esa-sceva/satcom-chunk-collection huggingface dataset:
# Transformer Self-Attention Change Detection Network with Frozen Parameters
## 6 Conclusions  
This paper proposes ZAQNet, a Transformer self-attention change detection network with frozen parameters, designed to improve the accuracy of change detection in remote sensing images. By leveraging the advantages of CNNs and Transformers, ZAQNet effectively extracts both local and global features while reducing computational costs. The network integrates three key self-attention modules--the GIAU, GSAU, and GSCU--alongside the  
\begin{table}
\begin{tabular}{l l l l l} \hline
**Method** & **Flops (G)** & **Param (M)** & **Inference (ms/Picture)** & **\(F\)1 (\%)** \\ \hline FC-EF & 1.19 & 1.35 & 2.29 & 83.42 \\ FC-Siam-Diff & 2.33 & 1.35 & 9.82 & 86.31 \\ FC-Siam-Conc & 2.33 & 1.55 & 10.41 & 86.37 \\ TCDNet & 19.01 & 8.76 & 20.83 & 87.19 \\ SNUNet & 43.94 & 12.03 & 12.51 & 87.28 \\ MFGAN & 67.88 & 45.99 & 48.02 & 87.34 \\ STANet & 18.03 & 16.94 & 13.16 & 87.51 \\ DASNet & 107.69 & 57.36 & 19.27 & 88.48 \\ TFI-GR & 14.25 & 33.23 & 18.37 & 88.50 \\ ChangeNet & 10.33 & 20.49 & 15.88 & 88.65 \\ BIT & 25.92 & 11.99 & 14.03 & 89.32 \\ ChangeFormer & 23.10 & 51.47 & 18.38 & 89.57 \\ \hline ZAQNet (our) & 10.55 & 9.09 & 14.52 & 91.36 \\ \hline \end{tabular}
\end{table}
Table 5: Comparative experiments of multiple efficiency indicators of the models.  
PRU module, ensuring precise feature extraction and refinement. Extensive experiments on the BTRS-CD and LEVIR-CD datasets validate the superiority of ZAQNet, achieving state-of-the-art performance in multiple evaluation metrics. These results highlight the effectiveness of parameter freezing and self-attention mechanisms in remote sensing change detection tasks. Looking ahead, further research will focus on improving model adaptability, optimizing computational efficiency, and extending the framework to multi-modal data fusion. By addressing these challenges, ZAQNet is expected to play a greater role in real-world applications such as environmental monitoring, urban planning, and disaster assessment.  
Conceptualization, P.C. and M.X.; methodology, P.C. and D.W.; software, P.C. and D.W.; validation, Z.Z. and H.L.; formal analysis, D.W.; investigation, P.C. and M.X.; resources, M.X.; data curation, D.W.; writing--original draft preparation, P.C. and D.W.; writing--review and editing, H.L.; visualization, M.X.; supervision, M.X.; project administration, M.X.; and funding acquisition, M.X. All authors have read and agreed to the published version of the manuscript.  
This work is supported in part by the National Natural Science Foundation of PR China (42075130).  
Not applicable  
The data and the code of this study are available from [[https://github.com/RenHongjin6/MYNet](https://github.com/RenHongjin6/MYNet)]([https://github.com/RenHongjin6/MYNet](https://github.com/RenHongjin6/MYNet)) accessed on 1 March 2025.  
The authors declare no conflicts of interest.
## 2 Related Works
### Audio Watermarking Algorithms  
Over the past few years, most proposed audio watermarking algorithms [8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24] can be grouped into two categories: Spread spectrum (SS) modulation [8; 9; 10] and quantization index modulation (QIM) [11; 12; 13; 14]. All these methods utilize either a time domain [15; 16] or a transform domain such as fast Fourier transform [17], discrete cosine transform [18], or discrete wavelet transform [19]. From the watermark extraction mode, digital watermarking algorithms can be divided into three schemes: Blind, semi-blind and non-blind. Among them, blind methods, which extract watermarks without knowing the host audio signal, are highly desirable, because semi-blind and non-blind methods are not applicable to most practical applications.  
