bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on Acoustic Emission Damage Signal Denoising of 2D-C/SiC Composites
Authors: Wang Yinling , Li Huacong 
Published: May 2020

Abstract
In the process of damage test of carbon fiber composites, the acoustic emission signal is affected by the measurement conditions and external environment, which contains a lot of noise problems. A denoising method based on wavelet threshold is proposed. Based on the analysis of the burst signal and continuous signal of carbon fiber composite, the wavelet analysis method is theoretically studied firstly. The selection criterion of wavelet base and the selection of wavelet decomposition layer are discussed theoretically, in order to solve the threshold of wavelet threshold denoising. A high-order non-conductible problem, a soft threshold function is proposed. Finally, the denoising experiments are carried out on the burst signal and the continuous signal respectively. The effects of different basis functions and different decomposition layers on the signal-to-noise ratio are compared. Finally, the optimal wavelet basis functions and the number of decomposition layers are obtained, which makes the denoising effect optimal.
Chip Breakability in Turning of 7075 Aluminium Alloy with a High-Pressure Coolant Supply
Authors: Wada Tadahiro , Yamaguchi Takuro , Morigo Yusuke 
Published: May 2020

Abstract
Because of its extremely high strength to weight ratio, 7075 aluminum alloy is used for highly stressed structural parts including aircraft fittings, gears and shafts and various other commercial aircraft, aerospace and transportation equipment. In the case of cutting aluminum alloys, the chip breakability is the most important feature to ensure reliable operation in automated machining. In this study, in turning of 7075 aluminum alloy with a high-pressure coolant supply, the chip configurations, and the mass and thickness of chips were experimentally investigated. The following results were obtained:(1) In the case of a cutting speed of 5.0 m/s, a feed rate from 0.05 mm/rev to 0.50 mm/rev and a depth of cut from 0.1 mm to 3.0 mm, chips were not broken at a feed rate of 0.15 mm/rev or less with the conventional coolant supply. With a high-pressure coolant supply, the combination area of feed rate and depth of cut in which chips were broken was wider than that with the conventional coolant supply. With the high-pressure coolant supply at a coolant pressure of 7 MPa, there was a combination area of feed rate and depth of cut in which chips were not broken. However, chips were broken in all areas at a coolant pressure of 20 MPa.(2) In the case of both the high-pressure coolant supply, which has a coolant pressure of 7, 14 or 20 MPa, and the conventional coolant supply, the thickness of chip increased with the increase of the depth of cut. And, the thickness of chip did not change depending on the cutting method, namely the high-pressure coolant supply cutting method and the conventional coolant supply cutting method.
Research on Fault Diagnosis of Gearbox Based on Acoustic Emission Signal Monitoring
Authors: Yao Jun , Yin Xianming , Wang Yinling 
Published: May 2020

Abstract
For the problem of large noise interference in gearbox fault diagnosis and inaccurate time-frequency resolution of analysis signals, a method for analyzing acoustic emission signals using Hilbert-Huang transform method was proposed. Firstly, use the acoustic emission method to collect the fault signal of the gearbox, which reduces the interference of environmental noise. Then perform domain of time analysis on the single, and the time-frequency analysis was performed by short-time Fourier transform, wavelet transform and Hilbert-Huang transform. The results show that the Hilbert-Huang transform method is the best to analyze the acoustic emission signal, and the frequency of the fault can be analyzed accurately, and the time-frequency aggregation is accurate, which verifies the superiority of the method in gear fault diagnosis.
Reduction Drag of Circular Cylinder Due to Installation of Four Flat Plates
Authors: Frolov Vladimir A. , Kozlova Anna S. 
Published: May 2020

Abstract
The paper presents theoretical and experimental studies on the reducing drag of a circular cylinder. The reduction drag is achieved by installing near a circular cylinder four flat plates. Flat plates installed under the meridional angle relative to the cylinder and at an angle of attack. Flat plates are symmetrically relative to the cylinder. There is a flat injection channel of constant width between the plates and the cylinder. We examine this situation of flat plates due to which the drag coefficient of the total combination reaches the smallest value. The study of reducing the drag of the cylinder was carried out in the package hydrodynamic analysis of Flow Simulation, as well as in the wind tunnel of Samara University. It has been shown that that the location of plates near the cylinder at certain angles, allows us to achieve reduction drag approximately before 40% compared with an isolated cylinder.
Two Dimensional Hypersonic Body-Intake Multi-Object Optimization with NSGA-II Algorithm
Authors: Qiao Lei , Fu Junjie , Bai Junqiang , Qu Feng 
Published: May 2020

