bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structure Optimization of Electromagnetic Railgun Armature Based on Machine Learning
Authors: Yu Zhenyuan 
Published: March 2021

Abstract
The armature is an important part of the electromagnetic railgun. It may break, wear, and transition during the working process, which increases the difficulty of maintaining the railgun and impairs the service life of the railgun. Therefore, studying the armature structure of the electromagnetic railgun is of great significance to the design of the electromagnetic railgun. This paper selects the five armature structure parameters of armature shoulder thickness, tail length, wing tip thickness, front end thickness, and interference, and focuses on "using armature structure parameters to predict prestress" and "using prestress and other armature to predict the interference of structural parameters". This paper uses the linear regression method in machine learning to construct the model, and use the normal equation method and the regularized normal equation method to optimize the loss function. The results show that the normal equation method is generally effective for the electromagnetic railgun structure optimization problem discussed in this paper.
Effect of Rehydration Ratio and Inlet Pressure on Shock Wave Focus in Hemispherical Concave Cavity
Authors: Peng Wenrui 
Published: March 2021

Abstract
Shock wave focus is a phenomenon where energy is rapidly converged in a small area of the medium through the interaction of shock waves, resulting in extremely high temperature and pressure near the aerodynamic focus. Experimental and numerical studies are in progress using the high energy area generated by shock wave focus to induce detonation to study shock wave focus phenomenon, the experiments of shock wave focus in the hemispherical concave cavity was carried out. The emphasis is placed on the effect of ring vent width and inlet pressure. By comparing the peak pressure at the bottom of the concave cavity under different ring vent widths, it was found that the reflection of the incident shock wave formed in the channel decreased with the width of the ring vent as well as the intensity of the shock wave increased. The greater the intensity, the more likely it is to produce the focusing of the shock wave. When the subsonic speed airflow flowed into the cavity through the ring vent, it was found that under the influence of the reflection of the concave cavity and complex motion of shock wave, a local high temperature and high pressure area was formed. By comparing the pressure spectrum at the bottom of the concave cavity under different flow pressures, it was found that with the increase of the flow pressure, there were two whistling modes on the spectrum map, C1 and D1 modes, respectively. It was also found that the pressure pulsation in the concave cavity was more disordered and the magnitude was smaller when the inlet pressure decreased, which means the shock waves were not well focused. It can be concluded that in ignition experiments, inlet pressure is significant to shock wave focusing phenomenon and there is a prompt rehydration ratio which lead to better shock wave focusing.
Research on an Analysis method of Engineering Mechanics in Bridge Field based on Machine learning
Authors: Gao Xinyi 
Published: March 2021

Abstract
The identification of bridge cable force has a great influence on the safety and reliability of arch bridge structure, which is a difficult problem in bridge construction. According to a certain tension sequence, the required sample library of suspender cable force is obtained by establishing the finite element model by MIDAS software. The designed cable force of the bridge is taken as the input vector of the radial basis function method (RBF method), and the initial cable force obtained is the output vector. The solution accuracy is controlled by distributed density parameters, the nonlinear mapping relationship between them is approached, and the initial cable force of suspender is calculated directly. The experimental results show that the error between the calculated value and the design value of the cable force can be controlled within 5% by the BRF method, which meets the engineering requirements.
Design and Verification Test of the Primary and Secondary Stage Compression Gap Size of Miniature High Pressure Air Compressor
Authors: Yang Lihua , Fang Bo , Qu Shengguan , Li Xiaoqiang , Mao Tao , Gao Hongyun , Xia Yumeng 
Published: March 2021

Abstract
Aiming at the prominent problem of the primary and secondary pistons hitting the cylinder head in the current miniature high-pressure three-stage air compressor, a design study on the size of the primary and secondary compression gap is carried out. Through the theoretical force analysis of the connecting rod, the force situation of the connecting rod at the top and bottom dead centers is obtained. The three-dimensional models of connecting rod and cylinder are established based on SolidWorks software, and the three-dimensional models are simplified. Based on Ansys Workbench software, the connecting rod and cylinder models are pre-processed, model discretized and post-processed. The structural statics and steady-state thermal comprehensive analysis of the connecting rod at the upper and lower dead points and the steady-state thermal analysis of the cylinder under working conditions are completed. Through analysis, the total axial deformation of the connecting rod and the total axial deformation of the cylinder under high temperature and high speed working conditions are obtained. According to the simulation analysis results, the first and second compression gap size is designed. Based on the design results, ten sets of air compressors are tested for dimensional design verification. The test results show that the air compressors of each test group can complete the charging requirements within the specified time, and there is no phenomenon of piston hitting the cylinder head, indicating the size design reliability.
A Design of Lowpass Filter with High Suppression in Stopband
Authors: Jin Liang , Li Xiaojun 
Published: March 2021

