esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Consensus on Challenges  
#### 4.1.1 Interface Manipulation  
Interface manipulation is a challenge that was highly reported in the review of these papers and showed consensus among 13 papers. Not all devices supporting AR are manipulated virtually and require gesture control; only head-mounted displays (i.e., head-sets) require virtual manipulation. Research has reported that this manipulation is not easy [30; 31; 32]. While implementing AR in a lab-based environment for multiscreen construction discussion, users reported that AR models (i.e., annotations and similar features) were hard to control [30]. In addition, when implementing AR in uncontrolled environments (i.e., live construction sites), the virtual interface manipulation of a head-mounted device was reported to be complicated and not easy, especially when physically moving [11].  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Journals** & **After Filtering** \\ \hline Automation in Construction & 22 \\ Journal of Applied Science & 5 \\ Journal of Computing in Civil Engineering & 5 \\ Journal of Information Technology in Construction (ITcon) & 4 \\ Visualization in Engineering & 2 \\ Advances in Civil Engineering & 2 \\ Advanced Engineering Informatics & 2 \\ International Journal of Human–Computer Interaction & 2 \\ Journal of Construction Engineering and Management & 2 \\ Journal of Management in Engineering & 1 \\ Journal of Computing and Information Science in Engineering & 1 \\ Organization, Technology and Management in Construction & 1 \\ Journal of Infrastructures System & 1 \\ \hline Conferences & \\ \hline Institute of Electrical and Electronics Engineers (IEEE) & 7 \\ Construction Research Congress (CRC) & 2 \\ \hline TOTAL & 59 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Journals selected before and after the filter.  
Although some papers mentioned that previous training provided to the users might ease the manipulation of the virtual interface and would provide a solution to overcome this challenge [33; 34; 35], studies still identified this attribute as a challenge, since most researchers were implementing AR with new practitioners who had no previous experience using virtual manipulation or had no extensive training. Therefore, this challenge is directly related to the type of device and software in use.
## 5 Discussion
### About the Set of Thresholds  
Last, but not least, some considerations must be indicated about the set of thresholds. Indeed, this is certainly the decisive issue if an SHM system is going to be installed, in other words, if it will be really capable of the early detection of damages.  
In the opinion of the authors, as well as other cited references, natural frequencies, once corrected by ambient variables and statistically analysed, can be adopted for setting thresholds. However, it must be pointed out once more that in steel and composite structures, values can be more precisely calculated than in concrete structures. This is because of the fact that damping is higher in these last cases, so accelerograms have a shorter extension and, in consequence, frequencies have a lower resolution.  
On the other hand, the set of thresholds based on damping values is a promising issue because it is a parameter that can reflect damage in structures in a more sensitive way, particularly in bridges. However, nowadays, two main aspects must be solved. First is the great dispersion in measurements, even under the same environmental conditions; therefore, further studies must be carried out, both in scale tests and in real structures. Second is the great dependence of these values on the calculation method. Therefore, it is important to clarify how these methods affect the results and if some improvements are possible.
# Experimental Study on Permeability Evolution of Sandstone during Triaxial Compression Damage
## 3 Analysis of Test Results
### Strength Characteristics  
Researchers have explored the strength characteristics of rocks from various perspectives. [PERSON] et al. (2016) examined the evolutionary attributes of sandstone's peak strength concerning confining pressure or effective confining pressure across both dry and saturated conditions. [PERSON] et al. (2017) investigated the impact of intermediate principal stresses on rock strength by utilizing the M-C strength criterion. The research explores the strength parameters of sandstone under dry and saturated conditions, such as cohesion and internal friction, as determined by the following Equations (5) and (6), the result as shown in Table 3.  
\[c=\frac{n}{2\sqrt{m}} \tag{5}\]  
\[\varphi=tan^{-1}(\frac{m-1}{2\sqrt{m}}) \tag{6}\]  
where \(c\) and \(\varphi\) represent the cohesion and the angle of internal friction, respectively. \(m\) and \(n\) denote fitting parameters.  
