bluuebunny/crossref_metadata_2025_split huggingface dataset:
Formation of hydrophobic polymer coatings on the track-etched membrane surface
Authors: Kravets L I , Yarmolenko M A , Gainutdinov R V , Satulu V , Mitu B , Dinescu G 
Published: June 2021

Abstract
Methods of forming coatings on the hydrophilic poly(ethylene terephthalate) track-$$$etched membrane surface by means of plasma polymerization of organic compounds, magnetron sputtering and electron-beam dispersion of polymers in vacuum are considered. It is shown that the usage of compounds with low surface energy as pristine materials to coatings application allows to obtaining hydrophobic coatings on the membrane surface. The resulting composite membranes with hydrophilic and hydrophobic layers can be used in membrane distillation processes for desalination of seawater.
Application of an anti-emission coating of pyrolytic carbon to the grid electrodes of high-power electrovacuum devices by deposition from the gas phase in carbon plasma
Authors: Kuznetsov V G , Kostrin D K 
Published: June 2021

Abstract
A technology for applying an anti-emission pyrocarbon coating by plasma-chemical gas-phase deposition to the grid electrodes of high-power electrovacuum devices has been developed. The plasma of a vacuum-arc discharge from a graphite cathode is simultaneously used for heating the grid electrodes, cleaning the grid electrodes from surface contamination, and for decomposing the reaction gas into active radicals. Experimental studies have shown that the satisfactory structure of the coatings and the adhesion of the coatings to the grid electrodes are provided at the temperature of the grid electrodes in the range from 550 to 1300 °C.
Evolution via friction of properties of DLC nanofilms on steel
Authors: Kuznetsova T A , Lapitskaya V A , Torskaya E V , Muravyeva T I , Mezrin A M , Samardak V Y , Khabarava A V , Trukhan R E , Chizhik S A 
Published: June 2021

Abstract
The results of the diamond-like carbon (DLC) coatings surface investigation with thickness of 100, 300 and 500 nm, applied on hardened steel via laser ablation methods and pulse arc discharge are presented. Topography, roughness, adhesion forces and specific surface energy of coatings before and after tribotests were studied using atomic force microscopy (AFM). The changes in the elastic modulus E and microhardness H of the surface after dry sliding friction have been established by nanoindentation method (NI).
Influence of magnetron spraying parameters on the structure of TiN-Pb coatings
Authors: Lozovan A A , Ya Betsofen S , Lyakhovetsky M A , Pavlov Yu S , Grushin I A , Nikolaev I A 
Published: June 2021

Abstract
Using X-ray diffraction analysis, we studied the effect of a number of deposition parameters of magnetron TiN-Pb coatings on substrates made of 30KhGSA and 12Kh18N10T steels on the structure of the coatings. It is shown that at a current value of 0.1 A on the Pb cathode, the coating consists mainly of TiN with a pronounced (111) texture. An increase in the current at the Pb cathode to 0.2 A leads to the dominance of Pb and PbO in the coating structure. The influence of ion-assisted and nitrogen consumption on the structure of coatings is noted.
Plasma jet stream simulation for formation coating and powder manufacturing processes
Authors: Okulov R A , Krashaninin V A , Popov E V 
Published: June 2021

Abstract
To carry out a comparative analysis of the parameters of the plasma jet flow, the configurations of the plasmatrons that are most common in industrial practice have been selected. The values of temperature, velocity and intensity of turbulence at the characteristic point are determined depending on the shape of the components of the plasmatrons. Recommendations have been developed for the configuration of technological equipment used in the processes of coating and powder production.
Biocoatings synthesized on magnesium alloy in system Ca3(PO4)2–CaSiO3 by micro-arc oxidation method
Authors: Sedelnikova M B , Ugodchikova A V , Tolkacheva T V , Sharkeev Yu P , Kazmina O V , Schmidt J 
Published: June 2021

