bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research and Design on Knowledge Base of NCCN-Based Cancer CDSS
Authors: Zhao Jiang-sheng , Xi Huang , Lv-qing Yang 
Published: August 2019

Abstract
At present, China faces a severe situation in which the incidence of malignant tumors is rising. At the same time, the search engines obtain a large amount of useless or even false medical information, and the tensions between doctors and patients are worsening every day. In order to enable patients to quickly and easily obtain the most authoritative and effective treatment solution, we are in imminent need of the research and development of tumor clinical diagnosis decision-making system. This system is based on NCCN’s latest clinical practice guidelines for malignant tumors, using the decision-making support system approach for research and development. This paper researches and analyzes the practice guidelines and gives the structure design for the knowledge base.
Unsupervised Learning of Visual Odometry with Depth Warp Constraints
Authors: Shi Haibin , Guo Menghao , Xu Zhi , Zou Yuanbin 
Published: August 2019

Abstract
Visual Odometry (VO) is one of the important components of Visual SLAM system. Some impressive work on the end-to-end deep neural networks for 6-DoF VO has appeared. We propose two-part cascade network structure to learn depth from binocular image and to infer ego-motion from consecutive frames. We propose depth warp constraints to make the Network learning more geometrically information. A lot of experiments on KITTI data set show that our model is superior to previous unsupervised methods and has comparable results with the supervised method, verifying that such a depth warp constraints perform successfully in the unsupervised deep method which is an important complement to the geometric method.
Design of Enterprise KB Assessment System Oriented to Operating Process
Authors: Ran Li , Yan Wang , Honglin Chang 
Published: August 2019

Abstract
Enterprise KM has the characteristics of complexity and long-term. Periodic self-assessment of KB system becomes the basis of self-innovation and continuous progress. In this paper, based on the process of KM, a four-dimensional assessment system of enterprise KB for assessing the operating and management of enterprise KB is constructed by combining qualitative analysis with quantitative statistical calculation. The four dimensions of systematization, knowledge precipitation, link rate, persistence and several sub-indicators are extracted from the four levels covering the platform, basis, means and objectives of enterprise KB and operating. An analysis method for cumulative results of assessment is also derived. Through the investigation and analysis of KB in four enterprises, the value of the assessment system is proved.
YOLO-RD: A lightweight object detection network for range doppler radar images
Authors: Zhou Long , Wei Suyuan , Cui Zhongma , Ding Wei 
Published: August 2019

Abstract
Under the condition of limited memory and computing power of radar aircraft equipment, large-scale object detection network based deep learning can not be deployed. Based on the darknet framework, Our paper proposes a lightweight object detection network for range doppler(RD) radar images: YOLO-RD, and builds a lightweight RD dataset: mini-RD, for efficient network training. Firstly, YOLO-RD extracts features from the input image through a series of small convolutional. Secondly, the dense block connection module is used to design the backbone extraction network. Finally, the prediction layer is combined with multi-scale features for prediction. Experiments show that YOLO-RD has achieved good results on the mini-RD dataset with a smaller memory budget, with a detection accuracy of 97.54%.
Using Deep Learning Techniques for Sandwich Panels with Truss Core Damage Detection
Authors: Wang Yabo , Lu Lingling , Song Hongwei 
Published: August 2019

Abstract
In the previous study, the accuracy of damage detection for the sandwich structures with truss core (SPTC) was affected by the selected damage index, Other than this, human subjective judgment could also not directly determine the degree and the location of damage for SPTC. In this paper, the deep learning method is applied to identify the damage for SPTC, and the dataset of the training deep learning model is obtained based on the dynamic method. This paper adopts to the Caffe, which is a deep learning open source framework, object detection model Faster R-CNN is utilized to study the lattice sandwich plate. The damage data set, the optimal hyperparameters for training the deep learning model, and the optimal ratios of the test set and training set for damage dataset are also studied. It is difficult to detect the damage of SPTC applying to the deep learning algorithms, so the good results cannot be gotten. In this paper, the method of Faster R-CNN has used extracts the deep features of the defective target by ZF that is a kind of Convolutional Neural Network (CNN), the method effectively solves the problem that the traditional algorithm cannot effectively detect the damage. As to the damage of SPTC that the traditional algorithms could also identify, the deep learning algorithm is excelled, the experimental mean average precision(mAP) can be raised to 90%. At the same time, the deep learning method can effectively identify locations and size of the damage in SPTC, the method is proven that the accuracy is higher and the speed is faster for damage detection. In the future, a real-time damage monitoring system is possible, and the theory is worth exploring further.
Research on Application of Microlecture to Teaching Reform of Higher Normal Education
Authors: Shuping Li , Taotang Liu , Jie Zhao 
Published: August 2019

