bluuebunny/crossref_metadata_2025 huggingface dataset:
Hierarchical simultaneous entanglement swapping for multi-hop quantum communication based on multi-particle entangled states*
Authors: Yang Guang , Xing Lei , Nie Min , Liu Yuan-Hua , Zhang Mei-Ling
Published: December 2020

Entanglement swapping is a key technology for multi-hop communication based on entanglement in quantum networks. However, the end-to-end delay of the traditional sequential entanglement swapping (SEQES) grows rapidly with the increase of network scale. To solve this problem, we first propose a low-delay multi-particle simultaneous entanglement swapping (SES) scheme to establish the remote four-particle Greenberger–Horne–Zeilinger (GHZ) channel states for the bidirectional teleportation of three-particle GHZ states, in which the intermediate nodes perform Bell state measurements, send the measurement results and the Bell state type to the user node Bob (or Alice) through classical channel simultaneously. Bob (or Alice) only needs to carry out a proper unitary operation according to the information he (or she) has received. Further, we put forward a hierarchical simultaneous entanglement swapping (HSES) scheme to reduce the classical information transmission cost, which is composed of level-1 SES and level-2 SES (schemes). The former is an inner segment SES, and the latter is an inter segments SES. Theoretical analysis and simulation results show the HSES can obtain the optimal performance tradeoff between end-to-end delay and classical cost.
Optical polarization characteristics for AlGaN-based light-emitting diodes with AlGaN multilayer structure as well layer*
Authors: Xue Lu , Li Yi , Ge Mei , Wang Mei-Yu , Zhu You-Hua
Published: December 2020

The optical properties of AlGaN-based quantum well (QW) structure with two coupled thin well layers are investigated by the six-by-six
K
–
P
method. Compared with the conventional structure, the new structure, especially the one with lower Al-content in the barrier layer, can enhance the TE-/TM-polarized total spontaneous emission rate due to the strong quantum confinement and wide recombination region. For the conventional QW structure, the reduction of well thickness can lead the degree of polarization (DOP) to decrease and the internal quantum efficiency (IQE) to increase. By using the coupled thin well layers, the DOP for the structure with high Al-content in the barrier layer can be improved, while the DOP will further decrease with low Al-content in the barrier layer. It can be attributed to the band adjustment induced by the combination of barrier height and well layer coupling. The IQE can also be further enhanced to 14.8%–20.5% for various Al-content of barrier layer at J = 100 A/cm2. In addition, the efficiency droop effect can be expected to be suppressed compared with the conventional structure.
A simplified approximate analytical model for Rayleigh–Taylor instability in elastic–plastic solid and viscous fluid with thicknesses*
Authors: Wang Xi , Hu Xiao-Mian , Wang Sheng-Tao , Pan Hao
Published: December 2020

A simplified theoretical model for the linear Rayleigh–Taylor instability of finite thickness elastic–plastic solid constantly accelerated by finite thickness viscous fluid is performed. With the irrotational assumption, it is possible to consider viscosity, surface tension, elasticity or plasticity effects simultaneously. The model considers thicknesses at rigid wall boundary conditions with the velocity potentials, and deals with solid elastic–plastic transition and fluid viscosity based on the velocity continuity and force equilibrium at contact interface. The complete analytical expressions of the amplitude motion equation, the growth rate, and the instability boundary are obtained for arbitrary Atwood number, viscosity, thicknesses of solid and fluid. The thicknesses effects of two materials on the growth rate and the instability boundary are discussed.
Performance and stability-enhanced inorganic perovskite light-emitting devices by employing triton X-100*
Authors: Chen Ao , Wang Peng , Lin Tao , Liu Ran , Liu Bo , Li Quan-Jun , Liu Bing-Bing
Published: December 2020

Significantly enhanced electroluminescence performance and stability of all-inorganic perovskite light-emitting devices (PeLEDs) have been achieved by adding triton X-100 into the perovskite precursors. The small perovskite grains arranged tightly and formed large grains as the triton X-100 were introduced. Thus the nonradiative defects originated from Pb atoms at the grain boundaries were highly passivated by triton X-100 and resulted in the promotion of PeLED performance, including a turn-on voltage of 3.2 V, a brightness of 63500 cd/m2, a current efficiency of 17.4 cd/A, and a prolonged lifetime of 2 h in air.
Super-resolution imaging of low-contrast periodic nanoparticle arrays by microsphere-assisted microscopy*
Authors: Shi Qin-Fang , Yang Song-Lin , Cao Yu-Rong , Wang Xiao-Qing , Chen Tao , Ye Yong-Hong
Published: December 2020

