bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classification of picture art style based on VGGNET
Authors: Yang Zihan 
Published: February 2021

Abstract
Aiming at the classification of various painting art styles in modern society, a method based on convolution neural network is proposed. The classification of various painting art styles is completed by using convolutional neural network. In VGG-19 (visual geometry) Based on Group-19 (Group-19) network, this paper proposes a picture style recognition algorithm based on visual geometry group 19 mixed transfer learning model. By using the feature extraction ability of convolution neural network, the convolution layer parameters of VGG-19 model on the source data are transferred to the target data model, and then the sparse automatic encoder SAE (sparse auto) is used Finally, softmax classifier is used to classify the artistic style of pictures. The artistic style of painting can be roughly divided into: characters, flowers and birds, landscape. The VGG-19 model is used to predict the three kinds of picture art styles, and then the proportion of the predicted results is compared with the actual naked eye proportion, and the conclusion that VGG-19 model is more suitable for classification of painting art styles is obtained.
Research on location and similar comments in point-of-interest recommendation system for users
Authors: Liu Yu , Wei Ning 
Published: February 2021

Abstract
By combining deep learning algorithms and potential probabilistic topic models, this paper proposes a new modeling strategy for individual users and constructs an effective point of interest recommendation system. First, Doc2vec is used to vectorize the user’s comments, and the Bow model is used to match the similarity of the points of interest, and then the potential probability model is used to cluster the positions of the points of interest. Finally, relying on the user’s historical comment data as a basis, the Top-K ranking recommendation scheme is obtained. The experimental results show that for large-scale location-based social network data sets, the algorithm in this paper has an ideal final effect on users’ personalized recommendations. The recommendation model for user location information and similar comment points of interest proposed in this paper is more subjectively and objectively in line with user behavior needs. On the premise of ensuring the real-time performance of recommendation, the model proposed in this paper effectively improves the accuracy of recommendation compared with traditional point-of-interest recommendation algorithms.
Application of BP neural network on quantitative evaluation of curriculum reform in advanced education-A case study of signal and system
Authors: Meng Lu , Gu Zhixing , Li Fei , Liu Xiaohui , Zeng Guoqiang , He Xingjie 
Published: February 2021

Abstract
In this paper, BP neural network model is used to study and analyse the teaching reform of signal and system course. Referring to the structure of BP neural network, the quality evaluation index system of signal and system course is established. On this basis, the factors influencing students’ examination results are predicted, and the questionnaire is designed and BP neural network is used for prediction. The mean square deviation of the result is 0.7788. Through the correlation coefficient analysis of the data obtained, we can get the major factors that affect students’ final scores. In view of this, the paper puts forward the direction and specific measures of teaching reform of this course.
Estimation of state of charge of lithium battery based on parameter identification of fractional order model
Authors: Shen H X , Li X , Chen L , Xun H H , Chen W X 
Published: February 2021

Abstract
Accurate estimation of state of charge of lithium battery is one of the important performance parameters for safe and reliable operation of lithium battery. A fractional order second-order Thevenin equivalent circuit model was proposed by based on the improvement of the traditional Thevenin equivalent circuit model for accurately estimating the state of charge of lithium-ion battery. In order to overcome the shortcomings of the least square method easily enter into local convergence or even unable to converge, an adaptive genetic algorithm is proposed to identify the parameters of lithium battery model, and global parameter identification is carried out to improve the convergence of the algorithm. Matlab simulation shows that the parameters of fractional order model of the second-order Thevenin equivalent circuit identified by adaptive genetic algorithm are better than those of integer order model identified by least square method. Combined with extended Kalman filter, the estimation of state of charge accuracy control is realized, with the accuracy error being within 1.61%.
Research on the driving mechanism of tourism regional brand development of tea production base based on the difference-in-difference method
Authors: Ye Yanghao , Wang Qing , Zhu Jie , Ma Wei , Huang Yajuan 
Published: February 2021

Abstract
A perfect tea production base can promote the development mechanism of regional tourism brand and improve the evaluation value of regional brand. A complete driving mechanism of regional tourism brand development of tea production base can promote the local economic development and the improvement of national economy. And with a certain scientific mathematical model to evaluate the role of this mechanism is the necessary content of the development of this mechanism. As a result, this article adopts the Difference-inDifference to analysis tea production base of regional brand, and study on the use of Difference-in-Difference of the various influence factors on the role of the output value. It gives a series of comparison of the predictive value and the actual value, and found the problems about tea base and related regional brand, and put forward the corresponding opinions and suggestions.
Game theory-oriented research and simulation analysis of housekeeping credit
Authors: Ma Qian 
Published: February 2021

