bluuebunny/crossref_metadata_2025 huggingface dataset:
An Optimal Initial Foot Position for Quadruped Robots in Trot Gait
Authors: He Dongqing
Published: November 2020

Gait planning parameters are important for quadruped robots to walk stably. In this paper, application of inverted pendulum model is widdened and a new collision model of quadruped trotting between feet and the ground that can indicate body-attitude changes in walking is established. Influences of initial foot position, walking cyclic period and stride length on walking stability are discussed. The influence varies with different initial foot positons and we get the optimal initial foot position for the quadruped in trot gait with minimum variation in body attitude and maximum walking stability. Finally, we get the optimal initial foot position and walking cyclic period with minimal collision velocity. Simulation results are presented.
Hotspots Prediction Based on LSTM Neural Network for Cellular Networks
Authors: Zhou Lixia , Chen Xia , Dong Runsha , Yang Shan
Published: November 2020

The tremendous growth in data traffic usage is a prominent challenge to cellular network operators. The aggregation of a small number of users’ services may lead to considerably high loads on base stations, thus generating traffic hotspots in the networks. To provide better quality of service in dynamic network scenarios efficiently, it is necessary to accurately distinguish and predict potential hotspots, so as to adjust resource configuration and allocation in advance and keep the network running smoothly. In this paper, a network traffic hotspots prediction method is proposed based on the Long Short-Term Memory (LSTM) neural network framework. To verify its effectiveness, real-world data are utilized in our experiments. Numerical results demonstrate that a time series model based on the LSTM framework can achieve 92.2% success rate for future hotspots prediction.
A Hybrid Methodology Based on Machine Learning for a Supply Chain Optimization Problem
Authors: Duc Duy Nguyen , Nananukul Narameth
Published: November 2020

This paper presents an advanced methodology that integrates a machine learning methodology into an optimization process. The framework of an interactive machine learning algorithm was developed to meet the challenges in solving large-scale optimization problems. An artificial neural network (ANN) is used with the knowledge gained from solving previous problems with different scenarios to define a good starting point for a solution searching process. By using an initial solution, known as “warm start”, the search space can be reduced to get more opportunity to find an optimal solution. The applicability of the proposed method was evaluated by using it to determine the optimal facility locations for a biomass supply chain problem using a real case study from Central Vietnam. The supply chain planning model is based on an optimization model, where the goal is to maximize the benefits from meeting the electricity demand minus the total cost from facility cost, penalty cost from lost demand, and operational costs form the supply chain. The structure of the ANN, the number of intermediate layers and the number of processing nodes, was determined by comparing the accuracy from different configurations. The ANN with two intermediate layers possesses the best performance from the training and testing datasets. The proposed model succeeded in predicting the facility location with more than 98% prediction accuracy. The results from our framework provide optimal solutions while saving runtime.
Recognition of Spam Messages Based on Text Mining
Authors: Fang Yajie , Zhang Ping
Published: November 2020

With the rapid development of science and technology, the application of artificial intelligence technology is becoming more and more extensive. The maturity of artificial intelligence technology is inseparable from big data and machine learning. Big data is the foundation of artificial intelligence, while machine learning is the core. To mine the value hidden in big data, in order to achieve text classification, data prediction, and provide strategic decision basis, we need the power of Machine Learning. This article will introduce the classic algorithm in machine learning, Naive Bayes, KNN nearest neighbor, and support vector machine algorithm, and apply them to text mining of spam text sets. It shows that Machine Learning is the fundamental way to make machines as intelligent as humans.
Analysis of High-Speed Railway Passenger’s Travel Choice Behavior Based on Deep Learning Model
Authors: Wang Shujie , He Zhenhuan
Published: November 2020

The analysis of railway passengers’ travel choice behavior plays an import role in railway passenger product design and transport organization. Many researchers focued on it and lots of models and methods had been proposed. With the rapid development of information technology in recent years, deep learning models are more and more widely used in many research fields, and also applied in this research. Based on the OD train ticket data of Beijing-Shanghai high-speed railway line, it studied travel choice behavior of passengers in Beijing-Shanghai high-speed railway line during the weekday, and then took attributes of ticket data (arrive-departure station, arrival-departure time, etc.) as the mapping features to study passengers’ choice of different trains, The result shows that the method given by the research has quite high fitting accuracy.
Unsupervised/Supervised Hybrid Deep Learning Framework for Low Dose Phase Contrast Imaging
Authors: Zhu Guogang , Fu Jian , Zhao Feng
Published: November 2020

