoc choice of the observable functions is used. When truncating to a finite number of basis, there is also no clear indication of the introduced approximation error. In this paper, we propose a systematic method to compute the finite dimensional Koopman embedding of a specific class of polynomial nonlinear systems in continuous-time such that, the embedding, without approximation, can fully represent the dynamics of the nonlinear system. © 2023, CC BY-NC-SA.

关键词： Nonlinear systems

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