bluuebunny/crossref_metadata_2025 huggingface dataset:
A Method for Dividing Line Replaceable Unit
Authors: Zhiming Guo , Ying Liu , Changfu Li , Hu Qiao
Published: November 2019

The problem of dividing the line replaceable unit (LRU) is one of the urgent problems to be solved in the RMS field in recent years. This paper proposes a method of line replaceable unit division, based on actual needs, to study the need of LRU division trade-off. On this basis, the indicators and parameters of LRU division trade-offs are studied to realize the scientific division of LRU, which provides support for product reliability, maintainability, supportability and test engineering design and analysis.
Finite Element Analysis of Underwater Ultrasonic Cleaning System Based on Ansys
Authors: Xu Haoran , Zhang Guohua , Wang Yanqing
Published: November 2019

In this study, the finite element model of the ultrasonic cleaning system was established and the harmonic response analysis was carried out to obtain the vibration distribution of the ultrasonic cleaning floor and the sound pressure distribution in the water. Scanning electron microscopy was used to observe the adhesion of fouling organisms. The results show that the ultrasonic treatment mode has a significant effect on the microscopic fouling adsorption of PMMA surface. When the total time of the ultrasonic action is same, the shorter the ultrasonic interval time, the more significant the effect of ultrasonic decontamination.
LED filament standard lamp for total luminous flux with uniform spatial distribution
Authors: Yan J , Liu H , Zhao W , Su Y
Published: November 2019

To measure the total luminous flux emitted by a light source, the standard lamp which provides an absolute value of the total luminous flux is used with a sphere-photometer. Many institutes have developed their standard lamps based on LED. However, it is difficult to acquire uniform light distribution like the traditional incandescent lamps. To solve this problem, a novel LED filament standard lamp for total luminous flux is developed. First, a luminous intensity distribution model of a single LED filament is established. Based on this model, a method to calculate the luminous intensity distribution of multiple LED filaments is derived. To evaluate the uniformity of a light source, a spatial distribution uniformity index is introduced. Second, the spatial distribution uniformity index of the developed standard lamp is calculated by simulation and the optimal design is obtained. Experiment shows that the LED filament standard lamp for total luminous flux with the optimal design obtained uniform luminous intensity distribution in 4π geometry.
User Departure Behavior Prediction in Social Group
Authors: Liu Jiayi , Han Qilong , Li Yinlong
Published: November 2019

We proposes a departure behavior prediction algorithm to predict the user’s departure behavior. The k-core decomposition is conducted on the graph. By considering the positive and negative affect users obtain, we calculate a score for each user. Finally, the user is predicted by the sliding window model. Experiments show that the DBP algorithm has a high prediction.
Community Detection based on Autoencoder Reconstruction Similarity Matrix
Authors: Li Yinlong , Han Qilong , Liu Jiayi
Published: November 2019

Community detection plays an important role in various fields. In the existing community detection algorithms, adjacency matrix is widely used in the process of community detection. However, the adjacency matrix cannot show the tightness between nodes and cannot show the characteristics of nodes. To solve this problem, we propose the concept of similarity matrix. We calculate the similarity of any two connected nodes and get the similarity matrix. Then, we use autoencoder to reconstruct the similarity matrix. The reconstructed similarity matrix can better reflect the node features. Based on the reconstructed similarity matrix, we propose a feature distance optimization formula. According to the feature distance optimization formula, we continue to optimize and reconstruct the community until we get the optimal community. Experiments on multiple real data sets show that compared with other classical efficient community detection algorithms, our proposed algorithm is more accurate in community detection.
Research on Ceramic Capacitor Automatic Test Application Technology
Authors: Wu Bo , Hu Xiaohai , Xu Wensheng
Published: November 2019

In order to improve the detection efficiency and quality of reliability screening for electronic component in military industry such as aerospace and aeronautics, and eliminate the hidden safety hazards caused by manual inspection operation, the ceramic capacitor automatic test technology was applied to the electrical performance testing of reliability screening process. An new original automatic detection system by using auto test technology of automatic loading and unloading, instrument automation control and parallel testing was designed and developed to realized one-key automatic measurement of capacitor four parameters such as capacity accuracy, loss, insulation resistance and dielectric withstand voltage. It solved the test quality problem that test data could not be automatically recorded and avoided the harm caused by high voltage and short circuit in the detection process. Finally, with the practical application and test, the efficiency and quality of detection process was improved.
Touchpoint Marketing System Design among Operators
Authors: Yuxin Cai
Published: November 2019

