bluuebunny/crossref_metadata_2025 huggingface dataset:
LDA_RAD: A Spam review detection method based on topic model and reviewer anomaly degree
Authors: Ya Zhou , Qingqing Zhou , Yuhan Wu , Shuai Zhang
Published: June 2020

Online shopping has become a popular activity among consumers. Reviews have become important standards for consumers to buy things. To detect the spam re-views that do not correctly response the right information of goods, a method based on topic model and reviewer anomaly degree is raised. This method divides spam reviews into content-type and deceptive spam review respectively. Firstly, the experimental data set is modelled by LDA topic, which detects the content-type spam reviews with different themes. Then the deceptive spam reviews are detected by the reviewer’s abnormality degree index. It assigns a score to each review according to extracted features and related weights. A score is finally combined with an adaptive weight calculation based on the abnormal period and the reviewer’s similarity to obtain the review score. The review with a high score is considered to be a spam review, and the review with a low score is a true review. Experiments show that this method has a certain improvement on the recognition rate of spam reviews.
Fireworks Algorithm Based on Opposition-Based Learning and Quantum Optimization Strategy
Authors: Jin Hongbin , Li Hao , Ma Yanyan , Fang Xi
Published: June 2020

Aiming at the bottleneck of optimization performance and slow convergence speed of fireworks algorithm, a new fireworks algorithm (FWA) is proposed by integrating Opposition-Based Learning and Quantum Optimization strategy (OQFWA). The new algorithm optimizes the original fireworks algorithm in the aspects of the selection of sparks and the local improvement of the optimal individuals, which effectively improves the convergence accuracy and speed of the algorithm. The simulation results of extremum optimization of typical test functions with different characteristics show that the fireworks algorithm, which integrates the Opposition-Based Learning and Quantum Optimization strategy, and has good optimization performance.
Research on Open System of Economic and Management Laboratory Center Based on Cloud Platform
Authors: Yan Honshu , Yin Qinghai
Published: June 2020

The traditional open management mode of economic and management experimental teaching center can no longer meet the needs of personalization, mobility and digitalization of college students in the new era. Through the questionnaire research of 56 experimental centers, we get the valid data of 56 experimental project managers and 372 college students’ questionnaire, and use SPSS19.0 software to analyze the data. Based on the analysis results and the design of laboratory teaching management, college entrepreneurship contest, open laboratory center and project management, this paper proposes that the traditional laboratory management mode should be transformed to the modern management mode supported by mobile, digital and We Chat public number technologies.
Research on Comparison Model of Connected Project Financing Model Based on Fuzzy Hierarchy Theory
Authors: Yongfang Jan , Lin Liu
Published: June 2020

A scientific and reasonable project financing mode is very important for the development of transnational grid interconnection projects. On this basis, this paper first analyzes the status of the interconnection project, and designs the interconnection project financing mode comparison index system from four dimensions, external financing environment, financing method, financing efficiency and financing risk. Secondly, with the help of fuzzy analytic hierarchy process, the comparison model and calculation process of the interconnection project financing model are established. Finally, the S interconnection project is selected for case analysis, and it is concluded that the interconnection project should adopt the BOT project financing model, which is helpful to reduce project financing risks and increase revenue.
Face Recognition Algorithm Based On Convolutional Neural Network
Authors: Xu Shiyuan , Xu Shicheng , Wang Zhaojun , Pu Chengyan , Meng Qingchuan
Published: June 2020

In response to the needs of modern enterprises for intelligent security of face authentication, a face recognition algorithm based on deep convolutional neural network is introduced in this paper. In order to improve the accuracy of face recognition, the design of 11 convolutional layers and 4 pooling layers. The network uses the standard face data set CASIA-WebFace for training, and the face recognition accuracy on the LTW database can reach more than 97.8%. Based on this deep learning network, a face recognition management system was designed. The system realized 1: 1 face authentication and 1: N face recognition. After applying the convolutional neural network algorithm, the face search time is significantly reduced, indicating that the algorithm has higher efficiency and practicability.
Artificial Intelligence and Career Development of College Teachers: Challenge and Countermeasures
Authors: Wang Lei
Published: June 2020

In this AI-dominated age, emergence of virtual teachers, advances in smart education and changes in the job market bring about new challenges to career development of college teachers. How to cope with the development of artificial intelligence, reshape the roles and improve their educational expertise has become an important issue that teachers should pay attention to. On the basis of previous studies and in-depth interviews with college staff and engineers, this study illustrates the strategies for career development and improvement of expertise of college teachers from the perspectives of building the human-computer collaboration philosophy, reshaping the role of teachers, improving expertise of smart education and increasing college support, in hopes of helping teachers to adapt to the AI-dominated age.
Research on Oral English Teaching System Based on VR in the Background of AI
Authors: Li Xi , Xie Ying , Liu Tianqin
Published: June 2020

