bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Method of Improving the Quality of Electric Energy Measurement Data
Authors: Sui Bing , Chen Xiaodong , Shou Zeng , Wang Hongzhe , Guo Zhitong 
Published: October 2020

Abstract
In the process of collecting data in the power grid harmonic monitoring and analysis system, changes in load, operating modes, and equipment failures will cause data changes. For the strong correlation index, this paper establishes a mathematical model of the monitoring value for the measurement index, while for the weak correlation index, considering that the monitoring data is a type of time series data, a time series model of the monitoring value for the measurement index can be established, and then the abnormal value monitoring is performed by statistical methods. Moreover, experiments prove that the research method used in the paper to detect whether abnormal data exists in the data can effectively improve the efficiency and provide a guarantee for the quality of data monitoring.
Enhanced Diffraction by a Completely Planar Adjacent Grating
Authors: Xiong Xuehui 
Published: October 2020

Abstract
A completely planar adjacent grating (AG) structure, which is composed of two identical planar dielectric gratings connected by thin metallic or dielectric film, is proposed in the paper. We carry out the numerical investigations of AG according to rigorous coupled-wave approach. The calculated results indicate that the completely planar grating structure is another highly efficient structure to enhance diffraction due to the interaction of surface waves excited by gratings at resonant conditions on both interfaces of the thin connection layer. The results also reveal that the modulation of refractive index is the same crucial role to excite or couple out surface wave as the roughness of the surface does.
Research Methods of Hawking Radiation
Authors: Han Jiaqi 
Published: October 2020

Abstract
Hawking radiation is the product of the combination of quantum field theory and general relativity, and is an important link in the study of quantum gravity. In this paper, Hawking radiation has been briefly introduced, and at the same time, several common calculation methods in the research of Hawking radiation are summarized. Readers can have a certain understanding of Hawking radiation research through this paper and can complete a simple introduction to Hawking radiation based on the introduction of calculation methods.
Numerical solution of special 2D Fredholm-Volterra integral equations using barycentric Gegenbauer interpolation collocation method
Authors: Liu Hongyan , Huang Jin 
Published: October 2020

Abstract
In this paper, an efficient collocation method based on two dimensional barycentric Gegenbauer interpolation is used to solve a kind of special two dimensional Fredholm-Volterra integral equations (2D-FVIEs). The explicit barycentric weights for the Gegenbauer-Gauss nodes not only reduce the complicated calculation but also preserve the numerical stability. The combination of the barycentric interpolation and the Legendre-Gauss quadrature formula transforms the 2D-FVIEs into a system of discrete algebraic equations whose solution is a set of the nodal function values. The numerical experiments provide the maximum absolute error and the convergent order to assess the accuracy and the convergence of the method.
A regularization method for solving the redundant problems in multibody dynamic system
Authors: Yang Liusong , Xue Shifeng , Yao Wenli 
Published: October 2020

Abstract
Redundant constraints may cause great difficulties during the numerical simulation, when solving the differential algebraic equations (DAEs). The article presents a regularization method based on optimization form of the Gauss principle of least constraint and the Udwadia and Kalaba (UK) method, which expresses the solution of the dynamic motion in an explicit expression. Compared with Lagrange method, the proposed method does not need to solve the Lagrange multipliers any more for the complex multibody mechanical systems. In the end, a numerical example is given to illustrate that the proposed method not only has the ability to handle the problems with redundant constraints, but also has higher accuracy and keep a stable constraint violation level than the traditional methods.
New theoretical system of physics in the 21st century
Authors: Zhou Jiang Hua 
Published: October 2020

Abstract
In 2000, the author published a new discovery about the same-sex charge produced by friction of the same substance at the ninth electrostatic academic conference of Chinese physical society. For this important new experimental discovery, the author puts forward a new understanding of “positive and negative charges” and finds a new theory to explain all electrostatic effects. Based on the subversive new understanding of “matter”, “entity” and “heat energy”, a new understanding of “particle charge dynamic atomic model” is initiated. It is clarified that the relationship between “entity” and “heat energy” is the root of the existence of gravitation and repulsion between matter, The law of equilibrium distance between gravity and repulsion is put forward. This paper reveals the causes of the formation of the earth’s gravity and many phenomena of attraction and repulsion force in the universe and so on. In the fields of gravitational field, magnetic field, electric field and so on, a series of important scientific problems have been revealed! The establishment of the new theoretical system provides a new vision for solving “all physical problems”! The new theoretical system consists of six parts: the first part introduces the reasons for the establishment of the “new theoretical system”, the second part proposes a new basic epistemology of the material world, the third part is a new epistemology of the gravitational repulsion field, the fourth part is a new epistemology of the magnetic field, and the fifth part is a new epistemology of the electric field, and the sixth part expounds the scientific significance of the new theoretical system. Starting from a new perspective of the basic composition of “entity” and “heat energy” in the material world, this paper makes a new understanding of matter, entity, heat energy, atom, element, gravity, repulsion, magnetic field and electric field, Established 21st century physics new theoretical system, Material world: “entity” and “heat energy” constitute “unified field theory”. Scientific research needs a new vision to expand the subjective human thought’s understanding of the objective nature. The establishment of this new theoretical system may lead to a new physics revolution in the 21st century.
The Research of Wind Power Project Company’s Engineering Management System
Authors: Cai Hualong , Xie Wanchao , Lin Dongliang 
Published: October 2020

