bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of GA-DA-Elman Neural Network Algorithm to Urban Air Quality Evaluation
Authors: Liu Haiyan , Geng Xuan 
Published: March 2020

Abstract
In order to improve the accuracy of air quality assessment, this paper presents an Elman neural network model based on dragonfly genetic algorithm fusion optimization. This model used genetic algorithm to optimize the weight and threshold of Elman neural network, introduced dragonfly algorithm in the process of searching for the optimal chromosome set, and used the best dragonfly decoded to replace the worst chromosome, thus forming an improved GA-DA-Elman neural network algorithm. According to the data from the atmospheric environment monitoring of shanghai, the air quality evaluation models of Elman neural network and GA-Elman neural network were established and compared with GA-DA-Elman neural network. The results show that the GA-DA-Elman air quality evaluation model has the highest accuracy (95%), and the error control stability is optimal.
Research on the Method of Context Modeling Based on Ontology —— a Case Study of Tea Sales
Authors: Mao Zhanzhan 
Published: March 2020

Abstract
With the raise of the Belt and Road strategy and the development of ubiquitous computing, the cross-platform context data coming from the wireless network,mobile computing and sensor network is increasing rapidly. How to shield the distribution and heterogeneity of context information so that users and their context information can be understood by computers has become a hot topic in current research. This paper takes tea sales as the research object. By building an ontology-based context model, this paper explores the effectiveness of the modeling method in solving semantic interaction and information fusion, and then promotes the organic integration of cross-platform and cross-industry scenario information in the new era .
Analysis of crowd flow characteristics based on multi-space scale and multi-source data fusion
Authors: Zhao Rongyong , Wang Yan , Liu Qiong , Dong Daheng , Li Cuiling , Ma Yunlong 
Published: March 2020

Abstract
In the big data background, multi-source data fusion provides a very effective means for researchers to extract hidden and valuable information and knowledge from many heterogeneous data sources. Large-scale crowd movement is a complex process with big size of data coming from several sources such as safety risks of crowding and trampling in public places in the possible form of subways, railway stations, airports, tourist attractions, or large-scale exhibitions. The analysis of crowd flow characteristics among these high risk areas has also become a major research hotspot. Based on the multi-space scale concept and the available data source information, this paper proposes a technical framework of crowd flow characteristics analysis. Finally, a case study of crowd flow characteristics analysis is implemented to validate this technical freamwork. This study can provide a effective theoretical support and security warning for the public management department.
The Application of Time, Location and Narrative Elements in Information Graphic Design--Taking the Information Sorting on the Development Process of the Honeysuckle Pattern as an Example
Authors: Liu Jiahui , Yu Jinhua 
Published: March 2020

Abstract
The Honeysuckle pattern is a decorative pattern of plants, which is formed by the mutual influence and interaction between Chinese and Western cultures. It is a traditional plant pattern that was introduced into China along with the Silk Road and Buddhist art. Its formation promoted the development of plant patterns in China, brought positive impact on the historical changes of China’s decorative patterns, and has also contributed a lot to China’s brilliant and splendid decorative pattern art. This paper aims to explore the development process of Honeysuckle pattern from the following three expression elements and perspective of information graphic design: time, location and narration. It combines traditional graphic information with modern information graphic design to explore the cultural value and charm behind this classic pattern, thus trying to make information graphic design more possible.
PPP project life cycle renegotiation trigger event identification
Authors: Mu Zhaorong , Gao Tian 
Published: March 2020

Abstract
This paper analyzes the obstacles of PPP project contract implementation and PPP related contract content, finds out the uncertain events in the whole life cycle of PPP project, and further summarizes and filters it to get the renegotiation trigger event. Through literature review and case analysis, the causes of renegotiation trigger events were confirmed and their impacts were analyzed. Finally, based on the compensation of the contract status and the supplement of the contract status, the renegotiation control mechanism and the post-event problem supervision are proposed.
A new Cghd I gene with negative regulation on the synthesis of chaetoglobosin A
Authors: Jiang Cheng , Song Jinzhu , Zhang Junzheng 
Published: March 2020