Abstract
The forebody/inlet shape of the scramjet engine is significant to airplane performance. A multi-object optimization of hypersonic body-intake configuration is reported in the present work. The optimization system consists of geometry parameterization, mesh deformation, aerodynamic performance evaluation via computational fluid dynamics (CFD) and the top level driving optimization algorithm. In the present work, geometry parameterization is accomplished through B-Spline based free form deformation (FFD) method, volume mesh deformation is computed via inverse distance weight (IDW) method. Aerodynamic performance is evaluated with shear stress transportation model closed Reynolds averaged Navier-Stokes equations. At the top level, optimization is driven by the non-dominated sorting genetic algorithm II (NSGA-II) algorithm. Finally, the present optimization system is applied to a two dimensional hypersonic combined forebody-intake configuration. Numerical result shows that optimization gained improvement of 5% thrust, 9% pressure rise ratio and 7% total mass flow rate, which approved the effectiveness of the present optimization methodology.
Double Propellers Synchronous Control Based on Cross-coupling Control for Buoyancy-lifting Aircraft
Authors: Jianli Su , Hua Wang 
Published: May 2020

Abstract
To solve the double propellers synchronous control problem of the buoyancy-lifting aircraft, a control approach which uses cross-coupling method to control the double propellers is proposed. Firstly, the lateral-directional stability and manoeuvrability of this type of aircraft with double propellers are analyzed. Secondly, the cross-coupling control method is used to study the speed synchronization performance of the double propellers to improve the control accuracy. The simulation results show that, the double propellers speed synchronization control system based on the cross-coupling control method has a good control performance and better anti-disturbance. Finally, based on the control theory, the cross-coupling controller of the buoyancy-lifting aircraft with double propellers was designed, and ground run test and flight test are carried out. The experiment results show that the control method proposed has better performance and resistance.
Periodic Trajectory of Relative Motion Controlled by Constant Thrust
Authors: Bai Shengzhou , Han Chao , Wang Xiaohui , Sun Xiucong , Zang Jie 
Published: May 2020

Abstract
Formation flying has received widespread attention in recent years. However, the conventional control approaches require high demand for engine. To deal with this problem, the relative periodic trajectory can be achieved by multiple two-section constant thrust control proposed in this study. Firstly, the concept of the constant thrust control is presented. Furthermore, the strategy is presented to guarantees periodic trajectory considering J2 perturbation. Simulations are conducted to demonstrate the efficacy of the method. The proposed control approach is applied for engineering applications.
A New Information Code for Robot Localization
Authors: Yang Puguang , Chen An , Gao Hongxia , Liu Haiming , Wen Xiaoqin 
Published: May 2020

Abstract
Localization is the basic problem of mobile robot. A new approach for information coding and decoding for robot localization is proposed in this paper. information codes are used as landmarks to provide a global attitude reference. The label and location information is stored in the information code and strategically placed in the operating environment. The mobile robot is equipped with a camera that can read the information code for localization purposes Firstly, the current situation of the coding methods used for robot localization is analyzed, and the exposed problems and defects in application are summarized. In view of these problems, a new code method which is more suitable for robot location is designed. Then, the coding and decoding methods of the design are elaborated in detail. Finally, relevant experiments are designed in combination with practical application scenarios. Compared with the traditional QR code decoding method, the effect is better than the traditional QR code.
MatchRec: A User-item Matching Method for Sequential Recommendation
Authors: Luo Lv , Chen Tiankai , Qiu Rong 
Published: May 2020

Abstract
Sequential recommendation is based on the sequence of items that users interact with to predict the items that users will interact with next time. The existing methods usually consider the hidden sequential patterns in the user’s action sequence, but modeling candidate item features is ignored. To solve this problem, in this paper, we use the two-tower network structure to model the user’s action sequence and candidate item features respectively, then recommend items to users according to the matching score of user interest and item attribute. Specifically, we use self-attention mechanism to mine the information in the user’s action sequence, and use Factorization machines to automatically construct the cross features of item. We named this method MatchRec. The experiments on the public datasets demonstrated that MatchRec has a significant improvement in recommendation accuracy compared with that of various baseline methods.
An Attention Mechanism Based Algorithm of Identifying Vulnerable Spots of the Internet Data Center Power Systems
Authors: Liu Xinpei , Kang Chunjian , Jiang Zhuo , Zhao Tiezheng 
Published: May 2020

