esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Application in Hot Wire Calibration
### HotWire Calibration
\begin{table}
\begin{tabular}{c c c} \hline \hline \(V_{\text{set}}\) (m/s) & \(\left|\Delta V\right|_{\text{max}}\) (m/s) & \(\left|\Delta V\right|_{\text{max}}\)/\(V_{\text{set}}\) (\%) \\ \hline \hline \(0.1\) & \(0.005120\) & \(5.12\) \\ \(0.2\) & \(0.009262\) & \(4.631\) \\ \(0.3\) & \(0.007840\) & \(2.613\) \\ \(0.4\) & \(0.02086\) & \(5.214\) \\ \(0.5\) & \(0.01130\) & \(2.260\) \\ \(0.6\) & \(0.01764\) & \(2.939\) \\ \(0.7\) & \(0.02236\) & \(3.194\) \\ \(0.8\) & \(0.01852\) & \(2.315\) \\ \(0.9\) & \(0.01763\) & \(1.959\) \\ \(1.0\) & \(0.01486\) & \(1.486\) \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Maximum deviation error of fitted velocity from real controlled velocity. Table 13 presents the values of constants \(A\), \(B\), and \(C\) of the fitting curves at different humidity values under three temperatures. Table 14 exhibits the deviation between the velocity estimated via the fitting curve by the hot-wire output voltage and the real velocity controlled by the motion control system at the same output voltage value under each parameter combination of set (nominal) velocity, set temperature, and set humidity. Table 15 shows the maximum of the absolute value of the velocity deviations under all the set temperatures and set humidity values at each set velocity (i.e., the maximum absolute value of the deviations in each line in Table 14), which represents the calibration error of the fitting curve at each set velocity and varies from 0.007343 m/s to 0.02322 m/s, leading to a maximum value of 0.02322 m/s that meets the calibration accuracy target 0.03 m/s. The maximum relative fitting error is 8.527%. Compared to 0.02236 m/s and 5.214%, the maximum fitting errors of modified King's law and the maximum fitting errors of [PERSON]'s formula (0.02322 m/s and 8.527%) look larger, indicating that the latter is not superior to the former, as claimed by Ref. [26] which stated that the use of [PERSON]'s formula \"compromises much of the inherent accuracy of the rig\".
## 5 Results and Discussion
Simulations assess the effects of varying conditions on wireless link performance, focusing on outage probability, throughput, and SSE. The analysis compares the proposed IOS-aided C-HNOMA system with conventional HNOMA [6] and IOS-aided HNOMA [16] to evaluate performance improvements. The simulation results show that the SW-SW pairing scheme outperforms other pairing schemes, and the optimal power fraction achieves maximum SSE. By fixing SW-SW pairing and optimal power allocation, the proposed IOS-aided C-HNOMA system is compared with conventional HNOMA and IOS-aided HNOMA systems. Figure 16 illustrates the average outage probability, Figure 17 presents the throughput performance, and Figure 18 shows the SSE of eight UEs under the proposed  
Figure 15: SSE (\(\rm{bps}/\rm{Hz}\)) comparison between optimal, sub-optimal, and minimum limit cases for varying \(L\) and \(\varepsilon=0.01\) of iSIC and \(d=0.08\) of HWDs. and conventional systems. All performance metrics--outage probability, throughput, and SSE--are evaluated under an iSIC condition of 1% and an HWD of \(d=0.08\). The results demonstrate that integrating IOSs into hybrid NOMA significantly improves system performance, while retransmission for the WUE or cell-edge UE in cooperative communication further enhances overall system efficiency. The integration of IOSs enhances system reliability, and cooperative communication improves the performance of the WUE in each pair, leading to better overall performance. According to Figure 16, achieving a target outage of \(10^{-3}\) requires \(\sim\)30 dB of SNR for conventional HNOMA. In contrast, IOS-aided HNOMA requires \(\sim\)\(-9\)dB of SNR, while the proposed IOS-aided C-HNOMA requires only \(\sim\)\(-13\) dB of SNR. This results in an SNR gain of \(\sim\)4 to \(\sim\)43 dB with the proposed solution. In Figure 17, to attain a throughput of 2 bps/Hz, conventional HNOMA demands \(\sim\)20 dB of SNR, whereas IOS-aided HNOMA needs \(\sim\)\(-8\) dB of SNR. The proposed IOS-aided C-HNOMA, on the other hand, requires only \(\sim\)\(-14\) dB of SNR, offering an SNR gain of \(\sim\)6 to \(\sim\)34 dB. Lastly, Figure 18 shows that, at an SNR of 5 dB, conventional HNOMA achieves \(\sim\)2.38 bps/Hz, while IOS-aided HNOMA reaches \(\sim\)15.98 bps/Hz of SSE. The proposed IOS-aided C-HNOMA achieves \(\sim\)16.71 bps/Hz of SSE. This results in a difference of \(\sim\)0.73 to \(\sim\)14.33 bps/Hz in SSE with the proposed solution. Thus, the proposed IOS-aided C-HNOMA outperforms both conventional HNOMA and IOS-aided HNOMA, demonstrating its significant advantages over existing NOMA variants. By effectively addressing the limitations of traditional HNOMA and IOS-aided HNOMA, the IOS-aided C-HNOMA system proves to be a strong candidate for future wireless networks requiring high SSE, throughput, and reliable connectivity.
