bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Wireless Sensor Network MAC Protocol: NSMAC
Authors: Zhang Yaoyao , Jiang Lingyun 
Published: November 2019

Abstract
How to reduce energy consumption and improve the life cycle is one of the hot spot issues in current wireless sensor network research. Media Access Control (MAC) has an important impact on sensor network life cycle and performance. This paper proposes a new MAC protocol--NSMAC protocol. This protocol dynamically changes the length of the contention window and the size of the duty cycle based on the load on the network. It can effectively reduce energy consumption, improve network throughput capacity, and improve sleep time-delay in a multi-hop network environment when the network load is large. The experimental results also prove that this protocol has significant improvement in energy consumption, time-delay and throughput capacity compared to SMAC protocol and RCMAC protocol.
Spectrum Occupancy State Predictor Based on Recurrent Neural Network
Authors: Fan Rong , Guo Hesong , Di Lujie , Ling Xing 
Published: November 2019

Abstract
To cope with the scarcity of spectrum resources and to improve the efficiency of spectrum utilization, spectrum occupancy prediction (or named channel state prediction) technology has been addressed into cognitive radio (CR) in recent years. In the paper, we first address the issue how to model the primary user behaviour in CR. And based on the presented behaviour model, a recurrent neural network (RNN) is chosen to design a spectrum occupancy state predictor. By exploiting the learning capacity of recurrent neural network, it can predict the spectrum occupancy state of primary user behaviour. Meanwhile, in order to reveal the proposed predictor’s advantages, the spectrum occupancy state predictor based on RNN and another existed two spectrum occupancy state predictors are also adapted in the simulation section of the paper. Numerical simulation results illustrate the advantages of the proposed method.
Potential Energy Field based Pedestrian Behavior Model for Crowd Evacuation Simulation in Airport Terminal
Authors: Ting Yuan , Yi Liu 
Published: November 2019

Abstract
The crowd evacuation simulation in airport terminal is an important method to improve the efficiency of the emergency evacuation decision. Different from traditional pedestrian simulation, the evacuation simulation in airport terminal should fully consider the layout of the terminal building and the characteristics of passenger behavior. This paper proposes a pedestrian behavior model based on potential energy field. On the one hand, the spatial region is modeled by fine grid, so as to model the pedestrian’s body type, pose and decision in airport terminal more realistically; on the other hand, the potential energy field mechanism fully considers following factors’ influence on the pedestrian behavior, including the shortest path to the destination, obstacles, other pedestrians and sudden events. Based on the model, this paper simulates the evacuation process on a certain airport terminal, and evaluates the evacuation ability of the building. Based on the simulation of evacuation time under different number of people and different utilization of building space, the quantitative emergency measures and building optimization recommendations are given. This research can provide advance scientific guidance for pedestrian organization, terminal building design, and emergency plan.
Current situation of information literacy of regional college teachers and improvement strategies in the age of “Internet+”
Authors: Wang Lei 
Published: November 2019

Abstract
“Internet + higher education” provides a vital opportunity for educational reforms. How to integrate information technology with teaching practices, how to improve information literacy have become a challenge for college teachers. This paper discusses the definition and components of information literacy for college teachers, analyzes the current situation and defects of college teachers’ information literacy in the age of “Internet+”, and makes case studies on G College. On that basis, this paper proposes suggestions to improve college teachers’ information literacy in the “Internet+” age: on the individual level, teachers should rely on the Internet training community to seek progress in cooperation and interaction; on the organizational level, colleges should promote upgrading of the college teachers development center, and make full use of the Internet and big data technology to optimize the training mode; on the environment level, colleges should face “Internet+” positively and provide a supporting environment.
Application and Research of VR Technology in Art Design Teaching
Authors: Wang Qinghai , Zhe Zhang , Xing Yadan 
Published: November 2019

Abstract
In recent years, with the rapid development of science and technology, VR virtual reality technology is now applied in various fields, and this technology is gradually applied to art design teaching. VR virtual technology can construct a simulation learning environment, which enables students to have a comprehensive and systematic understanding of various courses of art design specialty, and cultivate students’ creativity and imagination. By analyzing the advantages of VR technology in teaching, this paper puts forward the teaching method of integrating VR virtual reality technology into classroom teaching, and explores the feasibility of applying SLOODLE platform to art design teaching, so that the platform can be widely used in art design teaching.
The Influence of Internet on College Education Management and Countermeasures
Authors: Chen Shengjun 
Published: November 2019