Abstract
Biocoatings were formed on the surface of the Mg0.8Ca alloy by the method of micro-arc oxidation, in an electrolyte containing β-Ca3(PO4)2 (β-TCP) and CaSiO3, When the process voltage was varied in the range of 350–500 V, the thickness, roughness, and mass of the coatings increased to the values of 110 µm, 12 µm, and 11 mg, respectively. The presence of the following crystalline phases was determined in the coatings: α-TCP, wollastonite, forsterite and magnesium oxide. Coatings containing these compounds not only reduce the rate of bioresorption of the magnesium alloy, but also promote the process of bone tissue formation.
Acoustoelectronic interaction in metal island films
Authors: Simakov I G 
Published: June 2021

Abstract
The interaction of surface acoustic waves with conduction electrons of island films of various metals was investigated. Island films were formed on the surface of piezoelectric crystalline substrates: Lithium Niobate, Bismuth Germanate, and Piezoquartz. It is experimentally obtained that the surface acoustic wave attenuation as a function of film resistance has a characteristic maximum, and that the velocity changes from the velocity at the free surface of the substrate to that at the metallized surface.
Experimental research of film hydrogen accumulator model
Authors: Yurchenkov M I , Ivanov A G , Karpov D A , Chebukov E S 
Published: June 2021

Abstract
For the experimental research of hydrogen sorption / desorption processes, a model of a film hydrogen accumulator with a tape foil carrier has been developed and manufactured. Experiments were carried out to study the sorption / desorption (S / D) of hydrogen on a model of a film battery with a tape carrier (NiCr foil 20-50 microns with a titanium coating of 10-15 microns and a magnesium coating of 2-5 microns).
The features of porosity formation in multilayer stainless-steel samples formed by laser deposition of metal
Authors: Zavalov Y N , Dubrov A V 
Published: June 2021

Abstract
Experimental results of the identification of the intra-word and inter-layer porosity of multilayer objects formed during the laser deposition of austenitic stainless-steel powder at different values of technological parameters are presented. The dependences of the residual porosity, determined by processing the image from the cross-section sections of the samples, on the type of porosity and the scanning speed are given.
The surface roughness of samples formed in the combined technology of laser metal deposition with layer-by-layer remelting
Authors: Zavalov Y N , Dubrov A V , Makarova E S 
Published: June 2021

Abstract
The surface roughness of the layer formed during laser metal deposition before and after laser remelting is determined. The single-layer objects are formed using austenitic stainless-steel powder at different technological parameters in the combined technology of laser metal deposition with layer-by-layer remelting. The improvement of the roughness after laser remelting is shown.
Research on Data Mining of Intelligent Education Evaluation from the Perspective of the Knowledge Graph
Authors: Chen Yanan 
Published: June 2021

Abstract
The continuous development of Internet information technology given birth to data mining technology. Data mining is applied to analyze the internal relationships of data and provides a more optimized advancement way. The paper focuses on how to improve the data mining and analysis capabilities of intelligent education to associate students of the same characteristics. A cluster analysis method was utilized to construct a students’ knowledge graph model, which used a text classification algorithm to classify the evaluation questions and attribute them into various knowledge points. On the basis of the analysis on the data generated from online education, the clustering algorithm was adopted to classify the learning characteristics of the students. A knowledge graph developed by associating the students with similar characteristics was visualized be means of information technology in order to realize visualized and intelligent teaching.
A Comparative Genre Analysis of Chinese Folk Song Huar Based on Digital Humanities
Authors: Tang Qianqian , Xu Yan , Yuan Ying 
Published: June 2021

