bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Multi-fault-tolerant MDS Array Erasure code
Authors: Yuan Wei , Yu Ying , Gao Yan , Tang Dan
Published: July 2019

The array code has the advantages of high computational efficiency and simple structure. And the erasure code strategy based on the array code is one of the ideal fault-tolerant methods for distributed storage systems. However, low fault tolerance has always been a major obstacle to the practicality of array code. According to the known literature, the fault-tolerance of MDS array code is no more than three. And the array code with the biggest fault tolerance is the Grid code. Its fault tolerance is usually only 15. In view of this situation, this paper proposes a kind of multi-fault-tolerant MDS array code, called Reed-Solomon Array (RA). The RA code has higher coding efficiency, whose encoding process and decoding process only involve binary XOR operations. What is more, the construction method is simple and easy to be implemented by software and hardware. And then the RA code is a MDS code with optimal storage efficiency. Finally the size of the storage array of the RA code is not strictly limited. The extensibility of the distributed storage system is met.
Subcarrier interpolation and DFT channel estimation in ultra-wideband systems
Authors: Wan Xing , Huang Min , Luo Wanbo
Published: July 2019

Channel estimation algorithm is one of the key research directions in UWB systems. For the ECMA368 standard, there is a wave interference problem in channel estimation. This paper constructs a low-order ZP-OFDM-FAST model for improving channel estimation performance. The interpolation problem of virtual zero subcarriers is studied, and the interpolation DFT channel estimation method is proposed. Finally, a method of frequency domain instantaneous filtering is given.
Research on adaptive fractal image compression algorithm based on flexible classification technology
Authors: Jian Ning Han
Published: July 2019

This paper proposes a flexible classification technique for accelerating image matching and improving coding quality, using a fast adaptive fractal image compression method with four fork tree as image division and flexible classification technology, which is a kind of pre-segmentation of images. With using the self-similarity of each part of the image, the fractal encoding is carried out. In order to reduce the encoding time to dozens of seconds, it eliminate the block effect and realize the fast fractal coding of color image, so as to speed up the encoding speed and further improve the image comprehensive performance of compression ratio and signal-to-noise ratio/encoding time.
Bayesian acoustic impedance inversion with gamma distribution
Authors: Wu Hao , Li Shu , Chen Yingpin , Peng Zhenming
Published: July 2019

Bayesian model is popular in seismic acoustic impedance inversion because of the statistical information from Bayesian model. However, there are many distributions to simulate impedance distribution. Different distribution has different result. In this paper, the Gamma distribution is used as the prior distribution. A Bayesian impedance inversion method is proposed, under the assumption that the prior distribution is a Gamma distribution. Through the test from the field and model data, this method is feasible and this model based on Gamma distribution has a result with tall resolution.
Recognition of Planar Object in Stack via Local Prediction Consistency
Authors: Bao Jianying , Feng Lei , Gu Chengge , Mo Jinqiu
Published: July 2019

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Chinese spam filtering based on Stacked Denoising Autoencoders
Authors: Zhang Liuyan , Nie Yunfeng , Duan Shengyue
Published: July 2019

Aimed at the problem that the traditional feature selection method extracts the feature items and the filtering accuracy is degraded in the Chinese spam filtering process, this paper proposes a Chinese spam filtering method based on Stacked Denoising Autoencoder (SDA). Firstly, use the Continuous Bag-of-Words (CBOW) model training the Word2vec tool set for the processed corpus to transform word segments into vectors; the inputs are the word vectors; then apply the Stacked Denoising Autoencoder (SDA) to effectively extract the features text in unsupervised learning. Finally, the improved softmax classifier is used for regression classification. The test was carried out on the TREC06C dataset, the experimental results show that compared with Bayesian model, KNN classification algorithm and traditional Stacked Denoising Autoencoder, the accuracy, precision, recall, and f1 score of the method reached 93.5%, 94.8%, 92% and 93.2%, and had better dichotomous effect and robustness in the application.
The Application of Deep Learning in Vessel Extraction with Fundus Image
Authors: Yang Zuman , Wu Jiaxing , Jiang Kagyu
Published: July 2019

