bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Management of Digital Library Based on Information Platform
Authors: Wang Qingjie , Chen Xuegang , Duan Sheng , Wang Luda , Fan Hongbin
Published: July 2020

How to improve efficiency and service level of digital library by means of computer technology is becoming an urgent problem in higher education. In this context, this paper is developed a new set of digital library management information system. This paper is studied structure of digital library, and we use case modeling to analysis Web platform module, database module, further build the overall system architecture, design main database table. In the process of implementation, database connection is configured, and we do a lot of tests for Web system platform module and reader-discuss-community module. Since the system is online, the website has maintained a good number of visits, and is welcomed by many teachers and students.
The Design and Development of Student Electronic Homework Management System
Authors: Cheng Yun , Liang Fenglin , Wang Yanli , Liang Xiumei , Chen Xue , Tian Yuanyuan
Published: July 2020

With the continuous development of information technology, computers and networks have been deeply integrated into the basic process of teaching and learning. In order to solve the basic problems of the traditional homework management mode, on the basis of demand analysis, this paper designs and develops a student electronic homework management system, which provides teachers and students with a convenient and efficient electronic homework online management platform. The system adopts a three-tier architecture system of B/S mode, with clear navigation, convenient use, high operating efficiency, and strong security. It implements user management, course management, job management, announcement management, link management, communication management, system management, etc. The function has solved the collection, management, review, communication and other problems of students’ electronic homework, and can effectively improve the efficiency of electronic homework management in the teaching and learning process.
Prediction of Fire Spread Based on Geographical Cellular Automata
Authors: Li Juan , Zhang Xiaohua , Li Yunfeng , Yao Liqiang
Published: July 2020

China is a country with frequent forest fires. Forest fires not only damage the forest ecosystem, cause the loss of forest resources, but also threaten the safety of people’s lives and property. If the spread trend of forest fire can be predicted quickly and accurately after the fire, it will be of great significance and role to put out the fire and reduce the loss and casualties. In this study, based on the in-depth comparison of domestic and foreign commonly used forest fire spread models and related algorithms, the geographic cellular automata is selected as the diffusion algorithm, combined with the revised Wang Zhengfei fire spread model, and the host development method is adopted to achieve the forest fire spread prediction. Through the comparative analysis of the prediction results in the actual cases, the error is within the acceptable range, achieving the expected effect, meeting the requirements of real-time and efficient simulation of forest fire spread, and providing reliable decision support for the management.
Analysis of Privilege Escalation Based on Hierarchical RBAC Model
Authors: Ma Li , Yan Yongjie , Jiang Huowen , Zhou Yanjie
Published: July 2020

As access control policies become more and more complex, the detection of access control vulnerabilities becomes more important. Previous research efforts have concentrated on access control vulnerabilities due to programming errors, while the privilege escalation caused by logic errors or abuse of privileges has seldom attracted researchers’ attention, which is also a kind of access control vulnerabilities. To investigate the property of privilege escalation, hierarchical RBAC model is used to describe complex relations between different roles that are represented by a directed role graph. Permissions are divided into multiple categories according to the inheritance of permissions in the role hierarchy. Three types of vulnerabilities, Upward Privilege Escalation, Downward Privilege Escalation and Horizonal Privilege Escalation, are defined and decided theorically based on the inheritance relations between roles in a role graph. Besides the three type, another type of privilege escalation that is not related to the hierarchy of roles is also studied. Finally, the decision theorems of three vulnerabilities are used to optimize the access control decision algorithm.
Research and Implementation of Network Public Opinion Rrediction System
Authors: Chen Xuegang , Gao Shouping , Duan Sheng , Wang Luda
Published: July 2020