2016 is a year when AI (Artificial Intelligence) technology has made a significant breakthrough. The language service products of AI and VR (virtual reality) technology are increasingly appearing in the commercial market, which has brought a huge impact on the language service industry. Based on the analysis of the current principles and development status of the language service products of artificial intelligence and VR (virtual reality), this paper attempts to explore the enlightenment of new technology to language service, especially in oral English teaching, while oral English Corpus needs to be built. This research designs a set of oral English training system based on artificial intelligence and VR (virtual reality) technology, which makes oral English teaching conform to the requirements of the times. The research result is that it can improve the efficiency of oral English training.
Research and Application of Historical Building Conservation and Management System based on UAV
Authors: He Huagui , Li Qixing , Guo Liang , Yang Weijun
Published: June 2020

Guangzhou is one of the most famous historical cities in China which has abundant unique cultural resources. With the development of economy and the acceleration of urbanization, the preservation of historical buildings and urban construction have fallen apart, which leads to the destruction of historical buildings and the lack of efficient supervision of the protection of historical buildings. For the difficulties in digital preservation of historical buildings in Guangzhou, it is necessary to construct a comprehensive application of high-precision terminal application, network platform and other technologies, to control the whole process of information interaction, data processing and arrangement, thus achieving the implementation of historical building preservation plan and management.
Research on the application of Mobile GIS in the intelligent protection of historical buildings
Authors: Guo Liang , Zeng Zhihua , He Huagui , Yang Weijun
Published: June 2020

Aiming at the protection and management of urban historical buildings, this paper studies the methods of historical building information management and utilization based on mobile GIS to improve the accuracy, timeliness and scientificity of historical building protection and management. This article introduces the use of mobile GIS terminals to quickly collect and manage historical building attribute information, multimedia information, historical archive information, and spatial information. It also supports 3D scene browsing, information analysis, and thematic map production. The historical architecture culture was demonstrated, and the applicability and advancedness of the method were verified through the practical experience of intelligent management of historical buildings in Guangzhou.
Natural frequency analysis and simulation test of conical shell under support condition
Authors: Bao Xiaohan , Liu Yiling
Published: June 2020

This paper presents an analysis of the vibration characteristics of a conical shell with a fixed support. Firstly, a reasonable numerical calculation model has been established based on the Donnell shell theory, and the first 9 modes has been calculated by Numerical method with MATLAB. Then, the finite element model of conical shell has been built on the ANSYS Workbench simulation platform. With specific constraints set, modal analysis has been carried out on the model of conical shell to find and verify the corresponding numerical model is convergent.
A Facial Approach for Detection of Irregularly Entangled Copper Wire during Twining by Machine Vision
Authors: Zhang Yuhang
Published: June 2020

In this study, a computer vision-based inspection system is designed to detect the presence of irregularly entangled copper wire during twining for industrial processing. With the assistance of high speed industrial camera, the images of copper wire during twining would be recorded in real-time. All lines in the images are detected by Hough transform. According to the calculated slope of all lines detected in the images, a threshold is artificially set to distinguish between the regularly coiled and irregularly entangled copper wire. This defect detection system could greatly improve the efficiency of industrial production.
Simulation analysis of grid-type PVD thin film sensor based on COMSOL
Authors: Yujian Song , Ronghong Cui , Yuting He , Tao Chen , Xianghong Fan
Published: June 2020

On-line quantitative monitoring of fatigue crack sensors is an important part of structural health monitoring systems. A rectangular grid-type PVD (physical vapor deposition) thin film sensor based on the potentiometric method is designed in this paper. First, the sensor finite element model is established through the AC/DC module of COMSOL Multiphysics to verify the feasibility of the sensor to monitor cracks. Second, the effect of the number of sensing channels on the sensitivity of the sensor is studied. Finally, the structural parameters of the sensor are optimized. Significantly improved sensitivity for crack detection. The results show that the rectangular grid PVD film sensor can effectively monitor structural cracks.
Cross-domain few-shot classification through feature confusion
Authors: Ye Guoxiang , Xia Yan , Feng Zhangwei , Tian Feng
Published: June 2020

Few-shot classification has made great progress in recent years which aims to solve new tasks using the prior knowledge obtained from a set of similar tasks with few labeled examples. However, the performance of current methods drops when domain shift exists between training and testing samples. Considering the situation where target domain examples are hard to collect, it is necessary to focus on the cross-domain problem. In this paper, we propose a simple method which embeds the domain adaptation method into the few-shot problem under a novel cross-domain few-shot setting, and focus on supervised setting in the target domain where few labeled data available for domain adaptation. Extensive empirical evidence shows the effectiveness of our method.
Research on the Value of Inclusive Education Based on Big Data in Promoting the Development of Minority Education
Authors: Ai Yingtong , Lili
Published: June 2020

