bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gyro movement equations
Authors: Díaz P. , Cid A. , Granados J. , Velázquez A. JM , Velázquez J. A. 
Published: March 2021

Abstract
In this work the motion equations of a gyro with essential characteristics were constructed, where the rotor rotates to reason ψ around an axis mounted on a single universal joint, which can rotate freely around the vertical axis. The angle formed by the rotor shaft and the plane of the meridian is denoted with θ, latitude, the angle of the position on earth is denoted λ and with ωe the angular velocity of the Earth around its axis.
Based on the formulation of Lagrange, the motion equations governing this system were obtained, differential equations were also solved with the standardized Runge-Kutta method of order 4. Also, we present several phase spaces that show the temporal evolution of the system.
Research on Key Technologies of large capacity and long distance optical transmission systems
Authors: Zhou Quan 
Published: March 2021

Abstract
In recent years, with the rapid development of high-bandwidth applications and the rapid growth of Internet data services, the capacity of communication networks is growing rapidly. Optical fiber has become an ideal transmission medium for communication networks due to its advantages such as large bandwidth and low loss. Large-capacity and long-distance optical fiber communication networks have become the key research directions of optical communication systems. In this paper, the main technical means to achieve large-capacity and long-distance optical transmission are investigated. First, the application of orthogonal frequency division multiplexing (OFDM) technology in large-capacity transmission is briefly introduced, including its principle, main structure, advantages and disadvantages. Subsequently, wavelength division multiplexing (WDM) technology based on optical frequency comb is introduced. Finally, the methods to realize long-distance transmission are discussed, including Digital Backward Propagation (DBP), Phase-Conjugate Twin Wave (PCTW) and advanced modulation format.
Temperature control circuit design of high-precision laser diode based on type III compensation network
Authors: Tang Yu-long , He Yu-ling , Meng Yan-song , Wang Wei-wei , Zhang Rong-yan , Du Er-wang , Du Li-jun 
Published: March 2021

Abstract
Since the performance of laser diodes is sensitive to ambient temperature, thermoelectric cooler temperature control circuits based on standard PID temperature compensation networks are usually designed to achieve diode constant temperature control. The thermoelectric cooler time constant and thermistor thermal time constant introduced in the temperature control system will reduce the stability margin of the system. In view of this, this paper designed a high-precision laser diode temperature control circuit based on the type III compensation network, and established the transfer function model, optimized the compensation network parameter tuning method, made the phase margin of the temperature control system reach π/8, and the long-term temperature control accuracy was better than 3 mK in the ambient temperature range of 5 to 40 °C.
Block Fast FIR Algorithm and Circuit Design
Authors: Wang Di , Wu Tiebin , Guo Feng , Hao Ziyu , Li Hongliang 
Published: March 2021

Abstract
The performance of finite impulse response (FIR) filtering is an important index of the real-time processing ability of digital signal processing system. In this paper, various FIR filtering algorithms are analyzed, and based on fast fir algorithm (FFA), block FFA (BFFA) is proposed. A 128 order configurable FIR filter circuit with 16 order as a block is designed. The analysis of experimental data shows that the 16 bit integer FIR filter performance reaches 881.78Gop/s.
Identification circuit based on memristor
Authors: Gao Chang , Li Tong , Cao Xinzhou , Liu Na , Li Quan 
Published: March 2021

Abstract
Aiming at the characteristics of the memristor with memory function in the circuit, the establishment of the memristor model and the simulation of the recognition circuit based on the memristor were carried out through the PSPICE simulation software. The NiO memristor was successfully fabricated on Si substrate by magnetron sputtering method, and the typical V-I hysteresis characteristic curve was obtained. Connecting the NiO memristor to the identification hardware circuit, the physical test results show that it is the same as the simulation diagram of the recognition circuit based on the memristor, which further confirms that the identification circuit based on the memristor has the learning function.
Distributed diffusion fusion cooperative spectrum sensing based on reinforcement learning
Authors: Jiang Lijun , Zhang Xiaoge 
Published: March 2021

Abstract
The openness and complexity of wireless channels make collaborative spectrum sensing vulnerable to malicious users[1]. Therefore, it is very important to identify the attributes of malicious users before collaborative spectrum awareness networks make data fusion decisions. In this paper, a method combining reinforcement learning and cognitive user credit model is proposed, in which the maximum and minimum eigenvalues of signals are used as the initial information for exchange, and the whole sensing network tends to diffuse and fuse nodes with high credit. Finally, the convergence value of the whole network is compared with the decision threshold to complete collaborative spectrum sensing. By combining with consensus fusion network and traditional collaborative sensing algorithm, the proposed method can effectively improve the convergence speed of fusion network and shorten the sensing time on the premise of effectively identifying malicious users[2], so as to improve the spectrum sensing performance and make the collaborative sensing network more adaptive and stable.
Research on telemetry data compression technology based on inter frame differential adaptive run length encoding
Authors: Fenglei Shi 
Published: March 2021