This paper analyzes the demand of telecommunications operators about use and value of big data, and by referring to the Internet thinking and combining the advantages of multi-channel contact marketing of operators, this paper proposed the idea of big data contact marketing system. This paper described the process of building the system of big data contact marketing under the environment of operators on the basis of multi-domain data management, client profile labelling, multi-channel integration and contact marketing. Last, this paper introduces the realization situations of the big data contact marketing system, and analyzes the prospect of its value and future development.
Research on influence factors of product configuration rebuilt design with demand preferences of customers
Authors: Yang Tao , Li Yu Lin , Su Jia Fu
Published: November 2019

In order to improve the personalized demand satisfaction of customers and fully considering the demand preference characteristics of enterprise end customers, an analysis method of influence factors of product configuration rebuilt design considering customer demand preferences was proposed. Firstly, through literature analysis, market survey, questionnaire survey and other means, the demand preference characteristics of enterprise end customers are obtained and analyzed, and the influence factor set of product configuration rebuilt design considering customer demand preference is constructed. Then, the importance of influence factors is hierarchically divided by using the interpretive structural modeling method (ISM), and the key influence factors of product configuration rebuilt design considering customer demand preference are identified. On this basis, an example was given to verify the feasibility, rationality and effectiveness of proposed method.
Parametric Modeling and Finite Element Static Analysis of Large Reflector Antenna Based on APDL and MATLAB
Authors: Li Qin
Published: November 2019

In this paper, a Large Reflector Antenna is taken as the research object and the Parametric Modeling of Antenna Structure is achieved by using APDL language in ANSYS, and the APDL command flow generation was completed with the help of MATLAB, which achieved the program of modeling and improved its efficiency. Meanwhile, the paper applies parameterization to restrain and load the static load of Antenna, and makes an analysis on the Finite Element Static. This provides a basis for the analysis of the stiffness, deformation and structure optimization of Antenna.
The Method of Position Sensorless Inductance Model of SRM Based on FEA
Authors: Tang Xiaozheng , Liu Yidan , Zhao Xuehua , Zhao Shuai , Jiang Mengyao , Ma Hongzhong
Published: November 2019

The paper presents a position estimation method of the Switched Reluctance Motor(SRM) based on inductance model through FEA. The phase inductance of SRM is seriously nonlinear. Based on FEA, Fourier analysis result of phase inductance shows that more than three times harmonic contents are smaller. Ignoring more than three times harmonic, the simplified inductance model is expressed. Then a new rotor position estimation method is presented, which is based on the inductance model. Experiment results show that the effectiveness of the method proposed is verified, and under different saturated conditions, the method can accurately estimate the rotor position of Switched Reluctance Motor.
Unsupervised anomaly detection system for railway turnout based on GAN
Authors: Xue Lei , Gao Shuli
Published: November 2019

With the rapid development of society, the railway system plays an important role in human life, and the safety of railways has become an extremely important task. As we all know, the switch is one of the important equipment to ensure the safe operation of trains. Real-time detection of the turnout current plays a vital role in train safety. However, the previous signal-based processing methods require a large number of feature engineering, which greatly increases the workload of pre-processing. Some neural network-based methods show good performance, but for the time series data of the switch, these methods cannot fully extract its local features, resulting in poor information loss and poor prediction accuracy. Based on the generational confrontation network, this paper proposes a kind of unsupervised anomaly detection system. We combine the one-dimensional convolution with the Generative Adversarial Networks (GAN). The one-dimensional convolution network can effectively extract the local features of the time series. The GAN can self-game learning to sample distribution and is better than self-encoder and other models, which improves the accuracy of prediction. In the real railway system, abnormal data is extremely rare and varied, while unsupervised learning does not require label data, and it can well learn the distribution of normal samples. The system improves the efficiency of the staff, accurately diagnoses the switch, greatly shortens the processing time, and avoids the blindness in maintenance. Using our model on the turnout data, the accuracy rate is 0.992, the recall rate is 0.815, and the F1 score is 0.895.
Research on the Dynamic Properties of Electromagnetic Railgun Launch System
Authors: Li Xuan , Qiu Qunxian , Li Pengfei
Published: November 2019

Electromagnetic railgun launch system is the part designed for launching projectile. The dynamic properties of the launch system contribute to the firing accuracy. This paper models the finite element model of a square-shaped railgun. The Ansys ACP module is used to design the layer of carbon fibre barrel of the railgun. Modal analysis of the launch system is performed using Ansys. On this basis, the modal superposition method is used to calculate the dynamic response of the launch system caused by the electromagnetic expansion force during launching. This paper analyses the steel encapsulation barrel as a comparison and verifies the rationality of using the composite material. The results provide support for the engineering design of electromagnetic railgun.
Study on Laser Cladding Preparation of Bionic Surface of Cast Iron Brake Disc
Authors: Hu Yong , Li Maosen , Liu Xin , Zhai You , Yang Zilong , Li Yan , Zhu Xu
Published: November 2019

