bluuebunny/crossref_metadata_2025 huggingface dataset:
Time‐modulated sparse linear array synthesis with minimum elements and a specific sidelobe
Authors: Ma Yue , Miao Chen , Li Yue‐Hua , Wu Wen
Published: September 2020

In this study, a novel method is proposed to obtain the minimum elements and a specific sidelobe in time‐modulated sparse linear arrays. A genetic algorithm is used to optimise each generation of arrays to reach the required level and range of the sidelobe. Furthermore, the number, arrangement, and switching sequences of the array that satisfy the requirements are obtained. This method provides a scheme to reduce the number of elements using the optimised sparse structure and switching time. However, besides the control of the fundamental component, this method can also be applied to multi‐beam forming with the fundamental component and ±first harmonic. Finally, the effectiveness of the proposed method is verified by the simulation and numerical results.
Variations in shape among observed Lyman-α spectra due to intergalactic absorption
Authors: Byrohl C. , Gronke M.
Published: September 2020

Lyman-α (Lyα) spectra provide insights into the small-scale structure and kinematics of neutral hydrogen (HI) within galaxies as well as the ionization state of the intergalactic medium (IGM). The former defines the intrinsic spectrum of a galaxy, which, in turn, is modified by the latter. These two effects are degenerate. Using the IllustrisTNG100 simulation, we studied the impact of the IGM on Lyα spectral shapes between z ∼ 0 and 5. We computed the distribution of the expected Lyα peaks and of the peak asymmetry for different intrinsic spectra, redshifts, and large-scale environments. We find that the averaged transmission curves that are commonly applied give a misleading perception of the observed spectral properties. We show that the distributions of peak counts and asymmetry can lift the degeneracy between the intrinsic spectrum and IGM absorption. For example, we expect a significant number of triple-peaked Lyα spectra (up to 30% at z ∼ 3) if the galaxies’ HI distribution become more porous at higher redshift, as predicted by cosmological simulations. We provide a public catalog of transmission curves for simulations and observations to allow for a more realistic IGM treatment in future studies.
Radiography in high mass X-ray binaries
Authors: El Mellah I. , Grinberg V. , Sundqvist J. O. , Driessen F. A. , Leutenegger M. A.
Published: September 2020

Context.In high mass X-ray binaries, an accreting compact object orbits a high mass star, which loses mass through a dense and inhomogeneous wind.

Aims.Using the compact object as an X-ray backlight, the time variability of the absorbing column density in the wind can be exploited in order to shed light on the micro-structure of the wind and obtain unbiased stellar mass-loss rates for high mass stars.

Methods.We developed a simplified representation of the stellar wind where all the matter is gathered in spherical “clumps” that are radially advected away from the star. This model enables us to explore the connections between the stochastic properties of the wind and the variability of the column density for a comprehensive set of parameters related to the orbit and to the wind micro-structure, such as the size of the clumps and their individual mass. In particular, we focus on the evolution with the orbital phase of the standard deviation of the column density and of the characteristic duration of enhanced absorption episodes. Using the porosity length, we derive analytical predictions and compare them to the standard deviations and coherence time scales that were obtained.

Results.We identified the favorable systems and orbital phases to determine the wind micro-structure. The coherence time scale of the column density is shown to be the self-crossing time of a single clump in front of the compact object. We thus provide a procedure to get accurate measurements of the size and of the mass of the clumps, purely based on the observable time variability of the column density.

Conclusions.The coherence time scale grants direct access to the size of the clumps, while their mass can be deduced separately from the amplitude of the variability. We further show how monitoring the variability at superior conjunctions can probe the onset of the clump-forming region above the stellar photosphere. If the high column density variations in some high mass X-ray binaries are due to unaccreted clumps which are passing by the line-of-sight, this would require high mass clumps to reproduce the observed peak-to-peak amplitude and coherence time scales. These clump properties are marginally compatible with the ones derived from radiative-hydrodynamics simulations. Alternatively, the following components could contribute to the variability of the column density: larger orbital scale structures produced by a mechanism that has yet to be identified or a dense environment in the immediate vicinity of the accretor, such as an accretion disk, an outflow, or a spherical shell surrounding the magnetosphere of the accreting neutron star.
Mixed methods for degenerate elliptic problems and application to fractional Laplacian
Authors: Cejas María E. , Durán Ricardo G. , Prieto Mariana I.
Published: September 2020

We analyze the approximation by mixed finite element methods of solutions of equations of the form −div (a∇u) = g, where the coefficient a = a(x) can degenerate going to zero or infinity. First, we extend the classic error analysis to this case provided that the coefficient a belongs to the Muckenhoupt class A2. The analysis developed applies to general mixed finite element spaces satisfying the standard commutative diagram property, whenever some stability and interpolation error estimates are valid in weighted norms. Next, we consider in detail the case of Raviart–Thomas spaces of arbitrary order, obtaining optimal order error estimates for simplicial elements in any dimension and for convex quadrilateral elements in the two dimensional case, in both cases under a regularity assumption on the family of meshes. For the lowest order case we show that the regularity assumption can be removed and prove anisotropic error estimates which are of interest in problems with boundary layers. Finally we apply the results to a problem arising in the solution of the fractional Laplace equation.
Bounding CPT and Lorentz symmetry violations through ultra-high-energy cosmic rays
Authors: Escobar C A , Potting R
Published: September 2020

