bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Improved BEMD Method for Denoising the Phase-OTDR Signal
Authors: Hao Wei , Yu Jin , Hu Yanzhu , Wang Song 
Published: October 2020

Abstract
Empirical mode decomposition (EMD) is often used for the processing of non-linear and non-stationary signals, but it needs further improvement in some specific application scenarios. According to the characteristics of Phase-OTDR signal, this paper improves the two-dimensional empirical mode (BEMD) and uses it to denoise the Phase-OTDR signal. The improved method takes into account the inconsistency of the correlation between the time axis and the space axis, and uses the spatial resolution of the Phase-OTDR signal as the minimum interval to enter the envelope surface structure. At the same time, the boundary is smoothed during the reconstruction of the sub-envelope surface. Experiments on the noisy Phase-OTDR signal verified the effectiveness of the improved method in this paper.
Analysis of Halbach Permanent Magnet Array with Convex Type Section
Authors: Song Ningran , Zhou Guangxu , Zhu Mengmei , Mu Yongyun , Zhang Ke , Zhang Zhan , Gong Shilei , Ma Jianhui , Gao Jia 
Published: October 2020

Abstract
This paper proposes Halbach permanent magnet arrays with convex type section. The magnetic field is modeled according to Ampere’s hypothesis of molecular current. Based on the model, the fundamental component of the magnetic flux density and the sinusoidal distortion rate are selected as evaluation indexes. Compared with these of Halbach permanent magnet array with normal square section, the Halbach permanent magnet arrays with specific configuration own better performance, which provide direction for further optimization.
The Design and Simulation of Dual-band Beidou Navigation Receiver LNA
Authors: Liu Jinchang , Liao Baoquan , Ma Zhonggang , Ma Sheng , Gao Ping , Yang Huawei 
Published: October 2020

Abstract
The Beidou satellite navigation receiver requires receiving multi-band signals to ensure more accurate and reliable positioning and navigation. According to the working frequency bands B3I and L1 of the system, we propose a low-noise amplifier which is based on Infineon’s BFP740FESD transistor. We employ the ADS software to simulate and optimize the low-noise amplifier input, and adopt the conjugate matching two-stage amplifier circuit. The simulation results show that the gain Gain ≧ 30dB in the L1 and B3 dual frequency band, the input and output standing wave ratio VSWR < 1.5, the noise coefficient < 1.0dB, and the out-of-band suppression is more than -40dB, which effectively reduces the out-of-band noise interference.
Fault Diagnosis of Composite Features Rolling Bearing Based on Variational Mode Decomposition
Authors: Yuan Yi , Zhang Min , Li Xiaojun 
Published: October 2020

Abstract
In order to extract the vibration signal feature of rolling bearing with non-steady feature and improve the fault diagnosis rate accurately and stably, a variational mode decomposition (VMD) feature extraction method is proposed. Particle swarm optimization (PSO) is used to optimize the parameters of support vector machine to construct a fault diagnosis model to achieve fault diagnosis of rolling bearings. Firstly, change the modal decomposition of the known fault signal under the same load to get the modal function, and the modal function is further extracted by the singular value decomposition. The time domain, frequency domain feature and modal feature of the original signal are extracted. Constructing hybrid features to achieve efficient fault feature extraction. Optimizing SVM parameters through PSO algorithm to construct fault diagnosis models to achieve efficient fault diagnosis. Finally, by comparing with EMD-based feature extraction methods in the same load, the method shows better classification performance and the overall fault recognition rate remains above 99.17%, which verifies the reliability and effectiveness of the method.
Optimization Design of Shaper Mechanism Based on Nonlinear Programming Model
Authors: Wu Shibao , Chen Guanxu , Ma Jia , Gao Jing 
Published: October 2020