Fundus image is a very prevalent Biomedical data, so it is very important to choose a method to extract blood vessel from fundus images. Extracting vessel from the fundus image can be used for personal identity verification and assist doctor to diagnose diseases [1] such as diabetes. However, traditional extracted methods such as manually annotation area waste of time and energy. There is some another method [2] based on the image recognition, extracting the feature with the filter and segment with mathematical morphology method. But in the fact of the application, this method has low stability and accuracy. Traditional machine learning methods such as SVM [3] are also used for vessel extraction, but this method can only apply to dealing with one-dimensional data while the images showed up as matrix form. So, we have to stretch a matrix line by line or column by column into one-dimensional vectors [4-6]. However, by doing so, we will be face that some important information can’t be reflected because the position relation of rows and rows in the original matrix will be lost. Deep learning can process image data naturally and extract features automatically with convolution, and it is also popular for its good learning ability and high accuracy. U-net [7] is a convolutional network based on deep learning and widely used in biological image extraction, which constructs a U-shaped network from input image and output image. In this paper, building a U-Net convolutional network, which takes fundus image as input and vessel image as output, to extract vessels in fundus image. We established a training set with 20 fundus images and a test set with 20 fundus images. Finally, the accuracy rate of our U-net model on the training set can reach 99 percent, while the accuracy rate on the test set was stable above 99.5 percent.
Infrared Dim Target Detection Based on Multi-Feature Fusion
Authors: Wei Shuigen , Wang Chengwei , Zhang Congxuan , Yan Huibin
Published: July 2019

A novel infrared(IR) dim target detection algorithm based on multi-feature fusion is proposed in this paper. Firstly, the gray residuals map is obtained by calculating the 8-directional local gray residual. Secondly, the image is divided into a series of local image patches by using a sliding window, then the intensity mean of local image patches is constrained to achieve the local intensity mean constrained map. Lastly, the local image patch is further divided into 12 directional blocks, and the gradient direction constrained saliency map can be obtained by constraining the gradient direction of the pixels in each directional block. Then, the final saliency map is obtained from the above three feature maps by dot product operation, and dim targets are separated by threshold segmentation. The experimental results show that the proposed algorithm not only can effectively suppress background clutter and eliminate false targets, but also can accurately detect dim targets with high detection rate.
Implementation of automatic map based on saliency detection
Authors: Yuhong Liu , Xuan Wang , Xinyu Wang , Chunhong Cao
Published: July 2019

As one of the key technologies in film special effects production, virtual reality, augmented reality and digital image editing, image matting has been widely applied. In computer vision, art design and other aspects have played a very important role. In view of the limitations of traditional matting technology on background and the need for a large number of human interactions, this paper adopts an automatic matting algorithm based on saliency detection to solve this problem. Experimental results show that the improved RC algorithm can automatically mat out the images, and has a good effect and high efficiency in detail processing.
Part Attentioned Fine-Grained Categorization Using Context Sensitive Flow
Authors: Zhang Zhiqin , Zhang Bo
Published: July 2019

It is difficult to recognize fine-grained objects (e.g., dogs or cars) because of the challenges of difficult region localization and fine-grained feature learning. Current approaches neglect the fact that local context feature and global feature are mutually correlated and thus it is possible to use the related information from each other. In this paper, we propose a novel multiple scales attention fusing convolutional neural network which can learn region-based feature and discriminative object attention and at multiple scales in a mutually improved way. The learning is composed of several scales which consist of a classification sub-network and an attention fusing module. A Lrefine loss was proposed to refine the second sub-network category performance. We do some overall experiments and show that our proposed method achieves the best performance in two fine-grained tasks, with relative mean accuracy gains of 2.2%, on CUB Birds, and Stanford Cars.
A Rate Adaptation Scheme with Enhanced Loss Differentiation for LoRaWAN Communications
Authors: Xie HaoFei , Huang DaiWei , Long Yi , Wang QiuHua
Published: July 2019

