Function Modules Of System Research Articles

Design of a Traditional Village Cultural Heritage Preservation and Management System Based on Multi-Agent Networks

Preserving cultural heritage is essential for maintaining cultural diversity and promoting sustainable development. This study investigates the application of multi-agent networks in the protection and management of traditional village cultural heritage, capitalizing on their inherent distributed, collaborative, and adaptable characteristics. By integrating advanced technologies such as big data, data mining, and machine learning, the research meticulously develops a comprehensive system architecture and functional modules aimed at revitalizing traditional village spaces. The findings demonstrate significant enhancements in protection efficiency, while simultaneously fostering cultural inheritance and innovation within village communities. Through these innovative approaches, this study provides valuable insights into the preservation of traditional village cultural heritage and contributes to the broader objectives of cultural diversity conservation.

Mobile Learning and Resource Sharing Mode of College English Translation Based on 5G Mobile Communication Technology

The application of 5G and other mobile communication technologies to education and teaching, and the construction of College English Translation mobile learning and resource sharing model and related models have important scientific value and significance for the effective organization and management of learning resources and the improvement of the speed and efficiency of college english translation resource retrieval. This research mainly combines the characteristics of complementarity and expansion of mobile learning technology for traditional online learning technology. Based on Moodle online teaching platform, this research develops a mobile learning and resource sharing mode for college english translation based on 5G mobile communication technology, designs and implements a mobile learning model based on Moodle platform, and designs the system architecture, functional modules, learning mode and learning process, Finally, the main functional modules of the system model are implemented and tested. To promote mobile learning in the teaching field to play a helping role in a wide range. The experimental results show that the AKAZE algorithm is used to optimize the model, and the overall accuracy rate reaches 74.7%, and the test probability value P (siq)=0.00, which is significantly less than the significant level of 0.05. Therefore, we believe that the application of mobile learning instructional design mode will help students improve their academic performance.

Research on Fault Prediction and Health Management System of Power Electronic Devices Based on Computer Deep Learning Algorithm

This paper proposes a power equipment maintenance management system based on network and deep learning algorithm. First of all, the actual power network equipment maintenance and maintenance management of the power company, so as to clarify the tasks to be completed by the system. ASPNET technology is used to realize the management of business form data and various transaction processes of each system, and the related technology of process engine is applied to the maintenance of each equipment. A load forecasting method of power system based on SVR is proposed. It makes the operation and maintenance work of this system more intelligent. Each function module of the whole system is designed in detail. The system basically meets the needs of power equipment maintenance and repair management.

Design and Implementation of Booth Supply System Based on Internet Plus.

With the arrival of the Internet Plus era, the traditional vendor market management mode is facing severe challenges. The purpose of this paper is to propose an innovative management mode through the design and implementation of a stall supply system based on the Internet to solve the problems existing in vendor market management and better promote economic development and social stability. This paper first analyzes the characteristics and challenges of the vendor market in the Internet Plus era. Then, based on the idea of Internet Plus, we propose a design scheme for the vendor supply system, including system architecture, functional modules, and key technologies. In the following section, we elaborate on the implementation steps of the system, including system requirements analysis, database design, and system development. Finally, we verified the feasibility and effectiveness of the system through an actual case study and performed a comprehensive evaluation and in-depth analysis of the operation of the system. The research results show that the vendor supply system based on the Internet can realize the distributed management of the vendor market and optimize the allocation of resources, improve the efficiency and competitiveness of the market, and provide a reference for the development of the traditional vendor market.

SafeCity: A Heterogeneous Mobile Crowd Sensing System for Urban Public Safety

As important indicators of urban public safety, Public Safety and Environmental Security (PSES) is related to residents’ living security and greatly affects their quality of life and happiness index. Due to PSES characteristics such as diverse forms, wide distribution, and unpredictable occurrence times, traditional solutions consume huge manpower and time in the implementation process. Although some professional software and hardware systems have emerged to assist in solving the problems, there are still challenges such as limited sensing coverage and monotonous sensing modes, lack of interaction and understanding between systems and tasks, and scarcity of effective system architecture and functional modules. To meet these challenges, we design a PSES multi-terminal fusion system (SafeCity) based on the idea and technology of heterogeneous mobile crowd sensing. With collaboration among Humans, Machines, and Things (H-M-T), the proposed system makes full use of the idle mobility, sensing and computing resources in the city, and systematically provides a solution to the various PSES issues. Apart from the system architecture, functions, core mechanism, and algorithm libraries, the task execution flow is explained in depth through the description of several cases. We implement a prototype to verify the rationality and effectiveness of SafeCity. And comprehensive comparison and evaluation show that SafeCity is far superior to other solutions in terms of function, performance, and stability.

