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检索条件"任意字段=Proceedings of the 2023 5th International Conference on Big Data Engineering and Technology"

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Investigation of Cross-Polarization on GNSS-R Antenna 5

Investigation of Cross-Polarization on GNSS-R Antenna

引用

5th IEEE international conference on Electronic Information and Communication technology, ICEICT 2022

作者： Jia, Yan Xiao, Zhiyu Li, Wenmei Zou, Jiaqi Savi, Patrizia Han, Chong-Zhi Nanjing University of Posts and Telecommunications Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing210046 China Politecnico di Torino Department of Electronic and Telecommunication Torino10129 Italy School of Ocean Information Engineering Jimei University Xiamen China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

this paper investigates the requirements of the GNSS-Scatterometer. Remote sensing algorithms have been applied for extracting geophysical characteristics of the ground where the reflection of the GPS signal occurs. In particular, different characteristics of cross-polarization (X-pol) of antennas designed for GNSS-R experiments are tested and shown. this study is useful for GNSS-related experiments for improving the accuracy of parameter retrievals. © 2022 IEEE.

关键词： Polarization

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the Calibration of Inspection data on Juvenile theft Cases in 5G Context and IOT Age 6th

The Calibration of Inspection Data on Juvenile Theft Cases i...

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6th international conference on Smart Grid and Internet of things, SGIoT 2022

作者： Liu, Cheng-yong Wang, Zhi-xin Liang, Hui-lin Ye, Xiu-Wen College of Marine Culture and Law Jimei University Fujian Xiamen361021 China Higher School of Economics and Management Far Eastern Federal University Vladivostok Russia Yulin Normal University Guangxi China

ISBN: (纸本)9783031312748

In the context of 5g and IOT age, big data has many functions, and the core function of legal big data is to make predictions. However, there is a problem of data transmission errors, and all erroneous data signals cannot be ruled out. this article mainly takes juvenile theft cases as the starting point, and discusses the role of big data in the statistics of legal cases and the possibility of data transmission errors that may occur, and in the context of big data, for juvenile theft. Recidivism rates were studied and practical recommendations were made. Unlike other articles, this article integrates the Internet of things into judicial issues, aiming to better serve the law through technology. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： big data

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An Efficient Blockchain-Based Certificateless Anonymous Authentication Scheme for VANETs

An Efficient Blockchain-Based Certificateless Anonymous Auth...

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2023 international conference on Networking and Network Applications, NaNA 2023

作者： Bi, Changbing Tian, Youliang Li, Ta Wu, Shihong Zhou, Hua Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China College of Computer Science and Technology Guizhou University Guiyang550025 China Guizhou University Guizhou Province Key Laboratory of Cryptography and Block Chain Technology Guiyang550025 China Institute of Cryptography & Data Security Guizhou University Guiyang550025 China College of Big Data and Information Engineering Guizhou University Guiyang550025 China

ISBN: (纸本)9798350327380

Vehicle ad-hoc networks (VANETs) play a critical role in providing security and privacy protection for intelligent transportation systems. However, the limited network bandwidth and computing capacity within VANETs have resulted in existing authentication schemes having excessive computational overhead, which cannot meet the low-latency communication requirements of VANETs. To tackle these problems, we propose an efficient blockchain-based certificateless anonymous authentication scheme for VANETs. Firstly, we propose a novel signature scheme without bilinear pairing to reduce the computational overhead in VANETs. Secondly, we utilize blockchain to facilitate trusted information sharing. thirdly, we provide privacy-preserving through the use of anonymous keys, and enable tracing of vehicle identities in the event of malicious behavior. Finally, security analysis and simulation experiments demonstrate that our proposed scheme has lower communication and computational overhead, while satisfying various security requirements for VANETs, such as anonymity, unlinkability, and traceability. © 2023 IEEE.

关键词： Authentication

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Combining Traditional Stock Selection Models and Multi-factor Stock Selection Models: Achieving Dynamic Adjustments of Machine Learning Algorithms 24

Combining Traditional Stock Selection Models and Multi-facto...

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proceedings of the 2024 5th international conference on big data Economy and Information Management

作者： Jianlin Chen Wuhan University of Technology Wuhan Hubei China

ISBN: (纸本)9798400711862

Stock selection models which use machine learning (ML) techniques can capture the nonlinear influences of stock trends. However, there is a lack of comprehensive research on the combined use of various machine learning algorithms. this study bridges this gap by developing a new stock selection strategy that combines traditional stock selection models with machine learning multi-factor models. this study by using various machine learning algorithms to build a multi-factor stock selection model, and on each trading day, assigning corresponding weights based on the market performance of the previous \(n\) days according to the performance of different algorithms. the best-performing algorithms in each period can be selected through this method, and then the corresponding stock investments are selected. Finally, the experimental results show that the newly constructed stock selection strategy has excellent market performance.

