bluuebunny/crossref_metadata_2025 huggingface dataset:
Navy text data set equalization method based on deep learning
Authors: Yudong Qi , Haiqiang Ding , Jinchao Zhao
Published: November 2019

Traditional unbalanced data sets, such as artificial set processing method, exists in the complicated and poor universality. It is difficult to apply naval uneven text data set processing. Aiming at this problem, this paper proposes a Navy uneven text data processing model based on biRNN. It learns text sequence features through biRNN model. Then it generates text similar to the original to balance text data. Text classification experiments are carried out on original data set and balanced data set respectively. The experimental results show that balancing the original data set based on biRNN method can effectively improve the performance of text classification.
ASIC implementation of Up-sampling Built in 6GS/s-16bit DAC
Authors: Zhu Zehua , Quan Haiyang , Wang Zongmin , Zhang Tieliang , Peng Xinmang
Published: November 2019

This paper presents an interpolation filtering model including four Digital interpolation filters. The interpolation filter circuit can effectively increase the data rate without increasing the input rate of the interface, and realize the up-sampling processing of the external input low-frequency digital signal to meet the high-speed DAC core conversion data requirement.
Single Event Effect Characterization of High Speed Serial JESD204B Data Receiver
Authors: Li Junze , Yue Suge , Chen Maoxin , Song Xiaojing
Published: November 2019

This work proposed and discussed a serial JESD204B data receiver and conducted a single event effect test on it. The test is used to analyzed the Single Event Upset (SEU), single Event Latch-up (SEL) and Single Event Functional Interrupt (SEFI). The purpose of the test is to determine if single event effect caused the chip to crash or increase the on-track error rate. The results show that the circuit has a strong ability to resist Single event effect.
Research and Practice of Image Processing Based on Python
Authors: Guan Yurong , Zhou Fei , Zhou Jing
Published: November 2019

Image is an important means to acquire, express and transmit information. Digital image processing means computer processing of images. In this paper, firstly mainly analyse the application characteristics of Python, focus on the typical functions of image processing PIL library, and then consult the relevant application cases of image processing. Finally, the image processing functions of PIL library are put into practice, which has certain reference and guiding significance for the image processing functions of Python and other platforms. Image processing and graphics processing have always been important fields in the development of computer technology.
A Construction Idea of an Application System Based on Simple Data Table
Authors: Zhou Fei , Guan Yurong , Wang Zhuanli
Published: November 2019

Small databases (transcripts, address books, etc.) have fewer associated services, and the performance requirements of interactivity, concurrent connection and response time are not high. They can display data statically by spreadsheet or HTML pages, and can also construct simple information systems to display data dynamically. This paper discusses the idea of constructing application system based on simple data table, reducing the construction cost of information system and improving the convenience of data migration and maintenance management.
Reform and Practice of Big Data Driven Higher Education Management and Decision
Authors: Chen Shengjun
Published: November 2019

The current period is the period of big data, and the management and decision-making of higher education cannot be separated from the driving of big data. How to better apply big data for the management and decision-making of higher education is a problem that needs to be solved urgently. As an important node in the education system, the field of higher education has naturally become an important area for the use of big data technology. This paper analyzes how big data is effective in higher education from multiple perspectives, and proposes a strategy for higher education development in the context of big data.
Evaluation of a Patent value based on AHP fuzzy comprehensive evaluation method
Authors: Song Yewei , Wen Shimin , Li Weimiao , Yang Luorao , He Yue
Published: November 2019

In order to evaluate the patent value scientifically, objectively and effectively, many factors affecting the patent value are considered in order to make up for the shortcomings of the existing patent evaluation methods. In this paper, the analytic hierarchy process (AHP) (AHP) method is used to establish a comprehensive patent value evaluation index system, and the fuzzy comprehensive evaluation method is used to obtain the final evaluation results, which enriches the existing ideas and methods of patent value evaluation.
Research on Regional Medical Heterogeneous Data Integration Technology
Authors: Zhang Chunfei , Zhang Yuchun , Duan Yunna
Published: November 2019

The integration of regional medical heterogeneous information is a problem that must be solved in the process of modern medical digitization. Based on the analysis of the characteristics of the existing medical information system, combined with the existing data integration and exchange technology, this paper proposes a heterogeneous data integration scheme for regional medical care. It also focuses on the data processing in the process of regional medical data integration and exchange, and describes in detail the process of medical data extraction, medical data conversion and medical data loading. The goal is to integrate existing heterogeneous medical information systems and eliminate information barriers to improve the effective utilization of medical information.
An Encoder-Decoder Neural Network for Indefinite Length Digit Sequences in Natural Scene Recognition
Authors: Zhang Tong , Zhang Erhan , Zhang Hanfeng , Shen Feihong , Guo Dongwei , Lin Kaichao
Published: November 2019