We use the label-free microsphere-assisted microscopy to image low-contrast hexagonally close-packed polystyrene nanoparticle arrays with diameters of 300 and 250 nm. When a nanoparticle array is directly placed on a glass slide, it cannot be distinguished. If a 30-nm-thick Ag film is deposited on the surface of a nanoparticle array, the nanoparticle array with nanoparticle diameters of 300 and 250 nm can be distinguished. In addition, the Talbot effect of the 300-nm-diameter nanoparticle array is also observed. If a nanoparticle sample is assembled on a glass slide deposited with a 30-nm-thick Ag film, an array of 300-nm-diameter nanoparticles can be discerned. We propose that in microsphere-assisted microscopy imaging, the resolution can be improved by the excitation of surface plasmon polaritons (SPPs) on the sample surface or at the sample/substrate interface, and a higher near-field intensity due to the excited SPPs would benefit the resolution improvement. Our study of label-free super-resolution imaging of low-contrast objects will promote the applications of microsphere-assisted microscopy in life sciences.
Thermodynamic extremality relations in massive gravity *
Authors: Chen Deyou , Tao Jun , Wang Peng
Published: December 2020

A universal relation between the leading correction to the entropy and extremality was proposed in the work of Goon and Penco. In this paper, we extend this work to massive gravity and investigate thermodynamic extremality relations in a topologically higher-dimensional black hole. A rescaled cosmological constant is added to the action of the massive gravity as a perturbative correction. This correction modifies the extremality bound of the black hole and leads to shifts in the mass, entropy, etc. Regarding the cosmological constant as a variable related to pressure, we obtain the thermodynamic extremality relations between the mass and entropy, pressure, charge, and parameters ci
by accurate calculations. Finally, these relations are verified by a triple product identity, which shows that the universal relation exists in black holes.
Mass spectrum and strong decays of strangeonium in a constituent quark model *
Authors: Li Qi , Gui Long-Cheng , Liu Ming-Sheng , Lü Qi-Fang , Zhong Xian-Hui
Published: December 2020

In this work we calculate the mass spectrum of strangeonium up to the

multiplet within a nonrelativistic linear potential quark model. Furthermore, using the obtained wave functions, we also evaluate the strong decays of the strangeonium states with the

model. Based on our successful explanations of the well established states

,

,

,

, and

, we further discuss the possible assignments of strangeonium-like states from experiments by combining our theoretical results with observations. It is found that some resonances, such as

and

, listed by the Particle Data Group, and

and

, newly observed by BESIII, may be interpreted as strangeonium states. The possibility of

as a candidate for

or

cannot be excluded. We expect our results to provide useful references for looking for the missing

states in future experiments.
Joule-Thomson expansion of Born-Infeld AdS black holes *
Authors: Bi Shihao , Du Minghao , Tao Jun , Yao Feiyu
Published: December 2020

In this paper, the Joule-Thomson expansion of Born-Infeld AdS black holes is studied in the extended phase space, where the cosmological constant is identified with the pressure. The Joule-Thomson coefficient, the inversion curves and the isenthalpic curves are discussed in detail using a 4-dimensional black hole. The critical point of a Born-Infeld black hole is depicted with varying parameter

and the charge Q. In

plane, the inversion temperature curves and isenthalpic curves are obtained with different parameter

and charge Q. We find that the missing negative slope is still conserved in Born-Infeld black holes. We also extend our discussion to arbitrary dimension higher than 4. The critical temperature and the minimum of inversion temperature are compared. The ratio is asymptotically

as Q increases or

with

, and reproduces previous results at higher dimensions.
Investigation and analysis of the current situation of the application of WeChat public account in higher vocational education
Authors: Lin Wang
Published: December 2020

WeChat’s monthly activity has exceeded 1.1 billion, making it the APP with the largest number of users in China. In the new era, how to make good use of information technology, how to make it more immersed in the spirit of students, and realize the specific, normalized, and integrated path, has become an urgent problem for college ideological and political educators. Taking the students of higher vocational colleges as the research objects, using questionnaire survey and practical effect analysis to conduct research. The survey distributed 846 questionnaires, and analyzed the collected 820 sample data to understand the use of WeChat by vocational students, the use of the college’s WeChat public account, and the cognition and demand of the college’s WeChat public account. The WeChat public account has shown good results with wider coverage, faster dissemination, and stronger penetration. As one of the download forms of the Internet environment, it has a greater influence and has expanded new ideas, carried new tasks, took new missions of ideological and political education in colleges and universities.
An Object Recognition and Volume Calculation Method Based on Yolov3 and Depth Vision
Authors: Sun Y , Liu Z X , Li M , Zeng Z T , Zong Z X , Ji C L
Published: December 2020

In recent years, the logistics industry is in its full swing. The demand for logistics is increasing throughout the country, and this rising trend will continue during the following decades. With the substantial increase of workloads, traditional manual ways are increasingly unable to meet the new needs of the logistics industry, therefore new production and transportation modes are becoming imperative. Considering this, a new method was proposed to help detect, recognize and calculate the volume of rectangular objects automatically. In this method, a YOLO-based model was firstly applied to detect the object. Secondly, an RGB-D camera was used to obtain the depth information. Finally, after the length, width and height values were estimated from a single surface, the volume of the object can be calculated. Experimental results showed that the method is simpler and more accurate as compared with traditional three-dimensional reconstruction-based methods.
Building of Visual Analysis System for Design of Youth Sports Shoe Products Based on Comment Mining
Authors: Qian Shengbo , Zhang Kaixin
Published: December 2020

