bluuebunny/crossref_metadata_2025 huggingface dataset:
Periodenprävalenz von SARS-CoV-2 in einer unselektierten
Stichprobe schwangerer Frauen in Jena, Thüringen
Authors: Zöllkau Janine , Baier Michael , Scherag André , Schleußner Ekkehard , Groten Tanja
Published: August 2020

Einleitung Die Stadt Jena, Thüringen, führte nach
exponentiellem Anstieg der SARS-CoV-2 Infektionen bundesweit erstmalig eine
Pflicht zur Bedeckung von Mund und Nase ein. Durch Screening einer
unselektierten Kohorte von Schwangeren sollte eine Schätzung der
SARS-CoV-2 Periodenprävalenz erfolgen. Von Interesse war die Frage nach
der Dunkelziffer.

Methoden Bei stationärer Aufnahme erfolgte ein Screening sowie
eine Antikörperbestimmungen auf SARS-CoV-2, mittels spezifischer
Real-Time-PCR und Bestimmung spezifischer SARS-CoV-2 IgG im Serum mittels ELISA.
Die Schätzung der SARS-CoV2 Periodenprävalenz erfolgte nach der
exakten Methode von Clopper und Pearson, der Gruppenvergleich mit Fischers
exaktem Test.

Ergebnisse Vom 06.04. bis 13.05.2020 wurden 234 Schwangere
stationär aufgenommen. 225 (96,2%) durchgeführte
SARS-CoV2 PCR verblieben negativ. Bei einer (0,6%) von 180
(76,9%) erfolgten Antikörperbestimmungen wurden spezifische
IgG-Antikörper detektiert. Die Intervallschätzung der
Periodenprävalenz ergibt damit ein 95%-Konfidenzintervall
zwischen 0–1,7%. Für 96 Haushalten mit Kindern ergibt
sich eine Periodenprävalenz von 0–3,8%, die sich nicht
von der für 76 Haushalte ohne Kinder von 0–4,8%
unterscheidet (p=1,00).

Diskussion Erstmalig wird die SARS-CoV-2 Periodenprävalenz einer
unselektierten Stichprobe Schwangerer in Deutschland erfasst. Es ergab sich kein
Hinweis für eine befürchtet hohe Dunkelziffer asymptomatischer
Schwangerer für unbemerkte SARS-CoV-2 Infektionen mittels
Antikörpernachweis. Die messbare Serokonversionsrate lag bei unter
1% (0,6%).
Wie Familienhebammen Mütter mit Drogenkonsum unterstützen
Authors: Knott Christiane
Published: August 2020

Expertinnen-Interview | Wenn Frauen mit Drogenabhängigkeit schwanger werden und einen Säugling versorgen müssen, befinden sie sich in einer besonders belastenden Familiensituation. Christiane Knott hat als Familienhebamme im „Team Frühe Hilfen“ der Stadt Bochum schon viele dieser Frauen begleitet. Ihre Erfahrungen sind auch für Hebammen in der Regelbetreuung wertvoll.
Bleeding Complications Drive In-Hospital Mortality of Patients with Atrial Fibrillation after Transcatheter Aortic Valve Replacement
Authors: Lother Achim , Kaier Klaus , Ahrens Ingo , Bothe Wolfgang , Wolf Dennis , Zehender Manfred , Bode Christoph , von zur Mühlen Constantin , Stachon Peter
Published: August 2020

Background Atrial fibrillation (AF) is a risk factor for poor postoperative outcome after transfemoral transcatheter aortic valve replacement (TF-TAVR). The present study analyses the outcomes after TF-TAVR in patients with or without AF and identifies independent predictors for in-hospital mortality in clinical practice.

Methods and Results Among all 57,050 patients undergoing isolated TF-TAVR between 2008 and 2016 in Germany, 44.2% of patients (n = 25,309) had AF. Patients with AF were at higher risk for unfavorable in-hospital outcome after TAVR. Including all baseline characteristics for a risk-adjusted comparison, AF was an independent risk factor for in-hospital mortality after TAVR. Among patients with AF, EuroSCORE, New York Heart Association classification class, or renal disease had only moderate effects on mortality, while the occurrence of postprocedural stroke or moderate to major bleeding substantially increased in-hospital mortality (odds ratio [OR] 3.35, 95% confidence interval [CI] 2.61–4.30, p < 0.001 and OR 3.12, 95% CI 2.68–3.62, p < 0.001). However, the strongest independent predictor for in-hospital mortality among patients with AF was severe bleeding (OR 18.00, 95% CI 15.22–21.30, p < 0.001).

