bluuebunny/crossref_metadata_2025_split huggingface dataset:
Double Chain Blockchain Based on Improved Virginia Algorithm
Authors: Cao Yibo , Cheng Yuyang , Yang Chunyu , Zhan Anqi , Xu Chuxiao 
Published: March 2021

Abstract
As more and more people accept Bitcoin, block chain technology has received extensive attention and research. Block chain is a decentralized open dean technology that combines data blocks with the chain structure in chronological order, and combines encryption, protocol mechanisms, and smart contracts. Block chain technology has the characteristics of decentralization, high security, difficult information tampering, traceability, and transparency. Therefore, more and more companies and institutions are focusing on block chain technology research. In the wide application of block chain technology, the current centralized transaction model of e-commerce has gradually exposed some problems, such as the obvious monopoly trend of third-party platforms caused by the excessive central power, the difficulty of cross-border transactions, and the insecurity of user privacy information. Difficulties in accountability for transaction disputes, numerous phishing websites, and proliferation of fakes. Moreover, the current block chain transactions lack legal supervision and protection, transaction efficiency is low, smart contract functions are limited and difficult to understand, and block chain is highly professional and difficult to be accepted by the general public. Based on this, this article proposes a product anti-counterfeiting traceability system using a dual-chain block chain based on an improved Virginia algorithm, analyzes the security of the traceability system, and verifies the feasibility of the system through simulation experiments. The further combination of chain block chain technology and product security field provides reference and reference.
Attitude Interpolation Algorithm for Industrial Robot Based on Quaternion Method
Authors: Jiang Benchi , Li Jiankang , Du Xin , Duan Pengfei , Wang Jianbin 
Published: March 2021

Abstract
In order to achieve the smooth transition of the end-tool pose of the industrial robot, after determining the pose of the teaching points of the robot. Firstly, the path of the pose change between the adjacent teaching points is constructed by using the SLERP method, then, the position of the start and end points of the attitude transition curve is determined, and the expression of the attitude trajectory curve is obtained. According to the relation between the derivative of quaternion and Angular Velocity, the conversion between unit quaternion and angular velocity is realized by using Newton-Cortez formula. Finally, the velocity of the fitted industrial robot’s tool’s attitude trajectory is planned, and the whole attitude trajectory is interpolated.
Gerber File Parsing and the Implementation Method of its Conversion to Bitmap Image
Authors: Fan Yong , Wu Shuqin , Wu Xie , Yang Jianbo 
Published: March 2021

Abstract
In order to obtain the standard image based on the Gerber file in the AOI (Automatic Optical Inspection), an implementation method is proposed by analysing and converting the Gerber file into a bitmap image. According to the command format rules of Gerber file, the approach is designed to analyse Gerber files by constructing the command regular expression of Gerber files. In order to achieve convenient access to the drawing data, the drawing data processing is performed by defining a class, then the drawing data is stored in a dynamic array and the adjustment factors are added in the drawing data at the same time to meet the further post-processing needs of bitmap image. This method can quickly analyse Gerber files, adjust drawing data and generate bitmap images.
Tool Wear Prediction Based on Edge Data Processing and Deep Learning Model
Authors: Yan Dong , Ding Xinyu , Pan Shuaiyu , Huang Haoyang 
Published: March 2021

Abstract
In order to improve the accuracy of tool wear prediction and enhance the real-time application in industrial sites, a tool wear prediction method based on edge data processing and CNN-BiGRU neural network is proposed. This method first implements data preprocessing on edge nodes, effectively reducing the amount of data transmission to avoid network link congestion. After that, the CNN-BiGRU neural network was deployed in the cloud for model training. Experimental results show that the tool wear prediction method based on edge data processing and CNN-BiGRU neural network has good real-time performance and high prediction accuracy in simulated industrial field applications.
Recognition and classification of water surface targets based on deep learning
Authors: Peng Yanhua , Yan Yipu , Feng Biao , Gao Xingyu 
Published: March 2021

