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2024 China automation Congress, CAC 2024

作者： Fan, Lingling Chen, Kang Xu, Zhezhuang Yuan, Meng Huang, Ping Huang, Weibing College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350368604

Grasping tasks are crucial for the interaction between the robot and environment, requiring the robot to make autonomous decisions based on environmental conditions and instructions. Recently, multimodal Vision Language Models (VLMs) have demonstrated significant potential for robotic grasping. However, previous work has often been confined to high-level planning due to the gap between the text output of VLMs and the numerical predictions of robot actions, as well as the challenges of transferring rich semantic information from large models to the prediction of grasping actions. In this paper, we co-fine-tune a pre-trained VLM using the mix of large-scale visual language data and robotic grasping trajectory data, integrating model into an end-to-end robot control system to construct a Vision Language Action Model (VLA) capable of generating the robot’s underlying actions. Simultaneously, to fully leverage the prior knowledge and reasoning capabilities of the pre-trained model, we insert a language reasoning structure to bridge the mapping from high-level tasks to low-level actions. This method first deduces the relevant information regarding the target object and the end-effector motions, followed by predicting the grasping actions value with finer granularity based on the language reasoning, thereby enhancing the accuracy of action predictions. A series of grasping experiments demonstrate that our method achieves a high grasping success rate under flexible language instructions and exhibits strong generalization capabilities for unseen objects and scenes. © 2024 IEEE.

关键词： Visual languages

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Sharing and Collaborating When Teaching Automatic control: An Experience-Based Needs Analysis 32

Sharing and Collaborating When Teaching Automatic Control: A...

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32nd Mediterranean Conference on control and automation, MED 2024

作者： Knorn, Steffi Garone, Anja Varagnolo, Damiano Garone, Emanuele Technische Universität Department of Control Berlin Germany Brussels Institute for Advanced Studies Belgium Norwegian University of Science and Technology Department of Engineering Cybernetics Norway University of Padova Department of Information Engineering Italy Free University of Brussels Department of Automation and Systems Analysis Belgium

ISBN: (纸本)9798350395440

We discuss two specific issues that affected the workflows in our career as automatic control teachers and that are related to how teachers may establish teaching-oriented collaborations with colleagues from the same or different institutions. The first issue we identify is the systematic difficulty that one encounters when wanting to exchange instructional material with colleagues, while the second is the complexity of establishing students exchange programs across different institutions and nations. We discuss the nature and structure of the two problems, discuss why and how they are connected, and draw practical examples of how these problems may affect workflows. We then present a strategy that aims at solving these issues based on the introduction of an opportune indexing of instructional material in terms of contents and complexity of such contents, and how this information may be graphically displayed so to ease human and machine interpretability. We further discuss how this approach was used on a smaller scale to ease collaborations among close colleagues, and how it may be extended and adopted on a larger scale. © 2024 IEEE.

关键词： Process control

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Immoral post detection using a one-dimensional convolutional neural network-based LSTM network

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Multimedia Tools and Applications 2025年 1-20页

作者： Saqia, Bibi Khan, Khairullah Rahman, Atta Ur Khan, Aurangzeb Jain, Deepak Kumar Department of Computer Science University of Science and Technology Bannu28100 Pakistan Riphah Institute of Systems Engineering Riphah International University Islamabad46000 Pakistan Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China Symbiosis Institute of Technology Symbiosis International University Pune India

