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IEEE International Conference on Industrial technology (ICIT)

作者： Zixing Tao Weihua Cao Chao Gan School of Future Technology China University of Geosciences (Wuhan) Wuhan China School of Future Technology School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences (Wuhan) Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Air quality data exhibit nonlinearity, sensitivity to environmental factors, and long-term dependencies. Numerous factors influence air quality, making accurate predictions based on a single-dimensional dataset impractical. This study proposes a method for urban air quality prediction that integrates wide-area spatiotemporal data, designed to address the unique characteristics of air quality datasets. First, relevant wide-area spatiotemporal data are selected, and their correlations with air quality are systematically analyzed. Second, a Long Short-Term Memory (LSTM) network-based Transformer model is utilized to capture the long-term dependencies in the air quality sequences. Finally, the model successfully generates hourly multi-step predictions for six air pollutants. The experimental results show that the proposed method outperforms the method that relies on air quality data alone for multi-step air quality prediction.

关键词： Deep learning Sensitivity Atmospheric modeling Time series analysis Predictive models Air quality Transformers Environmental factors Spatiotemporal phenomena Long short term memory

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Spatial adaptivity with boundary refinement for smoothed particle hydrodynamics fluid simulation

Spatial adaptivity with boundary refinement for smoothed par...

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作者： Xu, Yanrui Song, Chongming Wang, Xiaokun Ban, Xiaojuan Wang, Jiamin Zhang, Yalan Chang, Jian School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology Beijing Beijing China National Centre for Computer Animation Bournemouth University Poole United Kingdom Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing China

Fluid simulation is well-known for being visually stunning while computationally expensive. Spatial adaptivity can effectively ease the computational cost by discretizing the simulation space with varying resolutions. Adaptive methods nowadays mainly focus on the mechanism of refining the fluid surfaces to obtain more vivid splashes and wave effects. But such techniques hinder further performance gain under the condition where most of the vast fluid surface is tranquil. Moreover, energetic flow beneath the surface cannot be adequately captured with the interior of the fluid still being simulated under coarse discretization. This article proposes a novel boundary-distance based adaptive method for smoothed particle hydrodynamics fluid simulation. The signed-distance field constructed with respect to the coupling boundary is introduced to determine particle resolution in different spatial positions. The resolution is maximal within a specific distance to the boundary and decreases smoothly as the distance increases until a threshold is reached. The sizes of the particles are then adjusted towards the resolution via splitting and merging. Additionally, a wake flow preservation mechanism is introduced to keep the particle resolution at a high level for a period of time after a particle flows through the boundary object to prevent the loss of flow details. Experiments show that our method can refine fluid–solid coupling details more efficiently and effectively capture dynamic effects beneath the surface. © 2023 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons Ltd.

关键词： Hydrodynamics

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Rail-Guided Multi-Robot System for the Cooperative Manipulation of Cross-Scale Targets

Rail-Guided Multi-Robot System for the Cooperative Manipulat...

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Han Tao Huaping Wang Yaozhen Hou Siyu Guo Kaijun Lin Maolin Wang Qiang Huang Toshio Fukuda Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology China Ministry of Education Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

In the field of biomedicine, contact micromanipulations are mostly based on multi-robot coordinated operations to achieve mechanical contact interactions with a single type of target in a specific task scenario, which has advantages such as high repeatability, high precision and high stability. With the rapid development of biomedical technology, the increasingly complex biological micromanipulation process has been transformed from a single task to a task sequence of several subtasks, which puts forward higher requirements for the coordination, flexibility, operation accuracy and so on. However, due to the immutable configuration of the end-effector, most microrobotic manipulation systems have a fixed operation dimension, which makes it difficult to include the whole processing of complex tasks and meet the differentiated needs of different operational tasks and objectives. Therefore, this paper proposes a formation control based multi-robot dynamical reconfiguration collaborative micromanipulation to meet the dynamic requirements of multi-process complex tasks. By combining macro multi-robot formation control with collaborative micromanipulation, the dynamical reconfiguration of the end-effector under different manipulation tasks is realized. It can execute efficient and precise manipulation on fragile micro-objects ranging from 50 $\mu \mathrm{m}$ and 1000 $\mu \mathrm{m}$, and provide a new idea for accomplishing the whole processing of complex tasks, such as biological microassembly.