Abstract
The influence of network culture on college students is all-round. It provides a large amount of information resources for contemporary college students, and provides them with a new model of study, research and communication, and also has a negative impact on contemporary college students. On the one hand, the Internet brings the convenience of college students to study and entertainment; on the other hand, it also has a certain impact on the education management of college students. This paper analyzes the impact of the network on the education management of college students, and gives corresponding suggestions and countermeasures.
Research on the Transition from Financial Accounting to Management Accounting under the Background of Artificial Intelligence
Authors: Guo Xiaohui 
Published: November 2019

Abstract
With the rapid development of AI information technology in China, it has brought certain impact on the traditional training mode of accounting personnel in Higher Vocational colleges. Faced with the constant change of technical means, the boundaries of industry, organization and function are all changing. Under such circumstances, accounting profession must change itself. Therefore, the training mode of traditional accountants should gradually change to management accounting. Firstly, this paper analyses the influence of AI on accounting industry. This paper then analyses the problems faced by financial accounting in the era of artificial intelligence. At last, this paper analyses the measures of transforming financial accounting into management accounting.
A Realtime Algorithm for Distinguish Obstacle from Accessible Area in 3D Scene
Authors: Zhang Ye , Zhou Ziwei , Xu Liang 
Published: November 2019

Abstract
A learning algorithm based on Hidden Markov random field model is designed, and three-dimensional data is extracted, and the robot is used as an experimental platform. In the process of recognition, obstacle areas and feasible areas are distinguished by template matching, and the accessible areas and obstacle areas of the scene around the robot are obtained by classification results. According to the state of the robot itself, the position and direction vectors of the robot are calculated. The robot adjusts its attitude under the control of the output vector, so as to avoid obstacles and move to the target point. Finally, it is proved that the experiment has ideal real-time performance, so it has an extensive practical application foundation.
UAV cooperative attack and route planning based on DPSO algorithm
Authors: Tianhan Tan , Kun Wang , Qishuang Wang , Bo FU , Gang Wang , Yongsheng LI 
Published: November 2019

Abstract
For UAV cooperative attack and route planning problem, a cooperative attack allocation model is established in fully considering the attack cost and attack revenue. Considering the threat cost and path distance cost, a flight path planning model is also established. An improved particle swarm optimization algorithm called DPSO is proposed by discrete space mapping, which can reduce redundant search and speed up search. Based on the model and optimization algorithm, reasonable cooperative attack target assignment and route planning are worked out, and the optimal performance is achieved.
Design and Implementation of Movie Recommendation System Based on Naive Bayes
Authors: Shuxian Liu , Sen Fang 
Published: November 2019

Abstract
Today, with the rapid development of the Internet industry, the era of big data has arrived. What follows is that the surge in data volume has brought great challenges to people’s rapid and timely screening of useful information. Based on this highly realistic problem, the recommendation system that solves the user’s individual needs is born. In this paper, based on the theory of Naive Bayes, the MovieLens data set is used for testing. The user’s scoring data are used for similar analysis to generate the user’s similarity matrix, and the target user can be personalized. Compared with other algorithms, this paper has a good recommendation effect.
Curve Fitting of Raspberry Pi Car-Route Based on Baseline Least Squares Method
Authors: Shen Feihong , Zhang Hanfeng , Lin Kaichao , Zhang Tong , Guo Dongwei , Zhang Erhan 
Published: November 2019

Abstract
Curve fitting has a wide range of applications in engineering design, computer graphics, etc. In some case traditional least square methods can’ t use known conditions as fully as possible, so we introduce a notion named baseline. We firstly estimate a baseline and use the point to line distance as the parameter of the probability density as the weight value of the least square. The software we developed shows that our methods needs less running time and can makes better fitting consequence.
Research on safety helmet wearing YOLO-V3 detection technology improvement in mine environment
Authors: Fuchuan  , RongXin Wang 
Published: November 2019

Abstract
The existing AI object detection technology cannot meet the demand of safety helmet wearing detection accuracy in mine environment. This paper studies YOLO correlation algorithm, establishing an optimal model based on YOLO-V3, combines the deep residual network technology with the multi-scale convolution feature based on the YOLO-V3 detection algorithm, combines the multi-scale detection training and adjusts the loss function in the training process. The experimental results show that with satisfying the detection speed, safety helmet wearing detection accuracy in mine environment is significantly improved.
Intelligent Library System Based on RFID Technology
Authors: Zhou Donghua 
Published: November 2019

Abstract
Radio Frequency Identification (RFID) is a kind of automatic identification technology. It uses radio frequency to communicate two-way non-contact data, and uses radio frequency to read and write recording media (electronic tags or radio frequency cards) so as to achieve identification objectives and data transfer. It is considered as one of the most promising information technologies in the 21st century. In the field of Library management, it can improve the overall efficiency of libraries and reduce the cost of library management of mass books. In this way, libraries can put more funds and manpower into improving the quality of Library services.
Research on optimal control model of complex networks security risk
Authors: Li Jizhen , Ren Baofeng , Zhang Tiantian , Li Chaowei , Liu Zihao 
Published: November 2019

