bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Joint Radar Signal Sorting Method For Multi-Radar Reconnaissance Station
Authors: Kun HE , Xubo LIU , Yi LIU , RiCheng GUO , KaiFeng GUO 
Published: November 2019

Abstract
Passive Detection Network Composed of Multi-Radar Reconnaissance Station, which can receive multiple sets of radar signal pulse descriptor word at the same time, joint signal sorting becomes an inevitable measure of such data. This paper proposes a multi-radar time-aligned association sorting method, and builds scenario close to actual conditions for testing. The results show that method can overcome the problem of partial pulse loss leading to sorting failure, and can quickly complete complex radar signal sorting in real electromagnetic environment.
Modified Eigenspace Based Iterative Robust Capon Beamformer
Authors: Jin Wei , Shen Xiaowei , Zhang Fenggan , Jia Weimin 
Published: November 2019

Abstract
To improve the performance of adaptive beamformer with large steering vector mismatch, a modified eigenspace based iterative robust capon beamformer (ME-IRCB) is proposed. The approach iteratively implements the robust Capon beamformer (RCB) with an adaptively adjusted uncertainty set. Based on the modified eigenspace method, the desired signal subspace is given, whereafter the size of the uncertainty set is adaptively adjusted according to the mismatch between the estimated and presumed steering vector of the desired signal at each iteration. The proposed approach gives two estimation methods about the uncertainty size, and both of them contribute to the robustness improving of the beamformer. Moreover, unlike other robust beamformers, the proposed approach does not take the integration of the steering vector’s outer product over the adjacent direction of the desired signal, and it works well with the adjacent directions of the desired signal and interference. This merit is due to that, the proposed approach only uses the fundamental sample covariance matrix during the subspace construction, therefore the influence of imprecise steering vector on the subspace is overcame. Simulation results show that the proposed approach performs better than the existing robust beamformers under different evaluation criteria.
K-means clustering algorithm in antenna selection for Massive MIMO
Authors: Xuefang Xiao , Guowei Lei , Yun Lin 
Published: November 2019

Abstract
Massive multiple-input multiple-output (MIMO) is considered as the promising technique in next generation of wireless communication system. It has high spectral efficiency and energy efficiency. In addition, it can mitigate the interferences among users as the amount of antennas at base station (BS) grows. But, the high complexity and cost of hardware pose huge challenges to massive MIMO. In future, antenna selection (AS) is still a choice to decrease the burden of BS. In this letter, the AS algorithm based on K-means clustering is proposed to maximizing the capacity with low computational complexity. Finally, the simulated results are presented to validate the proposed method.
Bayesian Network and Association Rules-based Transformer Oil Temperature Prediction
Authors: Rao Wei , Zhu Lipeng , Pan Sen , Yang Pei , Qiao Junfeng 
Published: November 2019

Abstract
The oil temperature prediction of transformer is very important for the operation stability and life evaluation of transformer. As the oil temperature prediction of transformer is still short of a comprehensive and efficient method with combining various information of transformer such as operation data and meteorological data, this paper proposed a Bayesian network and association rules-based transformer oil temperature prediction method, which can improve the prediction accuracy of RBF-NN for transformer oil temperature prediction. The proposed method first mines all association rules among transformer state data and transformer operation data and environmental meteorological information by combining the Bayesian network and the Apriori algorithm and then uses the association rules to improve the prediction accuracy of RBF-NN based on only transformer state data. A case study with a 500kV transformer is conducted to test the effectiveness of the proposed method, and the result shows that the proposed method can improve the prediction accuracy of RBF-NN about 10%.
A Method of Detecting Driver's Alcohol Concentration
Authors: Bin WU 
Published: November 2019

Abstract
Drivers drunk driving can bring a lot of harm. The paper studies a device that is placed in the car to detect whether the driver is drunk driving. The system consists of a core processor, an alcohol sensor, a display device, and an alarm device. The fitting curve of the alcohol sensor was determined through experiments, and the correspondence between the output voltage and the alcohol concentration was obtained. The design can detect the state of the driver’s alcohol concentration in real time in the car. When the system thinks that the driver’s alcohol concentration exceeds a certain value, a voice alarm is issued, and the device can effectively prevent the driver from drunk driving.
Survey of Recommendation Based on Collaborative Filtering
Authors: Juan Wang , Yue-xin Lan , Chun-ying Wu 
Published: November 2019