Abstract
Aiming at the shortcomings of low recognition rate and low calculation rate of surface unmanned ship in complex time-varying water surface environment, a surface target detection method based on Faster R-CNN is proposed in this paper. Firstly, the water surface image was enhanced by McCann Retinex method to improve the image quality under complex background. Secondly, a water surface target data set was established. Finally, based on Faster R-CNN algorithm, VGG, Resnet and Inception network structures were employed to test and analyze the data set. The results show that the detection method proposed in this paper can effectively complete the identification and classification of six categories of common targets on the water surface, which has significant guiding significance for the autonomous obstacle avoidance and maritime search and rescue of unmanned ships.
CdTe quantum dots film by electrospinning as bearing temperature sensor
Authors: Pan Zhang , Ke Yan , Jun Hong , Zhu Yongsheng 
Published: March 2021

Abstract
Temperature monitoring of bearing rotating elements is crucial for bearing condition assessment and early warning. Using CdTe quantum dots (QDs) to prepare sensors requires other membrane material as the substrate, which affects the accuracy of the test. Meanwhile, CdTe QDs exposed to air for long time will lead to oxidation, which affects the storage life of the sensors. Hence, based on excellent film forming properties of polyvinyl alcohol (PVA), the CdTe/PVA polymeric nanofiber was fabricated by electrospinning method. For comparison, the CdTe/PVA composite film by drop-casting method was also prepared. Thermal properties show that there are excellent linear relationships between peak wavelength and temperature of the CdTe/PVA composite film and the CdTe/PVA polymeric nanofiber respectively. However, the uniformity of the CdTe/PVA polymeric nanofiber obviously better than the CdTe/PVA composite film. Outstanding temperature dependence of photoluminescence spectra and uniform film formation demonstrating the potential value of the obtained CdTe/PVA polymeric nanofiber as temperature sensor for bearing rotating elements.
A method for assigning the motion precision of meta-action chain based on spinor theory
Authors: Ying Guangqi , Zhang Genbao , Ran Yan , Mu Zongyi 
Published: March 2021

Abstract
In order to provide theoretical guidance for the precision design and optimization of CNC machine tools, the motion precision distribution model of the meta-motion chain was established based on the minimum motion unit - meta-action. The motion function of CNC machine tool was decomposed into meta-action chain by using the “function-motion-action” (FMA) method, and the motion precision model of meta-action chain was established based on the screw theory. The sensitivity coefficient was used as the manufacturing cost index, and the spatial rotation error was used as the objective function to construct the motion precision distribution model. Finally, the NSGA-II genetic method was used to solve the distribution. The motion precision distribution of a numerical control machine tool is carried out, and the feasibility of the model is verified, which provides theoretical guidance for precision design of products.
Blur Regional Features Based Infrared And Visible Image Fusion Using An Improved C3Net Model
Authors: Xu Zhao , Liu Gang , Tang Li Li , Li Yan Hui 
Published: March 2021

Abstract
For ameliorate the drawback that useful information obtained through middle layers is lost in the conventional image fusion methods based on deep learning, an unsupervised deep learning framework based on Cascaded Convolutional Coding Networks (C3Net) is proposed for the fusion of infrared and visual images. A Blur Regional Features (BRF) scheme is also considered during fusion stage, so as to preserve the consistency of regions. Firstly, redundant and complementary features of infrared and visible images are obtained from the coding layer respectively. The output of each convolutional layer is connected to the input of the next layer in a cascading manner. Then, relying on the features of redundant features and complementary features, different fusion strategies are designed respectively based on BRF to obtain fusion feature maps. Finally, the fused image is reconstructed by decoding layer. Furthermore, the objective function of the training model is designed as a multitask loss function including Mean Square Error, Information Entropy and Structural Similarity, to reduce the loss of the original image information. The experimental results of C3Net fusion method is compared with state-of-the-art fusion methods, which is better synthesized performance in objective evaluation and subjective visual quality.
Application of Visual Technology in Fully Mechanized Coal Face
Authors: Gao Xubin 
Published: March 2021