Abstract
Chaetoglobosins have wide application prospect, but the low yields make it not widely used. The aim of this study was to obtain high-yielding strains and to find the genes regulating the synthesis of chaetoglobosins. A strain with yield increased to 115% was obtained through inserting a short-DNA randomly into the genome of Chaetomium globosum by agrobacterium. At the same time, inverse PCR was used to determine the insertion position of T-DNA. A new gene Cghd I with negative regulation on the synthesis of chaetoglobosin A was found, indicating that the detectable random insertability mutation technique established in this paper can be used to obtain high yield strains and find regulatory genes.
Chimeric-antigen receptor T (CAR-T) cell therapy for solid tumor
Authors: Ling Hao 
Published: March 2020

Abstract
Chimeric-antigen receptor T (CAR-T) cell therapy has been researched in the clinical. However, CAR-T cell therapy for solid tumor is faced with lots of challenges such as cytokine storm, how to find the specific antigen and limitation of microenvironment of tumor. In this review, we will discuss the research of CAR-T cell therapy for solid tumors of digestive system, and possible solutions and future direction.
The influence of inclusive finance on the income gap between urban and rural residents
Authors: Wu Binghui , Li Chenlu , Duan Tingting , Miao Wenlong 
Published: March 2020

Abstract
On the basis of China’s dual structure of urban and rural economy, this paper constructs the inclusive financial index, which contains eight sub-indexes coming from the demand and supply of financial service. And then we analyse the influence of inclusive finance on the income gap between urban and rural residents using the panel data model. The results show that (1) a negative correlation is found between the developmental level of inclusive finance and the urban-rural income gap; (2) under the influence of inclusive finance, the acceleration of economic growth narrows the income gap between urban and rural areas; and (3) the increase of government expenditure causes the income gap between urban and rural areas owing to the characteristic of financial expenditure structure.
Comparison and Analysis of Simulation methods for TSN Performance
Authors: Xie Dong , Li Jiang , Gao Huisheng 
Published: March 2020

Abstract
Network simulation method is one of the important methods to study the performance of TSN . However, different methods have different characteristics in the study of TSN. Therefore, before carrying out the research on the performance of TSN, it is particularly important for researchers to choose the appropriate simulation method. In this paper, firstly, the main network simulation methods are summarized, and the requirements of simulation methods for TSN performance research are analyzed. Finally, the adaptability of different network simulation methods for TSN performance research is obtained. The evaluation results provide a reference for the proper selection of simulation methods in the study of TSN performance.
A Chinese String matching Algorithm Based on Edit Distance for Electric Power Customer Service
Authors: Liu Xusheng , Mu Songhe , Li Zhiming , Yang Zixing , Han Wei , Wang Zhiwei 
Published: March 2020

Abstract
With the rapid development of information technology, electric power customer service needs to extract accurate information from the data centre to provide customers urgently. String matching is the most straightforward solution. There are some problems in the editing distance definition of traditional string matching algorithm when dealing with Chinese text. In this paper, the pronunciation characteristic of Chinese characters is integrated in the definition of edit distance and a string matching algorithm based on edit distance for electric power customer service data centre is proposed. Finally, through simulation analysis, we demonstrate that this algorithm has good reliability when dealing with Chinese string matching problem. Thus, it is suitable for electric power customer service to obtain the target string.
The Application of Information Technology in Condition-Based Maintenance of Power Transmission and Transformation Equipment
Authors: Li Jian , Wu Jia , Xie Zhi 
Published: March 2020