In text mining and Natural Language Processing (NLP), extracting emotions from textual data is gaining rapid attraction. The proliferation of online content and the freedom of expression on social media platforms has compelled the advancement of more sophisticated methods for the automatic identification of unwanted content. The One-Dimensional Convolutional Neural Network (1D-CNN) performs best for feature extraction, while the Long Short-Term Memory Network (LSTM) is well-known for extracting sequential features and classification of textual data. This study proposes a novel solution by combining 1D-CNN with LSTM. Utilizing a context-aware model, this study aims to enhance the detection of immoral posts, including hate speech and other forms of immoral content on social media platforms. Various posts are extracted from social media, which are then processed using Glove word embedding models. It depicts the word representations in the text, which yields the form of a real-valued vector determining the words' meaning. The 1D convolution utilizes a filter window over the input time-series data to extract features. Relying on the acquired parameters of the filters, they act as feature extractors. This feature extraction technique allows the model to distinguish detailed patterns and nuances from the textual contents of posts. The sequential processing capabilities of the LSTM network enable an in-depth examination of the text, capturing temporal relationships and context, which is critical for successful content categorization. To validate the proposed model, we utilized a benchmark dataset, called the Twitter dataset. The proposed model achieved the highest accuracy of 95.37% and outperforms state-of-the-art works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Transformer-Based Sequence Modeling with Action Discretization for Robotic Grasping

Transformer-Based Sequence Modeling with Action Discretizati...

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2024 China automation Congress, CAC 2024

作者： Hou, Yaokun Zheng, Song Xu, Zhezhuang Yuan, Meng Huang, Ping Huang, Weibing College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350368604

The powerful representational and sequential modeling capabilities of Transformer have been validated in various fields such as natural language processing. However, how to better address sequential decision-making problems like robotic grasping through the Transformer architecture and achieve autonomous control of robotic grasping remains a longstanding challenge. Models that directly output continuous decision actions for robotic arms often rely on mean squared error (MSE) loss for training, which is unable to effectively handle the randomness and diversity of actions. This limitation leads to the generation of relatively singular actions in certain grasping scenarios, reducing the success rate of grasping. To address this issue, this paper proposes a Transformer-based method for discretizing robotic arm actions, where actions are discretized by dimension to enable autoregressive modeling. Experimental results demonstrate that this method effectively improves the grasping performance of robotic arms in simulation environments. © 2024 IEEE.

关键词： Mean square error

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Tracking dynamic flow: Decoding flow fluctuations through performance in a fine motor control task

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IEEE Transactions on Affective Computing 2024年第2期16卷 891-902页

作者： Tian, Bohao Zhang, Shijun Chen, Sirui Zhang, Yuru Peng, Kaiping Zhang, Hongxing Wang, Dangxiao Tsinghua University Department of Psychology Beijing100084 China Beijing Institute of Life Omics Beijing102206 China Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing100191 China Beihang University School of Mechanical Engineering and Automation Beijing100191 China Peng Cheng Laboratory Shenzhen518000 China

Flow, an optimal mental state merging action and awareness, significantly impacts our emotion, performance, and well-being. However, capturing its swift transitions on a fine timescale is challenging due to the sparsity of the existing flow detecting tools. Here we present a fine fingertip force control (F3C) task to induce flow, wherein the task challenge is set at a compatible level with personal skill, and to quantitatively track the flow state variations from synchronous motor control performance. We select eight performance metrics from fingertip force sequence and reveal their significant differences under distinct self-reported flow states. Further, we built a machine learning-based decoder that aims to predict the continuous flow intensity during the user experiment through the performance metrics, taking the self-reported flow as the label. Cross-validation shows that the predicted flow intensity reaches significant correlation with the self-reported flow intensity (r = 0.81). Based on the decoding results, we can capture the flow fluctuations during the intervals between sparse self-reporting probes. This study showcases the feasibility of tracking intrinsic flow variations with high temporal resolution using task performance measures and may serve as foundation for future work aiming to take advantage of flow's dynamics to enhance performance and positive emotions. © 2010-2012 IEEE.

关键词： Force Measurement Force control Fluctuations Decoding Pressing Dynamics Affective Computing Transducers Real Time systems Flow Experience Intrinsic Fluctuations Fine Fingertip Force control Task Performance Cross Validation Dynamics Task Performance control Task Flow Dynamics Fine control Flow Fluctuations Fine Motor control Tasks Performance Metrics Volume Flow Flow Variables Personal Skills Force control Finer Time Scales Synchronization Performance Paired T Test Prediction Error Cohens D Flow Meter Task Difficulty Target Range Random Permutations Power Spectral Density Analysis Flow Experience Experience Sampling Method Flow Probe Main Session Force Output Subjective Metrics Decoding Performance Target Force Decoding Accuracy

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AirVista: Empowering UAVs with 3D Spatial Reasoning Abilities Through a Multimodal Large Language Model Agent 27

AirVista: Empowering UAVs with 3D Spatial Reasoning Abilitie...

