bluuebunny/crossref_metadata_2025_split huggingface dataset:
Semisupervised Classification Based on Tensor Convolutional Neural Network for Hyperspectral Images
Authors: Ye Fuyin , Chen Zhao 
Published: April 2021

Abstract
Deep neural network has been extensively applied to hyperspectral image (HSI) classification and shown promising performance recently. However, those popular deep learning models scarcely consider low-rank features of high-dimensional HSIs lying in intrinsic data subspaces. Besides, their results largely rely on numerous labeled samples, which are expensive and time-consuming. To address these issues, we propose a Three Dimensional Tensor Convolutional Neural Network (3DTCNN) for spectral-spatial low-rank feature representation and a Semisupervised Classifier based on 3DTCNN (S-TCNN) for classification with limited labeled samples. 3DTCNN integrates tensor decomposition with convolutional neural network to extract discriminative spectral-spatial low-rank features. It also combines multiple supervised discriminators and unsupervised clustering modules to exploit labeled and unlabeled samples. Experimental results show that S-TCNN outperforms several classic supervised classifiers and state-of-the-art semisupervised classifiers on one benchmark hyperspectral data set, Indian Pines. When there are only 3 samples with prior labels per class, the proposed model achieves 98.2%, in terms of overall accuracy. Therefore, the design of 3DTCNN is proved feasible while the efficacy and efficiency of S-TCNN are validated.
Optimization of Edge Extraction Algorithm for Objects in Complex Background
Authors: Huang Fengyun , Jiang Yu 
Published: April 2021

Abstract
In the field of artificial intelligence, machine vision is expected because of its low cost and easy popularization. Feature extraction is one of the core steps of machine vision. When we use Canny algorithm, which extracts edges by gray level change, we cannot directly separate the object from the background. The edge information of the object will also be lost when the Gaussian filter smoothes the image. The research proposes an improved edge extraction algorithm based on Canny algorithm. We use the image difference method and object envelopment method to separate the object from the background, so the data to be processed is greatly reduced and the speed and accuracy of the algorithm are improved. Then we use bilateral filtering instead of Gaussian filtering, which increases the weight of gray difference on the basis of Gaussian filtering, so we can to retain more edge information. Finally, we improve the gradient operator, by determining the gradient operator coefficient according to the inverse ratio of the Euclidean distance between the pixel and the center pixel. The average performance of the new gradient operator in the center of the picture is better than that of Sobel operator. Experimental simulation shows that the algorithm has good detection accuracy. Compared with traditional algorithms, the improved algorithm is not affected by complex backgrounds, and reduce the influence of light. The improved algorithm has clear edges in the center area of the image.
Incremental Learning Based on Angle Constraints
Authors: Zhou Yang , Qin Yunbai , Jiang F. , Zheng Kunkun , Cen Mingcan 
Published: April 2021

Abstract
With the rapid growth of the Internet, it has become easy to obtain new data for many application domains. However, when adding new data to the current system of artificial neural networks (ANNs) to learn, it can cause the network to completely forget what it has learned before, which is called catastrophic forgetting. The main reason for these problems is the inability of ANNs to balance new classes with old ones. Therefore, to address the challenge of learning new knowledge while not suffering from catastrophic forgetting, some incremental learning algorithms have been proposed to alleviate. This paper proposes features that balance new classes with old classes by using angular distillation. And some exemplars from the old classes are retained to improve the performance on the old data. The effectiveness of our algorithm is demonstrated on CIFAR-100 dataset.
Particle Swarm Optimization for Optimal Allocation of STATCOM on Transmission Network
Authors: Okelola M O , Ayanlade S O , Ogunwole E I 
Published: April 2021

Abstract
Static Synchronous Compensator (STATCOM) is one of the members of flexible alternating current transmission systems (FACTS) devices that controls one or more network parameters to increase system power transfer capability. However, it needs be optimally allocated to fully maximize its usage. Allocation of STATCOM simply refers to optimal placement and size of a STATCOM to solve some of the transmission network problems. This paper therefore utilizes particle swarm optimization (PSO) to allocate STATCOM to enhance the system voltage magnitudes and minimize the active power loss. A Matlab programme was developed for the proposed method and applied to IEEE 14 bus network and the results presented. The results showed that the total active power loss was reduced by 6.90%. The voltage magnitudes at buses 7 and 13, which were above the upper voltage limit, were reduced and brought to within acceptable voltage limits and hence improvement in the system voltage profile. Therefore, the optimal allocation of STATCOM improves the efficiency and operation of the network.
Anov: A Framework for Rapid Construction and Development of Web-Based Large Screen Visual Dashboard
Authors: Song Yulun , Xie Yunlong , Zhu Runya , Pang Zhihui , Zhuang Yuan 
Published: April 2021