Compulsory education for ethnic minorities is a weak link in China’s education system, which is mainly reflected in the unfair phenomena in educational opportunities, educational process and educational results. Inclusive education for ethnic minorities in the context of big data refers to the activities to promote the socialization of ethnic minority students in China by means of technological gifts in the era of big data for ethnic minorities whose population is relatively weak. As the largest developing country, promoting inclusive education in China is still the most basic task of the country, and the government will undoubtedly bear the most important responsibility in promoting inclusive education. The content of inclusive education is more and more broad, far beyond the scope of special education, involving all kinds of learning difficulties and students with special needs. In modern China, which has increasingly frequent international contacts, we need to re-examine China’s current education from the perspective of inclusive education based on the background of big data.
Research on Effects of Satellite Attitude on Modulation Transfer Function of High-resolution Space Optical Remote Sensor
Authors: Jiang Xiaonan , Fu Yao , Bao He , Liu Hailong , Sun Xuechen , Han Chengshan
Published: June 2020

In this paper, the necessity of analysing the satellite platform attitude maneuver performance impact on imaging quality is pointed out, basing on a review of high-resolution space optical remote sensor development. Using some mission requirements and the satellite performance indicators as simulation input conditions, with Monte Carlo method, the analysing of attitude maneuver range that meets the modulation transfer function of image motion velocity compensation larger than 0.95 was taken. The simulation results were showed in three-dimensional surface graphs intuitively, which indicated the attitude stability and attitude measurement accuracy specifications of the satellite platform meet the imaging requirements in the range of elevation angle within±5° and rolling angle within ±45°.
Comparison and Analysis of Different Numerical Schemes in Sod’s One-dimensional Shock Tube Problems
Authors: Ji Ning
Published: June 2020

In this paper, we apply a variety of numerical methods to calculate and analyze the Sod’s one-dimensional shock tube problem. Different schemes show different resolution capabilities for rarefaction waves, shock waves, and contact discontinuities. Under different grid density, we further analyze the performance of various schemes, and carry out error analysis to calculate the numerical accuracy. In conclusion, the accuracy of different numerical schemes decreases at discontinuities, and NND scheme and WENO scheme can effectively eliminate the non-physical oscillation.
Research on the Detection Method of SQL Injection Attack Based on Sequence Alignment
Authors: Qi Xiaoxia , Dai Tianyang
Published: June 2020

In order to improve the detection efficiency of SQL injection attack, this paper proposes a detection method of SQL injection attack based on sequence alignment algorithm. Needleman-Wunsch and its improved algorithm are used to carry out sequence alignment and then find out the best alignment results in the global-scope. Experiments show that 100% of the SQL injection attacks tested are detected in the detection rate; the algorithm has the minimum response delay compared with other types of SQL injection attacks. The detection method proposed in this paper can improve the detection effect quickly and effectively, and reduce the complexity of time and space.
Research on Experiential Solidification Learning Technology for Intelligent Mining of Power System Vulnerabilities
Authors: Zhao Di , Li Yan , Dong Yang , Ni Jiaming
Published: June 2020

Aiming at the problems that the experience of network security personnel in power system is difficult to solidify, and the basic and repetitive vulnerability mining work is intelligently replaced by the lack of experience guidance, this paper studies the experience solidification learning technology of power system vulnerability intelligent mining. Format specification and parsing language of vulnerability intelligent mining experience tree are proposed, which can transform flexible and complex vulnerability mining experience into a language that can be recognized and understood by machine. At the same time, it puts forward the solidification and intelligent learning technology of vulnerability mining experience, through the automatic pervasion test for the target, combined with reinforcement learning algorithm, intelligent learning generates vulnerability mining experience tree, and finally forms the high-efficient transformation of the red team personnel experience and the intelligent substitution of part of the work.
Research on the Design and Construction of University Informationized Learning Environment under the TPACK Framework
Authors: Gan Baiqiang , Zhang Chi
Published: June 2020

The rapid development of information technology has broken the traditional teaching methods and learning environment, and the traditional teaching environment is difficult to meet the needs of information-based teaching. Therefore, based on the TPACK theory, this paper integrates the teaching method, information technology and subject content, and uses cloud computing technology to design the information-based learning environment model and framework in line with the teaching characteristics of colleges and universities. finally, from the theoretical and technical aspects, a learning environment based on cloud computing technology has been established, which provides support and guarantee for the reform of basic information teaching in colleges and universities.
Pose measurement and ground validation Based on lidar in-orbit
Authors: Lin TingTing , Li Ronghua , Yang Youqing , Li Heng
Published: June 2020