Abstract
Power transmission and transformation equipment plays a very important role in the normal and stable operation of China’s power system. To ensure the safety and reliability of the operation of power transmission and transformation equipment, it is necessary to do a good job in the maintenance of equipment status. In recent years, with the further development of science and technology in China, the maintenance technology of power transmission and transformation equipment has become more and more advanced, and the information technology has been gradually applied to it, which has effectively improved the efficiency and accuracy of condition-based maintenance of power transmission and transformation equipment. In this paper, the application of information technology in condition-based maintenance of power transmission and transformation equipment is analyzed and studied.
A modified Latin hypercube sampling based on prior information
Authors: Cui Qing’an , Duan Huanjiao , Wang Xueqing 
Published: March 2020

Abstract
Latin hypercube sampling is widely used in industrial engineering. In the traditional Latin square sampling, engineers often arrange sample points in the feasible domain uniformly. However, in practice, engineers may have some prior information about the sub-domains where the response volatility is relatively large, named the interesting sub-domains. In order to make full use of these information, this paper employed the D-S evidence theory to fuse prior information from different sources/fields. Then we divide the feasible domain into different sub-domains and indicate the interesting sub-domains. For the sample placement, we put more points in these interesting sub-domains and less points in other sub-domains. Finally, we construct the model with the proposed sample points placement approach based on prior information. A case study was conducted to illustrate the proposed method. The case study shows that the proposed method performs better than the traditional model in MSE, MaxE and StdE.
Effects of salinity on intestinal flora composition of Penaeus vannamei
Authors: Cui Qingman , Zhan Wenhao , Zhao Ziyue , Yuan Chunying 
Published: March 2020

Abstract
Based on IonS5TMXL sequencing platform, the effects of salinity on intestinal flora composition of Penaeus vannamei were studied. The results showed that the total number of OTUs in intestinal tract of P. vannamei in groups 6‰, 18‰ and 30 was 99, the unique number of OTUs in group 6‰ was 18, the unique number of OTUs in group 18‰ was 110, and the unique number of OTUs in group 30‰ was 53. At phylum level, the dominant bacteria in intestinal tract of three groups shrimp were Proteobacteria, Bacteroides, Firmicutes, Cyanobacteria, Actinobacteria, Tenericutes and Fusobacteria. At genus level, the main predominant bacteria in intestinal tract of shrimps were Defluviimonas, Stenotrophomonas, Shinella, Acinetobacter, Ruegeria, Rhodobacter, Nautella, unidentified Cyanobacteria and Pseudoalteromonas, and the relative abundance of intestinal microflora in different salinity groups shrimp was quite different. Simpson, Chao l, ACE and PD total tree indices of shrimps in salinity 18‰ group were higher than those of shrimp in 6‰ and 30‰ groups, while Shannon index was lower than that of shrimp in salinity 30‰ group, indicating that diversity and richness of intestinal bacterial community in salinity 18‰ group were higher than those of shrimp in 6‰ and 30‰ group. The results laid a foundation for further study on the effects of salinity on growth and metabolism of P. vannamei.
Research on vulnerability assessment technology of power consumption based on data analysis
Authors: Wang Dong , Zhu Tuofu , Xie Aoyu , Guo Kangkang , Wang Jie 
Published: March 2020

Abstract
In this paper, an evaluation model for the vulnerability of power consumption in enterprises is proposed. Firstly, we establish the customer electricity vulnerability index system, which includes the organizational structure, hidden trouble and optimized power consumption. Then, we calculate the index weight and assignment based on the analytic hierarchy process (AHP). And the comprehensive index method is employed to get the customer electricity vulnerability. At last, an example is employed to show our results clearly.
Investigation and Analysis on Informatization of English Education in Higher Vocational Colleges in Information Age
Authors: Liu Miao , Zhao Dandan 
Published: March 2020

Abstract
The rapid development of the information age has promoted the rapid development of the information of higher vocational education. Taking the 13 vocational colleges in Jilin Province as the research object, this paper introduces the present situation of the information of English education, points out their achievements and shortcomings in the construction of information infrastructure, and puts forward the strategies to speed up the information process of the higher vocational English education.
Primary Exploration of the Protection and Reuse of “Abandoned Machines” in Industrial Heritage
Authors: Liu Wei , Lu Dongxiao 
Published: March 2020

