bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Computer Big Data in Internet Learning
Authors: Du Li , Sun Qian 
Published: February 2021

Abstract
In recent years, big data technology has been developed rapidly. While big data technology has been successfully applied in many industries, it has also completely changed the traditional education and teaching mode. Using big data technology for internet teaching is a mainstream trend at present, which makes up for many deficiencies in traditional teaching. As the current Internet teaching technology is still not perfect, this paper establishes the application research of computer big data in Internet learning. This paper makes an in-depth study on the current Internet learning. Through the survey, it can be seen that the popularity rate of Internet learning is very high, and the teaching effect has been affirmed in many aspects. However, because the technology is still in the initial stage of application, there are still many technical shortcomings, such as the information data security is not high, the teaching platform performance is not stable, the platform student management is not scientific and so on. For this reason, this paper gives the relevant suggestions for these deficiencies, as well as optimization and improvement measures. Moreover, through the in-depth study on the application form and application process of Internet learning, this paper believes that Internet learning is the major trend in the future teaching reform and development, and more attention should be paid to the students’ experience and the optimization and upgrading of related technologies in the process of reform and development.
Cross-Border E-commerce Marketing Development Model based on Big Data
Authors: Wang Xia , Cai Baoyu 
Published: February 2021

Abstract
With the popularity of cloud computing technology, the emergence of big data highlights its importance. Now big data has been used in the development mode of cross-border e-commerce platform of major Internet enterprises and has strong commercial value. However, there are still a variety of poor qualities goods and after-sales problems, which greatly limit the development of cross-border e-commerce. This paper analyzes the impact of big data technology on cross-border e-commerce marketing, formulates reasonable management strategies and environmental factors conducive to its own development, and analyzes the application of big data technology in the marketing system of a company. Drawing on the success factors of cross-border companies and applying the summarized marketing development model to local cross-border enterprises, it is found that the effect is significantly improved compared with the previous marketing mode, management mode and strategic planning, and enterprises using big data develop in a better direction.
Substation Location Selection Using GIS and Improved Matter-Element Extension Method
Authors: Chen Hong , Zhang Jianfeng , Tian Xiao , Liu Yuntian 
Published: February 2021

Abstract
In order to overcome the subjectivity and limitations of traditional substation site selection methods, and to achieve efficient and visualized substation site selection, this study conducted five candidate site locations to avoid the red line area in the geographic information system, then conducted a comprehensive evaluation of the site’s economics. Using the improved matter-element model, an evaluation index system for substation site selection was established covering four intermediate levels of poor geological treatment costs, vertical layout, policy compensation and special costs, and divided into five evaluation levels: excellent, good, average, and poor, Difference, and then determine each section domain and the object to be evaluated, use programming software to calculate the maximum correlation degree of the five areas to be selected for A, B, C, D, E are 0.9118, 0.8172, 0.9202, 0.9485, 0.8557. Respectively belong to the five levels of poor, general, general, poor, and general. Finally, in the GIS system, according to the economic efficiency of site selection from high to low, it corresponds to “cyan-blue, green, yellow, orange and red” in a gradual colour sequence for the five site selection areas Colouring. The results prove that this method has better early warning and auxiliary decision-making functions for substation site selection.
RETRACTED: Analyze the Development of Public English Courses education in Vocational schools Based on AI and Big Data
Authors: Feng Lijuan 
Published: February 2021

Abstract
Under the influence of economic globalization, more and more technical talents with good English expression ability are needed in modern society. At present, public English has become a compulsory course in vocational school. In order to train talents loved by enterprises, vocational school organize various education activities that are conducive to public English Learning under the background of national education reform. The purpose of this paper is to analyze the development of public English Courses education in Vocational schools Based on AI big data. This paper summarizes the latest research progress of big data analysis method based on AI technology. This paper analyzes the research status of machine learning in big data environment. Then this paper proposes a personalized and developmental curriculum education model. The model is based on the big data composed of classroom education, extracurricular self-study and part of daily life. Through data mining technology, the evaluation of each student in the course of learning is given. The results show that the failure rate and the average rate of the class are greatly reduced, and the good rate is increased from 30% to 66%.
Application Analysis of VR Virtual Technology in Environmental Art Design Teaching
Authors: Li Wenfang 
Published: February 2021

Abstract
VR technology has been widely used in various industries, and has brought huge benefits. The field also needs VR to inject more new vitality. The purpose of this paper is to analyze the application of vr virtual technology in environmental art design teaching. This paper introduces the basic concepts of panoramic video projection, then briefly analyzes the implementation principles and layout methods of mainstream projection methods. Using the knowledge and analyzing the advantages of practical teaching cases, constructions scheme of desktop virtual reality course. And the use of software for VR display. For the current art design teaching proposed new teaching methods. This paper evaluates the teaching effect of the application. The experimental results show that in the investigation, when you think that the use to create environment design situation is conducive to improving students’ enthusiasm for learning environment design, 37 students in the experimental class choose to promote, while 12 students choose to have no change, one of the students chose to be a hindrance.
Research on the Innovation of College Basketball Information Teaching Mode under the Background of Internet
Authors: Wei Wenting , Fang Wenxuan , Wei Jinrui 
Published: February 2021