The shellfish in nature was taken as the biological model, and the coupling design was carried out on the surface of grey cast iron. With the help of advanced laser cladding technology, the unit body was prepared on the surface of grey cast iron, so as to obtain the bionic samples of grey cast iron with high wear resistance and fatigue resistance. The composition, hardness distribution, morphology and phase of the unit were analyzed by micro-hardness tester, scanning electron microscopy (SEM) and XRD. Thermal fatigue test and friction and wear test were carried out on bionic and untreated grey cast iron samples. The effects on fatigue resistance and wear resistance of bionic laser cladding and grey cast iron were studied by comparing the experimental results. It was found that the laser cladding has a compact structure and a metallurgical bond with the substrate. The hardness of the unit is 2 times of that of the grey cast iron substrate. The thermal fatigue resistance of the material is improved by bionic laser cladding. The bionic laser cladding preparation can greatly improve the wear resistance of materials.
Study of Potential Distribution of UHV AC Arrester in Different Conditions
Authors: Wang Hui , Song Simeng , Yao Weijia , Zang Yiming , Qian Yong , Sheng Gehao
Published: November 2019

As is known to all, uhv ac lightning arrester will be attenuated to varying degrees due to long-term operation on site, including environmental temperature and humidity, breakdown of valve plate and short circuit, leading to uneven capacitor voltage divider, and causing explosion and other dangerous safety accidents in extreme cases. Therefore, it is very important to analyze the electric field potential distribution characteristics of arrester under different operating environment and conditions. In this paper, the equipotential distribution of uhv ac arrester in local damping and local short circuit test is verified theoretically and practically by using fiber optic current method. Based on the field structure and theoretical analysis, the ANSYS 3d theoretical model is constructed to analyze the actual test conditions. The oneness of field test and theoretical calculation shows the accuracy of theoretical calculation.
Research on Control Method of Valve-controlled Heating System
Authors: Zhang Xingchao , Lei Jinhui , Zhang Mingsheng
Published: November 2019

The valve-controlled heating system mainly controls the hot water flow to achieve the automatic adjustment of the room temperature. However, the common flow control algorithms have some disadvantages, such as large overshoot and slow response, which cannot meet the requirements of fine control of the system. On the basis of optimizing the fuzzy control algorithm, a model reference predictive fuzzy adaptive control method is adopted in this paper. The system simulation test showed that this control method had good dynamic performance and anti-jamming performance, which could achieve the relative accurate control of room temperature, and achieve control objectives.
Research on system testability index allocation of substation digital metering system
Authors: Wu Xiang , Huang Tianfu , Wu Zhiwu , Guo Zhiwei , Wang Chunguang , Yang Sen
Published: November 2019

In the testability engineering of measurement system, if the allocation of testability indicators is not combined with the overall scheme of the system, it will lead to the indicators too high to achieve or too low and thus lack of binding effect. At present, the test scheme for digital metering system can only effectively guarantee the accuracy and reliability of a digital metering device when it runs alone, and can not fully reflect the performance of this device when it runs as part of a complete system. Combining with the digital measurement system of substation, this paper introduces the engineering prediction method into the system, and designs the allocation scheme of testability index and an integrated framework for system-level testability scheme and index allocation. It has reference significance for optimizing the design scheme of testability, reducing the time and cost of testing, and improving the test efficiency.
Study on Test Method of Energy-saving Performance for Coal additives in Slime
Authors: Wang Zheng , Li Hongtao , Ji Yunguang , Chang Hao , Xue Shuqi
Published: November 2019

Adding coal additives in civil water heating coal furnace can effectively reduce coal consumption and has great economic benefits, but there is no standard method for testing energy-saving performance of coal additives in slime. Referring to GB/T 16155-2018 “Test Method for Performance of Civil Water Heating Coal Furnace”, this paper developed a measuring device for energy-saving performance of coal additives, and proposes a detection method based on the temperature of effluent and backwater as a measuring scale for heating capacity of slime combustion. The experimental results show that the energy-saving effect of coal additives on clean briquette is not obvious when it is sprayed on clean briquette and burned by dry clean briquette, while in wet mixed combustion, the cumulative heat of slime with coal additives increases by up to 50% compared with that of ordinary slime.
Identity-Based Threshold Key-Insulated Proxy Signature in the Standard Model
Authors: Chen Jianhong
Published: November 2019

Loss of secret keys is the deadly attack in public key cryptosystems. We present an identity-based threhold key-insulated proxy signature (IBTKIPS) scheme to settle the problem of key exposure in the identity-based proxy signature system. The proposed IBTKIPS scheme is secure in the standard model. In the IBTKIPS scheme, we use at least k out of n helper keys to refresh the temporary secret keys. The IBTKIPS scheme is more flexible and securer than the identity-based proxy signature scheme.
Research on the relationship between government policy and enterprise production decision in green background
Authors: Cai Xiaotian , yang Yang , Li Zhe
Published: November 2019