Abstract
As an intangible cultural heritage, the folk song Huar is a precious name card of Chinese national culture. Its protection and inheritance are of great significance for promoting multi-ethnic cultural identity and enhancing cultural confidence. Genre research is an important topic in the study of Huar. However, current Huar genre researches are mainly based on qualitative methods. Digital Humanities is an emerging discipline that applies computing and digital technology to the study of the humanities. Comparing to traditional methods, Digital Humanities is a more accurate and efficient method of style analysis on literary texts. Through the methods of Digital Humanities, we can objectively show and verify the similarities and differences between Huar genres, and make up for the lack of objectivity in the traditional Huar genre research. Therefore, in this paper we combined qualitative and quantitative methods to make a comparative style analysis on Hehuang Huar and Taomin Huar from two aspects, namely rhythm and sentence pattern. Furthermore, we explored the reasons in depth behind these surface rules from the perspectives of music, literature, nationality and history. We simultaneously use hierarchical clustering to verify the discrimination of genres on specific style features. The result of this research shows that the research perspective and methods of digital humanities can provide objective conclusions for Huar researches, which can provide data support and scientific basis for researchers or enthusiasts to distinguish, appreciate and study Huar.
AN Analysis of COVID-19 Clinical Research Based on Trials & Publications in 2020
Authors: Zong Yanxiang , Zhu Heying , Xin Jesse Z. X. , Zhang Yin , Li Huoyou , Wang Lei , Wu Qingqiang 
Published: June 2021

Abstract
The global pandemic of COVID-19 has brought huge public health challenges to the world. To meet the challenge, researchers worldwide have carried out a series of clinical studies. This article aims to analyze the progress of COVID-19, and explore the development and main research directions in 2020. The clinical trials focus on the design of the trial plan, which can be registered on the platform after the design is completed. The purpose of clinical publications is to publish trial results, focusing on in vitro tests, drug screening and so on. Based on these characteristics, this paper analyzes both clinical publications and clinical trials, and explores the development of global clinical research in 2020 from countries, intervention methods and trial designs. The experimental results show that the United States and China have published the most publications and carried out the most clinical trials. The maximum intervention methods in clinical trials & publications are focused on the drugs.
The Application of Computer Big Data in Internet Learning
Authors: Wu Zeyu 
Published: June 2021

Abstract
This article analyzes the application advantages and application process of computer big data in Internet learning. The author studies the specific applications of computer big data in online live broadcast, online interaction, online search, and online software. The author puts forward the optimization measures of how to do a good job in guiding students, optimizing course learning mode, and strengthening the training of teachers’ strength. The purpose of this article is to give full play to the application value of computer big data and continue to optimize the Internet learning model.
The Cross-agency Sharing Scheme and Data Quality Evaluation —— A Case study of Geo-spatial big Data
Authors: Bai Yi , Li Song , Zhang Wei 
Published: June 2021

Abstract
In order to improve the sharing degree of big data and solve the pain points that are unwilling to share and can not be shared, cross-agency analysis and research should be carried out. Aiming at the construction characteristics of Geo-spatial big data, the main problems and solutions in Geo-spatial data sharing were analyzed. Starting from the management system, technical standards and physical architecture, a big data cross-agency sharing scheme was proposed. Then the quality of 3D building model data were evaluated . The results showed that constructing systematic cross-agency sharing solution will be helpful to promote the rational, standardized and efficient application of Geo-spatial big data.
Research on City Center Identification and Optimization Strategy Based on POI Data——Taking the Four Districts of Qingdao as an Example
Authors: Xie Xudong , Luan Xuezhen , Xue Ying 
Published: June 2021

Abstract
With the help of analysis tools such as mean nearest neighbor, standardized ellipse and kernel density of ArcGIS software, this paper uses POI data to deeply identify and analyze the urban polycentric spatial structure of four districts in Qingdao, and draws the following conclusions: the multi-center layout of the four districts in Qingdao presents five major urban centers with “one principal, two assistants and two clusters”, and a polycentric spatial pattern with strong main center and weak sub-center. In the future urban planning and development, it is necessary to establish a hierarchical and orderly multi-center spatial structure system, strengthen the diversity and complexity of urban central functions, and improve the guidance and support role of transportation for each functional center.
On the Casas-Alvero’ s Conjecture
Authors: Su Jiaxuan 
Published: June 2021

