bluuebunny/crossref_metadata_2025 huggingface dataset:
A new Cghd I gene with negative regulation on the synthesis of chaetoglobosin A
Authors: Jiang Cheng , Song Jinzhu , Zhang Junzheng
Published: March 2020

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

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

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

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

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

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

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

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

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

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

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

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

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

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

In 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

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

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

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

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

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

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.
Random forest and watershed transformations for mapping quasi-circular vegetation patch using fused multispectral CBERS-04 images
Authors: Liu Qingsheng
Published: March 2020

To identify the quasi-circular vegetation patches (QVPs) and monitor their pattern dynamic is the most essential procedure for studying the establishment, encroachment, and maintenance of the QVPs. High resolution satellite remotely sensed technique is a cost-effective approach to distinguish the QVPs. However, the adhesion between the QVPs or between the QVPs and the vegetations of other shapes makes the detection accuracy of the QVPs low. This study used two-seasonal CBERS-04 pansharpened multispectral images to detect the QVPs by integrating random forest classification and watershed transformation image segmentation technique. The results showed that the method proposed by this study could raise the detection accuracy of QVPs, and 5 m spatial resolution CBERS-04 pansharpened imagery may be enough to obtain the number of the QVPs, but not sufficient to calculate the area and shape of QVPs. In the future, more advanced image segmentation algorithms and finer resolution images should be applied to detect the QVPs.
Design of State Evaluation Platform for Distribution Automation Terminal unit Based on AHP
Authors: Xiao Jinxing , Yao Kaiqiang , Huang Liangliang , Tang Heng
Published: March 2020

The requirement of modern power grid for distribution automation is becoming more and more stringent and standardized. Aiming at the situation that the large number of distribution automation terminal units brings to for a lot of inconvenience of maintenance work, this paper establishes a state evaluation system of distribution automation terminal unit based on AHP, and designs a software platform for the system. The software platform occupies little memory, and has friendly interface and is simple. It only needs to input the state of the terminal unit to get the evaluation level of the terminal unit. The software platform can also modify the weight score of each index according to the evaluation results, to constantly revise the judgment matrix and evaluate the terminal more accurately. It provides a reference for terminal state control of distribution automation.
Research on Risk Prevention Measures of Network Information Security in Power Systems
Authors: Lai Ji , Wu Jia , Jiang Yuchen
Published: March 2020

The imperfect network information security technology restricts the development process of network informatization of power systems. This paper mainly studies the network information security of power systems, analyzes the risks faced by power system network operation, and puts forward some preventive measures for the network information security of power systems.
Research on Remote Cooperative Plotting System for Power Emergency Commanding
Authors: Deng Chuang , Liu Yang , Wu Jiayu
Published: March 2020

Geographic information system (GIS) platform is one of the most important tools in electric emergency command area to improve the command efficiency. The GIS systems available only hold basic data and mainly used to browse, therefore can’t show the information and situation in the process of emergency command. This paper proposes a remote collaborative consultation system architecture for power emergency based on GIS. The collaborative plotting on the same GIS platform through computer network remote terminal is realized, using the GIS map plotting technology and XML symbols drive technology. System plotting symbols situation shows the time series mode based on event driven, can be displayed in chronological order and calculate the huge amounts of information along with emergency events. It can get the emergency situation quickly, and promote emergency command efficiency significantly.
Design of low noise electrical system for uncooled long wave infrared imaging
Authors: Zhu Depeng , Zhan Weida , Tian Yong , Wei Ranran , Hao Ziqiang , Tang Yanfeng
Published: March 2020