An effective ground validation method is proposed to solve the difficult problem of non-cooperative target position measurement in-orbit verification. First of all, this paper highlights the effectiveness of a light fuzzy target point cloud model visible part judgment method to search. Secondly, laser reflection intensity is used to realize the point cloud registration process, not only the influencing factors of the space radiation source to the image, but also the incident angle imaging quantitative analysis. Finally, points cloud precise registration is achieved according to the iterative algorithm. This method realizes the ground verification work of the robustness, real-time performance of the position, attitude measurement algorithm, and shortens the study cycle of the future on-orbit control task.
A predicton model for the seismic intensity in meizoseismal area based on Genetic Neural Network
Authors: Shao Dan , Tian Qinhu , Zhang Weichao , Ren Hao
Published: June 2020

In this paper, a novel model for seismic intensity prediction in meizoseismal area is proposed based on BP neural network. 322 earthquake events of MS
5.0 or more occurred in the mainland of China from 1966 to 2017 with detailed intensity records. From the collected sata set, seven factors related to the seismic intensity are selected. Principal component analysis is performed on these factors to generate the network input, while the intensity of the epicenter is the output of the network. The BP neural network is optimized by using genetic algorithm. Simulation results show that, compared to the traditonal prediction methods, the proposed prediction model based on BP neural network has obvious advantages in terms of prediction accuracy and correct prediction probability.
Using Topological Data Analysis to Process Time-series Data: A Persistent Homology Way
Authors: Ma Gang
Published: June 2020

Topological Data Analysis (TDA) is a novel new and strong-growing method to deal with various data in most areas. And Persistent Homology is one of the most pivotal tools in Topological Data Analysis to acquire topological properties of the data. This article is based on the main mathematics behind Topological and Topological Data Analysis. And it describes how to use the above theories and methods to do the analysis job for time-series data. Moreover, it discusses the further applications of TDA to other domains and the combination of machine learning with Topological Data Analysis. The article outlines the TDA model and principle behind the data set and provides insights into the function of TDA for time-series analysis as well as opportunities for future work.
An Extended Position Based Dynamics Method for Cloth Simulation
Authors: Quan Wei , Teng Dexin , Li Hua , Han Cheng
Published: June 2020

Position based dynamics is an effective method in real time deformable body simulation, which is widely used. But, as we all know, it is not suitable for greater accuracy applications. As to cloth simulation, the over-stretching problem especially affects its accuracy. Therefore, an extended simulation method based on position dynamics is proposed in this paper. The time step is subdivided effectively, and the number of iterations is controlled when cloth is deforming; We also optimize the Gauss-Seidel iterative solver in parallel using an improved grouping method which ensures the efficiency of the algorithm. This method is simple and easy to implement. Compared with the traditional method, the position error of deformation is significantly reduced while cloth is stretched, and the simulation efficiency is enhanced. Besides, it can be easily integrated into the existing position based dynamic framework.
A New Type of Marine Solar-energy Sail System
Authors: Chen Yan , Liu Xuetao , Tang Xujing , Zhang Yan
Published: June 2020

In this paper, a new type of marine intelligent solar-energy sail system is designed. According to the state and environmental parameters of the ship, it can increase the illuminated area of the sail by changing the sail attitude, realize the intelligent control of the sail, realize the efficient utilization of wind energy and light energy, and effectively increase the endurance capacity and application range of the clean energy ship. The promotion of the research results can greatly save the operation cost of cruise ships, have greater economic and environmental benefits in the long run, and conform to the concept of sustainable development.
Research on Similar Medical Records Recommend Model based on Natural Language Processing
Authors: Shuai Yong , Zhou Chunjiang , Pang Qiaoyue , Yuan Can , Xie Zheng
Published: June 2020

Aiming at the problem of low efficiency and poor credibility in medical record text data mining, this paper proposes a similar medical record recommend model based on natural language processing. Firstly, extract the samples by structured data in the medical record data and narrow down the extraction of similar medical records, then use the text keyword extraction algorithm to obtain the keyword text data about chief complaint, medical history and physical examination in the medical record text, use these data as input data, get the similarity between the input data and the patient data by text similarity algorithm, and use collaborative filtering algorithm to calculate the most similar medical records and obtain the most similar medical records diagnosis conclusions, take the chief complaint, medical history, physical examination data and diagnosis conclusions as input data to calculate the text similarity and collaborative filtering values and obtain the final recommend treatment plan. The case analysis proves that the model proposed in this paper has high credibility and practicality.
Difference Attention Based Error Correction LSTM Model for Time Series Prediction
Authors: Liu Yuxuan , Duan Jiangyong , Meng Juan
Published: June 2020

