esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis of Factors Influencing the Results  
The slanted edge of the imaging system represents a continuous input signal. When this signal is incident on the image detector element, it remains continuous. However, the sampling process discretizes this continuous signal, transforming it into a step-like distribution on the detector, as illustrated in Figure 11a. This distribution, highlighted by a red circle in the figure, defines the structure known as a \"sampling step\". The embodiment of the sampling step varies with different tilt angles, requiring different numbers of image lines, as demonstrated in Figure 11b,c.  
According to the mathematical relationship, the number of image elements, denoted as \(y\), required to represent a slanted edge with a width of \(x\) pixels is given by Equation (18):  
\[y\geq x\big{[}\cot\theta\big{]} \tag{18}\]  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Angle** & **Method** & **ISO-cos** & **OMNI-sine** & **Algorithm in This Paper** \\ \hline \(5^{\circ}\) & 0.0495 & 0.0808 & 0.0527 \\ \(10^{\circ}\) & 0.0301 & 0.0303 & 0.0276 \\ \(14^{\circ}\) & 0.0337 & 0.0405 & 0.0319 \\ \(26^{\circ}\) & 0.0905 & 0.0446 & 0.0478 \\ \hline \hline \end{tabular}
\end{table}
Table 2: RMSE of MTF calculation by different methods.  
Figure 10: MTF calculation curves at various slanted-edge angles for the three algorithms: (**a**) slanted-edge angle of \(5^{\circ}\); (**b**) slanted-edge angle of \(10^{\circ}\); (**c**) slanted-edge angle of \(14^{\circ}\); (**d**) slanted-edge angle of \(26^{\circ}\).  
Figure 12 depicts the minimum number of pixels along the height of the slanted edge necessary to represent the slanted-edge angle, varying from 1\({}^{\circ}\) to 45\({}^{\circ}\), when the width of the slanted edge is fixed at 1 pixel.
## 3 Results and Discussion
### Slope Soil Water Dissipation-Related Factors Analysis
shown that higher humidity makes it more difficult for soil water to evaporate into the atmosphere, as the water vapor content of the atmosphere is closer to saturation [29]. Additionally, higher wind speeds blow away air with higher soil water content from the soil surface, increasing soil water evaporation and dissipation rates [30,31]. The different results in this paper may be attributed to the combined effects of various meteorological factors, as well as differences in observation time and scale. Temperature has a more direct influence; hence, it has a stronger correlation. Solar radiation can heat the surface soil and influence soil water content through heat conduction. However, the correlation between solar radiation and soil water dissipation is lower due to delayed heat conduction in air and soil, as well as obstruction by vegetation [32]. Temperature shows a significant effect on water dissipation in the 0-40 cm soil layer (\(p<0.05\)), while humidity significantly affects the 0-20 cm soil layer (\(p<0.05\)) and wind speed has an extremely significant effect on the 20-40 cm soil layer (\(p<0.01\)). This is mainly because the transmission energy of meteorological factors decreases as soil depth increases, resulting in a reduced correlation between meteorological factors and soil water dissipation. In addition to meteorological factors and slope conditions, the dissipation of soil water is also significantly influenced by the water content of adjacent soil layers. The greater the difference in water content between soil layers, the more pronounced the effect on water dissipation [33]. While the slope conditions have a strong influence on water dissipation in the soil, meteorological factors have a relatively lesser impact.
# A High-Sensitivity Magnetic Field Sensor Based on PDMS Flexible Resonator
###### Abstract
The magnetic-field-induced strain of most magnetostrictive materials is very small, typically less than a few ppm/mT [32], and the bandwidth and sensitivity are limited by the degree of combination of the magnetostrictive material and the WGM resonator. As research on magnetic field sensing based on WGM resonators progresses, the Young's modulus is becoming one of the factors limiting the sensitivity of such sensing because WGM resonators exhibit excellent sensitivity to mechanical deformation. Therefore, compared to crystalline materials, we choose the PDMS flexible resonator with a relatively small Young's modulus as the magnetic field sensing platform. We have solved the problem of PDMS flexible resonators not having the characteristic of sensing magnetic fields by using a magnet sandwich. However, the mechanism of magnetic field detection based on the PDMS flexible resonator sandwich structure is still unclear. In this paper, we model the sandwich structure and investigate the sensitivity mechanism of magnetic field induction in the sandwich structure by analyzing three factors: the coupling position, different sizes and different mixing ratios of PDMS. The calculated results show that when all three factors influencing the structure are simultaneously controlled, a magnetic field sensitivity of 19.02 nm/mT is achieved. By optimizing the structural parameters, it is relatively easy to achieve magnetic field sensitivity at the nm/mT level. Therefore, this study provides theoretical support for magnetic field sensing based on PDMS flexible resonators. Relying on the existing experimental conditions and PDMS flexible resonator preparation technology, the sandwich structure is successfully fabricated, and the measured magnetic field sensitivity is 4.23 nm/mT.