The research and design of low-noise imaging circuit is of great significance to enhance the imaging quality of the detector. To improve the imaging quality of an uncooled infrared imaging system, a low noise imaging circuit is designed. The generation scheme of bias voltage is emphasized, and the design methods of timing drive module and ADC conversion module are briefly described. A filter with a pass-band cutoff frequency of 1 Hz is designed at the bias voltage output to filter out high-frequency noise. The experimental results show that the precision of bias voltage is over 98% and the RMS noise of bias voltage below 1kHz is 1.4uV. The feasibility of other modules is verified by simulation and experiment.
Research on Line Selection and Positioning of Zero-sequence Current Differential Protection in Distribution Network under the Power Internet of Things in Flexible Grounding System
Authors: Qiu Yutao , Wu Jiayi , Cai Yihang , Zhou Jie , Wang Lei
Published: March 2020

In 2019, China’s power industry proposed the goal of building a “ubiquitous power Internet of Things”. Through the ubiquitous construction of the Internet of Things, the traditional relay protection technology system gradually developed towards the intelligent direction. This paper mainly studies the fast zero-sequence current differential protection using the improved mutation quantity algorithm under the communication mode of power wireless private network. Through MATLAB simulation, it is proved that zero-sequence current differential protection can effectively realize fault location when there are overhead and cable lines in flexible grounding system in complex distribution network.
The Concept Layer, Feature Layer and Landing Layer of Ubiquitous Internet of Things in Power System
Authors: Wu Jia , Zhang Lijuan , Lv Hongzhi
Published: March 2020

With the deep reform and development of energy and power industry and the arrival of the era of Internet of everything, the ubiquitous Internet of Things in power system (IOTIPS) emerges as the times require. However, what is the implication of ubiquitous IOTIPS? What are its inherent attributes? How to get results in information system, digital economy and new business model? These problems have become the current focus of the important issues. This paper considers the above three dimensions.
Vienna Rectifier for DC Charging Pile
Authors: Chou Jun , Zhang Mingda , Wang Sijin , Sun Yihui , Bao Jianyu
Published: March 2020

A three-phase three-level Vienna rectifier is proposed to improve the power factor and reduce harmonic content for DC charging pile. Based on current hysteresis comparison control strategy, voltage deviation of midpoint of dc-link capacitor is introduced into current reference, and voltage balance of midpoint of dc-link is realized by adjusting the dc offset of current reference. Finally, the simulation model of Vienna rectifier based on PSIM is established, and the feasibility of the control method is verified under the conditions of voltage and load stepping. Under the steady-state condition, the power factor at the grid side is greater than 0.99, and the current harmonic distortion rate is less than 3%.
Design and Performance Testing of a 1.2 kA Peltier Current Lead
Authors: Hu Nannan , Ma Tao , Mei Guihua , Song Meng , Liu Mingchuang
Published: March 2020

Peltier current lead (PCL) is a device based on Seeback effects. PCL can reduce the leakage heat of the high-temperature superconducting (HTS) cable, which could improve the overall operating efficiency of the HTS cable. The numerical calculation and simulation analysis model of the PCL based on Bi2Te3 thermoelectric materials is established, and the optimized design method of PCL is obtained. Consequently, the design and manufacture of a kA-class PCL with 8 parallel connected Bi2Te3 thermoelectric elements is completed. The experimental results show that the maximum current deviation of the PCL under different transmission currents is less than 5 A, and the maximum temperature difference is less than 10 K, which is consistent with the designed value. At the same time, the heat leakage is approximately 32 W/kA at the rated current of 1200 A, which is about 25% lower than conventional copper current leads.
Effect of Thermal Aging on Breakdown Strength of Epdm Rubber
Authors: Wang Ruocheng , He Yunyi , Wang Zhao , Kang Hongwei , Ma Jiawei , Jin Haiyun
Published: March 2020

This paper takes the Ethylene Propylene Diene Monomer (EPDM) insulation layer of 220kV integral prefabricated cable joint as the research object, performs accelerated thermal aging experiments at 130°C, 145°C, and 160°C, and then conducted Fourier Transform Infrared spectroscopy (FTIR), Thermogravimetric Analysis (TGA) and power frequency breakdown strength test successively. The experimental results show that thermal aging results in long molecular chain degradation, bond breaking and oxidation of EPDM.The initial decomposition temperature decreases gradually with the aging time and the thermal stability decreases gradually under the action of thermal aging. The breakdown field strength decreased by 13.3%, 21.2% and 22.5% respectively at the end of thermal aging, and the decline rate increased with the aging temperature. The main reasons for the decrease of breakdown strength are the precipitation of crosslinking agent, the breaking down of molecular chain and the generation of oxygen-containing groups.
Wind power density assessment of Ruoqiang
Authors: Jiang Yingni
Published: March 2020