As depicted in Figure 9, an evident linear growth pattern in the peak strength of sandstone is observed with escalating confining pressures across distinct conditions. It is discernible that the strength characteristics of sandstone are significantly influenced by variations in the confining pressure. When comparing saturated sandstone to its dry counterpart, the cohesion of the former experiences a notable increase of 12.2%, while the angle of internal friction undergoes a reduction of 9.6%. Furthermore, under saturated conditions, the osmotic pressure effect on sandstone strength is apparent due to the weakening influence of water. Specifically, in contrast to a seepage pressure of 0 MPa, the cohesion of  
Figure 8: Failure modes of specimens under different seepage pressures (confining pressure of 15 MPa).  
\begin{table}
\begin{tabular}{c c c c} \hline
**Seepage** & **Condition** & **Cohesion/MPa** &
\begin{tabular}{c} **The Angle of** \\ **Internal Friction/\({}^{\circ}\)** \\ \end{tabular} \\
**Pressure/MPa** & **Condition** & **Cohesion/MPa** &
\begin{tabular}{c} **The Angle of** \\ **Internal Friction/\({}^{\circ}\)** \\ \end{tabular} \\ \hline / & Dry & 7.4 & 59.5 \\
0 & Saturated & 8.3 & 53.8 \\
2 & Saturated & 7.9 & 54.4 \\ \hline \end{tabular}
\end{table}
Table 3: Mechanical parameters of sandstone under different working conditions.  
Figure 7: Failure modes of specimens under different confining pressures (seepage pressure of 2 MPa).  
saturated sandstone under a seepage pressure of 2 MPa displays a reduction of 4.8%, while the angle of internal friction registers a marginal increase of 1.1%.
# Line Matching Based on Viewpoint-Invariance for Stereo Wide-Baseline Aerial Images
## 1 Introduction
However, it takes a good deal of time to build a pyramid in this way. The line matching for oblique images is difficult because the results obtained from a wide-baseline have a large viewing angle difference between the two images to be matched. This difference causes the perspective distortion generated in the same area to be inconsistent, resulting in similarity matching of the corresponding lines' neighborhoods being very low, or even unable to be matched; as such, the line matching effect decreases. [PERSON] et al. used a camera's exterior orientation elements and the 3D point cloud to find coplanar 3D points around the line segment to construct a homography matrix. This approach eliminates local perspective distortion, but it requires the precise camera orientation elements and known 3D points in advance [23]. [PERSON] et al. employed a disparity map in rectified image space for stereo aerial images [24]. Considering that a POS device is usually situated on an oblique photogrammetric aerial platform, it can provide the camera with initial exterior orientation elements. Therefore, this article contemplates constructing a perspective transformation matrix by using the camera's interior and exterior orientation elements in the case of unknown 3D coordinates. Firstly, the original two images are projected onto a new object plane (the geoid) by perspective projection matrices to eliminate perspective geometric distortions (including scale and rotation), and rectified into approximate conformal images. Then, line matching is performed on the conformal images. Finally,the matched line segments are back-projected to the original images, thereby improving the line matching effect of the oblique images. This article investigates the feasibility of the proposed method by comparing it with conventional methods. The proposed method adds two steps (rectification and back-projection) to the conventional method, while other processes are exactly the same.
# FedDB: A Federated Learning Approach Using DBSCAN for DDoS Attack Detection
## 3 Methodology
### Model Clustering  
Due to the data heterogeneity among clients, the output of personalized models varies between clients. If clients engage in deep mutual learning among models with significantly different outputs, the FedMe method utilizes K-means for clustering. However, this approach is not effective in grouping data to mitigate the non-IID problem. Therefore, our method replaces K-means with DBSCAN for improved performance. The DBSCAN clustering method has the advantage of not requiring a predefined number of clusters, directly grouping clients with similar characteristics.  
In FedDB, the models are clustered using DBSCAN based on their outputs. Through DBSCAN, models with similar outputs are grouped together, and each client retrieves a model from the same cluster from the server, which we refer to as the exchanged model. In the subsequent mutual learning process, the personalized model and the exchanged model undergo mutual learning. During mutual learning, Kullback-Leibler (KL) divergence is used to assess the similarity between different models, reducing model bias and enhancing accuracy. This approach prevents overfitting to noise, ultimately alleviating the non-IID problem and narrowing the accuracy gap among clients.  
DBSCAN is a density-based clustering algorithm with several advantages. Firstly, its shape diversity allows it to identify clusters of arbitrary shapes, not just convex shapes, distinguishing it from clustering methods like K-means that can only identify convex shapes. Secondly, DBSCAN does not require the pre-specification of the number of clusters; it only needs the setting of neighborhood EPS and the minimum number of cluster points MinPts to automatically determine the number of clusters, eliminating the need to know the number of clusters in advance.  
