bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the ratio expansion watermarking scheme and its improvement
Authors: Dong Keming , Yu Xiaohan 
Published: June 2020

Abstract
Ratio expansion is a recently proposed, remarkable method for reversible data hiding in 3D meshes. The capacity and distortion are the two most common performance measures for data hiding. This paper analyses the ratio expansion method, and a novel mathematical framework is introduced and described, which proves that the magnitude of the distortion depends on three parameters. By appropriately selecting two of these parameters and a factor called “reference value”, the proposed method achieves reduction of the distortion. Another novel coding and decoding phrase is also proposed to get higher capacity. The experimental results show that this method improves the embedding capacity significantly without affecting the visual quality of 3D mesh model.
A Novel LOS Rate Estimation Method Based on Images for Strap-down Inertial Guidance
Authors: Xu Zheng , Luo Haibo , Hui Bin , Chang Zheng 
Published: June 2020

Abstract
With the development of technology, precision guided weapon is becoming more and more important in modern war. In order to launch our recent guidance system on medium and small guided weapons, we propose a method to obtain the LOS rate by combining information from both camera and gyroscope. To be specific, we firstly calculate the body LOS angle through transforming the image pixel coordinate system into the image physical coordinate system according to camera internal parameters; then subtract the missile motion information contained in the measurement signal of the seeker and finally the LOS rate is deduced. Comparing with traditional gimballed seekers, our strap-down seekers with camera have significantly reduced costs and influences caused by external environments on platform.
Research on RSA Padding Identification Method in IoT Firmwares
Authors: Mu Chao , Yang Ming , Chen Zhenya , Wang Biao 
Published: June 2020

Abstract
Cryptography is a fundamental mechanism for security, various cryptographic algorithms are widely used in IoT firmwares, and identifying cryptographic algorithms is paramount for IoT security. RSA algorithm is the most popular asymmetric key cryptographic algorithm in use. Insecure RSA padding mode may result in padding oracle attack, causing certificate leakage, random number prediction, and plaintext recovery. In this paper, we show how to extract binaries from IoT firmwares, then describe 7 padding modes in RSA algorithm, and identify RSA padding in two methods -- function-name matching and IR expression constant analysis. We use Angr VEX model to translate specific code block into intermediate representation, and analyze their constant value to track RSA parameter int padding. We collect and filter 159 firmwares from 6 different vendors, analyze 7 kinds of RSA paddings using function-name matching, and 4 kinds of RSA paddings in RSA functions which contain parameter int padding using IR expression constant analysis. Then we identify 335 RSA paddings, and find out that flawed padding is still broadly in use in IoT environment.
Research on the Integration of Artificial Intelligence and Education
Authors: Qian Suping , Feng Qiming 
Published: June 2020

Abstract
With the development of big data intelligence, deep learning, brain-like intelligence, autonomous control and other new generation of artificial intelligence technologies, the integration of artificial intelligence and education has become an inevitable development trend. Intelligent education system, such as virtual reality, educational robot, intelligent tutoring system, online learning system, learning analysis and so on, needs the seamless integration of human and machine cognitive intelligence. Understanding-based teaching is the fundamental way to realize the high integration of human and machine cognitive intelligence. In this paper, the experimental research of understanding-based teaching is carried out, and the results show that understanding-based teaching in the network environment can promote the development of students’ creativity more than traditional teaching.
Rain Removal from images based on Computer Vision and conditional Generative Adversarial Networks
Authors: Li Yunfei , Wang Lidan , Chen Taixing , Wang Ziyuan , Duan Shukai 
Published: June 2020