The SS-based watermarking scheme embeds a watermark bit into a host audio segment by using pseudorandom number sequences which are shaped to fit under the masking threshold of the audio signal. At the extractor, the watermarks are extracted by a sliding correlator that correlates the received signal to the predefined spread spectrum template. One of the main drawbacks of the existing SS-based audio watermarking methods is their low embedding capacity. Hence, their main task is to increase embedding capacity while maintaining high imperceptibility and robustness.  
The QIM approach uses a set of quantizers to quantify the host signal features to embed watermarking data, and each quantizer is associated with different information. In most cases, to obtain high robustness, quantization is implemented to some coefficients in the transform domain rather than to signal samples. Though the QIM approach usually has merits of low complexity and high embedding capacity, it has low robustness.  
Another audio watermarking algorithm is autocorrelation modulation [20; 21; 22]. Its basic idea is that inserting a delayed or advanced version of the host signal itself can modify autocorrelation. In other words, it uses a delayed and modulated version of the host signal as a watermark signal (the difference between the host and watermarked signal), which is then inserted back to the host signal to make the final watermarked signal. A common watermarking approach is to introduce the watermark signal as noise, but a drawback to these approaches is that lossy audio compression algorithms tend to remove most imperceptible artifacts, including typical low dB noise. Autocorrelation modulation introduces changes to the host signal that are characteristic of environmental conditions rather than random noise. Therefore, using a host signal as a watermark signal can be robust against lossy audio compression. In this paper, we present an autocorrelation modulation-based audio blind watermarking algorithm which maximizes robustness against low-bit rate HE-AAC compression. In the next section, the detail of the proposed audio watermarking method is described.
# An Improved Approach to DNS Covert Channel Detection Based on DBM-ENSec
## 2 Related Work  
To effectively address the intricate and covert security threats presented by DCCs, researchers have conducted extensive investigations into innovative detection methodologies aimed at enhancing detection accuracy. These studies extend beyond the mere optimization and extraction of traditional features; they also prioritize the creation of detection frameworks that integrate deep learning with feature engineering to discern covert data transmission patterns within DCCs. The utilization of multi-dimensional analyses of traffic behavior and domain characteristics is crucial in the advancement of more robust and efficient detection systems.
# Post Quantum Cryptographic Keys Generated with Physical Unclonable Functions
## 5 Experimental Evaluation  
The purpose of this evaluation is to demonstrate the practicality of the proposed protocols and understand the potential limitations. The replacement of the random number generators by the PUFs follow a similar path for various PQC algorithms; therefore we reduced the scope of this evaluation to LWE (qTESLA, CRYSTALS-Dilithium), and LWR (LightSABER). The generation of the Seed K from the PUF is done using known methods, and the computation of the key pairs is based on the PQC codes made available by NIST, which are also considered known. The unknown in the practicality of the protocol is the sensitivity to bit error rates (BER) of the search engine of the CA for verifying the public keys. The RBC method [34; 35; 36; 37] uses the Seed K' as a starting point to generate an initial public key, then iterates by incrementally adding errors, eventually finding the public key computed from Seed K by the client device. At high BER, it is desirable to use cryptographic algorithms that have the ability to generate the key pairs at high throughput.  
The RBC itself is an interesting simulation platform for this evaluation, because of the possibility to directly measure the throughput in term of the number of key pairs generated by second. We selected the RBC to experimentally demonstrate that the PQC protocols are fast enough. We designed an experiment to benchmark three algorithms, (qTESLA, CRYSTALS-Dilithium, and LightSABER) with two known cryptosystems (AES and ECC). Each of these cryptosystems have a list of parameter sets as a part of their specifications. We chose parameter sets that were inherently compatible with a 256-bit output from a hypothetical PUF as well as these that were best optimized between performance, size, and security for IoT devices. For these reasons, the parameter sets AES256, ECC Secp256r1, qTESLA-p-I, CRYSTALS-Dilithium 2, and LightSABER were used for the performance comparison. In this analysis, the comparison with ECC is the most relevant one, because the PQC codes under consideration and ECC are similar in their objective to generate public-private keys pairs for PKI. Therefore, ECC and the three PQC algorithms are tested here with their software versions. The comparison with AES was included as a benchmark of excellence; we used the hardware implementation of AES, natively available in Intel processors. One of the objectives of the PQC standardization program driven by the NIST is to encourage private industry to eventually design hardware implementations of the selected codes.  
