A digital preservation system and method for folk culture

Abstract

This invention belongs to the interdisciplinary field of folk culture and big data technology, and discloses a digital protection system and method for folk culture. The system comprises five core modules, forming a closed-loop process: a folk culture uploading and administrator review module allows users to upload information in text, audio, and video formats, with administrators reviewing it intuitively according to cultural characteristics; a big data analysis and tracing module constructs a database through multi-path web crawlers, extracts multi-dimensional features, and establishes a tracing network to accurately determine the origin and connections of culture; a regional folk culture analysis module constructs regional feature datasets and mines cultural background; a digital display and database module realizes data classification management, cloud storage, and diversified display, supporting retrieval and sharing; and a folk culture education module provides diversified courses, knowledge graphs, gamified interactions, and VR / AR immersive experiences, adaptable to different learners. This invention provides an efficient solution for the digital inheritance of folk culture.

Description

Technical Field

[0001] This invention belongs to the field of interaction between folk culture and big data technology, specifically a digital protection system and method for folk culture. Background Technology

[0002] Folk culture is the core carrier of a nation's and people's historical and cultural heritage, encompassing traditional handicrafts, folk rituals, folk arts, oral traditions, and many other categories. It is a vivid manifestation of national spirit and cultural genes, and its inheritance and protection are of irreplaceable importance for maintaining cultural diversity, enhancing national identity, and promoting excellent traditional Chinese culture. As an ancient civilization with a long history, my country has nurtured rich and diverse folk cultural resources. These resources, passed down for thousands of years, not only carry the wisdom of our ancestors but also contain unique regional characteristics and ethnic customs, forming an important component of my country's cultural soft power.

[0003] Currently, the traditional methods of preserving folk culture mainly rely on physical collection, oral transmission, and offline exhibitions. These methods have inherent limitations. On the one hand, physical collection is constrained by storage environment, preservation technology, and display conditions. Many folk cultural artifacts are prone to aging, damage, and mold. Furthermore, the limited resources make it difficult to comprehensively cover all categories of folk culture. Offline exhibitions also have strong geographical limitations, narrowing the channels for public access and understanding, hindering widespread dissemination. On the other hand, most folk cultures rely on oral transmission. With the passing of older generations of inheritors, many precious folk skills, lineages, and cultural connotations face the risk of being lost. Meanwhile, the younger generation's awareness and acceptance of traditional folk culture are gradually declining, exacerbating the problem of a break in transmission, with some folk cultures even on the verge of extinction.

[0004] Furthermore, traditional preservation methods lack systematic organization and standardized recording of folk culture information. A large amount of folk culture-related written materials, techniques, and inheritance stories are scattered in different regions and among different groups, without forming a unified information resource database. This makes it difficult to carry out subsequent research, inheritance, and promotion work efficiently, and the value of folk culture cannot be fully explored and reflected.

[0005] In recent years, with the development of digital technology, some regions and institutions have begun to attempt the digital preservation of folk culture, such as building simple information display platforms, uploading some folk culture materials, and creating digital archives. However, most existing attempts at digital preservation are in a fragmented and piecemeal stage, lacking a complete and systematic solution. They have failed to form a complete closed loop from information collection, review, and tracing to display, education, and promotion. The specific shortcomings are mainly reflected in the following aspects:

[0006] Information collection and review lack standardization and rigor: Existing digital platforms often have simplistic user upload functions, lacking unified standards and guidance for uploaded information. User-uploaded folk culture information is often disorganized, incomplete, and lacks a dedicated review mechanism or clear review standards, making it difficult to guarantee the authenticity, completeness, and cultural value of uploaded information. Some false and invalid information infiltrates the platform, affecting the quality and effectiveness of digital protection. Furthermore, the feedback mechanism for review results is inadequate; information that fails review lacks clear reasons for rejection, making it difficult for users to supplement and improve their information, thus reducing the efficiency of information collection.

[0007] The analysis of the origins of folk culture lacks scientific and technological support: existing methods for tracing the origins of folk culture mostly rely on traditional approaches such as manual surveys and textual research, which are inefficient, highly subjective, and difficult to comprehensively uncover core information such as the historical context and regional connections of folk culture. There is a lack of the ability to build basic information databases based on big data and web crawling technologies, making it impossible to systematically extract the multidimensional characteristics of folk culture. Furthermore, it is difficult to accurately determine the origin region of folk culture and its connections with similar cultures in other regions through scientific feature analysis and correlation evaluation, resulting in insufficient accuracy and authority in the tracing results.

