Search

In order to find a simpler method to simulate the charging of spacecraft surface and further analyze the characteristics of the charging reaction of low-orbit spacecraft surface materials, this paper uses COMSOL to perform finite element analysis on the charging of low-orbit spacecraft surface materials at an altitude of 300–400 km. First, the surface charging potential is established using the particle transport equation. By calculating the thermal diffusion movement of particles, the adsorption, secondary electron emission and backscattering effects of the material surface are evaluated to simulate the charging potential of the spacecraft surface. The results show that COMSOL based on the plasma module can replace SPIS to simulate the charged properties of spacecraft surface materials, indicating that different physical properties of the material surface are attached with different magnitudes of potential and small potential differences; In addition, based on the particle transport equation, this paper obtains the surface charging results of the Kapton connector between the solar panel and the spacecraft body, which is prone to charging. This research content provides a simplified method and new direction for the simulation study of spacecraft surface charging.

Major water conservancy projects face the risk of damage from conflict, and the potential consequences of dam failure can lead to widespread public outrage, posing a threat to social stability. This study analyzed the formation model of network public opinion risk, using the Kakhovka Hydropower station damaged during conflict as a case study. Based on data analysis of netizen’ comments on Twitter and Weibo (a Chinese social media platform similar to Twitter), we used data mining algorithm to identify the primary topics of interest and examine the evolution of public opinion. The findings indicate that attention to incident resulting in war damage has a negative impact on social stability through a feedback loop. Netizen on Twitter and Weibo were primarily focused on “Flood” “Crisis” “Charge” and “Help” topics. Among them, Twitter was more popular in terms of public opinion and had faster dissemination speed. “Crisis” and “Charge” were more likely to generate public opinion risks. The potential impact of war damage on social stability is noteworthy, and social stability is largely dependent on the attention level of netizen.

Radar is a valuable tool for noncontact vital-sign detection. Interference from respiratory harmonics presents a major challenge in radar cardiogram (RCG) extraction—mainly when the frequency of respiratory harmonics is close to or equal to that of the cardiac sub-signals. To address this problem, a respiratory harmonic suppression method employing correlation analysis and an optimized feedback notch filter is proposed, which is based on 7.29 GHz center-frequency impulse-radio ultra-wideband radar. A genetic optimization algorithm is employed to optimize the parameters of the notch filter. Performance comparison analysis is conducted on the conventional notch filter and the feedback notch filter. Contact (ECG) and non-contact (RCG) data from 10 subjects were analyzed. The results verified that the performance of the optimized feedback notch filter is much better than that of the conventional notch filter in overshoot, bandwidth, and notch depth, and the proposed method can effectively locate, identify, and suppress respiratory harmonics from the RCG band while preserving heartbeat components. Consequently, this approach markedly enhances the precision of RCG extraction. The technique shows considerable promise for deployment in diverse practical settings, including non-contact auxiliary monitoring systems in both intelligent medical environments and home healthcare.

Homomorphic encryption (HE) enables third-party servers to perform computations on encrypted user data while preserving privacy. Although conceptually attractive, the speed of software implementations of HE is almost impractical. To address this challenge, various domain-specific architectures have been proposed to accelerate homomorphic evaluation, but efficiency remains a bottleneck. In this paper, we propose a homomorphic evaluation accelerator with heterogeneous reconfigurable modular computing units (RCUs) for the Brakerski/Fan-Vercauteren (BFV) scheme. RCUs leverage operator abstraction to efficiently perform basic sub-operations of homomorphic evaluation such as residue number system (RNS) conversion, number theoretic transform (NTT), and other modular computations. By combining these sub-operations, complex homomorphic evaluation operations like multiplication, rotation, and addition are efficiently executed. To address the high demand for data access and improve memory efficiency, we design a coordinate-based address encoding strategy that enables in-place and conflict-free data access. Furthermore, specific optimizations are performed on the core sub-operations such as NTT and automorphism. The proposed architecture is implemented on Xilinx Virtex-7 and UltraScale+ FPGA platforms and evaluated for polynomials of length 4096. Compared to state-of-the-art accelerators with the same parameter set, our accelerator achieves the following advantages: $1)\,\,2.04\times $ to $3.33\times $ reduction in the area-time product (ATP) for the key sub-operation NTT, $2)\,\,1.08\times $ to $7.42\times $ reduction in latency for homomorphic multiplication with higher area efficiency, and 3) support for a wider range of homomorphic evaluation operations, including rotation, compared to other BFV-based accelerators.

