bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulation and Optimization Design of CRH380A EMU Bogie Frame
Authors: Xing Bangsheng , Zhang Jialu , Xu Yongjie 
Published: April 2020

Abstract
Taking SKMB-200 power bogie frame applied to CRH380A EMU as the research object, based on UIC615-4 standard, four kinds of simulated operating conditions load and one kind of supernormal load are calculated, and then constraints and loads required for ABAQUS simulation analysis are determined. The results of static strength simulation show that the maximum stress of the frame under simulated operation conditions, and under abnormal load conditions are lower than the allowable stress of the main material SMA490BW weathering steel. The static strength of the frame meets the standard. Then, through setting design variables, selecting constraints and determining the objective function, the structural optimization analysis of the selected abnormal load cases is carried out. The optimization results show that the total mass is reduced by 109 kg, which is 6.8% lower than that before optimization, and the maximum equivalent stress value of the frame is 329.98 MPa, which still meets the strength requirements. By optimizing the structural parameters of the frame, the under-spring mass of SKMB-200 bogie can be effectively reduced, and its dynamic performance can be improved, which can provide reference for the optimum design of the bogie structure of EMU.
Existence of Global Solutions for Stochastic Population Models with Time Delays
Authors: Wang Changyou , Yang Kaixiang , Jia Lili 
Published: April 2020

Abstract
In this work, we study a class of stochastic multi-species predator-prey model with time delays. By constructing a appropriate Lyapunov functions, the existence of global positive solution for the models is proved, and some known results are generalized.
Design and Construction of Virtual Simulation Experiment Platform Based on Cloud Computing
Authors: Xing Zhihuan , Yao Ning , Lu Xinxi 
Published: April 2020

Abstract
This paper provides a new method to build a virtual simulation experiment platform. The platform is based on cloud computing, which has the ability to support elastic demands on different numbers of students or different experiments. Compared with traditional similar platforms, the platform raises resource utilization rate, requires less hardware, needs less management and has a better performance. The platform also provides many other functions related to virtual simulation experiments, such as course management, reports management, reports assessment, student management and so on, which means one single platform can satisfy almost all demands during the experiment teaching process.
Mesh Coarsening for Fast Simulation on Low Resource Machine
Authors: Luo Gan , Zhang Zhiguo 
Published: April 2020

Abstract
Mesh-based application uses a mesh to discretely represent a real physical system and then calls appropriate algorithm over the mesh to solve equation for simulation. Mesh-based application is usually developed by domain programmers and it runs with very large mesh on super computer. It takes a long time to run with such a large mesh on low resource machine. In this paper, we propose an algorithm designed for coarsening two-dimensional quadrilateral mesh aiming to reduce the size of the mesh so that the application could run with the smaller coarse mesh on low resource machine in a short time. This makes it more convenient for domain programmers to develop and debug the application on low resource machine. The algorithm first generates cells of the coarse mesh by agglomerating cells of the original mesh. Then it constructs internal edges, boundary edges, nodes and all mappings of the coarse mesh. At last, the algorithm constructs datasets of the coarse mesh according to the datasets of the original mesh. The experimental result shows that it takes much less time to run application over the coarse mesh produced by our algorithm, and the error of fast simulation results is within the acceptable range.
An Improved Non-coupled PCNN Model for Image Segmentation
Authors: Deng Xiangyu , Yang Yahan , Qin Wenjuan 
Published: April 2020

Abstract
Pulse-coupled neural network (PCNN) model is widely used in digital image processing, but it is always a difficult problem to set network parameters and determine the optimal segmentation. By analyzing the firing characteristics and network parameters setting for the non-coupled linking PCNN, we propose an improved non-coupled linking PCNN for image segmentation. The model introduce the coupling effect of neighboring neurons into the dynamic threshold subsystem, and using a combination of DNN network, manual adjusting on step length for setting the dynamic threshold initial value. When the dynamic threshold initial value is adjusted properly, the optimal segmentation for the image can be obtained. Using the proposed algorithm in image segmentation of Lena and mammographic images, the segmentation effect similar to that of the traditional model can be obtained by less iteration, and it shows faster speed and better robustness.
Structural Simulation and Fatigue Life Analysis of the Step Attenuator
Authors: Kong Zhigang , Liu Peng 
Published: April 2020

Abstract
In this paper, the internal reed of a type of wideband coaxial step attenuator was studied. The research unit was modeled, and the finite element ANSYS-Workbench simulation software was used for simulation analysis to clarify the stress status of the reed and determine the dangerous position. Based on the theory of structural fatigue damage, the nominal stress method is used to predict the theoretical life of the reed, and N-code fatigue simulation software is used for fatigue simulation. The result shows that the maximum stress of reed connector occurs at the fixed end of the reed, which is the dangerous part. The theoretical calculation value of maximum stress is 318.54MPa, the simulation value of finite element is 395.53MPa. The theoretical prediction of fatigue life is 8.65e6, and the simulation life of N-code is 7.003e6.
Transient Simulation Model for Electric Field Distribution in Cable Joint
Authors: Liao Lei , Zhang Ruxin , Du Gang , Wu Mingyan , Wu Zheng , Huang Xueyou , Li Haiming , Zhang Jian , Lu Binxian 
Published: April 2020