Abstract
Beeline compact microstrip resonance cell (BCMRC) is improved to reduce return loss. A lowpass filter in terahertz band is formed by two improved BCMRC cells and a central microstrip, which make the two cells incorporate into one structure successfully. The filter has widened stopband and high suppression characteristic under the same filter’s order. The optimized result is proposed with an insertion loss of less than 0.4dB in the lowpass band from 0 to 100GHz. The stopband with attenuation more than -20dB is from 140GHz to 350GHz, and the stopband with attenuation more than 40dB is from 158GHz to 312GHz. The size of the low-pass filter is 0.8mm×0.4mm, and this filter can be used in mixer or other devices of terahertz.
2μm widely tunable thulium-doped fiber laser seed oscillator
Authors: Hu Peixin , Ji Encai , Nie Zilin , Deng Jinchao , Yao Lu , He Zhengdi 
Published: March 2021

Abstract
2μm band laser can be used in transparent plastic welding, soft tissue laser surgery, LiDAR, toxic hazard gas sensing and medium-and far-infrared parametric oscillation conversion. However, there are still many problems that need to be clarified on how to break through the peak power limit, realize pulse time domain programmable and laser wavelength wide range tuning in the nanosecond thulium fiber system. In this experiment, wide tuning laser at 2μm band was used to realize different laser wavelength, constant seed laser power output, and EOM was used to define laser pulse waveform and pulse frequency.
Research on Low-Power Main Control Chip Architecture Based on Edge Computing Technology
Authors: Cui Guoyu , Ye Wei , Hou Zhanbin , Li Tong , Liu Ruolin 
Published: March 2021

Abstract
With the continuous development of the times, chip technology has also been innovated. In order to meet the needs of edge computing networks and data communication networks, it is necessary to make chips with shorter delay time and lower power consumption, which in turn brings challenges to chip architecture design. In the field of chip design, the problem of chip performance has been overcome. In many edge design networks, the core of the design is to allow the chip to meet low power consumption requirements, thereby extending the use time of edge devices. This article conducts research on a low-power master chip architecture to enable it to meet the needs of edge computing networks and enhance product competitiveness.
Research on Track and Field Teaching and Training Based on Computer-Aided Analysis
Authors: Lu Changchun 
Published: March 2021

Abstract
At present, the primary method of sports biomechanics research in track and field events is to use a high-speed image analysis system to monitor the training process and obtain kinematics information through special or general analytical software. To improve the training efficiency and correct the defects of technical movements in time, coaches urgently need a kind of equipment that can feedback the movement information in time during the training. Because of this situation, a track and field training information acquisition and feedback system based on a digital track are proposed based on sufficient condensing project requirements. The system USES flexible array sensors obtain contact interaction information during the run-up, and USES special analytical software to process kinematic parameters in an integrated manner, providing real-time biomechanical parameters such as step length and speed step frequency, and takeoff force in the process of moving. The system realizes the comprehensive analysis of sports representation and internal mechanical factors, which helps coaches and athletes to deeply grasp the internal law of the project. Its effectiveness and scientificity have been preliminarily verified through the athletes’ testing in the national track and field team’s long jump event.
Design and Implementation of Information Service System of Hunan Regional Seismic Network
Authors: Tang Hongliang , Zhang Yimei , She Xuming , Kang Chengxu , Tian Youping 
Published: March 2021

Abstract
In this paper, the framework of one-stop application service system of Hunan Regional Seismological Network is introduced, taking the fast earthquake reporting of Hunan Regional Seismological Network as an example, in order to realize the automatic, one-stop application service of graphic and text data display, which integrates "obtaining earthquake parameters-issuing earthquake message-completing website earthquake situation update-automatically sending fax".
Optimization of Train Operation Scheme for Container Sea- Rail Multimodal Transport
Authors: Hu Guojie , Sun Wanhua , Jiang Jian 
Published: March 2021

Abstract
In the past, the external costs, such as transportation costs and transit costs, are usually considered in the model of container sea-rail multimodal transport, without considering the time value cost of goods and the social costs such as traffic accident cost and environmental pollution cost caused by the transportation process. Goods transportation is a kind of social and economic activity. The whole transportation process of goods from the place of departure to the destination needs time. When time is connected with specific social and economic activities, it has value, that is time value. [1] The time value cost of goods will become a large part of the cost in the process of transportation. Improving the efficiency of goods transportation is a major goal of goods transportation. However, while improving the efficiency of goods transportation, we should also take into account the social costs brought about by the transportation of goods. In this paper, the time value of goods and social cost are considered to optimize the operation scheme of container sea-rail multimodal transport trains.
Line loss prediction based on particle swarm optimization combined with extreme learning machine
Authors: Qin Huaqin , Liu Jianfeng , Guan Yiqun 
Published: March 2021

