Network traffic anomaly detection method based on multi-scale characteristic by Xueyuan DUAN, Yu FU, Kun WANG, Taotao LIU, Bin LI

“…Aiming at the problem that most of the traditional network traffic anomaly detection methods only pay attention to the fine-grained features of traffic data, and make insufficient use of multi-scale feature information, which may lead to low accuracy of anomaly detection results, a network traffic anomaly detection method based on multi-scale features was proposed.The original traffic was divided into sub-sequences with multiple observation spans by using multiple sliding windows of different scales, and the multi-level sequences of each sub-sequence were reconstructed by wavelet transform technology.Multi-level reconstructed sequences were generated by Chain SAE through feature space mapping, and a preliminary judgment of abnormality was made by the classifiers of each level according to the errors of the reconstructed sequences.The weighted voting strategy was adopted to summarize the preliminary judgment results of each level to form the final result judgment.Experimental results show that the proposed method can effectively mine the multi-scale feature information of network traffic, and the detection performance of abnormal traffic is obviously improved compared with traditional methods.…”
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Fine-Grained Fault Diagnosis Method of Rolling Bearing Combining Multisynchrosqueezing Transform and Sparse Feature Coding Based on Dictionary Learning by Guodong Sun, Yuan Gao, Kai Lin, Ye Hu

“…To accurately diagnose fine-grained fault of rolling bearing, this paper proposed a new fault diagnosis method combining multisynchrosqueezing transform (MSST) and sparse feature coding based on dictionary learning (SFC-DL). …”
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Fault Detection of Cyber-Physical Systems Using a Transfer Learning Method Based on Pre-Trained Transformers by Pooya Sajjadi, Fateme Dinmohammadi, Mahmood Shafiee

“…A streamlined transformer model is first pre-trained on a large-scale source dataset and then fine-tuned end-to-end on a smaller dataset with a differing data distribution. …”
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A New Method for Fault Line Selection of Photovoltaic Power Station Collection Lines Based on TEO Energy by Ran ZHENG, Jiayi WU, Haoliang DU, Wulue PAN

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Detection method on pantograph-catenary arcing of electric locomotives based on multi-frequency-band characteristics of current signals by LUO Yinbei, GE Ting, SUN Zeyong

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Seasonal Analysis of Planetary Boundary Layer and Turbulence in Warsaw, Poland Through Lidar and LES Simulations by Rayonil G. Carneiro, Maciej Karasewicz, Camilla K. Borges, Lucja Janicka, Dongxiang Wang, Gilberto Fisch, Iwona S. Stachlewska

“…Using remote sensing lidar sensor data, the PBLH was calculated using wavelet covariance transform (WCT) and the gradient method (GM). Also, simulations of turbulent fluxes were performed utilizing the large eddy simulation (LES) from the Parallel Large Eddy Simulation Model (PALM) to better understand how turbulence and convection behave across different seasons in Warsaw. …”
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An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

“…This time-frequency analysis method, by preserving low-frequency features, is particularly suitable for SP signals. …”
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Research on Model Reconstruction Methods for Partial Point Cloud Information Loss by Zhengping CHANG, Guoshuai YUAN, Jiuhua LI, Yang ZHAO, Zhongqi WANG

“…Therefore, research on model reconstruction methods without local point clouds is essential. This study proposes a Laplace mesh transformation method to deform the theoretical triangular mesh based on the scanned area. …”
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Calculation Method of Shale Oil Fluid Component Content Based on Nuclear Magnetic Resonance T2 Distribution by LIU Jilong, XIE Ranhong, WEI Hongyuan, XU Chenyu, JIN Guowen, ZHENG Di, WANG Shaoxiang

“…On this basis, the random walk method is used to simulate the nuclear magnetic resonance response of the pore fluids at different echo spacing. …”
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Time-Frequency Feature Extraction Method for Weak Acoustic Signals from Drill Pipe of Seafloor Drill by Jingwei Xu, Buyan Wan, Weicai Quan, Yi Xi, Xianglin Tian