In the low-carbon background, China must develop green manufacturing actively, and take a new road to industrialization. Government subsidies can promote the promotion of low-energy products, and thus control the total carbon emissions. Aiming at production decision of a kind of manufacturing business, A 0-1 Nonlinear decision model was built with consumer surplus as the optimization objective. This model provided guidance for the government policy decision and the firm production decision. A genetic algorithm was put forward to solve the 0-1 nonlinear decision model. A case study of refrigerator was reported to demonstrate the feasibility and rationality of this approach.
Application and Prospect of Human-Machine Interaction in Power System
Authors: Yunfeng Zou , Mingming Pang
Published: November 2019

Poser system provide many scenarios the innovation of human-machine interaction technology. Four advanced human-machine interaction technologies in power system are introduced and the necessity of human-machine interaction in power system are summarized from four aspects. Development Course of Human-Machine Interaction in Power System are divided into five generations based on technical characteristics. Four technological trends which should be focused on are given.
Research on inertial stabilization platform on mobile carrier in complex environment
Authors: Yang Shuqiang , Zhu Hairong , Zhang Qianqian
Published: November 2019

The inertial stabilization platform on the mobile carrier has been widely used in military and civilian fields, such as modern satellite TV receiving and broadcasting, mobile satellite communication for vehicles and ships, as well as cash transport vehicles, public security, fire protection, disaster relief, environmental monitoring and many other industries. The platform needs the ability to isolate the effects of carrier motion, and to ensure the interception, identification and tracking of the target signal under various meteorological conditions. We choose the platform of photodetector component. It uses the electromechanical to control detector according to the instructions, automatically identifing and capturing the target. In the working process, the servo system is the key guarantee of the high performance of the platform. According to the high precision, fast response, wide frequency band and strong robust performance requirements of the system, we propose a single neuron adaptive PI+DOB (Proportional Integral+Disturbance Observer) control strategy, a method for continuous nonsingular terminal sliding mode control and a improved statistical model adaptive filtering algorithm. Through theoretical research and experimental analysis, our method improves the performance parameters based on the original system, and provides theoretical support for future researchers to develop high-precision inertial stabilization platform.
Improved text sentiment classification method based on BiGRU-Attention
Authors: Zhou Liang , Bian Xiaoyong
Published: November 2019

Aiming at the problem that the traditional text sentiment classification method is not sufficient for text context information learning and key feature extraction ability, this paper proposes a BiGRU-Attention based text sentiment classification method to classify Chinese texts. The method used a Bidirectional Gated Recurrent Unit (BiGRU) instead of the Bidirectional Long Short-Term Memory network (BiLSTM) to build a hidden layer, and introduces an attention model to input the result of each time point in the hidden layer to the fully connected layer yields a probability vector. Then use this probability vector to weight each hidden layer result and add it to get the result vector. The experimental shows that the model this paper proposed has better accuracy and effectiveness in text classification.
A Concurrent Dual Mode Adaptive Switching Blind Equalization System in Impulse Noise
Authors: Lei Yingke , Liao Xichang
Published: November 2019

Due to the influence of various factors, the noise in actual digital communication system is non-Gaussian and always assumed to be impulse noise. But most blind equalization algorithms are mainly directed against Gaussian noise and the performance of common algorithms under impulse noise is poor. So, in this paper, we have studied the problem of channel equalization under impulse noise and improved the fractional lower order constant modulus algorithm(FLOM-CMA). Then, by convex combining with decision-directed least mean p norm(DD-LMP) algorithm, a new concurrent adaptive switching blind equalization system had been proposed here. The advantages of different modes are fully combined in our system by soft-switching, which is the FLOM mode is used to make the equalization process converge quickly, and then, after the eye map of signal is open, the joint parameter is gradually reduced to zero and our system adaptive switching to DD mode to improve its convergence accuracy. The excess mean square error(EMSE) of our system is analyzed, and several experiments have been simulated to prove that our system performs better than other traditional algorithms.
Research on the Propagation Characteristics of Social Events in the Context of Micro-media
Authors: Zhi Hui , Wang Nan
Published: November 2019

With the great development of information science and technology, a variety of communication tools have come out, which enormously improved efficiency and speed of social communication, and people’s living conditions have endured a great change. The social events has always drawn mass attention and reflected publice focus, and people will soon get together, talking about social events by micro-media, such as QQ, Wechat, micro-blogs. The way people talked and publicized by micro-media, as well as the outcome, are all things we are going to research on.
Study on abnormal detection of ecg signal base on DCNN
Authors: Keyou Guo , Liping Ma , JiaTong Qin , Yunxia He
Published: November 2019

