bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recognition of Planar Object in Stack via Local Prediction Consistency
Authors: Bao Jianying , Feng Lei , Gu Chengge , Mo Jinqiu 
Published: July 2019

Abstract
A novel method for recognition of planar object in stack via local prediction consistency is proposed in this paper. By checking the consistency of local predictions, an object can be recognized and located. The prediction method by local features under uncertain scale is emphatically discussed. According to the distribution prior for local predictions, the similarity scale can be determined and the consistent local predictions can be composited. A great number of experiments are carried out to prove the stability of this method.
Research on the Integration of Modern Educational Information Technology and Advanced Mathematics Teaching
Authors: Xianfang Tang 
Published: July 2019

Abstract
The development and wide application of modern information technology have led to the improvement of the level of mathematics education in colleges and universities, and the new teaching mode of advanced mathematics teaching becomes more and more diversified and modern, which can not only enable students to experience information technology better, but also enable them to improve active consciousness at the same time when they participate in learning, and it also promotes the improvement of teachers’ teaching efficiency. Based on this situation, the author mainly takes modern educational information technology as the starting point in this paper, focusing on the integration and application of advanced mathematics teaching and modern educational technology in China.
The Generalized Power Graph of a Finite Group
Authors: Ma Xuanlong , Fu Ruiqin 
Published: July 2019

Abstract
Graphs associated with groups and other algebraic structures have been actively investigated, since they have valuable applications in data mining. For a finite group G, let ΓG be the graph with the non-identity elements of G as the vertex set, and two vertices are adjacent if they respectively lie in two conjugate proper subgroups of G. ΓG is called the generalized power graph with respect to G. This paper explores how the graph theoretical properties of ΓG can affect on the group theoretical properties of G.
RETRACTED: Security Analysis of Computer Information Processing Technology under the Background of Big Data Era
Authors: Le Luo , Zhimiao Fang , Zhenghan Wu 
Published: July 2019

Abstract
With the development of science and technology, society has entered the era of big data, and data information has been shown to be open, which has played a role in optimizing data calculation mode and improving data utilization efficiency. At the same time, computer information processing problems are also suffering. attention. This paper will take the school computer information processing technology security work as an example to analyze the computer information processing technology security management scheme under the background of big data era, and put forward personal opinions, hoping to provide reference solutions for computer information processing technology security management.
Privacy Revolution in the Big Data Age: from Privacy Protection to Personal Data Governance
Authors: Cui Shujie 
Published: July 2019

Abstract
The arrival of the big data era also means the emergence of the privacy crisis. Nowadays, privacy is challenged and privacy protection theories have obvious limitations. In the big data age, the focus of privacy protection should be shifted from traditional physical protection to personal data governance. Personal data has many similarities with privacy but also some noted differences. Compared with privacy’s static and exclusive features, personal data is characterized by extraversion and fluidity, and is a combination of personal interests and property interests. Based on the above conditions and China’s data development practices, it is crucial to pay attention to the transformation process of the data governance model especially from the privacy protection to the personal data governance, which is the core of achieving the balance between personal data protection and data application. To promote personal data governance, the following strategies should be applied: a) adhering to the purpose of balancing data application and personal data protection; b) attaching importance to data values and allocating data interests on data flowing process; c) improving personal data protection legislation; d) inducing technological innovation.
Population Statistics Algorithm Based on MobileNet
Authors: Feng Xiaoqin , Xie Rong , Sheng Junyang , Zhang Shuo 
Published: July 2019

Abstract
In today’s society, intelligent video surveillance plays an important role in social security, traffic scheduling, national security and other fields. One of the research hotspots is people statistics based on image processing, which has strategic significance in practical applications. Aimed at the problem that the low accuracy in the actual application scenario, the limited hardware resources, and the low operation efficiency, this paper proposes a multi-feature target detection model based on the lightweight deep learning network MobileNet [1], which can be used in intelligent terminals. The basic feature-extraction network MobileNet as a lightweight network can provide a flexible alternative configuration in terms of efficiency and accuracy. The underlying detection network selects a single deep nerual network, named SSD [2]. The algorithm can achieve multi-scale target detection, and uses the target position and category to perform one-time regression. In this paper, the activation function of SSD is changed into SeLU (scaled exponential linear units) [3], which improves the robustness of the algorithm. At the same time, the work of sample diversity and data enhancement has been made, and the characteristics of the human body above the shoulders have been fully utilized. Experiments have shown that the improved network structure based on MobileNet has higher detection accuracy, lower delay, excellent robustness, while the number of model parameters is effectively reduced.
Analysis of P2P Online Lending Default Based on Random Forest
Authors: Cai Haojiang 
Published: July 2019

