bluuebunny/crossref_metadata_2025_split huggingface dataset:
Edge to Cloud End to End Solution of Visual Based Gun Detection
Authors: Yao Qi , Tan Weijun , Liu Jingfeng , Qi Delong 
Published: October 2020

Abstract
There are over a half million cases of gun violence globally every year. State of the art video surveillance requires human to watch the video footage to monitor gun violence. In this paper, we present an AI based edge to cloud solution appropriate for smart surveillance and control. Firstly, we build the key training dataset by harvesting the publicly available videos and movies. Then we design three deep convolution neural networks (CNNs) models, there are two models running on the edge device, which is a video camera, and the third one runs on the cloud. By distributing these three models into edge and cloud, we are able to achieve a good gun detection system that can be deployed in real life.
Range Query in Blockchain-based Data Sharing Model for Electronic Medical Records
Authors: Li Jingwen , Dun Wenlong 
Published: October 2020

Abstract
The data sharing of electronic medical records (EMRs) has great positive significance for research on disease and epidemic prevention. Recently, blockchain-based EMRs storing and sharing schemes have brought many benefits. Nevertheless, the existing medical data sharing solutions cannot fully meet the query requirements in multi-user scenarios where data users with different identities have different needs for data usage. In this paper, we propose a block construction method for storing EMRs. We combine the characteristics of the Merkle tree and prefix dictionary tree in the block to reduce the time consumption of queries in the block. Besides, the block header is identified by four attributes, namely hospital ID, Department ID, disease type, and time period. According to the query conditions, the block where the requested data is located is quickly found. In the blockchain-based data sharing model of EMRs, data requesters with different identities can make combined queries with multiple conditions according to their own needs, and then the block and transactions in the block are located accurately. In conclusion, we are the first to build the block based on disease types and our model supports more flexible combined queries with multiple conditions.
Linear Regression from Uncertain Data and its Applications to Housing Price Prediction
Authors: Gao Shijian 
Published: October 2020

Abstract
Most of the figures we get in our daily life are imprecise, a person’s height is an approximation. Uncertain data is usually represented by many values around it in a limited region with probability density function. This paper first defines the uncertain data, and then proposes a linear regression algorithm based on the uncertain data. In order to verify the rationality, correctness and effectiveness of the algorithm, many experiments were carried out.
Improved Metric Factorization Recommendation Algorithm Based on Social Networks and Implicit Feedback
Authors: Wang Bilin , Han Jiaxin , Cuan Ying 
Published: October 2020

Abstract
The Metric Factorization algorithm solves the problem of the suboptimal solution caused by the inner product of the traditional matrix factorization algorithm. Although the basic metric factorization model has achieved good results in rating prediction and item ranking tasks, the algorithm ignores the role of implicit feedback and user social information. Considering the social relationship and implicit feedback information between users, this paper improves the basic metric factor Factorization algorithm, and proposes an improved metric factorization recommendation algorithm based on social networks and implicit feedback. We do rating prediction tasks on the Filmtrust and Last.FM datasets, experimental results show that the improved algorithm can further improve the accuracy of prediction.
Topological Data Analysis In Text Classification Based On Word Embedding And TF-IDF
Authors: Wen Xiaoyang 
Published: October 2020

Abstract
As a fresh and rapidly-developing method in data science, topological data analysis (TDA) offers a new set of ways to look at data and derive features out of high-dimensional models with topological and geometric tools. In this paper, the author briefly introduces the topological concepts that are involved several researches, then compares and examines different methods of extraction of topological features from the texts. The result shows that these topological tools provide some additional features of the document that are not detected by using the original methods. In the experiment, adding these topological features to the usual text mining tools results in improvement of prediction accuracy (as much as 5%). However, as expected, these topological features alone are not sufficient to classify text documents. Future experiments and discussions need to be conducted to determine whether these methods could be combined to make better classifications.
Research Progress and Prospects of Single-Layer 2D Materials Xenes
Authors: Nie Chen 
Published: October 2020

