bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nuclear form factor of xenon from photoproduction of vector mesons in Xe-Xe ultraperipheral collisions at the LHC
Authors: Guzey V , Zhalov M 
Published: December 2020

Abstract
Using the Gribov-Glauber model for photon-nucleus scattering and a generalization of the vector meson dominance model for the hadronic structure of the photon, we calculate cross sections of light and heavy vector meson photoproduction in ultraperipheral Xe-Xe collisions at 5.44 TeV at the Large Hadron Collider. Analyzing the momentum transfer distribution in this process, we examine the feasibility to extract the nuclear isoscalar form factor of Xe isotopes, which are needed in searches for dark matter with Xenon-based detectors.
Gravitational lensing by a black hole in non-Riemannian spacetimes
Authors: Zamani S S , Akhshabi S 
Published: December 2020

Abstract
We study gravitational lensing by a black hole in the framework of the poincaré gauge theory of gravity. By using a recent black hole solution in this setup, we derive the deflection angle for light rays grazing the black hole and numerically solve the resulting integral. Numerical result show that the effects of torsion generally increases the deflection angle.
Dynamics of Space at High Energies
Authors: Petriakova P M 
Published: December 2020

Abstract
The dynamics of space endowed by a metric of the 3-dimensional sphere in the framework of f(R)–gravity acting in D = 4 from the creation at high energies is studied. Spaces of finite size are found as a result of exact solution of the classical equations of motion. Generalization of the theory to other dimensions D = 3 and D = 5 are also considered.
CP-sensitive observables for the process pp → Z → ZH → 2e2μ
Authors: Belyaev N , Konoplich R , Prokofiev K , Reese S 
Published: December 2020

Abstract
After the discovery of the Higgs boson at the LHC, additional precise measurements were performed testing its compatibility with the Standard Model (SM). One of the most important deviations from the SM predictions is the possible CP violation in the Higgs sector that may have implications for the origin of the baryon asymmetry in the early Universe. In this paper, new kinematic observables are suggested to probe the CP properties of the Higgs boson. The Higgs boson associated production with a Z boson with a four-lepton final state is studied at theoretical and Monte Carlo levels. Sensitivity of considered observables to the CP nature of the Higgs boson is demonstrated.
Incorporating the Heisenberg and Pauli principles into the kinetic approach to neutrino oscillations
Authors: Kartavtsev A 
Published: December 2020

Abstract
Neutrinos play an important role in the supernovae explosions. The energy transfer from the core to the outer layers depends on the neutrino flavor evolution, affected by collective neutrino oscillations. The latter are damped by kinematic decoherence, developing in the course of the neutrino propagation. The kinematic decoherence caused by dephasing of many neutrinos is readily accounted for in the kinetic approach to neutrino oscillations. We show that the kinematic decoherence caused by dephasing of momentum modes of the neutrino wave-packets can also be accounted for in the kinetic approach through a choice of the initial conditions consistent with the uncertainty principle. According to the existing estimates, this effect may have a substantial impact on the phenomenology of supernovae neutrinos.
Tidal forces near a black hole with scalar hairy
Authors: Andre E L , Potashov I M , Tchemarina Ju V , Tsirulev A N 
Published: December 2020

Abstract
We deal with static, asymptotically flat, spherically symmetric black holes supported by a minimally coupled scalar field with an arbitrary self-interaction potential. We consider a scalar black hole as a simple model of supermassive black holes in the centers of galaxies surrounded by dark matter. Both the radius of the innermost stable circular orbit and the event horizon radius of such an object are less than those of a Schwarzschild black hole with the same mass. Moreover, they can be arbitrary small, so that tidal forces, acting on a star orbiting a scalar field black hole near its photon sphere, can be extremely large and can disrupt the star. This means, in turn, that tidal effects can play an important role for the interpretation of observations in galactic astrophysics.
Study of charge sharing effect in a GaAs:Cr-based Timepix3 detector
Authors: Rastorguev D , Kozhevnikov D , Smolyanskiy P 
Published: December 2020

Abstract
Hybrid pixel semiconductor detectors find more and more applications in modern experimental physical setups. In particular, pixelated detectors based on GaAs:Cr sensor and Timepix3 chip are used in R&D for a state-of-the-art Transition Radiation Detector prototype at CERN. Motivation and usage aspects for GaAs:Cr-Timepix3 device in the experiment are covered in the talk. Authors” contribution to the work of the research group is a study of charge collection and transportation processes in the sensor including fluorescence and so-called charge sharing effect. These are able to significantly affect both spatial and energy resolution of the system. Estimates for the effects are obtained via numerical modelling and then used to analyze the impact on the detector performance.
Research on Optimal Layout of the Mobile Project Department based on Internet technology
Authors: Wang Shao-rui , Wang Kang-nan , Yuan Li , Bai Wen-qi , Ma Zhi-hua 
Published: December 2020

