bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of follower motion law and optimization of fitting function in reverse design of cam
Authors: Ji Zhaoping 
Published: February 2021

Abstract
Because of its compact structure and reliable performance, the cam mechanism has been widely used in automatic machinery, such as automatic tool changing system, packaging machinery, automatic production line, automatic switching system and so on. At present, a variety of common drive and control devices have been developed with arc cam as the core component. The cam indexing mechanism is a new type of transmission device to realize high speed and high precision intermittent indexing motion. It is widely used and has been studied by more and more scholars at home and abroad, and has achieved remarkable results. At present, its theoretical research has matured. However, because the profile of indexing cam is a non-spiral surface in space, it brings inconvenience to the design and manufacture of cam. When the arc cam is damaged and the design parameters of the original arc cam cannot be known, the original arc cam profile can only be obtained by measuring limited data. In the original parameterized design method, the profile of the arc cam is determined by the motion law of the follower. If the motion law curve of the follower can be obtained, the contour curve of the arc cam can be obtained in reverse. So the problem of solving the profile surface of the cam can be transformed into a follower which meets the requirements the curve of motion law. Taking the CAM Z175 as an example, this paper describes in detail the whole process of motion rule analysis, optimization of the motion law curve and simulation verification in CAM reverse design.
Design of non-magnetic temperature control system for atomic vapor cell of atomic magnetometer
Authors: Jin K , Hu H , Liang Z , Geng X X , Wu T Y , Qu J L , Tang W W , Wang M , Li G X , Liang S Q , Yang G Q , Huang G M 
Published: February 2021

Abstract
In order to make the atomic magnetometer work, the heater of the atomic vapor cell must ensure that the temperature can be accurately controlled and the magnetic noise should be reduced as much as possible. This work proposed a non-magnetic heater and designed a corresponding temperature control system. It shows that the heater structure has good heat preservation performance and so, control of the heating process is made easy. The test results indicate that the fluctuation range of vapor cell temperature is less than 0.018°C, 0.015°C and 0.006°C respectively at 40°C, 50°C and 60°C. The effect of heater on the magnetic field cannot be observed by fluxgate magnetometer HS-MS-FG3LN-100 (<300pT).
Degradation analysis and optimization of temperature effect on MEMRISTOR-based Neural Network Accelerators by electro-thermal simulation
Authors: Shang Mengjun , Yin Longxiang , Xu Ning 
Published: February 2021

Abstract
Nowadays, memristor-based neural network accelerators have been widely studied due to their outstanding performance in massive parallel vector matrix multiplication. However, the memristor is sensitive to temperature and its on/off state operation window can be seriously degraded by the increasing temperature, which may lead to computation failures in memristor -based NN accelerators. In this work, we establish an electro-thermal simulation platform to evaluate the temperature impact on memristor -based NN accelerators. With this platform, we first investigate the impact on computation accuracy with the temperature increase in different NN layers in the accelerators. We then apply a temperature-aware NN weight mapping scheme to the most temperature-sensitive layer and achieve 28.89% improvement in computation accuracy, which only has 0.06% difference with the improvement achieved by applied the mapping scheme to the whole NN model. This finding can help to simplify the temperature-aware hardware optimization design in memristor-based neural network accelerators and reduce the power consumption.
Analysis research of industry accident law based on barrier theory and text semantic recognition technology
Authors: Yan Hongqiao , Tian Kun , Fan Zhiqiang , Mao Yaming 
Published: February 2021

Abstract
One of the important reasons for the repeated occurrence of the same type of accidents in the group company over the years is the insufficient utilization of accident resources. This paper introduces barrier theory and establishes an accident analysis method system based on barrier theory. Barrier theory changes the traditional accident analysis mode, and adjusts the object of accident analysis from consequence to barrier, which provides a new perspective for the analysis of accident law. This paper develops a HSE text semantic recognition model which can automatically extract the production operation link, production stage and type of failed barriers of the accidents from the accident investigation report, finds out the cause factors leading to the failures of these barriers and establishes a direct relationship with the HSE(Health, Safety and Environment) management system, in a way to find out some common laws of the accidents and reveal the defects and shortcomings in business management.
The integrated application of computer software in architectural space design
Authors: Yin Le , Lu Zheng 
Published: February 2021

Abstract
The characteristic of computer software for drawing construction drawings, making 3D models and rendering space effects is to express design concepts intuitively. Through training and mastering computer software technology, architects can accurately describe the structural relationship, proportion relationship, shape color and material texture of buildings in the process of drawing. Through the design works of architect Sou Fujimoto, this paper visually observes the integrated application of computer software in architectural design.
A strongly secure PF-CL-AKA protocol with two-way ID-based authentication in advance for smart IoT devices
Authors: Zhang Zhishuo , Sun Yu , Zhang Wei , Wu Yi , Qin Zhiguang 
Published: February 2021