Abstract
By analyzing the process of construction engineering management of Wind power project company, we can abstract the core professional work, which includes budgets, bits, contracts, schedules, quality, safety, finance, machine management and more contents. Combined with the organizational structure of project companies, linked with the process of core professional work, to design the hardware and software structure of construction engineering management system.
Image classification based on RESNET
Authors: Liang Jiazhi 
Published: October 2020

Abstract
at present, neural networks are becoming more and more complex, from several layers to dozens of layers or even more than 100 layers. The main advantage of deep network is that it can express very complex functions. It can learn features from different levels of abstraction, such as edge features at lower levels and complex features at higher levels.However, the use of deep networks is not always effective, because there is a very big obstacle - the disappearance of gradients: in very deep networks, gradient signals tend to approach zero very quickly, which makes the gradient descent process extremely slow.Specifically, in the process of gradient descent, the weight matrix product operation must be carried out in every step of back propagation from the last layer to the first layer, so that the gradient will drop exponentially to 0.(in rare cases, there is the problem of gradient explosion, that is, the gradient grows exponentially to the overflow in the process of propagation). Therefore, in the process of training, it will be found that with the increase of the number of layers, the rate of gradient decrease increases.Therefore, by deepening the network, although it can express any complex function, but in fact, with the increase of network layers, we are more and more difficult to train the network, until the proposal of residual network, which makes it possible to train deeper network[1].
Research on Coordinated Optimization of Active and Reactive Power in Active Distribution Network
Authors: Wu Xiaomeng , Li Chong 
Published: October 2020

Abstract
Traditional optimization for distribution network usually uses reactive power optimization to ensure the safe operation of the distribution network, and uses the distributed power and various adjustable resources of active power adjustment to ensure the economic operation of the distribution network. However, in the distribution network, the impedance ratio of the line is large and the coupling of active and reactive power is strong. Unilateral active or reactive optimization for distribution network is not comprehensive. In addition, the uncertainty of Distributed Generation and load poses a great challenge to optimization for active distribution network, the control strategy formulated by traditional deterministic optimization might inaccurate. In this paper, the mathematical model of active and reactive power coordinated optimization for active distribution network is given. Various algorithms dealing with the uncertainty of distribution are introduced, and advantages and disadvantages of various algorithms are analysed.
Infrared and Visible Image Fusion Based on Spatial Convolution Sparse representation
Authors: Shao Luling , Wu Jin , Wu Minghui 
Published: October 2020

Abstract
In the traditional sparse representation based infrared and visible image fusion method, the detail information is not able to be effectively extracted, resulting in the decrease of infrared target intensity and the blurry of visible background information. In order to solve the above issue, a new image fusion method based on spatial convolution sparse representation is proposed. Firstly, a spatial convolution sparse representation is used to perform two-scale decomposition of infrared and visible images by introducing a gradient regularization, and the detail and intensity information are extracted effectively from the source images. Then, the weighted average rule and the maximum selection rule are used to fuse the base layer and detail layer images, respectively. Finally, the fusion image is constructed. Experimental results illustrate that the proposed method is superior to the traditional fusion method based on sparse representation.
Prototypical Network for Radar Image Recognition with Few Samples
Authors: Liu Diyang , Gao Xunzhang , Shen Qinmu 
Published: October 2020

Abstract
At present, deep learning has surpassed humans in recognition tasks, but its performance strongly depends on sufficient training samples. When the training samples are extremely insufficient, overfitting also will damage the performance of network, despite the use of fine-tuning methods. One-shot learning (OSL) is proposed to overcome the difficulties of training neural networks while having almost no samples, which is a common situation in radar image recognition. This paper introduced OSL into recognition of some radar targets whose labelled images are seriously limited, and proposed an OSL method with prototypical networks based on the assumption that functions of the network trained with auxiliary samples also affects samples to be identified. The method of this paper involves image preprocessing, building of linearly separable feature space and feature vector clustering. Experiments on MSTAR dataset show that the performance of our method is better than deep transfer learning when the training samples in the target domain are seriously deficient.
Malicious vehicle node detection mechanism based on repeated game and trust evaluation in VANET
Authors: Zhu Yatao , Wang Yongli 
Published: October 2020