# Gold Nanofilm-Coated Porous Silicon as Surface-Enhanced Raman Scattering Substrate
## 3 Results and Discussion
Moreover, the inter-nanoparticle distance reached an optimized state to overlap the electromagnetic field to generate hot spots at the junctions of nanoparticles, hence generated hot spots mediated SERS signal amplification of the adsorbed R6G molecules. However, as deposition time was continued to achieve 10 nm thickness Au film, the corresponding SERS signal intensity of R6G molecules was observed to be significantly low. This might be due to the tightly packed Au nanocrystallites, where the interparticle distance was lapsed to form a continuous thick layer of Au film, acted like bulk Au material. As a result, there was no hot spot generation to amplify the SERS signal [16; 29]. Similar results were also observed by another few experiments. For example, [PERSON] et al. conducted an experiment with nanoporous anodic aluminum oxide (AAO) substrates of a range of pore sizes (18, 35, 55, 80, 100, and 150 nm) coated with 30-, 40-, 50-, 60-, 70-, 80-, 90-, 100-, and 120-nm-thick Au films. Here, the thick films of 50 to 80 nm exhibited the best results, while both the initial (30 and 40 nm) and the end (90 to 120 nm) showed reduced intensity [30]. Another study conducted by [PERSON] et al. fabricated Au-PSi substrate by e-beam deposition of Au on the rough Si backside at room temperature, and thickness of the Au film was regulated by varying the deposition time from 10 to 30 s. The corresponding SERS spectra of PSi-Au film for deposition time (t) below t = 15 s for both \(<\)100\(>\) and \(<\)110\(>\) orientation, showed a sharp decrease from higher to lower intensity. However, SERS intensity reached its maximum at t = 20 s for \(<\)100\(>\) orientation and at t = 20 and 25 s for the \(<\)110\(>\) orientation and at t = 25 and 30 s SERS intensities were at the lowest for \(<\)100\(>\) and \(<\)110\(>\) orientation, respectively. Therefore, our study proved that the thin films of Au on Si or PSi substrates are the active  
Figure 6: SERS spectra of \(1\times 10^{-6}\) M solution of R6G adsorbed onto the surface of (**a**) Si and (**b**) PSi coated with 5, 7, and 10 nm Au thin films. (**c**) Comparison of the SERS peak intensities of the six different composites. substrates for SERS enhancement. Among the two different platforms, PSi contributed more in SERS enhancement in comparison to Si wafer only. Though both types of SERS substrates were coated with the same three different layer Au thin films, however random surface roughness, densely packed and agglomerated nanoparticles of bigger size in PSi-Au thin films favor the generation of more hot spots in comparison to Si-Au thin films, hence leading to the significant enhancement of the SERS signals. Therefore, it could be concluded that SERS signal of the adsorbed R6G molecules depends on two main factors; firstly, the surface roughness features and crystallographic orientation of the silicon template, which ultimately defines the morphology, size, and arrangement of crystallites of the coated Au films, and secondly, the thickness of the Au layer.