Abstract
To solve the problems such as the security risk control and the optimization of the complex networks, an optimal control model of complex networks security risk based on discrete glowworm swarm optimization with key strategy adjustment is proposed. The basic framework of this model is built based on four functional modules including detection and evaluation, strategy selection, control optimization and performance feedback. The optimal evaluation criterions of the security control strategy are constituted of factors such as control cost, benefit reward and negative effect. The discrete glowworm swarm optimization algorithm with key strategy ad-justment is proposed to search for the optimal control strategy of complex network security risk. The concept of control parameter is introduced, whose feedback and adjustment make the optimal control model get evolution-ary. Finally, the model and the algorithm are tested for network security risk optimal control in the Nearest-Neighbor coupled with network, Erdos-Renyi random graph network, Watts-Strogatz small world network and Ba-rabasi-Albert power law network, separately. The availability of the model and the superiority of the algorithm are validated and the effect of the change for the attack strategy to the security risk optimal control model is analyzed by simulations.
Detection of Android malicious applications based on APIs
Authors: Jiang Xu , Mao Baolei , Guan Jun 
Published: November 2019

Abstract
Machine learning technology is widely used to detect Android malware, among which the selection of features is particularly important. Compared with the permission applied, the APIs invoked by applications can better reflect the behavior of the application. Therefore, many researches choose APIs as the features of machine learning classification algorithm to detect Android malware. Generally, researchers simply select APIs as features, rather than focus on how to select features more beneficial for detection. This paper proposes an Android malware detection method based on APIs frequent pattern selection and use Relief and particle swarm optimization algorithm to jointly select feature subset for detection.
No-overflowing Magnification Scheme in Redundant CORDIC algorithm and its implementation in FPGA
Authors: Jing Zhang 
Published: November 2019

Abstract
In this paper, normalization and magnification methods to maintain the calculating accuracy of CORDIC algorithm for small amplitude inputs are discussed, especially the overflowing boundaries are analyzed through mathematical deduction and the correctness has been proven by simulation. Finally, the FPGA implementations of different methods are conducted, which shows that the proposed magnification factor chosen scheme has an effective reduction on hardware resources consumption compared with the conventional normalization method.
3D SOM Initialization Pattern Dictionary Algorithm Based on FCM Clustering
Authors: Dong Ruihua , Zhang Xueyan , Li Hongsong 
Published: November 2019

Abstract
Aiming at the problem that the three-dimensional SOM reconstruction effect of the traditional pattern dictionary initialization algorithm is sensitive to the input order of the pattern, a three-dimensional SOM initialization mode dictionary algorithm based on FCM clustering is proposed. Calculate the mean square error of the training vector set and use the FCM algorithm to aggregate the resulting mean square differences into three categories. The average values are arranged in ascending order, and a certain pattern is extracted in the training vector at the same interval to form an initial pattern dictionary. The experimental results show that the 3D SOM initialization mode dictionary algorithm based on FCM clustering reduces the search time, increases the source matching degree, and improves the overall performance of the 3D SOM algorithm.
A Survey of Surface Reconstruction Techniques for Line Structured Light Systems
Authors: Changwei Wang , Ruiyin Tang , Jing Zhang 
Published: November 2019

Abstract
Reverse engineering has been widely used in industrial production, and surface reconstruction technology is the most important part of reverse engineering. Line structure measurement is a non-contact surface measurement method with high precision, low destructiveness, high data acquisition efficiency and strong anti-interference. This paper focuses on the measurement principle of line structured light, system calibration, strip center extraction and point cloud data processing and surface reconstruction. Finally, the existing surface reconstruction techniques that are widely used are summarized.
Optimization of Dairy Distribution Path Based on Genetic Algorithm
Authors: Liu Haidong 
Published: November 2019

Abstract
The distribution of dairy products is a key factor affecting the distribution cost, delivery time and service level of dairy products. In order to improve the efficiency and reduce the costs, it is necessary to optimize the distribution path of the dairy products. In this paper, the distribution of a local dairy enterprise is taken as the research object. On the basis of analyzing the existing distribution path, the mathematical model of the distribution path is constructed, and the genetic algorithm is designed. Then the optimized distribution path is obtained through programming and solving by MATLAB. By comparing before and after optimization, it is found that after the optimization, the total distribution distance is shortened, and the transportation cost and fixed cost are reduced. In addition, the penalty cost is avoided. Therefore, a reasonable distribution path is of great significance for the enterprises to improve the efficiency, reduce the costs, shorten the delivery time and other indicators.
Research on the recognition technology of human relationship in face image based on deep learning
Authors: Cheng Yunli 
Published: November 2019

