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Identification of gas-liquid two-phase flow patterns based on flexible ultrasound array and machine learning

npj Flexible Electronics 2024年第1期8卷 205-214页

作者： Hang Liu Jinhui Fan Xinyi Lin Kai Lin Suhao Wang Songyuan Liu Fei Wang Jizhou Song Department of Engineering Mechanics Soft Matter Research CenterKey Laboratory of Soft Machines and Smart Devices of Zhejiang Provinceand State Key Laboratory of Brain-Machine IntelligenceZhejiang UniversityHangzhou310027China Nanhu Brain-Computer Interface Institute Hangzhou311100China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou310027China Department of Rehabilitation Medicine The First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou310003China

Ultrasound technology has been recognized as the mainstream approach for the identification of gasliquid two-phase flow patterns,which holds great value in engineering ***,commercial rigid probes are bulky,limiting their adaptability to curved ***,we propose a strategy for autonomous identification of flow patterns based on flexible ultrasound array and machine *** array features high-performance 1–3 piezoelectric composite material,stretchable serpentine wires,soft Eco-flex layers and a polydimethylsiloxane(PDMS)adhesive *** resulting ultrasound array exhibits excellent electromechanical characteristics and offers a large stretchability for an intimate interfacial contact to curved surface without the need of ultrasound coupling *** demonstrated that the flexible ultrasound array combined with machine learning can accurately identify gas-liquid two-phase flow patterns,in a circular *** work presents an effective tool for recognizing gas-liquid two-phase flow patterns,offering engineering opportunities in petroleum extraction and natural gas transportation.

关键词： flow curved holds

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Study on neural information decoding of ground and flight motion state of pigeons in free-moving in the field 22

Study on neural information decoding of ground and flight mo...

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7th International Conference on Cyber Security and Information Engineering, ICCSIE 2022

作者： Ma, Erteng Yang, Lifang Shang, Zhigang School of Electrical Engineering Zhengzhou University Zhengzhou China Henan Key Laboratory of Brain-Computer Interface Technology Zhengzhou China

ISBN: (纸本)9781450397414

The neural information decoding of birds in natural flight is very significant for the development of new biological robots, but there is little research at present. In this paper, we recorded the local field potential signals of pigeons under free movement in the wild;and constructed the brain function connectivity network underground and flight motion state by using the coherence between channels. The analysis shows that the information transmission of pigeons' brains is higher during flight, and its gamma-band contains more movement-related information. Finally, the clustering coefficients and global efficiency features of the gamma band are extracted for decoding. The average decoding accuracy of the three pigeons is 82.66%. This work can provide theoretical support for bird neural information decoding in the future natural environment. © 2022 ACM.

关键词： Birds

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Two-step Thompson Sampling for Multi-Armed Bandit Problem

Two-step Thompson Sampling for Multi-Armed Bandit Problem

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第43届中国控制会议

作者： Zhigang Shang Lifang Yang Mengmeng Li School of Electrical and Information Engineering Zhengzhou University Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

An important feature of sequential decision-making under uncertain conditions is to strike a balance between exploration(obtaining information about the value of actions) and utilization(selecting the best action based on existing knowledge). The multi-armed bandit is a classic task for balancing their relationship. As the agent has learnt the relationship between two options in a 2-armed bandit task,it will no longer explore but instead use them directly. Inspired by the research, an algorithm based on two-step Thompson sampling(T-TS)is proposed to solve multi-armed bandit problem. First, posterior Beta distributions for the reward of each arm and the probability of the superior arm were established respectively. In the first-step TS, Thompson sampling was used to extract the maximum value from the posterior distribution of probability for the superior arm, determining it as the selected arm. In the two-step TS, Thompson sampling was used to sample from the distributions of the reward. During the updating, the posterior distribution of the probability for the superior arm was updated based on observations including actions and reward, and the distribution of the reward was updated based on the reward feedback. We performed the comparative experiments to solve the static multi-bandit tasks with 10, 20, 40, and 80 arms respectively by the state-of-the-art B-UCB algorithm, Thompson sampling and the proposed T-TS. The results shown that our proposed T-TS can learn the superior action more quickly with the best robustness.

关键词： Thompson sampling multi-armed bandit Beta distribution cumulative regret cumulative reward

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An Improvement of the Trajectory Segmented DDPC: Utilizing LQ Decomposition 43

An Improvement of the Trajectory Segmented DDPC: Utilizing L...

