bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fault Diagnosis Method of Analog Circuit Based on Radial Base Function Neural Network
Authors: Gebregiorgis Meron , He Yigang , Ning Shuguang , Wang Shi 
Published: July 2020

Abstract
Neural network is competent for fault diagnosis and pattern classification such as poorly defined model system, noisy input environment and nonlinearity in analog circuit. One of the most known type of neural network used to identify and classify the method of faulty diagnosis of analog circuit is presented based on the radial basis function (RBF) neural network. The proposed method introduces the fault features and classify the fault classes of the given two circuits. The experiment and simulations of the fault diagnosis for the two circuits (Sallen-Key and four OP-AMP band-pass filter) establish the diagnosing process of our method that proposed in this paper, locating faults effectively and be successful in classifying the fault values. Its performance analysis show that the fault diagnosability learned by RBF method accomplishes a better satisfactory diagnostic accurateness for the fault diagnosis of analog circuit.
Research and Application of SYA-I Microphone Intelligent Assembly System
Authors: Xie Yonghui , Hou Xujie , Zhou Quan , Wang Xiaojun 
Published: July 2020

Abstract
At present, most of the pin-plug type earphones and microphones rely on manual production, and the production efficiency is extremely low. It is difficult to accurately control the neatness and aesthetics of the microphone insertion. Based on the principle of electromagnetic vibration, this paper studies and designs a smart assembly system specifically for SYA-I microphones. This system realizes automatic feeding and docking of SYA-I microphone production, which greatly improves production efficiency and product quality.
Construction and Retrieval of New Ventures’ Growth Risk Case Based on Knowledge Gene Expression Method
Authors: Yang Bo , Liao Yiming 
Published: July 2020

Abstract
Constructing a knowledge service model of risk cases to realize the internal and external risks of new ventures is an important means of its risk management and prevention. And case expression is the key to improving the efficiency of case retrieval and reasoning. Combining the basic characteristics of new ventures, this paper constructs a gene mapping of growth risk cases based on knowledge gene expression, which includes a three-layer factors structure of Risk-Countermeasures-Effector. The gene mapping constructed in this paper has an excellent systemic and hierarchical structure, reflecting the connection between sub-factors, and also describes the risk case knowledge clearly and progressively. It makes up for the shortcomings of traditional ontology and structural representation and improves the efficiency of case storage and retrieval, while providing managers with a decision-making reference. In addition, this paper uses the longest common sub-sequence algorithm to evaluate the similarity of the risk level of cases, which is used for the preliminary retrieval of risk cases. Finally, the advantages of risk case representation based on knowledge gene expression compared with the framework and ontology model are compared, and the model of risk case retrieval is constructed.
Plasmonic Hot Carrier Transfer Modulated Room–Temperature Visible Light Emission of Cu2O–Au Nanowires
Authors: Li Kai , Zhao Xinhong , Fang Yongchu , Tao Yu 
Published: July 2020

Abstract
Cu2O nanowires decorated with Au nanoparticles (Cu2O–Au NWs) were synthesized by a facile solution method. Due to light excited plasmonic hot carrier transfer from Au nanoparticles into Cu2O nanowires, under 360 and 420 nm light excitation, the fluorescence emissions of Cu2O–Au NWs, compared with that of Cu2O nanowires, were enhanced 4.03 and 3.35 times, respectively. The decay time of Cu2O–Au NWs is 4.85 times longer than that of Cu2O NWs under 337 nm light excitation. The results indicate that hot carrier transfer can effectively modulate the optical properties of Cu2O NWs.
Weighted Calibration Algorithm of Multiple Laser Scanning Sensors Based on Measurement Error Correction
Authors: Liu Di , Zhu Liqiang , Zhang Qian 
Published: July 2020

Abstract
The calibration of pose transformation relationship among multiple laser scanning sensors or between one sensor and a reference coordinate system is of great importance to the accuracy of 3D laser scanning system. In some applications, such as section inspection of Metro tunnels, the sparsity of measuring points and high demand for accuracy make the calibration process very difficult. This paper proposes an automatically calibration algorithm, named GA-ICP-WHT, based on an improved ICP algorithm with point-wise measurement error corrections. The algorithm consists of stages: coarse registration with GA and fine registration with ICP and weighted Hong-Tan algorithm. Mathematical simulation and application experiments show that the proposed algorithm is accurate and robust for sparse point cloud registration.
Application of Blended Teaching in Public Administration Courses under the Background of Artificial Intelligence
Authors: He Hui , Wang Ting 
Published: July 2020