Abstract
Xenes, as a series of single-layer two-dimensional (2D) materials, present emerging properties in biological, electronics, medical and other relevant fields. This review introduces seven main Xenes materials (silicene, phosphorene, borophene, antimonene, stanene, germanene and bimetallene) demonstrating higher conductivity and flexibility and describes their current research works and new findings. Besides, current challenges such as those in stability and quality are concluded, and a prospective view on development of 2D Xenes materials in the future is brought out.
Failure Analysis of Computer Backplane Burning Down
Authors: Zhang Jiyuan 
Published: October 2020

Abstract
The bottom plate burned out during the computer power-on detection process. This was analyzed. Firstly, the fault tree of the bottom plate was built and analyzed. Then a fault tree is established for the problem of capacitor short-circuit failure, and finally the possibility of capacitor problem is eliminated. After analysis, it is concluded that the cause of the burning of the bottom plate is the presence of foreign objects in the chassis. In the process of random vibration, foreign objects may be short-circuited to the power supply, resulting in a short circuit of the bottom plate, which may cause burnout. The power supply has an overcurrent protection mechanism, but the protection mechanism is that the power supply reduces the voltage output in the event of an overcurrent, so even if a short circuit occurs, the power supply will still output current, resulting in a burnout failure.
The Application of Logistic Model in COVID-19
Authors: Wang Zhongyu , Shi Yuanhang , Xie Jiakun 
Published: October 2020

Abstract
COVID-19 began to break out in China in early 2020, characterized by rapid transmission and a high fatality rate. In the face of the outbreak, it is particularly important and urgent to predict the number of infections in each region. Even now, some countries are still in the early stages of an outbreak. The existing traditional mechanistic models such as SIR have a high demand for data. For example, parameters such as exit rate need a large number of data to ensure the accuracy of the model; otherwise, the prediction effect is poor, while the models or algorithms related to artificial intelligence have a higher demand for data. Moreover, both of them have a large amount of work to solve, which has poor effect on the prediction of early epidemic prevention and control. The problem of epidemic situation prediction in the absence of data urgently needs to be solved. After data preprocessing, this paper used the Logistic model (the growth retardation model) to predict the number of infections of China. Meanwhile, error analysis and stability analysis were carried out, and the data of Italy were used for checking the universality of the model. The results show that the Logistic model is easy to be solved, has good stability and accuracy, and is suitable for early prediction of COVID-19.
Guide Circle-based Improved Ant Colony Algorithm
Authors: Huang Chen , Gao Zhengzhong , Chen Junjun , Zhou Luyao , Lu Zhanming , Qu Qifei 
Published: October 2020

Abstract
In order to solve the path planning problem of autonomous mobile robots in an unknown environment, the traditional ant colony algorithm and the guide circle algorithm were combined, and an improved ant colony algorithm based on the guide circle was proposed. In terms of local path planning, the guide circle algorithm is used to avoid obstacles, which effectively solved the problem of unstable path planning ability in narrow spaces. In the aspect of global path planning, the concept of safety index circle is introduced according to the length between robot and obstacle, and partial heuristic information of ant colony algorithm is improved, so as to avoid the traditional ant colony algorithm falling into local optimal. It is verified by simulation experiments that the improved algorithm has a stronger global search capability, faster convergence speed, and enhanced path planning capability.
A method for single frame detection of infrared dim small target in complex background
Authors: Xu Yongli , Wang Weihua 
Published: October 2020

Abstract
In order to solve the problem of high false alarm rate caused by strong disturbance (the ground objects, uncertain strong noise) in complex background, we propose a novel algorithm based on density peaks searching and improved region growing. Initially, density peaks searching is employed to select the candidate targets quickly; then, improved region growing with introducing the relative local contrast and the local gray average is used to extract the features of candidate targets; finally, an adaptive threshold is applied to extract real targets. Experimental results on two real sequences show that the proposed algorithm has a better effectiveness against existing algorithms.
Research on the Economic Effect of “Polar Silk Road” on China and Arctic Countries Based on GTAP Model
Authors: Guan Xiaoguang , Li Zhenfu , Chen Zhuo , Ding Chaojun 
Published: October 2020