In this paper, we propose a novel model for time series prediction in which difference-attention LSTM model and error-correction LSTM model are respectively employed and combined in a cascade way. While difference-attention LSTM model introduces a difference feature to perform attention in traditional LSTM to focus on the obvious changes in time series. Error-correction LSTM model refines the prediction error of difference-attention LSTM model to further improve the prediction accuracy. Finally, we design a training strategy to jointly train the both models simultaneously. With additional difference features and new principle learning framework, our model can improve the prediction accuracy in time series. Experiments on various time series are conducted to demonstrate the effectiveness of our method.
Design and Research on Integrated Platform of EMC Laboratory
Authors: Shichao Guo , Dandan Guo , Qiongyu Zhang , Nankai Wu , Jiaxin Deng
Published: June 2020

The electromagnetic compatibility (EMC) laboratory plans to implement a proprietary EMC testing platform, which is customized according to the professional perspective of EMC testing. The integrated platform will fully utilize the overall advantages of knowledge resources from various angles to realize the automatic operation of various functions. The simple and tedious work of the engineers during the inspection process will be completed automatically, reducing the burden and devoting more time to creative and high-value work. At the same time, the platform will integrate higher-level related management systems and all EMC testing equipment to achieve overall data interaction among the testing department, design department and higher-level management agencies during the EMC testing process.
Unmanned Sorting Site Combined with Path Planning and Barcode Identification
Authors: Tan Haipeng , Zheng Xinrui , Chen Yiying , Zheng Weibin , Ni Weichuan
Published: June 2020

At present, the existing express sorting in the market has low accuracy and cannot be solved from manual handling. In addition, the management of express delivery sites is confusing, and the phenomenon of lost shipments is also endless. Regarding the issues above, we have proposed unmanned sorting site combining path planning and barcode identification. The site uses STM32 as the main control chip to realize barcode recognition and robotic arm control. Among them, barcode recognition uses calibration, image pre-processing and other related OpenMV technologies to realize fast identification, classification of express barcodes and obtain the location information of express shipments. The control of the robotic arm is achieved by using the D-H parameter method to locate each node of the robotic arm. And we are using introducing fuzzy adaptive PID algorithm to improve the control precision after path planning. After a large amount of experimental data analysis and comparison, the final conclusion is that the system can maintain high bar code recognition and fast picking accuracy under different conditions of different objects. And it can make up for many shortcomings of traditional express delivery sites and has certain market value.et value.
Study on the intelligent evaluation model after stoke based on random forest
Authors: Ge Yaru
Published: June 2020

According to the summary of “China cardiovascular report 2018”, in recent years, there are 2 million new stroke patients in China every year, and nearly 70% of them have lost hand function due to stroke. Therefore, the rehabilitation evaluation of postoperative hand function of stroke patients is complicated with low intelligence. In this paper, data collection methods are introduced firstly, and the original data are artificially classified. Then, starting from the decision tree method, the motion data of stroke patients are intelligently evaluated by establishing a random forest, and the evaluation results are returned to the patients for review in the form of floating point number based on their probability proportion. Finally, the results of the model experiment and its advantages and disadvantages are analyzed, and the future development direction and prospect are put forward.
Denoising Method for Underwater Acoustic Signals Based on Sparse Decomposition
Authors: Huang Guanqun , Xiao Yewei , Yin Zhe
Published: June 2020

In order to improve the problem of relatively low signal-to-noise in the extraction of underwater acoustic signals under the background of strong interference, a sparse decomposition-based underwater acoustic signal denoising method is proposed. The main work is as follows: First, the signal is decomposed into a complete dictionary that can reflect the characteristics of the signal environment through the singular value decomposition method. Then, a cyclic shift is used to construct a signal matrix and an initial dictionary. A newly generated super-complete dictionary is obtained through training and updating. The atoms in the dictionary matrix are correlated and orthogonalized by an adaptive orthogonal matching pursuit method. Finally, the linear combination of the atoms that can best reflect the characteristic information of the underwater acoustic signal is used to reconstruct the underwater acoustic signal to achieve the purpose of denoising. The noise filtering underwater noise signal is simulated and compared with the traditional filtering method. The simulation results show that this method improves the signal-to-noise ratio of the signal after sparse decomposition and reconstruction of the original underwater acoustic signal, and has a certain denoising ability under strong noise and various types of reverberation interference.
Media communication strategy in international disputes based on information Cybernetics
Authors: Li Kan
Published: June 2020

Media communication strategy is a key to controlling the initiative of public opinion in international disputes. In view of the problem that the public opinion strategy of safeguarding maritime rights in China is not systematic enough, this paper uses the cybernetic thinking of information dissemination, on the premise of analyzing the law of public opinion information movement, the expression of dispute elements and the positioning of communication perspective, This paper puts forward a strategic focus on the direction and efficiency of information dissemination, and promotes legal identity and public opinion strategies. Under the condition of information asymmetry, we can achieve the same effect as information symmetry through system, mechanism and scheme design, so as to lead the trend of social ideology in international disputes.
Void Aware Routing Protocols in Underwater Wireless Sensor Networks: Variants and challenges
Authors: Khasawneh Ahmad M. , Abualigah Laith , Al Shinwan Mohammad
Published: June 2020