Abstract
Diversified mobile project department layout has a positive impact on the formation of a guiding design of scheme. In this paper, the parametric analysis of design elements are carried out. And the random of generations and optimization of the schemes are simulated by Grasshopper and Excel. Firstly, the initial parameter input options are set. After the size of each partition is limited, the random generation is carried out, and the overall layout shape of each partition is recommended forming a variety of design schemes. Finally, the schemes are screened by combining the constraint of conditions, and the scheme is optimized by using the Galapagos genetic algorithm in Grasshopper [1] to generate the final scheme.
The Application of Computer Aided Translation in Practice——Taking the Chinese-English Translation of Tourism Texts in Hetao Region as an Example
Authors: Li Congsen , Zhang Hao 
Published: December 2020

Abstract
This article analyzes the characteristics of the Chinese-English translation of tourist texts in the Hetao region and computer-aided translation. The author combines the practical application strategies of computer-assisted translation, including the pre-translation, the translation matching work, and the post-translation inspection work to study the relevant content in the tourist text examples in the Hetao region. The purpose of this article is to improve the application value of computer-assisted translation and improve the accuracy of translation.
Application of Big Data Analysis in Flood Control of Small Reservoirs -A Case study of Liaoning Province, China
Authors: Chen Xi , Zhang Tong , Zheng Zeyu , Wang Tianran 
Published: December 2020

Abstract
Small reservoirs play an important role in the safety of flood control and economic development. Their operation and management are characterized by a large number of objects and a large amount of information, which requires effective data analysis means support. Based on this, big data analysis technology has been gradually applied and popularized in the operation and management of small reservoirs. In this paper, we first set up a small reservoir flood reporting system based on the data collection and analysis of various aspects such as reservoir capacity, characteristic water level, real-time data of water and rain situation, meteorological data, and presented the results in the paper. Secondly, we analyzed the under-reporting situation during the flood control period of the reservoir, and explored the under-reporting factors and the time when the under-reporting occurred. Finally, we conduct a time series analysis on the situation of water level exceeding the limit of 50 reservoirs during the flood control period, so that we can find the key reservoirs and important time points of flood control more intuitively and provide reference for the smooth development of the management of small reservoirs.
A New Component of Interactive Multi-task Network Model for Emotion-Cause Pair Extraction
Authors: Shan Jingzhe , Zhu Min 
Published: December 2020

Abstract
The task emotional-cause pair extraction (ECPE) is proposed based on the emotion cause extraction (ECE) task. The ECPE task proposes a new two-step frame method: first step is to extract emotion and cause information separately, then the second step is to match the emotional cause pair. Compared to the ECE task, this new research no longer relies on manual annotation of documents. However, the Inter-EC model component for the ECPE task does not fully consider the relevance of sentimental clause and causal clause, and the available context is limited. In this paper, we propose a new extraction component with self-attention for the Inter-EC model, optimizing the interactive multi-task network model. Our approach achieved a good recall score on the ECPE dataset, and the F1 value is slightly better than the baseline.
A summary of the research on the foundation and application of blockchain technology
Authors: Gai Rongli , Du Xiaoyan , Ma Shuya , Chen Na , Gao Shouchuan 
Published: December 2020

Abstract
Blockchain is an emerging distributed database technology. It has the characteristics of decentralization, non-tampering, traceability and final consistency. Blockchain can solve data management problems in untrusted environments. Based on the research and analysis of the blockchain system, this article expounds the application of the blockchain system in the distributed database environment. First, this article introduces the concept of the blockchain system and the classification of the blockchain system from multiple aspects. Then it introduces the data storage technology and data encryption technology adopted by the blockchain system in detail. Finally, the application prospects of the blockchain system in today’s society are introduced.
On-line Dense 3D Reconstruction Method based on ANN us-ing a Single Structured Light Pattern
Authors: Liu Jinbo , Sun Xiaoliang , Wu Jinshui 
Published: December 2020