Abstract
The accelerated melting of sea ice in the Arctic makes the potential value of the Arctic increasingly significant. The exploitation and utilization of the “Polar Silk Road” has important influence on the economic cooperation between China and the Arctic countries along the “Polar Silk Road”. This paper uses GTAP model to simulate and analyze the economic and trade impact of the “Polar Silk Road” on the Arctic countries along the “Polar Silk Road” and China. The results show that the construction of “Polar Silk Road” will have a positive impact on the import and export trade between China and Canada, USA and some Nordic countries, and the GDP and trade structure within the region. China should seize the opportunity to expand the width of “Polar Silk Road” and and further promote the construction of the “Polar Silk Road”.
An Improved Adaptive Window Stereo Matching Algorithm
Authors: Qiao Wenbo , Xu Yuanping , Zhang Chaolong , Xu Zhijie , Huang Jian , Xie Pan , Lu Jun 
Published: October 2020

Abstract
In order to solve the problem that the existing adaptive window stereo matching algorithms have insufficient feature extraction in low-texture regions, resulting in low matching accuracy. An adaptive window stereo matching algorithm based on the gradient is proposed. Firstly, the Sobel operator is used to extract the gradient value of each pixel in the image. Then, each pixel is divided into high, medium and low texture regions according to the gradient value. Next, different arm length thresholds are assigned to different region pixels, and matching windows are generated dynamically according to arm length and color threshold. Finally, the pixels closer to the center of the window are given higher weights by generating windows several times. It solves the problem that the stereo matching algorithm can not select a matching window dynamically. Experimental results on Middlebury dataset show that the proposed method improves the matching accuracy by 5.5% compared with the latest adaptive window stereo matching algorithm.
An Algorithm Combining the Branch-Cut Method and Rhombus Phase Unwrapping Algorithm
Authors: Jiang Han , Xu Yuanping , Zhang Chaolong , Xu Zhijie , Huang Jian , Tan Hailong , Lu Jun 
Published: October 2020

Abstract
In order to solve the problem that the wrapped phase cannot be unwrapped effectively, this paper proposes an algorithm combining the branch-cut method and rhombus phase unwrapping algorithm for unwrap phase. The algorithm combines the advantages of the two methods, at first, the Goldstein’s branch-cut method is used to find the residual points in the wrapping phase, then the rhombus phase unwrapping algorithm is used to unwrap the non-residual area phase, finally the phase of the residual area is obtained by using the cubic spline interpolation method, so as to ensure that the phase of each pixel can be unwrapped smoothly. The simulation results verify the feasibility and effectiveness of the algorithm, the combined phase unwrapping algorithm can effectively reduce the line and island phenomenon.
A Summary of analysis and application research on the spatial distribution of POI data based on urban service industry
Authors: Zhu Li , Wang Lu , Li Xiaoling , Zhang Lei 
Published: October 2020

Abstract
Data mining and data analysis based on POI data of urban service industry has gradually become the research trend of urban spatial layout. In the present study, many scholars use different research methods to analyze the agglomeration characteristics and development trend of urban service industry from multiple perspectives. This article combines POI data analysis methods and application fields to summarize the relevant research of urban service industry POI data analysis and application and summarizes the representative research methods of POI data analysis, and compares the characteristics of each method, and then the development trend of POI data mining, analysis and application in urban service industry is prospected.
Research on Key Technologies of Smart Logistics Dynamic Positioning Based on NB-IOT
Authors: Liao Yuanyuan , Liu Shuxian 
Published: October 2020

