bluuebunny/crossref_metadata_2025 huggingface dataset:
Aspect-oriented requirement analysis based on Formal method
Authors: Qu Can , Zhang Xuhui , Chen Haihua , Zhang Lichen
Published: June 2021

Aspect-Oriented Programming (AOP) can effectively solve the code-tangling and code-scattering which are caused by crosscutting attributes, However, much work is presented on the programming and the implementation phase, and few works have addressed the early model stages. In this paper, we do research on the requirements engineering phase of software by using AOP technology. First in the requirements analysis phase, we identified the functional requirements and non-functional requirements by the separation of concerns, then to realize the functional requirements with components and the non-functional requirements with aspects. Then we represent the components and aspects by combining with the formal language Aspect-Z which have characteristics of accurate description; As actions accompany with conflicts while two or more aspects effect on the same joint point synchronously, we propose a method to solve by defining aspects priority level.
Application of Beidou Satellite Navigation System in Finding Separated Children
Authors: Wu Yubo
Published: June 2021

The Beidou satellite navigation system is currently one of the most advanced navigation systems on an international scale. The purpose of this work is to design a system framework based on the Beidou navigation system for the positioning and tracking of children. The novel system designed in this work includes a Beidou satellite system, a tracker assembly mounted on the sole of a child’s shoe, a guardian’s cell phone terminal and a monitoring computer terminal. In particular, the present work creates a new tracker assembly that is communicatively connected to the guardian’s mobile phone terminal and the monitoring computer terminal through the Beidou satellite system, respectively. This paper designs and implements an effective monitoring and tracking of children’s location based on Beidou navigation, which is worth promoting and applying
Research on the Text Similarity Algorithms in Automatic Scoring of Subjective Questions
Authors: Peng Juan
Published: June 2021

The theme revolves around the automatic scoring of subjective questions. The key technologies involved in the whole automatic scoring process are discussed in this paper, analyzes the advantages, disadvantages and application scope of different calculation methods for text similarity to understand the development trend of this field. It is helpful for further research on the automatic scoring method of subjective questions based on Word2vec improved model.
Exploration on Smart Library Construction in 5G Era
Authors: Zhang Liqun
Published: June 2021

With the rapid development of information technology and network, we have ushered in a new round of communication technology called fifth generation communication technology (5G). The arrival of 5G has brought new opportunities and challenges to all walks of life. As a document information center, the library is the carrier of collecting, sorting and collecting document resources. As a librarian, we should keep up with the pace of the times, take practical and effective management methods to combine 5G with the construction of smart library, and establish efficient, intelligent, interconnected and convenient smart library services.
Theoretical Derivation of Student Basic Signal Monitoring System Based on Software Engineering
Authors: Yu Tianbo , Wang Yue , Sun Weidong , Sun Rui
Published: June 2021

At present, in China’s higher education institutions, with the rapid progress of software engineering theory, this paper adopts the signal monitoring system method and derives the mathematical analog signal strength monitoring system. It is optimized in combination with the software engineering wearable system. By using the heart rate acquisition module to improve the performance, using the temperature acquisition module empirical formula, and finally through the software engineering statistical comparison analysis, it is proved that the student basic signal monitoring system has a significant effect and can play a role in preventing students from fainting or sudden death. positive effect.
A fusion framework for automatic neuron reconstruction
Authors: He Ping , Zhao Xuan , Li Longfei
Published: June 2021

Neuron reconstruction is an important step to study the relationship between brain neuron morphology and function. Existing neuron reconstruction algorithms have achieved relatively good results under certain conditions. In the context of whole brain research, the conditions are more demanding, so the previous methods cannot guarantee high-quality results in any brain image data. This paper proposes a fusion framework for automatic reconstruction, which is dedicated to improving the applicability of traditional reconstruction algorithms and obtaining high-quality neuron morphological data. Experiments show that this framework is more flexible than traditional reconstruction methods and has broad application prospects in the current research background.
Research on the Application of Modern Computer Technology in the Modeling of Basketball Offensive Line Measurement and Calculation
Authors: Li Wang
Published: June 2021

In order to better improve the shooting percentage, this article proposes mathematical modeling and statistical analysis of the offensive line measurement of the basketball’s vertical height, horizontal speed, and vertical speed when shooting. Studies have found that excellent shooters can get a high and stable shooting percentage when using dominant hands. Excellent shooters usually like to use a variety of shooting postures. The thesis also develops an interactive and intelligent basketball tactics teaching software system to enable students to initially establish a perceptual understanding of basketball skills and tactics, and improve the teaching effect of teachers explaining basketball training techniques and tactics.
Research on Food Security system and Optimization method based on multiple regression Analysis
Authors: Bu Jiahui , Liu Ziang , Wu Junlin
Published: June 2021