Abstract
Dense 3D reconstruction techniques to measuring dynamic scenes and deformable objects with little texture have been widely studied for various applications like surface deformation measurement. We assume that the actual situation of scanning is acquiring sequential shape and measuring surface deformation online at the moment when an object deforms under the action of aerodynamic forces. This paper presents such a technique for on-line acquisition of 3D surface data based on a one-shot scanning method that reconstructs 3D shape from a single image where a simple color-coded pattern using de Bruijn sequence is projected onto an object. The proposed approach has advantages that it requires no assumption of global smoothness and continuous surface. To realize 3D reconstruction from a single image, there are sever-al issues to be solved, for example, difficulty on decoding structured light pattern because of influence of chromatic aberration in both projection systems and imaging systems, and difficul-ty on establishing accurate correspondences between projector and camera pixels. This paper describes the solutions of the issues by combining two methods, that is (1) an efficient and robust pattern decoding method based on artificial neural networks (ANN), and (2) a sub-pixel matching method using phase map and multiple view geometry. Furthermore, we adopt some effective strategies to improve algorithm robustness. Practical experiments were carried out to test the accuracy and efficiency of the scanning system in typical configuration. The results show that the scanning system can reconstruct 3D shape on-line in high-resolution with the accuracy of 0.09 mm and efficiency of 10 fps.
Constructing government procurement knowledge graph based on crawler data
Authors: Yaozu Yu , Jiangen Zhang 
Published: December 2020

Abstract
In the public information of government affairs, the public information of government procurement is more and more timely and complete, which makes it possible for the public to have a comprehensive understanding, in-depth analysis and intelligent use of government procurement information. This paper proposes a process for constructing government procurement knowledge graph: obtaining the bid-winning announcement information through web crawler technology, constructing the government procurement ontology by combining the professional knowledge of government procurement and professional standards and norms, and using Protégé, D2rq, Neo4j and other software to realize ontology instantiation, entity extraction, N-Triples storage. The establishment of knowledge graph for government procurement establishes a strong, convenient and efficient foundation for the public to inquire government procurement information, count government procurement content and analyze the relationship between government procurement.
Question Answering System Based on Knowledge Graph in Air Defense Field
Authors: Liuyang Yu , Guo Zhigang , Chen Gang , Zhang Xingxin , Tang Yongwang , Wei Han 
Published: December 2020

Abstract
With the development of artificial intelligence technology, question answering systems based on knowledge graphs (QAS-KGs) have become a prevalent information retrieval approach. However, current QAS-KGs which usually adopt general knowledge graphs have complex algorithms and high requirements for hardware. Moreover, in some specific fields, such as air defense field, the QAS-KGs usually cannot respond accurately and they can only handle questions composed of one language. In this paper, we introduce an efficient QAS-KG approach which can handle questions composed of Chinese, English, or both languages. First, we construct the knowledge graph in air defense field according to the domain characteristics and user needs. Then we design and implement a question answering system based on the knowledge graph. Finally, we test the system on the self-built data set. The results show that the system can understand the user’s intention quickly and make accurate responses without high requirements for hardware.
Research on Cross-network Exchange Method of Enterprise Application Business Process Data
Authors: Feng Xu , Sicheng Tao , Gongliang Li , Yang Xie , Yizheng Tao 
Published: December 2020

Abstract
To solve the problem of efficient, safe and controllable transfer of enterprise-level application systems’ data across network, this paper proposes a data exchange method for application systems across physically isolated networks. Firstly, the analysis of the cross-network data exchange business model and the design of the business scenario were carried out, and two typical cross-network data exchange business models were condensed. Then, the design of the overall scheme and the detailed technical scheme of cross-network data exchange based on the one-way import device was carried out. Finally, the cross-network ferry middleware system was developed, and the experimental environment of the cross-network data exchange system based on the one-way import device was built, the personnel organization and the leave process information ferry across physically isolated networks were achieved, and the feasibility of cross-network data exchange scheme was verified.
Captcha Recognition using convolutional neural networks with low structural complexity
Authors: Yang Haolin 
Published: December 2020

Abstract
CAPTCHAs are automated tests designed to distinguish between humans and computers. They could be easily solved by humans, but they become challenging for machines to solve, therefore preventing programs from abusing online services and occupying internet resources. Using Convolutional Neural Networks, the CAPTCHA tests could be solved automatically at high efficiency. Current approaches of high accuracy CAPTCHA recognition can be structurally complicated. As a result, our team explored a different approach to solve CAPTCHAs using a Convolutional Neural Network that is more efficient in terms of structural complexity and run time, with image processing being a possibility to enhance the accuracy. We also tested our networks on CAPTCHA datasets with character adhesion and background noise.
An Improved Full-text Retrieval for Elementary Education Resource Database System
Authors: Liu Cong , Huai Huai 
Published: December 2020

Abstract
With the rapid development of Internet and information technology, ways of teaching and learning in China’s elementary education have begun to change. In the face of massive resources, how to optimize the searching results and improve users’ satisfaction through the search services, has now become a major priority. Based on the in-depth study of full-text retrieval technology, combined with the actual searching needs of the elementary education resources, this paper focuses on Chinese word segmentation technology, and proposes a user-defined professional dictionary based on cell lexicon. Experiments show that using this professional dictionary to segment words improves the professionalism of word segmentation results and the accuracy of search results. Meanwhile, an improved full-text retrieval for elementary education resource database system based on Lucene is designed and implemented, including resource collection, text pre-processing, content indexing and resource retrieval. This system is successfully integrated and applied to the massive knowledge base platform for elementary education, which meets the needs of full-text retrieval of textbooks and supplementary content, and makes a good effect.
Optimization Strategy of Anti-interference Performance Based on BPSO
Authors: Baohua Wei , Shuyi Fan , Cheng Wan , Qiang Wang 
Published: December 2020