Abstract
With the rapid advancements of semiconductor technologies and wireless communication, Internet-of-Things (IoT) based network has a wider range adoption in the smart city. The Wireless Body Area Network (WBAN) is a representative IoT based network designed to connect various wearable IoT devices, located inside or outside of a human body. The WBAN typically connects itself to the mobile network and Internet via the smartphones. But how to mutually authenticate the entities’ identities and ensure the data confidentiality and integrity during the data transmission over a channel have still been the most prominent challenge in the IoT based networks. To solve the abovementioned challenge, in this paper, we propose a strongly secure pairing-free certificateless authenticated key agreement (PF-CL-AKA) protocol with two-way identity-based authentication before extracting the secure session key for the smartphones and wearable IoT devices. Our protocol is provably secure in the Lippold model, which means our protocol is still secure as long as each party of the channel has at least one uncompromised partial private term.
A Wavelength Selection Model Based on Successive Projections Algorithm for pH Detection of Water by VIS-NIR Spectroscopy
Authors: Li Lina , Guo Shangxing 
Published: February 2021

Abstract
A novel pH detection method using VIS-NIR (visible near infrared) spectroscopy for water is introduced in this paper. In order to improve prediction accuracy and calculation speed of pH detection using VIS-NIR spectroscopy, a wavelength selection model of SPA-MLR (successive projections algorithm and multiple linear regression) is proposed. Two experiments (pH measurement experiment by VIS-NIR spectrophotometer and pH measurement experiment by VIS-NIR grating spectrograph) are employed to evaluate the performance of SPA-MLR. At meanwhile, PLS (partial least squares), GA-PLS (genetic algorithm and partial least squares) are introduced to compare with SPA-MLR. The results indicate that, the prediction accuracy and calculation speed of SPA-MLR are all better than that of PLS and GA-PLS. Under the pH measurement experiment using VIS-NIR spectrophotometer, only one wavelength is selected from 351 original wavelengths for calibration, the RMSEP (root mean square errors of prediction) is 0.35, and the model training speed is 2.36s. Under the pH measurement experiment using VIS-NIR grating spectrograph, 3 wavelengths are selected from 2860 original wavelengths for calibration, the RMSEP is 0.50, and the model training speed is 56.45s. For the two experiments, the selected wavelength variables by SPA are distributed mainly in the band of 870 nm to 990 nm.
Research on UE4 - based Visualization Simulation of Underwater Vehicle Polar Region Sailing
Authors: Wang Luobin , Ge Jingyu , Li Pengcheng , Cheng Jianhua 
Published: February 2021

Abstract
With the continuous exploration of polar sea areas, the reliability and safety of polar navigation have become the top priority. Due to various influencing factors in the polar region, including sea ice, ocean currents, geomagnetism, gravity, etc., navigation equipment in the polar region cannot achieve the performance of the mid-low latitude region. Because of the limitation of the actual ship entering the polar region, the performance of navigation system in polar region cannot be fully verified. It is difficult to verify the performance of equipment on a real ship. In order to reduce the cost of the experiment while ensuring the accuracy of the verification and making the simulation training system available at the same time. Based on UE4(Unreal Engine4) to design a virtual 3D visual simulation platform of underwater vehicle that is able to simulate the six-degree-of-freedom(6-dof) motion of the underwater vehicle and verify the performance of navigation equipment in polar region. Verify the virtual simulation platform is able to simulate the movement of underwater vehicle in the virtual polar sea and realize the operation training simulation of underwater vehicle.
Simulation of Cooperative Positioning Flight Ad-hoc Network
Authors: He Chenglong , Yu Baoguo 
Published: February 2021

Abstract
Cooperative positioning method is necessary for multiple rotor-winged drone swarm applications for airborne satellite navigation receiver has less usability in urban canyon, which could be achieved by drones’ FANET (flight ad-hoc network): each drone broadcast and receive wireless signals containing measurement information with its neighbour drones, then calculate the relative position results or absolute results when some drone could positioning by satellite navigation receiver, to reduce the communication demand all drones distributed to multi-subnet dynamically. A simulation of the cooperative positioning process was shown, which achieves the continuous relative positioning result in denial environment.
Numerical Investigation on Gas Accumulation and Gas Migration in Enlarged Boreholes of Horizontal Gas Wells
Authors: Li Wentuo , Meng Lingyu , Du Xu , Huang Yi , Luo Ming , Deng Wenbiao 
Published: February 2021