X-ray phase contrast computed tomography (PCCT) has better imaging quality than conventional attenuation X-ray CT and has demonstrated promising application prospects in medical diagnosis. However, reducing the radiation dose during PCCT imaging still remains a major challenge. Recently, deep learning (DL) techniques have been applied to low dose CT and obtain significant progress. Most of them require massive paired images to train the network in a supervised manner, which may hamper their practical applications because the ground-truth images are hard to be obtained in most cases. To address this issue, we report a hybrid deep learning framework for low dose PCCT which capsules unsupervised and supervised learning manners. It combines the advantages of convolutional neural network (CNN) and total variation (TV) and is suitable for both unlabelled datasets and labelled datasets. This framework has been validated and demonstrated with experimental data. It will be helpful to push the practical application of low dose PCCT.
Cross Border Integration of Art Design and Artificial Intelligence
Authors: Li Shuo
Published: November 2020

Artificial intelligence technology has made remarkable achievements in driverless, security, smart city, image recognition, natural language processing, etc. Artificial intelligence is compared with human brain; these applications are all in pursuit of higher, faster, stronger and more accurate “left brain” category. To achieve human-computer cooperation, it is necessary to extend the right brain of artificial intelligence with sense of space, image, imagination and creativity, so as to make the machine more friendly and warm. AI is a system with intelligent decision as its core. AI thinking is a way of thinking to improve efficiency and human life through the application of artificial intelligence technology.
The Trend and Characteristic of AI in Art Design
Authors: Li Shuo
Published: November 2020

The future development trend of AI includes chat robot, knowledge extraction and calculation, AR enhancement, human-computer cooperation, automation and intelligent app platform. These trends will have a profound impact on art design, especially in the efficiency and aesthetic aspects of design, not only has the trend of replacing ordinary designers, but also is more likely to gradually have aesthetic awareness and thinking. These new changes will be combined with big data analysis and logical operation, sample learning and independent learning, and artificial intelligence will have greater development in the field of art design. The machine understands the data structure of the design. There are some related researches in the industry: parametric design and computational design.
Research on Location Selection of UAV Distribution Center Based on Improved Gravity Method
Authors: Zhang Zhao , Zhang Zhiguo , Chen Xue
Published: November 2020

In order to speed up logistics distribution efficiency and reduce distribution costs, logistics companies around the world began to use drones for related distribution work. In addition to upgrading the hardware technology of UAV, optimizing the distribution path is also one of the ways to reduce the distribution cost of UAV distribution center. In this paper, the location of UAV distribution center will be studied theoretically based on the economic optimization and equipment maintenance optimization. Finally, the feasibility of the algorithm is verified by simple simulation application.
Satellite Communication System adopts OFDM-MIMO Technology with High Speed Connectivity
Authors: Tian Dong , Xu Rujun , Ma Aili , Chai Yuan , Yang Tong
Published: November 2020

The space communication development has strong urgent requirement for technology upgrading and evolution. The satellite communication capacity can be advanced by the application of higher data transmission efficiency. It will be contented with diversified High Throughput Satellite (HTS) communication application requirements. A satellite communication system architecture design featured by higher transmission efficiency using Multi-Input & Multi-Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) technology which has been wildly used in next generation of terrestrial wireless communications has been presented. It is proposed to solving problems on multiplexing data transmission, receiving signal’s anti-interference, and supporting various multi-user terminals. The throughput and application analysis was done to evaluate system performance in terms of diverse HTSs. A comprehensive evaluation and simulation analysis of space communication application efficiency are carried out to verify the feasibility of basic space application under the diverse simulation conditions. The total throughput of the communication system can reach up to 259Gbps as extremely high speed connectivity, and the maximum spectrum efficiency is close to the ultimate performance of 100bits/s/Hz.
A Pricing Mechanism Which Implements Allocation in Shannon Formula of Home Cellular Wireless Communication
Authors: Wang Zekun , Zhang Fuxi
Published: November 2020

According to the requirements of resource management and interference suppression in-home cellular Wireless Communication, take the ratio of effective capacity to power consumption as the optimization objective, the Shannon formula was taken into account. A pricing mechanism that implements a rate allocation in Nash Equilibrium point in unicast provisioning was presented. The operation mechanism of this mechanism is described in detail, compared with previous similar mechanisms, the mechanism more able to meet the actual needs of communication.
Research on Power Consumption Information Acquisition System Based on Broadband Power Line Carrier Technology
Authors: Gu Jie , Guo Ronghui
Published: November 2020

At present, the broadband power line carrier communication technology is developing continuously. It has the advantages of improving the real-time, stability and reliability of acquisition, and it can carry out unified comprehensive management of the distribution power communication network, so it has a more extensive application prospect. This paper analyzes and compares the mainstream communication technologies of the current power consumption information acquisition system, discusses the advantages and disadvantages of various communication technologies, and discusses and analyzes the application prospect of broadband power line carrier communication technology.
Effects of Malware Attacks on the Cascading Failure of Cyber-physical Power System
Authors: Shen Meie , Gao Xingle , Peng Minfang
Published: November 2020