# Determining the Optimal Positions of Infill Balise Groups for ERTMS/ETCS Level 1 Applications
## 3 Results  
### Evaluating the Weighting Methods  
We have developed three weighting methods presented in Section 2.1.4. These three methods normally yield different results in terms of the positioning of the infill balise groups. We therefore evaluated them to narrow down their application scenarios. One thing to note is that the calculated weighted additional runtimes cannot be compared across the different weighting methods. To positively compare the methods, the resulting positions of the infill balise groups must be used as input for another weighting method to calculate the corresponding weighted additional runtime.  
During testing, it became obvious that using the \"Equal\" method yields neither realistic nor applicable results. Due to the nature of the weighting method, all infill balise groups are placed closest to the IP with their spacing only limited by the required minimum distance. With that, the algorithm achieves its optimum, as the trajectories receiving infill at those locations endure additional runtimes in the order of only a few seconds. The slowest trajectory with \"infill\" at the EOA cannot be optimized but always remains the same with its associated additional runtime. We therefore strongly advise against using the method with equal weighting of the individual additional runtimes.  
The method \"Distance\" yields promising results, close to that of the \"Time\" method. Upon further inspection, it returns slightly worse results in nearly all scenarios tested. Furthermore, the working of this method cannot be linked to a system behavior in the real world, as it would mean randomly distributing the probability of infill being available over the distance between EOA and the farthest infill balise group.  
In conclusion, only the weighting method \"Time\" can satisfy the requirements while also having a representation in the real world. It models a random behavior regarding the time the next section becomes available and the MA is updated via infill information at the next infill balise group passed, allowing the train to accelerate to its initial speed again.  
With this framework now set, testing and sensitivity analyses of different parameters influencing the positions of infill balise groups can be performed.
###### Abstract  
In the past few years, with the development of information technology and the focus on information security, many studies have gradually been aimed at data hiding technology. The embedding and extraction algorithms are mainly used by the technology to hide the data that requires secret transmission into a multimedia carrier so that the data transmission cannot be realized to achieve secure communication. Among them, _reversible data hiding_ (RDH) is a technology for the applications that demand the secret data extraction as well as the original carrier recovery without distortion, such as remote medical diagnosis or military secret transmission. In this work, we hypothesize that the RDH performance can be enhanced by a more accurate pixel value predictor. We propose a new RDH scheme of prediction-error expansion (PEE) based on a multilayer perceptron, which is an extensively used artificial neural network in plenty of applications. The scheme utilizes the correlation between image pixel values and their adjacent pixels to obtain a well-trained multilayer perceptron so that we are capable of achieving more accurate pixel prediction results. Our data mapping method based on the three-dimensional prediction-error histogram modification uses all eight octants in the three-dimensional space for secret data embedding. The experimental results of our RDH scheme show that the embedding capacity greatly increases and the image quality is still well maintained.  
Keywords:reversible data hiding; three-dimensional prediction-error histogram modification; multi-layer perceptron +
Footnote †: journal: Applied Sciences
## 6 Conclusions  
In this work, we propose a multi-beam satellite cooperative transmission scheme based on cross-layer and cross-dimension resources optimization and irregular gradient adaptive packet segmentation. The proposed algorithm is suitable for multi-beam satellite communication systems. Firstly, the optimal resources are selected by the cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm. In order to get high spectrum efficiency, based on the optimal resources, we put forward an adaptive packet segmentation scheme based on the irregular gradient algorithm to map different packets to radio resources, which can realize efficient transmission in multi-beam satellite communication systems. In the simulation analysis, the proposed algorithm in this paper improves the normalized system throughput and user satisfaction index by 18.7% and 6.2%, respectively. Furthermore, our work can be extended to several interesting further research directions, for example, beam selection and resource allocation of variable subcarrier in multi-beam satellite communication systems can be studied for future work.  
Conceptualization, X.Y., Z.D., W.L. and K.W.; methodology, X.Y., Z.D., W.L. and K.W.; software, X.Y.; validation, X.Y., Z.D., W.L. and K.W.; formal analysis, X.Y., Y.L., X.M.; investigation, X.Y.; resources, X.Y., Z.D., W.L. and K.W.; data curation, X.Y.; writing--original draft preparation, X.Y.; writing--review and editing, X.Y., H.L., G.; visualization, X.Y.; supervision, Z.D., W.L. and K.W.; project administration, X.Y., Z.D., W.L. and K.W.; funding acquisition, Z.D., W.L. and K.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by China National key Research and Development Plan (2020 YFB1808005), and the National Natural Science Foundation of China (61801039), and the Civil Aerospace Technology Advance Research Project and the Fundamental Research Funds for the Central Universities (2021 RC06).  
