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Research on optical properties of human hepatoma cells using terahertz time-domain spectroscopy

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Research on optical properties of human hepatoma cells using...

Ultrafast Phenomena and Terahertz Waves (ISUPTW), 2023 International Symposium on

作者： Hanxiao Guan Weihang Qiu Yehao Ma Liangfei Tian Yuqi Cao Guangxin Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou People’s Republic of China College of Biomedical Engineering and Instrument Science Zhejiang University Hangzhou People’s Republic of China Robotics Institute Ningbo University of Technology Ningbo China

Terahertz technology is a non-invasive and label-free inspection method, promising for applications in various fields, especially in biomedical diagnosis. Terahertz radiation is capable for cell physiological and pathological status recognition due to its sensitivity to cell composition and structural information of biomacromolecular. In this paper, the transmission properties of glass, polymethyl methacrylate and polypropylene in THz regime were compared and polypropylene was selected as the petri dish material for cell adhesion due to its high transmission of terahertz wave. The time-domain and frequency-domain spectra, refractive index and absorption coefficient of hepatoma cell line Huh7 and normal cell line MIHA were analyzed. The experimental results showed significant distinction between the terahertz characteristic spectra of hepatoma cells and normal cells. This work can be helpful for applying terahertz technology in cancer detection at the cellular level.

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Bearing-based Relative Localization for Robotic Swarm with Partially Mutual Observations

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arXiv 2022年

作者： Wang, Yingjian Wen, Xiangyong Cao, Yanjun Xu, Chao Gao, Fei The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China The Huzhou Institute of Zhejiang University Huzhou313000 China

Mutual localization provides a consensus of reference frame as an essential basis for cooperation in multi-robot systems. Previous works have developed certifiable and robust solvers for relative transformation estimation between each pair of robots. However, recovering relative poses for robotic swarm with partially mutual observations is still an unexploited problem. In this paper, we present a complete algorithm for it with optimality, scalability and robustness. Firstly, we fuse all odometry and bearing measurements in a unified minimization problem among the Stiefel manifold. Furthermore, we relax the original non-convex problem into a semi-definite programming (SDP) problem with a strict tightness guarantee. Then, to hold the exactness in noised cases, we add a convex (linear) rank cost and apply a convex iteration algorithm. We compare our approach with local optimization methods on extensive simulations with different robot amounts under various noise levels to show our global optimality and scalability advantage. Finally, we conduct real-world experiments to show the practicality and robustness. Copyright © 2022, The Authors. All rights reserved.

关键词： Scalability

Dynamic Free-Space Roadmap for Safe Quadrotor Motion Planning

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arXiv 2022年

作者： Guo, Junlong Xun, Zhiren Geng, Shuang Lin, Yi Xu, Chao Gao, Fei The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China The Huzhou Institute of Zhejiang University Huzhou313000 China

Free-space-oriented roadmaps typically generate a series of convex geometric primitives, which constitute the safe region for motion planning. However, a static environment is assumed for this kind of roadmap. This assumption makes it unable to deal with dynamic obstacles and limits its applications. In this paper, we present a dynamic free-space roadmap, which provides feasible spaces and a navigation graph for safe quadrotor motion planning. Our roadmap is constructed by continuously seeding and extracting free regions in the environment. In order to adapt our map to environments with dynamic obstacles, we incrementally decompose the polyhedra intersecting with obstacles into obstacle-free regions, while the graph is also updated by our well-designed mechanism. Extensive simulations and real-world experiments demonstrate that our method is practically applicable and efficient. © 2022, CC BY-NC-ND.

关键词： Motion planning

An intelligent maritime scene frame prediction based on digital twins technology 1

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An intelligent maritime scene frame prediction based on digi...

1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Guo, Zhong-Zheng Wang, Kai Qin, Jiang-Yi Li, Xian-Bin Ran, De-Chao Shen, Yu Unmanned Systems Research Center National Innovation Institute of Defense Technology Academy of Military Science Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

This paper proposes a scene frame prediction system based on digital twin technology. The system is mainly composed of an unmanned perception module, a communication link module, a command center module that provides intelligent computing services, and an interaction and visualization module for human operators. These modules together constitute a system for predicting and recovery the time-series matrix composed of scene frames and object frames. At the same time, in view of the current problems of lack of real-time information and long response time in the maritime search and rescue (SAR) field, this paper instantiates the above system to improve the existing SAR system. Satellites and unmanned vehicles perceive part of the scene data of the real cyber-physical system in real-time and divide them into multiple frames according to the timestamps. In addition, this paper also proposes an environmental graph-attention network (Env-GAT) to achieve efficient and reliable frame predicting. Finally, this paper verifies that the performance of the spatiotemporal attention graph network model has reached the optimal level through computational experiments. © 2021 IEEE.

关键词： Forecasting

Decentralized Planning for Car-Like Robotic Swarm in Cluttered Environments

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arXiv 2022年

作者： Ma, Changjia Han, Zhichao Zhang, Tingrui Wang, Jingping Xu, Long Li, Chengyang Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

Robot swarm is a hot spot in robotic research community. In this paper, we propose a decentralized framework for car-like robotic swarm which is capable of real-time planning in cluttered environments. In this system, path finding is guided by environmental topology information to avoid frequent topological change, and search-based speed planning is leveraged to escape from infeasible initial value’s local minima. Then spatial-temporal optimization is employed to generate a safe, smooth and dynamically feasible trajectory. During optimization, the trajectory is discretized by fixed time steps. Penalty is imposed on the signed distance between agents to realize collision avoidance, and differential flatness cooperated with limitation on front steer angle satisfies the non-holonomic constraints. With trajectories broadcast to the wireless network, agents are able to check and prevent potential collisions. We validate the robustness of our system in simulation and real-world experiments. Code will be released as open-source packages. Copyright © 2022, The Authors. All rights reserved.

