bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of Simulation Control Automation Tool Based on Android Accessibility Service
Authors: Xie Nan , Ni Yiran , Liu Xiaoxiao , Cao Yu , Chen Weimin 
Published: April 2021

Abstract
With the development of Internet plus era and the increasing popularity of mobile phone in China, people still use the traditional finger touch mode. However, in the face of some application scenarios with high repetition frequency, an automatic control method can be built to reduce repetitive operation of users. This paper introduces how to solve the problem of automatic control process for Android operating system, and provides a complete solution for the design and construction of automation tools. Starting from the wake-up of the device, the system automatically unlocks, and then uses intent to transfer parameters to start the target application and specify the activity. After entering the specified application interface, the tool will scan the XML information of the interface layout drawn by the system, and accurately capture the view control through the regular matching of attribute values and other information of the control. Finally, the control object can be operated by simulating events, so as to achieve the same effect as the user operation. In addition, the automatic control tool obtains the control information accurately through OCR identification, and realizes the multithreading cycle operation through the delay start function, which improves the operation efficiency of the tool automation degree and the user operation efficiency of the smart phone.
Virtual Tourism Simulation System Based on VR Technology
Authors: Hou Tingfei 
Published: April 2021

Abstract
With the development of tourism, the number of tourists in China has reached 6.7 billion every year. In order to alleviate the problem that the number of tourists in domestic popular scenic spots is too large to bear the burden, 3dsmax modeling software is used to realize 3D terrain and building wood construction, and unity3d platform is used to integrate to get 3D virtual scene. At the same time, the virtual tourism simulation system based on VR technology is realized by using VR hardware equipment in this paper, through the simulation of a park scene, the participants are investigated by questionnaire, and the function of the system is tested. The simulation system can meet the needs of tourism and provide a good direction for the future development of tourism.
Research on Optimization Methods of Public Grassroots Governance Based on Big Data Analysis
Authors: Cui Dandan 
Published: April 2021

Abstract
With the continuous progress of the society and the continuous improvement of the people’s level, the social mechanism is gradually sound, people also put forward higher requirements for public grass-roots governance. The development of science and technology, especially the emergence of artificial intelligence, provides convenient conditions for the expansion of the field of big data(BD), and BD analysis is gradually applied to various fields. At present, public grass-roots governance is faced with many difficulties due to its wide scope and complex content. Using BD for analysis provides more convenient conditions for promoting the optimization of public grass-roots governance methods. In recent years, the BD analysis and basic research deepening and expanding public governance scheme, we can conclude the traditional grassroots governance is to stay on the surface, there is no grass-roots level, the optimization study is based on analysis of large data base, only combined with digital information, through data analysis to improve work efficiency and better achieve better control effect. By studying the public grassroots governance based on BD analysis, this paper analyzes the existing problems of public grassroots governance under the background of BD, proposes solutions according to the existing problems, and continuously realizes the optimization of public grassroots governance methods.
Neural network model based on travel planning for travel time prediction
Authors: Xu Weixiang , Rong Weiyao 
Published: April 2021

Abstract
The development of smart cities presents new challenge to more convenient and intelligent transportation, while the advent of big data era promotes the sharing of travel data, which provides powerful data support for the development of smart travel. As an important part of smart travel, accurate travel time prediction is definitely crucial. Different from traditional passive forecasting methods which is only based on historical data, this paper proposes a Conv-LSTM network model based on travel planning data for travel time prediction from the perspective of user travel. This model can actively predict the upcoming traffic state according to the upcoming data generated by the user’s travel planning information released before travel. Specifically, we first introduce the definition of travel plan and how to calculate the future planned flow according to travel planning information. Then, the future planned data and the corresponding segment historical data are introduced into the designed Conv-LSTM model to extract spatial-temporal features and then realize the prediction of road travel time. In this study, specific travel path is taken as the research object. Extensive experimental results demonstrate that this method has high accuracy, and remarkably outperforms benchmark methods in various metrics.
Overview of Image Smoothing Algorithms
Authors: Li Pei , Wang Hongjuan , Yu Mengbei , Li Yeli 
Published: April 2021

Abstract
In the process of image generation and transmission, it is easy to be polluted and affected by various kinds of noise, which reduces the quality of the image. In order to avoid the adverse effects of image processing and image visual effect, we can use image smoothing technology to improve the adverse effects, so as to make the image clearer. There are a variety of image smoothing techniques, which had great smoothing effect, but there are also different defects. Based on the analysis of different noise models, this paper uses mean smoothing, median smoothing, Gaussian smoothing, bilateral filtering and other techniques to study and analyse the image processing algorithm, the implementation method and efficiency, which provides efficient theoretical value for image processing and image visual effect in various fields involved in image processing.
Study of Gender-based Playing Style Stereotype in Overwatch using Machine Learning Analysis
Authors: Zhou Ralph Jinghao , Gao Yumeng , Han Qian 
Published: April 2021