Moreover, DBSCAN exhibits high robustness in handling noise. It can differentiate core points, edge points, and noise points within clusters, helping to identify and ignore noise in the data. This feature gives DBSCAN excellent capability in dealing with clusters of varying sizes, enabling it to identify and handle clusters with different densities without requiring all clusters to have the same density or size.  
Aside from the neighborhood EPS and the minimum number of cluster points MinPts, DBSCAN does not require other complex parameter settings, making it relatively simple to use. Additionally, its computational efficiency is quite impressive. With appropriate data structures, its time complexity can reach \(O(n\log n)\), which is feasible in many situations.  
Lastly, DBSCAN also possesses semi-supervised learning capabilities. By combining it with other methods, it can be applied in semi-supervised learning scenarios. These characteristics make DBSCAN a powerful and versatile clustering tool suitable for various data mining and machine learning applications.
## 5 Simulation Results
### Discussion  
Table 3 summarizes all the results illustrated in the previous subsections. Specifically, based on the monitoring carried out through Grafana, in the table we can observe that the longest link achieves an SNR of 14 dB and can use MCS 9 guaranteeing a PER of approximately 0.2%. On the other hand, based on the simulations, the link is characterized by the same PER and MCS when it can achieve 15 dB SNR. Note that radio-to-radio variations of 1-2 dB on the SNRs monitored through Grafana are expected due to manufacturing tolerances and, therefore, the longest link modelled through MATLAB can be considered validated. Moreover, in the table we can observe that the short link, based on the monitored information, achieves an SNR of 18.5 dB and can use MCS 11 guaranteeing a PER of approximately 0.6%. On the other hand, based on the simulations, this link in the case of 18.5 dB SNR can use MCS 9 in order to guarantee the same value of PER. Note that, again considering a possible radio-to-radio variation of 1-2 dB on the monitored values, the short link could reach MCS 10 guaranteeing the same value of PER computed through Grafana. Therefore, even taking into account monitoring errors due to manufacturing tolerances, there is still a reduction in terms of maximum available throughput of 20% in the short link, which can provide 3080 Mbps in the simulator and 3850 Mbps in Grafana (see Table 1).  
In summary, our simulation results, therefore, provide a variable picture in terms of corroborating the performance for the short link. One explanation of this could be that the actual nodes are performing better under certain circumstances and this needs to be programmed into our simulator. Other explanations include minor differences in the physical deployment of the equipment (e.g., alignment) or environmental factors that affect link performance. These results, therefore, generally validate our simulations but highlight the issues in predicting link performance in such a dynamic environment and  
Figure 12: Performance in terms of MCS of Link 3.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**MATLAB**} & \multicolumn{3}{c}{**Grafana**} \\ \cline{2-7}  & **SNR (dB)** & **PER (\%)** & **MCS** & **SNR (dB)** & **PER (\%)** & **MCS** \\ \hline \multirow{3}{*}{Long Link 2–3} & 20 & 1.3 & 11 & & & \\ \cline{2-7}  & 15 & 0.2 & 9 & 14 & 0.18 & 9 \\ \cline{2-7}  & 14 & 1 & 8 & & & \\ \hline \multirow{3}{*}{Short Link 3–4} & 21 & 2.5 & 11 & & & \\ \cline{2-7}  & 18.5 & 0.57 & 9 & 18.5 & 0.56 & 11 \\ \cline{2-7}  & 16 & 0.8 & 8 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results Comparison.  
with a limited set of links to evaluate. Our immediate next steps are, therefore, to gather more data on the configuration and performance of the nodes as the deployment continues and monitor them further to refine our models over time.
