bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiological Characteristics of the Corona Virus Disease 2019 in Shaanxi Province Based on “Internet +” Epidemic Monitoring Cloud Platform
Authors: Zhang Hairui , Feng Yancheng , Ma Yonghong , Tan Jiao , Zhang Ye , Han Jiming , Men Ke 
Published: April 2021

AbstractSince the outbreak of the Corona Virus Disease 2019(COVID-19), medical staffs have reported cases of hospital infection of COVID-19, which has greatly affected the physical and mental health of medical staff. In order to effectively avoid the immunization situation and prevent the front-line medical staff from collecting information and reporting on the new coronary pneumonia patients, suspected patients, close contacts and other personnel, the possibility of being infected due to various direct and indirect contacts may arise. Information technology, the establishment of a new cloud monitoring platform based on “Internet +” for coronary epidemic outbreaks, and the realization of “zero touch” operation and “paperless” management of the entire process of information collection, confirmation, review and reporting, which greatly reducing the front-line work. The infection risk and labor intensity of personnel have reduced the workload and improved the efficiency of information collection. At the same time, it has also realized automatic statistics, intelligent statistical description and synchronous sharing of the information.
An Energy Efficient Clustering Algorithm in Wireless Sensor Networks for Internet of Things Applications
Authors: Ci Xingjie , Wen Kang , Sun Ying , Sun Weifan , Deng Wei 
Published: April 2021

Abstract
Internet of things (IoT) integrates sensor, radio frequency identification, network and cloud computing technology into a large-scale monitoring area. Wireless sensor network (WSN), as the most suitable infrastructure for the Internet of Things, how to reduce its energy consumption has been a research hotspot. In hierarchical networks, cluster head nodes need to take on more energy consumption tasks. Therefore, reasonable cluster head selection scheme and normal node joining cluster mechanism become particularly important. This paper proposes a new clustering method to save energy and prolong network life. Firstly, in the cluster head selection phase, the influence of energy threshold, residual energy, node density and communication factor is considered. Secondly, in the ordinary node joining cluster phase, the residual energy and distance factor are considered to form the non-uniform cluster set of the network. Simulation results show that the algorithm has good performance in reducing and balancing energy consumption.
Logo Based on Improved Generative Countermeasure Network Image Super Resolution Reconstruction Method
Authors: Luo Pengcheng , Hu Gengsheng , Tan Zhiping 
Published: April 2021

Abstract
In order to solve the problem that the existing learning based super-resolution reconstruction methods rely too much on the degenerate model while the degradation model is unknown, which leads to noise and edge jagged in the reconstructed image, an image super-resolution reconstruction method based on improved generative countermeasure network is proposed. The generator of the network consists of up sampling module, denoising module and anti-aliasing module Firstly, the input image is sampled by the up sampling module to generate the initial super-resolution image; then, the denoising module and anti-aliasing module are used to reconstruct the clear super-resolution image; in order to reconstruct a better logo image, a joint training loss is introduced, including content loss and resistance loss, and the content loss includes perception loss and edge loss Lost. The experimental results show that, compared with the current super-resolution reconstruction method based on generative countermeasure network (SRGAN), the peak signal-to-noise ratio (PSNR) of the reconstructed image is improved to 0.2675dB and the structural similarity is improved to 0.035, which can effectively improve the quality of logo image reconstruction.
Research on Airport Taxi Problem Based on Cell Transmission Simulation Model
Authors: Li Haizhen , Wang Chunli , Qin Lijuan , Su Linda , Xie Chengjie , Yang Qunxing 
Published: April 2021

Abstract
In order to solve the decision-making problem of taxi drivers at the airport, it constructed a non-aggregate stochastic utility model, a cell transmission simulation model, and a queuing model. Besides, it used software programming and drawing software such as MATLAB, SPSS, EXCEL, and rapid flow chart comprehensively. Finally, this paper solves the taxi problem at the airport and gives relevant suggestions.
Application of UAV Target Tracking Based on Computer Vision
Authors: Wang Xudong , Luo Bo , Zhang Zhiyuan 
Published: April 2021