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43rd Chinese Control Conference, CCC 2024

作者： Yan, Jingqian Sader, Malika Li, Yucheng Liu, Zhongxin Nankai University College of Artificial Intelligence Tianjin300350 China Nankai University Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Tianjin300350 China Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9789887581581

Behavioral systems theory has inspired the emergence of the data-driven predictive control methods (DDPC). These DDPC methods are influenced by non-causal terms, which are primarily responsible for the poor performance of systems in noisy environments. While the existing trajectory segmentation DDPC methods enforce causality, they increase the dimension of decision variables, resulting in computational disadvantages. To address this problem, an improvement of trajectory segmentation DDPC utilizing LQ decomposition is proposed in this paper. Specifically, the equivalence between the proposed DDPC and the existing DDPC is demonstrated in a noise-free environment. The proposed method decreases computational complexity and improves noise robustness by reducing decision variable dimensions and matching initial conditions offline. Even in noisy conditions, the proposed DDPC method effectively solves problems without needing extra regularization. Finally, the efficacy of the proposed method is shown through a numerical case study by varying parameters like noise level. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Predictive control systems

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Design and Verification of Tuning Platform for Micro-turbojet Aircraft

Design and Verification of Tuning Platform for Micro-turboje...

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International Symposium on Autonomous Systems (ISAS)

作者： Yu Tian Tianyu Ouyang Jiachen Zhang Feng Duan Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Nankai University Tianjin China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

Micro-turbojet is widely used in civil aviation due to high thrust-to-weight ratio, superior combustion efficiency and low fuel consumption. In order to exert the operation effect of micro-turbojet aircraft, it is very important to adjust the parameters of PID controller. The efficiency and accuracy of parameter tuning tests are determined by the platform used. However, existing platforms are limited to single tests, making the process complex and reliant on the experience of testing personnel. In order to optimize the tuning test of micro-turbojet aircraft, this study designed a new aircraft tuning platform based on BP neural network and fuzzy algorithm. The platform focuses on controlling the steering gear and electric cylinder. It adjusts the multidimensional parameters of the aircraft and determines the thrust of each turbojet engine, serving as the basis for evaluating optimization effects. This ensures improved adaptability and robustness of the aircraft. The feasibility of the parameter adjustment platform is verified by simulation. The tracking error peak value is ±0.088, which realizes the goal of multiple parameter adjustment in a single test. The results of this study offer robust support for advancing micro-turbojet technology. They also establish a solid foundation for extending its application into areas such as unmanned aerial vehicles and small-scale commercial aircraft.

关键词： Software packages neural networks Systems modeling Solids Personnel Aircraft Aircraft propulsion

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Control of defensive behavior by the nucleus of Darkschewitsch GABAergic neurons

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National Science Review 2024年第4期11卷 70-83页

作者： Huiying Zhao Jinrong Liu Yujin Shao Xiang Feng Binhan Zhao Li Sun Yijun Liu Linghui Zeng Xiao-ming Li Hongbin Yang Shumin Duan Yan-qin Yu Department of Neurology of Second Affiliated Hospital and School of Brain Science and Brain Medicine Zhejiang University School of Medicine Nanhu Brain-Computer Interface Institute Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-Machine Integration State Key Laboratory of Brain-Machine Intelligence Zhejiang University NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang University Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province School of Medicine Hangzhou City University

The nucleus of Darkschewitsch(ND), mainly composed of GABAergic neurons, is widely recognized as a component of the eye-movement controlling system. However, the functional contribution of ND GABAergic neurons(NDGABA) in animal behavior is largely unknown. Here, we show that NDGABA neurons were selectively activated by different types of fear stimuli, such as predator odor and foot *** and chemogenetic manipulations revealed that NDGABA neurons mediate freezing ***, using circuit-based optogenetic and neuroanatomical tracing methods, we identified an excitatory pathway from the lateral periaqueductal gray(l PAG) to the ND that induces freezing by exciting ND inhibitory outputs to the motor-related gigantocellular reticular nucleus, ventral part(Gi V). Together,these findings indicate the NDGABA population as a novel hub for controlling defensive response by relaying fearful information from the l PAG to Gi V, a mechanism critical for understanding how the freezing behavior is encoded in the mammalian brain.

关键词： nucleus of Darkschewitsch GABAergic population defensive behavior freezing neural circuitry

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Macrophage senescence in health and diseases

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1508-1524页

作者： Longling Wang Wenxiang Hong Hong Zhu Qiaojun He Bo Yang Jiajia Wang Qinjie Weng Center for Drug Safety Evaluation and Research Zhejiang Province Key Laboratory of Anti-Cancer Drug ResearchCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China Nanhu Brain-Computer Interface Institute Hangzhou 311100China Taizhou Institute of Zhejiang University Taizhou 318000China The Second Affiliated Hospital Zhejiang University School of MedicineHangzhou 310009China

Macrophage senescence,manifested by the special form of durable cell cycle arrest and chronic low-grade inflammation like senescence-associated secretory phenotype,has long been consid-ered *** senescence of macrophages may lead to maladaptation,immune dysfunction,and finally the development of age-related diseases,infections,autoimmune diseases,and ***,it is a ubiquitous,multi-factorial,and dynamic complex phenomenon that also plays roles in remodeled processes,including wound repair and *** this review,we summarize some general molecular changes and several specific biomarkers during macrophage senescence,which may bring new sight to recognize senescent macrophages in different ***,we take an in-depth look at the functional changes in senescent macrophages,including metabolism,autophagy,polarization,phagocytosis,antigen presentation,and infiltration or ***,some degenerations and diseases associated with senescent macrophages as well as the mechanisms or relevant genetic regulations of senescent macrophages are integrated,not only emphasizing the possibility of regulating macrophage senescence to benefit age-associated diseases but also has an implication on the finding of potential tar-gets ordrugs clinically.

