bluuebunny/crossref_metadata_2025 huggingface dataset:
Turbulent boundary layer perturbation by two wall-mounted cylindrical roughness elements arranged in tandem: Effects of spacing and height ratio
Authors: Hamed Ali M. , Peterlein Adam M. , Randle Lindsey V.
Published: June 2019

The perturbation of a turbulent boundary layer by two cylindrical roughness elements in close proximity was experimentally investigated in a water channel using planar particle image velocimetry. The two cylinders were arranged in tandem with center-to-center streamwise spacings of 2d, 4d, and 6d, where d is the diameter of the cylinders. The downstream cylinder had a fixed height 0.2δ, where δ is the incoming boundary layer thickness; the height of the upstream cylinder was varied to achieve upstream to downstream cylinder height ratios of 1, 0.75, and 0.5. The flow measurements were made at Reδ = 56 800 and included measurements over an isolated cylinder as a baseline case. The results highlight the effects of sheltering by an upstream cylinder on the wake of the downstream cylinder. Flow features in the wake, including the downwash, upwash, recirculation zone, velocity deficit, Reynolds shear stress, and turbulent kinetic energy (TKE), are dependent on the degree of sheltering, which is reliant on both the streamwise spacing and height ratio. Overall, sheltering results in a reduction in the downwash and size of the recirculation zone past the downstream cylinder. The magnitude and spatial distribution of the Reynolds shear stress and TKE varied significantly from those past the isolated cylinder. Depending on the streamwise spacing and height ratio, the presence of an upstream cylinder has the potential to enhance or reduce the Reynolds shear stress past the downstream cylinder. For example, the maximum Reynolds shear stress in the near wake was approximately doubled for a spacing of 2d and a height ratio of 0.5 and nearly halved for a spacing of 2d and a height ratio of 1 (relative to that past the isolated cylinder). The variations in these flow features across the 9 considered arrangements suggest changes to the wake and its vortical structures due to the presence of an upstream cylinder. The results highlight the potential of flow control through a pair of roughness elements in close proximity to achieve desired outcomes such as reduced or redistributed Reynolds shear stress and TKE, relative to the isolated cylinder.
Linear stability characteristics of the pressure-gradient driven flow confined in concentric cylinders with the rotation of outer cylinder and translation of inner cylinder
Authors: Khan M. Ijaz , Khan M. Sabeel , Araya A. Gonzalez
Published: June 2019

In this contribution laminar to turbulent transition is studied in a pressure gradient driven flow confined between Taylor cylinders. The outer cylinder is assumed rotating and the inner cylinder is under translational motion. In this respect, a mathematical model describing the physics of flow dynamics is presented and implemented using MATLAB. Spectral collocation approach is used to calculate the eigenvalues which predict the critical stability parameter value. The critical parameters at which the laminar to turbulent transition just starts are calculated. The neutral stability diagrams are obtained for various physical situations characterizing the limit points of damping and growth of the wave disturbances. It is observed that an increase in the swirl and translation allows the transition to start later than the classical case. However, increase in the gap width allows the transition to appear earlier than the classical case. A change in the Tollmien Schlichting mechanism is seen with the change in swirl, translation and gap width of the two cylinders. Moreover, the linear stability analysis discussed here provides a basis for the nonlinear stability analysis with the help of adjoints calculated and presented.
Effect of angle of attack on vortex dynamics in laminar separation bubbles
Authors: Lambert Andrew , Yarusevych Serhiy
Published: June 2019

The dynamics of coherent structures that develop within laminar separation bubbles over a NACA 0018 airfoil at Rec = 100 000 and Angles of Attack (AOA) of 0°, 5°, 8°, and 10° are investigated experimentally using a high-speed flow visualization technique and vortex tracking via embedded microphones. The results identify vortex shedding within the separation bubble for all the cases investigated. The vortices form upstream of mean transition location and break down in the vicinity of mean reattachment, with irregular vortex merging events detected in the aft portion of the separation bubble. As the mean size of the separation bubble decreases with increasing angle of attack, vortex shedding characteristics also change appreciably, with shedding frequency increasing and characteristic streamwise wavelength decreasing. However, vortex roll up and salient aspects of vortex development take place within approximately the same regions downstream of separation location in terms of percentage of the bubble length. For all the cases examined, significant cycle-to-cycle variability is observed in salient vortex characteristics, being particularly pronounced in the aft portion of the bubble where vortex merging occurs and significant spanwise deformations of vortex filaments are expected. Merging of the shear layer vortices is shown to occur irregularly between the mean transition and reattachment location, with merging events separated by a relatively wide range of shedding cycles. As the angle of attack increases from AOA = 5° to 10°, the fraction of primary vortices involved in merging increases up to about 25%. However, enhancement in vortex merging is also noted at lower AOA where shedding occurs close to the trailing edge, which is speculated to be linked to upstream scattering of periodic pressure fluctuations induced at the trailing edge.
A laser source driver with adjustable amplitude and pulse-width in 130-nm CMOS technology for quantum key distribution experiments
Authors: Feng Bo , Liang Futian , Wang Xinzhe , Zhu Chenxi , Zhu Yulong , Jin Ge
Published: June 2019