We summarize the parameter sets for each algorithm and our motivation for their selection in Table 2, as shown below.
## 2 SGP System Description
### Measurement Strategy  
The system is designed to work autonomously, being able to localize itself within the first 24 h of being switched on. This implies that the system can determine its coordinates without any previous information besides the time.  
Given a sufficient supply of electric power, for instance if the object has a steady power supply, the initialization can be simply performed using brute force by continuously sampling the lighting condition. If the light sensor is sampled at \(r\) samples per second, then this is the same as \(M\) samples for each 24 h cycle, given by:  
\[M=24\times 60\times 60\times r\]  
The accuracy of the measurements will therefore be in the range of:  
\[a=\frac{360}{M}\]  
It will take maximum 24 h to identify the location and the effort involved is defined by \(E~{}=~{}M\times p\), where \(p\) is the energy consumed to perform each sample and \(E\) is the total energy. This is the optimal solution in terms of speed and accuracy. However, for a power constrained device the strategy is unrealistic as a very simple device could run out of power after just a few hours or sooner, although the latest technologies released are improving the energy consumption and some devices can run for months with standard off-the-shelf AA batteries.
###### Abstract  
In this paper, a wideband circularly polarized folded reflectarray antenna (CPFRA) based on a transmissive linear-to-circular polarization converter is proposed. The CPFRA consists of a primary reflector and a sub-reflector. To achieve broadband performance, a metasurface-based RA element on the primary reflector surface and a transmissive linear-to-circular polarization converter on the sub-reflector surface are applied. Moreover, the transmissive linear-to-circular polarization converter on the sub-reflector surface helps convert linear polarization to circular polarization. To verify the proposed CPFRA, a prototype is designed, fabricated, and tested. The measured results exhibit that the proposed CPFRA presents a 3 dB gain bandwidth of 27.4% and a 3 dB axial ratio bandwidth of 23%. The CPFRA achieves a peak gain of 21.2 dBi with an aperture efficiency of 27.2%. The proposed CPFRA is a promising candidate for millimeter-wave (mm-W) satellite communication applications because of its advantages of high gain, low cost, low profile, and broad bandwidth.  
folded reflectarray antenna (FRA); metasurface; transmissive linear-to-circular polarization converter; millimeter-wave (mm-W); wideband; circularly polarized (CP) antennas +
Footnote †: journal:  
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# Analysis of Security Issues and Countermeasures for the Industrial Internet of Things
## 3 Security Issues in IIoT Systems
### Security Issue 5--Impact on Devices' Performance  
In these types of attacks, one or more devices are compromised by the attackers. Then, a collection of malicious devices are controlled by the attackers to enact malevolent performances on the sensitive data without the user's knowledge. For example, in an IoT-enabled healthcare system, if an attacker gains access to a portable mobile device (e.g., Fitbit, or smartphone), it can then enter and hack the hospital's internal database management system through identity spoofing. Attackers can collect a patient's health record or even steal the identity of the patient [95].  
It further helps attackers to perform replay attacks to the IIoT systems by transmitting copies of a stream of messages between the devices to make delays in a valid data transmission [96]. Combined with device controlling and analysis of the devices' data, it becomes a possible threat towards the privacy in the IIoT systems.  
An attacker can attack an IIoT device to degrade the memory space and battery capacity by memory exhaustion and battery corruption attacks [71]. In the former (i.e., memory space), the IIoT devices, in general, are restrained from extended processing capabilities due to less memory and processing power. Thus, attacking these resource-limited devices on a mass scale can be a potential threat to break down the entire system's operations that are connected to these devices. This attack can be made by state manipulating both the \"memory performance\" and \"memory allocation\", for instance, a heatstroke attack, in which an attacker repeatedly accesses a shared memory/resource and makes the space unavailable to other definite applications [97]. In the latter (i.e., battery capacity), a DoS/DDoS attack can drain a huge amount of power, and it would potentially affect the device to gain further service availability for computational processing and data transmission by keeping them in a busy state [98].
