bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distribution Network Planning Method Based on Hybrid Genetic Algorithm
Authors: Shao Yunfeng , Sun Yuanming , Wang Yajing , Ma Zhongjing , Liu Yongqiang , Zhao Yang 
Published: November 2020

Abstract
Facing the discrete, multi-constrained, non-linear, multi-objective combination optimization problem of distribution network grid planning, some traditional heuristic algorithms such as genetic algorithms sometimes fall into local optimum. This paper proposes a distribution network planning method based on hybrid genetic algorithm The algorithm consists of two stages. In the first stage, the genetic algorithm is used to obtain the initial planning scheme. In the second stage, the initial planning scheme obtained in the first stage is used to form the planned route set. The improved minimum spanning tree method is used to obtain the final planning scheme. In order to make full use of the effective information obtained in the first stage, this paper proposes a transmission line classification method to assess the importance of the transmission line, provide guidance for the second stage, and improve the search efficiency and accuracy. The algorithm solves the problem that heuristic algorithms such as genetic algorithm often fall into local optimization to a certain extent, and the problem of slow convergence when the minimum spanning tree algorithm has a large number of lines to be planned.
Application of Rank Likelihood Ratio Scanning Method in Multiple Mean Changes in Long Memory Time Series with Heavy Tail
Authors: Xu Qiongyao , Xi Li 
Published: November 2020

Abstract
In this paper, a rank-likelihood ratio scanning method for long memory time series with heavy tail is proposed to solve the problem that when likelihood ratio scanning method is used to estimate the mean change points in the long memory time series with heavy tail, the estimation accuracy decreases rapidly with the decrease of the heavy tail index. Numerical simulation and analysis of real data demonstrate the effectiveness and practicability of the rank-likelihood ratio scanning method.
A Real-time Face Tracking and Recognition System Based on SeetaFace
Authors: Yilihamu Dilizhati , Tuerxun Palidan , Dawut Abdusalam , Hamdulla Askar 
Published: November 2020

Abstract
A real-time face tracking and recognition system is constructed based on Seetaface, and it is proposed to use Gamma correction to reduce the impact of illumination changes on the detection and recognition results. First, the system has face detection function, then by using OpenCV to get the image in front of the camera, the system completes the function of real-time face tracking, users can also upload local images to make face comparison. If a stranger’s face is detected, the system can collect information and train it. The system achieves multiple face tracking as well as recognition. Through the analysis and evaluation on public datasets. The improved face tracking and recognition system has a satisfactory accuracy and performance.
Fingertip-Specific Mobile Interaction Through Camera-Based Fingertip Identification
Authors: Chen Liang , Chen Dongyi , Tan Zhizhong 
Published: November 2020

Abstract
In this paper, we propose to utilize camera-based fingertip identification to enable fingertip-specific mobile interaction without hand occlusion. The core idea of the proposed fingertip identification method is to utilize features, whether innate or got-up, on a fingertip to recognize its identity rather than utilize hand information to infer the fingertip’s identity. A fighter game prototype is presented to demonstrate the interaction idea. Possible ways to realize fingertip identification and how to utilize fingertip identification to enable richer interactions on mobile devices are also discussed.
Speedup and Password Recovery for Encrypted WinRAR3 without Encrypting Filename on GPUs
Authors: Ji Qingbing , Yin Hao 
Published: November 2020

Abstract
The encryption mode of WinRAR3 which does not encrypt the file name uses encryption and compression, the password recovery complexity is high. The existing cracking systems crack on a single CPU or GPU platform. Because the decryption algorithm is slow on the CPU platform, while the decompression algorithm is slow on the GPU platform, the overall performance of the cracking algorithm is not high. This paper studies the mode of CPU and GPU collaborative computing, and proposes an efficient cracking method of encrypted WinRAR3 without encrypting filename. By using the CPU + GPU pipeline cooperation method, the waiting time in the calculation is reduced, and the performance of the algorithm is improved; by using the magic number matching method of compressed files, the decompression calculation can be effectively reduced. The experimental results show that the speed of the cracking algorithm proposed by this paper for 8-digit passwords is 24423/s, which is 2.3 times as fast as before.
Identification of Friction Parameters of Robot Joints Based on Energy Consumption Model
Authors: Lv Ningbo , Zhu Xuejun , Ding Yunpeng , Meng Xiangxiu 
Published: November 2020

