bluuebunny/crossref_metadata_2025 huggingface dataset:
A Simulation Platform for Airport Runway Collision Warning System
Authors: Liao Kai , Zhao Yi , Zhang Xinai
Published: March 2021

The increasing passenger throughput makes the large-scale aviation hub being unable to bear the burden gradually. Flight delays caused by cannot fly through the ATC tower in time are becoming more and more common, which makes airlines have to face the problem of passenger loss. Meanwhile, runway intrusion incidents caused by the high load operation of the airport also occur frequently. Once there is a collision, airlines will suffer huge economic losses. In order to avoid runway intrusion, improve air transport efficiency and reduce airline losses, runway collision avoidance system emerges as the times require. Based on the real airport map geographic coordinate data, this paper draws the airport dynamic map in the on-board moving map for the pilot, defines several kinds of runway intrusion scenarios, and introduces 3D real-time visual display into the platform in order to build a complete set of simulation verification platform for airport runway collision avoidance system. The research results of this paper can be used to verify the optimization algorithm of runway collision avoidance system and the test of airport dynamic map in the future, which is of great significance to improve the traffic condition of large airports in the future.
Demand-side response Resource Value Evaluation Method based on Entropy-weighted Close Value Method
Authors: Liang Kai , Liu Yu , He Huan , Du Liang , Ning Liaoyi , Jiao Zhen , Sun Xinyu
Published: March 2021

The main benefits and social welfare of demand response resources participating in the market are mostly based on qualitative evaluation in previous studies, and no more mature evaluation methods have been seen. This paper uses the evaluation model of the entropy-weighted close value method to analyze the advantages and disadvantages of the evaluation units. Advantages, the standard of each evaluation index is used as the sample to participate in the composition of the original environmental matrix, the entropy weight method is used to determine the weight of each evaluation index, the “most advantages” and “the worst points” are determined in a limited sample, and the sum of each sample point is calculated. The Euclidean distance between the above two points is used to determine the close value of the sample point, determine the order of the merits of each evaluation unit according to the close value, and finally determine the optimal solution for the demand side response.
Research on Systematic Construction of Organizational Project Management (OPM) for Large Business
Authors: Xie Wenjia , Liu Xiangyang , Zhang Shuai
Published: March 2021

This article reshapes the construction elements of Organizational Project Management (OPM) from the aspects of OPM governance, OPM methodology, knowledge management, talent management, etc. It establishes three main lines of strategy implementation, end-to-end process and revenue orientation, as well as clarifying the hierarchical division of the project and improving the information management mechanism, etc. Finally, it provides thoughts and suggestions for the construction of the OPM system of medium and large enterprises.
A Comparative Study on the Safety Management System Standards for Chinese Power Enterprises
Authors: Jiang Feng , Guo Chenggong , Li Ying , Chen Tao
Published: March 2021

The safety management system standards are the basic document for enterprises to carry out safe production activities. This paper uses the methods of literature research and comparative analysis to sort out the safety standardization requirements of China’s power companies. The development history of China’s power safety management system standards is summarized. Through comparative research on the safety management system standards of three Chinese power enterprises, the concepts and methods of safety management of Chinese power companies was summed up, as well as the element settings and key features. The results show that the safety management system standards of Chinese power enterprises are mostly guided by risk management concepts to develop modular systems, and provides some guidance and suggestions for the preparation of safety management system standards for other Chinese power enterprises.
Experimental investigation on fatigue crack growth of directional solidified superalloy with single hole
Authors: Liu Shuangbo , Hu Weibing
Published: March 2021

In order to study the fatigue crack growth of directional solidified superalloy with single hole, the fatigue crack growth test of DZ125 was carried out under different stress levels. The fracture morphology of the specimens were analyzed by field emission scanning electron microscope, and the relationship between stress and life was fitted. It is found that the stress concentration around the hole and the defects lead to the crack initiation near the maximum principal stress point. The da/dN - Δ K satisfies Paris formula well.
Research on the Construction of Cooperative Production Risk Prevention and Control Management Mechanism Based on MQPT Fuzzy Analytic Hierarchy Process
Authors: Zheng Huali
Published: March 2021