[0008] The depth of regional folk culture characteristics exploration is insufficient: existing digital platforms provide only a superficial integration and analysis of regional folk cultures, failing to utilize big data technology to construct datasets of regional folk culture characteristics, and thus unable to accurately extract the unique identifiers and core features of different regional folk cultures. Furthermore, the exploration of the cultural background, historical origins, regional connections, and contributions to the transmission of folk cultures is not in-depth enough, remaining only at a superficial level. This fails to fully demonstrate the rich connotations and unique value of folk cultures, and cannot meet users' needs for a deeper understanding of them.

[0009] Weak Digital Display and Data Management Capabilities: Existing digital platforms rely heavily on static displays such as text and images, lacking immersive experiences like 3D displays and virtual tours. This prevents users from directly experiencing the details and characteristics of folk culture, resulting in a poor user experience. Furthermore, the classification, labeling, and retrieval functions for digital folk culture information are inadequate, and database management is chaotic, making it difficult for users to quickly and accurately obtain the information they need. Simultaneously, data storage often employs a single storage method, lacking effective encryption protection and multiple backup mechanisms, compromising data security and stability. In addition, insufficient information sharing capabilities hinder the widespread dissemination of folk culture.

[0010] The promotion of folk culture education suffers from a lack of diversity and interactivity: current folk culture education primarily relies on offline lectures and simple online courses, resulting in a lack of targeted and diversified curriculum that fails to meet the learning needs of different audiences, including teenagers, enthusiasts, and researchers. Furthermore, the absence of dedicated folk culture education resource databases and knowledge graphs leads to fragmented learning resources, hindering systematic learning. Interactive learning tools are also scarce, lacking gamified and immersive learning experiences, resulting in low user engagement and enthusiasm, and hindering the effective popularization and in-depth inheritance of folk culture knowledge.

[0011] Currently, the protection and inheritance of folk culture has entered the digital and intelligent era, requiring the use of advanced information technology to build a comprehensive and systematic protection and inheritance system. However, existing technologies have significant shortcomings, both in terms of the functionality of individual links and in the coordination and linkage between links. They have failed to form a complete protection chain covering "collection-review-tracing-display-education-promotion" of folk culture, and cannot effectively solve core problems such as the break in the inheritance of folk culture, the dispersion of information, the difficulty in tracing its origins, the limited dissemination, and the lack of interaction.

[0012] In summary, existing methods and attempts at digital preservation of folk culture have many shortcomings, lacking a comprehensive solution capable of achieving standardized collection, rigorous review, accurate tracing, systematic integration, diversified display, and interactive educational promotion of folk culture information. Therefore, developing a fully functional, standardized, and technologically advanced digital preservation system and method for folk culture is of significant practical importance and application value for overcoming existing technological bottlenecks, promoting the digital and dynamic inheritance of folk culture, and enhancing its dissemination and influence. Summary of the Invention

[0013] The purpose of this invention is to provide a digital protection system and method for folk culture, which can help the public submit applications for the protection of folk culture, improve the efficiency of folk culture protection work, provide a more intuitive way to understand folk culture, and enhance people's attention to and interest in folk culture.

[0014] The objective of this invention is achieved through the following technical solution:

[0015] A system and method for the digital protection of folk culture, characterized by including a folk culture uploading and administrator review module, a big data analysis and tracing module, a regional folk culture analysis module, a digital display and database module, and a folk culture education module;

[0016] The folk culture upload and administrator review module is implemented through the following process:

[0017] The user upload submodule allows users to upload information about folk culture to the system for administrator review.

[0018] The administrator review submodule allows administrators to review user-uploaded folk culture information, approving those that meet the criteria and rejecting those that do not.

[0019] The big data analysis and tracing module is implemented through the following process:

[0020] The basic information database submodule is built based on big data to form a database about the origin of folk culture, and extracts features from the folk culture in the database to construct a multi-dimensional feature extraction set;

[0021] The feature analysis submodule performs feature analysis on samples from the same region in the multidimensional feature extraction set, sets feature limit intervals, evaluates feature similarity between different regions, and determines the source region.