Abstract
Face images contain rich and complex information, and similar genes are directly expressed as facial resemblance. In this paper, based on the theoretical background of biology and aiming at the wider application of artificial intelligence in the field of face image analysis, deep learning based recognition of the kinship of people in face images is studied in depth.
Kinship recognition is a new and challenging research. In order to recognize the kinship between characters from face images, this paper defines a new correlation feature to represent the correlation between two characters. Based on the idea of multi-layer self-encoder to input and reconstruct the target, and combined with the powerful feature extraction ability of deep convolutional neural network, this paper designs a new deep convolutional self-coding neural network, and the correlation feature is the activation value of the deep hidden layer of this deep neural network. The deep convolutional self-coding neural network USES back propagation algorithm in a supervised way. With the deepening of the network hierarchy, the identity features of representative characters are extracted from face images step by step, and the identity features of a pair of characters are fused into the associated features that represent the relationship between them. Based on deep learning, the associated features extracted from face images can effectively identify a given character relationship.
An Effective Method for Dynamic Global Optimal Scheduling of RGV Based on Probability Function
Authors: Ge Xueren , Huang Heyaojing 
Published: November 2019

Abstract
In this study, an effective dynamic scheduling strategy based on quasi-global optimizing search method is designed to plan the working sequence of RGV. By using ‘0-1’ variable, the working state of CNC is simplified and the whole processing procedure could be simulated by Matlab. Also, probability function is applied to decide the scheduling sequences, thus avoiding local optimal solutions. Then, the dynamic global optimizing scheduling strategy is completed. Besides, the efficiency of the whole system is calculated and the corresponding results are compared with local optimizing scheduling. This dynamic scheduling strategy could improve the efficiency of the whole system during the processing materials.
Internal Model Controller Applied to LCL-type Grid-connected Inverters in Weak Grid
Authors: Wang Kai , Huang Jingtao , Zhang Shengguo , Li Yumei , Wu Fei 
Published: November 2019

Abstract
Power grid in remote areas may show the feature of weak grid with time-variable impedance. Robustness of control of grid connected inverter (GCI) to grid impedance is one of the key technologies. For grid connected inverters with voltage feed-forward and time delay, IMC (Internal Model Controller) is used so that the adaptability to the grid impedance is improved. Detailed IMC and its parameter design method are provided, theoretical analysis and simulation results verify that IMC has robustness of grid and LCL impedance.
A node-centric network congestion estimation method considering average spatio-temporal scale
Authors: Wen Guoyi , Huang Ning , Zhu Juxing 
Published: November 2019

Abstract
Congestion estimation is a significant issue to analyse and mitigate network congestion. Many researchers have used various estimation methods based on the load data of roads in a single moment. However, congestion is always node-centric and formed around intersections gradually. An estimation method to describe the average congestion around intersections or nodes is also valuable and needed to discover the most congested parts but is absent according to our literature researches. In this paper, we propose a node-centric network congestion method, which can evaluate the average spatio-temporal congestion scale around nodes. Based on the widely used simulation platform NetLogo, the simulation results have proved the reasonability of the proposed estimation method by the stable values of the fixed traffic network intersections, which becomes increasingly stable as time goes on, and it is found that the node-centric values calculated by our estimation method is more stable than the values by the edge-centric because of its superiority. This node-centric network congestion estimation method considering average spatio-temporal scale will be widely used because of its simplicity and universality.
Integration of Vibration Acceleration Signal Based on LabVIEW
Authors: Qihe Liu 
Published: November 2019

Abstract
In vibration measurement, the measurement of acceleration is more convenient than that of displacement, but the observation of vibration displacement is more intuitive than that of acceleration. In order to convert acceleration signal into displacement, the traditional method is time domain integration, but there is trend term problem in time domain integration, while there is no trend term problem in frequency domain integration. Firstly, the algorithm of time domain integration and frequency domain integration is analyzed. Based on this algorithm, a program is programmed based on Labview 2015. The simulation results of time domain integration and frequency domain integration are compared by using this program. The results show that frequency domain integration can recover waveform better. In practical measurement and analysis, frequency domain integration is better than time domain integration.
Practical Research on Mechatronics Technology in Intelligent Manufacturing
Authors: Wang Dawei 
Published: November 2019

Abstract
This paper analyzes the related content of mechatronics technology, combines the current development status of intelligent manufacturing and the practice of mechatronics technology in intelligent manufacturing, and improves people’s practical content in intelligent manufacturing by studying the practical content of mechatronics technology in intelligent manufacturing. The cognitive ability of mechatronics technology promotes the stable development of the industry economy.