Abstract
Due to the lack of the optimization algorithm or model which could be used to optimize the complicated plane linkage mechanism (like a shaper mechanism), a nonlinear programming model which could solve this problem was proposed in this work, whose objective function was the minimum initial velocity of the cutting tool in the shaper mechanism, and the length of the linkages in the shaper mechanism was regarded as the constraint conditions. Subsequently, a typical shaper mechanism was chosen as the example to be optimized via this nonlinear programming model. The optimization results revealed that this model could acquire an appropriate optimization scheme effectively and the optimization scheme was reasonable.
An Indoor Geolocation Algorithm based on CSI and Affine Propagation Clustering
Authors: Liu Lei , Zhang Shuwei 
Published: October 2020

Abstract
An indoor geolocation algorithm based on WLAN CSI and affine propagation clustering is proposed in this paper. In this algorithm, the wireless network adaptor Intel 5300 and 802.11n CSI Tools is used to collect the CSI data, and the PCA algorithm is used to reduce the dimension of the CSI data from 30 to 3, based on which the CSI fingerprint database is established. And the affine propagation clustering algorithm is used to group the reference nodes into clusters and then the WKNN is adopted to realize precise indoor geolocation. Experiment results show that the algorithm in this paper has a better performance in the location accuracy, 74% of the testing results has the accuracy of 1m, and 95% of the testing results has the accuracy of 2m.
Research on pure electric vehicle driving motor
Authors: Song Shuang , Sun Chao , Zheng Cong , Song Guicui 
Published: October 2020

Abstract
The current promotion of new energy vehicles, These include fuel cell vehicles, pure electric vehicles and plug-in hybrids. “Pure electric cars” are no stranger to today’s people, It has many advantages, Such as good acceleration performance, high power, environmental protection and energy saving, It is very much in line with the changing demands of The Times for transportation modes. Because of the significant environmental and energy savings, In particular, there is no direct discharge of air pollutants during use. So there’s a big push at the national level. In order to optimize the performance of the driving motor system of pure electric vehicles, Improve its efficiency, improve its structural design, Further research on vehicle driving motor.
Research on Image Recognition Algorithm Technology for Power Line Business Audit
Authors: Mao Qianqian , Pan Zheqiong , Si Dongmei , Kong Xufeng 
Published: October 2020

Abstract
The development of electric power business is not only limited to the on-site office of the business hall, but also can be carried out on the mobile Internet. At present, the power supply company’s review of business such as name change, transfer, reclassification-peak shaving, etc., because customers use different methods to handle business, Resulting in a wide variety of certificate pictures, which caused great trouble to the staff. This paper studies an image recognition algorithm that can be applied to power business audits, can accurately identify various types of certificate images, and automates the overall business process. Implementation provides preparation. Users can use the mobile phone APP and computer network to handle all the business processes of electricity business online, know the main items of each link, the materials that should be provided, and the various procedures that should be handled, etc., electricity customers do not have to go out, just log on to the Internet All business can be handled well, which greatly facilitates the efficiency of users in handling various power businesses and saves time very convenient.
Predicting Metamorphic Relations Based on Path Features
Authors: Zhang Hanyue , Liu Lei , Zhang Peng 
Published: October 2020

Abstract
Metamorphic test has been proposed to effectively solve the oracle problem, but the most of the existing metamorphic relations are difficult to reuse, which leads to a large cost of in the metamorphic test. In order to improve the efficiency of the metamorphic test and solve the problem of low reuse rate of metamorphic relations, based on the common set of metamorphic relations in scientific computing programs and execution path, we propose a novel string feature with a new extraction method. Then, this feature can be used to train support vector machine to decide the metamorphic relations for test. At last, we construct a various of experiments, and the experiments results show that our method can effectively predict the satisfaction of the input features for the metamorphic relations.
Study of A designed and experimental multi-beam antennas based on Spoof Surface Plasmon Polaritors structure
Authors: Liu Tianyi , Chen Ziqi , Xu Jikai 
Published: October 2020

