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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Zhang, Xu Feng, Chuan Han, Pengchao Liu, Wei Gong, Xiaoxue Zhang, Qiupei Guo, Lei School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Institute of Intelligent Communication and Network Security Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Chongqing400065 China School of Information Engineering Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9789819616978

Network monitoring and measurement is an important part of realizing the network digital twin. However, it introduces the problem of high cost when obtaining the status data of physical networks. Therefore, to efficiently achieve network observability, we first introduce potential techniques and network scenarios for implementing network measurements. Then, a High-Yield Segment Routing over IPv6 based In-band Network Telemetry (HY-SRv6-INT) system is proposed in this paper. In particular, we design the HY-SRv6-INT system architecture. It consists of IPv6 switches implemented by the P4 language and a Software-Defined Networking (SDN) controller containing the HY-SRv6-INT application. Next, we experimentally demonstrate a packet-level path-associated network measurement process. In addition, the performance of the HY-SRv6-INT system is also quantitatively evaluated to verify its advantages. Finally, we discuss some research challenges and open issues for future network telemetry. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Internet protocols

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Research on Ultra-wide Bandwidth Low-frequency Signal Channelization for Xinjiang 110m Radio Telescope

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Research in Astronomy and Astrophysics 2023年第12期23卷 263-274页

作者： Hai-Long Zhang Ya-Zhou Zhang Meng Zhang Jie Wang Jian Li Xin-Chen Ye Xin Pei Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Radio Astronomy Chinese Academy of SciencesNanjing 210008China National Astronomical Data Center Beijing 100101China School of Cyber Science and Engineering Qufu Normal UniversityQufu 273165China

Aiming at the subband division of ultra-wide bandwidth low-frequency(UWL)signal(frequency coverage range:704–4032 MHz)of the Xinjiang 110 m QiTai radio Telescope(QTT),a scheme of ultra-wide bandwidth signal is ***,we analyze the effect of different window functions such as the Hanning window,Hamming window,and Kaiser window on the performance of finite impulse response(FIR)digital filters,and implement a critical sampling polyphase filter bank(CS-PFB)based on the Hamming window FIR digital ***,we generate 3328 MHz simulation data of ultra-wideband pulsar baseband in the frequency range of 704–4032 MHz using the ultra-wide bandwidth pulsar baseband data generation algorithm based on the 400 MHz bandwidth pulsar baseband data obtained from Parkes CASPSR ***,we obtain 26 subbands of 128 MHz based on CS-PFB and the simulation data,and the pulse profile of each subband by coherent dispersion,integration,and ***,the phase of each subband pulse profile is aligned by non-coherent dedispersion,and to generate a broadband pulse profile,which is basically the same as the pulse profile obtained from the original data using *** experimental results show that the scheme for the QTT UWL receiving system is feasible,and the proposed channel algorithm in this paper is effective.

关键词： pulsars general-methods data analysis-techniques miscellaneous

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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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Fault Assessment for Mechanical Equipment with Adaptive Weights Incorporating Sensitivity and Monotonicity

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IFAC-PapersOnLine 2023年第2期56卷 11796-11801页

作者： Yinghao Zhao Xu Yang Jian Huang Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing PR China

Driven by the increasing needs in industrial processes for condition-based maintenance, this paper present an adaptive weighting strategy based on sensitivity and monotonicity for fault assessment. Since the sensitivities of features vary with the changes of fault severity, adaptive weight coefficients are designed based on sensitivities to strengthen the feature information. Meanwhile, considering the irreversibility of fault evolution and the difference of sensitive features to different faults, unique monotonic multi-domain feature set with high sensitivity can be selected. Finally, a monotonic health index (HI) is fused based on adaptive weight coefficients for fault assessment which satisfies the needs for intuitiveness in industrial sites. Moreover, the effectiveness of the proposed method is demonstrated by rolling bearing test rig. Results show that the average assessment accuracy can reach 87.5%, 95.375% and 95.375%.

关键词： Fault assessment Feature fusion Feature selection Feature sensitivity

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Research on Ethnic Pattern Generation Based on Generative Adversarial Networks

Research on Ethnic Pattern Generation Based on Generative Ad...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Hao Wu Wenze He Xiongfei Li Yanchun Liang Zhuhai Sub Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Zhuhai College of Science and Technology Zhuhai China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China

In this paper, we take Mongolian ethnic patterns as the research object and conduct a technical study on ethnic pattern generation and super-resolution reconstruction based on deep learning generative adversarial networks to address the problems of low quality of ethnic pattern data collection and lack of innovation. In this paper, we use a database including 1621 Mongolian ethnic patterns, train StyleGAN2 on the pre-processed images, and generate images After that, we use ESRGAN to perform super-resolution reconstruction on the generated images to generate high-resolution patterns with Mongolian style. The model designed in this paper can generate high quality images with ethnic characteristics in the case of insufficient original data. Compared with the time-consuming and labor-intensive traditional ethnic pattern design methods, the model designed in this paper lowers the threshold of ethnic pattern innovation and contributes to the innovative design of ethnic patterns to a certain extent, which has some positive significance for the protection and inheritance of ethnic patterns.