Abstract
With the rapid development of Mobile Internet and Big Data in recent years, the demand for data centers is increasing. The number of super large data centers (more than 1000 counters) has increased. This paper focus on the distribution system, who is responsible for providing a continuous, stable and uninterrupted power supply for the data center. In the event of a large-scale power outage, all business in the data center will be interrupted. Therefore, identifying which electrical equipment in the data center paly the key role in a large-scale power outage is extremely important. Considering the computational complexity of the algorithm, the validity of the vulnerable nodes, the intelligence of the algorithm, this paper proposes a two-layer fragile node identification method based on attention mechanism. The algorithm selects the topology structure and electrical parameters of the data center power distribution system, and considers the flow load of the nodes around each electrical device to form an expression vector. After the vulnerability ranking of the candidate node expression vectors, the k most vulnerable nodes are selected. The outline of the two-layer node identification method is as follows, the first layer calculates an alternative node sequence through a variety of graph-based fragile node identification methods, and the second layer re-calibrates the expression vector of each candidate node based on the attention mechanism and then sorts all candidate nodes. Through the simulation test of a real data center power distribution system, we can see that the proposed algorithm in this paper identifies the effectiveness of the vulnerable nodes in the data center power distribution system.
Research on Defect Priority Classification of Crowdsourcing Testing for Mobile Applications
Authors: Liu Ying , Ma Chunyan , Dong Zhanwei , Zhang Tao , Cheng Jing , Zhang Jie 
Published: May 2020

Abstract
Crowdsourcing testing technology has developed in recent years with the development of software testing, which can speed up releasing cycle and improve the quality of testing. It is of great practical value to study the priority classification and cause analysis of defect reports by using the potential information of crowdsourcing test defect reports. This paper combines the research of mobile application crowdsourcing test defect report with machine learning data analysis technology, studies the priority classification of mobile application crowdsourcing test defect report, and then carries out defect cause analysis on the basis of defect priority classification. Defect classification is an intuitive reflection of defect research. This paper takes defect priority classification as the breakthrough point of defect report research, uses σ – AdaBoostSVM classification algorithm to classify defect reports, and then carries out cause analysis after defect report classification, which is conducive to the faster location and repair of defects. The experimental verification results demonstrate the effectiveness of the proposed method.
Reliability Analysis of Distribution Network with Distributed Power Supply
Authors: Li Shenghui , Bai Xue , Zhang Xiaotong , Gu Cailian , Chen Zixuan 
Published: May 2020

Abstract
In this paper, the reliability index calculation method of power equipment, load and system dispatching is studied. According to the location of the circuit breaker and disconnecting switch, the fault is partitioned, and the load reliability index is the same in each minimum distribution area, so that the reliability evaluation of the distribution network can improve the efficiency. On this basis, the partition coding table is also established, and the calculation of the minimum distribution area can be directly transformed into the calculation of the corresponding coding area. Combined with monte carlo method, the correctness of the method used in this paper is proved by comparing the example analysis with other literatures.
Analysis and Optimization of the Admission Capability of Distribution Network to Distributed Power Sources
Authors: Sun Feng , Li Shenghui , Jin Ying , Gu Cailian , Shu Xinlei 
Published: May 2020

Abstract
This paper establishes a model for the ability of the distribution network to adopt distributed power sources, and proposes adoption constraints that consider the safe operation of the distribution network. The optimized assessment method of the ability of the distribution network to adopt distributed power sources proposed by analysis of simulation examples can help distribution network planners to ascertain the main limiting factors affecting the ability of the distribution network to adopt distributed power sources. According to the identified main limiting factors, distribution network planners can take appropriate measures to improve the ability of the distribution network to adopt distributed power sources.
Design and Implementation of Traffic Signal Control System Based on Parallel Simulation Technology
Authors: Tan Linglong , Zhou Xinliang , Su Yu , Wu Fengzhi 
Published: May 2020

Abstract
A traffic signal control system based on parallel simulation technology is designed in this article. Based on the second-level acquisition of intersection data, this system builds a control algorithm matching rule base based on offline algorithm adaptive analysis. In addition, the system can select the signal control algorithm that matches the real-time traffic status online, and realize the online evaluation of the control algorithm through the online parallel simulation and control algorithm evaluation platform, and provide a decision basis for further implementation of the algorithm. This system improves some existing deficiencies in signal control systems, and also provides decision support for the application of complex control algorithms. The system is applied to the control of actual signalized intersections. Practice shows that the system can better adapt to the actual situation of signalized intersections in District, improve the capacity of intersections and the efficiency of the entire road network.
Research on Experience Design Optimization of Mobile Reading Based on Continuous Using Behaviour
Authors: Lan Ma , Jianping Su 
Published: May 2020