Abstract
The new type of artificial electromagnetic two-dimensional surface consists of an array of subwavelength unit structures arranged according to the periodicity of the dispersion curve. It has a significant role in regulating electromagnetic waves, and it has become one of the hot topics in the field of information. In this paper, the Spoof Surface Plasmon Polaritons (SSPPs) are regulated and applied to the wireless millimeter-wave base station communication. It has the characteristics of low profile, low cost, high isolation, broadband, and high gain. As a proof of concept, the antenna array is designed, simulated, processed and measured. The dual-beam adaptive antenna based on SSPPs at 10 GHz. The experimental results are in good agreement with numerical simulations. The proposed antenna has promising applications on planar wireless communication devices, such as multi-beam antennas, beam-scanning antennas, and wave controllers.
Model on Selection of Shells for Gun to Fire on Ground Target Based on Probability Ranking Decision
Authors: Hu Jiang , Sun Dongyan 
Published: October 2020

Abstract
During gun firing on ground target, because the ammunition consumption is large, it is necessary to select shells in the light of effectiveness-cost. In order to solve the problem of selecting shells, this paper puts forward analysis method of firing effectiveness-cost firstly. Then by using the calculation model of probability ranking decision, we can select appropriate shells by comparing average value of effectiveness-cost expectation extremum. This provides reference for user of gun to make decision during firing on ground target.
Research on BP model optimization of PSO algorithm based on Computational Mathematics
Authors: Wang Pin , Gao Yuefei 
Published: October 2020

Abstract
Construction of the quality and safety evaluation model for dairy products is significant to ensure food safety for people. In the case that there is a big error in the BP neural network quality and safety evaluation model for dairy products, this paper put forward the optimization method based on the PSO algorithm to reduce the output error of the BP neural network evaluation model through optimizing the weights and thresholds of BP neural network. By simulation of optimizing the BP evaluation model through specific data, experiments showed that compared with the standard BP evaluation model and standard BP evaluation, the optimized BP evaluation model is greatly improved in output error.
Model of Colour Value and Substance Concentration Based on Ridge Regression
Authors: Ling Zhonghua , Gao Yushan , Duan Luling 
Published: October 2020

Abstract
Based on the data of colour value and substance concentration, the quantitative relationship between colour reading and substance concentration in digital photos is studied in this paper. Correlation coefficient, variance inflation factor (VIF) and condition indices are used to analyse the collinearity of variables, and the regression model of colour value and material concentration of digital photos is established by ridge regression method. The ridge trace shows that the least square regression coefficient is very unstable at high collinearity. As the bias parameter increases from 0 to 0.0477, the ridge regression coefficient becomes stabilized and the model’s coefficient of determination does not decrease significantly. The maximum VIF (k) is 3.5161 (less than 10), which indicates that the coefficients of the model constructed by the ridge regression method is more robust, and the prediction effect of the model is better than that estimated by the least square method.
Numerical Prediction of the Hydrofoil Noise
Authors: He Xiaohui , Liu Zhongle , Wang Xianyong , Yuan Zhiyong 
Published: October 2020

Abstract
Using the improved Sauer cavitation model and K-FWH acoustic model proposed by Yang Qiongfang to numerically calculate the unsteady cavitation flow field of NACA0015 three-dimensional hydrofoil, the noise of the three-dimensional hydrofoil was calculated, and the cavitation process and cavitation noise of the hydrofoil were numerically predicted. The results demonstrate that the hydrofoil cavitation shows distinctive characteristics of pulsation and periodicity. The main cause of formation and detachment of cavitation bubbles is the reverse jet nearby the hydrofoil wall due to eddies. By analyzing the sound pressure pulsation characteristics of each monitoring point, it can be concluded that the noise transmission in the leading edge of the hydrofoil is consistent with the direction of the mainstream, no reverse transmission. In the development process of cavitation, the noise signals in cavitation area tend to be superimposed downstream. When the signals transmit to the flowing area at the trailing edge of the hydrofoil, they gradually attenuate until being exhausted.
Method for Detecting Surface Defects of Ceramic Tableware Based on Deep Learning
Authors: Ye Shuo , Sun Lingzhen 
Published: October 2020

