bluuebunny/crossref_metadata_2025_split huggingface dataset:
Face pose estimation of SDM based on multi-template matching
Authors: Chen Hu , Gao Chaoqian , Li Tianping 
Published: June 2020

Abstract
This paper presents the face pose research of SDM algorithm and POSIT algorithm with multiple template matching. Firstly we detect the input face image, locate the feature points in the detected facial area, then compare the traditional SDM algorithm with the improved multi-template SDM algorithm, and then select the multi-template SDM algorithm. Feature point location is finally applied to the POSIT algorithm. Experimental results prove the effectiveness of the method and make it competitive.
Ultrasonic signal denoising technology based on SMP algorithm
Authors: Ailing Qi , Bingwen Bai , Guangming Zhang 
Published: June 2020

Abstract
Flip chip technology has been rapidly developed and widely used in the field of microelectronic packaging, and defect detection has received increasing attention. The ultrasonic detection method is used to detect the defect information of the packaged chip. However, the ultrasonic signal obtained during the detection process is disturbed by noise, which seriously affects the true information of the defect signal. For this problem, the matching matching pursuit (SMP) algorithm is used in combination with Gabor. The atomic library realizes adaptive matching of noisy ultrasonic signals. The linear combination of selected atoms is used to represent the denoised signals to achieve the denoising effect of noisy ultrasonic signals. The denoising effect of the SMP algorithm in the experiment is compared with the MP algorithm, and the results show that the denoising effect of the SMP algorithm is better.
An Improved Naive Bayesian Classification Model Based on Attribute Weighting
Authors: Yue Xi , Tang Mengxuan 
Published: June 2020

Abstract
Naive Bayesian model has good classification accuracy and efficiency, which makes it show good performance in many fields, especially in data mining and artificial intelligence. However, the traditional Naive Bayesian classification model ignores the attributes’ independence, resulting in the reduction of classification accuracy. For this reason, an improved model based on attribute fusion and weighting(AWNBC) is proposed, in which data fusion is realized by Spearman coefficient and weighting is realized by average confidence and ReliefF coefficient. The experiment classifies the selected data in UCI database. The result of experiments show that the improved classification model has good classification accuracy and efficiency.
Application of particle swarm optimization BP neural network algorithm in image compression
Authors: Wang Hai-jun , Jin Tao 
Published: June 2020

Abstract
In order to overcome the problems of weak global search ability, slow convergence speed and easy to fall into local minima in the process of image compression of BP neural network model, an image compression model based on particle swarm optimization algorithm and improved BP algorithm is proposed. In this model, a group of optimal approximate solutions of weights and thresholds of BP network are obtained through global search of particle swarm optimization according to objective function, and then the approximate solution is taken as the initial value of BP model, and the improved BP algorithm is used to conduct quadratic optimization training on these weights and thresholds to obtain the final image compression model. The experimental results show that with the same error accuracy, the quality of model compressed image reconstruction based on particle swarm BP neural network algorithm is significantly higher than that of BP and improved BP algorithm models.
Research on Internet of Things Technology and Its Application in Building Smart Communities
Authors: Huang Lu , Yuan Xiaoyu , Zhang Junyuan , Zhang Nannan , Li Jin , Wang Le 
Published: June 2020

Abstract
The Internet of Things technology is widely used in many industries and fields, including smart production and management, smart transportation and environmental protection, industrial monitoring and social security. Community construction is turning to smart communities. The construction of smart communities mainly uses network communication system facilities to realize the integrated networking of community residents and public facilities, to carry out information management of community residents, living and service facilities, and to improve the living environment by using modern technical measures. Aiming at the decentralization of IoT technology and smart community fusion products, an integrated information system platform needs to be built. In this article, the overall design framework of smart communities based on Internet of Things technologies is studied, and the smart community information management platform is divided into several main parts; Each part as Subsystem, discusses the basic functions of the subsystem, and finally realizes the intelligent construction of the smart community as a whole. We start work from the reality of the systematic construction of smart communities, combining with the latest Internet of Things technology, research and build a smart community information management platform with a unified architecture to achieve unified management and scheduling of smart community sub-products.
Research on Computer Security Guarantee Measures in Network Environment
Authors: Shi Zi-xin 
Published: June 2020

Abstract
In recent years, computer network technology has been rapidly developed and popularized, and it also plays an important role in people’s life and work. However, because the computer network itself has the characteristics of openness, it is easy to cause some security problems in the process of use. Computer networks not only affect people’s experience of using computer networks, but also cause certain economic losses in severe cases. Therefore, how to do a good job of computer security protection in the network environment has become an important issue that relevant technical personnel need to pay attention to.
Clustering algorithm based on analytic hierarchy process in LTE-V2V
Authors: Chang Xin , Yu Jianguo 
Published: June 2020