The Internet has become a distribution center of ideological and cultural information and an amplifier of public opinion. To dig, analyze and study hot public opinions on the Internet is an important means to fully understand what netizens are thinking and doing. This paper analyzes the function of public opinion system, and introduces the key technology to realize the prediction of network public opinion, which can well realize the prediction function of public opinion.
Exploiting Gabor Feature Extraction Method for Chinese Character Writing Quality Evaluation
Authors: Wang Zhixiao , Yan Wenyao , Guo Mingtao , Zhang Jiulong
Published: July 2020

The automatic evaluation of Chinese character writing quality has a wide application prospect. Most of the existing evaluation methods of Chinese character writing quality are based on radical segmentation and feature judgment, which require the high accuracy of Chinese character segmentation. However, there are many problems in the real handwriting, such as continuous writing, uneven strength of writing, personalized writing style and so on, which lead to the difficulty of segmentation in the ordinary handwriting. To solve the above problems, we propose an effective method based on image texture where the uniformity of writing lines and writing style is taken as an effective criterion. In our method, Gabor transform is used to extract the image features of writing samples, and finally the statistical learning method of support vector machine is used to effectively evaluate the writing quality. Experiments on multiple real datasets including CHAED show that our method is effective and accurate. The advantage of this method is that it does not need to segment fonts, and the cost of global feature extraction is small.
Channel Allocation Scheme for Wireless Sensor Networks Based on Graphical Topology Information
Authors: Li Zhengping , Wei Qimin , Chen Hong
Published: July 2020

Wireless sensor network (WSN) is a distributed sensor network. The main research direction of wireless sensor network is the distribution method of its channel. With the development of information technology, the contradiction that between scarce wireless resources and high-density AP points will adversely affect people’s daily life. In this paper, we design a heuristic algorithm based on the channel assignment method by comparing the similarity of the network graphic topology. By calculating the pre-allocation scheme, the optimal throughput of the new topology is compared with the optimal throughput of the genetic algorithm to verify the superiority in the new algorithm. The network model is constructed by three graphical methods: scatter plot, density map and thermal graph. Finally determine the heat map-based channel allocation algorithm as the optimal solution.
Research and Application on Microservices Architecture in Civil Affairs Informatization
Authors: Tao Liang , Fan Yida , Zhang Tong , Zhao Chao , Yang Tianrong
Published: July 2020

With the development of information technology, microservices have been applied to more and more industries. Firstly, we introduce microservices and microservices architecture, analyse the main problem of civil affairs informatization, and explain the composition of microservices architecture. Secondly, we give the key technology of microservices which include abstract methods of microservices, microservices process management and the schedule of microservices workflow. Finally, we talk about the situation of civil affairs applications for using microservices architecture and give the conclusion.
Performance Analysis of Intelligent Reflecting Surface in Multi-user MIMO Systems
Authors: Liu Shaobo , Xiao Limin , Zhao Ming , Xu Xibin , Li Yunzhou
Published: July 2020

Intelligent Reflecting Surface (IRS) is a revolutionary technology which is able to improve the performance of wireless data transmission system. Specially, large numbers of small reflecting unit are jointly adjusted to reconfigure the wireless signal transmitting environment. In this paper, we study the use of IRS in a multi-user MIMO system where IRS is deployed to assist the data transmission in both uplink and downlink phases. We first present an overview of the technology of intelligent surfaces, including its fundamental principles and practical applications. Then we derive the signal model of IRS aided multi-user MIMO system and provide data transmission schemes. Finally, numerical results are demonstrated to show the superb signal enhancement with the use of intelligent surfaces in wireless system.
Single Image De-raining Based on a Novel Enhanced Attentive Generative Adversarial Network
Authors: Zhou Haochen , Wei Qin
Published: July 2020

With rapid development of deep learning in artificial intelligence and computer vision, generative adversarial network plays an important role in single image de-raining. Attentive generative adversarial network (AttGAN) has problems about complicated network structure and distortion of background color. Considering the relative complex background in the real image with raindrops, a new single image de-raining algorithm based on enhanced attentive generative adversarial network (EAttGAN) is proposed to retain the original background of the blurred image. In order to restore more complete background and accelerate network training, a generator enhanced by residual scaling and a Markovian discriminator are fused effectively in the network. Compared with AttGAN, experimental results indicate that EAttGAN can not only achieve higher sharpness of a single image, but also take less time in the training process.
Research and Implementation of Time Synchronization Mechanism in Simulation Architecture
Authors: Wang Kunfu , Mao Wanfeng , Feng Wei
Published: July 2020