# Comprehensive Analysis of Maritime Cybersecurity Landscape Based on the NIST CSF v2.0
## 5 NIST CSF-Based Analysis of Maritime Cybersecurity  
The adoption of the NIST CSF has enabled the maritime industry to better address cybersecurity threats, enhance risk management strategies, and protect critical assets and operations [6]. It provides an extensive framework that assists companies in developing robust cybersecurity solutions tailored to their particular needs, which is why the IMO recommends it [7]. By aligning with the NIST CSF, the maritime industry can strengthen its cybersecurity posture and foster a more secure and resilient environment for maritime operations.  
In the following sections, we examine each function of the NIST CSF v2.0 and discuss specific studies for both its functions and the categories below. In order to improve cybersecurity procedures in the maritime industry, this thorough analysis seeks to offer nuanced insights into how these roles function both independently and together. We demonstrate the importance and maturity of each function in strengthening the industry's defenses against cyber threats and identifying any gaps.
## 3 Results and Discussion
### Landslide Susceptibility Mapping and Comparison of Models
#### 3.8.4 Road and Fault Exposure Across Susceptibility Classes  
As shown in Figure 22a, all three models exhibit a comparable degree of fault-line intersection in the Very High landslide susceptibility class, ranging from approximately  
Figure 21: Distribution of total landslide area (in km\({}^{2}\) and percentages) across susceptibility classes.  
Figure 20: Horizontal bar chart showing landslide count distributions and percentages across susceptibility classes for three models.  
30% to 40%. LR displays a progressive increase in overlap across susceptibility levels, culminating in 37.5% in the Very High class. RF shows a slightly more uniform distribution, yet still attributes 31.4% of fault overlap to the Very High zone. XGBoost registers the most significant fault concentrated exposure at 39.1% in this category, reinforcing its responsiveness to terrain features near fault structures.  
To assess the implications of susceptibility predictions for critical infrastructure, we performed a spatial overlay of road networks with the susceptibility zones generated by the LR, RF, and XGBoost models. As shown in Figure 22b, the overlap percentages reveal notable differences in exposure patterns. The XGBoost model mapped a dominant 49.6% of roads within the Very Low susceptibility zone, suggesting a more conservative risk assignment. Conversely, the RF model distributed road exposure more moderately, with 43.1% in the Very Low zone and a higher proportion (15.9%) intersecting High susceptibility areas. The LR model exhibited a relatively uniform distribution, placing approximately 17-24% of roads across all five classes. These variations underscore how model-specific zoning affects the spatial exposure of transportation infrastructure and highlight the need for careful model selection in applied hazard risk assessments.  
Overall, the LR model appears to exhibit a more conservative approach in forecasting lower-risk zones, whereas the RF model demonstrates heightened sensitivity toward lower- and medium-risk classifications. The predictive patterns exhibited by each model can provide guidance for decision making regarding the appropriate model selection, contingent upon the requisite level of conservatism or sensitivity for a specific application. However, this study shows that the XGBoost and RF ensemble models outperformed individual bivariate models in predicting co-seismic landslide susceptibility.
# Millimeter Wave Attenuation Due to Wind and Heavy Rain in a Tropical Region
###### Abstract  
Millimeter wave fixed wireless systems in future backhaul and access network applications can be affected by weather conditions. The losses caused by rain attenuation and antenna misalignment due to wind-induced vibrations have greater impacts on the link budget reduction at E-band frequencies and higher. The current International Telecommunications Union Radiocommunication Sector (ITU-R) recommendation has been widely used to estimate rain attenuation, and the recent Asia Pacific Telecommunity (APT) report provides the model to estimate the wind-induced attenuation. This article provides the first experimental study of the combined rain and wind effects in a tropical location using both models at a frequency in the E band (74.625 GHz) and a short distance of 150 m. In addition to using wind speeds for attenuation estimation, the setup also provides direct antenna inclination angle measurements using the accelerometer data. This solves the limitation of relying on the wind speed since the wind-induced loss is dependent on the inclination direction. The results show that the current ITU-R model can be used to estimate the attenuation of a short fixed wireless link under heavy rain, and the addition of wind attenuation via the APT model can estimate the worst-case link budget during high wind speeds.  