Extracting text information from raw images has always been a hot and difficult problem in computer vision research. Due to blurred image, uneven illumination and complex backgrounds, etc., the recognition of natural scene digit is difficult to achieve desired results. In this paper, an encoder-decoder neural network model is proposed to solve the problem of recognition of indefinite length digit sequences in natural scene. The encoder is convolutional neural network (CNN), and the decoder is long short-term memory (LSTM). The encoder accepts a fixed-format image and outputs a fixed-length feature vector; the decoder accepts the feature vector and outputs a predictive sequence of indefinite length. The verification based on Google Street View house number Dataset (SVHN) shows that our method has a good performance. After 10 hours of training, whose accuracy is 96.57%.
Application of Wavelet Transform in Image Super-Resolution
Authors: Zhao Yucong , Zhu Xiaonan , Wang Ping , Wang Yuanchen , Ma Jiquan
Published: November 2019

Most of learning-based super-resolution (SR) methods reconstructed high resolution (HR) image using a very deep convolutional neural network (CNN). CNN-based methods are used to process low resolution images, the predicted image is too smooth and some texture details are ignored. In order to improve the quality of the recovered high resolution image, wavelet transform is applied at the end of our model. Firstly, the prediction image is obtained through the CNN model; then, the predicted image and the ground truth image are processed into four frequency channels by wavelet transform; at last, four frequency channels and original image are considered when calculating loss. Compared with the original CNN model, the results of adding wavelet transform is obviously improved.
Research on Identity Mechanism of Large-scale Drug Virtual Screening in Heterogeneous Multicore Environment and SMP Environment
Authors: Li Xiaohu , Zhang Zhiyu , Wang Xinru , Liu Hao , Wei Zhiqiang
Published: November 2019

This paper studies the mechanism of ultra-large-scale drug virtual screening in the heterogeneous multicore environment and SMP (Symmetric Multi-Processor) environment. Given the differences caused by different CPUs, we solved the incompatibility of the open-source molecular docking software Autodock Vina on two supercomputer systems in different environments and realized the automatic and intelligent large-scale virtual screening process for small-molecule ligands. At the same time, we propose a processing method of large-scale virtual screening using Autodock Vina in two environments, which makes full use of the dominant computing power of supercomputers to improve the efficiency of large-scale molecular docking and reduce the load of different supercomputer systems facing large-scale molecular docking tasks. Finally, we conduct a virtual screening experiment on the X86 platform supercomputer and the Sunway TaihuLight Supercomputer based on the heterogeneous multicore architecture CPU—SW26010. The experimental results show that our large-scale drug virtual screening method for different CPU environments is effective.
Management Evaluation of Distribution Network Based on Fuzzy Evaluation Matrix
Authors: Ran Chen , Kunhua Ji , Yun Wang , Jian Lu , Haining Xie , Liming Zhuang
Published: November 2019

Focused on automation management level of distribution network, an evaluation method based on fuzzy matrix is proposed in this paper. First, data extraction efficiency, data quality and automation ratio are selected as evaluation indicators. Then, by establishing an analytical model, each indicator is compared in pairs to construct a judgment matrix. And the consistency test of the matrix is done before the follow step. Next, through the experts’ scores of the influencing factors, fuzzy mathematics is used to make a comprehensive evaluation of the automation management evaluation indicators. Finally, according to the evaluation results, the automation management level of the distribution network is analysed. According to the above method, a certain urban area is taken as an example to obtain the quantitative index of the automation management level of the distribution network. It is of great significance to strengthen the distribution network construction with the cooperation management mode, so as to realize the comprehensive improvement of the distribution network management level.
Reliability Evaluation of Mechatronics Products Based on Intuitionistic Fuzzy Set Theory
Authors: He Zhiyuan , Lv Weimin , He Hailong
Published: November 2019

In view of the lack of test data for some unmonitored electromechanical products, this paper mainly proposes a multi-source information reliability assessment method based on Intuitionistic Fuzzy sets and evidence theory. The method first uses the group decision-making idea to obtain multiple evaluation information and distributes the evaluation information as the reliability of the evidence. Using the relationship between evidence theory and Intuitionistic Fuzzy sets, the reliability distribution is transformed into intuitionistic fuzzy numbers. Then a method for determining the degree of evidence support is proposed, and the reliability of the evidence information is evaluated by this method. Finally, the combination rules are improved and information fusion is performed. The case analysis proves the feasibility of the method.
Shape Feature Extraction Methods of Rodents in the Field Based on Machine Vision
Authors: Zhu Deli , Chen Bingqi , Han Liliang , Wang Yong , Wei Chaojie , Feng Jie
Published: November 2019