# Optical OFDM for SiPM-Based Underwater Optical Wireless Communication Links
## 7 Discussions and Conclusions  
For the case of an SiPM-based UWOC system and in order to increase the link data rate, this work investigated the use of high spectral efficiency modulation schemes based on O-OFDM, namely the three schemes of DCO-, ACO-, and LACO-OFDM. We discussed the limitations in terms of the SiPM-based Rx saturation and the limited Tx DR, which determine the range of operation of the UWOC link for a given target BER. Indeed, the novelty of our study is that we take into account the required DC bias at the Tx for signal transmission, based on typical and practical LED characteristics. The presented results provide a reliable performance comparison of the considered schemes.
## 4 Experimental Results and Analysis
### Analysis of Different Tampering Test Results
#### 4.2.6 Large Area Attack  
This tamper type is used primarily to test the performance of the filtering operation. The location and recovery results are shown in Figure 13.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Indexes** & **[PERSON] et al. [8]** & **[PERSON] et al. [9]** & **[PERSON] et al. [7]** & **Proposed** \\ \hline PSNR (dB) & 19.48 & 36.36 & 39.53 & 39.35 \\ SSIM & 0.7968 & 0.9010 & 0.9925 & 0.9930 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Objective comparison of the recovery performances for the content-only attack on the Clock image.  
Figure 12: Tamper detection and recovery results of a content-only attack on the Clock image: (**a**) original image; (**b**) watermarked image; (**c**) tamper reference; (**d**) tampered image; (**e**) tamper detection result of [8]; (**f**) tamper detection result of [9]; (**g**) tamper detection result of [7]; (**h**) tamper detection result of the proposed method; (**i**) recovery result of [8]; (**j**) recovery result of [9]; (**k**) recovery result of [7]; (**l**) recovery result of the proposed method.  
Due to the implementation of chaotic mapping, even though the original image is largely tampered, most of the affected pixels can still be detected and recovered by the watermark information extracted from the corresponding blocks. Moreover, the neighborhood adjustment is used to further recover the tampered area from the neighboring pixel values. This approach generates a fully restored image but with more distortion. As shown in Figure 13, the proposed method with edge detection can identify all tampered areas. However, just as in the previous attacks, many misjudgments are present. Figure 13e shows the obvious confusions in the restored region, which is exactly what we want to improve. After the filtering operation, the final result of the proposed method possesses better quality as reflected by the PSNR and SSIM values displayed in parentheses in the corresponding figure captions.  
As the enlarged images in Figure 14 show, due to the median filtering, the woman's chin, hand and right leg are clearer and contain less noise. Meanwhile, the texture information on the scarf demonstrates that the threshold adjustment can offset the detail loss caused by filtering.
## 3 Results and Discussion  
### Structure and Morphology Analysis  
The XRD pattern of the C-Fe\({}_{3}\)O\({}_{4}\) nanoparticles is presented in Figure 3. Clearly, all diffraction peaks located at 18.3, 30.1, 35.4, 43.1, 53.4, 56.9, 62.5 and 73.9\({}^{\circ}\) can be indexed to the crystal planes of (111), (220), (311), (400), (422), (511), (440), and (533) of Fe\({}_{3}\)O\({}_{4}\) (JCPDS no. 19-0629). The average crystal size of the C-Fe\({}_{3}\)O\({}_{4}\) nanoparticles was calculated using the Scherrer equation as follows.  