Abstract
With the advent of the era of big data, extract and display effective information from massive amount of data has become a hot research field. Visualization is the most direct way for users to perceive and understand data. That’s why data dashboard with its cool dynamic visual effect has become so popular. In this paper, we propose a framework for rapid construction and development of web-based large screen visual dashboard—Anov. Anov dedicates to three goals: high efficiency, innovative AI user interaction and 3D scene. First, this framework provides a “30% configuration, 70% customization” development scheme which shortens the development cycle by at least one third. Second, Anov adopts a hierarchical architecture model to achieve high reusability, easy extensibility, high reliability, and easy maintenance. Finally, this paper introduces Anov’s wide range of application field and rich user experience through multiple cases to demonstrate the practicality of the framework.
Modeling and Analysis of Massive College Sports Data Based on Cloud Computing
Authors: Su Taotao 
Published: April 2021

Abstract
With the advantages of cloud computing in the process of education and teaching practice in China gradually highlighted, it is increasingly urgent to use cloud computing to promote technological change in education and promote educational modernization with educational information. This paper introduces the problems existing in the construction of sports information resources in Colleges and universities. This paper discusses the impact of cloud computing on college sports information resources and the new opportunities brought by cloud computing. Finally, the paper puts forward some suggestions on the construction of sports information resources in Colleges and universities. The results show that the passing rate of freshmen, sophomores, juniors and seniors is 13%, 20%, 22% and 45%, respectively. The pass rate of high school physical education is the highest, the pass rate of freshman physical education is the lowest, and the pass rate of sophomore physical education is lower than that of junior middle school physical education.
Database Construction in Computer Audit under Big Data Environment
Authors: Wu Yanhong 
Published: April 2021

Abstract
In the information age, the explosive growth of data forces users to deliver the data to the database service provider to manage. This paper mainly studies the database construction of computer audit under the environment of big data. This paper proposes a queryable database encryption storage scheme and a searchable multi-keyword encryption scheme under distributed environment. In this paper, the non-relational database is used in distributed storage in the form of key-value to improve the query performance. For distributed database, this paper proposes a queryable database encryption scheme. In this scheme, there are two encryption query modes: exact matching mode and range matching mode. Users encrypt and store data to the corresponding server nodes in these two ways, which can support rich queries. In the process of query, the user generates the corresponding query password for each server node, and then the parallel query can be realized. While protecting data privacy, the performance of the scheme is also well guaranteed.
Application of Neural Network and Computer in Intelligent Robot
Authors: Zhou Huikui , Gu Mudan 
Published: April 2021

Abstract
Autonomous mobile robot is widely used in security patrol, freight, autopilot, and family life and other fields, improve the application effect is one of the most important factor is to be able to accurate navigation path, so how to design a highly efficient, intelligent autonomous mobile robot navigation path algorithm has been a popular research topic in the field. This paper mainly studies the application of the combination of neural network and computer in the field of intelligent robot. The Pninnet model is used to simulate the 3D simulation environment built in this paper, and the path navigation method of the autonomous mobile robot based on the end-to-end model is realized, and an algorithm based on ray detection is proposed to achieve obstacle avoidance. Through several groups of comparative experiments (such as comparison with Pilotnet model, etc.) and analysis, it is proved that the algorithm in this paper improves the efficiency of robot navigation research and the robot developed has a better performance in navigation in unknown or familiar environments.
Design and Implementation of Vocational Education Cross Border E-Commerce Comprehensive Training System Based On Big Data Analysis
Authors: Hu Shuyu , Huang Ming 
Published: April 2021