Abstract
With the gradual improvement of coal mining automation, visual technology is more and more widely used in coal mine production line. Especially in fully mechanized coal face, visual technology provides a guarantee for reducing the working face personnel and remote control. Aiming at the application scene of fully mechanized coal face, the key technologies such as visual imaging algorithm, visual data compression algorithm, panoramic reconstruction technology of fully mechanized coal face and reliable video data storage technology are combed. The distortion correction, image registration, image fusion and video data compression methods based on depth learning technology in panoramic video surveillance system of fully mechanized coal face are mainly expounded. It effectively solves the problems of large bandwidth, incomplete video storage, non-intuitive working picture of shearer and uneven video splicing picture. At the same time, the development direction of video surveillance system in fully mechanized coal face is discussed.
Feasibility Analysis of Integrating Augmented Reality Application into Education System to Improve Students’ Learning Experience
Authors: Zhang Kun-Shan , Chen Chiu-Mei , Chang Wen-Yu 
Published: March 2021

Abstract
Integrating Augmented Reality (AR) application into education system can improve students’ learning experience, this study analyzes the feasibility of the application of augmented reality technology in education through literature review. It also commend the AR use survey of three disciplines in education industry, including potential advantages, challenges and learning experience, and takes PDCD mode as AR resource development mode. Then it analyzes the advantages and disadvantages of its intelligent learning environment and technology in education, the utilization of AR is considered a suitable tool to incorporate in the education industry.
Classical nonlinear simulation of low-order modes of Lamb waves in plate
Authors: Meng Tao , Meng Xiangji , Li Xiaolong , Chen Jinzhong , Jiao Jingpin 
Published: March 2021

Abstract
For the classical nonlinear research of low-order modes of Lamb waves, this paper firstly introduces the classical nonlinearity derived from the intrinsic nonlinear induced low-order Lamb waves (S0 and A0 modes). Theoretical and numerical calculations are studied in two aspects. The influence of nonlinear effects on the nonlinear effects of classical nonlinear low-order Lamb waves and the cumulative growth effect are analyzed by finite element simulation. The results show that the nonlinear effect produced by the superelastic material model is greater than the geometric nonlinearity, and the linear elastic material model does not produce nonlinear effects. In addition, as the third-order elasticity increases in the material, the amplitude of the second harmonic gradually increases. The second harmonic generated by the A0 mode with phase velocity mismatch is the S0 mode. It can be seen that the group velocity matching is not a necessary condition for generating the second harmonic. Since the phase velocity matching is not satisfied, there is no cumulative growth effect; The higher the S0 mode phase velocity matching degree, the more obvious the cumulative growth effect, and the second harmonic is the S0 mode.
Research on Route Planning based on improved Ant Colony Algorithm
Authors: Xin Chen , Luo Qiang , Wang Changhong , Yan Zheng , Wang Haibao 
Published: March 2021

Abstract
In order to enhance the safe flight performance of UAV and better complete complex tasks, it is extremely necessary to study route planning. Firstly, the feature points of the landform landform are extracted as the flight track points of the UAV, and the track planning problem is transformed into the traveling salesman problem. Secondly, an adaptive pheromone update method is proposed, and an improved ant colony algorithm for optimizing the local pheromone is proposed to avoid the basic ant colony algorithm from falling into the local optimal solution and improve the global search ability. Finally, the proposed algorithm is verified by simulation experiments. The experimental results show that the improved ant colony algorithm is practical and superior, and can effectively solve the problem of route planning and obtain the optimal path of route planning.
Research on Information Security Encryption Method Based on Blockchain
Authors: Lu Aifen , Xiong Yongping 
Published: March 2021

