Satellite networks can enhance global network coverage without geographical restrictions. By applying edge computing paradigm to satellite networks, they can provide communication and computation services for Internet of Remote Things (IoRT) mobile devices (IMDs) at any time. Thus, in 6G mobile systems, satellite networks serve as a complement to terrestrial networks. This paper places its emphasis on satellite-terrestrial integrated networks (STINs). Computation offloading and resource allocation (CORA) play a crucial role in STINs given the limited communication and computation resources of satellites. In this paper, we investigate the CORA to minimize system energy consumption while ensuring the latency tolerance via jointly optimizing the offloading decision and the allocation of radio and computation resources. Taking into account the dynamic characteristics of network conditions, the CORA problem is formulated as a Markov decision process (MDP). Subsequently, an algorithm based on twin delayed deep deterministic policy gradient (TD3) is designed to automatically determine the optimal decisions. Finally, the convergence and superiority of the proposed algorithm in terms of energy efficiency are evaluated through extensive simulation experiments.

The feasibility of employing a continuous-wave terahertz detection system for non-contact and non-destructive testing (NDT) in multi-layered bonding structures is assessed in this study. The paper introduces the detection principle of terahertz frequency modulated continuous wave (FMCW) radar and outlines the two-dimensional (2D) scanning platform, which integrates optical lenses, three linear actuators, a control platform, and data acquisition units. Experimental results on two types of insulation with prefabricated defects demonstrate the capability of terahertz waves for transparent inspection imaging. These results confirm the viability of terahertz FMCW detection technology as an advanced NDT tool for multi-layered bonding structures. However, the inherent limitations of terahertz wavelength and hardware systems pose challenges in discriminating reflection peaks on upper and lower surfaces. To address this issue, a local adaptive empirical wavelet coefficient modal decomposition (LAEWCMD) method is proposed to enhance the longitudinal discrimination ability of terahertz detection. The proposed method involves segmenting the 2D terahertz detection image into regions to differentiate between defective and non-defective areas. Continuous wavelet transforms (CWT) are then applied to the range signals of each region to derive continuous wavelet coefficients (CWCs). Subsequently, empirical mode decomposition (EMD) is performed on the CWCs to decompose them into intrinsic mode functions (IMFs) and residual signals. The 1st IMF is utilized for three-dimensional (3D) reconstruction, and the regions are fused to generate the final output. The effectiveness of the proposed method is validated on aircraft thermal protection structures (TPS), achieving high-precision 3D reconstruction. This offers a novel approach for the application of terahertz computed tomography imaging and NDT.

Continuous terahertz detection imaging technology is widely used in polymer detection. However, it is very difficult to quantitatively analyze defects due to the characteristics of focusing lenses. On the one hand, a lens with a short focal length means the achievement of a better spatial resolution and a poor depth resolution. On the other hand, a lens with a long focal length results in a better depth resolution and a worse spatial resolution. In addition, in order to ensure the positioning accuracy, the upper surface of a sample is often used as the focal plane for detection, which causes the energy outside the range of the focal depth to drastically decrease and seriously affect the imaging quality. In this paper, a method is proposed for debond detection and quantitative analysis in layered structures. Firstly, by using multi-directional structural elements for measuring the difference between the debonding region and local surroundings, we extract defective edges and suppress clutters by extracting a multi-directional morphological filter. Then, the improved Otsu method is used for threshold segmentation. The superiority of the proposed method is confirmed on synthetic datasets with low SNR image and real terahertz images. Moreover, the detection error in the terahertz images of layered structures is controlled within 10.17%-11.27%. It provides a new method and idea for quantitative analysis of terahertz detection in layered structures.

Due to the weak longitudinal signals generated by laser ultrasound in the thermoelastic mechanism, the characteristic echoes are weak when evaluating the interior of solids, thus limiting its application to internal defect detection. A glass confinement layer is introduced to enhance the longitudinal excitation effectiveness. Specially, a thermoelastic model of laser ultrasound with a glass confinement is established to explain the mechanism of the enhancement of the longitudinal wave effectiveness, and the effect of the glass width on the longitudinal wave generated by the base ultrasound is investigated. The effect of the glass confinement layer on the enhancement of the effectiveness of the internal defects detection is studied. The simulation and experimental results show that the longitudinal waves with high signal-to-noise ratio induced from thermoelastic effect are excited similar to the ablation mechanism, which greatly improves the excitation efficiency of the longitudinal waves. The deep detection defects and the accurate localization of depth information are realized with an error of no more than 1.2%.

In order to meet the increasing demand of non-destructive testing (NDT) in engineering practice, a continuous terahertz NDT platform based on linear scanning has been developed, with a center frequency of 154 GHz and a bandwidth of 56 GHz. This system combines frequency modulation continuous wave (FMCW) radar technology with a continuous scanning structure, as well as a data acquisition platform to provide a non-contact detection method; this is highly efficient and compensates for the shortcomings of traditional methods such as microwave, X-ray, ultrasonic, and others in safety inspection and special detection. In addition, a signal processing method of spectral refinement and correction is proposed in this paper for accurate thickness measurement. The results show that the method has a high accuracy for ABS, PVC, and ceramic matrix composites. By extracting the characteristic parameters, the detection and imaging of prefabricated defects, such as debonding and bubbles in composite materials, have been successfully achieved. This helps to evaluate the internal state of the inspected object more intuitively and further meets the requirements of industrial NDT.

Most existing studies on the optimal bandwidth selection for plant nitrogen are based on the sensitive band center, and determine the optimal bands by manually adjusting the bandwidth, step by step. However, this method has a high level of manual involvement and is time-consuming. This paper focused on rice as the research subject, based on determining the center of the rice plant nitrogen-sensitive bands and the maximum region Ω of the fitted R² between the narrow-band vegetation indices (N-VIs) and plant nitrogen, a method was proposed to automatically select the optimal bandwidth by constructing inscribed rectangles. UAV hyperspectral images were used to carry out the spatial inversion and precision verification of the rice plant nitrogen, based on the optimal width of sensitive bands. The results revealed that the optimal bandwidths, automatically selected on the basis of N-VIs via the inscribed rectangle method, achieved good results in the remote sensing inversion of plant nitrogen at the rice jointing and flowering stages, with the coefficient of determination (R²) greater than 0.49 to satisfy the requirement of significance (p < 0.05) and the normalized root mean square error (NRMSE) and mean relative error (MRE) of less than 13%. These findings indicate that the method of crop plant nitrogen inversion band center screening and automatic search for the optimal bandwidth in this study has certain feasibility, which provides a new idea for screening the optimal bandwidth on the basis of the sensitive band center and provides technical support for the design of satellite band parameters.