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2024 International Conference on Future of Medicine and Biological information Engineering, MBIE 2024

作者： Lin, Ziwei Zhang, Kaiyue Li, Shanshan Qin, Qing Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education Tianjin300350 China

ISBN: (纸本)9781510682825

Polyp segmentation has consistently been a difficult task because of the varying sizes of polyps and the significant intrinsic similarity between polyps and the surrounding tissues. To address the above problems, a contextual feature aggregation polyp segmentation algorithm combining Transformer and convolution is proposed. Firstly, the Pyramid Vision Transformer is used to extract image global features, and the stage bridging module(SBM) is employed to enhance the ability of the network to handle polyp details and aggregate high-level polyp features. Subsequently, a feature enhancement module (FEM) is used to explore shallow polyp information. Finally, cross-layer feature fusion is performed by a global adaptive module (GAM) to realize feature interaction. This algorithm is evaluated on the CVC-ClinicDB and Kvasir-SEG datasets and further tested for generalization capability on the CVC-ColonDB dataset. Compared to other classic segmentation networks, the proposed method demonstrates superior segmentation performance in both visual results and quantitative analysis. The method effectively segments colorectal polyp images, offering a new approach to diagnosing colorectal polyps. © 2024 SPIE.

关键词： Image enhancement

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive Control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Analysis of spiking evoked by acupuncture based on statistical models

Analysis of spiking evoked by acupuncture based on statistic...

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2024 International Conference on Future of Medicine and Biological information Engineering, MBIE 2024

作者： Zhang, Kaiyue Lin, Ziwei Qin, Yingmei Wang, Ruofan Qin, Qing Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781510682825

Acupuncture and moxibustion act on acupoint areas with different frequencies, evoking a large number of responding activity of neurons to achieve the purpose of regulating human body functions. In the process of acupuncture, different frequencies of acupuncture evoked different neuronal spiking activity. In order to study the mechanism of acupuncture with different frequencies, Bayesian statistical model is used to optimize the results of the traditional classification algorithm based on spiking waveforms, which greatly reduces the missed detection rate of acupuncture responding activity. Then, the spiking events evoked by acupuncture at different frequencies were statistically analyzed, and the results showed that the number of neuronal spikes gradually increased with the increase of frequency. However, when the stimulation was increased to 120 times/min, the increase in the stimulation frequency will not evoke more spikes due to the saturation of frequency adaptation of the neurons. Finally, a probabilistic statistical model was used to encode the neuronal responding activity evoked by different acupuncture, and the maximum likelihood estimation method was used to fit the model parameters. The results show that the coupling parameters of stimulus are significantly smaller than the coupling parameters of spike-history, and the more the historical spikes, the smaller the coupling parameters of stimulus. This suggests that since acupuncture is a low-frequency mechanical stimulation, a large number of historical spikes in the spiking activity are the main factors that evoke the neuronal response. Thus, revealing the responding mechanism of different acupuncture frequencies. © 2024 SPIE.

关键词： Neurons

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An approximate algorithm for simulating Fresnel diffraction patterns without Fourier transform 6

An approximate algorithm for simulating Fresnel diffraction ...

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6th International Conference on Optoelectronic Science and Materials, ICOSM 2024

作者： Zhang, Zhiyuan Li, Chongguang Lou, Yuli Liu, Siqi Liang, Xiyuan Song, Qinghe Gui, Jinbin Key Laboratory of Laser Information Processing Technology and Application College of Science Kunming University of Science and Technology Yunnan Kunming650500 China

ISBN: (数字)9781510686823

ISBN: (纸本)9781510686816

In the study of optical systems, accurately calculating Fresnel diffraction patterns is crucial for understanding and designing various applications, from imaging systems to laser technologies. However, existing commonly used calculation methods each have their limitations. This paper proposes an approximate algorithm for calculating Fresnel diffraction to address these shortcomings. The algorithm is based on the oscillatory characteristics of the quadratic phase exponential function in the Fresnel diffraction integral. By convolving this quadratic phase exponential function with another slowly varying function, it is found that the rapidly oscillating parts cancel each other out, having little impact on the final calculation result. Therefore, only the areas that primarily contribute to the diffraction need to be computed. The study shows that this algorithm significantly reduces the computational load while maintaining a certain level of accuracy. Compared to the direct integration method, it shows a notable improvement in calculation speed. It also maintains high accuracy compared to both the direct integration method and the Fast Fourier Transform (FFT) algorithm. Additionally, since it does not involve the frequency domain transformation used in FFT, it avoids under-sampling issues. This algorithm offers a feasible method for calculating diffraction patterns while ensuring a balance between accuracy and computational efficiency. © 2024 SPIE.

关键词： Exponential functions

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MTL-SRN: Multi-task Learning-based Signal Recognition Network

MTL-SRN: Multi-task Learning-based Signal Recognition Networ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Pengxu Zhang, Xingjian Ma, Yuan Zhu, Hao Jiao, Jian Zhang, Qinyu Department of Electronics and Information Engineering Shenzhen518055 China Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Shenzhen518055 China Peng Cheng Laboratory Shenzhen518055 China Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration Guangdong Key Laboratory of Intelligent Information Processing The College of Electronic and Information Engineering Shenzhen518060 China

ISBN: (纸本)9798350351255

Wideband signal recognition is a crucial task in the cognitive wireless communication, involving accurate classification of different signal types, modulation types, center frequencies, etc. However, most conventional approaches treat the recognition of different parameters as multiple independent tasks, and often face performance bottlenecks due to the complexity and diversity of wideband signals. To overcome these challenges, we propose a multi-task learning (MTL) network that integrates multiple tasks of signal recognition into an end-to-end model to accomplish spectrum sensing, modulation recognition, and signal classification simultaneously. By employing a shared feature extraction network and a multi-task classification header, the proposed framework effectively captures the correlations and shared information among different tasks, thereby enhancing overall recognition performance. To validate the effectiveness of the proposed scheme, we compare its performance with other state-of-the-art recognition and classification networks. Experimental results demonstrate the significant performance of the proposed MTL network in spectrum sensing, modulation recognition, and signal classification tasks. © 2024 IEEE.

