bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Digital Twin Framework of Military Large-scale UAV Based on Cloud Computing
Authors: Wang Yin-chuan , Zhang Na , Li Hongshun , Cao Junjie 
Published: January 2021

Abstract
Firstly, this article explains the characteristics and advantages of military large-scale UAVs, and points out the three basic problems currently encountered by military large-scale UAVs; secondly, this article is based on the current design, manufacturing and application reality of large-scale military UAVs, analyzed the urgent need to build a cloud computing-based digital twin framework for military large-scale UAVs, and discussed in detail from the aspects of test cost, integrated perception, centralized control, business prediction, and mission planning; again, this article proposed cloud-based computing The digital twin framework for military large-scale UAVs discusses the composition and functions of each layer; finally, it points out the five directions and work priorities that need to be paid attention to in the construction of the digital twin system of military large-scale UAVs, including UAV model, flight status measurement, reliable propagation channel, intelligent command and control, and capability evaluation analysis.
Research on the Application of English Course Online Examination System Based on Face Recognition Technology
Authors: Li Qiuyan 
Published: January 2021

Abstract
With the development of information and technology, the English course online examination has been promoted comprehensively. However, in online examination, the authentication link mostly relies on the manual authentication method, which has the limitation of the manual identification. Based on this problem, this paper proposes an online examination system for English courses which is based on face recognition technology. Face Recognition is used to judge the correctness of the user’s login identity by invoking the Baidu Face Recognition API for online live Face detection and comparison.
One Study on IEEE1588 clock synchronization algorithm based on Kalman filter
Authors: Zheng Kewang , Zhang Lei 
Published: January 2021

Abstract
Clock synchronization is a major indicator of the distributed network test and control system. The precise time synchronization is also one of the core technologies of the network communication of test and control system. The paper illustrates the fundamental principle for clock synchronization under IEEE1588 protocol and concludes that its synchronized accuracy is influenced by the accuracy of time stamp and transmission delay jitter through analysis. An autoregressive clock drift model has been put forward in the paper in an effort to improve the time synchronization accuracy. It makes use of the Kalman filter to estimate the deviation and drift of the master and slave clock so as to offset it. The results of simulation indicate that the method can effectively ease the impact on time synchronization for time stamp and improve its accuracy of the test and control system.
Adjacent vertex distinguishing edge coloring of the semistrong product of paths
Authors: Zhuo-mo AN , Cai Jing , Tian Shuang-liang 
Published: January 2021

Abstract
An adjacent vertex distinguishing edge coloring of a graph G is a proper edge coloring of G such that no pair of adjacent vertices meets the same set of colors. The minimum number of colors required for an adjacent vertex distinguishing edge coloring of G is called the adjacent vertex distinguishing edge chromatic number of G, and denoted by

χ
a
′

(
G
)

. In this paper, use the method of structural chromatic and the method of proof to the contrary and obtain the adjacent vertex distinguishing edge chromatic numbers of the semi-strong product of two paths.
Research on accelerating CEE-DGCNN event extraction algorithm based on multi-CPU platform
Authors: Li Yan , Jiang Jinfei , Xu Jinwei , Gao Zikai , Dou Yong , Zhou Haifang 
Published: January 2021

Abstract
With the development of the Internet, the volume of information is expanding rapidly, and the complex information makes it particularly important to extract information quickly and intelligently. Event extraction algorithm is such a kind of fast and accurate information acquisition algorithm. With the development of deep learning in recent years, deep learning also shines in the field of time extraction. CEE-DGCNN network is an efficient and accurate event extraction algorithm for Chinese text. At present, the acceleration research on deep learning in the academic community mainly focuses on GPU, FPGA and other platforms. In fact, compared with these platforms, CPU is more versatile. Considering that the algorithm should have universality and universality in industrial application, this paper makes an in-depth analysis of CEE-DGCNN algorithm to study its acceleration on CPU. Experiments were carried out on x86 and ARM architectures respectively, and good acceleration effects were achieved.
Design and Study of Simulation Model for Organization of the VHF Station Network
Authors: Luo Yingguang , Fu Guobin , Yan Qifei , Zhang Yang , Tong Jie 
Published: January 2021

Abstract
A scientific and reasonable construction of the organizational simulation model of the VHF station is based on executing the simulation evaluation of the organization and effectiveness of the VHF station network. First, we analyzed in detail the requirements of the VHF station network organization simulation model construction from the perspective of organization. Secondly, the entity-oriented modeling method is adopted to design the model composition of the simulation entity, the relationship between the entity models, and the entity model behavior. Eventually, the UML modeling language is employed to create a connection between entity model behavior and information interaction. The simulation model constructed in this paper can provide core model resources for the design and implementation of the simulation system for VHF station network organization. Moreover, it can also provide reference for constructing organization simulation models of the other communication network.
Design and development of constructing the basic probability assignment function software in D-S evidence theory
Authors: Wei Zhangjian , Geng Junbao , Wei Shuhuan 
Published: January 2021

