Jiyao Yin

In the era of rapid urban digitalization, intelligent analysis systems are pivotal for urban safety management, yet their applicability lacks a robust evaluation framework. This study develops a comprehensive model integrating the Delphi method, Fuzz...

The rise of “Internet + Recycling” platforms is transforming the domestic waste management landscape, creating dual-channel reverse supply chains where new platforms interact with traditional recyclers. However, these platforms face critical strategic decisions regarding their service portfolios (convenient but costly door-to-door vs. economical fixed-point drop-off) and their relationship with incumbents (cooperation vs. competition). This study aims to determine the optimal pricing, service level, and relationship strategies for an “Internet + Recycling” center to maximize profitability under the influence of consumer channel preferences and government subsidies. We developed four Stackelberg game-theoretic models representing different scenarios of service modes (fixed-point only vs. fixed-point with door-to-door) and relationship structures (cooperation vs. competition). We derived equilibrium solutions for recycling prices, service levels, and profits. Our results reveal that while cooperation generally leads to higher systemic profits, the addition of a door-to-door service significantly alters the strategic landscape. We find that a higher consumer preference for the platform channel allows the center to lower prices while increasing profits, and that government subsidies are the most effective at enhancing service levels in cooperative models. Crucially, intense competition incentivizes recycling centers to reduce rather than increase their service levels to cut costs. This research provides a decision-making framework for recycling enterprises to select optimal service and competitive strategies. It also offers insights for policymakers on how to design subsidies to effectively promote high-convenience recycling services and foster a more efficient circular economy.

As a crucial paradigm for addressing urbanization-related problems, smart community construction is in full swing, and its goal is to enhance residents’ sense of gain. Prior studies have not been able to account for all aspects of smart community construction, especially the evaluation tools from the perspective of residents’ sense of gain. Therefore, this paper seeks to establish a comprehensive evaluation framework for residents’ sense of gain in the smart community through the integrated method, which includes the entropy weight method (EWM), the fuzzy comprehensive evaluation (FCE), and the obstacle degree model (ODM). For the purpose of verifying the feasibility of the evaluation framework, 31 smart communities in 6 Chinese cities (Shenzhen City, Putian City, Huizhou City, Dongguan City, Zhengzhou City, and Luoyang City) were selected. The results indicated that the weight of “Cultural activities for the elderly” indicator is the highest while the “Overall design” indicator is the lowest. In addition, Putian City had the best performance, but Shenzhen City ranked last among the six cities. Moreover, among the 31 communities, the Fengshan community in Putian City performed the best while the Xinglong community in Luoyang City performed the worst. Several suggestions are proposed to improve residents’ sense of gain in smart communities, such as enhancing the quality of healthcare services, meeting the needs of the elderly through multiple channels, and enriching business services. This study not only innovates the evaluation method of smart community construction from the perspective of residents’ sense of gain but also provides suggestions for promoting the sustainable development of the smart community and enabling residents to feel more satisfied.

Due to the randomness of interior combustibles, wall thermal inertia, and opening factor, the fire temperature rise in high-rise residential buildings is uncertain. This study investigated 38 urban high-rise residential buildings, created the probability density functions of fire load density, opening factor, and wall thermal inertia, and constructed random fire scenarios for urban high-rise residential buildings. On this basis, relying on the Latin Hypercube Sampling method, this study further explored the probabilistic model for fire temperature rise in urban high-rise residential buildings under the action of uncertain factors, generated the possible temperature rise curves of fires in urban high-rise residential buildings and their probability distribution, and established the most representative temperature rise curve.

Previous studies have shown that there is a large difference in the temperature of smoke in the upstream and downstream of a vertical shaft, but no quantitative study on the subject has been conducted. In this paper, a model experimental test was conducted to study the effect of a natural vertical shaft on the distribution of smoke temperature in tunnel fires. A laser sheet was used as an assisting tool to show the smoke flow field. A series of tests were conducted with shaft heights varying from 0.2 m to 1.2 m and a heat release rate (HRR) of 9 kW, 17 kW, 29 kW, and 65 kW. The entrainment phenomenon around the vertical shaft was analyzed, and the results showed that the amount of fresh air entrainment is the main reason for the temperature decrease in upstream and downstream smoke temperatures. Based on the experimental results, an empirical model for predicting the amount of fresh air entrainment and a prediction model of the downstream smoke temperature were proposed, and the predicted values are in good agreement with the experimental values.