We present a laser source driver using a 130-nm complementary metal oxide semiconductor technology, named quantum laser source driver 2018 (QLSD2018). QLSD2018 drives the optical source with a current pulse signal, and the output of QLSD2018 has an adjustable pulse-width from 300 ps to 3.8 ns and an adjustable amplitude up to 70 mA. The data rate is up to 625 Mb/s, and the extinction ratio of the optical source (the 1550-nm distributed feedback laser or the 850-nm vertical-cavity surface-emitting laser) driven by QLSD2018 can reach 26 dB. The test results indicate that QLSD2018 can be used in quantum key distribution experiments. Using QLSD2018 on the transmitter side can significantly simplify the peripheral circuit of the optical source.
Real-time dynamic holographic display realized by bismuth and magnesium co-doped lithium niobate
Authors: Zheng Dahuai , Wang Weiwei , Wang Shuolin , Qu Da , Liu Hongde , Kong Yongfa , Liu Shiguo , Chen Shaolin , Rupp Romano , Xu Jingjun
Published: June 2019

Particular attention has been given to updatable or dynamic holographic displays in recent years. The absence of ideal recording materials hampered the realization of their commercial applications. A lithium niobate crystal codoped with 1.0 mol. % bismuth and 6.0 mol. % magnesium has been grown with a diameter of 2-in. A moderately large saturation diffraction efficiency of 26% can be achieved, which corresponds to a refractive index change of 2.45 × 10−5. However, the photorefractive response time turns out to be only 13 ms, and the photorefractive sensitivity reaches 1.63 × 102 cm/J. This is by a factor of 104 larger than the one of congruent lithium niobate. The codoped crystal was used to demonstrate a real-time holographic display with a refresh rate of 30 Hz, which is a significant step forward for inorganic crystals in holographic display applications. Band structure calculations indicate that the dopants influence the charge distribution of the oxygen atoms which may be the clue to the origin of their excellent properties.
Compressed liquid marble ruptures at edge
Authors: Liu Zhou , Zhang Yage , Yang Tiyun , Wang Zhi , Shum Ho Cheung
Published: June 2019

An improved understanding of the rupture dynamics for liquid marbles is essential for their application in sensors, miniaturized reactions, biomedical scaffolds, the synthesis of functional materials, and others. This work suggests that a compressed liquid marble always ruptures at the edge of the contact area between the marble and a substrate. The rupture dynamics of a compressed marble is visualized with a particle-level resolution using a marble coated with monodispersed microparticles. High-speed photography indicates that the particle density decreases significantly from the center to the edge, and the sparse particle layer at the edge initiates rupturing. Such a particle density distribution is well depicted with our proposed model, which predicts the theoretical values that agree well with the experimental results. This study generalizes the understanding for the rupture dynamics of particle-stabilized droplets and is beneficial to any applications that involve the rupture or coalescence of liquid marbles as well as Pickering emulsions.
A new framework presents quasi-locality bounds for quantum lattice systems
Authors: Johnson-Groh Mara
Published: June 2019

A new paper provides a comprehensive mathematical framework for quasi-locality in quantum lattice systems.
Avérogavér?
Authors: Paoli Sandra
Published: June 2019

This contribution is an investigation of the distribution and nature of a structure found across Northern Italian varieties, a reflex of Latinhabereto which a locative particleghas been added, within the contexts of the relation between microvariation and gradual language change. A detailed morpho-syntactic description forms the basis for an analysis that suggests a probable path of univerbation of the two elements. Driving the analysis is the consideration of the original semantic features of the Latin element from which the locative particle has developed, in particular of the order of their weakening.
Condensation for random variables conditioned by the value of their sum
Authors: Godrèche Claude
Published: June 2019

We revisit the problem of condensation for independent, identically distributed random variables with a power-law tail, conditioned by the value of their sum. For large values of the sum, and for a large number of summands, a condensation transition occurs where the largest summand accommodates the excess difference between the value of the sum and its mean. This simple scenario of condensation underlies a number of studies in statistical physics, such as, e.g. in random allocation and urn models, random maps, zero-range processes and mass transport models. Much of the effort here is devoted to presenting the subject in simple terms, reproducing known results and adding some new ones. In particular we address the question of the quantitative comparison between asymptotic estimates and exact finite-size results. Simply stated, one would like to know how accurate are the asymptotic estimates of the observables of interest, compared to their exact finite-size counterparts, to the extent that they are known. This comparison, illustrated on the particular exemple of a distribution with Lévy index equal to 3/2, demonstrates the role of the contributions of the dip and large deviation regimes. Except for the last section devoted to a brief review of extremal statistics, the presentation is self-contained and uses simple analytical methods.
A Method for System Reliability Evaluation Based on Inexact Interval Probability
Authors: Li Chen , Wang Li , Yu Qiao , Li Meng , Wang Bolun , Zhou Yingjian , Zhang Zhewen
Published: June 2019