Abstract
This article, based on Renren Loan website, will utilize SMOTE to process the debit and credit data in a balanced way. In addition, the importance for the variable-Random Forest and cross-validation conception will be applied for feature selection before the parameter optimization by grid searching, so that the model of basic Random Forest will be derived. Finally, featured modules of LDA will be added to further explore the reference value of loan description. The research findings show that the model has a satisfactory performance on test set in terms of predicting the results.
Change Detection Method based on Block Similarity Measure
Authors: Li Yu , Sun Tao 
Published: July 2019

Abstract
Due to the random distribution of speckle noises in SAR images, the method based on direct pixel contrast cannot correctly judge the change of the pixels. In this paper, Convolutional Neural Network (CNN) is used to describe the multitemporal image blocks. Then the learned image block features are input into the decision network for further learning. The change detection of the whole image is completed on the basis of comparing the image blocks. The innovation of this method is that the input of the network is not the difference image produced by traditional methods, but the corresponding multitemporal image blocks. The output of the network is the judgment of the change between blocks. In addition, CNN is adopted to describe the features, which can extract the main features of the image blocks and is more robust to coherent speckle noises. This method has excellent performance in the accuracy of change detection.
Research on Well Trajectory Optimization Design Based on Ant Colony Algorithm
Authors: Xu Yingzhuo , Li Chengyuan , Wang Liupeng 
Published: July 2019

Abstract
The intelligent optimization algorithm designed for the current drilling well trajectory has shortcomings such as slow convergence rate and easy to fall into local optimal solution. This paper proposes an optimization method based on ant colony algorithm for well trajectory optimized design. Firstly, the three-stage well trajectory optimization design is taken as an example. The shortest space curve length is the optimization target, and the vertical depth, well angle and azimuth angle are used as constraints to establish the optimal mathematical model of the well trajectory. Then the ant colony algorithm is used to find the optimal parameters of the well trajectory under the constraint conditions, so as to realize the optimization of the well trajectory design.
Research on 3D skeletal model extraction algorithm of branch based on SR4000
Authors: Liu Shiyang , Yao Jiaojiao , Li Hui , Qiu Changpeng , Liu Ruijun 
Published: July 2019

Abstract
A branch 3D Skeleton extraction method based on SR4000 is proposed, which can be used for pruning robot visual recognition. In this method a 3D Skeleton model of the branches of apple trees in the initial fruit stage was successfully constructed. According to the experimental results, the average computational efficiency of the 2AHC(2-level Aggregation Hierarchy Clustering) is increased by 369%, the detection rate is 84.69%, and the error rate is 5.03%. The average detection rate of depth analytic hierarchy process was 64%; The overall 3D Skeleton restoration effect is better. Therefore, the algorithm can better reflect the qualitative relationship between branches, improve the computational efficiency, and provide algorithm support for automatic pruning robot visual recognition.
Application Research of Moving Target Detection Based on Optical Flow Algorithms
Authors: Lou Li , Liang Shuo , Zhang Yanyan 
Published: July 2019

Abstract
After many years of research, optical flow algorithm has achieved good results in detecting moving objects in simple scenes, but the detection effect in some complex scenes is not ideal, for example, in scenes with changing illumination and large displacement, the accuracy of moving objects detection is low. In order to solve this problem, this paper proposes texture decomposition of images, and applies texture image and pyramid technology to Lucas-Kanade optical flow algorithm. Relevant experiments show that this method can achieve better detection results for moving objects in static scenes.
Design & Development of Well Site Drilling Information System used in South Azadagan
Authors: Liu Zhikun , Zhang Chaoqun , Wu Wenrui 
Published: July 2019

Abstract
Based on our experience and successe in the development of drilling information management software as well as our understanding of the South Azadagan well site situation in Iran, the South Azadagan Well Site Drilling Information Management System has been designed. Through the establishment of database of DIMS, the integrated well site drilling information management and application system is developed. In the process of collaborative information management under network environment, a convenient and unified data manage and analysis platform for well site drillers in different Rigs has been provided. This paper describes the design and development of South Azadagan Well Site Drilling Information Management System in detail.
RETRACTED: Research on the Database of Competitive Sports Talents in Colleges and Universities in China under the Background of “Internet+”
Authors: Gao Jianxin 
Published: July 2019