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Integrating vegetation phenological characteristics and polarization features with object-oriented techniques for grassland type identification

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地球空间信息科学学报（英文版） 2024年第3期27卷 794-810页

作者： Bin Sun Pengyao Qin Changlong Li Zhihai Gao Alan Grainger Xiaosong Li Yan Wang Wei Yue Institute of Forest Resource Information Techniques Chinese Academy of ForestryBeijingChina Key Laboratory of Forestry Remote Sensing and Information System NFGABeijingChina School of Information Technology and Engineering Guangzhou College of CommerceGuangzhouChina School of Geography University of LeedsLeedsUK Aerospace Information Research Institute Chinese Academy of SciencesBeijingChina Shandong Geographical Institute of Land Spatial Data and Remote Sensing Technology JinanChina

Due to the small size,variety,and high degree of mixing of herbaceous vegetation,remote sensing-based identification of grassland types primarily focuses on extracting major grassland categories,lacking detailed *** limitation significantly hampers the development of effective evaluation and fine supervision for the rational utilization of grassland *** address this issue,this study concentrates on the representative grassland of Zhenglan Banner in Inner Mongolia as the study *** integrates the strengths of Sentinel-1 and Sentinel-2 active-passive synergistic observations and introduces innovative object-oriented techniques for grassland type classification,thereby enhancing the accuracy and refinement of grassland *** results demonstrate the following:(1)To meet the supervision requirements of grassland resources,we propose a grassland type classification system based on remote sensing and the vegetation-habitat classification method,specifically applicable to natural grasslands in northern China.(2)By utilizing the high-spatial-resolution Normalized Difference Vegetation Index(NDVI)synthesized through the Spatial and Temporal Non-Local Filter-based Fusion Model(STNLFFM),we are able to capture the NDVI time profiles of grass-land types,accurately extract vegetation phenological information within the year,and further enhance the temporal resolution.(3)The integration of multi-seasonal spectral,polarization,and phenological characteristics significantly improves the classification accuracy of grassland *** overall accuracy reaches 82.61％,with a kappa coefficient of *** to using only multi-seasonal spectral features,the accuracy and kappa coefficient have improved by 15.94％and 0.19,***,the accuracy improvement of the gently sloping steppe is the highest,exceeding 38％.(4)Sandy grassland is the most widespread in the study area,and the growth season of grassland vegetation mainly occurs from May to

关键词： Grassland types vegetation phenological characteristics polarization feature integrated active and passive remote sensing object-oriented classification

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Research and implementation of image enhancement method based on improved retinex algorithm 3

Research and implementation of image enhancement method base...

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3rd International Conference on Optics and Image Processing, ICOIP 2023

作者： Zhang, Diya Wang, Yumeng Wang, Yanrui Pu, Yile Bi, Zhenbo Rao, Wei School of Information Engineering Zhejiang Ocean University Zhoushan316022 China Department of Physics Key Laboratory of Oceanographic Big Data Mining Application of Zhejiang Province Zhejiang Ocean University Zhoushan316000 China

ISBN: (纸本)9781510667426

In view of the phenomenon of detail loss and edge blurring in color images collected underwater, noise reduction is mostly ignored in underwater image enhancement research. In this paper, an improved image enhancement method based on Retinex algorithm is proposed. First,the original underwater image is transferred from RGB channels to HSI color space, and the saturation component is adaptively linearly stretched by gamma correction, The improved Retinex decomposition network based on homomorphic filtering is used to decompose and enhance the Lightness component separately. Eventually, the fused image is transferred from HSI to RGB color space, and the processed image is output. According to the experimental results, this algorithm can not only eliminate the halo artifacts, but also improve the brightness and contrast of the image, restore the original details of the image, and effectively remove the image noise. It greatly improves the visual effect and objective evaluation results of images. © 2023 SPIE. All rights reserved.

