bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Computer Virtual Reality Technology in Design
Authors: Xie Hui , Wei Li , Li Peng 
Published: July 2020

Abstract
With the continuous development of technology, the design of the environment can be simulated by computer technology. The virtual reality (VR) technology can be used to take the real world as a three-dimensional space, three-dimensional space can be designed to simulate the actual environment. In this paper, virtual reality technology is applied to design, and design is divided into two fields, namely landscape design and scene lighting rendering. We study characteristics of virtual reality technology and framework of virtual reality technology, at the same time, we define the concept of light and the concept of landscape in design, and analyze the problem of lighting rendering and the problem of landscape design. From the perspective of landscape design, we discuss the difficulties of virtual reality-landscape design, and further analyze the landscape design level and multi environment elements display based on virtual reality technology, and propose a feasible virtual reality-landscape design method; from the perspective of light rendering, the principle of lighting tracking algorithm can be analysised, the realized method is used for lighting rendering, the game engine is used as the rendering engine, MAYA and Photoshop software are used as the main rendering techniques of virtual reality, therefore, the real-time rendering of landscape’s surrounding environment is realized.
Research On Key Technologies Of Equipment Support Intelligent System
Authors: Chen Jian , Wang Yan , Jiang Xuepeng 
Published: July 2020

Abstract
In view of the rapid development of information technology, the construction requirements of intelligent equipment support system are proposed based on the results of intelligent construction. On the basis of putting forward the logical framework of the intelligent equipment support system, this paper analyzes its technical framework. To provide theoretical support for the construction of the intelligent support system, analyzes its key technologies, especially the concepts of GIS visualization technology, Internet of things technology deep learning technology and big data technology, and their functions in the intelligent equipment support system.
An Intelligent Learning Method and System for Cybersecurity Threat Detection
Authors: Tao Yuan , Hu Wei , Li Moyan 
Published: July 2020

Abstract
To protect information system and data effectively is the core of cybersecurity. At present, most technologies are based on known static protection strategies. Through the cybersecurity threat is dynamic, so it is necessary to detect the cybersecurity in advance, so as to update the protection strategy in time, which means the dynamic and active defence. The intelligent learning method and system for cybersecurity threat detection is proposed. And the immune selection of cybersecurity threat detection is proposed to select the appropriate threshold, and the knowledge map of cybersecurity threat detection are constructed from suspicious time, security management centre, security computing environment, security area boundary and security communication network. The threshold is built by immune selection, and the cybersecurity intelligent detection can be achieved by knowledge map. The architecture of intelligent detection system is proposed. So that the cybersecurity threat detection can be dynamic and intelligent, and the performance of cybersecurity threat detection and analysis can be greatly improved.
Cooperative Training Video Surveillance Technology under the Edge Computing
Authors: Lian Dong , Xu Aidong , Chen Songlin , Xu Xinchen , Jiang Yixin , Hong Wen 
Published: July 2020

Abstract
Edge computing offsets the computing power devices to close the terminals, which avoids delay caused by long-distance transmission and network congestion under the cloud computing support scenarios. This paper presents the video surveillance model under the edge computing. A novel cooperative training edge computing system for the image processing is proposed to realize the shortest training and processing time. The simulation of the novel system is performed under Tensorflow software and the results verify the advantages of the new system.
Analysis of the Topological Structure of the Convolution Neural Network Model RESNET
Authors: Shang Tao , Song Ying 
Published: July 2020

Abstract
With the advent of the era of big data and the development of artificial neural network, a large number of different neural network models have come out. In the field of image recognition, the application proportion of convolutional neural network model is very high, and the different structure levels of the same convolutional neural network model are also very different, and the recognition effect in solving different problems is not the same. Taking the application of image recognition as an example, this paper analyzes and compares the influence of different topological structures in RESNET model on recognition accuracy. Through the experimental comparison and analysis, it is concluded that the structure of shortcut_6 in RESNET convolutional neural network is the turning point. When the length of shortcut is less than 6, the recognition efficiency is on the rising trend with the deepening of the network. When it is equal to 6, the recognition efficiency is basically fixed, and when it exceeds 6, the recognition accuracy is reduced.
The Exploration of Progressive Experimental Training Teaching Mode Based on O2O
Authors: Hu Yahui , Lv Shujun , Fang Qiqing 
Published: July 2020

Abstract
In view of the current situation that the experimental teaching hours are few and the task is heavy, the offline progressive experimental teaching, online micro class teaching and online progressive practical training breakthrough teaching mode are adopted, the experimental teaching contents with progressive logical relationship are designed, the difficult and in-depth practical training tasks are allocated, and the trainees’ practical training results are mastered openly, fairly and fairly in real time on the training platform It is proved that this method can improve the quality of practical teaching.
Intelligent Decision Algorithm of Nutrients based on Big Data
Authors: Chen Yungui , Fan Hongbin 
Published: July 2020