Abstract
As a hot area of urban transportation, the development of internet of vehicles and related technologies has received widespread attention. This paper proposes an analytic hierarchy process clustering algorithm (AHP-CA) based on the analytic hierarchy process in the LTE vehicle self-organizing network in the scenario of urban two-direction road intersections. The AHP-CA algorithm introduces the average distance between vehicles, normalizes the average relative speed, and uses the average relative motion direction as the vehicle eigenvalue for the clustering index. The analytic hierarchy process (Analytic Hierarchy Process, AHP) is used to determine the weights of different vehicle feature values, and the appropriate nodes are selected as cluster heads by combining the weights. The simulation results verify the stability of the cluster head under different vehicle speeds and communication distances.
A Variable Threshold Image Secret Sharing Method
Authors: Liu Shanzheng , Zhang Hang , Yu Ying , Cai Hongliang , Tang Dan 
Published: June 2020

Abstract
Image secret sharing has been widely discussed in recent years because of its high security. The threshold variable image secret sharing method is a hot research topic recently. The Lagrange interpolation method is easy to establish. Therefore, most of the existing secret sharing schemes are based on Lagrange interpolation polynomials. However, when the secret is updated, the existing secret sharing scheme needs to re-establish the polynomial, and the original computing resources cannot be utilized. When the cheater is found, it is not convenient to add or delete participants flexibly, resulting in a large waste of computer resources. Therefore, an image secret sharing method with variable threshold based on Newton interpolation method is proposed, which can reduce the computational complexity of the system and the amount of repeated computation. The experimental results show that the method is superior when the threshold is changed.
Research on the management information of scientific research institutes
Authors: Zhang Yun-jie 
Published: June 2020

Abstract
Through the analysis of the management information system, this paper analyzes the pain points in the process of enterprise information construction, and puts forward solutions from the aspects of master data management, process management, the application of ESB and other basic common platform construction. Finally, this paper analyzes the special situation of informatization construction in military research institutes, and probes into the difficulties and development direction of informatization construction.
Research on Surface Crack Detection Technology Based on Digital Image Processing
Authors: Xiao Yuling , Zhang Haoran 
Published: June 2020

Abstract
Digital image technology is used to monitor the fatigue and fracture of components under the operating conditions of mechanical parts, which is beneficial to monitor the causes of shallow cracks and whether the test results affect the life and safety of parts. The detection technology based on the digital image processing mechanism belongs to the category of non-destructive testing. It can quickly detect the surface cracks of mechanical parts and achieve accurate and effective evaluation of the surface defects of the parts. Based on the application of actual digital image processing technology, this paper presents an effective evaluation system for the defect detection of component surface cracks in image processing technology for programming tools used in simulation experiments, digital image processing algorithms, and design experimental software features, calculation methods and steps. After the above argument, the digital image processing method for surface cracks of parts is proposed. We can properly process the acquired images on the spot, obtain the values of piecewise linear stretching mean, median filtering, etc., and prove that digital image processing technology has the advantages of image detail processing the advantage is that it can realize rapid judgment and accurate detection of surface crack defects.
Target Tracking Based on Camshift Algorithm and Multi-feature Fusion
Authors: Chaoqian Gao , Hu Chen , Tianping Li 
Published: June 2020

Abstract
This paper proposes a new algorithm on the basics of Camshift algorithm and multi-feature fusion. First, the target area is weighted by the Gaussian function. Then LBP is used to extract local texture features, next fuse the texture features with the color features to obtain the color and texture histogram. Finally, for the purpose of tracking the target accurately and preventing occlusion, the Kalman filter is used to forecast the position of the moving target. From the comparison of the experimental results, the conclusion can be drawn that the new algorithm can effectively overcome the interference of objects and track the target accurately in a more complex environment.
Research on Weather Condition Influence Factors on Intelligent Connected Vehicle
Authors: Ma Bingbing , Li Wenqiang , Zhang Zhiguo , Song Rui 
Published: June 2020

Abstract
Now, there is no standard test method and flow for the performance of Intelligent Connected Vehicle under the complex weather conditions, which has greatly limited the development of Intelligent Connected Vehicle. This paper test and study the weather conditions that affect the performance of the on-board sensors, then analyse the weather conditions that affect Intelligent Connected Vehicle, the meteorological factors which affect Intelligent Connected Vehicle performance are obtained. It turns out that different conditions such as rain, fog, snow and light have different influence on the Intelligent Connected Vehicle, which provides the foundation for the performance test of Intelligent Connected Vehicle.
Active Defense Technology Based on Natural Software Diversity in Java Web Services
Authors: Liu Zhenwu , Zhang Zheng , Liu Hao , Zhang Gaofei , Chen Yuan 
Published: June 2020

