To address the problem that the imaging inversion method based on a single model in integrated aperture imaging is difficult to effectively correct model errors and perform accurate image reconstruction, a dual-model (DM)-based integrated aperture imaging inversion method is proposed for correcting the parametric errors of the inversion model and performing highly accurate millimeter-wave image reconstruction of the target scene. In view of the different parameter sensitivities of the Fourier transform (MFFT) model and the G-matrix (GM) model, the proposed DM method first corrects the imaging parameters with errors accurately by comparing the reconstruction errors of the two models; then recon-structs a high-precision target image based on the accurate GM model with the help of an improved regularization method. It is proved by simulation experiments that the proposed DM method can effectively correct the parameter errors of the imaging model and reconstruct the target scene with high accuracy in millimeter wave images compared with the traditional single-model imaging method.

This article concerns  with  the  construction of the  analytical traveling  wave so- lutions  for the Generalized-Zakharov System  by the Riccati-Bernoulli Sub- ODE technique. Also, we will discuss this  technique  in random  case by using random  traveling  wave trans- formation  in order  to  find what  is the  effect of the  randomness  input  for this  technique. We presented the Generalized-Zakharov System as an example to show the difference effect between the deterministic and stochastic Riccati-Bernoulli Sub-ODE technique.  The first moment of random solution is computed for different statistical probability distributions.

Aiming at the current problems of poor dynamic reconstruction of UAV aerial remote sensing images and low image clarity, the dynamic reconstruction method of UAV aerial remote sensing images based on compression perception is proposed. Construct a quality reduction model for UAV aerial remote sensing images, obtain image feature information, and further noise reduction preprocessing of UAV aerial remote sensing images to better improve the resolution, spectral and multi-temporal trends of UAV aerial remote sensing images, and effectively solve the problems of resource waste such as large amount of sampled data, long sampling time and large amount of data transmission and storage. Maximize the UAV aerial remote sensing images sampling rate, reduce the complexity of dynamic reconstruction of UAV aerial remote sensing images, and effectively obtain the research requirements of high-quality image reconstruction. The experimental results show that the proposed dynamic reconstruction method of UAV aerial remote sensing images based on compressed sensing is correct and effective, which is better than the current mainstream methods.

With the advent of the era of globalized economy, more attention should be paid to the training mode of comprehensive English literacy in colleges and universities in teaching. Therefore, how to cultivate and improve students' higher-level teaching methods in the context of ecolinguistics, so as to improve the quality of English teaching, is the current focus of English teaching in colleges and universities. By summarizing the basic concepts of ecolinguistics, this paper studies effective measures to improve the quality of linguistics teaching in colleges and universities, and comprehensively improves the quality and efficiency of English language teaching in colleges and universities under the background of ecolinguistics.

China is currently at a critical juncture in implementing the rural revitalization strategy, with urbanization and tourism development as crucial components. This study investigates 41 counties (cities) in the Wuling Mountain area of central China, constructing an evaluation system for the coordinated development of these two sectors. The coupling coordination degree is calculated using a combination weighting method and the coupling coordination degree model. Spatio-temporal evolution characteristics are analyzed through spatial autocorrelation, while the geographic detector explores the driving factors of spatial variation. The findings reveal a significant increase in coupling coordination between urbanization and tourism, transitioning towards a coordinated phase. Spatially, urbanization and tourism exhibit positive correlations, with high-value clusters in the southeast and northwest and low-value clusters in the south. The geographical detector identifies industrial factors as the most critical drivers of spatial variation. This study offers novel insights into the dynamics of urbanization and tourism, contributing to the broader literature by providing practical implications for regional planning and sustainable development. The results are relevant to the Wuling Mountain area and serve as a reference for similar regions globally. However, the study has certain limitations, such as regional specificity and data availability, which should be considered in the context of this research.

This article explores a method for evaluating the achievement of learning effectiveness based on virtual reality technology. The research analyzed the design and construction of a virtual learning environment, data collection of learner behavior, data analysis and evaluation methods, evaluation indicators and personalized feedback, as well as a case study of a virtual learning evaluation system. By using virtual reality technology to create an immersive learning environment, learners can gain an immersive learning experience, and evaluators can accurately record learners' behavior and performance. The learning effectiveness evaluation method based on virtual reality technology can improve learning effectiveness and teaching quality, promote educational innovation and development. These research results are of great significance for the evaluation of virtual learning effectiveness and personalized teaching in the field of education.