\[\mathrm{D}=\frac{\mathrm{k}\lambda}{\beta\cos\theta} \tag{10}\]  
where D, K, \(\lambda\), \(\beta\) and \(\theta\) are the average crystal size, Scherrer constant (0.94), wavelength of the X-ray sources (0.15406 nm), peak width at half the maximum peak, and angle correlated with highest diffraction peak, respectively. The calculated average crystal size from Scherrer equation was 8.85 nm. The nanostructure and morphology were investigated by FESEM. Figure 4a shows that the sample is made up of nanoparticles with an interconnected porous structure. This porous network would provide multiple pathways for the propagation of the EM wave. The magnified image shown in Figure 4b reveals that the C-Fe\({}_{3}\)O\({}_{4}\) nanoparticles are compacted with high agglomeration despite the citric acid coating and displays spherical nanostructure. The high agglomeration could be attributed to strong inter-particles Van der Waals force and strong magnetic attraction among the particles. Figure 4c presents the magnified image of C-Fe\({}_{3}\)O\({}_{4}\)/PVDF (M40), which shows that C-Fe\({}_{3}\)O\({}_{4}\) nanoparticlesare tightly anchored on the PVDF matrix and retain a spherical structure after the electrical stirring. The energy dispersive X-ray spectrum (EDS) analysis of M40 was carried out (Figure 4d) which reveals the presence of Fe, O, C, and F. Elemental mapping was also conducted (Figure 4e) to investigate the spatial distribution of the elements present. The obtained image depicts that the M40 comprises of homogenous distribution of Fe, O, C and F. FTIR results presented in Figure 5 was used to further investigate the chemical bonds presents in the sample. The strong peak at 567.43 cm\({}^{-1}\) and a weak peak at 444.18 cm\({}^{-1}\) can be attributed to the stretching of Fe-O vibration, which confirms the sample as Fe\({}_{3}\)O\({}_{4}\)[17], and the absorption bands at 1628.27 cm\({}^{-1}\) and 1397.34 cm\({}^{-1}\) are vibrational characteristics of the C=O emanating from the C\({}_{6}\)H\({}_{8}\)O\({}_{7}\)-H\({}_{2}\)O coating [14]. The peak around 3413.24 cm\({}^{-1}\) are also vibrational characteristics of the hydroxyl functional group (H-O-H) [18]. These analyses confirm the successful doping of Fe\({}_{3}\)O\({}_{4}\) with carboxyl and hydroxyl group.  
Figure 4: FESEM images of **(a,b)** C-Fe\({}_{3}\)O\({}_{4}\) nanoparticles, (**c**) C-Fe\({}_{3}\)O\({}_{4}\)/PVDF (M40), **(d)** EDS spectrum of M40, and **(e)** elemental mapping of M40.  
Figure 3: XRD pattern of the C-Fe\({}_{3}\)O\({}_{4}\) nanoparticles.
## 4 Results and Discussion
### Measurement Results with SUV
When using the roll motion, the authors calculated the center of gravity's height as 56.42 cm, and when using the pitch motion, it was 71.40 cm. Thus, the difference in heights of the center of gravity was 14.98 cm, resp. 26.6%, and the measurements were performed under the same conditions, i.e., an empty vehicle without a driver. Concerning the empty SUV with a driver, the center of gravity's height was determined as 67 cm, which corresponds to the interval with the measurement results of Skoda Yety. However, the method mentioned in the publication [97], would not be used for measuring the change in the center of gravity's height due to different load distribution, since in that situation it led to the shift by 1 cm in some cases, and the above-mentioned method showed the measurement deviation of about 15 cm between two measurements [97]. The methodology presented in this article can thus be considered significantly more accurate and suitable than other compared methodologies. As can be seen from Figures 7 and 8, each change in the load position caused a different deformation of the tires and suspension. In scientific articles aimed at mathematically determining the position of the center of gravity, the position of the vehicle's center of gravity is often given with an accuracy of millimeters. In the article [98], the position of the tractor's center of gravity is given with an accuracy of hundredths of a millimeter. Specifically the mathematically calculated height of the center of gravity is given as 682.06 mm. However, based on the results of the measurements presented in this article, it can be concluded that such a precise indication of the position of the center of gravity is irrelevant, since, as was stated, the position of the center of gravity changes. Figure 8: Position of the center of gravity of SUV.
