bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Research Status and Hotspots in the Domain of Smart Education from 2003-2019
Authors: Donghua Wang , Nanning Yu , Jinfei Wu , Yuyan Shi , Rui Hu , Yuanyuan Guan , Haibin Wang 
Published: April 2020

Abstract
To explore the status and hotspots in the domain of smart education, 183 related articles form the Web of Science (WOS) were analyzed by the visualization software CiteSpace. The results show that: (1) the area of smart education stared in 2003 while there was no research in the next six years. There was an upward trend year by year form 2011 and the number of articles reached the historical peak in 2016. Bakken, Lee and Shi, China and Smart Innovation Systems and Technologies topped the lists of contributing authors, country and publication respectively. (2) “engineering education”, “smart city”, “pedagogical affordance”, “ICT” and “big data” were the top five largest clusters on the area of smart education from 2003-2019.
Students’ Classification Model Based on Stacking Algorithm
Authors: Pan Fei , Yuan Yingchun , Song Yufei 
Published: April 2020

Abstract
A model for Students’ Classification which aims to help college teachers teach in accordance with students’ aptitude is proposed based on the daily practice data of a course. Based on the Stacking method, this classifier model ensembles eXtreme Gradient Boosting algorithm, Random Forest algorithm and the Logistic Regression algorithm. The experimental results show that this model can divide effectively students into different classes and the accuracy can be significantly improved by comparing with other classifier models. And it can serve as reference and guidance for college students’ classifier on other courses.
Naive Bayesian Algorithm for Spam Classification Based on Random Forest Method
Authors: Wang Lu , Zeng Guohui , Huang Bo 
Published: April 2020

Abstract
Aiming at the problem of dimensionality disasters in the spam filtering system, a spam filtering model based on content feature selection random forest algorithm is proposed. The method combines the Naïve Bayesian algorithm and effectively reduces the influence of redundant information on classification performance through feature selection filtering of Gini impurity. The improved algorithm takes advantage of decision tree integration and naive Bayesian algorithm. The experimental results show that compared with the naive Bayesian algorithm, the improved algorithm has been improved in the classification performance indicators of spam filtering, which is more feasible and effective in practical applications.
Comparative and Analysis of spatial domain and frequency domaindigital image watermarking algorithm
Authors: Ma Yongqiang , Wang Shunli , Song Jinping , Yu Yandong , Sun Wei , Bian Jing 
Published: April 2020

Abstract
Digital image watermarking belongs to the branch of information hiding discipline, the study of the digital watermarking will play an invaluable role in the integrity of business transactions and the protection of personal privacy.This paper introduce the embedding process of digital watermarking technology and the extraction process of digital watermarking technology. We analyze the the characteristics of digital image watermarking and juxtapose the basic principle of the Lease Significant Bits algorithm and the basic principle of the Quaternion Fourier Transform algorithm. Finally, According to analysis and comparison, we summarize the advantages of the frequency domain method.
Multi-level feature filtering algorithm based on MapReduce
Authors: Zhang Zhenling , Wang Chao , Li Zhiyuan 
Published: April 2020

Abstract
In engineering practice, we need to consult a large number of professional data to support theoretical innovation. If we rely on manual classification and screening one by one, it will take a lot of time and energy, and the classification accuracy can not meet the requirements. In order to improve the work efficiency, a multi-level feature selection algorithm based on MapReduce is proposed. The improved Chi feature selection algorithm can be used for the initial screening, and then the noise words and pre quality features can be filtered by mutual information method. The experimental results show that the algorithm not only ensures the low time complexity of processing big data, but also improves the accuracy of text classification.
Parameter Identification of Electro-Hydrostatic Actuator Based on Particle Swarm Optimization
Authors: Zhou Guozhe , Feng Tieshan , Lv Xin , Liu Lihui 
Published: April 2020

Abstract
The Electro-hydrostatic actuator with high power/weight ratio is compact and efficient. In order to obtain an accurate linear model of the actuator, particle swarm optimization is adopted to identify the parameters of the model. A group of parameters can be seen as the position coordinates of a particle. The real frequency response data of the system is used to evaluate the quality of the particle position and a fitness function is established. The evolution equation with constraint conditions is employed. The particle swarm gradually evolves to search for the optimal solution. Finally, the identification result is presented to prove the efficacy of this method.
Optimization of PSO Algorithm Based on Adaptive Inertia Weight and Escape Strategy
Authors: Gu Lili , Liu Yong , Zhen Jiaqi 
Published: April 2020

