bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Survey on Recent Applications of Cloud Computing in Education: COVID-19 Perspective
Authors: Agrawal Somya 
Published: March 2021

Abstract
Due to the outbreak of coronavirus pandemic (COVID-19) in recent times, almost all countries have been affected in a drastic way, impacting delivery mode of education in world everywhere. Several schools, colleges and universities are under lockdown or have been forced to provide online education. To meet the existing challenges due to COVID-19, it has become highly critical that educational institutes become more efficient in virtual delivery of quality teaching services. In here, cloud computing provides an excellent platform for educators to improve their teaching practices and productivity. Cloud computing presents an ideal opportunity as it not only saves costs, but also power, due to the simultaneous usage of infrastructure by several stakeholders for the purposes of teaching, learning, and research. This is a short survey paper which explores the applicability of cloud computing within the context of educational settings. It also describes a few applications such as cloud rendering, gamification and collaborative e-learning technologies. In the end, a few challenges have also been presented.
Asynchronous Communication for Improved Data Transport in The Network
Authors: Zepeda S , Nuñez A 
Published: March 2021

Abstract
Currently there are two types of interaction in web systems mediated by synchronous and asynchronous communication, each of them with its programming and interaction paradigms. Although intuitively we can say that asynchronous communication is more efficient in data transport, there is not much research on this topic. We present a comparison of these two types of communication by requesting the same data from a server and receiving a client. The requests are through the traditional web forms and an experimental semantic interface, which only needs the data in plain text as a response from the server. The results found are of interest for the problem of excessive traffic on the network. This research can open new lines of investigation or generate new paradigms and programming models to improve communication between client and server.
An Intelligent Mobile Application Testing Experience Report
Authors: Tran Chi Thi Phuong , Valmiki Mohana Gudur , Xu Guoyan , Gao Jerry Zeyu 
Published: March 2021

Abstract
Artificial intelligence applications provide tremendous opportunities to improve human life and drive innovation. AI systems/applications which operate in a real-world environment have to encounter an infinite set of feasible scenarios. Conventional testing approach to test the AI application allows only limited testing and does not allow taking the different contexts into consideration and may lead to insufficient validation and characterization. Therefore, to ensure robustness, certainty and reliability of AI applications, the authors applied classification-based AI software testing framework and 3D decision tables to generate test cases. Moreover, the authors compared the quality assurance metrics (accuracy, correctness, reliability and consistency) of AI and non-AI functions in the AI mobile application scenario. Our results indicate and confirm that complete AI function validation is not possible with conventional testing methods, but AI software testing strategy proposed based on classification framework and 3D decision tables has a good effect.
A Fault Line Selection Technique for Single-Phase-to-Earth in network grounded with Arc Extinguishing Coil
Authors: Si Rui-Qi , Zhao Hu , Guo Jia-Dong , Shi Jia-Wei 
Published: March 2021

Abstract
For the fault line selection of single-phase-to-earth network, the instantaneous characteristic of the arc extinguishing coil is worth expecting. Focused on the transient characteristics in fault line selection technique, the sinusoid adaptive filter (SAF) and the sinusoid approximation of instantaneous signal (SAIS) are adopted in this paper. SAF is used to obtain the grounding moment, while SAIS is applied to obtain the direction and amplitude of the zero-sequence fundamental current when grounding happens. As for eliminating the influence of current transformer (CT) polarity, the compensation feature realized by SAIS is effectively adopted in selecting process. The techniques and methods in the paper have been applied to Chongqing Electric Power Co. for 5 years. In 5 years, hundreds of grounding faulted line has been chosen correctly, 6 wave records of which are shown in the paper.
Test Platform of LTE-U Communication System Based on FPGA
Authors: Zhang Rui , Shi Guchen , Jiang Wei , Chen Qiuxia 
Published: March 2021

