Management and control review system capable of realizing classified storage

Abstract

The invention discloses a management and control review system capable of realizing classified storage, and particularly relates to the technical field of science and technology project review, the system comprises a project information input module, and the output end of the project information input module is connected with a material uploading and preliminary classification module; the output end of the material uploading and preliminary classification module is connected with an expert intelligent matching module and a review rule setting module, and the output end of the expert intelligent matching module and the output end of the review rule setting module are connected with a file automatic identification module. During project declaration, operation of a person in charge is facilitated, efficiency is improved, accurate feedback is provided, accuracy and fairness are improved for review experts, professional matching is ensured, tasks are clarified, an auxiliary module improves accuracy and fairness, experience sharing is promoted for an expert community, review quality is improved on the whole through multiple modules, valuable projects are screened, and efficient storage management is achieved. Big data assists decision making, and the public participates in increasing transparency and innovative ideas.

Description

Technical Field

[0001] The present invention relates to the technical field of scientific and technological project evaluation, and more specifically, to a management and control evaluation system capable of realizing classified storage. Background Art

[0002] In today's era of rapid technological development, in order to solve major scientific and technological problems in production, construction and business development, enterprises are actively promoting and facilitating the improvement of their own technological level, modern management level and economic benefits. The importance of scientific and technological projects is becoming increasingly prominent, and it is crucial to lay a technical and equipment foundation for the company's development.

[0003] In recent years, with the continuous increase in power grid science and technology projects and the continuous improvement in the research quality of provincial company science and technology projects, the review of science and technology projects has become more and more complicated. Although each node of the current science and technology project review has been strictly standardized and streamlined, due to the insufficient application of intelligent technology, problems in the review process have gradually emerged; the verification and classification storage of application materials are not accurate enough to meet the growing number and quality requirements of projects; there is a lack of effective means to ensure the integrity and authenticity of the review materials, and it is difficult to adaptively adjust the review process according to the characteristics of different projects; at the same time, the interactivity, transparency and participation in the review process are limited, which is not conducive to knowledge sharing and cooperation as well as the introduction of innovative ideas.

[0004] In order to realize the informatization and standardization of the scientific and technological project review management process, solve the problems of chaotic data management and low efficiency of the existing review method when facing a large number of scientific and technological projects, and explore a new model of lightweight review of scientific and technological projects, a management and review system that can realize classified storage came into being. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a management and review system capable of implementing classified storage to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a management and control review system capable of realizing classified storage, comprising a project information entry module, the output end of the project information entry module is connected to a material upload and preliminary classification module, the output ends of the material upload and preliminary classification module are respectively connected to an expert intelligent matching module and a review rule setting module, the output ends of the expert intelligent matching module and the review rule setting module are connected to a file automatic identification module, the output end of the file automatic identification module is connected to a compliance check module, the output end of the compliance check module is connected to a review module, and the output end of the review module is connected to a user management module; The output end of the review module is connected to a review task allocation module, the output end of the review task allocation module is connected to an opinion collection and aggregation module, the output end of the opinion collection and aggregation module is respectively connected to an integrity verification module and an authenticity confirmation module, the output ends of the integrity verification module and the authenticity confirmation module are both connected to a review data verification and archiving module, and the output ends of the review data verification and archiving module are respectively connected to a blockchain application module and a big data analysis and prediction module; The output end of the user management module is connected to a parameter setting module, and the output end of the parameter setting module is connected to a data backup and recovery module.

[0007] Preferably, the output end of the review module is respectively connected to a dynamic adaptive review module, an artificial intelligence assisted review module and a social review module; the output end of the dynamic adaptive review module is respectively connected to a process adjustment sub-module and a feedback optimization sub-module; the output end of the artificial intelligence assisted review module is respectively connected to a deep semantic analysis sub-module and a personalized suggestion sub-module; the output end of the social review module is respectively connected to an expert community sub-module and a public participation sub-module.

[0008] Preferably, the output ends of the big data analysis and prediction module are respectively connected to the review result analysis sub-module and the project trend prediction sub-module, and the output ends of the blockchain application module are respectively connected to the data recording sub-module and the smart contract execution sub-module.