Winding deformation caused by short-circuit is one of the main causes of transformer damage. Even if the transformer successfully withstands one short-circuit impact, accumulative effect of multiple short-circuit impacts will cause sudden permanent deformation of the winding. Internal winding deformation is a hidden fault due to the visual blocking of the shell of transformer, so it is extremely important to measure the accumulative effect and analyze its influence. In this paper, a SFSZ7-31500/110 transformer was used for short-time multiple short-circuit impact tests. The measurability of accumulative effect was determined by calculating the difference between measured value and reference value of the acceleration of the time-domain vibration acceleration signal, and then a time-frequency matrix was constructed based on Wigner-Ville Distribution (WVD) time-frequency analysis. Based on Fuzzy C-Means (FCM) clustering and the singular values of the matrix, the membership degree of winding mechanical state was calculated, and the influence degree of the accumulative effect was quantitatively analyzed. Results show the method can reflect the deformation trend and degree of winding before the impedance change rate. Research provides some reference for the mechanical state evaluation and fault early warning of windings, and also has a guiding significance for the safe and stable operation of transformers.

Different types of noise interference lead to low accuracy of image edge detection and severe loss of feature extraction details. A new noise-robust edge detection method is proposed, which uses a set of multiscale anisotropic morphological directional derivatives to extract the edge map of an input image. The main advantage of the method is that high edge resolution is maintained while reducing noise interference. The following five parts form the whole framework of this paper. First, multiscale anisotropic morphologic directional derivatives (MSAMDDs) are proposed to filter and obtain the local gray value of the image. Second, the edge strength map (ESM) is extracted by using spatial matching filters. In the third stage, multiscale edge direction maps (EDMs) based on the directional matched filters are fused, and the new EDM is constructed. Fourth, edge contours are obtained by embedding the ESM and the EDM into the standard route of Canny detection. Finally, the precision-recall curve and Pratt’s figure of merit (FOM) are used to evaluate the proposed method against eight state-of-the-art methods on three data sets. The experimental results show that the proposed method can perform better for noise-free (F-measure value of 0.776) and Gaussian noise (FOM value of 95.75%) and attains the best performance in impulse noise images (highest FOM value of 98.90%).

Submarine cables are indispensable in today’s international data transmission. In the process of submarine cable path planning, any factors that may potentially affect reliability and cost should be considered. Still, the degree of importance of these factors is difficult to assess accurately. Currently, cable path planning is done manually, meter by meter, over thousands of kilometers by experts that rely on their experience and expertise. This paper provides a submarine cable path planning algorithm based on simulated annealing (SA) and the fast marching method (FMM). Accordingly, we name the algorithm FMM/SA. FMM/SA can be used as a guide and benchmark for cable path planners and also enhances understanding of the multiple considerations and their corresponding weights aiming to further improve the end-results beyond what is obtained currently by experts. In FMM/SA, SA is used to optimize weights of design considerations to minimize the Fréchet distance between existing cable paths and paths with minimized total life-cycle cost obtained by FMM. FMM/SA is demonstrated to be superior to two other algorithms based on random-restart hill-climbing and Monte Carlo using real-life cable paths.

Base station (BS) plays a critical role in the wireless network. There has been some research on exploring the spatio-temporal information of BS in different fields. However, these works lack re-usability, which require the new researcher to re-do the work of representing the spatio-temporal information. To solve this problem, we propose a neural network model based on autoencoder and representation learning called BSENet to learn embedding of BS based on raw data. The embedding contains spatio-temporal information of BS. In this way, other fields that are related to BS can make use of spatio-temporal information with BSENet embeddings. Besides the spatial information, BSENet can maintain the independence of BS. Moreover, we use bi-directional LSTM to get temporal information and propose a time dropout method to improve the generalization ability. We propose a soft threshold to consider all spatial relations. In addition, we introduce weight to enhance compatibility. We treat the missing states as the inputs to deal with the missing values. The results of clustering show that BSENet embedding is better than other embeddings. In experiments of mobile traffic prediction, BSENet embedding helps a temporal model to improve the Mean Squared Error (MSE) from 0.01463 to 0.01334, which is similar to 0.01302 of a spatio-temporal model. At the same time, the training time increases a little but is still $5.0 times$ faster than spatio-temporal model.