Abstract
In view of the quick development of modern computer technology, more pictures of natural scenes have been collected and analyzed for application in military fields, scientific research, and computer vision fields related to object detection. However, the sharpness of these pictures collected will be affected by rain and snow, which will reduce the visibility of things in the pictures. This will not only affect the viewing, but also affect scientific research fields such as autonomous driving and video surveillance. Therefore, the research on image rain removing is very practical. An improved algorithm model named pixel-GAN is proposed in this article, which based on conditional Generative Adversarial Networks (cGAN). This new method regards the problem of removing rain from specific images as the style conversion problem. What we improved is that a VGG-16 module is added to the original network to extract perceptual loss as a new part of the loss function. We show the excellent rain-removing ability of the improved algorithm and also illustrate the reason why we add the perceptual loss. Compared with other existing methods, there is no need to set a prior model, the training speed is faster and the proposed model finally generates higher quality pictures.
Research on image processing based on pattern recognition
Authors: Peng Kai , Chen Jing 
Published: June 2020

Abstract
Image processing is to transform the image into digital matrix by mathematical formula, then store the data in the computer, and enhance the source bitmap by computer, including gray-scale processing, median filtering and binarization. Then the image is cut, including contour edge processing, seed filling and so on. In this paper, the image is recognized and processed based on pattern recognition, and then a pre classifier is designed to build a system model of fruit intelligent classification. After the fruit is taken by industrial camera, the corresponding image processing and feature value extraction are carried out. Then the extracted eigenvalues are used for classification. Through this method to achieve a variety of fruit classification effect.
Research on the Application of Electronic Information Technology in the Internet of Things
Authors: Kejin Wang , Wenhui Sun , Aichun Zhu 
Published: June 2020

Abstract
In the current era, with the continuous development of China’s science and technology, the development of electronic information technology has also been significantly improved. Electronic information technology plays an irreplaceable role in people’s daily production and work, which helps to entirely improve work efficiency. In addition, the Internet of Things technology has developed rapidly in Internet era. In the process of the Internet of Things technology, electronic technology has a good role in promoting it. Therefore, the use of electronic information technology is very important and helps promote the comprehensive development of the Internet of Things in the current era.
Filter Order and Transmission Zeroes Calculation of Crosscoupled Resonator filters
Authors: Qi Li-hua , Xing Dong-qiu , Wang Rui , Li Yan-ni 
Published: June 2020

Abstract
Determination of filter order and transmission zeroes is the precondition of synthesizing cross-coupled filters. Firstly, we propose a method to determine them according to given filter specifications using Genetic Algorithm. The effective objective function is proposed for Genetic Algorithm. We can obtain the least filter order and the optimum locations of transmission zeros to fulfil filter specifications by this method.
Influence of Tower Line Coupling Effect on Stress of Iron Tower in Mining Area
Authors: Zhang Hongjie , Yang Fengli , Yang Gang , Lu Zhumao 
Published: June 2020

Abstract
During the deformation process of power transmission iron tower base along with the ground surface settlement, the conductor and ground wire can support the iron tower structure to some extent. Through defining the influential coefficient of coupling effect of tower line, we have obtained the influential coefficients of coupling effect of tower line under two working conditions, i.e. base settlement and horizontal slipping, and evaluated the influence of the tower line coupling effect on bearing performance of iron tower during the base deformation process. The research shows that the shaft force of main material of tower leg during the base deformation process is slightly increased, and the increasing amplitude is within 10%, and the influence of the tower line coupling effect on the bearing performance of iron tower during the base deformation process can be neglected basically.
Research on Entrepreneurship Policy of College Students Based on Quantitative Analysis of Text Data Mining
Authors: Xu Jie , Liu Fei 
Published: June 2020

Abstract
Encouraging college students to become entrepreneurs has become the policy orientation of many countries including China and entrepreneurship policy is an important macro environment for college students to innovate and engage in entrepreneurial activities.This paper focuses on the entrepreneurial policy of college students in Changzhou. Based on text data mining and big data, it analyzes the quantity, form, subject, theme and use of policy tools in Changzhou and discusses the macroscopic development trend and logical path of Changzhou college students’ entrepreneurial policies. Provide theoretical guidance for the analysis of policies in the future through the construction of, the check of, and the classification of text big database.
Stacked Attention Recurrent Relational Networks for Question Answering
Authors: Liu Pei , Xiang Chao , Jia Dan , Zhao Xiaoyu , Meng Weiye , Wang Jianxiu 
Published: June 2020