In order to obtain the shape features of rodents from the field, a feature extraction scheme based on machine vision was proposed. We design an experimental device with a camera. The camera placed on the top of the device to get the rodent image. After thresholding rodent image based on the global value, we get the binary image, and then the morphological erosion and dilation operation are used to denoise, and the contour are detected by the 8 adjacent pixels of a point. Chain code analysis method is used to track the contour. Multi-contour tracking extraction method is used to remove the non-rodent region. Based on the shape of the rodent tail that is slenderer than the body, we split the rodent’s tail from the body on the precise contour image. The length of the tail, the length of the body, the height of the body, the proportions of the tail and the body are extract based on contour analysis. Experiments show that this method can extract shape features of rodents accurately. It can provide basic data for analyzing the life habits and population evolution of field rodents.
Research and Analysis on Key Techniques of Digital Speckle Correlation Method
Authors: Dong Yi , Hong Liang , Wang GuiRong , Dong Yi
Published: November 2019

The registration of speckle images plays a key role in many fields, such as: material mechanics; accident monitoring; geodetic survey; missile guidance. Speckle image is composed of a large number of random spots, that it is difficult to obtain obvious feature values through feature extraction. Digital speckle correlation method is to directly extract the surface displacement and deformation information of objects from digital images, so all kinds of digital images can be used as processing objects. However, when the target image quality is poor or has a large deformation, its registration accuracy is difficult to reach the sub-pixel level. In this paper, we will study and analyze the key technologies of existing digital speckle correlation methods.
Research on High Availability Architecture of Cloud Platform
Authors: Xinming Lai , Haitao Wang , Jing Zhao , Fan Zhang , Chao Zhao , Gang Wu
Published: November 2019

Cloud computing platforms have extremely requirements for high availability, and many solutions have proposed to ensure high availability of system. In view of the shortcomings of the existing solutions, we improve the high availability of the cloud computing platform based on the 3 tiers cluster environment, including the business layer cluster, the management cluster, and the main control layer. The management cluster ensures high availability of the service layer cluster. The main control layer ensures high availability of the management cluster. The main control layer uses the dock mechanism to ensure certain high availability. Through practical application, the solution achieves high availability of the cloud computing platform, achieving availability 99.99%.
The Application of CAD/CAE Technology in the Teaching of vehicle Engineering Specialty
Authors: Chunxia Zhu , Tiying Wang , Mingwei Xiao
Published: November 2019

Good teaching method is an important way to improve teaching quality and cultivate students’ creative thinking. This paper mainly describes the application of CAD/CAE technology in vehicle engineering teaching, enriched teaching methods, can improve students’ ability of learning and engineering practice, improve teaching quality, and has good practical significance.
Fusion of Handcrafted and Deep Features for Medical Image Classification
Authors: Liu Dong , Liu Yaohui , Li Shanglin , Li Weiqing , Wang Luda
Published: November 2019

Medical image classification has recently attracted increased attention. Effective feature extraction and learning are key means to improve classification performance. However, in the current study, handcrafted feature are mostly designed with intuitive mode, while the deep feature depends on a large amount of training samples and has weak interpretability. To capture more discriminative features for medical image, a novel feature fusion approach, termed multi-layer visual feature fusion (MLVSF), has been proposed on the basis of low-level, mid-level and deep features. More specifically, by fusing the handcrafted and deep features generated by local binary pattern variant, bag-of-visual-words, convolutional neural network, respectively, MLVSF can effectively enhance the discriminating power of features for medical image recognition. Experimental results on two medical image datasets show that MLVSF can improve convolutional neural networks, and achieve a better classification accuracy in comparison with some state-of-the-art methods.
An Improved Active Contour Model in Medical Image Segmentation
Authors: Zhang Xuefei
Published: November 2019

Aiming at the problem that medical image segmentation has low precision because of restriction of image principle, this paper proposes an improved active contour model based on vector field convolution, and combining both the balloon force and gradient directional information. This method improves the energy function of model, has more chances to approximate the complex boundary. The experimental results show that the new model not only inherits the advantages of the previous models, but also show fast speed, limits the influence of false edge and noise disturbance.
Anomaly Detection for Water Supply Data using Machine Learning Technique
Authors: Fang Shu , Sun Weize , Huang Lei
Published: November 2019

The advent of the era of big data brings new challenges and opportunities to water data processing. Abnormal detection or authenticity verification of water supply data becomes an urgent problem in natural resource data processing. This article addresses the issue of anomaly detection for a set of measured water supply data that provided by the Ministry of Water Resources of China. The machine learning technique, namely, One-Class support vector machine, is used for anomaly detection, and a detailed analysis of the features of anomalies is also provided. Experiments on three situations, namely, one dimensional situation, three dimensional situation and seven dimensional situation are carried out to analyse the features of anomalies. The experiment results revealed that the cases with entries of large values more than 10 times of median, zero entries together with some large values and ascending or descending sequences tend to have high abnormality scores.
Overview of Research on Health Assessment and Fault Prediction of Complex Equipment Driven by Big Data
Authors: Jin Can-can , Zhang Hong , Liu Jun , Lu Yang
Published: November 2019