关键词： Image enhancement

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BERD+: A Generic Sequential Recommendation Framework by Eliminating Unreliable data with Item- and Attribute-level Signals

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ACM Transactions on Information Systems 2023年第2期42卷 1-33页

作者： Sun, Yatong Yang, Xiaochun Sun, Zhu Wang, Bin School of Computer Science and Engineering Northeastern University School of Computing Macquarie University China Australia Institute of High Performance Computing Centre for Frontier AI Research A*STAR Singapore School of Computer Science and Engineering Northeastern University China National Frontiers Science Center for Industrial Intelligence and Systems Optimization China Key Laboratory of Data Analytics and Optimization for Smart Industry [Northeastern University Ministry of Education China

A preliminary work of our study was published at IJCAI’21 [47], which is substantially extended in the following aspects: (1) In Section 1, we analyze the necessity of introducing item attributes for detecting unreliable instances, together with the problems and challenges that attributes may bring in. (2) In Section 2, we add discussions about the limitations of existing attribute-aware recommender systems (Section 2.2) and denoising methods (Section 2.3) in the context of detecting unreliable instances. (3) In Section 4.2, we further conduct an in-depth analysis at the attribute level to demonstrate the capability of attributes for rectifying instance loss and uncertainty, as well as the disturbance caused by attributes. (4) We generalize BERD to a generic framework BERD+ in Section 5.1, equipped with novel modules, i.e., HU-GCN (Section 5.2) and EPE (Section 5.4), which properly incorporate item attributes while reducing their disturbance for rectifying instance uncer tainty (Section 5.5) and loss (Section 5.6). The generic BERD+ can be flexibly plugged into existing SRSs for performance enhanced recommendation via eliminating unreliable data. (5) In Section 6.2, we apply our BERD+ framework to seven state-of-the-art SRSs on five real-world datasets to illustrate its superiority. (6) To avoid unfair comparison caused by item attributes, we build and compare with the baseline that combines the original BERD and an advanced attribute-aware recommender system, KSR [19]. (7) For more comprehensive comparison, in Section 6.2.2, we compare BRED+ with two state-of-the-art denoising approaches;in Section 6.2.3, to examine the efficacy of HU-GCN and EPE, we compare HU-GCN with various attribute embedding techniques, i.e., variants of graph neural networks, and compare EPE with different attribute fusing methods, i.e., adding, concatenation, and weighted sum. (8) In Section 6.2.4, a detailed ablation study is conducted to verify the effectiveness of each module of BERD+. (

关键词： Convolution

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Cooperative Physical Layer Authentication for Massive MIMO Machine-Type Communications 23

Cooperative Physical Layer Authentication for Massive MIMO M...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Zhang, Haotian Wang, Junjie Han, Gangtao Wang, Ning School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou450001 China Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China

ISBN: (纸本)9798350325959

Aiming to improve the identity security of massive machine-type communications networks, a two-user cooperative physical layer authentication (PLA) scheme is proposed for the uplink transmission of a massive multiple-input multiple-output (MIMO) systems. In the proposed scheme, two single-antenna users synchronously transmit signals to the base station which is equipped with a large number of antennas, and fast varying channels are considered. A space-time modulation scheme is adopted for the two users to implement cooperative PLA, in which tags are selectively embedded into the transmitted signals based on the bit-relationships between the tags and the messages in order to improve the covertness of tags. A minimum Riemannian distance detector is proposed to implement the tag detection, while a fast noncoherent maximum likelihood (ML) detector is introduced to carry out the messages estimation. Binary hypothesis test is carried out for authentication by comparing the detected tags to the regenerated ones, in which the PLAs of the two users are handled as a whole. The closed-form bit error probability of the message is derived, while the authentication performance is analyzed. Computer simulation results demonstrate that the proposed scheme performs better on signal detection as well as identity authentication. © 2023 IEEE.

关键词： cooperative physical layer authentication massive MIMO noncoherent detection selective tag

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Design and implementation of fire alarm module for smart home

Design and implementation of fire alarm module for smart hom...

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2023 International Conference on Electronic Information engineering and data Processing, EIEDP 2023

作者： Liu, Xiaohong Yan, Kai College of Big Data and Intelligent Engineering Southwest Forestry University Kunming650224 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9781510666160

With the continuous development of information technology, artificial intelligence fire automatic alarm system is gradually developed. However, the current system is based on a single sensor for identification, when a fire still uses manual active fire extinguishing, low efficiency in handling fire, high failure rate, poor system scalability, poor anti-interference ability, high false alarm rate. At the same time, the recognition accuracy is low, the processing speed and intelligence are also insufficient. Therefore. To address the above problems, this study designs a multi-sensor artificial intelligence fire prevention system using smoke and temperature sensors. The fire prevention system can send alarm signals at the earliest stage of fire and can intelligently extinguish the fire, so that the disaster can be controlled and extinguished by taking measures in advance. Meanwhile, the system can continue to work even if one of the sensors is not working properly. © 2023 SPIE.

关键词： Fires

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