[0022] The regional origin tracing submodule establishes a regional origin tracing network based on the multidimensional feature extraction set and the feature limit interval, inputs folk culture into the tracing network, and generates regional origin tracing results.

[0023] The regional folk culture analysis module is implemented through the following process:

[0024] The regional map module uses a multi-threaded web crawler to obtain folk culture data for various regions on the map and constructs a dataset of folk culture characteristics for each region.

[0025] The information mining module uses a folk culture feature dataset to find the cultural background and similar folk cultures of folk cultures.

[0026] The digital display and database module is implemented through the following process:

[0027] The digital database submodule establishes a dedicated folk culture database, systematically organizing various folk culture materials for retrieval and management.

[0028] The cloud platform storage submodule utilizes cloud storage technology to store digital information about folk culture on the cloud platform, ensuring long-term storage of the information and providing sharing services for visitors.

[0029] The digital display submodule showcases folk culture in a digital format, allowing people to learn about and understand folk culture anytime, anywhere via the internet.

[0030] The folk culture education module is implemented through the following process:

[0031] The digital education platform, based on digital technology, transforms user-uploaded folk culture into digital courses, helping users understand and learn about folk culture.

[0032] Interactive learning tools, through digital interactive platforms and gamification, allow users to participate in traditional activities and gain a deeper understanding of folk culture through hands-on activities.

[0033] The folk culture simulation platform uses VR immersive scenes and AR real-scene technology to provide users with a simulated experience, as well as real-time explanations from inheritors to answer users' questions.

[0034] The folk culture digital protection system and method of this invention, through the coordinated operation of five modules—upload review, big data tracing, regional cultural analysis, digital display and storage, and interactive education—achieves standardized collection and review of folk culture information, precise tracing analysis, and in-depth exploration of regional cultural characteristics. Furthermore, relying on technologies such as cloud storage, 3D display, and VR / AR, it completes the diversified and immersive display and secure storage and dissemination of folk culture, and creates a gamified and immersive folk culture education experience. This effectively solves many shortcomings of traditional and existing digital protection methods, significantly improves the efficiency of folk culture protection work, promotes the digital and living inheritance of folk culture, fully explores and showcases the value of folk culture, and enhances its dissemination and influence. Attached Figure Description

[0035] Figure 1 This is a structural block diagram of the folk culture digital protection system of the present invention;

[0036] Figure 2 This is a block diagram showing the structural composition of the big data analysis and tracing module of the present invention;

[0037] Figure 3 This is a block diagram illustrating the structural composition of the digital display and database module of the present invention;

[0038] Figure 4 This is a block diagram showing the structural components of the folk culture education module of the present invention. Detailed Implementation

[0039] The overall concept of the technical solution provided in this application is as follows:

[0040] First, an information entry point is established through the folk culture upload and administrator review module. Users can upload folk culture-related information in various forms such as text, audio, and video through the user upload sub-module, comprehensively recording cultural details. Administrators can intuitively grasp the core characteristics of folk culture through the administrator review sub-module, and screen the uploaded information according to the established standards. Those that meet the requirements will enter the subsequent process, while those that do not meet the requirements will be returned with feedback on the reasons, ensuring information quality.

[0041] Subsequently, the big data analysis and tracing module was launched. The basic information database submodule adopted a multi-path web crawler and priority search strategy to crawl relevant data from authoritative channels to build a basic database, while extracting multi-dimensional features of folk culture to form a feature extraction set. The feature analysis submodule conducted feature analysis on samples from the same region, set feature limit intervals, and then evaluated similarity with features from different regions to accurately lock the tracing association. The regional tracing submodule built a place of origin tracing network based on the feature extraction set and limit intervals, input folk culture information to generate tracing results, and clarified the origin region and related context.

[0042] The regional folk culture analysis module operates synchronously, while the regional map module uses big data to acquire folk culture data from various regions and constructs a regional feature dataset. The information mining module determines the region to which the folk culture belongs based on the dataset and completes the classification, deeply exploring its historical origins, regional connections and other cultural backgrounds to enrich its cultural connotations.