Strengthening the cooperative production of cigarette brands is to actively promote the reform of the resource allocation method centered on the brand. It is an important measure to promote the rational flow of production factors and the optimal allocation of industry resources. It is also to promote the rapid development of key brands in the industry, and it is truly a leading an important guarantee for the new pattern of brand development. However, due to many reasons, the cooperative production of cigarettes will inevitably produce various risks, which will endanger the brand reputation. How to achieve the common and sustainable development of cooperative production of cigarettes, strive to promote the high-quality development of cooperative production, and carry out risk prevention of cooperative production Research is very necessary. This subject research and the actual situation of cooperative production to carry out specific research. From a qualitative point of view, the possible risks of cooperative production are classified according to work attributes and work cycles, and the cooperative production is analyzed from the aspects of quality (equipment hardware and technology and key processes), material management, and basic management (plan and personnel). Quality risk sources and identification methods; from a quantitative perspective, combined with some possible risk sources proposed by qualitative analysis, a risk assessment model for cooperative production is constructed.
Visual Analysis of Miner Safety Research Based on Knowledge Graph
Authors: Hongxia Li , Meidan Liu
Published: March 2021

Li Hongxia (1965-), female, from Zunhua, Hebei, professor, doctoral tutor, currently the deputy dean of the Graduate School of Xi’an University of Science and Technology, her main research direction is safety management, corporate organizational behavior and management, safety economy and management, etc.

In order to better understand the current research status and development trends in the field of miner safety, with the help of CiteSpace analysis tools, 450 papers on the safety of miners from core publications and above in the CNKI database from 1992 to 2020 conduct bibliometric analysis. The results found that the main research content of current miner safety can be roughly summarized into six aspects, including coal mine production and management, miner safety quality, physical and psychological research methods. In the future, in the research of miner safety, it is necessary to adhere to the combination of theory and practice, and multi-disciplinary integrated research, to provide deeper and more comprehensive protection for miner safety.
Design of an Interactive Device for Children’s Environmental Science Education on Plastic Pollution in Polar Regions Based on Open Source Programming Language
Authors: Fan Yuning
Published: March 2021

With open-source programming languages, Processing and Arduino, this device realizes man-machine interaction. It has the characteristics of a wide application range and a strong visual expression. Designers and artists can make their ideas real through Processing and Arduino. In recent years, plastic waste can be seen in every corner of the world, which means that raising people’s awareness of environmental protection is urgently needed. Childhood is a key period for developing environmental awareness. In this paper, a popular science device related to environmental protection, taking children as the main target group, was designed and produced. The device provides a combination of technology and art to educate children about environmental enlightenment through external hardware configurations (switches, light sensing and pressure sensing) and on-screen images that show polar bears living in large amounts of plastic pollution.
Optimization of distribution cabinet assembly process based on value stream mapping technology
Authors: Feng Taozhu , Wang Chunna
Published: March 2021

Aiming at the problems of excessive work-in-process, unbalanced production, and unreasonable production methods in the assembly process of S company’s low-voltage switch gear A cabinet, the value stream mapping technology was used to propose an improvement plan for the assembly process, and finally the Flexsim simulation technology The optimization effect of the scheme was tested, and the simulation results showed that the production balance rate, delivery cycle, number of products in process, and fatigue strength of workers have all been effectively improved, which also reduced production costs for the company.
Design of adaptive rate FH-OFDM system based on 802.11g
Authors: WeiQing Fu , JianRu Liang , MingLai Yang
Published: March 2021

In this paper, the wireless communication system based on 802.11g protocol is studied, and a set of FH-OFDM system supporting adaptive transmission rate is designed. The maximum transmission rate can reach 6.75Mbps, which is much higher than 2Mbps transmission rate of traditional FHSS system. A new joint receiver and transmitter detection algorithm is proposed to reduce the error rate of FH position detection by 8.8dB∼11.68dB. The frequency hopping codebook is obtained by counting the bit error rate (BER) of each subcarrier. Selecting the subcarriers with lower bit error rate as frequency hopping points can further reduce the detection error rate by 4.27dB∼6.17dB, the bit error rate by 8.0778dB∼17.4121dB (in the case of 54/8Mbps), and 0.0533dB∼21.6286dB (in the case of 6/8Mbps). And in this paper, we choose the most appropriate transmission rate under different mobile speed and different SNR. By adaptive rate, we can get high performance and efficient equalization of the system.
Segmentation of Workpiece Rust Based on Cross Maximum
Authors: Yang Xu , Lu Xiaotao , Kong Qiming , Song Yuantao
Published: March 2021

Rust is an oxide produced by the reaction of metal and alloy surface with oxygen. It is a defect that greatly affects the quality of the workpiece. In order to solve the problem of rust segmentation more conveniently, a threshold segmentation algorithm based on cross extremum method is proposed, which determines the threshold of rust segmentation adaptively combining the global and local features of the image. Firstly, as the threshold is hard to determine in the small and medium area rust segmentation of a workpiece, the super red method and saturation method are combined to pre-process the image. Secondly, because the gray value of the rust spot area is the maximum value of the image neighborhood, the cross-extremum method is used to extract the characteristic points of the rust spot. Finally, the threshold of rust segmentation is determined according to the proposed feature points. Experiments show that the horizontal and vertical extremum method can complement each other to extract the feature points of rust as fully as possible. And the algorithm can extract some feature points of rust better for different workpieces in varying backgrounds. The detection accuracy of the algorithm reaches 96.3%, which has important signification of application.
Research on prediction of online purchasing behavior based on hybrid model
Authors: Chen Xi , Ding Shichou , Xiang Yongsheng , Liu Lin
Published: March 2021