Abstract
With the popular use of network application services and the growing number of users, web services have become the main target of hackers. Traditional single software has insufficient security protection against unknown threats and is prone to various vulnerabilities. In this paper, we adopt a new type of active defense strategy in java web services. At different application layers, we use existing components based on the natural software diversity to form different software stacks, and use dynamic scheduling mechanisms to change the attack surface at all times to obtain security protection. Our analysis shows that the flexibility of java web services using this defense strategy is enhanced, and the exploitability of its vulnerabilities is effectively reduced.
Research on Radar Servo System Based On Disturbance Observer Sliding Mode Control
Authors: Chen Siyuan , Guan Tao , Wang Yibo , Liu Yunfeng 
Published: June 2020

Abstract
Radar turntable servo system has strong friction at low speed, and the traditional PID control method due to its fixed parameters, poor stability and low control accuracy, is difficult to meet the high requirements of modern radar servo system for control quality. In this paper, a sliding mode controller with disturbance observer is proposed for the radar servo system. The friction is estimated by the exponential convergence disturbance observer; meanwhile the exponential approach law sliding mode controller is also designed. The simulation results show that the radar servo system controlled by sliding mode disturbance observer is better than the traditional PID controlled system. It can overcome the friction at low speed and improve the response speed and control accuracy of the radar servo system.
Analysis on the Research Approach and Trends of Medical Image Processing in China
Authors: Feng Yibo , Qiu Dawei , Cao Hui , Zhang Junzhong , Liu Jing 
Published: June 2020

Abstract
In order to explore the research approach and hotspots in the field of medical image processing in China, the authors retrieved related literature in the field of medical image processing in China from 2009 to 2019 in CNKI database, and preprocessed the retrieved data. Then Citespace was used to analyze the retrieved data of 1363 documents from 2009 to 2019, the paper counted the basic situation of the article’s publication time, subject, and analyzed the high frequency keywords, cited literatures with high frequency. The results show that the domestic medical image processing field has a high degree of attention to image segmentation, registration, and fusion. Deep learning, convolutional neural networks and transfer learning have been applied to medical image processing in recent years. This paper revealed domestic research trends in medical image processing, with a view to providing reference for research in medical image processing.
Prediction of Consumer Price Index based on Long Short-Term Memory Model
Authors: Ao Xiqin , Gong Yujie , Zuo Beibei 
Published: June 2020

Abstract
Consumer Price Index(CPI) is the main standard to identify inflation or deflation. Accurate prediction of CPI will help the government to implement macro-control and formulate price stabilization policies, so as to achieve the goal of building a moderately prosperous society. CPI is a non-stationary and non-linear time series, and has relevance in time dimension. In order to fully mine the correlation of CPI sequence in long and short time span, a method of predicting CPI using Long Short-Term Memory(LSTM) model is proposed. Taking historical CPI data of Anhui Province as the empirical analysis object, modeling and predicting are carried out. The prediction effect of LSTM is compared with classic time series model-Autoregressive Integrated Moving Average(ARIMA). According to the predicted results, LSTM model has significantly improvement in RMSE and MAE indicators compared with ARIMA model, indicating the LSTM model has higher prediction accuracy. The SDAE indicator of LSTM model is smaller than ARIMA model, indicating the LSTM model has better prediction stability.
Bearing fault diagnosis based on Empirical Mode Decomposition and Adaptive Network-based Fuzzy Inference System
Authors: Dong Wenzhi , Qi Chundong 
Published: June 2020

Abstract
The early fault characteristics of rolling bearings are weak and time-varying, and there are problems of modal aliasing and end effect in Empirical Mode Decomposition (EMD), and the decomposition effect is unstable. A bearing fault diagnosis method based on EMD and Adaptive Network-based Fuzzy Inference System (ANFIS) is proposed. Firstly, the signal is decomposed into several Intrinsic Mode Functions (IMF) by EMD, then multiple fault feature quantities are obtained from the IMF1 component to construct the fault feature set. Finally, the extracted fault feature set is classified and identified by ANFIS. The experimental results show that the proposed method has high diagnostic accuracy and can effectively identify the fault type.
Research on Power Market Stability and Risk Management Based on Heterogeneous Information Sources
Authors: Chunxiao Liu , Zhiyong Li , Qiang Zhou , Peishen Zhang 
Published: June 2020