关键词： Viscosity Vibrations Rails Microscopy Collaboration End effectors Formation control

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Clustering single-cell RNA sequencing data by deep learning algorithm 9

Clustering single-cell RNA sequencing data by deep learning ...

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9th IEEE International Conference on Bioinformatics and Computational Biology, ICBCB 2021

作者： Bai, Litai Zhu, Yuan Yi, Ming Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Wuhan China

ISBN: (纸本)9780738132020

The development of single-cell RNA sequencing (scRNA-seq) technology provides a good opportunity to study cell heterogeneity and diversity. Especially, clustering is an important step in scRNA-seq analysis. With the advance of technology, many scRNA-seq data are available, which develop a lot of clustering methods. However, the existing methods usually employ the gene expression data, ignoring the related information between genes and the structure information in data. Therefore, we propose a new method (NDMgcn) to reconstruct the gene expression data based on the association of gene network, and cluster the data by Variational Autoencoder (V AE) and Graph Convolutional Network (GCN). The V AE learns low-dimensional information and the GCN learns structural information. The experimental results indicate that NDMgcn outperforms other popular algorithms in terms of NMI and ARI metrics. It provides a new insight for clustering scRNA-seq data from the network perspective. © 2021 IEEE.

关键词： RNA

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Backstepping Controller Design for the Medium and Low Voltage Stages of Smart Transformer

Backstepping Controller Design for the Medium and Low Voltag...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Hiba Helali Adel Khedher Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisie

Smart Transformer (ST) is a smart device allowing the integration of renewable energy resources, energy storage systems and electric vehicle charging stations into the grid. The ST plays a manager role between the different parts of the Smart Grid (SG), due to its features, namely, bidirectional power control, automatic voltage regulation, power quality improvement and advanced communication services. The three-stage topology of the smart transformer is considered as the most appropriate one for SG requirements. To improve the ST performance, several controller strategies such as, Proportional-Integral controller, predictive controller, and linear-quadratic-regulator, have been proposed. These controllers, practically, show good performance, but they are not robust to parameter variations and grid perturbations. To overcome these limitations, a nonlinear adaptive Backstepping controller is proposed in this paper. The accurate design steps of Backstepping controller are presented and investigated. The effectiveness of the proposed controller is validated through simulations results.

关键词： Reactive power Renewable energy sources Backstepping Simulation Power quality Topology Smart grids

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Integration of automatic voltage regulator and power system stabilizer: small-signal stability in DFIG-based wind farms

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Journal of Modern Power systems and Clean Energy 2019年第5期7卷 1115-1128页

作者： Sirine ESSALLAH Adel BOUALLEGUE Adel KHEDHER Universite de Sousse Ecole Nationale d’Ingenieurs de SousseLATIS-Laboratory of Advanced Technology and Intelligent Systems4023 SousseTunisia

The increasing penetration of wind farms in the energy sector directly affects the dynamic behavior of the power *** increasing use of wind energy in the power system worsens its stability and inherently influences the firmness of a small *** investigate these effects,one of the synchronous generators(SGs)of the grid is considered defective and is replaced by a doubly fed induction generator(DFIG)-based wind farm of the same *** small-signal stability of a power system is usually evaluated via eigenvalue analysis where local-area and inter-area oscillatory modes for the New England test system are *** controls,such as automatic voltage regulator(AVR)and power system stabilizer(PSS),are added to attenuate the generated *** this study,the impact of wind energy on the small-signal stability of the power system is *** combinations of AVR and PSS types are considered to mitigate the undesirable alterations.A comparative study is performed based on numerical simulations to choose the best combination of AVR and PSS *** obtained results prove that the proposed combination yields good results in terms of stability enhancement both under normal operating conditions and in DFIG-based wind farms.

关键词： Power system stability Power transmission system Transient analysis Voltage regulation

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Multi-modal Based Fuzzy Atmosfield in Human-robot Interaction

Multi-modal Based Fuzzy Atmosfield in Human-robot Interactio...