We review recent work on CPT and Lorentz violation in the context of the Standard-Model Extension. In particular, we show that, when CPT and Lorentz violation is present in the kinetic terms of any particle in the gauge boson or the lepton sector, this will generally lead to proton decay at sufficiently high energy. Using observational data from ultra-high energy cosmic rays, this has allowed to derive new bounds on the corresponding CPT and Lorentz-violation parameters.
Three Higgs doublet model with horizontal S
3 symmetry
Authors: Alvarez-Cruz A , Gómez-Bock M , Mondragón M , Pérez-Martínez A
Published: September 2020

We present a brief overview of a three-Higgs-doublet Model CP-invariant with S
3-symmetry as a flavor symmetry. This model contains three Higgs SU(2) doublets as well as three right handed neutrinos, besides the usual Standard Model particles. We discuss some features of the Yukawa, Higgs and neutrino sectors of this model, and present some new results on the trilinear couplings of the Higgs sector, plus a fit of all parameters in the neutrino one.
S
4 modular symmetry, seesaw mechanism and lepton masses and mixing
Authors: Novichkov P P , Penedo J T
Published: September 2020

We report on two works which exploit the approach to charged lepton and neutrino masses, neutrino mixing and leptonic CP violation based on the modular S
4 symmetry. The light neutrino masses are assumed to be generated via the type I seesaw mechanism. Realistic models without flavons and compatible with the data are constructed and the predicted correlations between neutrino mixing observables are studied.
Sterile neutrinos as a source of CP violation
Authors: Palazzo A
Published: September 2020

Several anomalous results have been reported at short-baseline neutrino oscillation experiments, which cannot be accommodated in the standard 3-flavor framework. The most popular interpretation of these anomalies entails new light sterile neutrinos (with mass in the eV range) which mix with the three ordinary “active” species. We show that the presence of sterile neutrinos induces new CP violating phenomena and how the the planned LBL experiments will be able to probe them.
Master Majorana neutrino mass parametrization
Authors: Cordero-Carrión I , Hirsch M , Vicente A
Published: September 2020

After showing that the neutrino mass matrix in all Majorana models can be described by a general master formula, we will present a master parametrization for the Yukawa matrices, also valid for all Majorana models, that automatically ensures agreement with neutrino oscillation data. The application of the master parametrization will be illustrated in an example model.
Towards machine learning in the classification of Z
2 × Z
2 orbifold compactifications
Authors: Faraggi A E , Harries G , Percival B , Rizos J
Published: September 2020

Systematic classification of Z
2 × Z
2 orbifold compactifications of the heterotic-string was pursued by using its free fermion formulation. The method entails random generation of string vacua and analysis of their entire spectra, and led to discovery of spinor-vector duality and three generation exophobic string vacua. The classification was performed for string vacua with unbroken SO(10) GUT symmetry, and progressively extended to models in which the SO(10) symmetry is broken to the SO(6) × SO(4), SU(5) × U(1), SU(3) × SU(2) × U(1)2 and SU(3) × U(1) × SU(2)2 subgroups. Obtaining sizeable numbers of phenomenologically viable vacua in the last two cases requires identification of fertility conditions. Adaptation of machine learning tools to identify the fertility conditions will be useful when the frequency of viable models becomes exceedingly small in the total space of vacua.
Probing modified dispersion relations in vacuum with high-energy γ-ray sources: review and prospects
Authors: Bolmont J , Perennes C
Published: September 2020

A possible violation of Lorentz Invariance (LIV) in the form of Modified Dispersion Relations (MDR) for photons in vacuum appeared in the late 90s as a possible outcome of some models developed with the goal to provide a full theory of Quantum Gravity (QG). Since then, several ways to probe quantum spacetime from high-energy gamma-ray observations of distant sources have been followed and provide stringent limits on the characteristic energy scale of these QG-related phenomena.