Health evaluation is an important content of health management for complex equipment, and fault prediction is a key link to realize condition-based maintenance. Based on the literature review, this paper gives a feasible modeling method: The health status of complex equipment is expressed as time series by constructing forward and backward LSTM model, and the health evaluation model is constructed and trained based on the deep learning platform TensorFlow. The improved particle filter constraint algorithm is used to optimize LSTM neural network which is to generate PF-LSTM prediction model. The research on health evaluation and fault prediction of complex equipment based on machine learning discussed in this paper puts forward new requirements and development direction for machine learning of complex equipment, and is of great significance for practical implementation of lean intelligent manufacturing, improvement of stability and economic benefits of complex equipment, and reduction of operation and maintenance costs.
Analysis of Computer Network Security in the Age of Large Data
Authors: Gao Lu , Yang YinGen
Published: November 2019

The arrival of the information age is driving the continuous development of our country’s economy and the continuous transformation of our society. At present, the number of Internet users in our country is increasing rapidly. Smartphones and portable computers have become necessary for people to travel. In the era of big data, the problem of computer network security needs our attention. Technology is a double-edged sword. While bringing convenience to all of us, it also brings a lot of problems, such as telecom fraud, information leakage and other problems about network information security caused public discussion. Therefore, this paper analyzes the problems and solutions of computer network security in the era of large data.
Research on Fault Diagnosis Technology of Thermal Test Measurement and Control System Based on Data Driven
Authors: ZeYuan Liu , Qiang Zhang , XiYuan Li , XinMing Su , Lin Zhu
Published: November 2019

Temperature data, as one of the most important parameters in spacecraft vacuum thermal test, is also an important characteristic parameter for fault detection of spacecraft thermal test system. From the perspective of numerical heat transfer, the physical and mathematical models of thermal test specimens are established by using finite difference method. Based on the data driving of specimen measurement temperature and heating power, the mathematical model coefficients are fitted by the combination of least squares and sliding window filtering, and then realize the on-line prediction of temperature data and fault detection of thermal test measurement and control system. Based on the thermal test data of the solar wing of a certain type of spacecraft, the above-mentioned method was verified by physical experiments. The experimental result shows that the method can accurately and effectively realize the temperature prediction not less than 2 periods, and the prediction accuracy is less than ±2°C. It can provide an effective fault detection means for the thermal test measurement and control system.
RETRACTED: Design and Implementation of Bank Wind Control Anti-fraud Project Based on Big Data Technology
Authors: Jianhao Yu
Published: November 2019

With the advent of the big data era, the construction process of financial big data product system is also gradually accelerating. This paper discusses a case of financial big data products created by banks-“credit risk control anti-fraud project”. The author first clarifies the requirements and background of the project construction, then shares the framework and application architecture design scheme, highlights the specific design and implementation methods of the system, finally summarizes the bottlenecks encountered in the project construction process and solutions, and points out the characteristics of the system in practical application.
2-D Scanning Galvanometer Error Analysis and Its Correction
Authors: Meng Xianyu , Cao Guohua , Li Xue , Lv Qiongying
Published: November 2019

The 2-D Scanning Galvanometer is an optical scanner with high precision, high reliability and high repeatability. It is also widely used. In order to eliminate the nonlinear scanning error of the 2-D Scanning Galvanometer system, in order to improve the scanning precision of the system, the theoretical distortion is derived, and the geometric distortion and various errors in the 2-D Scanning Galvanometer system are analyzed in detail. The targeted coordinate transformation method is used to correct the distortion error. The experiment proves that the method can significantly improve the scanning precision of the rapid prototyping machine.
Digital platform architecture design based on JavaEE
Authors: Li Hao , Yang Heda
Published: November 2019

With the comprehensive popularization of electronic technology and the internet, more and more people prefer to use smart phones, tablets and other intelligent terminal devices to read digital information on apps or Web pages, which makes the traditional publishing industry to transform to digital service. Based on the platform of JavaEE, this project provides architecture design for the transformation of rail transit publishing house to digital publishing service, integrates the traditional publishing industry resource base, and brings great help to the utilization, optimization and management of knowledge resource base.
Research on Resource Allocation Optimization of Information Management System Based on Big data Association Mining
Authors: Chen Yuyong
Published: November 2019