Abstract
Since its release in 2016, Overwatch has become a game with a high amount of daily users (over 50 million users Worldwide) and made a great amount of profit for the company that produced it — Blizzard. However, it is common that the stereotypes and biases hide under the popularity of the games. In past researches, it is shown that gender could affect the designs, abilities, and player’s view of in-game characters. In this research, a survey regarding gender stereotypes in Overwatch is conducted, and statistical and machine learning methods are applied to analyze the results. The result suggests that many of the players in the game had given biased or stereotypical actions or thoughts toward female players. Simultaneously, we propose an Ensemble Late Fusion (ELF) method that unifies the weighted predicted probabilities generated from various state-of-art classifiers to classify the player behaviors with or without gender-based stereotypes in Overwatch. The experimental results show that when using ELF, the optimal classification result reaches AUC to 0.9044, which beats several well-known traditional machine learning and deep learning classifiers. Moreover, the connection between certain biased ideas and rather a user in sexist is graphed and discussed in the paper.
Research on the Application of Computer Technology in Music Creation
Authors: Liu Chuanli , Wei Lizhi , Chen Libin 
Published: April 2021

Abstract
Along with the development of science and technology, computer technology is not only widely used in manufacturing, IT, construction, e-commerce and other industries, but also rapidly popularized in the creation and dissemination of music. The introduction of computer technology makes music more possible in writing, polyphony, harmony and secondary creation. In a sense, computer technology can not only enrich the means and forms of music creation, but also be an essential factor in the production and development of modern music. In view of this, this paper analyzes the advantages of computer technology in music creation, and systematically explains the specific application of this technology in music writing, harmony practice, orchestration and so on.
Research Based on The Improved Grey Wolf Optimization Algorithm
Authors: Jia Shaoyong , Sun Shibao , Wang Jing , Xu Fengkui 
Published: April 2021

Abstract
With the continuous progress of machine learning methods, more and more methods are widely used in various fields. Grey Wolf Optimization Algorithm (GWO), as a kind of population algorithm, has become a research hotspot in recent years because of its good optimization ability. Similar to other population algorithms, gray wolf optimization algorithm itself has the problem of imbalance between global search and local search capabilities. In order to solve this problem, the following improvements are proposed to the standard gray wolf optimization algorithm: First, change the decrement method of the convergence factor and adopt a non-linear decrement method to meet the actual search process; At the same time, a weighting strategy is introduced to dynamically assign weights to the guide wolves. It can ensure that the population jumps out of the local optimal solution. In order to verify the effectiveness of the improved algorithm, an international general test function is selected for simulation. The simulation results show that the improved gray wolf optimization algorithm has faster convergence speed, higher solution accuracy and better stability.
Statistical measure researches for the impacts of COVID-19 on Shanghai Securities Composite Index: based on mode regression model using skew-normal distribution
Authors: Zeng Xin , Ju Yuanyuan , Wu Liucang 
Published: April 2021

Abstract
The economy of China has been affected by the COVID-19 and it is necessary to measure and investigate it. The mode regression model and its data deletion model using skew-normal distribution are established via the industry sub-index data of Shanghai Stock Exchange. Statistical diagnosis method of the model is proposed by using Pena distance diagnosis statistics, and the unknown parameters are estimated by the EM algorithm facilitated by gradient descent (GDEM) method. The results show that the outliers are accurately identified by the proposed statistical diagnostic method, and parameter estimation results indicate that the contribution of all industries to economy during the COVID-19 is lower than before, among which industry and commerce are the hardest hit.
OCR Service Platform Based on OpenCV
Authors: Cai Jianjun , Sun Erxin , Chen Zongjuan 
Published: April 2021

Abstract
This paper builded an ocr service platform based on opencv. Cut images of license plates and characters were generated by analyzing and processing the images based on the opencv algorithm and utilizing the image big data accumulated in the production of application software in the automobile industry. Label these cut images as training data and input SVM, ANN and other trainers to train the model to recognize the characters in the new license plate image. In addition to license plate recognition, vin code recognition, driver’s license number recognition and other ocr functions can also be developed in a similar way. The platform is developed based on java language and springboot framework in order to be technically unified with other automotive industry application software. It needs to use java to call opencv c++ interface implementation, and the platform provides rest interface externally.
Research on Performance Testing Technology Based on Scenario Design
Authors: Hui Zhang 
Published: April 2021

