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检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

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3rd international conference on signal & data processing, icsdp 2023

3rd International Conference on Signal & Data Processing, IC...

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3rd international conference on signal and data processing, icsdp 2023

ISBN: (纸本)9789819795772

The proceedings contain 51 papers. The special focus in this conference is on signal and data processing. The topics include: Toward Feature Preserving High-Resolution Virtual Try-On;Single-Qubit Quantum Teleportation Using Three-Qubit Greenberger–Horne–Zeilinger (GHZ) State as Entanglement Resource and Basis for Quantum Measurement;performance Analysis of Optical Networks Using Deep Reinforcement Learning;design of Intelligent Solar Cooling System with IoT Monitoring;Analytical Review of 5G NR Channel Coding Techniques LDPC and Polar Codes;exploring Deep Learning Models for Classifying Wind Profiler Doppler Power Spectrum Contaminated by Ground Clutter;Harmonic Minimization in a Three-Phase Network Using the SSA Algorithm and Instantaneous PQ Theory;Efficient Rice Yield Classification: Accelerating ANN processing on PYNQ-Z2 Processor;An Area Efficient And Improvised Fault-Tolerant FIR Filter Using Word Voter;FPGA-Based Implementation of Cuffless Blood Pressure Measurement Using Photoplethysmogram signal;the Influence of Hybrid Algorithm in Manet for Estimating the Capacity of Quality of Service;classification of Currencies as Authentic or Counterfeit: A data-Driven Approach;sentiment Analysis in Image Caption Generation;implementation of Hybrid Machine Learning Algorithms in Classification of Real and Fake Profiles;image Extraction for Linear Segment in 3D Space;Suppression of Electromagnetic Emission in Electric Vehicle for EMC;Generating F1-Score to Predict Parkinson Disease with CNN Algorithm;Security and Privacy Analysis of Internet of Medical Things (IoMT) Based Smart Care Homes;machine Learning Model Based on Deep Neural Networks for Emotion Detection Using Audio-Visual Modalities;enhancing the Leaf Disease Detection Through Convolutional Neural Network;a Computational Analysis of Climate Change Sentiment on Social Media;gaussian Processes for Automating Model Selection.

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Proceedings of the 3rd international conference on signal and data processing 1

Proceedings of the 3rd International Conference on Signal an...

引用

丛书名： Lecture Notes in Electrical Engineering

1000年

作者： Raghunath K. Shevgaonkar Debashis Adhikari Soumitra Keshari Nayak Febe de Wet

ISBN: (数字)9789819795789

ISBN: (纸本)9789819795772;9789819795802

This volume comprises the select proceedings of the 3rd international conference on signal & data processing - icsdp 2023. The contents focus on the latest research and developments in the field of artificial intelligence & machine learning, Internet of Things (IoT), cybernetics, advanced communication systems, VLSI embedded systems, power electronics and automation, MEMS/ nanotechnology, renewable energy, bioinformatics, data acquisition and mining, antenna & RF systems, power systems, biomedical engineering, aerospace & navigation. This volume will prove to be a valuable resource for those in academia and industry.

关键词： Control, Robotics, Mechatronics signal, Image and Speech processing Microwaves, RF and Optical Engineering Communications Engineering, Networks

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Noise reduction analysis of high slope deformation data based on the EMD-SG model 24

Noise reduction analysis of high slope deformation data base...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Duan, Qingda Xia, Hua College of Forestry Xinyang Agriculture and Forestry University Henan Xinyang China

ISBN: (纸本)9798400710834

The accuracy of high slope deformation data is crucial for slope stability assessment and disaster warning. However, a large amount of noise often exists in the actual monitoring data, which affects the quality of the data and the reliability of the analysis results. In view of this, this paper proposes a noise cancellation method for high slope deformation data based on empirical modal decomposition and SG filtering. Firstly, the original deformation data are decomposed into a number of intrinsic modal functions (IMFs) using EMD, then the decomposed IMF components are processed by SG filtering respectively, and finally the filtered IMF components are reconstructed to obtain the deformation data after noise cancellation. The effectiveness and superiority of the method is verified by processing and analyzing the deformation data of actual high slopes. © 2024 Copyright held by the owner/author(s).