The research on the potential purchase behavior of users can help merchants develop better marketing strategies. At present, many research methods of online purchasing behavior are based on simple rule prediction, and the prediction results are not satisfactory. We design a hybrid model of Gradient Boosting Decision Tree and logistic regression to accurately predict the purchase behavior of users, which combines the association characteristics between users and commodities. Firstly, clustering algorithm and association rules are used to solve the problem of data imbalance and mine more potential related features. This scheme not only improves the processing efficiency of large data, but also solves the problem of user cold start. Secondly, we construct a scalable tree enhancement system (XGBoost) to train the initial feature set, which is a strong classifier composed of several weak classifiers. A new training set combines the new features with the original features through feature reconstruction, and a hybrid machine learning system is constructed by logistic regression (LR) model. Finally, the LR model is trained by the new training set. Compared with the existing schemes, the integrated decision tree model can train more sample sets with less resources. The experimental results show that the accuracy of the hybrid model is better than single model, and the F1_score is higher.
Analysis of COVID-19 Based on Several Machine Learning Techniques
Authors: Sun Tonglin
Published: March 2021

COVID-19 sweeps the world with high infection and high death rates. It is essential for researchers to find an effective model to predict the trend of epidemic. With the good performances of several traditional models in predicting and analyzing previous epidemics, we compare several popular machine learning methods, including multi polynomial regression, logistic growth model and Long Short-Term Memory (LSTM) in epidemic prediction. We use least squares method for feature selection to determine the most relevant features and we also scale the data according to different experiment environments. We measure the accuracy using Mean Squared Error (MSE) and R2. We conclude that the LSTM model is the most effective model among all the competitors with the highest R2 (R2 = 0.97). We find that LSTM model is the most effective model among all the competitors. Our study gives a good example of feature and model selection for epidemic prediction and attempts to make a significant contribution to the government and hospital to supply the public resources and provide drugs to handle the incoming issues.
Transformer optimization system design based on deep learning and evolutionary algorithm
Authors: He Hongjia , Liu Peipei , Zhou Huili , Jiang Yanli
Published: March 2021

A single shallow learning algorithm cannot fit the characteristics of high-voltage reactors well. Aiming at the above problems, this paper uses the error back propagation neural network and the particle swarm algorithm optimized by adaptive inertia weight to optimize the combined prediction model B for data training, verification and testing are carried out to achieve the purpose of effectively reducing the manufacturing cost of high-voltage reactors. Through experimental verification, the maximum error between the predicted value and the true value is 2.9%, and the minimum error is 0.05%. This provides certain technical support and inspiration for future devices such as optimizing high-voltage reactors.
Design of Kinematic Mechanism of Wheel-legged Robot
Authors: Ying Lei
Published: March 2021

Mobile robots can be roughly categorized in wheeled type, tracked-skidded type, legged type, trunked type, etc. Among them, the wheeled mobile robot can move on the flat road, but with poor performance when crossing an obstacle; the legged type mobile robot has a slow motion speed and poor bearing capacity; the tracked-skidded mobile robot has a large weight; while the trunked mobile robot has limited use occasions. In order to overcome these shortcomings, this paper studies the wheel-legged structure and distributes the performance of various commonly used structures. On the other hand, by analyzing the newly emerged structure, the impact of the organization’s own shortcomings on performance is hoped to be reduced. By comparing the structure and distribution of different leg configurations, the advantages of the locomotion performance of each type of wheel-legged mobile robot and the development trend of the wheel-legged mobile robot in the future are analyzed.
Quantitative risk correction method of storage tank based on safety measures
Authors: Geng Jiezhe , Hu Yuchang
Published: March 2021

Aiming at the safety risk of storage tank in port area, the control measures of tank safety risk are analysed, and the quantitative risk correction method based on safety measures is studied to reduce the risk of tank accident in port area.
A Systematic Review of Binary Program Vulnerabilities Feature Extraction and Discovery Strategy Generation Methods
Authors: Zhang Bo , Xi Zesheng
Published: March 2021