Aiming at the problem that the resource allocation accuracy of information management system in cloud computing environment is not high, the resource allocation method of information management system in cloud computing environment is improved and designed. A resource allocation algorithm of information management system is proposed based on big data association mining. The information of resource distribution in information management system is fused and reconstructed according to the key words and semantic association features, and then the feature extraction of association rules of information management system resources in cloud computing environment is carried out. The extracted association rules are used for big data training set to allocate the resources of information management system, and big data association mining and adaptive scheduling method are used for adaptive optimization control of resource allocation. The simulation results show that this method can improve the resource allocation accuracy of information management system, the anti-interference ability of resource allocation, and the efficiency of resource utilization and information management.
Simulation of gear drive design based on unity3D
Authors: Wang Yanwu , Shen Bin , Li Longteng
Published: November 2019

Electromechanical integration technology has developed rapidly in recent years. It is based on the information technology represented by Microelectronics technology and microcomputers. Its development is a modern industry that rapidly penetrates the traditional machinery industry and deeply integrates with electromechanical integration technology. It has mechanical technology, Microelectronics technology and information, automatic control technology, sensing and testing technology, software programming technology, interface technology and power electronics technology. With the rapid development and widespread use of computers, electromechanical integration technology has achieved advanced development and has become a system technology for computer integration, sensor detection technology, automatic control technology, and mechanical technology. And in the direction of photo-electromechanical integration, the scope of use has become larger and larger.

And we’re looking at one of the most important ones -- the gear drive, which is now the most versatile of all mechanical devices in the world. Its transmission is more accurate, more efficient, compact, reliable, and long-lasting. This time we use Solid Works and 3DS Max software to map and model gear drives and analyze their main functions.

In addition, Unity3D is also a virtual simulation software that is widely used today, and domestic talents are scarce in this area. In this context, we can try to study the design simulation of gear drive based on unity3D.
Multi-dimensional Resource Optimal Allocation Method for Service Function Chain Deployment
Authors: Hu Jingping , Pu Yojun , Li Ziyong , Wang Lisheng
Published: November 2019

Aiming at the problem of multi-dimensional resource service function chain deployment in a resource-limited network, a resource allocation method based on optimal weighted graph matching is proposed. The node and link resources are embodied as weights of the weighted graph, and the eigenvector decomposition of the adjacency matrix is used to get graph matching method. The simulation results show that the algorithm optimizes the bandwidth required for the deployment of the service function chain, optimizes the balance of node load and link bandwidth, supports more service requests, and has low algorithm complexity.
Fully Integrated Navigation based on INSGPS Magnetometer
Authors: Yaya Wang , Yajuan Jia , Junhui Liu
Published: November 2019

Inertial Navigation System (INS) and Global Positioning System (GPS) composite guidance technology are the most advanced all-weather, autonomous guidance technology. The principle is to use a Almanac filter to combine the two and after filtering, give an optimal estimate of a set of state variables (such as position, velocity, attitude angle, gyro drift, accelerometer bias, clock difference, etc.). And periodically feedback back to INS to correct it. The combined system can output all navigation information at a higher rate, superior short-term and long-term accuracy, greatly improve system availability and smoother positioning and output trajectory. The inertial navigation system (Inertial Navigation Oyster, INS) and the satellite-based positioning system represented by GPS have strong complementary advantages. GPS provides high accuracy and stability and continuously monitors the inertia sensor’s error (gyro drift).
Method to Obtain Target Speed with Underwater Acoustic Positioning System
Authors: Lv Chengcai , Shen Binjian , Tian Chuan , Xu Dazhen , Song Yuanjie , Luo Peng
Published: November 2019

There has been considerable recent interest in the positioning of autonomous underwater vehicles (AUVs). Underwater acoustic positioning system (UAPS) are usually used to determine position and speed of the moving target in water environment. Generally, moving target speed is estimated by derivative of the target position with traditional method. However, this approach relies heavily on accuracy of positioning. Thus, this paper presents a novel method for estimation of target speed with the UAPS only, especially with long baseline (LBL) acoustic positioning system. The method is made by estimating the Doppler frequency shift of the received signals and solving the set of linear equations. It could depend less on positioning accuracy than the traditional method. What’s more, it works well even though the moving target is subjected to acceleration or jerk. With simulations by MATLAB, it is shown that the method achieves very good performance.
Research on GSTAR-SVM Traffic Prediction Model Based on Wavelet Transform
Authors: Hu Jinghao , Wang Shandong , Mao Jian
Published: November 2019

With the continuous advancement of urbanization in China, the number of urban vehicles has increased rapidly, and traffic congestion has become an urgent problem for modern cities. Therefore, accurate real-time traffic flow prediction is of great significance for solving this problem. However, traffic flow, as a special type of prediction object, has the characteristics of complexity, uncertainty and nonlinearity, which bring great difficulties to the prediction, and the external spatial correlation also has a great influence on the prediction results. In this paper, based on the above problems, the GSTAR-SVM traffic prediction model based on wavelet transform is constructed to predict the short-term traffic flow, and the model is verified based on the data. The experimental results show that the proposed model has higher prediction accuracy.
Study on SEC Reserve Evaluation Method for Low Permeability Reservoirs
Authors: Sen Liu
Published: November 2019