Conclusion The present study demonstrates that the incidence of bleeding defines the in-hospital outcome of patients with AF after TF-TAVR. Thus, the periprocedural phase demands particular care in bleeding prevention.
Suitability of binary oxides for molecular-beam epitaxy source materials: A comprehensive thermodynamic analysis
Authors: Adkison Kate M. , Shang Shun-Li , Bocklund Brandon J. , Klimm Detlef , Schlom Darrell G. , Liu Zi-Kui
Published: August 2020

We have conducted a comprehensive thermodynamic analysis of the volatility of 128 binary oxides to evaluate their suitability as source materials for oxide molecular-beam epitaxy (MBE). 16 solid or liquid oxides are identified that evaporate nearly congruently from stable oxide sources to gas species: As2O3, B2O3, BaO, MoO3, OsO4, P2O5, PbO, PuO2, Rb2O, Re2O7, Sb2O3, SeO2, SnO, ThO2, Tl2O, and WO3. An additional 24 oxides could provide molecular beams with dominant gas species of CeO, Cs2O, DyO, ErO, Ga2O, GdO, GeO, HfO, HoO, In2O, LaO, LuO, NdO, PmO, PrO, PuO, ScO, SiO, SmO, TbO, Te2O2, U2O6, VO2, and YO2. The present findings are in close accord with available experimental results in the literature. For example, As2O3, B2O3, BaO, MoO3, PbO, Sb2O3, and WO3 are the only oxides in the ideal category that have been used in MBE. The remaining oxides deemed ideal for MBE awaiting experimental verification. We also consider two-phase mixtures as a route to achieve the desired congruent evaporation characteristic of an ideal MBE source. These include (Ga2O3 + Ga) to produce a molecular beam of Ga2O(g), (GeO2 + Ge) to produce GeO(g), (SiO2 + Si) to produce SiO(g), (SnO2 + Sn) to produce SnO(g), etc.; these suboxide sources enable suboxide MBE. Our analysis provides the vapor pressures of the gas species over the condensed phases of 128 binary oxides, which may be either solid or liquid depending on the melting temperature.
Struggling for professional identity
Authors: Hong Sulyoung , Choi Eunah
Published: August 2020

Despite growing academic interest in the personal experiences of translators and interpreters with a focus on status,
identity, role and ethics, and job satisfaction, there have been few academic attempts to inquire into the experiences of respective genders
in the profession. Also, outside of T&I studies, most occupational research has examined the experience of women in male-dominated
fields. Thus, the current study aims to shed light on the professional experiences and challenges of male interpreters working in a
predominantly female profession in Korea. Taking a qualitative approach to interpret the male experience from a temporal, spatial, and
cultural context, a narrative inquiry was conducted with male conference interpreters currently working in Korea to closely examine the
struggles they experience in the process of their professional identity formation. Data analysis reveals that male interpreters face extreme
gender bias and stereotypes at work, and struggle with issues such as emotional remoteness with colleagues, job insecurity, and crisis of
identity stemming from an unstable social status for male interpreters.
A model of live interlingual subtitling using respeaking technology
Authors: Jin Silhee
Published: August 2020

This paper proposes a model of delivering live interlingual subtitling (LIS) as a formal translation and
interpreting (T&I) service in Korea, replacing the existing model of combining stenographic transcriptions with simultaneous
interpreting. The model proposes that these two processes, currently delivered by two different professional groups, should be
converged using respeaking technology. As a means to supply relevant talent, the paper proposes that formal interpreting and
translation schools should include respeaking using automatic speech recognition technology (ASR) as part of their training.
Intertitle translation of Chinese silent films
Authors: Haina Jin
Published: August 2020

There is a misconception that film translation did not exist in China before 1949. The paper argues that the translation
of Chinese silent films was vibrant in the 1920s and the early 1930s. Most of the extant copies of Chinese films from that period have
bilingual intertitles. Chinese film companies have two purposes in translating their productions: the potential profit obtained from
international audiences, and the desire to change the negative image of Chinese people portrayed in Hollywood films and project a positive
image of China. Driven by these two objectives, Chinese film companies placed considerable emphasis on translation quality and hired both
Chinese translators and foreign translators to translate their productions.
Translation of visual poetic spatiality
Authors: Liu Yongzhi , Tang Chunlan
Published: August 2020

Spatiality in literature has been explored in depth in recent years, but there are still few applications in literary
translation studies. With space cognitively defined and the trichotomy of iconic signs adopted, we argue that the written text of a poem has
its visual poetic spaces – the scene properties of linguistic signs (letters, character parts, words, lineation etc.) and relational
reference of linguistic signs (distance, sequence etc.) – and that these poetic spaces are imagically and diagrammatically iconic. Our
analysis of the English-Chinese and Chinese-English translation of poems’ iconic letters, lineation, distance, and sequence reveals that
some translators have successfully reproduced the source text’s visual spatiality in the target text, but some have simply ignored or
neglected the rendering; visual poetic spaces are semantically important and translatable, and the translation techniques involve direct
reproduction and complementary renderings. We argue that, in addition to portraying the linguistic and cultural information found in poems,
translators should pay more attention to visual poetic spatiality in their work in order to ensure an accurate portrayal of the original
author’s work.
Ethics of journalistic translation and its implications for machine translation
Authors: Song Yonsuk
Published: August 2020