This paper proposes a visual analysis system for data collection, pre-preprocessing and sentiment analysis to support whole-process innovative design of youth sports shoes. This system aims to analyze the sales data of sports shoe e-commerce sellers before and after design, provide reference for key design elements in innovative design of sports shoes based on 3D printing and realize dynamic closed design of pre-design data investigation and analysis and post-design feedback data analysis. With dynamic data collection technology based on a crawler, product feature extraction model, sentiment analysis model and big data visualization technology, this system can better satisfy data analysis requirement for innovative design of sports shoes.
A review of research on object detection based on deep learning
Authors: Deng Jun , Xuan Xiaojing , Wang Weifeng , Li Zhao , Yao Hanwen , Wang Zhiqiang
Published: December 2020

As one of the important tasks in computer vision, target detection has become an important research hotspot in the past 20 years and has been widely used. It aims to quickly and accurately identify and locate a large number of objects of predefined categories in a given image. According to the model training method, the algorithms can be divided into two types: single-stage detection algorithm and two-stage detection algorithm. In this paper, the representative algorithms of each stage are introduced in detail. Then the public and special datasets commonly used in target detection are introduced, and various representative algorithms are analyzed and compared in this field. Finally, the potential challenges for target detection are prospected.
The Practical Aapplication of the YOLOv3 Model from the Perspective of Machine Learning in Pedestrian Detection
Authors: Li Yanan , Sun Xuehong , Liu Liping
Published: December 2020

Target detection and tracking technology is particularly important in the field of computer vision. With the needs of social production and the development of science and technology, the research of video pedestrian detection and tracking technology based on mobile platforms also needs to be put on the agenda. In this paper, the mobile robot is based on the Gmapping method to map the unknown environment, based on the A* and Dijistra algorithm to complete the safety inspection in the known environment, collect, record and save the video during the inspection process,and based on YOLOv3, the pedestrian target in the video for detection, the Deep_Sort target tracking algorithm establishes tracking of the dectected target, and creates a learning sample data set 2019.
Application of deep learning in defect Detection
Authors: Gong Xiaoyuan , Bai Yuewei , Liu Yiqun , Mu Hua
Published: December 2020

Defect detection has been the important link in the process of manufacturing enterprise production, is also one of the challenging parts, with the rapid development of science and technology and the introduction of [[CHECK_DOUBLEQUOT_ENT]] Industry 4.0 ", Intelligent Manufacturing, “Made in China 2025” put forward of the concept and development, manufacturing enterprises for the industrial product defect detection requirements are increasingly high, industrial product defect detection has also received more and more attention. In this paper, the application of deep learning in defect detection of industrial products is analyzed and discussed. Meanwhile, the traditional defect detection methods are summarized and compared with those using deep learning method. By combing and analyzing ICCV2019, the top conference in the field of computer vision, new technologies, new methods and new ideas that may be applied in the field of defect detection in the future were explored, and the challenges faced by them were analyzed in depth.
Research on Underground Pipeline Fault Monitoring Method Based on Big Data
Authors: Li Wenpeng , Ding Xiaopeng , Cui Hengle , Zhang Zipan , Li Jian
Published: December 2020

Distributed optical fiber sensors can sensitively sense local temperature changes caused by leakage at any position of the pipeline, but massive monitoring data has significant spatio-temporal non-stationary characteristics, and it is difficult to directly diagnose leakage based on the monitoring data. Under the framework of statistical pattern recognition, a spatio-temporal big data analysis method based on sliding window outlier analysis is proposed. Only the internal characteristics of distributed temperature monitoring data can be used to realize the intelligent identification of pipeline leakage, and the sliding is determined. The value method of window length and abnormal state diagnosis window length, and the physical simulation of prototype insulation steel pipe leakage monitoring was carried out. The results show that when the pipeline is intact, this method will not cause false alarms. Once the pipeline leaks, the method can quickly identify the pipeline leakage event and accurately locate the leak location.
A novel cloud game framework in dual Gigabit Network
Authors: Sun Kai , Xu Tao
Published: December 2020

With the development of 5G, cloud computing, and artificial intelligence (AI) technology, cloud game has become a hotspot about application and innovation of Gigabit bandwidth. This paper, firstly, analyses the present situation and development of cloud game to clarify the key business and key technology of cloud game, then, proposes an operational framework of cloud game, finally, the feasibility of the proposed framework is discussed and several suggestions about the operation of cloud game are given.
Research on Wireless Ad Hoc Network Technology for Building Monitoring
Authors: Feng Li , XiaoDong Cheng , Youying Wang , Huazhong Sun , Haijing Zhang
Published: December 2020

Aiming at the difficulties of equipment expansion, high data collection cost, and difficulty in data sharing faced by traditional building monitoring systems, this paper proposes a wireless ad hoc network technology for building monitoring. This method establishes a wireless ad hoc network through wireless network structure selection, wireless network self-organization and dynamic maintenance. Experimental results show that the wireless ad hoc network technology greatly reduces the cost of networking and debugging of intelligent systems, and can well meet the needs of intelligent monitoring of existing traditional buildings.
A collaborative filtering recommendation framework based on Wasserstein GAN
Authors: Li Rui , Qian Fulan , Du Xiuquan , Zhao Shu , Zhang Yanping
Published: December 2020