Analysis of using big data to achieve precise employment of college students

Abstract In order to solve the social phenomenon of difficult employment of college students, this paper constructs a college employment recommendation platform based on an improved collaborative filtering algorithm. Firstly, the framework of the employment recommendation system is designed for the user use case, system architecture, system function module, database and user portrait of the platform, respectively. The functional modules are divided into six module parts: campus recruitment management, internship management, employment information management, employment affairs management, employment analysis management, and employment guidance management. Next, the platform is analyzed to combine the recommendation algorithm of collaborative filtering algorithm and clustering technology based on users and items to realize the recommendation of employment information for college students. Then the employment platform is used to get the high stickiness of users in the employment of college students, which can retain about 62% of the number of people, and even 5% of the number of people are particularly fond of the platform. With the increase in recommendation times, the recommendation accuracy increased from 22% to 83%, and the accuracy increased by about 61%, and the comparison with the traditional employment form is much higher than the traditional method in both accuracy and recall rate by about 30%. It is concluded that using the college employment recommendation platform can realize the precise employment of college students.

AI-Based Mean Field Game against Resource-Consuming Attacks in Edge Computing

With the rapid development of edge computing, a new paradigm has formed for providing the nearest end service close to the data source. However, insufficient supply of resources makes edge computing devices vulnerable to attacks, especially sensitive to resource-consuming attacks. This article first designs system function module, aiming to deal with resource-consuming attacks based on the general three-layer architecture of edge computing. Combined with the mean field game, an anti-attack model is designed to transform the security defense problem of large terminal-edge-cloud devices into the mean field countermeasure problem, and the self-organizing neural network is used to approximate the mean field coupling equation. On this basis, a distributed AI-driven resource-consuming attack security defense (ARASD) algorithm is designed to obtain the optimal solution for devices security interaction, thereby improving the system’s anti-attack ability. Finally, the effectiveness of the self-organizing neural network is verified through numerical simulation, and the parameters such as the number of initial terminal-edge-cloud devices and the number of iterations of different security defense algorithms are evaluated. The results show that the ARASD algorithm can achieve better resistance to resource-consuming attacks than other state-of-the-art algorithms in a large-scale edge computing architecture.

RETRACTED: Research on the mechanism and efficiency of agricultural products logistics transportation based on big data

AbstractIn order to improve the efficiency of agricultural product logistics transportation, based on big data technology, this paper starts from the factors that affect the efficiency of agricultural product logistics and combines big data technology to conduct the research on the mechanism and efficiency of agricultural products logistics transportation. Moreover, this paper analyzes how to improve the efficiency of agricultural product logistics by studying the dynamic relationship between influencing factors and the efficiency of agricultural product logistics. At the same time, this paper takes the efficiency evaluation of agricultural product logistics transportation network as the research object to improve the agricultural product data analysis algorithm, and constructs the system model from the perspective of the supply chain. In addition, this paper constructs system function modules according to the actual needs of agricultural product logistics transportation, and analyzes agricultural product transportation logistics by factor analysis. Finally, this paper verifies the effect of the model proposed in this paper through experimental research. From the test results, it can be seen that the model proposed in this paper basically meets the actual needs.