Abstract
With the improvement of living standard, People’s requirements are also improving for children’s dietary nutrition, which fully illustrates the attention of people for healthy development of children. Children’s dietary nutrition should not be solely based on advice of expert, because every child needs different dietary nutrients. In this paper, a large data computing framework MapReduce is studied, which fully considers the eating habits of children, the balance of dietary types and the interaction of food. A intelligent decision algorithm based on large data is proposed for the best children’s dietary nutritional components. The algorithm is divided into two steps, the fuzzy GK algorithm is realized by the MapReduce framework, and the main nutrients are selected effectively; these nutrients are taken as parameters and used for multivariate linear regression model, so as to realize the rational allocation of nutrients. We design the algorithm, introduce the details of the algorithm in detail, and continuously optimize relevant parameters to produce a better dietary nutrition composition scheme. In the process of experiment, we analyze the performance of decision algorithm by testing examples, and make a lot of comparisons with the existing decision analysis algorithms. After a large number of arguments, it is proved that the algorithm is effective.
Research on Plant Lighting Driver Control Strategy Based on LED Spectral Characteristics
Authors: Fei Jingwei , Xu Yuzhen 
Published: July 2020

Abstract
To realize the continuous adjustment of the light quality ratio of LED plant lighting power supply, a plant lighting driver control strategy based on the spectral characteristics is studied in this paper. First of all, the spectral mathematical model of monochromatic LED chip is established. Secondly, the mathematical model of the number of photons generated by LED the driving current is further studied and then, a new driver control strategy about the pant lighting is proposed based on the model of the number of LED photons. At last, a step-down circuit built by RT8471 chip is used as the LED driver power supply to verify the correctness of the new driver control strategy in this paper. Different color LED chips of Cree and Philips Lumileds companies are used as the circuit loads. It shows that the errors values between the results from the experiments and the theoretical model calculations of the number of LED photons are all less than 5%. So, the new plant lighting driver control strategy proposed in this paper is feasibility and has certain theoretical guiding significance and engineering value.
Main Content and Implementation Path of College Sports Informatization Construction
Authors: Yu Qiaoyan , Pan Xiaofei 
Published: July 2020

Abstract
Information technology not only has a revolutionary influence on the development of physical education, but also plays a strategic role in the development of physical education. Based on the current situation and significance of sports informatization development in colleges and universities in China, the author makes an in-depth analysis of informatization innovation of sports teaching and research, optimization and management of sports training, physical fitness monitoring and evaluation, cloud platform construction of extracurricular sports activities and competitions, scientific material selection and talent cultivation of young athletes, and intelligent management of campus competitions. From the aspects of the development goal of college sports informatization, the establishment of information platform, the building of characteristic team, the utilization ability of sports teachers’ information and the utilization of information achievements, this paper puts forward the implementation path of college sports informatization construction, aim to provide theoretical support and practical guidance for college sports informatization construction and development in China.
Quantitative Analysis of Protein and Polysaccharide in Lilium Lanzhou Based on Near Infrared Spectroscopy
Authors: Lian Xiaoqin , Tang Shenmiao , Wu Jingzhu , Wu Yelan , Chen Qun 
Published: July 2020

Abstract
In order to quickly detect the nutritional components of Lilium Lanzhou, a national geographical indication product, a quantitative analysis model of protein and polysaccharide was established by near infrared spectroscopy and chemometrics. A total of 81 samples of Lilium Lanzhou were collected. SG smoothing + first derivative + MSc spectral preprocessing method was selected to establish the spectral model of protein and polysaccharide quantitative detection of Lilium Lanzhou Based on partial least square method. The correlation coefficient (R2) of protein model is 0.844, RMSEP is 0.268, the correlation coefficient (R2) of polysaccharide model is 0.715, RMSEP is 0.273. The experimental results show that NIRS technology is feasible for the rapid detection of key quality of Lilium Lanzhou, which is expected to provide a new method for the rapid evaluation of key nutritional quality of Lilium Lanzhou.
A Low-Complexity 2D-DOA Estimation Algorithm with Massive URA
Authors: Lu Zhou , Li Baobao , Lai Xin , Zeng Haowei 
Published: July 2020