Abstract
In order to solve the problem that the joint friction torque value of industrial robots is difficult to be measured in practice, the joint friction identification method based on the energy model is used to indirectly obtain the friction model parameters by measuring the energy consumption value. According to the energy model and the measured robot energy value, the genetic algorithm is used to realize the parameter identification of the Stribeck friction model of joint friction. The results of the two identification methods based on friction torque identification and energy model identification are compared. The simulation results show that the error ratio of all the friction model parameters obtained by the two identification methods is less than 8%, and the error target value of the two identification results is less than 0.1%, which can effectively identify the relevant friction parameters. By designing an experimental scheme, the different speeds and corresponding energy consumption data of the IRB140 robot when joint 1 operates at a constant speed in a specified time are measured, and the Stribeck friction model parameters of the IRB140 robot’s joint 1 are identified by the proposed method.
Some Certiticateless Short Signature Schemes of Security Analysis and Simple Improvement
Authors: Hu Xiaoming , Chen Fangshu , Tan Wenan , Ma Chuang 
Published: November 2020

Abstract
Certificateless signature (CLS) scheme as an important filed of cryptography has a wide range of applications, such as information security, network security and so on. But, in the CLS scheme, the public key of the signer is generated directly by the signer itself without the verification of the trusted third part, so the public key easily is replaced by the malicious users which lead to the forgeability of the signature. In this paper, we show three CLS schemes proposed recently which have high efficient with short signature are not secure and the malicious user can forge a signature by replacing the public key of the signer. In the same, we also present three improved CLS schemes with simple modifying based on the original CLS schemes respectively. We also make a simple security analysis and efficiency analysis on the three improved CLS schemes. The analysis shows that the improved schemes not only can overcome the security problem but also almost have the same efficiency with the original CLS schemes.
Research on a New Attribute Encryption Anonymous Algorithm in Cloud Computing Environment
Authors: Zha Xin 
Published: November 2020

Abstract
The attribute encryption anonymous model is used to encrypt data and protect anonymity in cloud computing environment, so as to realize attribute encryption and privacy protection in cloud computing environment. In order to improve the self-adaptability and accurate control of data encryption in cloud computing environment, an anonymous data encryption algorithm based on hyperbolic cyclic mapping is proposed. The priority list control model of adaptive privacy protection for cloud data is constructed. The load balancing control and encryption key design of anonymous big data with hyperbolic cyclic mapping are implemented by using bilinear differential control protocol. The hyperbolic differential equation control and adaptive weighting method are used to construct the key function for anonymous encryption of cloud computing data. The time window and privacy protection protocol of attribute encryption anonymous control is optimized by slot allocation. The encryption anonymous algorithm is improved. Simulation results show that the adaptive equalization performance of attribute anonymous encryption in cloud computing environment is better, the ability of anti-attack is better, and the recall rate of data is better than the traditional method.
Research on Electric Vehicle Charging Scheduling Strategy Based on Graph Model
Authors: Wang Zhen , Xu Aidong , Zhang Yunan , Wang Qianru , Xu Xinchen , Jiang Yixin , Wen Hong 
Published: November 2020

Abstract
In recent years, electric vehicles (EVs) have gradually become the development trend of the future automotive industry due to its advantages of zero emission, low noise, and high efficiency. At this stage, a large number of EV freely charging without guidance will bring many negative effects on the operation of urban traffic and power distribution systems. Therefore, how to correctly guide the vehicle to charge efficiently has become an urgent problem to be solved. Starting from economic factors, time factors, and user characteristics, this paper proposes an electric vehicle charging recommendation optimization model based on graph calculation. The graph model is generated according to the geographic location of the charging station, and the shortest path algorithm and charging scheduling strategy, which is used to recommend EV to users. The charging station with the smallest comprehensive cost within a certain range of the car.
Terminal Security Configuration Optimization under Edge Computing
Authors: Wang Qianru , Xu Aidong , Zhang Yunan , Cao Minggui , Song Jianfang , Jiang Yixin , Wen Hong 
Published: November 2020

Abstract
It is an important task of system security management to configure terminal security policy reasonably in edge computing (EC) to implement necessary security protection for terminals and EC system. Therefore, this paper analyses the security goals and requirements of terminal access for multi-service EC systems under the power grid, conducts terminal security risk assessment based on the AHP algorithm, and proposes an edge computing platform terminal security configuration optimization strategy, creatively using the OS-ELM algorithm. A framework for cloud training and edge-side online learning to meet the real-time and lightweight communication needs of edge platforms.
Application of neural network to predict mutations in proteins from influenza A viruses - A review of our approaches with implication for predicting mutations in coronaviruses
Authors: Yan Shaomin , Wu Guang 
Published: November 2020