Comprehensive Evaluation Method of Supply Chain Logistics System Quality Based on 3D Image Processing Technology

With the rise of manufacturing informatization, many transactions are conducted on the Internet, but the final form of transaction completion is the transaction of actual products, which makes the logistics industry emerge as the times require. How to achieve the optimal allocation scheme and the fastest efficiency in the supply chain has become an urgent problem to be solved. This paper considers the characteristics and advantages of 3D image processing technology, describes the characteristics of 3D image processing supply chain (SC), and analyzes the channels that 3D image technology affects SC. Combining the respective characteristics of fuzzy theory and grey theory, the two theories are combined to develop strengths and circumvent weaknesses to form grey fuzzy theory. Comprehensive evaluation of supply chain logistics capability can achieve better evaluation results. The application of grey theory in this chapter includes constructing the factor set of the evaluation index system and determining the weight matrix of the factor set with the game method. The grey fuzzy evaluation weight matrix (i.e., single index evaluation result) is determined with the grey theory, and the fuzzy comprehensive evaluation result is finally calculated. This paper studies the supply chain logistics capability evaluation and optimization system from the aspects of system analysis, system function module design, and system architecture design and analyzes the overall goal, demand, feasibility, system business process, and data flow of the system construction. At the same time, this paper designs the supply chain logistics capability evaluation and optimization system and shows some functional interfaces. It is of great significance to improve the responsiveness, total inventory level, total cost level, supply chain performance, agility, and flexibility of the supply chain in the new environment.

Development and Application of MOOC System for English Intercultural Communication Courses Using Neural Network

Presently, many researchers are focusing on the English intercultural communication course. However, these courses face serious challenges, such as individual student variances in conventional English cross-cultural teaching, fostering students’ cross-cultural communication abilities, and enhancing teaching quality. These problems need to be solved; therefore, this paper aims to explore the development and application of the Massive open online courses (MOOCs) system in the English cross-cultural communication course based on neural networks. Firstly, the overall function modules of the MOOC system for the English intercultural communication courses are described, with emphasis on the student function module, teacher function module, administrator function module, and system database design of the MOOC system. Second, the MOOC system’s teaching technique in an English intercultural communication course is based on a genetic algorithm, and the MOOC system’s teaching quality index in an English intercultural communication course is chosen using principal component analysis. We conducted several tests to demonstrate that the MOOC system of the English intercultural communication course using the neural network suggested in this work is resilient and may successfully increase teaching quality. The experiment proves that the MOOC system of the English intercultural communication course based on the neural network developed in this paper has efficient results as compared to existing studies. In addition, it can effectively improve the teaching quality and can train students’ intercultural communication skills and their ability to adapt to intercultural communication.

Application of Symmetric Encryption Algorithm Sensor in the Research of College Student Security Management System

In order to solve the problem of information leakage in the process of college students’ information security management, this paper proposes a design of college students’ security management system based on a symmetric encryption algorithm. The system is based on the principle of the symmetric encryption algorithm and follows the principle of encryption independence to ensure the security and reliability of the system. The general framework of the system is analyzed in detail. Secondly, the security and database of system function modules are designed, and finally, the performance of the system is tested. The results are as follows: the safety management system designed in this paper has obtained satisfactory evaluation in the trial universities, accounting for 93% of the trial population. It is proved that this system has clear authority design, high efficiency, and security. Managers can query students’ basic information, students’ real-time location, alarm data information, and so on in real time, which can ensure students’ safety to the greatest extent.

Design of Travel Route Identification and Scheduling System Based on Artificial Intelligence-Aided Image Segmentation.

This study designs a travel recognition and scheduling system using artificial intelligence and image segmentation techniques. To address the problem of low division quality of current point division algorithms, this study proposes a streaming graph division model based on a sliding window (GraphWin), which dynamically adjusts the amount of information (vertex degree information and adjacency information) referenced at each division according to the current division quality and division time by introducing a sliding window mechanism, to achieve the highest possible division while allowing loss of certain division efficiency. The goal is to improve the division quality as much as possible while allowing a certain loss of division efficiency. To meet the user's need to travel through multiple destinations with the shortest route, this thesis proposes a deep reinforcement learning actor-critic (AC)-based multiobjective point path planning algorithm. The algorithm builds a strategy network and an evaluation network based on actor-critic's multiobjective point path planning, updates the strategy network and evaluation network parameters using AC optimization training, reduces the reliance of the algorithm model on a large amount of high-quality label data, and speeds up the convergence speed of the deep reinforcement learning algorithm by pretraining, finally completing the multiobjective point access sequential path planning task. Finally, the personalized travel recommendation system is designed and implemented, and the system performance analysis is conducted to clarify the system requirements in terms of functional and nonfunctional aspects: the system architecture, system functional modules, and database tables are designed to conduct use case testing of the main functional modules of the system, and the usability of the attraction recommendation algorithm is verified through the concrete implementation of the functional modules such as attraction recommendation in the system.