## 3 Methodology
### Structure of AWID3 Dataset  
The AWID3 dataset has been carefully curated to record and examine the traces of different assaults within the IEEE 802.1X extensible authentication protocol (EAP) environment. It is valuable and publicly available. It is significant for being the first dataset to offer a review of the IEEE 802.11 w standard, which is necessary for hardware to be approved for use with the WPA3 protocol. The AWID dataset, from which AWID3 was built, has 254 features, of which 253 are general features and one is used for labeling. The dataset is offered in CSV format for simple access and interoperability with many different data analysis tools and methodologies. A thorough understanding of network activity and attack patterns is made possible by the extracted features, which cover both the MAC (media access control) layer and the application layer. The dataset consists of 36,913,503 instances, 30,387,099 of normal traffic, and 6,526,404 malicious ones. Malicious traffic includes 13 types of attacks.  
- Deauthentication Attack.  
- Disassociation Attack.  
- Re-association Attack.  
- Rogue AP Attack.  
- Crack Attack.  
- Kr00k Attack.  
- SSH Brute Force Attack.  
- Botnet Attack.  
- Malware.  
- SSDP Amplification.  
- SQL Injection Attack.  
- Evil Twin.  
Website Spoofing.  
In our research, we used two types of these attacks which are Krack and Kr00k, since these two types are the most recent type of attacks discovered in IEEE 802.11 [37].
# Pore Solution Chemistry of Calcium Sulfoaluminate Cement and Its Effects on Steel Passivation
###### Abstract  
Calcium sulfoaluminate cement (CSA) is a type of low-CO2 binder which has been widely applied in the production of concrete. To investigate the protection capability offered by CSA to keep steel from corrosion, the pore solution chemistry of CSA on steel passivation was investigated in this study. The pore solution of CSA pastes, extracted by an ex situ leaching method, was studied and compared with ordinary Portland cement (OPC). The results show that the alkalinity of the CSA pore solution is not only much lower than that of OPC, but also that a new type of ion, Al(OH)4\({}^{-}\), and high concentration of SO4\({}^{2-}\) were detected in the liquid phase of CSA. Based on pore solution chemistry analysis, a simulated pore solution (SPS) system was designed to assess the comprehensive impact of alkalinity and ion composition, featured as properties of CSA, on steel passivation. The results of the corrosion potential evolution highlight the importance of alkalinity in passivation. SO4\({}^{2-}\) can cause degassivation when there is not enough hydroxyl, but Al(OH)4\({}^{-}\) is able to maintain the alkalinity of the system, enhancing the stability of the passive film.  
calcium sulfoaluminate cement; passivation; pore solution; alkalinity; sulfate; aluminate
## 6 Discussion  
### Summary of Observations  
From the accuracy comparison across different virtual sensor configurations, the following observations can be deduced:  
* **Adding 15 Virtual Sensors**: While some categories, such as _Lightning_, show significant improvements (+33.33%), others, such as _No Fire_, see a notable decrease in accuracy (\(-42.11\%\)). This indicates a mixed effect of adding virtual sensors at this stage, with some categories benefiting while others suffer.
* **Adding 30 Virtual Sensors**: The addition of 15 more virtual sensors (bringing the total to 30) yields a more consistent and noticeable improvement across many categories. For example, _Fire Increasing_ shows a strong improvement of +26.67%, while _Fire with Thundering_ maintains a steady increase of +66.67%. Although some categories like _Thundering_ experienced a small drop (\(-5.26\%\)), the overall trend towards improvement is more evident than the previous configuration.
* **Adding 45 Virtual Sensors**: Adding more virtual sensors (up to 45) does lead to some improvements, but they are smaller and less consistent. For instance, while _Fire with Thundering_ improved significantly by +66.67%, other categories, such as _Fire Decreasing_, showed a decrease of \(-12.50\%\).  
The results show that adding 30 virtual sensors provides the most consistent and meaningful improvement in model performance. This suggests that beyond 30 virtual sensors, the marginal benefit starts to diminish, and in some cases, the additional complexity might not yield substantial improvements. However, with a minor decrease in accuracy in some scenarios, we gain a huge advantage in expanding our model's coverage of a very large area of the forest field. While 45 virtual sensors offer some improvements in certain categories, the overall accuracy gains become less pronounced and less consistent compared to the 30 virtual sensors configuration. Therefore, 30 virtual sensors represent the optimal configuration for maximizing accuracy improvements across the scenarios tested. In Figure 2, we compare the accuracy across different virtual sensors (VSs) using a bar chart to highlight individual values across various fire-related scenarios.  