Abstract
For Particle Swarm Algorithm uses fixed inertia weights, weaken too slow and extremely easy to fall into local optimum so I propose an adaptive inertia weight method, this inertia weight has a larger weight in the early stage, can increase the global search capability and avoid algorithm falling into local optimum, in late period, this inertia weight has a smaller weight and can increase algorithm local search ability and overall increase convergence rate. But during the optimization process, There are some more complicated functions that will still fall into the local minimum even using this adaptive inertia weight. In order to avoid the occurrence of premature phenomenon so use reverse escape strategy, apply new optimization methods to the basic particle swarm algorithm, the application of several basic functions proves that the proposed optimization method has higher precision and convergence speed.
Product Parameter Calculation Based On Configurable Bom Model
Authors: Lin Xia , Jiang Ri Nian , Tao Zhu Han 
Published: April 2020

Abstract
In order to meet the customer ‘s demand for product customization and to solve the problem of complicated BOM configuration and product parameter calculation in manufacturing enterprises, we design a configurable BOM model and realize a dynamic calculation engine of product parameters based on the model. The configurable BOM model abstracts key entities such as product, product attribute, material, material attribute, material brand, and so on. It realizes flexible expansion of customized product and its materials. In order to get the key parameters of the product, such as raw material cost, sale price, etc., the key parameter’s expressions of the product are dynamically configured, the values of product attribute and material attribute are used as input parameters and the real-time dynamic calculation is realized by using the algorithm based on the JavaScript engine-Mozilla Rhino, which makes the parameter calculation logic decoupled from the business logic and achieves the scalability of the product parameter calculation. The validity of the configurable BOM model and the calculating engine of product parameters are illustrated by an example of BOM structure and raw material cost calculation of a flat box in carton manufacturing industry.
Hepatic vessel segmentation based on animproved 3D region growing algorithm
Authors: Zhang Huahai , Bai Peirui , Min Xiaolin , Liu Qingyi , Ren Yande , Li Hui , Li Yixuan 
Published: April 2020

Abstract
Hepatic vessel segmentation of CT image is of great importance in the computer aided diagnosis. This paper proposes an automatic segmentation method of 3D vessel CT images to obtain better segmentation results. First, the single Gaussian kernel of Hessian matrix in the Jerman’s algorithm is replaced by bi-Gaussian kernel. Then, a histogram-based method is adopted to adaptively estimate the threshold value of the region growing. Finally, a new scheme is proposed forautomatically searching seed points of the region growing. The experimental results show that the proposed method achieves a significant enhancement of hepatic vessels segmentation with an average accuracy 98.1%.
Research and Practice of Neural Network PID Process Control Algorithm Based on Offshore Oil and Gas Platform
Authors: Yang Qing , Liu Zhiyao , Zhang Yu 
Published: April 2020

Abstract
Since the exploitation of offshore oil and gas, after decades of development, it has gradually played an important role in world economic development. The central control system of offshore platforms is the core equipment of offshore oil and gas fields. Offshore platform industrial process control requires PID control most of the time. However, in practical applications, the tuning of PID parameters has not been well resolved. This paper combines neural network and PID control to build a neural network PID controller. At the same time, using OPC communication technology, the intelligent control PID algorithm is perfectly combined with the central control system, and the optimized model and parameters are applied to the actual control object of the oil level control of the offshore oil production platform, and the control effect is obtained satisfactorily.
Research on the Development of Smart Home Based on Multi-Perspectives
Authors: Wang Yujie , Liao Zhipeng , Shen Yongluo 
Published: April 2020

Abstract
With the continuous growth of China’s emerging industries, the digital life of Chinesehas ushered in a new era, and smart home has a huge market and user value. In order to provide a reference for the theoretical research of smart home, and help the application and development of the important concept of “smart+” wasfirst proposed in the 2019 government work report.Through systematic review of domestic and foreign literature on smart home, the reasons for the rapid development are summarized from the functional and social technology perspective. The challenges faced in the development are summarized from the user’s point of view. The trend of smart home development is summarized from the perspective of industry and society.
Research on state prediction of secondary device in smart substation based on dynamic interval weighted fuzzy c-means algorithm
Authors: Zhongyang Chen , Pengfei Zhang , Mahuan  
Published: April 2020

Abstract
A weighted fuzzy clustering algorithm based on dynamic interval is proposed to solve the problem of inaccuracy of missing attributes in clustering. By selecting the index that can reflect the secondary equipment state of intelligent substation comprehensively and combining with the weighted fuzzy clustering algorithm based on dynamic interval, the clustering classification result of the whole secondary equipment state of intelligent substation can be obtained accurately. According to the result, the corresponding maintenance strategy is adopted. The experimental results show that the weighted fuzzy clustering algorithm based on dynamic interval can effectively improve the clustering accuracy and the stability of the convergence, which can be very good to adapt themselves to the secondary device state overhaul.
Method for Detecting Visible Impurity in Oral Liquid Based on Improved SURF Algorithm
Authors: Liu Xiongfei , Liu Huimin 
Published: April 2020

