bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling Uncertainties of Wind Field Reconstruction Using Lidar
Authors: Schlipf David , Koch Martin , Raach Steffen 
Published: March 2020

AbstractThe use of nacelle-based lidar systems for power performance testing of wind turbines is promising. Here, the knowledge of uncertainties is crucial. Wind field reconstruction is necessary to estimate wind field characteristics such as horizontal wind speed and wind direction from line-of-sight wind speed measurements using a wind flow model. In this work, two types of uncertainties in this process are investigated and confirmed in simulation: the uncertainty caused by measurement errors and by modeling errors. Based on this first investigation, the modeling uncertainty is exceeding the measurement uncertainty.
Multicast Routing Algorithms Based on Levy Flying Particle Swarm Optimization
Authors: Zhi Chun , Cui jianming , Zhu liangshuai 
Published: March 2020

Abstract
Aiming at the problems of bandwidth, network delay and cost in IPv6 multicast routing transmission, a particle swarm optimization multicast routing algorithm (LPSO) based on Levy flight mechanism is proposed to find the optimal path in the multicast tree. In the iteration process, the cost, bandwidth, delay and delay jitter of multicast tree are taken as indexes, and penalty function is combined to constrain the algorithm. Compared with existing multicast routing algorithms, this algorithm improves the global search and meets the requirements of QoS in multicast routing.
Improvement of Text Segmentation TextTiling Algorithm
Authors: He Xin , Wang Jian , Zhang Quan , Ju Xiaoming 
Published: March 2020

Abstract
Text segmentation has a wide range of applications in the fields of information extraction and abstract generation. The method uses local information to determine a specific segmentation, and cannot fully consider the information of the remaining paragraphs. In response to this problem, this paper improves the segmentation point selection of the algorithm. After the similarity values of the respective interval points are obtained by the similarity calculation, the sliding window is used to slide on the interval points, and the similarity value of the interval points at the center of the window is replaced with the average of all the similarity values in the window. The experimental results show that the text segmentation based on the improved method can suppress small local changes on the curve, thus highlighting the large similarity value changes, and effectively improving the performance of text segmentation.
An improved weighted fusion algorithm of multi-sensor
Authors: Liu Haibin , Fang Shengyu , Jianhua JI 
Published: March 2020

Abstract
Multi-sensor data fusion is to take full advantage of the complementary nature of multivariate data to improve the feasibility of the statistics. The weighted fusion algorithm is commonly used due to its easiness to achieve. Among the relative factors, the weight directly impacts the results of the data fusion, therefore, the selection of weight is particularly important, as choosing an inappropriate weight will lead to the instability of algorithm performance. To find the best weight, we develop an improved weighted fusion algorithm, introducing the concept of the optimal proportion weight and using secondary weighted approach ----- the single sensor will be weighted individually before the whole sensor system is weighted in order to achieve the optimal algorithm performance.
An Intrusion Detection Method based on Stacked Autoencoder and Support Vector Machine
Authors: Shuaixin Tan 
Published: March 2020

Abstract
To explore the feasibility of forming a combined classifier for intrusion detection by applying Support Vector Machine (SVM) and Stacked Autoencoder (SAE), an intrusion detection method based on Stacked Autoencoder and Support Vector Machine is proposed. Considering that the Piecewise Radial Basis Function (P-RBF) in the Support Vector Machine can improve the classification performance, the Radial Basis Function (RBF) and P-RBF are selected for the proposed method, and the detection performance of the above two methods are compared. Experiments show that the method based on Stack Autoencoder and Support Vector Machine using P-RBF kernel are superior to the one using RBF kernel in accuracy, detection rate and false alarm rate. The method based on Stack Autoencoder and Support Vector Machine provides an idea for the application in the field of intrusion detection.
Research on Improved Access Control Model Based on T-RBAC
Authors: Wang Yong , Yang Yueping , Wang Binxu , Ran Qingwen , Ju Xiaoming 
Published: March 2020

Abstract
The T-RBAC model has a wide range of applications in various fields, but has certain disadvantages. Aiming at the shortcomings of T-RBAC model in task assignment and authority management, an improved model is proposed. The new model simplifies the task classification of T-RBAC model. Considering the task context, task time limit, and task status attributes, the role manager, task manager, and authority manager are introduced, and the grant of authority is closely linked with the three managers, which enhances the dynamic management of rights. The constraints are strengthened and expanded to ensure dynamic separation of duties during task execution. The model has finer-grained rights management, better meets the principle of separation of duties and least privilege, and has higher security.
The Application of GABP Neural Network Algorithm in the Aspect of Security Assessment of Computer Network
Authors: Zhang Yan-lin , Yu Jun 
Published: March 2020