Airborne hyperspectral data have both high spectral and spatial resolutions. Although the finer spatial resolution allows more abundant spatial characteristics to be exhibited, the spectral variability problem remains. However, few of the current spatial-spectral target detection methods can fully exploit the spatial information while solving the spectral variability problem. In this paper, a sparse spatial-spectral conditional random field (CRF) target detection framework for airborne hyperspectral data, namely S3CRF, is proposed to address these problems, in which the unary and pairwise potential functions are designed accordingly. To model the spatial information in a larger neighborhood while solving the spectral variability problem, an object-oriented strategy is introduced to modify the residual map obtained by sparse representation. For the pairwise potential function, the adaptive local eight-neighborhood structure is constructed considering the neighboring spatial correlations. Furthermore, global spatial-contextual information is captured through the inference of S3CRF. Finally, the a posteriori probability of each pixel belonging to the target is utilized for the target detection. The experiments undertaken in this study confirmed that the proposed method can effectively suppress the background while achieving a competitive quantitative and qualitative target detection performance.

Security is critical to the growing popularity of the Internet of Things(IoT), and true random number generator (TRNG) plays an increasingly important role in information security systems. Conventional TRNGs use natural physical stochastic processes including thermal noise, chaos-based circuit, and so on to generate random numbers. These analog circuits based TRNG structures often consume excessive hardware resources. Meanwhile, it is difficult to incorporate them into digital system. In this paper, a novel all-digital true random number generator in SRAM-based FPGAs is proposed by using Vernier technique that precisely quantize random edge jitter. The proposed TRNG design is implemented on Xilinx Virtex-6 XC6VLX240T-1FF1156 FPGA and shows a high quality of randomness which has passed the NIST test suite with relatively high p-values, achieves a high throughput of 127 Mbps with occupying 32 slices. Experimental results show a good tolerance to bias phenomenon induced by process, voltage, and temperature variations.

Self-decoupled and passive characteristics are crucial requirements for a multi-dimensional sensor. A T-type self-decoupled and passive dynamic tension and torque sensor was proposed, analyzed, and fabricated. The sensor mainly consisted of a T-type torque deforming block, a force deforming ring, and a torque shaft. The T-type torque deforming block withstood the torque individually; the force deforming ring bore the tension force separately; and the decoupling of the tension force and torque was realized by the torque shaft. After that, the tension force and torque were measured, respectively. The decoupling operation was fully completed by mechanical structure. Two pieces of magnetostrictive material were pasted on the T-type torque deforming block and force deforming ring as the sensing units. The passive feature was fulfilled by the magnetostrictive material via the Villari effect. Finite Element Method (FEM) analysis was carried out to verify the decoupling principle. The sensor was fabricated, and then the experiments were conducted. The results showed that the sensor had a good decoupling ability. The sensor could work dynamically with a voltage deviation less than 0.5 mV. The force and torque ranges of the sensor were 1000 N and 6.5 $\text{N}\cdot \text{m}$ respectively. The sensor could also work effectively in a passive state. Furthermore, the sensor displayed the advantages of being wireless, the ability to work dynamically and in a liquid environment. Thus, this sensor could be mounted on a cutting tool of a machine center to detect the compound force on the cutting tool.

We describe a cost-effective approach to path planning for submarine cables connecting a given site to an existing cable network on the Earth's surface. The objective is to minimize the overall life-cycle cost of submarine cables by considering multiple design considerations. With the surface terrain represented by a triangulated manifold, we formulate the problem as one of the variational optimization framed in terms of an Eikonal equation and solved by leveraging the fast marching method. The results based on real-world three-dimensional data are presented to illustrate the performance of this approach in the submarine cable network extension.

The study on terahertz radiators will not only boost the development of theoretical research, but also raise severe challenges to solid-state electronics and circuit technology. In the present paper, the transmission characteristics of microstrip-slot coupling structures are primarily studied in 1-3THz band. Based on the single-layer dielectric structure, a double-layer dielectric microstrip-slot coupling structure with air as one layer is presented. It is reported that adding air layer based on the single-layer structure helps reduce the loss. Besides, given the factors of Engineering processing, the structure of three-layer media is also proposed; it is found that the structure of three-layer media still has exhibits transmission loss when the engineering realization is satisfied. However, this study suggests that the loss of the three-layer structure is higher than that of the two-layer structure, whereas the effect is better than that of the single-layer structure.