Abstract
The progress in computer sciences and information technology provides more teaching modes. Recently, the microlecture has drawn extensive attentions, which could make the knowledge points clear in a shorter teaching time than traditional ways. In addition, it is not limited by time and space. This study makes some explanations and discussions on microlecture in order to apply it to higher normal education. First, the basic concept of microlecture is presented to explain the background. Afterwards, the teaching mode and advantages of microlecture are discussed. Accordingly, its potential in higher normal education can be inferred. Finally, some feasible ways are suggested to apply microlecture to the higher normal education. Conclusions are drawn based on all these analyses. And it is promising that microlecure could make contributions to the teaching reform of higher normal education.
Integrating knowledge-based engineering in body-in-white lightweight design
Authors: Tang Peicheng 
Published: August 2019

Abstract
During the vehicle design process, the body-in-white (BIW) lightweight design needs to consider factors from multiple aspects, such as topology, mechanical properties of the material, thickness parameters, BIW stiffness, modality and crashworthiness. At present, the commonly used BIW lightweight technology around the world includes the application of high-strength lightweight material, the optimization of vehicle structure as well as application of new molding and connection technology. The optimization of vehicle structure changes the mechanical properties of the components by selecting shape parameters of the components (such as the geometric characteristics of the components), in order to achieve lightweight design or performance optimization design. Since BIW contains a large number of structural components and design variables, designing BIW is always time-consuming and knowledgeable-extensive, which requires the collaboration of multidisciplinary engineers. This paper reviews the main methods of lightweight design of BIW and focuses on the application of knowledge engineering. Additionally, the paper introduces the effectiveness of knowledge reuse in practical cases.
3D-Finite Element Analysis for Influences of PCM Inserted in Garment on Body Temperature Responses
Authors: Ye Jialin , Li Fengzhi , Liu Weihua 
Published: August 2019

Abstract
To investigate the influences of the PCM micro-capsules in the garment on the body temperature responses, a mathematical model of heat and moisture transfer in garments inserted PCM micro-capsules is developed. The model is solved by the finite element method. Then, this garments model is interfaced with the thermal regulatory model of the human body based on the 3D FEM. Furthermore, the temperature distribution of garment and human body is simulated by using the model. The results show that garment with PCM can significantly delay the temperature rise compared with garment without PCM.
Research of the Principle and Method for the Long-term Preservation of the Product Structure Design Information of the Launch Vehicle
Authors: Wang Teng , Nie Rongmei 
Published: August 2019

Abstract
Aimed at the long term preservation of the product structure design information in the launch vehicle 3D model, the article researches the feasibility of long-term preservation solutions for the product 3D model information, and raises a suitable method to preserve the structure design information of the 3D model . At the end of the article, an information automatic reading module and 3D model visualization module is developed which is based on the OpenCascade to solve the long term preservation of the product 3D model structure design information.
Chaotic Search Optimal Design and Modeling of Permanent Magnet Synchronous Linear Motor
Authors: Fei Yang Yi , Cun Zhou Zheng , Bin Wang Hong , Chen Jin Xiao 
Published: August 2019

Abstract
This paper presents an electromagnetic finite element model of permanent magnet synchronous linear motor and distortion rate of the air gap flux density waveform is analyzed in detail. By designing the sample space of the parameters, nonlinear regression modeling of the orthogonal experimental design is introduced. We put forward possible air gap flux density waveform sine electromagnetic scheme. Parameters optimization of the permanent magnet synchronous linear motor is also introduced, which is based on chaotic search and adaptation function. Simulation results prove that the pole shifting does not affect the motor back electromotive symmetry based on the structural parameters, which provides a novel way for the optimum design of permanent magnet synchronous linear motor and other engineering.
Research on Key Technologies of MEMS-based 3D Imaging LIDAR Vision System
Authors: Li Lianchun , Qian Keyuan , Zhou Jingkun 
Published: August 2019

Abstract
In this paper, a new type of 3D imaging light detection and ranging (LIDAR) vision system based on Micro-Electro-Mechanical System (MEMS) mirror and novel optical system is proposed. The co-aperture transceiver optical system offers a compact architecture and wide Field-of-View (FOV), which also solves the problem of stray light affecting the system. Thanks to the MEMS and the optical system, the detecting FOV is greatly enlarged and the system volume is much smaller compared to the traditional system. The whole system is designed and verified by simulations and experiments.
Finite element analysis and experimental research on multi-wheel planetary intermittent type spinning mechanism for internally-externally toothed parts with thin-wall cup-shaped
Authors: Guo Yaming , Li Mingzhe , Huang Tao , Luo Wei , Lu Bo , Zhang Rui , Guan Ruoyang , Zhao Xing 
Published: August 2019