In this paper, a stochastic cascading failure model considering the structure and operation of cyber-physical power system is proposed. The model takes into account the community structure and the heterogeneity of networks as well as the complex interdependence of coupling networks. Moreover, the malware spreading in the cyber network and the power flow redistribution in the power grid are considered to describe the dynamic operational characteristics of the system, and a stochastic method is adopted to describe the operating state transition of network components. In addition, the effects of community structure strength and immunization strategy on the cascading failure of coupled system are studied. The results show that the cascading failure of coupled system is the result of malware attacks repeatedly triggering the power grid. Results also suggest increasing the community structure strength of cyber network helps to suppress the impact of cyber-attacks on the coupled system, and community bridge immunization is the optimal immunization strategy for inhibiting failure propagation in the modular interdependent network.
THz Pseudo-Bessel Beam Generation Base on Axicon-frustum Antenna Array
Authors: Huang Han , Zeng Yongxi , Zhang Weiyu , Yu Yanzhong
Published: November 2020

An axicon-frustum antenna array was designed. Circular microstrip antenna with coaxial feeding was taken as an element to place on concentric rings at equal intervals, constructing a phased axicon-frustum antenna array, which were then simulated and optimized by Ansoft HFSS. The results showed this antenna array can not only radiate a 0-order narrow beam with stable gain, but also generate a high-order radiation pattern with orbital angular momentum, which was demonstrated as an axicon-frustum antenna array which can generate pseudo-Bessel beams.
Robust Power Allocation for Multi-Homing Heterogeneous Networks with Energy Harvesting
Authors: Hossain MD Tanim , Xu Yongjun , Yang Yang , Gu Bowen , Li Guoquan
Published: November 2020

To improve user’s data rate and network coverage, multi-homing heterogeneous network has been considered as a key technology in recent years. However, traditional power allocation schemes cannot provide good robustness and suppress the impact of parameter perturbation due to the random interference and channel delays. A robust power allocation algorithm is proposed for an orthogonal frequency division multiple access based multi-homing heterogeneous network under energy harvesting. Considering the channel uncertainties from base stations to users, the total data rate of all mobile terminals (MTs) is maximized under the rate outage constraint of MT. Based on the uniform distribution of uncertainty, the originally robust counterpart problem is transformed to a deterministic and convex one. The Lagrange dual decomposition theory is used to solve it. Simulation results demonstrate that the proposed scheme has good convergence and robustness.
Research on the Blended Teaching Practice Based on the Ketangpai Network Teaching Cloud Platform
Authors: Zhu Yangqing
Published: November 2020

The Ketangpai cloud teaching platform gives full play to the ability of teachers and students to carry out teaching design, and can fully manage all teaching activities before, during and after class. It is a very practical and effective blended teaching tool. Taking the course “Application of Excel in business” as an example, the blended teaching practice and blended teaching investigation evaluation were carried out by using the Ketangpai cloud teaching platform. Through the exploration and practice of this blended teaching, the ability of Excel data processing and business management of students were effectively improved, the ability of students’ autonomous learning, cooperative learning and inquiry learning were cultivated, enhanced the spirit of students’ diligent study, self-discipline, overcoming difficulties, being willing to help others and striving for perfection, realized the transformation of students from shallow learning to deep learning. It fully verified the positive role of Ketangpai cloud teaching platform in blended teaching.
The Investigation of the Improvement of Agricultural Product Uplink Based on Rural E-commerce
Authors: Chen Zhaohan , Shi Li
Published: November 2020

Agricultural product uplink(APU) refers to selling agricultural products produced in rural areas from the place of origin to various regions across the country with the help of advanced Internet technology, so that the agricultural and information technologies can be organically combined to achieve the sales of agricultural products on the Internet platform. APU can promote the integrated development of urban and rural areas in our country, thereby helping the country to head towards common prosperity. However, China’ s APU is difficult to be effectively carried out across the country.

Therefore, this paper hopes to do some deep researches through this issue, gathering some information about rural E-commerce at home and abroad and pointing out that there are still some problems. Based on this, putting forward the corresponding solutions in order to create a complete system of theory further to help guide to raising people’s consciousness and ability on APU.

The results show that there are indeed great obstacles during the development and implementation of APU, such as the failure to achieve the standardization and branding of agricultural products, as well as the shortage of talents. Nowadays China should do a good job in improving the quality of agricultural products, building characteristic brands, and vigorously cultivating rural E-commerce talents to promote the development of agricultural products. It is still a long way to go for APU to achieve significant results.
Application Research of Virtual Reality Technology
Authors: Ma Xueliang
Published: November 2020