Abstract
Currently, in most college physical education curriculum, college basketball teaching is based on students’ interests, but different students have different interests and hobbies, which leads to some students’ resistance to basketball knowledge and lack of learning interest in the actual teaching process. In recent years, the rapid development of Internet technology has made it widely used in all fields of life and work, which leads to the reform of traditional basketball teaching. On this basis, combined with the current teaching mode of colleges and universities in China, the concept of network teaching is introduced into basketball teaching. In this paper, the experimental class and the control class were established. The experimental class adopts the college basketball information teaching under the background of Internet, while the control class adopts the existing college basketball teaching mode. After the end of the semester, comparative analysis shows that the college basketball class designed in this paper can better play the enthusiasm of students and improve students’ interest in basketball class.
Application of MOOC in Physical Education Teaching Mode Under the Background of Big Data
Authors: Wang Linhan , Wang Ming 
Published: February 2021

AbstractWith the continuous development of network technology, the application of Internet technology in education mode is becoming more and more closely. MOOC education method that should be applied to online teaching platform is called the current mainstream hot topic. Applying big data technology to online teaching platform can effectively solve the problems of numerous and confusing teaching resources, difficult user selection, weak management of online learning process and teaching The resources can not be efficiently utilized, and the user’s sense of role is missing. The application of big data technology in network teaching has, to a certain extent, subverted the traditional teaching system, changed the teaching mode of unified place, unified time and unified content. According to the analysis results of big data, learners can flexibly choose the time and place of class according to their own needs and characteristics, and carry out personalized and customized teaching resource learning. These decisions are not Subjective, but through the analysis of big data, on the basis of objective and reliable data, the decision is made. In this paper, through a comparative experiment of two classes of students in Physical Education in a university, the results of big data analysis show that the application of MOOC in physical education teaching mode can improve students’ learning enthusiasm to a certain extent, and the satisfaction degree of students to MOOC is as high as 92%; it can also assist students to improve their academic performance, and the average score of classes using MOOC is 10 points higher than that under the traditional education mode about.
MGCN: Graph Convolutional Network for Drug Molecular Screening
Authors: Wang Shoujin , Zhu Yongyuan , Liu Jifei 
Published: February 2021

Abstract
The intersection of drug research and development and neural network research is getting closer, new methods and new technologies are emerging one after another, using neural network to improve the efficiency of drug research and development, and rapidly innovate the treatment of diseases. In drug development, one target protein corresponds to multiple drug molecules. In order to save the time and cost of new drug development, virtual screening of key steps in new drug development is studied. A virtual screening model for drug molecules is proposed, and the graph convolutional neural network is used to classify drug molecules to achieve the purpose of preliminary screening. The graph convolutional network model is constructed based on DGL and combined with cross-entropy and fully connected networks. The model is carried out by experimental means analysis. The experimental results show that the graph neural network can complete the classification task of drug molecules. Through the verification of molecular docking software, the screened molecules are real and effective, reducing the time spent on virtual screening, and it has become an inspiration for further exploration of graph neural networks in drug development.
A simple note on the growth rate of Covid-19 in Indonesia based on a curve trend generated by a spreadsheet
Authors: Anggaryani M , Prastowo T , Madlazim  , Supardiyono  , Asnawi  
Published: February 2021

AbstractThis preliminary study is aimed at examining the growth rate of Covid-19 pandemic in Indonesia in a framework of a nationwide issue. Using a spreadsheet, this study generates time-series development of the disease from its early stage in March to the late of July 2020. The study focuses on the analysis of three indicators, namely the number of people confirmly infected, recovered, and dead, daily reported by the authorities to monitor the severe outbreak. A number of groups of people, such as people under observation (ODP), suspected (PDP), and with no symptoms (OTG) are excluded from selected indicators due to difficulties in detection of people accounted for in each group. Cases confirmed are given by the results ofPolymerase Chain Reaction(PCR)testsfrom swab sampled and are not determined by those ofrapid tests. The data were collected from The Ministry of Health, The Republic of Indonesia and National Agency for Disaster Relief (BNPB). We report findings on the effectiveness of a PSBB policy that includes physical and social distancing during different stages and the possible roles of four connected parameters, namely community resilience, goverment control, medical access and treatment, and economy recovery. From the data acquired and presented in separate curves, we analyse the growth rate of Covid-19 in Indonesia. Regarding distinct trends of the curves with an indication of a continuous transmission, we conclude that combined factors, involving ineffective implementation of the policy and a low community resilience make the infectious disease outbreak uncontrollable in some sense.
Study of Steady State Heat Conduction in Composite Layer by Linear Triangular Finite Element
Authors: Riupassa Robi Dany , Waris Abdul , Viridi Sparisoma , Basar Khairul , Novitrian  , Abdillah Habibi 
Published: February 2021