关键词： Dynamic adjustment

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Bayesian Sampling Method Design Based on Hierarchical Model 5

Bayesian Sampling Method Design Based on Hierarchical Model

引用

5th international conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2023

作者： Yin, Yiting Xu, Wenxia Zhu, Liping Cheng, Wen Mo, Yani Lin, Ren School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin541004 China School of mathematics and data science Changji University Changji831100 China Guangzhou Jingyuan Pharmaceutical Research Co. LTD. Guangzhou510860 China

ISBN: (纸本)9781839539848

Bayesian sampling methods based on Hierarchical models Bayesian analysis methods are commonly used to estimate and infer the parameters of hierarchical models. In this paper, a sampling method based on the three-stage Bayesian hierarchical model is proposed by combining the relationship between layers and the posterior estimation of hierarchical Bayes. In the first stage, the data is modeled as a function with unknown parameters. In the second stage, after taking into account the covariate information, each parameter is assigned some form of distribution. In the Bayesian model, a third stage is required, specifying prior distributions for all parameters that define the distribution form of the second stage and the variance-covariance matrix. Based on Bayesian Maximum a posteriori estimation (MAPB) and the complete Bayes Markov Chain Monte Carlo (MCMC) algorithm are combined to solve it. the results show that the MCMC algorithm converges, and the model is well fitted and has good prediction ability. © the Institution of engineering & technology 2023.

关键词： Inference engines

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GCN-ICD: A Graph Convolutional Network for Icing Cover Detection 5th

GCN-ICD: A Graph Convolutional Network for Icing Cover Detec...

引用

5th international conference on 3D Imaging Technologies—Multidimensional Signal Processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Yang, Qi Zeng, Huarong Xiao, Shuzhou Huang, Huan Xie, Quan Electric Power Research Institute of Guizhou Power Grid Co. Ltd Guiyang550002 China College of Big Data and Information Engineering College of Physics Guizhou University Guiyang550025 China

ISBN: (纸本)9789819751808

We propose a novel icing prediction model consisting of a heterogeneous information embedding layer, a direction-aware information aggregation layer, and a detection layer. In particular, we represent transmission lines as nodes in a graph and establish edges based on their connections. Taking visual images and meteorological data as the content of nodes, we design a large language model (LLM) based embedding layer to fuse the heterogeneous information. then, the direction-aware information aggregation layer efficiently absorbs and aggregates information from neighbor nodes while considering the edge weights and directions. Finally, with the obtained representations of nodes, the detection layer is able to measure the icing probability of the transmission line. By conducting extensive experiments on a real-world dataset, we demonstrate the superiority of our proposed model compared to baseline methods. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Visual languages

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A Design of LVDS High-speed data Transmission System Based on FPGA 5

A Design of LVDS High-speed Data Transmission System Based o...

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5th international conference on Computer Information Science and Application technology, CISAT 2022

作者： Li, Jianhua Lan, Wu Liu, Changjian Hu, Yi You, Bin Wu, Haochen Liao, Xiaoming Jiangxi Hongdu Aviation Industry Group Co. Ltd Jiangxi Nanchang China

ISBN: (纸本)9781510660076

In order to meet the requirements of mass data transmission between various communication systems today, this paper proposes a high-speed LVDS data transmission system based on FPGA, which uses a high-speed serial LVDS bus for communication. the transmission system makes full use of the advantages of LVDS, such as strong anti-interference ability, low power consumption, and fewer external cores. Combined with the characteristics of FPGA field programmability, it can transmit data efficiently in real time. According to the LVDS-related transmission characteristics, the LVDS-related transmission layer is built through FPGA, including the conversion of serial data and parallel data, the synchronization of clock and data, the framing and de-framing of transmission data, etc. detailed design. Finally, the loopback simulation test shows that the system has high transmission rate, stable and reliable operation, simple design and broad application prospects. © 2022 SPIE.

关键词： Field programmable gate arrays (FPGA)

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Privacy risk analysis and metrics in capturing and storing network traffic 24

Privacy risk analysis and metrics in capturing and storing n...