Abstract
[Purpose / Meaning] The rich tools and media forms of mobile reading, while improving the convenience of reading, are also accompanied by the difficulty of maintaining the user’s concentration, and tend to be superficial reading experiences. How to use interaction design to improve the user’s reading experience and then cultivate its deep reading ability is of great significance to promote the quality of mobile reading services.[Methods / Processes]Guided by promoting users’ continuous use behaviours, this paper adopts an empirical research method in the form of questionnaires and conducts relevant regression analysis on the recovered questionnaire data to explore the influencing factors and influencing path of mobile reading applications on user cognitive experience and behavioural results. [Results / Conclusions] The factors extracted by factor analysis are classified into three categories: independent variables (content, function, interaction, vision), and intermediate variables (perceived usefulness, flow experience, reading social experience, perceived value) and outcome variables (adoption and continuous using behaviour). Furthermore, via the path analysis, this paper builds the influential factor path model on mobile reading behaviour. Based on the final empirical research results, this paper proposes specific interactive optimization strategies for mobile reading application design around Internet product design.
Skeleton-Based Pedestrian Abnormal Behavior Detection with Spatio-Temporal Model in Public Places
Authors: Wu Xiaojun , Zhao Wuyao , Yuan Sheng 
Published: May 2020

Abstract
In computer vision, there is growing interest in the recognition of pedestrian abnormal behaviors. The abnormal behavior of a person could be the sign of some dangerous activities. However, it’s still challenging to extract the discriminative spatial and temporal features effectively faced with video data. In this paper, we propose skeleton-based pedestrian abnormal behavior detection models. The base model is consisting of ResNet as a spatial feature extractor, LSTM as a global temporal feature extractor, and the ResNet network that use the dual-stream network to extract local temporal features. The proposed model is an improvement of all ResNet into Conv1x1_ResNet, and added a layer of Conv1x1_ResNet after dual-stream Conv1x1_ResNet to extract more accurate global space features. The proposed model achieved the highest accuracy of 89.29%, and the averaged get batch time is 0.3399 ms. The base model achieved 88.12% accuracy, and the averaged get batch time is 0.3174 ms less than the time taken by other models. Both models reach speed of 80 frames/sec. Compared with the models made in previous work, the base model has the shortest training time, and the proposed model provides the highest accuracy in the field of pedestrian detection.
Research on Multi-feature Adaptive Fusion Face Tracking Algorithm
Authors: Lei Qing , Li Zhijun , Wang Motao , Feng Jun , Zhang Rui 
Published: May 2020

Abstract
Under the premise of fixed computer performance, it is necessary to take into account the accuracy and real-time of face tracking. For this detection requirement, the image processing method of skin color segmentation is incorporated into AdaBoost’s face detection algorithm to accurately and quickly locate the face position. However, in the previous stage of face detection, there is a case where the real-time detection does not respond fast enough and fails the detection. In this case, a particle filter tracking algorithm based on multi-feature adaptive fusion is proposed, which uses the face area detected in the first frame as the tracking target, and achieves face detection by self-adjusting CS-LBP and the weight of how the skin color influences tracking effect, in which way the computational efficiency of face detection between frames is improved when the detection accuracy is maintained. And it is also robust to various complex external factors. It has been proved by experiments.
Research on Natural Human-Computer Interaction in Virtual Roaming
Authors: Li Fuyun , Feng Jianping , Fu Mousong 
Published: May 2020

Abstract
With the development of computer technology, human-computer interaction technology has gone through the development process of “command line interface”, “graphical user interface” and “natural user interface”. This paper explores the use of low-cost Kinect body sensor, in close to the premise of people’s habits, let users interact with the virtual scene roaming system in a natural way. Using the Kinect skeleton tracking technology, human posture is recognized through the relative position between joint points, and four kinds of self-defined postures are used to control the change of camera’s view angle to realize virtual scene roaming. The algorithm of this method is simple, it realizes the natural interaction between human and computer, and provides reference for the development of related systems in the future.
Unsupervised Person Re-identification via Discriminative Exemplar-level and Patch-level Feature Fusion
Authors: Lai Zhiping , Qi Meibin , Chen Cuiqun , Jiang Jianguo 
Published: May 2020

Abstract
The majority of existing person re-identification(re-ID) approaches adopt supervised learning pattern, which require large amount of labeled data to train models. However, due to the high cost of marking by hand, they are limited to be widely used in reality. On the other hand, due to the difference of the camera angle, there are many variations in pedestrian postures and illumination. It is known that Extracting discriminative features is pretty effective to solve the problem of person re-ID. Therefore, we propose to fuse exemplar-level features and patch-level features to obtain more distinguishing pedestrian image features for unsupervised person re-ID. Firstly, We carefully design exemplar-level and patch-level feature learning framework(EPFL). The skeleton frame adopts bicomponent branch, one branch is used to learn the global features of pedestrian images, the other is used to learn local features. Then, the global features at the example level and local features at the patch level are fused, thus the discriminative pedestrian image features can be obtained. Furthermore, feature memory bank (FMB) is introduced to facilitate the calculation of the similarity between pedestrian images on unlabeled dataset. We carry on our proposed method on two frequently-used datasets, namely, Market-1501 and DukeMTMC-reID dateset. Experimental results clearly demonstrate the advantage of the proposed approach for unsupervised person re-ID.