Compared with the original GAN, Wasserstein GAN minimizes the Wasserstein Distance between the generative distribution and the real distribution, can well capture the potential distribution of data and has achieved excellent results in image generation. However, the exploration of Wasserstein GAN on recommendation systems has received relatively less scrutiny. In this paper, we propose a collaborative filtering recommendation framework based on Wasserstein GAN called CFWGAN to improve recommendation accuracy. By learning the real user distribution, we can mine the potential nonlinear interactions between users and items, and capture users’ preferences for all items. Besides, we combine two positive and negative item sampling methods and add the reconstruction loss to the generator’s loss. This can well handle the problem of discrete data in recommendation (relative to the continuity of image data). By continuously approximating the generative distribution to the real user distribution, we can finally obtain better users’ preference information and provide higher accuracy in recommendation. We evaluate the CFWGAN model on three real-world datasets, and the empirical results show that our method is competitive with or superior to state-of-the-art approaches on the benchmark top-N recommendation task.
An algorithm of the recognition of inferior barcode
Authors: Chuanliang He , Xin Xia , Yingjie Lv , Yongping Liu
Published: December 2020

Objective: Bar code recognition is widely used. This paper introduces a method of using digital image algorithm to complete the identification of stain bar code. Methods: firstly, the barcode image was binarized and positioned; secondly, the pixels in the barcode image were stacked on the abscissa axis by projection technology to remove the barcode stains; finally, the barcodes were effectively identified by the center distance algorithm. Results: the experiments show that the barcodes with different degrees of pollution are well recognized by our method, which is better than the traditional recognition algorithm. Conclusion: This paper proposes a new barcode recognition algorithm, which can quickly and accurately identify the bad barcode
Design of Flight Closed Loop Simulation System Based on Runge-Kutta Algorithm
Authors: He Jinsong , Xiao Jia , Li Xiaojun
Published: December 2020

To solve the problem that the function/performance of the module cannot be fully verified in the laboratory or in the field during the design stage of the airborne radar system, the paper proposes and designs an airborne flight closed-loop simulation system. The flight simulator, which is the core of the entire simulation system, uses the Runge-Kutta algorithm to solve the model and solve the 6-degree-of-freedom nonlinear model of the aircraft in real time, providing realistic aircraft movement data for the airborne radar system. The design builds a Matlab/Simulink simulation model and embeds it in simulation test software to run independently as a model component. The verification test of the closed-loop simulation system shows that the system can realize the real-time simulation of the entire flight environment and meet the design performance requirements.
Research on Organization Name Matching Based on Word Vector
Authors: Song KaiLi , Li YunLing , Yao LuLu , Wang Yuan
Published: December 2020

Organization names usually exist in the form of abbreviations, aliases, etc. in daily use, which brings great difficulties to online search and matching in the Internet era. Through extensive analysis of Chinese organization name data and research on word embedding technology based on neural network, this paper proposes a BERT model based on organization name field data training to achieve organization name matching. The experimental results show that the accuracy is improved by 17% compared with the method based on edit distance.
Application of an improved BP neural network algorithm in intrusion detection
Authors: Xuan Chen
Published: December 2020

Based on the analysis of the existing problems of BP neural network used in the detection system, on the basis of the traditional BP algorithm, the automatic variable rate learning method is adopted, the forgetting factor and random optimization operator are introduced, and they are used in the network intrusion detection system. The simulation results show that the improved BP neural network algorithm is fast and easy to converge. The algorithm effectively improves the detection rate, reduces the false positive rate and false negative rate, and has obvious advantages.
Improved Mosaic: Algorithms for more Complex Images
Authors: Hao Wang , Zhili Song
Published: December 2020

Data augmentation plays a vital role in deep learning, and image augmentation, as an important part of target detection and image classification, significantly improves the performance of the algorithm. The Mosaic data augmentation algorithm in YOLOv4 randomly selects 4 pictures from the train set and puts the contents of the 4 pictures into a synthetic picture that is directly used for training. This data augmentation method can improve the model’s recognition ability in complex backgrounds. In this paper, we improve the Mosaic data augmentation algorithm. After analyzing the synthesized picture area, it is divided into irregular grids, and a certain number of training set pictures are filled randomly, which further improves the synthesis ability and achieves a synthesis picture that can accommodate 6 and 9 training set pictures. After basic image processing methods such as zooming, flipping, and color gamut transformation, the model’s recognition ability under complex backgrounds is improved, and the accuracy of identifying small targets is improved. During the batch normalization operation, the data of 6 or 9 pictures can be calculated at the same time, which makes the model hyperparameter mini-batch need not be set very large, which reduces the GPU memory requirements.
Image iterative method for handwritten Chinese character recognition
Authors: Yu Wanbo , Li Yaosheng , Peng Hongwei , Zhang Li
Published: December 2020

