Planetary Gearbox Fault Diagnosis based on LMD Sample Entropy and ELM by Zhang Ning, Wei Xiuye, Xu Jinhong

“…In order to solve the difficult problem of early fault feature extraction of planetary gearbox and consider that the planetary gearbox vibration signal is coupling and nonlinear，and the signal has multiple transmission paths，a planetary gearbox fault diagnosis method based on Local Mean Decomposition（LMD） and Sample Entropy and Extreme Learning Machine（ELM） is proposed.Firstly，the vibration signal is adaptively decomposed into a plurality of PF components by LMD，and the first four PF components including the main fault information are selected in combination with the correlation coefficient and the variance contribution rate.Secondly，the Sample Entropy of the signal is calculated to form a feature vector.Finally，the feature vector is input into ELM for fault classification.Experiments are carried out on the planetary gearbox test bench，compared with the probabilistic neural network classification algorithm，and compared with the feature vector based on Singular Value Decomposition （SVD）.The results verify the effectiveness of the proposed method.…”
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Fault Diagnosis and Fault Tolerant Control for Non-Gaussian Singular Time-Delayed Stochastic Distribution Systems with Disturbance Based on the Rational Square-Root Model by Yuancheng Sun, Zhanhong Liang

“…Finally, a simulation example is included to illustrate the effectiveness of the proposed algorithms and encouraging results have been obtained.…”
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Retroperitoneal Extrarenal Angiomyolipomas: An Evidence-Based Approach to a Rare Clinical Entity by Emmanuel J. Minja, Megan Pellerin, Nicole Saviano, Ronald S. Chamberlain

“…Our case report provides a comprehensive literature review and an evidence-based algorithm for taking care of patients with ERAMLs.…”
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Harmonic Classification with Enhancing Music Using Deep Learning Techniques by Wen Tang, Linlin Gu

“…Two aspects of harmony are considered, chord and global key, facing the issue of the extraction problem by the algorithm of machine learning. Contribution here is to recognize chords in the music by the feature extraction method (voiced models) that performd better than manually one. …”
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An Approach for Modeling, Simulation, and Optimization of Catalytic Production of Methyl Ethyl Ketone by Zahra Parhizi, Milad Nayebi, Edris Mohammadzadeh, Reza Torfi

“…Eventually, an evolutionary genetic algorithm was adopted to optimize the reactor to maximize MEK production. …”
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Network traffic classification method basing on CNN by Yong WANG, Huiyi ZHOU, Hao FENG, Miao YE, Wenlong KE

“…Since the feature selection process will directly affect the accuracy of the traffic classification based on the traditional machine learning method,a traffic classification algorithm based on convolution neural network was tailored.First,the min-max normalization method was utilized to process the traffic data and map them into gray images,which would be used as the input data of convolution neural network to realize the independent feature learning.Then,an improved structure of the classical convolution neural network was proposed,and the parameters of the feature map and the full connection layer were designed to select the optimal classification model to realize the traffic classification.The tailored method can improve the classification accuracy without the complex operation of the network traffic.A series of simulation test results with the public data sets and real data sets show that compared with the traditional classification methods,the tailored convolution neural network traffic classification method can improve the accuracy and reduce the time of classification.…”
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Channel estimation for hybrid intelligent reflecting surface structure assisted mmWave communications by Youhua FU, Dong CHEN

“…When adding intelligent reflecting surface (IRS) for assist communication in millimeter wave communication, the system becomes complicated and difficult to obtain channel state information (CSI).To solve these challenges, a hybrid intelligent reflecting surface structure was adopted, that is, the IRS was composed of a large number of passive elements and the limited radio frequency (RF) chains, where the limited RF chains were used to estimate the channel between the base station/terminal and the IRS.Based on the structure, a channel estimation scheme was proposed, which was based on the limited RF chains.First, an improved multiple signal classification algorithm was used to estimate the departure angle and arrival angle of the channel at the same time, and then a complex parallel deep neural network was proposed to estimate the path gain.Through simulation and comparison between the proposed scheme and other methods, the superiority of the proposed scheme is proved.…”
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Single image visibility restoration using optical compensation and pixel-by-pixel transmission estimation by Yan YANG, Gao-ke CHEN

“…Aiming at image degradation in hazy and sandstorm weather,an optical compensation color restoration and pixel-by-pixel transmissvity estimation algorithm was proposed.The blue light was absorbed by sandstorm particles.The color shift phenomenon could be eliminated by optical compensate method,which convert the sandstorm images into hazy images.Then the ratio relationship between the minimum channel and its Gaussian function as the transmissivity,and median filter was used to eliminate its texture effects.The depth of the restored transmissivity alternated obviously and the edge was well preserved,which did not need the time-consuming postprocessing operativity.Finally,the image was restored by the atmospheric scattering model.The experimental results show that recovered sandstorm image treatment is better,and the saturation of the haze image is appropriate,the bright area is more nature,and running time is faster.…”
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The Multistage Homotopy Perturbation Method for Solving Chaotic and Hyperchaotic Lü System by M. S. H. Chowdhury, Nur Isnida Razali, Waqar Asrar, M. M. Rahman

“…MHPM is a technique adapted from the standard homotopy-perturbation method (HPM) where the HPM is treated as an algorithm in a sequence of time intervals. To ensure the precision of the technique applied in this work, the results are compared with a fourth-order Runge-Kutta method and the standard HPM. …”
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Bayesian Non-Parametric Mixtures of GARCH(1,1) Models by John W. Lau, Ed Cripps

“…Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. …”
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Credit risk identification of high-risk online lending enterprises based on neural network model by Mao-guang WANG, Zi-jun ZHU