AbstractIn order to solve the problems that the visible foreign objects in the large bottle oral liquid are small, the detection speed is low and the single feature would be easy to cause the mis-tracking. In this paper, the speed-up robust features (SURF) algorithm is improved and applied to the detection of visible foreign objects. Firstly, features from accelerated segment test (FAST) detection algorithm is used instead of the Hessian matrix for feature point detection to avoid the extraction of numerous and useless feature points in the edge region. Secondly, two-way fast library for approximate nearest neighbours (Flann) algorithm is adopted for the feature matching to accelerate the matching rate and improve the accuracy of matching. The related experiment shows that the proposed algorithm can accurately match the target and effectively improve the detection speed, which meets the requirements of online detection.
A novel numerical function optimization framework: campaign based optimization framework
Authors: Liang Yuntao , Xiao Jiangwen , Huang Zhengyi , Liu Tiqian 
Published: April 2020

Abstract
This paper proposes a new optimization framework: campaign optimization framework (COF), which is based on the historical results of traditional swarm intelligence algorithms and uses two different campaign rules to get better solutions. Firstly, the candidate solution set is generated by running the swarm optimization algorithm. Secondly, cross campaign rule (CCR) or increment campaign rule (ICR) is used to update the candidate solution set. The campaign rule describes the steps to get better solutions. In CCR, the better solution is obtained by combining the variable bits of two randomly selected solutions. But in ICR, it is generated by every variable bits’ optimal pools. Then, the best candidate solution is optimized by swarm optimization algorithm again. Finally, the proposed framework is tested on two well-known benchmark functions. Through the analysis of the experimental results, the proposed algorithm is compared with traditional swarm optimization algorithm. And two campaign rules are compared in terms of results and optimization time dimensions.
Design and Implementation of an Adaptive Assembly Algorithm for Edge Nodes of Satellite OBS Networks
Authors: Li Lisiyang , Qiao Lufeng , Chen Qinghua 
Published: April 2020

AbstractThe edge nodes of the satellite optical burst switching network are the interface devices of the ground network and the satellite optical burst network. Ground network data needs to be classified, assembled, and generated bursts at the edge nodes. The burst will be transmitted on different wavelength channels. Reasonable selection of the assembly algorithm of the edge nodes can reduce the design complexity and improve the forwarding performance and QoS capability of the satellite optical burst switching network. In this paper, an adaptive assembly algorithm is proposed to adjust the length threshold and time threshold dynamically. The basic principle is to evaluate current network traffic depend on the actual burst parameters of previous bursts, and then determine the specific value of length threshold and time threshold. The algorithm is implemented on a Xilinx’s XC7VX690T-2FFG1927I FPGA, and verified by Modelsim SE 10.6d.
An Improvement of Remote Sensing Images Edge Extraction Algorithm Based on Quantum Derivation
Authors: Rao Siwei , Chen Shi 
Published: April 2020

Abstract
Aiming at the problem that the edge connectivity is poor when the original quantum derived edge extraction algorithm detects the edge of remote sensing image, it is necessary to improve the original algorithm in this study. The remote sensing image is initially multi-threshold segmented globally by quantum genetic algorithm, and then the method of quantum probability statistic is used to extract the edge of images. The experiment results show that the proposed algorithm improves the edge connectivity under the premise of preserving the precise edge of the image edge.
The Efficient Erasure code with Low Recovery-Overhead and degraded reads optimization
Authors: Zhang Hang , Zheng Liu Shan , Tan Dang 
Published: April 2020

Abstract
At present, the distributed storage systems are being adopted by more and more Internet companies because of their reliability and efficiency. In the distributed storage systems, some fault-tolerant technologies are often used to ensure the data reliability. Since the erasure code technology can store more data with lower storage space, it is often used as one of fault-tolerant technologies by some distributed storage systems. However, the existing erasure code technology has many problems. The large amount of repair overhead and I/O overhead consumed to recover data after data loss has become the biggest obstacle in actual use. This paper starts from the RS code, and constructs a new packet repair SLRC code by using the coding idea of stripe set, which can effectively reduce the repair cost required for single-node data recovery. At the same time, for the structure of SLRC code, a new data storage method, Curve storage, can effectively reduce the extra I/O overhead required for SLRC code degraded read operation. The experimental horizontal comparison with the LRC code and the RS code shows that the new method can effectively reduce the single node repair overhead and the additional I/O overhead required for the degraded read operation.
Construction of Experiential Learning Space Model Based on Virtual Reality Technology
Authors: Gan Baiqiang , Zhang Chi , Meng Hainie 
Published: April 2020