Abstract
The analysis of the impact of the switching impulse voltage on the internal electric field of the cable joint plays a key role in studying the breakdown of the joint. In this paper, the finite element method is used to simulate the transient electric field of the axisymmetric model of the cable joint. By changing the closing moment, the influence of different closing moments on the electric field intensity distribution is studied and analyzed. The results show that under the switching voltage excitation, when the closing moment at t
0=nT, the electric field distribution in the cable joint is consistent with the steady state without distortion. Others, the point near the root of the stress cone will distort when the switch is closed, the closing moment is at 7.5ms, which is the most serious. The closing time is at 10ms, has the greatest influence on the electric field intensity distribution in the cable joint, especially the stress cone end, the bottom of the high voltage shield and the position near the high voltage conductor in the air domain.
Study on the Computational Trust and Its Model
Authors: Wang Qingnian , Hong Wenqian , Huang Chuling 
Published: April 2020

Abstract
The application of block chain technology has greatly improved our digital ability in work and daily life. By fostering greater trust, blockchain technology has not only increased productivity, but is sure to reshape the relationship between individuals and businesses, leading us toward a true digital economy. For hundreds of millions of people and tens of billions of smart devices, this could mean hundreds of billions of smart contracts running autonomously and significantly enhancing global synergies. This paper aims to explore the computational trust model to demonstrate how the trust be computationalised. By building a global blockchain infrastructure, we are spreading trust, and computational trust will be a ubiquitous part of our society. As more businesses and individuals join in, more people will benefit from this new technology, and the future of human society will become more inclusive, transparent, and trustworthy.
Research and Application of Server Health State Prediction Model Based on BP Neural Network
Authors: Wu Qianjun , Jin Dan , Chen Yuhang , Wang Xiaolong 
Published: April 2020

Abstract
As the core equipment of the data center, the importance of the operation and maintenance of the server is self-evident. In order to improve the operation and maintenance of data center server, this paper selected the feature quantity using the analysis method of grey correlation and established server operation parameters and health state prediction model using BP neural network algorithm in machine learning. The model can predict server health status and made fault early warning which provide decision support for operation and maintenance. This can reserve the responding time for problems and realize “active” operation and maintenance of data center servers.
Data Aggregation Privacy in WSN
Authors: Yao Jianbo , Yang Chaoqiong 
Published: April 2020

Abstract
When WSN is applied to monitoring, the privacy of monitoring data from monitoring objects becomes an important issue for the successful application of WSN, which requires effective privacy protection for data aggregation. CPDA (Cluster-based Private Data Aggregation) has a problem that energy costs become higher with increase of nodes within a cluster. In this paper, UCPDA (Upgrade Cluster-based Private Data Aggregation) is established to perform data aggregation while preserving data privacy. According to required privacy, the sensors in a cluster are partitioned into some groups. Data preprocessing is performed only in the same group. Compared to CPDA, UCPDA has lower energy consumption for required privacy.
Dynamic Facial Expression Recognition Based on ResNet and LSTM
Authors: Guo Hong , Chen Jiayou 
Published: April 2020

Abstract
The face image data collected by ordinary face recognition system is usually static. In real life, to fully capture the state information of human emotion change, we need to collect dynamic face expression change data, which needs to capture a video sequence to reflect the process of emotion change. In this paper, we combine ResNet residual neural network and long-term memory network (LSTM) to extract features from video sequences and then recognize them. In the residual neural network, the residual element has a very good effect on the training and optimization process of deep CNN model, and shortens the convergence time of the model. Combined with the LSTM network, the captured dynamic sequence data is incorporated into the CNN model. Compared with the static single frame expression recognition system, the research of dynamic expression recognition has more application value.
Research on Evaluation Factors of Intelligent Level of Dam Safety Monitoring System
Authors: Lu Qiling , Wang Xue , Yu Keping 
Published: April 2020

Abstract
With the continuous improvement of intelligence level, intelligent evaluation of a safety monitoring system has become the key to system evaluation. In order to improve the pertinence of evaluation, according to the application environment and demand of dam safety monitoring, this paper makes an in-depth study on the evaluation factors of the intelligent level of dam safety monitoring system from the system occurrence environment, system composition, network communications, system function and performance, channel protection and power control, remote maintenance, system parameters, running log, statistical analysis, rule discovery, hidden trouble diagnosis, maintenance advice, method and expert recommendation algorithm, intelligent query and human-computer interaction, etc., providing a beneficial reference for the evaluation of improving the intelligent level of dam safety monitoring system.
A Convolutional Neural Network-based Prediction Mechanism for Sewage Treatment
Authors: Zeng Wenru , Guo Zhiwei , Wang Jianhui , Shen Yu , Gao Xu 
Published: April 2020