[0043] The digital display and database module builds upon previous achievements. The digital database submodule establishes a dedicated database, achieving standardized data management through classification, annotation, and tagging functions. It presents content in the form of images, audio, and video, and adds interactive functions such as search, browsing, and commenting to enhance user engagement. The cloud platform storage submodule uses cloud storage technology to encrypt and store digital information, ensuring data security through multiple backups, while also providing sharing services to facilitate cultural dissemination. The digital display submodule presents folk culture in diverse digital forms, allowing users to learn online anytime, anywhere.

[0044] Finally, the cultural heritage is effectively implemented through the folk culture education module. The digital education platform creates diversified digital teaching materials and courses to meet the needs of learners of different ages, and constructs a folk culture education resource library and knowledge graph to support users in-depth exploration of key content. The interactive learning tools are driven by gamification, enhancing user participation through hands-on operations, interactive Q&A, knowledge competitions, and other forms. The folk culture simulation platform uses VR / AR technology and 3D virtual scenes to achieve first / third-person switching and on-site atmosphere restoration. Users can role-play to complete folk customs processes and simulate skills, accompanied by real-time explanations and Q&A from inheritors, making learning more immersive.

[0045] Example 1

[0046] Users can upload information about a specific folk culture (such as traditional embroidery techniques) through the user upload submodule on the system client. This includes embroidery process videos (supporting common formats such as MP4 and AVI), textual descriptions of the technique's transmission, and images of representative works. Administrators can log in to the administrator review submodule through the review backend. The system automatically displays the core characteristics of the folk culture (such as the style of the technique, the region of transmission, and unique craftsmanship). Administrators review the information based on preset review standards (such as information completeness, authenticity, and cultural value). Information that passes the review proceeds to the next processing step, while information that fails the review is returned with the reason provided, allowing users to supplement and improve the information.

[0047] The basic information database submodule initiates a multi-path web crawler, using a priority search strategy to crawl historical documents, transmission records, and regional distribution data related to traditional embroidery techniques from authoritative cultural websites, academic databases, and local cultural tourism platforms. This data is then stored in the basic information database, and multi-dimensional features of the technique (such as stitch type, pattern style, material selection, and lineage) are extracted to construct a multi-dimensional feature extraction set. The feature analysis submodule performs feature analysis on embroidery technique samples from the same region (such as Suzhou, the birthplace of Suzhou embroidery), setting limit ranges for features such as stitch complexity and pattern elements. Simultaneously, it evaluates the similarity of embroidery techniques with those from other regions (such as the birthplaces of Sichuan embroidery and Guangdong embroidery) to determine the degree of origin correlation. The regional origin tracing submodule, based on the aforementioned multi-dimensional feature extraction set and feature limit ranges, establishes an origin tracing network. Information about the traditional embroidery technique is input into the network to generate tracing results, clarifying its origin in Suzhou and its connection with embroidery techniques in surrounding areas.

[0048] The regional map module utilizes big data technology to acquire folk culture data related to embroidery from various provinces and cities across the country, constructing a dataset of embroidery technique characteristics for each region (e.g., Suzhou region emphasizes "refined elegance," while Chengdu region emphasizes "rigorous detail"). The information mining module, based on the Suzhou region's embroidery technique characteristic dataset, mines its cultural background, including its peak development during the Ming and Qing dynasties, its connection to the Jiangnan water town culture, and the contributions of representative inheritors throughout history.

[0049] The digital database submodule categorizes traditional embroidery techniques information that has passed review and completed traceability analysis (classifying it into the "Traditional Handicrafts" category and labeling it as "Suzhou Embroidery"), adds tags (such as "Intangible Cultural Heritage," "Hand Embroidery," and "Jiangnan Culture"), and integrates and presents the technique process, representative works, cultural background, and other content through images, audio, and video. Users can search (supporting keyword search and category filtering) and browse through the system platform. The cloud platform storage submodule encrypts and stores the above digital information on a cloud server, employing multiple backup mechanisms to ensure data security, and also supports users to share relevant content to social media platforms via sharing links. The digital display submodule allows users to intuitively experience the embroidery technique production process and work details through 3D displays, virtual tours, and other forms, enabling online access anytime, anywhere.