With a large number of new components and new technologies widely used in power system, the method of power equipment outage probability based on law of large number will no longer be applicable due to the lack of statistical data. This paper considers the high order uncertainty of component failure probability under the condition of small sample size and uses interval values to represent the reliability parameters of the component when carrying out the risk assessment of power system, and propose Belief Universal Generating Function by combining Universal Generating Function with Belief Function Theory. This method can effectively avoid over estimation in interval arithmetic and get a more accurate interval value of power system risk assessment index.
Fatigue Scatter Factor Analysis of Airplane Structures Based on Zero-failure Data
Authors: Wang Junling , Zhang Yongbo , Shi Wenjing , Wang Zhihua , Huang Yuliang , Cui Yi
Published: June 2019

In the fatigue life test of high-reliability airplane structures, a large number of zero-failure data can be obtained, in which case the fatigue life scatter factor is significantly different from that of complete data. This paper conducted a study to define a scatter factor correction coefficient for normal distribution and two-parameter Weibull distribution under the condition of zero-failure data and derived the difference of the scatter factor under these two cases theoretically. At the same time, in order to analyze the difference, a comparative analysis of numerical simulation results under a certain reliability index is presented. The results show that this method makes full use of the product information under the conditions of zero-failure data to enhance the structures’ fatigue safe life and to meet the practical engineering requirements.
The Research Characteristics and Status on the Area of Educational Big Data from 2012-2019
Authors: Jiang Cheng , Wang Qi , Qing Wu , Zhu LeiYe , Ding Cong , Wang HaiBin
Published: June 2019

To explore the status on the area of educational big data, 476 related articles form the from Web of Science core collection were analyzed by CiteSpace V. The results show that: (1) the area of Educational Big Data stared in 2012 and shows an upward trend year by year form 2014-2018, and the number of publications reached the historical peak in 2018. Williamson and Huda, USA and China, Educational sciences theory practice and Agro food industry hi tech top the list of contributing authors, country and publication respectively. (2) “eHealth research”, “current state”, “corporate use” “data entry”, “analytics discipline” and “psychological language” are the top six largest clusters on the area of educational big data from 2012-2019.
Intelligent Research on Customer Complaints Based on 95598 Work Orders Track
Authors: Xin Xu , Jun Fu , Li Wang , Dongmei Gong , Yujun Wang , Peilin Tang
Published: June 2019

With the rapid development of society and economy, the living standard of people is continuously improving, which makes the society’s demand for electricity increasing day by day, as well as the demand for power supply capability and service quality. When the power supply service enjoyed by customers does not meet the expected value, it will stimulate various demands of customers and even the customer complaints. How to accurately grasp customer demands and effectively prevent customer complaints is the key to improve customer satisfaction of power supply service and maintain a good image of power enterprises. The purpose of this article is to excavate the internal connection of the existing data through the serialization research based on the national power grid data, so as to predict whether users will make complaints after the call.
Acoustic fatigue life prediction of structure based on power spectral density method
Authors: Rong Yinlong , Li shiji
Published: June 2019

In the field of aerospace engineering, a large amount of thin shell structure is used in order to reduce the weight. These structures will be damaged by acoustic fatigue at high levels of noise and vibration loads. Acoustic fatigue analysis of thin walled structure is a very important part of the aircraft structure design. Simulation and analysis of three different fixation methods for random acoustic loads of thin-walled structure of aluminium alloy were introduced in this article. A method of power spectral density (PSD) was calculated for sound pressure level respectively in the band limited white noise 145 dB, 148 dB, 151 dB combined with fatigue damage theory based on linear length of the sound. The length of the 7075 Aluminium alloy material is 300 mm, and the thickness is 1.5 mm. The results show that: in the case of different ways of holding, the maximum stress suffered by the aluminium alloy thin sheet appeared at the constraint location, and this position is dangerous position for structural fatigue where will first be destroyed by random loads. Under random acoustic loads, the strain cloud of aluminium alloy thin sheet structure is the same with the first vibration mode, so the random vibration response was most effected by the first modal. Acoustic fatigue of the different sound pressure level was calculated by using the method of PSD and Miner linear damage rule.
Research on intelligent transportation solution based on big data mode
Authors: Chen Baiyu , Fu Da , Yang Yuanyuan , He Linhuan
Published: June 2019