Modern warfare is changing from independent mode to cooperative mode, and time synchronization is the basis of cooperative operation. In this paper, the NTP based time service system (st simulation system) is designed and developed under the environment of windows QT 4.8.5 with the object-oriented thinking of C + +, the time synchronization mechanism in simulation architecture is described, including the design of time synchronization algorithm of ST simulation system and the design of time service flow between ST simulation system and other simulation nodes in the architecture, it can effectively improve the time accuracy and accuracy in the simulation architecture.
A Device Data EvaluationSystemBased on Hierarchical Weighting Algorithm
Authors: Gu Yeqing , Yang Jian , Wang Zhiyuan
Published: July 2020

The more applications are supported by a dccloud, the higher quality are required on the fundamental data. This paper developed an evaluation system based on hierarchical weighting decision-making to evaluate the data quality of devices on dccloud. This evaluation system could also evaluate the satisfaction of applications on various devices, and the overall relationship among devices to improve data quality of device models.
RETRACTED: Research on Informatization Development of Minshuku in the Background of Big Data Era
Authors: Wu Yinghui
Published: July 2020

With the popularization of intelligent mobile devices and the rise of tourism Internet platforms, tourism consumer behavior also shows strong information characteristics. The booming tourism industry has entered the era of big data. Under the trend of tourism big data, minshuku has become a noticeable growth point. This paper analyzes the characteristics of minshuku informatization under the background of big data era and the current situation of minshuku informatization development, and puts forward some countermeasures such as building big data, informatization system, efficiently utilizing multiple tourism Internet platforms, and combining big data analysis on the basis of the two, creating minshuku characteristic brands, etc. Fully mining big data can provide more comprehensive and accurate decision support for the future development of minshuku.
Research on Automatic Programming of Cross Stitch Equipment Based on Machine Vision Technology
Authors: Guo Dalu , Liu Feng , Zhou Quan , Hou Xujie
Published: July 2020

In the past, cross-stitch was mainly mainly by manual embroidery. It has a large workload, long time-consuming and easy to make mistakes. With the development of artificial intelligence and image recognition in recent years, the application scene is very wide.
Network Layer Security Detection Model of Internet of Things Based on Immune System
Authors: Yang Bo
Published: July 2020

The traditional network security detection model use attack samples of known types to train the security detection model offline. Although it has a high detection rate for the known attack types, it cannot identify the new attack types on the network layer. At present, detection system has disadvantages of slow speed of system construction and high cost of model update. Facing increasingly expanding network and endless attacks, the detection system lacks self-adaptability and expansibility. In this paper, the integrated use of immunology theory and complex adaptive system theory and computational experiment technology, based on Internet network layer security detection model of the immune system, existing Internet network layer security, the new type of attack occurred in the process of on-line detection of immune learning, realize the dynamic extension of network security detection model, and through calculating experiment and example analysis verify the scientific nature and feasibility of the model.
Research on Intelligent Identification of Ore Minerals Based on CART Algorithm
Authors: Shen Ying , Zhao Yongyi
Published: July 2020

The identification of ores and minerals is essential in geology, and the use of data mining to identify and classify ores in the era of widespread use of big data will help its development more effectively. This article takes the pyrite simulation data as an example and based on the ore mineral color, hardness, relative density, and electrical conductivity as the characteristic values. It is built in the CHDC model to use the CART algorithm to classify and identify the pyrite ore. After a lot of training on the data, the recognition model tends to be stable. The probability of correct discrimination in the CHDC model based on the CART algorithm’s confusion matrix is 93.8%. However, due to the complex composition of ore minerals, the component analysis cannot be performed in a short time, so the component characteristic value is not taken. The ore returned by the sensor is different in color under different light sources, which affects the accuracy of judgment. Using the CART algorithm in the CHDC model can judge the identification of the ore, thereby completing the intelligent identification of the ore mineral.
Efficient Dense Spatial Pyramid Network for Lane Detection
Authors: Li Yinggang , Lu Xiaobo
Published: July 2020