Journalistic translation is governed by a target-oriented norm that allows varying degrees of intervention by
journalists. Given the public’s expectations for the fidelity of translated news, this norm entails ethical issues. This paper
examines the ethical dimensions of journalistic translation through a case study of political news translation in the South Korean
context. It investigates how newspapers translated a US president’s references to two South Korean presidents in accordance with
the newspapers’ ideologies and then came to apply the translations as negative labels as the political situation evolved over
time. The study demonstrates how even word-level translation can require an intricate understanding of the sociopolitical context
and cumulative meanings of a word. It then draws its implications for machine translation by comparing the human translations with
machine translations of the references in question. It concludes by discussing why machine translation cannot yet replace human
translation, at least between Korean and English, and what translation studies should do regarding the ethics of journalistic
translation.
Research on Risk Prediction Model of Contract Terms Based on Big Data
Authors: Qingzhuo Yang , Pengfei Cai , Yan Lu , Hongyuan Zhang
Published: August 2020

With the rising power industry, the demand for power supplies in the market is gradually expanding, and many power supply companies have poured into the market. Therefore, so as to standardize corporate behavior and make the market procurement behavior more programmatic, a contract for the purchase of power supplies came into being. Meanwhile, the research on the risk prediction model of the material purchase contract terms based on the big data environment is mainly discussed in the paper, in which AHP and fair entropy algorithm are applied to analyze the benefit flow of each core participant, and establish a risk assessment model framework for management projects to realize visual analysis of risk prediction and big data evaluation with an effective risk management method. According to verification by examples, the research content in the paper provides a safety guarantee for the supply of power supplies.
A clustering algorithm based on the combination of screening strategy and swarm
Authors: yudifei
Published: August 2020

aiming at the problem that the k-means clustering algorithm is affected by the initial clustering center, a k-means clustering optimization algorithm combining the screening strategy and artificial colony (ABC) was proposed.This algorithm operates in an unsupervised way, separating data from outlier points through screening, combining the advantages of ABC algorithm, using the objective function of ABC algorithm as the measurement function of initial clustering, and improving the effectiveness and accuracy of k-means clustering by changing the initial clustering center.
Analysis on Regional Differences and Influencing Factors of Household Asset Allocation in China
Authors: Liu Shiying
Published: August 2020

Households participate in financial activities through asset allocation, which will not only maintain and increase the value of household assets, but also have a significant impact on China’s economic and financial development. China has a vast territory and obvious regional characteristics, and there are significant differences in economic structure and urbanization level among the eastern, central and western regions. Under this background, the development of family finance among regions is also unbalanced. After summarizing the macro characteristics of household asset allocation in China, this paper makes a micro empirical study of urban households in China with the help of China Household Financial survey database, and explores the regional differences between the eastern region and the central and western regions from different perspectives, by using the Tobit model. The empirical analysis results show that the proportion of stable holding in the eastern region is significantly lower than that in the central and western regions, and households in the eastern region have a greater preference for risky financial assets.
Investigation and Study on Students’ Online Shopping Consumption under the Background of Big Data
Authors: Tao Chun-rui , Wang Si-wei
Published: August 2020

With the rapid development of social and economic growth of the Internet, online shopping has become an indispensable part of people’s lives, college students has become a main force in online shopping. Although online shopping has gradually matured, there are still many problems, and the problems are worth discussing. Based on the social background of big data, based on the questionnaire survey on the online shopping consumption of students of the International College of Zhengzhou University, this article uses the basic statistical analysis methods, correspondence analysis, and SPSS software and EXCEL software. Use Logistic regression method to analyze students’ online shopping consumption. Combined with the status of students’ online shopping, find out the differences of students’ online shopping behaviors, analyze the psychological characteristics of online shopping consumption, in order to correctly guide students’ consumption concepts. Then logistic regression analysis was used to find out the key factors that influence students’ online shopping frequency. Finally, based on the previous analysis conclusions, the school, e-commerce, and the government propose corresponding countermeasures.
RETRACTED: Management Innovations Research of the Logistics Enterprises Based on the Big Data Environment
Authors: Jin Wang , Jitao Yang
Published: August 2020

In the operation of logistics enterprises, both internal management and external operation will produce a lot of data. It can be effectively used as the information assets of enterprises and the guidance for enterprise management optimization, cost control, efficiency enhancement, risk identification and avoidance, which is of great significance to the future of enterprises. Big data with its advantages is different from traditional data processing. It can be combined with management innovation of logistics enterprises to effectively optimize the allocation of logistics enterprises resources. The paper mainly explores the direction of the combination of big data and logistics enterprise management and innovative measures.
Based on the construction of financial management information platform of colleges and universities in 5G environment——Take Guangzhou Nanyang Polytechnic Vocational College as an example
Authors: Li Meiling
Published: August 2020

