bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Theory of Navigation Pilot Sharing Mechanism and Network Sharing Platform Construction
Authors: Wang Wenfang , Luo Liangsheng , Ren Dawei 
Published: June 2021

Abstract
Sharing of general aviation pilots is beneficial to the growth of pilots. It is beneficial to achieve the balance between supply and demand of general aviation pilots and reduce the cost to a certain extent. It is beneficial to improve the flight safety level of general aviation enterprises. With the continuous deepening of the reform of “distribution suit”, there are fewer and fewer policy constraints on navigation development, which creates a favorable policy environment for navigation to “fly”. However, under the background of loose policies, China’s navigation development still faces many challenges, among which the high transaction cost of navigation industry is an important reason restricting navigation development. Among them, the cost of pilots accounts for the vast majority of the labor cost.
Management forecast based on big data fusion DEA and RBF algorithm
Authors: Zhu Yan 
Published: June 2021

Abstract
with the rapid development of information technology, how to use big data for effective analysis has become the focus of various industries. Big data will inevitably bring data noise and data redundancy. The traditional big data preprocessing methods do not take into account the functional relationship between variables, and the commonly used big data modeling tools can not effectively model big data with complex nonlinear relationships. This paper puts forward a prediction method combining DEA and RBF, uses DEA to preprocess big data to select the effective date, then uses RBF to model the data, and compares the prediction accuracy with the original environmental management fund data without pre-processing. The results show that the DEA-RBF method has higher prediction efficiency and better prediction accuracy.
Research on Digital Resource System Construction of Smart Library Based on Computer Network and Artificial Intelligence
Authors: Wang Chunyu , Sha Zhengyu , Jia Lin 
Published: June 2021

Abstract
With the development of science and technology, artificial intelligence has become one of the main driving forces for the development of modern society, and has also injected new vitality into the future development of libraries. Based on the high efficiency and scientific of artificial intelligence technology, the technology has been widely used in intelligent search and reasoning, machine learning and human imitation. In the “internet plus” era, the information service carried out by libraries has changed to a new intelligent information service mode. With the support of new technologies, the intelligent library has gradually become a new form of library development, showing the characteristics of digitalization, networking, intelligence and mobility. Artificial intelligence technology has changed the management mode, management content and service mechanism of libraries, and promoted the transformation of traditional libraries towards smart libraries. This paper first expounds the basic concepts of artificial intelligence and smart library, then analyses the constituent elements of smart library, and finally focuses on the construction method of digital resource system of smart library.
Research on OPNET energy simulation application in wireless sensor network
Authors: Qin Yu 
Published: June 2021

Abstract
Considering the problem of not providing energy model in OPNET, a modeling method in WSN is presented. First the modeling process of energy model and the way of its realization are analyzed. Then by introducing RM battery model with higher precision in describing the battery discharge, the energy model in OPNET is established. The results of simulation shows that the modeling method is valid and a better estimation of node lifetime can be achieved using RM model.
Research on Application of Convolutional Neural Network Algorithm
Authors: Ye Ling , Yin Peng 
Published: June 2021

Abstract
This paper proposes a method based on deep learning to improve the efficiency of children’s English learning. Firstly, the migration method is used to improve the accuracy of Resnet18 model. Then the accuracy of the model was further improved by adding channel attention mechanism. Finally, the model fine-tuning method is used to reduce the computational load of the model, so as to facilitate the transplantation to embedded devices and improve the efficiency of the classification model. By comparing with the classical classification model, it is found that the classification model proposed in this paper has higher accuracy and fewer parameters, so it is suitable for transplantation into the English teaching of children.
Non-functionality analysis and verification based on Aspect-Z
Authors: Qu Can , Chen Haihua , Zhang Xuhui , Zhang Lichen 
Published: June 2021

Abstract
The non-functional requirements of the software system usually cross the whole system, and the object-oriented software development method can lead to the entanglement and dispersion of the code. ASECT-Z proposed a formal method for non-functional requirements, it is the formal specification for the extension of Z language. The language based on set theory and mathematical logic, with strict logic, and the formal specification of reasoning. In this paper, we describe a library management system based on Aspect-Z, and then give a formal proof of the formal specification for formal verification.
Prediction of rice yield based on LSTM long short term memory network
Authors: Mo Haoming , Zhang Ying , Liu Yifei , Zheng Yanzi 
Published: June 2021