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第42届中国控制会议

作者： Xin-Heng Li Zhen-Tao Liu School of Automation China University of Geosciences(Wuhan) Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Recently,the emotional robot has basic functions of perceiving and expressing emotions,but it still hard to communicate naturally between humans and *** major reason is that communication atmosphere is seldom considered in Human-robot Interaction(HRI).We propose Multi-modal(i.e.,music background,speech,and semantics) Based Fuzzy Atmosfield(FA),which can not only realize the dynamic adjustment of FA but also dynamically regulate human *** the experiment,a Pepper robot is used and one hundred volunteers are invited for HRI,and soothing piano pieces are used as background *** were filled by the volunteers after the experiments,from which the results show that 90% of the volunteers felt the dynamic changes in the communication atmosphere and 77% of the volunteers felt significant emotional regulation,which demonstrates the effectiveness of our method.

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Traction Mode of an Electric Vehicle based on a Delta Inverter feeding a Split Stator Windings PMSM

Traction Mode of an Electric Vehicle based on a Delta Invert...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Asma Ben Rhouma Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisie

In this paper, a traction mode of an electric vehicle based on a delta inverter feeding a split stator windings permanent magnet synchronous machine (PMSM) is proposed. The use of reduced inverter topologies such as the delta inverter allows the cost-effectiveness and the compactness of the electric propulsion systems. The PMSM with split stator windings is adopted in the integrated battery charger of hybrid electric vehicles as a motor with reconfigured stator windings for all different modes: traction/charge operation. This paper develops the traction mode operation of these motor/inverter association under a vector control strategy. Simulation results of the proposed association under the dedicated strategy are registered.

关键词： Battery chargers Simulation Windings Stator windings Propulsion Traction motors Synchronous motors

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Transformer-based Joint Source Channel Coding for Textual Semantic Communication

Transformer-based Joint Source Channel Coding for Textual Se...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Liu, Shicong Gao, Zhen Chen, Gaojie Su, Yu Peng, Lu Beiing Institute of Technology Miit Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Beijing Institute of Technology Advanced Research Institute of Multidisciplinary Science Jinan250307 China Yangtze Delta Region Academy of Beijing Institute of Technology Beijing Institute of Technology Jiaxing314000 China Institute for Communication Systems University of Surrey Guildford United Kingdom Institute of Research and Development Chengdu610000 China

ISBN: (纸本)9798350345384

The Space-Air-Ground-Sea integrated network calls for more robust and secure transmission techniques against jamming. In this paper, we propose a textual semantic transmission framework for robust transmission, which utilizes the advanced natural language processing techniques to model and encode sentences. Specifically, the textual sentences are firstly split into tokens using wordpiece algorithm, and are embedded to token vectors for semantic extraction by Transformer-based encoder. The encoded data are quantized to a fixed length binary sequence for transmission, where binary erasure, symmetric, and deletion channels are considered for transmission. The received binary sequences are further decoded by the transformer decoders into tokens used for sentence reconstruction. Our proposed approach leverages the power of neural networks and attention mechanism to provide reliable and efficient communication of textual data in challenging wireless environments, and simulation results on semantic similarity and bilingual evaluation understudy prove the superiority of the proposed model in semantic transmission. © 2023 IEEE.

关键词： Semantics

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Three-dimensional recognition method of fruit target based on PointNet++ 5

Three-dimensional recognition method of fruit target based o...

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5th World Conference on Mechanical Engineering and intelligent Manufacturing, WCMEIM 2022

作者： Wu, Xiangxiang Tan, Libin Xu, Xiangrong Anhui University of Technology AnHui Province Key Laboratory of Special Heavy Load Robot Ma'anshan China Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China School of Mechanical Engineering Anhui University of Technology Ma'anshan China

ISBN: (纸本)9781665473699

Aiming at the problem that the conventional target recognition algorithm is highly dependent on light and has a poor fruit recognition effect in low light and dark environments, this paper proposes a three-dimensional fruit recognition method based on PointNet++. First, a depth camera is used to obtain point clouds to construct a dataset, and then the network is trained using the dataset. Finally, the fruit point cloud is recognized by the trained network. The experimental results show that the PointNet++ algorithm can recognize both unoccluded and partially occluded fruit point clouds, and the IoU of the predicted and real results are 0.92 and 0.89, respectively, which meets the actual production requirements. © 2022 IEEE.

关键词： Fruits

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