Virtual reality technology is an important subject in the 21st century, as well as one of the important technologies affecting people’s lives. The characteristic of the latest technology in the field of computer is to create a virtual environment for users in an imitative way, and to make users feel immersed in the virtual environment through perceptual behaviors such as seeing, hearing and touching, and interact with the virtual environment to cause real-time changes of the virtual environment. Virtual reality technology integrates computer graphics technology, multimedia technology, human-computer interaction technology, network technology, three-dimensional display technology and simulation technology, and it is the latest technology in the field of computer science and technology that has been developed comprehensively. It is also the comprehensive application of mechanics, mathematics, optics, mechanism kinematics and other disciplines. This paper fully discusses the research status of virtual reality technology at home and abroad, and forecasts the development trend of virtual reality.
Design of Intelligent Multi-layer Three-dimensional Bicycle Parking Garage
Authors: Wang Chenglin , Jia Ye , Zhao Lijun , Guo Pengyuan
Published: November 2020

Along with the comprehensive construction of resource-saving, environment-friendly, low-carbon response to the call for green environmental protection. In view of the difficulties of bicycle parking, waste of public land resources and easy to lose, a new scheme of bicycle parking garage is designed. An automatic bicycle access system based on Arduino control chip is designed, including pneumatic and circuit control. Pneumatic control is used to grasp the bicycle manipulator; external circuit is used to process the input and output signals; AC and stepping motor are used to realize the lifting and horizontal movement of bicycle transportation. UG software is used to model, simulate and analyse the bicycle garage; Arduino software is used to write the control and management program of the automatic bicycle garage to realize the automatic access, record and safety protection functions of the bicycle. Through the establishment of the actual bicycle garage model, the feasibility of the design is verified; it has the advantages of convenient use, fast access to the car, high security, and high space utilization rate; it greatly saves the public land resources and facilitates people’s travel. Foreword: in recent years, people’s awareness of environmental protection has been strengthened, and the slogan of energy conservation and emission reduction has been put forward, and gradually a large number of shared bicycles have emerged. The use of bicycles is on the rise, which also leads to the difficulty of access to bicycles. The storage area covers a large area and is easy to be damaged and lost outdoors. In order to solve these problems and realize the concept of building an environment-friendly and smart city, the bicycle parking garage combines the intelligent system, and various intelligent parking garages emerge as the times require.
Leak Source Beam-forming Location of Spacecraft in Orbit Based on Dispersion Characteristics of Lamb Wave
Authors: Qi Lei , Feng Yaoqi , Sun Lichen , Li Xi , Liao Tao , Zhang Yu , Rui Xiaobo
Published: November 2020

In recent years, the number of space debris is increasing rapidly, threatening the safety of spacecraft. More and more spacecraft are at risk of colliding with space debris, which may cause air leakages on the sealed container of spacecraft. This is a huge danger for spacecraft and astronauts. In this paper, a leak source location method based on beam-forming and dispersion characteristics of Lamb wave is proposed. The ‘L’ shaped sensor array with 8 acoustic emission sensors is used to collect the Lamb waves. Due to the dispersion characteristics, a 10 kHz narrow band pass filter is used firstly to process the signals. And then with a priori knowledge of guided-mode frequency dispersion curves of Lamb waves, the corresponding propagation speeds of waves are determined to obtain the time delay matrixes. By the delay-and-sum beam-forming algorithm, the leak source can be directed. The experiment result shows that the accuracy rate of the leak location is more than 90% evaluated by location error less than 5°.
Study on Flow Interference of Multi-group Parallel Jets between Heat Transfer Tubes
Authors: Wu Weirang , Tao Yuchun , Yu Tong , Yang Xunzong , Ye Chun
Published: November 2020

In order to find an approach to optimize the hydraulic cleaning equipment of steam generator secondary side of CPR1000 reactor, the Computational Fluid Dynamics (CFD) method was used to simulate the flow of multiple groups of parallel jets. In this simulation, the RNG k-ε turbulence model and the gas-liquid two-phase flow model is employed to distribute the jet flow between heat transfer tubes. The results show that with the increase of the jet angle, the pressure aggregation on the tube sheet decreases obviously, which is caused by the deflection force due to the pressure difference between the two sides of the jet. With the jets distance increasing, the interaction between jets decreases obviously. When the distance is up to more than nine times of tube spacing, the force that causes deflection of the jet will almost disappear. With this distance, the jets can maintain a good linearity and obtain a satisfied cleaning effect on the heat transfer tubes.
E-commerce Item Identification Based on Improved SqueezeNet
Authors: Fan Kai , Niu Lianqiang , Zhang Shengnan
Published: November 2020

In order to improve the recognition rate of product images in e-commerce recommendation scenes, we proposed a high-performance improved SqueezeNet convolutional neural network, which uses a Fire Module structure containing two large convolution kernels to reduce the complexity of the model while fully extracting features, and adding a pooling layer behind each Fire Module to effectively filter key features of the classification. Experiments show that the algorithm in this paper has a better application in image recognition in e-commerce scenes, and the recognition accuracy is improved by 1%.
Optimization and Comparison of Photovoltaic MPPT
Authors: Zhao Anlei , Zhu Rui , Wang Guangchao
Published: November 2020