Innovation of Ideological and Political Education Management of College Students Based on IOT Big Data Technology in a Wireless Network Environment.

Universities are not only the front line of national ideological and political works but also the gathering place of national talent training, which is of far-reaching significance to the national strategic development, and it is vital to do a good job of ideological and political education in universities for the construction and development of the country. “The university has become a place where wireless network technology can be used. The paper examines the current state of mobile learning in the United States and abroad, explains the principles for developing a mobile ideological and political learning system, designs and studies the system's overall structure and functional modules, and shows how the system's application can replace traditional ideological and political learning methods, allowing students to improve their ideological and political abilities using mobile devices.

Current trends and future perspective of designing on-chip antennas

AbstractWith the evolution of 5G and 6G network architectures, the demand for highly compact system-on-chip-based devices with high data transfer capabilities has been increased significantly. While the advancement of very large-scale integration technology with the continuous scaling of complementary metal–oxide–semiconductor nodes put forward to integrate different functional modules of a complete system on a single IC board, the antenna being the largest component still remains outside of the chip. Integration of the antenna and other functional modules of a system on the same chip leads to produce a really compact and economical design. Though on-chip antenna (OCAs) have several other advantages and emerging applications, they have some design challenges in terms of low gain due to losses in the substrate, requirement of miniaturization at lower microwave frequencies (LMFs) (particularly, below 10 GHz), unavailability of proper design rules, etc. In this paper, analyzing the design challenges of OCAs, their current research trends and future perspective applications are discussed.

Design of Multichannel Multirate Signal Acquisition System Based on FPGA

With the continuous advancement of science and technology, the fields of national defense, astronomy, industry, agriculture, and so on often require real-time acquisition of voltage, current, temperature, pressure, flow, and other signals, and the real-time requirements for signal acquisition are getting higher and higher. The traditional temperature acquisition method is to use the single chip or DSP as the control core to design the temperature monitoring system. However, this method has certain defects and cannot meet many high-demand signal acquisition occasions. On the one hand, most functions of this system are realized by software, and the operation of software will occupy part of the system sampling time, thus reducing the system sampling rate; on the other hand, the logic of the system to complex peripheral circuits cannot be well controlled. And Field Programmable Gate Array (FPGA) has characteristics such as parallel processing, controllability, and processing speed; therefore, the signal acquisition system with FPGA as the control core can realize high-speed signal collection. This paper studies the signal acquisition based on FPGA. In the signal acquisition system, FPGA is the control core of the whole system, and the relevant function modules of the control system complete the signal acquisition task. The acquisition control module is mainly to control the channel selection switch and the A/D converter to work, that is, to generate the logic control signal of multichannel selection and the control sequence of A/D conversion, so as to complete the acquisition and control of the multichannel analog input signal. The FPGA-based signal acquisition control system has the characteristics of short development cycle, flexible design, low cost, and high reliability. FPGA is an ideal architecture for signal acquisition, and the FPGA-based signal acquisition technology has very broad application prospects.

