Construction Of Information Platform Research Articles

Application Requirements of Artificial Intelligence in the Field of Building Materials Informatization

Under the background of the continuous development of information technology, strengthening the construction of grassroots material management information platform of construction industry projects is conducive to promoting the information development of construction industry and improving the economic benefits of enterprises. For the construction industry, material management is not only to ensure the supply demand and normal operation of the project site, but also an important part of the profits of each project. However, the information platform of construction enterprises often has problems such as cumbersome operation, low professional level of operators, repeated and cumbersome data recording. Moreover, the large amount of data in the grassroots construction project department can rarely be effectively used, and the large amount of data recorded by the system rarely forms historical data through analysis and forms empirical data for the enterprise. From the perspective of optimization of information platform by artificial intelligence technology, this paper describes the existing problems of information platform for building materials management, analyzes the development needs of information management for grassroots materials in construction industry projects, and then takes the price analysis of steel reinforcement materials in material management as an example to illustrate. A constructive idea is put forward for the optimization scheme of artificial intelligence technology embedding information platform.

Digital Government Information Platform Construction: Technology, Challenges and Prospects

The construction of digital government information platforms plays a crucial role in modern governance. This paper provides an in-depth exploration of the technology, challenges, and prospects associated with these platforms. Firstly, it analyzes the technological aspects, emphasizing the utilization of advanced technologies such as big data, cloud computing, and artificial intelligence to build efficient and integrated government information systems. The integration of these technologies can significantly enhance the accessibility and usability of public services, contributing to the overall effectiveness of governmental operations. Secondly, it delves into the challenges that accompany the development and implementation of digital government information platforms, including data security, privacy protection, and addressing the digital divide among citizens. Overcoming these challenges is essential to ensure the successful deployment and widespread adoption of digital government platforms. Lastly, the paper discusses the prospects, highlighting the potential for improved public services, enhanced transparency, and more effective decision-making through the utilization of digital government information platforms. By examining the opportunities offered by these platforms, such as increased citizen engagement and streamlined administrative processes, this research contributes to an understanding of their comprehensive impact on governance and public administration.

The Construction of Information Platform of Ideological and Political Education in Universities Based on Information Diffusion Model

Abstract This paper examines the role of the information diffusion model in constructing ideological and political education information platforms in colleges and universities. The degree of information diffusion is calculated by establishing the diffusion coefficient to estimate the number of two-dimensional information diffusion losses combined with the two-dimensional information diffusion loss function of information sample points. The optimization of the information diffusion maximization algorithm improves the accuracy of calculating information diffusion, and the evaluation index of information diffusion maximization is formulated to judge the degree of information diffusion. The results indicate that the Civic Education Information Platform is highly practical. The functional index scores are all above 70 and have usability, among which the functional practicality index has the highest score, with an index score of 77.21. The information technology platform is effective. The correct rate of students completing questions on the platform is generally above 75%.

Scalability and Sustainability in the Construction of a Social Sports Management Information Platform based on Web Technology

Scalability and Sustainability are a major traits that a website requires. Moreover, in Social sports management, information platforms must be reliable. Thus, different tools for developing a platform based on web technology are discussed in an empirical study for the purposes mentioned earlier. For the study, secondary data was analyzed, and qualitative methods were used. In addition, it was noticed that there are some problems related to a web technology-based platform. It was found that an improved development strategy in the beginning aids in traffic management. In addition, an improved tech stack is directly related to the data analysis process of a sports management system. A lack of such factors in the construction process reduced the scalability and sustainability of a social sports management information platform. Thus, a complete discussion aimed at understanding the sustainability and scalability of a web management platform is done.

DMAIC Model’s Relative Efficiency Analysis of Input and Output in Cultural Construction of University Library and Mental Health Education of College Students

Abstract To solve the problems in the construction of the internal quality assurance system in some colleges and universities, such as the difficulty in forming the quality culture, the imperfection of the system construction, and the insufficiency of the information platform construction, etc. By analyzing the five stages of the DMAIC model, the process of diagnosis and improvement is proposed, and from the definition stage, measurement stage, analysis stage, improvement stage, control stage, the improvement strategy of diagnosis, and improvement of internal quality assurance system is described. Through the application of the DMAIC model in actual cases, it can provide ide reference for the construction of internal quality assurance systems in colleges and universities. According to the BCC model in the DEA model, the author studies the relative effectiveness of the input and output of 12 university libraries in China. The results show that university libraries with effective technology accounted for 66.67%, while those without effective technology accounted for 33.33%, it also analyzes the investment changes of non-technical effective university libraries. This has an important reference and inspiration to improve the management of university libraries.