Abstract
The horizontal section of the horizontal gas well will form a horizontally enlarged borehole due to factors such as the collapse of the well wall, and it is easy to form gas accumulation in the enlarged section, which will cause accidents such as overflow. Therefore, it is very important to study the gas accumulation law in the horizontal enlarged section. Based on the actual horizontal wellbore size, a three-dimensional horizontal rectangular-enlarged borehole model and a three-dimensional horizontal curved-enlarged borehole model are established in this paper to simulate the phenomenon of gas clustering in the enlarged diameter section. The research results show that, under the same length of the enlarged section, the gas discharge of the horizontally rectangular-enlarged borehole is difficult, which is more likely to cause gas accumulation, but the horizontally curved-enlarged borehole is less likely to cause gas accumulation; When the fluid flows through the horizontal enlarged diameter section, the pressure will increase and the pressure flowing out of the expansion section will decrease, and the faster the flow velocity, the greater the pressure in the expanding section.
Predict and Analyze Exchange Rate Fluctuations Accordingly Based on Quantile Regression Model and K-Nearest Neighbor
Authors: Zhang Dongyang , Wang Xiaojie , Gao Liyuan , Gong Yicheng 
Published: February 2021

Abstract
The exchange rate is one of the important indicators to measure macroeconomic fluctuations. The exchange rate of the US dollar against the RMB reflects the currency exchange rates of the world’s two largest economies. As a global emergency, the new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) has a significant impact on all aspects of society, so fluctuations in the exchange rate market cannot be ignored. This article uses the daily exchange rate of USD to RMB published on the official website of China Merchants Bank as the dependent variable representing the economic situation. The daily new confirmed cases of new coronavirus pneumonia confirmed by the National Health Commission, the number of new deaths each day, and the number of new cured cases each day are the influencing variables, and the Shanghai Interbank Offered Rate is used as the control variable. In order to explore the relationship between variables and predict and analyze exchange rate fluctuations accordingly, multiple linear regression and quantile regression are used for impact analysis. Comparing the prediction results of the multiple linear regression and the K nearest neighbor model, it is found that daily new confirmed cases, daily new cured cases, and market interest rates harm the exchange rate. At 0.5 quintile, the number of newly diagnosed cases per day increases by 1 unit, and the exchange rate of the U.S. dollar to the renminbi will correspondingly decrease by 0.00001%. At the 0.75 quantiles, new cured cases will change by one unit every day, and the exchange rate will change. The percentage is -0.00003%, the market interest rate changes by one unit, and the percentage of exchange rate changes are -0.037%, which is significant. And after comparison, it is found that the prediction effect obtained by the K nearest neighbor model is better than the multiple linear regression model. At the beginning of the epidemic, the exchange rate fluctuated by 1.78%. After the government took a series of prevention and control measures against major emergencies, the epidemic was effectively controlled, worries gradually eased, and the exchange rate has returned to a relatively stable state.
Application of Semantic Analysis System in Intelligent Navigation Path Planning Based on Pulse Lidar Profiler
Authors: Yang Zhongyi , Tao Li 
Published: February 2021

Abstract
The daily operation and maintenance of rock tunnel and coal mine roadway focuses on ensuring safety and data validity. Although a lot of related research has been published, most of them focus on one or several categories of dangerous situation handling. This research combines the concepts of pulse lidar profiler and semantic analysis system, and proposes a new system oriented security operation and maintenance method. The scanning of the conventional area can even be skipped in the case of time constraint, but the sub key area and the primary key area must be scanned and monitored strictly according to the scanning times converted from the weight value of real-time calibration. For the primary focus area, the maximum scanning cycle of 7 cycles can be specified directly. In short, it classifies the continuous spatial point cloud data scanned by pulse lidar profiler through semantic analysis system, and allocates weights according to different classes of object mapping, and makes multiple scanning decision arrangement for high weight classes.
Image Classification Algorithm Based on Improved AlexNet
Authors: Li Shaojuan , Wang Lizhi , Li Jia , Yao Yuan 
Published: February 2021

Abstract
Aiming at the problems that the traditional CNN has many parameters and a large proportion of fully connected parameters, a image classification method is proposed, which based on improved AlexNet. This method adds deconvolution layer to traditional AlexNet and classifies the images by full connection layer. Using Cifar-10 data set to test the classification algorithm. The results indicate that the method not only reduces the number of parameters and parameters proportion of the full connection layer, but also improves the classification accuracy compared with AlexNet.
Empirical Research on the Coupling Degree of Anhui Regional Based on Index Coefficients, Models and Calculation Methods
Authors: Hu Liangyi 
Published: February 2021

Abstract
In recent years, Anhui Province has made considerable progress in economy development, but there are still many problems. What is particularly prominent is that the contribution of tourism to economy growth is not obvious, and the coupling and coordinated development of tourism industry and regional economy is particularly important. Therefore, the article establishes index coefficients, models and calculation methods, to conduct an empirical analysis of the coupling and coordination degree between the economy and tourism in various regions of Anhui. The results show that there are obvious regional differences on the degree of coordination between the tourism industry and the regional economy in Anhui Province, and the tourism industry and regional economy development are restricted each other. On this basis, measures such as optimizing resources, promoting sustainable development, and changing vacation modes are proposed to optimize the development of tourism.
Second Order Asymptotics Formula for Discounted Total Claims with Constant Interest Force
Authors: Dong Yinghua 
Published: February 2021