Abstract
Aiming at the extraordinary dependency on manual experience during the process of sewage treatment, it is required to explore intelligent prediction mechanism for sewage quality. Due to the fact that convolutional neural network (CNN) has some unique advantages for fast prediction, this paper proposes a convolutional neural network-based prediction mechanism for sewage treatment (CPST). It contains two mains parts respectively named learning process and training process. A group of experiments are managed to evaluate the efficiency of the proposed CPST, and the results demonstrate that CPST obtain the lower prediction error compared with baselines.
Research on “Face Swiping” Medical Service Diffusion from the Perspective of Game Theory
Authors: Zhu Keyu , Cheng Peiling , Sun Qirui , Zhang Shanshan , Wang Xiaojia 
Published: April 2020

Abstract
“Face swiping” medical service (FSMS) is one of the important breakthroughs in the field of medical care. FSMS is at a growing stage, and whether it can develop stably in the traditional medical mode has not been well studied at present. This paper establishes an evolutionary game model to analyze the behaviors of the two main participants of FSMS (the hospitals and the patients); And it finds out the factors that affect the choice behavior of the two main participants to analyze different strategies that participants choose how influence the development of FSMS in the future. Furthermore, the profit matrix is analyzed by establishing a replicator dynamic system, and the effectiveness of the model is verified by simulation using Python3.7 software.
Multi - mechanism Coalescence Design and Matrix Expression of Logic Action Sequences of the Over-turn Nursing Robot Part II: Gesture-state in Sets and Matrix
Authors: Gu Lizhi , Gao Shanping , Gu Chunyang , Huang Yuantang , Xu Feiyue , Zhong Xiang , Chen Kai , Song Jinling 
Published: April 2020

Abstract
As is expressed in Part I, Functions and coalescence design of the over-turn nursing robot, the performance and requirements have been put forward with systematic design of several mechanisms. Here, in order to control and function well the over-turn nursing robot, the three-dimensional and five-dimensional Euclidean space with the real number were adopted in terms of sets for gesture of the bedridden person and the corresponding state of the robot, respectively. The matrix method was employed to define and describe the gestures-robot performance and its transition path. The gesture-state sequence matrix not only accurately and clearly expressed the gesture series, state sequence and their corresponding relations, but also laid a theoretical and technical foundation for the path planning from the current gesture to the target one. The control and operation of 7 states and 5 gestures were done to realize the automation and intelligent over-turning safely, comfortably and conveniently.
Research on Autonomous Vehicle Storage and Retrieval System Cargo Location Optimization in E-commerce Automated Warehouse
Authors: Wang Haoxiang , Ji Shouwen , Su Gang 
Published: April 2020

Abstract
Cargo allocation optimization is important to improve the efficiency of e-commerce automated warehouse’s autonomous vehicle storage and retrieval system (AVS/RS) operations. Considering the electrical business logistics characteristic of small batch, batches, variety characteristics, this paper aiming at maximizing the highest efficiency and shelf stability for warehousing efficiency, we established an initial cargo location model, designed an adaptive multi-objective genetic algorithm. MATLAB software programming was used to implement the model solution, and an example verification was performed with an automation warehouse named Jing-dong in China. The comparison between the initial cargo location model and the random storage strategy shows that the model can significantly improve the overall warehousing efficiency and shelf stability of AVS/RS.
Cold-Chain Logistics Distribution Routing Optimization Based on PSO
Authors: Hu Lishuan , Xiang Caihong , Qi Chengming 
Published: April 2020

Abstract
Recently, cold chain which aims to keep agricultural product fresh before arrive to the designated customers has been greatly developed. The distribution routing optimization problem of cold chain has been an attractive research hotspot. In this paper, we introduce the basic PSO method and it’s advantaged about good robustness, global convergence, and intelligent search. Then, we put forward a method for distribution path optimization based on PSO. Taking an example, the evaluation results show that our proposed method can achieve the optimal solution effectively.
Electrical Modification and Experimental Study of Combine Harvester Reaping Unit
Authors: Wang Pengfei , Tian Muhao , Wang Haili , Jiang Wenjun , Cao Qixin 
Published: April 2020