Considering that the current model of the world food system puts efficiency and profit first, many people still go hungry and seriously pollute the environment. In this paper, the multiple nonlinear regression method is used to optimize the existing food system. Firstly, the food security evaluation system is established, and the global food security situation in recent years is obtained by calculating FSSI. Then, the model of influencing factors of food security is established, and the relationship between food system security index and various factors is obtained by multiple nonlinear regression, on this basis, fairness and sustainability index are obtained by the same method, and the existing food system is optimized. After analyzing the current situation of countries with different standards, we have formulated a series of intelligent optimization policies for them. Finally, by comparing the change trend of the index before and after optimization, it is found that the optimized index can reach the ideal value more quickly.
Application of Artificial Intelligence System in Libraries through Data Mining and Content Filtering Methods
Authors: Tian Zhaoxia
Published: June 2021

With the rapid advancement of artificial intelligence theory, this paper adopts a multi-intelligent agent collaboration method and derives through data mining. In combination with content filtering methods and intelligent agent learning optimization, it improves the high performance by using a personalized information service system architecture. The performance of the library system of vocational colleges. According to the difference of readers’ interest, it matches the results of traditional document retrieval, effectively filtering out readers’ demand information, reducing the time for readers to search for required information, improving reader retrieval efficiency, realizing information push of similar users, and realizing “information looking for people”.
Research on Real-time and Reliability of Wireless Transmission of High-speed Train Control Data Based on Data Mining Technology
Authors: Luo Mingyu , Zhu Liguo
Published: June 2021

The informationization of high-speed railway is of great significance to the operation and maintenance of high-speed trains. Through the operation and maintenance data communication based on wireless public network, the ground monitoring system can know the real-time status of trains in time, which can facilitate the daily arrangement of inbound inspection and maintenance of trains and improve the operation and maintenance efficiency of high-speed trains. The reliability of data transmission in wireless sensor networks is low under the influence of resource constraints and environmental factors. However, the reliability of data transmission is an important index to evaluate the network performance in application fields such as national defense, military affairs and industrial control. Based on data mining technology, this paper analyzes the real-time, reliability and security of data transmission according to the characteristics of digital mobile communication used for data transmission in railway running and train automatic control. Combined with the characteristics of wireless channel in the environment of intelligent railway transportation system, this paper puts forward concrete measures to improve the performance of wireless link and concrete methods to judge whether wireless transmission can meet the requirements of IRTS environment.
Community Search in Spatial Uncertain Network
Authors: Zhang Wenqian , Zhong Yingli , Yang Yan
Published: June 2021

Community search is to explore valuable target community structure from a large social network. In real community, every point has a geographic location information, and many edges are uncertain. Such a network is called spatial uncertain network. In order to meet the existing needs, this paper studies the community search in the spatial uncertain network so that the searched communities can be relatively close in the geographical location and the relationship between each other is also very close. Based on the spatial uncertain graph, this paper proposes K-R-τ community, and proposes a linear algorithm and a two-dimensional algorithm for community search in the spatial uncertain network. A large number of experiments are carried out on several real datasets, and the results show that the algorithm proposed in this paper is effective and accurate.
Stability Evaluation and Optimization of Food System Using PEFS Mathematical Model and Big Data Technology
Authors: Li Zesheng , Huang Yue , Li Zhenjia
Published: June 2021

Today in our world, the food system is very unstable despite its high efficiency and profitability. More and more problems and even tragedies are caused by the instability of today’s food system. Therefore, the stability evaluation and optimization of the food system need to be implemented as soon as possible. A basic model named PEFS is established for better understangdings of our global food system based on the mechanism analysis of the food supply chain. Its output is the efficiency and profitability of any food system. We can use the PEFS model to simulate the global food system. Relying on the collected data, the model gives the profitability and efficiency of food systems in 162 countries around the world. The visualized map is shown in Figure 4. Among them, Guatemala is the country with the highest profitability, reached 0.812. Argentina is the country with the highest effciency, reached 0.854.
Research on High Precision solution of Fractional partial differential equations under Heat conduction Model
Authors: Wang Zhizhen , Liu Mengchen
Published: June 2021