Abstract
Aiming at the problem of massive historical telemetry data storage in flight test, a lossless compression method based on adaptive interval run length encoding is proposed. Aiming at the problem of low compression efficiency of traditional run length encoding algorithm for word data, by studying the storage characteristics of telemetry data, this algorithm automatically identifies the frame format of telemetry data, and carries out longitudinal run length adaptive interval encoding for inter frame differential data to improve the compression efficiency. The test results show that the compression ratio of the improved algorithm is improved by 58.1% and 1.5% compared with the traditional run length encoding algorithm and the inter frame differential lateral run length encoding algorithm.
Influence of Retinal Degeneration Stages on RGC Threshold under epiretinal electrical stimulation: A Modeling Study
Authors: Zheng Shiwei , Zhou Wenqi , Song Xiaoyu , Li Liming 
Published: March 2021

Abstract
Retinal prosthesis is an effective treatment to restore partial functional vision for degeneration diseases such as retinitis pigmentosa (RP). The persistent degeneration of the retina can influence the effect of retina prosthesis. However, how the different stages of retinal degeneration influence the retinal ganglion cell (RGC) responses to external electric stimulation remains unclear. In our present study, we established the multilayer retinal model of normal mouse and retinal degeneration (rd1) mouse in different degeneration stages (early, middle and late stage). Meanwhile, the morphology-realistic RGC models with membrane dynamics in different degeneration stages were also established. The effects of retinal structure, ganglion cell morphology and Na+ conductance on RGC threshold in response to electrical stimulation were explored. The simulation results showed that the RGC threshold of early degeneration stage was basically the same as that of the normal retina. While the thresholds of middle and late degeneration stages were both higher than that of the early stage, and the late stage showed a higher RGC threshold than the middle stage. This study would provide theoretical support for personalizing design of visual prostheses to treat different degeneration stages of RP patients.
Mapping Algorithm of Multi - code combination spread spectrum technology for Short Packet Transmission
Authors: Lu Yikun , Dou Gaoqi , Zhang Wenjuan 
Published: March 2021

Abstract
Multi-code combined spread spectrum (MCSS) is based on M-ary spread spectrum to improve information payload by combining multiple spread spectrum sequences, which solved the contradictions between spread spectrum gain and transmission efficiency under limited channel bandwidth conditions. This paper focuses on two mapping algorithms of multi-code combination spread spectrum and their decoding algorithms for MCSS, which transmits the information by combining multiple spreading sequences. The R-combined mapping algorithm is provided to keep the sequence orthogonal and the design complexity increases with the increase of the number of correlators at the receiver while the SVC algorithm is adopted and MMP algorithm is used to realize multi-code combination spread spectrum with increasing sequences. The BER performance of the two algorithms is compared through simulation analysis
Application of 5G+VR technology in training and teaching of integrated wiring technology
Authors: Zheng Liping 
Published: March 2021

Abstract
The successful research and development, promotion and application of 5G technology in the new era will have a huge impact on the various industries in society. The development of computer and network technology plays an important role in promoting the practical training. VR technology is one of the important products of information and network technology. It takes multimedia technology as the core and presents knowledge to students more vividly in an audio-visual way, which can help students better understand. The paper analyzes the application of 5G+VR technology in the training and teaching of integrated wiring technology in detail, and aims to provide help for better application of 5G+VR technology.
Data-driven based optimization for high-speed dry cutting gear hobbing processing parameters
Authors: Wu Dayuan , Yan Ping , Pei Jie , Zhou Hui , Yi Runzhong , Guo You 
Published: March 2021

Abstract
The formulation of gear hobbing processing parameters relies on extensive professional knowledge and artificial experience, and inappropriate processing parameters will lead to low machining precision and high manufacturing costs. In order to obtain suitable processing parameters in high speed dry hobbing gear process, Gradient boosting regression (GBR) and Generalized Regression Neural Network (GRNN) are adopted to establish a process parameter optimization model targeting gear machining accuracy and machining energy consumption. And then a method based on Differential Evolution (DE) algorithm, parameter adaptive multi-object differential evolution (AMDE), for hobbing processing parameter optimization is proposed. Machining experiment verification shows that the established gear hobbing accuracy prediction model and energy consumption estimation model have high prediction accuracy, and AMDE has strong optimization capabilities and robustness.
Measurement of Small Defect Testing Accuracy in Additive Manufacturing Alloy Using Industrial CT Method
Authors: Guo Zhimin , Ni Peijun , Dai Yuelai , Zhang Weiguo , Huang Kuidong 
Published: March 2021