In this paper, the Dropout deep convolutional neural network based on ecg signal anomaly detection method is proposed. Then, the double threshold method is used to detect the R wave and calculate the width of corresponding QRS wave group and the position of QRS wave is taken as the reference to include several points forward and backward respectively. These data points are intercepted and made into data sets for training and testing of deep convolutional neural network. Finally, the data set is read into deep convolutional neural network for abnormal measurement, and the test results are statistically analysed. In this paper, the detection rate of QRS composite wave is up to 99.5%, and the classification accuracy of abnormal signals can reach 99.26%. Experimental results show that the algorithm has the characteristics of high implementation rate, high accuracy, convenient and fast.
An improved scheme of searchable encryption algorithm based on NTRU
Authors: Cheng Sipei , Li Mengdong , Duan Yuwei
Published: November 2019

R. Behnia et al proposed a NTRU-based searchable encryption scheme in 2017. Compared with the previous searchable encryption scheme, this scheme has a great improvement in security and efficiency, and can resist quantum computing. But this scheme will expose a lot of information to the server. If the server is not completely honest, an attacker can use the information to attack a user’s keywords. This paper proposes an improvement of Rouzbeh’s scheme, solves this problem and improves security.
Classification of Alzheimer’s disease in MobileNet
Authors: Lu Xiaoling , Wu Haifeng , Zeng Yu
Published: November 2019

As the aging of Chinese society becomes more and more serious, the number of elderly people has increased dramatically. At the same time, the number of patients with Alzheimer’s disease (AD) has increased. At present, the main diagnostic method for Alzheimer’s disease relies on experienced radiologists to analyse brain structural nuclear magnetic resonance (MRI) images to judge the condition, but this method is time-consuming and labor-intensive, and there is a certain subjectivity. This may cause misdiagnosis. By classifying the MRI images of patients with Alzheimer’s disease and healthy controls (NC), for image classification, the Convolutional Neural Network (CNN) in deep learning has outstanding performance and accurate classification. The VGG 16 network model and the MobileNet network model of the convolutional neural network are compared, using deep learning and transfer learning. We can find that the MobileNet network model is superior to the VGG 16 network model in classification accuracy.
Shellcode Location Based on Register Information Flow
Authors: Song Yu , Kuang Hongyu , Wang Jian
Published: November 2019

Due to the high detection accuracy of dynamic simulation in which network traffic is sent to the emulator as executable code to detect suspicious behaviour, static analysis has become less popular. Earlier static shellcode detection methods are mainly based on statistical method which focus on instruction abstract features or byte patterns. Although these method can be used for detection, it can’t guarantee the detection effect.

It is hard for both of them to locate the position of shellcode. However, a new static analysis based approach is proposed in this paper. The shellcode instructions rely heavily on contextual information, so we use static disassembly to capture the fine-grained malicious mode of registers. In order to enhance the detection performance, several rules are designed based on the characteristics of the shellcode. Experimental results show that our method has certain potential, which may show better effects when combined with other shellcode detection methods.
A New Wireless Sensor Network MAC Protocol: NSMAC
Authors: Zhang Yaoyao , Jiang Lingyun
Published: November 2019

How to reduce energy consumption and improve the life cycle is one of the hot spot issues in current wireless sensor network research. Media Access Control (MAC) has an important impact on sensor network life cycle and performance. This paper proposes a new MAC protocol--NSMAC protocol. This protocol dynamically changes the length of the contention window and the size of the duty cycle based on the load on the network. It can effectively reduce energy consumption, improve network throughput capacity, and improve sleep time-delay in a multi-hop network environment when the network load is large. The experimental results also prove that this protocol has significant improvement in energy consumption, time-delay and throughput capacity compared to SMAC protocol and RCMAC protocol.
Spectrum Occupancy State Predictor Based on Recurrent Neural Network
Authors: Fan Rong , Guo Hesong , Di Lujie , Ling Xing
Published: November 2019

To cope with the scarcity of spectrum resources and to improve the efficiency of spectrum utilization, spectrum occupancy prediction (or named channel state prediction) technology has been addressed into cognitive radio (CR) in recent years. In the paper, we first address the issue how to model the primary user behaviour in CR. And based on the presented behaviour model, a recurrent neural network (RNN) is chosen to design a spectrum occupancy state predictor. By exploiting the learning capacity of recurrent neural network, it can predict the spectrum occupancy state of primary user behaviour. Meanwhile, in order to reveal the proposed predictor’s advantages, the spectrum occupancy state predictor based on RNN and another existed two spectrum occupancy state predictors are also adapted in the simulation section of the paper. Numerical simulation results illustrate the advantages of the proposed method.
Potential Energy Field based Pedestrian Behavior Model for Crowd Evacuation Simulation in Airport Terminal
Authors: Ting Yuan , Yi Liu
Published: November 2019