Recently, Underwater Wireless Sensor Network (UWSN) become a wide range technology for gathering important events from underwater world. UWSNs is consisting of underwater sensors with limited energy and using acoustic link as a communication medium. Routing methods is the major part that need to be designed in order to transmit the data with minimum cost such as high delivery rate and low energy consumption. Communication void is one of the major perspectives that effects the delivery ratio and energy consumption in the whole network. Therefore, this issue attracts researchers to follow up and design techniques that helps in improving the overall performance of the networks. This article reviews and compares different void aware algorithms proposed for UWSNs. We analyze and discuss representative routing protocols, and discover the requirements considered by the different routing algorithms, as well as limitations and the design requirements under different operations. Finally, we highlight some important future perspectives for UWSNs belonging to routing protocols.
Interpretable Neural Network Construction: From Neural Network to Interpretable Neural Tree
Authors: Ouyang Xuming , Feng Cunguang
Published: June 2020

The neural network has made outstanding achievements in many fields, while comparing with traditional machine learning models, the neural network has poor interpretability, which brings great limitation to its practical application. Therefore, many researchers try to combine neural networks with traditional models to improve the interpretability of the neural network. Their methods either result in performance depreciation or lead to computation-intensive. In this paper, we propose to transform a neural network into the interpretable neural tree. In the interpretable neural tree, each node contains transformation function and routing function. Each transformation function corresponds to a layer in the neural network, using for controlling data transformation. The routing function is utilized to control the direction of data flow in the tree structure. Our experiments have indicated that the interpretable neural tree makes the neural network interpretable to some extent while maintaining the performance.
Ensemble of online sequential extreme learning machine based on cross-validation
Authors: Wei Liyun , Wang Lidan , Li Yunfei , Duan Shukai
Published: June 2020

The online sequential extreme learning machine (OS-ELM) was proposed as an evolution of the Extreme learning machine (ELM) in 2006. The learning algorithm can learn data by fixing or changing the size of the chunk (a block of data). Compared with other online algorithms, it has faster training speed, and the generalization performance is better. The proposed ensemble of neural networks further demonstrates that the use of the neural network sets with multiple consensus schemes has a greater improvement over the stability of a single network. The basic idea of cross-validation is to group the original data sets, part of which is to train as the training set and the other part of which is to verify as the test set, so the algorithm can reduce the over-fitting problem of the data to a certain extent, and extract more valid information in the limited data set. In this paper, a new ensemble of online sequential extreme learning machine based on cross-validation (ENOS-ELM) is proposed. Through application of cross-validation and integration to the training stage, the accuracy of the algorithm in classification is further improved.
From Viewpoint of 3C Model to Use Supply Chain Integrating to Create Competitive Advantage
Authors: Liu Jia , Chang Shih-Feng , Lee Xin-Ru , Tan Yong-Lin
Published: June 2020

While global environment is proceeding globalization and internationalization, traditional logistics management can not be coped with the change. Therefore, to be the winner, supply chain integrating is necessary. Domestic car manufacturers take supply chain integrating to cope with the pressure of the market in now and future, and they hope to keep the competitive advantage. In view of this, from viewpoint of 3C model, we use case study to discuss and analysis supply chain integrating on company C which is the benchmark of the car industry, and then we offer a good suggestion to car manufacturers and future study direction.
Development and verification of wireless torque sensor node for rotating shaft
Authors: Wang Dajian , Wang Zhinan , Chen Demin , Li Zhimin , Yang Sujun
Published: June 2020

There are many torque measurement technologies at present, because the rotating shafting torque monitoring is very important. However, compared with the cost-effective strain measurement technology, there are signal transmission and power supply technology bottlenecks in the long-term monitoring of large shafting torque. In view of these technical bottlenecks, this paper designs a strain torque monitoring system based on wireless signal transmission technology and wireless inductive power supply technology. In this paper, the current torque measurement technology is analyzed. The design principle and technical characteristics of wireless torque sensor and wireless induction power supply device are developed. This paper is a complete long-term monitoring solution for shafting torque, which has a good referent value for relevant engineers and technicians.
Torque allocation strategy for two axles four wheel drive electric vehicle with improvement of economy and stability
Authors: Ou Yang , Wang Peng , Xu Lei , Fan Jie , Zhou Zhou , Li Zhe , Bai Qin , Zhang Yuanwei , Gao Zihao
Published: June 2020