Abstract
The paper studies credibility issues in the housekeeping industry based on the aspect of the theory of game. Domestic service personnel cut work and reduce time, business capabilities are not up to standard, and domestic enterprise supervision is not in place, causing consumers’ dissatisfaction. This article points out that housekeeping companies can strengthen the relationship with employees and encourage employees to choose integrity; housekeeping service personnel need to improve their self-service capabilities; at the same time, consumers need to respond to the situation based on facts. This can better maintain the integrity of the housekeeping industry and increase consumer satisfaction. The game results show that when the housekeeping enterprise strengthens supervision, the housekeeping service staff will tend to operate with integrity, and when the housekeeping service personnel are honest, the probability of consumer complaints will also decrease. Finally, this article uses Matlab to simulate the integrity of the housekeeping industry based on games for the first time, allowing us to more clearly understand the relationship between different factors and the decision-making probability of each party to verify the game results.
Research on the information sharing in the linkage between manufacturing and logistics industry based on blockchain
Authors: Li Qiong , Wang Lei 
Published: February 2021

Abstract
In order to promote the linkage and integration of manufacturing industry and logistics industry, we should not only pay attention to the convergence of movement time and function among industries, but also consider the orderly combination of industrial subsystems in time, space or function. At present, due to the lack of trust between industries, seeking the maximization of their own interests and other reasons, the information sharing between industries can not be realized. The industrial linkage with many advantages not only fails to operate efficiently, but aggravates the inefficient operation. In this paper, information sharing system in the linkage between manufacturing and logistics industry based on blockchain is proposed, and a detailed sharing model is given on such basis. With the help of blockchain, we hope to break the information flow barrier in the linkage between manufacturing and logistics, realize the efficient coordination and management of the linkage process between manufacturing and logistics, and improve the modernization level of China’s industrial chain and supply chain.
Research on risk assessment of clients before loan based on decision tree algorithm
Authors: Wang Yongkai , Duan Ditao 
Published: February 2021

Abstract
How to transform credit funds into the endogenous development capacity of the market and promote the sustainable development of the economy, the first consideration is how to conduct risk management. How to do a good job in risk assessment has gradually become an important part of current financial risk management. This paper uses the decision tree algorithm to conduct a research on the risk assessment of customers before loan. After the model verification of the cross-validation method and the random validation method, the results show that the risk estimation accuracy of the decision tree algorithm reaches 81.2% and 83.6%, which proves that this model can be an effective reference for pre-loan risk assessment.
Research on classification management of car dealers in used car platform based on sd simulation model
Authors: Qu Ying , Yang Na , Sun Zhuangzhi 
Published: February 2021

Abstract
In recent years, the used car e-commerce industry has risen rapidly, at present, the number of car dealers on the used car e-commerce platform is large and scattered, and car dealer management has become a mainstream issue. Based on this question, this article selects 40 car dealer data on the Y used car platform, and classifies them on the three dimensions of car dealers’ relative scale, integrity, and professionalism. Based on the classification results of car dealers, strategies are proposed, and system dynamics models of the relationship between each strategy and revenue are constructed respectively. Assign initial values or initial functions to each variable to obtain simulation results, and apply the simulation results to the differentiated management of car dealers’ classification. Targeted strategies and scopes for different types of car dealers are proposed, management goals for all types of car dealers in harsh environments are put forward, and it is suggested for the establishment of a dynamic tracking system based on the transaction process.
Comparison between the influence of mechanical vibration and junction temperature rise originated bond wires detachment on the characteristics of IGBT module
Authors: Teng Yiran , Wang Liancheng 
Published: February 2021

Abstract
As the main device in a power system, the IGBT module works in the frequent power cycle for a long time, resulting to the fluctuation of junction temperature and heavy mechanical stress loading. These two factors threaten the reliability of bond wires and the IGBT module significantly. This study aimed at improving the reliability of the semiconductor device. IGBT dual bridge module was used as the primary research object, establishing the relationship between the bond wires detachment and resistance. MATLAB was used for mathematical analysis to determine the quantitative influence of the two conditions on several static characteristics of the IGBT module. Our study provides more samples and references to monitoring the IGBT bond wires and demonstrates the difference and similarity of these two factors.
A digital multi-informational stochastic dynamic medical decision-making model and the application
Authors: Xiao Xiaonan 
Published: February 2021

AbstractAs we all know, big data and intelligent computing have been widely used in information science, life science, computer science and intelligent control, intelligent robots, vehicle networking, space technology, marine development and other fields, especially in the future life science and medical field. The results of the discussion show that the intersection and fusion research of big data analysis, mathematics, computational science and life science in the 21st century is getting more tightly. We can understand life science from a new perspective by using big data and Intelligent Computing technology. Thus a new research model is being used to shift the application of mathematics from non-life to life. Furthermore, it greatly strengthens the mutual penetration and connection of big data analysis, mathematics, computational science and life science. It also greatly accelerates the research process of modern life science.
Effect of different pretreatment methods on pore structure of activated carbon
Authors: Yang H , Liu J , Pang B , Chi J 
Published: February 2021