At present, the cyber security situation has turned increasingly serious across the globe. The cyberspace has become the fifth domain of various nations following the four domains of land, sea, sky and outer space. It is gradually obvious for the cyber attacks to collectivize and nationalize. Under this circumstance, as the first line of defense in maintaining cyber security defense, the control on the vulnerabilities is extremely significant. In consideration of the problem of low discovering efficiency in current vulnerability fuzzy testing discovery methods, this paper intends to explore the binary program vulnerability feature extraction and vulnerability discovery guiding strategy generation methods. Then, the extraction of the program control flow and data flow information and slicing operation are obtained according to program logic. Depending on a potential assessment model of binary program vulnerabilities based on the main hierarchy analysis method, the paper achieves a reasonable assessment of the potential of vulnerabilities in different slices of the program. Finally, in accordance with the evaluation results, a generation method for the vulnerability discovery path is proposed to improve the efficiency of binary program vulnerability discovery.
Research on Means of Compliance for Airborne COTS Software
Authors: Hua Hui , Luo Jialu , Chu Yi , Xu Bing
Published: March 2021

The cost of airborne software development is very high, and the functions implemented by airborne software are becoming more and more complex. Using the COTS software has become a trend in case of saving cost. The COTS software brings conveniency, meanwhile raise problems when showing compliance to airworthiness requirements. This paper researches the design assurance method of COTS software, summaries the certification risks and propose a feasibility analysis of using COTS software, thus providing reference for airborne systems designs.
Architecting commercial aircraft with a Domain Specific Language extended from SysML
Authors: Li Haomin , Zhan Chao , Wu Haomin , Yu Miao , Dai Jie , Zou Wenbin
Published: March 2021

Architecting commercial aircraft has been always challenging due to the complexity of the product. A Model-Based Systems Engineering (MBSE) method was employed in this paper to handle this challenge, and a widely used general-purpose systems modeling language - SysML - was adopted to support the architecting work. To ensure compatibility between the modeling language and the specific aircraft architecting methodology, we explored construction and application methods of a Domain Specific Language. A new Domain Specific Language was created, in which several extensions to SysML were made, including Function & Components, Port, Exchanged Item and Relation. Benefiting from this new Domain Specific Language, an overall aircraft architecture model was precisely constructed.
Research on Optimization of Rebar Cutting Process for Prefabricated Concrete Components Based on BPI
Authors: Wang Ru , Wang Yue
Published: March 2021

In view of the characteristics of the production of precast concrete components and the cutting of rebar, from a production point of view, the introduction of BPI (business process improvement) management ideas has been introduced to optimize the rebar cutting process of precast concrete components. A multi-objective prefabricated concrete component rebar cutting model is established and an improved genetic particle swarm hybrid algorithm is proposed. It is proved by examples that the model reduces the number of raw materials and the number of rebar cuts by rationally arranging the rebar cutting combination plan, and the optimization of the prefabricated concrete components rebar process can rationally use the rebar remaining material and improve the utilization rate of rebar.
Research on Pressure bearing capacity of Defective Urban Gas Polyethylene Pipes
Authors: Hai-zhou Lv , Ming Sun , Yu-bin Xu , Yun Wu , Long-long Sun
Published: March 2021

Polyethylene pipes have been widely used in the urban gas industry. However, there are few researches on the safety performance evaluation of polyethylene pipes in use at home and abroad, which makes it impossible to carry out Fitness-For-Service evaluation of defects found in the inspection, and thus cannot accurately judge the safety status of defective polyethylene pipes. In this paper, two typical polyethylene pipe materials, PE80 and PE100 are selected. Based on the tensile performance test, the constitutive model is established. Using the method of finite element simulation, the ultimate pressure bearing capacity of 9 defect models was analyzed and studied. And the relationship between defect size and pressure bearing capacity was initially determined. Provides a foundation for subsequent engineering applications.
System Dynamics Modeling of the Supply Chain Performance of Prefabricated Construction Based on the Stakeholder Analysis
Authors: Yin Yue , Zhang Youzhi , Jin Kai
Published: March 2021

The supply chain performance of prefabricated construction plays an important role in the development of prefabricated construction. In this paper, in order to improve the supply chain performance of prefabricated construction and identify its factors, the indicators system for the supply chain performance of prefabricated construction based on the stakeholders’ perspective on the three dimensions of schedule, cost, and quality was built. Based on the indicators system, the system dynamics simulation model of supply chain performance of prefabricated construction was established. This study provides a dynamic performance management tool for prefabricated construction supply chain stakeholders.
Reuse Strategy for the Previously Qualified Software Tool of Airborne Software
Authors: Liu Jianfang , Zhang Xinai , Zhao Yi , Fan Hui
Published: March 2021