Abstract
With the rapid development of web system application, performance testing is very important to ensure the fault free operation of web system. The scenario design in performance testing is the basis of performance testing. Only reasonable design of test scenarios can obtain valuable test data. This paper starts from the web performance testing, explains the function and design of performance testing scenarios, then analyzes the common performance testing scenarios, and finally carries out web performance testing practice through testing tools. The experimental results show that the performance test of different scenarios can help to find out and solve the main problems in the web system, and provide an effective basis for system optimization.
Structural Change and Mode Innovation Based on Recommendation Algorithm and 5G Technology -- a New Format Brought by Streaming Media for China’s Documentary Industry
Authors: yinjun Wu 
Published: April 2021

Abstract
The streaming media platform represented by Netflix is constantly promoting the vertical integration of content and platform providers by using algorithms and data, changing the previous transmission mode of documentary. Documentary is no longer limited by the schedule threshold of traditional media and film festivals. It has a wider transmission channel and obtains positive marketing under the agenda setting. Virtual reality technology and Web online interaction technology will also change documentary from recording the reality to experiencing the reality in the future. With the introduction of Netflix algorithm and mode, the industrial trend in North America will also affect the documentary production in Chinese speaking areas. Compared with the documentary industry in North America, this paper predicted the structural changes and mode innovation of Chinese documentary industry brought by streaming media algorithm and technology, and discussed the opportunities and challenges that Chinese documentary creation will face in the streaming media era.
Analysis of Mobile Push Service Model of Smart Library Based on Big Data
Authors: Shu Zongying , Jiang Yiqun , Liu Jia , Wang Maohan 
Published: April 2021

Abstract
[Purpose / Significance] With the development of big data, massive data resources appear. Smart library should provide more personalized services to better meet the needs of users. [Method/Process] This article analyzes the characteristics of smart library services. It includes precision, timeliness, interactivity and personalization. [Result / Conclusion] This paper analyzes the development opportunities of knowledge push service in Smart Library, and establishes the mobile push service model of Smart Library.
Analysis of shock calculation based on Newmark integral method
Authors: Chen Benlan 
Published: April 2021

Abstract
In this paper, the time domain method for the calculation of impact resistance is studied. Firstly, the central difference method and the Newmark integration method based on the analysis of the linear equations and the solution of the nonlinear equations are educed. Then, the advantages and disadvantages of these two methods are compared and analyzed, and the conclusion is that the Newmark integral method is suitable for the calculation of the non dynamic equation.
Asymmetry analysis of melanoma based on ABCD rule
Authors: Zhang Guolan , Guo Siwen 
Published: April 2021

Abstract
Malignant melanoma is a malignant tumor that is extremely harmful and prone to lymphatic metastasis. If it cannot be diagnosed and effectively treated at an early stage, it will cause irreversible consequences. There is a lot of evidence that if you can get the exact treatment in the early stage, it can effectively improve the recovery rate. At this stage, clinical diagnosis of melanoma is mainly performed manually, which has defects such as low overall efficiency. This article is based on ABCD rule, combined with the clinical features of melanoma in dermoscopic images, to determine the benign and malignant melanocytes. Firstly, the image processing technology and pattern recognition technology are used to acquire and preprocess the dermoscopic image, and the image feature points are extracted. Then, the microscopic asymmetry and macroscopic asymmetry of the image were analyzed. Finally, the symmetry score was calculated by TDS to judge the benign and malignant of melanocytes. It is expected to assist dermatologists in diagnosing melanoma, provide timely feedback information to patients and provide targeted treatment for patients, improve the efficiency and accuracy of medical clinical diagnosis, achieve the purpose of curing, and reduce the harm of melanoma to human health.
Global asymptotic stability for neutral-type Hopfield neural networks with multiple delays
Authors: Wu Fei 
Published: April 2021

AbstractThis paper aims to study stability problem for neutral-type Hopfield neural networks including multiple time delays in states and multiple neutral delays in time derivative of states. The stability criteria cannot be derived by linear matrix inequality since the networks cannot be transformed into the vector-matrix form. By constructing LyapunovKrasovskii functional and using inequality techniques, novel stability criteria of global asymptotic stability are established. Finally, an example is given to show the effectiveness of the theoretical result.
RETRACTED: A Practical Research on the Online Learning Mode of Business English Majors under the Background of “Internet+”
Authors: Tang Jianfeng 
Published: April 2021