关键词： Noise abatement

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A Multi-source Trajectory data Preprocessing Method and Implementation for Aircraft Track Fusion 24

A Multi-source Trajectory Data Preprocessing Method and Impl...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Zhou, Bo Chen, Yun Li, Jiayuan COMAC Flight Test Center Commercial Aircraft Corporation of China. Ltd. Shanghai Shanghai China

ISBN: (纸本)9798400710834

Currently, the trajectory data utilized for civilian flight operation surveillance is classified into various types, such as primary radar data, secondary radar data, ADS-B data, Beidou positioning data, etc. The fusion processing of trajectory data from multiple different sources and its application in flight surveillance have emerged as a trend. Nevertheless, distinct data possess diverse parsing methods, thereby demanding preprocessing of these data. Moreover, to fulfill engineering applications, the implementation of high-speed parallel processing of large volumes of data during the preprocessing stage is necessary. This paper offers a data preprocessing software design solution for multi-source trajectory fusion for the reference of relevant technicians. This approach leans towards the rapid preprocessing of data during engineering applications to better accomplish multi-source trajectory fusion. © 2024 Copyright held by the owner/author(s).

关键词： Manned space flight

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Comparative Analysis of Photodiode signal Conditioning Circuits 3rd

Comparative Analysis of Photodiode Signal Conditioning Circu...

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3rd international conference on signal and data processing, icsdp 2023

作者： Sasikala, G. Dwik, Shaher Department of Electronics and Communication Engineering School of Electrical and Communication Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600062 India

ISBN: (纸本)9789819795772

A photodiode plays a major role in most optical sensors. The output of a photodiode is current, so a signal conditioning circuit is used to convert the current signal to a voltage signal as well as amplify it. This paper presents a comparison in performance between two signal conditioning circuits for a photodiode. The first one is implemented using discrete elements, and the other one is implemented using a Programmable System-on-Chip (PSoC). The circuit mainly consists of a transimpedance amplifier (TIA) and a single level of amplification. Furthermore, a simulation of the circuit was performed using MATLAB. The results demonstrate that PSoC attained better accuracy and precision in performance for DC and low-frequency signals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： MATLAB

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Online Network Intrusion Detection Based on Self-Encoder Integration 24

Online Network Intrusion Detection Based on Self-Encoder Int...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Sun, Dongxu Li, Peng Pei, Lina Wei, Chuhang Co. Ltd. Hebei Shijiazhuang China School of School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China

ISBN: (纸本)9798400710834

With the development of information technology, network security problems have intensified, and the performance enhancement of network intrusion detection systems has attracted much attention In this paper, we propose an online system based on self-encoder integration that utilizes deep learning to improve detection accuracy and robustness Neural networks are popular for their ability to learn complex patterns, but training resources are in high demand and existing supervised schemes require expert labeling and regular updates. Therefore, this paper introduces Kitsune, which uses unsupervised, efficient online self-encoder integration to distinguish between normal and abnormal traffic and is optimized to improve detection efficiency In this paper, we experimentally validate that the optimized Kitsune achieves improvements in accuracy, recall, false-positive rate, false-negative rate. © 2024 Copyright held by the owner/author(s).

关键词： Network intrusion

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Proceedings of the 3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

Proceedings of the 3rd International Conference on Signal Pr...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

ISBN: (纸本)9798400710834

The proceedings contain 96 papers. The topics discussed include: study on attenuation characteristics of THz waves in dusty plasma with full ionization under multi-angle and multi-magnetic fields;research on the application of spatiotemporal feature analysis in radar target classification;research on secure authentication for cross-domain cloud edge collaborative communication based on attribute encryption;radar echo signals analysis and modeling for low-altitude target detection;a compressed storage system for power communication network traffic data based on microservices architecture;research on efficient development and management methods for satellite models;research on the environmental adaptation and optimization of unmanned driving road detection vehicles with ground penetrating radar;and achieving covert communication in UCRNs via energy harvesting and primary transmitter jamming.