Abstract
The prediction of rice yield is of great significance for improving rice yield and preventing disasters. At present, there is no exact and effective solution to the problem of rice yield prediction, and there are many factors affecting the rice yield, which may lead to large errors in the prediction results. Based on the rice yield data of 81 counties in Guangxi Province of China for three years, a long short time memory network (LSTM) model was established and used to predict rice yield under the influence of meteorological factors. The results show that the performance of the recurrent neural network with LSTM structure is better than that of the standard recurrent neural network, which solves the problems of gradient dispersion and gradient explosion of RNN model, and enables the model to learn long-term laws. At the same time, the traditional machine learning model is established to compare with LSTM model. The neural network model can better mine the information hidden in the data and make full use of the rules in the data. Combined with meteorological factors, the test shows that LSTM model has higher prediction accuracy. It provides a reference for rice yield prediction.
Synchronization for VHF Data Exchange System
Authors: Rong Shijie , Li Huiyuan , Xiang Qian , Zhang Zhe , Yin Huihui 
Published: June 2021

Abstract
In wireless communications, rapid acquisition of synchronization parameters is essential. Very High Frequency (VHF) Data Exchange System (VDES), a new maritime communication system developed on the basis of traditional Automatic Identification System (AIS), uses time division multiple access (TDMA) and belongs to burst communication. Therefore, synchronization is the top priority of VDES research. VDES includes the terrestrial part and satellite part, named as VDE-TER and VDE-SAT, and the two parts have different channel conditions. This paper studies synchronization algorithms for VDE-TER and VDE-SAT respectively on the basis of different channel conditions and focuses on the derivation, the theoretic analysis and performance simulation of the algorithms.
Research on the Application of Factor Analysis Model
Authors: Liu Tingting 
Published: June 2021

Abstract
This article uses a factor analysis model to conduct an empirical analysis using data analysis. The data comes from a questionnaire survey. The subjects of the survey are college students in Guangxi, China. The research topic is the dual “3+1” training model for compound talents. Based on the SPSS analysis that KMO=0.812 and spherical Bartlett=0.000, the contribution rates of the extracted 8 common factor variances are: H =13.487%, H2 =8.535%, H3 =8.303%, H4 =6.152%, Hs =5.814%, H6 =5.622%, H7 =4.925%, H8 =4.870%, the above data results indicate: government support and social support, school publicity, government and university implementation efforts, student satisfaction with the training model, students’ willingness for future development, etc. The Factor Analysis Model provides reference and enriches the theoretical basis.
An improved genetic algorithm for solving flexible job shop
Authors: Yang Ruifeng 
Published: June 2021

Abstract
According to the characteristics of flexible job shop scheduling (FJPS), a mathematical model was established to minimize the maximum completion time, and an improved genetic algorithm was proposed to solve the problem. A variety of heuristic methods are used to improve the quality of the initial solution. The parallel double-chain encoding is designed and the optimal insertion method is proposed to improve the quality of the solution. Two crossover methods, namely IPOX crossover and multi-point crossover, are adopted to inherit the excellent genes from the parent generation and balance the global development ability of the algorithm. In different coding layers, a variety of variation methods were used to maintain the diversity of the population. The local development ability of the algorithm is enhanced by variable neighborhood search. Finally, by solving the Brandimarte standard example and comparing with other algorithms, the feasibility and effectiveness of the proposed algorithm are verified.
Research on The Optimal Solution of Lagrangian Multiplier Function Method in Nonlinear Programming
Authors: Jin Xue 
Published: June 2021

Abstract
For the general nonlinear constrained optimization model, this article will propose a new nonlinear Lagrange function, discuss the properties of the function at the KKT point, and prove that under appropriate conditions, the iterative point generated by the dual algorithm based on the function The column is locally convergent, and then an error estimate of the solution related to the penalty parameter is given. This provides a new way to solve nonlinear constrained optimization problems.
Research on optimal Modeling of Food system based on data potential Distribution Mining and quantitative Analysis
Authors: Chen Yanqian , Qu Hongtu , Kong Chunming 
Published: June 2021

Abstract
The current world food system gives priority to efficiency and profitability, creating some environmental and inequality problems in the world. In order to re-optimize our food system, we have developed a food system model to adjust the efficiency, profitability, fairness and sustainability of the food system. First of all, we describe the positive and negative effects of food systems optimized for fairness and sustainability, respectively. We have established the index system, and on the basis of the existing data, we use the grey prediction and fitting method to obtain the future data of each index. After that, we divide the previous 12 indicators into benefit category and cost category, and use entropy method to get the weight of indicators that affect benefit and cost each year. We use the “scale factor” method to quantify indicators that are difficult to measure, build models to calculate cost and benefit priorities for changing the world food system, and chart changes that benefit cost ratios in different years.
An Efficient Algorithm for Frequency Estimation of Sinusoid Signal Based on Improved Quinn
Authors: Liu Yibing , Xu Zhongfu , Zhou Hanbing , Zhao Yang 
Published: June 2021