This paper presents an intelligent traffic road resource allocation solution based on the traffic big data model. Through the collection and analysis of road traffic information big data, a planning scheme that can minimize road congestion when shared road resources between manned vehicles and unmanned vehicles is established. In order to alleviate the traffic congestion caused by the imbalance between road resources and traffic demand, taking 2020 as an example, the road congestion level is solved and given. When the judgment criterion is between 0 and 0.5, the road congestion level is set to level 3. When the judgment criterion is between 0.5 and 1, the road congestion level is set to level 2, and the remaining levels are level 1 and level 4. When: 1. The speed of the front car before braking is v

b
= 40km / h. 2. The speed of the rear car before braking is v
a = 60km / h, and the car is moving at a constant speed in a short time. 3. When the dry asphalt pavement is taken a

b max = 6m / s
2. 4. When the wet asphalt pavement is a

bmax = 4.5m / s
2. The degree of road congestion is level 1.
Research on Radar/Infrared Fusion Algorithm Based on IMM/MS-MDPDAF
Authors: Chen Xing , Li Zhan-wu , Hu Xiao-dong , Cui Yun-hua
Published: June 2019

In the clutter environment, radar/infrared sensors are used to track the background of maneuvering targets. Aiming at the shortcomings of traditional probabilistic data association theory in solving multiple target echoes and numbers in measurement, it is presented by combining interactive multiple model (IMM) and multiple detection probabilistic data association filter (MDPDAF) in a multi-sensor (radar and infrared) scenario known as IMM/MS-MDPDAF algorithm. The IMM algorithm has the ability to adapt to the target high maneuver and clutter environment. The MS-MDPDAF algorithm can detect multiple effective target echoes, considering various uncertainties in the clutter environment. According to the multi-detection mode of radar sensor, the target is effectively measured and the state vector is updated. Then the data fusion and probability data association theory are used to calculate the corresponding probability and state prediction, estimation and update under the Bayesian framework. The simulation results show that the IMM/MS-MDPDAF algorithm can improve the effectiveness and tracking accuracy of target, and has better tracking performance than IMM/MSPDAF.
Research Status and Development Trend of Path Planning Algorithm for Unmanned Vehicles
Authors: Lu Kaida , Zhang Yan , Li Huiyuan
Published: June 2019

With the wide application of unmanned ships in the fields of water surface bleaching, sea exploration, water quality monitoring and emergency rescue, unmanned ship technology has attracted more and more people’s attention. Due to the navigation environment of unmanned ship is very complex, diverse and changeable, it has become the primary task of unmanned ship technology research to study how to use path planning algorithm to integrate a large number of multi-sensor data, quickly and accurately make navigation strategies and achieve accurate motion control. This paper mainly summarizes the current research status of unmanned ship path planning algorithms, analyzes the differences and advantages of various path planning algorithms in practical applications, and finally points out the research trend of unmanned ship path planning algorithms.
Research on Knowledge Classification Based on KNN and Naive Bayesian Algorithms
Authors: Chenyang Wu , Xiaohua Wang , Jinbo Wang , Jiawei Song
Published: June 2019

With the development of the Internet, the speed of knowledge update is getting faster and faster, and the Internet is full of various knowledge data. For knowledge management systems, the knowledge classification function is very important. The main task of this paper is to learn the mapping relationship between text content and text category according to the given text content and text category, so as to get a classification model. Finally, use this classification model to process the text of the unknown classification, and judge or predict the category of the unknown text.
DMC-PID Cascade Control Algorithm for the Constant Rate Temperature Rising Process in Differential Scanning Calorimeter
Authors: Yang Yu , Jingtao Hu , Laixing Wei
Published: June 2019

In view of the poor tracking performance of conventional control method in differential scanning calorimeter during constant speed heating progress, a DMC-PID cascade control algorithm for differential scanning calorimetry is proposed. Firstly, based on the predictability and optimality of the DMC algorithm, the DMC controller is used in the main circuit to control the generalized object composed of the PID controller and the reheating furnace. Secondly, on the basis of the characteristics that PID controller can improve the dynamic of the controlled object, the PID controller is used in the secondary loop of the control system to improve the linearity of the controlled object. Finally, the proposed control method is applied to differential scanning calorimetry constant temperature control process. Experimental results show that the proposed method can effectively reduce the static error and improve the tracking performance of the control process.
Spatio-Temporal Context Tracking Algorithm Based on Correlation Filtering
Authors: Fang Qi , Zhou Hao , Zhang Lu
Published: June 2019

The Correlation Filter tracking algorithm is different from the traditional method based on target feature, which has high accuracy and fast tracking speed. In this paper, the Spatio-Temporal Context(STC) target tracking algorithm is combined with Correlation Filtering, the position of the target is predicted by using Correlation Filtering and the prediction result is corrected by using the STC target tracking algorithm. The target tracking algorithm combined with Correlation Filtering and STC can realize effective tracking when the target is occluded or there is an interference target. The experimental results show that the proposed algorithm can not only be applied to the tracking of visual targets in complex backgrounds such as illumination changes, target rotation and background region interference, but also have better robustness.
An Improved LeaderRank Algorithm for Identifying Critical Components in Service-Oriented Systems
Authors: Jiang Shuo , Zhang Xiuguo , Cao Zhiying
Published: June 2019