Abstract
With the rapid maturity and development of positioning technology, location-based service (LBS) has become an indispensable part of many industries in social life and national economy, including transportation, social platforms, medical fields, military National defense, etc. With the rapid promotion of wireless network technology and the continuous enrichment of related application fields, LBS has become more complete and convenient, and has a wide range of application prospects. LBS refers to providing location-related services to users through location sharing. In the traditional centralized management mode, problems such as location privacy leakage and location information tampering caused by third parties have brought huge security risks to users. Taking into account the distributed data storage method of the blockchain and the characteristics of openness and autonomy, this paper uses the blockchain to realize the decentralized storage of location information, and on this basis, research and design the location of multi-level privacy protection. The sharing scheme eliminates the security problems caused by third parties and realizes the security of user location information shared.
Modeling and Research of Fuzzy PID Control Strategy for Hydraulic Rock Drill Propulsion System
Authors: LIU Zhong , Wang Hanying , Xiong Zhonggang , Huo Jiabo , Zhan Jiangzheng , HE Yanfei 
Published: March 2021

Abstract
According to the coupling characteristic of propulsion system and impact system of hydraulic rock drill, deduced the calculation formula of optimal axial thrust for the propulsion system of hydraulic rock drill. On the basics of the calculation formula before, the paper constructed compound driven propulsion system of hydraulic rock drill based on electro-hydraulic proportional pressure-reducing valve and high speed on-off valve, and established its dynamics model. Finally, the paper considered optimal axial thrust as the goal, and adopted the fuzzy PID control strategy to realize on-line, intelligent control to axial thrust of the propulsion system of hydraulic rock drill. Through mathematical modelling and simulation study show that fuzzy PID control method has its advantages as the fast response follow by target, high control precision, and small fluctuation, and provided theory reference and technology method for intelligent control of the propulsion system of hydraulic rock drill.
Research on the Temperature Control System of 6KA Neodymium Oxide Electrolysis Furnace with BAS_PID Algorithm
Authors: Bai Song , Ran Junming , Gan Jiayi , Chen Jianbin , Tang Shenglong , Gao Peng 
Published: March 2021

Abstract
In order to solve the obvious temperature fluctuations in the cell during the neodymium oxide electrolysis process, the traditional PID control algorithm has a large lag, the timeliness of the multi-variable electrolysis temperature control system is poor, and the manual parameter adjustment is difficult, the beetle PID automatic temperature control system is proposed. Through the control of the key variable cathode current density, speed up the system to adjust the output speed; use the orthogonal temperature measurement method to replace the traditional single point temperature measurement, and use the domain temperature to represent the point temperature to solve the problem of large temperature measurement errors. This algorithm model is based on MATLAB2017 platform for modeling simulation and experimental research. Compared with traditional PID, this method has better adaptive ability and robust performance. The maximum deviation between the actual electrolysis temperature and the set target temperature is 45°C, and the overshoot is 3.3 %, to meet the process index requirements in the actual production process, and provide a reference case for the improvement of neodymium oxide electrolysis process.
Research on Optimization of Heterogeneous Air Cargo Network Based on Hybrid Particle Swarm Algorithm
Authors: Zhang Mingwei , Chen Rong 
Published: March 2021

Abstract
In order to solve the problem of poor timeliness and high operating cost caused by the failure to consider the types of cargo aircrafts and the lack of scientific and reasonable optimization model in the process of transportation scheduling optimization of China’s air cargo network, a transport network optimization model of heterogeneous cargo aircraft formation is established, which takes the total flight cost and the number of all-cargo aircrafts as two optimization objectives. The model takes into account the demand time window of air nodes, the maximum payload constraint of cargo aircrafts, the dynamic loading and unloading time of cargo aircrafts, the take-off and landing time and the handover time of cargo aircrafts. In this paper, a hybrid particle swarm algorithm is proposed. The crossover operator of genetic algorithm is used to keep the directivity of particles, and the acceptance criterion of simulated annealing is used to enhance the ability of the algorithm to jump out of local optimum. The effectiveness of the algorithm and the model is verified by the simulation optimization and comparative analysis of a numerical example.
Image Filter Processing Algorithm Analysis and Comparison
Authors: Hai Xia , Cao Shukun , Cui Shoubo , Ma Jianzhong , Gao Kuizeng 
Published: March 2021