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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Lin, Fei Tian, Yonglin Wang, Yunzhe Zhang, Tengchao Zhang, Xinyuan Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Capital University of Economics and Business Beijing100070 China University of Chinese Academy of Sciences Department of Artificial Intelligence Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Department of Engineering Science 999078 China

ISBN: (纸本)9798331505929

In urban environments, complex transportation demands, including land, air, and maritime transport, are increasingly growing. While significant advancements have been made in land transportation and autonomous driving, research on urban air mobility (UAM) systems is still in its early stages. This paper presents an innovative urban air unmanned aerial vehicle (UAV) framework: AirVista, which is designed and built based on the Artificial systems, Computational experiments, and Parallel execution (ACP) approach, integrated with a multimodal large language model (MLLM) agent. Considering that UAM tasks often require UAVs to possess fine-grained spatial perception and reasoning capabilities, and given that existing MLLMs are somewhat lacking in exploring 3D spaces, this paper further proposes an instruction fine-tuning strategy integrated with 3D spatial knowledge, which has been validated experimentally for its effectiveness. Additionally, to enhance the understanding of the efficiency of MLLM for UAV tasks, this paper delves into prompt fine-tuning templates tailored for UAV task decomposition. Through experimental demonstrations, we showcase that the prompt-tuned MLLM exhibits efficient task decomposition and execution capabilities in handling complex UAV tasks. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Effective distributed algorithm for solving linear matrix equations

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Science China(Information Sciences) 2023年第8期66卷 265-266页

作者： Songsong CHENG Jinlong LEI Xianlin ZENG Yuan FAN Yiguang HONG Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Department of Control Science and Engineering Tongji University Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic ...

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Creating a semi-opened micro-cavity ovary through sacrificial microspheres as an in vitro model for discovering the potential effect of ovarian toxic agents

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Bioactive Materials 2023年第8期26卷 216-230页

作者： Min Ye Yiran Shan Bingchuan Lu Hao Luo Binhan Li Yanmei Zhang Zixuan Wang Yuzhi Guo Liliang Ouyang Jin Gu Zhuo Xiong Ting Zhang Biomanufacturing Center Department of Mechanical EngineeringTsinghua UniversityBeijing100084China Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing Beijing100084China Biomanufacturing and Engineering Living Systems Innovation International Talents Base(111 Base)Beijing100084China MOE Key Laboratory of Bioinformatics BNRIST Bioinformatics DivisionDepartment of AutomationTsinghua UniversityBeijing100084China

The bio-engineered ovary is an essential technology for treating female *** the development of relevant in vitro models could be a critical step in a drug ***,we develop a semi-opened culturing system(SOCS)strategy that maintains a 3D structure of follicles during the *** on the SOCS,we further developed micro-cavity ovary(MCO)with mouse follicles by the microsphere-templated technique,where sacrificial gelatin microspheres were mixed with photo-crosslinkable gelatin methacryloyl(GelMA)to engineer a micro-cavity niche for follicle *** semi-opened MCO could support the follicle growing to the antral stage,secreting hormones,and ovulating cumulus-oocyte complex out of the MCO without extra *** MCO-ovulated oocyte exhibits a highly similar transcriptome to the in vivo counterpart(correlation of 0.97)and can be ***,we found that a high ROS level could affect the cumulus expansion,which may result in anovulation *** damage could be rescued by melatonin,but the end of cumulus expansion was 3h earlier than anticipation,validating that MCO has the potential for investigating ovarian toxic agents in *** provide a novel approach for building an in vitro ovarian model to recapitulate ovarian functions and test chemical toxicity,suggesting it has the potential for clinical research in the future.