Abstract
To balance the performance and complexity for frequency estimation of sinusoid wave using DFT-based methods, an efficient estimation algorithm based on improved Quinn is proposed. The amplitude and phase information are used to interpolate which ensures the accuracy of the frequency shift direction. A method of piecewise frequency shift is performed, and it has the characteristics of higher precision and lower computational costs. Simulation results show that the judgment of direction factor is more correct using Quinn, the Root Mean Square Error (RMSE) of this method is closer to Cramer-Rao Lower Bound (CRLB) under the conditions of different frequencies and SNRs comparing with Quinn and other improved algorithms, and it can attain remarkable decrease of computational cost which facilitates the algorithm implementation.
The two-layer SRU Neural Network Based Analysis of Time Series
Authors: Han Junjun , Zhu Xiaoqing 
Published: June 2021

Abstract
The traditional measurement model cannot meet the processing requirements of non-linear and high-noise time series data. A two-layer simple recurrent unit (DSRU) prediction model based on BPSO and SO-PMI sentiment analysis algorithm is proposed. First, the model uses the SO-PMI algorithm to calculate the stock market sentiment tendency measurement index. Then the BPSO algorithm is used to extract the characteristics of stock technical indicators with greater stock price correlation. Finally, the DSRU network model is used to predict the stock price. Taking Shanghai Pudong Development Bank stock as an example, the results show that the model has a significant improvement in prediction accuracy, reaching 65.84%, with an average absolute error of 0.0541, which proves the superiority and effectiveness of the method.
System Composition and Optimization of Small Soccer Robot
Authors: Du Jinhua , Li Shuang , Wang Hang , Sun Zhaoming , Du Gang 
Published: June 2021

Abstract
In view of the present intelligent and practicability of the small soccer robot system is still at the lower level, to improve and optimize the small soccer robot system performance, from the visual model to optimize the design of the decision system physical error control three perspective, based on the visual subsystem, decision-making subsystem and physical subsystems through the research of the three subsystems respectively through the model establishment and design improvement strategy is put forward, and USES the SOM simulation software to verify the simulation experiment and data results show that based on visual decision-making and physical three subsystems of the modified method is helpful to improve the overall performance of soccer robot system and intelligent level.
Research on System of Data Mining Technology Based on Computer
Authors: Zhu Yuan , Chen Jingjie 
Published: June 2021

Abstract
The existing implicit feedback collaborative algorithm directly uses sparse binary social trust information to assist recommendation, which has serious data sparse problems and does not have the influence of deep integration of social trust information. In response to the above problems, the paper proposes an algorithm that uses a denoising autoencoder to deeply integrate user implicit feedback data and social information. At the same time, a cloud computing-based social trust information data mining system architecture is constructed, and its modules are described. This framework is conducive to solving the problems of high data complexity and large amount of data encountered in current data mining, and can significantly improve the performance of data mining.
Simulation analysis of mechanical properties of composite materials
Authors: Su Jintao , Lou Jianping , Jiang Xiaolu 
Published: June 2021

Abstract
Based on the technical study of a composite vertical tail, the mechanical properties of honeycomb sandwich structure at the leading edge of the composite were studied fundamental computational analysis. The stress calculation and modal analysis of sandwich beam/plate structure are carried out by using engineering algorithm and two finite element modeling methods. The comparative analysis of the results shows that the two modeling methods can effectively simulate the mechanical properties of composite sandwich structure. In the actual analysis of complex structures, a simple 2D shell element modeling method can be used for preliminary simulation analysis.
Research on Industrial Upgrading and Technology Spillovers by Mathematical Model and Calculation Analysis
Authors: Li Zhiyuan , Li Zhenzhen , Gao Renhao , Li Jia 
Published: June 2021

Abstract
In the context of global economic integration, the economic links between countries are getting closer and closer, and international direct investment is an important link to connect the economies of various countries. In recent years, with the rapid development of China’s economy and the further improvement of the level of opening to the outside world, China’s IFDI (foreign direct investment) and OFDI (outbound direct investment) have developed rapidly. At the same time, the contradiction of China’s industrial structure has gradually emerged, and it is urgent to promote economic intensive development and industrial structure upgrade. Based on this research background, the thesis puts IFDI, OFDI and China ’s industrial structure upgrade into the same theoretical analysis framework, and explores the mechanism of two-way FDI to promote industrial structure upgrade from the perspective of technology spillover; Panel data of several provinces (municipalities), through the construction of simultaneous equation models, empirical analysis of the impact of two-way FDI technology spillovers on the optimization and upgrading of China’s industrial structure.
Influencing Factors Study on Green Development Using Principal Component Analysis and Factor Analysis
Authors: Sun Yihong , Gao Han , Yuan Xuemei 
Published: June 2021