Abstract
Finite element method with linear triangular shape function was used to numerically investigate steady state heat conduction in composite layer. This method divides each layer into a number of small elements. By defining elements, local node, global node, and temperature boundary conditions, an element coefficient matrix can be formed. Element coefficient matrix needs to be assembled to form a global coefficient matrix. The solution of the global coefficient matrix will provide the temperature value at each node. In this research, variations of the thermal conductivity value and temperature boundary conditions are applied. The results of the study will show the effect of different thermal conductivity value against temperature gradient.
Comparative Study on Fuel Assembly of Modular Gas-cooled Fast Reactor using MCNP and OpenMC Code
Authors: Raflis H. , Ilham M. , Su’ud Z. , Waris A. , Irwanto D. 
Published: February 2021

Abstract
The design study of GFR concepts comprises neutronic analysis of fuel pin and fuel assembly. The Monte Carlo method has advantages in three-dimensional (3D) geometry modeling but requires a high computation time. In this research, the comparative study of Gas-cooled Fast Reactor (GFR) using the Monte Carlo code. The GFR feasibility design study will be carried out with natural uranium with plutonium as fuel cycle inputs. The Monte Carlo method simulates GFR model at full-scale and heterogeneous three-dimensional (3D) using Evaluated Nuclear Data File (ENDF/B-VIII.b5) nuclear data. The code of Monte Carlo methods will be used in this research are the Monte Carlo N - Particle (MCNP) and OpenMC. The comparison of the GFR fuel assembly calculation simulation results is made between the MCNP and OpenMC code. The equilibrium cycle configuration is used as the basis model for the comparisons. The comparison of MCNP and OpenMC code gives a good agreement in criticality calculation of GFR that achieves delta kinf less than 1%. The (U-Pu)N fuel is a good candidate to be chosen in GFR research that gives kinf more than 1.1 in fissile contain 10%Pu and has the highest thermal conductivity. The Zircaloy-4 is the best candidate for material cladding in GFR design that provides the highest kinf.
Pebble Bed High Temperature Reactor for Electric and Cogeneration Application
Authors: Setiadipura T. , Irwanto D. , Suwoto  , Zuhair  
Published: February 2021

Abstract
Specific energy demand of Indonesia with its distributed energy demand required a special energy supply solution. The energy supply solution should be able to fulfil the electric demand of huge and growing population which spread in many different islands also to fulfil the energy demand to process abundances yet distributed natural sources. This paper proposes a pebble bed high temperature reactor as an energy supply in the form electric and/or cogeneration application. A parametric survey of the core geometry of a 150MWt Pebble Bed Reactor called PeLUIt is performed, follow by an equilibrium analysis of the optimized design. An accident analysis of depressurized loss of forced cooling (DLOFC) is performed to show the strong passive safety features of the design. Finally the heat-mass balance of the plant is also presented.
Heat transfer simulation in reactor cavity cooling system for experimental power reactor (RDE)
Authors: Yunus M , Kusumastuti R , Subekti M 
Published: February 2021

Abstract
To enhance the safety of experimental power reactor (RDE), Reactor Cavity Cooling System (RCCS) is required to support primary helium coolant. RCCS can be utilized for both normal condition or under accident. During the reactor accident with no power supplies and cooling pump down, RCCS works in a natural-circulation by using air in cavity and water in the cooling pipe. In this study, the process of radiation heat transfer from Reactor Pressure Vessel (RPV) to Water Cooled Pipe (WCP) was simulated. The natural circulation of air cavity and around the WCP was studied in three dimensional numerical model. The analyses are performed with Fluent code, which is a computational fluid dynamic code. Three parameter conditions of simulation were studied to compare the difference of them, so in this primary study, it can be known the influence of each parameter to the obtained results and it can be considered for development of future safety simulation in RDE reactor. From the simulation result, the temperature at bottom air cavity is higher than the top of the cavity. The temperature profile of water in the pipe also changes because of influence the heat transfer from Reactor Pressure Vessel. Gravity and radiation are very important parameter inputs to simulations in order to approach the real conditions.
Mechatronic Design HPS Test Loop of RDE
Authors: Kiswanta  , Sumarno E. , Santosa K. , Indrakoesoema K. , Handono K. 
Published: February 2021

