bluuebunny/crossref_metadata_2025_split huggingface dataset:
From thin to thick domain walls: An example of the φ
8 model
Authors: Blinov Petr A , Gani Vakhid A , Marjaneh Aliakbar Moradi 
Published: December 2020

Abstract
We demonstrate that for some certain values of parameters of the (1 + 1)-dimensional φ
8 model, the kink solutions can be found from polynomial equations. For some selected values of the parameters we give the explicit formulas for the kinks in all topological sectors of the model. Based on the obtained algebraic equations, we show that in a special limiting case, kinks with power-law asymptotics arise in the model, describing, in particular, thick domain walls. Objects of this kind could be of interest for modern cosmology.
QCD corrections for double charmonia production in e+e− annihilation
Authors: Berezhnoy A V , Belov I N , Onishchenko A I 
Published: December 2020

Abstract
We discuss J/ψ ηc
production in e
+
e
− annihilation at next-to-leading order of pQCD. We are focusing at virtual Z
0 contribution into this process: the interference between virtual photon and Z
0-boson is required for careful study. Cross-sections behavior at high energies is studied. At energies ~ M
Z0 the NLO contribution enhances cross-sections up to 2 times.
Identical pion and kaon femtoscopy in EPOS 3 with and without the hadronic afterburner UrQMD
Authors: Batyunya B , Malinina L , Mikhaylov K , Rogochaya E , Romanenko G , Werner K 
Published: December 2020

Abstract
Femtoscopy is an effective instrument to study the size and dynamics of the system created in heavy-ion collisions. In particular, a decreasing dependence of system size on increasing pair momentum and particle mass could be interpreted as an evidence of the strong collective flow. Such phenomena are naturally modeled by hydrodynamics. The large data sample collected in Pb–Pb collisions at

s

NN

=
2.76

TeV

by the ALICE collaboration enables femtoscopic measurements for pions and kaons. In this paper, the ALICE data are compared with calculations within the EPOS 3 hadronic interaction model, which is based on a (3+1)D viscous hydrodynamical evolution and employs the UrQMD cascade to describe the hadronic phase. The femtoscopic radii for pions and kaons are considered as a function of pair transverse momentum/mass and collision centrality. The obtained results show the importance of the hadronic rescattering phase at LHC energies.
Special dyon-like black hole solution in the model with two Abelian gauge fields and two scalar fields
Authors: Belissarova F B , Boshkayev K A , Ivashchuk V D , Malybayev A N 
Published: December 2020

Abstract
Dilatonic black hole dyon-like solution in the gravitational 4d model with two scalar fields and two 2-forms, governed by two 2-dimensional dilatonic coupling vectors

λ
→

i

obeying

λ
→

i

(

λ
→

1

+

λ
→

2

)
>
0

, i = 1, 2, is found. Some physical parameters of the solutions are obtained: gravitational mass, scalar charge, Hawking temperature, black hole area entropy and parametrized post-Newtonian (PPN) parameters β and γ. The PPN parameters do not depend on the coupling vectors

λ
→

i

. A bound on the gravitational mass is proved.
Scientific Data Lake for High Luminosity LHC project and other data-intensive particle and astro-particle physics experiments
Authors: Alekseev A , Kiryanov A , Klimentov A , Korchuganova T , Mitsyn V , Oleynik D , Smirnov A , Smirnov S , Zarochentsev A 
Published: December 2020

Abstract
The next phase of LHC Operations – High Luminosity LHC (HL-LHC), which is aimed at ten-fold increase in the luminosity of proton-proton collisions at the energy of 14 TeV, is expected to start operation in 2027-2028 and will deliver an unprecedented scientific data volume of multi-exabyte scale. This amount of data has to be stored and the corresponding storage system should ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data processing model will not be able to provide the required infrastructure growth even taking into account the expected hardware technology evolution. To address this challenge the new state-of-the-art computing infrastructure technologies are now being developed and are presented here. The possibilities of application of the HL-LHC distributed data handling technique for other particle and astro-particle physics experiments dealing with large-scale data volumes like DUNE, LSST, Belle-II, JUNO, SKAO etc. are also discussed.
Atomic effects in reactor antineutrino spectra calculation
Authors: Lomonosov A , Titov O 
Published: December 2020