引用

24th international conference on Control Systems and Computer Science, CSCS 2023

作者： Mastroianni, Michele Palmieri, Francesco Ficco, Massimo Kozik, Rafal Choras, Michal Fisciano84084 Italy Bydgoszcz University of Science and Technology Bydgoszcz Poland

ISBN: (纸本)9798350313390

Network traffic analysis is a process of paramount importance to monitor network availability and operational activity, identify anomalies, maximize performance, find threats, and detect attacks. Due to this fact, in everyday work network managers need to capture, analyze and store a tremendous amount of data which can definitely be classified as 'big data'. On the other side, it is crucial to point out that the captured network traffic has significant privacy implications, in particular in the territorial scope of GDPR or other similar regulations because, according to GDPR, not only the payload but also the IP address of the sender and the receiver of packets have to be considered personal data. this paper deals with the privacy issues related to network traffic capture/processing/storage, the risks, and the associated mitigation techniques. As a conclusion of the work, a privacy risk analysis using PIA, together with the methodology developed by the French data Protection Authority (CNIL) is discussed. the analysis performed highlights the effect of the use of some well-known anonymization and pseudonymization techniques on the severity and likelihood of risk. © 2023 IEEE.

关键词： Risk analysis

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Retrieval of tropical cyclone temperature and humidity profiles from FY-3E MWTS and MWHS data using deep learning algorithm 5

Retrieval of tropical cyclone temperature and humidity profi...

引用

5th international conference on Geoscience and Remote Sensing Mapping, ICGRSM 2023

作者： Zhang, Tianxu Meng, Shengxiang Jiang, Gengming Ye, Hongxia Fudan University Shanghai200433 China

ISBN: (纸本)9781510672789

Tropical cyclone (TC) disasters have a serious threat to social and economic development, so it is necessary to retrieve atmospheric temperature and humidity profiles in the typhoon region to provide timely and accurate information on the initial field of atmospheric humidity and temperature for numerical weather prediction, and to enhance the early warning capability of catastrophic typhoon weather. this paper addresses the retrieval of tropical cyclone temperature and humidity profiles over the western Pacific Ocean from the data acquired by the Microwave Temperature Sounder(MWTS) and the Microwave Humidity Sounder (MWHS) on Fengyun 3E (FY-3E) using the batch normalization and robust neural network (BRNN) algorithm. To improve retrieval accuracy, the FY-3E MWTS and MWHS observations in the TC region are classified according to different scattering conditions (clear, stratiform, convective), and the atmospheric temperature and humidity profiles in the TC region are retrieved by a deep learning method. the results show that, the root mean square errors (RMSEs) of the retrieved temperature profiles are less than 1.4 K, while the RMSEs of the derived humidity profile are less than 1.1 g/kg. In general, the retrieval algorithm can invert a reasonable TC thermal structure. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Tropical cyclone

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Applicability of Machine Learning in Process Industry: A Review 5

Applicability of Machine Learning in Process Industry: A Rev...

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5th IEEE international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Walke, Suchita Bakal, Jagdish W. Pillai Hoc College of Engineering and Technology Computer Engineering Department Mumbai India

ISBN: (纸本)9798350383522

this article undertakes a thorough assessment of the suitability of machine learning for the process industry, examining both its potential advantages and obstacles. this research examines the extant body of literature and focuses on instances where machine learning techniques have been effectively applied to a range of processes, such as optimization, quality control, and predictive maintenance Technological advancements and the accessibility of vast amounts of data have facilitated the development of more complex machine learning applications within the sector. the review further underscores the difficulties linked to the standardization of data and concerns regarding privacy, which necessitate efficient resolution. the establishment of data standardization is critical in order to guarantee interoperability and compatibility among diverse systems and processes. Furthermore, the process industry is confronted with privacy concerns that stem from the sensitive nature of the data involved. As a result, stringent security protocols and compliance with privacy regulations are imperative. Notwithstanding these obstacles, the assessment suggests that the application of machine learning in the process industry is positioned for expansion in the coming years. the potential for machine learning algorithms to analyze massive datasets and derive relevant insights could significantly enhance the efficiency and competitiveness of businesses in this sector. through the implementation of machine learning techniques, process industries have the ability to streamline their operations, improve product quality by means of real-time monitoring, decrease outage via predictive maintenance, and accelerate their overall processes. the application of machine learning techniques within the process industry holds considerable promise. the paper emphasizes the potential benefits that can be gained by implementing machine learning techniques across a range of operational contexts. Nevertheless

关键词： ANN IoT Machine Learning Neural network

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