Abstract
The electrical, mechanical and control system design of Helium Purification System Experimental Power Reactor Test Loop (RDE) has been conducted. The requirement system designed must be reliable operated, safety to personnel and equipments, ease of maintenance and operation, protection of equipment electrically, interchangeability of equipments and addition of the several model of tranducer. In order to achieve the above goals and obtain the desired results, the system based on electrical and instrumentation practical experiences will be needed. In this paper consist of the HPS electrical design and the instrumentation and control system. The criteria and the methods of designs of electrical and instrument equipments of the system have been discussed and investigated. The electrical and instrumentation control system drawing and requirement of design will be presented as the outcome of the design. The designed of power system analisys and also to overcome the problem of under voltage is consequently simulated by ETAP 12.6.
Mechanical properties and meso-damage evolution behavior of SUS 304 austenitic stainless steel
Authors: Liu Q , Li L , Shi Z M , Zhang H , Zhao H 
Published: February 2021

Abstract
Using MTS-Landmark material testing machine, Quanta-650 scanning electronic microscopy and Leica-LM/DM optical properties microscope, the mechanical properties and meso-damage evolution behavior of AISI304 steel at different annealing temperatures were studied. The results showed that the grain of AISI 304 steel grew up with increasing annealing temperature, and annealing twins appeared during the grain growth. The yield strength, tensile strength and micro-hardness of the samples decreased gradually with increasing annealing temperature. Based on the evolution characteristics of austenite grain boundaries, evolution of shape factor of the samples was researched at different plastic strains. Meso-damage evolution equations of the materials were established, and the material constant in the equation were closely related to the annealing temperatures. Normalized shape factor can reflect meso-damage evolution behavior of AISI 304 steel, which simply and effectively revealed the relation between marco deformation and microstructure.
Stepped Impedance 7th order Maximally Flat Low Pass Filter Using Microstrip Line for X-Band Applications
Authors: Salama S , Battah Y , Abuelhaija A 
Published: February 2021

Abstract
In this paper stepped impedance 7th order maximally flat low pass filter is designed and analyzed for X-band range at 9 GHz cut-off frequency. The filter is printed on Alumni substrate of dielectric constant 9.6 and thickness of 1.6 mm. The obtained attenuation is more than 20 dB. The Advanced Design System (ADS) software is used to design and simulate the proposed low pass filter. In addition, a comparison between filter design using insertion loss method implemented in stubs and stepped impedance is presented and discussed.
Dijkstra and Bidirectional Dijkstra on Determining Evacuation Routes
Authors: Rahayuda I G S , Santiari N P L 
Published: February 2021

Abstract
Determination of the best path or often called the shortest path finding is a method that has many benefits and can be applied in various cases and fields of science. In previous studies, authors have developed the shortest path finding program using various algorithms, such as held-karp, iterative deepening search, bidirectional depth first search and depth limited search. In this research author implements shortest path finding on information system for determining fire disaster evacuation route using Dijkstra and bidirectional Dijkstra. The program was developed based on web using vuetify.js framework. Both algorithms were tested on several datasets and the results will be compared to find out the strengths and weaknesses. Based on the research, the algorithm was successfully developed based on the web using the vuetify.js framework and successfully tested on several datasets, it is known that 40% of the test results show that bidirectional Dijkstra is better than Dijkstra, 10% vice versa and 50% get the same results from both algorithms. From this comparison it can be concluded that the bidirectional Dijkstra algorithm is better than Dijkstra. This research succeeded in proving that the bidirectional Dijkstra algorithm can produce a better route than the standard or classic Dijkstra algorithm.
Improving cold-region streamflow estimation by winter precipitation adjustment using passive microwave snow remote sensing datasets
Authors: Kang D , Lee K , Kim E J 
Published: February 2021

Abstract
Winter precipitation estimations and spatially sparse snow observations are key challenges when predicting snowmelt-driven floods. An improvement in streamflow prediction is achieved in a snowmelt-dominant basin, i.e. the Red River Basin (RRB), by adjusting the amounts of snowfall through satellite-borne passive microwave observations of snow water equivalent (SWE). A snowfall forcing dataset is scaled to minimize the difference between simulated and observed SWE over the RRB. Advanced microwave scanning radiometer-E (AMSR-E) SWE products serve as the observed SWE to obtain the solution to the linear equation between the AMSR-E and the baseline (no snowfall-forcing adjustment) SWE to yield a multiplication factor (M
factor). In the headwaters of the RRB in the United States, a Nash–Sutcliffe efficiency (NSE) of 0.74 is obtained against observed streamflow, with M
factor-adjusted streamflow during the snowmelt seasons (January to April). The baseline streamflow simulation without M
factor exhibits an NSE of 0.38 owing to an underestimated SWE.