Abstract
In order to solve a problem of the anti-interference performance optimization strategy for electronic equipment, an optimization strategy based on BPSO is proposed and studied. A systematic analysis to the anti-interference performance optimization strategy for electronic equipment is made, and then the mathematical description of the optimization strategy are built. The general method and process of the solution based on BPSO to anti-interference performance optimization strategy is presented. What’s more, the method is tested and verified by a specific example. The results show that the way based on BPSO to search anti-interference performance optimization strategy is feasible. Furthermore, not only do the algorithms have good global search performance and robustness, but also the optimization efficiency and performance have advantages.
Classification Model based on Choquet Integral Discriminant
Authors: Qiao Yaqin , Dai Xuezhen , Chang Zaibin 
Published: December 2020

Abstract
At present, the classification method based on nonlinear integral has been widely used. In this paper, Choquet integral value is used as a nonlinear integral discriminant, and a new discriminant classification model is proposed. The classification model maps the data sets which cannot be linearly separable in low dimensional space into high-dimensional space by nonlinear integral discriminant, and then classifies them by Choquet integral. Because there are too many parameters of classification model in the process of classification, particle swarm optimization is used to optimize the parameters, and then combined with the idea of support vector machine to classify the model. Finally, through the MATLAB programming experiment, the classification model proposed in this paper is compared with the SVM classification model, and the experimental results show the feasibility and effectiveness of the model.
Research on the Big Data Intelligent Application
Authors: Yan Zhong , Wensi Guo , Yanling Zhong , Maosheng Sun , Jiasong Shi 
Published: December 2020

Abstract
In order to improve the big data intelligent application ability based on network information system, the big data intelligent application mode with advanced system, unified standard and efficient service is constructed from different dimensions and levels, and the direction for the overall technology and system development of the big data intelligence application is pointed out.
Research on Overfitting Problem and Correction in Machine Learning
Authors: Bu Chao , Zhang Zengping 
Published: December 2020

Abstract
Machine learning is the key technology of artificial intelligence, which uses learning and training data model to find the problem to achieve the law. In practical applications, there is always a difference between the input data of the model and the training data. Based on the biased training data, overfitting will occur, which will cause the machine learning to fail to achieve the expected goals. Generalization is the process of ensuring that the model can fully reflect the characteristics of the actual input data. Therefore, the ability of the machine learning model depends to a large extent on the effectiveness of generalization. In order to fully understand the learning and generalization model, we conducted a study by the polynomial curve fitting. First, based on the training data, we analyzed using matrix theory and analytical solutions derived polynomial fit. Then, numerical and maximum likelihood theoretical analysis was carried out for the overfitting problem. Finally, combined with the objective function, a typical regularization method to overcome overfitting and improve generalization ability is elaborated.
A Real-time Trademark Detection Method
Authors: Leng Yang , Fan Qixiong 
Published: December 2020

Abstract
In natural scenes, it is an important and challenging task to improve the accuracy while maintaining the real-time capability of trademark detection. For the needs of real-time trademark detection in natural scenes, a method called LOGO-YOLOv3 based on improved YOLOv3 is proposed in this paper. Channel attention and spatial attention mechanisms are introduced into the Darknet53 feature extraction network. And an additional layer is added to the detection layer, which will be combined with the original three detection layers of YOLOv3 to construct a feature pyramid networks containing four detection layers with different scales. This method can not only greatly reduce the false detection of trademarks in complex scenes, but also deal with the problem of large differences in the size of different types of trademarks. Experiments on the Flickrlogos-32 dataset show that the proposed method outperform the original YOLOv3 in general.
Application of LightGBM and LSTM combined model in vegetable sales forecast
Authors: He Zhang , Yu Sun 
Published: December 2020

Abstract
In view of the nonlinear and linear influence of vegetables in sales forecasting, the previous single model could not fully explore the variation law of vegetables in sales, a combined model based on LightGBM and LSTM is proposed, and the significant and abstract characteristics affecting sales forecasting are explored respectively by combining the advantages of the two models. First, the LightGBM model and the LSTM model based on intensive learning are modeled and analyzed, and then the two models are weighted array by the error reciprocal method for sales forecasting. The experimental results show that the proposed combination model based on LightGBM and LSTM is more accurate than the single model, and the prediction results of the model for vegetable short-term sales have provided important reference value for the strategic marketing of enterprises.