Although accuracy and calculation time of handwritten Chinese character recognition have been greatly improved, it has not yet reached the practical application standard. Recently literatures, iterative method is used to recognize face images and good results are obtained. Therefore, image recognition is improved based on this idea. In this paper, linear combination of trigonometric functions is used as auxiliary function and image to construct discrete dynamic system. By adding bevel and shift to construct font surface and so on, the system structure is improved to solve problem of system convergence caused by large area flatness of handwritten Chinese character image, and good recognition effect is achieved. Preliminary experiments(for example, extracting 20 Chinese characters written by 9 people in the data set) are carried out, and recognition rate can reach 100% when all of them are trained, and recognition rate can reach 76.7% when each Chinese character is trained to 3 pieces; in addition, experiments were conducted on handwritten Chinese character sets changing from different angles, and the recognition rate reached 80%, which was compared with other algorithms to verify the feasibility of handwritten Chinese character recognition algorithm based on chaotic iterative trajectory characteristics of images.
Intelligent Auxiliary Operation and Maintenance System of Power Communication Network based on Knowledge Graph
Authors: Miao Weiwei , Wu Haiyang , Chen Peng , Jing Jiangping
Published: December 2020

With the deepening application of knowledge graph technology, in order to solve the problems that it is difficult to quickly obtain knowledge and complete the maintenance task, an intelligent auxiliary operation and maintenance system of power communication network based on knowledge graph is designed and implemented. The proposed system addresses effectively the two mentioned challenges accordingly by aggregating semantic information of different granularity in the constructed knowledge graph. Specifically, a Relation-Tuple-Entity Heterogeneous Graph Neural Network (SG-HGNN) is proposed to model effectively the different granularities of semantic information for knowledge reasoning. Comprehensive experiments which are conducted on the constructed knowledge graph demonstrate the effectiveness of the proposed framework. After the pilot application of the system, the problem hit rate and problem response time are significantly reduced, which greatly improves the operation and maintenance efficiency of power communication network.
An adaptive intelligent collaborative optimization method based on inconsistent information
Authors: Shu JunMing , Fu Chao , Liu Jihong , Xu WenTing , Yu HongYan
Published: December 2020

Multidisciplinary Design Optimization (MDO) is a design optimization method for dealing with large-scale and multi coupling complex engineering systems. The collaborative optimization (CO) has the characteristics of high degree of discipline autonomy, multi-level optimization and distributed computing. It can effectively solve the design optimization problems of large-scale complex engineering systems, and has been widely used in aerospace, ship, automobile, machinery and other fields. Because of its own optimization model and principle, the CO method has the defects of low computational efficiency and difficult convergence. In this paper, in order to overcome the convergence difficulty caused by the internal definition defects of the CO method, combined with the adaptive mechanism, the position relationship between the system level optimization points and the constraint conditions is analyzed, and the adaptive penalty function is constructed based on the inconsistent information of the system. The system level optimization model of the CO method is reconstructed by transforming the system level constraints. Finally, an example is given to demonstrate the effectiveness of the proposed method.
Design of an integrated monitoring system based on object-oriented
Authors: Li Aiguo , Yue SU
Published: December 2020

The integrated monitoring system is a security system that integrates information, storage, transfer and transportation management. This paper takes the security and defense integrated monitoring system of a certain military warehouse area as the background. Aiming at its complexity and diversity, in order to enhance the security and robustness of the integrated monitoring system, this paper adopts object-oriented software development technology. Taking the Rational Unified Process (RUP) as the software development method, the Unified Modeling Language (UML) as the main analysis and design description language, and the requirements analysis and system design of the integrated monitoring system are carried out. This system is based on the C/S structure model to realize the development and deployment of the integrated monitoring system, uses the database design tool PowerDesign to design the database, and uses the ASP.NET development tool realizes the functional modules. In order to achieve a clear security system framework, traditional use case diagrams, data flow diagrams, ER diagrams and other description tools are used as a supplement to system requirements analysis and design.
Research of the Smart Substations Scheme Based on Centralized Protection and Control Unit
Authors: Shouquan Tang , Jungang Wang , Fan LI , Zhangtao  , Xiaoli Huang , Zhenjie Li
Published: December 2020

The smart substation plays an important role in the smart grid. This paper expounds the ideas of centralized protection and control unit (CPC) in smart substation, and analyzes the situation in the engineering applications.
Comparative analysis of the performance influence of isolated bus open-end winding BLDCM and star-end winding BLDCM
Authors: Lisi TAN , Chaohui ZHAO , Fan DING , Zhaoyang JIAN
Published: December 2020

The open-end winding motor (OEWM) system is a hot spot of current scholars’ research due to its advantages of large output power, wide speed range, and strong fault tolerance. Through Maxwell and Simplorer software co-simulation, the open-end winding brushless direct current motor (OEWM-BLDCM) and the star-end winding BLDCM under three-phase six-state control mode are compared and analyzed, including conduct current, torque, speed and mechanical characteristics. The simulation results show that: OEW-BLDCM has faster response speed, smaller torque ripple, and doubled the maximum speed.
Bearing fault diagnosis based on wavelet packet energy spectrum and SVM
Authors: He Cheng , Wu Tao , Gu Runwei , Qu Huaying
Published: December 2020