Abstract
This paper introduces the domestic and international research of collaborative filtering, and discusses the main problems of collaborative filtering algorithm, including data sparsity, cold start and accuracy of similarity measure.Then, future research and development trends of integrating deep learning to recommender systems are pointed out. In order to solve the data sparsity and cold start problems in the personalized recommendation system, a hybrid collaborative filtering recommendation algorithm is proposed, which combines the KNN model and XGBoost model. When deep learning is applied to recommendation system by integrating massive multi-sources heterogeneous data,it could improve the performance of the recommendation system.
Drawing and inspection of the axial projection view of the centrifugal pump impeller
Authors: Feng Ke , Song Piwei , Chen Yang , Liu Hongli , Li Xuelai , jun Liu , Lidan  
Published: November 2019

Abstract
Artificial scaffolds play an important role in tissue engineering, which used to mimic extracellular matrix (ECM) to provide a suitable microenvironment for cell growth. Many natural and synthetic biomaterials have been used to fabricate two dimension or three dimension scaffolds. However, missing electrical conductivity of these materials is one of the disadvantages. Recently, conductive polymers (CPs) and conductive nanomaterials (CNMs) have been chosen for doping into scaffolds to improve their conductivity. This review focuses on conductive scaffolds design, fabrication and application in tissue engineering for enhancing cell attachment and proliferation, promoting differentiation and maturation with and without electrical stimulations.
Analysis of interior ballistic performance degradation of a worn gun barrel based on finite element method
Authors: Li Xiaolong , Wang Yuan , Zang Yong , Guan Ben , Qin Qin 
Published: November 2019

AbstractA comprehensive accelerated life test of a 12.7mm caliber barrel gun barrel was carried out to study the variation in interior ballistic performance during the lifespan of a large- caliber machine gun. The wear mechanism at different positions in the bore was analyzed, and the wear data for the bore was obtained from the test. On this basis, a three-dimensional barrel- wear finite element model was established using the parametric model-ing method. The variation law of interior ballistic performance and the influence of wear location on ballistic performance were studied. The results showed that, after shooting 4300 rounds, the radial swing of the projectile head at the muzzle reached 0.35 mm and the projectile rotational speed decreased by 57.5% compared with the unworn performance. In addition, the wear on the initial position of the rifling not only caused the swing of pro-jectile in the barrel, but also aggravated the wear of other parts of the inner wall. The wear at the muzzle had a more obvious effect on the rotational speed of the projectile. Finally, it was concluded that the fundamental reason for interior ballistic performance degradation was wear on the initial position of the rifling.
An improved saliency detection method based on hypercomplex Fourier transform
Authors: Pan Yongcai , Zhang Yuwei , Liu Qingzheng 
Published: November 2019

Abstract
Saliency detection is a challenging direction in the field of computer vision. It can help us quickly obtain important information of image and video, and plays an important role in image compression, image segmentation, target recognition and other applications. Based on the Hypercomplex Fourier Transform (HFT) model, median filter and threshold segmentation are employed to obtain the image salient region, which solves the problem that the boundary is not clear and multiple targets cannot be separated, and achieves more accurate and stable detection effect.
Influence of Torque Load on Internal Load Distribution of Tapered Roller Bearings
Authors: Dong J J , Cao P Y , Wang J W 
Published: November 2019

Abstract
The effect of simultaneous application of external torque load on the internal load distribution of tapered rolling bearings under axial and radial loads is studied. The radial deformation and axial deformation of the bearing under the torque load are studied, and the mathematical model of force balance of tapered roller bearing is established. Then the Newton-Raphson method is used to solve the established mathematical model, and the load distribution of the bearing under the two-direction and three-direction loads is obtained respectively. The influence of the torque load on the internal load distribution of the bearing is obtained by the global and local comparison analysis.
Content-Based Personalized Dating Recommendation System
Authors: Hu Yujiao , Gui Xiaolin , Hu Xinyue , Zeng Cong , Wu Youqi 
Published: November 2019

Abstract
In order to improve the accuracy of recommendation on dating websites, a personalized recommendation algorithm aiming at dating objects is put forward. The algorithm firstly extracts the user’s personal characteristic information and defines quantification criteria to quantify the characteristics. Then, the characteristics will be weighted according to the users’ different degree of emphasis on the eigenvalue and similarity between users will be calculated with Euclidean distance. Finally, possible candidates will be recommended according to similarity. The rationality of the algorithm is verified by some experiments.
Short-term wind speed prediction based on EEMD-LSTM
Authors: Huang Yuansheng , Zhang Xiangrong , Yang Lei 
Published: November 2019