Lane detection separating the roads and positioning each lane is a significant task in Autonomous-driving field. Most of existing methods take lane detection as a semantic segmentation problem, and the methods based on encoder-decoder networks achieve robust performances than traditional methods with the disadvantages of large amounts of parameters and high computational cost. To improve efficiency and better adapt to adverse environments, we propose an EDSPnet by compiling the efficient dense module of depthwise dilated separable convolution (EDD module) and dense spatial pyramid (DSP) module. The two proposed modules enable our network to make full use of the contextual information from different feature maps when compared to a chain of layers. Different from symmetrical segmentation networks, we concentrate on the encoder block and a simple decoder is designed to match the input resolution. The decoder is complemented by two methods of upsampling: bilinear interpolation and deconvolution, which guarantee the accuracy and efficiency simultaneously. Our method is evaluated on the TuSimple dataset, and the experimental results show that our network has less parameters and is still efficient even compared with the state-of-the-art semantic segmentation networks.
A New Text Sentiment Analysis Method Based on Chinese Morphological Features and HowNet
Authors: Cheng Yan , Liu Chunjia , Li Yunhong , Zhong Linhui , Feng Yue
Published: July 2020

Traditional deep learning methods have two problems when using vectorized words as input. One is that they only consider the overall semantic information of the vocabulary, but ignore the morphological features of the Chinese vocabulary and the prior knowledge of the Chinese external knowledge base. Second, the word vector corresponding to each word will be limited to a single word vector training model. Aiming at these problems, we propose a double-channel convolutional neural network model based on Chinese morphological features and HowNet. First, the cw2vec model and the SAT model (Sememe Attention over Target Model) are used to train the word vectors. Second, the two different word vectors are used as the input of the two channels of the model. Finally, the convolutional neural network are used to extract the characteristics of the two channels to complete the sentiment analysis task. The comparative experimental results on the two data sets show that the proposed model achieves significantly better classification performance than traditional sentiment analysis methods.
New Decoupled 2-Dof Parallel Mechanism with Fully Spherical Workspace
Authors: Yu Shanshan , Zhang Jianjun , Li Weimin , Yang Xianhai
Published: July 2020

Decoupled 2-dof spherical parallel mechanism is an important valued spherical parallel mechanism. It is one of the preferred solutions in the field of large-angle spherical workspaces. By studying the configuration of the exiting kinematic decoupled spherical parallel mechanism, it is found that the key issues that it cannot achieve a fully spherical workspace is that the output angle range of the “linear input – rotation output” kinematic chain cannot reach 180°. Based on the input and output characteristics of the double rocker mechanism, two new ideas for constructing the configuration of the “linear input – rotation output” kinematic chain are presented. The output angle range of the new “linear input – rotation output” kinematic chain can reach 180°. Based on the new design idea for “linear input – rotation output” kinematic chain, two new kinematic chains are designed: P5R and PRR. Based on the above kinematic chains, two 2-dof decoupled parallel mechanism with a fully spherical workspace are designed, i.e. RR&P5R parallel mechanism and RR&PRR parallel mechanism.
The Fog Computing Attemper Layer Model Based on Agent Role
Authors: Wu Chenhan , Chen Wei , Chen Xiong
Published: July 2020