Abstract
As we all know, every derivation of a polynomial that is a nth degree of another polynomial has a common factor with this polynomial. Then, Eduardo Casas-Alvero came up with a conjecture that think opposite with the axiom we just talked before. That is to proof this polynomial is a nth degree of another polynomial if every derivation of this polynomial has a common factor with this polynomial. We are going to use different method to attack this conjecture and prove it when n is small.
RETRACTED: Research on Decentralized Access Control in Big Data Environment
Authors: Liu Nianzu , Ma Weichen , Shen Danjie , Guo Bing 
Published: June 2021

Abstract
With the rapid increase of network data, there are many challenges of security about data sharing in big data environment. The traditional attribute-based access control model generally adopts the centralized method. In the process of practical operation, once the decision node is attacked, the method will bring security risks to data resources. In order to improve the security of centralized access control and adapt to both dynamic and fine-grained characteristics of data access control in big data environment. The decentralized access control method for big data is proposed by combining the blockchain technology with attribute-based access control model.
Research on E-commerce Customer Evaluation System in the Context of Big Data: Taking Amazon as an Example
Authors: Yuelin Xu , Danyang Xu , LiHui  
Published: June 2021

Abstract
Amazon provides the customers an opportunity to assess their purchases. Manufacturers use this data to acquire further insights into the marketing the timing of participation, and potentially successful product designs.
The first step is to preprocess the raw data by detecting outliers and using cubic spline method to complete them and verify the correctness. Then, the data is analyzed in time order, followed by data quantification and visualization. The conclusion is that the comment does affect the star rating.
Finally, as a consultant hired by Sunshine, put forward some suggestions to the company’s marketing director: elaborating the establishment of relevant models, explaining the problems solved by the corresponding models, and summarizing the team’s analysis and results.
Research on the Application Status and Countermeasures of College English Blended Teaching Model under Big Data
Authors: Ding Zhaoxia 
Published: June 2021

Absrtact
Under the background of the development of big data, the mixed teaching mode has been widely used in college English teaching, which can make full use of the advantages of big data and realize the sharing of teaching resources. Especially for the English teaching of science and engineering major, the application of big data can provide students with more opportunities for autonomous learning and practical application, which greatly enhances the English thinking ability, inquiry ability and application ability of college students. This paper analyzes the role of hybrid teaching in college English teaching under big data, probes into the present situation of hybrid teaching, and puts forward the strategy of applying hybrid teaching in college English.
An accurate diagnosis of coronary heart disease by Catboost, with easily accessible data
Authors: Zhang Xiaoyu , Wang Mu , Wei Wei , Xu Yang , Gao Lisheng , Sun Yining , Ma Zuchang , Wang Shijun 
Published: June 2021

Abstract
Coronary heart diseases (CHD) have become the leading cause of death worldwide. Coronary angiography is the “gold standard” for diagnosing this disease. However, the invasive risk and expensive price make it difficult to promote on a large scale. This study was using Catboost to diagnose CHD through simple indicators. 2642 samples, including 717 patients, were collected from 2018 to 2019. 33 features were collected, including demography, anthropometry, questionnaire and laboratory examination indicators. The diagnosis model of CHD was established by using Catboost, random forest and logistic regression. Accuracy and area under ROC (AUROC) were used to evaluate the classification performance of the diagnosis models. In order to facilitate the application, we also set up a simplified model merely based on non-laboratory dataset. Catboost showed the best performance in identifying patients with CHD. The accuracy of Catboost, random forest and logistic regression was 82.5%, 75.1%, 75.8%, respectively, and the AUROC of them was 0.881, 0.837, 0.832, respectively. Age, total cholesterol and family history of coronary heart disease were the three most important risk factors for diagnosing CHD. Catboost also worked best in simplified models with 77.9% accuracy and 0.857 AUROC. The models can contribute to early screening and diagnosis for CHD, which would facilitate the prevention and timely treatment of the diseases.
A crowdsourcing framework for retinal image semantic annotation and report documentation with deep learning enhancement
Authors: Shao Jiahui , Li Jin , Kong Weizheng , Liu Shifan , Wu Junyi , Wu Huiqun 
Published: June 2021