Abstract
The deep integration of artificial intelligence and education has become an inevitable trend in the development of higher education in the near future. Taking public administration courses for example, this paper constructed a blended teaching mode in the teaching and learning process, which was proved to be more suitable and helpful for teachers to play a guiding role in public administration professionals. By using big data in the teaching platform, teachers could generate appropriate teaching plans to improve students’ learning efficiency and subjective initiatives according to the knowledge and learning habits of each student. Meanwhile, the assessment system in the platform could also improve teaching quality by helping teachers acquire the learning outcome of their students. The blended teaching mode could largely promote the reform of the traditional teaching mode of the course in colleges and universities in China.
Study on the Fuzzy Interval Evaluation for EPS Schemes
Authors: Guan Zhiwei , Hu Leyuan , Xiao Jinjian , Shi Xingyan , Wu Di , Cai Yijie 
Published: July 2020

Abstract
In order to evaluate vehicle steering feels of the electric power steering (EPS) system effectively, portability, returnability, the ISO lane change capability, and the on-center steering capability were adopted as test factors. On the basis of group multi-criteria decision-making and fuzzy analytical hierarchy process (AHP) method, the EPS hierarchic fuzzy evaluation model was established, and a simplified scale method was adopted to generate the consistent relation judgment matrices. The drivers’ opinions were aggregated to form Triangular Fuzzy Number method with fuzzy Delphi method. Finally, EPS schemes were ranked with total utility values of fuzzy numbers and the optimal alternative could be selected. An example was given, under this approach, it shows that the decision-making process was a systematic and practical method for EPS schemes selection.
Study of High-Speed Mechanical Micro Drilling Process Fundamentals for Small Holes
Authors: Li Yang , Cheng Xiang , Ling Siying , Zheng Guangming , Manea Hisham 
Published: July 2020

Abstract
High-speed mechanical micro drilling would be a promising process for small hole fabrications with high productivity and high quality. But there are limited studies on this topic. Fundamental questions such as the minimum undeformed chip thickness (MUCT) due to the size effect in microcutting, burr size, cutting force, and optimal parameters are discussed for high-speed mechanical micro drilling in this paper. Based on finite element method (FEM) modelling, the MUCT is identified as 0.86 μm for copper C26000 with the cutting edge radius of 5 μm from both chip generation and force variation analyses. The ratio of MUCT to the cutting edge radius is 0.17, which is smaller than that (usually 0.2 or 0.25 for copper) in micro shaping and micromilling processes. This result has been successfully verified by experiments with the drill with a diameter of 1 mm and the spindle speed of 80,000 min-1. Burr width at the hole entrance reaches the maximum value when the undeformed chip thickness (UCT) is smaller than the MUCT. Experimental optimizations with the integrated considerations of cutting forces and burrs have been conducted. The optimal high-speed micro drilling parameters have realized a material removal rate (MRR) of 25% increasement compared with conventional micro drilling.
Hub Network Design in a Cooperative Environment
Authors: Fang Huimin , Li Shuxia , Liu Zhiying 
Published: July 2020

Abstract
As an important strategic decision, the design of the hub network directly affects the transportation efficiency and costs of the entire network. Sharing resources to reduce costs through cooperation is the future development of logistics and transportation networks. From the perspective of horizontal cooperation, this paper focuses on the hub location problem of two carriers sharing hub facilities in a cooperative environment. A mixed-integer programming model with minimum total network cost in a cooperative environment is constructed. Numerical examples demonstrate that the supplementary cost due to cooperation will affect the result of cooperation. When the supplementary cost is within a specific range, the cooperative network is more cost-effective than non-cooperative networks.
Application of Broadband PLC Technology in Monitoring Railway Trackside Signal Equipment
Authors: Shi Long 
Published: July 2020

Abstract
It is very important for railway operation and maintenance to monitor railway trackside signal equipment, which is the key foundational part of train control system. But the problem of how to transfer the monitoring data safely and efficiently is difficult to be solved. This paper introduces the technical characteristics of PLC, analyzies and compares the applicability of various communication methods under the application conditions. A scheme of trackside equipment monitoring network is proposed based on the broadband PLC technology and a monitoring system meeting the application requirements is developed.
Location Problem of Production and Sales under Carbon Tax Policy
Authors: Xiang Chong , Li Xiaoshen , Sun Guanglei 
Published: July 2020

AbstractThis paper considers a location problem of production and sales of a production-oriented enterprise under carbon tax policy. Consumers are distributed on a straight line with linear transportation costs. In addition to paying the transportation costs of its own products, the enterprise is also responsibile for the transportation costs of consumers. A profit maximization model is established, properties of the profit function are analyzed, and a solving method is given. Numerical experiments show that even if the distribution of consumers is center-symmetric, the optimal location is not necessarily center-symmetric, which corrects the illusion of people. It is concluded that different carbon tax policies lead to different cost ratios of different modes of transportation, which lead to different locations and profits.
Research on Adaptability of After-treatment Device for Diesel Vehicles In-use Based on Actual Road Conditions
Authors: Xie Zhenkai , Wang Jiguang , Li Jingyuan , Ling Jian , Zhang Xiaowen 
Published: July 2020