Abstract
With the rapid development and wide application of computer and network technology, there appear increasing number of factors affecting the security of network system. Therefore, it is urgent for network security administrators to adopt efficient network security algorithm to guarantee the network security. On the basis of GABP neural network algorithm, and in combination with different sub-modules and supporting platforms, the small complex network can be evaluated in an all-round way, and the network security can be effectively managed.
Mining Important Functions in Software Network by Node Vulnerability
Authors: Zhang Bing , Sun Shengting , Hao Xiaobing 
Published: March 2020

Abstract
Given that analysis on the vulnerability of functions is helpful to the detection and improvement of software security, this paper aims to propose an efficient methods to identify the vulnerable nodes (ITVN) in different software by the interdependence of functions. First, the dynamic software execution process was constructed as Software Execution Dependency Network (SEDN) based on Complex network theory. Second, by analyzing the dependency relationship among functions, the algorithm calVulAndScoOfNodes (CVSN) was designed to compute the vulnerability and the affected scope of each node for further analysis. Third, in order to measure the functions vulnerability in the whole software network, the algorithm calVulDegreeOfNodes (CVDN) was put forward to calculate the vulnerable degree of each node. Finally, the Vulnerable Nodes in different software were obtained by ITVN. Experimental results show that the vulnerable nodes selected as important nodes are well-reasoned in software network by testing different software, and the measures are effective for evaluating nodes vulnerability.
The Construction and Application of Hybrid Teaching Model of Flipping Classroom and Divided Classroom Base on Project-driven in the Teaching of Java programming
Authors: Zhang Maohong , Yu Zhenmei , Sun Yuhong , Gong Xueyan , Liu Yuan 
Published: March 2020

Abstract
In view of the problems existing in the teaching of Java programming, in order to further improve the teaching quality of Java programming, a hybrid teaching model of flipping classroom and divided classroom based on project-driven was proposed. The problem-oriented, student-cantered teaching concept forms an effective teaching activity for teachers and students. With a complete project throughout the course, online learning is adopted to deeply explore students’ independent learning ability, assist the teaching of course content and group communication learning, combine the flipped classroom with the divided classroom to construct a hybrid teaching model. The experiment proves that under the project-driven teaching mode, the full use of the hybrid teaching of the flipped classroom and the divided classroom can greatly improve learning effect of students at different levels of knowledge, and students’ independent learning ability, innovation and creativity ability can also be improved accordingly.
Intelligent Fault Diagnosis of Engine Based on PCA-SOM
Authors: Zhang Yangyang , Jia Yunxian , Guo Chiming , Wu Weiyi 
Published: March 2020

Abstract
Self-Organizing Feature Map (SOM) is a kind of self-organizing and self-learning network without teacher. It is mainly used for pattern recognition and region classification of input vectors. A fault diagnosis method of engine fuel supply system based on SOM neural network is proposed. The sensor is used to monitor the fuel pressure waveform of a certain engine fuel supply system, time domain analysis and feature extraction are carried out on the waveform, and the feature dimension reduction is realized by PCA to form the input vector of SOM neural network. The SOM neural network is used to establish the diagnosis model and then recognize fault patterns for test samples. The results of pattern recognition show that SOM neural network can identify and classify faults accurately, and it has certain engineering application value.
RBF neural network sliding mode control on pitching motion of an underwater spherical vechicle
Authors: Liu Zhimin , Zhou Yiyang 
Published: March 2020

Abstract
The pendulum spherical underwater vehicle can realize the ascending and descending motion in water by using the internal pitch pendulum and the central propeller. It is the frequent swing of the pitch pendulum that causes the fluctuation of the speed of the robot and reduces the stability of the system. A two-stage sliding method is proposed for the pitch driving characteristics of the robot and it can control the pitch angle and the swing angle of the pitch pendulum of the robot at the same time. The neural network is introduced to compensate the interference items adaptively. The stability of the designed controller is proved in theory. The simulation and experimental results show that the proposed control method can realize the rapid control of the pitch angle of the robot and the frequency of the pitch pendulum. The complex swing is restrained effectively, and the stability of the underwater motion of the robot is improved.
A Requirement Engineering Approach to User-Centered Design
Authors: Xiao Bin , Su Kai , Su Xiaoguang 
Published: March 2020

Abstract
This paper introduces a user-centered design method in software engineering practice. This method can develop software more effectively based on the design results of UCD, and make these results be tracked and tested in the future. Another feature of this method is to make UCD as schedulable and manageable as other software development activities. This paper introduces a requirement analysis framework based on three types of usability requirements, which reflect the results of UCD activities in software development. These types of requirements come from the description of UCD in ISO 13407 model.
An Integrated Cell Region Reconstruction Method Based upon Mask R-CNN Model and Improved Voronoi Algorithm
Authors: Zou Shun , Wei Shengyun , Liu Han 
Published: March 2020