Abstract
To predict and interpret the results of reactor antineutrino experiments, precise theoretical knowledge of the antineutrino spectrum is needed. Reactor antineutrinos are produced in beta-decay of fission products, so, in general, any correction to individual beta-spectra will show up in the resulting antineutrino spectrum. We discuss the influence of atomic effects on reactor antineutrino spectra. We note that these effects may be particularly important for the conversion method, which is based on the transformation of experimental electron spectra.
Based on J2EE Research and Realization of National Fitness Sports Convenience Service Platform
Authors: Fang Wu 
Published: December 2020

Abstract
The concept of the national fitness convenient service platform for further study, combined with the current needs, design the convenient universal mobile end the development environment and development tools, at the same time, this paper expounds how to set up the national fitness convenient service platform of mobile terminal development environment, function classification of fitness service platform, each module development mode, the overall framework design.
Application and Analysis of Modern Information Technology in Fine Management of Hospital Medical Insurance
Authors: xunqi Quan , Fangli Dai 
Published: December 2020

Abstract
with the continuous development of science and technology and the arrival of the information age, modern information technology is more and more widely used in the fine management of hospital medical insurance. The importance of hospital medical insurance fine management can solve the problems and shortcomings of traditional human management hospital medical insurance and realize the fine management of medical insurance control fee. Therefore, it is necessary to pay more attention to the application of modern information technology in the fine management of hospital medical insurance, clarify the problems and shortcomings in the current application of information technology, and take targeted measures to solve them. Give full play to the role and value of modern information technology carrier, promote the sustainable and stable development of hospitals. Modern information technology has been continuously applied, which plays a key role that can not be ignored and greatly improves the overall quality of hospital medical insurance. This paper objectively analyzes the importance and effective way of applying modern information technology in the fine management of hospital medical insurance from different angles.
Impulse Noise Suppression based Iterative Hybrid Nonlinear in Power Line Communication
Authors: Teng Deyang , Zheng Yanxi , Zhang Kai , Zhao Shilin , Zhang Hairong 
Published: December 2020

Abstract
In power line orthogonal frequency division multiplexing (OFDM) communication systems, the presence of impulse noise can seriously affect system performance. One of the conventional solutions is to perform a mixed nonlinear processing on the time domain signal at the receiving end before performing subsequent OFDM demodulation. Therefore, this thesis studies an improved method based on iterative elimination of nonlinear distortion. Firstly, the received OFDM signal is subjected to hybrid nonlinear processing in the time domain. Secondly, the nonlinear distortion introduced by the time domain nonlinear processing is reconstructed by the symbols initially detected in the frequency domain, and the reconstruction accuracy is improved by iteration. Finally, the reconstructed nonlinear distortion is subtracted from the output of the hybrid nonlinear processing unit. The simulation results show that compared with the traditional hybrid nonlinear method, the performance of the proposed algorithm is much better than that of the traditional algorithm.
Research on coal mine safety monitoring data storage based on HBase
Authors: Jiang Lizheng , Li Yanbin 
Published: December 2020

Abstract
In order to solve the problem of low storage efficiency and slow query speed when massive coal mine safety monitoring data is stored in relational database, a method of storage and retrieval based on HBase was designed. By combining the hash value of the combination of coal mine code, substation code and transducer code as well as the timestamp after inversion, the hot spot and data skew caused by the unreasonable design of rowkey in HBase were avoided. In order to improve the efficiency of data storage, the swing door trending (SDT) algorithm was used to compress the monitoring data, and in order to improve the efficiency of data retrieval, a secondary index based on ElasticSearch was constructed. The experimental results on the real coal mine data show that the efficiency of data storage and retrieval has been significantly improved.
Research on information system risk Assessment Based on Improved AHP-Fuzzy theory
Authors: Peisheng Liu , Yunping Han , Xiaole Zhu , Shunshun Wang , Zhenglin Li 
Published: December 2020