In this work, the wind energy potential of Ruoqiang (39.03°N, 88.17°E) located in Xinjiang province of China is estimated by Weibull density function. Studies show that Ruoqiang is a possible place for the establishment of a wind farm.
Calculation of working temperature of water wall of ultra-supercritical boiler
Authors: Li Yang , Jin Yingai , Jiang Zhipeng
Published: March 2020

Ultra-supercritical coal-fired power generation technology is an advanced and efficient power generation technology. Due to the high parameters of the ultra-supercritical boiler, the heat transfer of the working substance in the water wall is complicated. Therefore, this paper takes an ultra-supercritical boiler as the research object and uses MATLAB to calculate the temperature of working substance inside the water cooling wall. The results show that when operating under low load there is a phase change zone in the working substance of the water cooling wall, the heat transfer is complex in this zone, and the temperature of the water cooling wall may rise to dangerous range. Therefore, it is necessary to pay attention to the fluctuation of temperature of working substance.
Thermal Stability Analysis of a Stainless Steel Reinforced Stacked YBCO Cable
Authors: Hu Nannan , Ma Tao , Mei Guihua , Song Meng , Li Tingting
Published: March 2020

The thermal stability analysis of a stacked strand consisting of the YBCO tapes with square cross-section is presented. Symmetrically arranged YBCO tapes are sheathed by stainless steel. The thermal stability characteristics, including the minimum quench energy (MQE) and the quench propagation velocity (QPV), are calculated by finite element analysis method. The experimental results show that the MQE and QPV of stainless steel reinforced strand are consistent with the simualtion results.
Modelling and Analysis of Dielectric Charge of CMUTs
Authors: Li Jucai , Li Yan , Zhang Peiyu
Published: March 2020

Capacitive micromechanical ultrasonic transducers ( CMUTs ) have the remarkable advantages that the traditional piezoelectric ultrasonic transducers do not have, and they are expected to replace the traditional piezoelectric ultrasonic transducers as the mainstream product in the market. However, the dielectric charging problem has a great influence on the normal work of CMUT, and it is also one of the main obstacles to its commercialization. In this paper, the influence of dielectric charging is introduced, and then the model of non-contact charging and contact charging is established to analyse the mechanism of charging. The influencing factors of dielectric charging were found out, and the influence of each influencing factor on charging was analysed. The charging of the diaphragm and the insulating layer were compared. The results showed that silicon dioxide is less charged than the silicon nitride. Finally, based on the analysis of non-contact charging and contact charging, a method of changing the shape and coverage area of the insulating layer to reduce dielectric charging is proposed.
Researches on Visualization of Switching Arc
Authors: Zhong Jianying , Tan Shengwu , Yao Yongqi , Wang Zhigang , Ye Sanpai , Wang Zhengqi
Published: March 2020

The change of the arc shape directly affects or determines the breaking performance of the arc extinguishing phase and the medium recovery phase after the arc. Through the diagnosis of the arc shape, the arc shape can be related to the performance of the switch. Therefore, the study of the arc shape plays a key role in the development of the large capacity switch. The collected arc shape change data was used to visualize the 2D dimensional arc model by extracting the edges and observing the changes of arc column diameter. The evolution of the arc was explained in detail from the three stages of arc initiation, stable ignition and quenching. From the results we can see: The upper edge position of the arc is maintained between 90-91 pixels, and the lower edge position satisfies the linear increasing relationship of the linear regression equation, and the correlation coefficient is greater than 0.95. The obtained 2D dimensional visualization data is in good agreement with the actual arc shape change, and can be used as a criterion for the quality of the switch.
Efficient Algorithm of Splitting and Merging Classes on Elective Course of College Education
Authors: Liu Jian
Published: March 2020