In this paper, the use of astrophysical sources for constraining MDR will be described. In particular, strengths and weaknesses of each category of sources as well as temporal effects due to emission mechanisms will be discussed. The latest results obtained from observations of Gamma-Ray Bursts, flaring Active Galactic Nuclei and pulsars will be briefly reviewed. Then, efforts on-going to get more robust constraints on MDR and LIV will be discussed and put in context with the beginning of the Cherenkov Telescope Array operations in the next few years.
Ultra High Energy Cosmic Rays and the Highest Energies Universe
Authors: Aloisio R
Published: September 2020

We will discuss the main relevant aspects of the physics of ultra high energy cosmic rays. After a short recap of the experimental evidences, we will review theoretical models aiming at describing the sources of these extremely energetic particles opening a window on the highest energies universe. We will discuss the production of secondary particles and the possible tests of new physics that ultra high energy cosmic rays could provide. The present proceedings paper is mainly based on review papers written by the author in the last two years.
Pushing the Energy and Cosmic Frontiers with High-Energy Astrophysical Neutrinos1
Authors: Bustamante M
Published: September 2020

The astrophysical neutrinos recently discovered by the IceCube neutrino telescope have the highest detected neutrino energies — from TeV to PeV — and travel the longest distances — up to a few Gpc, the size of the observable Universe. These features make them naturally attractive probes of fundamental particle-physics properties, possibly tiny in size, at energy scales unreachable by any other means. The decades before the IceCube discovery saw many proposals of particle-physics studies in this direction. Today, those proposals have become a reality, in spite of prevalent astrophysical unknowns. We showcase examples of studying fundamental neutrino physics at these scales, including some of the most stringent tests of physics beyond the Standard Model.
The dispersion method and dimensional regularization applied to the decay

H→Zγ
Authors: Boradjiev I , Christova E , Eberl H
Published: September 2020

We have calculated the W-loop contribution to the amplitude of the decay

H
→
Z
γ

in the unitary gauge through the dispersion method and in the

R
ξ

gauge using dimensional regularization (DimReg). We show that the results of the calculations with DimReg and the dispersion method, adopting the boundary condition at the limit

M
W

→
0

defined by the Goldstone boson equivalence theorem (GBET), completely coincide. This implies that the dispersion method obeying the GBET is compatible with DimReg. The advantage of the applied dispersion method is that we work with finite quantities and no regularization is required.
The CP-symmetries of the 2HDM
Authors: Grzadkowski B , Ogreid O M , Osland P
Published: September 2020

We discuss the three different classes of CP-symmetries that can be realized in a two-Higgs-doublet model, CP1, CP2 and CP3. We express conditions for realizing these symmetries in terms of masses and couplings of the model, thereby providing a way of verifying which, if any, of these symmetries is realized by nature.
Research on application of an improved deep convolutional neural network in handwritten character recognition
Authors: Wu Lan , Jia Xueying , Zhu Canshi
Published: September 2020

The classical convolutional neural network has been widely used for handwritten digit character recognition with high accuracy. However, due to its small convolutional layer, fixed size of convolution kernel and few extracted features, the recognition accuracy of complex handwritten characters are reduced. In this paper, an improved deep convolutional neural network model is proposed, which can allocate different convolution kernels according to the different information amount in the handwritten character image area for convolution, so as to better extract the effective information of the image and is more suitable for complex handwritten character recognition applications. Experiments show that the recognition rate can be higher.
Research on the influencing factors of Chinese medicine cultural identity of international students in Chinese medicine schools
Authors: Chen Yang , Guan Cuiling
Published: September 2020

In order to explore the influencing factors of Chinese medicine cultural identity of international students from Chinese medicine schools. The paper questionnaire survey was conducted among overseas students with academic degrees from nine Chinese medicine colleges by means of convenient sampling, and the data were analyzed by multiple linear regression. In conclusion, the mean of Chinese medicine cultural identity score of international students from Chinese medicine colleges was (3.80±0.70), Chinese medicine cultural identity that there are statistically significant differences in the four variables: whether Chinese or not, motivation of studying abroad, medical training and home medicine (p< 0.05). Conclusion: The motivation of studying abroad is an important factor affecting the cultural identity of Chinese medicine for international students in China, and Colleges of Chinese medicine should enhance the education and guidance of cultural identity of Chinese medicine for international students in China.
Visual module based on VSLAM
Authors: Xiong Letian , Liao Guojiao , Xiong Shiqi
Published: September 2020

With the rapid development of science and technology, VSLAM (real-time positioning and map construction technology) has been widely used in AR/VR, robots, drones and unmanned aerial vehicles and other fields because of its unique theory and application value in the era of artificial intelligence. However, there are still difficulties on indoor and outdoor positioning navigation and image scene understanding, such as auxiliary rescue after disaster, inspection of large factories, etc. In addition, the combination entity of VSLAM and artificial intelligence has not realized the popularization of consumption level. A vision system positioning module based on VSLAM technology can be transferred to be the carrier of any intelligent robots, which can be used in post-disaster auxiliary rescue, intelligent inspection of large factories, intelligent logistics sorting field and the construction of intelligent city in the future. People can save rescue time, help save life, reduce economic loss and the safety risk of rescue personnel on the auxiliary disaster rescue and intelligent inspection with it. At the same time, it can help achieve intelligent logistics sorting (and its scope expansion) by setting up network with 5G (5th generation wireless systems) in logistics community distribution.
Automatic classification of CT images of cerebral hemorrhage in dicom format based on BP neural network
Authors: Zhang Kang , Xu Shaozhong , Hu Chenxuan , Zhang Heling
Published: September 2020