Abstract
In view of the advantages of simple and high-precision detection methods for surface defects of ceramic tableware based on machine vision, the various links involved in such methods are reviewed. First, it summarizes the various imaging methods and common defect types on the surface of ceramic tableware; secondly, introduces and analyses the existing detection methods according to different mathematical modelling ideas; finally, summarizes the content the future research on the detection method of surface defects of ceramic tableware is prospected. It can be seen that the surface defect detection method of ceramic tableware based on machine vision has made great progress, but there is still room for improvement in the design of feature extraction algorithms, such as the feature extraction algorithm based on deep neural networks.
Research on Modeling of New Energy Power Plant Interface Characteristics Based on Computer Power Flow Calculation Model
Authors: Wang Yanan 
Published: October 2020

Abstract
In view of the adverse effects of wind power and photovoltaics as the representative of new energy power stations’ active power output fluctuations on the security and stability of the grid, a solution to smooth the active power output of intermittent power sources using energy storage systems is presented. In this paper, the boundary coordination equation in the form of implicit function is used to model the coordinated solution of dynamic power flow equations in the whole network. This model can uniformly consider the reasonable distribution of boundary node power balance and unbalanced power among the district grids.
Improved Wavelet Packet Energy Spectrum Feature Extraction Method of MFL Detection Signal
Authors: Song Zhiqiang , Zhang Ying 
Published: October 2020

Abstract
Wavelet packet energy spectrum method is an effective signal processing method to extract the features of magnetic flux leakage (MFL) detection signals, which has been widely used. However, sometimes the features of MFL detection signals in the high frequency band are not obvious, and their spectrum changes are very scattered, so it is difficult to extract the features. The improved wavelet packet energy spectrum and Wigner-Ville Transform (WVT) algorithm is a signal analysis algorithm based on continuous wavelet transform and discrete wavelet transform, which matches WVT. In the process of signal processing, the eigenvalues to be extracted are defined in the form of energy spectrum, and the recognition and extraction of eigenvalues are transformed into the corresponding signal eigenvalue energy recognition and extraction, so as to improve the accuracy of high step signal feature of MFL detection signal.
ResSCNN: A semantic segmentation method for fast processing of large-scale input
Authors: Yu Haoyang , Xu Siyuan , Su Wenliang , Xiao Zihan , Yang Jie , Mu Jiong 
Published: October 2020

Abstract
With the development of driver-assistance systems and driverless cars, vehicles are becoming more and more intelligent. However, today’s intelligent vehicles rely more on large sensors to sense the environment, so it is becoming more and more important for vehicles to be able to understand road information, and semantic segmentation has developed greatly. We find that the current mainstream semantic segmentation model is slow and inaccurate in the case of large scale input images. In this paper, we combine the large-scale input Fast-SCNN with the residual module to construct the residual semantic segmentation convolutional neural network (ResSCNN), after the experimental test, when the input scale is 1024 × 2048 px, yielding an accuracy of 68.4% mean intersection over union at 123.1 frames per second on Cityscapes dateset. Our network has achieved better results than the previous mainstream methods.
Research on Video-based Moving Vehicle Detection Technology
Authors: Ma Lei , Qiao Qiao , Huang Lingxiao , Xu Weichang , Niu Wanhong 
Published: October 2020