In this paper, a new role task scheduling method based on behavior flow is proposed for fog computing system. Because the traditional computing has changed from data oriented to edge oriented and distributed computing, the task scheduling method combines the role collaboration behavior and role Organization definition behavior in resource nodes by establishing the role behavior flow system, and establishes the role behavior flow mode from the center to the edge, so that the computing nodes can advance according to the behavior roles of their respective nodes Line classification processing. Therefore, it can effectively solve the problems of slow service response, high power consumption and frequent task interruption caused by large amount of data and redundant operations in traditional cloud computing systems.
Optimization Simulation Technology of Cement Packaging System Based On YL-235A Equipment
Authors: Zhou Quan , Wang Liqing , Liu Kai
Published: July 2020

Cement packaging is an important part of cement production and sales. This research is based on the automatic control of the cement packaging system, using the YL-235A automatic production line equipment to optimization and simulation the automatic control system of the process flow of cement packaging. The simulation study of cement packaging production line of a cement factory was carried out. Achieve the goal of optimizing production control, solving technical problems, improving equipment efficiency and continuously improving production capacity. The application of equipment simulation can greatly shorten the development cycle of the cement packaging control system, find problems in operation, save running cost. In order to solve some technical problems existing in the cement packaging control, an effective approach is provided.
A UWB-Based Low-Cost and Precise Localization Method for Mobile Robots
Authors: Shi Dongqing , Mi Haiyan
Published: July 2020

The need for automating cargo management in a manufacture environment is urgent. Recent advance in big data and artificial intelligence areas has made it possible. As we known, most cargoes are transported using autonomously guided vehicles or manpower. Many autonomously guided vehicles follow paths that are predefined and usually marked by labels that can be easily found by vehicles. The use of predefined path for vehicle navigation greatly limits the deployment of autonomously guided vehicles. A few vehicles use high accuracy Light Laser Detection and Ranging for sensing and guidance. In this paper, a low-cost and precise method for mobile robots has been developed. Considering the high nonlinearity of UWB ranging data, a least square method is used to find optimal locations and a gradient decent approach is applied for fast convergence to the optimal results. The proposed method is also able to diagnose the ultra-wide band data and will throw away any data corrupted by noise. Therefore, the robustness is obtained.
Cultivation of Solving Problems with Computing Thinking
Authors: Hu Yahui , Xiao Lei , He Ling , Fang Qiqing
Published: July 2020

Aiming to solve many people do not know how to use computers to solve practical problems in life and work, we design a series of detailed steps to analyze, design, represent, program and verify with computing thinking. We demonstrate our steps in detail with an example to help them which will encounter similar problems in the future.
Research on Optimal Shift Control Strategy of Two-speed AMT based on Fuzzy Control
Authors: Ma Ning , Hou Benjiang , Wang Yexuan , Ren Kai , Chen Shaoxin , Wang Peng , Lin Rongfeng , Ji Jianyi , Ji Yichun , Han Zhendong , Yang Chaohui , Wang Lingmin , Yu Nan
Published: July 2020

For a two-speed AMT pure electric commercial vehicle, the pros and cons of the shift control strategy directly determine the overall vehicle performance of the electric vehicle, such as power and economy. This article takes a certain type of commercial pure electric vehicle equipped with a two-speed automatic transmission as the research object, formulates a dynamic shift rule based on the torque map of the motor, structures an economic shift rule based on the efficiency map, and identifies road gradient and Car load quality, comprehensive consideration of the car’s loading quality, road slope, accelerator pedal opening, accelerator pedal opening change rate, vehicle speed and other parameters for optimal shift control strategy formulation. Comparing the dynamic shift strategy with the economic shift strategy, simulation analysis results show that the optimized shift control strategy can meet the requirements of dynamic performance and has the advantages of economy and energy saving.
Optimizing AGV Calculation MAP Path of Waste Smoke Recovery
Authors: Chen Haitao , Shu Meng , Lin Yizhen , Sun Shunkai , Shen Xue , Chen Ming , Hu Wangdi , Jiang Junjie
Published: July 2020