Abstract
In order to solve the problem that the LTE communication system cannot be easily deployed, we design a test platform of LTE-U communication system based on FPGA. The test platform includes mobile terminals, base stations and base station networking system. It supports 5G unauthorized frequency band, WIFI and 100M network. A single base station can support up to 8 terminals with a distance of 1 km. It uses an omnidirectional antenna to communicate with the terminal and uses a gigabit ring network between base stations. In the process of mobile communication, we use RSSI (received signal strength indication) and bit error rate as the evaluation criteria and test the 32 terminals covered by the chain network and 4 base stations. The test platform can complete the LTE-U test well.
Computational-Efficient Iterative TDOA Localization Scheme Using a Simplified Multidimensional Scaling-Based Cost Function
Authors: Li Liming , Ding Baogang , Sun Rui , Jiang Wuyang 
Published: March 2021

Abstract
This work deals with source localization with time-difference-of-arrival (TDOA) measurements. Recently, a multidimensional scaling (MDS)-based iterative localization scheme is introduced in the literature, where an MDS-based cost function is defined as the norm of the difference matrix between two scalar product matrices. The minimizer of the MDS-based cost function which is computed by Newton’s iteration is considered as the estimate of the source position. However, the scalar product matrices of the MDS-based cost function are of high order, which need a lot of computations in each step of the Newton’s iteration. In this paper, a computational-efficient iterative localization scheme is proposed. In the proposed scheme, a simplified MDS-based cost function is constructed from two low-order matrices that are converted from the high-order scalar product matrices by a few steps of Lanczos iteration, and then the Newton’s iteration is applied to find the minimizer of the simplified MDS-based cost function. Simulation results show that the localization accuracy of the proposed scheme is nearly the same as that of the original scheme, whereas the computational complexity of the proposed scheme is about 20% as much as that of the original scheme.
Remote Sensing Camera Automatic Test System Based on Ethernet
Authors: Zhang Zhandong , Yang Luping , Zhang Xiaohong , Zheng Jun 
Published: March 2021

Abstract
With the rapid development of high-resolution remote sensing camera and the rapid increase of the number of remote sensors, telemetry data and image data have the characteristics of large amount of concurrency and high real-time. These characteristics bring great challenges to the test, interpretation and processing of massive data, which requires a lot of manpower and time resources, meanwhile, it is easy to cause repeated test work because of the errors occur during operations and interpretations. In order to improve work efficiency, test coverage, test accuracy, comprehensiveness, and human resources, developing automatic and intelligent test equipment is becoming much more particularly urgent and necessary. The test system proposed in this paper uses the on-line monitoring and diagnosis system to analyse the running state of the equipment in real time, find out the system fault in time, locate and eliminate it. The system can put forward the network protocol of data processing and storage, command control, real-time analysis and transmission of telemetry information and display the realization way of the test system workflow. It is expected that the system test efficiency will be increased by more than 5 times. In addition, the efficiency of fault diagnosis and data processing will be increased by more than 3 times. The automatic test system can solve the conflicts between test quality and human resources, moreover, the architecture patterns based on Ethernet is easy to expand and reconstruct.
The Research of an On-demand Threaded Interrupt Technology of Serial Port Based on the Power Edge Smart Device
Authors: She Wenkui , Yang Fan , Wang Shuang , Li Yuanyu 
Published: March 2021

Abstract
At present, the common problems facing the low-voltage power distribution system lie in plenty of equipment and wide range of power distribution. In order to address these problems, the overall architecture of the cloud-pipe-side-end is introduced through the IoT system in electric power distribution, where the end device is connected to the low-voltage power distribution system via the serial bus of the edge device and carries on data collection and real-time edge computing. As the core node, the edge device is required to have excellent real-time capability of timely detection and real-time response to the fault of various low-voltage power distribution facilities. In consideration of this, this paper proposes an on-demand serial port interrupt threading design to ensure the real-time performance of an electrical edge smart system. According to the experimental results, as the number and load of serial port devices increase, the real-time task dispatching rate continues to decline until the transformation, and the impact on the real-time task dispatching rate is limited after the threaded interrupt. That is to say, the method is effective in ensuring the dispatching rate of real-time tasks for the edge smart terminals.
Microbial Community Analysis based on Bipartite Graph Clustering of Metabolic Network
Authors: Zhang Chen , Deng Li 
Published: March 2021