Research on the Construction Path of China's Zero-carbon Ports from the Perspective of Marine Carbon Sink Trading

At present, the international market has gradually carried out research on forecasting the trading price of carbon emissions with macroeconomics and energy market as the main influencing factors, supplemented by other factors such as policy factors. In order to speed up the construction of carbon accounting system, enrich the content of China's carbon pricing mechanism and improve the carbon emission trading market, this study constructs an index system from four aspects: macro-economy, energy price, climate environment and international market, and objectively screens out the important influencing factors of carbon trading price through Lasso regression, and uses BP neural network prediction model to predict carbon trading price. [7] We should focus on reducing the proportion of coal consumption by port enterprises and increasing other clean energy consumption. This result can provide basis and reference for the construction of zero-carbon ports and the construction of ocean-port carbon trading information platform in China.

Key Technologies of Marine Environment Safety

An increasing number of marine disasters and maritime accidents occurred frequently in coastal area of China which lead to giant loss of life and property in recent years. In response to those disasters and accidents, China had put enormous effort into ocean observation, disaster prediction and forecasting, risk assessment and informationization, which lead to the preliminary improvement on safety capability of marine environment. In this paper, China’s marine environment safety situation are analyzed for concluding the insufficient research on Multi-source Information Aggregation, Assistant Decision-Making, Emergency Dispatching and relevant informationization. Hence plenty of key technologies as Multi-source Information Aggregation and Fusion, Dynamic Risk Assessment, Scenario Deduction, Command Coordination and Information Platform Construction Technology are also analyzed for feasible implementation mean and possible development direction..

Construction and Practice of Teaching Staff and Teaching Quality Monitoring System in University Affiliated Hospitals Under the Background of Education Informatization

Objective: To build a set of teaching staff construction and teaching quality monitoring system suitable for clinical practice teaching in affiliated hospitals of medical colleges, achieve continuous improvement of clinical education and teaching level, and ensure the quality of medical education talent cultivation. Methods: A modern clinical practice teaching quality monitoring system is constructed based on organizational structure construction, teaching staff system construction, quality control system construction, and information platform construction, combined with external audit and evaluation. Results: The hospital has established a Faculty Development and Teaching Evaluation Office specifically responsible for the cultivation of clinical teachers and the evaluation and supervision of teaching quality. A relatively complete teacher construction and teaching quality monitoring system has also been established for clinical practice teaching, thus achieving integration with the school’s quality control system in terms of management mechanism. At the same time, a set of teaching quality control mode based on the “Internet +” platform has been created by means of informatization. At present, this mode has won three national computer software copyrights and two second prizes for school-level teaching achievements. Conclusion: Through five years of practice, an “Internet +” teaching quality evaluation and monitoring system with the characteristics of teaching hospitals affiliated to local medical colleges has been established. In order to further standardize the training system of clinical teachers in affiliated hospitals, achieve self-monitoring and self-improvement in terms of teaching quality, and ensure the continuous improvement of clinical teaching quality, we will continue to promote the development of clinical teachers with quality and excellence, enrich the main team of quality monitoring, guide the transformation of the education mode from being “centered on teachers” to being “centered on students,” and realize the integration of internal and external quality monitoring systems.

Construction of smart older adults care service model driven by primary health care.

In recent years, with the arrival of an overall aging population, how to provide for the elderly has become the focus of government departments and society. The traditional elderly care service model has problems such as backward construction of information platforms, low quality of elderly care services, and "digital divide". For this reason, based on grassroots medical and health care, this paper improves the quality of elderly care services by establishing a smart elderly care service model. Through experiments, it can be found that compared with the traditional elderly care service model, the intelligent elderly care service model has an absolute advantage in the identification of nursing data. The recognition accuracy rate of the smart elderly care service model for all kinds of daily care data is above 94%, while the recognition accuracy rate of the traditional elderly care service model is below 90%. Therefore, it is of great significance to study the smart elderly care service model driven by primary medical care and health.

Thoughts on the construction of public health informatization for community health archives grass roots management system.

With the development of social economy and the continuous improvement of people's living standards, people expect to receive high-level medical services, and the requirements for medical care are also getting higher and higher. However, there are still objective problems such as rising medical costs, difficulty in seeking medical treatment, uneven distribution of medical resources, low efficiency of medical services, and uneven medical quality. This paper first analyzes the significance of public health informatization construction, focuses on the elements of public health informatization construction, and expounds the status quo of health informatization construction and the existing problems in community health informatization. Then, this paper expounds the construction of public health informatization based on the grass-roots management system of community health records, and discusses the construction of a health information platform centered on the health records of community residents. Afterwards, this paper proposes and studies the functions of the community medical information archives management system from three aspects: the composition of the community medical information archives management system, the problems of system management, and the development requirements of the system, and proposes an algorithm based on a decision tree model to enhance public health informology. Finally, on the basis of experiments and investigations, Internet technology and decision tree model algorithms are introduced into the public health information system construction of the community health archives system to build a new public health information system, and the satisfaction rate can be increased by 23%.