Although the software tool qualification should be based on the specific airborne software, it is impractical to develop the software tool for one software program. Most software tools, especially for the COTS tools, would be reused in multiple software programs. This paper capture and analyzes the requirements for the previously qualified software tool in the related standards and certification guidance, and proposes a strategy and framework for the reusing the previously qualified software tool to meet the requirements of different standards and certification authority.
Research on Safety Management of Small and Micro-sized Mining Enterprises
Authors: Ronggang Lv , Qizhong Luo , Jianqiao Yang
Published: March 2021

In view of the characteristics, status and present situation of small and micro-sized enterprises and small and micro-sized mines, this paper investigates the common safety problems or hidden dangers of small and micro-sized mining enterprises on the basis of practice, analyzes their causes, discusses the current safety management system and operation mechanism of small and micro-sized mines, and puts forward various effective ways to improve the safety management of small and micro-sized mines. It has strong practical and theoretical significance for mine safety.
Research on the calculation and improvement of a company’s activity cost based on activity-based costing and industrial engineering method
Authors: Gao Xiaoqin
Published: March 2021

The traditional cost management mode of China is used to make the cost of the production, and the cost management of the “commodity” is the cost management of the production process, the cost management of the product development and design of the pre-production, which is increasingly difficult to adapt to the needs of the modern social and economic development, has greatly hindered the improvement of the competition capacity of the enterprise commodity market. Based on the operation cost method, the paper will provide an example for the application of the operating cost method in manufacturing. In addition, the research on the final implementation of cost management is not very good. Combined with the methods of reducing the cost of industrial engineering, this paper continuously improves and controls the problems in the company’s operating cost management, and verifies the feasibility through empirical research and a large number of experiments.
Automatic 3D CAD Model and 2D Drawings Generation in Construction Engineering
Authors: Jin Sheng , Zhang Yuanrui , Yamazaki Tomohiro , Jiang Zhu
Published: March 2021

Automatic CAD design is difficult in construction field, since the construction environments vary case by case. Although the steps are similar, each creation is very time-consuming. Therefore, in this research a method that could automatically generate 3D CAD models and 2D drawings from the onsite measured geomorphological features is proposed to solve the complicated and similar process. This proposed method was implemented through the API (Application Programmable Interface) of CAD system and has been verified in practice that labor costs and time costs have been greatly reduced. In addition, mixed reality is applied to verify the assembly results, and an effective and realistic experience is provided to the user and the customer.
Stakeholder’s Needs Analysis Methodology For Civil Aircraft Projects
Authors: Yuwei He , Haomin Li , Xinai Zhang , Yaming Shi , Fudong Chen
Published: March 2021

Aircraft product development process is quite complex, involving many stakeholders. Therefore, aircraft owner manufacturers need to fully capture the needs of stakeholders at the beginning of design, establish analysis methods of stakeholder’s needs, and transform “customer voice” into aircraft development requirements, so as to ensure that the aircraft products can meet the needs of stakeholders. This paper introduces stakeholder’s needs analysis methods such as quality function deployment (QFD), analytic hierarchy process (AHP), and analytic network process (ANP). This paper establishes a Stakeholder’s needs analysis model, which can be used to carry out stakeholder’s needs analysis of civil aircraft.
Weibo Text Classification Based on Knowledge Graph
Authors: Liu Yingjun
Published: March 2021

As a platform for sharing and communication, Weibo can produce a large amount of short text data every day. Because the Weibo text is short and the text features are sparse, it contains less information, serious colloquialization and weak anti-noise ability, so it is difficult to achieve the desired results by using the traditional text classification method to classify Weibo text. This paper proposes a Weibo text classification method based on knowledge graph, which uses knowledge graph to expand text semantics and enrich text features on the basis of the original Weibo text. Then the TextCNN model is used to classify Weibo texts with extended semantics. The experimental results show that the classification accuracy of this method is better than that of Weibo text classification directly.
Topic-to-Essay Generation with Corpus-Based Background Information
Authors: Luo Dan , Ning Xinyi , Wu Chunhua , Wang Maonan , Wu Jing
Published: March 2021

This study aims to generate more topic-related and coherence essays based on user-defined topic words. Existing research generates essays without considering the semantic information from the corpus. However, the corpus contains statistical relationships of words which can be used to guide the model to generate more coherent and fluent essays. To fill this gap, we propose a corpus-based topic-to-essay generation model (C-TEG). We elaborately devise a background network based on the co-occurrence relationships of words from the corpus. The empirical results demonstrate that our approach has achieved 4.14 average score in subjective evaluation and a better BLEU-2 score, which shows that our model is able to generate more topic-related and coherent text than existing models.
Research on Distributed Operation Mode of Internet of Things
Authors: Li Yijie
Published: March 2021