Aiming at the heat conduction equation, the heat conduction model is a very typical example of the partial differential equation. This paper focuses on the development and preliminary knowledge of the partial differential equation, the establishment of the heat conduction model and the solution of the heat conduction model. The partial differential equation with fractional Laplace operator is a kind of typical fractional partial differential equation, which has important applications in the fields of science and engineering. Fractional Laplace operator is a kind of nonlocal quasi-differential operator, which is the infinitesimal generator of L é vy steady-state process. It is essentially different from the classical Laplace operator, which leads to the disappearance of some classical properties, which generally brings difficulties to the study of this kind of problems. It is very difficult to solve the explicit solution of partial differential equation with fractional Laplace operator. In order to improve the accuracy and speed of solving partial differential equation, a high precision method for solving partial differential equation based on deep learning network is proposed. A multilayer radial basis function neural network is constructed and its structural layers are determined. By introducing subnetworks into each layer of the multilayer radial basis function neural network, a composite multilayer radial basis function neural network is constructed to improve the real function approximation performance and operation accuracy of the multilayer radial basis function neural network. The high-precision compound multi-layer radial basis function neural network is used to solve the partial differential equation. By giving a specific example of solving the partial differential equation, the solution effect of the method is tested. The results show that the method has very high solution accuracy under the four-layer network structure, which can improve about 1.5 orders of magnitude compared with the first layer. Under different number of training samples, it has higher solution accuracy and speed, and the comprehensive performance is superior. Therefore, it is a practical but challenging work to study the existence of solutions of partial differential equations with fractional Laplace operators. This paper mainly describes the research progress and trends of the existence of solutions of several classes of partial differential equations with fractional Laplace operators, including some of the work done by the author in this field in recent years.
Evaluation and Application of Cloud Model Controller in Financial Technologies in the Age of Big Data
Authors: Chen Jin , Xu Yifan , Wu Yang
Published: June 2021

Financial innovation is of great significance to the long-term and stable development of commercial banks and the entire financial market. Reasonable and effective innovation under the current changing financial situation is of great significance to the development of the overall banking industry and financial market, but to varying degrees and Different ways of innovation often produce different results. The article uses the cloud model to comprehensively evaluate the financial innovation indicators of the five state-owned commercial banks. By taking into account the characteristics of ambiguity and randomness, and using the characteristics of the cloud, the evaluation results are more objective and authentic.
Research on Combined Optimization of Intercontinental Intermodal Transport Scheme by Railway Network and Double Difference Model
Authors: Jing Ruisi
Published: June 2021

The China-EU freight train is a physical link connecting the Eurasian continent in the new era and a new bridge for expanding China-EU economic and trade cooperation. Since its opening in 2011, China-EU freight trains have developed rapidly. Since 2015, it has been normalized and fixed, and now it has entered a stage of steady growth. Based on the trade gravity model, this paper calculates the trade gravity coefficients between China and the rest of the world in 2015 and 2019, and then establishes the analysis and construction of China-EU freight trains and cross-border transport models. The combined optimization of intercontinental transport scheme and regional transport scheme is constructed, which is composed of tractor, semi-trailer and intercontinental railway intermodal transport. The transport network of this model consists of two types of nodes: multimodal transport station and highway transport station. Based on the double difference regression analysis of gravity coefficient, it is concluded that the central attractiveness of trade between China and the rest of the world is relatively low in the past, but under the overall downward trend of trade attractiveness between China and the rest of the world, the China-EU train has significantly promoted the growth of trade in recent years, which is attractive.
Implementation of PMF and FFT Acquisition Design for B1C Signal Based on ASPeCT
Authors: Liu Xianyang , Yin Chengxiang , Yu Qian , Li Bochen
Published: June 2021

According to the characteristics of BDS B1C signal, there are many sub peaks in the autocorrelation characteristics, which leads to the ambiguity of B1C signal acquisition. In this paper, the characteristics of B1C signal, acquisition strategy and the ambiguity of different acquisition strategies are analyzed. Based on ASPeCT algorithm, PMF and FFT is implemented in FPGA of navigation receiver. The B1C signal is generated by spiren gss9000 satellite signal simulator, and a test scenario is built for the navigation receiver, which proves the effectiveness of B1C signal acquisition.
Application of Reliability Simulation Based on Monte Carlo Method in GNSS Receiver
Authors: Liu Ningbo , Guan Yu , Liu Xianyang , Liu LiHong , Wang Haiyue
Published: June 2021

At present, the analytical method (reliability prediction) is mainly used to calculate the equipment reliability of electronic equipment system. But reliability verification and evaluation of electronic equipment, which is highly reliable, needs a lot of time and economic costs. In this paper, a reliability simulation algorithm based on Monte Carlo method is proposed to verify and evaluate the reliability of highly reliable GNSS receiver. Which can meet the requirements and greatly reduce the project cost.
The Study of Privacy Protection of Scientific Data Sharing Based on Data Life Cycle
Authors: Song Dacheng , Chen Ming , Fan Sheng
Published: June 2021

Scientific data sharing has become an important activity to promote modern research findings in which helps to reduce costs and save time for data collection, but it also brings certain privacy issues when using scientific data. First, based the network and literature survey method to described the basic conceptual of scientific data sharing, and discussed the issues of privacy violation in scientific data sharing during the data lifecycle. Second, tried to propose a privacy protection model and framework to prevent privacy violation. Finally, provided some suggestions for the current privacy protection in scientific data sharing from different perspectives. The study contributes to the scientific data sharing by shedding light on how to protect privacy of scientific data sharing through the privacy protection model and framework.
Influence of the drying method on the structure of aluminum oxide capillary-porous nanomembranes
Authors: Batalova M S , Korobova N E , Alpysbayeva B E
Published: June 2021