关键词： Bio-engineered ovary SOCS Semi-opened MCO Ovarian model Drug study

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A time-coded multi-concentration microfluidic chemical waveform generator for high-throughput probing suspension single-cell signaling

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Chinese Chemical Letters 2022年第6期33卷 3091-3096页

作者： Yiran Guo Peng Chen Zhaolong Gao Yiwei Li Shunji Li Xiaojun Feng Bi-Feng Liu The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics and Molecular Imaging Key Laboratory Systems Biology ThemeDepartment of Biomedical EngineeringCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

The cellular response to the complex extracellular microenvironment is highly dynamic in time and type of extracellular *** reconstructing this process and analyzing the changes in receptor conformation on the cell membrane surface and intracellular or intercellular signaling has been a major challenge in analytical chemistry and biophysical *** this paper,a time-coded multiconcentration microfluidic chemical waveform generator was developed for the dynamic signaling probing with single-cell array of high temporal resolution,high throughput,and multi-concentration combination *** on innovative microchannel structure,sophisticated external control methods and multiplexing technology,the system not only allowed for temporally sequential permutations of the four concentrations of stimuli(time code),but also generated pulsed and continuous waveforms at different frequencies in a highly controllable ***,the single-cell trap array was set up to efficiently capture cells in suspension,dramatically increasing throughput and reducing experiment preparation *** maximum frequency of the platform was 1 Hz,and one cell could be stimulated at multiple *** show the ability of the system to investigate rapid biochemical events in high throughput,pulse stimulation and continuous stimulation of different frequencies and different time codes,combined with four concentrations of histamine(HA),were generated for probing G protein-coupled receptor(GPCR)signaling in He La ***,statistical analysis was performed for the mean peak height and mean peak area of the cellular *** believe that the time-coded multi-concentration microfluidic chemical waveform generator will provide a novel strategy for analytical chemistry,biophysics,cell signaling,and individualized medicine applications.

关键词： Microfluidics Dynamic stimulation Time code High-throughput Single-cell array

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Health assessment method for core components of switching quantity interface circuit based on active excitation test 14

Health assessment method for core components of switching qu...

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14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023

作者： Xu, Peiyang Jia, Long Ma, Jian Chen, Chang Chen, Wei Lan, Chunyun Zou, Xinyu Li, Tianhao Science & Technology on Reliability & Environmental Engineering Laboratory School of Reliability and Systems Engineering Beihang University Beijing China School of Automation Science and Electrical Engineering Beijing Aerospace Institute of Automatic Control Beihang University Beijing China Science & Technology on Reliability & Environmental Engineering Laboratory School of Reliability and Systems Engineering Institute of Reliability Engineering Beihang University Beijing China Beijing Aerospace Institute of Automatic Control Beijing China

ISBN: (纸本)9798350329988

As power electronics technology continues to advance, the prevalence of switching quantity interface circuits has grown in diverse domains, encompassing industrial production and everyday civilian applications. An analysis of operational data from these circuits, along with an assessment of their overall health, proves instrumental in the timely detection and resolution of operational anomalies. This holds paramount significance in upholding the reliability of these interface circuits. Nevertheless, tracking the degradation trajectory of the core components during their operational lifespan poses a challenge. Typically, only two states, normal and abnormal, are readily discernible, making direct health assessment elusive. To address this issue, this study introduces a health assessment methodology for the fundamental components of switch quantity interface circuits based on active excitation testing. Through the application of active excitation, the performance decay profile of the optical coupler is ascertained, solving the problem of capturing the degradation process within these circuits. This approach facilitates the stable and precise characterization of the health status of switching quantity interface circuits. The health assessment method presented in this paper is characterized by modest computational resource demands and a reduced reliance on expert knowledge. It is adept at quantitatively delineating the health status of switch-quantity interface circuits with precision, thereby offering guidance for the maintenance and replacement of pivotal electronic components within these circuits. In doing so, it contributes to the assurance of operational dependability and an extension of the service life of switch quantity interface circuits. © 2023 IEEE.

关键词： Reliability analysis

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