Abstract
The basic probability assignment function is the basis of D-S evidence theory and the premise of evidence combination. A kind of basic probability assignment function generation software is designed and developed in this paper. After the index values is input, the software can automatically generate the basic probability assignment values, which meet the requirement of the users. The main functions, key algorithms, program logic, development language and interface design of the software are introduced. The calculation case is given to describe the software.
Handwritten Arabic numerals recognition system using probabilistic neural networks
Authors: Tang Yushun , Zhang Shengguo , Niu Lu 
Published: January 2021

Abstract
This paper presents a system for the recognition of the handwritten Arabic numerals zero to nine (0–9) using a probabilistic neural network (PNN) approach. This system can recognize handwritten input and externally imported Arabic numerals in real time, including two processes of image pre-processing and recognition. Image pre-processing involved normalization and expansion to enlarge the characteristics of the picture for easy recognition. Recognition process involves the calculation of mode distance, which can help obtain the similarity match between sample matrix and learning matrix. According to similarity matching the input feature matrix will be classified into one of the ten numbers. This study uses MATLAB to establish a graphical interface that is easy to operate. The system has good performance and strong scalability, which established a simple experimental platform for a more in-depth study of the recognition of handwritten Arabic numerals.
A Parallel Decimal Multiplier Based on a novel 4:2 Fully Redundant Decimal Adder
Authors: Yao Zewei , Cui Xiaoping , Wang Tao 
Published: January 2021

Abstract
Due to requirements for computational accuracy in the fields of business computing, the decimal arithmetic computing system has gradually become a research hotspot. A parallel decimal multiplication consists of three stages: partial product generation (PPG), partial product reduction (PPR) and the final product generation (FPG). In the PPR stage, a novel 4:2 fully redundant decimal adder based overloaded decimal digit set (ODDS) is proposed in this paper. The 4:2 ODDS adder is formed by the binary 4:2 compressors, a decimal compressor and a converter. Moreover, the signed-digit radix-10 code, the redundant excess-3 code and the ODDS code are used in the PPG stage. In the FPG stage, an ODDS–BCD conversion is adopted to quickly generate BCD-8421 product. The analysis and comparison by using the 45nm technology show that the proposed decimal multiplier based on the 4:2 ODDS adder has less area and better synthesis performance.
The full separability of three-qubit superposition state and its decayed states in white noise environment
Authors: Shen Weidong , Chen Xiaoyu 
Published: January 2021

Abstract
The research on the separability of quantum states is one of the important research directions in quantum information theory. In this paper, we propose a new entanglement witness to study the full separability of the superposition of three-qubit W and

W
¯

(the qubit inverted W state) states in white noise environment. The witness accounts for most results of separable condition of the state obtained with numerical calculation. The witness also accounts for the decayed state which is the superposition state with and terms decayed by a factor. The separability criterion from our witness is better than that of the further generalized Wootters formula.
Domestic garbage recognition and detection based on Faster R-CNN
Authors: Nie Zhifeng , Duan Wenjie , Li Xiangdong 
Published: January 2021

Abstract
The core of intelligent garbage sorting is target identification and detection. In order to achieve effective garbage sorting, on the basis of deep learning, the Faster R-CNN target detection model and ResNet50 image classification model are used to identify and train 3984 garbage images, and predict 3552 images. The results show that the accuracy of garbage recognition is 89.681%, the average accuracy of each garbage prediction is 91.68%, and the accuracy of each category of garbage image prediction is over 93.3%. Through the identification, detection and classification prediction of garbage images, it provides data support for the intelligent classification of domestic garbage.
The Application of Data Warehouse in Teaching Management in Colleges and Universities
Authors: Yu Xiaobing 
Published: January 2021

Abstract
Data warehousing refers to the process of organizing data from different sources to support the process of decision making in organizations as well as support data analytics. Data warehousing assimilates and systematizes data from across different departments in an organization to have a single analysis of the full information. This data is then used to make the decisions in an organization. However, data warehousing has been underestimated in education institutions. The reason is that they are non-profits organizations. With the increase in the number of educational institutions coming up, colleges and universities should consider the integration of such data-driven support systems to make better decisions and for more organization in the academic processes especially for those institutions with different branches. The intricacy in managing these institutions requires development on how consistent information can be relayed to the decision-makers of an institution. This paper explains the need for data warehouses in education institutions and how the teaching institutions can implement data warehousing to help in the management of the institutions. The paper also explores and reviews various methods that institutions can use to mine data. Various stages for promoting and actualizing the system have been shown.
Basic Intrusion Technology of Industrial Internet of Things—Based on Machine Learning
Authors: Wu Yizhan 
Published: January 2021