Abstract
In recent years, the rapid development of e-commerce logistics puts forward new requirements for personnel training. With the rapid development of e-commerce, there is a serious shortage of e-commerce talents, which poses a great challenge to e-commerce education and teaching. As the main position of cultivating skilled talents, vocational education has unique advantages in cultivating e-commerce talents. On the basis of the survey, this paper analyzes the demand level and knowledge skills of e-commerce talents. The results show that the highest proportion of mixed M & A of digital marketing communication is 44%, and the lowest proportion of horizontal communication is 21%.
Production Technology and Stability Study of Chaenomeles Lagenaria Leben Based On Data Analysis
Authors: Wu Yahua 
Published: April 2021

Abstract

Objective: Chaenomeles lagenaria fermented milk beverage was will to raw milk fermented yogurt after adding concentrated C. lagenaria juice, stabilizer and organic acid, sugar, water allocation. The production technology of fermented beverage for C. lagenaria and its stability were studied, thus for C. lagenaria the production technology of fermented beverage used to provide reliable reference for industrial production. Methods: Through the experiment, optimized condition of the production process of milk beverage, and to make good C. lagenaria stability of fermented milk beverage were studied. Results: add the yogurt, 40% 0.5% concentrated C. lagenaria juice stabilizer for optimum process conditions. The optimum proportion of stabilizers for sodium carboxymethyl cellulose 0.15%, polysaccharide compounds 0.1%, xanthan gum 0.2%. Conclusion: Through data analysis that C. lagenaria fermented milk beverage production need reasonable ratio of concentrated C. lagenaria juice and yogurt combine to produce fermented milk quality and taste are good C. lagenaria.
Development Trend Layered Technology Optimization Strategy in Computer Software Development
Authors: Cao Xiao-Long , Hu Yuan-Yuan 
Published: April 2021

Abstract
With the development of society and the rapid progress of science and technology, computer software development technology has brought new development trends, among which layering technology is a relatively common technology in software development. This article has conducted a series of research and discussion on the development trend of layered technology in the development of computer software. In modern society, the application of computer technology is more and more extensive, the technology used in computer software development is more and more diversified, and the traditional single-layer software system is more and more difficult to meet people’s requirements. As the actual requirements of users continue to increase, the application of layered technology in computer software development is becoming more and more common. The globalization of information technology has not only changed people’s production and lifestyle, but also improved people’s quality of life, and promoted the continuous progress of society and the times. As an important development field in the information age, software technology plays an important role. The situation of globalization is becoming more and more obvious. As one of the main means of cultural communication, information globalization depends to a large extent on the development and popularization of the Internet, and determines the speed of globalization. The computer is the external outlet of the Internet. The upgrading of computers is getting more and more attention. The development of network technology provides opportunities for the development of computers. In the process of computer software development, layering technology has improved the computer’s operational capabilities and data processing capabilities. These two improvements provide effective protection and bring us a better user experience. This article is based on the particle swarm algorithm to carry out research and discussion. The experimental research results show that the development trend of layering technology in computer software development has shown a trend of vigorous development. Under this trend, we should follow this pace and keep going.
Function and Influence of Database Technology in Distributed Accounting Books under Network Environment
Authors: Liu Ying 
Published: April 2021

Abstract
As the main form of value embodiment of accounting subject, distributed account book is becoming more and more important in accounting management activities. However, due to its own specific economic attributes, it is often restricted by many internal and external conditions such as enterprise development. Especially in the objective situation of the continuous popularization of network application in recent years, with the continuous progress of database technology, its role in business management is increasingly obvious, and its impact on the quality of corporate accounting information is more and more obvious. The development of database technology in the network environment is conducive to the development of distributed accounting records through artificial system, and the establishment of a computer-based traditional system and modern Distributed Accounting registry. In this changing process, the development of innovation and management theory runs through all fields, but the influence of network information technology is the most basic. It directly or indirectly affects the evolution of distributed accounting system structure. The development of network database technology will contribute to the smooth connection between the Distributed Accounting registry and other management system subsystems. An enterprise ensures the data exchange within the enterprise, even between the supply and demand chains. In this process, the quality of accounting information improves the efficiency in the decision-making process. However, the research of computer accounting is usually dealing with the accounting treatment of specific business. It mainly studies the impact of database technology on the network environment in distributed accounting books.
A Hybrid News Recommendation Algorithm Based On K-means Clustering and Collaborative Filtering
Authors: Liu Jing , Song Jinbao , Li Chen , Zhu Xiaoya , Deng Ruyi 
Published: April 2021