With the rapid development of wireless technology, mobile communication service has experienced the development from voice service to mobile broadband data service, mobile communication network has gradually evolved from 3G, 4G to 5G, namely the fifth generation of mobile communication network.With the advent of 5G technology, the new generation of information technology has accelerated the reform of higher education system, and the construction of an information platform for financial management in colleges and universities has become an important research topic for the information construction and financial work in colleges and universities.Under the background of “Internet +", the construction target of “financial management informatization platform” from the construction stage of “smart campus” is being promoted to the informatization application service of “smart campus” and “Internet of Things +", and the development of financial management informatization in colleges and universities is changing from business process-oriented to service informatization.Financial resources are transformed from digitization to digitization, and the integration, analysis and utilization of data are emphasized to provide personalized services. The main network scenarios of 5G can be summarized as continuous wide area coverage, high capacity of hot spots, large connection with low power consumption and high reliability with low delay. Now that 5G technology is on the way, in the connected society of the future, everyone and everything will be connected to each other, thus achieving the so-called “Internet of everything”.

In this paper, using the method of literature research, field survey and data analysis of guangzhou nanyang technological vocational college financial management informationization development research and analysis, combining the present situation of the financial management informatization, with the help of a financial management concepts and network information technology, knowledge, financial software system using financial management information platform for the school financial management software for scientific and standardized management, based on a student online payment platform, financial reimbursement platform, campus all-in-one-card platform, improve the service efficiency of funds, the school to further enhance the level of school financial management.
Research on the application of WeChat mobile learning platform in ideological and political course teaching in universities
Authors: Yan li
Published: August 2020

With the rapid popularization of personal mobile devices (such as mobile phones, tablets, etc.) and the mobile Internet, learning can take place anytime and anywhere and is no longer limited by time and space. The effective use of mobile technology for learning is mobile learning.Current, WeChat platform with the rapid development of the public will WeChat tentacles extend to mobile learning areas, the former because of its ease of operation, the diversity of interactivity, content delivery precision, and access to information in the sexual and other unique advantages, in the field of education in colleges and universities in the rapid rise, became popular with the teachers and students in the course of mobile learning platform, not only for college students to provide a convenient, simple, cheap and efficient mobile learning applications, also for the innovative development of colleges and universities education courses provides the high quality network carrier.Therefore, to explore the intrinsic educational value and learning support function of WeChat mobile learning platform and apply it effectively to ideological and political course teaching in colleges and universities has increasingly become an important topic of widespread concern for front-line teachers, experts and scholars.Based on marxist communication theory, ideological and political course teaching process theory and constructivism learning theory, this study aims to improve the effectiveness of ideological and political course teaching in colleges and universities, and conducts theoretical research and practical exploration closely around the issue of “how to use WeChat mobile learning platform to assist ideological and political course teaching”.
Research and application of Improved snake algorithm in Boundary detection of Core CT image
Authors: Sun Wenhua , Zhang Wei
Published: August 2020

With the continuous refinement of oilfield development, computed tomography (CT) scanning technology has gradually become an important means to study the core microstructure, through the analysis of core CT image to obtain the core structure information. Active contour model (snake algorithm model) has been widely used in medical image segmentation. Considering the great similarity between core CT image and medical CT image of petroleum geology department, this paper attempts to improve the traditional snake algorithm model. The experimental results show that the improved algorithm has achieved good results in the boundary extraction of core CT sequence image.
Research on the Quality Evaluation Strategy of Multi-source Heterogeneous Aggregation Data
Authors: Zhan Gaofeng , Jiang Yong , Wang Xiaofeng , Zhao Yuyang , Zhao Tong
Published: August 2020

In the era of big data, the application of multi-source heterogeneous aggregation data is more and more extensive. If the quality of aggregation data is uneven, it will bring a lot of troubles to the subsequent data mining, and then lead to inaccurate decision-making. A comprehensive quality evaluation method for aggregation data is proposed in this paper, based on factor analysis and multivariate variance analysis which is from the perspective of multivariate statistical inference. The case study shows that the method proposed in this paper is feasible and adaptive for the long-term evaluation of the quality of multi-source heterogeneous aggregation data.
Route Mining from Satellite-AIS Data Using Density-based Clustering Algorithm
Authors: Yitao Wang , Lei Yang , Xin Song
Published: August 2020

Automatic Identification System (AIS) provides a large number of vessel navigation data for Marine traffic research. In this paper, we proposed a route mining method based on satellite AIS. The method includes data preprocessing, structure similarity calculation, clustering and route extraction. The validity of the route mining method was verified by satellite AIS data from seas near Australia and Warrior Strait. This method is helpful to understand Marine traffic pattern. It provides reliable basis for route planning and lay a foundation for ship abnormal behavior detection.
Research on Improving the Quality of Online Teaching Based on Big Data under the COVID-19 Coronavirus Epidemic
Authors: Su Bowen , Hu Qiliang
Published: August 2020