Abstract
In the context of “Internet +”, we need to strengthen research on the application of the online learning model for business English majors. This article analyzes the various effects of online learning models on business English majors. This article will discuss the shortcomings in the application of the current online learning model for business English majors. Only by mastering relevant materials can we propose effective practical strategies, improve the application level of online learning models and students’ learning effects, and give full play to the positive role of Internet technology in the teaching of business English.
Research on the relationship between e-commerce ratings and reviews based on Naive Bayes
Authors: Qin Zeqing , Wang Zesong 
Published: April 2021

Abstract
With the popularization of the Internet, online shopping has gradually replaced traditional shopping methods. Product ratings and comments from buyers have become important indicators for users when purchasing products. Because of this, the behavior of employing someone to rate high, known as click farming, has gradually risen. To deal with this phenomenon, users pay more attention to the content of the review itself rather than the score to make judgments. Then why are the stores still keen on employing click farm? We think that the high scores seem to play a guiding role in the user’s comments. To explore whether this phenomenon exists, we crawled sales information from Amazon and built a mathematical model. A Naive Bayes Classifier is employed to screen out the high-frequency vocabulary from the comments. And we defined the important concept of Irrational Discrimination base on Multiple Linear Regression. After analyzing the data for the whole year, we found that discrimination does exist. The specific vocabulary appearing in the review has a large star rating relevance shows that not only the time guiding role exists between star ratings and reviews, but also a strong interaction.
Research on Composition and Topology of Wireless Sensor Network
Authors: Li Yijie 
Published: April 2021

Abstract
Wireless sensor network is a kind of computer network which is composed of many automatic devices distributed in space. These devices use sensors to collaboratively monitor physical or environmental conditions (such as temperature, sound, vibration, pressure, motion, or contaminants) at different locations. Based on the composition of sensor nodes, sensor network is composed of intelligent sensors with multiple wireless communication modules. This paper studies the distribution and arrangement of sensor nodes in the sensor network, which is used to sense and monitor the physical information of the environment, so that the sensor network has higher reliability and availability.
The Study on High-Value User Identification of Localized Information Platform
Authors: Li Jinyi , Cao Sheng 
Published: April 2021

Abstract
In the current business environment, enterprise competition is fierce, high value customers are increasingly important to enterprises. However, with the development of social networks, the traditional RFM model of user value stratification is not accurate enough. Therefore, this paper introduces the characteristics of customer social attributes and establishes RFMS model to classify customer groups more accurately and effectively and identify high-value customers. Thus, it can help enterprises allocate resources reasonably and carry out customer operation in a targeted way.
Application of Robust Digital Watermarking Technology in Image Copyright Disputes
Authors: Cheng Bin , Zhang Bo 
Published: April 2021

Abstract
In recent years, with the increasing application of computer technology in daily life, the phenomenon of data transmission or transaction on the network is becoming more and more common. On the one hand, it brings great convenience to our life, on the other hand, there are also great hidden dangers, such as information replication, forwarding, and even tampering. Based on the research of DWT dual color image digital watermarking algorithm based on HVS, this paper introduces Arnold transform to improve the robustness of the algorithm, and studies the application of the improved algorithm in e-commerce image disputes.
An efficient method for compressing neuron morphology data
Authors: Li Longfei 
Published: April 2021

Abstract
The human brain has a very complex network structure. In order to understand the information integration process of the neural network in the brain, the current research of computational neurology focuses on studying the laws of neuron morphology. In recent years, the reconstruction technology in the field has developed rapidly, and the production speed of neuron data has been greatly accelerated. The problem of neuron data management under the background of Big-Data has gradually emerged. This paper proposes a method for compressing neuron morphology data based on binary coding, so as to efficiently store neuron morphology data. Relevant experimental results prove that the method in this paper is widely applicable to various types and sizes of neuron data.
The relationship between the corresponding author and its byline position: An investigation based on the academic big data
Authors: Yu Jianfei , Yin Chunxiao 
Published: April 2021

Abstract
With the increase of international collaboration, author contribution is becoming a key issue in research evaluation. Different counting methods may result in different results. Given the importance of the byline position and the significant role of the corresponding author, this study investigates the relationship between corresponding author and its byline position. By analyzing over 11 million papers from Web of Science published from 2000 to 2008, we find that the relationship between the corresponding author and byline position varies with year, the number of authors, countries and research fields. Our findings can provide insights to scientific research evaluation.