Abstract
This article is based on the application of industrial CT testing in additive manufacturing parts. Based on the existing industrial X-ray CT inspection equipment, it aims to solve the problem of identifying small defects under the uncertainty of test results. Under the premise of removing artifacts, this paper studies the measurement methods of small defects, and analyzes the uncertainty of the test results by designing a comparison test block. This paper combines theoretical analysis and experimental research, and compares the test results with the half-width method to study the accuracy of the test method. In order to improve the accuracy of industrial CT quantitative non-destructive detection of small defects, this paper closely studies the engineering application and combines the practical application of industrial CT to solve the basic problems of key research work.
Research review about the progress of transient electronics in sensor and electronic skin
Authors: Jiang Min , Gan Hua , Xiao Jinxing , Zhu Zhiyuan 
Published: March 2021

AbstractTransient electronics, a new type of electronic device, is made of degradable materials. After a programmed set period of operations, transient electronics can be partially or completely degraded when they are subjected to certain stimulus. Transient electronics can work normally without extreme conditions, and can degrade immediately after stable operation. It could supplement the limitation of traditional electronics, and could be of great interest for applications in electronic skin and sensors.
A Review of Research Topics of Safety Management Systems
Authors: Guo Chenggong , Jiang Feng , Chen Tao , Li Ying 
Published: March 2021

Abstract
Safety management systems(SMSs) is a systematic safety management method, which is widely used and researched all over the world. This article reviews the current literature of safety management systems, summarizes and analyzes eight important research topics at the theoretical level, practical level, and standard level, including analysis of the connotation and extension, effectiveness analysis, integration of a safety management system and other systems, steps and content of construction, evaluation, comparison and selection of standards. Furthermore, based on the above analysis results and the current status of the application of safety management systems in China, two recommendations on important research directions are proposed. The research indicates that in order to improve the application effect of safety management systems in Chinese enterprises, we should concentrate on the basic theoretical research. Three questions need to be answered urgently at this stage: “What is a safety management system (SMS)?”, “Why does it fail?” and “How to improve?”.
Study on the Construction of Safety Management System of Chinese Electric Power Enterprises Based on Systematic Thinking
Authors: Chenggong Guo , Feng Jiang , Ying Li , Yun Luo 
Published: March 2021

Abstract
In order to clarify the construction process and content of Safety Management System (SMS) and deepen the systematic construction of safety management of power enterprises in China, the paper analyses the current problems of SMS construction of domestic electric power enterprises. A construction method of SMS for China’s electric enterprises is proposed based on systematic thinking and system modelling method. Taking State Grid Corporation of China (SGCC) as an example, the construction model of SMS is designed based on the Hall three dimensions structure model. According to China’s national regulations and power industry safety management requirements, as well as practical experience of SGCC, ten core elements of the system were screened. The SMS operation cycle of Leadership-Responsibility-Plan-Do-Check-Act (LRPDCA) was designed based on the concept of Plan-Do-Check-Act (PDCA) and the characteristics of China’s power safety management. The results have some guidance significance to continually promote safety management capacity of electric power enterprise in the new era.
Web application vulnerability detection method based on machine learning
Authors: Hu Lilan , Chang Jie , Chen Ze , Hou Botao 
Published: March 2021

Abstract
In order to solve the security problems caused by network vulnerabilities, a web application vulnerability detection method based on machine learning is proposed to effectively prevent cross site scripting attacks of web applications and reduce the occurrence of network security incidents. Through the in-depth study of the existing security vulnerability detection technology, combined with the development process of machine learning security vulnerability detection technology, the requirements of security vulnerability detection model are analyzed in detail, and a cross site scripting security vulnerability detection model for web application is designed and implemented. Based on the existing network vulnerability detection technology and tools, the verification code identification function is added, which solves the problem that the data can be submitted to the server only by inputting the verification code. According to the server filtering rules, the network code bypassing the server filtering is constructed. Experimental results show that the model has a low rate of missed detection and false alarm, and the improved model is more efficient.
Challenges and Corresponding Solutions of Generative Adversarial Networks (GANs): A Survey Study
Authors: Chen Haiyang 
Published: March 2021

Abstract
Generative Adversarial Networks (GANs) are an innovative class of deep learning generative model that has been popular among academics recently. GANs are able to learn distributions on complex high-dimensional data which made it efficient in images and audio processing. Nevertheless, in the training of GANs, some major challenges exist namely mode collapse, non-convergence, and instability. In recent years, in order to overcome these challenges, researchers have proposed many variants of GANs by redesigning network architecture, changing the form of objective functions, and altering optimization algorithms. In this research, we conducted a comprehensive investigation on the progress of GANs design and optimization solutions. Finally, according to the classification method, we provided a problem-solving structure to solve conquer the GANs training challenges.
An Auto-segmentation and Measurement of Visceral Adipose Tissue On Ultrasound Image
Authors: Yi Shifan , Liu Paul , Liu Dong c. , Yin Hao 
Published: March 2021