Aiming at the limitation of wavelet analysis in fault diagnosis, combining wavelet packet energy spectrum and support vector machine algorithm, a fault diagnosis method based on wavelet packet energy spectrum and support vector machine algorithm (SVM) is proposed. This method first performs wavelet packet transformation on the test data, and the vibration signal is decomposed into independent frequency bands. The signal energy changes in different frequency bands reflect the change of the operating state, and the wavelet packet energy spectrum of each frequency band is extracted as a feature vector. Finally, the SVM algorithm is used to test the bearing faults. The test results show that after processing and analysis of a large number of measured bearing data, the fault of the bearing can be diagnosed relatively accurately.
Automatic disassembly and recovery device for mobile phone circuit board CPU based on machine vision
Authors: He Cheng , Jin Zhongyan , Gu Runwei , Qu Huaying
Published: December 2020

Aiming at the problem of dismantling and recycling the circuit boards of used mobile phones, A device based on machine vision to automatically disassemble and recycle the CPU on the mobile phone circuit board is proposed. The device is equipped with a visual inspection system, a feeding device, a heating device, a CPU transfer device, a robot, and a visualization system to realize automatic disassembly and storage of the CPU on the mobile phone circuit board. Finally, experiments show that the device can achieve stable and reliable CPU disassembly and recovery.
Research on the effect of icing on aerodynamic performance of airfoil and power generation performance of wind turbine
Authors: Jiang Feilong , Qiu Tengwei
Published: December 2020

In order to study the effects of icing on the aerodynamic performance of airfoils and the power generation performance of wind turbines, CFD (computational fluid dynamics) is used in this paper to simulate and analyze the airfoil before and after icing based on the numerical simulation of a NACA airfoil. Results of the analysis show that ice accretion on the airfoil causes the lift coefficient to decrease and the drag coefficient to increase, which results in a significant deterioration in the aerodynamic performance of the airfoil. To further verify the analysis results, real-time icing monitoring is carried out on a 1.5MW wind farm. Statistics show that after ice accretes on the blades, the power curve of the blades decreases overall, and the blades stall at a speed close to the rated wind speed.
SOC Estimation of Lithium Battery Based on IPSO-BP Neural Network
Authors: Mao Xinjian , Song Shaojing , Ding Feng , Tang Pan
Published: December 2020

Based on the analysis of the accurate estimation method of the state of charge (SOC) of lithium battery for electric vehicles, aiming at the shortcomings of back propagation (BP) neural network model, an algorithm based on Improved Particle Swarm Optimization (IPSO) is proposed to optimize the parameters of BP neural network. In this algorithm, the particle swarm optimization algorithm is optimized by introducing shrinkage factor to limit the particle speed, so as to determine the initial parameters of BP neural network. Finally, the battery estimation model is established by using the data set of lithium battery published by NASA PCoE, and the simulation test is carried out by using MATLAB platform. The results show that the method can effectively reduce the SOC error and control the error within 2%. It has practical significance for SOC estimation in battery management system.
Probabilistic Neural Network Motor Bearing Fault Diagnosis Based on Improved Feature Extraction
Authors: Min Fanchao , Xue Jingyu , Ma Fengying
Published: December 2020

According to the fault characteristics of the rolling bearing in the motor, Db6 wavelet is used to decompose the waveform data, and the feature vector extraction method is improved. The probabilistic neural network is used to diagnose the fault category of the rolling bearing of the motor, and compared with the traditional feature extraction method. Experiments show that the accuracy of the method proposed in this paper reaches 98%, and it has a very broad application prospect in fault diagnosis in actual industrial production.
Telecommand encryption for intercommunication of substation control centers
Authors: Mesa F , Devia D M , Ospina R
Published: December 2020

New technologies are constantly generated and advanced every day and, with them, the need to use them to maintain constant communication with different people located anywhere in the world is also increasing. But this exponential growth also generates a very important security problem, since any information that is found in a device connected to the communications network or that travels through it, can be susceptible to being detected or intercepted by an unauthorized person that can be used improperly, causing large economic losses to companies or personal problems. For this reason, it is essential to use some mechanism that helps to protect the information from a malicious attack, one of the most used is cryptography that is responsible for writing in secret, providing confidentiality to the information through an encryption method.
System to monitor and locate water leaks using LabVIEW software
Authors: Gómez J A , Jaramillo H Y , Nolasco C
Published: December 2020