Abstract
Microbial metabolism network is significant for the study of the microbial community, which is crucial for microbiome related diseases, such as inflammatory bowel diseases (IBD). In order to understand the difference of gut microbial communities between IBD patients and healthy people. Firstly, metabolic bipartite networks—microbes-compound graph are proposed and then built for healthy people and IBD patients respectively, which preserve more metabolic information than the traditional unipartite network. Secondly, with the use of the community detection of LPA in weighted bipartite graphs, the community modules of the two networks are obtained. Finally, two networks are compared to analyse the differences between healthy people and IBD people from several perspectives, such as NMI, centrality, clustering coefficient, species and compounds related to IBD disease, and cross-validation is performed to prove that all results are reliable and robust. The result shows that the gut microbial communities of healthy people and IBD patients are quite different, and the diversity and stability declined. From the clustering results, it can be judged that the distribution of disease-related bacteria changed.
The Throughput of TCP Over Wireless Loacal Area Networks
Authors: Liu J , Lu J , Wang J , Dang J 
Published: March 2021

Abstract
The TCP protocol performance over Wireless Local Area Networks with 802.11b is analysed in this paper. Based on the communication system consisting of a large number of source-destination TCP pairs, a model for a TCP connection is proposed. According to the principles of TCP and RTS/CTS Access mechanism, the normalized throughput and the utilization of time slots are conducted. Based on the relevant parameters at TCP and MAC layers, TCP performance are analysed, and factors which determine TCP performance are explicitly obtained.
Development of Requirements for The Content of a Digital Passport and Design Solutions
Authors: Donetskaya Julia V. , Gatchin Yuriy A. 
Published: March 2021

Abstract
The work presents the results of the development of requirements for the content of a digital passport and design solutions. The composition of each of them is listed, taking into account the specifics of the activities of a particular enterprise and the design tasks to be solved. On this basis, an execution sequence for creating and using a digital passport is proposed.
Design Procedures for The Analysis of The Components and Parameters of a Digital Passport
Authors: Donetskaya Julia V. 
Published: March 2021

Abstract
The design procedures for the analysis of the components and parameters of a digital passport is a main part of the development of design procedures for the analysis of design solutions. Its main idea is to clarify the models of components and their parameters, formed at the stage of creating a digital passport, and use them to find the desired solution. Further, the development of rules for the selection of digital passport components descriptions in the form of fuzzy variables is performed. As a result, for each component, a range of values is determined that is comparable to a similar range specified by the requirements for the design solution. The results obtained in this case are used in the development of a similarity criterion, as well as an algorithm for forming a design solution.
Twitter Sentiment Analysis on Coronavirus: Machine Learning Approach
Authors: Machuca Cristian R. , Gallardo Cristian , Toasa Renato M. 
Published: March 2021

Abstract
In machine learning, a fundamental challenge is the analysis of data to identify feelings using algorithms that allow us to determine the positive or negative emotions that people have regarding a topic. Social networks and microblogging are a valuable source of information, being mostly used to express personal points of view and thoughts. Based on this knowledge we propose a sentiment analysis of English tweets during the pandemic COVID-19 in 2020. The tweets were classified as positive or negative by applying the Logistic Regression algorithm, using this method we got a classification accuracy of 78.5%.
Electronic Contract Ledger System Based on Blockchain Technology
Authors: Ma Feng , Tang Ning , Xu Rui , Zhang Ziqian 
Published: March 2021