Abstract
In order to deal with the gradual shortage of labour force in the aging society, it is necessary to make intelligent and unmanned improvements to mechanical equipment such as combine harvesters for repetitive daily work. Based on a special combine harvester, the electrical modification for its reaping unit is designed, which includes the selection of motor and reducer, the 3D design and finite element analysis for two kinds of working conditions. Moreover, the electrical driver method is proposed, which can automatic adjustment harvest speed based on the walking speed of vehicle. Finally, some filed tests of wheat harvesting verified the correctness for electric refit. The electrical modification of reaping unit provides theoretical basis and experimental data for the robotics research of whole combine harvester.
Theoretical Research on the Uniformity of Planetary Side Lapping Trajectory
Authors: Wu Yaoyu 
Published: April 2020

Abstract
The reduction to absurdity is adopted to analyze equation of planetary double-side lapping motion built by kinematics, and study the important parameter in the process of lapping-I (the ratio of grinding disc and the inner pin ring in rotary speed) satisfies the condition of uniformity of lapping trajectory of a point in workpiece relative to surface of grinding disc. The results show the ratio I that meet uniformity of lapping trajectory is a function of time t. On the other hand, for a given planetary double-side lapping machine, the I of constant ratio (rational or irrational) that satisfies uniformity of lappingtrajectory does not exist unless it continues to change over the time. This research has laid a theoretical foundation for the further studying in uniformity of lapping trajectory, and also provided a new idea and method for the analysis of relative velocity between workpiece and grinding wheel, the wear uniformity of grinding wheel, and the study of workpiece surface quality.
Study on Flux-Pinned Load Characteristics of High Temperature Superconducting Maglev Vehicle
Authors: Wu Haoran , Mao Rancheng , Yuan Yuhang 
Published: April 2020

Abstract
With the distinctive pinned effects, the high temperature superconducting magnetic levitation vehicle is characterized by its high-performance self-stability, strong anti-interference ability and non-contact features, which are worthy of being studied in detail. In this paper, the high temperature superconducting maglev test platform in Southwest Jiaotong University was utilized to study the flux-pinned force. The calibration of vertical and lateral load characteristic curve under corresponding quasi-static conditions were conducted firstly, then it was transformed through polynomial fitting. In addition, the variation law of flux-pinned force under straight and curved tracks at different running speeds of maglev vehicle was attained based on the experiment.
A New Direct 9-line Geometric Error Measurement Method for CNC Machine Tools
Authors: Liu Huanlao , Rasheed Muzammil , Su Miaojing , Liu Can , Li Xiaoli 
Published: April 2020

Abstract
The existing line measurement methods are analyzed. In the process of obtaining the existing error parameters, the assumption conditions in the model developing are adopted, which makes the insufficient adaptability of the model and unreliable measurement results. A method for directly obtaining the error values of the machine tools have suggested by using a high-precision laser interferometer. The 9 lines at different places in the working space of the machine tool is proposed. A three-axes CNC vertical machining center was measured, which proved that the measurement process is easy to operate and the operation is relatively simple, which can be applied to actual industrial field measurement. This method is further popularized and can be used to verify other line measurement methods and check the error models, which has great practical application value.
Multi-scale Calibration Board Based Accurate Calibration of a Scanning Electron Microscope
Authors: Hua Yiran , Zhang Xianmin , Li Hai , Yang Zhuobo 
Published: April 2020

Abstract
We present a new calibration method based on multi-scale calibration board for scanning electronic microscopy (SEM) at low magnifications. The implementation of the calibration mainly depends on automatic center-point features detection from the calibration board image instead of corner detection. The center-point feature is the centroid of each squares, which is obtained via morphological processing. We use the calibration model consisting of projective model and static distortion model. It is proved the point detection proposed in this paper is more accurate, efficient and robust, compared with corner point detection in the traditional calibration process. Then, reprojection error is used to evaluate the accuracy of the calibration results. At last, the method is efficient and reliable with accuracy, which is testified by experiment.
Design, prototyping, and experiment of the ocean current power generation system using Bach Savoniusrotor
Authors: Yusiran  , Erwin  , Lazuardi  
Published: April 2020

Abstract
Design, prototyping, and experiment of ocean current power generation system have been carried out using the Bach Savonius rotor. The introduced ocean current power generation prototype is validated on real measurement obtained in the Rupat Strait, Indonesia. In this research, the influence of the velocity of ocean currents, the number of turbine blades, and the blade arc angle of the generator output power are studied. The results showed that the turbine output power is strongly influenced by the velocity of ocean currents where the velocity values of ocean currents varied in the range 0,63-1,98 m/sec. The maximum electrical power of the turbine occurs at a current velocity of 1,98 m/sec of 26,88 Watts. The number of turbine blades has a significant effect on turbine output power. The turbine reaches maximum power is found in the rotor with a number of 3 blades with a power coefficient of 0,1176 on the tip speed ratio of 0,359. The blade arc angle is varied at angles of 90°, 135° and 165°. The blade arc angle 135° gives the best performance with a power coefficient of 0,102 on the tip speed ratio of 0,298.