SEC reserves assessment is an important indicator to measure the development potential of oil companies. Based on the evaluation of SEC reserves, this paper summarizes the dynamic evaluation methods of SEC reserves, including analogy method, volume method, decline method, material balance method and reservoir simulation. Among them, the decline method is the most commonly used method, which has the characteristics of easy prediction of production and economic life cycle. Therefore, this paper discusses how to choose the decline method, the initial output and the determination method of the decline rate.
Research on the Spread of Embroidery Art and Non-material Culture and Art in the Internet Multimedia Age
Authors: Wang Qinghai , Zhe Zhang , Xing Yadan
Published: November 2019

With the rapid development of industrialization, traditional handicraft has disappeared silently. Therefore, in the era of rapid development of information technology, it is of great significance to widely disseminate embroidery art of traditional culture through digital technology. This paper expounds the concept of digitalization, and from the thinking dimension of digitalization communication, puts forward the way of embroidery art communication in the Internet multimedia era.
An Analysis of the Path of the Reform of Mixed Ownership in State-owned Enterprises
Authors: Wang Zhen Min
Published: November 2019

The report of the 19th National Congress pointed out that it is necessary to develop a mixed ownership economy and cultivate world-class enterprises. This paper analyzes the history, background and significance of the reform of state-owned enterprise mixed system with the aim of exploring the path of mixed ownership reform of state-owned enterprises. Based on the analysis of the existing problems, some suggestions are proposed.
Semi-supervised Classification Method for Remote Sensing scene Based on Deep Learning
Authors: Han Yaochang , Wang Jie , Lu Li
Published: November 2019

Aiming at the classification problem of remote sensing scenes, this paper proposes a semi-supervised deep learning method combining the generative generation network with the convolutional neural network. The method improves the loss function of the deep convolutional generation network, and designs the even convolutional network EM-10 and its transposed convolution network as discriminators and generators respectively, which improves its ability to extract remote sensing features. The trained discriminator is used for the classification of remote sensing scenes with an accuracy of over 90%.
Direct-ORB-SLAM: Direct Monocular ORB-SLAM
Authors: Cui Linyan , Ma Chaowei , Wen Fei
Published: November 2019

Simultaneous Localization and Mapping (SLAM) plays an important role in the computer vision and robotics field. The well-known ORB-SLAM extracts ORB features and uses feature matching to estimate the camera pose and construct a sparse map. However, the features extracted in the common frame (relative to the keyframe) are not used again except in this camera pose estimation stage, which will cause the waste of computation resources. In this work, we propose a new SLAM framework, i.e. Direct-ORB-SLAM. It uses image intensity for data association in common frames to avoid the redundant computations and performs the relocalization and loop closure detection in ORB-SLAM2 for keyframes. The photometric calibration is also employed to benefit for accuracy and robustness. The popular public dataset EuRoC is adopted to approve the efficiency of proposed method. Results indicate that the proposed Direct-ORB-SLAM algorithm runs two times faster than the well-known ORB-SLAM at the expense of a slight reduction in accuracy.
A Zero Velocity Detection Method for Soldier Navigation Based on Deep Learning
Authors: Zhu Tengda , Pan Xianfei , Zhang Shufang
Published: November 2019

In this paper, deep learning is introduced into the zero-speed detection of individual navigation. Through the combination of one-dimensional CNN and LSTM, the accuracy of zero-speed detection is further improved, and other cumbersome adjustment procedures based on thresholds and other methods are avoided. At the same time, a method of establishing a zero-speed label using ultrasonic ranging method is also demonstrated. Since the error of running and other sports mainly comes from the device error and not the algorithm itself, in this paper, the 6-axis IMU data is first imported into the one-dimensional CNN and is divided into a part that can perform zero-speed detection and a part that is not suitable for zero-speed detection. It can be used for zero speed detection and reuse LSTM based zero speed detection. Compared with other algorithms, this method uses the deep learning method to train the appropriate model in advance and can be used without adjusting the reference. It is especially suitable for the urgency of the soldier’s mission. The experimentally proven SHOE algorithm has a navigation accuracy of less than 3.5m/186.06m without adjustment, and the accuracy of the proposed method is stable above 1.0m/186.06m, which improves the overall navigation accuracy.
Numerical research of influence of residual stress on interface crack propagation
Authors: Chen Li , Ding Ke-qin
Published: November 2019