关键词： Trajectories

An Improved Active Disturbance Rejection control Method for Crane System

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An Improved Active Disturbance Rejection Control Method for ...

Chinese control and Decision Conference, CCDC

作者： Yubo Sun Xiyuan Shan Zhicheng Zong School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

In order to improve the dynamic performance of the underdriven crane system, an improved linear active disturbance rejection controller (LADRC) based on the new error was proposed. The improved LADRC takes the error value between the disturbance and its observed value multiplied by a coefficient as the basis for adjusting the linear extended state observer (LESO). The improved method has two advantages. Firstly, the new error can prevent the traditional LESO from choosing larger parameter adjustment disturbances, which will limit the performance of the observer. Secondly, the pole can be configured by adjusting the coefficient to obtain better dynamic characteristics. Finally, the effectiveness of the proposed method is verified by simulation and experiment. The proposed method can effectively restrain the swing of the payload and it is robust to system parameters perturbation as well.

关键词： Robust control Couplings Adaptation models Cranes Uncertainty Perturbation methods Bandwidth

A DRL-enabled Adaptive Sparsity Promoting Wide-area Damping controller for Power System with Time-delay and Packet Dropout

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A DRL-enabled Adaptive Sparsity Promoting Wide-area Damping ...

Power and Energy (PandaFPE), Panda Forum on

作者： Di Cao Guozhou Zhang Jiaxiang Hu Weihao Hu Yuehui Huang Zhe Chen State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China Department of Energy Technology Aalborg University Aalborg Denmark

This paper proposes a deep reinforcement learning (DRL) based adaptive sparsity promoting wide-area damping controller for power system. Different from traditional fixed wide-area control structure, the proposed method employs DRL algorithm to identify the optimal sparsity promoting control structure and obtain corresponding parameter settings under different operating conditions considering the time-delay and packet drop. Simulation are carried out on 10-machine 39-bus system to demonstrate the effectiveness of the proposed approach.

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Residual Tensor Train: A Quantum-inspired Approach for Learning Multiple Multilinear Correlations

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arXiv 2021年

作者： Chen, Yiwei Pan, Yu Dong, Daoyi The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China The School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia

states of quantum many-body systems are defined in a high-dimensional Hilbert space, where rich and complex interactions among subsystems can be modelled. In machine learning, complex multiple multilinear correlations may also exist within input features. In this paper, we present a quantum-inspired multilinear model, named Residual Tensor Train (ResTT), to capture the multiple multilinear correlations of features, from low to high orders, within a single model. ResTT is able to build a robust decision boundary in a high-dimensional space for solving fitting and classification tasks. In particular, we prove that the fully-connected layer and the Volterra series can be taken as special cases of ResTT. Furthermore, we derive the rule for weight initialization that stabilizes the training of ResTT based on a mean-field analysis. We prove that such a rule is much more relaxed than that of TT, which means ResTT can easily address the vanishing and exploding gradient problem that exists in the existing TT models. Numerical experiments demonstrate that ResTT outperforms the state-of-the-art tensor network and benchmark deep learning models on MNIST and Fashion-MNIST datasets. Moreover, ResTT achieves better performance than other statistical methods on two practical examples with limited data which are known to have complex feature interactions. Impact statement—Optimal learning may require considering high-order multilinear feature interactions. Recently, quantum-inspired tensor networks have been proposed to exploit high-order correlations. However, the vanilla tensor networks are specialized in capturing only one type of multilinear feature interaction. This paper proposes a novel network design which is able to describe generic feature interactions of different orders, within one model. Due to the residual connections, the training stability has also been promoted to an unprecedented level when compared to previous tensor network methods. Our methodology offers an alte

关键词： Tensors

Fast Vision Decoder: A Robust Automatic Target Recognition Model for Sar Images

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SSRN

SSRN 2022年

作者： Ayodeji, Abiodun Wang, Wenhai Su, Jianzhong Yuan, Jianquan Liu, Xinggao State Key Laboratory of Industrial Control Technology Control Department Zhejiang University Hangzhou310027 China Tianjin Jinhang Technical Physics Institute Tianjin300192 China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing100074 China

The synthetic aperture radar (SAR) is the recent all-weather technology used to monitor areas with low to moderate penetration. However, the scarcity of SAR imagery, and the high-level noise in the images makes it difficult for real-time image interpretation. This work presents a novel fast vision decoder (FViD), a target recognition model with a frozen backbone and stack dilated autoencoder. The autoencoder architecture is introduced to learn the compressed latent representation. Moreover, a robust backbone selection method is introduced to select a task-specific optimal backbone. The proposed FViD is extensively evaluated using the Chinese TerraSAR-X ship images, and the US MSTAR datasets. Evaluation results show that the proposed method has significant improvement over the conventional models. The speed and accuracy of the proposed FViD are further compared with five state of the art models previously used for SAR target recognition tasks, and the comparison result shows that the FViD performs better. Moreover, an ablation study is performed to provide insights into the contribution of FViD architecture. The results of the ablation study as well as the performance improvement of FViD are discussed in this paper. © 2022, The Authors. All rights reserved.

关键词： Computer vision