bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparison on Data Augmentation Methods Based on Deep Learning for Audio Classification
Authors: Wei Shengyun , Zou Shun , Liao Feifan , lang weimin 
Published: March 2020

Abstract
Deep learning focuses on the representation of the input data and generalization of the model. It is well known that data augmentation can combat overfitting and improve the generalization ability of deep neural network. In this paper, we summarize and compare multiple data augmentation methods for audio classification. These strategies include traditional methods on raw audio signal, as well as the current popular augmentation of linear interpolation and nonlinear mixing on the spectrum. We explore the generation of new samples, the transformation of labels, and the combination patterns of samples and labels of each data augmentation method. Finally, inspired by SpecAugment and Mixup, we propose an effective and easy to implement data augmentation method, which we call Mixed frequency Masking data augmentation. This method adopts nonlinear combination method to construct new samples and linear method to construct labels. All methods are verified on the Freesound Dataset Kaggle2018 dataset, and ResNet is adopted as the classifier. The baseline system uses the log-mel spectrogram feature as the input. We use mean Average Precision @3 (mAP@3) as the evaluation metric to evaluate the performance of all data augmentation methods.
Adaptive Robust of RBF Neural Network Control Based on Model Local Approximation Method for Upper Limb Rehabilitation Robotic Arm
Authors: Li Yafeng , An Aimin , Wang Jinlei , Zhang Haochen , Meng Fancheng 
Published: March 2020

Abstract
For the problem of patient spasm disturbance and random disturbance of external environment in rehabilitation process of upper limb rehabilitation arm, Considering the approximation ability of neural network for arbitrary functions, an adaptive robust of radial basis function (RBF) neural network control algorithm based on model local approximation is proposed. This control algorithm introduces robust term to reduce the approximation error of neural network and the robustness of the rehabilitation manipulator control system is improved. The system can also obtain good track tracking performance under the condition of patient spasm disturbance and random disturbance of external environment. The asymptotic stability of the control system is proved by the stability theory of Lyapunov. Simulation results show that the proposed control algorithm has good control performance.
Track detection system of UAV based on line structure light
Authors: Huang Ruiting , Jia Mengyao , Guo Simeng 
Published: March 2020

Abstract
Aiming at the present problems of strong subjectivity and low efficiency of manual push flaw detection vehicle, in order to meet the requirements of high-speed rail detection, this system uses UAV aircraft combined with line structured light technology to realize a track detection system based on multiple sensors. In the method of joint positioning, after coarse positioning of the UAV through satellite positioning, the camera on the UAV is used to identify the image of the track to complete accurate positioning and single-track tracking. The high precision and fast scanning speed of structural light are used to obtain the profile data of rail. The obtained measurement data were calibrated by combining the mathematical model established with the track CAD model to eliminate the influence of the UAV’s self-disturbance on the acquired data and achieve the acquisition of rail wear data. At the same time, the computer vision technology is used to extract the window in the track, and the track intrusion detection is carried out through the analysis of the gray map distribution in the window.
Machine Learning Based Epileptic Seizure Detection for Responsive Neurostimulator System Optimization
Authors: Shen Yangchicheng 
Published: March 2020

Abstract
This paper proposes a novel method of identifying the time of epileptic seizure happening on patients by employing feature extraction and machine learning-based classification on Electroencephalogram (EEG) signal collected from a closed-loop interface implanted in the brain of patients. The closed-loop device was served as a neurostimulator which introduced stimuli to epilepsy patients when detecting the occurrence of seizure. A set of multiple time- and frequency-domain features are extracted from intracranial electroencephalography recordings of 7 subjects with epilepsy. Trained and tested on the extracted features, an ensemble of machine learning models with parameter tuning achieves an area under the curve (AUC) score of 0.99.
Study on Influence of Opening Roads in Community on Urban Traffic Planning and Scheduling
Authors: Sun Ziqiang 
Published: March 2020

Abstract
With the development of modern economy and society, the urban population grows and the number of motor vehicles keeps increasing. The traffic jam follows up, and has become a common problem in many cities, especially in the large cities. How to plan and schedule in advance is an intelligent planning problem. Reasonable planning and scheduling can effectively alleviate the urban traffic jams. In this paper, AHP method is used to establish a hierarchical structure, and demonstrate the effect of opening roads in community in different time by the qualitative to quantitative principle. In view of this, this paper gives rational suggestion of the opening roads in the community, and provides reference for the construction of the new intelligent living community in the future.
Research on the application of VR technology in the digital inheritance of ancient papermaking technology
Authors: Zhong Lishi , Zhong Zhou , Peng Xiaopeng 
Published: March 2020