Abstract
The rapid economic development and high incidence of crises in emerging economies make them play an increasingly important role in the transmission of global financial risks. As a new trend in the development of the financial industry, the development of green finance also indicates the direction of the future development of the financial industry. Faced with the increasingly concerned environmental issues, it is necessary for emerging economies, mainly represented by developing countries, to learn from the experience of developed countries in this field. In this paper, principal component analysis (PCA) and factor analysis (FPM) are applied to study the factors influencing financial fragility of emerging economies at different stages of development, and then the degree of fragility is analyzed and compared. The empirical results show that there are differences in the influencing factors of financial fragility in emerging economies at different stages of development. For middle- and low-income economies, credit security, social stability and the development of capital market are the priorities they should consider at present. For the Middle- and high-income economies, we should be alert to the malignant changes in a certain indicator. For high-income economies, macroeconomic stability is the focus of their financial security. The research results provide a basis for the emerging economies to reduce economic vulnerability according to local conditions, which is of great significance to avoid the outbreak of global financial crisis.
Study of Multiple Linear Regression on the Technology Upgrading of Sichuan Province by Mathematical Statistics and Computational Science
Authors: Zou Xiaowei , Liu Xinyan , Liu Jiyu , Lu Shaozhuo 
Published: June 2021

Abstract
China’s economy has entered a new normal, and the industrial structure must be upgraded in order to realize the transformation of economic growth kinetic energy. Sichuan Province, as the economic leader in western China, needs to accelerate the optimization of its industrial structure. Therefore, this paper makes an empirical analysis of the factors that affect the upgrading of Sichuan’s industrial structure, and puts forward countermeasures and suggestions to promote the optimization of Sichuan’s industrial structure.
Study on Physical Effects of Optical Fiber Transmission Characteristics Under Nonlinear Optical Effects
Authors: Lu Jing 
Published: June 2021

Abstract
Photonic crystal fiber has a special light guiding mechanism and structural tunability, which can produce singular dispersion characteristics and high nonlinearity, which provides new conditions for the research in the field of nonlinear fiber optics. Due to the combined action of a variety of nonlinear optical effects, photonic crystal fibres with different structural parameters and transmission characteristics can produce rich nonlinear spectra under different pump light pulse parameters. We use the photonic crystal fiber cladding section to conduct nonlinear optical experimental research, and obtain the broadband spectral output of soliton wave and dispersive wave. The theoretical analysis and experimentally measured spectra include blue-shifted dispersion waves in the visible light band near 0.5 μm, residual pump light in the 0.82 μm band, soliton waves in the 1.1 μm band, and red-shifted broadband dispersive waves near 2 μm. Corresponding to this, the formation and redshift of solitons can be clearly seen in the time domain, and there is no more oscillation secondary peak in the femtosecond transmission pulse.
Application of AsiaSat-3S satellite in CAPS system
Authors: Hu Zhengqun , Zhang Lirong , Zhang Lirong , Zhang Lirong , Zhang Lirong , Lü Chang , Pei Jun , Ma Lihua 
Published: June 2021

Abstract
CAPS is an integrated system of navigation and communication. The orbit position of AsiaSat-3S satellite has been pushed from 105.5E to 147.5E. It has become a SIGSO satellite, which plays a certain role in improving the constellation DOP of CAPS navigation system. According to the characteristic parameters of AsiaSat-3S satellite (mainly including orbit parameters, polarization parameters, frequency offset parameters, etc.), this paper expounds the changes of azimuth, elevation angle and polarization angle of 16-meter paraboloid antenna in Tianjin pointing and tracking AsiaSat-3S satellite in CAPS ground system, and analyzes the dynamic changes of frequency offset of AsiaSat-3S satellite transponder through the spontaneous receiving of navigation signals The parameter model prediction of CAPS repeater navigation system has a good reference value.
Precision Analysis of Solar Astrometric Positions from the JPL DE431 Ephemeris
Authors: Ma Lihua , Wang Xiaolan , Pang Feng , Kong Ting 
Published: June 2021

Abstract
The DE (Development Ephemeris) series of planetary ephemeris released by NASA’s Jet Propulsion Laboratory (JPL) have been widely used in deep-space navigation, interplanetary exploration, analysis and reduction of high-precision astronomical observations, and calibrations of gravitational theories etc. This work takes solar astronomic positions as an example to analyze precision of the JPL DE431 planetary ephemeris data. The results show that the DE431 ephemeris has high precision, which can be guaranteed within 0.08 milliarcseconds (mas), and can be used to carry out high-precision calculation of planetary positions.