Abstract
Cell region segmentation in IHC staining images is the basis for quantitative analysis, which is very challenging due to the incomplete membrane staining in IHC images. In this paper, we propose a novel integrated cell region reconstruction method based upon Mask R-CNN model and improved Voronoi algorithm to reconstruct cell region in incomplete IHC staining images, in which Mask R-CNN model is introduced to perform nucleus segmentation, and then the improved Voronoi algorithm with the prior knowledge of nucleus-cytoplasm ratio is used to reconstruct the whole cell region. We also develop a framework for the integrated method to achieve automatic end-to-end cell region segmentation. Our method could better solve the problem of cell segmentation under incomplete staining than only deep-learning method or standard Voronoi algorithm, and the reconstructed cell region could better fit the real cell boundary.
A G2G Similarity Guided Pedestrian Re-identification Algorithm
Authors: Wang Guangcai , Gao Shang , Fan Di 
Published: March 2020

Abstract
Pedestrian re-identification aims to settle the matching problem for a given target pedestrian under the multi-camera with non-overlapping visual field, so as to achieve the goal of pedestrian retrieval. In this paper, the similarity between the gallery images (G2G similarity) will be used to guide and refine the similarity between query images and gallery images (P2G similarity). It is also introduced into the training process and playing a supervisory role. To fully utilize details of the images, the image features are horizontally overlapped into groups, and the similarities between each group of the query images and the gallery images are calculated respectively. By learning the weights of grouping features in the training process, the importance of key parts can be automatically perceived. The results on the Market-1501 and CUHK03 datasets prove the effectiveness of proposed algorithm.
Research on Extension Innovation Design Method of Product Family Based on Kano Demand Model
Authors: Chen Huihong , Liu Shiming 
Published: March 2020

Abstract
By the existing innovation design methods of product family, people can get new products design effectively. However, these methods can’t make their products to meet customers’ demand completely, because they can’t help people turn customers’ demands into products characteristics using model methods. This paper uses Kano requirement model to find essential demands, clarify customers’ demands, and utilizes extension innovation methods to establish models for the products, which have different characteristics, then uses extensive analysis and extension transformations to obtained new products designs, and finally get innovation designs of product family according to superiority evaluation methods. A design for mobile phone is taken as an example to demonstrate this method..
Method of Controlling Vehicles at Intersections Based on the Auction Algorithm
Authors: Liu Mingjian , Zhang Sijia , Teng Lin 
Published: March 2020

Abstract
In this study, a method of controlling vehicles at intersections based on the auction idea was proposed, which can be compatible with unmanned vehicles and human driving vehicles, ensuring driving safety and improving traffic efficiency at intersections. Collecting vehicle reservation requests through the bidding unit at intersections, this method provided reasonable vehicle traffic strategies according to information such as vehicle routing (Route), budget (M), hunger coefficient and credit coefficient. The simulation results show that the method of controlling vehicles at intersections based on the auction idea can effectively reduce the average delay of vehicles caused by waiting and improve the throughput of the intersection, verifying the effectiveness of this method.
An improved measurement method of size of mechanical parts based on monocular vision
Authors: Guo Qiang , Fu Wenyu 
Published: March 2020

Abstract
During the monocular measurement of multiple mechanical parts with non-negligible thickness at the same time, the physical dimensions of the pixels on the upper and lower surface edges of the mechanical parts in the image taken by the camera are different, resulting in the deviation of the actual measurement results of the mechanical parts In this paper, a measurement method based on unit pixel size compensation is proposed. This method compensates the measurement data by the distance between the upper and lower surfaces of the mechanical parts and the camera, thus reducing or even eliminating the measurement error caused by the thickness of mechanical parts. The simulation results show that, under the same measuring platform, for the mechanical parts of different sizes and thicknesses, this method can achieve a significant improvement in measurement accuracy.
Research on “Internet +” Rural Precision Poverty Alleviation and Sharing Financial Model
Authors: Li Qiutong , Yang Chuansheng 
Published: March 2020

Abstract
Internet technology has many advantages and can provide a good tool for all aspects of development. In China’s economic and social development, “Internet +” has become an important strategy at present. The work to the “Internet +” has become a new development trend. The use of modern technologies such as computer networks has been put on the agenda. After continuous exploration and comparison, the shared service platform is a relatively good mode of operation, and a financial sharing model has been formed in the financial aspect. Financial sharing can significantly reduce the cost of precision poverty alleviation, thus accelerating the process of standardization of rural poverty alleviation. Based on the background of “Internet +”, this paper discusses the new model of rural poverty alleviation and analyzes the framework model of rural poverty alleviation. In the context of “Internet +”, poverty alleviation work combined with computer Internet technology, using computer networks and other modern technologies to carry out rural precision poverty alleviation work, has become the development direction of application of new technologies in the era of computer networks. This article explores financial sharing and social development to explore the advantages of financial sharing and how it affects financial management; It makes full use of the convenience brought by high-tech development to the government service work.
Analysis on Dietary Behavior and Dietary Intake of Children in Chongqing City, China by SPSS Statistical Software
Authors: Tan Fang , Zhao Xin , Huang Qianqian , Zhang Jiaqiong 
Published: March 2020