This paper presents a method that can scan all the DICOM format CT images of cerebral hemorrhage in the specified folder and automatically analyze the parameters of the hemorrhage area. The automatic segmentation of cerebral hemorrhage area and brain tissue area is realized by threshold method, and the volume of cerebral hemorrhage area and brain tissue area is calculated according to the layer height and resolution parameters of Dicom format image. The proportion of hemorrhage area to brain tissue is calculated. Then, the position information of hemorrhage area and the percentage of hemorrhage area in brain tissue are used as the input of BP neural network to realize the automatic classification of the severity of cerebral hemorrhage.
Research on improved sharpening algorithm based on closed operation and binarization
Authors: Wang Xuesong , Wang Shigang , Guo Yifeng , Wu Shukun , Li Kene
Published: September 2020

In this paper, binarization and closed operation are used to improve traditional sharpening algorithms. Aiming at the problem that traditional sharpening algorithm tends to sharpen noise when processing pictures. First of all, this paper eliminates noise through binarization, and then uses morphological closed operation to fill the cavities generated by noise. Finally, the Sobel operator is used to detect the edge of the image, which is superimposed with the original image and simulated on matlab. The simulation result shows that the improved sharpening algorithm based on binarization and closed operation can not only sharpen the edges of the image, but also not sharpen the noise. The innovation of this paper is to make the image sharpening effect better than traditional phase algorithm.
Effect of IL-8, IL-2 and IL-15 Gene Expression in Different Tissues of Jinghai Yellow Chicken Infected by Eimeria Tenella
Authors: Wang Chengli , Yu Hailiang , Wang Xiaohui , Zou Wenbin , Mi Changhao , Hu Tingyan , Dai Guojun
Published: September 2020

For research the role of IL-8, IL-2 and IL-15 genes in immune regulation after E. tenella infection, with Jinghai yellow chickens as material, the mRNA expression levels of IL-8, IL-2 and IL-15 genes in ten different tissues after infection with different doses of E. tenella oocysts were compared to determine the expression difference of the three genes in the same tissue with different infection doses. The results showed that IL-8, IL-2 and IL-15 genes were expressed in all tissues at the 7th day of infection, and the infection group was higher than the control group in most tissues. The mRNA expression of IL-8 gene in infection group II in the liver was significantly higher than that in the other two groups (P<0.05), and was extremely far higher the other two groups in the spleen and cecum (P<0.01). The mRNA expression of IL-8 gene in infection group II was also far higher in the bursa and thymus than that in the control group (P<0.05). The mRNA expression of IL-2 gene in infection group II in liver and lungs were significantly (P<0.05) and extremely significant (P<0.01) higher than that in the control group, respectively. The IL-15 gene mRNA expression. The infection group was obvious (P<0.05) and extremely significantly (P<0.01) higher in the lung and cecum than that in the control group, respectively. These results indicate that the three genes play a role in the infection of E. tenella in chickens, and provide a basis for the subsequent study of the relationship between these three genes and chicken coccidiosis resistance.
Identification of money laundering accounts based on weighted capital flow network
Authors: Xiong Jianying , Zhong Haifeng
Published: September 2020

Money laundering is an activity of transferring money through fraud and concealment. And its behaviour is different from normal transaction. The key to identifying money laundering crime is to find illegal account from massive capital flow data. The paper studies a method to identify the money laundering nodes by constructing the structural features of the capital flow network. According to the characteristics, we define the calculation methods of node outgoing, incoming and connectivity in the capital flow network, and identify the key nodes. The experimental results show that this method can find abnormal account from large-scale capital transaction data. Although the accuracy needs to be improved, it can help extract evidence of money laundering by ranking the weight and analyzing the capital flow from high-weight account.
Experimental study on road performance of asphalt mixture mixed with antifreeze
Authors: Liu Wenjiang , Chen Jie , Chen Yunquan , Chen Renshan
Published: September 2020

In order to ensure the fast and efficient snow removal of roads in winter, a kind of slow-release antifreeze combined with asphalt concrete is developed, and its road performance is studied. In this paper, a kind of antifreeze performance of AC - 13 is developed, therefore, the low and high temperature performance, water resistance, damaging antifreeze performance of asphalt mixture are studied under different dosage of antifreeze. Based on the analysis of the performance evaluation of the road at the same time the climate suitability of different antifreeze, this paper studies changes of dosage of antifreeze antifreeze performance decay law of asphalt mixture. The results show that the water damage resistance, low and high temperature performance of the antifreeze mixture are decreased with the increase of the antifreeze dosage, but under the appropriate dosage, the performance of the asphalt mixture could meet the requirements of the specification, and the optimal dosage of AC-13 antifreeze is 5.5%.
Improved big data filtering algorithm based on bloom filter
Authors: Liang Yujie , Yu Ying , Ouyang Wenhao
Published: September 2020

