Chang Liu

Rural public cultural spaces serve as vital venues for information exchange, interpersonal interaction, and cultural and leisure activities in rural communities. Since the Rural Revitalization Strategy was proposed in 2017, the planning and provision of rural public cultural spaces have attracted increasing attention in China. However, many such spaces remain underutilized, accompanied by low levels of user satisfaction among villagers. A key reason for this is the mismatch between standardized spatial configurations and villagers’ dynamic functional needs. Drawing on Hertzberger’s theory of spatial polyvalence, this study proposes a framework to evaluate spatial flexibility in rural public cultural spaces. The framework introduces quantitative indicators and computational methods across two dimensions: “competence”, referring to a space’s potential to accommodate multiple functions, and “performance”, reflecting the efficiency of functional transformation during actual use. Employing the proposed method, this study conducts a case analysis of the Xiangyang Village Neighborhood Center in Shanghai to evaluate its spatial characteristics and actual usage. The evaluation reveals two key issues at the overall level: (1) many residual spaces remain undesigned and lack strategies to support spontaneous use; (2) the spatial layout shows rigid public–private divisions, with little adaptability. At the room level, spaces such as the elevator, hairdressing room, party secretary’s office, and health center are functionally rigid and underutilized. Drawing on exemplary cases, this study proposes several key strategies such as (1) optimizing and innovatively activating residual spaces, (2) integrating multifunctional programs, and (3) improving spatial inclusiveness.

Recent advancements in artificial intelligence, particularly in generative technologies, have significantly redefined the design paradigm for community public cultural spaces, shifting from a traditionally designer-centric model to one that emphasizes multi-stakeholder co-creation. This paper focuses on the design of public cultural spaces at the community scale, proposing a generative dynamic workflow-based co-creation framework that integrates large language models (LLMs) with text-to-image technologies. The framework includes a natural dialogue-based needs-capturing module, a needs analysis module, and a needs expression text-to-image module. This study validates the proposed framework by developing a system prototype for renovating a public space in a student dormitory at Tongji University’s Jiading campus. The results show that the prototype demonstrates good usability and a relatively satisfactory capability in capturing user requirements. These findings indicate that this research helps address key limitations in traditional community design practices, such as limited resident participation, inefficient integration of diverse needs, and slow iteration processes.

Urban historical and cultural districts, serving as multi-functional compounds integrating cultural preservation, consumer experience, and economic growth, are increasingly becoming the preferred choice for in-depth tourism under the trend of historical heritage protection and consumption upgrading. Due to the complexity of the construction purpose, inherent functions, and operational management of historical districts, scientifically and rationally evaluating them poses a challenge. This paper attempts to construct an evaluation method for the tourism competitiveness of urban historical and cultural districts based on multi-source data and the Analytic Hierarchy Process (AHP) method. First, based on the model of destination competitiveness and combined with literature research and open-ended expert interviews, an evaluation framework for the tourism competitiveness of urban historical and cultural districts is established, using the AHP method to calculate the specific weights of each evaluation indicator. Then, the corresponding data sources for each indicator and the data processing and calculation methods are further clarified. To verify the effectiveness of the proposed evaluation model, this paper selects three key historical and cultural districts in Suzhou City, calculates the tourism competitiveness of each district based on the proposed model, and collects tourist satisfaction surveys from the three districts for cross-validation with the evaluation results. The experimental results show that the evaluation model is reliably effective in assessing the cultural, commercial, and tourism service aspects of historical districts, thereby providing a theoretical basis for future tourism decision-making information systems and practical applications of historical districts.

Community Service Facilities are the basic unit that carries the daily activities of residents. The evaluation of community service facilities is the key to ensuring a balance between the supply of facilities and the needs of residents. Existing studies mainly focus on a specific type of facility from the perspective of an independent discipline. A lack of a holistic understanding leads to several problems, such as the incompatibility of different disciplines' perspectives and the inconsistency between evaluation results and users' needs. Design is being considered and explored as a tool for dealing with systems-level issues. We re-cognized the evaluation problem of community service facilities based on DesignX. And Buchanan's four strategies of design inquiry were introduced to develop new thinking on evaluation. This paper provides a systematic perspective on the facility evaluation problem and the research direction of the evaluation in the context of design.

In recent years, public security safety has been one of the core issues of high concern to the whole society. Building a smart patrol command and dispatch system has become one of the development directions for public security organs in response to the increasingly complex and ever-changing public security situation. This article was based on big data technology, analyzing the characteristics and value of patrol data, and using methods such as machine learning and deep learning to construct a smart patrol command and scheduling system for public security, in order to improve the efficiency and level of public security work. By applying experimental testing methods and comparing with traditional methods, performance data of the public security intelligent patrol command and dispatch system can be obtained. Experimental data showed that the stability of the intelligent patrol command and scheduling system based on big data technology reached 86%, accuracy reached 88%, security reached 84%, and work efficiency reached 85%. After comprehensive testing, the performance, safety, and stability of the public security intelligent patrol command and dispatch system have been effectively verified.