Abstract
In order to understand the current situation of children’s dietary behavior and its influencing factors in Chongqing City, China, this study investigated the dietary behavior of children in Chongqing City by random sampling of 2200 parents of children in the main urban area of Chongqing City by questionnaires. Through SPSS statistical software analysis, it was found that children’s dietary behavior problems were prominent, 83.5% of children had food concentration problems, 57% of children had selective eating behavior. In addition, children’s dietary preferences are also uneven. It can be seen from this that families, kindergartens and all sectors of society work together to carry out the education of infants’ dietary behavior, so as to cultivate infants’ scientific and healthy dietary behavior.
Prediction model of household appliance energy consumption based on machine learning
Authors: Xiang Lei , Xie Tao , Xie Wei 
Published: March 2020

Abstract
This paper presents and discusses the prediction model of household appliance energy consumption. The paper discusses data filtering to remove non-predictive parameters, and used for model training. Five prediction models are trained with repeated cross validation and evaluated in the testing set: support vector machine (SVM), k nearest neighbor (KNN), random forest (RF), extreme random forest (ERF), and long short-term memory network (LSTM). Among them, the LSTM, which is a deep learning method, behaves the best performance. LSTM has the highest R2 (0.97) and the lowest RMSE (21.36) in the testing set. The analysis results show that the deep learning method has advantages in the prediction of household appliance energy consumption.
Compact Prediction Tree (CPT) Application Research on the Causes of Faults in the Use of Multimedia Classrooms in Colleges and Universities
Authors: Bai Haicheng , Yang Shuai 
Published: March 2020

Abstract
In addition to maintaining equipment, the management of multimedia classrooms in colleges and universities is mainly to provide timely assistance to teachers. When a failure occurs, if the cause can be automatically predicted and online real-time assistance is provided in time, this will greatly enhance the teacher teaching experience. Series prediction is one of the hotspots of deep learning research, for it has been widely used in many fields from recommendation systems to speech recognition to natural language processing. The Compact Prediction Tree (CPT) is faster and more accurate than other sequence prediction models. Based on this, this paper studies how to generate prediction trees for multimedia fault text events in colleges and universities, and uses CPT to predict the causes of multimedia classroom failures to improve management efficiency and user experience.
Blink Detection Based on Pixel Fluctuation Ratio of Eye Image
Authors: Dou Dou , Zhang Zhaogong 
Published: March 2020

Abstract
In this paper, an algorithm of real-time eye blink monitoring using ordinary camera is proposed. This algorithm is based on pixel fluctuation ratio (FRP) of eye region image to detect eye blink. Position the eye area according to the facial landmark algorithm and then convert the image to a grayscale image. According to the point detected by the eye region in the grayscale image, the eye region is divided into three segments from the corner of the eye to the end of the eye. Calculate the value of the pixels in each segment, and find the partial image pixel value fluctuation ratio (FRP), and train the selected training samples with the support vector machine (SVM). We tested it on two data sets, and the blink detection algorithm achieved good results on both data sets.
Application of Computer Information Technology in Modern Distance Education System
Authors: He Lifang 
Published: March 2020

Abstract
The key to the application of computer information technology in distance education system is how to effectively apply the advantages of information technology to better achieve the goal of curriculum learning, cultivate students’ information literacy, innovative spirit and time ability. Computer information technology does play a huge role in distance education. And good teaching resources have laid a solid foundation for teachers to implement distance education, attaching importance to the construction of teaching resources. This paper introduces the necessity of applying computer information technology in modern distance education system and its application in modern distance education.
Application of New Relay Protection Technology in Agricultural Power System
Authors: Li Aichuan 
Published: March 2020

Abstract
With the continuous development and progress of society, information technology and computer technology have also been highly developed and improved. With the support of technology, new technologies of relay protection system have emerged, which has great significance and role for the effective operation of power system. Especially for the rural power system, the emergence of new relay protection technology has brought many benefits, solved some problems in the rural power system, and guaranteed the effectiveness and security of the rural power system. This paper mainly analyses what is the new technology of relay protection, what specific application of the new technology of relay protection in agricultural power system and the future development trend of the new technology of relay protection.