The application of distributed system in the Internet of things makes the system control completely networked, realizes the connection of point-to-point and star data transmission control, makes the system highly scalable, convenient for centralized management, and is suitable for multi-functional Internet of things applications. In the distributed architecture, data is distributed on multiple servers. A distributed database is composed of multiple logically related databases distributed on the Internet of things. Each node on the network has independent processing ability, so it is necessary to find a suitable distributed system solution between code and database.
Real-time facial emotion recognition using lightweight convolution neural network
Authors: Li Qi , Liu Yun Qing , Peng Yue Qi , Liu Cong , Shi Jun , Yan Fei , Zhang Qiong
Published: March 2021

In recent years, facial expression recognition has played an important role in the field of human-computer interaction, and the application of deep learning technology has enabled it to develop more rapidly. In this paper, we create a lightweight network model for real-time emotion classification to recognize student facial expressions. The system includes: using Haar cascade for face detection, combined with the idea of Xception to propose a lightweight CNN network model, using pre-activation in the residual block to optimize the model and reduce the impact of overfitting. The experimental results on the FER2013 database show that our model has a better expression classification effect than other state-of-the-art methods. Besides, our model uses fewer parameters, which reduces the complexity of network training. When real-time emotional recognition of students, the system can help teachers adjust their teaching methods according to the emotional state of students.
Performance research and prospect exploration of distributed object storage of meteorological data in domestic platform
Authors: Cheng Kexin
Published: March 2021

Meteorological data are important information data in China, and have made tremendous contributions to disaster prevention and disaster reduction in China. However, the current meteorological system has a long-term dependence on foreign hardware and software platforms, showing obvious security problems. It is an urgent task to complete the domestication and performance improvement of the meteorological system. At the same time, as the black box architecture of flash memory devices greatly hinders the co-optimization of software and hardware, open-channel flash memory has begun to attract attention as a new type of flash memory architecture. In this article, we have adopted new excellent domestic products including Phytium chips, Starblaze open-channel flash memory devices, and Kylin operating systems as components of a new domestic software and hardware platform. The object storage system of meteorological data has been implemented in a real environment by Ceph. We provides a built solution and optimizes the parameters. Based on the comparison with the commercial platform storage system, the problems and challenges faced by the meteorological data distributed object storage system in autonomy are discussed. Finally, this article looks forward to the distributed storage of meteorological data under domestic platforms.
Bibliometrics and Knowledge Graph Analysis of Domestic Big Data Management Research
Authors: Weihua Yang , Dong Xu
Published: March 2021

This article uses CiteSpace software to perform a visual analysis of the knowledge graph of the literature about the direction of big data management in the CNKI database using the method of document measurement. The analysis content includes: paper attention, author of the article, hot keywords, and the organization of the article, and big data is found. The hot research of management can be summarized into four categories: education management, information management, enterprise management and government management. The domestic scholars’ research status on big data management is obtained, and the development trend of big data management research is revealed, with a view to providing reference for the research and development of big data management in various subject areas.
Speaker Identification Based On Ivector And Xvector
Authors: Yuan Xinyu , Li Guanyu , Han Jiao , Wang Di , Tiankai Zhi
Published: March 2021

As an important branch of AI (Artificial Intelligence), speaker recogniti-on technology has developed rapidly in recent years. At present, speaker recognition technologies based on traditional methods and deep learning methods are very mature and have achieved good results. As a key technology in human-machine voice intera-ction, speaker recognition has changed human life in many ways. However, there is almost no research on speaker recognition in Tibetan. This paper uses Gaussian mix-ture model and deep neural network TDNN as the theoretical basis. On the Tibetan language corpus, the speaker identification on the ivector of GMM-UBM and the speaker identification on the xvector of TDNN are performed respectively, and the experimental results are compared. The experimental system is divided into prepro-cessing, feature extraction, model training and decision.
The Application of Big Data Technology in the Construction of Smart Campus in Vocational Colleges
Authors: Guofeng Xu , Mingzhu Li
Published: March 2021

Informational education is a new requirement for education in the information age and it is an inevitable trend in the development of education modernization. In the rapid development of the Internet, the use of cloud computing technology can play a greater role in the construction of smart campuses. It can not only improve the school’s digital service management level, but also promote the progress of education. This article briefly introduces the concept and necessity of smart campus construction, analyzes the role of big data technology in the construction of smart campus, and proposes smart campus construction measures based on big data.
Research on Near far field transform algorithm based on probe compensation
Authors: Zhang Yiyue , Jia Yunfei , Liu Xingxun , Li Jinsong
Published: March 2021