Identifying critical components of Service-Oriented Systems is of great significance to the overall reliability of the system. As the size of software systems increases, identifying critical components can reduce the number of components that need to be predicted and shorten the prediction time in the process of predicting system reliability. Moreover, predicting the reliability of critical components can also ensure the stability of system. Therefore, we propose a method for identifying the critical components in Service-Oriented Systems. This method transforms the interaction between service components of Service-Oriented Systems into service dependency graph. An improved weighted LeaderRank algorithm is used to measure the importance of components and obtain the sequence of critical components. Through experimental analysis, the method can accurately and efficiently identify critical components in the system.
Weight Adjusting Algorithm Based on Sensor-space-time Quantum for Air-Information Fusion Precision Evaluation
Authors: Xiao-chao Wu , Ying Cheng , Long-fei Cui , Yun-ge Tang
Published: June 2019

The precision index in the performance test of air-information fusion system is one of the important indexes, which benchmark to be determined in complex environment is difficult. This paper proposes a space-time weight adjusting algorithm for the air-information fusion system to solve this problem, as follows: The first is to build the weight priority by the magnitude of radar detection precision; the second is to find the sets of the radars’ time domain that play a dominant role during fusing; the third is to calculate the time cumulate value of radar precision; the fourth is to use the time cumulate value of radar precision and fusion track to allocate all the radar precision weights, and calculate the reference precision by weighting the radar detection data precision; the last is to evaluate the precision index according to fuzzy evaluation method. This algorithm applies to the precision evaluation of the air-information fusion system under the static simulation or dynamic flight conditions with good adaptability and credibility. The simulation shows its value.
Review of Polar Integrated Navigation Algorithm
Authors: Ming Tian
Published: June 2019

Developing the research of navigation and positioning in high latitude area has important political, economic and military value, and it is of great significance to realize the global navigation of inertial navigation system. In this paper, the basic algorithms suitable for polar navigation are summarized, various polar integrated navigation methods are compared, and the research of inertial / astronomical integrated navigation with small error, high accuracy, wide application is particularly introduced.
Maximum Entropy Image Segmentation Method Based On Improved Firefly Algorithm
Authors: Liu Qianru , Jiang Zhanjun , Shi Haoqiang
Published: June 2019

An adaptive parametric firefly algorithm is proposed for the premature convergence of the firefly algorithm itself and the late oscillation of the algorithm iteration. In the image threshold segmentation test experiment, the algorithm is used to optimize the maximum entropy image segmentation, and the maximum entropy and the basic firefly improved maximum entropy algorithm are compared. At the same time, two important indicators of image segmentation evaluation index regional consistency are used to evaluate the results. It shows that the experimental results of the algorithm have better intra-regional consistency and noise immunity.
Research on Weighted Clustering Algorithm for Ad Hoc Networks Based on Topology Correlation
Authors: Shan Luchao , Zhang Luyong
Published: June 2019

In order to improve the clustering performance of wireless networks, an improved multi-parameter weighted clustering algorithm named TCWCA was proposed. The algorithm takes into account the calculation factors of node degree, inter-node distance, node mobility, node energy, and the increment of network topology association in the clustering process. In addition, the algorithm applies the increments of regional topology association of network nodes to the process of calculating weighting factors. The simulation results show that the algorithm has better clustering performance and improves the stability of the network clustering structure.
Ternary Search Trie based Algorithms for Recognizing the Names of Power Devices
Authors: Liu Yi , Xu Jiahui , Gong Xiujun , Bai Jingjie , Xiao Linpeng , Zhu Hongqin , Tan Chen , Lou Tianyue
Published: June 2019

With the development of the smart grid technology and the advent of the big data, it is highly desired to develop efficient computational methods for mining the values behind of huge volumes of data on the grid. However non-unified naming of the electronic devices from the de-centralized and heterogeneous power systems makes the procedure a hard problem. In the present work, we proposed a Ternary Search Trie based algorithm for recognizing the devices from the huge volumes of transaction data in the power grid. On the base of well-defined professional vocabulary of electronic devices, the algorithm scans and segments records having names of devices using the Ternary Search Trie method. An integrative scoring schema combing semantic and word order similarity is designed to evaluate the segments against the target device names. Experimental results indicate that the proposed method achieves only 3.13% error in parsing stage, and higher recognition rate. Moreover, the algorithm lists top-n matches for professional judgments to make the work more useful and rigorous.
A Spectrum Allocation Algorithm Based on Non-cooperative Game
Authors: Zhang LuYong , Wang Chao
Published: June 2019