Abstract
The traditional papermaking technique of ancient method is confronted with the problem of difficult inheritance. In order to enable the public to experience or learn the ancient papermaking technology with the help of virtual platform and make the ancient papermaking technology have more possibilities for future development, the VR experience project of ancient papermaking technology is designed and planned through data collection, virtual scene production, digital interactive design and other steps by means of integrating disciplines. It can retain the integrity of the information of ancient papermaking technology to the greatest extent, provide a safe, efficient and green simulation learning platform, rapidly promote the traditional ancient papermaking culture in a large range, enrich the presentation of ancient papermaking materials and predict the future development direction.
Construction Research on Index System of Quality Evaluation of Labour Education in China
Authors: Sun Xi 
Published: March 2020

Abstract
With the development of modern economy and society, labour education has been gradually weakened. In recent years, the declining status of labour education position in schools and colleges has weakened the function of labour education, resulting in the quality decline of labour education. The contemporary students have many problems in the aspects of labour quality and labour ability. Therefore, improving the quality of labour education in China has important historical and practical significance. This paper gives an explanation of the importance of labour education to personnel training, and analyses the innovation embodiment of labour education. On this basis, this paper constructs the evaluation index system of labour education quality in China, which consists of six criteria levels and twenty-four program levels. According to the Analytic Hierarchy Process, the paper evaluates the weight of each scheme layer, constructs a complete evaluation index system of labour education quality in China, and provides some references for relevant researchers.
Safety Assessment System of Launching Tower Structure with Multi-information Fusion and Data-driven
Authors: Gu Yufei , Chen Shaojiang , Zhang Lijun , Jia Hongliang , Xu Feiran 
Published: March 2020

Abstract
In order to monitor and evaluate the impact of rocket launching shock, strain, vibration, typhoon, earthquake and other loads on the launch tower, an online monitoring and evaluation system was established based on multi-sensor information fusion technology in a space launch site. Firstly, the system integrates the information of vibration, pressure, deformation, wind load, temperature and other sensors to comprehensively analyze and evaluate the safety of tower structure, and realizes health diagnosis. Then use 3dmax to draw the 3D simulation model, and realize the real-time 3D display of various monitoring and analysis results based on the 3D visualization and data-driven technologies.
Access control mechanism based on image recognition and user level
Authors: Qi Haojin , Wang Yong , Yang Yueping , Yu Xiaodie , Ju Xiaoming 
Published: March 2020

Abstract
The rapid development of big data and the Internet has brought enormous challenges to data security. Aiming at protecting the sensitive image data protection and secure access of information, an access control mechanism based on image recognition and user level is proposed. On the one hand, the mechanism is based on deep learning, mining sensitive information in images, realizing hierarchical classification and precise positioning of sensitive areas in images; on the other hand, combining identity authentication to achieve user management based on identity level; The image sensitivity level is mapped with the user identity level, which realizes the user’s access authority control, prevents unauthorized or illegal access of sensitive image information, and effectively protects sensitive image information.
A Social Mobilized Inspection System against External Damage of Power Grid Based on Block Chain Technology
Authors: Bing HE , Ren-de LI , Wang Shan-shan , Jian-guo LIU 
Published: March 2020

Abstract
The operation and inspection of external damage of power grid is becoming more and more difficult, mainly reflected in the uncertainty of risk and insufficient manpower. At present, most of the on-site inspection rely on human inspection since new technology cannot respond to unexpected situations. In this paper, we proposed a social mobilized inspection system. By mobilized the social forces around power facilities, we propose an inspection framework to encourage people upload photos of external damage. To ensure the incentive system transparency, we use block chain technology as the decentralized database. This method provides a new insight against external damage of power grid and is hopefully to be used in inspection system.
A Simple Dual-Frequency Circularly Polarized Slot Antenna With a Modified Crossed Patch
Authors: Hua Lu , Chen Tingting , Liu Hengxiang 
Published: March 2020

Abstract
A simple single-layer single-fed dual-frequency circularly polarized(cp) antenna with a crossed patch is proposed in this paper. The modified crossed patch with dual-frequency cp provides a new method for the design of other multi-frequency cp antennas. A horizontal stub is introduced at the upper end of the long arm and sharp angles protrude from both ends of the short arm to achieve dual circular polarization at low frequency (1.64 GHz) and high frequency (3.45 GHz), respectively. The antenna proposed in this paper can be applied to WIMAX with a compact size of 53 × 60mm2. The experimental results show that the impedance bandwidth of 250 MHz (1.55 GHz-1.8 GHz) and 1440 MHz (2.2 GHz-3.64 GHz), and the 3 dB axis-ratio bandwidth of 250 MHz (1.52 GHz-1.78 GHz) and 520 MHz (3.08GHz-3.6 GHz) are achieved in these two bands respectively. The proposed antenna has been printed and fabricated, and the measured results are in good agreement with the simulated results.
Defect diagnosis technology of typical components on transmission line based on Fully Convolutional Network
Authors: Zhenyu LI , Wanguo Wang , Tao LI , Guangxiu LIU , Zengwei LI , Yuan Tian 
Published: March 2020