Abstract
Aiming at the problem of security of information systems, a security risk assessment model based on improved AHP-fuzzy theory is proposed. First, the evaluation index system is constructed by using the Delphi method. Second, the improved AHP method is used to calculate the weight of the index system. On this basis, the multilevel fuzzy comprehensive evaluation model is constructed for risk assessment. Finally, taking an OA system in a university as an example, the empirical analysis is carried out. The result shows that the method proposed in this paper is accurate, effective and time-saving. The study will provide a new method for a risk assessment of information systems.
A Safety Quota-variable Mail Transfer Protocol under Isolated Environment
Authors: Zhang Jiangli 
Published: December 2020

Abstract
The information security problems of e-mail have become a major threat of the network information security in recent years. In this paper, we did deeply analyze on the principles and safety of the protocols of e-mail system, such as SMTP and ESMTP. An improved protocol based on SMTP and ESMTP was proposed, and protocol mode was designed as well. The protocol was denominated as Safety quota-variable Mail Transfer Protocol (SVMTP) under isolated environment. The results show that svmtp protocol has more obvious effect in blocking suspicious connections, security classification and minimizing the waste of communication resources.
A Privacy Preserving Network Coding Signature Scheme Based on Lattice
Authors: Wu Bin , Wang Caifen 
Published: December 2020

Abstract
Network coding is a desirable method to optimize network throughput and improve routing reliability, and is widely used in distributed Internet of Things systems. However, the packet mixing characteristic of network coding makes the transmission vulnerable to pollution attacks, which may hinder the reconstruction of the original data. Moreover, network coding has the potential to resist privacy threats such as eavesdropping attacks since intermediate nodes encourage coding / mixing operations, however, once adversary collects enough packets, simple network coding deployment can not achieve this purpose. In this paper we first present a privacy-preserving network coding signature scheme using lattice theory, which can be viewed as a promising tool for designing post-quantum cryptographic protocols. We blind the global coefficient matrix by encrypting the original encoding vector so as to resist eavesdropping attack, while preventing both intra/inter-generation pollution attacks by simultaneously signing the data packet and the generation identifier. We showed that our scheme is correct, and also proved that our scheme is secure against both eavesdropping and pollution attacks under the security of pseudo-random function and the small integer solution (SIS) assumption in standard lattices.
An improved feature matching ORB-SLAM algorithm
Authors: Li Qiang , Kang Jia , Wang Yangxi , Cao Xiaofang 
Published: December 2020

Abstract
To solve the problems of low accuracy and poor real-time performance in traditional mobile robot vision simultaneous positioning and map construction (SLAM), the original algorithm was improved. First, the ORB features of adjacent images are extracted, and the PROSAC algorithm is used to achieve feature point matching. At the same time, the PROSAC algorithm is improved and optimized, and the execution time of the optimized PROSAC algorithm is significantly reduced; finally, based on the graph optimization model, a global Bundle Adjustment algorithm based on the largest common-view weight frame is proposed to achieve dense and sparse map creation. The algorithm is verified by Tum data set, and the experiment shows that the root mean square error has dropped significantly. The results on the data set effectively prove the effectiveness of the algorithm in this paper.
Application of artificial intelligence based on machine learning
Authors: Chen Xue , Xu Shiyuan , Cao Yibo , He Jiahuan , Jiao Yang 
Published: December 2020