Figure 2: Comparison of accuracy across virtual sensors using a bar chart.
## 3 Polymer AWG-Based OLTs
With LDs (EMLs) that can be direct modulated faster than 25 Gb/s [21], a total bit rate larger than 1 Tb/s can be achieved for this type of OLT-Tx device. The OLT-Rx at the receiver side is shown in Figure 8a,b. 4 \(\times\) PD arrays, each containing 10 planar PDs are vertically coupled to the polymer DMX AWG by an integrated 45 \(\,\mathrm{\SIUnitSymbolMicro mirror}\). The 40-channel polymer DMX AWG is designed to operate at 100-GHz channel spacing over the C-band (1534.2 nm-1561.4 nm). A \(\lambda\)/2 plate can be inserted via a deep etched slot in the middle of the arrayed waveguide region to minimize the polarization dependence [2]. Figure 8: 40-channel OLT-Rx based on 4 \(\times\) 10 planar PD arrays vertically coupled to a polymer AWG via an integrated 45 \(\,\mathrm{\SIUnitSymbolMicro mirror}\). (**a**) The schematic layout and (**b**) photograph of the assembly. Figure 7: Multiplexed transmission spectra at the output of the OLT-Tx (measured in fiber). Figure 9 shows the responsivities of the OLT-Rx. For the measurements, the chosen PDs have an intrinsic responsivity of 1.1 A/W and an effective responsivity of \(\sim\)0.22 A/W is obtained on the OLT. The device insertion loss, including the fiber coupling loss, mirror coupling loss and the propagation loss of the polymer AWG, is calculated to be \(\sim\)7.5 dB. At somewhat compromised responsivity, the planar PDs have been reported to provide a bandwidth exceeding 30 GHz. With such PDs, each channel can reach a detection rate \(>\)25 Gb/s, and a total data rate over 1 Tb/s can be realized for such an OLT-Rx.
## 7 Conclusions  
This paper is focused on the capabilities of Deimos-2 PAN L1B stereo pairs (1 m GSD) to extract high quality DSMs over different land covers. A statistical analysis of the sensor orientation phase for Deimos-2 imagery is carried out as a previous step. The statistical analysis of the obtained results recommends the use of the RPC1 model with 12 GCPs to carry out the orientation phase of the Deimos-2 optical sensor.  
Concerning the extracted DSMs, the best quality results for both completeness and vertical accuracy were achieved from the WV2 stereo pair used as benchmark, mainly due to its lower GSD. However, the quality of the DSMs attained from Deimos-2 stereo pairs also yielded very good figures. The major differences between WV2 and Deimos-2 were observed in very uneven urban land cover areas, where the lower GSD of WV2 imagery produced DSMs with higher vertical accuracy. In that sense, the SGM method applied to extract DSMs could have minimized the differences attributable to the optical sensor, especially in urban environments, where SGM usually achieves its better performance.  
Finally, it should be emphasized that the results obtained on the quality of the DSMs produced from Deimos-2 could be classified as good or bad according to the level of detail required for their application. It is important to note that, in the frame of the research project about plastic covered greenhouse detection in which our team is working on, SD values ranging from 1.07 m to 1.78 m turn out to be too high for the objectives pursued.  
Conceptualization, M.A.A. and F.J.A.; methodology, M.A.A. and R.J.-L.; validation, M.A.A. and A.N.; formal analysis, R.J.-L. and A.N.; writing--original draft preparation, M.A.A. and F.J.A.; writing--review and editing, F.J.A.; funding acquisition, M.A.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Spanish Ministry for Science, Innovation and Universities (Spain) and the European Union (European Regional Development Fund, ERDF) funds, grant number RTI2018-095403-B-I00.  
We acknowledge the support of the Spanish Ministry for Science, Innovation and Universities (Spain) and the European Union (European Regional Development Fund, ERDF) funds (grant reference RTI2018-095403-B-I00). It is part of the general research lines promoted by the Agrifood Campus of International Excellence ceiA3 ([[http://www.ceia3.es/](http://www.ceia3.es/)]([http://www.ceia3.es/](http://www.ceia3.es/))). Deimos-2 stereo pairs were provided by the European Space Agency (ESA) through the ESA project ID: 51010.  
The authors declare no conflict of interest.