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2021 OES China Ocean Acoustics, COA 2021

作者： Li, Yuelin Sun, Chao Liu, Yuechan Ai, Shiqin Harbin University of Science and Technology Harbin School of Measurement-Control Technology and Communication Engineering China Harbin City150080 China

ISBN: (纸本)9781728181905

Taking the heat exchange tube in the condenser as the research object, the three-dimensional finite element model of the heat exchange tube and the Internal and external fluid of pipe is established, and the bidirectional fluid-solid coupling calculation of the heat exchange tube is carried out. The time-domain and frequency-domain curves of lift, drag and displacement of the heat exchange tube and the time-domain and frequency-domain curves of the pressure pulsation in the tube are obtained. At the same time, the acoustic simulation calculation is carried out for the vibration noise of the heat exchange tube. The time domain and frequency domain curves of sound pressure near the heat exchange tube are obtained. The simulation results show that the frequency of pressure pulsation corresponds to the frequency of lift and drag. The flow velocity in the tube studied in this paper will affect the amplitude and waveform of the pressure pulsation but will not affect its frequency. The sound pressure frequency of the upper and lower sides of the heat exchange tube only corresponds to the lift frequency, and the sound pressure frequency on the left and right side corresponds to the lift and drag frequencies. © 2021 IEEE.

关键词： Flow velocity

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Uplink Security Analysis of Hybrid RF-FSO Cooperative Satellite-Aerial-Terrestrial Networks

Uplink Security Analysis of Hybrid RF-FSO Cooperative Satell...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Ma, Yuanyuan Xu, Zhan Tian, Lu Zhi, Ruxin Ding, Xuhui Bu, Xiangyuan Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China School of Information and Electronics Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9798350370218

This work investigates the secrecy outage per-formance of the uplink transmission of hybrid radio-frequency (RF)-free-space optical (FSO) cooperative satellite-aerial-terrestrial network (SATN). Specifically, we adopt most popular content wireless caching scheme at aerial relay, while a group of eavesdropping aerial terminals (Eves) try to over-hear the confidential information. In particular, considering the transmit antenna selection (TAS) at the source and the maximal ratio combining (MRC) at the aerial relay, and the randomness of satellite receiver, relay, and Eves, the secrecy outage performance of the cooperative uplink transmission in the considered SATN is investigated and a closed-form analytical expression for the end-to-end secrecy outage probability (SOP) is derived. Finally, Monte-Carlo simulations are shown to verify the accuracy of our analysis. © 2023 IEEE.

关键词： radio-frequency (RF)-free-space optical (FSO) satellite-aerial-terrestrial network (SATN) secrecy outage prob-ability (SOP) uplink transmission wireless caching

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Human Activity Classification Using Supervised Machine Learning Algorithms 1

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19th control Instrumentation System Conference, CISCON 2022

作者： Akhila Rao, Vidya S. Jayalakshmi, N.S. Pai, Smitha N. Kolekar, Suchetha V. Department of Instrumentation and Control Engineering Manipal Academy of Higher Education Manipal India Department of Electrical and Electronics Engineering Manipal Academy of Higher Education Manipal India Department of Information and Communication Technology Manipal Academy of Higher Education Manipal India Manipal Institute of Technology Manipal Academy of Higher Education Manipal India

ISBN: (数字)9789819995547

ISBN: (纸本)9789819995530

In this paper, using smartphones the human static and dynamic activities are measured via the inbuilt inertial measurement sensors. The dataset obtained from the experiments carried out on thirty individuals contains all the data regarding the angle change with different activities like walking, laying, sitting, etc. The machine learning techniques are applied to this dataset right from the onset of data cleaning to eliminate outliers and missing values and exploratory data analysis (EDA) to visualize the data and find relation between the variables. For eliminating the redundant data and improve execution time, a feature engineering technique called principal component analysis (PCA) is employed on the dataset. Finally, machine learning algorithms such as logistic regression, support vector machine and linear discriminant analysis are applied to the processed dataset. The accuracy is compared with all the algorithms with logistic regression outperforming the other two mentioned classifiers. These classifier models are found to be useful in applications where it is vital to monitor sensor data such as elderly monitoring, patient rehabilitation, fall detection and so on. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Graph Convolutional Networks with Visual Masking and Social Interaction Models for Pedestrian Trajectory Prediction

Graph Convolutional Networks with Visual Masking and Social ...