Abstract
Accurate wind speed prediction is of great significance for the smooth output of wind farms. To this end, this paper proposes a short-term wind speed prediction model based on the combination of ensemble empirical mode decomposition (EEMD) and long-term and short-term memory model (LSTM). Firstly, in order to reduce the nonlinearity and volatility of wind speed, the ensemble empirical mode decomposition technique is used to decompose the original wind speed time series into a plurality of different sub-sequences; then LSTM is used to predict each sub-sequence to obtain multiple prediction results. Finally, the prediction results of each LSTM model are superimposed to obtain the final wind speed prediction result of the combined model. The prediction model is verified by historical wind speed data of a wind farm in Hebei Province, and compared with ARIMA, GRNN and LSTM models. The simulation results show that the combined wind speed prediction model based on ensemble empirical mode decomposition and long-term and short-term memory model proposed in this paper has a higher prediction accuracy.
Modeling and simulation of aircraft integrated thermal management system
Authors: Binbin Lu , Honghu JI , Mei TANG , Guofeng Wang 
Published: November 2019

Abstract
The integrated thermal management system for a certain type of aircraft was studied. The integrated thermal management system, which takes fuel oil as the main heat sink, thermal protection structure and liquid evaporator as auxiliary heat sink, can comprehensively control and manage the heat of the whole aircraft. The mathematical model for simulation of integrated thermal management system was established. The simulation model of the system was built based on Flowmaster software for calculation. Results show that the system proposed in this paper can meet the overall thermal requirements of the aircraft, and provide a reference for the design of the aircraft integrated thermal management system and its subsystems.
Research on Bearing Fault Monitoring Technology Based on the Acoustic Array in Working Environment
Authors: Lei Wu , Liming Fan , Xiaoran Shi 
Published: November 2019

Abstract
At present the most widely used method in mechanical fault diagnosis is feature extraction based on vibration signal analysis, but the test results are not accurate. Fault diagnosis method based on acoustic measurement can overcome this shortcoming, although traditional acoustic measurement based on single channel is susceptible to interference and it is difficult to obtain effective signals under strong background noise or complex testing environment. Directional noise measurement technology based on acoustic array and beamforming method can effectively suppress background noise. In this paper, the 3D constant beam width beam forming array is used to extract the broadband radiated noise from the monitored equipment and the sensitive frequency bands corresponding to different fault stages of bearings are preprocessed to obtain the corresponding eigenvectors. BP Neural Network is used to identify the fault of the tested bearings. The results show that the 3D microphone array based on constant beam width beam forming can effectively suppress the interference of environmental noise to ensure the validity of monitoring data and improve the reliability of fault diagnosis.
Economic Life Prediction of Transformer Based on Repairing Profit and Decommissioning Profit
Authors: Hu Bin , Chen Qipeng , Rao Wei , Qiao Junfeng 
Published: November 2019

Abstract
Transformer lifecycle management is an important research field that power grid enterprises pay great focus on. The economic life prediction of transformer can provide a basis for transformer equipment management and power grid planning, contribute to prolong the service time of transformer and improve the operation safety and economy of power grid. This paper proposes an economic life prediction model of transformer by analysing various economic factors of transformer and taking the maximum annual average net profit of transformer as the judging criterion, and achieves the economic life quantitative prediction of transformer by comparing the annual average net profit of repairing a transformer and the annual average net profit of decommissioning a transformer. Finally, a case study on the economic life prediction of transformer by selecting an 110kV transformer in service as an example is carried out according to the proposed model, and the results show that the proposed model can not only effectively analyse the economic factors of the transformer, but also reasonably predict the economic life of the transformer, which has a guiding significance for the decision-making of transformer management and the future planning of substation.
Simulation Analysis and Test of the Thread Joint of High Strength Directional Drill Pipe with Large Through Hole
Authors: Dayong Tang , Yu Zhang , Wannian Lei 
Published: November 2019

Abstract
According to the requirements of the directional drilling, the Φ89*3000 type directional drill pipe with high strength and large through hole is designed. The pre-tightening force and axial force acting on the threaded joint of the drill pipe are analysed theoretically, and the finite element analysis model of the screw thread joint is established. According to the three working conditions of directional drill pipe, the stress conditions of threaded joints under different working conditions are simulated respectively. Based on the simulation results, the optimization measures of threaded joints are put forward, the design of threaded joint structure is improved, and the structure type and parameters of threaded joint are adjusted. Finally, the performance test and industrial test of high-strength directional drill pipe with large hole are carried out to verify the rationality of the improved design of drill pipe. The new directional drilling technology of “replacing tunnel with hole” is put forward innovatively, which promotes the popularization and application of directional drilling technology in coal mine gas control and contributes to coal mine gas control.
Study on heavy-duty journal bearing lubrication based on Elasto-hydrodynamic lubrication method
Authors: Li Wen , Liu Jintao , Chen Lei , Liu Zhenxing , Zhuang Baotang 
Published: November 2019

