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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xinling Li Qingyan Wang Junping Zhang Yujing Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The remote sensing satellite system has steadily developed, and the availability of massive high-quality satellite remote sensing data has rapidly improved. The dynamic monitoring of land cover changes using hyperspectral data has received great attention. The existing change detection methods usually use the spatial correlation or spatial-spectral correlation of hyperspectral images, lacking an overall consideration of the three-dimensional temporal-spatial-spectral joint features, resulting in suboptimal change detection results. Given the considerations above, this paper proposes a SimAM multi-scale joint feature extraction network for hyperspectral image change detection. The proposed method first adopts SimAM multi-scale joint features network to consider the hyperspectral image as a whole, and extracts multi-scale temporal-spatial-spectral joint features from the network. Then, uses multi-scale feature weighted fusion module to weight different scale features after simple fusion, highlighting the change regions. Finally, adopts the batch-balance measurement module to measure the similarity of the bi-temporal fusion features and output the change detection result map. Experiments show that on two public datasets, the proposed method can achieve a good change detection effect.

关键词： Satellites Correlation Fuses Land surface Euclidean distance Feature extraction Monitoring

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Hyperspectral Image Classification Method Based On Node Similarity Feature Fusion

Hyperspectral Image Classification Method Based On Node Simi...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jiameng Wang Qingyan Wang Junping Zhang Yujing Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

There is abundant spectral and spatial information in Hyperspectral images (HSI). However, there exists a limitation of not using spatial information sufficiently in HSI classification. Besides, there is the limitation of mononuclear in feature extraction, resulting in insufficient feature extraction and insufficient utilization of data information. In view of these problems, a node similarity semi-supervised classification method of multiscale feature is proposed to break the limitation of mononuclear and achieve full extraction of spatial information. First, to extract pixel-level features, a three-dimensional (3-D) multiscale convolutional neural network (CNN) is used. Second, based on node similarity superpixel graph U-Net (NSGUNet) is proposed to extract superpixel-level features. Finally, the above two features are weighted fusing, the fused features are classified by sparse graph regularization. Experiments on three datasets illustrate that the proposed method is effective.

关键词： Accuracy Geoscience and remote sensing Feature extraction Convolutional neural networks Data mining Hyperspectral imaging Image classification

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Joint Classification Of Hyperspectral And LiDAR Data Based On Heterogeneous Attention Feature Fusion Network

Joint Classification Of Hyperspectral And LiDAR Data Based O...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zhaoyang Wang Qingyan Wang Junping Zhang Xintao Liang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The fusion of hyperspectral image (HSI) and LiDAR data for classification has gained widespread attention. However, the current fusion methods still have limitations on the use of heterogeneous data information and the interaction of heterogeneous data features. Therefore, we propose a classification method based on heterogeneous attention feature fusion network (HAFF-Net). Firstly, The convolutional neural network is employed to capture local spatial features from multi-scale inputs of heterogeneous data. Secondly, the heterogeneous feature attention module is designed to deeply fuse the extracted local spatial features and promote the interaction of heterogeneous data. Next, a transformer encoder is utilized to extract global spectral features. Finally, the two extracted features are classified by decision fusion using different classifiers. The proposed approach exhibits effectiveness through experimental results on two datasets.

关键词： Laser radar Fuses Convolution Soft sensors Geoscience and remote sensing Feature extraction Transformers

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Design of Accelerated Reliability Validation Plan for Smart Electrical Energy Meters under Time-Varying Environments 6

Design of Accelerated Reliability Validation Plan for Smart ...

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6th International Conference on System Reliability and Safety engineering, SRSE 2024

作者： Zhang, Youmei Li, Ning Zhang, Wei Chen, Qihong Li, Lin Qi, Jia Harbin University of Science and Technology School of Measurement-Control Technology and Communications Engineering Harbin China Marketing Service Centre of State Grid Xinjiang Electric Power Co. Urumqi China

ISBN: (纸本)9798350356083

To address the challenge of validating high-quality and long-lifetime products, this study developed a model that accounts for accelerated degradation under typical time-varying environments. Utilizing data from test bases and field operations in a certain region, a model was constructed to describe the impact of temperature stress on the lifespan of smart meters over time. The Arrhenius model was employed to create an acceleration model for time-varying temperatures influencing the lifespan of the smart electrical energy meters, enabling the determination of activation energy and dynamic acceleration factors under two distinct time-varying environmental conditions. Leveraging these acceleration factors, an accelerated reliability acceptance plan was designed specifically for smart electrical energy meters with Weibull-distributed lifetimes under time-varying stress conditions. © 2024 IEEE.