Study on the harmonious development of regional logistics coordination and the geographical environment from a low-carbon perspective

It is clarified that evolutionary conditions are the premise and foundation of the study of evolutionary dynamics, and the study of evolutionary dynamics is the basis for the division of evolutionary stages and their characteristics. Secondly, in the study of evolutionary conditions, it is argued that internal and external environmental conditions, dissipative structural conditions, and rising and falling conditions are the specific evolutionary preconditions of coordination in the perspective of a low carbon economy. The harmonious development of regional coordination and ecological environment is an important guarantee for the sustainable development of the region. This paper provides an in-depth study and analysis of the coordinated development of regional coordination and the geographical environment through a low-carbon perspective. Firstly, the three relationships of evolutionary conditions, evolutionary dynamics, and evolutionary stages are analyzed through the analysis of the applicability of self-organization theory in the study of coordination evolution from the perspective of a low-carbon economy. First, we take the composite system of “coordination and ecological environment” as the research object, and use the theory of cooperation to construct a scientific and systematic index system of orderly parameters of the coordination subsystem and ecological environment subsystem, and establish the model of the orderliness of subsystem and the model of coordination of the composite system. Finally, we analyze the reasonableness of the calculation results based on the development of coordination and ecological environment and propose countermeasures from three aspects: the formulation of regional development policies and regulations, the construction of regional coordination public information platform, and the optimization of the energy structure of the coordination industry.

Research on English Education online Learning Platform based on Big Data of Education

In the modern social economy and technological innovation and development, education big data technology research is the main issue of scientific research. According to the accumulated experience of education innovation in recent years, the construction and promotion of big data network information platform can provide more convenient conditions for English education, but most colleges and universities have not realized the importance of network teaching mode, nor have they strengthened the research on network teaching technology in the era of big data. Therefore, on the basis of understanding the development trend of big data of education, this article discusses the design structure of network learning platform of English education deeply, and puts forward effective educational reform measures according to the problems faced by Chinese colleges English education.

Design of College Online Resource Sharing and Practice Platform Assisted by Opensource Public Cloud Big Data

The educational resource sharing platform is designed and developed with open source tools such as Spark computing engine, Hive data warehouse, MySQL database, InfluxDB timing library and Akka toolkit. Combined with the characteristics of private cloud computing technology, it gives full play to the advantages of cloud computing, which can save investment costs, provide secure storage and improve the level of resource sharing in the construction of information platforms. Design and implement an educational resource sharing scheme; implement a resource search algorithm based on a complex network-based resource search model; design and implement the platform's resource processing module, blog module, circle module, user management module, etc.

Research on English Education online Learning Platform based on Big Data of Education

In the modern social economy and technological innovation and development, education big data technology research is the main issue of scientific research. According to the accumulated experience of education innovation in recent years, the construction and promotion of big data network information platform can provide more convenient conditions for English education, but most colleges and universities have not realized the importance of network teaching mode, nor have they strengthened the research on network teaching technology in the era of big data. Therefore, on the basis of understanding the development trend of big data of education, this article discusses the design structure of network learning platform of English education deeply, and puts forward effective educational reform measures according to the problems faced by Chinese colleges English education.

Network Information Platform Construction Based on Computer Data Mining and Processing

Network Information Platform Construction Based on Computer Data Mining and Processing

Research on Promoting Reading in University Libraries in the Era of Artificial Intelligence

With the rapid development of artificial intelligence technology, the reading promotion services of libraries are facing new opportunities and challenges. It is necessary to transform from traditional modes to intelligent modes in order to meet the diversified and personalized reading needs of readers. This article takes demand-oriented approach and explores the implementation path of promoting reading in university libraries in the era of artificial intelligence from four aspects: intelligent resource construction, intelligent information platform construction, training of reading promotion personnel, and creation of intelligent reading promotion services. The aim is to provide reference and inspiration for improving the level and quality of reading promotion services in university libraries.

Performance management algorithm of financial shared service center based on Internet of Things public cloud privacy protection.