Abstract
In order to better help learners to improve their learning experience and learning efficiency, this paper starts from the interaction, immersion and imagination of virtual reality technology, and sorts out the evolutionary process of formal learning space, informal learning space and virtual learning space. It also proposes the conception of experiential learning space with the virtuality and reality combination. Aiming at the application of virtual reality technology in the knowledge presentation, simulation training and experience environment of experiential learning space, an experiential learning space model based on the virtuality and reality combination is constructed to enrich the learning environment and information presentation of learners, enhance learners’ situational experience and improve their learning efficiency.
Research onC/SProtocol and P2PProtocol in Wireless Communication
Authors: Yue Geng 
Published: April 2020

Abstract
This paper mainly studies how the two communication protocols c/s protocol and p2p protocol are implemented and applied in the communication system. The traditional c/s protocol and p2p protocol are two widely used communication protocols. This paper studies how these two communication systems are implemented, and imagines how the two protocols work together. This paper first studies the development and characteristics of the two protocols, and then studies the structure of the two communication systems separately, how to implement the two communication systems separately and explore how to apply them in practice.
Research and Implementation on OFDM Technology for Machine Communication
Authors: Li Zhihao 
Published: April 2020

Abstract
Machine communication provides the means of information interaction for Internet of Everything (IoE) and unattended operation, promoting the development on the related areas such as Internet of Things, automatic drive, robot, and unmanned aerial vehicle (UAV) which are on this basis. In machine communication on a large scale, mass user multiplexing will give rise to high peak-to-average ratio (PAR) of OFDM and redundant control information will lower the utilization efficiency of OFDM’s effective frequency. In the light of the problems above, OFDM optimization technique used in machine communication is put forward in this thesis. Under the circumstances of more user access currently, more complex application context, high PAR and low utilization efficiency, the thesis proposes computer emulating by OFDM and optimization of access mode. Additionally, OFDM optimization technique, applying partial transmit sequence and carrier to noise ratio (CTNR) to realize the redundant information control of short frame carrier, optimize PAR and enhance the transmission efficiency. Finally, simulation experiment and hardware design verify the feasibility of OFDM optimization technique in machine communication.
Research on interactive design of multilingual e-commerce platform based on eye tracker
Authors: Zhu Shengyin , He Xiangzhen , Yu Hongzhi 
Published: April 2020

Abstract
In “interactive design”, designers usually rely on personal experience and understanding to work. The design interface has strong subjectivity, and it is difficult to match the intention of users. Based on the basic experiments of eye movements, this study collected and analyzed the pages of the search engine for a multilingual e-commerce platform through the indicators such as the duration of the objects being watched, the number of objects to be followed, and the sequence of objects to be looked at. After the experiment, we found that the first movement of the eyeball was still focused on the upper left corner of the page. During the browsing process, the subjects were used to the order from top to bottom and from left to right. So when we design the page, we should keep this style and respect the user’s habits. After analyzing the data, we found that the simple design made a good impression on the subjects, so we should keep the simple style in the page design, avoid filling every inch of space, otherwise it will cause the burden of visual memory. The data analysis also showed that the use of controls, prompt wording, color settings and page style are consistent, which can make users easily speculate about various functions and increase the user’s preference.
The Feasibility Study of The Application of Virtual Machine Technology in OPC of GDX1/2 Cigarette Packing Machine
Authors: Jibo Li , Yuanzheng Huang 
Published: April 2020

Abstract
OPC is the operation interface of GDX1/2 packaging machine. Its application software and related drivers are developed in Windows XP operating system. This paper introduces the virtualization of the OPC system and finally realizes the function of human-computer interaction of OPC in win7 operating system. It can improve the maintainability of GDX1/2 cigarette packaging machine.
Exploration on the application of 3D printing and dyeing patterns in modern clothing visual communication design
Authors: Bo Yan 
Published: April 2020

Abstract
3D printing and dyeing is a widely used pattern processing mode in the new era, which can adapt to the design requirements of visual communication and effectively enhance the aesthetic art taste and fashion of modern clothing. Based on the status quo, firstly, the characteristics of digital printing and dyeing technology are discussed. Secondly, the choice of the visual design of modern clothing is discussed. Finally, the application of 3D printing and dyeing patterns in the visual communication design of modern clothing is expounded. It can effectively improve the overall application level of visual communication design and lay a solid foundation for the progress and development of the fashion design industry.
Research on the layout and value space of China’s 5G industry——Based on the Sino-US “trade war” perspective
Authors: Li Jiarun 
Published: April 2020

Abstract
At present, no matter in the technical field or the commercial field, China has no doubt become the leader in developing the 5G industry. Based on the perspective of Sino-US trade war, this paper analyzes the layout and value space of China’s 5G industry, and believes that technological innovation is the first driving force and an important means to seek a leading position in the international market. Take practical measures from the aspects of policy design, industrial layout and technical standards.