Water pipelines are prone to critical failures due to aging, corrosion, and external factors. These failures can lead to water leaks in the pipeline, which in turn can cause property damage and environmental contamination if not detected in time. This work presents a system for monitoring and locating water leaks using LabVIEW software. The system describes the mathematical model used to locate the leak, which is implemented in a virtual instrument, obtaining the flow and pressure behavior of the system in the presence and absence of leaks in a transient state through a virtual platform coupled to a data acquisition system. With the implementation of the mathematical model in the virtual instrument, it was possible to locate the leak in real time to ensure its immediate correction, without false alarms.
Necessities, opportunities, and challenges for tympanic membrane perforation scaffolding-based bioengineering
Authors: Hussain Zahid , Pei Renjun
Published: December 2020

Tympanic membrane (TM) perforation is a global clinical dilemma. It occurs as a consequence of object penetration, blast trauma, barotrauma, and middle ear diseases. TM perforation may lead to otitis media, retraction pockets, cholesteatoma, and conductive deafness. Molecular therapies may not be suitable to treat perforation because there is no underlying tissue matrix to support epithelium bridging. Chronic perforations are usually reconstructed with autologous grafts via surgical myringoplasty. Surgical treatment is uncomfortable for the patients. The grafting materials are not perfect because they produce an opaque membrane, fail in up to 20% of cases, and are suboptimal to restore acoustic function. Millions of patients from developing parts of the world have not got access to surgical grafting due to operational complexities, lack of surgical resources, and high cost. These shortcomings emphasize bioengineering to improve placement options, healing rate, hearing outcomes, and minimize surgical procedures. This review highlights cellular, structural, pathophysiological, and perforation specific determinants that affect healing, acoustic and surgical outcomes; and integrates necessities relevant to bioengineered scaffolds. This study further summarizes scaffolding components, progress in scaffolding strategies and design, and engenders limitations and challenges for optimal bioengineering of chronic perforation.
Trajectory Optimization of Deep Shale Gas Horizontal Wells
Authors: Li Wenzhe , Gao Dewei , Dai Feng , Wu Pengcheng , Lin Hairui , Fu Jianhong
Published: December 2020

The development mode of deep shale gas “Pad drilling” cluster horizontal wells could greatly reduce the single-well drilling cost and is also the significant measure for scale benefit development of shale gas. For pad drilling, the small wellhead distance of cluster well group, complicated well profile and long horizontal section result in such engineering problems as high well collision probability in upper well section, high trajectory control difficulties and large drill string torque and drag. A reasonable 3D horizontal well profile and the reasonable profile parameters are the premise for the safe and rapid drilling of shale gas horizontal well. Therefore, optimizing type and the well profile parameters suitable for deep shale gas horizontal well could help improve drilling efficiency, lower drilling risk and save drilling cost. In this paper, the three types of trajectory profile, including 3D trajectory in spatial oblique plane (large 3D), dual 2D trajectory and dual 2D and small 3D combined trajectory profile were developed, and under the same surface location and target zone, three different types of shale gas horizontal well were planed; the differences of these three trajectories in well depth, drill string torque and drag and well separation factor were compared through drill string torque and drag analysis and collision prevention analysis. The analysis results show: Dual 2D trajectory or dual 2D and small 3D combined trajectory is featured by small drill string drag and torque, low trajectory control difficulty and low well collision probability and is therefore more suitable for trajectory plan of deep shale gas horizontal wells.
A Regression Analysis on the Effects of Factors on Plastic Waste Production
Authors: Yang Junnan , Zhang Lingchang , Wang Weitao , Qiu Zheyong
Published: December 2020

Plastic is a multi-purpose material produced in large quantities. However, the non-degradability of plastic waste also brings many negative effects. In order to solve the problem of plastic production waste, we first analyze which factors have a greater impact on the production of plastic waste, and for this reason, a multiple linear regression has been established. We quantify abstract influencing factors. After that, the data is put into Statistical Product and Service Solutions (SPSS) for processing, and the influence of different factors on plastic waste is calculated. We find that the production of plastics has the greatest impact on the increase of plastic waste, while mainland policies have the greatest impact on the reduction of plastic waste. Finally, we have a sensitivity analysis on this model to analyze the impact of various factors on the output of plastic waste.
Experimental Study on Heat Dissipation Performance of Enclosed Space with Envelope Embedded Flat Heat Pipe
Authors: Song Sihong , Ruan Yu , Wang Jianli , Xu Jiafeng , Pi Changqian
Published: December 2020

A lot of heat source equipment must work in enclosed space for noise controlling, electromagnetic shielding or three proofings requirement, the heat dissipation is an important problem for being restricted by the enclosed space. In order to solve the heat dissipation problem, the technology scheme was proposed that quantity of heat in enclosed space is conducted out by the flat heat pipe embedding in envelope. Furthermore, the flat heat pipe was designed and fabricated, and the heat dissipation performance of enclosed space with envelope embedded flat heat pipe was studied experimentally. It was found that the convective heat transfer on evaporation fins of heat pipe is the most important section influencing the heat dissipation performance of enclosed space. The temperature in enclosed space decreases greatly with increasing the disturbance air quantity in enclosed space. The temperature difference between inside and outside increases linearly with increasing heat source intensity. It is a novel method to solve effectively the heat dissipation problem of heat source equipment in enclosed space by embedding the flat heat pipe in the envelope.
Risk Assessment Method of Coal Spontaneous Combustion Based on Catastrophe Theory
Authors: Qiu Xiaoxuan , Cao Qinggui , Wang Yunna , Liu Qing
Published: December 2020