The authors declare no conflict of interest.
###### Abstract  
With the rapid development of high integrations in large complex systems, such as aircraft, satellite, and railway systems, due to the increasingly complex coupling relationship between components within the system, local disturbances or faults may cause global effects on the system by fault propagation. Therefore, there are new challenges in safety analysis and risk assessment for complex systems. Aiming at analyzing and evaluating the inherent risks of the complex system with coupling correlation characteristics objectively, this paper proposes a novel risk assessment and analysis method for correlation in complex system based on multi-dimensional theory. Firstly, the formal description and coupling degree analysis method of the hierarchical structure of complex systems is established. Moreover, considering the three safety risk factors of fault propagation probability, potential severity, and fault propagation time, a multi-dimensional safety risk theory is proposed, in order to evaluate the risk of each element within the system effecting on the overall system. Furthermore, critical safety elements are identified based on Pareto rules, As Low As Reasonably Practicable (ALARP) principles, and safety risk entropy to support the preventive measures. Finally, an application of an avionics system is provided to demonstrate the effectiveness of the proposed method.  
safety; coupling correlation; risk assessment; multi-dimensional theory +
Footnote †: journal: Applied Sciences
## 6 Verification and Results
### Episode 2: Resilience and Availability (req: v, vii)
#### 6.2.2 Protection of Invalid VM Migration  
The main objective of the architecture is to enable hop-by-hop encryption of VLs (req: i). This includes protecting the data traffic between two SFs with a pair of EFs. Hence, one of the most important features of the architecture is to ensure that non-encrypted data between an SF and an EF reside on the same Compute Node. We demonstrated the feasibility of the hop-by-hop encryption during the provisioning in episode 1 by running end-to-end traffic tests. Here, we also verified that the traffic was encrypted by monitoring the data traffic in the SFFs.  
However, with respect to resilience, the aforementioned episode did not consider the consequences of VM migration. A failover of the VMs implies that SFs and their connected EFs must be migrated all together. A misconfiguration or failure in the VM migrations can result in an irregular topology of SFs and EFs. Hence, we aim to verify that the layered network topology introduced in Section 4.1.1 is protecting the non-encrypted flows from entering the network. We configured an invalid network topology by migrating one of the EFs to another Compute Node as we showed in Figure 5 (2). In this case, our architecture and flow policy disallowed the distribution of the flow rules. This result was expected. However, we successfully managed to manually override and manipulate the flow rules in order to allow such traffic flows. In order to accomplish this, we had to (1) manipulate the NSH packet coming from the SF and (2) define a flow rule that sets the NSH next hop to be a remote SFF destination for an NSH packet that is tagged for going into an EF for encryption. This is a clear flow-rule policy violation. This policy violation is easy to detect because the SFFs are pinned to the Compute Node. Hence, an NSH packet that is heading to an encryption function should never leave the outer SFF.  
The demonstration confirms that the tiered SFF infrastructure and the pinned SFFs make it easy to control the inner encryption flows. It also shows that there is a need for providing policy rules for the P4 switches. We enforced this rule only by implementing it in the overlay RESTconf API.
# A Real-Time Hybrid Approach to Combat In-Browser Cryptojacking Malware
## 6 Conclusions and Future Work  
Hackers have been using in-browser cryptojacking malware for mining crypto on the victim's computer (of course, without consent and knowledge). Research has shown to be limited to its detection by using static and dynamic malware analysis techniques only; however, none of the studies report detection and prevention in the way we propose. In this paper, we have presented a hybrid approach to detect and prevent installing cryptojacking malware. Further, our approach advances the state of the art in terms of accuracy as well: we report an overall accuracy of 99.6%. Unlike the existing approaches, which focus mainly on WASM-based detection, our approach is equally useful in both WASM and non-WASM cryptojacking attacks. The proposed methodology aims to improve the detection and prevention of in-browser cryptojacking attacks by including both WASM and non-WASM code instructions. The results of the experiments show that this approach is more accurate than the previous state-of-the-art approach, with an accuracy of 99.6% and a false negative rate of only 10%. Additionally, the experiments were performed on a larger dataset, making the results more reliable. The proposed approach has also shown a low-performance overhead of 10.7%. Overall, the proposed approach is a suitable defense against in-browser cryptojacking attacks.  