Maximum Power Point Tracking (MPPT), as the contral core of the output power of photovoltaic power generation system, is extremely crucial to the entire photovoltaic power generation system. In this paper, a number of common MPPT control methods are analyzed in comparison, and the traditional conductance increment method is improved as well. By means of comparative analysis in the simulation software MATLAB/Simulink, it turns out that the improved conductance increment method excels the traditional method with regards to optimization speed and stability.
Electric Performance Model and Finite Element Analysis of Fuzz Button
Authors: Zhang Zuozhen , Zhang Hengwen , Wang Baoyou , Zhang Lei , Zhu Ming , Yang Fan , Li Jinteng
Published: November 2020

This article focuses on the electrical properties of the Fuzz buttons, determines the relevant parameters that reflect the electrical properties of the Fuzz buttons at work, and establishes three electrical models of Fuzz buttons based on the actual shape and manufacturing process of the Fuzz buttons. Using HFSS software to analyze the electrical performance of the Fuzz button, various curves of the electrical performance parameters of the Fuzz button following the frequency change are obtained. By comparing with the electrical performance data measured by the Fuzz button laboratory, the accuracy of electrical performance parameters are analyzed under three models, so that providing a basis for the establishment of a more accurate electrical performance model of the Fuzz button.
Research on Micro-arc Oxidation Power Supply with High and Low Frequency Coupled Pulse
Authors: Guo Yupeng , Zhu Hailei , Ma Daqiang , Yang He , Lu Xiaofeng
Published: November 2020

A novel micro-arc oxidation power supply with high and low frequency coupled pulse was presented, which was proposed to improve the performance of the fabricated ceramic coatings. The micro-arc oxidation power supply was composed of the human machine interface, the main control board, the three-phase SCR driving circuit, the main circuit power device and the cooling system. The inputting of parameters and the monitoring of power supply process were realized by HMI. The ARM of main control board was communicated via USB to RS232. The voltage regulating part of the main circuit was driven by three-phase SCR to adjust the voltage value during the micro-arc oxidation process. The load test shows that the power supply was realized the output of coupled pulse, and the coatings was smooth which prepared by coupled pulse.
The Effect of Dust Size Distribution on the Propagation of Electromagnetic Waves in a Weakly Ionized Dusty Plasma
Authors: Zhang Jie , Yan Shaohui , Zhao Shanchao , Zhang Guodong , Duan Wenshan
Published: November 2020

The propagation characteristics of electromagnetic (EM) waves in dusty plasma of rocket exhaust are studied. Usually, the dust sizes are different in a general dusty plasma. However, most previous studies have focused on the mono-sized dusty plasma. The influence of dust size distribution on the EM wave attenuation of dusty plasmas has been investigated. The dependence of the EM wave attenuation on the electron density of dusty plasmas, the neutral gas density and the EM wave frequency are obtained and discussed. The results illustrate that the EM wave attenuation constant has a maximum value when the electron-neutral particles collision frequency is close to the EM wave frequency. The EM wave attenuation constant increase with the increase of electron density and dust particles density. Moreover, the EM wave attenuation constant decreases as the dust size decrease for mono-sized dust particles. It indicates that the attenuation of the EM wave is mainly determined by the largest dust particles. Finally, we conclude that the larger the dust particle, the stronger the attenuation to the EM wave.
Parameter Identification of Generator Excitation System Based on Improved Grey Wolf Optimization
Authors: Liu Hengming , Cao Lu
Published: November 2020

In order to ensure the accuracy of power system modelling and the reliability of safety and stability analysis, it is important to confirm the true parameters of the excitation system. This paper proposes that using hunting group division strategy and convergence factor non-linear decreasing strategy to improve the standard grey wolf optimization algorithm, and applied it to the identification of the generator excitation system. The simulation results show that the identification of the excitation system based on the improved grey wolf optimization algorithm has higher identification accuracy and stability, which provides an effective new method for the parameter identification of the nonlinear.
Fault Prediction of Electromagnetic Brake Based on AINN and Grey MGM(1,n) Model
Authors: Li Shoujun , Li Guangyu , Wang Zhiming
Published: November 2020

In order to predict the possible fault points of electromagnetic brake, a novel combined diagnosis model based on multivariable grey prediction model MGM(1,n) and adaptive integrated neural network (AINN) was proposed in this paper. MGM(1,n) model was used to predict the development trend of multiple groups of fault feature factors. Then by Fuzzy C-mean (FCM) algorithm, cluster analysis on the predicted results from MGM(1,1) was performed, and in turn, clustering results feed into of AINN to predict and identify fault features. To verify the performance of the combined model, a case of electronic brake fault diagnosis is given, and the model analysis consisting of 8 possible faults is carried out, finding that the proposed combined model has better fault identification capacity with better convergence and less error, showing stronger promotional practical value.
Robust Controller for Permanent Magnet Linear Motor Based on Interval Matrix Theory
Authors: Sun Haijun , Li Xiaohong
Published: November 2020