关键词： Signal modulation

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Multi-layer network embedding on scc-based network with motif

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Digital Communications and Networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu Department of Communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China School of Information and Communication Engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing Multi-layer network Graph neural network Motif

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Adaptive dynamic surface control for quadrotor-slung load transportation system with uncertainties

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Science China(Technological Sciences) 2023年第10期66卷 2917-2929页

作者： DING Feng HUANG Jian SUN Chong AI Yong XU WenXia YANG ChenGuang School of Computer Science South-Central Minzu UniversityWuhan 430074China Key Laboratory of Ministryof EducationforImage Processing and Intelligent ControlHubei Key Laboratoryof Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Engineering Wuhan Institute of TechnologyWuhan 430205China Key Laboratory of Ministry of Education for Autonomous Systems and Networked Control Guangdong Engineering Technology Research Center of Control of Intelligent SystemsCollege of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Quadrotors play a significant role in our lives and are transforming our *** cable-suspended loads is an unavoidable quadrotor application trend and a hot research topic in the control ***,the load swing and unpredictability pose significant challenges to the quadrotor's *** this paper,an anti-swing controller with an inner-outer control strategy for the quadrotor-slung load transportation system is *** facilitate the controller design,the outer position dynamics are restructured in the form of ***,a virtual controller is created to force the underactuated states to the dynamic surface to ensure the position subsystem's *** improve robustness,an adaptive law is used to eliminate the effects of uncertain cable ***,a dynamic surface controller for the inner attitude subsystem is presented to drive the actual force to the virtual *** is demonstrated that the control strategy can stabilize the quadrotor despite mass and cable length *** results are provided to demonstrate the efficacy and durability of the proposed method.

关键词： quadrotor-slung load transportation system dynamic surface control adaptive law cascade system model uncertainties

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Motor imagery EEG signals classification based on attention mechanism and EEGNet

Motor imagery EEG signals classification based on attention ...

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2024 International Conference on Future of Medicine and Biological information Engineering, MBIE 2024

作者： Song, Yaru Qin, Yingmei Li, Shanshan Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education Tianjin300350 China

ISBN: (纸本)9781510682825

Brain-computer interface technology (BCI) enables users to directly control external devices by establishing an information transmission path between the brain and external devices. Brain-computer interfaces based on the motor imagination paradigm have also begun to enter various fields. Therefore, the research on the brain-computer interface encoding and decoding algorithm of the motor imagination paradigm is particularly important. This paper proposes a model based on attention mechanism CBAM and EEGNet to classify motor imagination electroencephalogram signals (MI-EEG), and verified it on a public data set. Compared with a single EEGNet model, it improved by 3.7%, which is 8.1% higher than the traditional FBCSP model. The experimental results show the effectiveness of the new CBAM-EEGNet model on the four classification tasks of motor imagery. © 2024 SPIE.

关键词： Electroencephalography

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Lower limb motor imagery EEG signals classification based on 1D-CNN-LSTM algorithm

Lower limb motor imagery EEG signals classification based on...

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2024 International Conference on Future of Medicine and Biological information Engineering, MBIE 2024

作者： Han, Chunxiao Hu, Yue Ren, Hui Chen, Wenjin Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781510682825

With the continuous development of the brain-computer interface (BCI) technology, the lower limb rehabilitation system based on Motor Imagery (MI) has graduallybecome a researchhotspot in the field of *** recognize the lower limbs MI, this paper designed an experimental paradigmfor MIlower limb MI and used the 1D-CNN-LSTMdeep learning algorithm to classify lower limb movement features from MI EEG signals. Compared with classical machine learning algorithms, the results showed that 1D-CNN-LSTM has relatively higher accuracy. Meanwhile, the paper built a real-time lower limb rehabilitation system based on the 1D-CNN-LSTM algorithm, which verifies the effectiveness and feasibility of the algorithm. The system provides an advanced and effective solution for brain-computer interfaces based on MI. © 2024 SPIE.

关键词： Image reconstruction

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Research on financial social public opinion communication model based on variation mechanism 6

Research on financial social public opinion communication mo...

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6th International Conference on Electronic information technology and Computer Engineering, EITCE 2022

作者： Huang, Maojun Hong, Mei Dong, Lin Yuan, Da Key Laboratory of Intelligent Information Processing Shandong Technology and Business University Shandong Yantai264005 China

ISBN: (纸本)9781450397148

In the context of rapid development of the Internet, the place of spreading financial public opinion is converted from traditional offline places to major online social platforms. Mastering the development mechanism of financial social opinion dissemination on online social media can effectively estimate the length of influence of public opinion and the scope of affected people, and provide effective guidance to relevant staff. Based on the Susceptible Infected Recovered Model, this paper divides the people involved in opinion diffusion into commenters and discussers, and introduces the variation mechanism to design the Susceptible-comment-discussion-removal model, then simulates the model to study the effects of different initial states and parameters on the model, and finally verifies the validity of the model by combining the real data of stock bars. The simulation experiments and validation show that the model can effectively describe the spread of public opinion among the user groups of financial social platforms when it occurs, and provide a valid reference for related workers. However, the content of public opinion, the personal influence of communicators, and the lag effect of communication all have an impact on communication, and these issues need to be addressed in future research. © 2022 Association for Computing Machinery.

关键词： Social aspects

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