In 2020, the global COVID-19 outbreak came out of the blue and caught people and businesses by surprise, including the education sector. In order to ensure the “suspension of classes”, schools at all levels in China implement online teaching. How to ensure the quality of online teaching is an important issue. Based on the big data of online teaching, it is of great practical significance to analyze the factors affecting the quality of online teaching, so as to improve the path of improving the quality of online teaching. With the help of big data analysis, the index system of online teaching quality improvement is constructed and applied. Through questionnaire survey and SPSS software analysis, it can be concluded that the teaching quality of online teaching can be improved from three aspects: the behavior level of school, the learning level of students and the behavior level. Therefore, the following Suggestions are put forward: improve the hardware environment, perfect the teaching organization, strengthen the teaching supervision, strengthen students’ mastery of knowledge and skills, strengthen students’ active inspection and team learning. It is hoped that the implementation of such recommendations will further improve the quality of online teaching in the context of COVID-19.
Conceptual Housing and Housing Prices: An Empirical Study Based on Micro-big Data of Hangzhou Newly-built Housing Market
Authors: Lian Yukun , Li Shuyuan , Wen Haizhen
Published: August 2020

With the fierce competition in the market and the improvement of residents’ consumption concepts, a multitude of new concept products have emerged in the real estate market, including green housing, education housing, subway housing, and park housing. However, the existing research does not fully explain how these housing concept labels affect the housing price. This study takes Hangzhou as an example, collects a total of 36,907 transaction data of new housing districts in 2016, and constructs a hedonic price model to analyze the influence of four housing concept labels, namely green housing, education housing, subway housing, and park housing, on housing prices. The empirical results show that the impact of diverse types of concept labels on housing prices is heterogeneous. In addition to education housing, the impact of green housing, subway housing, and park housing on housing prices is significant and positive, which can bring an 8.2%, 3.0 %, and 4.1% price increase.
Public Opinion Guidance with New Government Media In the Age of Big Data
Authors: Ji Yunqing
Published: August 2020

The Internet has changed the way of people’s life, meanwhile, the emergence of new media is changing people’s habit of reading news and getting information. Recently, in order to take use of the new media platform to guide the network public opinion, The government gradually increased the construction of new government media. This paper aim to study the new characteristics of public opinion in new media age, analyzes the problems of the new government media in the public opinion guiding, and also put forward some optimization strategies.
Demographic Structure and Household Tourism Decisisions Based on Microdata
Authors: Jiang Zhiping , Zhang Jiping
Published: August 2020

Due to the differences of demographic structure, household tourism preference and travel choice behavior are more microcosmic. Based on a large nationwide sample of micro-household survey data, some mathematical models are used to empirically study the influence of demographic structure on the decision-making behavior of household tourism in China. Our research shows that the relationship between the proportion of the elderly in a family and the tourism decision of the family is not always a inverse proportion, which only exists in the non-elderly families with younger heads.However, for the elderly families with older heads, the proportion of the elderly population is a positive factor to promote the increase of household tourism intention and tourism expenditure. It shows that the aging of the population has not only brought challenges to China’s tourism industry, but also brought opportunities for sustainable development.
Research on Export Efficiency Measurement and Influencing Factors of the Pearl River Delta Urban Agglomeration
Authors: Wu Yan , Li Minyi
Published: August 2020

This paper firstly analyses the export situation of the Pearl River Delta urban agglomeration in the past 10 years, and then uses the DEA model and panel data model to analyse export efficiency measurement and influencing factors of Pearl River Delta urban agglomeration. Finally, it proposes countermeasures to promote the improvement of the export efficiency of the Pearl River Delta urban agglomeration.
Research on Massive News Events Evolution Prediction Based on Improved PrefixSpan Algorithm
Authors: Wang Biao , Dai Xiao , Yang Jing , Li Shun
Published: August 2020

The Internet reports massive news event every day. Sequential pattern mining is adopted to study the timing relationship between news event, which can provide reference for the development or prediction of news events. With its advantages in performance and efficiency, PrefixSpan often becomes preferred algorithm in the field of sequence pattern mining. But unfortunately, because of the large amount of news and the long time span between some news events, the event sequences is long and dense, which results many subsequences in the frequent pattern and reduces the algorithm performance. In this paper, we propose an improved PrefixSpan algorithm by integrate subsequences of the supersequences in the frequent pattern and introduce news event weight in the pruning step of the PrefixSpan algorithm. Experiment results show that without affecting expression ability of frequent patterns, the improved PrefixSpan algorithm increases the efficiency by about 20 times as before and eliminates about 10% of the redundant subsequences to get a more concise frequent patterns set.
RETRACTED: Study in the Big Data Talent Training Oriented Reform of Information Management and Information System Major under the Management Category
Authors: Hou Ke , Guo Mingcheng , Li Xinhao
Published: August 2020