Keywords:fixed wireless link; millimeter wave; link budget; attenuation; tropical region +
Footnote †: journal: _Sensors_
# A Low-Power WLAN Communication Scheme for IoT WLAN Devices Using Wake-Up Receivers
## 4 Proposed System for Massive Uplink Scenario
### Discussion on the Wake-Up Frame Format for Multi-User Operation  
To apply the MU transmission procedure as described in previous section, there is a need to wake up multiple STAs. In addition to the proposed methods in [17], there are some recent proposals for the MU wake-up frame format in IEEE 802.11 ba, although it is still under standardization. In [23], the MU format of the wake-up frame is proposed. Because the wake-up frame consists of a 20-MHz IEEE 802.11 preamble and a narrow-band wake-up payload, the wake-up payload may be transmitted in a frequency-division multiple access (FDMA) OOK signal, as depicted in Figure 11. To apply this wake-up frame structure in the association procedure, STAs should negotiate the frequency band on which to receive the wake-up packet with the AP. After the negotiation, wake-up receivers in STAs only need to scan the predetermined band in order to receive the wake-up packet. Another proposal for the MU wake-up frame [24] is to use a group identifier (ID) in the receiver address field. The group ID should be negotiated with the AP when the STA is associated or when it switches to the wake-up mode. To use the group ID, the grouping method is important, because there may be unnecessary wake-up procedures, which causes power wastage.  
Figure 10: Scheduled uplink multiuser transmission using wake-up packet for multiple user. UL MU = uplink multi-user.  
Figure 9: Normal uplink multiuser transmission using wake-up packet for multiple user.
###### Abstract  
As sensitive human-environment systems, lake-intensive regions are critical governance areas for advancing global low-carbon development. Rapid economic growth has intensified the imbalance between economic carbon sources and ecological carbon sinks in these regions. However, methods for measuring territorial space carbon budgets tailored to \"production-living-ecological\" functions are underdeveloped, and the mechanisms driving carbon imbalance risks remain unclear. To address these issues, this study develops a spatial measurement model for \"carbon sources-carbon sinks\" in the Dongting Lake region. Using exploratory spatiotemporal data analysis, this study identifies grid-scale variation patterns in carbon budgets. Finally, using the logarithmic mean Divisia index (LMDI) decomposition model, this study examines the driving mechanisms of carbon budgets from a territorial space perspective. The results indicate the following: (1) The territorial space of the Dongting Lake region follows a pattern where \"ecological spaces surround production spaces, with living spaces interspersed among water network spaces\". Between 2005 and 2020, functional transitions primarily occurred between agricultural production spaces and forest or water ecological spaces. (2) The study area's territorial space carbon budgets increased annually, though the growth rate slowed. Construction land was the most significant carbon emission source in territorial space. Spatially, carbon budgets exhibit a radial pattern, with high values concentrated in plains near water bodies, gradually decreasing inland. Spatiotemporal differentiation followed a north-south development trend along the water system axis. High-High clusters were concentrated in municipal areas with dense water networks. In contrast, Low-Low clusters appeared in peripheral mountainous regions to the west, east, and south. (3) Land-use efficiency had the most potent inhibitory effect on carbon budgets, cumulatively reducing carbon emissions by \(1.37\times 10^{8}\) tC. Economic development had the strongest positive effect, adding \(1.31\times 10^{8}\) tC in carbon emissions. Therefore, the Dongting Lake region should promote intensive land use, adjust industrial structures, and develop a green ecological economy to achieve sustainable carbon source-sink management.  
Keywords:lake-intensive regions; territorial space; carbon budgets; spatiotemporal variation; driving mechanisms; Dongting Lake region +
Footnote †: journal: Applied sciences