With the emergence of Industry 4.0, Technological reform and technological model innovation will surely be launched in the industrial manufacturing industry. Based on the intelligent development direction explained by Industry 4.0 and the current status of the tobacco industry logistics, AGV for waste smoke recycling is proposed Example map route optimization topic. In the complex operation and maintenance environment of the tobacco industry, unmanned transportation technology is used to automatically recover the residual cigarettes in the wrapping workshop, replacing the traditional manual forklift recycling model. Focusing on the auxiliary production of intelligent production, with the automatic recycling of residual cigarettes as the core, we will further optimize and perfect the intelligent recovery or supply of production waste and other raw and auxiliary materials.
Semantic Segmentation of Remote Sensing Images Based on Multi-Model Fusion
Authors: Miao Zuohua , Liu Likun , Ren Lei , Tang Yang , Chen Yong , Li Jun
Published: July 2020

Convolutional neural networks have created a new field in the research of semantic segmentation of remote sensing images. However, different network structures have different effects on the semantic segmentation of different land types. In this paper, the original data set is expanded, and an improved U-Net model is used to train a model for each type of feature target. Then combined with conditional random field (CRF) and image overlapping strategy for optimization processing; Finally, the two binary classification models obtained by training are fused to obtain multi-classified semantic segmentation images. Solve the obvious problem of large-scale remote sensing image edge stitching. The experimental results show that this method has higher accuracy in solving the segmentation of large-scale remote sensing images.
A Panoramic View System of Guilin Tourism Based on Interactive Projection Technology
Authors: Yu Ke , Shi Zhuo , Feng Ye , Shen Tianlong , Huang Zhixiong , Gu Yinwei , Deng Yingzhuo , Liang Yushi
Published: July 2020

This paper introduces a panoramic view system of Guilin Tourism based on virtual reality and infrared image tracking. Users interact with images on the ground through body movements, the system can achieve unattended, interactive guided, automatic voice interpretation function, with virtualization, high efficiency, easy maintenance, good interactive experience and so on. Suitable for placing in exhibition venues, scenic spots exhibition hall and so on, so that tourists can enjoy Guilin landscape without leaving home.
Atrial Fibrillation Prediction Algorithm Based on Attention Model
Authors: Shen Mengting , Zhang Luqiao , Luo Xue , Xu Jing
Published: July 2020

Atrial Fibrillation is a common arrhythmia. when the heart is in the state of atrial fibrillation, can not deliver enough oxygen rich blood to the body. It may be asymptomatic when AF occurs. The patient does not know that AF has occurred. If the patient is not treated in time, the consequences of AF may be fatal. The diagnosis of AF needs a doctor with rich clinical experience, because the ECG signal of AF type is similar to that of other types of heart rate, which is difficult to confirm. The purpose of this paper is to train a better model through machine learning method, to realize the automatic detection of long-term AF ECG signal, to predict AF in advance, to automatically classify, recognize and inform patients. In this way, even if the patient himself can know the physical condition in time, early treatment. Automatic prediction and diagnosis of AF by machine learning method can play a positive role in the treatment of AF, but the existing scheme is not ideal for the detection and recognition rate of AF type. This paper proposes a deep learning framework based on attention mechanism. The segmented data are sequentially input into the deep convolution neural network for feature extraction, and then input into the two-way recurrent neural network with attention layer to predict the AF signal. The accuracy of 99.1% in the existing data set is better than the existing deep learning classification algorithm, which proves the validity and feasibility of the model.
Metrological Research on the Application Literature of AI Education in China: 2009-2019
Authors: Cheng Yun , Zhang Man , Wang Yanli , Liang Fenglin , Wang Feng
Published: July 2020

Based on the CSSCI (Chinese Social Sciences Citation Index) full-text database of CNKI, this paper selects 468 journal articles on the application of AI in education from 2009 to the present. Based on the measurement visualization software CiteSpace, the data mining and content analysis are carried out, and the in-depth analysis is carried out from six aspects: the overall trend, core authors, research institutions and fund distribution, research hotspot, evolution trend and research clustering, etc. It also shows the research situation in the field of AI education application in recent ten years by means of tables and visual knowledge maps, which can provide important reference for researchers in this field.
Study in Network Stability based on MC
Authors: Fan Hongbin , Deng Gehong
Published: July 2020