Abstract
In this paper, a multi-wheel planetary intermittent type spinning process was investigated through finite element analysis(FEA) and process experiment. The spinning deformation mechanism of cup-shaped internally-externally toothed parts was studied by simulating the planetary spinning process. The distribution of the transient stresses in the contact zones between the roller and blank, and the equivalent plastic strains after spinning were analyzed. The location and causes of defects were determined through analyzing three-dimensional stress and equivalent strain. By comparing the distribution of workpiece thickness after spinning with the simulation result, it has indicated that this research is favorable for developing the technological forming criterion to guide the practical manufacture processes.
Motion design and Stability study of Biped Robot
Authors: Limei Zhao , Xiaotie Ma 
Published: August 2019

Abstract
Biped robot is one of many kinds of humanoid robot, with upper and lower limb structure of multiple degrees of freedom, humanoid appearance and friendly human-computer interaction interface. Robobasic programming language is used to set the rotation angle and direction of each steering gear, so as to carry out motion design and flexibly control the robot. Then, through the theoretical analysis of zero moment point (ZMP), the ideal motion trajectory of the robot in different environments can be determined to ensure that the robot can realize simple machine movements similar to those of human beings on the basis of stable motion.
Study and Application of Intelligent Control Technology in Local Fan of Coal Mine
Authors: Jing Zhao 
Published: August 2019

Abstract
Local ventilator is an important equipment in the process of underground coal mine excavation, and its reliability and efficiency directly affect the safety of gas emission. Because of the characteristics of large lag, non-linearity and multi-disturbance of local fan control system, the traditional PID control method can not achieve the desired control effect, so an intelligent control technology, i.e. fuzzy control, is put forward and applied to the local fan control system, and the fuzzy control algorithm is improved. The improved fuzzy controller can pass through the local part according to the gas concentration in the heading face. The speed of fan is adjusted in real time to ensure the safety of underground working environment, and the fuzzy control of gas concentration and frequency conversion speed regulation of local fan is realized. The fuzzy control not only improves the ventilation control performance and automation level, but also has remarkable energy-saving effect and better control performance.
Optimal Design of Gap Sensor for High-Speed Maglev Train
Authors: Liu Xiankai , Miao Xin , Jin Hao , Jing Yongzhi , Wang Fengchao 
Published: August 2019

Abstract
The gap sensor plays an important role in high-speed maglev train which is able to measure the variation of trains’ suspension gap. The magnetic fields distribution is different clearly when the sensor is opposite to different position in a tooth-groove period of stator railway. The fluctuation of equivalent inductance leads to the slot-effect. The slot-effect is an important factor affecting the stability of the high-speed maglev train suspension control system. The distribution of magnetic field intensity of the flat rectangular coil in different gaps and positions is analysed, and the mechanism of slot-effect is revealed. A new coil is proposed in this paper and this optimized coil can create a smaller slot error than the flat rectangle coil. The simulation results show that the slot error of optimized coil is always less than the error of original coil in any gap distance. The slot error is reduced by half at the working air gap from 8mm to12mm. The slot error of the optimized coil reaches a maximum at 2mm and reaches its minimum at the rated suspension gap 10mm.
Application of High-frequency EMI on Shell SHM with Diverse Radians
Authors: Zhang Xin , Zhang Yu-xiang , Tang Tao , Zhao Jian-gang , Liu Wan-lei 
Published: August 2019

Abstract
Exploring the application of electric-mechanical impedance (EMI) on structural health monitoring (SHM) of diverse systems or structures, especially the radian shell is very necessary to achieve the rapid online monitoring of structural damage. This paper studies the application of EMI on damage detection of shell structure with different radians. Using the piezoelectric equations of piezo-material lead zirconate titanate (PZT), the admittance values of aluminum shell before and after structural damage were got in a given frequency domain. Then by designing experiments based on Agilent 4294A instrument and analyzing the changes of admittance-frequency spectra before and after damage, it concluded the corresponding relationship between the sensitive detection frequency and the radian of the aluminum plate under given thickness; on the meantime, it is found that the damage index (DI) - root mean square deviation (RMSD) can be a judgment standard of damage by analyzing the data of special frequency band, which will has strong guiding significance for the selection of damage detection frequency and damage judging in arc structure hereafter.
Predicting Virtual Machine Resource Consumption Based on Optimized Grey Model
Authors: Aiwu Shi , Di Gao , Kai He 
Published: August 2019

Abstract
In order to relatively change the computing specifications of virtual machines (VMs for short) for the changing resource consumption of VMs, and reduce the impact of the changes, this paper proposes the optimized grey GM(1, 1) model to predict the resource consumption of VMs. Because VM resources may fluctuate greatly in a short time, the initial data are smoothed first, and then modeled, the model edge value is optimized according to the characteristics of cloud environment. Experiments show that the accuracy and stability of the prediction model can be improved by sorting out the initial data and optimizing the model. The prediction value is helpful to design the allocation scheme of VM resources, improve the utilization rate of physical resources in cloud environment.
Research on Genetic Algorithm Fault Diagnosis in Chemical Process
Authors: Li Zhihua , Chen Jing 
Published: August 2019