Aiming at the problem of spectrum allocation among cognitive users, this paper proposes a spectrum allocation algorithm under non-cooperative game conditions, and presents a non-cooperative game Nash equilibrium algorithm, which can be iterated faster. Under the model and system settings, the improved fireworks algorithm is used to solve the spectrum allocation problem among cognitive users, and the utility function of cognitive users is improved to ensure the fairness of spectrum allocation.
A Node Localization Algorithm in Wireless Sensor Network
Authors: Fang Yanfeng , Zhang Yijiang
Published: June 2019

In order to solve the problems such as complex topology computation and low positioning accuracy induced by the random error factors in the localization process of Wireless Sensor Network(WSN), a new node localization algorithm for WSN is proposed. Firstly, the preliminary position estimation of positioned network node is finished based on the linear parameter evaluation mechanism and evaluates the received anchor node information to calculate the linear parameter value for searching the best anchor triangle, then the precise positioning of the node is done by using the weighted evaluation method and triangle positioning parameters of different anchor nodes to multiple weighted average for obtaining the accurate location information of nodes. Simulation results show that this algorithm has higher localization accuracy and lower error compared with DV-hop algorithm and DV-distance algorithm.
A High-Precision Moving Target Tracking Algorithm Based on UKF
Authors: Yao Ling , Peng Xia , Wang Enliang
Published: June 2019

Since Kalman Filter is not applicable to non-linear systems, a moving target tracking algorithm based on Untracked Kalman Filter (UKF) is proposed. The algorithm performance is analyzed by algorithm principle analysis, building mathematical model of the system, and simulation GUI design. Simulation results show that the algorithm has an expected tracking precision and high reliability in 6-dimensional CA mode, and has a good application prospect.
Research on keyword indexing algorithm based on big data
Authors: Hui Baofeng
Published: June 2019

Keyword retrieval is widely used in various aspects of Web information, such as information processing, data mining, etc. Keyword search has been studied for a long time. Many research results have been obtained from keyword search of early relational database, keyword search of semi-structured data and keyword search of graph data. Given multiple keywords, the goal of keyword retrieval is to find the matching node of keywords and find the most compact data fragment containing all keywords. For traditional retrieval model exists in the retrieval of data redundancy, the disadvantage of fuzzy matching, retrieval information deviation, combined with the current hot, discusses the heterogeneous data integration and redundant data, efficient data classification, keyword retrieval model and the method, such as to big data environment, make full use of the traditional technology combined with spatial retrieval model and other technical storage model, improved classification algorithm, and optimize the retrieval algorithm, thus improve the operation efficiency of the algorithm, to provide users with a set of data storage, classification and retrieval in the integration of large data retrieval platform.
Research on the Model of Lyric Emotion Algorithm
Authors: Xia Xiaoling , Gu Xin , Lu Qinyang
Published: June 2019

With the rapid development of Internet technology, various social networking platforms, especially mobile social networking platforms, continue to increase, resulting in a large amount of public opinion information. Internet public opinion has a clear emotional orientation, and its emotional orientation is very easy to spread and be infected, and even affect the development of the event. Aiming at the characteristics of lyric information rich and which are easy to change with time, the lyric theme analysis model and the lyric emotion evolution model are proposed. The LDA model is used to extract the topic from the lyric text in a period of time, and the sensational heat value is calculated according to the forwarding amount and the number of comments, and the lyrical theme with the highest heat is obtained. The relative entropy between sub-topics in the adjacent time slice of a specific hot topic is calculated, and the degree of association between the topics in the adjacent time slice is determined, thereby analyzing whether there is a split of the sub-topic and a new topic. Then the evaluation object is extracted, combined with the joint deep neural network model to judge the emotions of each evaluation object in different time, and the emotional evolution of the hot topic is analyzed from multiple dimensions. Finally, an example analysis of the network public opinion information from June to July 2018 is carried out to verify the validity of the above model. The model effectively solves the problems of immature emotion analysis model and low accuracy of emotion classification in the current public opinion analysis.
Research on Collision Avoidance Method Based on Image Recognition Technology
Authors: Ma Ziyan , Zhang Yan , Li Huiyuan
Published: June 2019

This paper describes the development of unmanned surface vessel (USV) collision avoidance technology, introduces the basic principles and key technologies of image recognition technology, analyzes the shortcomings of traditional collision avoidance technology, and explains the research status of the image recognition technology in the collision avoidance of unmanned surface vessel. The design ideas of the existing research and development results are summarized. Advantages and disadvantages are analyzed and compared. This paper focuses on the techniques of stereo vision, deep learning, multi-sensor fusion, and the method of unmanned surface vessel collision avoidance based on image recognition technology. The future development trend of this field is also discussed.
Exploration and Research on Computer Aided Translation Technology and English Translation Practice
Authors: Chen Guoping
Published: June 2019

