AN INCIPIENT FAULT DIAGNOSIS METHOD FOR ROLLING BEARING BASED ON MCKD AND LMD by SUN Wei, LI XinMin, JIN XiaoQiang, HUANG JianPing, ZHANG XianHui

“…Aiming at the problem that the Local mean decomposition（LMD） method is difficult to draw early weak fault,a fault diagnosis method for the roller bearing based on maximum correlated kurtosis deconvolution（MCKD） and LMD was proposed.Firstly,the fault signal was de-noised and meantime periodic impact components were enhanced by MCKD method,Then,that result is decomposed by LMD to get PF,the correlation coefficient between the PF and the signal is used as the standard of judgment,so that the redundant low-frequency PF can be rejected.Finally,the effective PF is selected to analyze the spectrum and extract the fault feature.The experiment of the simulation data and the actual roller bearing fault diagnosis data show that the method can effectively extract the feature frequency information of incipient fault and has a certain reliability.…”
Get full text

ZFD-Net: Zinc flower defect detection model of galvanized steel surface based on improved YOLOV5. by Yang Gao, Hanquan Zhang, Lifu Zhu, Feitong Xie, Dong Xiao

“…Firstly, the model combined the YOLOV5 model with our proposed cross stage partial transformer (CSTR) module in this paper to increase the model receptive field and improve the global feature extraction (FE) capability. Secondly, we use bi-directional feature pyramid network (Bi-FPN) weighted bidirectional feature pyramid network to fuse defect details of different levels and scales to improve them. …”
Get full text

Multiscale Hjorth Descriptor on Epileptic EEG Classification by Achmad Rizal, Sugondo Hadiyoso, Suci Aulia, Inung Wijayanto, null Triwiyanto, Ziani Said

“…This process produces a feature vector that is used in the classification stage. …”
Get full text

Full-Wave Analysis of Periodic Baffle System in Beamforming Applications by Yuriy TASINKEVYCH, Eugeniusz DANICKI

“…Mixed boundary-value problem for periodic baffles in acoustic medium is solved with help of the method developed earlier in electrostatics. …”
Get full text

Bio-Inspired Structure Representation Based Cross-View Discriminative Subspace Learning via Simultaneous Local and Global Alignment by Ao Li, Yu Ding, Xunjiang Zheng, Deyun Chen, Guanglu Sun, Kezheng Lin

“…Nevertheless, the distribution discrepancy between cross-views leads to the fact that instances of the different views from same class are farther than those within the same view but from different classes. To address this problem, in this paper, we develop a novel cross-view discriminative feature subspace learning method inspired by layered visual perception from human. …”
Get full text

Customer Attrition Detection Using the LGBM Model by Huang Jie

“…To select the most suitable model for accurately detecting customer churn, this study performs preprocessing, including data cleaning, feature engineering, and feature selection. The dataset is then split into training, testing, and validation sets. …”
Get full text

Engineering Vibration Recognition Using CWT-VGG19 by Wei Huang, Jian Xu

“…The continuous wavelet transform converts the original one-dimensional vibration signals into two-dimensional time-frequency representations with richer feature information, which are then input into the convolutional layers for automatic feature extraction, culminating in vibration recognition through the SoftMax layer. …”
Get full text

Human action recognition method based on multi-view semi-supervised ensemble learning by Shengnan CHEN, Xinmin FAN

“…Mass labeled data are hard to get in mobile devices.Inadequate training leads to bad performance of classifiers in human action recognition.To tackle this problem, a multi-view semi-supervised ensemble learning method was proposed.First, data of two different inertial sensors was used to construct two feature views.Two feature views and two base classifiers were combined to construct co-training framework.Then, the confidence degree was redefined in multi-class task and was combined with active learning method to control predict pseudo-label result in each iteration.Finally, extended training data was used as input to train LightGBM.Experiments show that the method has good performance in precision rate, recall rate and F1 value, which can effectively detect different human action.…”
Get full text

Research and prospect of standard for biometric multi-modal fusion used with mobile devices by Guanchen LIN, Zhifei WANG