关键词： Weibull distribution

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Data Security Storage Mechanism Based on Blockchain Network

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Computers, Materials & Continua 2023年第3期74卷 4933-4950页

作者： Jin Wang WeiOu Wenhai Wang RSimon Sherratt Yongjun Ren Xiaofeng Yu School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410004China School of Control Science and Engineering Zhejiang UniversityHangzhou310058China School of Systems Engineering The University of ReadingReadingRG66AYUK School of Computer Engineering Research Center of Digital Forensics of Ministry of EducationNanjing University of Information Science&TechnologyNanjing210044China School of Business Nanjing UniversityNanjing210093China

With the rapid development of information technology,the development of blockchain technology has also been deeply *** performing block verification in the blockchain network,if all transactions are verified on the chain,this will cause the accumulation of data on the chain,resulting in data storage *** the same time,the security of data is also challenged,which will put enormous pressure on the block,resulting in extremely low communication efficiency of the *** traditional blockchain system uses theMerkle Tree method to store *** verifying the integrity and correctness of the data,the amount of proof is large,and it is impossible to verify the data in batches.A large amount of data proof will greatly impact the verification efficiency,which will cause end-to-end communication delays and seriously affect the blockchain system’s stability,efficiency,and *** order to solve this problem,this paper proposes to replace the Merkle tree with polynomial commitments,which take advantage of the properties of polynomials to reduce the proof size and communication *** realizing the ingenious use of aggregated proof and smart contracts,the verification efficiency of blocks is improved,and the pressure of node communication is reduced.

关键词： Blockchain cryptographic commitment smart contract data storage

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Construction of Industry-Teaching-Innovation Cases for Robot Training under the Integration of Virtuality and Reality 14

Construction of Industry-Teaching-Innovation Cases for Robot...

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14th International Conference on Educational and Information technology, ICEIT 2025

作者： Jin-Gang, Jiang Jiang-Long, Xiong Ya-Ping, Wang Kai-Rui, Wang Tao, Shen Yudong, Bao National Experimental Teaching Demonstration Center for Mechanical Engineering Experiment and Practice Harbin University of Science and Technology Harbin China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin China School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin China

ISBN: (纸本)9798331540883

Aiming to address the current problems in robot training teaching, this paper focuses on the construction of industry-teaching-innovation cases for robot training under the integration of virtuality and reality, such as the disconnection between training content and industry practice, delays in digital transformation, and the lack of training resources. Relying on the intelligent manufacturing industry academy (IMIA), the teaching model integrates virtual simulation training with practical operation to enhance students' practical skills and innovative abilities. The study introduces complex technical challenges faced by enterprises in production, combining a dual-mentor system and a collaborative resource-sharing mechanism between school and enterprises. This ensures that students can master key skills required by enterprises during training, while innovation and entrepreneurship education is integrated throughout the whole training process to stimulate students' creative thinking and entrepreneurial mindset. © 2025 IEEE.

关键词： Students

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Lighting control with Myo armband based on customized classifier

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The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 106-116页

作者： Jiang Yujian Yang Xue Zhang Junming Song Yang Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China

This paper focuses on gesture recognition and interactive lighting *** collection of gesture data adopts the Myo armband to obtain surface electromyography(sEMG).Considering that many factors affect sEMG,a customized classifier based on user calibration data is used for gesture *** this paper,machine learning classifiers k-nearest neighbor(KNN),support vector machines(SVM),and naive Bayesian(NB)classifier,which can be used in small sample sets,are selected to classify four gesture *** performance of the three classifiers under different training parameters,different input features,including root mean square(RMS),mean absolute value(MAV),waveform length(WL),slope sign change(SSC)number,zero crossing(ZC)number,and variance(VAR)are tested,and different input channels are also *** results show that:The NB classifier,which assumes that the prior probability of features is polynomial distribution,has the best performance,reaching more than 95%***,an interactive stage lighting control system based on Myo armband gesture recognition is implemented.