Abstract
The effects of pretreatment on the pore structure of activated carbon were studied by the methods of water washing, acid washing, alkali washing and a combination of acid washing and alkali washing. It can be known from experiments that water washing has a cleaning effect on activated carbon, while acid washing helps to open the micropores of activated carbon and improve its porosity. Sodium hydroxide solution has an etching effect on activated carbon, which can increase the porosity and average particle size of activated carbon. All the pretreatment methods in this article can improve the adsorption capacity of activated carbon for nitrogen, and the pretreatment by dilute hydrochloric acid is tested to be the most effective.
Research on network vulnerability assessment based on attack graph and security metrics
Authors: Ma Wanzhi 
Published: February 2021

Abstract
In recent years, the information security environment is undergoing great changes. On one hand, with the development of technology and the advancement of network integration, network involves in a larger and larger scale, and its structure is becoming more and more complex. On the other hand, the development of attack technology has also taken a qualitative leap. The ability of violent cracking and the scale of botnets are no longer the primary factors that determine the attack effect. On the contrary, attackers are more likely to adopt information-driven complex combination attacks with clear attack targets. These changes have brought great challenges to network security defense. Therefore, from the perspective of building a secure network environment, this paper studies network vulnerability assessment in the field of computer network security, and proposes a method of network vulnerability assessment based on attack graph and security metrics. This method models and constructs the attack graph for the possible network attack behaviors. Besides, taking it as the analysis model, the risk assessment technology is taken to determine the indicators and calculating methods of security metrics so as to realize the evaluation of network vulnerability. Finally, the discussion was conducted based on the results, and a follow-up study was suggested.
Network traffic detection based on part matching and section evolution of immune elements
Authors: Liu Caiming , Zhang Yan , Xie Chunming , Wang Deming , Li Zhonghua 
Published: February 2021

Abstract
Immune algorithms can improve the self-adaptability for network traffic detection. Classical immune algorithms dynamically evolve and match the whole content of immune elements. However, most features of network traffic are isomeric to each other. The general matching and evolution for the whole immune elements slow down the process of self-adaptability to an extent and reduce the accuracy of immune elements’ evolution. In this paper, available network data features are analysed for the network traffic detection. The section simulation method in the immune system is studied by creating a math method for part matching of immune elements which can evolve in parts. The process of section evolution for immune elements is inferred. A detection method for recognizing anomaly network traffic is proposed. Simulation experiments show that the self-adaptability of the proposed method to the real network environment is superior to that of traditional immune algorithms.
Slowdown and reversal of terrestrial near-surface wind speed and its future changes over eastern China
Authors: Zha Jinlin , Shen Cheng , Zhao Deming , Wu Jian , Fan Wenxuan 
Published: February 2021

Abstract
A recovery of near-surface wind speed (SWS) in the last decade has been reported over China; nevertheless, the contributions of large-scale ocean-atmosphere circulations (LOACs) to the SWS changes are rarely investigated. In this study, the turning point (TP) of the terrestrial stilling was validated over eastern China for 1979–2017. Furthermore, a forward stepwise regression algorithm was used to assess the contribution of LOACs to SWS changes. The results revealed that the TP of the SWS reversal occurred in approximately 2011 during the study period. Mean annual and seasonal SWSs exhibited decreases before the TP, with the largest decrease in spring (–0.134 ± 0.014 m s−1 decade−1), while SWSs increased after the TP, most strongly in autumn (0.377 ± 0.053 m s−1 decade−1). The SWS decrease before the TP and increase after the TP were caused by the decreasing and increasing frequencies of strong windy days (>75th percentile of SWS), respectively. The effects of LOACs on the long-term changes of SWS were pronounced. The contributions of LOACs to the decreasing and increasing trends of SWSs were >60.0%, with the exception of autumn. The projected SWSs exhibited increases in the near-term (2021–2040) for the low-emission scenarios (e.g. Shared Socioeconomic Pathway 245). For the mid-term and long-term projections, the SWSs still displayed a downward trend, which was mainly attributed to the reduction of strong windy days. Consequently, the present SWS recovery in the recent decade may be only expected to last for a short amount of time before winds start decreasing again.
Z2×Z2

-graded parastatistics in multiparticle quantum Hamiltonians
Authors: Toppan Francesco 
Published: February 2021

Abstract
The recent surge of interest in

Z

2

×

Z

2

-graded invariant mechanics poses the challenge of understanding the physical consequences of a