It should take human intervention to adjust the number of each class after the students select elective courses on web by educational administration system in college, because the numbers are often less than the lower limit. This paper puts out an efficient scheduling algorithm to get the resolution of splitting and merging classes by linear time complexity computing on mathematical model. It introduces in detail the principle, the precondition, the procedure and the operation of splitting and merging classes, which illustrated with several charts, diagrams, pseudo-codes in key steps and some notes, and at last validated it by example. Then it could extend to similar issues, for example enrolling and distributing issue.
Study on the Relation between Gender Characteristics of CFO and Earnings Management
Authors: Dong Li , Wu Baozhong , Wang Ping
Published: March 2020

Based on panel data of A-share listed companies in Shanghai and Shenzhen Stock Exchange from 2013 to 2017, according to the "Upper echelons theory", the relation between gender characteristics of CFO and earnings management was empirically tested with ordinary least squares(OLS) regression model. The study proves that:(1)CFO gender has a significant impact on earnings management. Compared with the company with male CFO, the company with female CFO has a lower overall level of earnings management. (2)The higher the education level of female CFO, the stronger the negative correlation with earnings management degree. This paper provides a new perspective for the study of the influencing factors between CFO gender and earnings management, and also broadens the angle for the research of company earnings management, which has certain significance for the appointment of senior executives of listed companies and the promotion of the healthy development of China’s capital market.
A Method of Retrieval Target Information of Social Network Platform Based on Overlapping Communities
Authors: Zhang Kai
Published: March 2020

With the advent of the 5G era, the social network platform has become the most important way for people to obtain information daily. How to retrieve the desired target information from a large amount of information has been the research direction of researchers. This paper proposes a fast overlapping community detection method based on local neighbor information to detect the target information of the social network platform. This method preprocesses the social network platform data within a certain period of time,constructs edges between highly relevant keywords to obtain a complex network.Through the fast overlapping community detection algorithm of local neighbor information, find overlapping communities, and treat each community as a target information. This method can solve the problem that the detection accuracy of one or more keywords belonging to multiple target information is low. Experiments on a social platform verify the reasonableness and effectiveness of the method.
Answer Selection Using Multi-Layer Semantic Representation Learning
Authors: Yuan Yuan , Chen Lei
Published: March 2020

Answer selection is the most important module of question answering system. Mining the semantic relevance between questions and answers is the key point of answer selection. However, the answer texts often contain some colloquial expressions and redundant information in some fields. In these cases, some traditional methods of mining text features are complex and the performance improvement is limited. In this paper we investigate using deep learning to enhance the computability of semantics and eliminate the semantic gap for the answer selection module of non-factual question answering system. By integrating different networks to mine the association semantic between questions and answers, a novel multi-layer answer selection model is proposed. The shallow semantic relevance between questions and answers is mined by adding the attention mechanism to CNN, and then the features are input into Bi-LSTM model for further mining to obtain more efficient semantic representation. The experimental results show that compared with other models, our method can achieve the better accuracy in the task of answer selection.
An Image Dehazing Algorithm Based on the Improved CGAN
Authors: Li Xuelian , Chen Zhibin , Zheng Wenqian , Chang Ying
Published: March 2020

In order to improve the haze removal effect of image, a modified Conditional Generative Adversarial Nets (CGAN) based algorithm is proposed. In the new algorithm, the pre-trained visual geometry group (VGG) model is adopted, the DenseNet instead of the traditional U-net as the network structure of the generator, the Patch-GAN as the network structure of the discriminator, and the loss function is modified by the total variation regularization gradient. The defogged image can be obtained without estimating the projection map and the related defogging feature. The experiments indicate that our new algorithm effectively reduces the halo phenomenon and haze residue problem caused by the traditional dehazing method, and can preserve more details of the image, the structural similarity is improved from 75.9% to 92.6%.
UAV intelligent optical communication based on conditional generation against network
Authors: Mu Di , Meng Wen , Zhao Shanghong , Wang Xiang
Published: March 2020