关键词： Myo armband gesture recognition surface electromyography customized classifier lighting control

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A Method for Constructing an Olfactory Dataset Based on fNIRS 9

A Method for Constructing an Olfactory Dataset Based on fNIR...

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9th International Conference on Systems and Informatics, ICSAI 2023

作者： Li, Wei He, Haobo Li, Guang Kuang, Lidan Zhang, Jin Changsha University of Science and Technology School of Computer and Communication Engineering Changsha410076 China Zhejiang University School of Control Science and Engineering Hangzhou310027 China

ISBN: (纸本)9798350383706

Biomimetic olfaction models have been applied to various fields such as image recognition, text classification, electroencephalography (EEG) recognition, and spatio-temporal sequence prediction. However, the challenge of obtaining olfactory data complicates the construction of olfactory datasets, ultimately resulting in a scarcity of applications for biomimetic olfaction models in olfactory tasks. In this work, we begin by conducting a comprehensive comparison of existing biomimetic olfactory models from various aspects such as structure, degree of biomimicry, and performance. Following this, prefrontal lobe olfactory data from ten subjects were collected for three different odors using functional Near-Infrared Spectroscopy (fNIRS). Finally, the data underwent denoising through the use of various data processing methods, and the quantity of the olfactory dataset was expanded. The olfactory dataset constructed in this study can be used to evaluate the performance of biomimetic olfactory models in processing olfactory tasks, which may aid in advancing the development of these models in real-world olfactory applications. © 2023 IEEE.

关键词： Image recognition

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Zero-Sample Multiple Fault Diagnosis of Diesel Engine Based on Attribute Prediction 43

Zero-Sample Multiple Fault Diagnosis of Diesel Engine Based ...

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43rd Chinese control Conference, CCC 2024

作者： Su, Qian Lv, Xuantao Qiu, Zhengxing Liu, Zhenxing Wuhan University of Science and Technology Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan430081 China Wuhan University of Science and Technology School of Information Science and Engineering/School of Artificial Intelligence Wuhan430081 China Wuhan Maritime Communication Research Institute Wuhan430205 China

ISBN: (纸本)9789887581581

A zero-sample fault diagnosis method based on fuzzy fault feature representation for attribute prediction is proposed to address the challenge of insufficient fault data samples covering all types of multiple faults in actual diesel engine operations. Through simulation analysis of single and multiple fault operational states of diesel engines using AVL-boost ledR simulation software, along with the variation patterns of single fault thermodynamic parameters and the coupling patterns of multiple faults, category information for multiple fault diagnosis is provided. Gaussian membership functions are employed to describe fault features, and an SVM attribute trainer is established using single fault data to predict attribute values for multiple faults without data samples. The nearest neighbor search algorithm is utilized to infer the most suitable multiple fault category. Experimental results demonstrate that the proposed method exhibits excellent performance in the diagnosis of multiple fault in diesel engines, with a prediction accuracy of 96.62% for fault attributes and a final multiple fault diagnosis accuracy of 97.31%, thereby providing a basis for zero-sample multiple fault diagnosis in diesel engines. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Diesel engines

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Fixed-Time Consensus-Based Nash Equilibrium Seeking

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 267-269页

作者： Mengwei Sun Jian Liu Lu Ren Changyin Sun the Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China the School of Artificial Intelligence and the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationAnhui UniversityHefei 230601China

Dear Editor,This letter examines the fixed-time stability of the Nash equilibrium(NE)in non-cooperative *** propose a consensus-based NE seeking algorithm for situations where players do not have perfect information and communicate via a topology *** proposed algorithm can achieve NE in a fixed time that does not depend on initial conditions and can be adjusted in advance.

关键词： Fixed seeking letter

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