In order to solve the problem of sidelobe error caused by probe pattern in current antenna planar near-field and far-field transformation, a new near-field and far-field transform algorithm with probe compensation is studied by combining the advantages of traditional pattern development and edge current approximation method. By measuring the array antenna in a microwave anechoic chamber, the traditional mode expansion method is compared with the hybrid algorithm. The results show that the measurement accuracy of this method is 1.445dB higher than that of the traditional method, and the calculation efficiency is significantly improved, which proves the effectiveness and engineering practicability of this method.
Application of WebCrawler in Information Search and Data Mining
Authors: Qinghua Chen
Published: March 2021

With the development of network technology, the scope of information search and the ability of data mining are also increasing. On this basis, a WebCrawler technology is proposed. WebCrawler technology plays a very important role in improving the ability of data information search. This article mainly analyzes the working principle of WebCrawler technology and the principle of Web information search and data mining, and focuses on the application in information search.
Using AI to Enhance Recruitment Effect
Authors: Liu Jia , Chang Shih-Hsuan , Xu Yu-Ci , Wu Guo-An , Chang Shih-Feng
Published: March 2021

In today’s rapid economic development, the competitiveness of enterprises is more and more reflected in the talent competition, and the important means to obtain talents is recruitment. With the development of economy, recruitment channels are becoming more and more diversified. Enterprises will choose recruitment channels according to various reasons to recruit suitable candidates for the vacant positions of the enterprise. However, after finding the suitable people, how to keep them or hire them. After the recruitment of employees, whether the performance of employees is related to the recruitment channels has an important reference role for the selection of human resources. We use AI technology to measure the performance of employees through the three dimensions of subjective initiative, job satisfaction and job self dedication. Therefore, it has theoretical and practical value for improving the recruitment effect and contribution.
Research on Particle Swarm Optimization Algorithm
Authors: Wang Shouya , Zhu Jiabing , Shen Xiaobo , Wang Qianchun , Shu Renyi , Cai Jun
Published: March 2021

Aiming at the unsatisfactory performance of the particle swarm optimization algorithm in the optimization process of complex problems and being easy to fall into premature convergence, a power law function to improve the weight value of the particle swarm algorithm is proposed in the paper. It is compared with the linearly decreasing weight particle swarm algorithm, and the test is performed on four typical single-peak and multi-peak functions. The test results show that the particle swarm optimization algorithm in this paper has a better optimization effect.
Providing Domain Specific Model via Universal No Data Exchange Domain Adaptation
Authors: Wang Lixu , Liang Songtao , Gao Feng
Published: March 2021

High quality Data and its derivative machine learning (ML) models are gradually becoming commercial commodity and provided to work effectively in an increasing number of areas. These ML model providers possess a set of trained models along with immense amount of source data stored on their servers. In order to obtain specific models, providers will require consumers to upload their domain-specialized data and conduct domain adaptation at the server side. However, considering the protection of the private information reflected by consumers’ training data, as well as maintaining the commercial competitiveness of ML service, it is best that there is no data exchange between servers and consumers. Besides, consumers’ data is always lack of supervision, i.e., classification labels, thus we are searching for how to conduct unsupervised domain adaptation (UDA) with no data exchange among domains in this work. We are the first to propose a novel memory cache based adversarial training (AT) strategy for UDA at the target side without the source data (the existence of source data is an essential requirement for regular AT). And our method includes a multiple pseudo labelling operation which is more accurate and robust than single pseudo labelling. The AT and multiple labelling work collaboratively to extract shared features among domains and adapt the learning model more specific to target domain. We carry out extensive evaluation experiments with a number of data sets and baselines, and according to the results, our proposed method can perform very well and exceed the state-of-art performance on all tasks. In the end, we also discuss how to extend our method to partial and open-set domain adaptation.
Generating Anime Sketches With C-GAN
Authors: Wang Ziyuan
Published: March 2021

Generating a decent colored anime drawing from black-and-white sketches is not a simple task in the anime industry. For this problem, a novel deep learning model is introduced based on Conditional Generative Adversarial Networks(C-GAN), which can automatically colorize the anime sketches and output satisfactory pictures. By testing the structure of this model, a typical structure is found to have the best performance.
A Scanner Jitter Test Method of CR System Based on Improved Hough Transform Algorithm
Authors: Wenming Guo , Huilin Zhao
Published: March 2021