Abstract
In order to promote the rapid development of competitive sports in colleges and universities in China, the database of talent cultivation is constructed by using Internet technology so as to provide high-level sports talent for colleges and universities. Using field investigation and logical analysis to construct the base of training database of competitive sports talents in colleges and universities under the background of “Internet+” situation and feasibility of scientific cloud computing analysis and the construction of a database, this paper is intended to provide a variety of valuable information and data for the training of competitive sports talents in colleges and universities, to enhance the quality and level of competitive sports talents in colleges and universities.
Application of Improved Multi-Objective Bacterial Foraging Algorithm in Virtual Network Mapping Algorithm
Authors: Qu Yihui , Li Jun 
Published: July 2019

Abstract
For the virtual network mapping problem, consideration of many aspects will be more comprehensive. In this paper, the multi-objective bacterial foraging optimization algorithm is improved to solve this problem. First, because the virtual network mapping problem is a discrete problem, the operator of the algorithm is redefined as discrete; secondly, the resource congestion factor and 2-opt algorithm are introduced in the chemotaxis operation of the algorithm, and the cross-factor is introduced in the copy operation, so that the found solution is better. At the same time, the node resource load balance degree and the minimum cost are used as the fitness function, so that the found solution solves the problem more. The experimental results show that the algorithm is used to solve the virtual network mapping problem. The algorithm has good validity and stability in both large-scale virtual network requests and standard cases.
A Real-time Character-level Subtitle Detector based on Faster R-CNN
Authors: Chen Haipeng , Song Qing 
Published: July 2019

Abstract
Faced with a deluge of video data, automatic subtitle text detection and recognition using computer vision technology can be extremely useful. This paper proposes a real-time character-level subtitle detector, which detects subtitle text with high accuracy and efficiency in a single forward pass. It also provides an efficient method to build dataset aimed at video subtitle text detection problem. This paper’s method can achieve both 99.5% precision and recall for text detection, and the whole detection and recognition process can achieve 45 fps.
Research on Colleges and Universities Assistant Teaching Application Design Based on Cloud Computing
Authors: Bei Wang 
Published: July 2019

Abstract
Based on infrastructure and computing power provided by cloud computing service providers, more and more colleges and universities have developed information-based educational resources and implemented information-based educational applications in a virtualized environment. After accessing cloud computing services, universities do not need to spend a lot of money to purchase commercial software licenses, because cloud computing can provide a large number of commonly used application software. However, there are few cases about these educational information software resources applied to actual teaching and combined with specific courses, which makes the information software resources disconnected from the courses and reduces the teaching efficiency and effectiveness of the classroom. Based on aforementioned background, this study is aimed at the existing teaching mode in colleges and universities, to conduct research on the specific cloud computing application and practice in the teaching of colleges and universities. With rapid development of information technology, the education informatization will certainly transit from the computer-aided education to the education centered on calculation, data and service, of which possibility and technical support can be provided by the development of cloud computing. With the continuous development and popularization of cloud computing technology, its advantages of low cost, convenience and security will surely attract more colleges and universities to carry out daily education on cloud platform.
Improve Repairing Data Process by Using Multiple Based-Rules
Authors: Feng Yuan , Liu Guohua 
Published: July 2019

Abstract
This paper proposes a method on solving the problem of dealing with dirty data in the database. Considering the complexity of the structure of the data, based on the previous methods that work on this problem, our method combines the methods that use regular expression and methods that use conditional functional dependencies, to complete the data quality improvement. This method uses dependencies to improve the repairing speed and the searching time on the data. The repairing based on the regular expression is regular while there exist questions that the repairing efficient is influenced by the amount of data. When dealing with the database from company Standard Solution Group (SSG) which is from the reality world data, we have tried other related methods and inspired by these methods, we propose this method. The experiments on the data from SSG shows that this method is much efficient.
Fast 3D Body Measurement Based on Multi-directional Point Cloud Piecing
Authors: Wan Yan , Jiang Jianpeng , Fan Jinghua , Liu Min , Zhao Yingbin , Yao Li 
Published: July 2019

Abstract
In order to realize fast, accurate and device-lightweight 3D body measurement, this paper proposes a quick measurement scheme which obtains measurement results by combining multi-directional human point cloud data. In this paper, the depth camera captures the point cloud data in front, side and rear of the human body, and combine the point cloud data with the skeleton point data provided by the depth camera somatosensory function. Taking the measurement of waist circumference as an example, the method of extracting the point cloud data of the waist is described. The curve equation of the waist curve is obtained by polynomial curve fitting with the discrete points. Finally, the length of the waist curve is calculated by the integral method. The measurement results are satisfactory.
Research on 3D Technology Based on Point Cloud
Authors: Deng Xi , Zhang Zhiyong , Liu Xicheng , Tian Huiling 
Published: July 2019