Abstract
In order to solve the problem of malicious vehicle nodes attack in VANET system and improve the security of VANET communication, the paper proposes a method of malicious vehicle nodes detection based on repeated games and trust evaluation. First of all, according to vehicle nodes communicating, a repeated game model is established to generate vehicle nodes revenue by punishing attack behavior nodes and rewarding normal behavior nodes. Secondly, a trust evaluation mechanism is introduced to convert vehicle nodes revenue into nodes trust value. Finally, the optimal dynamic threshold is calculated through multiple iterations, comparing and analyzing nodes trust value and dynamic threshold to screen out the malicious vehicle nodes. Simulation experiments show that this mechanism improves the detection rate of malicious nodes and reduces the error detection rate, effectively isolates malicious vehicle nodes according to the change of node trust value, and improves the security of VANET communication.
Application of Hyperspectral Images and Spectral Features of Yolks in Egg Freshness Detection
Authors: Huang Shiqi , Pu Xuewen , Luo Peng 
Published: October 2020

Abstract
The detection of egg freshness is an important basis and means to obtain the effective value of eggs. In order to more effectively and reasonably classify and monitor the quality of eggs, a new egg quality identification method based on the hyperspectral image data of egg yolk and its spectral characteristics data is proposed. In this method, the spectral and hyperspectral data of the raw yolk and the boiled yolk are obtained by using a spectrometer and a hyperspectral imager, respectively. By analyzing different spectral properties, building a relationship model between each other, combining with different results, the new proposed method has achieved the purpose of identifying the freshness of eggs. The test experiments were carried out with different batches eggs of the same type. The results show that the method proposed in this paper can detect the freshness of eggs, and can provide new ideas and references for egg quality classification and detection.
Local path planning for unmanned surface vehicle with improved artificial potential field method
Authors: Xiao Ma , Zuan Lin , Song Ruiyin 
Published: October 2020

Abstract
Aiming at the drawbacks of traditional artificial potential field method in local path planning for USV (unmanned surface vehicle), an improved artificial potential field method is proposed. By improving the gravitational potential field model and restraining the distant gravitational potential field, the problem of USV colliding with obstacles is solved. In the repulsion field model, the influence factors such as relative position and relative velocity are introduced to reduce the repulsion potential field intensity of the obstacle near the target, so as to solve the problem of goal nonreachable with obstacle nearby. The regulation mechanism of random perturbation potential energy is introduced to solve the problem that it is difficult to move at local minimum points. The rationality and superiority of the proposed improved artificial potential field method are verified by simulation and comparison experiments.
A low illumination image enhancement algorithm based on adaptive fractional differentiation
Authors: Wang Liangyan , Zhan Xiaoyi , Wang Chunling , Chen Zihong , Xia Yunfei 
Published: October 2020

Abstract
Using fixed order fractional differential for image enhancement, some regions of the image may not achieve the desired enhancement effect. According to the characteristics of human vision and low illumination image, an adaptive order fractional differential enhancement algorithm is proposed. Three different differential orders are selected for enhancement, and one of them is adaptively selected for each pixel according to the comparison results of gradient values. The experimental results show that the adaptive order can not only enhance the image with high gradient value such as the edge, but also reduce the noise interference in the flat area, which has better visual effect than fixed order enhancement.
Study on 3D Pore Label of Porous Materials Based on CT Images
Authors: Liu Zhidong 
Published: October 2020

Abstract
Microscopic pore structure is one of the important factors affecting macro porous materials physical properties, pore structure research for characterization of physical properties of porous materials is of great significance. In order to study the three-dimensional parameters of porous materials in each pore structure, such as pore size, volume, specific surface area, fractal and connectivity, it is necessary to label each pore structure in the three-dimensional structure. Two-dimensional CT image sequences in porous material as the research object, three-dimensional target marking algorithm is proposed. The sequence images using median filter algorithm to remove noise, through the automatic threshold segmentation algorithm, get the binary image. The boundary information of each pore is computed by Using the algorithm of two-dimensional multi-target label in each layer image. The 3D pore structure is labelled by the calculation of the projection relationship between the targets in the tomography image. The labelled result of pore structure is verified by single and whole reconstruction with marching cube algorithm. Results show that the porous three-dimensional pore structure was marked accurately, which lays a foundation for the calculation of 3D pore structure parameters.
Estimation of SPAD value in tomato leaves by multispectral images
Authors: Ding Yongjun , Zhang Jingjing 
Published: October 2020