Abstract
Atmospheric environment is seriously threatened by the particulate matter and nitrogen oxide emissions of diesel vehicles in-use. Feasibility of the emission reduction technology and its application used in the China III diesel vehicles was studied, and an emission control device that meets the target vehicle according to the characteristics of vehicle operating conditions was designed. Furthermore, demonstration of emission treatment of particulate matter and nitrogen oxides in diesel vehicles was implemented. The working conditions and matching applicability between vehicles and after-treatment devices during actual road operation were analyzed, and results of emission reduction were counted. The research indicates that matched with the working conditions, the emission reduction technology for the diesel vehicles in-use can be effectively reduce pollutant emissions under actual road conditions and achieve continuous emission reduction effects.
Multi-periodic Refinery Scheduling Based on Generalized Disjunctive Programming
Authors: Li Ming 
Published: July 2020

Abstract
Refinery complex production process usually involves some distinct or implied production rules and expert experiences. Representation and utilizing these heuristic rules is conducive to efficient scheduling optimization. In this paper, the heuristic rules were formulated using disjunctive form and logical proposition, and a discrete-time based multi-periodic generalized disjunctive programming (GDP) scheduling model was built. Due to the combining of logic expressions and algebra expressions, heuristic rules were utilized by the proposed model, while scheduling optimization was ensured. The formulated model was used to deal with a refinery scheduling problem. Case study shows the model’s feasibility and efficiency.
Research on Text Data Pool of Intelligent Manufacturing for Plate Parts
Authors: Li Guangrong , Cao Yuanguo , Zhao Sufang , Bao Yongqiang , Yu Chao 
Published: July 2020

Abstract
Based on understanding of the structure and function of plate parts, these are analyzed including the data produced in the process of intelligent manufacturing and the characteristics and contents of the way of information expression in this paper. The data of the whole life cycle of plate parts is the research object combined with research status. The characteristics and functions of the text data pool are analysed. The framework of the text data pool for plate parts is constructed. The text data pool for intelligent manufacturing of plate parts is designed. A Hadoop platform is built by using Java, hive and other components. And the modules are built to achieve text data pool data fusion. A large number of data generated in the process of plate parts design and intelligent manufacturing can be analysed, processed and extracted more clearly, such as data collection, data format conversion, text disambiguation and other fusion functions, so as to achieve the purpose of data processing. These researches not only play an important role in data storage and processing, but also improve the efficiency and accuracy of plate parts design and intelligent manufacturing.
Modelling and Simulation of an Anti-skid Braking System for Rail Vehicles
Authors: Ma Tianhe , Wu Mengling , Tian Chun 
Published: July 2020

Abstract
Pneumatic braking systems are widely used on rail vehicles. Anti-skid control systems are equipped to prevent wheels from locking and ensure braking distances in low adhesion conditions. To model and simulate an anti-skid pneumatic braking system, a concise modelling method was proposed. By dividing the pneumatic braking control unit into two parts, the complex model was simplified according to its working principle. The pneumatic model, kinematic model, adhesion force model and controller model were established and simulated with MATLAB/Simulink and AMESim. The results show that this method is suitable for anti-skid control modelling and simulation and can be used for controller development and verification.
Research on Standard Legend Production of the Geological Map Interpreted with Remote Sensing Images
Authors: Zhao Yuling , Yang Jinzhong , Fu Zongtang 
Published: July 2020

Abstract
It is necessary to standardize the legends of the geological map interpreted with remote sensing images in various application fields duly to achieve standardization and automation of the legends. This paper analyzes main contents and expression forms of legends based on the principle of legend compilation and expansion, and discusses generation method, compilation and expression of various legends. 455 legends of the geological map interpreted with remote sensing images were designed and produced by using Font Creator and ArcGIS software. These legends can be applied to remote sensing survey of regional geology and mineral geology, remote sensing monitoring of fundamental geology environment, remote sensing monitoring of geological disasters, remote sensing monitoring of mineral resources development and others, which can basically meet needs of actual work, and can provide technical support for standardized research of the geological map interpreted with remote sensing images.
Research on Multi-source Data Fusion of 3D Scene in Power Grid
Authors: Zou Biao , Wang Heping , Zhou Xiangxian , Jiang Wendong , Du Wei 
Published: July 2020