As an emerging technology for long-range communication, LoRaWAN provides several data rates for transmission and the choice of data rates will affect the communication distance and the link quality. So how to allocate this communication resource in a network with a large amount of devices is a challenge. In this paper, we classify the reasons of packets loss as channel attenuation and data collision and then propose a rate adaptation scheme with enhanced loss differentiation. The proposed scheme can estimate two packet loss rates according to the channel attenuation probability model and data collision probability model respectively. And the selection of communication data rate is given by the balance of probabilities. Simulation results indicate that the proposed scheme is better than ADR and EXPLoRa on Data Extraction Rate and Goodput.
Research on Denoise Methods of Channel Estimation in OFDM System with High-speed Multipath Channels
Authors: Yao Ling
Published: July 2019

To solve the problem of low accuracy of channel estimation in OFDM systems in the scenario of high-speed multipath channels, it is proposed in the paper that a noise reduction scheme of channel estimation is based on DFT (Discrete Fourier Transform) algorithm. By analyzing the algorithm principles, the mathematical model of the system is built, and the performance of the scheme is analyzed. Simulation results reveal that in high-speed scenario, the scheme has effectively achieved low bit error rate and low mean square error, thus having good application value.
Design of a Small-size Broadband Circularly Polarization Microstrip Antenna
Authors: Sun Hang , Li Chang-sheng , Qiu Tian-ye
Published: July 2019

The information transmission of wireless system in coal mine has been faced with severe challenges, and the traditional wireless measurement method has the problems of low anti-interference ability and low reliability. The wireless system based on the temperature, humidity and harmful gas measurement of ultra-high frequency radio frequency identification (UHF RFID) technology can effectively improve the reliability of the system and enhance the safety of the operation in the coal mine. In order to detect the status in the coal mines in real time, this paper designs an ultra-high frequency micro-strip antenna with high gain, wide frequency band and circular polarization. Through the simulation, it can show the influence of different parameters on the antenna performance and obtain the optimal design size of the antenna with center frequency of 915MHz. Finally, through the experiment, it can obtain the micro-strip antenna with the gain of 3.84dBi and the circular polarization frequency band of 75MHz which meets the application of the ultra-high frequency radio frequency identification system in the coal mines.
Design of Burr Detection Based on Image Processing
Authors: Chen Xiaorong , Shi Gaohui , Xi Chuanli , Zhong Linshan , Wei Xiaoxiang , Zhang Kaikai
Published: July 2019

Traditional burr detection methods are increasingly unable to meet the requirements of deburring in terms of accuracy and efficiency. In this paper, machine vision is adopted. Firstly, the image of the workpiece is preprocessed, and appropriate edge detection operators are selected to detect the basic edge of the burr. Then, the closed burr edge is generated by detecting the slow changing area with the regional growth. Finally, the edge is judged to be burr by comparing the contour and other methods. Experiments show that this method has the advantages of fast, high efficiency and strong stability in the study of burr detection, and can meet the requirements of the project.
A vertical cavity surface emitting laser based on Fibonacci photon quasicrystal cavity
Authors: Liu Xiaolin , Sun Xiaohong
Published: July 2019

In this paper, a vertical cavity surface emitting laser (VCSEL) is designed based on Fibonacci photonic quasicrystal (FPQC) cavity. This laser uses a light source with a spectral center of 460 nm. Two different FPQC structures are designed and optimized to serve as the total reflection mirror (TRM) and the transmission mirror (TM) of the resonant cavity, respectively. Compared with the distributed Bragg reflection (DBR) cavity, the designed FPQC cavity laser has smaller far-field divergence angle and relative mode field area, as well as higher brightness.
Personalized Recommendation via Suppressing by Users and Items
Authors: Wang Can , Wang Kun , Wei Tao
Published: July 2019