This paper focuses on the Bloom Filter deformation algorithm. The storage space occupied by Bloom Filter is independent of elements, which has high space efficiency and low time complexity of insert and query operations. However, as the number of added collections increases, the Bloom Filter’s error rate increases, thus filtering out a lot of non-repeating information. In order to solve this problem, the standard Bloom Filter is improved by introducing an algorithm of the structure of the master-slave Bloom Filter. Only when the master-slave Bloom Filter produces errors, the filter is considered as an error. At the same time, by dynamically increasing the number of filters, the growth of misjudgment rate is delayed. This paper also involves an improved Bloom Filter algorithm to reduce the error rate of the repeated data in the judgment filter.
Research on the protection and mechanism of coptis alkaloids on acetic acid type gastric ulcer
Authors: Duan Qionghui , Li Yong , Qin Feng
Published: September 2020

This paper studied the therapeutic effect of Coptis alkaloids on acetic acid type gastric ulcer and its possible mechanism. Acetic acid type gastric ulcer model is used and administered for 7 days, and the rats are killed, and then IPP software is used to calculate the area of ulcer of gastric tissue and the inhibition rate of ulcer. ELISA kit is also used to measure the expression level of epidermal growth factor (EGF) in serum of rats, 5-hydroxytryptamine (5-HT) in brain and noradrenaline (NE) in adrenal tissue. At the same time, HE staining is used to observe the healing state of gastric tissue. The experiment result shows that the ulcer area of Coptis total alkaloids group 25 mg/kg/day is significantly lower than that of the model group (P < 0.01), and the inhibition rate of ulcer is more than 50%; at the same time, it increases the content of EGF in serum (P < 0.05), promotes the healing of injured gastric tissue; and it also significantly increases 5-HT content in brain tissue and NE content in adrenal tissue (P < 0.01, P < 0.01), and to some extent, it regulates the mood of rats and prevents the recurrence of ulcer; the HE staining results shows that the Coptis total alkaloids promotes the recovery of gastric injury. Therefore, the Coptis total alkaloids can promote the healing of acetic acid type gastric ulcer, and its mechanism may be that it improves the healing quality of gastric ulcer by regulating the emotion of rats, which results in the effect of treating gastric ulcer.
Research on the impact of energy saving policies on subsidy income for regulated food enterprises: based on PSM-DID method
Authors: Chen Jianling , Dai Yongwu , Lin Weiming
Published: September 2020

Taking the “Energy Saving and Low Carbon Action in Ten-thousand Enterprises” officially implemented in 2012 as the target of the energy saving policy, based on the data of food enterprises which are extracted from China Industry Business Performance Data, and by using the one-by-one propensity score matching method (one-by-one PSM), the balanced panel data of regulated enterprises (totalling 617) and unregulated food enterprises (totalling 617) from 2010 to 2013 are obtained through matching. Later, the difference-in-difference model (DID) with energy saving policy treatment variables is used for estimation to quantitatively evaluate the “net” effect of the energy-saving policy on subsidy income for regulated food enterprises. The results indicate that: The proportion of subsidized enterprises in all regulated food enterprises is higher than that of subsidized enterprises in unregulated food enterprises. Regulated food enterprises can obtain more subsidies than unregulated enterprises, which means, the proportion of subsidies in regulated enterprises is 43.1% higher than that in unregulated enterprises.
A new type of RMB counting device
Authors: Huang Jian
Published: September 2020

In order to measure the quantity of paper with high speed and accuracy, a new measuring technology based on the principle of capacitance sensing is proposed and a measuring device is made. Put two metal plates of the same size at a certain distance with a piece of A4 paper in the middle. When the thickness of the paper changes, the capacitance on the metal plate will change. Use the capacitance sensor fdc2214 to sense the change. After modeling and analysis, determine the functional relationship between the thickness of the paper and the measured value, and calculate the paper quantity. The test results show that the device can count the number of paper accurately and quickly.
The impact of artificial intelligence on job insecurity: A moderating role based on vocational learning capabilities
Authors: Liu Renbao , Zhan Yige
Published: September 2020

In order to explore the psychological impact of artificial intelligence on the job insecurity of manufacturing employees, a quantitative model of artificial intelligence (AI) on employees’ job insecurity was constructed by using vocational learning ability as a moderating variable. This paper constructs the measurement model of artificial intelligence on the job insecurity of employees, and makes statistical analysis of the data by using SPSS22.0. The results show that artificial intelligence has no significant negative influence on the job insecurity at present. However, the interaction items between vocational learning ability and artificial intelligence have significant negative effects on job insecurity, and vocational learning ability has a significant moderating effect on job insecurity. This paper has theoretical guidance and practical significance for the government, enterprises and employees to take active measures to solve the structural unemployment problem caused by the development and application of artificial intelligence in the labor market.
Construction and evaluation of a smart learning ecosystem for college English
Authors: Wen Lu
Published: September 2020