With the coming Big Data era, the curriculum system of the Information Management and Information System (IMIS for short) Major under the Management Category cannot meet the needs of modern society for talents. Many universities have taken many measures to deal with this situation, which means creating the Big Data Major among current majors or directly replacing the IMIS Major under the Management Category under the Management Category with the Big Data Major. In this paper, the overview of IMIS Major under the Management Category is introduced firstly, and then its problems in the Big Data era are analyzed. By referencing to relevant research results, the current situation and trend of IMIS Major under the Management Category reform under the Management Category is studied. Finally, our solution is put forwarded.
An Improved ORB Feature Extraction Algorithm
Authors: Geng Chuanping , Yang Junjie , Lin Jinchen , Yu Ting , Shi Kexin
Published: August 2020

In this paper, an improved ORB feature extraction algorithm is proposed to solve the insufficient detection effect of the traditional ORB algorithm on the image edges as well as the low actual extraction of feature points. First, the image pyramid layering was established, and then on basis of the improved oFAST12-20 corner point algorithm, the method with a setting dynamic threshold, according to the idea of adaptive threshold, was proposed to extract feature points, and the candidate set of feature points was obtained. Then, Harris algorithm was used to calculate the response value of each candidate point, and the response value was sorted from high to low. Finally, the top 80% of the feature points with high response value were extracted as the most important feature points. The experimental results show that the improved oFAST algorithm improved the extraction rate of feature points and reduces the algorithm time compared with the traditional ORB corner detection.
RSS Ranging Algorithm Based on Kalman Filtering Combined BP Neural Network
Authors: Zhou Yuanyang , Liu Yang , Wang Pengfei
Published: August 2020

Accurate distance estimation is an important prerequisite for positioning using wireless sensor networks (WSN). However, the path loss model (PLM) cannot accurately express the relationship between distance and received signal strength (RSS), because of the complexity of the indoor environment. Therefore, this paper proposes an improved Kalman filter as the RSS preprocessing method to make up for the defects of PLM. The improved algorithm uses BP neural network to correct the Kalman filter error, improve the filtering performance, and use the compensated RSS for PLM-based ranging. The experiment shows that the proposed method has better ranging accuracy than the method based on Kalman filtering. And the average is 0.29m, which has dropped by 0.61m.
Analysis of the Impacts of Urban Public Transport on the Housing Price in Hangzhou, China
Authors: Wei Feiyang , Zhang Donglin , Wen Haizhen
Published: August 2020

With the rapid increase of urban population, housing demand is gradually increasing, and traffic congestion is becoming more and more serious. People are increasingly concerned about the relationship between housing and public transportation. Hence, studying the impact of public transport on housing prices will be conducive to promoting the coordinated development of urban public transport and urban social economy. Taking Hangzhou, China as a case city, this study selected 477 residential districts and their surrounding comprehensive public transport characteristics to construct the hedonic price model, and further quantitatively analyses the impact of urban public transport on housing prices. The empirical results showed that most of the public transport characteristics produce significant premium capacity to the housing market. The ranking of the premium capacity from high to low is the distance between the community to the subway station, the speed of nearby roads, and the number of public bicycle stations. In addition, a few public transport characteristics, such as the number of bus and water bus stops, have no significant impact on housing prices. This research can serve as a theoretical basis for government departments to carry out urban planning and real estate enterprises to make decisions.
Design and Implementation of Intelligent Library System Based on Big data
Authors: Peng Zhibin , Chen Yuefeng , Luo Xiaoying , Fan Rui , Meng JiaHui
Published: August 2020

In most traditional library management systems, readers have to find their interest books through the name or search approximate content from library, which results in wasting time. With the help of big data technology, we construct the intelligent library system using SSM framework and Hadoop framework. A recommendation approach combined co-filtering with content-based recommendations, is introduced to make better recommend efficiency. The system has the intelligent ability of self-learning. For historical lending books data, it uses the Spark MLlib machine learning algorithm library to build clustering or classification models. On the other hand, the system uses Kafka and SparkStreaming to process real-time data. System simulation shows that it has high recommendation accuracy and good timeliness.
Analysis of the application trend of big data in power industry
Authors: Zhang Qian , Xia Liyu , Feng Wangren
Published: August 2020

With the permeate of new forms of digital economy into various fields of social development, the application of big data has become a driving force for innovation, transformation and upgrading in all walks of life. Internet enterprises and traditional power grid enterprises are actively exploring the innovation of big data application scenarios, which relevant data analysis ideas and methods are worth to learn.
Research on the Influencing Factors of Collaborative Innovation of Science and Technology in the Pearl River Delta Urban Agglomeration
Authors: Wu Yan , Wu Yating
Published: August 2020