An efficient recommendation system is fundamental to solve the problem of information overload in modern society. In physical dynamics, material diffusion based on binary networks has a wide range of applications in recommendation systems. However, material diffusion has the disadvantage of excessive diffusion and excessive attention to high-prevalence items. Most of the previous studies focused on reducing the popularity of the item. This paper suppresses the excessive diffusion between people and objects by simultaneously adjusting popular users and items. It evaluates the algorithm through two real datasets (Movielens and Netflix), which proves the method is superior to other algorithms in accuracy, diversity and novelty.
Research on Lost Circulation Risk Intelligent Identification and Processing System Based on CBR
Authors: Xiaorong Gao , Yingzhuo Xu
Published: July 2019

Due to the large number of complex and uncertain factors in the drilling process, it is very difficult to identify and deal with the risk of lost circulation by establishing an accurate mathematical model, and the existing intelligent methods are difficult to acquire or require large sample data. In view of the defects, an intelligent decision-making method based on case-based reasoning is proposed, and a software system for intelligent identification and processing of lost circulation risk is developed. In this system, the lost circulation cases of oil fields in the past are represented as case forms in the case base. The design idea of the case retrieval model is to design an improved similarity calculation model for different types of attributes, based on the traditional instance similarity calculation model, which can effectively solve the information uncertainty. The system was tested by field data and the results show that the lost circulation risk identification and processing method can meet the application requirements of the drilling site, and can effectively improve the intelligent level of lost circulation risk management.
Three-dimension Point Cloud Technology and Intelligent Extraction of Trace Evidence at the Scene of Crime
Authors: Liu Shuxia
Published: July 2019

Three-dimensional (3D) point cloud technology is a kind of high-tech for the extraction of trace evidence from crime scenes. It is also an artificial intelligence technology for criminal justice investigation and diagnosis with great development prospects. It is one of the frontier issues in the field of criminal science and technology research. The purpose of this paper is to explore and analyze how to use 3D point cloud technology to extract trace evidence of crime scenes on the basis of understanding 3D point cloud technology, and to discuss the intelligent features of 3D point cloud trace evidence extraction. The principle and characteristics of 3D point cloud technology are introduced and described by the method of comparison and example. According to the technical characteristics of laser scanning, the methods and steps of extracting trace evidence from crime scenes are designed, and the overall workflow is given. This paper analyzes the intellectualization of 3D point cloud technology for trace evidence extraction from the perspective of the fusion of technology and perception, and draws some conclusions through simple practical description. Research shows, trace evidence extraction based on 3D point cloud technology is the full embodiment of digitalization and intellectualization of crime scene investigation. Doing a good job in information collection, data sample database construction, human-computer interaction platform design, and the data and knowledge of crime scene diagnosis experience are the basis for the development of this intelligent technology. In addition, with the different characteristics of different crime scenes, the improvement and innovation of the 3D laser scanning method is also an important work in the future.
Visible Light Communications Relying on Cell-Free Amorphous Networks
Authors: Wen-yan Xu , Hong-yi Yu , Sen Yang
Published: July 2019

The user-centric architecture is the trend for constructing future networks. To improve user experience, visible light communication system adopts user-centric cooperative transmission technology, which breaks the traditional concept of network-centric. Generating user-centric cells for each user can make the best of network resources, which is of great significance in the 5G era with the design concept of small unit scenes. However, it is still in the initial stage, and the basic theories and key technologies need to be further studied. This paper expounds the new design concept, describes the characteristics and the forming process of user-centric virtual community centering on users, and introduces the key technologies of multi-user processing, channel estimation and network resource management combined with the unique features of visible light. This new mode of transmission can provide the user with the service of the network and improve the user’s peak rate and edge user performance.
Discussion on the development of mechanical and electrical integration of construction machinery in China
Authors: Meiying Hou
Published: July 2019