Parameter perturbation, end effect and external interference of AC permanent magnet linear motor affect the accuracy and performance of servo system. In this paper, the PMLSM servo system controller designed by the interval matrix theory is used to solve this problem. The uncertainty of servo system is described by interval matrix. Compared with the precise mathematical model, the controller designed by this theory has strong robustness. The simulation and experiment of the system show that the strategy has excellent dynamic and static performance, it has strong parameter robustness.
Research on the Layout and Data Processing Method of Distributed Optical Fiber in Shield Tunnel Monitoring
Authors: Li Yujie , Li Qiang , Shen Wenyong , Meng Lei
Published: November 2020

With the increase of subway service time, shield tunnels will produce different degrees of damage and destruction. This is related to external factors such as differences in stratum soil, groundwater seepage, construction disturbance to soil, and operating vehicle load. With the increase of subway service time, shield tunnels will produce different degrees of damage and destruction. This is related to external factors such as differences in stratum soil, groundwater seepage, construction disturbance to soil, and operating vehicle load. In order to ensure the operation safety of the subway, long-term and large-scale safety condition monitoring of the shield tunnel is very important. This study summarizes the technical characteristics, layout methods, data collection and processing of distributed optical fiber in shield tunnel deformation monitoring. The feasibility of distributed optical fiber monitoring technology is verified through the segmental deformation monitoring project of Beijing Metro Airport Line and Line 10 shield tunnel. In addition, some experiences in fiber layout and data processing are summarized, which has reference value for similar projects.
Real-time Monitoring Mechanism of Underwater WSN
Authors: Guo Dongjiao , Liu Yanping , Qiu Bo , Xiang Guanjie , Li Mengci
Published: November 2020

Sensor node energy is the key to the long life cycle of a sensor network. This paper considers the correlation of sensor nodes in continuous time on-chip data transfer, and compares the derivative-based prediction, polynomial regression, back propagation and convolutional neural networks prediction algorithms for data transfer and energy consumption minimization. Experimental results show that convolutional neural networks are the optimal control solution.
Stellar Spectral Classification with 2D Spectrum and Fully Connected Neural Network
Authors: Lu Yakun , Qiu Bo , Xiang Guanjie , Li Mengci , He Zhendong
Published: November 2020

It is one of the basic tasks to realize the automatic classification of celestial spectrum. This paper presents a method of star classification based on two-dimensional spectral data. The data used in the experiment are two-dimensional spectral data of LAMOST DR6 from the National Astronomical Observatory. There are about 2000 two-dimensional spectral data in total to use to classify F, G and G, K stars spectra. By observing a large number of two-dimensional data of stars, different region data are selected as input data according to the stars. Then the data are normalized and put into the full connection neural network for training. The whole neural network consists of one input layer, nine hidden layers and one output layer. Each hidden layer is activated by rule function, and the output layer is activated by softmax function. Experiments show that the accuracy of classification is 80% by classifying the two-dimensional spectra of F, G and G, K. It shows that the two-dimensional characteristics of the spectrum can effectively classify the spectrum.
A Routing Protocol Based on CP Neural Network for Vehicular Ad Hoc Networks
Authors: Wen Wei
Published: November 2020

It is important to design efficient routing protocols based on link connectivity and the selection of optimal link forwarding data in vehicular ad hoc networks (VANET). We propose A routing protocol based on counter propagation (CP) neural network for Vehicular Ad Hoc Networks (CP-GPSR), which is to take into account the connectivity probability of the link, adopts a routing method based on data packets forwarded at intersections. The priority of the next segment is classified by the CP neural network, vehicle select the next segment of highest priority for data forwarding at the intersection. The simulation results show that CP-GPSR has a high packet delivery rate, the control overhead is lower.
Respiratory Motion Prediction with Random Vector Functional Link (RVFL) Based Neural Networks
Authors: Rasheed Asad , Adebisi A.T. , Veluvolu Kalyana C.
Published: November 2020

Respiratory motion exhibits non-linear and non-stationary behavior in nature and this has been a great hindrance to the accurate prediction of tumor in motion adaptive radiotherapy. Accurate prediction of respiratory motion and subsequent tracking of tumor has been a challenge due to the irregularities and intra-trace variabilities. In order to overcome this issue, prediction models can be trained by using neural networks. However due to the burden of large training data, computational efficacy of existing neural networks can be affected. Moreover, training of neural networks using conventional methods like back-propagation (BP) may result in local minima and it may slow down the learning rate and convergence respectively. As a solution, in this paper, we employed random vector function link (RVFL) based neural networks to train the model in a very efficient way to achieve high accuracy in respiratory motion prediction. In RVFL, the direct link from input features to output layer acts as regularization to prevent the network from overfitting. The proposed method is tested with real respiratory motion traces acquired from 31 patients. Results show that RVFL with the use of direct link performs quite better than without direct link.
Visual Positioning Algorithm Based on Micro Assembly Line
Authors: Ni Quandong , Li Dazhai , Chen Yun , Dai Haiyang
Published: November 2020