Porosity characteristics are widely used to assess the internal structure of nanomembranes. The membrane was considered complex in the analysis of the structure. The membrane was presented in a simplified way as a system interacting with a dispersion medium, for example, water. A physicochemical model of the membrane has been proposed, which allows one to study the logical and structural similarity between systems, the properties of which are known, with similar systems, but with unknown properties. We have chosen a simple mechanical model of a membrane permeable to liquid and gas molecules. Permeability was determined by the characteristics of the porosity, shape, and size of the pores.
Flame sprayed and plasma sprayed Al2O3-TiO2 coatings
Authors: Blinkov I V , Belov D S , Laptev A I , Anikeev A S , Ivanov V V
Published: June 2021

Al2O3–TiO2 coatings were received by flame sprayed of flexible cord and plasma sprayed using powder. Shown higher mechanical and tribological properties of flame sprayed coating compared plasma sprayed coating.
Rheological properties of suspensions of nanoparticles based on polyethylsiloxane
Authors: Dembelova T S , Badmaev B B , Makarova D N , Vershinina Ye D
Published: June 2021

Suspensions of nanoparticles of silicon dioxide in polyethylsiloxane liquid used in engineering as greases and instrument oils have been synthesized. The effective viscosity of nanosuspensions depending on the shear stress was determined by the acoustic resonance method using a piezoelectric quartz resonator. An increase in the strength of the structure of nanosuspensions due to the formation of a supramolecular structure has been shown.
Research of hydrogen saturation of magnesium and magnesium-aluminum films and the influence of a protective nickel coating on it
Authors: Ivanov A G , Karpov D A , Chebukov E S , Yurchenkov M I
Published: June 2021

Experiments on the hydrogenation of Mg-Al films during their deposition by magnetron sputtering in a hydrogen atmosphere and subsequent gas-phase hydrogenation have been carried out. The hydrogen mass content and the rate of hydrogen desorption from the obtained metal hydride films have been determined. The key effect of the nickel protective coating on Mg-Al films for their use in hydrogen film accumulators is shown.
Cleaning substrates and subsequent deposition of coatings with coaxial magnetron discharge
Authors: Kalandiia M R , Trofimov V N , Yakushkin A A , Sokolov A V , Isakov A O
Published: June 2021

The created experimental magnetron sputtering system allows preliminary cleaning of the substrate surface and subsequent deposition of coatings on long cylindrical products within a single system using a coaxial magnetron discharge at a working gas pressure of 150 mTorr. The coating discharge has reverse electrodes polarity relative to the cleaning discharge. A theoretical calculation of the discharge parameters has been carried out.
Thermal processes during friction and wearing of medium carbon steel after plasma electrolytic processing
Authors: Komarov A O , Smirnov A A , Mukhacheva T L , Kusmanov S A
Published: June 2021

The thermal state of a frictional contact with varying normal loads and sliding speeds of a friction pair after plasma electrolytic processing is considered. It is shown that an increase in the temperature of the frictional contact decreases the coefficient of friction, and the wear rate of the tribointerface increases with an increase in the temperature of the frictional contact.
Discharge parameters of a magnetron with a molybdenum target
Authors: Kraynov N S , Sharipov A A , Shapovalov V I
Published: June 2021

In this work, we study the features of the discharge of a magnetron with a cold molybdenum target in an argon environment using a Langmuir probe. The novelty of this work is due to the placement of the probe near the anode. I-V characteristics of the probe were measured in the range of discharge current densities of 27–96 mA/cm2 at argon pressures of 2 – 4 mTorr. The experimental I-V characteristics of the probe were used to calculate the electron temperature, ion and electron density. It was found that the density of charge carriers increases and the electron temperature decreases with an increase in the discharge current. In addition, it was found that the density of ions near the anode is almost an order of magnitude lower than the density of electrons, and the electron temperature weakly depends on the argon pressure.
Possibilities of combining plasma electrolytic nitriding and polishing of steel by varying the operating voltage
Authors: Kusmanov S A , Zhirov A V , Dyakonova A D , Tambovskiy I V , Mukhacheva T L , Dyakov I G , Silkin S A
Published: June 2021

The possibility of realizing surface plasma electrolyte modification of the steel surface by successive diffusion saturation and polishing by changing the value of the applied voltage is shown. The composition, structure and properties of the formed coating have been studied.
Obtaining of Nd-Co films by electrolysis in a chloride-fluoride melt
Authors: Markovich S I , Popova A V , Semushin V V , Kuznetsov S A
Published: June 2021

