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2022 International Conference on Signal processing and Communication Technology, SPCT 2022

作者： Gao, Shuai He, Tao Key Laboratory of Optoelectronic Technology and Intelligent Control Ministry of Education Lanzhou Jiaotong University China Institute of Automatic Control Lanzhou Jiaotong University China

ISBN: (纸本)9781510664333

With the vigorous promotion of railway infrastructure construction in china, higher requirements have been put forward for railway running safety. Railway signal monitoring equipment, as the key equipment to ensure driving safety, find and solve the fault, has a broad development prospect in the process of railway system modernization[1]. By analyzing the practical significance of railway signal training system and referring to the technical conditions of railway signal centralized monitoring system, the DC switch acquisition module of railway signal training system is developed and designed based on the microcontroller of Cortex-M4 kernel. The acquisition board has unique advantages in power consumption, acquisition speed and scalability, high integration, good reliability, its accuracy and stability meet the requirements of railway signal training, has a broad space for development, and is of great significance for the pre-job training of railway related majors and the improvement of teaching quality. © 2023 SPIE.

关键词： Railroads

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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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Segmentation of railway region of interest based on image recognition 2

Segmentation of railway region of interest based on image re...

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2nd International Conference on Algorithms, Microchips, and Network Applications, AMNA 2023

作者： Gao, Hailong He, Tao Key Laboratory of Optoelectronic Technology and Intelligent Control Ministry of Education Lanzhou Jiaotong University China Institute of Automatic Control Lanzhou Jiaotong University China

ISBN: (纸本)9781510664791

In recent years, with the continuous progress of china's high-speed railway construction, railways play an important role in the country's economic development and provide a strong driving force for people to live a better life. The country has put forward higher requirements for train running safety. Track foreign body intrusion is one of the important factors threatening the safe running of trains. In order to ensure the safe operation of the train, the detection of foreign body intrusion on the track has become the top priority. It is necessary to further narrow the detection scope in the actual railway scene graph,and only need to detect whether there is a foreign object invasion in the region of interest. Therefore, the division of the railway area of interest is particularly important. In this paper, the improved Sobel image edge detection algorithm is used for edge detection. The least square method cubic polynomial was used for track line fitting. The track line is translated outward to obtain the region of interest. The division of the region of interest improves the accuracy of the prediction. © 2023 SPIE.

关键词： Least squares approximations

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Design of Load Frequency controller for Power System Based on Equivalent Input Disturbance Method 4

Design of Load Frequency Controller for Power System Based o...

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4th IEEE New Energy and Energy Storage System control Summit Forum, NEESSC 2024

作者： Zhang, Jianrong Xu, Hang Wang, Hongzhang Zhang, Chuanke China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan China

ISBN: (纸本)9798350389012

In the power system, due to the instability of the external environment, safe and stable operation cannot always be guaranteed, as it frequently encounters varying degrees of external disturbances. In order to mitigate the effects of these disturbances on the system, the power system can operate safely and stably, In this paper, a power system load frequency control (LFC) based on Equivalent Input Disturbance (EID) method is proposed from the perspective of active disturbance suppression. Firstly, the disturbances present in the environment are unified as external disturbances, and then a single area the electric power system model with external disturbance was constructed. Then, a controller algorithm based on EID was designed using EID equivalent processing method and linear matrix inequality method to address the issue of external interference in the power system. Finally, a numerical example is used to validate the effectiveness and accuracy of the controller by simulating with two aspects, fixed perturbation and random perturbation, respectively. © 2024 IEEE.

关键词： Linear matrix inequalities

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Feedback Generative Adversarial Network With Channel-Space Attention for image-Based Optimal Path Search Planning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4293-4307页

作者： Sun, Tao Li, Jian-Sheng Zhang, Yi-Fan Ru, Xin-Feng Wang, Ke Tsinghua University Department of Automation Beijing100084 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tongji University School of Economics and Management Shanghai200092 China

Path planning and seeking is one of the most challenging and interesting problems in the field of artificial intelligence. In this article, we propose a new image-based path planning algorithm to overcome traditional design concepts based on complex topological networks. Specifically, a novel feedback generative adversarial network learning model with channel-space attention (CSA-FGAN) is developed to search and plan an optimal path. It is worth noting that the input and output of the proposed feedback learning model are RGB images with complex spatial obstacle environment maps and RGB images with feasible paths, respectively. In particular, in order to further enhance the feature extraction ability and path prediction accuracy of image data, the feedback attention mechanism controls and improves the depth of the network by forming a closed loop of the proposed learning model. Final, three application scenario image examples are conducted to verify the superiority of the proposed path planning policy. © 2020 IEEE.