Abstract
The rapid development of the information Internet has promoted the development of electronic contracts, but user identities have been stolen and electronic contracts are easily tampered with. Seriously affected the fairness and security of online electronic transactions. For the main body of the transaction, how to confirm that the data identity of the transaction body has not been misused and the transaction electronic contract has not been tampered is the key problem which needs to be solved first. This paper designs the electronic contract platform by combining user identity authentication, encrypted transmission of electronic contracts and blockchain ledger storage. Ensure user identity uniqueness, contract transmission data integrity and non-tampering, and traceability of the signing process, thereby achieving security and fairness.
Blockchain-based Searchable Proxy Re-encryption Scheme for EHR Security Storage and Sharing
Authors: Yang Xiaodong , Li Xixi , Chen Aijia , Xi Wanting 
Published: March 2021

Abstract
The sharing of electronic health records (EHR) has shown significant advantages in the accurate diagnosis of patients and the development of medical institutions. However, due to the privacy and sensitivity of medical data, it is easy to cause security issues such as difficulty in data sharing among different medical institutions and easy leakage of data privacy. Because the blockchain has the characteristics of non-tampering, anonymity, and decentralization. We propose a blockchain-based searchable proxy re-encryption scheme for EHR security storage and sharing. First, we use blockchain and cloud server to store encrypted EHR together to prevent EHR from being tampered with and leaked. Secondly, we use a certificateless encryption and proxy re-encryption based on identity and type scheme as a data sharing protocol. Meanwhile, searchable encryption technology is used to generate a keyword index. Moreover, the proxy node is selected by the delegated proof-of-stake (DPOS) consensus algorithm, which ensures the privacy, immutability and security. It realizes the safe access of third-party data users to medical health data. Finally, security analysis and evaluation show that our scheme can resist identity disguise and replay attacks. In addition, it has stronger security and higher efficiency.
Forecasting of Credit Card Default Based on Incremental Random Forest
Authors: Gao Xiang , Wen Junhao , Zhang Cheng 
Published: March 2021

Abstract
In this paper, the incremental random forest algorithm is proposed for the classification and prediction problem of dynamically increasing data. Traditional batch machine learning algorithms perform modeling at one time and cannot allow newly generated samples to participate in learning, which leads to too much model deviation. This paper combines incremental learning with random forest and proposes incremental random forest. Applying this algorithm to the problem of predicting credit card customer default behavior can help banks control risks and reduce losses. It is important to conduct card issuance audits on card issuers and early warning of risks to cardholders. The algorithm performed better in the experiment of predicting the default behavior of credit card customers based on a batch of credit card holder data of a bank in Taiwan. Compared with random forest, decision tree, logistic regression, naive bayes, BP neural network, and support vector machine, it has relatively better performance in our experiment.
How Science and Inventing Play Together: Example of Averaging and Mixing Processes Design
Authors: Yakovis L M , Chechurin L S , Federa V D 
Published: March 2021

Abstract
The problem of poor systematic support of the stage of ideation in practical engineering design is addressed. Mathematical modelling of process’s dynamics is used to generate alternative architecture of a technological unit. The approach is applied to the design of mixing-averaging complex, where the analysis of statistical dynamics equations paves the road to new design concepts. The parametric analysis and optimization of new solution demonstrates potential benefits and savings. The study suggests an iterative scheme of conceptual design, where quantitative and qualitative design tools work together.
Evaluation of the Color of Mango Puree (Mangifera Indica) Creole Variety of Chulucanas Influenced by the Size of the Refined Pulp and Interaction Time to Environmental Air
Authors: Hernandez Ernesto , Sôcola Zury , Choque Tania , Hernandez Miguel 
Published: March 2021