In recent years, the rapid development of science and technology and economic globalization have made the demand for translation more and more in all walks of life. Therefore, computer-aided translation technology has received more and more attention. Combining modern information technology with traditional translation theory, this paper expounds the principle of computer-aided translation technology, and uses the combination of translation memory technology and mixed strategy of statistics and examples to realize computer-assisted translation system. According to the specific English translation practice research, it is proposed to use translation memory technology to optimize translation process, improve translation quality and translation efficiency, and hope to bring work help to the majority of people engaged in English translation, so that their work can be carried out more smoothly.
Color Quantization Application Based on K-Means in Remote Sensing Image Processing
Authors: Cheng Guojian , Wei Junjie
Published: June 2019

In this paper, four kinds of RGB remote sensing images are processed using color quantization algorithm based on K-Means to reduce the number of colors in the image. The color quantization algorithm is to select the most representative color and reduce the useless color in the image as much as possible. This paper assumes that the RGB remote sensing image is composed of multiple pixels. Using the K-Means algorithm to perform unsupervised clustering on these pixels with specific colors, color quantization can be realized. The use of K-Means for color quantization of remote sensing images can reduce the number of colors in those images, so that remote sensing images can be reproduced well in lower performance computer equipment. At the same time, color quantization reduces the size of remote sensing images and improves the efficiency of remote sensing image processing.
Web Service Recommendation Technology Based on Knowledge Graph Representation Learning
Authors: Qiao Xinghao , Cao Zhiying , Zhang Xiuguo
Published: June 2019

This paper proposed a recommendation algorithm based on knowledge graph representation learning (RABKGRL).The algorithm embeds the entities and relationships of the knowledge graph into the low-dimensional vector space. The relationship information of services is incorporated into the recommendation algorithm by calculating the distance between the service entities. The association between services that is not considered when using the collaborative filtering algorithm can be supplemented, and the recommendation effect is enhanced. The experimental results show that this algorithm can not only effectively improve the accuracy rate, recall rate and coverage rate of recommendation, but also solve the cold start problem to some extent.
Research on SAR Image Target Recognition Based on Convolutional Neural Network
Authors: Xinyan Fan , Weigang Zhu
Published: June 2019

A synthetic aperture radar (SAR) automatic target recognition can effectively improve the utilization efficiency of SAR image data. In order to improve the generalization and accuracy of SAR image target recognition, a convolutional neural network model is proposed to be applied to SAR image target recognition. Firstly, the network structure is designed for the characteristics of SAR image. Secondly, the introduction of dense block network structure improves the generalization performance of the model. Finally, Dropout reduced the computational complexity of the network and improved the generalization performance of the model. Experimental data were obtained from the United States Moving and Stationary Target Acquisition and recognition database. Experimental results of 10 types of target recognition showed that the overall recognition rate of the improved convolutional neural network is 99.18%. The convolutional neural network model proposed in this study improves the accuracy and generalization of the network, and is an effective method for target recognition of SAR images.
Method on parametric design technology of spacecraft assembly MGSE
Authors: Zhu Yahong , Li Xiaohuan , Zhang Chengli , Meng Shaohua
Published: June 2019

MGSE [1] (Mechanical Ground Support Equipment) is necessary equipment for spacecraft research and development. The traditional MGSE design method requires repeated modeling, analysis and drawing, so the traditional design method is inefficient for the design of stereotyped MGSE. This paper introduces a new parameter-based fast design MGSE method. This method extracts the key parameters to drive the establishment of the model. Parametric analysis can be carried out in the system. Compared with traditional design methods, the efficiency can be at least double.
Predicting the structural, electronic and mechanical properties of three-dimensional boron nitride foam containing sp, sp2 and sp3 hybridized bonds
Authors: Zheng Haibin , Bu Hongxia , Sun Lili
Published: June 2019

A first-principles approach is utilized to systematically investigate the structural, electronic and mechanical properties from a new BN phase (denoted super-(BN)16). Super-(BN)16 contains sp, sp

2
and sp

3
hybridized bonds. It is mechanically stable, even though it is energetically unfavorable than c-BN, w-BN, yne-BN, and so on. Due to the different hybridization type and the B-N covalent bonds with ionic characteristics, super-(BN)16 has unequal bonds and bond angles in these equal space positions. The calculated electronic structure showed it is a semiconductor with a direct band gap of 1.94 eV. The electronic states in the region near Fermi level mainly come from the 2p orbitals of the sp hybridized B and N atoms. The elastic constants and moduli of this phase exhibit clear anisotropy and super-(BN)16 should have a low hardness and high ductility. Additionally, it can be obtained from nanosheets, nanotubes and nanoribbons of yne-BN family under pressure.
Error compensation method of large size steel sheet measurement based on control field
Authors: Geng Lei , Yao Fucai , Wang Wen , Xi Jiangtao , Li Yaru
Published: June 2019