Abstract
Relational reasoning is ability to reason about entities and their interactions, which is not applicable for many deep neural networks. Recurrent relational networks, introduced by Palm et al. (2017), increase the complexity of the reasoning tasks they can address [1]. In this paper, we introduce Stacked Attention Recurrent Relational Networks (SARRN) to answer natural language questions from facts, which fundamentally hinge on multiple steps of relational reasoning and improve the ability of reasoning. Our model is a stacked attention model that use recurrent attention to focus on fine-grained parts of the documents. We apply our model to the BaBi tasks, which have a set of proxy tasks that evaluate reading comprehension via question answering. Our model solve 19/20 tasks and the experimental results on the test sets tasks show that our model yields great improvement. We also use qualitative analysis to show the result intuitively.
Simulation analysis the aerodynamic characteristics of variable sweep wing missile
Authors: Li Yu , Yi Lin , Ao Yuntu , Ma Liangzheng , wang Ying 
Published: June 2020

Abstract
When the sweep of the variable sweep folding wing missile changes, the lift-drag ratio is improved so that the missile is able to adapt to subsonic flight, transonic flight and supersonic flight. This paper designs different 3D models of variable sweep wing missile aerodynamic shape and completes the aerodynamic characteristics analysis of the missile by CFD according to the Basic Aerodynamics, Missile General Design Principle, Flight Dynamics of Missile. The simulation analysis of the missile in different flight conditions with different sweeps is carried out, and the wing sweeps applicable to different flight conditions are summarized.
HAZOP_LOPA-based operation process risk analysis and management research
Authors: Qu Jing , Zhang Mingxing , Zheng Dengfeng , Ning Shuangsheng 
Published: June 2020

Abstract
At present, HAZOP analysis and LOPA analysis are widely used to analyze and control the risk of process flow, but few people manage HAZOP and LOPA for risk during operation. Through the research of HAZOP and LOPA analysis methods, combined with long-term work experience in the field, the author proposes to combine HAZOP and LOPA analysis methods into operational process safety risk analysis, and use the same subject expert team to identify the risks in the operation process. Control and control results also help to re-revise the operating procedures, conduct risk management and control from the operational level, and improve the completeness of safety evaluation. This paper introduces the basic method of HAZOP_LOPA joint analysis operation process, clarifies the analysis points, and lists the commonly used 8 types of guidance words. Finally, the risk of maintenance and maintenance operation of quick-open blind filter is analyzed by examples. The results show that Based on HAZOP_LOPA, operational risk analysis can quantitatively evaluate the reliability of existing protection measures, eliminate or reduce safety risks, and achieve safety risk review of operational procedures. This method improves the reliability of operating procedures and enhances the safe operation level of employees. It is of great significance.
Vibration Analysis of Gear with Asymmetric Teeth and Double Pressure Angles based on Transient Stiffness and Transfer Error
Authors: Li Huachuan 
Published: June 2020

Abstract
Transient stiffness formula of dynamic load of asymmetric gear is deduced. Considering the effect of transient stiffness and transfer error, the formula of dynamic load of asymmetric gear is deducted and programmed using MATLAB, the variation regulation of dynamic load was obtained. That is the foundation of doing transient EHL analysis of asymmetric gear. The asymmetric gear model program has been made using VBA, and modal analysis of asymmetric gear has been done using ANSYS, which is the foundation of dynamic response of structural calculation and analysis.
Wind-ice Joint Probability Distribution Analysis based on Copula Function
Authors: Yang Fengli , Zhang Hongjie , Zhou Qi , Liu Shanshan 
Published: June 2020