This paper has measured the level of collaborative innovation of science and technology in the Pearl River Delta urban agglomeration from 2010 to 2018 by using the DEA-Malmquist index model. The empirical results show that the overall level of technological collaboration and innovation in the Pearl River Delta urban agglomeration is relatively high. The pure technical efficiency value of the Pearl River Delta urban agglomeration has hit its peak. In terms of its scale efficiency, that of Zhuhai and Jiangmen still has room for improvement, while that of other cities has reached the optimal level. Then, through the establishment of a panel data model of the Pearl River Delta urban agglomeration from 2009 to 2018, the influencing factors of technology collaborative innovation in the Pearl River Delta urban agglomeration was analyzed. Finally, this proposal was made.
An Empirical Analysis of Student Satisfaction in Practical Teaching––Research Based on Structural Equation Model
Authors: Huang Wenyan , Jin Wei
Published: August 2020

Since the middle of the last century, so far, practical teaching has been the focus of vocational education in our country[1]. This paper compares other practical teaching models at home and abroad, based on the two courses of “Real Estate Operation and Management” and “Curriculum Design” in the civil engineering major of our school, and discusses the satisfaction of the curriculum theory and practical teaching model. This paper mainly adopts the satisfaction model proposed by American scholars, combined with the data collected by the questionnaire survey, constructs the student satisfaction model of the practical teaching link, and obtains the linear path coefficient of the student’s practical teaching satisfaction and the student’s satisfaction index for the practical teaching link, so as to improve reform measures such as the assessment system, and improve the level of practical teaching, and ensure the effectiveness of practical ability training.
Music Data Mining Based on MusicXML
Authors: Chen Gen-Fang
Published: August 2020

In this paper, we use the music resources of the Internet to analyze and mine the data of MusicXML file. First, the structure of MusicXML file is introduced briefly, then the data source is explained, then the database is established by MySQL and PHP, and finally the data is analyzed by MATLAB. The experimental results show that the music group is centered on the group of small characters in which the center C is located, showing normal distribution, while the music group is centered on the group of small characters in G, showing normal distribution.
Fuzzy Matter-element Analysis Model of IP-influence Based on EFA-Euclid Approach Degree
Authors: Zhang Wenjing , Li Bo , Chai Jianping
Published: August 2020

With the rise of Intellectual Property (IP) films, IP influence has become one of the important criterias to consider whether an IP film has development value[1]. The influence of the IP films is a fuzzy concept, and its evaluation is not only affected by a variety of factors(both qualitative and quantitative indicators), but also has the problem of incompatible of single indicator evaluation. Based on the actual situation of China’s IP film market and the characteristics of literary works IP, this paper constructs an evaluation index system of the influence of IP films. On the basis of fuzzy matter-element analysis theory, the exploratory factor analysis is introduced into the weight calculation, and combined with the Euclid approach degree, the fuzzy matter-element model based on EFA-Euclid Approach Degree is established, which sorts the IP influence according to the size of the relative paste progress, and the evaluation result is more objective and reasonable. This model ranks IP influence according to the relative approach degree, and the evaluation results are more objective and reasonable.
A New Reversible Database Watermarking Approach with Ant Colony Optimization Algorithm
Authors: Lian Junyao
Published: August 2020

In many fields such as medicine, science, transportation, it is often necessary to maintain the real-time information, and the data in the centralized database that saves data in these fields is distributed to various clients. On the insecure public Internet, there are distributed databases stored in data centers. Sharing may create risks, such as unauthorized copies, changes to data, and distribution of data to unauthorized persons for reuse. Many database watermarking methods have been proposed to protect digital rights. In order to reduce watermark distortion and increase watermark capacity, people pay more and more attention to the optimization of watermark technology. This paper proposes a method of embedding differential expansion watermarking (DEW) based on ant colony algorithm (ACO) in relational database. This method uses a secure hash algorithm for grouping, increasing the privacy of watermark embedding. The ant colony algorithm performs the optimization operation, finds the best attribute columns for embedding the watermark in the subgroup, and finally uses the differential expansion technology to embed the watermark. Experimental results show that compared with similar works reported in the literature, the reversible watermarking method based on ant colony algorithm database proposed in this paper not only increases the watermarking capacity, but also improves the robustness against various types of attacks.
A Structural Equation Model Study on the Cognitive Factors of Irony Processing
Authors: Ran LI , Shide LI
Published: August 2020

Irony processing has always been a hot issue in experimental pragmatics. Existing studies have found out many cognitive factors contributing irony processing with unique paths and contribution rate of their own. Structural equation model can clearly demonstrate the exact path and contribution rate of each factor to irony processing, namely the need for cognition, empathy ability, sarcasm preference and working memory capacity. Three offline questionnaires on the need for cognition, empathy ability and sarcasm preference and two online tests of working memory capacity and irony processing have been conducted. Two hypotheses are verified through hierarchical linear modeling and structural equation modeling. Statistic results show that the four cognitive factors all exert positive effect on irony processing, with sarcasm preference exerting a direct effect while the need for cognition showing an indirect effect through the mediation of working memory capacity and empathy ability respectively, which is of great significance to the teaching of linguistics and rhetorics.
Study on Security Countermeasures of Cross-border E-Commerce Payment Risk
Authors: Lei Wang
Published: August 2020