Abstract
In recent years, China’s science and technology is developing rapidly, and has made a lot of achievements in the field of high-tech, which greatly promotes the improvement of China’s national economy and the improvement of people’s daily life quality. Computer information technology is one of the most important modules in the development of science and technology. The traditional computer information technology has effectively improved the efficiency of people’s production and life, and played a good bridge role in the communication between people. However, in view of the current development of electronic information technology, the traditional computer information technology has been unable to meet the growing needs of people’s computing. Artificial intelligence based on machine learning has gradually stepped into people’s vision and attracted more and more attention. In this paper, the application of artificial intelligence based on machine learning will be discussed and studied in detail from multiple perspectives, so as to better apply artificial intelligence in future life.
Adaptive threshold modeling algorithm for monitoring indicators of power network server based on Chebyshev inequality
Authors: Hu Benran , Li Yanjun , Ren Jiyuan , Li Yiqun 
Published: December 2020

Abstract
The business system server under the IT automation operation and maintenance platform generates massive data samples, based on which the threshold can be set to realize the allocation and management of hardware resources. The traditional threshold selection method is to determine an appropriate threshold based on human experience. If the threshold is too high, it will not play its due role. But if the threshold is too low, it will frequently produce false positives. To solve this problem, an adaptive threshold method based on Chebyshev inequality theory combined with kernel density estimation is proposed to determine monitoring indexes, and a new dynamic implicit threshold model is established to analyse the data generated by the business system server for real-time monitoring and alarm processing. Through the experimental study on the CPU utilization data of the power grid server, lower missing and false positive rate are obtained, which verifies the feasibility and effectiveness of the proposed method.
Research on 6G mobile communication system
Authors: Xu Guangbin 
Published: December 2020

Abstract
6G will have super flexibility in the utilization of time, frequency and space resources. The time slot can be compressed to use the high frequency band more effectively and meet the demand of delay sensitive service. Terahertz frequency band is used to make up for the current shortage of spectrum resources. The 6G system will adopt the technical architecture of multi frequency close integration and no cellular cell communication network in air, sky and ground areas. 6G system will realize the integration of network and intelligence, communication and sensor, and adopt novel discontinuous communication technology, wireless power transmission and energy harvesting technology, so as to access all people, information and goods with ultra real experience, and completely eliminate the restrictions of working place and time.
Research on the Influence of Online-shopping Additional Reviews on Product Sales of Search Commodity and Experience Commodity
Authors: Zhang Xintong , Zhang Chong , Wang Jingyi 
Published: December 2020

Abstract
This paper explored the impact of online-shopping additional reviews on sales of search and experience commodity from five perspectives: proportion, length, emotional attitude tendency and time interval. The result shows that the proportion, length, and the emotional attitude tendency of the online-shopping additional reviews have a positive impact on both sales of search commodity and experience commodity. What is more, the number, length and the emotional attitude tendency of online-shopping additional reviews have a larger impact on the sales of experience commodity.
Research on the Innovation of Multimedia Technology and Visual Communication Technology
Authors: Jiang Bian , Qing He 
Published: December 2020

Abstract
Visual communication technology is widely used in the field of design. With the continuous advancement of science and technology, multimedia technology in China has also made great progress. The application of multimedia technology to visual communication technology is of great significance. Only by combining the two ingeniously and actively can it ensure the long-term development of visual communication technology and vitality. Based on this, this article will briefly describe the concept of multimedia technology and visual communication, analyze the impact of multimedia on visual communication technology, and propose innovative strategies for multimedia and visual communication technology for reference.
A Hybrid Deep Learning and Handcrafted Features based Approach for Thyroid Nodule Classification in Ultrasound Images
Authors: Xie Jiahao , Guo Lehang , Zhao Chongke , Li Xiaolong , Luo Ye , Jianwei Lu 
Published: December 2020