Monte Carlo is a convenient method for statistics sampling theory of mathematical and physical. It is widely applied to the field of staff performance in geological, electric, medical, optical, water conservancy and so on. In order to effectively assess the stability and reliability of the network, this paper put forward an improved Monte Carlo evaluation method on the basis of the traditional Monte Carlo method. First of all, the paper elaborated the principle of improved Monte Carlo method and the specific method of how to calculate the stability of the network. The improved Monte Carlo method employed the recursive variance reduction method to get a smaller sample in the original sample, to ensure the estimate is unbiased. Secondly, the paper applied the ideology of permutation and combination to the network nodes and links in the model, and combined with the upper and lower boundary of network performance, to calculate the connected stability. Finally, the paper carried out experiments between the improved and traditional Monte Carlo method in Matlab simulation to contrast and analyze. The results show that the improved Monte Carlo method to evaluate the stability of the network has higher accuracy and smaller variance. So the experiment proved that it has the high feasibility and validity.
A Hybrid GCN and RNN Structure Based on Attention Mechanism for Text Classification
Authors: Gao Lingchao , Wang Jiakai , Pi Zhixian , Zhang Huaixun , Yang Xiao , Huang Peizhuo , Sun Jiasong
Published: July 2020

In the field of deep learning, for problems and tasks that are sensitive to time series, such as natural language processing or speech recognition, the recurrent neural network is usually more suitable. Long short-term memory (LSTM) is a representative network structure in recurrent neural network. It is time-dependent and enables a global representation of features. However, some problems such as the network parameters of LSTMs limit the applicability of their solutions. This paper proposes an improved hybrid structure of graph convolutional neural network and recurrent neural network. In the input layer, a two-dimensional convolutional neural network is used to build a text corpus map. Graphic embedding is used to preserve the global structure of the entire text graph structures. The LSTM layer and attention mechanism are used to fully implement text classification and improve the computational efficiency. The test results show that the hybrid network structure has better operation speed on the IMDb dataset.
Research on User Behavior with Collaborative Recommendation Based on Social Network
Authors: Wang Hongxia
Published: July 2020

With the rise of social networks and the existence of a large number of active users, a large number of data recording daily life are constantly generated. This kind of data has the characteristics of interactivity, real-time and sociality, which implies a lot of valuable information. Therefore, social network data has a very positive role in promoting the construction of smart city. In this paper, users’ annotation information of the item in social network is used. Similarity model is established with appropriate similarity calculation method. Users’ social relationship in social network is used to establish trust relationship and model for users. Personalized recommendation algorithm is improved to dig user behavior data, analyze users’ interests and hobbies. Information of interest or item can be recommended to meet the needs of users to the maximum extent. And the stickiness of users to the website is increased. Based on the widely used recommendation algorithm, this paper analyzes the user behavior with trust-based collaborative recommendation algorithm based on user relationship of social network.
A Robot Self-Positioning System based on Robust EKF Using Degree of Confidence
Authors: Shi Hui , Tan Yingzi
Published: July 2020

Self-positioning system is the key link of humanoid soccer robot, in which the robot needs to estimate its position and direction in the football field based on non-probing sensors. However, the modeling error of the robot system and the deviation of information acquisition bring the uncertain noise to the self-positioning system, which makes it difficult to carry out effective real-time positioning by using the traditional methods such as geometric measurement and track prediction. Existing filtering methods such as Kalman Filter and Monte Carlo Filter estimate the position and direction of the robot through observations, reducing the influence of uncertain factors. Although the accuracy of positioning is improved, the state estimation method relies on the accuracy of observations. The deviation in blurred image processing and camera ranging during the motion of the robot results in the deviation of the observations, which is more obvious in the case of multi-target observations. In this paper, a self-positioning method based on robust EKF using confidence is proposed to improve the accuracy of the robot’s self-positioning by integrating observations.
Classification Method of Ethnic Minority Patterns Based on Faster R-CNN
Authors: Kong Qian , Shi Zhuo , Feng Ye , Yang Ming , Zhang Mengxue , Zeng Shuzhen , Li Rongbin , Yu Ke , Shen Jing
Published: July 2020