China has now fully entered the era of Internet +, cross-border e-commerce has achieved stable development. If we want to promote the sustainable development of cross-border e-commerce, we must constantly improve and optimize the existing payment mode of cross-border e-commerce. This paper analyzes this, analyzes the payment risk of cross-border e-commerce, and puts forward targeted security countermeasures to lay a good foundation for the stable development of cross-border e-commerce.

The national economic growth rate has a clear downward trend, many businesses in the operation and development process, gradually looking for new channels to achieve business development and development. Cross-border e-commerce is in this context put forward a new business channel, its overall development speed is relatively fast. According to relevant statistics and survey results, China’s entire cross-border e-commerce transactions reached 6.7 trillion yuan in 2016, an increase of 22.2 percent over the same period last year. At the same time, imports of e-commerce transactions also reached 1.2 trillion yuan, a year-on-year growth rate of 33.3%. It can be seen from this that the overall development situation of cross-border e-commerce is generally good in the process of modern society development. But to achieve stable and sustainable development, we must ensure that there are corresponding supporting services to support, the most important point is cross-border payment. Only by ensuring the perfection and optimization of cross-border payment mode can we promote the stable and sustainable development of cross-border e-commerce.
ARIMA Based on Linear Interpolation for SO2 Monitoring Data’s Calibration
Authors: Xu Yan , Xu Enhua
Published: August 2020

Linear interpolation filling the missing values could be effectively solved the problem of data missing and improved the effect of the addictive model of ARIMA and multivariate linear regression. The addictive calibration model by ARIMA and Multiple linear regression for SO2 was reconstructed based on linear interpolation filling. The error analysis showed that the accuracy of SO2 was improved. The prediction effect was also improved by considering the interaction effect.
Controlling Shareholder’s Share Pledge, Earnings Management and Audit Decision—Based on Regression Method in Statistics
Authors: Zhao Minshu , Yuan Fangying
Published: August 2020

This article uses 2009-2019 Shanghai and Shenzhen A-share listed companies as a sample to study the impact of listed companies’ equity pledge behaviour on auditors’ decision-making. The empirical results show that if there is a pledge of large shareholder equity, the audit pricing will be higher than when it does not exist. At the same time, the greater the proportion of pledged equity is, the higher the audit pricing accordingly is. The study finds that the equity pledge behaviour would make auditors more likely to issue non-standard audit opinions. The state-owned nature has a positive regulating effect on the relationship between equity pledge and audit opinion. But it has a negative regulating effect on the relationship between equity pledge and audit pricing. In the study of the mechanism of action, it is found that the equity pledge affects the auditor’s decision-making by affecting the level of earnings management. The research in this article provides a reference for listed companies, auditor firms and regulatory authorities.
Data Diven Based Extraction and Recognition of Space Target’s Radar Micromotion Features
Authors: Guo Wenbo , Zhu Jubo , Wang Zelong , Liu Jiying , Yu Qi
Published: August 2020

The micromotion features of the space target is an important information source of radar target recognition. Multiple micromotions due to certain complex features can further characterize the specific targets and then improve the accuracy of the target recognition. With regard to the extraction and recognition of space target complex micromotion features, the data-driven method was used to conduct effective extraction and training recognition. On the one hand, the EMD method was used to effectively separate the complex micromotion components of the space target, and then the motion parameters of the target are estimated with high precision. On the other hand, we take the motion parameters of the target in various forms of micromotion as input and learn typical object movement characteristics by a machine learning algorithm, thus improve the precision and accuracy of target detection. The simulation results show that EMD method can accurately extract various motion parameters of space complex micromotion targets, and the neural network model can complete the target classification and recognition task with high accuracy.
Analysis of Relationship Between Hot News and Stock Market——Based on LDA Model and Event Study
Authors: Liu Chanyuan
Published: August 2020

This paper clustered the document of news released by major mainstream media outlets in November 2019 through LDA topic model and finds out the hot topic this month through the probability distributions between the topics and within the words. Then we backtracked on the topic and find the initial occurrence of the news, then categorized the news according to the status of the facts reported in the news. Then we carried on the research through using the constituent stock of concept stock in this model to report the event in a short-term event study, which finally find the breaking news could cause the related module in the short-term abnormal return while the continuing news would not do. It means that breaking news could allow media report to keep pace with market reactions, which the continuing news cannot promised. Investors will not be affected by continuing media reports on investment judgment as they have received relevant information in advance.