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Consumer Electronics and Computer engineering (ICCECE), 2021 IEEE International Conference on

作者： Guopei Zeng Luping Wang School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China Zhejiang Aerospace Runbo Measurement and Control Technology Co. Ltd Zhejiang China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

Pedestrian trajectory prediction is critical for autonomous driving, crowd analysis, and urban surveillance. To address insufficient interaction modeling in existing methods, we propose two enhancements. First, a field-of-view(FoV)-aware masking mechanism filters irrelevant interactions by dynamically adjusting to pedestrian distances and motion directions. Second, we introduce a more detailed modeling of the influence among pedestrians, replacing the traditional modeling based on reciprocal of distance. This model, integrated with FoV masks to construct sparse adjacency matrices for graph convolution. A temporal convolutional network then predicts trajectories as bivariate Gaussian distributions. Evaluations on ETH and UCY benchmarks demonstrate the effectiveness of our method.

关键词： Analytical models Visualization Pedestrians Filters Surveillance Predictive models Benchmark testing Vectors Trajectory Sparse matrices

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Research on Grid Connection control Strategy of Building Energy Router Based on Pre Synchronous VSG control technology 1

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8th Purple Mountain Forum on Smart Grid Protection and control, PMF 2023

作者： Guan, Baojin Wang, Hui Zhang, Xiaohua Yin, Pan Meng, Xiangping Safe Operation of Smart Distribution Network of the Measurement and Control Joint Engineering Research Center Changchun Institute of Technology Changchun Jilin130012 China State Grid Jilin Electric Power Co. Ltd. Yanbian Power Supply Company Jilin Yanji130012 China Jilin Institute of Chemical Technology Jinlin Jilin130012 China

ISBN: (数字)9789819992515

ISBN: (纸本)9789819992508

Aiming at the problem of unstable DC bus connection in building energy routers, this paper proposes a grid connection control strategy for building energy routers based on pre-synchronous virtual synchronous generator (VSG) control technology. Firstly, an energy router topology is designed, and secondly, the pre-synchronous VSG is analyzed. Pre-synchronous VSG control is adopted for the DC bus connection in the energy router to maintain the stability of the system and reduce the voltage and current impact of the common coupling point. In this paper, the simulation model of pre-synchronous VSG control energy router connected to the grid is established by MATLAB/simulink. In MATLAB, simulation results show that the pre-synchronous virtual synchronous machine (VSG) control has the characteristics of small overshoot. The proposed control strategy proposes a new solution for the grid-connected operation of energy routers. © 2024, State Grid Electric Power.

关键词： MATLAB

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Performance analysis of Polar Codes in a Visible Light communication System 4

Performance analysis of Polar Codes in a Visible Light Commu...

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4th National Conference on communication Systems, NCOCS 2022

作者： Vaz, Aldrin Claytus Hegde, Navya Thirumaleshwar Shetty, Akhil Appu Department of Electronics and Communication Engineering St Joseph Engineering College Vamanjoor Karnataka Mangaluru575028 India Department of Aeronautical and Automobile Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India

One of the vital entity of any communication systems is Channel coding, which leads to the design of high performance codes for future wireless systems having low complexity encoder and decoder design. These systems will have a requirement of operating in highly reliable conditions, maximum throughput, and low and high code rates and to work with short and long information messages. Polar codes are one of the promising error correcting channel codes that can be used in these situations to obtain maximum throughput and coding gain in a communication systems because of their capacity approaching performance and finds interests in Satellite communication and 4G/5G services. These codes uses the concept of channel polarization to be constructed. The work proposed in this paper focusses on the Bit Error Rate evaluation and analysis of the Polar codes using traditional approach and Deep learning approach. The feedforward deep learning networks using different activation functions were used for the Deep learning approach. The Successive Cancellation algorithm and its variant using List decoding were used as traditional decoding methodology. The results obtained using Deep learning approach were satisfactory and was matching as per the traditional decoding. © Published under licence by IOP Publishing Ltd.

关键词： Decoding

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Fiber Microcavity Lasers with Complex Lasing

Fiber Microcavity Lasers with Complex Lasing

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Frontiers in Optics + Laser Science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser Science 2023

作者： Zhu, Hongyang Li, Zhenning Tianjin Key Laboratory of Quantum Precision Measurement Tianjin Navigation and Instrument Institute Tianjin300131 China Fiber Optics Research Centre School of Information and Communication Engineering University of Electronic Science & Technology of China Chengdu611731 China

A fiber microcavity laser with multi-mechanism emission is proposed. Due to boundary effect of cavity and scattering of the gain medium, different mechanisms of lasing can be obtained by changing cavity length and pum... 详细信息

ISBN: (纸本)9781957171296

关键词： Effective refractive index Fiber lasers Hollow core fibers Q switched lasers Random lasers Scattering media

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GRU-Net: Gaussian Attention Aided Dense Skip Connection Based MultiResUNet for Breast Histopathology Image Segmentation 28th

GRU-Net: Gaussian Attention Aided Dense Skip Connection Base...