The crowd evacuation simulation in airport terminal is an important method to improve the efficiency of the emergency evacuation decision. Different from traditional pedestrian simulation, the evacuation simulation in airport terminal should fully consider the layout of the terminal building and the characteristics of passenger behavior. This paper proposes a pedestrian behavior model based on potential energy field. On the one hand, the spatial region is modeled by fine grid, so as to model the pedestrian’s body type, pose and decision in airport terminal more realistically; on the other hand, the potential energy field mechanism fully considers following factors’ influence on the pedestrian behavior, including the shortest path to the destination, obstacles, other pedestrians and sudden events. Based on the model, this paper simulates the evacuation process on a certain airport terminal, and evaluates the evacuation ability of the building. Based on the simulation of evacuation time under different number of people and different utilization of building space, the quantitative emergency measures and building optimization recommendations are given. This research can provide advance scientific guidance for pedestrian organization, terminal building design, and emergency plan.
Current situation of information literacy of regional college teachers and improvement strategies in the age of “Internet+”
Authors: Wang Lei
Published: November 2019

“Internet + higher education” provides a vital opportunity for educational reforms. How to integrate information technology with teaching practices, how to improve information literacy have become a challenge for college teachers. This paper discusses the definition and components of information literacy for college teachers, analyzes the current situation and defects of college teachers’ information literacy in the age of “Internet+”, and makes case studies on G College. On that basis, this paper proposes suggestions to improve college teachers’ information literacy in the “Internet+” age: on the individual level, teachers should rely on the Internet training community to seek progress in cooperation and interaction; on the organizational level, colleges should promote upgrading of the college teachers development center, and make full use of the Internet and big data technology to optimize the training mode; on the environment level, colleges should face “Internet+” positively and provide a supporting environment.
Application and Research of VR Technology in Art Design Teaching
Authors: Wang Qinghai , Zhe Zhang , Xing Yadan
Published: November 2019

In recent years, with the rapid development of science and technology, VR virtual reality technology is now applied in various fields, and this technology is gradually applied to art design teaching. VR virtual technology can construct a simulation learning environment, which enables students to have a comprehensive and systematic understanding of various courses of art design specialty, and cultivate students’ creativity and imagination. By analyzing the advantages of VR technology in teaching, this paper puts forward the teaching method of integrating VR virtual reality technology into classroom teaching, and explores the feasibility of applying SLOODLE platform to art design teaching, so that the platform can be widely used in art design teaching.
The Influence of Internet on College Education Management and Countermeasures
Authors: Chen Shengjun
Published: November 2019

The influence of network culture on college students is all-round. It provides a large amount of information resources for contemporary college students, and provides them with a new model of study, research and communication, and also has a negative impact on contemporary college students. On the one hand, the Internet brings the convenience of college students to study and entertainment; on the other hand, it also has a certain impact on the education management of college students. This paper analyzes the impact of the network on the education management of college students, and gives corresponding suggestions and countermeasures.
Research on the Transition from Financial Accounting to Management Accounting under the Background of Artificial Intelligence
Authors: Guo Xiaohui
Published: November 2019

With the rapid development of AI information technology in China, it has brought certain impact on the traditional training mode of accounting personnel in Higher Vocational colleges. Faced with the constant change of technical means, the boundaries of industry, organization and function are all changing. Under such circumstances, accounting profession must change itself. Therefore, the training mode of traditional accountants should gradually change to management accounting. Firstly, this paper analyses the influence of AI on accounting industry. This paper then analyses the problems faced by financial accounting in the era of artificial intelligence. At last, this paper analyses the measures of transforming financial accounting into management accounting.
A Realtime Algorithm for Distinguish Obstacle from Accessible Area in 3D Scene
Authors: Zhang Ye , Zhou Ziwei , Xu Liang
Published: November 2019

A learning algorithm based on Hidden Markov random field model is designed, and three-dimensional data is extracted, and the robot is used as an experimental platform. In the process of recognition, obstacle areas and feasible areas are distinguished by template matching, and the accessible areas and obstacle areas of the scene around the robot are obtained by classification results. According to the state of the robot itself, the position and direction vectors of the robot are calculated. The robot adjusts its attitude under the control of the output vector, so as to avoid obstacles and move to the target point. Finally, it is proved that the experiment has ideal real-time performance, so it has an extensive practical application foundation.
UAV cooperative attack and route planning based on DPSO algorithm
Authors: Tianhan Tan , Kun Wang , Qishuang Wang , Bo FU , Gang Wang , Yongsheng LI
Published: November 2019

For UAV cooperative attack and route planning problem, a cooperative attack allocation model is established in fully considering the attack cost and attack revenue. Considering the threat cost and path distance cost, a flight path planning model is also established. An improved particle swarm optimization algorithm called DPSO is proposed by discrete space mapping, which can reduce redundant search and speed up search. Based on the model and optimization algorithm, reasonable cooperative attack target assignment and route planning are worked out, and the optimal performance is achieved.
Design and Implementation of Movie Recommendation System Based on Naive Bayes
Authors: Shuxian Liu , Sen Fang
Published: November 2019