Abstract
The recent outbreak of COVID-19 pandemic is attributed to cross-species transmission of new coronavirus from bats to humans through unknown intermediate hosts, and the essence of the transmission is closely related to the mutations in coronaviruses. Furthermore, the effort to develop the vaccines against coronaviruses always faces the challenge of unexpected mutations in coronaviruses. In fact, it is very difficult to predict the mutations in any virus and bacterium, although mutations are a process of evolution. Over years, we have been applied the neural network to predict the mutations in proteins from influenza A viruses in comparison with the predictions using logistic regression. Our results are encouraging, but our approaches still need the improvements, for example, to upgrade to using machine learning and artificial intelligence instead of neural network. In this review, we summarize the rationales of neural network modelling, its strength and weakness, with the hope that we can apply the improved methods to predict the mutations in coronaviruses, thus to explore the origin of SARS-CoV-2, to find its intermediate host, and eventually to predict its mutations.
Research on Sponge Landscape Design of Primary School Campus Based on BIM Technology——Take Hefei Experimental School as an example
Authors: Tieqiao Xiao , Shaojie Zhang , Ziyu Zhao , Zijun Xia , Jianghui Guo , Chengyong Zhang , Yanuo Wang 
Published: November 2020

Abstract
With my country’s vigorous advancement of the construction of sponge cities, the research on the sponge landscape design of primary school campuses has become a hot spot. This paper takes Hefei Experimental School as an example, through the investigation of the current situation of the school landscape, using BIM technology to assist modelling, summarizes the shortcomings of the campus landscape and proposes a sponge landscape design strategy. With Revit and Vectorworks2019 as the main tools and platforms, under the support of the whole process of BIM technology, according to the current situation of the primary school campus and the behaviour characteristics of the primary school students, a design plan for the sponge landscape of Hefei Experimental School is proposed, showing that BIM technology is fully used in the sponge landscape design of the primary school campus, and put forward deficiencies and prospects.
Design of offline transfer management software base on QR code
Authors: Cong Lihu , He Weixin 
Published: November 2020

Abstract
With the development of our army’s informatization and actual combat, the transfer of ordnance has become more frequent, and higher requirements have been placed on the efficiency, accuracy and security of data recording during the transfer. At present, the data management of our military ordnance allocation still uses manual methods. This method has the disadvantages of inconvenient storage of transfer slips, handwriting errors, and information leakage during the flow. At the same time, staff query and statistical transfer data are inconvenient and inaccurate. This design research uses database technology to manage the transfer data to overcome the current shortcomings in the management of ordnance transfer data. The research uses QR code technology to realize the exchange of transfer data, and solves the problem of reading the transfer data and lowering the accuracy of entry. This system uses C # language for development and design in Visual Studio2015 software. The data is stored in the SQL server database. The QR code technology is used to develop and design a transfer management software based on two-dimensional bar code to exchange offline data. By operating the software, operators can realize the exchange of transfer data, query and statistics of historical transfer data, and at the same time can ensure efficiency, accuracy and security.
Research and Application on Smart Courtyard Monitoring System
Authors: Li Zhen-hua , Li He-he , Liu Bo-fang 
Published: November 2020

Abstract
Residential safety has always been a basic need for people’s lives. In the vast suburbs and villages of China, quantities of courtyard houses are distributed, and the level of security monitoring is related to the people’s security and happiness. This study takes the characteristics of the human body with a large aspect ratio into account. By improving the structure of the Faster-RCNN network, a method for enhancing human body features is designed to enhance the network’s ability to recognize the human body, and covers various human postures such as standing and lying down, and eventually improves the accuracy of the original human body recognition by 7%. In addition, this study designs and deploys a complete set of real-time monitoring system, which continuously saves images when detecting human intrusion, and sends alarm messages to the user’s mobile phone WeChat in real time, which meets the real-time and adds convenience. The actual deployment shows that the system can find the target within 120 milliseconds when the intruder enters the sight and send out alarm messages to meet the realtime design requirements.
Research on Application of Ant Colony Algorithm Based on Multi-sensor Image Fuzzy Fusion in Image Recognition
Authors: Liu Chenyu 
Published: November 2020

Abstract
In the current rapidly developing society, image recognition technology is currently an important means that can provide a full range of dynamic data. It plays an important role in economics, politics and other fields. Fuzzy image fusion algorithms have opened up to solve these problems in image recognition. Based on the current wide application of image recognition, this paper studies the research of multi-sensor image fuzzy fusion algorithm in the application of high-definition image recognition. Aiming at the characteristics of infrared and visible image fusion, an infrared-visible image fusion algorithm based on non-down sampling transformation and hybrid particle swarm algorithm is proposed. For low-frequency sub-images, an improved weighted average method based on area average is used for neighborhood fusion. For high-frequency sub-images, a hybrid particle swarm optimization algorithm is used to select the threshold, and the neighborhood algorithm based on average gradient selection is used for fusion. This algorithm can effectively improve the fusion effect of fused images. The experimental research results show that combining the characteristics of gradient intensity and phase consistency, the characteristic method of compressing the information while retaining important information, which is convenient for real-time processing, is used for related research on sensor image fusion.
Channel Mismatch Speaker Verification Based on Deep Learning and PLDA
Authors: Li Pengqi , Li Guanyu , Han Jiao , Zhi Tiankai , Wang Di 
Published: November 2020