Abstract
In the era of paper media, the information channels and the information content were integrated. With the birth of the Internet, they tended to be separated while the information channels continued to expand, which brought a massive amount of news information to process. Therefore, it’s essential for us to adopt new methods and new models to deal with all the information. This paper gives a brief overview of news recommendation technology, and proposes a hybrid news recommendation algorithm, which combines content-based recommendation algorithm and collaborative filtering, using TF-IDF method and K-means clustering technology to extract and process the features of news content, meanwhile, this paper applies SVD technology to solving the matrix sparse problem in the traditional collaborative filtering algorithm. Moreover, news popularity is taken into consideration in this paper then it combines the candidate recommendation results of each approach. At last, this algorithm achieves a better result compared to traditional recommendation algorithm’s result.
Design and Implementation of Digital Platform of Academic Test in Colleges and Universities
Authors: Wang Fuqiang , Hu Qiang 
Published: April 2021

Abstract
With the rapid development of Internet technology, academic testing in colleges and universities also ushered in changes. The disadvantages of a test paper are becoming more and more obvious. This paper expounds in detail the design and implementation process of the online academic test digital platform designed and developed by using Java development language and MySQL database and eclipse development tools. The test results show that the digital platform of academic test in colleges and universities is flexible in practical application, and it is convenient to group papers, test and mark papers, and data collection and analysis, which provides work efficiency.
University Sports Information Management System Based on Big Data
Authors: He Qinhong , Lu Long , Xu Xiangdong 
Published: April 2021

Abstract
Student information management is not only the basis of realizing efficient education and teaching management in Colleges and universities, but also an important link. However, in recent years, with the popular development of higher education, the number of students is further expanded, the number of students has increased a lot compared with the past, and the work of student information management has become increasingly heavy, which has brought new challenges to student information management. This requires managers (class teachers, class cadres) to update the concept of student management, innovate the student management mode, and use modern information technology to manage class affairs and student information. This topic is based on the realization of the standardization, digitization and automation of student information management, which can help class teachers and class cadres save manpower, material resources and financial resources, further improve the efficiency and accuracy of class information management in sports colleges and universities, strive to improve the scientific level of student information management, and provide a platform for students to broaden their horizons and actively participate in school activities. In this paper, through the design and development of sports information management system, and through the function and performance test, it is found that the system can meet the needs of colleges and universities, which simulates the results of 200 users’ concurrent number of operating system. The user concurrent number is the largest user concurrent number index of non functional requirements of the system, and the corresponding test items have passed the performance test requirements.
Research and Application of Business Ability Evaluation Based On DBSCAN Algorithm and Entropy Method
Authors: Yang Jing , Liu Kunpeng , Zhang Mingjie , Xu Qing , Jin Peng 
Published: April 2021

Abstract
Based on the data of 95598 work sheets and quality inspection, this paper constructs customer commissioners business capability evaluation models of different business types. Firstly, through DBSCAN algorithm we mine the potential category characteristics of customer commissioners. Then, entropy method is used to score the customer commissioners under the target category comprehensively. Finally combining the clustering results and entropy score, the customer commissioners with relatively strong and weak business capabilities are identified accurately. By marking the business capacity labels for the corresponding customer commissioners, it has guiding significance for the post adjustment and business training, which can improve the quality of power supply service and customer satisfaction for customer service center.
Axiomatic Design Based Association Network Mining Method for Complex Mechanical and Electrical Products
Authors: Zhang Fudong , Xia Qiongpei , Yang Xianchao , Xia Yuanfei 
Published: April 2021

Abstract
Complex mechanical and electrical products have complex functions and structures, and simple customer requirements often hide the complex relationship between components. In order to effectively analyze the relationship between components of complex mechanical and electrical products and better deal with the problem of adaptive design, from the perspective of product requirements, a method of mining association network of components of complex mechanical and electrical products based on axiomatic design is proposed. Firstly, based on the whole life cycle of the product, the product use environment of product environment designer interaction is constructed, and the product requirements are obtained based on the product use environment; then, the axiomatic design of different domain mapping relationship is used to mine the association relationship of product parts, and the association network between product parts is constructed, and the association network is expressed structurally. Finally, taking the segment assembly machine of shield machine as an example, the effectiveness of the proposed method is verified.