[0009] Preferably, the project information entry module is used to input basic project information, project name, research field and expected results; the material upload and preliminary classification module is used to upload various application materials, scientific research reports, implementation plans and technical plans, and perform preliminary classification according to file type and preset rules; the expert intelligent matching module uses intelligent algorithms to automatically assign suitable review experts according to the field and characteristics of the project; the review rule setting module is used to determine the review standards, process nodes and required material requirements; the file automatic identification module is used to automatically identify the type, name and content of uploaded files using advanced technology; the compliance check module is used to check whether the files comply with the naming rules, file type and project-specific requirements against preset specifications.

[0010] Preferably, the review task assignment module is used to assign projects to corresponding review experts and clarify review tasks and time requirements; the opinion collection and summary module is used for review experts to submit review opinions and scores online, and the system summarizes and feeds back to project leaders and managers in real time; the integrity verification module is used to check the packaged materials after review item by item to ensure the integrity of the materials; the authenticity confirmation module confirms the authenticity of the archived materials through digital signature technology; the review material verification and archiving module is used to ensure the integrity, authenticity and standardization of the science and technology project review materials, and realize efficient classified storage and subsequent query management.

[0011] Preferably, the parameter setting module is used by the administrator to set system parameters, file naming rules and review process nodes according to actual needs, and the data backup and recovery module is used to regularly back up system data to ensure data security and quickly restore data when needed.

[0012] Preferably, the process adjustment submodule is used to automatically adjust the review process and required materials according to project characteristics, the feedback optimization submodule is used to collect user feedback and optimize the review process in real time, the deep semantic analysis submodule is used to perform deep semantic analysis on the application materials and provide a more comprehensive analysis report for the review experts, and the personalized suggestion submodule is used to provide personalized review suggestions based on the review experts' historical records and professional fields.

[0013] Preferably, the expert community submodule is an expert communication platform to promote experience sharing and knowledge exchange, and the public participation submodule is used to manage the public's review of the review project and the collection of opinions.

[0014] Preferably, the data recording submodule is used to record the review key node information on the blockchain to ensure that it cannot be tampered with, and the smart contract execution submodule is used to automatically execute operations in the review process according to preset rules.

[0015] Preferably, the dynamic adaptive review module is used to automatically adjust the review process and required materials according to the characteristics and actual situation of the scientific and technological project, so as to improve the pertinence and efficiency of the review, and at the same time collect user feedback to continuously optimize the review process. The artificial intelligence-assisted review module provides intelligent support for the review of scientific and technological projects, improves the accuracy, efficiency and fairness of the review, and the socialized review module is used to enhance the interactivity, transparency and participation of the scientific and technological project review, and promote knowledge sharing and cooperation.

[0016] Technical effects and advantages of the present invention: 1. By setting up the project information entry module and the material upload and preliminary classification module, the project leader can clearly and conveniently input the basic information of the project and upload the application materials. The preliminary classification function of the system helps to organize the materials and improve the efficiency of application. Through the opinion collection and summary module, the project leader can obtain the detailed opinions and scores of the review experts in a timely manner, which helps to understand the advantages and disadvantages of the project and provide direction for subsequent improvements. At the same time, the deep semantic analysis submodule and personalized suggestion submodule in the artificial intelligence-assisted review module can provide the review experts with more comprehensive analysis reports and personalized suggestions, indirectly enabling the project leader to obtain more accurate feedback. The expert intelligent matching module automatically assigns review tasks according to the project field and characteristics to ensure the matching degree between the professionalism of the review experts and the project. The review task assignment module clarifies the review tasks and time requirements, making the review work more orderly and efficient. The artificial intelligence-assisted review module provides the review experts with deep semantic analysis reports and personalized suggestions to help them understand the project more deeply and improve the accuracy and fairness of the review. 2. By setting up the expert community submodule in the social review module, a communication platform is provided for review experts to promote experience sharing and knowledge exchange, improve their own professional level, and ensure that the application materials meet the specifications. The integrity verification module and the authenticity confirmation module ensure the integrity and authenticity of the review materials. In addition, the optimization effect of the artificial intelligence-assisted review module and the dynamic adaptive review module jointly improves the review quality and selects more valuable scientific and technological projects for enterprises. The review material verification and archiving module realizes efficient classification storage and subsequent query management, which facilitates enterprises to manage and trace project materials. The big data analysis and prediction module provides strong support for the company's scientific and technological planning and decision-making through analysis of review results and prediction of project trends. The public participation submodule in the social review module increases the transparency and public participation of the review, bringing more innovative ideas to the project; 3. In summary, through the mutual influence of the above-mentioned multiple functions, the management and control review system that can realize classified storage is convenient for the person in charge to operate and improve efficiency when applying for a project, provides accurate feedback, ensures professional matching and clarifies tasks for review experts, auxiliary modules improve accuracy and fairness, and the expert community promotes experience sharing. Overall, multiple modules improve the quality of review, screen valuable projects, and achieve efficient storage management. Big data assists decision-making, and public participation increases transparency and innovative ideas. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0018] Figure 2 A schematic diagram of the review allocation function structure of the present invention.