Abstract
With the progress and development of China’s reform and opening up and economic globalization, China has made great progress in science and technology, especially in computer vision technology. From the current development of our country, the progress and development of computer vision technology plays an important role in the development and utilization of UAV automatic navigation. With the continuous development of automatic navigation technology, artificial intelligence has been widely used in various fields, and computer vision technology as the main direction of this field has also been rapid development in recent years, which also makes the important branch of computer vision moving object tracking technology has more and more extensive application, such as intelligent security, intelligent transportation, safe driving And video analysis.
RETRACTED: Analysis of the Fine Management Strategy for the Cultivation of Vocational College Students’ Core Quality based on Big Data
Authors: Yanxia Wang , Qian Wang 
Published: April 2021

Abstract
The key to the development of vocational education is to improve the training quality of college students, and the key to improve the quality of college students is to cultivate the core quality of vocational college students. Based on the above background, the purpose of this paper is the application of big data in the fine management strategy analysis of Vocational College Students’ core literacy cultivation. This study adopts the methods of literature research, questionnaire survey and interview to study and investigate the current situation of vocational college students’ core literacy. This paper expounds the theory, practical significance and feasibility of the integration of data mining technology and fine management analysis in the era of big data from three aspects: the problems in the refined management analysis of traditional college students’ core literacy cultivation, the expansion and deepening of the fine management analysis by data mining technology, and the construction path of the fine management analysis platform. This paper puts forward the reflection and promotion strategies for the fine management of college students from three aspects: Deepening the concept of student management, internalizing the concept into the practice of student management, and constructing the mechanism of campus characteristic culture education. Finally, the study found that the core quality that college students lack most is social participation, accounting for 37.1%. Therefore, in order to change the current situation of college students training, the most important thing is to enhance the social participation of college students, so that college students can adapt to the needs of life-long development and social development.
Research on Automatic Processing of Worn Tread Test Data
Authors: Xiaojie Sun , Pengfei Gu , Cong Xu , Zhaoqin Li 
Published: April 2021

Abstract
Wheel tread wear monitoring is great significance to ensure the safety of train operation. In view of the large amount of data in daily test of tread and the error easily occurred in manual analysis and processing, a solution of automatic processing of tread wear test tool based on MATLAB is proposed. The automatic tool first loads the test data of WPA + wheel profile measuring instrument, eliminates the data with large error, gives the index of wheel wear and generates a report; then according to the generated report, it gives the analysis data of wheel wear, and draws the comparison diagram between the measured tread profile and the standard one, and finally gives the wear analysis conclusion. At last, some test data are used to verify the effectiveness of the program.
Design of English Autonomous Learning System Based on Digital Signal Processing
Authors: Kang Pingping 
Published: April 2021

Abstract
The network is beginning to change people’s production and life style, which has produced earth-shaking changes in many industries. The learning method based on the network also has a great impact on the traditional education. The emergence of individualized autonomous learning mode of college English with teachers as the leading factor and students as the main body makes students change from passive learning to active learning. Many college students take acquiring knowledge and information as their important purpose in the use of the Internet, which shows that online autonomous learning has become an important means of learning in universities. On this platform, students can flexibly grasp their own learning time and progress, so as to achieve targeted learning and further improve their interest in English learning. This paper expounds the construction of college English autonomous learning environment based on digital signal processing, and puts forward corresponding management measures in view of the existing problems in autonomous learning management, in order to give full play to the effectiveness of digital signal processing technology in assisting college English autonomous learning.
Research on Literature Aesthetic Education Based on Neural Network Algorithm
Authors: Yang Bofeng 
Published: April 2021

Abstract
Chinese traditional Chinese language and literature learning mode emphasizes the application of knowledge, and pays attention to strengthening students’ memory of literary knowledge and literary theory in the process of Chinese language and literature learning, but the cultivation of aesthetic education has not been implemented. With the great development of ideology and culture, literary workers have created a large number of literary works, which poses new challenges to the application of natural language processing technology. Chinese language and literature, as a treasure of the Chinese nation, contains rich aesthetic elements and plays an important role in improving people’s humanistic cultivation and cultivating people’s aesthetic consciousness. In the teaching of Chinese language and literature, aesthetic education is beneficial to highlight the core connotation of the major and promote the overall development of students. On the basis of expounding the value connotation of aesthetic education in Chinese language and literature teaching, this paper analyzes the application of aesthetic education in Chinese language and literature teaching, and explores the specific implementation path of aesthetic education in Chinese language and culture specialty based on neural network algorithm.
Research on Enterprise Financial Management Supervision Mode Based on Data Mining
Authors: Liu Bochuan 
Published: April 2021