This paper aims to construct a smart learning ecosystem for College English from the inorganic environment and ecological communities in order to generate the greatest energy flow and information flow among the physical environment, visual environment, resource environment and teachers, students, administrators and developers. After a two-year experiment of GUET, the findings are as follows. First, this model has significant effects on improving the passing rate of CET-4. Second, this model has obvious improvement on improving students’ writing ability, while there is no obvious improvements in students’ listening and reading ability. This paper analyzes the research results and puts forward corresponding solutions to these problems to promote a sustainable development of College English.
Evolution characteristics of total factor productivity of industrial enterprises in Fujian Province
Authors: Zheng Shunhui
Published: September 2020

The DEA-based Malmquist index method was used to measure the total factor productivity of the industrial sector of Fujian Province and the industrial enterprises under four forms of ownership from 2004 to 2016. The research conclusions are as follows: First, the total factor productivity of the industrial sector of Fujian Province improves year by year, with an average growth rate of 8.9%. Technical progress is the only driving force for the improvement of total factor productivity. The technical efficiency, pure technical efficiency and scale efficiency remain unchanged; second, from the perspective of ownership, the total factor productivity of collective enterprises grows fastest, reaching 11.3%, followed by private enterprises (10.3%), foreign-invested enterprises (7.9%), HKMT enterprises (7.5%). Technical progress is also the only driving force. Therefore, the Fujian Provincial Government should increase investment, and support industrial enterprises to enhance the capacity for technological innovation, the conversion rate of technological achievements and the efficiency of resource allocation.
Improved genetic algorithm applied to model identification of typical thermal process of gas-steam combined cycle unit
Authors: Ni Weichen , Li Haoran , Cao Xiaonan , Zhang Changzhi , Zhao Yi , Wang Jian
Published: September 2020

The gas-steam combined cycle unit has high thermal efficiency, low pollution to the natural environment, and high cost performance. It has become the first choice in the sustainable development planning of the power industry, especially for the steel companies. It is of great practical value to establish the mathematical model of the combined cycle unit, especially the thermal process model. However, due to the influence of multi-parameters and non-linear correlation in a typical combined cycle unit, this paper uses an improved genetic algorithm to identify four typical thermal process models. The simulation results show that it is highly consistent with the measured results and is consistent with the traditional genetic algorithm. In contrast, there is also a significant improvement in fitting accuracy, which proves the feasibility and effectiveness of the improved algorithm in this paper in the identification of typical thermal process models of combined units.
Evaluation of teaching quality in higher vocational colleges based on quantum behaviour particle swarm optimization
Authors: Ma Wanzhi , Yang Zhangcheng
Published: September 2020

The implementation of teaching evaluation comprehensive evaluation system and effective management on teaching quality can scientifically manage the development of teachers’ teaching activities. At present, the teaching quality evaluation of teachers in higher vocational colleges has not yet realized algorithm operation based on quantum behavior particle swarm optimization. Therefore, it is necessary to study the teaching quality evaluation system consistent with the characteristics of higher vocational colleges. Quantum particle swarm optimization can construct a system model that can evaluate the quality of teaching. The system includes various functions like management and evaluation, which can be closely combined with the actual needs of each college. User name and password can effectively improve the security performance of the system. Convenient and fast database management operation, as well as intelligent and friendly database management interface, can ensure the timeliness and accuracy of query results. Research shows that, based on the practical application of quantum behavior particle swarm optimization in the field of teaching quality evaluation, the means of teaching evaluation are more scientific.
Research on accurate quantification of membership of distribution terminal index based on cloud model
Authors: Liao Mengke , Xu Hairui , Cao Xinhui , Dong Yuting , Zhou Honglian , Bai Shengli , Xing Xiaomin
Published: September 2020

In order to accurately assess the health status of distribution terminals, it is necessary to solve the problems of strong subjectivity and high redundancy of the index membership results in the evaluation index system. According to the empirical score given by experts, the cloud model is used to describe the actual index state and the level boundary interval respectively to form floating cloud and standard state cloud space, and the overlapping area of the two is used to represent the membership degree of the actual index. This can not only directly determine the results, but also eliminate the influence of redundant factors, and realize the accurate quantification of the index membership degree results, which widens the direction for further improving the final evaluation effect.
RETRACTED: Research on innovation mode of new material enterprises under the background of big data
Authors: Chen Zhangliang , Shi Junwei , Zheng Binbin
Published: September 2020