This paper first introduces the advancement and importance of laser communication technology for drones., then introduced Deep Neural Network (DNN) to develop wireless end-to-end communication systems. Accurate channel state parameters (CSI) are necessary for computing DNN, but in laser communication systems, channel information is difficult to gain in advance or changes quickly with time and environment. This paper will use conditional generation network (GAN) to represent channels. The coded signal of the transmitter and the pilot data are used as condition information. By simulating the simulation results of the lognormal channel, the method can achieve high-quality transmission without clear CSI.
False Trajectory Privacy Protection Scheme Based on Location Service
Authors: Yang Chen , Yan Wei
Published: March 2020

When the user applies for a location continuous query service, the user location privacy may be revealed due to different types of trajectory identification. A false trajectory privacy protection scheme is proposed, which uses the real-time generation of similar trajectories to protect the user’s personal location privacy. The false location set is established by initial anonymous location selection, similar trajectory location calculation and generated location selection. The false location is used to form a false trajectory similar to the real location trajectory, which reduces the probability of attacker identification and achieves real-time trajectory anonymity based on location service. Finally, the effectiveness of the scheme is verified by performance analysis and experimental results.
Research on Clothing Classification Based on Convolutional Neural Network
Authors: Hong Ying , Lv Chao
Published: March 2020

Convolutional neuron network is a deep learning technology in the field of image classification and image recognition. In this paper, two convolutional neuron network structures having different convolution layers and pooling layers are designed. Each model is train and test with Fashion-MNIST dataset. The experiment results show that convolutional neuron network is an efficient method in clothing image classification. The complex structure model can achieve higher classification accuracy but it will increase the computation costs.
Research on quorum sensing particle swarm optimization based on chaos
Authors: Yu Benyan , Kang Hongwei , Shen Yong , Sun Xingping , Chen Qingyi
Published: March 2020

particle swarm optimization (PSO) is a kind of swarm optimization algorithm with fast search speed, high efficiency and suitable for practical optimization problems. Once it was put forward, it has attracted extensive attention of scholars in various fields. A quorum sensing particle swarm optimization (CPSOQS) algorithm based on chaos is proposed to solve the shortcomings of traditional PSO algorithms, such as poor handling of discrete optimization problems and the loss of searching ability due to the fast particle velocity decline in the later stage. Firstly, the search ability of the algorithm is improved by generating chaotic sequences and mapping them to the solution space of the definition domain; Secondly, the quorum sensing mechanism of bacteria is introduced into PSO. Chaos search was used twice in the algorithm, which improved the global search ability. CEC 2005 benchmark is used to test the performance of the algorithm. The experimental results show that among the 14 selected test functions, 11 test functions have better experimental results than the comparison algorithm.
Design and Implementation of Petrochemical 3D Model Database Platform
Authors: Li Lei
Published: March 2020

In order to meet the demands of petrochemical engineering enterprises for 3D digitalization management of production equipment, and realize rapid building of accident site environment, a set of 3D model database platform facing petrochemical engineering industry is designed and developed aiming at characteristics of standard, regular and repeated model of petrochemical engineering. The 3D model platform is comprised of 3D model data sub-module, interactive editing sub-module, and 3D product application sub-module. It realizes multi-dimensional and integrated information management, and effectively serves equipment management, accident emergency and employee training. With expansion of petrochemical engineering production scale, strengthening of safety requirements, ceaseless improvement of technical grade and gradual increase and complexity of production equipment and facilities, it is necessary to establish a digitalization management system for production facilities and equipment in the petrochemical engineering industry to meet demands of petrochemical enterprises for 3D digitalization management, further dig potentials of petrochemical enterprises in production and management, improve automatic information level, and make information development better serve safety production and accident emergency.
Weighted Laplacian Method and Its Theoretical Applications
Authors: Xu Shijie , Fang Jiayan , Li Xiangyang
Published: March 2020