“…In order to more accurately assess the differences between the different time-frequency analysis methods in the extraction of weak acoustic wave signals, short-time Fourier transform, wavelet transform, and ST are used to extract the weak acoustic wave characteristics of the drill pipe, respectively. …”
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Fast and Accurate Detection of Forty Types of Fruits and Vegetables: Dataset and Method by Xiaosheng Bu, Yongfeng Wu, Hongtai Lv, Youling Yu

“…However, existing detection methods typically focus on identifying a single type of fruit or vegetable and are not equipped to handle complex and diverse environments. …”
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A Survey of Dense Object Detection Methods Based on Deep Learning by Yang Zhou, Hui Li

“…This paper comprehensively surveys the latest advancements in dense object detection, summarizing and analyzing the most advanced methods. We discuss the similarities and differences, as well as the advantages and disadvantages, of dense object detection algorithms based on five different approaches: NMS, LOSS, re-scoring, transform and YOLO. …”
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Survey on video image reconstruction method based on generative model by Yanwen WANG, Weimin LEI, Wei ZHANG, Huan MENG, Xinyi CHEN, Wenhui YE, Qingyang JING

“…Traditional video compression technology based on pixel correlation has limited performance improvement space, semantic compression has become the new direction of video compression coding, and video image reconstruction is the key link of semantic compression coding.First, the video image reconstruction methods for traditional coding optimization were introduced, including how to use deep learning to improve prediction accuracy and enhance reconstruction quality with super-resolution techniques.Second, the video image reconstruction methods based on variational auto-encoders, generative adversarial networks, autoregressive models and transformer models were discussed emphatically.Then, the models were classified according to different semantic representations of images.The advantages, disadvantages, and applicable scenarios of various methods were compared.Finally, the existing problems of video image reconstruction were summarized, and the further research directions were prospected.…”
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A Knock Detection Method for a Marine Micro-Ignition Dual-Fuel Engine Based on Vibration Signals by Hu Nao, Zhao He, Yang Jianguo, Zheng Xianquan, Li Hongmei, Xie Liangtao, Liu Fuze, Chen Gang

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Targets Spatial Coordinates Calculation in Angle-Difference Rangefinder Passive Location Complexes by Numerical Iterative Methods by A. A. Dmitrenko, S. Y. Sedyshev

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NUMERICAL AND ANALYTICAL SOLUTIONS OF BOUNDARY VALUE PROBLEM FOR PARABOLIC EQUATIONS IN NON-CYLINDRICAL AREA by G. S. Krotov, O. I. Remizova

Subjects: “…thermodynamics, heat stroke, equation of parabolic type, integral fourier-laplace-hankelâ transformation, boundary value problem, method of green's functions, finite difference method.…”
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Modulation recognition method based on multiscale convolutional fusion coding networks by LI Guojun, ZHU Siyuan, ZHENG Jianzhong, WANG Jie, YE Changrong

“…To address the issue of insufficient feature extraction in existing modulation recognition methods that limited classification accuracy, a Transformer-based modulation recognition method was proposed. …”
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Exploration of Weak Peak Detection Method Based on Gamma Spectra Deconvolution by SONG Yiming, ZHOU Qianqian, CHEN Ye, LIU Dahai, ZHOU Hongzhao, XIAO Wuyun

“…Finally, the symmetric zero-area transformation method was used to detect the weak peaks. …”
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Evaluation of Photogrammetric Methods for Displacement Measurement During Structural Load Testing by Ante Marendić, Dubravko Gajski, Ivan Duvnjak, Rinaldo Paar

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A novel method for optimizing epilepsy detection features through multi-domain feature fusion and selection by Guanqing Kong, Guanqing Kong, Shuang Ma, Shuang Ma, Wei Zhao, Wei Zhao, Haifeng Wang, Haifeng Wang, Qingxi Fu, Qingxi Fu, Jiuru Wang

“…This problem is addressed through the use of a novel multi-domain feature fusion and selection method (PMPSO).MethodDiscrete Wavelet Transforms (DWT) and Welch are used initially to extract features from different domains, including frequency domain, time-frequency domain, and non-linear domain. …”
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