Abstract
To propose and implement a crowdsourcing framework for retinal image annotations to improve the annotation efficiency. In this study, open-source Bluelight was taken as backbone of the front end for online manual retinal image annotation for image semantic annotation and report documents, and based on that intelligent annotation and classification with deep learning (DL) was supplemented. For DL modules, we trained Mask-RCNN model to explicitly label the area of optic disc and macula. Furthermore, we trained Inception V3 model to classify diabetic retinopathy (DR) and normal retina. Then, we used Flask as the backend serving DL models. Finally, the implementation of interoperable annotation reports documentation and retrieval were conducted based on Lucene. The crowdsourcing framework was specially designed for professional doctors and computer researchers who have the ability to annotate. It efficiently and quickly completed the annotation of the retinal image and the macular area, and at the same time classified DR. Under this Browser/Server architecture, the tool achieved good cross-platform performance. In particular, the framework could provide annotation report documents to facilitate the optimization of subsequent DL models. Such crowdsourcing framework and reports documentation for retina semantic annotation could improve the effect of annotation and classification and worth further improvement and clinical validation.
Research on Intelligent Construction Algorithm of Subject Knowledge Thesaurus Based on Literature Resources
Authors: Wang Xiaoxia , Xu Xiaozhong , Zhang Jiarui , Zhu Yue , Fan Yuhang , Xu Pengjing 
Published: June 2021

Abstract
The implementation of National Science and Technology Innovation Strategy demands exponential growing in knowledge services on literature information institutions. It is the most important knowledge organization tool for Information Retrieval, which can be widely used for semantic citation, organization and retrieval of literature resources. This study aims to develop an innovative algorithm for constructing subject thesaurus based on massive literature resource data and mining academic neologisms, also the semantic relationship between academic neologisms and subject system. We firstly collect a dataset of literature corpus, corresponding work for data pre-processing carried out. Then using the FastText model to complete academic neologisms mining, we construct an automatic categorization model of academic neologisms based on the Bert and TextCNN algorithm. The algorithm proposed in this study is validated by 8.1 million multi-source and heterogeneous literature data in the field of marine disciplines. The result shows that the algorithm can effectively replace 90% of the manual annotation volume, mine a large number of high-quality marine neologisms and successfully build the marine science knowledge base with a pass rate of 82.6% reviewed by expert, which present high accuracy and certain engineering application prospects.
Network Security Monitoring Method Based on Deep Learning
Authors: Yu Tianxi , Yin Xiaoyao , Yao Menglin , Liu Tong 
Published: June 2021

Absrtact
With the rise and rapid development of mobile communication, big data and artificial intelligence technology, we are entering the era of mobile Internet. With the continuous intellectualization of network security and infrastructure, information technology has been widely used in the field of industrial control, making network security more and more open, which brings a new network security control system to the traditional relatively closed industrial control system. This paper mainly introduces the network security monitoring method based on deep learning. In this paper, the network security monitoring method based on deep learning is studied, and the network security monitoring planning is designed by using image analysis, and the feasibility of detection model and deep learning is analyzed reasonably. A network security monitoring method based on deep learning is designed. Through data collection, feature extraction and neural network model training of network security power consumption information, non-invasive network security monitoring is realized. This method can detect network security information attacks that cannot be found at the network level, and improve the security performance of network security. The experimental results show that the network security monitoring method for deep learning increases the network security efficiency by 24%. The limitations of the research on network security monitoring method for deep learning and the methods and paths to provide good network security monitoring planning for image analysis application are analyzed, discussed and summarized, so as to enrich the academic research results.
Training framework based on multi model competition for deep reinforcement learning
Authors: Lin Yixian 
Published: June 2021

AbstractIn this paper, we propose a simple, effective and universal deep reinforcement learning training framework, inspired by A3C algorithm and genetic algorithm. The framework uses multi-process technology to realize multiple model competition and optimal evolution to optimize the deep neural network during the training process. The experimental results show that the proposed training framework can improve the training effect of reinforcement learning algorithms to a certain extent.