“…The rapid development of online lending alleviates the difficulty of financing for small and micro enterprises to a certain extent,but it also exposes the credit risk identification problem of online lending platform.In order to fully identify the characteristics of high-risk network lending enterprises,small and medium-sized network lending companies were selected as samples,and indicators that were highly correlated with risk identification were chosen as indicators variables.And by using the BP neural network algorithm model,the credit risk identification rate and credit risk classification accuracy rate of high risk network lending enterprises,under different conditions,were obtained.The results show that the credit risks of high-risk network lending enterprises are highly recognized,and have the characteristics of high recall rate and high accuracy.…”
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Research progress of abnormal user detection technology in social network by Qiang QU, Hongtao YU, Ruiyang HUANG

“…In social networks,the problem of anomalous users detection is one of the key problems in network security research.The anomalous users conduct false comments,cyberbullying or cyberattacks by creating multiple vests,which seriously threaten the information security of normal users and the credit system of social networks ,so a large number of researchers conducted in-depth study of the issue.The research results of the issue in recent years were reviewed and an overall structure was summarized.The data collection layer introduces the data acquisition methods and related data sets,and the feature presentation layer expounds attribute features,content features,network features,activity features and auxiliary features.The algorithm selection layer introduces supervised algorithms,unsupervised algorithms and graph algorithms.The result evaluation layer elaborates the method of data annotation method and index.Finally,the future research direction in this field was looked forward.…”
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Research on EEG signal classification of motor imagery based on AE and Transformer by Rui JIANG, Liuting SUN, Xiaoming WANG, Dapeng LI, Youyun XU

“…The motor imagery brain-computer interface has always been the focus of scholars.But traditional system cannot accurately extract significant signals and has low classification accuracy.To overcome such difficulty, a new Transformer model was proposed based on the auto-encoder (AE).The filter bank common spatial pattern (FBCSP) was used to extract the features of multiple frequency bands, and the AE was exploited to obtain the dimensionality-reduced feature matrix.Finally, it considered the influence of the global signal features by the position encoding of the Transformer model and considered the internal correlation of the feature matrix by using the multi-head self-attention mechanism.By comparison with the traditional K-nearest neighbors (KNN) system based on linear discriminant analysis (LDA), the experimental results validates that the classification effect of AE+Transformer model is better than that of LDA+KNN system.It shows that the improved algorithm is suitable for the binary classification of motor imagery.…”
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Digital media representation under complex number base and its application on information hiding by Wei CHEN, Ya-nan CHEN, IUYuan L

“…With the rapid development and wide application of the digital media technology,the information security problem is becoming more and more highly attention.Because of the various kinds of medias,previous research works have focused on a specific digital media from,such as text,image,audio and video.As a fact that all the objects were expressed in digital forms under the environment of computer and network,a unified form for all kinds of digital media under the complex number base system was proposed.The algorithm of the digital media signal and the complex number intercom version were given,so the relationship among the digital media could be converted to the corresponding geometric relationship on the complex plane.In the experiments,the proposed method was applied to the application of the digital media information hiding.…”
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Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration by XIE Mande, HUANG Zhufang, SUN Hao

“…Then, a multi-user subtask scheduling scheme was proposed and an improved simulated annealing particle swarm algorithm was designed to minimize the total system cost to achieve the optimal offloading decision. …”
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Connectivity analysis of IoV based on scale-free network by Tao HAN, Wei HE, Jun DAI, Yong ZUO, Yang YANG, Xiaohu GE

“…The connectivity of moving vehicles is one of the critical metrics in Internet of vehicles (IoV) that critically influence the performance of data transmission.Due to the high-frequency dynamic changes of the network topology of the IoV, which causes the link to be easily disconnected frequently.It is a critical issue to reduce the probability of link disconnection, and reducing the randomness of link establishment improves the overall network connectivity.To solve the above problems, the network’s connectivity was analyzed under the line of sight path loss model and the interference model, and the dynamic growth (DN) algorithm was designed through the characterization of the IoV link in the real world.Moreover, a scale-free VANET was built through the network’s addition and deletion of nodes and link preference connections.Simulation results indicate that the overall connectivity of the network is improved by 16%.…”
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Research on the Classification of Policy Instruments Based on BERT Model by Jiani Zhao, Cheng Li

“…The research tries to apply the automatic classification algorithm based on BERT (Bidirectional Encoder Representation from Transformer) to the policy instruments to improve the efficiency and accuracy of policy instruments classification. …”
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A Self-Adaptive and Link-Aware Beaconless Forwarding Protocol for VANETs by Changle Li, Yun Chen, Xiaolei Han, Lina Zhu

“…Furthermore, it proposes a comprehensive algorithm to calculate the waiting time by taking the greedy strategy, link quality, and the traffic load into account. …”
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Design and Application of Electromechanical Control System Based on Computer Fault Tolerance Technology by Rui Wei

“…In order to improve the stability and control effect of the electromechanical control system, this paper designs the electromechanical control system combined with the computer fault-tolerant technology and proposes an electromechanical control signal processing algorithm. In order to improve the accuracy of the path loss calculation, according to Fresnel’s law, this paper deduces the expression of the reflection coefficient of electromechanical control signal with the distance between the transmitting antenna and the receiving antenna as the main variable and then compares the path loss with the ground and the ceiling as the reflecting surface. …”
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Retracted: Image Recognition Technology Based on Neural Network by Jianqiu Chen

“…Using deep learning algorithms to recognize and classify image has become a hot issue for scholars from all walks of life. …”
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