Abstract
Conventional Direction of Arrival (DOA) estimation algorithms, such as Multiple Signal Classification (MUSIC), Root-MUSIC, and Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithms, are difficult to apply to large-scale antenna arrays. Because these algorithms not only require a lot of snapshots of the received data, but also the hardware equipment cannot meet the algorithm complexity requirements. This paper presents a low-complexity DOA estimation algorithm for large-scale Uniform Rectangle Array (URA). We first obtain coarse initial DOA estimates via the two-dimensional fast Fourier transform and then search for the accurate estimates within a very small region. The proposed algorithm only needs one snapshot of the received data to obtain the estimation accuracy of the traditional algorithm. The algorithm also has good robustness, and it can estimate DOA accurately even under extremely low signal-to-noise ratio and many sources. Theoretical results and numerical simulations are provided to assess the superiority of the proposed algorithm.
Extracting and Reconstructing Human Behavior Video Feature in High Voltage Exclusion Zone
Authors: Chen Jun , Sun Jian , Rao Yuanliang , Rao Xiaoyong 
Published: July 2020

Abstract
A method is presented to the discrimination, extraction and reconstruction of human behavior in the area forbidden by high voltage, in particular, a method of scene reproduction of the accident scene when a high-voltage area endangers the power equipment injury or causes a personal property accident due to human behavior. To validate this method, an experiment was conducted on a small lake with high voltage transmission line over through. The Server video after the proposed method can be used to recognize human behavior, and transmission efficiency has been improved up to 35%.
Development and Allometry Patterns of Fine Scale Fish Larvae at Low Temperature
Authors: Yang Guiqiang , Wang Zhanquan , He Jie , Li Wentong , Yuan Ding 
Published: July 2020

Abstract
Ecological experiment was conducted to study the allometry of fine scale fish yolk-sac larvae and its significance in adaptation in early life stage. The results indicated organs such as feeding, breathing and swimming of larvae in the yolk sac stage are rapidly differentiated, and all key organs are allomorphic. In all parts of the body, the head length and tail fin length are growing at an allometric speed, the trunk is growing at a slow speed, and the body height is isokinetic growth; in the head organs, the rostrum length and head length are growing at a positive allometric speed; in the swimming organs, tail fin length is positive allometric growth; yolk sac width and yolk sac height are positive allometry consumption. The fast development of feeding, breathing, swimming and other organs in yolk-sac larvae of fine scale fish, increases larval survival ability at the early stage in the shortest possible time, and there were important ecological significance to adapt the complex and changing external environment.
Innovative Applications and Development of AI for Emergency Services
Authors: Kong Depeng , Lv Shangyi , Gu Weisi , Li Jiusheng , Dai Shaoqing 
Published: July 2020

Abstract
With the outbreak of 2019-ncov (NCP) virus, many AI technologies, equipment and platforms are emerging in the main battlefield of anti-epidemic, such as patrol UVA, 360 disinfection robot, infrared intelligent temperature measuring equipment, throat swab robot, whole lung quantitative analysis technology, medical robot, etc. In the future, AI will continue to play an important role not only in virus type identification, abnormal pathology detection, optimization of treatment methods, prediction of the flow of people, etc., but also in emergency services such as plugging loopholes, making up for shortcomings, strengthening weaknesses. It is suggested to integrate AI into the construction of the emergency system, strengthen the institutional guarantee and make a top-level design, build a coordination platform for AI emergency response, promote the research of key technologies in the field of emergency services and solve the problem of cross-platform coupling in order to build an efficient, scientific and intelligent emergency management system as soon as possible.
A Markov Chain Model of Air Quality Index: Modelling and Simulation
Authors: Gao Yannan 
Published: July 2020

Abstract
This paper discusses a Markov chain model of discrete-time and discrete state and applies this model to detect the stochastic performance of AQI time series. First, it covers the set-up of the model, makes useful definitions like Markov property, transition matrix, steady-state distribution vector and present the maximum likelihood estimation method. Then an empirical research is performed using true data of some place with transition matrix estimated. At last, simulated data are generated to be a comparison of true data.
Modeling of Lighting Load in Office and Living Area Based on Multi-region
Authors: Jin Feng , Kang Li , Hu Biwu 
Published: July 2020

Abstract
Driven by the third round of industrial revolution, the Power supply-distribution network-load connection has become more and more tight, and the development of microgrid has become an inevitable trend. It can supplement the shortage of large power grids in response to fragmentation load. The load characteristics under the power grid also play an extremely important role in the distributed system. Studying the load in the microgrid not only has a positive effect on the construction and planning of the microgrid, but also has a guiding role on the economic dispatch of the microgrid. The paper investigates the lighting situation in the office and living area, and divides the office and living area into multiple areas for detailed modeling. Firstly, the working time, building condition and lighting equipment in different areas were studied. Secondly, the probability model of the lighting load was established. Finally, Monte Carlo was used to establish the multi-area office and living park lighting load model.
A Five-Dimensional Grid Multi-wing Butterfly Chaotic System and Its Circuit Simulation
Authors: Huang Yun 
Published: July 2020