Abstract
At present, speaker recognition technology is developing continuously, but in real world, existing speaker recognition algorithms are generally disturbed by channel factors. With the increase of current data volume, neural network has also become a key technology for speaker recognition. This paper introduction a speaker recognition method based on supervised training and a channel compensation algorithm. The experimental results show that this method combined with channel compensation algorithm can remove the influence of channel noise and has a good speaker recognition effect. The experimental results show that the combination of x-vector and PLDA channel compensation algorithm can obtain better recognition rate and ensure the robustness of the algorithm.
Research on multi vehicle tracking based on TLD optimization algorithm
Authors: Wang Chao , Huang Lei , Li Zhiyuan 
Published: November 2020

Abstract
With the increasing complexity of traffic conditions, the research on multi tracking technology of vehicle targets has become a hot topic. In this paper, a multi vehicle tracking algorithm based on TLD optimization algorithm is proposed, including TLD optimization algorithm of detection module and KCF algorithm of tracking module. The experimental results show that the proposed algorithm has small time delay in multi vehicle target tracking, and it can track multiple targets stably and meet the performance requirements.
DRNN: Deep Residual Neural Network for Heart Disease Prediction
Authors: Xiao Nianhao , Zou Yuanchen , Yin Yaguang , Liu Peishun , Tang Ruichun 
Published: November 2020

Abstract
Heart disease is one of the major diseases threatening human health. This paper proposed a novel deep neural network model to predict heart disease based on routine clinical data. We adapt the deep residual structure to discover a novel Deep Residual Neural Network (DRNN). In order to verify the effectiveness of DRNN, we performed experiments on Heart Disease UCI. The accuracy reached 95%, which is better than the traditional machine learning methods among Random Forest 83%, Decision Tree 68%, Logistic Regression 87%, KNN 60%, Native Bayes 80%.
Research on Computer Test Paper Generation Algorithm Based on Gene Expression Programming
Authors: Wenyan Yang 
Published: November 2020

Abstract
This article analyzes the common classifications of computer test paper algorithms. This article includes random method, backtracking method, genetic algorithm, random location search method, ant colony algorithm, gene expression algorithm, etc. The author obtains the expected calculated values by studying the technologies of setting control parameters, creating initial populations, calculating individual fitness, optimizing preservation strategies, performing genetic operations, and generating new populations. The author’s purpose is to improve the application effect of the computer test paper algorithm and the practicability of the information in the question bank.
Research on Underground Remote Control Detonation System
Authors: Hong-peng Chi 
Published: November 2020

Abstract
In order to meet the technical requirements for unmanned mining of underground metal mines and overcome the key technologies of unmanned blasting, a wireless network-based underground remote control detonation system was studied. The research content includes the software and hardware of the underground and surface initiation control unit and the initiation control process, the communication realization method of the underground and surface initiation control terminal, the remote wireless initiation network security encryption technology, and the system security design. Under the premise of ensuring safety, the requirements of underground remote control blasting are realized, which is of great significance to the development of underground unmanned blasting technology.
Analysis of spatial interaction vitality based on high-speed railway network and highway network
Authors: Jia Hui-di , Li Qian 
Published: November 2020

Abstract
This paper applies spatial interaction model theory to analyse the impact of transportation network infrastructure construction on the city. 36 cities in Chinese high-speed railways network and 72 cities in Chinese highway networks are selected, and the interactive vitality of cities is calculated and analysed from the perspective of the two networks. The spatial interaction vitality of some cities on two networks is different. Cities like Beijing, Shanghai and Zhengzhou perform well on both networks, while the remote areas such as Kuerle and Lasa has low values, indicating the urban spatial interaction vitality is related to the construction of transportation network infrastructure and is consistent with the actual situation.
Thermal behavior of C32 carbon nanoparticles in a nitrogen atmosphere
Authors: Barbin N M , Yakupova L V , Terent’ev D I , Kuanyshev V T 
Published: November 2020

Abstract
Using the method of computer thermodynamic modeling, the behavior of carbon nanoparticles is studied C32 when heated in nitrogen atmosphere at pressure 105 Pa. The modeling consisted in a complete thermodynamic analysis of the system using the TERRA software package. Experiment temperature range – from 273 to 3373 К. A graph of the carbon balance in the system is built C32-N2, the ongoing physical and chemical processes are described, divided into four classes. The equilibrium constants of reactions with the allocation of temperature ranges are calculated and graphs of the dependence of the equilibrium constants of reactions on temperature are given.