Abstract
The development of power markets in various countries in the world and the gradual formation of China’s power market require academic circles to provide research theories related to the power market to support them. In the competitive environment, fundamental changes have taken place in power production, trading and consumption. The operating conditions of the system are harsh and uncertain. The problem of safety and stability is becoming more and more prominent. Judging from the international and domestic development situation, it is a historical necessity for electricity to enter the market. When electric power goes to market, it is necessary to bring electric power industry into the framework of market economy. Stability is the basis for the normal operation and sustainable development of the system, so it is more urgent to promote the healthy development of the power market by the research results of power market stability. The risk analysis method reflects the mathematical expectation of loss by the product of accident probability and accident consequence, so it can effectively unify the stability and economy on the dimension of currency, and realize the analysis and decision-making of technical and economic integration.
Research on Communication Transmission Management Strategy Based on Artificial Neural Network Algorithm
Authors: Zeng Huaxiang 
Published: June 2020

Abstract
Communication engineering technology belongs to a main component of electronic engineering. Its main operation principle is to transmit information in the form of light wave or electronic wave to achieve the effect and purpose of timely transmission and high-speed transmission. The real development of communication enterprises cannot only depend on the development of communication technology transmission, but also need to manage all aspects of communication technology transmission. Communication engineering technology transmission, as a key project of communication engineering, plays a key role in improving the competitiveness and market share of communication enterprises. Optimize and integrate the existing resources, manage the cost of each work in the communication engineering technology transmission, and improve the efficiency of technology transmission to the greatest extent, so as to ensure the transmission speed and quality. This paper analyzes the management problems of communication engineering technology transmission through the artificial neural network algorithm, designs the artificial neural network for information transmission loss prediction, and puts forward the corresponding solutions in order to promote the development of communication enterprises.
Breaking Cause Analysis on a 110 kV Overhead Grounding Wire (OGW)
Authors: Zheng Jianjun , Han Kuo , Wang Yingjun , Shi Xianda 
Published: June 2020

Abstract
An in-serviced 110kV overhead grounding wire (OGW) was found to be broken, and the fracture cause was then studied by means of macroscopic morphology and metallographic observations, fracture microanalysis and mechanical properties testing. The results revealed that the fracture of OGW was mainly resulted from the lightning stroke, which was mainly informed from the craters on the surface of the broken wire steel strand by fracture morphology observation results. The lightning currents led to a rapid temperature rise, which eventually caused the surface OGW to be broken by tension after fusing or partially fusing under high temperature. At last, it was advised that coarser steel strands should be used in areas with frequent lightning strikes to improve the thermal stability of OGW, and the metal technical supervision in the operation process of high voltage transmission lines should also be strengthened.
Based on Randomly Executed Sequence and GA-SVC Applied on Air Quality Analysis
Authors: Wei Fan , Sun Honglin 
Published: June 2020

Abstract
Air quality is a key factor affecting people’s daily travel. In order to analyze and classify air quality, and to solve the problem of low classification accuracy, this paper mainly studied the SVC (multi-classification support vector machine) Algorithm based on the random sequence selection of optimized parameters through Genetic Algorithm. Aiming at the problems of insufficient classification accuracy in current multi-feature sequence analysis and unstable parameter selection in SVC algorithm, comprehensive classification evaluation of data is carried out by analyzing data features and correlation among features and integrating genetic algorithm into SVC to optimize parameter selection, so as to improve classification accuracy. The experimental results show that the classification accuracy has been improved by 5% on average with the current popular decision tree classification algorithm, unoptimized SVC algorithm and KNN algorithm.
Cause Analysis of the Crooked High Voltage End Fittings for a 220kV Composite Insulator in-service
Authors: Zheng Jianjun , Han Kuo , Wang Yingjun , Shi Xianda 
Published: June 2020

Abstract
The high voltage end fitting for an in-serviced 220kV composite insulator was found to be crooked by the transmission line inspector, and the deformed cause was then investigated by digital X-ray imaging, chemical composition analysis, metallographic observation and mechanical properties testing in this paper. The results indicated that both the material quality and mechanical properties of the composite insulator high voltage (HV) end fitting met the standard requirements. And the main reason for the crooking of HV end fitting was the effect of abnormal force, such as falling from high position, impact of heavy objects. At last, it was advised that the supervision on the installation quality of fittings and the inspection of in-service composite insulator fittings should be strengthened. In addition, composite insulator with deformed or fractured end fitting should be timely handled, avoiding similar metal section failures.