Two axles four wheel drive electric vehicle is an important development tendency of electric vehicle. However, how to coordinate the torque distribution between front and rear axles thus ensuring vehicle stability while maximizing motor’s efficiency still confronts great challenges. In this paper, we propose a three-layer hierarchical control method, which not only incorporates prior engineering knowledge into the control policy so as to relieve computational burden for real-time usage, but also properly deals with the priority between safety and system efficiency. Simulations are conducted to verify the effectiveness of the proposed method. Results show that the derived control policy can ensure high system efficiency when safety is guarenteed. Simultaneously, it can actively decrease the motor torque to improve vehicle stability when wheel slip occurs.
Research on automatic aerodynamic optimization for a SUV based on RBF model
Authors: Wu L L , Fu Y , Bu X B , Li X R , Ma X L
Published: June 2020

Considering the continuous shortening of automobile R & D cycle, mathematical methods have been more used in automotive aerodynamic optimization design for their capability to fit the law and calculate the optimal results. In this paper, the deformation software, fluid analysis software and optimization software are connected to build an automatic aerodynamics optimization platform of automotive shape. Based on the RBF model, the automatic aerodynamic optimization for a SUV is completed with the front windshield angle, rear windshield angle, engine cover angle, approach angle and departure angle as design parameters and the drag coefficient as design objective. The drag coefficient of the optimal model is 9.40% lower than that of the initial model, and remarkable drag reduction effect is achieved.
Experimental Study on Determining the Elastic Modulus of Metal Materials by Deflection Method
Authors: Wei Liuchuang , Wei Ping , Yang Yabiao
Published: June 2020

This paper studies the method of measuring the elastic modulus of metal materials by the deflection method. The relationship between the deflection and the load and the elastic modulus of the metal cantilever beam is established, so that the elastic modulus of the cantilever beam is indirectly measured. The experiment requires that the deformation of the material is within the elastic range. Furthermore, the deflection method is adopted. Not only the method is simple and does not require expensive equipment, but also the average value of multiple sets of experimental results is used as the modulus of elasticity of the material during measurement, which ensures a certain accuracy.
Detection of Rotor Position with MR Sensor TLE5309D
Authors: Cai Bingkun , Li Jianqiu , Hu Jiayi , Liu Shucheng , Xu Liangfei , Ouyang Minggao
Published: June 2020

The rotor position is a key state in the closed-loop control system of the permanent magnet synchronous motor (PMSM). Its measurement accuracy has a significant effect on steady accuracy, dynamic response, and torque ripple. The magnetoresistance (MR) sensor is widely used in the rotor position detection due to its distinct advantages, such as simple structure, high sensitivity, and strong robustness. In this paper, a solution using the giant magnetoresistance (GMR) sensor in TLE5309D chip for angle measurement is introduced, and its feasibility is verified by finite element analysis (FEA) simulation and bench test. In the simulation, two schemes different in the sensor location and the number of permanent magnet poles, are evaluated according to the higher harmonic content and field direction stability near the sensor. The experiment from 1 rpm to 1000 rpm is implemented, and the measurement results after calibration based on discrete Fourier series (DFS) show that the GMR sensor has a good performance in the test.
Research and design of scanning servo device for airborne microwave radiometer
Authors: Hu Yong , Liu Xin , Hu Ye , Wang Xianli , Xu Mingxu , Li Bin
Published: June 2020

The Microwave Radiometer can obtain various characteristics of the measured target. The remote sensing aircraft has several outstanding advantages such as stronger mobility and larger capacity, which makes the Airborne Microwave Radiometer become the most important part of Microwave Remote Sensing technology. The mechanical structure was designed in this paper, which included airborne microwave radiometer scanning servo device structure and servo control system according to the requirements of the project. The statics and dynamics simulation of the scanning servo device were analyzed, the maximum value is 46.48MPa at the connection between the left support pedestal and the left drive shaft in the statics analysis and the first-order natural frequency of the scanning servo device is 50.516Hz in the modal analysis. The results showed that the mechanical structure meets the requirements of airborne working environment. The current - speed double closed loop control system was used to achieve the high precision speed control. The current - speed double closed loop control system was used to meet the high precision speed control requirements of high precision airborne microwave remote sensing technology.
Driving Behavior Recognition Based on EEG Data From a Driver Taking Over Experiment on a Simulated Autonomous Vehicle
Authors: Zou Bin , Xiao Zhenming , Liu Mutian
Published: June 2020

Driving behavior recognition is a critical part of the driver safety system. Most of the popular researches have utilized the driver’s questionnaire data and driving data to recognize driving behavior. But few studies have used physiological data to recognize different driving behaviors, such as EEG data. In this paper, a new method was presented to recognize different driving behaviors based on EEG data. The driving data and EEG data were collected when participants took over the autonomous vehicle. Through K-means, the driving data were classified into two groups, and the classification results were utilized as inputs to generate a k-Nearest-Neighbor model to recognize driving behavior groups via EEG data. The results showed that the average recognition accuracy was 80.6%, and the highest recognition accuracy was 84.2%, indicating that there is an obvious relation between EEG data and driver taking over behavior.
Study on the Influence of Damping Hole of DCT Complex Valve Body Lubricating Oil on System Dynamic Characteristics
Authors: Wang Li , Qin Yiwei
Published: June 2020