Abstract
In order to solve the problem on how to visualize the point cloud data in the web front-end domain, this paper proposes and develops a point cloud resolution based on Web technology. The user interface is achieved by opening web technology HTML5 and CSS3, and web interaction function is developed by using JavaScript. The visualization operation and the positional information of the point cloud image data are converted and calculated by the depth-perspective correlation function and applied to the module test. The experimental results show that the system can resolve about 30, 000 points of cloud data, the less point cloud data, the faster resolution speed is, which has greater practical value.
Investigation on Automatic Data Acquisition of Well Logging Curve based on Color Recognition
Authors: Wang Han , Ye Zhihui , Chen Dong , Zhu Dandan , Li Shouding 
Published: July 2019

Abstract
Well logging data are important to evaluate rock and fluid properties underground. Many well logging data, as functions of well depth, are conserved as figures in the literature. Digitizing technics should be applied when utilizing the well logging data. In order to address this problem, a method was proposed to automatically identify and acquire the well logging data from well logging curves. Based on the color recognition, this algorithm is able to extract curve features based on pixels. Comparing to other data digitizing methods, the background grid lines could be easily filtered and removed. The algorithm is verified by digitizing some typical well logging curves. This main contribution of this work is to provide a new and efficient way for data digitizing from well logging curves.
Human body moderate training control method based on flexible mechanical characteristic analysis
Authors: Tao Wu 
Published: July 2019

Abstract
It has important application value to the human body moderate training control in the sports training guidance and the sports training big data analysis and so on. Aiming at the problem that the current master-slave arm motion data acquisition method is not accurate enough for human body moderate training and control, a human body appropriate training control method based on flexible mechanical characteristics analysis is proposed. Firstly, the flexible mechanical data analysis and kinematic attitude space reconstruction of human body are carried out. Then the motion state equation is constructed to sample the human body moderate training control attitude data and analyze the fusion of flexible mechanical features. The human body moderate training control is realized. Finally, the simulation results show that the modeling method has good stability, high accuracy of mechanical parameter estimation, and good reconstruction ability for human movement, such as running, jumping, gymnastics and so on, and the simulation results show that the modeling method has good stability and accuracy for human body moderate training and control, and the accuracy of mechanical parameter data estimation is high.
Image Analysis and Processing of Skin Cell Injury Based on OpenCV
Authors: Li Gaohe , Zhang Yanli , Xu Bo , Li Xinhao 
Published: July 2019

Abstract
OpenCV is an open source computer vision and machine learning software library that provides a common infrastructure for computer vision applications and accelerates their use of machine awareness in commercial products[1].This paper uses the visual processing algorithm provided by OpenCV to analyze and process the image of skin cells in detail, and quantitatively determine the percentage of damaged cells in the image. First, dilation, opening operation, closing operation, coarsening, refinement, skeleton, tailoring, boundary extraction, holes filling, connected components and so on of a variety of morphological methods are used in the process of corrosion for the graphics pretreatment. Then the watershed algorithm is adopted to image segmentation. This paper expounds the ridge algorithm to water in detail. Finally, in order to determine the proportion of damaged cells in the segmented cells, the polygonal fitting method in graphic image processing was creatively used, and the polygonal fitting method was described in detail, which successfully solved the task of the research topic.
Global salient object detection based on multiple visual features
Authors: Li Zhengyi , Li Heng , Chai Xinyu 
Published: July 2019

Abstract
Salient object detection has become an important tool in the fields of computer vision and image processing. In this paper, we propose a novel global salient object detection model based on multiple visual features. Firstly, following the mechanism of parallel processing of visual information, we obtain three saliency maps based on colour, intensity difference, and spatial distribution. Secondly, introducing the concept of spatial gaze point of an image, we calculate three Gaussian weighted maps based on three saliency maps to constrain their background noise and get three weighted saliency maps. Finally, the final saliency map is produced by fusing three weighted saliency maps. We compare our method with 10 state-of-the-art saliency methods on a public dataset, and the results show that our method outperforms the other 10 methods.
sEMG Signal Processing Methods: A Review
Authors: Wu Jiajia , Li Xiaoou , Liu Wanyang , Jane Wang Z. 
Published: July 2019

Abstract
Surface electromyography (sEMG) is one type of bioelectrical signal produced by the human body. sEMG contains meaningful information associated with muscle activity and has numerous applications in motor control and neuromuscular physiology. sEMG signals can be used to identify the movement intention and evaluate the function status of muscles. sEMG is also applied in virtual reality with the advances of technology development. In this review paper, sEMG feature extraction methods and classification methods are summarized, and the future development is prospected.