Abstract
In this article, we analyse discounted total claims of insurance company, where the claim-size distribution is second order subexponential and the claim-number forms a renewal process. Using the asymptotic theory of the right-tail probability of randomly weighted sums, we study the right tail probability of discounted aggregate claims, and obtain a second order asymptotic expression, which was established uniformly for any finite-time level. The result is superior to the first order asymptotic formula.
A Neural Network Prediction Method Based on NNSOA
Authors: Zhao Yong , Xu Mengjie , Wang Qianhan , Ma Bin 
Published: February 2021

Abstract
By using a neural network synchronization optimization algorithm (NNSOA) as a search technique, this paper applies a neural network to forecast the promotion of the employees in a home appliances manufacturing enterprise in Hefei, Anhui province. NNSOA not only optimizes the neural network, but also eliminates the unnecessary weight in the neural network structure. The results prove that a neural network trained by ten times of cross-validation experiment design can make a high-accuracy prediction on the promotion of the employees in the enterprise. The prediction efficiency of predictive variables can be identified by the neural network trained with NNSOA. The study provides more targeted suggestions for enterprises to improve the overall employee development environment.
Measuring the Micro Deformation and Crack of Rock Surface and Make Robot Intelligent Walking Path from Pulse Lidar Profiler
Authors: Zhou Tao , Tao Li 
Published: February 2021

Abstract
Derived from accumulated lidar point cloud, 3D model building appears to be a crucial technology for autonomous navigation of car. In this paper, we present a method of monitoring rock wall cracks and micro rock top displacement of underground tunnel by using pulse lidar profiler, so as to achieve the purpose of timely and real-time early warning. With the help of the Internet of things, cloud data and fog computing, the pulse lidar profiler is regarded as an extended terminal of cloud computing. It performs many tasks such as daily contour data and key electronic equipment monitoring status data recording, danger alarm calculation and emergency situation uploading to the cloud database.
Simulation Analysis for Effect of Rear Structure of Hatchback Car on Rear Field Characteristics
Authors: Qu Xian , Xie Jun 
Published: February 2021

AbstractThe tail shape of the hatchback car is crucial to the rear field. To improve the tail aerodynamic design of the hatchback car, the orthogonal optimization method is used to reveal the rule of different tail structures affecting the aerodynamic drag and lift force considering their interference with each other. First, the different tail structures, such as the top, the side, the bottom and the tail structures, are analysed to reveal the influence of the wake based on the MIRA model. Then, the orthogonal optimization method is applied to investigate the tail shape optimal design considering the mutual influence of each tail structure. The aerodynamic drag coefficient and the lift coefficient are calculated to evaluate the aerodynamic characteristics in the orthogonal analysis. The results show that the angles of the rear windshield and the diffuser has a great influence on the aerodynamic drag. While the diffuser angle have the greatest influence on the lift coefficient. The influence of the rear windshield angle and roof angle is also noteworthy. In a word, the diffuser angle, the rear windshield angle and the roof angle are the key structures for the aerodynamic optimization of the tail of hatchback cars.
Computer-aided Linear Algebra Course on Jupyter-Python Notebook for Engineering Undergraduates
Authors: Tang Chang 
Published: February 2021

AbstractAs an important basic course, linear algebra plays critical role for engineering undergraduates. However, traditional purely theoretical explanation makes students difficult to deeply understand the essence of linear algebra. In this paper, we introduce a new form of computer-aided linear algebra course with the application of a set of Python computer programs implemented on the Jupyter notebooks platform, and also aim to improve the development of innovative teaching methodologies for this course. In addition, in order to help students understand the intrinsic physical meanings of some concepts, we design some visual examples which demonstrate the practical applications of linear algebra. A serious of user-friendly Jupyter notebooks workflows developed in this work allow teachers–students to intuitively teach and learn theoretical concepts, description of practical problems, programming code, and simulation results with a visual output. The designed environment can help teachers/students to implement their simulations in Python language.
Software Environment Modelling Method
Authors: Li Qiuying , Sun Ruize 
Published: February 2021

Abstract
The influence of software environment and its changes on software functions and performance is becoming more and more important. Through literature investigation, this paper studies the concept, composition and characteristics of software environment, and analyzes the relationship between software environment and software requirements. This paper also presents the environment modelling method based on feature model and ontology model, and proposes the procedure and the important steps, together with the differences between the two models. Finally, case studies are given for each model.