Recently, a class of multilevel graph clustering (graph partitioning) algorithms have been extensively studied due to their practical utility. Although these newly proposed algorithms work well, there is still not many theoretical guarantees for the quality of partition in these existing methods due to their intrinsic heuristic properties to a great extent. In this paper, we propose a novel weighted Laplacian method for the multilevel graph clustering problem with more powerful theoretical background to further improve clustering performance mainly in terms of accuracy. Since our algorithm inherits the virtues of spectral methods, it possesses a friendly optimization property since it can produce the global optimal solution of a relaxation to the weighted cut on the coarsened graph in the middle stage. Meanwhile, the multilevel strategy can make it possible for our method to produce final clustering results with reasonable time range. Additionally, the weighted graph Laplacian is also suitable for doubly-weighted graph, which will endow our algorithm with a potential wide range of applications. The experimental results verify that our weighted Laplacian methods is indeed superior over existing algorithms in terms of clustering accuracy while also maintains comparable clustering speed.
On the Operability of Computer-aided Translation Software
Authors: Peng Hao
Published: March 2020

Under the context of globalization, communications between countries and cultures are becoming increasingly frequent, which make it imperative to use some techniques to help translation. This paper is to explore the requirements of computer-aided translation software during the translation practice, optimize the design of computer-aided translation software, and carry out a research on its operability in translation.
Multi-task convolution neural network regression prediction model based on vis-NIR spectroscopy
Authors: Jia Dongning , Du Zehua , Huang Xianqing , Li Kexin , Ren Guoxing , Li Ruixue
Published: March 2020

Aiming at the limitation of the current time-consuming and low-efficiency of regression prediction model based on visible and near infrared (vis-NIR) spectroscopy, this paper uses multi-task convolutional neural network model to predict various attributes such as soil total carbon, total nitrogen and alkali nitrogen. Considering the influence of the soil itself and the uncertain factors in the measurement process on the prediction results, the near-infrared soil spectral data is subjected to multi-scatter correction pre-processing, and the model is input and trained to optimize various parameters in the network. The experimental results verify that compared with the single attribute model, multi-task learning optimizes all output variables, maintains the correlation between data, improves learning efficiency and reduces training parameters and training time. The network model also achieves excellent evaluation criteria.
Multi person pose estimation based on improved openpose model
Authors: Xing Jiayuan , Zhang Jun , Xue Chenxing
Published: March 2020

In order to solve the problem of multi person pose estimation, a human body pose estimation model framework based on openpose from American Carnegie Mellon University is presented, which uses the COCO (Microsoft common objects in context) data set to augment the data, optimize the network structure and retrain, adjust the learning rate properly and the convergence speed in the early stage of the model, finally using the model to carry out research on human key point detection and visualizing analysis in a multi-person complex scene. It is found that the improved openpose model adopts a bottom to up detection strategy to avoid the influence of the number of human bodies on real-time performance, and has higher key point detection efficiency than the top to down method. The study provides a real-time position feedback scheme for human pose estimation in complex scenes.
Research of shopping recommendation system based on improved wide-depth network
Authors: Wang Shanshan
Published: March 2020

With the development of e-commerce, there are more and more commodities. How to recommend the commodities that users are interested in quickly and accurately has become an important research topic in the field of e-commerce.we propose a product recommendation algorithm based on DeepFM network. Firstly, we embed the user’s purchased products, and transform the sparse feature into the low-dimensional dense feature, while the user’s personal attribute features can express the user’s purchase intention to a certain extent, and also use embedded coding to transform the features.DeepFM considers both wide and deep (i.e. low-level and high-level) at the same time to further improve the generalization ability of the model. So we use DeepFM to predict the interest of users in purchasing goods.Learning the expression of user’s interest from user’s purchase and personal preference, so as to accurately predict user’s purchase behavior.Finally, we use the real record data set purchased by online users to evaluate the effect of the model, and compare it with other models to verify the effectiveness of the model.