关键词： Motion planning

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A New Island Genetic Algorithm for Path Planning Problems *

A New Island Genetic Algorithm for Path Planning Problems *

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhang, Jinghao Chen, Zhe Li, Ning Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9798350327182

Genetic algorithm (GA) is an effective method for path planning problems. As a powerful variant of GA, island genetic algorithm (IGA) has considerable improvement in performance. In this paper, a new island model of GA is proposed to avoid the premature phenomenon and achieve better efficiency. First, a new method of creating subpopulations is presented based on K-means to expand the searching area for the optima. Meanwhile, recombining subpopulations is proposed as a new strategy to improve the diversity of populations and save computational time. Moreover, a method is designed based on Monte Carlo sampling to handle the uncertainty of maps. Comparative experiments are presented to verify the efficiency of the proposed algorithm. Then, a proper number of samples is found by simulation to balance the accuracy and the time cost of Monte Carlo sampling. © 2023 IEEE.

关键词： Genetic algorithms

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Tissue P Systems with Look-Ahead Mode

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Chinese Journal of Electronics 2025年第1期23卷 81-86页

作者： Yun Jiang Tao Song Zheng Zhang School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P system with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and helping implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a space-time tradeoff, which is illustrated with a polynomial solution to 3-coloring problem.

关键词： Computers Computational modeling Medical services Parallel processing Polynomials Computational efficiency Registers Business

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Dim-light image processing strategy rooted in improved dual-branch generative adversarial network

Dim-light image processing strategy rooted in improved dual-...

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2024 International Conference on image processing and Artificial Intelligence, ICIPAl 2024

作者： Li, keyi Wei, Zongshou Key Laboratory of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou Jiaotong University Lanzhou730070 China Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province Lanzhou Jiaotong University Lanzhou730070 China

ISBN: (纸本)9781510681514

images taken in dim lighting conditions usually suffer from drawbacks such as weak contrast along with unwanted interference. As a solution to this issue, this paper suggests a dim-light image processing strategy rooted in an improved dual-branch adversarial generative model. This method utilizes a generator network that combines a dim-light processing module and an image segmentation module, along with a patch discriminator network, trained using an adversarial loss function. The experiments demonstrate that the suggested approach for improving low-light image quality produces visually more captivating results when applied to real-world datasets. Moreover, it surpasses existing methods in terms of both preserving image structure and reducing noise. © 2024 SPIE.

关键词： Generative adversarial networks

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Structure-constrain Source Free Domain Adaptation with Regularized Knowledge Distillation of Source Model 13

Structure-constrain Source Free Domain Adaptation with Regul...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Yang, Dan Peng, Xin Su, Cheng Tan, Dayu Chen, Chaoyang Zhong, Weimin Ministry of Education East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing Anhui Hefei230601 China School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9798350361674

Transfer learning aims to leverage the knowledge of the source domain to help the learning of unlabeled target domain models. However, all conventional transfer learning methods assume that samples from source and target domains are always freely accessible. However, this assumption is rarely plausible in real-world due to data privacy. To combat this challenge, we introduce Structure-constrain Source Free Domain Adaptation with regularized Knowledge Distillation of source model (SSFDA-KD). Our method is based on the observations that a deterministic classification result can be obtained when the target data distribution aligns with the source data distribution, and a well-trained model not only yields a deterministic classification for a sample but also has clear category boundaries, which implies samples that are close together belong to the same category. From those, we first generate the source model with labeled source data, which is regarded as a well-trained model. Then, we identify target prototypes with lower self-entropy and assign the pseudo-labels to other samples according to the neighborhood structure. Finally, we refine the target model by minimizing prediction loss, constraining internal structure via triplet loss, and reducing knowledge distillation loss. Experiments of fault diagnosis based on WWTPs are conducted to validate its effectiveness. © 2024 IEEE.

关键词： Domain Knowledge

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TMMM: Transformer in Multimodal Sentiment Analysis under Missing Modalities

TMMM: Transformer in Multimodal Sentiment Analysis under Mis...

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International Joint Conference on Neural Networks (IJCNN)

作者： Huanyu Wu Siyang Li Dongrui Wu Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

The cross-task gap presents a significant challenge for multimodal models because of the differences in input-output workflows. For instance, multimodal pre-trained transformers may encounter uni-modal data during testing. To mitigate the gap, this paper introduces a Transformer in Multimodal Sentiment Analysis under Missing Modalities (TMMM) aims to perform well using missing-modal data during testing. TMMM uses a missing multimodal training approach to prevent accuracy degradation in testing. At the same time, a new network architecture allows the model to reconstruct missing modalities during testing. Classification token fusion and Mixture-of-Experts structures further enhance the model’s performance. A pre-training method utilizing contrastive learning, which can construct negative samples with positive samples, is proposed to overcome insufficient labeled data. Our experiments demonstrated the effectiveness of TMMM on two datasets with no modalities missing, i.e., it consistently achieved the highest classification accuracy and Macro-F1, which outperformed the best state-of-the-art baseline on each dataset by about 2% and 2.5%. Additionally, TMMM usually performs better than other baselines on datasets with missing modalities during testing.

关键词： Training Sentiment analysis Accuracy Contrastive learning Network architecture Transformers Brain modeling

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