Abstract
In the current era of rapid development of digital global economy, facing fierce market competition, managers’ decision-making behavior will directly affect the development of enterprises and determine the development direction. Under the background of big data era, it becomes more convenient and efficient for people to obtain data. However, people still face the confusion of complicated data and limited valuable information. People are eager to find a tool in order to realize effective processing of huge and complicated data in the shortest possible time. Through the application of data mining technology, it not only brings great convenience to the financial analysis of enterprises, but also can quickly obtain the required knowledge and information from a large number of data, providing important basis for enterprise decision makers. Data mining technology has many advantages, such as rapidity and accuracy, which opens a new development direction for enterprise financial analysis. This paper mainly discusses the application of mining technology in enterprise financial analysis in detail, which plays an important role in ensuring the competitiveness of enterprises in the market.
Construction and Development Countermeasures of Characteristic Towns Based on Geographical Big Data
Authors: Guomin Liu 
Published: April 2021

Abstract
This paper studies the hot spot distribution and Construction Development Countermeasures of characteristic small towns based on geographical large number. This paper first uses the big data method of Baidu map POI points of interest to explore the construction method of industrialization and urbanization transformation. Secondly, it analyzes the consumption transformation from the production-oriented economy in large and medium-sized cities to the multi pole enjoyment economy in urban and rural areas by using statistical big data, and points out that the transformation has the characteristics of market demand pulling and policy supply promoting. At the same time, this paper points out that the differentiation of location preference of four industries, namely, historical classics, traditional county economy, new economy and tourism, lays a foundation for the development of characteristic towns, but it also faces the dilemma of imbalance of urban system structure and failure of micro design. Finally, this paper proposes that it is necessary to complete the overall site selection and spatial scale intensity control with the help of big data, complete the regional spatial organization and the spatial supply of characteristic industries by means of data fusion, and organize and create the environment by micro characteristic spatial sequence. This conclusion has a certain reference value for the research on the hot spot distribution and construction development of characteristic towns.
Environmental Evaluation of Small Coastal Cities Based on Street View Images
Authors: Chen Jing , Wang Xiaoxuan , Wu Yujing , Shi Bing , Lu Jifu 
Published: April 2021

Abstract
Whether out of the need of theoretical exploration or practical application, carrying out urban environmental assessment research can attract the attention of the public and managers, and it is conducive to improving the existing environmental impact assessment system. With the continuous breakthrough of artificial intelligence technology and its application in various fields, it is possible to carry out urban environmental assessment research based on street view images on a large spatial scale. Based on the analysis of the theories and methods of urban environmental assessment, combined with the landscape vision application in the planning of small coastal cities (littoral), this paper constructs an overall understanding of urban environment, specifically the assessment of environmental quality.
Establishment of Parallel Text Corpus of Equipment Manufacturing Industry Based on Data Mining Technology
Authors: Liu Dongxia , Liu Jianguo , Zhang Xianghui , Chen Manqian 
Published: April 2021

Abstract
In the era of language big data, traditional data analysis methods can’t analyze semi-structured or unstructured data such as text, but all the contents in the equipment manufacturing corpus belong to text data. The equipment manufacturing corpus is a linguistic information base for legal activities and equipment manufacturing research, which aims to study equipment manufacturing and collect equipment manufacturing cases. At present, the construction of legal database in China is not perfect, and there are still many problems. In this paper, a method based on template transformation is proposed to automatically acquire parallel corpus on the Internet, and a method based on the number of transformation patterns and the retrieval and sorting of transformation patterns is adopted to verify bilingual parallel texts. This system can build a large-scale parallel corpus of equipment manufacturing industry by automatically acquiring a large number of parallel texts from the Internet.
Research on Translation Processing of Complex Long Sentences Based on Multi-strategy Analysis Algorithm
Authors: Liu Jing 
Published: April 2021

