bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Unbalanced Data Classification Algorithm in Quantitative Financial Risk Management
Authors: Zhu JinPeng , Wang HanChen 
Published: October 2020

Abstract
The global financial crisis that has erupted many times in recent years has not only harmed the financial systems of various countries, but even severely hit the economies of various countries. Therefore, the importance of financial risk early warning has become more prominent and the challenges facing it have become more severe. In view of this, it is very important to explore an extreme risk early warning model that suits the reality of the Chinese financial market, and to accurately predict and prevent extreme financial risks. This article first constructs the model’s early-warning indicator system, and determines the state indicators by synthesizing the two state indicator definition methods based on the crisis period and EVT, in order to determine whether extreme financial risks occur in the financial market at a certain time. The prediction performance of the improved SVM under different unbalanced sample data sets is compared. It is highly feasible to use it for early warning of extreme risks in China’s financial market. This paper presents a BADASYN algorithm based on boundary sample adaptive synthesis at the data level. The algorithm first finds a small number of samples in the class boundary region, then adaptively synthesizes some samples according to their distribution, and adds the newly synthesized samples to the training set. In the data set sampled by BADASYN, the support vector of the trained SVM model is mainly composed of newly synthesized samples, and finally the separation hyperplane is close to multiple types of samples. Experimental research shows that after testing SVMs constructed with four kernel functions, the prediction accuracy of each model is very high, reaching more than 93%, reflecting the stability of SVM prediction performance.
Preschool Teacher Education System Based on Remote Network System
Authors: Xu Meng 
Published: October 2020

Abstract
How to achieve effective communication between school parents on online platforms, online office work on campus, and storage and sharing of massive learning resources will surely become important issues facing early childhood education. The purpose of this article is to design a kindergarten teacher education system based on the remote network system. This paper uses the increasingly perfect non-relational database technology to help store massive big data resources, and uses its characteristics to improve the access and operation speed of big data resources, which will effectively solve campus information management and improve the processing efficiency of resource storage and access. Develop a comprehensive platform for online office, communication, learning, and resource sharing for early childhood education. Research In order to realize the storage of massive data and the rapid operation of the system, the system database chose a complementary method of combining MySQL database and MongoDB database, using MySQL to store data involving operations such as relational lookup, and using MongoDB to store various file and photo resources. The system is developed using the SSH framework. First, the functional and non-functional requirements of the system are analyzed. The functional requirements use UML to establish the overall use case diagram of the foreground and background modules respectively. Through the complementary technology of MySQL and MongoDB, the storage and access efficiency of big data and the operating speed of the system’s functional modules are greatly improved.
Research and Hardware Design of Image Processing Algorithm Based on FPGA
Authors: Wei Yanping , Xiao Hailiu 
Published: October 2020

Abstract
With the continuous development of computer technology and microelectronics technology, image processing technology is constantly being improved, especially real-time image processing technology has been studied by a large number of scholars. This article aims to achieve the purpose of FPGA-based fast image processing through the research of FPGA’s fast image processing algorithm. Based on the advantages of FPGA high-speed hardware computing and parallel computing, this paper proposes a design based on FPGA parallel dual template strategy, and designs a comparative experiment to verify. Obtain objective evaluation indexes of image processing results through experiments, and analyze the data results. The experimental results show that: the implementation of the mean filter algorithm based on FPGA parallel dual templates, the time required is about half that of the mean filter algorithm based on FPGA single templates. Relative to the reference Matlab software programming method to achieve 678 times performance improvement. It shows that the realization method of the mean filter algorithm based on FPGA parallel dual template is feasible. Give full play to the advantages of FPGA parallel processing data, improve the processing speed of the image algorithm module.
VR Open Computer Network Virtual Laboratory Based on Big Data Technology
Authors: Xiao Shoubai 
Published: October 2020

Abstract
The rapid development of computer technology and network bandwidth has produced unprecedented influence on the way of human learning. Along with the humanized development of computer software technology and high-level program language, experimental teaching is gradually becoming virtualized. Not only a variety of multimedia teaching courseware emerges one after another, but also a large number of virtual laboratories appear on the network. Virtual laboratory is essentially the simulation of real experiment scene, in which students should have similar experience and the same learning effect as real laboratory. Therefore, the virtual laboratory should be able to satisfy the students to carry out autonomous exploratory operation. The purpose of this paper is to study the open computer network virtual laboratory based on big data technology. This paper first introduces the meaning of big data technology, then studies the content of video decoding technology, and then introduces the definition scope and characteristics of virtual reality technology. This paper designs and implements VR open computer network virtual laboratory based on big data technology. The test results show that the system designed in this paper has good performance. The CPU consumption rate of the system server designed in this paper only accounts for 4.5%.
Economic evaluation model of greenhouse soil information collection technology based on fuzzy comprehensive evaluation
Authors: Lu Shuisheng , Sun Xiaoying 
Published: October 2020