Abstract
To improve the prediction accuracy of tomato chlorophyll content based on multispectral images, three preprocessing methods that can weaken illumination influence, i.e., self-adaptive gamma correction, multiscale Retinex and reflectance reconstruction, are compared and analyzed, and corresponding estimation models for the tomato Soil-Plant Analysis Development (SPAD) value are established. The correction coefficients are set according to the deviations between the grayscale values of the pixels in the highlighted and shaded areas and the average grayscale values in the area of uniform illumination to realize the self-adaptive gamma correction. The SPAD estimation model is constructed by the corrected image, with input parameters of nir, RVIb,g, RVIg,nir, RVIr,nir, NDVIr,g, and NDVIb,r, and the Rc2 and Rv2 of the model are 0.87 and 0.8, respectively. The original image is convolved with three different Gaussian functions to obtain a multiscale Retinex corrected image, and the SPAD estimation model is constructed. The input parameters are b, RVIr,g, RVIr,nir, RVIg,b, RVIg,nir, RVIb,nir, and NDVIr,g, and the Rc2 and Rv2 of the model are 0.91 and 0.84, respectively. The accuracy of the above two models depends on the selection of the corrected gamma value and the convolution kernel, and improper selections could seriously affect the accuracy of the model. For the SPAD value estimation model based on the reflectance reconstruction, its input parameters are nir, RVIg,nir, RVIr,g, NDVIg,b, NDVIr,nir, and NDVIb,r, and the Rc2 and Rv2 of the model are 0.90 and 0.88, respectively. The preprocessing procedure is simple, and the universality is high, making it suitable for the application of the digital field management of the crop.
Stamen movement detection of Commelina purpurea based on feature matching
Authors: Gui Chengbo , Jiang Haibo , He Jin , Tang Dan 
Published: October 2020

Abstract
The stamen movement is very important to reproduction of plant. This paper presents a feature-matching-based method to detect stamen movement of Commelina Purpurea using image processing. The regions of stamen were firstly extracted by image segmentation using thresholding. Then, the area discrimination factor of each stamen region was calculated to judge whether these stamens were adhered or not, if such adhesion did exist, the adhered stamens were segmented by watershed algorithm. After that, feature detection and matching were carried out between two adjacent frames in the image sequence in order. Then, the slope and distance statistics between the matching feature points are maded to further optimize the matching results and figure out the matching relation of different stamens in the two frames. Finally, through the matching result of different stamens in consecutive frame images, the moving trajectory of the stamens was obtained. The empirical results show that, this method can accurately segment the adhered stamens and acquire stamen trajectory of Commelina Purpurea.
Calibration method of simulation data of virtual GPS and truth value in real world
Authors: Chen Chen , Zhang Dongze , Mei Junyu , Zhao Yuliang , Chen Rongjie 
Published: October 2020

Abstract
At present, the complexity of the research and development process of the intelligent connected vehicle and the diversity of research methods increase the difficulty of establishing, integrating and verifying of virtual simulation experiments. In view of the deviation of the virtual vehicle sensor in the simulation experiment to the restoration of the real environment, this paper proposes to use the multi-point positioning method for data calibration, use the least square method to estimate the unknown point position in complex situations, and according to the error size after calibration, specific evaluation criteria are given. Finally, the scene verification and simulation evaluation of the calibration method of the GPS simulation data in the virtual environment and the truth value in the real world were carried out. The results show that this method effectively improves the restoration degree of the virtual simulation sensor to the real environment.
A Time Dependent Process Zone Model for Slow Crack Growth of Polyethylene Pipe Material
Authors: Liu Yijiang , Li Yan , Liu Xiu , Luo Wenbo , Yang Bo , Li Maodong 
Published: October 2020

Abstract
Polyethylene (PE) pipe is widely used in water supply and gas transportation engineering. Its fracture behavior is very important for the safe operation of the pipeline. The objective of this work is to simulate the slow crack growth (SCG) process of PE pipe material via a time dependent crack-tip process zone model. To achieve this end, the crazing damage caused by stress concentration at crack tip of PE material is taken into account, the stress on the bulk/craze interface layer is supposed to be uniformly distributed due to the micro necking mechanism of the layer, and a linear crack growth kinetics is used. In order to describe the delay characteristics of the fracture process of PE materials, the fracture surface energy is considered as an exponential decay function of time, which is attributed to the creep damage of the craze fibrils. A simulation algorithm of the proposed process zone model is suggested using iterative method. The model is verified by comparing the simulation with the discontinuous SCG behavior reported in the literature.