As the basic unit of a smart city, the smart community has received considerable attention and problems in community governance have appeared simultaneously. Previous studies of smart community governance have failed to encompass all aspects, especially the evaluation tools for ensuring its outcomes. Therefore, this paper developed a comprehensive evaluation framework based on the CRITIC-TOPSIS method combined with the identified evaluation indicators. Seven smart communities from four cities in China were selected as cases to show how this evaluation framework could be applied to decision-making. The results indicated that the evaluation indicator ”Mediation of Conflict” had the highest weight while ”The participation of social enterprises in governance” had the lowest weight. Furthermore, the Yucun community presented the highest governance performance among these seven smart communities. Several strategies are proposed for improving the level of smart community governance, such as devoting significant resources to develop infrastructure in smart communities, facilitating communication among multiple participants, and increasing funding for the implementation of smart communities. This research contributes both to the innovation of community governance evaluation and to the improvement of smart communities.

As an essential part of intelligent monitoring, behavior recognition, automatic driving, and others, the challenge of multi-object tracking is still to ensure tracking accuracy and robustness, especially in complex occlusion environments. Aiming at the issues of the occlusion, background noise, and motion state violent change for multi-object in a complex scene, an improved DeepSORT algorithm based on YOLOv5 is proposed for multi-object tracking to enhance the speed and accuracy of tracking. Firstly, a general object motion model is devised, which is similar to the variable acceleration motion model, and a multi-object tracking framework with the general motion model is established. Then, the latest YOLOv5 algorithm, which has satisfactory detection accuracy, is utilized to obtain the object information as the input of multi-object tracking. An unscented Kalman filter (UKF) is proposed to estimate the motion state of multi-object to solve nonlinear errors. In addition, the adaptive factor is introduced to evaluate observation noise and detect abnormal observations so as to adaptively adjust the innovation covariance matrix. Finally, an improved DeepSORT algorithm for multi-object tracking is formed to promote robustness and accuracy. Extensive experiments are carried out on the MOT16 data set, and we compare the proposed algorithm with the DeepSORT algorithm. The results indicate that the speed and precision of the improved DeepSORT are increased by 4.75% and 2.30%, respectively. Especially in the MOT16 of the dynamic camera, the improved DeepSORT shows better performance.

Tourism networks are an important research part of tourism geography. Despite the significance of transportation in shaping tourism networks, current studies have mainly focused on the “daily behavior” of urban travel at the expense of tourism travel, which has been regarded as an “exceptional behavior”. To fill this gap, this study proposes a framework for exploring the spatial and temporal characteristics of urban tourism travel by taxi. We chose Shenzhen, a densely populated mega-city in China with abundant tourism resources, as a case study. First, we extracted tourist trips from taxi trajectories and used kernel density estimation to analyze the spatial aggregation characteristics of tourist trip origins. Second, we investigated the spatial dependence of tourist trips using local spatial autocorrelation analysis (Getis-Ord Gi*). Third, we explored the correlations between the tourist trip origins and urban geographic contextual factors (e.g., catering services and transportation facilities) using a geographically weighted regression model. The results show the following: (1) the trends between the coverage of tourist travel networks and the volume of tourist trips are similar; (2) the spatial interaction intensity of urban tourism has grouping and hierarchical characteristics; and (3) the spatial distribution of tourist trips by taxi is uneven and influenced by the distribution of urban morphology, tourism resources, and the preferences of taxi pick-up passengers. Our proposed framework and revealed spatial and temporal patterns have implications for urban tourism traffic planning, tourism product development, and tourist flow control in tourist attractions.