In the background of big data, the innovation process of new material enterprises is the result of full and effective integration of many external forces. This paper analyzes the impact and challenges of the emerging big data phenomenon on new material enterprise innovation, including internet plus, material genome project and so on. This paper also puts forward the mechanism of external driving force for innovation of new material enterprises in the big data environment, and discusses the influence of DMAIC model on the decision-making of new material enterprises. Finally, the paper expounds how to establish a multivariate and opening innovation platform for new material enterprises based on big data ecosystem under the two major support systems of internet of things and cloud computing, so as to make full use of various big data resources to serve the innovation and development of new material enterprises.
Economic analysis of the change of tea production layout in China
Authors: Wu Qinyao , Sun Chaofeng , Yang Jiangfan
Published: September 2020

In the context of deepening supply-side reform in China, based on the national tea planting area and yield data from 1993 to 2018, combined with GIS technology and spatial center of gravity statistical models, this paper analyzes the characteristics of China’s tea development and change in 25 years in detail, and comprehensively analyses the driving mechanism of the changes. The following conclusions are drawn: China’s tea production space has changed significantly, and the country’s tea planting area and output have been on the rise, but the changes are inconsistent; The continuous westward shift of the center of tea production in China is caused by the joint influence of nature, economy and society, among which resource endowment and policy support are the most important driving forces.
How online reviews drive enterprise innovation: the intermediary role of customer participation
Authors: Li Qianqian , Pu Jiaying
Published: September 2020

With the rapid development of the Internet, online reviews have become a hot topic. Online reviews have an influence on sales, brand loyalty and consumer behavior, but there is still a lack of systematic research on whether it can drive enterprise innovation. This paper explores the dimensions of online review, constructs a theoretical model of the influence mechanism of online review on enterprise innovation, and uses empirical analysis to verify the relevant hypotheses. It is found that the professionalism, homogeneity and relationship strength of online reviews have a significant positive influence on innovation performance of enterprises, and customer participation plays an intermediary role. By revealing the function mechanism of online reviews, this paper can make managers deeply understand the inherent law of “how to effectively manage online reviews to promote enterprise innovation performance”, which has a certain guiding significance for the marketing practice of enterprises.
Performance analysis of independent suspension coil spring
Authors: Dong Jihao
Published: September 2020

Compared to ordinary springs, the unique advantages of variable-parameter coil springs are explained. Their main characteristics and evaluation indexes are analyzed. And focus on the analysis of their load-deformation characteristics and stress characteristics in combination with the parameter characteristics of variable-parameter springs to provide a certain theory for vehicle suspension spring selection support.
Dynamic game pricing model of car-free carrier platform based on GA-BP theory
Authors: Xiong Zhenyu , Su Youkang
Published: September 2020

With the rapid development of China’s logistics industry, transport demand continues to be strong, and how to scientifically give platform pricing to achieve rapid transactions and reduce operating costs is a major problem. Firstly, in order to solve this problem, after collecting data from the car-free carrier company P, due to the excessive influence factors of the data, it is necessary to clean the data and normalize the data. Six indexes that affect the pricing are screened out by the grey correlation model, which are total mileage, total line cost, vehicle length, vehicle tonnage, transportation grade and the time needed for plan execution. In order to verify the rationality, we do multiple linear regression to the data. Secondly, in order to solve the nonlinear fitting problem, the improved initial value GA-BP model is introduced to perform data fitting and prediction, it is concluded that the first pricing is to achieve the required accuracy at n=94, and the error is less than 0.1% when the number of iterations no more than 100, which verifies the model is suitable for such problems. Lastly, In order to simulate the dynamic pricing process of the platform, it is required to predict three times of pricing. Based on the first pricing and known data, a neural network decision tree prediction model based on game theory is established. The dichotomy is applied to the value of information entropy to measure the proportion of price adjustment, and a conclusion is drawn. When the information entropy value I>26.7204, the second price adjustment decreases by 3.87%, and the third price adjustment decreases by 0.39% .When the information entropy value I>26.7204, the second price adjustment decreases by 1.64%, and the third price adjustment decreases by 1.27%.
Interdisciplinary phenomena and their regional differences in management science
Authors: Ge Zhiyuan , Zhao Huiyuan
Published: September 2020

It is of great significance to discuss the interdisciplinary phenomenon and its regional differences for a comprehensive insight into the intersection and integration of disciplines in the field of science and technology. In this study, based on the text information of the National Nature Fund Project, the corpus is constructed by using keyword information, combined with TF-IDF algorithm to improve cosine similarity, and a region-specific measurement method of discipline intersection is proposed. Using this method, the interdisciplinary difference maps of this discipline among provinces, autonomous regions and municipalities directly under the Central Government in China are obtained, and the interdisciplinary and regional differences in this field are analyzed. The results show that management science has small-world characteristics, and there are great differences in the degree of discipline intersection among different regions, which verifies the effectiveness of the construction method of this study.
Access to the Internet and the Chinese household consumption structure: Based on IV regression and PSM analysis
Authors: Wang Liping , Deng Hao
Published: September 2020

