From real to virtual sensors, an artificial intelligence approach for the industrial phase of end-of-line quality control of GDI pumps

The improvement of the quality of urban parks plays a vital role in the construction and development of urban society. This study examined the factors influencing recreational satisfaction with urban parks, providing a reference for measures to improve the quality of urban parks. Based on the theory of “Homo Urbanicus”, we conducted a factor analysis of recreation satisfaction with urban parks and constructed a structural equation model. It can be seen from the analysis results produced by the causal model that “supporting facilities” and “functional facilities” have the highest contributions to the factor load of the model, which indicates that individual recreational satisfaction with urban parks is mainly based on the relationship between individuals and space conditions. In other words, these elements are necessary to meet the requirement of the “physical” in the “Homo Urbanicus” theory and to supplement the “physical–group–rational” method structure in the “Homo Urbanicus” theory. This conclusion indicates that the improvement of the “functional facilities” and “supporting facilities” of urban parks will play an important role in improving recreational satisfaction with urban parks. The results of this study can help researchers to build an urban park quality evaluation system from the perspective of recreation quality.

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Research on the Factors Influencing the Perception of Urban Park Recreational Behavior Based on the “Homo Urbanicus” Theory

Light detection and ranging (LiDAR)-derived point cloud has become the standard spatial data for digital terrain model (DTM) construction; however, it suffers from huge data with much redundant information due to the oversampling. This often causes considerable inconvenience in the downstream data processing. To this end, an adaptive coarse-to-fine clustering and terrain feature-aware-based method is proposed to reduce data points in the context of terrain modeling in this paper. Firstly, a coarse-to-fine clustering method with the consideration of terrain complexity is developed to adaptively cluster LiDAR terrain points. Then, according to the geometric properties of terrain breaklines, a terrain feature-aware multi-strategy method is presented to pick representative points in the clusters. Finally, important boundary points including inflection point on the boundary curve and critical point on terrain features are further selected. The proposed method is compared with seven state-of-the-art point cloud simplification methods under six data reduction ratios on six plots with different terrain characteristics. Results indicate that the proposed method obtains a good balance between terrain-feature preservation and uniform distribution of data points. Compared to the state-of-the-art methods, the proposed method reduces the average root mean square errors (absolute errors) of the DTMs by 12.2%-51.7% (7.69%-83.8%) on the six plots. Moreover, the proposed method obtains the mean terrain slope and terrain roughness more reasonably approximate to the references. In short, the newly developed method can be considered as an alternative tool to select representative points from the huge remote-sensing-derived point cloud in the context of DTM production. 

Adaptive coarse-to-fine clustering and terrain feature-aware-based method for reducing LiDAR terrain point clouds

The detection of sidewall protrusions in highway tunnel is significant for the intelligent cleaning of tunnel walls. An automatic detection method for sidewall protrusions based on LiDAR in the scene of long curved tunnel walls is proposed in this paper. First, the ground point clouds are removed by using cloth simulation filter (CSF) algorithm. Then, the obstacles point clouds are clustered by combining the region growing (RG) algorithm and the improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. Finally, in order to separate wall protrusions and other obstacles, tunnel boundary is extracted by horizontally projecting the remaining point clouds after removing the ground point clouds. The experiments show that the proposed method in this paper can effectively detect the protrusions on the sidewall of the tunnel. 

Detection of Side Wall Protrusions in Highway Tunnel Based on LiDAR

The detection of sidewall protrusions in highway tunnel is significant for the intelligent cleaning of tunnel walls. An automatic detection method for sidewall protrusions based on LiDAR in the scene of long curved tunnel walls is proposed in this paper. First, the ground point clouds are removed by using cloth simulation filter (CSF) algorithm. Then, the obstacles point clouds are clustered by combining the region growing (RG) algorithm and the improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. Finally, in order to separate wall protrusions and other obstacles, tunnel boundary is extracted by horizontally projecting the remaining point clouds after removing the ground point clouds. The experiments show that the proposed method in this paper can effectively detect the protrusions on the sidewall of the tunnel.

A New Point Cloud Simplification Method with Feature and Integrity Preservation by Partition Strategy

With China’s urban renewal, parks have developed into significant green recreational areas in cities. This paper analyzed social media texts and compared the evaluation outcomes of the 50 most popular urban parks in Beijing from various perspectives, such as the characteristics of various groups of people, park types, and the spatial and temporal distribution characteristics of recreational activities. The importance–performance analysis method was used to analyze the main factors affecting visitors’ satisfaction with parks. The research found the following: (1) Positive evaluation of parks was related to environmental construction, event organization, etc., and negative evaluations focused on ticket supply, consumer spending, etc. (2) Visitors of different genders and from different regions focused on different aspects of parks. (3) In terms of traffic accessibility, historical and cultural display, parent–child activity organization, and ecological environment experience, people had diverse demands from various types of parks. (4) People were more likely to visit parks located within the range of all green belts in springs and parks located in the second green isolation belt in the fall. (5) The number of non-holiday reviews of parks was higher than that of holiday reviews. (6) Managers could improve visitor satisfaction by improving the infrastructure and management of parks.

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Shuaiqing Wang

Papers

A New Point Cloud Simplification Method with Feature and Integrity Preservation by Partition Strategy

Comparative Study of Park Evaluation Based on Text Analysis of Social Media: A Case Study of 50 Popular Parks in Beijing