关键词： Macrophages Senescence Molecular changes Functional alterations Aging tissues Age-associated diseases Drug treatment Genetic regulation

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The Bird Flight Movement Information Acquisition Equipment Design and Implementation Based on The STM32

The Bird Flight Movement Information Acquisition Equipment D...

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2022 International Conference on computer, Artificial Intelligence, and Control Engineering, CAICE 2022

作者： Guo, Zhixin Yang, Long Ma, Erteng Li, Yang Shang, Zhigang School of Electrical Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9781510655942

Birds have excellent three-dimensional space movement ability. The research and design of small and lightweight bird flight movement behavior information collection equipment has important application value in the research of bird robots and other aspects. Based on STM32F103 series chips, this paper designs a low cost small lightweight bird flight movement information acquisition device, and uses FREERTOS multi-task real-time operating system to realize the acquisition and storage of movement behavior information on this device. © 2022 SPIE.

关键词： Birds

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Multi-domain feature fusion for target color decoding from multichannel neural recordings of pigeons

Multi-domain feature fusion for target color decoding from m...

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2023 International Conference on Image, Signal Processing, and Pattern Recognition, ISPP 2023

作者： Li, Hongxun Liu, Ruiqing Niu, Xiaoke Wang, Zhizhong Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology School of Electrical Engineering Zhengzhou University Zhengzhou450001 China Department of Mechanical and Electrical Engineering Henan Light Industry Vocational College Zhengzhou450000 China

ISBN: (纸本)9781510666351

The entopallium is a high-level neural structure of the avian visual system that is related to the processing of color- and shape-related information during target recognition. The mechanism underlying it remains unclear and has drawn a considerable amount of research interest. Decoding has invariably been used in relevant studies to verify whether the extracted response-related features contain visual information. However, local field potentials (LFPs) often contain rich features. In this study, We combine the features of different domains to decode color information, including those in the time and frequency domains as well as features related to non-linear and functional network connectivity. To extract valuable response-related features, three types of feature selection methods are compared. The LFP data from the entopallium of a pigeon were recorded during periods of stimulus presentation in which two colors were randomly presented in each trial. The selected feature set was finally used to decode the colors by using several general classifiers. The results showed that the fusion of multi-domain features helped improve decoding performance, and the optimal feature set was a fusion of multiple domains of features. These results improve our understanding of the avian neural mechanisms involved in encoding color-related information. © 2023 SPIE.

关键词： Color

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Research on EEG Signal Classification Method Based on brain-computer interface Control of Rehabilitation Robot 17

Research on EEG Signal Classification Method Based on Brain-...

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17th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2024

作者： Zhang, Yiwen Wang, Wenzhi Liu, Gan Qiao, Yi Shi, Ruochuan Duan, Yahan Du, Ying Li, Sining Guo, Fengrui McHugh, Thomas John Duan, Feng Nankai University Tianjin key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation No.38 Tongyan Road Tianjin300350 China Riken Center for Brain Science Laboratory for Circuit and Behavioral Physiology Wakoshi Saitama Japan Graduate School of Arts and Sciences The University of Tokyo Department of Life Sciences Tokyo Japan

ISBN: (纸本)9798350355154

brain-computer interface (BCI) control of multiple rehabilitation robots provides a novel type of human-robot interaction and an important research direction in the field of intelligent rehabilitation. However, most current EEG signal classification algorithms for controlling rehabilitation robots exhibit several drawbacks, including a lack of novelty, insufficient classification accuracy and poor adaptability to different experimental paradigms. Therefore, we designed a new deep-learning method to classify EEG signals to enhance the effectiveness of BCI control of rehabilitation robots. Here we apply this method to classify EEG signals and control the rehabilitation robot to accomplish a target task. In addition, we compare our algorithm with several different EEG signal classification algorithms in two experimental paradigms: motor imagery and motor execution. Our deep learning method has the highest offline accuracy of 72.7% and an average accuracy of 72.4% under the motor imagery experimental paradigm, and the highest offline accuracy of 97.5% and an average accuracy of 90.4% under the motor execution experimental paradigm. These results show that our EEG signal classification algorithms is more effective compared to other EEG signal classification algorithms and can effectively be used to control a rehabilitation robot across a wider range of applications. © 2024 IEEE.

关键词： Human robot interaction

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