Aiming at the problem of low accuracy of large size sheet edge, a method of sheet size error measurement based on control field is proposed. Firstly, an error compensation model of the measuring system based on control field is established by analyzing the causes of the errors of the measuring system. A grid standard plate is designed and the error distribution on the grid line is obtained by using the measurement results of the standard plate. Secondly, the error curve is established according to the distribution, and the trig function theorem is used to project the curve into the image pixel coordinate system. Finally, the control field of the whole measurement area is reconstructed by linear interpolation, and the measurement results are compensated and corrected. The steel sheet is measured in the measuring area of 1.2m × 2.6m on the basis of these theories and technologies. The experiment shows that the precision of the measuring system can reach 1mm per meter, which satisfies the accuracy and speed requirements of large-size steel sheet measurement in industry, and has high application value.
The application and research of cloud platform in practice teaching integrated service
Authors: Ai Ting , Zhang Qiaoling
Published: June 2019

The paper introduces the characteristics of cloud desktop and cloud desktop system composition structure, including hardware structure and software structure, it can be done from cloud desktop functionality in the application of computer network laboratory is put forward.
Error Analysis of High-time-resolution Na Lidar Data and Power Spectrum Density of Mesospheric Na Layer
Authors: Wang Xiaodong , Yi Fan
Published: June 2019

The observed 6-s Na layer data at Beijing (40.2°N, 116°E), China was conducted error analysis and compared with 5-minute Na Lidar data located at Wuhan (30.5° N, 114.4° E), china. It was found that 6-s time resolution fluctuations/change rates of Na atomic density were geophysical phenomenon rather than measurement error. The relative measurement errors between Beijing and Wuhan are comparable around 90 km. Based on the long-duration (longer than 10 hours in an observational night) 6-s Na profiles, power spectral density (PSD) of the Na density fluctuations has been calculated. There exist strong fluctuations at frequencies larger than the typical value (2.5×10-3 Hz, equivalent to a period of ∼5 min) of the Brunt-Väisälä frequency in the mesopause region.
Application of Virtual Reality Technology in College Physical Education Teaching and Training
Authors: Liu Hao
Published: June 2019

With the continuous development of social science and technology, the application range of computers is wider and wider. The computer “virtual reality” technology is used in college sports training, which can enrich the content of physical education classrooms, update classroom teaching methods, and improve the quality and efficiency of physical education training. However, in the process of actual application, there are still some problems to be solved.
Topology-Aware Software Assignment in Networked Systems
Authors: Wang Junchao , Liu Hao , Liu Zhenwu , Zhang Zheng , Pang Jianmin
Published: June 2019

Cyberspace mimic defense has been proven to be a revolutionary defense technology that “changes the rules of the game” to ensure the security of cyberspace. However, the software diversity inherent in mimic defense technology may increase the difficulty in managing software executable binaries, especially when updating or debugging a software. In this paper, we study the problem of software assignment in a networked system to minimise the number of binaries generated by mimic compilers. Mimic compilers can help to generate functional equivelant software executables which exhibits diverse characteristics such as binary size etc. Theoretically the software assignment problem is equal to the traditional graph coloring problem. To guarantee network severity, we apply a Welsh-Powell-based Software Assignment (WPSA) algorithm to determine the number of binaries needed and the assignment of these binaries to hosts in a network. We conduct experiments on real world network topologies. Experimental results show that our algorithm can effectively reduce the number of binaries needed in networked systems.
Automatic Segmentation and Reconstruction of Coronary Arteries Based on Sphere Model and Hessian Matrix using CCTA Images
Authors: Zhao Jie , Gong Wenke , Jiang Shizhong , Huang Zhanpeng , Qin Jiangwei , Tu Yongqiu , Zhou Sujuan , Ou Shanxing
Published: June 2019

Cardiovascular disease (CVD) is the most common cause of death in the world. Accurate coronary arteries segmentation is the basis for heart disease diagnose. But in coronary computed tomography angiography(CCTA) images, the complex structure of coronary vessels and the low contrast of thin vessels cause difficulty in coronary arteries segmentation. In this paper, an automatic segmentation algorithm is proposed to extract vessels from CCTA. Firstly, the hessian matrix is used to enhance vessels in CCTA images, and then, the moving sphere model we proposed is used to extract centerline of coronary arteries. Experimental results showed that the proposed model provides good-quality segmentation.
The Precise Positioning Algorithm Optimization Base on PSO-PF for Agricultural Machinery Navigation System
Authors: Yan Zhang , Jingtao Hu
Published: June 2019

A Modified Weight Particle Swarm Optimization-Particle Filter is proposed for the integrated navigation nonlinear system in agricultural machinery operation. The algorithm combines the advantages of particle filter and the global and local searching ability of particle swarm optimization, which modifies the particle weight and accelerates the particle convergence on optimizing particle update mode by adding advantage and disadvantage. It reduces the probability of falling into local optimum, and the global accurate positioning is achieved in a short time. The feasibility and superiority of modified weight particle swarm optimization particle filter are verified by simulation and experiment.