Today, with the rapid development of the Internet industry, the era of big data has arrived. What follows is that the surge in data volume has brought great challenges to people’s rapid and timely screening of useful information. Based on this highly realistic problem, the recommendation system that solves the user’s individual needs is born. In this paper, based on the theory of Naive Bayes, the MovieLens data set is used for testing. The user’s scoring data are used for similar analysis to generate the user’s similarity matrix, and the target user can be personalized. Compared with other algorithms, this paper has a good recommendation effect.
Curve Fitting of Raspberry Pi Car-Route Based on Baseline Least Squares Method
Authors: Shen Feihong , Zhang Hanfeng , Lin Kaichao , Zhang Tong , Guo Dongwei , Zhang Erhan
Published: November 2019

Curve fitting has a wide range of applications in engineering design, computer graphics, etc. In some case traditional least square methods can’ t use known conditions as fully as possible, so we introduce a notion named baseline. We firstly estimate a baseline and use the point to line distance as the parameter of the probability density as the weight value of the least square. The software we developed shows that our methods needs less running time and can makes better fitting consequence.
Research on safety helmet wearing YOLO-V3 detection technology improvement in mine environment
Authors: Fuchuan  , RongXin Wang
Published: November 2019

The existing AI object detection technology cannot meet the demand of safety helmet wearing detection accuracy in mine environment. This paper studies YOLO correlation algorithm, establishing an optimal model based on YOLO-V3, combines the deep residual network technology with the multi-scale convolution feature based on the YOLO-V3 detection algorithm, combines the multi-scale detection training and adjusts the loss function in the training process. The experimental results show that with satisfying the detection speed, safety helmet wearing detection accuracy in mine environment is significantly improved.
Intelligent Library System Based on RFID Technology
Authors: Zhou Donghua
Published: November 2019

Radio Frequency Identification (RFID) is a kind of automatic identification technology. It uses radio frequency to communicate two-way non-contact data, and uses radio frequency to read and write recording media (electronic tags or radio frequency cards) so as to achieve identification objectives and data transfer. It is considered as one of the most promising information technologies in the 21st century. In the field of Library management, it can improve the overall efficiency of libraries and reduce the cost of library management of mass books. In this way, libraries can put more funds and manpower into improving the quality of Library services.
Research on optimal control model of complex networks security risk
Authors: Li Jizhen , Ren Baofeng , Zhang Tiantian , Li Chaowei , Liu Zihao
Published: November 2019

To solve the problems such as the security risk control and the optimization of the complex networks, an optimal control model of complex networks security risk based on discrete glowworm swarm optimization with key strategy adjustment is proposed. The basic framework of this model is built based on four functional modules including detection and evaluation, strategy selection, control optimization and performance feedback. The optimal evaluation criterions of the security control strategy are constituted of factors such as control cost, benefit reward and negative effect. The discrete glowworm swarm optimization algorithm with key strategy ad-justment is proposed to search for the optimal control strategy of complex network security risk. The concept of control parameter is introduced, whose feedback and adjustment make the optimal control model get evolution-ary. Finally, the model and the algorithm are tested for network security risk optimal control in the Nearest-Neighbor coupled with network, Erdos-Renyi random graph network, Watts-Strogatz small world network and Ba-rabasi-Albert power law network, separately. The availability of the model and the superiority of the algorithm are validated and the effect of the change for the attack strategy to the security risk optimal control model is analyzed by simulations.
Detection of Android malicious applications based on APIs
Authors: Jiang Xu , Mao Baolei , Guan Jun
Published: November 2019

Machine learning technology is widely used to detect Android malware, among which the selection of features is particularly important. Compared with the permission applied, the APIs invoked by applications can better reflect the behavior of the application. Therefore, many researches choose APIs as the features of machine learning classification algorithm to detect Android malware. Generally, researchers simply select APIs as features, rather than focus on how to select features more beneficial for detection. This paper proposes an Android malware detection method based on APIs frequent pattern selection and use Relief and particle swarm optimization algorithm to jointly select feature subset for detection.
No-overflowing Magnification Scheme in Redundant CORDIC algorithm and its implementation in FPGA
Authors: Jing Zhang
Published: November 2019

In this paper, normalization and magnification methods to maintain the calculating accuracy of CORDIC algorithm for small amplitude inputs are discussed, especially the overflowing boundaries are analyzed through mathematical deduction and the correctness has been proven by simulation. Finally, the FPGA implementations of different methods are conducted, which shows that the proposed magnification factor chosen scheme has an effective reduction on hardware resources consumption compared with the conventional normalization method.
3D SOM Initialization Pattern Dictionary Algorithm Based on FCM Clustering
Authors: Dong Ruihua , Zhang Xueyan , Li Hongsong
Published: November 2019