Abstract
With the rapid development of information technology, 3D panoramic technology has been more and more widely used, and it has played a role in urban planning, power grid engineering design, and geological analysis. This technology can provide people with a variety of scene information intuitively and realistically. With realistic space simulation scenes, users can feel a sense of immersion. Due to the different types of geographic information and related data involved, it is necessary to use the idea of data fusion and combine data from different spaces to achieve information fusion, thereby improving the accuracy of geographic information in design scenarios and better promoting 3D panoramic technology in urban planning, Widely used in power grid design, community management and other fields.
Using GF-2 Images to Detect Tamarix Chinensis Community within a Vegetation Patch
Authors: Liu Qingsheng 
Published: July 2020

Abstract
The quasi-circular vegetation patches (QVPs) are mainly composed of suaeda salsa, Tamarix chinensis, and Phragmites australis in the Yellow River Delta, China. The previous studies indicate that the shrubs within a vegetation patch play an important role in the establishment and disappearance of vegetation patch. Therefore, in this work, the method based on the tasselled cap brightness and greenness components derived from the April image and the August GF-2 image acquired after water replenishment with the decision tree classifier was developed for quickly detecting the Tamarix chinensis community. The detection rate was 73.5%, and the misclassification rate was 12.1%. In the future, more samples of plant community and multi-seasonal images such as the late fall-early winter leaf-off data needs to be applied to further improve the detection accuracy.
Location of Underground Parking Lot Based on Bluetooth Ibeacon Technology
Authors: Luo JinMan , Liu LiYuan , Wang LiNa , Liu ZhuoXian 
Published: July 2020

Abstract
With the popularity of electric vehicles in China, how to guide the vehicle to the charging facility in the underground garage has become an urgent problem to be solved. Among them, the realization of real-time vehicle location is one of the keys. In this paper, the location fingerprint scheme based on iBeacon technology is adopted, and the improved k-proximity algorithm is combined to realize the positioning.
Power System Optimization Based on Multi-agent Structure and Lion Swarm Optimization
Authors: Guo Ying , Jiang Mingyan 
Published: July 2020

Abstract
To improve the global exploration capability of lion swarm optimization, this paper presents a novel lion swarm optimization based on multi-agent structure. The new algorithm combines the lion swarm optimization and the multi-agent system in order to improve efficiency and accuracy. It could use the group information and environment information to determine the search strategy in the iterative process. In solving the economic load distribution problem of power system, the lion swarm optimization based on multi-agent structure has significantly improved performance compared with lion swarm optimization in terms of efficiency and robustness. The experimental results on power system prove the effectiveness of this new algorithm.
Value Analysis and Mode Construction of Tutorial System for P2P Undergraduates in Computer Science—-Based on the Reform Practice of Tutorial System in the College of Computer Science, Xi’an University of Technology
Authors: Ma Fu , Song Yuanyuan 
Published: July 2020

Abstract
With the implementation of credit system, undergraduate tutorial system is becoming a new system of student education management in colleges and universities. The implementation of tutorial system of undergraduate students is based on educational theories, such as teachers teaching to educate people, teaching students in accordance of their aptitudes, and constructing a harmonious teacher-students’ relationship. This paper puts forward a feasible operation mode for the optimization of the tutorial system for undergraduate students, which has achieved good results.
Application of Multi Sensor Fusion in Attitude Measurement of Crawler Mountain Forest Robot
Authors: Liu Bin , Ren Yan 
Published: July 2020

Abstract
Due to the complex terrain of the special robots in mountain forests application environment and the roughness of the road, it is difficult to solve the problem of the measurement of robot’s attitude, especially the real-time dynamic solution. In this paper, an attitude measurement system based on gyroscope, accelerometer and three-axis magnetometer multi-sensor fusion is proposed, and adds the complementary filtering algorithm to the attitude solution, the real-time dynamic attitude measurement of the robot is improved obviously.
A Real-time Image Recognition System Based on Improved Jacintonet Convolutional Neural Network
Authors: Chen Shixing , Yuan Hongfang , Cao Xi , Li Xiang 
Published: July 2020

Abstract
With the emergence and development of new automation industries such as unattended supermarkets and smart picking orchards, the demand for real-time systems based on embedded platforms is increasing day by day. Heterogeneous multi-core processors are widely used in modern integrated circuit design due to their advantages of low power consumption and high parallelism. More and more real-time systems are implemented on heterogeneous multi-core platforms. Based on the heterogeneous multi-core embedded system, the network parameters and architecture of jacintonet model are improved, and a real-time system for fruit image recognition is realized by using the improved network. A small sample data set is used to train the modified network and the trained network is imported into the system for testing. The result shows that the improved jacintonet network can run well on heterogeneous multi-core system and has the same recognition performance as the original network.
Traffic Sign Recognition with Neural Networks in the Frequency Domain
Authors: Franzen Florian , Yuan Chunrong , Li Zhong 
Published: July 2020

Abstract
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.