Abstract
The purpose of soil information collection is to grasp the real-time status of soil, which is of great significance to improve the yield and quality of crops and improve the ecological environment. The purpose of this paper is to build a comprehensive benefit evaluation model of soil information collection technology based on the fuzzy comprehensive evaluation of the economy of greenhouse soil information collection technology. The experimental results show that in terms of economic and environmental benefits, the scores of wired communication technology and wireless acquisition technology are average and good respectively. In terms of social benefits, the scores of wired communication technology and wireless acquisition technology are good and excellent respectively, the scores of social benefits, the scores of wired communication technology and wireless acquisition technology are good and excellent respectively, the scores of comprehensive benefits of wired communication technology and wireless acquisition technology are general and good respectively, and the membership degrees of corresponding grades are 0.4144 and 0.5898 respectively.
RETRACTED: Network Information Security Risk Assessment Based on Artificial Intelligence
Authors: Wang Yaosheng 
Published: October 2020

Abstract
With the development of society and the progress of human civilization, science and technology are more and more widely used in people’s daily production and life, and artificial intelligence technology is also more and more widely used in this era. With the advent of the information age, the development of the network is faster and faster, and the popularization rate is higher and higher. The network information security problem has gradually become a hot issue of social concern question. With the increasingly open network environment, network attack tools become easier to obtain, more automated, more intelligent, which poses a huge challenge to information security protection. Therefore, in order to deal with the network information security problems in this information age, this paper studies the method of network information security risk assessment and analysis based on artificial intelligence, through in-depth study of network information security, simulate attacks on network information, so as to find the weakness of the current network information security system. In the research, a large number of network information security vulnerabilities are found by simulating the attack of network information, so as to repair the vulnerabilities one by one. Through the analysis, this paper studies the Content Filtering Gateway filtering system to filter out 94.8% of the virus and garbage, improve the network information security rate.
Application of Task Driven Method in the Computer Application Basic Course
Authors: Zhang Yan , Sun Shujie 
Published: October 2020

Abstract
In view of the existing that occupation college students’ learning interest is not high, docking and enterprise skills learned cannot work well in the computer application basic course, we use the task driven teaching method instead of the traditional, summarized the eight major tasks of the enterprise and its sub tasks based on the real work, and puts forward some problems should pay attention to in the process of operation.
Mooc Method of Military Theory Course Based on Network Technology
Authors: Zhao Jing-Yuan 
Published: October 2020

Abstract
With the development of information technology and the increasingly mature of network teaching, it has become an indispensable part of teaching reform to introduce moocs into the public curriculum system of colleges and universities. Combined with the characteristics of the Internet and big data, moocs and teaching have greatly improved the teaching effect and brought many advantages to the traditional teaching methods. Under the background of information technology era, military theory courses in colleges and universities have ushered in new development opportunities. Faced with the new teaching form of moocs, many colleges and universities have successively introduced military theory moocs, but the effect is not satisfactory. Therefore, it is very important to accelerate the combination of theory and online and optimize the teaching methods of military theory. The purpose of this paper is to explore the research on the application of military theory courses under the theoretical basis of network technology, so as to update the existing teaching Internet model by combining the application technology of Internet of things. This paper will adopt the research method of concrete analysis of specific problems and make data comparison to draw conclusions. The research results of this paper show that the advantages and disadvantages of moocs reflect the teaching reform path of military theory course based on moocs, which requires the establishment of professional moocs team and the provision of abundant course resources.
A Newton Type Iterative Method with Seventh-Order Convergence
Authors: Tao Yuxi , Wan Xiaofeng 
Published: October 2020

AbstractWe based on King Method, a seventh-order convergent Newton type iterative scheme is proposed in order to solving the root of nonlinear equation, the efficiency index of proposed method is 1.627. Numerical experiment show that the new iterative scheme has some advantages over other iterative schemes.
Molecular modelling as a downstream effort in the discovery of novel anionic sulphate surfactants
Authors: Iswanto P , Delsy E V Y 
Published: October 2020

Abstract
Sulphate anionic surfactant is a type of surfactant that is widely used as a cleaning agent. The discovery and development of anionic sulphate surfactant molecule is necessary because it has a huge impact, both in science and economics. Molecular modelling to produce new anionic sulphate surfactant molecules has been carried out. The mathematical equation of the Quantitative Structure-Property Relationship (QSPR) based on Ab Initio has been obtained. Molecules that were candidates for structural modelling and modification were those that have the smallest critical micelle concentration (CMC). The smallest experimental data was C16H33SO4Na with a CMC value = 0.000579 M. The result of this study was CnH3sSO4Na molecules with a theoretical CMC value of 0.000515 M.
Glucose-water interactions at increasing concentrations and temperatures as revealed by Near-Infrared Spectroscopy
Authors: Rondonuwu F S , Setiawan A , Muninggar J , Karwur F F 
Published: October 2020