Abstract
Moving vehicle detection technology has been used more and more widely in monitoring traffic conditions such as vehicle flow, vehicle speed, traffic accidents, and escape from violations. The most commonly used methods of moving vehicle detection technology include the inter-frame difference method, the background difference method, and the optical flow method. The inter-frame difference method subtracts the images of two or three adjacent frames, the pixel whose brightness change does not exceed the threshold value is considered as the background, and the pixel whose brightness change exceeds the threshold value is considered as the foreground; The background difference method uses a difference comparison between the current image and the background model to realize the moving vehicle detection; The optical flow method is to construct an optical flow field by changing the brightness value of each pixel point in an adjacent frame in a video image, and realize the detection of a moving vehicle through a moving field of the moving vehicle. The frame difference method can detect the contour edge information of a moving vehicle, and the detection result is less noisy; the background difference method can detect a more complete moving vehicle, including not only the contour information of the moving vehicle, but also the connected area inside the moving vehicle; The optical flow method can detect moving vehicles, but can only obtain the contour edge information of moving vehicles, and there are large voids in the interior of moving vehicles. In short, these methods can realize the detection of moving vehicles, but there are still some problems. With the research and implementation of improved algorithms, the detection technology of moving vehicles will be more and more widely used.
Multiple-instance Learning based on Bernoulli Mixture Model
Authors: Yang Lilin , Wu Wei 
Published: October 2020

Abstract
Multiple-instance learning (MIL) is a form of weakly supervised learning. Its instances are arranged in groups (called bags), and labels are provided for the entire bag after training. The classic MIL method represents examples with pre-calculated features, and the classification process is also cumbersome. In this paper, we use neural networks to extract features, parameterize all transformations, and use Bernoulli mixture model to construct MIL models for baggage tags, using simpler network structures and more accurately solving these problems. Experiments show that our results can be competitive with the classical MIL algorithm on the MINST dataset.
Real-time License plate number detection based on image contour
Authors: Li Xingxing 
Published: October 2020

Abstract
The license plate number detection technology is an application of computer video image recognition technology in vehicle license plate recognition. In this paper, an image processing technology is used to extract and detect a license plate in motion from a complex background to a license plate recognition system. The method in this paper is mainly divided into four steps. First, the original image is preprocessed, the color image is converted into a grayscale image, and the gradient edge features are extracted by Sobel operator. Secondly, after the image is binarized, the image generated through the morphological operation of the image to highlight the image outline. Then detect the contour of the entire image and label the contour. Finally, the RGB space is converted into the HSV color space through color space conversion, and the color of the license plate is used to find the area where the license plate is located in the image.
Design of cancer classification and visualization platform based on Internet big data
Authors: Xu Yipeng , Zhang Zhixiao , Liu Min 
Published: October 2020

Abstract
With the development of Internet technology, Internet technology is widely used in the medical industry. Based on the medical Internet big data, using visualization, data mining and other technologies, combined with distributed crawler, HTTP data transmission technology, vue2 front-end framework and the application of visualization technology, this paper completed the development and design of the analysis platform based on the internet medical big data. From the three aspects of presentation layer, business logic layer and data access layer, the architecture can show the number of hospitals, the proportion of doctors, the number of departments, the hospital’s praise, poor evaluation and other information. Then, the cancer big data classification model based on the new bionic optimization algorithm is established. The experimental results show that the method has high classification accuracy and speed. In the era of big data, the integration of early diagnosis and treatment of cancer resources and information construction is very necessary and has far-reaching significance.
Research on Key Technologies of Multi-rotor UAV High-precision Positioning and Navigation System
Authors: Cao Yu , Zhang Xiaofeng , Huang Xiangjie , Wang Fei 
Published: October 2020

Abstract
For the continuous high-precision navigation and positioning needs of rotorcraft UAVs based on industry applications, based on low-cost GNSS single-frequency positioning modules and MEMS inertial navigation, the design high-precision GNSS / INS integrated navigation module. At the same time using computer vision algorithms. Aiming at the requirement of high precision, the original data acquisition scheme that fully guarantees the accuracy of MEMS inertial navigation is designed. No one against the rotor for the high-frequency vibration problem of the mobile platform, the effect of IMU white noise parameters on the performance of MEMS inertial navigation and integrated navigation was analysed. The test results show that the IMU white noise parameters can effectively improve the combined navigation performance under high-frequency vibration conditions; the positioning accuracy of the module can reach centimetre level and be continuous and stable.