Abstract
In order to effectively segment the visceral adipose tissue and help the doctors to rapidly diagnose the potential risks of metabolic syndrome, here we developed a deep learning-based method which is based on the U-net architecture for segmenting and measuring the visceral adipose tissue(VAT). And even no matter which orientation that the operator takes, the model can segment the visceral fat area and then use the appropriate outputs to compute the max thickness of VAT. One hundred and fourteen healthy volunteers were enrolled in this study. Ultrasound(US) was performed, and then the visceral adipose tissue was segmented and measured by the model that we use. We regard the distance behind the linea alba in the xiphoid process as the thickest visceral adipose tissue(VAT max). The dice score and accuracy are 3.46%, 96.44% respectively. In addition, compared with the manually outlined segmentation, the pearson correlation coefficient and the mean relative error (MRE) are R=0.9231 (P<0.001) and 10.12% in the measurement of the VAT max between original and output images. The auto-segmentation and measurement of visceral adipose tissue on ultrasound method demonstrate the accuracy of deep learning in segmentation and measurement of visceral adipose tissue.
Citation Recommendation based on Citation links Explanation
Authors: Zhang Yanping , Lin Dongyang , Chen Xi , Qian Fulan 
Published: March 2021

Abstract
With the rapid increase of scientific papers, it is difficult for researchers to obtain appropriate references. Due to the black-box property of neural network, the existing content-based citation recommendation methods are mainly embedding text into a low-dimensional space, and citation links are not interpretable (e.g., paper A cites paper B because of topic X). To solve this problem, we propose a Weighted Citation Network with Citation Links Explanation (WCN-CLE) algorithm. Because citation links mainly depends on the content, we need to explore textual reasons for citation links. Firstly, we extract word fragments through citation network information for each citation link as its explanation. Secondly, we construct a weighted HIN network with two kinds of vertex (paper and author). The weight of each edge is calculated by its word fragments. Then the query document is linked to the HIN network through author information and word fragments similarity with candidate papers. Finally, each vertex’s feature representation is obtained by network representation learning method, and recommend papers through vector similarity. Experimental results on two real-world datasets show that WCN-CLE has better performance due to its integration of structural information and semantic information.
An Adaptive End-to-end Codec based on Multi-source Fusion for UAV Equipped with 5G NSA Network
Authors: Su Yu , Cheng Qianqian , Wang Shuijie , Qiu Yuhe 
Published: March 2021

Abstract
This paper proposed an adaptive end-to-end codec based on multi-source fusion. Our codec adjusts the coding scheme according to the channel condition adaptively, selects deep recursion when the channel is good to obtain sufficient and effective information, and shallow recursion to ensure the transmission of key frames when the channel condition is poor. Besides, communication information is also imported into the codec through parallel branches to avoid confusion caused by multiple sources. We test on the DJI M210 UAV equipped with 5G network to verify the usability of the adaptive end-to-end codec both quantitatively and qualitatively. Under the same target detection level, our codec provides higher compression rate, and adjusts the compression rate to adapt to different conditions.
Application of weighted sample entropy in detection of abnormal signal
Authors: Zhang Hong , Lv Shengze , He Shasha 
Published: March 2021

Abstract
An improved sample entropy (SE) algorithm named weighted sample entropy(WSE) is proposed in this paper to optimize the problems existing in SE based on weighting. The principle of WSE algorithm is given, and the performance of it for dynamical change detection is analyzed using synthetic signal. The results show that WSE can accurately capture amplitude information and amplify the detection results of dynamical changes compared with SE and PE in the case of high complexity, but it requires a higher computation cost than the others. From all the analyses in this paper, we find that WSE has a better performance for dynamical change detection compared with the other three algorithms in abnormal amplitude.
Analysis of Object Detection Performance Based on Faster R-CNN
Authors: Li Wenze 
Published: March 2021

Abstract
The related regions with convolutional neural networks (R-CNN) models have been widely used in the field of object detection. Faster R-CNN significantly improves the overall performance by adding RPN, especially in terms of detection speed. However, the application of different pre-training models will result in a great difference in the performance of Faster R-CNN. This paper analyzed the performance of Faster R-CNN models based on different pre-training models and conducted a comprehensive evaluation of the performance of Faster R-CNN. The experimental results showed the accuracy and detection speed of R-CNN, fast R-CNN and faster R-CNN based on three different data sets. They can objectively and comprehensively evaluate the performance of R-CNN, fast R-CNN, and faster R-CNN.