Abstract
With the continuous advancement of technology and the continuous development of the Industrial Internet of Things, network security has become particularly important, especially in the detection of intrusion attacks. This article briefly introduces the Industrial Internet of Things, and the current network security threats faced by the Industrial Internet of Things, as well as analyzes different intrusion methods. Three machine learning algorithms are applied in this article to analyze and compare their effects in intrusion detection. Through experiments, a more suitable machine learning model for industrial IoT intrusion detection is selected.
Research on the Construction of Comprehensive Practice Platform for Big Data Analysis of E-commerce under the Environment of Internet of Things
Authors: Yan Weibin 
Published: January 2021

Abstract
Due to the rapid development and wide application of Internet information technology, there is an urgent need for e-commerce talents in various industries. Internship is an important part of on-the-job training in universities, which helps to provide outstanding talents for the society, and internship management system can ensure the quality of internship. Under the Internet of Things environment, a new comprehensive practice platform for big data analysis is constructed, and high-quality e-commerce talents in society are trained on the basis of overall research, so as to give full play to their roles and functions. Practice has proved that the comprehensive practice platform of e-commerce big data analysis can improve the quality of education and students' ability.
Study on the Influence of Blended Teaching Mode on English Learners’ Motivation under the Background of Information Technology
Authors: Liu Jinfeng 
Published: January 2021

Abstract
With the rapid development of Information Technology (IT) and the popularization of IT-based education, blended learning mode (BLM) under the background of IT has emerged. Thus, the investigation into English learners’ motivation under the IT-based BLM is conducive to the development of China’s college English teaching. Both the quantitative and qualitative research methods are employed in this study to investigate the issue that whether BLM have effects on English learners’ motivation in universities. It can be found that the instrumental motivation is the major motivation of English learners from 6 classes. Three motivational types are higher than the average and the motivational intensity is considerably high. After a semester, three motivational types and intensity in blended learning group (BLG) have promoted separately. The results can demonstrate that employing IT-based BLM is feasible and superior, which can positively motivate foreign language teaching and learning.
Research on Online CAD Course Teaching Mode Based on N+X Mode
Authors: Mingxia Zhao 
Published: January 2021

Abstract
In order to further enhance the design and innovation ability of students, students are taught hierarchically through the online learning teaching platform and the knowledge module setting of product structure design. Meanwhile, based on the curriculum research of the mixed classroom teaching model, this paper is composed to enhance the initiative of students in learning, realize layered teaching, and enhance the effectiveness of teaching. Classrooms are not the only place to give a lecture, and the diversification of teaching locations and learning time can be achieved, which makes communication and guidance between teachers and students as well as cooperation and communication between students and students more convenient, so that students' team assistance ability can be effectively improved. Therefore, on the online learning platform, curriculum resources can realize the quantification of resources, which enriches the classroom and achieves the process and data evaluation of students so as to implement the objectivity and effectiveness of the evaluation.
License Plate recognition in fog weather based on deep learning
Authors: Wu Huaihong , Zhou Bing , Wei Wei 
Published: January 2021

Abstract
The traditional license plate recognition is generally carried out under normal conditions, but there is little work to carry out license plate recognition in fog.With the deterioration of the global environment, the probability of winter fog increases. Therefore, efficient and accurate license plate recognition under fog conditions is the research focus of this paper. This paper introduces the defogging of license plate images in foggy weather and the detailed work of license plate recognition through deep learning, which can improve the accuracy of license plate recognition in foggy weather and is conducive to ensuring the driving safety of vehicles in foggy weather.
Study on optimal allocation of rural integrated energy system with biogas and photovoltaic
Authors: Li Peng , Du Songhuai , Zheng Yongle , Su Juan , Wang Shiqian , Li Huixuan , Yang Man 
Published: January 2021

Abstract
The development of rural energy is directly related to the process of China's energy reform. At present, the energy structure of villages and towns in China is still unreasonable. It is urgent to build a rural energy station integrating the characteristics of rural industrial development to meet the demand of production and living load. In this paper, considering that the rural areas mainly rely on natural production economy and have the advantages of clean energy endowment, through the establishment of a rural comprehensive energy system containing biogas and photovoltaic, the model seeks to maximize the comprehensive benefits including investment cost and expected income, optimize the allocation of energy device capacity, and verify its feasibility with practical cases, so as to provide reference for future rural comprehensive energy planning and green industry Economic upgrading provides theoretical and technical support.
Research on Three-phase PWM Rectifier based on Double Closed-loop Feedforward decoupling control
Authors: Li Houxiang , Cheng Guochu , Zhang Yongming 
Published: January 2021