The crack propagation was simulated by a generalized potential-based mixed-mode (PPR) cohesive interface model. Based on the principle of equivalence of thermal and mechanics, the effects of residual stress on interface crack propagation was researched by finite element model. The results demonstrate that residual compressive stress is more likely to cause material interface crack propagation. The material interface is more likely to fail when there is residual compressive stress in the material. The residual compressive stress is more likely to cause the interface crack propagation when the crack propagation length caused by certain residual compressive stress value is seen an important influence parameter.
Study on beam bunching and rotation characteristics of low power laser in permanent magnetic field
Authors: Wang R , Lu Y H , Zhang C , Zhang J
Published: November 2019

In this paper, a test platform based on the Faraday Effect was designed to investigate the beam bunching and rotation characteristics of low power laser in permanent magnetic field. By changing the structural parameters of the permanent magnetic confined cavity, the effects of permanent magnetic field on the rotation characteristics of linearly polarized light and the beam bunching characteristics of low power laser were studied. In the tests of the rotation characteristics of the linearly polarized light, it was found that the rotation angle of linearly polarized light tended to decrease with the increase of the diameter of the magnetic cavity and the decrease of the number of magnets. The maximum rotation angle of linearly polarized light was 142.6°, and the minimum rotation angle was 13.6°. In the tests of beam bunching characteristics of low power laser, it was found that the laser spot area had a slight reduction and the laser power was slightly enhanced when the magnetic flux density increased from 0.4563T to 0.8243T, which proved that the strong magnetic field had a bunching effect on the low power laser.
A Type of Electromagnetic Biased Axial Magnetic Bearing with Low Target OD
Authors: Kong Ruijie , Mei Lei
Published: November 2019

A type of electromagnetic biased axial magnetic bearing is proposed. Compared with traditional axial magnetic bearings, it has low target OD, which is helpful to improve the critical speed of the rotor in theory. By using the equivalent magnetic circuit method, a magnetic circuit analysis is carried out. The expressions of magnetic flux density of each part are obtained, and the structural parameters are obtained and the finite element model (FEM) is established. The magnetic flux leakage coefficient and magnetic reculance are calculated by using simulation data, and the rationality of the parameter design is verified. The results show that the parameter design and electromagnetic field simulation of this type of the electromagnetic bias axial magnetic bearing are in accordance with the rationality of the design. It can be used as a reference for the design of magnetic bearing.
Research on the health management of an automatic magazine control system to the naval gun
Authors: Jiang H , Yao ZH , Xun P P
Published: November 2019

According to the problems of low maintenance efficiency and high cost for traditional regular maintenance and after-the-fact maintenance methods, PHM technology is introduced to improve the success rate of the system operation, extend the service life, and reduce maintenance difficulty and cost. Aiming at the overall situation of the automatic magazine control system of a large-caliber gun weapon, a new health management system based on a data-driven method is proposed. Establishing a PHM model applied to automatic magazine control system by using the structure of open system architecture for condition-based Maintenance (OSA-CBM); the prediction and evaluation function of PHM system is studied with an example of transfer servo drive system; the prediction model based on BP neural network is established to predict the health parameters of the automatic magazine control system. Then the health state of system is evaluated according to the prediction result and the function is verified by simulation. The simulation results show this BP neural network model is applicable for the parameter prediction of the prediction and evaluation module of the automatic magazine PHM system. The prediction accuracy is over 90%, and the model has a good applicability.
The Maximum Potential Analysis of Wind Plant Development Based on Power Storage’s System Self-adaptive Tracking Control
Authors: Xue Feng , Wangcheng Long , Wenhua Yang , Zheng Chen , Xiaoli Gao
Published: November 2019

Wind plant had a great influence on the power grid operation because of the volatility to the power supply layout. Moreover, the power system cannot consume all generated power when it exceeded the demands. However, the power storage device would change the wind plant output curves, and then the more new energy power could be utilized. How to analyse the maximum potential was an important matter to energy planning and power system development. The analysed results could decide the trends of energy supply structure in the future. In this paper, the reasonable generation scale arrangement was discussed considering the energy resources, land planning, ecological requirements, and the power storage system tracking control principle was proposed to optimize power output.
Pose Error Compensation for the Actuator of an Automatic Docking Connector
Authors: Zhou Cheng , Yu Cungui , Liu Huaying , Zhao Chun
Published: November 2019

To improve the automatic docking connector (ADC) of a launch vehicle docking accuracy and reduce the pose error of the actuator, an error compensation prediction model based on BP neural network is established. An error compensation method based on pseudo-object pose is developed to ensure the real-time performance of the control system. A prototype ADC is constructed, and a control system was set up to verify the effectiveness of the proposed error compensation method. A comparison of the measured positions before and after the application of error compensation and the theoretic position of the reference point revealed that the output error could be significantly reduced after application of the proposed error compensation method.
Research Status and Progress of Oxygen Sensor
Authors: Shuaishuai Lv , Jiaqiao Zhang , Hongjun Ni , Haiqin Huang , Xingxing Wang , Jianbing Tao , Wenxiu Kang
Published: November 2019