The rapid development of science and technology has changed the engineering application of the model, the backward technology and procedures such as microelectronics, information has been replaced by a variety of new technology, has realized the integration of mechanical products production and application, makes the product more safe and reliable, lower energy consumption amount, realized the high precision products and high quality control, the future will also toward miniaturization, greening, such as direction, product application is more efficient, convenient, and convenient people’s life, and provide technical support for the development of various industries. This paper discusses this problem in detail.
A power management circuit based on autonomous control
Authors: Cheng-ying Yang , Yong Chen
Published: July 2019

Based on the concept of external triggering and internal autonomous control, by using the semiconductor device with switching characteristics, using the function of capacitor voltage regulation and energy storage, and fully utilizing the charge and discharge function of the capacitor, the author introduces a new type of power management circuit. The circuit realizes the function of the device to independently control the power supply that is turned off when the storage, standby, etc. do not need to work. When the device needs to work, the power supply switch of the circuit is triggered by the external condition, and the power supply automatically supplies power to the device through the circuit. Therefore, the function of energy saving and energy saving of the device is realized, the battery life capability of the battery is improved, the loss of the power supply of the device is greatly reduced, and the technical problem that the battery of the current device is largely lost during idle and standby periods is solved, and the environmental protection and energy saving has Certain meaning.
Synchronized Vibration Transition of Three Exciters in Non-resonant Vibration System
Authors: Zhang Nan , Zhang Junling
Published: July 2019

The synchronized vibration transition has been proposed in the non-resonant vibration system with three exciters. Based on former man, the movement equations of self-synchronous vibration system with three rotors are replaced by differential equation of phase difference angle first, and the necessary conditions of synchronous movement for system are analyzed, stability and bifurcation of equilibrium points of vibration system are discussed. Firstly, dynamics model are established, differential equation of phase difference angle is deduced based on the dynamics equation of the vibration system. Then, the necessary conditions of synchronous movement are established, stability and bifurcation of equilibrium points of vibration system are discussed using Lyapunov theories. Finally, the effects of system parameters on synchronization stability about self-synchronous vibration system are investigated with numerical simulations.
Compressed sensing model for vibration signals of mechanical faults based on modulated wideband converters
Authors: Zhong Hua , Zuo Xiaobo , Dai Dongsheng , Liang Xiaolong
Published: July 2019

Based on Compressive Sampling, the Modulated Wideband Converter (MWC) sampling method can implement sampling at a rate lower than the required by Nyquist theory. This paper designs a spectrum reconstruction system, based on MWC, which can reconstruct the spectrum of Sparse-Frequency signal at the rate lower than Nyquist-Frequency, and verify through the simulation signals and the measured fault bearing vibration signals.
Text Tiling Text Segmentation Based on Hierarchical Dirichlet Process Model
Authors: Ye Wei , Gong Xiaogang , Zhang Quan , Ju Xiaoming
Published: July 2019

Text segmentation plays an extremely important role in many areas such as abstract extraction and information retrieval. Topic model is one of important methods in text segmentation. However, the current methods based on topic model generally rely on the manual setting of the number of topics. In order to improve the efficiency of text segmentation, this paper proposes a TextTiling text segmentation method based on Hierarchical Dirichlet process (HDP) model. Firstly, the method uses the HDP model to obtain a vector representation of the text in the topic space, which can also automatically generate the number of topics. Applying the theme vector to the TextTiling segmentation algorithm can implement text segmentation. The results show that the method can effectively improve the performance of text segmentation, and be free from manually set topics.
Research on Wear Status of Diesel Engine Cylinder Based on BP Neural Network and Instantaneous Speed
Authors: Qiao Xinyong , Gu Cheng
Published: July 2019

The instantaneous speed contains a large amount of diesel engine operating state information. This paper establishes the diesel engine dynamics model to obtain the instantaneous speed curve under different cylinder wear states, and extracts its four dimensionless parameters, then establishes the cylinder wear state model based on BP neural network using the simulated fault signal, and the actual vehicle test data is used to verify. The results show that the cylinder wear analysis model based on BP neural network can accurately determine the cylinder wear state.