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With the development of the trend of cultural and tourism integration, intangible cultural heritage has become an important part of the development of experiential tourism. This paper combines information visualization technology to construct a framework for the design of non-heritage information visualization. By constructing a relevant spatio-temporal retrieval function to reduce the redundancy of non-heritage spatial data storage, combined with the base state correction model, the change process of non-heritage spatial features is retraced. GRU is applied as a unit of temporal feature correlation analysis to model the serial data of the degree of participation in non-heritage tourism revitalization. Two gating controls, the reset gate and the update gate, are used to regulate the flow of NRM information. The relationship between participation level in NRH tourism revitalization and experience was focused on in the information visualization design. The results show that the p-value of tourism experience and tourism revitalization is 0.521**, which is the most significant among all p-values, indicating that tourism experience has the closest relationship with tourism revitalization, and there is a significant positive correlation between both. Among the different groups of tourists, most of the experience scores of group C tourists are concentrated in the range of (80,90), while the advanced level of participation brings visual enjoyment to tourists while conveying the cultural spirit and emotional experience.

Bistatic and multistatic SAR technology, with its multi-dimensional, ultra-wide swath, and high-resolution advantages, is widely used in earth observation, military reconnaissance, deep space exploration, and other fields. The LuTan-1 (LT-1) mission employs two full-polarimetric L-band SAR satellites for the BiSAR system. The bistatic mode introduces phase errors in echo reception paths due to different transmission links, making echo compensation a key factor in ensuring BiSAR performance. This paper proposes a novel bistatic internal calibration strategy that combines ground temperature compensation, in-orbit internal calibration, and pulsed alternate synchronization to achieve echo compensation. Prior to launch, temperature compensation data for the internal calibration system are obtained via temperature experiments. During in-orbit operation, calibration data are acquired by executing the internal calibration pulse sequence and noninterrupted pulsed alternate synchronization. In ground processing, echo compensation is completed based on the above two parts of calibration data. A comprehensive analysis of the entire calibration chain reveals a temperature compensation accuracy of 0.10 dB/1.38°. Additionally, a ground verification system is established to conduct BiSAR experiments, achieving a phase synchronization accuracy of 0.16°. Furthermore, the in-orbit test obtained DSM products with an average error of 1.3 m. This strategy provides a valuable reference for future spaceborne bistatic and multistatic SAR systems. [ABSTRACT FROM AUTHOR]

Čerenkov luminescence tomography (CLT) is a highly sensitive and promising technique for three-dimensional non-invasive detection of radiopharmaceuticals in living organisms. However, the severe photon scattering effect causes ill-posedness of the inverse problem, and the results of CLT reconstruction are still unsatisfactory. In this work, a multi-stage cascade neural network is proposed to improve the performance of CLT reconstruction, which is based on the attention mechanism and introduces a special constraint. The network cascades an inverse sub-network (ISN) and a forward sub-network (FSN), where the ISN extrapolates the distribution of internal Čerenkov sources from the surface photon intensity, and the FSN is used to derive the surface photon intensity from the reconstructed Čerenkov source, similar to the transmission process of photons in living organisms. In addition, the FSN further optimizes the reconstruction results of the ISN. To evaluate the performance of our proposed method, numerical simulation experiments and in vivo experiments were carried out. The results show that compared with the existing methods, this method can achieve superior performance in terms of location accuracy and shape recovery capability. [ABSTRACT FROM AUTHOR]