[0050] The digital education platform develops diverse digital teaching materials and courses for traditional embroidery techniques: introductory courses for teenagers (explaining basic stitches through animation), advanced courses for enthusiasts (video tutorials on complex pattern design), and professional courses for researchers (integrating historical archives and academic literature). The folk culture education resource database collects digitized ancient records, oral accounts from modern inheritors, and award-winning works of this technique, constructing a knowledge graph. Users can click on the "Evolution of Stitching Techniques" node to view the development of Suzhou embroidery stitches from ancient times to the present. Interactive learning tools include an embroidery simulation game, allowing users to virtually experience the processes of threading a needle and filling patterns. Interactive features such as Q&A (e.g., what are the core stitches of Suzhou embroidery?) and knowledge competitions (e.g., answering questions about representative Suzhou embroidery works) enhance user engagement and learning effectiveness.

[0051] Example 2

[0052] Users upload information related to traditional paper-cutting techniques through the user upload sub-module of the system client, including videos of the paper-cutting process, textual descriptions of the technique's heritage, and images of representative works. Administrators log in through the administrator review sub-module in the review backend. The system automatically displays the core characteristics of the traditional paper-cutting technique, and administrators can use preset review standards to facilitate users in supplementing and improving the information.

[0053] The basic information database submodule launches a multi-path web crawler. Based on a priority search strategy, it crawls data related to traditional paper-cutting techniques, such as historical documents, transmission records, and regional distribution, from authoritative cultural websites, academic databases, and local cultural tourism platforms. It then completes the storage of the basic information database and extracts the multidimensional features of the technique to construct a multidimensional feature extraction set.

[0054] The feature analysis submodule performs feature analysis on paper-cutting technique samples from the same region, sets limit ranges for features such as knife complexity and pattern elements, and evaluates the similarity of paper-cutting techniques from other regions to determine the degree of tracing back to the source.

[0055] Based on the aforementioned multidimensional feature extraction set and feature limit interval, the regional traceability submodule establishes a traceability network for the place of origin. The information of this traditional paper-cutting technique is input into the network to generate traceability results, clarifying its origin in Weixian County, Hebei Province, and its connection with paper-cutting techniques in surrounding areas.

[0056] The regional map module utilizes big data technology to acquire folk culture data related to paper-cutting from various provinces and cities across the country, constructing a dataset of paper-cutting techniques characteristics for each region. The information mining module, based on the paper-cutting technique characteristic dataset of Weixian County, mines its cultural background, including its peak development during the Ming and Qing dynasties, its connection with northern folk customs, and the contributions of representative inheritors throughout history.

[0057] The digital database submodule categorizes and tags traditional paper-cutting techniques information that has passed review and completed traceability analysis, and integrates and presents content such as technique processes, representative works, and cultural background through images, audio, and video. Users can search and browse through the system platform.

[0058] The cloud platform storage submodule encrypts and stores the aforementioned digital information on the cloud server, employing a multi-layered backup mechanism. It also supports users sharing the content to social media platforms via sharing links. The digital display submodule uses 3D displays and virtual tours to allow users to intuitively experience the paper-cutting technique's production process and the details of the artwork, enabling online access anytime, anywhere.

[0059] The digital education platform has developed diverse digital teaching materials and courses for traditional paper-cutting techniques: introductory courses for teenagers, advanced courses for enthusiasts, and professional courses for researchers.

[0060] The folk culture education resource database collects digitized ancient records, oral accounts of modern inheritors, award-winning works, and other materials related to this craft, and constructs a knowledge graph. Users can click on the "Evolution of Knife Techniques" node to view the development history of Weixian paper-cutting knife techniques from ancient times to the present.

[0061] Interactive learning tools have been developed to create paper-cutting simulation games, allowing users to virtually experience the process of holding a knife, carving lines, and filling patterns. The games also include interactive Q&A and knowledge quizzes to enhance user engagement and learning effectiveness.