Network Education Resource Information Sharing System Based on Data Mining

To enter a new stage of development of education informatization, network education has become a global trend of education training, the development of lifelong education, and resource sharing platform for higher vocational colleges to some extent, with network technology and multimedia technology as the core of the rapid development of modern information technology. The sharing of network education resource sharing system and the application in the whole advancement provide the conditions, it promotes the construction and development of higher vocational education resource system. This study examines the problems that exist in the construction of higher vocational college education resources, such as unreasonable management of education resources, unclear goals of higher vocational colleges, and unclear school-enterprise cooperation, based on the research status and achievements of higher vocational college education resources at home and abroad. On the basis of combing and analyzing the related concepts, theoretical basis, and construction principles of higher vocational education resources, the paper designs the network sharing system of higher vocational education resources in detail from its design objectives, design ideas, user needs, overall framework system, hierarchical structure, and functional modules. The core part is the realization of system function modules, including the resource management function module, system management function module, and user management function module. At present, domestic scholars have carried out a lot of research on the construction of basic education network resources. Although the research focuses on resource allocation, coconstruction and sharing mechanisms, and the current state of building and development methods, it also serves as a guide for the development of basic education network resources. However, most of these research results analyze problems from the qualitative perspective, and most of the research results are speculative research at the macro level, lacking practicality. With the rapid development of network education, the construction of network resource libraries is developing in the direction of intelligence and individuation to meet the different learning needs of learners. Based on the analysis of the problems encountered by learners in using the resource library for learning, this paper puts forward the application of data mining technology (DM) to guide the construction of the resource library and discusses how to improve the organizational structure of the resource library, improve the utilization rate of the resource library, and adapt to personalized learning. At present, the system is still in the system testing and experience stage, through the continuous testing of relevant functional modules, further improves the function of the sharing system, and constantly increases the scalability of the system function, in order to establish a perfect, comprehensive, and nationwide higher vocational education resource network sharing system.

Research on Design Method of Intelligent Operation and Maintenance System for Secondary Equipment in Intelligent Substation

Abstract Smart substations are an important part of establishing a strong smart grid. In view of the large variety of secondary equipment in the current power system, the rapid increase in quantity, and the complex working conditions of the current power supply company maintenance classes to inspect substations, a design method for the intelligent operation and maintenance system of secondary equipment in smart substations is proposed in this article. First, the intelligent operation and maintenance system architecture of the secondary equipment of the smart substation is established via Redis and ActiveMQ technologies. Then the system function module model is established. Finally, taking a 220kV substation in a certain area of southern China as an example, a new type of intelligent substation secondary equipment intelligent operation and maintenance system was installed and connected to the main line system, and the effectiveness of the proposed method was verified.

Development of the Music Teaching System Based on Speech Recognition and Artificial Intelligence

Intelligent music teaching is the direction of subsequent reforms in music teaching methods. In order to improve the intelligence of music teaching, this paper conducts research on speech recognition technology. The speech conversion system based on Multiscale Star GAN extracts different levels of multiscale features of the global features of music utterance through the multiscale structure, which enhances the details of the converted speech and uses residual connections to alleviate the problem of gradient disappearance and enable the network to spread more deeply. In addition, after improving the speech recognition algorithm, this paper combines the needs of music teaching to construct a music teaching system based on speech recognition and artificial intelligence and designs system functional modules. Finally, this paper evaluates the performance of the system constructed in this paper by means of teaching experiments. From the experimental analysis, it can be seen that the system constructed in this paper has a good teaching effect.

Analysis of Communication Compression and Transmission in a Multimedia and Internet of Things Environment Integrating Scene Elements

In order to improve the effect of multimedia data transmission, this paper integrates scene elements to analyze the needs of multiple types of data transmission and uses the technology of the Internet of Things to analyze the compression and transmission of multimedia data communication. Moreover, this paper proposes a reversible information hiding algorithm for encrypted images based on pixel sorting and grouping prediction and discusses how to improve the prediction accuracy through the histogram of prediction errors. In addition, this paper designs a communication compression transmission system in a multimedia and Internet of Things environment integrating scene elements and builds system function modules and system processes. Finally, this paper verifies the performance of the proposed system by means of simulation experiments. From the experimental results, we can see that the system proposed in this paper has a good multimedia information transmission effect.

WITHDRAWN: Development of Music Teaching System based on Speech Recognition and Artificial Intelligence through Optic Communication

Intelligent music teaching is the direction of subsequent reforms in music teaching methods. In order to improve the intelligence of music teaching, this paper conducts research on speech recognition technology through optic communication. The speech conversion system based on Multi-Scale Star GAN extracts different levels of multi-scale features of the global features of music utterance through the Multi-Scale structure, which enhances the details of the converted speech, and uses residual connections to alleviate the problem of gradient disappearance and enable the network to spread more deeply through optic communication. In addition, after improving the speech recognition algorithm, this paper combines the needs of music teaching to construct a music teaching system based on speech recognition and artificial intelligence, and design system functional modules. Finally, this paper evaluates the performance of the system constructed in this paper by means of teaching experiments through optic communication. From the experimental analysis, it can be seen that the system constructed in this paper has a good teaching effect.