Abstract
For rectifier link widely used traditional diode rectifier circuit and brake pipe phased rectifier circuit, resulting in net side current, voltage distortion, problem of higher harmonic and low power factor, and put forward a double closed-loop feed-forward decoupling control strategy, used in three-phase voltage source PWM rectifier was established in Matlab/Simulink simulation model, compared with traditional SVPWM control of three-phase PWM rectifier, verifies the correctness of the proposed control strategy. From the simulation results, it can be seen that the voltage on the grid side is nearly consistent with the phase of the current, which realizes the operation of unit power factor and makes the voltage on the DC side reach steady-state rapidly, thus reducing the harmonic pollution and improving the power quality, which has a good practical application effect in the power transformation.
Research on Robustness of Critical information infrastructure Based on Attack-Defensive Game Model
Authors: Liu Diyang , Zhang Zhen 
Published: January 2021

Abstract
Because the traditional network robustness research ignores the confrontation process and information asymmetry conditions, this paper analyzes the impact of information asymmetry conditions on the robustness and simulates the information asymmetry conditions through a perturbation model. Based on the stackelberg game, an attack-defensive game model under asymmetric information is established, by solving the game equilibrium solution, the defensive resource allocation strategy that optimizes the network robustness is obtained. The simulation results show that when attack resources are scarce, the attacker tends to respond with a low priority attack; when the attack resources are abundant, the attacker tends to have a high priority attack response. Under the mixed defensive strategy corresponding to the equilibrium solution of the game, the optimization rate of the defender's robustness payoff compared with the expected return under the pure strategy reached 4% to 12%.
2 ps Time-to-Digital Converter for Frequency Synthesis in 55 nm CMOS Technology
Authors: Yao Yan , Li Zhiqun , Yang Geliang 
Published: January 2021

Abstract
This paper presents a 2-ps time-to-digital converter (TDC) in 55 nm CMOS technology for all-digital phased-locked loop (ADPLL) system. Innovative inverter delay chain and Vernier delay chain cascade structure is adopted in the TDC to expand the measurement range while ensuring high resolution, so as to meet the wideband application requirements. Time window technology is employed to reduce circuit working frequency to save power by extracting single rising/falling edge of clock signal. Multiplexing technology is exploited to further reduce the power consumption by reusing the rising/falling edge detection delay chain of the first-level TDC, and also the time deviation detection circuit and resolution scaling factor detection circuit of the second-level TDC. The TDC features a differential nonlinearity (DNL) of 0.31 least significant bits (LSB) and an integral nonlinearity (INL) of 0.62 LSB, with a total current consumption of 4 mA from a 1.2 V supply voltage.
Design and Implementation of On-Line Practice System Based on Software Testing
Authors: Jiang Weiyi , Deng Junyu 
Published: January 2021

Abstract
As an important branch of software testing, software automated testing has brought many conveniences to the B/S architecture of Web application software testing. At the same time, it has also put forward new requirements for talents in the field of software testing. It is necessary to understand the theoretical knowledge of software testing and to master the use of software testing tools. Therefore, colleges and universities must adopt a teaching model that combines theory with practice to train more excellent test talents. The online practice system adopts the B/S architecture mode, integrates Spring, SpringMVC, and MyBatis open-source frameworks for system development, realizes the function module of super administrator management background, and supports student users to practice theoretical exercises related to software testing online, and write Web-compliant Selenium test script for applying test questions. The system can refer to the Selenium test script according to the standard and compare the test script submitted by the student user. The Selenium tags, positioning methods, elements, and attribute values are regarded as important scoring objects, and finally, judge and make reasonable scoring feedback.
System Design of Network Data classification Based on Deep Packet Inspection
Authors: Lu Qi , Lin Jiadong , Su Zhou , Liu Fei 
Published: January 2021

Abstract
With the rapid development of the Internet, as an important method of network security protection, network data classification has become the focus of high-tech research. In order to efficiently process massive network data, filter irrelevant data packets, and resist malicious attacks, so as to ensure the safety and stability of network operating, based on the research of deep packet inspection (DPI) technology, a kind of network data classification system has been presented. This system is based on the architecture of field-programmable gate array (FPGA) and ternary content addressable memory (TCAM). Tests show that the system can meet actual requirements of network data classification.