Abstract
Aiming at the high false positive rate of traditional PCA (principal component analysis) algorithm in chemical process fault diagnosis, an algorithm combining GA (genetic algorithm) and PCA algorithm is proposed. Optimize the training samples of the PCA algorithm. In this method, when selecting training samples, not only the specific data is selected, but the selected data is optimized by the GA. Select a set of best performing data as a new training sample. Experiments using continuous stirred tank reactor data show that the improved PCA algorithm can effectively reduce the false positive rate compared with the traditional PCA algorithm.
Design of OFDM Joint Synchronization Algorithm Based on Cyclic Prefix
Authors: Liu Mengyang , Wang Hongjuan , Li Yeli , Bian Yuning 
Published: August 2019

Abstract
By studying the Maximum Likelihood (ML) algorithm and applying it to Orthogonal Frequency Division Multiplexing (OFDM) system, we analyze its performance. OFDM system has obvious advantages over other wireless communication systems, but it also has disadvantages, such as being sensitive to synchronization errors. The ML algorithm can solve this shortcoming of OFDM system. ML algorithm uses the redundant information carried by the cyclic prefix in OFDM code element. At the same time, ML algorithm calculates its maximum likelihood estimation algorithm to complete the code element timing synchronization and carrier frequency synchronization. Compared with other synchronization algorithms, ML algorithm can complete initial capture and synchronous tracking in one step, so it is widely used in OFDM systems. In this paper, we build a traditional OFDM system and apply the ML algorithm to OFDM synchronization simulation. By changing the design of relevant parameters, we describe the ML algorithm in detail and obtain the same results as the theory.
Some new theorems of α-admissible mappings on c-distance in cone metric spaces over Banach algebras
Authors: Yan Han , Yi-duo Bian , Chang-ji Shan 
Published: August 2019

Abstract
In this work, we introduce some new fixed point results of α-admissible mappings on c-distance in cone metric spaces over Banach algebras, which are significant extensions and generalizations of many important known results. Furthermore, we give an example to illustrate our main results.
A Double Threshold Collaborative Detection Algorithm Based on Mutual Trust Degree Correction
Authors: Lujie ZHANG , Dechun GUO 
Published: August 2019

Abstract
This paper proposes a double threshold detection algorithm based on mutual trust degree correction, in order to reduce the probability of missed detection. First, the algorithm performs mutual trust correction on the local detection statistic of the information fusion center, next, performs information fusion. The algorithm reduces the influence of a single user on the detection result, which is caused by the weight distribution in the information fusion process. The algorithm makes the weight distribution in the information fusion process more reasonable and balanced. The simulation results show that the detection performance of the double threshold detection algorithm modified by the mutual trust matrix is better than that of the traditional double threshold detection algorithm.
Impact of Confusion Factor on Simulation of An Agent-based Panic Crowd Evacuation Model
Authors: Chen Xiaowei , Wang Jian 
Published: August 2019

Abstract
Aiming at how panic and chaos affect pedestrian behavior and evacuation efficiency, we propose a panic crowd evacuation model based on entropy. Boltzmann entropy and Shannon entropy are used to simulate people’s escape behavior in panic disorder. The simulation results suggest that the proposed model can effectively reflect the negative impact of chaos on evacuation, which leads to longer evacuation time. Compared with Shannon Entropy, Boltzmann Entropy is more sensitive to the number of persons and helpful to identify the evacuation bottleneck area. This work provides a new insight for understanding how crowds behave in an emergency evacuation.
Research on the Security Data Transmission based on Linux
Authors: Li ShuLiang , zhang Jie , Liu Youzhu 
Published: August 2019

Abstract
This paper develops system software in application layer based on Linux operating system. Linux operation system in this paper. Different transmission modes are adopted in different parts to improve the transmission efficiency in the network. The data capture encryption method is used for the file data, and the storage transmission method is used for the image data. It designs an identity authentication protocol and key exchange protocol based on digital certificate and digital sign technology, to avoid the sophistication and filch and improve the reliability of the identity authentication and the security of the key exchange. The common algorithms of symmetric encryption, asymmetric encryption and information digest are studied by using OpenSSL standard library function to realize data encryption module of the system.
Research on reliability evaluation method of active distribution network
Authors: Yue Chao , Qi Qiumin , Wang Yu , Wang Bojun , Zhang Xilong 
Published: August 2019

Abstract
The operation time of active distribution network is affected by distributed power supply, which brings complex problems including power quality, power supply reliability and relay protection, among which the reliability problem is particularly prominent. This paper discusses the component mathematical model, evaluation index and evaluation method for the reliability evaluation of active distribution network.