Abstract
This study takes the large-scale freight yard in The free trade zone of Xinjiang and cargo reloading in international railway transit as the prototype scene, and takes NB-IoT network as the core to realize dynamic positioning electronic tags for people, vehicles and containers through Beidou positioning module and RTK technology.Finally, the positioning information will be transmitted to the command center through integrated NB-IoT communication function, and the three-dimensional simulation of the freight yard will be realized by using Threejs to build the intelligent logistics cargo dynamic real-time positioning system with the advantages of low power consumption, low cost, wide and deep coverage, massive connectivity, and precise positioning, so as to realize the role of reducing cost and improving logistics efficiency in intelligent logistics.
Research on Electricity Information Acquisition System Based on Sample Data Mining Model
Authors: Zhongkui Dang , Lei Fu 
Published: October 2020

Abstract
In power user information collection and detection, power companies generally have a variety of different detection needs, or need to solve the problem while having additional requirements for certain aspects. Therefore, the SVM classification technology is used in the paper to carry out more detailed pattern recognition of power consumption characteristics for small-scale users or users with major suspicions. Moreover, given the imbalance of the abnormal electricity detection data set, a comprehensive processing model of unbalanced samples is constructed. Meanwhile, the differential evolution algorithm is applied to complete the SVM parameter optimization, which not only solves the problem that the SVM classification performance is significantly affected by the parameters, but also ensures the operating efficiency of the integrated classification model.
The Integral Points On A Class Of Elliptic Curve
Authors: Yang Lixing 
Published: October 2020

Abstract
It is very important to study the integer points of various elliptic curves in elementary number theory. On the one hand, as an important research object in elementary number theory, elliptic curve plays an indispensable role in the development of mathematics. On the other hand, as an important research object in elementary number theory, elliptic curve has practical application in many aspects. So far, there are some conclusions about elliptic curve y
2 = x
3 + a
x + b, a, b ∈ Z. In 1987, D. Zagier proposed the integer points problem on y
2 = x
3 - 27x + 62, which is important for studying the arithmetic and geometric properties of elliptic curves. In 2009, Zhu H L and Chen J H used the methods of P-adic analysis and algebraic number theory to solve the problem of the integer points on y
2 = x
3 - 27x + 62. In 2010, Wu H M used the elementary methods to find all the integral points of elliptic curves y
2 = x
3 - 27x - 62. In 2015, Li Y Z and Cui B J used the elementary methods to solve the problem of the integer points on y
2 = x
3 - 21x - 90. In 2016, Guo J used the elementary methods to solve the problem of the integer points on y
2 = x
3 + 27x + 62. In 2017, Guo J used the elementary method proves that y
2 = x
3 - 21x + 90 has no integer points. Up to now, there is no relevant conclusions on the integral points of elliptic curves y
2 = x
3 + 19x - 46, which is the subject of this paper. By using congruence and Legendre Symbol, it can be proved that elliptic curve y
2 = x
3 + 19x - 46 has only one integer point: (x, y) = (2,0).
Vehicle Detection: A Review
Authors: Meng Chaochao , Bao Hong , Ma Yan 
Published: October 2020

Abstract
Vehicle detection based computer vision is the essential algorithm in autonomous driving, aims at identifying which locating vehicles by digital images or videos. The basic idea of vehicle detection is detecting “blocks,” which reflects the position of the vehicle in images or videos. Besides, this paper discusses 3D vehicle detection algorithms based on stereo perception, which originated from advanced planar vehicle detection perception. Finally, this paper summarizes the vehicle detection algorithms in recent years in terms of the difference between the feature extraction approach and the perceived results. It proposes hypotheses for further in-depth study of the vehicle detection algorithms.
Research on signal processing technology in φ-OTDR system based on non-uniform sampling
Authors: Chen Jin , Qiao Xiao Rui , Gao Zhi 
Published: October 2020