[0019] Figure 3 It is a schematic diagram of the user management function structure of the present invention.

[0020] Figure 4 This is a schematic diagram of the functional structure of the blockchain application of the present invention.

[0021] Figure 5 It is a schematic diagram of the auxiliary review function structure of the present invention.

[0022] Figure 6 It is a schematic diagram of the big data analysis and prediction function structure of the present invention.

[0023] The accompanying drawings are marked as follows: 1. Project information entry module; 2. Material upload and preliminary classification module; 3. Expert intelligent matching module; 4. Review rule setting module; 5. File automatic identification module; 6. Compliance check module; 7. Review module; 8. User management module; 9. Review task allocation module; 10. Opinion collection and summary module; 11. Integrity verification module; 12. Authenticity confirmation module; 13. Review material verification and archiving module; 14. Blockchain application module; 15. Big data analysis and prediction module; 16. Parameter setting module; 17. Data backup and recovery module; 18. Dynamic adaptive review module; 19. Artificial intelligence assisted review module; 20. Social review module; 21. Process adjustment submodule; 22. Feedback optimization submodule; 23. Deep semantic analysis submodule; 24. Personalized suggestion submodule; 25. Expert community submodule; 26. Public participation submodule; 27. Data recording submodule; 28. Smart contract execution submodule; 29. ​​Review result analysis submodule; 30. Project trend prediction submodule. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] As attached Figure 1-6 A management and control review system capable of realizing classified storage is shown, comprising a project information entry module 1, the output end of the project information entry module 1 is connected to a material upload and preliminary classification module 2, the output ends of the material upload and preliminary classification module 2 are respectively connected to an expert intelligent matching module 3 and a review rule setting module 4, the output ends of the expert intelligent matching module 3 and the review rule setting module 4 are connected to a file automatic identification module 5, the output end of the file automatic identification module 5 is connected to a compliance check module 6, the output end of the compliance check module 6 is connected to a review module 7, and the output end of the review module 7 is connected to a user management module 8; The output end of the review module 7 is connected to the review task allocation module 9, the output end of the review task allocation module 9 is connected to the opinion collection and aggregation module 10, the output end of the opinion collection and aggregation module 10 is respectively connected to the integrity verification module 11 and the authenticity confirmation module 12, the output ends of the integrity verification module 11 and the authenticity confirmation module 12 are both connected to the review data verification and archiving module 13, and the output ends of the review data verification and archiving module 13 are respectively connected to the blockchain application module 14 and the big data analysis and prediction module 15; The output end of the user management module 8 is connected to a parameter setting module 16 , and the output end of the parameter setting module 16 is connected to a data backup and recovery module 17 .