Abstract
As a key economic index to measure the planning and management level of power grid company, line loss is not only the main content of completing the construction and transformation task of power grid company, but also an important assessment standard for the operation level of power grid company. In order to improve the generalization ability and prediction accuracy of extreme learning machine (ELM), particle swarm optimization (PSO) algorithm is applied to extreme learning machine (ELM), and a line loss prediction method based on PSO combined with ELM is proposed. The particle swarm optimization algorithm is used to select the optimal hidden layer deviation and input weight matrix to calculate the output weight matrix, so as to improve the accuracy and stability of the extreme learning machine. Experimental results show that the proposed method can effectively improve the accuracy of line loss prediction.
The Application of Financial Mathematics in the Market Analysis of the Electrical Industry
Authors: Wu Linlin , Liu Kai , Zhou Wei 
Published: March 2021

Abstract
With the rapid development of the financial market in the economic field, more and more financial problems need to be solved with mathematical knowledge. This article combines the development history and current status of each electrical appliance, from the three aspects of solvency, operating capacity and profitability. In terms of analyzing the company’s financial ratio, the company’s current ratio, asset-liability ratio, return on equity, and total return on assets of the company in the past three years were calculated.The analysis of these indicators revealed that the assets of Shanghai Liangxin Electric Co., Ltd. The debt ratio is extremely low, and the risk is small. However, in comparison with competitors in the same industry, we find that the company’s profitability is at the middle and upper levels, and the overall development trend is good in the past three years, but it is generally higher than the industry’s advanced level. Companies still need improvement.
Research on Mobile Terminal Technology Supporting Intelligent Maintenance of Substation
Authors: Zhao Zhanglei , Yang Jianyou , Xi Honglei , Wang Jiaxing , Gao Bingwei 
Published: March 2021

Abstract
In view of the fact that traditional substation maintenance operations need to carry a large amount of paper data and the on-site paperlessness is low, a mobile terminal supporting intelligent maintenance of substations has been developed. Introduce the development background, system integration scheme, various management functions of the device and its application in substation maintenance operations, recorder viewing and grid fault analysis. The application of the mobile terminal can improve the intelligence level and convenience of on-site maintenance operations, shorten maintenance time, improve maintenance quality, and improve the level of relay protection lean management.
Design of Simulation and Verification Software of Crew Operation Program
Authors: Yang Shuo , Wang Yingsheng , Man Yi 
Published: March 2021

Abstract
For easily and timely simulating and verifying the design of crew operation programs, improving the rationality of the design, the open source graphic display framework Qt based on the Windows platform is used to design and development of crew display and operation software. It can provide support for the system designers to further optimize the design. This program has been adopted in a pre-research project with major background.
Research on Information Security System of Ship Platform Based on Cloud Computing
Authors: Lin Tao , Zhao Yang , Zhang Haotian , Li Guobing , Zhang Jian 
Published: March 2021

Abstract
To improve ship positioning identification and implementation monitoring, ensure the safe navigation of ships, and optimize ship information retrieval design, the paper proposes a ship information retrieval system based on cloud computing technology. It adopts the fuzzy C-means clustering method for ships, the classification and processing of the subordinate characteristics of the information, the design of the ship network video monitoring system, some study of the critical technology of cloud computing technology, and the algorithm of the video image detection. The simulation results show that this system has a siginificant improvement on accuracy and recall rate of ship navigation safety information monitoring. The system is a ship-shore integrated monitoring platform that meets maritime safety requirements and the needs of low- carbon management with outstanding efficiency.
Convergence of Online Gradient Method with Momentum for BP Neural Network
Authors: Pan Chengyan , Xie Gang 
Published: March 2021

Abstract
The BP neural network, which uses the steepest descent method (gradient descent method) as the basic idea for learning, is often used to deal with approximation problems because of its strong nonlinear mapping ability. The gradient method with added momentum can improve the learning speed of BP neural network. We study the convergence of the online gradient method with momentum for two-layer BP neural network when the training samples are randomly arranged in each iteration. Choosing appropriate learning rates, and selecting momentum coefficients in an adaptive manner, we prove the weak and strong convergence theorems of the algorithm.
The Influence of Speech Translation Technology on Interpreter’s Career Prospects in the Era of Artificial Intelligence
Authors: Jiang Kai , Lu Xi 
Published: March 2021