Abstract
Syntax analysis depends on a certain grammatical theory. In formal grammar system, dependency grammar has gradually become the focus of researchers. In this paper, an automatic translation method of English-Chinese terms based on multi-strategy fusion is proposed, which uses the term case base to optimize the translation of terms with low evaluation scores obtained from the translation quality estimation method. Through the levenshtein algorithm, we find a number of terms translation examples with high similarity with the source language of the terms to be optimized, including grammatical semantic features, sentence length, punctuation marks, functional words and context conditions, etc., to segment and simplify complex long sentences and compound generate translations. By designing the same knowledge representation for different languages, the algorithm can be universally used for translation systems of different languages.
Analysis of Factors Influencing Intercultural Communication Competence Based on Big Data
Authors: Rui Xun , Tong Sun 
Published: April 2021

Abstract
The cross cultural communication is an important part of cultural communication and language learning. Based on the method of big data analysis, 400 college students are divided into three groups to test their intercultural awareness and intercultural communicative competence. The test paper covers cross-cultural awareness, communication culture and knowledge culture. The results show that Chinese college students’ deep intercultural communication awareness is generally weak. Intercultural communication course can effectively improve the level of cross-cultural communication. The main mistake in cross-cultural communication lies in the negative transfer of culture. The results of this paper have a certain reference value for the analysis of the factors influencing intercultural communication competence under big data.
Ballistic Target Signal Separation Based on Differential Evolution Algorithm
Authors: Li Yuxi , Shi Baodai , Pan Xinrui 
Published: April 2021

Abstract
During the course of the ballistic target’s mid-flight, it is very important to accurately identify the target. Separating the target micro-Doppler curve is the key to accurate identification. Aiming at this problem, this paper proposes and improves a differential evolution algorithm to separate the micro-Doppler curves of the scattering points. According to the results of the simulation experiment, the signal is separated well, which verifies the effectiveness of the proposed algorithm.
NDN congestion control based on fuzzy comprehensive evaluation algorithm
Authors: Cui Gaolin , Wang Hui , Fan Zhihui , Li Peiyu 
Published: April 2021

Abstract
The congestion control algorithm of the named data network is not accurate in obtaining the congestion status, and the research is not carried out in time, and a congestion control strategy based on the fuzzy comprehensive evaluation algorithm is proposed. This strategy uses the fuzzy comprehensive evaluation algorithm to calculate and analyze the above two network parameters to obtain the network congestion state by detecting the buffer queue length of the network intermediate node and the actual and predicted round-trip time ratio. In order to refine the degree of network congestion, a variety of congestion is designed. The feedback signal uses the existing NACK feedback mechanism of the NDN network to send a congestion signal to the downstream node, and the downstream node adaptively adjusts the interest packet sending rate according to the congestion signal to achieve the purpose of reducing network congestion. In the NDN-SIM simulator, this algorithm is compared and analyzed with mainstream algorithms, and it is confirmed that this strategy can make full use of network resources and has higher transmission efficiency.
Discussion on Legal Model of Intellectual Property of Computer Software
Authors: Hou Kewen , Zhang Meili 
Published: April 2021

Abstract
With the development of computer software and information technology, software industry has become one of the important engines of modern economic construction and structural transformation in China. However, because the computer software is very complex and the industry value is high, it is easy to lead to the flood of intellectual property infringement, which is undoubtedly a great blow to the researchers in the field of computer technology and related industries. Therefore, through analyzing the current situation of intellectual property protection of computer software, this paper fully discusses the comprehensive construction mode of copyright law, patent law and trade secret protection law, in order to ensure the innovation and application environment of this intellectual property right.
Identification of depression using support vector machine with different connectivity
Authors: Yang Jiale , Li Liyuan , Shen Fei , Zeng Ling , Li Rong 
Published: April 2021

AbstractPatients with depression have shown attention bias and inhibition deficits of negative emotional valance. However, it is not clear how the distributed brain networks support the function of inhibition and whether the modulation altered in depression. Thirty-seven patients with depression and 37 matched controls were undertook the audio-visual emotion task-fMRI and whole-brain psychophysiological interaction analysis was employed to obtain three different types of connectivity features, including task-modulated connectivity (TMC), task-independent connectivity (TMC) and task-functional connectivity (TFC). Support vector machine method was used to classify depression and explore the relation of reaction time prediction. Results indicated decreased modulation related to frontoparietal cortex, increased in temporal lobe and sensorimotor system in depression. Moreover, TMC performed better in predicting RT, while TIC and TFC had better classification performance. This study reveals that aberrant modulation of neural response is widely associated with the inhibitory dysfunction in depression and support that different connectivity features provide supplementary information for underpinning the functional integration and its alterations of brain networks.