The dual clutch automatic transmission (DCT) technology can realize powerless interruption of the shifting process, and its hydraulic control system is a complex hydraulic valve body. The cooling lubricating oil circuit is very important for the lubrication of the clutch and the adjustment of the transmission oil temperature. This paper mainly analyzed the influence of the damping hole on the dynamic characteristics of the system in the lubricating oil circuit. Based on AMESIM software, the simulation model of the lubrication regulating main valve was established. The influence of the size of the damping hole on the output pressure, the lubrication flow of the output clutch and the lubrication flow of the output gear shaft were analyzed under the flow rate step condition. Combined with the vibration of the system, it was found that the reasonable diameter interval of the damping hole was 1.8∼2.3 mm.
Fire detector based on serial FBG temperature sensors optical cabling
Authors: Junwei Dong , Weiping Liu , Cui Tian , Xida Ye
Published: June 2020

Absrtact. Fiber Bragg Grating (FBG) is directly made into low-cost and high-efficiency cable with temperature detection function without secondary packaging. Using the linear relationship between the reflected wavelength of FBG and temperature in the cable, the temperature is calculated, and the alarm of fixed temperature, differential temperature and consistency is determined by software. This system is realized through the design of optical cable structure and algorithm.
Applied Research of Industrial Robots in Automotive Intelligent Manufacturing Production Line
Authors: Wang Weizheng
Published: June 2020

In recent years, most Chinese car manufacturers have seen the use in industrial robots as the key to intelligent transformation in the car manufacturing industry. Industrial robots consist of several major divisions of labor, with the technical advantages of a small footprint and high availability, which can improve the work efficiency of the automobile manufacturing industry. Therefore, it is fully utilized in various fields of intelligent manufacturing production lines for automobiles, such as material mixing, car body painting, car body welding, and vehicle assembly. This article introduces the application status and characteristics of industrial robots and describes industrial robot applications in the intelligent manufacturing line of automobiles.
Study on Surface Modification of Aluminum Alloy Electron Beam for Surgical Medical Devices
Authors: Li Xinkai , Zhang Chunxiao , Yao Xing , Han Yi , Wei Minsheng , Ji Yumin , Song Qi
Published: June 2020

Surgical and medical devices need excellent lightweight, surface abrasion resistance, corrosion resistance and other characteristics. In this paper, the surface modification of 6061 aluminum alloy commonly used in medicine is studied. The method of electron beam cladding 1Cr13 stainless steel powder is used to improve aluminum. The surface hardness and abrasion resistance were studied. The influence of electron beam process parameters on the cladding effect was studied. This method Provides new ideas for upgrading the industrialization of medical devices.
Research and Design of Field and Office Work Integration System for Historical Buildings Conservation: Case Study on Guangzhou
Authors: Yang Weijun , Li Qixing , Guo Liang , He Huagui
Published: June 2020

In recent years, GIS-based technologies has been applied in multiple fields of study, including historical building conservation. In the field of historic building conservation, GIS technology is mainly used for the spatial information display and spatial analysis of buildings. In terms of traditional methods of historical buildings information collection, GIS technology is mainly applied in the functions of data warehousing and statistical analysis, but barely in the early stage of data acquisition. This article introduces the technology of historical building information acquisition based on mobile GIS device, as well as the integrated data acquisition system, which changes the pattern that separates field and office work. The field collected data is directly imported into the data processing system on the basis of unified data standard, which shortens the intermediate link and integrates the field and office work. As a result of the improved pattern, the efficiency of historical building conservation will be significantly increased.
Application of airborne lidar technology in transmission line survey
Authors: Ren Yu , Chai Linjie , Guo Jiyuan , Ren Yaning , Liu Jian , Shen Xiangliang , Li Guangyi , Xing Lin
Published: June 2020

In the survey of transmission line, the traditional aerial survey method is difficult to get the surface elevation through the vegetation, corn field and other surface attachments, while the manual survey method has the disadvantages of low efficiency and high cost in mountainous and hilly areas. In this paper, the airborne lidar surveying and mapping technology is used, combined with a 110kV transmission line engineering survey example, generating high-precision surface DEM based on the point cloud classification results and extracting the single wood information based on the point cloud to accurately count the amount of tree felling. A panoramic simulation line corridor engineering geographic information system is established, which provides technical support for the route scheme optimization and plane section extraction, and is applied to the project. It is of practical significance to evaluate the effect.