Abstract
As the advancements in artificial intelligence, discussions on whether machine translation will replace human translation are found in the media and the public, but scholars have rarely explored this in research. This paper first reviews the history and recent progress in speech translation technology, and analyzes its merits and limitations. Then, in view of the history and features of the interpreting profession, the paper discusses the influence of speech translation technology on interpreter’s career prospects. The author holds that even if future speech translation technology is highly sophisticated, it still cannot completely replace human interpreters. Artificial intelligence is considered as both a challenge and an opportunity for the translation industry. The future trends in interpretation will be mainly human-led and machine-aided. After analyzing the trends and challenges to the interpreting profession, the paper proposes suggestions to interpretation teaching, hoping to give reference to interpretation teachers, learners and researchers.
Performance research and Simulation analysis of magnetorheological torque servo device
Authors: Sha Shujing , Zhang Fuhao 
Published: March 2021

Abstract
This paper expounds the rheological mechanism of magnetorheological fluid and the working principle of magnetorheological moment servo, studies the relationship between excitation current and magnetic field strength, magnetic flux and magnetic flux potential, and analyzes and designs the magnetic circuit. The electromagnetic analysis of the magnetorheological moment servo device was carried out by ANSYS software, and the relevant information such as the distribution of magnetic field lines and magnetic induction intensity was analyzed. The relationship between excitation current and magnetic flux density was obtained by fitting the data under different excitation current. The quantitative relationship between the input current and output torque of the magne-orheological drive device is simulated by matlab software.
A Dynamic Reconfiguration Scheme for Embedded System Based on Multi-core DSP
Authors: Liu Xiaojian , Liu Shuo , Lv Hao 
Published: March 2021

Abstract
High-performance embedded system is needed in high-speed and accurate avionics control systems, but its hardware resources are limited. It is of great significance to reuse hardware resource through static or dynamic reconfiguration. A dynamic local reconfiguration scheme is designed based on c6678 isomorphic multi-core DSP to realize the dynamic reconfiguration of software on a single core under the premise of ensuring the normal operation of the whole system. This reconfiguration scheme can realize the complete switching of software on the whole core and realize the time division multiplexing of multiple algorithms in the same memory space. Experimental results show that the scheme can fully meet the requirements of real-time.
Research and development of "Internet + training" collaborative simulation platform
Authors: Wang Jin , Li Jie , Kang Yi , Wu Ping , Sun Aichun 
Published: March 2021

Abstract
This article introduces a development method of "Internet + training" collaborative simulation platform. It explains in detail how to make full use of Internet technology to bring convenience to the development of power system simulation training platform, and to solve the problem of coordination of simulation calculation. The method can effectively use the computer resources of the training system, avoid the waste of resources of the training system on the simulation computing platform, and reduce the investment in hardware equipment. Finally, this article verifies the feasibility of the development method proposed in the article through a practical case.
The Study of Imaging Methods for Sparse Targets through Walls with Fuzzy Wall Geometry Parameters
Authors: Sun Yanpeng , Sun Lu , Qu Lele 
Published: March 2021

Abstract
Multipath exploitation has been successfully applied in through-the-wall radar imaging given prior knowledge of the room geometry. Actually, the prior information of the walls is generally not known. A Contraposition Subtraction (CONS) algorithm is proposed to solve the problems of poor wall parameter reconstruction accuracy and extremely high initial value requirements of iterative algorithms under fuzzy wall geometry, and the CONS algorithm model is established to solve the problems of high initial value requirements of traditional quasi-Newton algorithms and improved quasi- Newton-particle swarm optimization algorithms. The estimates obtained have large errors and other problems. The CONS algorithm combined with the Block Orthogonal Matching Pursuit (BOMP) algorithm can not only accurately reconstruct the position of the sidewalls, but also reconstruct the moving and stationary targets, which improves the limitations and accuracy of the algorithm to a certain extent. The simulation results and data analysis verify the performance of the proposed method.
Review of Deep Learning Algorithms in Computational biochemistry
Authors: Sino Nezar Ismet , Farhan Rabah N. , Seno Mohammed E. 
Published: March 2021

Abstract
Biochemistry actually is a fertile pool of resources, including modeling, DL and optimization techniques for chemical data and associated phenomena. Computational Biochemistry is a very effective entity. These include rapid literature research, physical and quantum chemical propaganda analyzes, transition states, chemical structures, chemical reactions as well as new catalysts and candidates for drugs. DL algorithms can integrate raw input into intermediary layers of features and successfully fit the desired compound into optimum combinations. This review study introduces a series of biochemical applications with the most exciting discoveries involving the use of DL in wide range of applications such as Modeling bio-processes, algorithms and methods to promote the design and synthesis of bio compounds, material design, binding forecasting and molecular activity are given special importance.