Claims

1. A system and method for the digital preservation of folk culture, characterized in that, It includes modules for uploading folk culture content and administrator review, big data analysis and tracing, regional folk culture analysis, digital display and database, and folk culture education. The folk culture upload and administrator review module includes: The user upload submodule allows users to upload information about folk culture to the system for administrator review. The administrator review submodule allows administrators to review the folk culture information uploaded by users, approving those that meet the criteria and returning those that do not. The big data analysis and tracing module includes: The basic information database submodule is built based on big data to form a database about the origin of folk culture, and extracts features from the folk culture in the database to construct a multi-dimensional feature extraction set; The feature analysis submodule performs feature analysis on samples from the same region in the multidimensional feature extraction set, sets feature limit intervals, evaluates feature similarity between different regions, and determines the source region. The regional origin tracing submodule establishes a regional origin tracing network based on the multidimensional feature extraction set and the feature limit interval, inputs folk culture into the tracing network, and generates regional origin tracing results. The regional folk culture analysis module includes: The regional map module uses big data to acquire folk culture data of various regions and constructs a dataset of folk culture characteristics of each region. The information mining module identifies the regions where folk cultures are located based on the data sets of folk culture characteristics of each region, classifies them, and mines the cultural background of the folk culture. The digital display and database module includes: The digital database submodule establishes a dedicated folk culture database, systematically organizing various folk culture materials for retrieval and management. The cloud platform storage submodule utilizes cloud storage technology to store digital information about folk culture on the cloud platform, ensuring long-term storage of the information and providing sharing services for visitors. The digital display submodule showcases folk culture in a digital format, enabling people to learn about and understand folk culture anytime, anywhere via the internet. The folk culture education module includes: The digital education platform, based on digital technology, transforms user-uploaded folk culture into digital courses, helping users understand and learn about folk culture. Interactive learning tools, through digital interactive platforms and gamification, allow users to participate in traditional activities through hands-on activities and gain a deeper understanding of folk culture; The folk culture simulation platform uses VR immersive scenes and AR real-scene technology to provide users with a simulated experience, as well as real-time explanations from inheritors to answer users' questions.

2. The system and method for digital preservation of folk culture according to claim 1, characterized in that, The user upload submodule can receive materials uploaded by users and provide high-quality introductions and displays of folk culture through text, audio, and video descriptions so that administrators can understand the folk culture. The administrator review submodule can receive materials uploaded by users and intuitively understand the characteristics of folk culture, so that the administrator can select folk culture that meets the requirements.

3. The system and method for digital preservation of folk culture according to claim 1, characterized in that, The big data analysis and tracing module is implemented through the following process: A basic information database was established, and a multi-path web crawler was used to crawl relevant data based on a priority search strategy. The basic information database was then stored, and features of folk culture were extracted to construct a multi-dimensional feature extraction set. A traceability network is established, which uses a multidimensional feature extraction set and feature limit intervals to build the origin traceability network. Based on the results, feature similarity evaluation is performed on different regions to determine similar traceability regions.

4. The system and method for digital preservation of folk culture according to claim 1, characterized in that, The digital database submodule is implemented through the following process: Data management provides classification, annotation, and tagging functions to effectively manage different folk cultures; The data display and interaction utilize diverse formats such as images, audio, and video to present folk culture-related content. It also features interactive functional modules that support user search, browsing, and commenting, thereby enhancing user engagement and interactivity on the platform.

5. The system and method for digital preservation of folk culture according to claim 1, characterized in that, The digital education platform includes: Diverse digital teaching materials and courses provide systematic learning content covering all aspects of folk culture. The course content can be presented in various ways, such as text, images, audio, and video, so that learners of different ages can learn. The Folk Culture Education Resource Database collects a large number of digital documents and historical archives related to folk culture, providing learners with abundant resources and constructing a knowledge graph of folk culture. Users can click on the graph to gain a deeper understanding of the key content of a particular project.

6. The system and method for digital preservation of folk culture according to claim 1, characterized in that, The folk culture simulation platform includes: Scene simulation: The process of folk culture is displayed through 3D virtual scenes, and the first / third person perspective can be switched, and the atmosphere of the scene can be restored with dynamic effects; Interactive experience: Users can role-play and complete the folk custom process step by step, with the system providing feedback on whether they are correct or not, and can also simulate the skills.

7. A digital preservation system and method for folk culture, characterized in that, The system operation steps are as follows: Step S1. First, users upload folk culture information, which is recorded and displayed in detail. Step S2. The administrator reviews the folk culture uploaded by users, saves the folk culture that meets the requirements, and returns the folk culture that does not meet the requirements. Step S3. Use the big data analysis and tracing module to trace the origins of folk culture and find its background stories; Step S4. Create a dedicated digital platform for folk culture to showcase it. The platform will provide videos, images, audio files, and explanations of the cultural background. Step S5. Through online courses and interactive experiences, users can learn about and experience these folk cultures. Interactive Q&A sessions and knowledge competitions can also increase user engagement.

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