QR codes are applied widely on the Internet and mobile devices in recent years.Its open standards and the characteristics of easy to generate lead to anyone can generate their QR code easily.Also,the QR code does not have the ability of hiding information,which leads to everyone can get access to read the content in any QR code,including those hiding some secret content in the bytes of QR code.Therefore,in recent years,information tampering and information leakage cases caused by poor security of two-dimensional code occur frequently,especially in the financial field and multi-party verification scenarios.QR codes are almost impossible to use in these scenarios.Therefore,this paper proposes a distributed information sharing method based on information hiding QR code.This method can make secret code in QR code safer and robust,and the secret shared between receivers can be used for decryption and attacking detection.Therefore,on the one hand,the information hiding method can maximize the capacity of embedded secret information,on the other hand,it can prevent attacks by disguised attackers and recover hidden secret information through reconstruction.This paper illustrates the feasibility of this scheme through the form of theoretical proof.
One of the main problems of machine learning and data mining is to develop a basic model with a few features,to reduce the algorithms involved in classification’s computational complexity.In this paper,the collection of features has an essential importance in the classification process to be able minimize computational time,which decreases data size and increases the precision and effectiveness of specific machine learning activities.Due to its superiority to conventional optimization methods,several metaheuristics have been used to resolve FS issues.This is why hybrid metaheuristics help increase the search and convergence rate of the critical algorithms.A modern hybrid selection algorithm combining the two algorithms;the genetic algorithm(GA)and the Particle Swarm Optimization(PSO)to enhance search capabilities is developed in this paper.The efficacy of our proposed method is illustrated in a series of simulation phases,using the UCI learning array as a benchmark dataset.
According to some data in the Industrial Purchasing Trends report released by China in 2017,we can see that e-commerce purchasing channels have ranked first among all industrial products purchasing channels in China compared with European and American countries.In addition,in the whole industrial product purchasing market,we can also see that both manufacturers and suppliers are making active e-commerce transformation,and some other Internet giants are also actively entering the industrial product e-commerce industry.But at present,the revenue of all kinds of subjects is still a lot of room for improvement compared to the United States industrial giants.Although the domestic e-commerce market of industrial products has a variety of problems,also contains huge opportunities and development space.Today mobile Internet technology is becoming more and more popular.It is particularly important to develop a cross-platform industrial product order system that supports the collaborative work and unified experience of Android,iOS,and Web.This system uses a uni-app framework to develop front-end applications,which can realize an order management system with code running across multiple platforms.The back end is built based on LNMP architecture.Linux is the most popular free operating system.Nginx is a free and efficient web server with good stable performance,rich functions,simple operation and maintenance,fast processing of static files,and minimal system resource consumption.MySQL database is one of the most widely used relational databases in Web application data processing.The server side is written by PHP script under ThinkPHP framework,which is quick,open-source,and cross-platform in system construction.And these four kinds of software are free,open-source software,together,they can become a free,efficient,highly extensible website service system.
Teaching equipment management is an important factor for colleges and universities to improve their teaching level,and its management level directly affects the service life and efficiency of teaching equipment.But in recent years,our university recruitment of students scale is increasing year by year,the size of the corresponding teaching equipment is also growing,therefore to develop a teaching equipment management information system is necessary,not only can help universities to effective use of the existing teaching resources,also can update scrap equipment,related equipment maintenance,and build a good learning environment to students and to the improvement of the teaching quality of colleges and universities play a reliable safeguard role.This paper first introduces some common development tools,and then analyzes the user functional requirements and data requirements of the system,and analyzes the feasibility of the system development from many aspects,finally based on B/S mode,using Java language,JSP technology and MySQL database design and implementation of a teaching equipment management information system.The main functional modules of the system include equipment basic information management,equipment loan and return information management,equipment maintenance information management,equipment scrap information management,the interface of each functional module is shown in the paper.