[0026] The output ends of the review module 7 are respectively connected to the dynamic adaptive review module 18, the artificial intelligence assisted review module 19 and the social review module 20; the output ends of the dynamic adaptive review module 18 are respectively connected to the process adjustment sub-module 21 and the feedback optimization sub-module 22; the output ends of the artificial intelligence assisted review module 19 are respectively connected to the deep semantic analysis sub-module 23 and the personalized suggestion sub-module 24; the output ends of the social review module 20 are respectively connected to the expert community sub-module 25 and the public participation sub-module 26.

[0027] The output ends of the big data analysis and prediction module 15 are respectively connected to the review result analysis submodule 29 and the project trend prediction submodule 30, and the output ends of the blockchain application module 14 are respectively connected to the data recording submodule 27 and the smart contract execution submodule 28.

[0028] The project information entry module 1 is used to input basic project information, project name, research field and expected results. The material upload and preliminary classification module 2 is used to upload various application materials, scientific research reports, implementation plans and technical plans, and perform preliminary classification according to file types and preset rules. The expert intelligent matching module 3 automatically assigns suitable review experts based on the field and characteristics of the project using intelligent algorithms. The review rule setting module 4 is used to determine the review standards, process nodes and required material requirements. The file automatic identification module 5 is used to automatically identify the type, name and content of the uploaded file using advanced technology. The compliance check module 6 is used to check whether the file complies with the naming rules, file type and project-specific requirements against the preset specifications.

[0029] The review task assignment module 9 is used to assign projects to corresponding review experts and clarify review tasks and time requirements. The opinion collection and summary module 10 is used for review experts to submit review opinions and scores online, and the system summarizes and feeds back to project leaders and managers in real time. The integrity verification module 11 is used to check the packaged materials after the review item by item to ensure the integrity of the materials. The authenticity confirmation module 12 confirms the authenticity of the archived materials through digital signature technology. The review material verification and archiving module 13 is used to ensure the integrity, authenticity and standardization of the science and technology project review materials, and realize efficient classified storage and subsequent query management.

[0030] The parameter setting module 16 is used by the administrator to set system parameters, file naming rules and review process nodes according to actual needs. The data backup and recovery module 17 is used to regularly back up system data to ensure data security and quickly restore data when needed.

[0031] The process adjustment submodule 21 is used to automatically adjust the review process and required materials according to the project characteristics. The feedback optimization submodule 22 is used to collect user feedback and optimize the review process in real time. The deep semantic analysis submodule 23 is used to perform deep semantic analysis on the application materials and provide more comprehensive analysis reports for the review experts. The personalized suggestion submodule 24 is used to provide personalized review suggestions based on the review experts' historical records and professional fields.

[0032] The expert community submodule 25 is an expert communication platform to promote experience sharing and knowledge exchange, and the public participation submodule 26 is used to manage the public's review of the review project and the collection of opinions.

[0033] The data recording submodule 27 is used to record the review key node information on the blockchain to ensure that it cannot be tampered with. The smart contract execution submodule 28 is used to automatically execute operations in the review process according to preset rules.

[0034] The dynamic adaptive review module 18 is used to automatically adjust the review process and required materials according to the characteristics and actual situation of the scientific and technological projects, so as to improve the pertinence and efficiency of the review, and collect user feedback to continuously optimize the review process. The artificial intelligence-assisted review module 19 provides intelligent support for the review of scientific and technological projects, improves the accuracy, efficiency and fairness of the review, and the socialized review module 20 is used to enhance the interactivity, transparency and participation of the scientific and technological project review, and promote knowledge sharing and cooperation.