Abstract
This paper presents an intelligent defect diagnosis algorithm based on fully convolutional neural network for typical transmission line components. Based on the region-based fully convolutional neural network algorithm and combined with deformable convolution, feature context fusion, clustering, the feature expression ability of neural network is improved. Through the improvement, the algorithm adapts to the object deformation and scale difference. In addition, the training effect is improved by improving the sample labeling strategy. In this paper, the defect diagnosis of four kinds of transmission line components(insulator, vibration damper, grading ring, wire clamp) is realized.
Influencers Identification in Weighted and Directed Networks Based on k-layer Decomposition
Authors: Cai Yuecheng , Zhou Wen 
Published: March 2020

AbstractIn recent years, complex network research has received wide attention from scientific and industrial circles in different academic fields owing to its high application value. In the field of complex network research, identifying influencers has far-reaching implications for various real-world propagation dynamics, such as epidemic outbreaks, and cascading failures. In this paper, we analyse the node-specific attributes of weighted and directed networks and propose two new influencers identification indices for weighted and directed networks. For weighted networks, in k-layer decomposition, weighted degree is used in the algorithm instead of degree as the basis for decomposition. For directed networks, we separately consider the effect of in-degree and out-degree on network decomposition and propose directed k-layer (KLD) indicators that are more suitable for directed networks. Thereafter, a Susceptible-Infected-Recovered (SIR) model and network robustness evaluation methods are used to compare and evaluate the proposed indices on multiple real-world complex network datasets. We found that using the proposed indices resulted in improved node ranking ability for weighted or directed networks.
Application Research of Transmission Technology in Information Communication Engineering
Authors: Jiang Meng 
Published: March 2020

Abstract
In the planning, design and concrete construction of information communication engineering, transmission technology has an irreplaceable role in the transmission system because it has very important influence and effect. The overall application effect of the transmission technology will directly affect the basic situation of the entire information communication project during construction and utilization.Therefore, this paper analyzes the specific application of transmission technology in information communication engineering, and lays a good foundation for improving the efficiency of information communication engineering.
Research on Winding Deformation Detection and Diagnosis Technology of Power Transformer
Authors: Lu Wei , Ma Jun , Ma Bo 
Published: March 2020

Abstract
With the continuous increase of power grid capacity, transformer damage accidents caused by short-circuit faults are on the rise. Timely and effective measurement of transformer winding deformation can effectively prevent further deterioration of transformer deformation and ensure that transformer does not occur accidents. This paper summarizes the methods, principles, influencing factors and judging criteria of winding deformation detection, and summarizes the important research results in the field of transformer winding deformation in recent years. Finally, this paper compares different detection methods from the aspects of detection methods, influencing factors of test results, detection information, detection sensitivity, deformation judgment methods and detection standards.
Multilayer WFRFT and chaotic encryption wireless communication system based on MIMO
Authors: Zhuang Lei , Hu Jing , Cheng Jian 
Published: March 2020

Abstract
In order to improve the concealment and anti interception performance of satellite and other wireless communication.Based on the characteristics of multilayer weighted fractional-order Fourier transform and chaotic mapping, a multilayer weighted fractional-order Fourier transform and chaotic mapping wireless communication system is designed. The number of modulation layers of multilayer WFRFT is consistent with the number of transmitting antennas, and different modulation orders are adopted in each layer, which makes it more difficult to crack the information by chaotic mapping scrambling codes on the modulated signals. The simulation results show that the designed system has better concealment performance by comparing the bit error rate of the receiver with that of the eavesdropper. The bit error rate of the eavesdropper is about 0.5 when the eavesdropper does not know the specific parameters.
Design of an Intelligent Leakage Prevention System for High pressure Injector
Authors: Zhengdong LI , Xiuling LI , Haimei XU , Juan CAI , Xiaoling XU , Yan HE 
Published: March 2020