Abstract
Taking the wind speed and ice thickness field measurement data in Southwest China during November 2016 to March 2018 as analytical sample, the probability distribution of the wind speed and ice intensity were analyzed and fitted by using Gumbel distribution model, Weibull distribution model and Generalized extreme value distribution (GEV) model, respectively. The goodness of fitting results had been compared. After the determination of marginal distribution functions for wind speed and ice intensity, 500-year pseudo wind speed and ice intensity samples were generated based on the Monto Carlo method. Five Copula functions were employed in the construction of joint probability distribution function and the most suitable Copula function was chosen for building the wind-ice joint probability distribution model. On the basis of the model, the return periods for 30 years, 50 years and 100 years had been calculated, respectively. The analysis results show that the GEV model well matches the characteristics of wind speed and ice intensity. As for binary Copula function, the Frank Copula function has the best goodness for the joint probability distribution of wind speed and ice intensity. The return period calculations show that the design value of wind-ice joint return period (JRP) is larger than that of co-occurrence return period (CRP) and the value of Kendall return period (KRP) is between that of JRP and CRP. Considering that the dangerous areas of return periods are different, the return period for design should be determined by the combination analysis of different kinds of the return periods. Meanwhile, the importance and the failure results of the project should be taken into account.
Analysis of the Testing and Evaluation Rules for the Carrying Capacity of Highway Bridges
Authors: Zhao Fengli , Zhang Yang 
Published: June 2020

Abstract
Combining with the understanding of the "Procedures for Testing and Evaluating the Carrying Capacity of Highway Bridges" (JTG/T J21-2011) and practical engineering applications, it is found that there are some deficiencies in the process of carrying out the carrying capacity testing and evaluation of bridges by using the "Procedures for Testing and Evaluating the Bearing Capacity of Highway Bridges" Some points, such as the difference in the calculation results of the bearing capacity check coefficient Z1, the ambiguity of some concepts in the specification, and the actual operability still need to be improved, etc., and put forward some suggestions for these problems.
Research on Motion Blur Image of Infrared Target Deblurring Based on Wavelet Transform
Authors: Li Jing , Wang Liqian , Xu Bing 
Published: June 2020

Abstract
Aiming At Removing the Motion Blur to Restore Images, a deblurring Method of Infrared Image Based on Wavelet Transform is Proposed. Determining Whether There is Motion Blur by Using Wavelet Transform to Extract and Analyze the High Frequency Information of Level Subband; Blur Direction and Blur Length Are Calculated by Rotating the Image; the Image Deblurring and Recovery Are Completed by the Optimization Program of Wiener Filtering Algorithm. the Experiments Show That the Proposed Method Can Effectively Removes Motion Blur, and Provide Clear Infrared Images for the Next Image Processing, It Has the Characteristics of Strong Robustness, Good Real-Time Capability and Higher Application Value.
Image classification model based on GAT
Authors: Xu Binghui , Ding Sizhe , Zhang Yan 
Published: June 2020

Abstract
In the field of image classification, graph neural network (GNN) is a kind of structured data modeling architecture with larger functions. However, there are still some problems, such as low efficiency of updating nodes, fixed network parameters and the inability to effectively model the information features of some edges in the graph. In order to solve these problems, this paper introduces attention mechanism on the basis of GNN to improve it, proposes a graph attention network (GAT), establishes a double-layer GAT model, and uses regularization method in model iterative training to achieve image classification. The model is applied to three datasets for experiments. The experimental results show that the average classification accuracy of the proposed model is high and it has good application performance.
A Semi-active Vehicle Suspension Control Strategy Based on Negative Stiffness Characteristics
Authors: Wen Shuyuan , Feng Zihao , Song Mingrui 
Published: June 2020