Abstract
In order to determine the values of the dependent variable called “Color of the mango puree”, first the peel and the seed must be extracted by pulping and secondly refined again on a fine mesh sieve to obtain the puree. Five mesh sizes were evaluated from the first independent variable called “Sieve size” and corresponding to the second independent variable “Interaction time” ten different times were evaluated every 15 minutes from zero minute to 135 minutes. As for the dependent variable, the Hunter Lab coordinates were evaluated, using a Minolta CR-400 colorimeter, with three levels of the variable, which are the brightness, the a-coordinate a (a+: yellow/a-: blue), and the b-coordinate (b+: red/b-: green). As far as the results of the colour coordinates are concerned, during refined pulping for the same time, predominantly the smaller the hole size (larger mesh size) the lower the values for luminosity and the b-coordinate (b+) will be obtained: yellow colour; whereas as the interaction time increases from 0 minutes (freshly refined) to 135 minutes (final interaction time), predominantly lower values will be obtained for both brightness and b-coordinate, and there is no marked difference to the a-coordinate values (a+: red colour).
Parallel Dynamic Domain Decomposition in Space - Time for Data Assimilation problems
Authors: D’Amore L , Cacciapuoti R 
Published: March 2021

Abstract
In the present work we employ a load balancing scheme involving an adaptive and dynamic workload redistribution both along Space and Time directions for solving Data Assimilation problems where the observations are non-uniformly distributed, general sparse and its distribution changes during the time. We will consider the Constrained Least Square model (CLS) as prototype of Data Assimilation problems and we will validate the proposed approach on different configurations. Validation is performed using Parallel Computing Toolbox of MATLABR2013a on high performance hybrid computing architecture.
Strategic Forecasting of Multimodal Container Traffic Basing on Transport and Economic Balance of the Russian Federation
Authors: Evseev Oleg , Tulenev Kirill , Kagan Dmitry , Kryazhev Andrey , Murashov Vasily , Zaboev Alexander , Zemtsov Anton , Buslov Victor , Shubin Anton , Shubin Alexander , Urazov Anton , Anikina Elena 
Published: March 2021

Abstract
International cargo containerization system continues progressive development supporting increase of multimodal transport traffic. Containerized commodity transportation schemes are highly efficient for majority of transcontinental and long-distance deliveries optimizing costs, time and quality of transport operations basing on exact forecasting of container turnover. Following these headline routes, research article represents actual methodology of forecasting cargo volumes in accordance with Big Data stated in Transport and Economic Balance of the Russian Federation (TEB), as per spatial input-output predictions of freight traffic between regions of the country by rail, road, inland water and maritime transport by types of commodities. Expanding transportation network is linked to the core freight multimodal transport and logistics centers (TLC), connected with 12 transport hubs having strategic value for Russian economics. Represented research algorithms consider cargo base for 12 TLCs in backbone network subject to types of commodities, growth production and consumption, import and export balance in the strategic timelines of 2024 and 2035. Methodology of forecasting container traffic balance across the country is based on coefficients of container demand for each category of cargo as well as transport modes and transportation schemes. Container traffic forecast indicated by scenarios of TEB model reflect strategy of development and optimization for the freight flows in TLC network. These information models, due to their complex structure and rich semantics, are more likely to belong to the class of models based on knowledge, than on data, that requires further improvement of forecasting methods using intelligent processing of Big Knowledge-Based models.
Automated Ontology Population and Enrichment of Scientific Publications
Authors: Bravo Maricela , Aldea Arantza , Hoyos-Reyes Luis F. 
Published: March 2021

AbstractScientific publications are the most important resources available to the research communities. Researchers want their work to be widely recognized and available and also need powerful search engines to identify other publications and researchers working in the same area. Therefore, a good representation and organization of scientific products is crucial for an accurate retrieval of information. This paper describes an approach for automated population and semantic enrichment of an ontology model that represents scientific publications. Specifically, the type of enrichment used in this approach consists of implementing semantic similarity measurements between publications. Several experiments were performed to identify the best similarity measurement, using a statistical approach and the precision of the measurements.