[0035] The working principle of the present invention is as follows: the project leader inputs basic project information, such as the project name, research field and expected results, through the project information entry module (1), and then uploads various application materials, such as scientific research reports, implementation plans and technical plans, in the material upload and preliminary classification module (2), and performs preliminary classification according to the file type and preset rules. On the one hand, this information is transmitted to the expert intelligent matching module (3) so that appropriate review experts can be automatically assigned according to the field and characteristics of the project using an intelligent algorithm; on the other hand, it is transmitted to the review rule setting module (4) for determining the review standards, process nodes and required material requirements; The outputs of the expert intelligent matching module (3) and the review rule setting module (4) are jointly passed to the file automatic identification module (5), which uses advanced technology to automatically identify the type, name and content of the uploaded file. Subsequently, the compliance check module (6) checks whether the file complies with the naming rules, file type and project-specific requirements against the preset specifications. The verified file enters the review module (7) and is ready for formal review. At this time, the artificial intelligence assisted review module (19) begins to play a role. The deep semantic analysis submodule (23) performs deep semantic analysis on the application materials, extracts key information and potential logic, and provides a more comprehensive analysis report for the review experts, helping them to quickly understand the core content and innovation points of the project before the review; The review module (7) reviews the project. The results are passed to the user management module (8) for managing system user information and permissions. The results are passed to the review task allocation module (9) for allocating the project to the corresponding review expert and specifying the review task and time requirements. The review experts submit their review opinions and scores online through the opinion collection and summary module (10). The system summarizes and feeds back to the project leader and management personnel in real time. During the review process, the personalized suggestion submodule (24) provides personalized review suggestions based on the review experts' historical records and professional fields, guiding the experts to analyze the advantages and disadvantages of the project more deeply and improve the accuracy and fairness of the review. At the same time, the dynamic adaptive review module (18) is also running. The process adjustment submodule (21) automatically adjusts the review process and required materials according to the characteristics of the project. For example, for complex large-scale projects, the number of review links and experts may be increased; for highly innovative projects, experts in specific fields may be introduced for more in-depth evaluation. The feedback optimization submodule (22) collects user feedback, including the opinions of review experts and feedback from project leaders, and optimizes the review process in real time to improve review efficiency and user satisfaction. The integrity verification module (11) checks the packaged materials after the review item by item to ensure the integrity of the materials. The authenticity confirmation module (12) confirms the authenticity of the archived materials through digital signature technology. These two modules jointly ensure the integrity, authenticity and standardization of the science and technology project review materials, and then pass the information to the review material verification and archiving module (13) to achieve efficient classified storage and subsequent query management. During the archiving process, the blockchain application module (14) plays a role, and the data recording submodule (27) records the key node information of the review on the blockchain to ensure that the review process cannot be tampered with and is traceable; the smart contract execution submodule (28) automatically executes the operations in the review process according to the preset rules, such as automatically triggering the next data analysis task after the data is archived; The review result analysis submodule (29) in the big data analysis and prediction module (15) analyzes historical review data, explores the relationship between review results and project characteristics, and provides reference for project leaders to help them better prepare application materials. The project trend prediction submodule (30) uses big data analysis technology to predict the development trends and needs of scientific and technological projects, and provide support for the company's scientific and technological planning and decision-making. The social review module (20) also adds new vitality to the review process. The expert community submodule (25) is an expert communication platform where review experts can share review experience, exchange professional knowledge, and discuss hot issues in the community to promote teamwork and knowledge sharing. The public participation submodule (26) is used to manage the public's viewing of review projects and the collection of opinions, increase the transparency of the review and public participation, and provide more feedback and innovative ideas for the project.

[0036] Finally, it should be noted that the drawings of the embodiments disclosed in the present invention only involve structures related to the embodiments disclosed in the present invention, and other structures can refer to common designs. In the absence of conflicts, the same embodiment and different embodiments of the present invention can be combined with each other; Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A management and control review system capable of implementing classified storage, comprising a project information entry module (1), characterized in that: The output end of the project information input module (1) is connected to the material upload and preliminary classification module (2), the output end of the material upload and preliminary classification module (2) is respectively connected to the expert intelligent matching module (3) and the review rule setting module (4), the output ends of the expert intelligent matching module (3) and the review rule setting module (4) are connected to the file automatic identification module (5), the output end of the file automatic identification module (5) is connected to the compliance check module (6), the output end of the compliance check module (6) is connected to the review module (7), and the output end of the review module (7) is connected to the user management module (8); The output end of the review module (7) is connected to a review task allocation module (9), the output end of the review task allocation module (9) is connected to an opinion collection and aggregation module (10), the output end of the opinion collection and aggregation module (10) is respectively connected to an integrity verification module (11) and an authenticity confirmation module (12), the output ends of the integrity verification module (11) and the authenticity confirmation module (12) are both connected to a review material verification and archiving module (13), and the output end of the review material verification and archiving module (13) is respectively connected to a blockchain application module (14) and a big data analysis and prediction module (15); The output end of the user management module (8) is connected to a parameter setting module (16), and the output end of the parameter setting module (16) is connected to a data backup and recovery module (17).

2. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The output end of the review module (7) is respectively connected to a dynamic adaptive review module (18), an artificial intelligence assisted review module (19) and a social review module (20); the output end of the dynamic adaptive review module (18) is respectively connected to a process adjustment submodule (21) and a feedback optimization submodule (22); the output end of the artificial intelligence assisted review module (19) is respectively connected to a deep semantic analysis submodule (23) and a personalized suggestion submodule (24); and the output end of the social review module (20) is respectively connected to an expert community submodule (25) and a public participation submodule (26).

3. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The output end of the big data analysis and prediction module (15) is respectively connected to a review result analysis submodule (29) and a project trend prediction submodule (30), and the output end of the blockchain application module (14) is respectively connected to a data recording submodule (27) and a smart contract execution submodule (28).

4. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The project information entry module (1) is used to input basic project information, project name, research field and expected results. The material upload and preliminary classification module (2) is used to upload various application materials, scientific research reports, implementation plans and technical plans, and to perform preliminary classification according to file types and preset rules. The expert intelligent matching module (3) automatically assigns suitable review experts according to the field and characteristics of the project using intelligent algorithms. The review rule setting module (4) is used to determine the review standards, process nodes and required material requirements. The file automatic identification module (5) is used to automatically identify the type, name and content of the uploaded file using advanced technology. The compliance check module (6) is used to check whether the file complies with the naming rules, file type and project-specific requirements against the preset specifications.

5. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The review task assignment module (9) is used to assign projects to corresponding review experts and to specify review tasks and time requirements. The opinion collection and summary module (10) is used for review experts to submit review opinions and scores online, and the system summarizes and feeds back to project leaders and managers in real time. The integrity verification module (11) is used to check the packaged materials after review item by item to ensure the integrity of the materials. The authenticity confirmation module (12) confirms the authenticity of the archived materials through digital signature technology. The review material verification and archiving module (13) is used to ensure the integrity, authenticity and standardization of the science and technology project review materials, and realize efficient classified storage and subsequent query management.

6. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The parameter setting module (16) is used by the administrator to set system parameters, file naming rules and review process nodes according to actual needs, and the data backup and recovery module (17) is used to regularly back up system data to ensure data security and quickly restore data when needed.

7. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The process adjustment submodule (21) is used to automatically adjust the review process and required materials according to project characteristics, the feedback optimization submodule (22) is used to collect user feedback and optimize the review process in real time, the deep semantic analysis submodule (23) is used to perform deep semantic analysis on the application materials and provide a more comprehensive analysis report for the review experts, and the personalized suggestion submodule (24) is used to provide personalized review suggestions based on the review experts' historical records and professional fields.

8. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The expert community submodule (25) is an expert communication platform to promote experience sharing and knowledge exchange, and the public participation submodule (26) is used to manage the public's review of the review project and the collection of opinions.

9. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The data recording submodule (27) is used to record the review key node information on the blockchain to ensure that it cannot be tampered with, and the smart contract execution submodule (28) is used to automatically execute operations in the review process according to preset rules.

10. The control and review system capable of realizing classified storage according to claim 1 is characterized in that: The dynamic adaptive review module (18) is used to automatically adjust the review process and required materials according to the characteristics and actual situation of the scientific and technological projects, so as to improve the pertinence and efficiency of the review, and at the same time collect user feedback to continuously optimize the review process. The artificial intelligence-assisted review module (19) provides intelligent support for the review of scientific and technological projects, improves the accuracy, efficiency and fairness of the review, and the social review module (20) is used to enhance the interactivity, transparency and participation of the scientific and technological project review, and promote knowledge sharing and cooperation.

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