Abstract
During the rapid development of a city, it is inevitable to expand and abandon some space, so industrial heritage that cannot bear the production function is regarded as a symbol of waste, decline and decay. Only the city where the old and new coexists is a real sense of city. In this paper, through the analysis on the current situation of “abandoned machines” in the contemporary industrial heritage, the innovative strategies for the protection and reuse of “abandoned machines” in the industrial heritage are generalized and expounded by taking into account the existing problems, referring to relevant cases and summing up experience.
RETRACTED: The Impact of the Arrival of the Big Data Era on Accounting Work
Authors: Jia Ziqi 
Published: March 2020

Abstract
We are living in the era of “Internet +”. As time goes by, business development is getting deeper and deeper, and global data is growing rapidly and will continue to grow. Big data technology is imperceptibly changing our lives. Its influence is not limited to the original business field, but now it is deeply affecting smart manufacturing, financial securities, e-commerce and so on. This article takes the impact of big data technology on accounting work as an entry point, and discusses the positive impact and challenges of big data technology on modern accounting work. Discuss how companies can meet challenges in the face of multiple challenges. I hope that some of my small suggestions can be of some benefit to accounting practitioners and companies.
LMDI Model-Based Analysis of Direct Carbon Emission Accounting and Influencing Factors of China’s Building industry
Authors: Liu Zhenyu , Yin Yue 
Published: March 2020

Abstract
It is generally believed that the building industry is a high-energy and non-environmentally friendly industry. Accounting and analysis of carbon emissions in the building industry is essential for the low-carbon sustainable development of the building industry. This study uses the 2010-2018 China energy consumption data, using the LDMI method to split the influencing factors into four parts: energy intensity, energy structure, economic output (per capita construction GDP) and population size, and proposes low-carbon building industry development. Countermeasures. Studies have shown that all four parts contribute to the carbon emissions of China’s building industry.
Review on the Application of Knowledge Graph in Cyber Security Assessment
Authors: Zhang Kai , Liu Jingju 
Published: March 2020

Abstract
The development of artificial intelligence technology has advanced by leaps and bounds and made significant progress in many areas. Many researchers have begun to apply artificial intelligence technology to the cyber security domain. Knowledge graphs can describe the concepts, entities and their relationships in the objective world in a structured way. Applying knowledge graph to the cyber security domain can organize, manage, and utilize massive amounts of information in cyberspace in a better way. In this paper, the common cyber security assessment models and their shortcomings is summarized, the research progress of ontology-based knowledge representation is discussed, thus leading to a conclusion that ontology-based knowledge representation can completely and accurately represent the complex knowledge of heterogeneous systems in the cyber security domain. Then we introduce the concept of knowledge graph, summarize the application progress of knowledge graphs in the cyber security domain, and discuss directions of future research.
Supplier Selection and Evaluation System of Delphi Method and Analytic Hierarchy Process
Authors: Su Tianen , Zhan Feng 
Published: March 2020

AbstractIn order to solve the problem of selecting and evaluating suppliers by subjective experience and emotional factors. In combination with the actual situation of the enterprise and the plan for the next ten years, an expert group was set up according to multi-attribute, group decision, the basic principles and steps of supplier selection and evaluation, and 4 first-level indicators of quality, cost, delivery time and service and 11 second-level indicators corresponding to each first-level indicator were selected by Delphi method. Analytic hierarchy process was used to determine the weight of each index, and a suitable supplier selection and evaluation system was constructed. This paper improved the current situation of supplier selection and evaluation, which was beneficial to the long-term development of enterprises.
First Price Sealed-Bid Auction Based Cell Selection in 5G Ultra Dense Networks
Authors: Li Hanxuan , Xu Shaoyi 
Published: March 2020

