bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Wireless Ad Hoc Network Technology for Building Monitoring
Authors: Feng Li , XiaoDong Cheng , Youying Wang , Huazhong Sun , Haijing Zhang 
Published: December 2020

Abstract
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

AbstractCompared 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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

AbstractBased 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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.