Abstract
In the process of capturing images by the camera, various noises will be generated due to the interference of the external environment or the interference of the internal environment. The noise must be filtered to ensure the accuracy of the size measurement. This article takes Gaussian noise and salt and pepper noise as examples. Experimental simulation analysis of image filtering by different filtering methods. Then combined with the image quality evaluation index to analyze the optimal image filtering processing method, finally it is concluded that the most suitable methods for Gaussian noise and salt and pepper noise filtering are adaptive Gaussian filtering and median filtering.
Fitting the space line of high repeatability to noisy point cloud data
Authors: Huang Shuai , Chen Ming , Lu ShengLian , Chen ShouXin , Zha YongJian 
Published: March 2021

Abstract
The spatial line fitting algorithm with high repeatability for noise point cloud data is challenging and it is of great significance for high-precision measurement, visual guidance of robotics and CNC machining, but little study has been done at this topic. In this paper, a new algorithm is proposed to fit the spatial line with high repeatability to adapt to the point cloud data with noises. This method combines the idea of repeated residuals and the least square algorithm to filter out the noises and then solve the problem. The algorithm can successfully filter the noises. Four popular straight lines fitting algorithms are implemented as benchmarks. A large number of experimental results show that this algorithm can obtain highly repeatable and accurate straight lines.
Study on the application of automatic cleaning technology of the inner wall of pipeline
Authors: Liu Huimei , Chen Yan , Hu Junjie 
Published: March 2021

Abstract
The problem of the inner wall scaling of pipeline has been a bottleneck of the production of all fields for a long time, because it makes the industrial accidents happen frequently, which not only causes enormous economic losses, but also causes the great environment pollution. In this study, the ultrasonic cleaning technology applied to the pipeline wall of milk pasteurization system was put forward, because the pipeline wall of milk pasteurization system was very difficult to clean. Subsequently, the main effect of ultrasonic wave used in pipeline of antiscaling descaling principle and influence factors of cavitation field were analyzed, the pasteurized milk system device and the ultrasonic transducer installation method were designed. Finally, the results showed that pipeline automatic cleaning effect had much to do with the ultrasonic frequency and sound source location, and it had obtained the basis of parameter selection of ultrasonic wave applied in pipe fouling prevention. This study had the great practical significance to solve the problem of cleaning the inner wall of pipelines.
Identifying heavy-flavor jets using vectors of locally aggregated descriptors
Authors: Bielčíková J. , Kunnawalkam Elayavalli R. , Ponimatkin G. , Putschke J.H. , Sivic J. 
Published: March 2021

Abstract
Jets of collimated particles serve a multitude of purposes in high energy collisions. Recently, studies of jet interaction with the quark-gluon plasma (QGP) created in high energy heavy ion collisions are of growing interest, particularly towards understanding partonic energy loss in the QGP medium and its related modifications of the jet shower and fragmentation. Since the QGP is a colored medium, the extent of jet quenching and consequently, the transport properties of the medium are expected to be sensitive to fundamental properties of the jets such as the flavor of the parton that initiates the jet. Identifying the jet flavor enables an extraction of the mass dependence in jet-QGP interactions. We present a novel approach to tagging heavy-flavor jets at collider experiments utilizing the information contained within jet constituents via the model architecture. We show the performance of this model in proton-proton collisions at center of mass energy √(s) = 200 GeV as characterized by common metrics and showcase its ability to extract high purity heavy-flavor jet sample at various jet momenta and realistic production cross-sections including a brief discussion on the impact of out-of-time pile-up. Such studies open new opportunities for future high purity heavy-flavor measurements at jet energies accessible at current and future collider experiments.