Abstract
The users in the ultra dense networks are faced with the problem of how to choose the right small cell to access. Reasonable choices can not only give the users a better quality of service, but also enhance the effectiveness of the overall system. A novel first-price sealed-bid auction based distributed cell selection algorithm is proposed in this paper, and it can be used to solve the problem existed in ultra dense networks. And it can be concluded from the results that the proposed algorithm achieves better performance in terms of user throughput and reception probability compared to the random access mechanisms.
Prediction of Multiple Diseases of Soybean in Complex Environment Based on Improved Apriori Algorithm
Authors: Hu Xiaonan , Deng Fangyi , Zou Yu , Guo Yan , Fang Yuchao 
Published: March 2020

Abstract
The existence and persistence of soybean diseases are not conducive to the effective operation of the global soybean market. Many detection and prediction methods have been used to prevent and detect soybean diseases, but the practicability of these methods has always been a big challenge for researchers due to there are too few variables in the prediction model, which show bad prediction effect of soybean disease in complex environment. In this paper, the popular Apriori algorithm in data mining is used to analyze the common disease data of soybean in complex environment, so as to achieve the goal of early prediction and control of soybean disease. The variables used in this paper are the characteristic factors of 35 kinds of Soybean under 18 common diseases. The experimental results show that the improved Apriori algorithm can complete the better prediction of soybean diseases in complex environment, so as to reduce the impact of diseases on soybean yield, which is of great significance for economic development, agricultural production and other fields.
Analysis and Optimization of Opioid Drug Transmission Based on Spatial-time-based Model
Authors: Yin Mingjun , Yang Hua , Hu Xinyue , Liu Wenrui 
Published: March 2020

Abstract
The abuse of opioids has become a serious problem in the world. In order to help control the use of opioids, this paper established a new spatial-time-based model based on Logistic model and SIR model to analyse the source and threshold of opioids, and then used factor vector association method to study the social factors of drug abuse in the data of NFLIS and the U.S. socio-economic census. Further we optimized the spatial-time-based model and make sensitivity analysis of parameters of model.
Research on Regional Debt Risk in Hubei Province Based on Modified KMV Model
Authors: Xu Zhiheng , Fan Wen , Zhu Fan 
Published: March 2020

Abstract
With the increasing amount of Regional debt, how to explain and describe this phenomenon has become very important. The revised KMV model can precisely undertake this work, and quantify the level of debt risk through the description of default probability and other factors, providing a theoretical basis for managers to solve this risk.
Research on Influencing Factors of Children’s Rearing Style Change Based on Big Data Analysis
Authors: Yi Binbin 
Published: March 2020

Abstract
Anxiety caused by education is spreading in society. Through big data analysis, educational anxiety comes from the competition for high quality educational resources, which is manipulated by the market. Markets need to create demand and anxiety about scarcity, and then provide solutions. The invisible market and benefit chain outside the education system have existed for a long time, and the core of which is the fairness of education. Mothers’anxieties stem from fears of scarcity and injustice of upward mobility.
Study on Influence of Noise on Nuclear Pulse Trapezoidal Shaping
Authors: Zhou Huanyin , He Gaokui , Xie Yanhui , Huang Weiqi , Yang Qian , Hu Jiewei , Lu Zhanzhan , Yang Zhongping 
Published: March 2020

Abstract
Because real nuclear pulses contain some noises, they are not ideal exponential pulses. These noises have influence on trapezoidal shaping and energy resolution. In this paper, influence of noise on nuclear pulse trapezoidal shaping is studied. The relationship between influence of shaping error and width of trapezoidal shaping is analyzed. The research shows that trapezoidal shaping can suppress noise strongly. Both increasing whole width and decreasing top-line width of trapezoidal pulses can suppress noise further. Trapezoidal shaping can improve energy resolution, so it is very useful and can be widely used in spectrometer.