The Internet of Things (IoT) refers to the use of various communication technologies to achieve the interconnection of everything in cyberspace, and to achieve smart home and intelligent transportation, thus generating unprecedented amounts of data. In the financial sharing center, all businesses can extract effective data from these massive databases for analysis, and use data analysis tools to collect business, financial, human, process, knowledge and social data. At present, various types of IT (Internet Technology) systems have been widely used in financial sharing centers. However, a large number of sensitive data have also been generated. In order to protect these sensitive data, there is a high requirement for the personal information of IT system operation and financial sharing center personnel. In order to protect user data privacy, the optimal and most effective use of IT systems is an important issue that must be considered in privacy management. At present, there are many algorithms to protect data and privacy, but the effect is not ideal. Considering the balance between privacy issues, this paper proposed a K-means clustering algorithm based on IoT public cloud privacy protection technology to analyze the performance management of financial sharing center. The research results showed that before the improvement, the average number of employees who were dissatisfied with the post training ability and information platform construction ability of the financial sharing center was 57.9 and 57.8% respectively, more than half of them. After the improvement of IoT based public cloud privacy protection, the average number of employees dissatisfied with the post training ability and information platform construction ability of the financial sharing center was 5 and 3.9%, far less than the data prior to the improvement. It showed that IoT public cloud privacy protection was conducive to the performance management of the financial sharing center, and the relationship between the two was positive.

A data cube modeling method for longitudinal cohort study

Longitudinal cohort study is an effective way to probe into the risk factors of disease and evaluate intervention measures. It has gradually become the mainstream research method in precision medicine, chronic disease management and evidence-based education, and has been deployed in many National Science and Technology Major Projects, which established its specialized cohorts for natural populations, chronic diseases, specialized diseases. The quality of data is a make-or-break factor of longitudinal cohort study. The subjects and test tasks in longitudinal cohort study have dynamic changes over time, and the data generated involves multiple modalities and scales. Therefore, exploring how to model business-oriented longitudinal cohort data will contribute to a unified understanding and governance of longitudinal cohort data, and ultimately improve data quality. On the one hand, because different modal data in longitudinal cohort study have different dimensional indicators, it is difficult to carry out data modeling based on unified dimensional indicators through simple dimensional splicing; on the other hand, the needs of the longitudinal cohort management scenario determine the calculations should be focused on the granularity of individual subjects and data modal types. Considering the above, the traditional multi-dimensional data modeling method based on data dimension indicators and their measurements as basic elements couldn’t be fully adapted to the counting and statistical requirements under the longitudinal cohort scenarios. This paper proposes a data cube model based on MOLAP named SubTaP, which take multimodal data objects as basic granularity. This model constructs a cube structure with three dimensions of Subject, Task and Phase. It can be applied to meet the visualization requirements of longitudinal cohort management scenario and guide the construction of a data information platform for cohort study. At the same time, it helps to build a unified understanding of longitudinal cohort study data among data generators, cohort maintainers, and data users.

Logistics Finance Collaborative Development Model Based on Machine Learning.

In the context of rapid social development, a logistics financial model that can meet the financing needs of small and medium-sized enterprises and has high returns is widely used in all aspects of the logistics financial industry. Logistics finance is a new financing model that can effectively integrate logistics enterprises, financial companies, and financing institutions to achieve mutual benefit and win-win results. The uncertainty of financial information, the motivation of each business service object to pursue high returns in a short period of time, and the inadequate risk preuniversal conditions have led to credit risks in the development of logistics financial services. Promoting the close integration of improved neural network algorithms based on machine learning and logistics financial financing models is inseparable from the active cooperation of all aspects, the trust of various business service objects, and the construction of logistics financial information platforms. Based on machine learning, this paper analyzes and models the collaborative development of logistics finance, analyzes the original data, and constructs sample characteristics. Due to the small amount of information in part of the sample features, this causes problems such as overfitting in the process of model building. Therefore, we designed a new feature selection based on Pearson correlation coefficient and PCA. Method. Using this algorithm for feature selection, an integrated learning method is proposed. In order to solve the shortcomings of traditional neural network logistics algorithms, a neural network-based noncomplete vehicle path optimization mining model is proposed. By weighting the time domain length and spatial probability of logistics finance, the stable state of the neural network is restricted. Simulation results show that this method can effectively improve logistics efficiency and maximize the economic value of the transportation process.

Digital technology-driven smart society governance mechanism and practice exploration

A smart society is an advanced form of society following agricultural society, industrial society, and information society, with digital data processing system as its main carrier. However, the governance of a smart society still faces many challenges. In view of this problem, first, this research constructs a smart society governance modernization strategy. Second, the innovation mode of a society governance mechanism driven by digital technology is proposed, including the precise intellectual control of a digital twin, the intelligent ubiquitous sensing of the Internet of Things, the empowerment remodeling of a blockchain and the livelihood service of artificial intelligence. Third, this study systematically explores the practice of smart society governance modernization from the aspects of basic information platform construction, evaluation system construction, application demonstration of epidemic prevention and control driven by big data, support of spatial intelligence and artificial intelligence technology for people’s livelihood, smart campus, public resources, and data governance application demonstration to provide theoretical guidance for promoting digital technology innovation in the process of the governance of a smart society.