Computed radiology system (CR) test technology has been applied in the testing of industrial welding defect after the promulgation and implementation of digital radiographic imaging test standards. The performance of CR system directly affects the testing rate of welding defects. Therefore, testing and evaluating the performance of CR system becomes the premise and guarantee for the application of CR system. In this paper, based on the testing image of CR phantom and the simulation of scanner dither results, an algorithm combining fault-tolerant voting and improved point-based hoof transform is proposed to test the performance index of scanner dither in CR system. Experimental results show that the proposed algorithm can test not only the row and column dithering, but also the subtle arc dithering. Compared with standard Hough transform algorithm, this algorithm has higher accuracy and can avoid the influence of other image indicators around the T-shaped image quality indicator used in CR phantom.
Research on the Application of Mind Map in Multimedia Network Teaching Environment
Authors: Guo Qinrong
Published: March 2021

With the rapid development of Internet technology, multimedia network teaching has become a new teaching mode in the teaching work of major universities. In the context of multimedia technology, the use of mind maps to carry out teaching activities in various disciplines can give full play to the advantages of both, which can use mind maps to present the knowledge learned in an intuitive and vivid way. This not only helps students sort out their knowledge, but also enables students to master important and difficult knowledge faster and more efficiently, and enhance their memory and thinking skills. This is also conducive to the cultivation of students’ divergent systems, systematic thinking and creative logical thinking. Based on this, this article will discuss and study the application of mind mapping in college multimedia network teaching environment. The author hopes that the combination of multimedia technology and mind mapping can maximize the effectiveness of teaching.
Medical Record Storage Model Based on Credibility Assessment H-Algorand Consensus Mechanism
Authors: Sun Jiatai , Zhao Zengnan , Zhang Minghui , Wang Ning , Wang Lihua
Published: March 2021

In order to solve the problems of poor security and low throughput of the current electronic medical records, this paper proposes an electronic medical record storage model based on H-Algorand consensus mechanism of credibility assessment combined with blockchain technology. To ensure the normal operation of blockchain system effectively, the model used a credibility assessment algorithm to obtain the trust value and replace the account balance in the H-Algorand consensus mechanism with the trust value as the node weight. The results show that the storage model adopted here has higher security and throughput efficiency.
Improved Object Detection using Data Enhancement method based on Generative Adversarial Nets
Authors: Ruiqiang Zhang , Jiajia Liu , Yu Zeng , Kejia Pan , Lin Huang
Published: March 2021

In deep learning-based object detection, especially in face detection, small target and small face has always been a practical and common difficult problem due to its low resolution, blurred image, less information and more noise. In some applications, sensing image data is hard to collect, leading to limited object detection performance. In this paper, we investigate using a generative adversarial network model to augment data for object detection in images. We use generative adversarial network to generate the diverse objects based on the current image data. An improved generative adversarial network is added in the network and a new loss funtion is applied during the trianing process to generate diverse and high-quality traing images. Experiments show that images generated by generative adversarial network have higher quality than counterparts.
On the In-application Value of Emotional Intelligence Interaction Based on Interactive Art Installation
Authors: Zhou Xinyu
Published: March 2021

The design of interactive art installation, which integrates interactivity, artistry and education, leads people to think their relationship with nature and society by human-installation interactive movement. Due to the repaid development of science and technology, the simple interaction with settled program cannot satisfy people’s demands. Instead, they want to step into the world of installation through personalized emotional catharsis. The current mode of communication will be changed by the in-application program within the interactive art installation. The single installation totally produced by artists’ thought will be replaced by the finished installation product with the participation of the audience. In this way, participants will immerse in the story plot and feel various emotional changes psychologically by sound, image and touch, which relies on the interactive art installation. The Listen is taken as the example to spread the idea of sharing the ecological nature of human beings and the world. Arduino, an open source platform, will be studied to show the change of modern interactive communication mode, exploring the impact of programming tool on the development of future interactive installation and providing some new ideas for the integration of artistic creation and science and technology in the future.
Resource Allocation for High-Speed Train Communication Based on Deep Reinforcement Learning
Authors: Zhou Lanlan , Yu Jianguo
Published: March 2021

With the advent of high-speed railway era, users’ demands for high link capacity and high reliability are increasing. In this paper, a resource allocation algorithm based on deep reinforcement learning (DRL) is proposed in the high-speed railway (HSR) scenario. The communication link between high-speed train and high-speed train (T2T) is taken as an agent, and the link capacity and packet transmission success probability (PTSP) are taken as optimization objectives, which are mapped into the reward function. The agents gain experience by constantly interacting with the HSR communication environment to update the neural networks in DRL and eventually learned the optimization policy. The simulation shows that when the trains’ speed is 350km/h and the transmission packet size is 2385Bits, the high reliability of T2T link can still be maintained, and the capacity of high-speed train to Infrastructure (T2I) link is improved by 1Mbps compared with the baseline, which proves that the proposed algorithm can mitigate the interference introduced by spectrum reuse and doppler shift.