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A Compressed Storage System for Power Communication Network Traffic data Based on Microservices Architecture 24

A Compressed Storage System for Power Communication Network ...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： He, Xi Gan, Rundong Wang, Ce Zhu, Xianfeng Hu, Qidi Chen, Yuxu Information Center of Guizhou Power Grid Co. Ltd. Guizhou Guiyang China China Southern Power Grid Digital Platform Technology Company Guangdong Guangzhou China

ISBN: (纸本)9798400710834

When dealing with large amounts of data, ensuring data consistency and synchronization may become a non-negligible problem due to the fact that the services in the microservice architecture are distributed on different servers. Therefore, this paper proposes a compressed storage system for power communication network traffic data based on microservice architecture. While coping with the massive amount of data generated in power communication networks, the system is combined with statistical methods to realize an efficient and reversible data compression and fusion model by encoding and converting the raw data. It supports protocol-independent and adaptive abnormal behavior detection. Experimental results show that the system combines the flexibility of microservice architecture and the advantages of data compression technology to realize efficient data storage and transmission. © 2024 Copyright held by the owner/author(s).

关键词： data consistency

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Visual Analysis of Time Series data for Multi-Agent Systems Driven by Large Language Models 24

Visual Analysis of Time Series Data for Multi-Agent Systems ...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Xu, Chao Zhang, Qi Li, Baiyan Wang, Anmin Bao, Jingsong College of Computer Science and Technology Donghua University Shanghai China College of Mechanical Engineering Donghua University Shanghai China

ISBN: (纸本)9798400710834

The application of digitalization in manufacturing involves using sensors to collect and transmit large amounts of data in real-time. These complex, timestamped sequence data require effective analytical support to drive the generation of analysis summaries. Visual analysis helps researchers identify hidden patterns by intuitively displaying complex data, but its implementation relies on specialized knowledge and a deep understanding of data analysis techniques. Moreover, the analysis process often requires users to recall and process large amounts of information, which increases the complexity of the analysis. Therefore, there is an increasing demand for intelligent visual analysis technology. Large language models, with their powerful reasoning, summarization, and code generation capabilities, provide the possibility of visual analysis for general users. We propose a large language model-based multi-agent framework that integrates domain knowledge to achieve an automated data analysis workflow, from data acquisition to analysis summarization, helping users extract valuable analytical results from complex data and improving both efficiency and experience. © 2024 Copyright held by the owner/author(s).

关键词： Interactive data Analysis

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Attack detection on multi-architecture Internet of Vehicles honeypots and response mechanism research 24

Attack detection on multi-architecture Internet of Vehicles ...

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3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Ning, Yuqiao Huo, Quanrui Mu, Shiyu Xue, Shihao China Automobile Data of Tianjin Co. Ltd. Tianjin China CATARC Intelligent and Connected Technology Co. Ltd. Tianjin China

ISBN: (纸本)9798400710834

Intelligent connected vehicles (ICVs) refer to a new vehicle type that utilizes advanced information and communication technology to enable information exchange among vehicles, between vehicles and roads, and between vehicles and the internet. Malicious actors may exploit vulnerabilities in ICVs to gain malicious control, steal data, or launch denial-of-service attacks, resulting in significant economic losses and personal harm. Therefore, it is crucial to research attack detection and response mechanisms for ICVs and build effective network defense systems to ensure the safe operation of these vehicles. However, different manufacturers may adopt different architectures, posing significant challenges to network security defense for these vehicles. To address this issue, this paper proposes an attack detection and response mechanism based on Docker container technology for Multi-Architecture Vehicle Honeypots (MAV-honeypots). The aim is to simulate ICVs under various architectures using honeypot technology, attracting and inducing attackers to carry out attacks, thus achieving identification, analysis, and response to attackers. © 2024 Copyright held by the owner/author(s).

关键词： Network security

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