Abstract
In order to solve the problem of liquid leakage due to high injection pressure and fast injection speed in the current medical high pressure injector, a set of intelligent anti-leakage diversion alarm system for high pressure injector was designed by using TI microcontroller MSP430F4619, precision electronic FS2050 pressure sensor and Nordic company’s NRF24L01+ wireless transmission chip. The system can monitor the process of high pressure injection in real time. Once the leakage of drug solution is detected, wireless acousto-optic alarm will be given immediately and diversion switch will be made quickly. This system not only overcomes the disadvantage of the previous mechanical design scheme which is easy to be loosened, but also increases the function of diversion switch which can effectively reduce the pain of patients. The results of animal experiments show that the intelligent diversion alarm system is stable, reliable and highly sensitive, which can effectively reduce the leakage of drug solution in high pressure injector.
Methods for High Voltage Transmission Line Detection Based on Image Recognition
Authors: Qiang Liu , Fangbo Gong , Zhiming Jiao , Juning Li , Xin Feng , Lichuan Wang 
Published: March 2020

Abstract
With the development of national economy, the demand for electric power from all walks of life is expanding. How to prevent and discover the natural disaster and accident that harm the transmission line in time has become an important basic work to guarantee the power supply. Image identification and automatic alarm system of transmission lines adopts image technology to monitor and analyze and process transmission lines, which can automatically identify and alarm the safe operation of transmission lines, provide basis for scientific decision-making of power enterprises, and improve response efficiency of natural disasters and accidents. Based on the research direction of identification and detection of transmission lines, this paper summarizes the commonly used methods of detection of transmission lines.
Weighted network community division based on co-neighbor nodes and similarity
Authors: Xiaoxia LUO , Xin SUN , Xiangyu LUO , Yunzhong LUO 
Published: March 2020

Abstract
In order to realize the accuracy of weighted network community division, based on the analysis of existing weighted network community dividing algorithm, a community dividing algorithm based on co-neighbor nodes and similarity is proposed. Firstly, the similarity between nodes is defined, and the weight of the edge is added to the local modularity function. Secondly, the Burt structural hole principle is used to select the important nodes. Then, the local clustering method is used to continuously expand the community. Finally, the judgment is made. The change of the Local modularity determines whether to continue the clustering, so as to obtain a more accurate result. Experiments on the simulation dataset and Zachary’s Karate club dataset show that compared with the CRMA algorithm, the algorithm is effectively improved in weighted network division time and accuracy.
A distortion image correction method based on machine vision
Authors: Tan Guangxing , Ding Ying , Fu Dandan , Wang Yuchen 
Published: March 2020

Abstract
As autopilot becomes a hot spot in the field of automobile, machine vision is widely used in autopilot technology, and calibration of camera parameters is the basic work of obtaining driving environment by using vision. In this paper, based on camera parameters and machine vision technology, the monocular camera image distortion correction algorithm is studied. Based on the perspective transformation principle, the method of controlling transformation point is used to correct the image. The black-and-white checkerboard is taken as the object of image acquisition, and the results obtained in this paper are compared with those obtained by the calibration toolbox camera calibrator of matlab camera. The algorithm proposed in this paper is used to correct the images collected in traffic environment, which lays a foundation for the subsequent recognition of traffic signs. The experimental results show that the distorted image correction results are good, the accuracy is higher, and it is practical and effective.
Edge detection methods and key parameters study
Authors: Li Qingyu 
Published: March 2020

Abstract
Edge is essential for diverse vision processing tasks and it constitutes a crucial part in the image of objects. There has already been a huge amount of researches about edge detection algorithms. The Canny method and the Sobel method are the most widely used techniques because of their relative advantages. Some parameters can drastically affect the performance and results of the two methods, which will be discussed in this paper. In addition, noise is also a factor affecting the number of the extracted edges. Experiment results have demonstrated that the noise filter will achieve better edge detection performance. Further improvements with suitable parameters of different applications for the two methods are possible.
Multivalued function recognition based on spectral clustering
Authors: Huang Zongchao , Zhang Zhaogong , Yu Guanwen 
Published: March 2020

Abstract
In scientific research, bioinformatics, Internet applications, e-commerce and many other application fields, the amount of data is growing at an extremely fast rate. To analyze and utilize these huge data resources, it is necessary to rely on effective data analysis technology. Big data application is a process of mining effective information from big data by using data analysis methods, providing auxiliary decisions for users and realizing the value of big data. In the process of data calculation and analysis, we will often find that the data from the same source will show multiple function images in the same coordinate system, which will make the same variable correspond to multiple values in data prediction analysis. We call it multivalued function here. This paper provides a method to identify multivalued functions. By using the maximum information coefficient (MIC) theory proposed by David n. Reshef, and using the data sampling method to calculate the function identifiability of the data set, then, the spectral clustering method is used for recognition, segment and mark the images of different functions. Finally, the regression function equations with different marks are obtained by Gauss-newton iteration method. The results can be used for data prediction and analysis to assist decision-makers to make reasonable judgments.