Based on the data of China’s Household Finance Survey (CHFS) in 2017 consisting of 38230 samples across China, this paper uses the instrument variable (IV) regression method and the propensity score matching (PSM) technique to study the influence of access to the Internet on the household consumption structure. The conclusions are as follows: first, access to the Internet is conducive to the upgrading of the consumption structure of the residents. Increase of the income, assets and education level could upgrade the consumption structure. Second, people who do not use the Internet will upgrade the consumption structure if they use the Internet, but the upgrading degree of the consumption structure is limited by the income level. Third, from the regional perspective, the Internet can promote the upgrading of consumption structure in the eastern and western regions of China, but it has no significant effect on the consumption structure in the central and northeast regions.
Factors affecting cross-border RMB settlement under the Belt and Road Initiative: An empirical study based on panel data of 19 countries (regions)
Authors: Wang Yang-Chao , Tsai Jui-Jung , Chen Wenyu
Published: September 2020

Based on the panel data of 19 countries (regions) under the background of the Belt and Road Initiative (BRI) from 2014 to 2018, this study uses generalized least squares (GLS) models, which reduce the heteroscedasticity to explore the factors affecting partner countries’ RMB settlement choice. Further, this study compares the differences of influencing factors between BRI and non-BRI countries (regions). The results show that for countries (regions) along the Belt and Road, China’s economic and financial development more effectively promote the use of RMB settlement. In addition, the trade characteristics are closely related to the cross-border RMB receipts and payments. In terms of trade volume, the larger the bilateral trade between China and BRI countries (regions), the larger the cross-border RMB receipts and payments will be. In terms of trade structure, due to low degree of substitution for high-tech products, the higher the proportion of China’s high-tech products exported to foreign countries (regions), the greater bargaining power in the choice of pricing and settlement currency. Moreover, bilateral currency swap agreements, the establishment of RMB clearing centers, and currency stability are also critical influencing factors.
Dynamic analysis of piezoelectrically driven flapping wing
Authors: Guo Buyuan , Zhang Yafeng , Zhang Jiajia
Published: September 2020

The micro flapping wing using the traditional flapping wing mechanism has the disadvantages of low aerodynamic efficiency and high energy consumption. The bionic flapping wings driven by piezoelectric materials can effectively combine the two main systems of flapping wings and wings. It not only has the task of reducing weight but also has the characteristics of strong deformation ability, high aerodynamic efficiency, and low energy consumption of mechanism. The structure simulation of piezoelectrically driven bionic flapping wing was carried out to use aerodynamic experimental data of the same size of flapping wing. The piezoelectrically driven bionic flapping wing was developed by using the simulation results. The studies show flapping frequency of bionic flapping wing has been improved obviously after using the piezoelectric actuator. The piezoelectric patches can effectively control the wing bending and torsion deformation, which is helpful to improve aerodynamic efficiency of the flapping wing.
Design and analysis of single-degree-of-freedom flapping wing mechanism based on UG
Authors: Zhang Yafeng , Wang Xiaobo , Zhang Guoqiang , Yang Jinhua
Published: September 2020

According to the structural characteristics of bird wings, this paper presents a new type of flapping wing mechanism with single degree of freedom. The mathematical model of this structure has been established by this study. The left and right flapping angles of the mechanism are obtained through this simulation. The change rules of the left and right flapping angular velocities and the left and right flapping angular accelerations of the left and right rocker arm instantaneous flapping angular difference mechanism are also simulated by this model. This model lays a theoretical foundation for the dynamic characteristics of the mechanism. This study also makes a experimental plane. In this study, a high-speed camera was used to record the motion process of the experimental plane. The experimental results show that the test aircraft in this paper can realize the required movement of bionic wings. This study provides some theoretical and engineering guidance for the design of flapping wing mechanism.
Hybrid matrix factorization recommendation algorithm based on item similarity
Authors: Min Lu , Huang Xuejian , Wang Gensheng
Published: September 2020

In order to solve the problem of sparse data in matrix factorization recommendation algorithm, a hybrid matrix factorization recommendation algorithm based on item similarity is proposed. First of all, Worde2vec is used to mine the content information of items in user’s comment data to get the content similarity of items; secondly, the attribute similarity of items is calculated according to the attribute information of items; then, the content similarity and attribute similarity are fused to get the final item similarity; finally, the similarity of item is integrated into the objective function of matrix factorization algorithm. The experimental results show that the hybrid recommendation algorithm has higher accuracy, recall and coverage than the traditional matrix factorization recommendation algorithm.
Prediction of international Chinese liquor market based on convolution neural network
Authors: Zhou Liwen
Published: September 2020

In view of the low market share of Chinese liquor in the international market, domestic liquor export strategies are mostly analyzed from the qualitative aspect, while the reasonable quantitative mathematical model is seldom studied. In this paper, the Convolutional Neural Network (CNN) was used to analyze the current development of Chinese liquor export market by establishing the nonlinear relation model between liquor export amount and various influencing factors, so as to forecast the future market export volume and provide quantitative reference for the development of Chinese liquor export industry.