Abstract
Water is an essential molecule and one of the most intensive research subjects, yet it is a peculiar molecule. The non-invasive measurement of blood glucose levels by near-infrared spectroscopy requires detailed information about the glucose-water interactions. The glucose in water induces strong hydrogen bonds and may influence the tetrahedral structure of water molecules. This knowledge is essential in constructing a non-invasive calibration of the blood glucose prediction model. How they are related to the absorption spectra of water and glucose is particularly valuable to comprehend. The evaluations were carried out using near-infrared spectroscopy, tracing changes in absorption intensity and shifts in corresponding peaks with glucose varying at an increasing concentration from a 0-0.9 molar fraction. The near-infrared spectra analysed were around 6900 cm-1 and 4716 cm-1 corresponding to the overtone and the combination band of water and glucose absorptions, respectively. The analysis suggests that glucose prefers to enter a water cluster, rather than bind to free molecules, and induce bond breaking at low glucose concentrations at which the molecular fraction is less than 0.05.
Ab initio computational study: Adsorption of CO molecule on various base metal oxide surfaces
Authors: Kurnia I , Siahaan P , Suseno A 
Published: October 2020

Abstract
The use of some base metal oxide already widely studied for having beneficial properties in CO oxidation catalytic system. The properties of these base metals such as lower working temperature, high CO affinity, and economically cheaper would be beneficial for this solid system catalyst. The study of various base metal oxides shown these kinds of characteristics, but there still a few analyses of comparison among the various base oxide metals used as the support system for the oxidation reaction catalytic system. This study would give a comparison in the difference of the adsorption energy of various base oxide metals. This adsorption energy is one factor that promoting the activity of the catalytic system due to its affinity to the reactant on their surfaces. The DFT ab initio calculation for this comparison shows that NiO is the base metal oxide that having the highest CO adsorption energy. This oxide could be a potential support system combined with potential solid oxidative catalytic system.
The effectiveness of online learning by EdPuzzle in polymer materials on students’ problem-solving skills
Authors: Giyanto  , Heliawaty L , Rubini B 
Published: October 2020

Abstract
This study aims to produce EdPuzzle content in polymer materials and examine its effectiveness on students’ problem-solving skills. The method used in this research is experimental research, employing a pre-test post-test one-group design through online learning. The subject of this study is 70 tenth grade students. Data were collected using students’ problem-solving skills tests and analysis of the learning process to determine the effectiveness of online learning. The data obtained were then analyzed using quantitative descriptive. The results showed that learning using EdPuzzle is statistically very significant in improving students’ problem-solving skills and is quite effective in online learning. The study concludes that EdPuzzle is quite effective to improve students’ problem-solving skills which are characterized by an increase in the score of pre-test to post-test, with an N-gain of 63%. The implementation of online learning EdPuzzle is quite effective with an effectiveness score reaching 91%.
Study of final temperature and heating rate variation to pyrolysis of Acacia (Acacia mangium W.) wood waste
Authors: Pranoto  , Nugrahaningtyas K D , Putri R N O 
Published: October 2020

Abstract
The research pyrolysis of acacia wood waste has been carried out. This research was conducted to determine the optimal conditions that can be used for the pyrolysis process of acacia sawdust and the effect of the pyrolysis products. The pyrolysis process was carried out on the principle of slow pyrolysis using a batch type reactor. Pyrolysis was carried out by varying the final temperature of pyrolysis 375°C, 475°C, and 575°C and variations of heating rates 5°C/min, 10°C/min, and 15°C/min with a holding time of 20 minutes. The content of cellulose, hemicellulose and lignin at raw material was determined with the van soest method and the values are 32.75%, 35.16%, and 16.81%, respectively. The result of the pyrolysis process in the form of char at the final temperature of 575°C with a heating rate of 5°C/min produces a calorific value of 6.816 cal/gram. In the tar (oil) tested using GCMS, the acacia tar contains quite high phenol, acetic acid, 2 propanone. The results of pyrolysis can be seen that the highest activation energy value is found in the pyrolysis process with a variation of the heating rate of 15°C/min and the final temperature of the pyrolysis 575°C which is 49.56 kJ/mol.
Carbon and zinc oxide synthesized by gelatin template as potential material for fight viruses covid-19: Future potential material
Authors: Ulfa M , Prasetoko D , Fajar M 
Published: October 2020