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28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024

作者： Roy, Ayush Pramanik, Payel Ghosal, Sohom Valenkova, Daria Kaplun, Dmitrii Sarkar, Ram Department of Electrical Engineering Jadavpur University Kolkata700032 India Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Department of Electronics and Communication Engineering International Institute of Information Technology Chhattisgarh India Department of Automation and Control Processes Saint Petersburg Electrotechnical University LETI Saint Petersburg Russia Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China

ISBN: (纸本)9783031669545

Breast cancer is a major global health concern. Pathologists face challenges in analyzing complex features from pathological images, which is a time-consuming and labor-intensive task. Therefore, efficient computer-based diagnostic tools are needed for early detection and treatment planning. This paper presents a modified version of MultiResU-Net for histopathology image segmentation, which is selected as the backbone for its ability to analyze and segment complex features at multiple scales and ensure effective feature flow via skip connections. The modified version also utilizes the Gaussian distribution-based Attention Module (GdAM) to incorporate histopathology-relevant text information in a Gaussian distribution. The sampled features from the Gaussian text feature-guided distribution highlight specific spatial regions based on prior knowledge. Finally, using the controlled Dense Residual Block (CDRB) on skip connections of MultiResU-Net, the information is transferred from the encoder layers to the decoder layers in a controlled manner using a scaling parameter derived from the extracted spatial features. We validate our approach on two diverse breast cancer histopathology image datasets: TNBC and MonuSeg, demonstrating superior segmentation performance compared to state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Gaussian distribution

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Research on Fault Diagnosis Method and Application of Gas Turbine Based on Acoustic Imaging technology

Research on Fault Diagnosis Method and Application of Gas Tu...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Yan, Wen Hu, Mingliang Wen, Fei Guo, Peipei Guo, Ziang AVIC Shanghai Aviation Measurement & Control Technology Research Institute Shanghai201601 China Xi'an Aeronautics Computing Technique Research Institute AVIC Xi'an710068 China Department of Electronics College of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Aviation Technology for Fault Diagnosis and Health Management Technology Shanghai201601 China

Gas turbine health management is of great significant for enhancing flight safety and reducing maintenance costs. Based on the architecture of gas turbine fault identification system, a multi-arm spiral microphone array with high positioning accuracy, high beam resolution, and strong anti-interference capability is designed in this paper with simulation and experiment. On this basis, by utilizing multi-channel acoustic digital acquisition and analysis equipment, high-precision, wide dynamic range, and high-real-time acquisition of audio data from the combustion chamber of gas turbines are achieved. An audio data analysis strategy based on feature extraction and an autoencoder network construction strategy are proposed, fulfilling the imaging of audio data from the combustion chamber of gas turbines, which can effectively identify gas turbine faults. Experiments conducted on the platform of the multi-arm spiral microphone array indecates that the proposed fault detection strategy has an accuracy rate of over 98%. This is of great theoretical significance and practical value for enhancing the level of gas turbine fault detection, and improving the performance, reliability, and lifespan of gas turbine systems. © The Institution of engineering & technology 2024.

关键词： Combustion chambers

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Modulation classification analysis of CNN model for wireless communication systems

AIMS Electronics and Electrical Engineering

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AIMS Electronics and Electrical engineering 2023年第4期7卷 337-353页

作者： Tamizhelakkiya, K. Gauni, Sabitha Chandhar, Prabhu Department of Electronics and Communication Engineering SRM Institute of Science and Technology SRM Nagar Kattankulathur Tamil Nadu Chennai India Autosys Control Systems India Pvt Ltd. Tamil Nadu Chennai India Chandhar Research Labs Pvt Ltd. Tamil Nadu Chennai India

Modulation classification (MC) is a critical task in wireless communication systems, enabling the identification of the modulation class in the received signals. In this paper, we analyzed a novel multi-layer convolutional neural network (CNN) to extract hierarchical features directly from the raw baseband samples. Moreover, we compared the training and testing accuracy of the CNN model for various decimation rates, input sample size and the number of convolutional layers. The results showed that the three-layer CNN model provided better classification accuracy with less computation cost. Furthermore, we observed that the MC performance of the proposed CNN model was better than the other deep learning (DL) and cumulant-based models. © 2023 the Author(s), licensee AIMS Press.

关键词： Convolutional neural networks

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