The proposed methodology has improved the detection accuracy of the state-of-the-art work. Using multiple behavior parameters in a dynamic analysis, such as the network behavior and CPU time, could potentially improve further the detection accuracy. This can be a future direction for this type of research. As the malicious script has to communicate with the mining service provider, different network behaviors could be studied and included in the analysis to yield better results.  
M.H.K.A.: Conceptualization, Data Curation, Software, Writing--Original Draft, Investigation, Validation, and Visualization; S.U.: Methodology, Formal Analysis, Resources, Writing--Original Draft, Validation, and Investigation; T.A.: Writing--Original Draft, Writing--Review and Editing, Funding Acquisition, Validation, and Visualization; A.B.: Methodology, Supervision, Writing--Original Draft, Project Administration, and Visualization. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Available upon request.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# The Sensitivity Analysis of Parameters in the 1D-2D Coupled Model for Urban Flooding
## 4 Results and Analysis
### Global Sensitivity Analysis
If \(S_{1}\approx S_{T}\), it indicates that the influence of the parameter comes mainly from the direct effect, and the interaction sensitivity is small, while if \(<\)\(S_{T}\), it indicates that the parameter has significant interactions with other parameters, and the overall response of the system relies more on the synergistic influence among the parameters. Figure 6 illustrates the comparison between \(S_{1}\) and \(S_{T}\). A comparison of the results for \(S_{1}\) and \(S_{T}\) reveals significant differences in the direct sensitivity and interaction of the key parameters under different rainfall patterns. To illustrate, the minimum infiltration rate (Minrate) is observed to have \(S_{1}>S_{T}\) in cxzd50a and Chicago50a, indicating that the effect of this parameter is predominantly manifested through the direct effect, with the interaction effect being relatively weak. In contrast, the interaction sensitivity of Minrate was more pronounced in szzbl50a. In the case of szzbl50a, the sum of Manning's coefficient of permeable surface area (N-Perv) exhibits a notable discrepancy of 0.76, which is considerably higher than the value of 0.64. This suggests that its direct impact is considerably more pronounced than its interaction with other variables. This may be attributed to the distribution of rainfall peaks, and further  
Figure 5: Sobol sensitivity analysis: (**a**) \(S_{1}\) sensitivity; (**b**) \(S_{T}\) sensitivity. Figure 6: Comparison of Sobol’s \(S_{1}\) and \(S_{T}\) result. investigation is necessary to gain a more comprehensive understanding. Similarly, pipe roughness (Roughness) exhibited analogous interaction characteristics. In Chicago50a and cxzd50a, the direct effect of Roughness is significant, as indicated by the greater value of \(S_{1}\) compared to \(S_{T}\). However, in szzbl50a, the effect is not as pronounced. However, the magnitude relationship between \(S_{1}\) and \(S_{T}\) for surface roughness (friction) was consistently independent of the specific rain type, indicating that this parameter played a pivotal role in the interaction effect. In contrast, the extremely low and similar values of the sums of Courant number (CFL) and impervious area puddle storage (S-Imperv) indicate that these parameters have both low global and direct sensitivities to the system, little interaction sensitivity, and very limited effects. In general, the parameters that contribute most significantly to the total ponding volume are the minimum infiltration rate (Minrate) and surface roughness (Friction). However, other parameters, such as Manning's coefficient of permeable surface area (N-Perv) and pipeline roughness (Roughness), also have an effect under specific rainfall patterns.
## 4 Results and Discussions  
In this section, we simulate, implement, and present theoretical results obtained by computer software in terms of multiple evaluation parameters of wireless communication systems based on the proposed theoretical channel model in order to examine the capacity, behavior, and performance of the UM-VLC system. Furthermore, we make a fair comparison with the UM-VLC channel model and its scenario developed in [12]. Among the parameters that are validated are the CIR, the received power, the RMS delay spread, the SNR, and the BER. Both the parameters of the simulation model that were used in this manuscript as well as the description of the UM scenario are presented in Table 1.