Coal spontaneous combustion is one of the major threats to coal production in China. It is very important to quote scientific and effective evaluation in order to prevent coal spontaneous combustion effectively. This paper use catastrophe theory to study the risk assessment method of coal spontaneous combustion. Used analytic hierarchy process (AHP) to determine the weight of 16 indicators to establish an evaluation model which based on catastrophe theory. Analyzed the catastrophe level value of coal spontaneous combustion hazard obtained by the catastrophe theory calculation method to determine the hazard level,and put forward corresponding suggestions. Through engineering case studies, the feasibility and effectiveness of the coal spontaneous combustion risk assessment method proposed in this paper is verified.
Effects of Applying Symbex on Tea Yield, Quality and Soil Fertility
Authors: Huang Dongfeng , Li Yu , Qiu Xiaoxuan
Published: December 2020

Field plot experiments were conducted to study the effects of different doses of Symbex products (i.e., clear water, 50 times, 100 times, 150 times, 200 times and 250 times diluent) on tea yield, quality and soil fertility. The results showed that, compared with CK (clear water), applying different doses of Symbex diluent could increase the density of tea bud head by 2.7% ∼ 25.3%, 100 bud weight by 3.6% ∼ 21.1%, internode length by 5.3% ∼ 21.1%, increase annual fresh tea yield by 7.6% ∼ 37.9%, increase tea polyphenols by 9.4% ∼ 41.4%, amino acids by 7.1% ∼ 39.3%, soluble sugar by 9.4% ∼ 41.4%, and water extract by 7.5%∼43.9%. Results also showed that the soil organic matter, available nitrogen, available phosphorus and available potassium in the topsoil of tea garden increased by 2.4% ∼ 29.8%, 13.7% ∼ 98.1%, 26.2% ∼ 98.0% and 24.4% ∼ 102.2% respectively. Among them, T200 (Symbex 200 times diluent) and T250 (Symbex 250 times diluent) treatments had better effects on improving the morphological indexes and biochemical composition indexes of tea garden, increasing the yield of fresh tea leaves, and improving the basic available nutrient content in the topsoil of tea garden.
Role of Boundary Layer Jet in the Occurrence and Development of Warm-sector Heavy Rainfall over South China: a Case Study
Authors: Dong Fu , Zhang Ling , Chen Weidong , Li Dengxuan , Wang Jia , Zhi Xiefei
Published: December 2020

Warm-sector heavy rainfall which occurred at the coastal area of southern China on 8 June 2015 was associated with a boundary layer jet (BLJ). The initiation and maintenance mechanism of the BLJ is further investigated based on the Weather Research and Forecasting (WRF) model simulations and reanalysis data. The results showed that the BLJ developing at night transported moisture to the coastal area of Guangxi in southern China, which lead to the instability of the atmosphere over the coastal areas of Guangxi. The terrain blocking and lifting the southerly with abundance of water vapor is the major trigger mechanism in present case. As the BLJ weakened and vanished after midday, the amount of rainfall decreased correspondingly. Based on the numerical model sensitivity test with different parameterization schemes, the key role of the BLJ for the occurrence and development of the warm-sector heavy rainfall is further verified.
Research and Development of Full Energy Efficiency Grade Motor
Authors: Su Hui , Wen Hui , Zheng Xinhua , Tang Xueqin , Su Jianxin
Published: December 2020

This paper proposes the concept of “full energy efficiency grade motor”, explains the characteristics of the full energy efficiency grade motor, and introduces in detail the main techniques and design methods for realizing the full energy efficiency grade motor, and gives a set of design data and test results. The test results show that the designed motor spans three power grades and energy efficiency grades, and its technical parameters fully meet the national standards of each energy efficiency level. This technology can improve motor efficiency, reduce size, reduce tooling and mould, and simplify production management. It can solve the problem of high efficiency and energy saving of the motor in a wide range of variable conditions.
A Novel Method for Power Quality Disturbance Detection Based on LSTM Network Model Residuals
Authors: Wang Xuechun , Duan Chendong , Dai Jie
Published: December 2020

In order to accurately detect the time when the disturbance of power quality (PQ) occurs and the variation of voltage amplitude, a novel method of power quality disturbance detection that is based on the residual of the long short-term memory (LSTM) network model is proposed. Firstly, an offline model is developed based on historical voltage signals from a power grid under the normal condition by using the LSTM theory. Then, in order to detect PQ events online, the grid voltage signal is taken as the input of the model to obtain the residual component between the input signal and the normal signal. Finally, the amplitude change of the residual component reflects the amplitude change of the voltage. The starting and ending time and duration of the disturbance are located by detecting the mutation points of the residual component. Experiments on simulation data and engineering data show that the proposed method can well reflect the amplitude change when the voltage is disturbed, and the disturbance positioning accuracy is high.