The pattern on the costumes and brocades of ethnic minorities are of profound significance, but they are various and often composed of many kinds of patterns. It is not accurate and time-consuming to classify them only by artificial methods. Taking Yao’s pattern symbols as an example, this paper collects and arranges the pattern pictures on clothing and brocade, preprocesses the pictures and labels the patterns on the processed pictures according to the preliminary classification. After the data set is made, the data set is trained and tested by Faster R-CNN algorithm. The results show that this method can effectively identify and classify the patterns of Yao nationality while reducing the time-consuming, and the average accuracy can reach 88.71%. It provides a useful exploration to help more ethnic minorities realize the intelligent classification of patterns.
Research on the Focused Crawler of Mineral Intelligence Service Based on Semantic Similarity
Authors: Deng Shiqi
Published: July 2020

Large-scale general search engines have been unable to meet the needs of “specialized, sophisticated and deep” information in the field of mineral intelligence services. Vertical search engines have emerged at the historic moment, and the focused crawler is the key technology to achieve vertical search engines. This paper proposes a hybrid topic strategy based on text content and web link structure for the characteristics of mineral information field. In order to improve the topic relevance determination ability of the focused crawler, this article introduces HowNet and the word embedding technology in the field of natural language processing, and combines them to carry out the text-based topic relevance determination; at the same time, it also introduces the HITS algorithm based on the link structure of web pages. The topic strategy based on text content is organically combined with the topic strategy based on the webpage link structure to realize the recognition and prediction of the webpage topic. Simulation experiment results show that the method proposed in this paper can achieve a high recall rate and precision rate for the acquisition of mineral intelligence information on the Internet.
Trajectory Planning of Multi-arm Robot for Mandible Reconstruction Surgery
Authors: Zhao Honghua , Gong Xuyin , Sun Dianmin , Zhao Jian , Lin Yifei
Published: July 2020

The task of the surgical robot for jaw reconstruction is to complete the accurate and stable lifting and positioning of the restoration implant, and the continuous trajectory of its space is not high. Therefore, joint space is used for trajectory planning. The task of mandible reconstruction robot is to set the constraint of trajectory function at the beginning and the end. There is no mandatory requirement for the middle path. Therefore, the PTP (point to point) method with middle point is chosen. The middle point needed by PTP is far less than CP (continuous path), and it does not need frequent interpolation. The calculation avoids the singular position on the continuous trajectory, improves the safety and real-time of the robot control, and the reasonable selection of the middle point is also conducive to the realization of collision avoidance between the arms.
Design and Research of Intelligent All-area-advancing Tourism Cloud Platform in the Era of Big Data
Authors: Lin Qian , Wei Wei
Published: July 2020

In the era of big data, it is one of the important ways to make intelligent all-area-advancing tourism by informatization. This paper, through big data, cloud computing, mobile, Internet and other information technologies, combined with the practical application of tourism information in Shandong Province, puts forward the construction content of intelligent all-area-advancing tourism cloud platform, and designs the overall framework, system structure and database system of the platform, which is of great significance to integrate the tourism resources of the whole province to build an information resource sharing system of intelligent all-area-advancing tourism that integrating intelligent tourism management, intelligent tourist service and intelligent tourism marketing.
Fault Diagnosis Method of Analog Circuit Based on Radial Base Function Neural Network
Authors: Gebregiorgis Meron , He Yigang , Ning Shuguang , Wang Shi
Published: July 2020

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

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

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

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

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

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

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

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

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