“…Aiming at the problem of inconsistent biometric multi-modal fusion technology framework for mobile devices and lack of standards, a unified technical framework of multi-modal fusion standards was proposed.Firstly, the current status of standardization related to biometric used with mobile device was analyzed.Secondly, the local recognition and remote recognition application modes of mobile device biometrics standards were studied, and then four sub-multimodal fusion classification methods of multi-feature, multi-algorithm, multi-instance, and multi-sensor were analyzed and proposed.Then, four levels of multi-modal fusion were researched and proposed: sample-level fusion, feature-level fusion, score-level fusion, and decision-level fusion, and a standard technical framework for biometric multi-modal fusion for mobile devices was proposed.Finally, prospects for the application of biometric multi-modal fusion technology were given.…”
Get full text

Multi-class fault diagnosis of BF based on global optimization LS-SVM by ZHANG Hai-gang, ZHANG Sen, YIN Yi-xin

“…Aiming at the requirement of high speed and precision in blast furnace fault diagnosis systems, a new strategy based on global optimization least-squares support vector machines (LS-SVM) was proposed to solve this problem. Firstly, the variable metric discrete particle swarm optimization algorithm was employed to optimize the feature selection and LS-SVM parameters. …”
Get full text

Wavelet transform and cyclic cumulant based modulation classification in wireless network by Wenwen Li, Zheng Dou, Lin Qi

“…It leads to the low-modulation classification probability in multipath channel. To resolve this problem, we propose a novel modulation classification algorithm. …”
Get full text

Absolute Stability Criteria for Large-Scale Lurie Direct Control Systems with Time-Varying Coefficients by Fucheng Liao, Di Wang

“…The main idea of the methodology is that even if the coefficients are norm-unbounded, by restricting their relative magnitude, the problem of negative definiteness for the derivative can also be changed into the problem of stability for a constant matrix. …”
Get full text

A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller by Jorge Aráez, Santiago Real, Alvaro Araujo

“…This problem has commonly been solved by delegating this task to hardware-accelerated solutions like FPGAs or ASICs. …”
Get full text

DefogNet: A Single-Image Dehazing Algorithm with Cyclic Structure and Cross-Layer Connections by Suting Chen, Wenhao Fan, Shaw Peter, Chuang Zhang, Kui Chen, Yong Huang

“…Inspired by the application of CycleGAN networks to the image style conversion problem Zhu et al. (2017), this paper proposes an end-to-end network, DefogNet, for solving the single-image dehazing problem, treating the image dehazing problem as a style conversion problem from a fogged image to a nonfogged image, without the need to estimate a priori information from an atmospheric scattering model. …”
Get full text

Mean Shift Fusion Color Histogram Algorithm for Nonrigid Complex Target Tracking in Sports Video by Yu Liu, Xiaoyan Wang

“…The multiple hypothesis target tracking algorithms are used to track multiple targets, while the chunking feature is used to solve the problem of mutual occlusion and adhesion between targets. …”
Get full text

A generative adversarial network–based method for generating negative financial samples by Zhaohui Zhang, Lijun Yang, Ligong Chen, Qiuwen Liu, Ying Meng, Pengwei Wang, Maozhen Li

“…In financial anti-fraud field, negative samples are small and sparse with serious sample imbalanced problem. Generating negative samples consistent with original data to naturally solve imbalanced problem is a serious problem. …”
Get full text

WAIVER OF FIRST REFUSAL RIGHT IN LIMITED LIABILITY COMPANY: THEORETICAL AND PRACTICAL FLAWS OF RUSSIAN APPROACH by GORDIENKO D.A

“…Comprehensive review of the problem leads to the conclusion that a right of first refusal is not an immanent feature of a closed corporation, due to the limited scope of its impact on the interests of the latter. …”
Get full text

Lack of Method, Physicalism Approach and Lack of Phenomenological Perspective in Philosophy of Superstitions by Mahmood Hedayatafza, Rasool Rasoolipour

“…Meanwhile, the most important problem is concerned with the “definition of superstition”. …”
Get full text

Understanding street protests: from a mathematical model to protest management. by Sergei Petrovskii, Maxim Shishlenin, Anton Glukhov

“…Understanding of factors that may affect the duration of street protests and the number of participants is a problem of pivotal importance. Mathematical modelling is an efficient research approach to study this problem. …”
Get full text

Machine learning for Internet of things anomaly detection under low-quality data by Shangbin Han, Qianhong Wu, Yang Yang

“…Therefore, practitioners may not know which algorithm to choose due to the lack of review and evaluation of anomaly detection methods under low-quality data. To address this problem, we give a detailed review and evaluation of six supervised anomaly detection methods, as well as release the core code of feature extractor for pcap format traffic traces and anomaly detection methods for reuse. …”
Get full text