Abstract
With the increasing incidence rate of thyroid cancer, the diagnosis of thyroid nodules has become an important task. In this paper, we designed a deep neural network (DNN) to classify whether a thyroid nodule is benign or malignant, and proposed a structure which combines local binary pattern (LBP) with deep learning. Our method mitigates the effects of overfitting in medical image diagnosis tasks. With well-designed transfer leaning, we achieve an accuracy of 85% on our own ultrasound thyroid dataset. To ensure the reliability of our experiments, all examples are estimated by experts in Shanghai Tenth People’s Hospital using fine needle analysis (FNA), which is a gold standard for thyroid nodules diagnosis. The experimental results show that combinations of the traditional medial image features can help the deep learning network get more semantic information from low-level inputs.
Deep Residual Fusion Network for Single Image Super-Resolution
Authors: Wang Jia , Lan Chuwen , Gao Zehua 
Published: December 2020

Abstract
Convolutional neural networks have been applied in the field of single-image super-resolution (SISR) and have achieved a series of outstanding results. However, most of the SISR research still attempt to pursue wider and deeper network structure, without paying enough attention to the correlations between different features. In order to solve these problems, deep residual fusion network (DRFN) is proposed for more powerful feature expression and feature learning. Specifically, we propose a feature fusion group (FFG) structure, which can effectively use the relevant features extracted from the residual attention group (RAG) and fuse them to be more discriminative. Residual attention group (RAG) includes channel attention module (CAM) and spatial attention module (SAM), which uses attention mechanism to refine features. DRFN also makes full use of nested residual connections, skipping redundant low-frequency information to enhance circulation, thereby focusing the calculation on more important high-frequency components. Extensive experimental results have proved the effectiveness of our model. And our model finally achieves excellent performance in terms of both quantitative metrics and visual quality.
Design and Implementation of virtual simulation experiment platform for computer specialized courses
Authors: Song Guanghui , Nie Yan , Chen Genlang , Tong Youcheng 
Published: December 2020

Abstract
For the practical teaching of computer specialized courses in colleges and universities, this study proposes the construction method of virtual simulation experiment platform based on OpenStack, Docker, Seafile and Raspberry Pi, and on this basis, deeply discuss the design and implementation details of the course experiment. The construction and application of virtual simulation experiment platform change the traditional teaching method fundamentally, reduce the cost of laboratory construction and management, which have important reference value to realize the remote experiment teaching. The virtual simulation experiment platform is composed of four parts: virtual machine, application container, cloud storage and client, which can meet the daily teaching needs, cultivate students’ interest in learning, and improve their innovation ability.
Nonuniformity Correction Design and Implementation for Infrared Image Based on FPGA and Artificial Neural Networks
Authors: JunLu YuYang 
Published: December 2020

Abstract
Infrared imaging technology is widely used in military and civilian applications. However, due to the materials and manufacturing technology, the response of each unit in the infrared detector is not completely consistent, which leads to the nonuniformity of the infrared focal plane array. In this article, we propose a way to use artificial neural network by self-adaptively updating the correction coefficients based on FPGA. Compared with traditional calibration-based method, our method is more flexible and can avoid the effects of temperature drift efficiently.
CNN-Based Speaker Verification and Speech Recognition in Tibetan
Authors: Gan Zhenye , Yu Yue , Wang Rui , Zhao Xin 
Published: December 2020

Abstract
In recent years, there have a little studies on speaker and speech recognition in Tibetan, which are mainly based on traditional methods of probability statistics. With the development of deep learning, neural networks have been widely used in speaker and automatic speech recognition, which have achieved remarkable results. In this paper, we utilize end-to-end model to study speaker verification and speech recognition in Tibetan. This article uses the ResCNN network for Tibetan speaker verification. In speech recognition, we adopt the DFCNN-CTC structure, where connectionist temporal classification (CTC) directly outputs the probability of sequence prediction without external post-processing. We have made some improvements to the two models. Experiments show that the improved model reduces EER by 3% and WER by 18% in speaker verification and speech recognition, respectively.