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2

×

Z

2

-graded symmetry. In this paper it is shown that non-trivial physics can be detected in the multiparticle sector of a theory, being induced by the

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2

×

Z

2

-graded parastatistics obeyed by the particles. The toy model of the

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=
4

supersymmetric/

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2

×

Z

2

-graded oscillator is used. In this set-up the one-particle energy levels and their degenerations are the same for both supersymmetric and

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2

×

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2

-graded versions. Nevertheless, in the multiparticle sector, a measurement of an observable operator on suitable states can discriminate whether the system under consideration is composed by ordinary bosons/fermions or by

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2

×

Z

2

-graded particles. Therefore,

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2

×

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2

-graded mechanics has experimentally testable consequences. Furthermore, the

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2

×

Z

2

-grading constrains the observables to obey a superselection rule. As a technical tool, the multiparticle sector is encoded in the coproduct of a Hopf algebra defined on a Universal enveloping algebra of a graded Lie superalgebra with a braided tensor product.
The Noise Level Analysis of Hybrid of Passenger-Freight Railway based on On-line Automatic Monitoring System
Authors: Xuan Xiao-mei 
Published: February 2021

Abstract
A large amount of data is accumulated from the German railway noise on-line monitoring system, which is online for the first time since 2019. In this paper, the monitoring system is introduced simply. By collating and analysing the monitoring data of the last year, overall noise level of current hybrid of passenger-freight railway in Germany and noise level of each measuring station is given for the first time respectively. Finally it is pointed out that the flow of freight is the key factor affecting the noise level of each station. It provides a basis for the follow-up research on the optimization of train traffic volume based on noise level.
Numerical simulation of shield underneath passing a river in shallow water-rich sand layer
Authors: He Qiang , Jian Gong , Ning Wengxiang 
Published: February 2021

Abstract
In view of the situation that the tunnel of Hangzhou Metro Line 6 underneath passed the Yongjiu River, the influences of the construction of the new double-line tunnel on the seepage field and stress field of the shallow buried water-rich sand layer were analyzed, and the ground reinforcement measures to ensure the safety of shield construction was proposed. The results show that: (1) After the tunnel is excavated, the seepage field gradually returns to the original seepage field, but there is still a slight disturbance in the seepage field within 30 m below the arch bottom; (2) The maximum displacement and maximum principal stress of the tunnel model are located at the bottom of the arch; (3) It is necessary to fully consider the conditions of the river, control the settlement and cracking of the foundation, and prevent the occurrence of gushing.
The characteristics purifying formaldehyde of air purification system for haze-absorbing wall
Authors: Ji Kai , Qiao Chunzhen , Zhang Zhen , Li Zhiyong 
Published: February 2021

Abstract
Formaldehyde in indoor air is very harmful to human body. In this paper, a haze-absorbing wall air purification system was constructed based on assembly buildings. The experimental device was set up with bulk activated carbon as adsorption material. The purification performance for formaldehyde of the system was studied experimentally. The effects of air velocity and air passage size on formaldehyde purification efficiency were analysed. It was found that the haze-absorbing wall system can effectively purify the formaldehyde in the air. After the experiment, the purification efficiency of the system to the formaldehyde is more than 90% under all conditions of the experiment. With the increase of inlet air velocity, the purification efficiency of haze-absorbing wall to formaldehyde increases first and then decreases, and the peak value appears when the air velocity is 0.4m/s. When the air passage is 20cm and the air velocity is 0.4m/s, the haze-absorbing wall has the best purification performance for formaldehyde.
Experimental study on anti-eroding effect of slope protected by degradable geocell
Authors: De-yong Wang , Jun-long Hu , Jing Wang , Qing-jun Zun 
Published: February 2021

Abstract
In order to study the anti-erosion mechanism of the new degradable geocell which is designed for slope protection and the influence of rainfall intensity and materials on its anti-erosion performance, based on the laboratory simulated rainfall tests, the erosion damage mode and water erosion of slope under the protection of linen fiber and bamboo fiber braided geocell under different rainfall intensities are studied by taking photos of the slope surface and collecting and weighing the erosion material. The results show that the new type of degradable geocell for slope protection can effectively prevent the development of slope gullies, and the slope damage is mainly splash erosion and sheet erosion. The use of linen fiber and bamboo fiber braided geocell can effectively reduce the maximum water erosion by more than 10% and the accumulated water erosion by more than 20%. With the increase of rainfall intensity, the maximum water erosion and accumulated water erosion are increased, but the increase range is 20% ∼ 33% and 35% ∼ 57% lower than that of bare slope, respectively. The results show that the anti-erosion ability of bamboo fiber braided geocell is slightly better than that of linen fiber braided geocell, and the ratio of maximum water erosion and accumulated water erosion reduced is slightly higher than that of linen fiber braided geocell.