To achieve mass production of microelectronic devices, this paper designs a microelectronic device detection scheme based on monocular vision, on the assembly robot platform of micro-electronic devices. By analyzing the principle of camera calibration and distortion and performing internal parameter calibration of the camera with Zhang Zhengyou calibration method, this paper establishes a hand-eye calibration model of the relationship between the robot’s motion and the relative position of the camera, so as to calculate the transformation matrix from the camera model to the gripper. In the end, the paper proposes an accurate positioning method which combined boundary tracking algorithm based on binary image and template matching algorithm, identifying the type of workpieces through barcode.
Image-based Deflection Measurement and Error Analysis
Authors: Hu Bingyi , Gao Weihe , Yan Cuiping , Ni Yongjun , Li Chenqian
Published: November 2020

This paper gives an image-based and computerized solution to the deflection measurement of bridges with its corresponding design scheme of measuring devices. A laser transmitter is fixed on one end of the bridge. A dark cartridge with an optical screen and a camera is installed in the middle of the bridge. Light beam projects onto the optical screen, while the camera captures the image on the screen. Bridge deflection is measured by applying image-processing algorithms and then performing the related computation. The systematic error caused by tilting film and geometric distortion is analysed and eliminated. One of the advantages is that, this low-cost measuring scheme obtains direct deflection data and requires simple operations comparing with existing methods. Other advantages and disadvantages are also highlighted.
A Novel Channel Amplitude and Phase Correction Algorithm Based on Phased Array Space-based TT&C Communication
Authors: Yang Yanqiu , Zhao Yi , Chen Zhanfeng , Deng Xi , Wei Lili
Published: November 2020

According to the characteristics of phased array space-based TT&C satellite antenna aperture size and transponder power limitation, this paper proposes a correction algorithm based on PN code and BPSK without data modulation. At the same time, combined with multi-period coherent accumulation, the channel amplitude and phase correction accuracy is guaranteed under low signal-to-noise ratio. From the simulation test, we can see that our method has the characteristics of low interception and anti-barrage jamming.
The Calculation of Thermal Temperature of Specified Radar Based on Domain Decomposition Method
Authors: Fan Hui , Zhang Yang , Li Yi , Liu Youming , Zhang Haibo , Li Tingjun
Published: November 2020

Approached the method of Domain Decomposition Method calculating specified radar’s thermal temperature. Used Domain Decomposition Method to analyze the specified radar, changed the complex geometric object to simple one, which simplified the calculation procedure. Through the calculation of practical, we calculated the radar’s thermal temperature when solar horizon and vertical incidence. The thermal temperatures of radar in two conditions are all agreed to physical circumstances, which indicated this method is valid. Keywords: Radar; Domain Decomposition Method; IR; Thermal temperature.
Design of Wireless Communication System in Mine
Authors: Liu Gaiye , Chen Peng
Published: November 2020

In order to improve the control efficiency of large equipment such as scraper, transporter and crusher, and reduction in personnel, increased security factor, based on PLC automatic control and wireless interconnection technology, a mine wireless communication system including wireless control host, wireless handheld and wireless relay substation is developed. The system carried out industrial experiments on the mining face in coal mine. The test results show that the system is easy to install and maintain, the equipment is stable, the wireless signal covers no blind areas, the call is clear, the data transmission is reliable, and the wireless remote control of the large equipment is achieved.
A Method of Network Security Risk Measurement Based on Improved D-S Evidence Theory
Authors: Zhao Xiaolin , Pei Mingzhe , Wu Meijing , Liang Yaoyuan , Peng Hui
Published: November 2020

This paper applies Dempster-Shafer (D-S) evidence theory to network security measurement and assessment, which improved the accuracy of network security measurement results. The main contents include improving the composition rules to solve the paradox, establishing a security measurement model, and proving the rationality of the improved method by three Distributed Denial of Service (DDoS) attacks experiment. The results show that this method is more accurate in detecting traffic attacks.
Research on Temperature Rise Performance of EV Charging Coupler
Authors: Wei Qianqian , Chen He , Wang Jiaojiao , Li Xiao
Published: November 2020

In order to orrectly evaluate the temperature rise performance for Electric Vehicle charging Coupler more reasonably, this paper analyzed the factors affecting the temperature rise performance, compared the existing standards and regulations.The test and verification activities were carried out from two aspects of temperature rise evaluation method and complex environment adaptability, and a more rigorous temperature rise evaluation method was proposed
Micropumps for Microfluidic Devices and BioMEMS
Authors: Huo Cheng , Bai Chenlin , Zhang Peiyu
Published: November 2020