Abstract
Main bearing wear failure to become one of the main factors affecting the service-life of the engine, so it is necessary to form the effective analysis of the main bearing lubrication method, which is used in the design of main bearing lubrication and friction. In this paper, the model of substructure of V8 diesel engine is built based on flexible multi-body dynamics, the various nonlinear factors in the process of engine working process are considered, and the EHD of main bearings is analysed by the EXCITE software. On the basis of the V8 engine model, the bearing load and lubrication performances of different poly- condensation of main bearing are compared. The main bearing lubrication properties of the analysis results can be used for the engine lubrication system design and optimization.
Research on Crack Propagation Law of Assembly Concrete Structure in Hydraulic Engineering Based on Large Data Analysis
Authors: Chen Renshan , Zhang Wei , Zhao Liandi , Wang Kebo , Nan Feng 
Published: November 2019

Abstract
In order to grasp the law of crack propagation in concrete structure, the research on the law of crack propagation in assembly concrete structure of hydraulic engineering based on large data analysis is put forward. The mechanical parameters in the process of concrete structure fracture are obtained by digital image measurement method, and the loss difference is calculated. According to the calculation results, the fracture orientation change is judged, and the law of concrete fracture orientation change is concluded, thus the law of crack propagation in assembled concrete structure is deduced. At last, the experiment proves that the research on crack propagation law of assembly concrete structure in hydraulic engineering based on large data analysis has high accuracy and practicability, and fully meets the research requirements.
A Method of Constructing Mobile Ground Station Location System Based on Optimizing Algorithms
Authors: Gao Saisai , Tao Zhu , Huang Ying 
Published: November 2019

Abstract
Aiming at the problem that the satellite navigation and positioning system can not cover the whole area and that the positioning accuracy of the existing ground-based reinforcement system decreases with the increase of the distance between the target and the ground station, a method for optimizing the positioning system of mobile ground station based on whale optimization algorithm is proposed. Based on the mobile ground station, the method identifies the positioning target with the optimal whale individual and the mobile ground station with other whale individuals, realizes that the position of the ground station varies with the position of the target point, and ensures the high precision positioning of the target in area with weak signals or without satellite navigation and without the support of the enhanced system. The feasibility of this method is proved by MATLAB, which provides a new way of thinking for solving the problem of regional target location.
Research on Agricultural Big Data Analysis System Based on Hadoop
Authors: Wang Lihong , Liu Ping 
Published: November 2019

Abstract
In order to improve intelligent agricultural management, control and decision-making, in view of the practical needs of agricultural big data application, it is necessary to collect and process large amounts of agricultural data. In order to deal with these massive agricultural data, based on Hadoop large data analysis tool, a large agricultural data analysis and processing system is designed and implemented. Through its powerful distributed data processing capability, various agricultural related data can be analyzed efficiently and quickly. Experiments show that the system can effectively complete large-scale data processing and analysis of agriculture, mining useful information from massive data, so as to store and analyze agricultural data reliably and efficiently. The large-scale data system has important practical significance for improving the level of intelligent agriculture development.
Design of Energy Refinement Management System for Agricultural Machinery Painting Based on Internet of Things
Authors: Ma Guoqi , Zhang Guiqing , Li Qingfeng , Tian Chenlu , Wang Peiyi 
Published: November 2019

Abstract
At present, because of extensive energy management methods and manual meter reading collection methods, the domestic agricultural machinery manufacturing industry has caused serious energy waste in agricultural machinery production line, which can not meet the energy management needs of modern agricultural machinery enterprises. In view of the above problems, after thorough analysis of agricultural machinery production process and its demand for energy management, this paper takes full advantage of the characteristics of low cost and comprehensive perception of the Internet of Things, puts forward an energy refinement management system of painting workshop based on the Internet of Things, and achieves energy consumption tracking of production workpieces and energy refinement management of workshop. BP neural network is used to predict energy consumption and diagnose energy saving in workshop. Finally, the test application in the demonstration project shows that the system can real-time and accurate monitor the abnormal situation of energy consumption and energy consumption in the workshop, and realize the fine management of energy in the agricultural machinery painting production line, thus saving production energy and improving enterprise efficiency.
Application of Multimedia Technology in Business English Interactive Teaching
Authors: Xing Yichen 
Published: November 2019

Abstract
The application of multimedia technology is a comprehensive and creative application of traditional teaching forms. In particular, multimedia courseware has the advantages of integration of display, selection of hypertext links, operation of human-computer interaction, richness of large-capacity storage, and convenience of high-speed transmission and so on. It can realize the unified combination of classroom teaching integrity, science, art and technology. Higher education has always emphasized the student-centered, teacher-led teaching model, and flexible use of multimedia in business English teaching has achieved remarkable teaching results. This paper expounds the current situation and problems of the application of multimedia technology in business English teaching, and puts forward some innovative application methods of multimedia in business English teaching.