The electrodeposition of neodymium on a cobalt substrate in a chloride-fluoride melt NaCl-KCl-10 wt.% NaF-5 wt.% NdF3 was studied. It is shown that during electrolysis, a coating with a crystal size of 2-5 microns is formed. Microanalysis of the coating determined the electrocrystallization of intermetallic compounds Co17Nd2 and Co5Nd on a cobalt substrate.
Obtaining of TiSiCN coatings by anodic evaporation of titanium and decomposition of hexamethyldisilazane in a low-pressure arc discharge
Authors: Menshakov A I , Bruhanova Yu A , Skorynina P A
Published: June 2021

The method of TiSiCN-coatings deposition by anodic evaporation of Ti and decomposition of an organosilicon precursor (hexamethyldisilazane) in a low-pressure (∼1 mTorr) nitrogen-argon arc discharge with a self-heated hollow cathode is investigated. The plasma composition was analyzed by optical emission spectroscopy. TiSiCN coatings with a thickness of up to 10 microns and a hardness of up to 30 GPa were obtained in 1.5 hours at a temperature of 400°C.
Deposition of solid solution films using reactive magnetron sputtering of a sandwich target
Authors: Shapovalov V I
Published: June 2021

This work presents a magnetron with a sputtering unit (sandwich target). The novel-$$$ty of the work is due to the three parallel plates of different metals included in the unit. They are mounted on the same axis with the magnetron and rigidly attached to it. The unit is located in a reactive environment consisting of plasma-forming argon and reactive gas (nitrogen, oxy-$$$gen, etc.). The lower plate is cold, while the middle and outer ones operate in the hot target mode. In the erosion zone of the middle and outer plates, eight slits were made. They are locat-$$$ed on the same axis and symmetrically relative to their center. The lower plate is sputtered through these slits. A magnetron with the above sandwich target can be used for the synthesis of composite films of the three-compound solid solutions. The possibility of synthesizing Ti
x-
Mo
y
Cr1–

x–y
N films with a continuous change in the stoichiometric coefficients x and y due to the change in the current density and relative areas of the slits, which provide a smooth change in the hardness of the films, is shown.
Dielectric relaxation in water of the adsorption layer on the surface of a solid
Authors: Simakov I G , Zh Gulgenov Ch , Bazarova S B
Published: June 2021

The influence of temperature and interphase boundary energy on the dielectric relaxation parameters in adsorbed water was investigated within the framework of thermodynamic consideration. It is shown that accounting for the interfacial boundary energy greatly increases the orientation dielectric relaxation time in adsorbed water. This allows us to determine the dispersion of the dielectric characteristics of adsorbed water using Debye’s relaxation theory.
Investigation of the influence of the nature of surface deformation on coating adhesion
Authors: Yakupov S N , Gubaidullin R I , Yakupov N M
Published: June 2021

The effect of deformation of the surface of a supporting metal element on the adhesion of a thin polymer film has been studied by an experimental-theoretical method. A setup has been developed that allows testing of adhesive coatings at various deformations of the substrate surface of various materials. The adhesion properties of a polymer film to a metal substrate have been determined. An explanation of the results obtained is given.
Evaluative analysis of traffic guidance forecasting system based on DTW algorithm——With the big data era as the background
Authors: Tao Mengyao , Liu Chaohong
Published: June 2021

With the development of the economy and society and the improvement of transportation infrastructure, the number of motor vehicles and the flow of road vehicles have increased rapidly, resulting in traffic congestion and frequent traffic accidents, which not only affects the efficiency of road traffic, but also affects the realization of social benefits as a whole. Based on this, services such as road condition prediction and real-time road condition detection came into being. In order to study the difference between the predicted value and the real value, this article selects the domestically used AutoNavi map platform and the Baidu map platform as the research objects, and calculates the relevant values. The predicted value provided by the AutoNavi platform is the same as that provided by the Baidu map platform. The real-time detection values were compared, and at the same time, the relevant index in the Baidu map platform was used in the calculation, and the index weight formula was proposed, and the problems in the relevant prediction were found. According to the actual background of the problem, suggestions are made for traffic congestion prediction and smart city construction.
RFID E-plate Data based Travel Time Reliability Estimation of Urban Expressway
Authors: Zhong Siyuan
Published: June 2021