Abstract
The COVID-19 pandemic that attacks the respiratory tract is spreading rapidly to all regions in Indonesia. In this pandemic situation, daily products such as sprays, tissue paper and masks need to be developed using nanomaterials. In this paper, graphite carbon and zinc oxide were synthesized using gelatin as a pore guide. The morphology and character of graphite carbon and zinc oxide were characterized by SEM, EDX and XRD to address appropriate active centers to counteract the protein spike interaction in covid-19 with ACE in the human body. Several illustrations are presented in this paper to understand the opportunity of carbon and zinc oxide materials as the basis for making antiviral devices to store viral molecules so that human-to-human transmission can be prevented.
Silver nanoparticles (AgNPs) as photocatalyst in the photodegradation of rhemazol brilliant blue
Authors: Suprihatin I E , Lestari G A D , Mardhani R , Edoway V 
Published: October 2020

Abstract
The phytosynthesis of silver nano particles (AgNPs) and its use as a photocatalyst to photodegrade rhemazol brilliant blue are discussed. The AgNPs was prepared by reducing Ag+ from 0.01 M AgNO3 using frangipani (Plumeria rubra) water extract. The photodegradation was conducted by irradiating the suspension of the coloring agent and the AgNPs with UV rays at 259 nm. The optimum p H, AgNPs volume, and irradiation time were determined by measuring the degradation percentages at various pH, AgNPs volumes, and irradiation times. The study found that the optimum photodegradation occurred at pH 4, using 10 mL AgNPs, and irradiated for 60 minutes. Under the optimum conditions, AgNPs is capable of effectively photodegrading (97.84 ± 1.09) % of 600 ppm rhemazol brilliant blue
Synthesis of Carbon Nanotubes (CNT) by Chemical Vapor Deposition (CVD) using a biogas-based carbon precursor: A review
Authors: Saputri D D , Jan’ah A M , Saraswati T E 
Published: October 2020

AbstractCarbon is the fourth most abundant element in the universe. Among all carbon allotropes, carbon nanotube (CNT) with a cylindrical tube structure becomes an attractive carbon nanomaterial due to its unique physical and chemical properties. The typical gas sources that are usually used in CNT synthesis are mostly hydrocarbons, e.g., alcohol, methanol, methane (CH4), ethylene (C2H4), acetylene (C2H2), propane (C3H8), and cyclohexane (C6H12). Unfortunately, those carbon precursors are not environmentally friendly due to their origin from fossil fuels. Considering its continuity production, utilizing “green” alternatives and inexpensive materials will be more promising for industrial-scale production. Biogas is one of the alternative ideas as a carbon precursor in the process of CNT synthesis. Biogas consists of 40–60% methane (CH4), 40–60% carbon dioxide (CO2), and traces of nitrogen (N2), oxygen (O2), hydrogen sulfide (H2S), hydrogen (H2), and ammonia (NH3). The most commonly used to produce CNT is CH4through chemical vapor deposition (CVD). CVD is the most expectant and scalable method for future power and electronic devices with its economical and straightforward friendly design.
The Effect of Mandatory Insurer Reporting on Settlement Delay
Authors: Heaton Paul 
Published: October 2020

Abstract
To improve their fiscal position, Medicare and some state Medicaid programs have recently taken steps to mandate reporting of personal injury awards and thus facilitate subrogation against such awards. Participants in the tort system have argued these additional reporting requirements might delay settlement of claims, harming both plaintiffs and defendants. This article examines this problem empirically, using a rich, national data set of closed automobile bodily injury claims. Using a differences-in-differences research design that exploits the introduction of a new Medicare reporting requirement in 2011, it demonstrates that mandated reporting increased time to settlement by 19%, or an average of 58 days. Robustness checks using data from closed malpractice claims reveal a similar delay. Conservative calculations suggest such delays could generate hundreds of millions of dollars in waiting costs each year. Policymakers should be aware of and seek to avoid such costs as they assess whether and how to expand reporting of personal injury awards.
Medium-term results of arthroscopic treatment for femoroacetabular impingement
Authors: Migliorini Filippo , Liu Yu , Catalano Giovanni , Trivellas Andromahi , Eschweiler Jörg , Tingart Markus , Maffulli Nicola 
Published: October 2020

Abstract

Introduction
Femoroacetabular impingement (FAI) is a dynamic pathomechanical process of the femoral head–neck junction. Arthroscopic surgery for FAI has increased exponentially in the last decade, and this trend is expected to increase.

Source of data
Recent published literatures.

Areas of agreement
FAI promotes quick rehabilitation and low complication rates in the short-term follow-up.

Areas of controversy
Despite the growing interest on arthroscopic surgery for FAI, current evidence regarding the medium- and long-term role of arthroscopy are unsatisfactory.

Growing points
Systematically summarize current evidences, analyse the quantitative available data and investigate the medium- and long-term outcomes of arthroscopic surgery for FAI.

Areas timely for developing research
Arthroscopic surgery achieves very satisfactory outcomes for patients with FAI at a mean follow-up of 4 years.