Abstract
A suspension is an indispensable part of a vehicle. It is of great significance for passengers’ comfort and vehicle stability. This paper proposes a semi-active vehicle suspension model with negative stiffness, and analyzes the effect of negative stiffness characteristics upon vehicle response. When analyzing the performance of semi-active vehicle suspension, a quarter vehicle suspension model is established, and the space state model is built for numerical simulation. After contrasting and analyzing the response of semi-active passive suspension with negative stiffness and semi-active suspension controlled by Skyhook damping algorithm, we conclude that semi-active suspension with negative stiffness decreases the vibration speed of the vehicle body and the deflection of the tire in the low-frequency stage, and improves the smoothness and stability of the suspension. Hence, the negative stiffness characteristic is beneficial to improve the comfort and stability of the vehicle.
An Efficient and Wear-Leveling-Aware Frequent-Pattern Mining on Non-Volatile Memory
Authors: Dong Jiaqi , Zhang Runyu , Yang Chaoshu , Tan Yujuan , Liu Duo 
Published: June 2020

Abstract
Frequent-pattern mining is a common approach to reveal the valuable hidden trends behind data. However, existing frequent-pattern mining algorithms are designed for DRAM, instead of persistent memories (PMs), which can lead to severe performance and energy overhead due to the utterly different characteristics between DRAM and PMs when they are running on PMs. In this paper, we propose an efficient and Wear-leveling-aware Frequent-Pattern Mining scheme, WFPM, to solve this problem. The proposed WFPM is evaluated by a series of experiments based on realistic datasets from diversified application scenarios, where WFPM achieves 32.0% performance improvement and prolongs the NVM lifetime of header table by 7.4× over the EvFP-Tree.
Control System of IMU Calibration Equipment Based on Multi Control Method
Authors: Liu Hao , Li Xiang , Xu Wenli , Liu Yang , Liu Kaiping , Zhang Yue 
Published: June 2020

Abstract
Compared with the previous inertial navigation calibration equipment using a single controller method, the IMU calibration equipment control system based on multiple control methods can be more customized and more flexible. The spindle controller uses a self-developed algorithm. It is realized in real-time control system, which has the advantages of high control positioning accuracy and high rate stability; the automatic turning device controller adopts mature industrial controllers and uses sequential function diagrams to realize the automation process, which is simple, stable and reliable, and can realize complex automation testing process. The two control methods use the way of TCP/IP communication to combine the advantages of the two controllers, shorten the development time, save costs, and achieve high performance, high efficiency and accurate testing.
Model of P controller’s effect on tension of UAV motor
Authors: Li Tiansong , Zhang Haoqiang , Liu Qinghua , Zhou Xiaoyan 
Published: June 2020

Abstract
The tuning of the multi-rotor UAV PID parameters is a long and iterative process, and sometimes it is impossible to find a suitable magnitude. To improve the setting efficiency of control parameters, the classic PID control algorithm is combined with the dynamic model of the UAV to build a mathematical model that describes the effect about parameters of P controller on the tension of brushless motor. Computer simulation and open-loop experimental verification were conducted under the change of parameter of P controller. The simulation and experimental results show that this mathematical model describes the effect of parameters of P controller on the UAV motor’s tension under different attitude angle errors. When the parameters of the P controller are input to the UAV which has determined the parameters of the power system, the motor’s tension can be calculated directly from this model, and this model can assist in determining the magnitude of parameters of the P controller.
A study on Multi-objective Flexible Job-shop Dynamic Scheduling Based on Control Window
Authors: Daqi DAI , Weiping FU , Jianhua SHE 
Published: June 2020

Abstract
It is of great practical significance to study the dynamic scheduling of production in flexible job-shop. In the flexible job-shop scheduling, process, cost, machine tool and processing environment constitute the constraint set of scheduling. In this paper, starting from the multi constraints of scheduling system, the multi-objective linear synthesis of cost, time, quality and resource utilization is carried out. The scheduling intelligent algorithm is improved by using the polychromatic sets contour matrix to improve the operational efficiency. On the basis of the multi-objective flexible job-shop scheduling model under this multi constraints condition, from the actual situation of production scheduling, this paper constructs a scheduling control window according to the dynamic influence domain formed by the dynamic factors in the scheduling process. Dynamic scheduling control is carried out through control window to realize flexible scheduling and intelligent production. The effectiveness and feasibility of the model are verified by dynamic scheduling analysis of a simulation example.