Travel time distribution shows the aggregation degree of vehicle travel time in road network, and travel time reliability is the key index to measure the aggregation degree of travel time. In order to quantitatively evaluate the fluctuation of travel time of expressway vehicles, it is necessary to establish an estimation method of travel time reliability of expressway. Travel time reliability estimation needs to obtain travel time data of vehicles. Traditional Global Position System (GPS) and video detection methods are easily affected by external factors such as weather and environment, and the description of travel time distribution is not comprehensive under the condition of low permeability. On the other hand, in the evaluation of travel time reliability, although there are lots of travel time probability distribution models, the correlation of vehicle travel time between links is ignored when calculating travel time reliability. In order to estimate travel time reliability more accurately, based on Radio Frequency Identification (RFID) electronic license plate (E-plate) data, this paper proposes a path travel time reliability evaluation model considering travel time correlation between links. First, the RFID readers installed on the gantry of expressway acquires data from the electronic tags deployed on vehicles. Secondly, a percentile travel time estimation method is proposed based on Cornish-Fisher expansion and the skewness of travel time distribution. Finally, considering the reliability estimation of travel time under the correlation of links, the estimated value is closer to the true value. The experimental results show that the travel time reliability estimation method considering the correlation between links improves the accuracy of estimation in the expressway network environment.
Big data and Artificial Intelligence Drive Human Resource Management Innovation Research
Authors: Xuanbei Shi
Published: June 2021

The arrival of the era of artificial intelligence and big data is subtly changing people’s production and life. This article mainly studies and analyzes the results of previous surveys. The impact of big data and artificial intelligence on human resource management has led to more diversified employee training methods, more oriented performance management, and more diversified welfare management. Effective use of big data and artificial intelligence can better optimize business management and improve market core competitiveness.
RETRACTED: Application of Big Data Blockchain Technology in Financial Support of Real Economy
Authors: Hui Feng
Published: June 2021

In the era of big data, the development of Internet technology has caused earth-shaking changes and innovations in various fields of the financial industry. Especially in the financial market, big data has become an important research topic. It can accelerate the deep integration of Blockchain technology with the most advanced information technologies such as artificial intelligence, big data, and the Internet of Things, as well as the in-depth integration with the real economy, and innovatively solve the “trilemma” of difficulties in loan financing for small and medium-sized enterprises, difficulties in bank risk control, and difficulties in departmental supervision. It can provide a way for the application and innovation of Blockchain, and it can also provide assistance for the development of the financial industry. Therefore, how to make good use of big data and better integrate it into the operation of the financial industry is the primary issue at present.
Feature coding method based on shared weights support vector data description for face recognition
Authors: Liao Mengmeng , Li Yunjie , Gao Meiguo
Published: June 2021

In this paper, we propose a feature coding method based on shared weights support vector data description (FCM-SWSVDD). The proposed process of FCM-SWSVDD is as follows. By considering the density information of the clusters and introducing the weighting learning, we propose an improved support vector data description (SVDD), named shared weights support vector data description (SWSVDD). SWSVDD can obtain the cluster center and cluster radius more accurately. Incorporating SWSVDD and the triangle coding into the same feature coding learning process, FCM-SWSVDD is proposed. After the features of those images are extracted by using FCM-SWSVDD, a sparse representation classifier is used to classify those features. Experimental results show that the performance of the proposed method exceeds many methods.
Analysis and evaluation of relevant influencing factors based on the big data of Douyin live broadcast sales
Authors: Cui Faqiang
Published: June 2021

In order to explore the influence of live broadcasters’ own factors on the effect of live delivery, we conducted field surveys of no less than 1680 minutes for live broadcasters and audiences participating in live events on the Douyin platform for 14 consecutive days. We also collected 488 valid questionnaires through online surveys, and used Eviews10.0 software to analyze the collected primary data. The results proved that the optimization of the live broadcaster’s image and the improvement of the interactive effect of the live broadcaster can better stimulate the consumers who participate in the live broadcast and continuously increase their consumption quota and consumption times. Through research, the live broadcaster has finally achieved the goal of improving the ability to carry goods by optimizing himself.
Application of explainable machine learning based on Catboost in credit scoring
Authors: Qi Ji , Yang Ruicheng , Wang Pucong
Published: June 2021

Credit scoring is the core part of an institution’s lending. As artificial intelligence is used in various fields, credit rating is also under the same topic of accepting technological changes. Combining credit evaluation and machine learning can incorporate relatively comprehensive features into the credit evaluation process. Through the excellent performance of Catboost, while ensuring accuracy, it demonstrates the explainability of the model as much as possible, avoiding the traditional trust problem of the black-box model. Explainability is proposed to the machine learning model, which reduces the difficulty of processing large amounts of data and the threshold for non-professionals to understand the model. In this article, the dataset is the personal loan data of LendingClub obtained through python. By analyzing the data through Catboost, we can derive excellent results in applying the explainability of machine learning in personal credit evaluation.
A Multi-dimensional Scientometrics Analysis on Alfalfa Research
Authors: Zhu Heying , Zong Yanxiang , Yang Yanping , Li Huoyou , Dong Yu , Wu Qingqiang
Published: June 2021

