This paper investigates the aperiodic sampled-data control for a chaotic system. Firstly, Takagi–Sugeno fuzzy models for the chaotic systems are established. The lower and upper bounds of the sampling period are taken into consideration. Then, the criteria for mean square exponential stability analysis and aperiodic sampled-data controller synthesis are provided by means of linear matrix inequalities. And the real sampling patterns can be fully captured by constructing suitable Lyapunov functions. Finally, an illustrative example shows that the proposed method is effective (...) to guarantee that the system’s states are stable with aperiodic sampled data. (shrink)

This study investigates the sampled-data admissibility problem for a singular system. The objective of this paper is to design a sampled-data controller to ensure the admissibility of a singular system and to construct an appropriate Lyapunov–Krasovskii functional to get less conservative results for the sampled-data singular system. To accomplish these objectives, the system is converted into a time-delay system by the input delay approach firstly, and both lower and upper bounds of the delay are considered. Secondly, by introducing a suitable (...) LKF, the admissibility criteria are obtained. Then, when estimating the derivative of the LKF, a relaxation variable is introduced by the method of reciprocally convex inequality, and it is proved that the conservatism is reduced. Finally, two numerical examples are given to prove that the designed sampled-data controller can ensure the states of the systems under the influence of external interference. (shrink)

In this paper, we analyze and calculate the crowd density in a tourist area utilizing video surveillance dynamic information analysis and divide the crowd counting and density estimation task into three stages. In this paper, novel scale perception module and inverse scale perception module are designed to further facilitate the mining of multiscale information by the counting model; the main function of the third stage is to generate the population distribution density map, which mainly consists of three columns of void (...) convolution with different void rates and generates the final population distribution density map using the feature maps of different branch regressions. Also, the algorithm uses jump connections between the top convolution and the bottom void convolution layers to reduce the risk of network gradient disappearance and gradient explosion and optimizes the network parameters using an intermediate supervision strategy. The hierarchical density estimator uses a hierarchical strategy to mine semantic features and multiscale information in a coarse-to-fine manner, and this is used to solve the problem of scale variation and perspective distortion. Also, considering that the background noise affects the quality of the generated density map, the soft attention mechanism is integrated into the model to stretch the distance between the foreground and background to further improve the quality of the density map. Also, inspired by multitask learning, this paper embeds an auxiliary count classifier in the count model to perform the count classification auxiliary task and to increase the model’s ability to express semantic information. Numerous experimental results demonstrate the effectiveness and feasibility of the proposed algorithm in solving the problems of scale variation and perspective distortion. (shrink)

According to conceptual metaphor theory, individuals are thought to understand or express abstract concepts by using referents in the physical world—right and left for moral and immoral, for example. In this research, we used a modified Stroop paradigm to explore how abstract moral concepts are metaphorically translated onto physical referents in Chinese culture using the Chinese language. We presented Chinese characters related to moral and immoral abstract concepts in either non-distorted or distorted positions or rotated to the right or to (...) the left. When we asked participants to identify the Chinese characters, they more quickly and accurately identified morally positive characters if they were oriented upright or turned to the right and more quickly and accurately identified immoral characters when the characters were distorted or rotated left. These results support the idea that physical cues are used in metaphorically encoding social abstractions and moral norms and provided cross-cultural validation for conceptual metaphor theory, which would predict our results. (shrink)

This study aimed to examine the relationship between parents' intelligence mindset and children's math anxiety and the mediating role of parents' failure mindset and evaluations of their child's math performance. A total of 419 Chinese students and their parents were recruited to complete a series of questionnaires on topics such as math anxiety, parent's failure mindset, parent's intelligence mindset, and parents' evaluations of their child's mathematical performance. The results revealed that parents' intelligence mindset was not correlated with children's math anxiety. (...) However, parents' intelligence mindset indirectly predicted children's math anxiety through the chain-mediated role of parents' failure beliefs and parents' evaluations of their child's math performance. Further, sex differences were found through a multigroup analysis, which showed a chain-mediated effect between parents' intelligence mindset and girls' math anxiety. (shrink)