The development of micropumps are reviewed and their applications are summarized. The micropumps are categorized into indirectly-driven and directly-driven micropumps according to the ways of driven origination from working principles. The actuation principles are introduced in detail including electrostatic, piezoelectric, thermopneumatic actuation, etc. Moreover, the performance influencing parameters on the property and the applications of various micropumps for medical therapy are described such as reciprocating, peristaltic, rotary, electrohydrodynamic, micropumps, etc. The challenge of micropumps is also discussed.
Temperature Field Distribution Model in Drilling of CFRP/Ti Stacks Structure
Authors: Li Jian , Zou Peng , Qiao Cheng , Dong Li
Published: November 2020

CFRP and Ti alloy, which have several excellent properties, are widely used in the field of aircraft manufacturing. CFRP/Ti stacks is one kind of common structure in aircraft assembly process. Drilling is one of the key processes to assemble such structure. Heat concentrated and high drilling temperature may happen during drilling CFRP/Ti stacks due to their low thermal conductivity, and it may lead to hole damages. The paper gets the heat flux to workpiece through analyzing the heat source during drilling CFRP/Ti stacks, base on which a model to predict the drilling temperature field during drilling CFRP/Ti stacks is established by the Fourier’s law. The drilling temperature field is calculated by the finite difference method, and the experiment of drilling CFRP/Ti stacks is carried out. The analytical result agrees well with experimental data. The model can be used to predict the temperature field of stacks drilling process.
Experiment of Thermal Conductivity of Coal-fired Boiler Ash
Authors: Wu Jialing , Liu Yi , Cheng Rui , Zhang Xiaofei , He Qing
Published: November 2020

In order to study the problem of ash deposition and slagging on the heating surface of coal-fired boiler, the ash specimens with different thickness are prepared in this paper, and the unsteady state method is used to test the thermal conductivity of the ash. The results show that the average thermal conductivity of the ash specimen is 0.3114W/(m·K), and the thermal conductivity of the ash does not change with the thickness. This paper provides important parameters for the study of heat transfer of boiler heating surface.
On the Problem of Pursuit of the Fractional Order in a Dynamic System with Nonlinear Controls
Authors: Mamatov Mashrabjon , Alimov Xakimjon
Published: November 2020

This article discusses the problem of expanding the results for fractional differential games and optimal control systems. Fractional order management allows ensuring the quality and safety of products, environmental process control. Solving the pursuit problem, we rely on the Pontryagin methods developed for linear differential games of entire orders, and we obtain new sufficient conditions for solving the pursuit problem.
Construction and Practice of Public Service Platform Based on Trusted Blockchain
Authors: Xuan Jiaxing , Shi Xin , Sun Xuyang
Published: November 2020

In recent years, the digital economy has experienced the era of digital economy 1.0, the era of all-round electronization brought about by the rise of personal computers, and the era of 2.0, the era of all-round data brought about by the popularity of the Internet and mobile Internet, and entered the era of 3.0, the era of “digital right economy”. In the era of digital rights economy, all aspects of social and economic life will create new ecology and models. Digital identity and digital governance, digital asset transaction circulation, digital payment and settlement, and digital industry integration constitute the core sector of digital rights economic development. Blockchains has become the preferred model for establishing digital identity and governance due to its characteristics of multi-party co-governance, distributed storage, transparent rules, and permanent and true data persistence. This paper proposes to solve the problem of economic governance derived from the era of digital economy by building a blockchain service platform. The main achievements of this paper are to create new business models, actively explore the deepening application of blockchain technology in the field of energy and power, break through data barriers, activate data value, develop digital economy, and promote data fusion and data resource integration in the field of energy and power.
Higher-order Approximations of Nonlinear Oscillator with Coordinate-dependent Mass
Authors: Guo Zhongjin , Sun Dan
Published: November 2020

This paper analyses a nonlinear oscillator with coordinate-dependent mass based on the presented methods of multi-term harmonic balance (MHB) and iterative residue harmonic balance (IRHB). The proposed methods calculate higher-order approximations. After using the MHB, a group of complicated nonlinear algebraic equations are obtained which are cumbersome to calculate analytically. This limitation is overcome in the presented other method by using the IRHB. In the solution procedure of IRHB method, the higher-order approximations to angular frequencies and periodic responses can be determined due to linear residue equations. Results show that the presented solutions give high accuracy and better results than those obtained by other existing ones from the homotopy perturbation method and the frequency-amplitude formulation. The advantage of the IRHB method is that it balances the all residues step by step and the present second-order approximations almost coincide with the corresponding exact solutions. Thus, the presented IRHB method could be applied to other strongly nonlinear oscillator systems.