Alfalfa is known as “the king of forage”. It not only has high yield, but also has good quality. Studying the development process of alfalfa will help scholars in this field grasp the future research direction. In this paper, the data of alfalfa field from 2009 to August 14, 2020 retrieved on Web of Science is taken as the research object. Firstly, this paper analyses the current research status by using basic statistical methods. The selected analysis dimensions include time, country, funding source etc. Then, we conduct topic clustering research based on Latent Dirichlet Allocation (LDA) model and the scientometrics method to compare and analyze its interests from both the overall and time perspectives. Finally, the experimental results are presented in diagrams. The results reveal that the development of alfalfa field tends to be stable. China and the United States have made remarkable achievements in the field of alfalfa. The topics integration and decomposition trend is weak, and the research content has strong coherence.
Improving the Transferability of Adversarial Examples with Image Affine Transformation
Authors: Yin Heng , Zhang Hengwei , Li Zheming , Liu Zhilin
Published: June 2021

Deep learning is widely regarded as a black-box technology. We all know its performance is very good, but we have limited understanding of why it is so good. At present, there are many researches on the interpretability of deep neural network. By studying adversarial example, we can understand the internal semantics of neural network and find the decision boundary with problems, which in turn helps to improve the robustness and performance of neural network and its interpretability. With the development of adversarial example research, more and more adversarial example generation methods are proposed. Although the attack from adversarial example poses a great security threat to the deep learning system, it can also be used as an effective tool to measure the robustness and reliability of the model, and the attack and defense are two mutually promoting processes. Therefore, how to generate adversarial example with stronger attack ability is worth further study. And this study proposes a method named Affine-Invariant Method, aimed to improve the transferability of adversarial examples in black-box environment.
The application of big data in the analysis of the impact of urban floods: A case study of Qianshan River Basin
Authors: Shao Weiwei , Su Xin , Lu Jie , Liu Jiahong , Yang Zhiyong , Cao Yongqiang , Yang Zhaohui , Wang Kaibo
Published: June 2021

In recent years, with the acceleration of climate change and urban modernization, the flood risk of economic and social development has increased. The problem of urban flood disasters needs to be solved urgently. It is particularly important to conduct flood disaster loss assessment research for further flood control and disaster reduction, and emerging big data have opened a new direction for solving the problem of urban flooding. In this study, the Qianshan River Basin in Guangdong Province was used as an example. The TELEMAC model was used to simulate the inundation process under the design rainstorms of 50a and 100a in the Qianshan River Basin. Based on the heat map service, route planning service, and search service functions of Baidu Maps and Amap open platforms, this study used crawler technology to integrate multi-source data, including traffic survey data, geospatial data, population heat map data at different times (day/night) on weekdays and non-weekdays, and point of interest (POI) data from various industries. A dynamic assessment model of flood disaster loss for traffic, population, and POIs was constructed. The research results could greatly improve the timeliness and accuracy of urban flood disaster analysis, early warning, monitoring, and disaster risk assessment.
Smart Campus Microservice Recommendation Algorithm Based on Neighborhood Clustering and Time Collaboration
Authors: Lian Jin , Gao Ming
Published: June 2021

The basic algorithm research of smart campus construction is the basic path for education to benefit from the development of science and technology. Based on the application environment of higher education teaching and management, according to the teaching periodicity and the closed-loop characteristics of the business system in universities, a neighborhood-based user attribute clustering algorithm is used in this paper to form user clusters, which are coupled micro-application clustering with periodic time. Finally, through normalized conversion and Pearson correlation coefficient analysis, the Top-N recommendation list is obtained, and a recommendation algorithm suitable for smart campus microservice system is constructed. In this paper, matrix sparsity and cold start are discussed, and data compensation is carried out by analyzing the general behavior patterns of teachers and students, which effectively solves the problem of insufficient recommendation list caused by matrix sparsity and cold start. Upon data analysis before and after the algorithm deployment, the algorithm effectively reduces the number of times that users use the search function.
Edge detection algorithm of medical image based on Canny operator
Authors: Xu Ziqi , Ji Xiaoqiang , Wang Meijiao , Sun Xiaobing
Published: June 2021

Edge detection is an important part of image segmentation, in this paper, the edge detection algorithm based on traditional Canny operator for medical images is studied. The Canny operator is improved using Otsu algorithm and double-gate limit detection method, and the ability of Canny operator edge detection is strengthened. The simulation of the algorithm is realized on the computer platform by MATLAB, and the experimental results are analyzed from two image objective evaluation indexes of information entropy and mean square error. The experimental results show that compared with the traditional Canny algorithm, the improved adaptive double threshold Canny algorithm has better edge detection effect, richer image details, better noise suppression and less false edges.
Credit decision system based on combination weight and eXtreme Gradient Boosting algorithm
Authors: Youlve Chen , Kaiyun Bi , Jiangtian Chen
Published: June 2021