Abstract
In the optical cable communication system, because the optical cable often has a long span, the sampling frequency is limited when φ-OTDR is used as the monitoring method. When the system adopts the traditional uniform sampling method, the sampling frequency must be greater than 2 times of the signal frequency, otherwise spectrum aliasing will occur. How to get the frequency information of high frequency signal with lower sampling frequency, and how to solve the problem that the highest response frequency of the system decreases when the sensing distance of φ-OTDR system is extended, is a major technical problem for the monitoring of optical cable communication system. In this paper, through the analysis of the common methods of broadening the response frequency band of Φ-OTDR system, a non-uniform sampling method is selected to analyze the optimal value of some parameters of Φ-OTDR system based on non-uniform sampling, and a method of using the mean square change value to locate the vibration source is proposed. The simulation results show that this method is suitable for monitoring vibration signals with sparse characteristics in frequency domain, and the location SNR is better than the traditional method, and has good anti noise performance.
Research on Power Load Forecast Based on Ceemdan Optimization Algorithm
Authors: Lilong Huang , Chao Zhang , Ping Yu 
Published: October 2020

Abstract
With the continuous development of the power industry, power data has become more complex. However, it is difficult for common shallow neural networks to fully extract the original load data features, thus greatly limiting the load prediction accuracy. Therefore, given the advantages of CEEMDAN, a prediction model based on CEEMDAN is proposed in the paper, the advantages of which are verified by simulation analysis of measured power data. Experiments prove that the algorithm proposed in the paper has higher prediction accuracy, which effectively overcomes the EMD modal aliasing problem, and the decomposition process is more complete, so that the prediction accuracy of the subsequent prediction model is improved.
Research on Jet Quenching with Isolated-Photon+Jet correlation in Pb-Pb and p-p collisions at collision energy 5.02 TeV
Authors: Li Zhaobo , Zhang Boxuan , Wang Haomin 
Published: October 2020

Abstract
This paper is dedicated on the phenomenon of jet quenching and its quantitative description at

S

N
N

=
5.02
T
e
V

. Data from collision events with an isolated leading photon,

p

T

γ

>
40
G
e
V

, associate jets with

p

T

j
e
t

>
30
G
e
V

, are plotted as a function of centrality; result is then matched to reference function in p-p events at the same level of energy to infer some model for parton energy loss in PbPb collisions. The main motivation for this paper is to overcome the difficulties of comparing the theoretical models and experimental data, which are linked with a hypothetical equation for energy loss.
Exponential Cubic B-spline Collocation Method for Solving the One Dimensional Wave Equation Subject to an Integral Conservation Condition
Authors: Wu Beibei , Deng Wenchao 
Published: October 2020

Abstract
In this paper, a collocation method is presented based on the exponential B-spline functions for the numerical solution of the one-dimensional wave equation subject to an integral conservation condition. The wave equation is fully-discretized by using the exponential cubic B-spline collocation for spatial discretization and the finite difference method for the time discretization. The difference scheme is analyzed to be unconditionally stable. The results of a numerical experiment show the stability and efficiency of the proposed method.
Research on Response Characteristics of Hydraulic Gate Subjected to Non-contact Underwater Explosion Load
Authors: Yang Zhuoyi , Sun Xingquan , Song Lei , Wang Hui , Yu Fulin 
Published: October 2020

Abstract
In this paper, the response characteristics of deep-hole planar steel gates under the separate induction of bubble pulsating load are studied. Through the large-scale finite element simulation software ABAQUS, using the explicit dynamic finite element analysis method, the contact surface of the gate and the water is taken into account by the fluid-solid coupling algorithm. When the water level is constant, the gate is subjected to explosion and the impact of the generated bubble impact on the gate structure and its anti-explosion ability are analyzed. The equivalent stress, displacement, and equivalent plastic strain of the gate under six different cases were simulated. Then, the effect of bubble pulsating load on the stress characteristics of the gate and the anti-explosion ability of the gate were summarized.