Aiming at the problem that the three-dimensional SOM reconstruction effect of the traditional pattern dictionary initialization algorithm is sensitive to the input order of the pattern, a three-dimensional SOM initialization mode dictionary algorithm based on FCM clustering is proposed. Calculate the mean square error of the training vector set and use the FCM algorithm to aggregate the resulting mean square differences into three categories. The average values are arranged in ascending order, and a certain pattern is extracted in the training vector at the same interval to form an initial pattern dictionary. The experimental results show that the 3D SOM initialization mode dictionary algorithm based on FCM clustering reduces the search time, increases the source matching degree, and improves the overall performance of the 3D SOM algorithm.
A Survey of Surface Reconstruction Techniques for Line Structured Light Systems
Authors: Changwei Wang , Ruiyin Tang , Jing Zhang
Published: November 2019

Reverse engineering has been widely used in industrial production, and surface reconstruction technology is the most important part of reverse engineering. Line structure measurement is a non-contact surface measurement method with high precision, low destructiveness, high data acquisition efficiency and strong anti-interference. This paper focuses on the measurement principle of line structured light, system calibration, strip center extraction and point cloud data processing and surface reconstruction. Finally, the existing surface reconstruction techniques that are widely used are summarized.
Optimization of Dairy Distribution Path Based on Genetic Algorithm
Authors: Liu Haidong
Published: November 2019

The distribution of dairy products is a key factor affecting the distribution cost, delivery time and service level of dairy products. In order to improve the efficiency and reduce the costs, it is necessary to optimize the distribution path of the dairy products. In this paper, the distribution of a local dairy enterprise is taken as the research object. On the basis of analyzing the existing distribution path, the mathematical model of the distribution path is constructed, and the genetic algorithm is designed. Then the optimized distribution path is obtained through programming and solving by MATLAB. By comparing before and after optimization, it is found that after the optimization, the total distribution distance is shortened, and the transportation cost and fixed cost are reduced. In addition, the penalty cost is avoided. Therefore, a reasonable distribution path is of great significance for the enterprises to improve the efficiency, reduce the costs, shorten the delivery time and other indicators.
Research on the recognition technology of human relationship in face image based on deep learning
Authors: Cheng Yunli
Published: November 2019

Face images contain rich and complex information, and similar genes are directly expressed as facial resemblance. In this paper, based on the theoretical background of biology and aiming at the wider application of artificial intelligence in the field of face image analysis, deep learning based recognition of the kinship of people in face images is studied in depth.

Kinship recognition is a new and challenging research. In order to recognize the kinship between characters from face images, this paper defines a new correlation feature to represent the correlation between two characters. Based on the idea of multi-layer self-encoder to input and reconstruct the target, and combined with the powerful feature extraction ability of deep convolutional neural network, this paper designs a new deep convolutional self-coding neural network, and the correlation feature is the activation value of the deep hidden layer of this deep neural network. The deep convolutional self-coding neural network USES back propagation algorithm in a supervised way. With the deepening of the network hierarchy, the identity features of representative characters are extracted from face images step by step, and the identity features of a pair of characters are fused into the associated features that represent the relationship between them. Based on deep learning, the associated features extracted from face images can effectively identify a given character relationship.
An Effective Method for Dynamic Global Optimal Scheduling of RGV Based on Probability Function
Authors: Ge Xueren , Huang Heyaojing
Published: November 2019

In this study, an effective dynamic scheduling strategy based on quasi-global optimizing search method is designed to plan the working sequence of RGV. By using ‘0-1’ variable, the working state of CNC is simplified and the whole processing procedure could be simulated by Matlab. Also, probability function is applied to decide the scheduling sequences, thus avoiding local optimal solutions. Then, the dynamic global optimizing scheduling strategy is completed. Besides, the efficiency of the whole system is calculated and the corresponding results are compared with local optimizing scheduling. This dynamic scheduling strategy could improve the efficiency of the whole system during the processing materials.
Internal Model Controller Applied to LCL-type Grid-connected Inverters in Weak Grid
Authors: Wang Kai , Huang Jingtao , Zhang Shengguo , Li Yumei , Wu Fei
Published: November 2019

Power grid in remote areas may show the feature of weak grid with time-variable impedance. Robustness of control of grid connected inverter (GCI) to grid impedance is one of the key technologies. For grid connected inverters with voltage feed-forward and time delay, IMC (Internal Model Controller) is used so that the adaptability to the grid impedance is improved. Detailed IMC and its parameter design method are provided, theoretical analysis and simulation results verify that IMC has robustness of grid and LCL impedance.