The research progress of oxygen sensors was reviewed, the working principles of different types of oxygen sensors were summarized, and the control methods of temperature and pump current were briefly introduced. Then some problems encountered in the development of oxygen sensors were pointed out. Finally, the oxygen sensor technology was summarized and prospected.
An approach of FEM analysis of the influence of pretension on the transverse vibration of belt drive
Authors: Nie Wenting , Zheng Dayu
Published: November 2019

Belt drive has been widely used in various types of mechanical transmission. Because the belt is sensitive to the pretension, the tension force directly affects the vibration characteristics of the belt, in order to reduce the impact of the pretension on the belt drive, the finite element software is used to simulate the belt, the effect of the change in pretension on the frequency and amplitude of the transverse vibration in the belt drive is obtained. Reasonable selection of the pretension can reduce the vibration amplitude of the belt, reduce the transmission noise and improve the service life of the belt. This method can provide reference for vibration characteristics analysis and system design optimization of the belt drive structure.
The e-commercial quality components impact on customers’ purchase intention
Authors: Ke Yang
Published: November 2019

The Internet has been widely used in these years and in recent years, it is still showing continuous growth. The Internet has become an important means of online transactions and services. This study examines the impact of e-commerce functions on people’s willingness to purchase by telling American e-commerce giant Amazon and China’s largest online merchants.
The optimization of parameters for controlling iron ore sintering process based on maximum satisfaction
Authors: Yunlian Liu , Xinjun Li , Dan Gao
Published: November 2019

This research put forwards a stepwise parameter optimization approach based on maximum satisfaction aiming at the characteristics of multi-process control indices and cascading in iron ore sintering process. Given the sintering process involves multiple quality indices and the demand of reducing cost of first proportioning and the consumption of coking coal has to be met, we built a satisfaction evaluation function, based on which, an improved whale optimization algorithm(IWOA) is used to optimize control parameters. Simulation results indicate that the optimization approach of control parameters proposed in this research can effectively promote the quality indices of increasing sintering iron ore and decrease production cost.
Control Strategy of Energy Storage Inverter Based on Virtual Synchronous Generator Technology
Authors: Chen Yin , Men Fuyuan , Wu Yichun , Zhao Daiping , Li Caifang , Liang Hao
Published: November 2019

In the microgrid system, the power supply quality of sensitive loads is directly affected by the grid-connected and off-grid operation states of the energy storage power supply as well as the dynamic switching process between the two states. To solve this problem, this paper adopts a control method of energy storage inverter based on virtual synchronous generator, which makes the energy storage inverter equivalent to a controlled voltage source with functions of inertia simulation, frequency modulation and voltage regulation. Besides, a seamless switching control strategy of energy storage inverter is proposed, which can realize the automatic smooth switching of the grid-connected state, off-grid state and state between the two.
Study on Forming Technology of TBM Disc Cutter Ring
Authors: Hu Yong , Li Maosen , Fu Zhongguo , Hu Yikai , Zhang Aiwu , Cao Changye
Published: November 2019

The tunnels and underground projects bring an unprecedented development of hard rock tunneling technology. The forming process and material properties of the 20 inch disc cutter ring has been studied by the finite element simulation and test methods. The effects of blank size, blank heating temperature, mold preheating temperature and friction coefficient on the forming load, minimum surface temperature and blank deformation uniformity of 20 inch cutter ring were analyzed. The results show the optimum combination of the forming process of the 20 inch disc cutter ring is when the blank height is 90 mm, the blank heating temperature is 1200 °C, the preheating temperature is 280 °C, and the friction coefficient is 0.2. Compression test and hardness test were carried out on the edge material of the cutter ring. The test results show that when the temperature exceeds 600 °C, the hardness and compressive strength of the cutter ring material will drop sharply. Therefore, the TBM should be properly cooled during construction. The research results in this paper can provide a basis for the optimization of TBM disc cutter ring processing technology and engineering applications.
Research on millimeter wave spectrum planning for 5G
Authors: Kang Guoqin , Jiang Shuiqiao , Zhao Zhiyuan
Published: November 2019

In order to allocate reasonable frequency resources in millimeter wave band for 5th-Generation (5G), this paper summarizes the position and consideration of USA and China. It analyses the feasibility of sharing and compatibility in 24.25-27.5GHz, 66-71GHz, 81-86GHz with Monte-Carlo simulation. There is a high possibility to allocate 24.75-27.5GHz, 66-71 GHz and 81-86 GHz to 5G in ITU and China. But the commercial deployment in millimeter wave in China will be delayed 1-2 years because of industry bottleneck.