Abstract
Based on the two-wing butterfly chaotic system, through adding two first-order differential equations with the piecewise linear function, a five-dimensional grid multi-wing butterfly chaotic system is presented. Through numerical simulation, it is studied for the gird multi-wing butterfly chaotic attractors, the Lyapunov exponent spectrum and the bifurcation diagram of the system. At the end, an electronic circuit is designed to carry out the system. The circuit experimental results are consistent with the results of numerical simulation, which confirm the availability and feasibility of this approach.
Explore on Application of Two-Dimensional Hydraulics Model in Flood Impact Assessment of the New Century Bridge
Authors: Liu Yanhong , Jin Zhiwei , Sun Xiaowei 
Published: July 2020

Abstract
The New Century Bridge will be built across Xiliao River. The construction of the bridge increases the complexity of water flow condition of Xiliao River. By establishing the mathematical model and adopting the form of finite element mesh dissection, the distribution of the maximum depth of flood water, the maximum flow velocity and the highest water level for flood in front of the dam and bridge are simulated before and after the bridge built to judge flow pattern effectively. By establishing a numerical model of flow pattern, which plays a decisive role for bridge abutment protective, depth of the pile foundation and pile caps, and has the greatest impact for next structure optimization of the bridge.
Research on the Evolutionary Path of COVID-19
Authors: Dong Yunyuan , Guo Wei , Ren Qiong 
Published: July 2020

Abstract
World Health Organization reported that a novel coronavirus (COVID-19) was identified as the causative virus of pneumonia of unknown etiology first reported by Chinese authorities on 7 January, 2020. Our objectives were to discover the evolutionary path and evolutionary characteristics of COVID-19. As time goes on, the evolution of COVID-19 has shown a variety of trends. In this paper, we proposed a method of constructing the evolutionary network of COVID-19 in chronological order, and analysed the evolutionary tree and haplotype of COVID-19.
Revisiting Cloud Migration: Strategies and Methods
Authors: Wang Zhixiao , Yan Wenyao , Wang Wendong 
Published: July 2020

Abstract
Cloud computing attracts users with its advantage of unlimited resource supply where resources can be elastically expanded on demand and balanced-load at the same time. This means that the application in the cloud environment should run in the way of elastic expansion cluster. At present, most of the elastic expansion and load balancing technologies provided by IaaS level are oriented to virtual machines (VM), with little consideration of application level, which does not fundamentally meet the needs of users. Based on this, starting from the motivation of cloud migration, we first analyse the cloud migration technology from three aspects: migration object, migration means and migration objectives, then explore the cloud migration criteria and four cloud migration strategies at the application level in the cloud environment, and point out that cloud migration should be optimized and maintained in terms of elastic expansion, load balancing, security, etc.
The Thermal Error Modeling with Deep Transfer Learning
Authors: Li Peiwen , Lou Ping , Yan Junwei , Liu Nianyun 
Published: July 2020

Abstract
Thermal error of CNC machine tools is one of the main factors affecting the machining accuracy. The data-driven method for thermal error modeling is an effective and efficient, but they have some flaws, such as poor accuracy, bad robustness, and etc. because of having no quite enough data set and imbalanced data set. In this paper, a new method based on transfer learning for thermal error modeling is presented for solving the issue of imbalanced data set. The dataset of monitoring the temperature field of the machine tools includes monitoring data of three kinds of operating conditions, namely stopping, idling, and machining. When the fewer idling data is used to train a model, the larger stopping data are introduced as train aids. Transfer learning is adopted to fully learn the common characteristics of the two different working conditions, which can effectively solve the problem of imbalanced dataset. The experimental results prove that our method have better performance than other methods trained only with limited idling data.
Research on Methods for Complex Chinese Entity Recognition
Authors: Mengxing Ren , Lei Ma , Ye Tian , Hongchen Qin 
Published: July 2020

Abstract
Named entity recognition(NER), as a key task of natural language processing, is of great significance in relational capture, information retrieval, knowledge mapping, machine translation, and question and answer systems. In the neural network-based Chinese named entity recognition method, the vectorized word representation only maps words into one vector, which cannot represent the above problem, In order to solve these problems, this paper proposes a Cascading model based on the character vectorization, This method uses BERT to represent the ambiguity of the word. In the agile BIGRU model, the initial entity recall is completed to increase the entity recall rate. Then the output of this layer is input into the high-level bilstm model of self attention mechanism to further filter and improve the accuracy of the final recognition. Finally, the CRF is used to complete the output of the final recognition result. Experiments show that the model can effectively improve the accuracy, accuracy and recall rate of complex Chinese entity recognition. The f1 value has increased by about 2% overall.