According to the demand of bank credit business, a credit decision system is established. The system mainly uses principal component analysis and eXtreme Gradient Boosting algorithm to establish a credit risk assessment model. When calculating the index weight, it proposes a more accurate method: combination weight method, which combines the advantages of entropy weight method and expert scoring method to calculate the relatively accurate weight. Then, the credit risk of each enterprise is analyzed quantitatively. Through the results, we give the corresponding credit strategies of banks in different situations.
Image Segmentation of Pitaya Disease Based on Genetic Algorithm and Otsu Algorithm
Authors: Yan Haokun , Ma Jiachen , Feng Zejing
Published: June 2021

Aiming at the problem of using traditional Otsu algorithm to segment pitaya disease images, this paper proposes the Otsu algorithm combined with genetic algorithm. The maximum variance between classes obtained by Otsu is calculated as the fitness value of the genetic algorithm to improve accuracy and improve efficiency of optimization. The experimental results show that the segmentation accuracy and efficiency of the algorithm in this paper are higher, and it has certain practical value.
Research on the impact of Credit, Brand and Service Recovery on Online Sales Based on Web Crawler Technology and Regression Analysis Methods
Authors: Luo Mi , Lin Jianzong
Published: June 2021

In order to explore the relationship between credit, brand, service recovery and the merchandise sales in online transactions, based on web crawler technology and regression analysis methods, the paper empirically analyzes the co-influence of credit, brand and service recovery on online merchandise sales volume by using the data of Baijiu in Tmall platform. The research results show that seller credit score has a significant positive effect on online merchandise sales volume; Merchandise brand has no significant impact on online merchandise sales volume, but brand as a moderator has a significant positive effect on the relationship between seller credit score and merchandise sales volume; The seller’s service recovery has no significant influence on the sales volume of online merchandises.
Optimal Network Defense Decision-making Method Based on Delay-Time Differential Game
Authors: Mi Yan , Zhang Hengwei , Sun Pengyu , Wang Jindong
Published: June 2021

In the process of attack and defense, there will be a period of delay in the implementation of the decision-making and strategy, therefore, the paper is based on the theory of the dynamic and time-delay differential game theory, and puts forward the network security status evolution model, and puts forward the network attack defense delay differential game model, and the design of the method of the optimal defense strategy of the most optimal defense strategy is designed, and the optimal decision is achieved. Finally, the validity of the model and the algorithm is verified by experiment.
An Improved Just-in-time-learning Based Soft Sensor Method Using Dimensionality Reduction Analysis
Authors: Chen Yu , Ye Tong
Published: June 2021

In recent years, the data-driven soft sensor has achieved unprecedented development, which can update the model in real-time and save many costs. Most traditional methods are only suitable for single-mode processes, but the existing working conditions are generally multi-modal. In this paper, we propose an improved JITL method to modeling the complex industrial process. First, we apply AE to reduce the data dimensionality, exploring the intrinsic structure of data. Then a JITL strategy is adopted to select similar samples on the low-dimensional data and use them for the local model. Finally, PLS is developed for each model and predicts the variables. A three-phase flow case verifies the effectiveness of the proposed method. We find that compared with other methods, the proposed method has the highest accuracy.
Remote sensing inversion modeling of chlorophyll-a concentration in Wuliangsuhai Lake based on BP neural network
Authors: Fu Xueliang , Liu Wenyao , Hu Hua
Published: June 2021

Monitoring chlorophyll-a concentration in Wuliangsuhai Lake can effectively grasp the primary production of Wuliangsuhai Lake. The traditional manual sampling monitoring method is time-consuming and laborious, compared with the monitoring method, the monitoring range of chlorophyll-a in lake water by remote sensing is not only wide, long time sequence, but also lower than that of the original. Based on the Landsat 8 remote sensing image data of Wuliangsuhai Lake and the measured data of chlorophyll-a concentration sampling points in Wuliangsuhai Lake, the spectral reflectance of each sampling point was extracted through the longitude and latitude coordinates of each sampling point, the first to fifth band spectral reflectance combination of Landsat 8 remote sensing image data is used as input, and the measured chlorophyll-a concentration is used as output, 26 BP neural network models were constructed to Retrieve Chlorophyll-a Concentration in Wuliangsuhai Lake. Through the verification and analysis of all the models, it is found that the inversion model with spectral reflectance of band 1, 2, 3, 4 and 5 as input has the best performance.
WGCNA revisited: Module indetification
Authors: Yan Shaomin , Wu Guang
Published: June 2021

WGCNA is a very popular R language software package used in biomedical field. It is mainly designed to deal with gene microarray samples to find clusters (modules), which include highly correlated genes, in biomedical studies. Theoretically, it results in the hierarchical modules, which are different from the results based on the edge density inside module and outside modules. In this study, we address this difference and indicate that caution should be exercised when using these two methods to interpret the implication of studies.