## 3 Results  
Among 152 patients, 32 were excluded due to the following reasons: presence of concomitant headache diagnosis (n = 6), history of head or neck trauma (n = 4), headache frequency lesser than three days/month (n = 6), and failure to attend the scheduled assessment (n = 16). Therefore, 120 participants (30 in each group) were included and completed the assessment. No differences were verified between groups regarding age, migraine onset, and migraine intensity (\(p\) > 0.05, Table 1). The use of prophylactic medication was similar between migraine groups (x\({}^{2}\) = 4.46, \(p\) = 0.107, Table 1). As expected, the headache frequency of the chronic migraine group was higher than the other migraine groups (\(p\) < 0.05, Table 1).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Control (n = 30)** & **Migraine without** & **Migraine with** & **Chronic Migraine** & **\(p\)-Value** \\  & **Aura (n = 30)** & **Aura (n = 30)** & **Aronic Migraine** & **\(p\)-Value** \\ \hline Age, years: mean (SD) & 31.30 (9.27) & 32.46 (8.66) & 32.16 (8.33) & 34.56 (10.00) & 0.556 \\ Migraine onset, years: & - & 16.50 (12.25) & 15.50 (11.25) & 15.00 (16.25) & 0.670 \\ median (Q3–Q1) & - & 7.00 (6.00) a  & 8.00 (5.00) a  & 20.00 (10.00) & \textless{}0.001 \\ Migraine intensity, NPRS: & - & 8.00 (1.00) & 8.00 (2.00) & 8.00 (3.00) & 0.168 \\ median (Q3–Q1) & - & 9 (30) & 12 (40) & 17 (56.7) & 0.107 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sample demographics and headache characteristics.
# A Digital Currency Architecture for Privacy and Owner-Custodianship
## 4 Analysis
### CBDC as a Retail Payment System  
We suggest that a primary benefit of CBDC is its ability to be held in non-custodial wallets by retail users. The argument that CBDC should be held only in custodial accounts actually follows from two assumptions: first, that it is not possible to remunerate tokenized assets directly; and second, that the purpose of CBDC is primarily to solve a problem of efficiency, for example of transaction costs or monetary policy transmission, and nothing more. However, there are plausible mechanisms that can remunerate tokenized assets directly, and the inexorable decline in cash as a means of payment presents a problem that is manifestly deeper than monetary policy transmission. Thanks to cash, people have always had the ability to conduct financial transactions using assets that they could control completely, for which their spending habits cannot be profiled, and which are not generally subject to discrimination or interception by third parties. However, the decline in cash use suggests that cash infrastructure might soon become economically untenable, in which case these foundational rights face elimination by default. Therefore, CBDC can be seen, perhaps first and foremost, as an opportunity to allow retail users to continue to enjoy the benefits of accountless money in the digital age.  
We ask whether CBDC is best seen as a modern form of bank deposits or as a digital form of cash. If CBDC were to be account-based and suitable for rehypothecation, then it might plausibly substitute for bank deposits in the general case, although if, as we propose, CBDC were to be token-based and not suitable for rehypothecation, then it would be much more cash-like. In the latter case, users would still have reasons, including interest and inflation risk, to continue to prefer bank deposits as a store of value and to use CBDC principally as a means of payment, even if both forms of money were usable for both purposes.  
Importantly, the architectural features of our proposal make it private _by design and by default_. Our proposal shows how a measure of true anonymity can be maintained even with an institutionally operated platform, thus disrupting the notion that electronic, institutionally supported retail payment methods must necessarily capture all available data about transacting parties.
# Adding Flavor to Beverages with Non-Conventional Yeasts
## 3 Results
### Aroma Profiles of Fermentations
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Strain Identifier** & **CBS261** & **CBS262** & **CBS188** & **CBS249** & **CBS248** & **CBS1082** & **CBS133** \\ \hline Position & F10 & F11 & E7 & F9 & F8 & G3 & F6 \\ Species & _W. anomalies_ & _W. anomalies_ & _P. Khayrevi_ & _W. anomalies_ & _W. anomalies_ & _Z. biograms_ & _T. delphractiki_ \\ Buyl acetate & 23.64 & 16.84 & 9.18 & 8.76 & 11.73 & 3.84 & 3.56 \\ Ethyl (4E)-4-deconoate & 0.00 & 0.00 & 0.17 & 0.00 & 0.04 & 0.56 & 0.07 \\ Ethyl 2-methylbutyrate & 50.89 & 368.00 & 36.00 & 62.34 & 39.06 & 2.94 & 10.63 \\ Ethyl acetate & 31.81 & 29.17 & 15.88 & 13.09 & 10.02 & 8.72 & 5.70 \\ Ethyl butanoate & 16.59 & 26.92 & 8.00 & 9.26 & 10.75 & 2.58 & 2.71 \\ Ethyl decanoate & 0.14 & 0.00 & 2.07 & 0.46 & 0.45 & 2.67 & 0.72 \\ Ethyl dodecanoate & 0.91 & 0.00 & 2.60 & 0.88 & 1.44 & 2.69 & 0.98 \\ Ethyl heptanoate & 1.17 & 2.19 & 6.96 & 3.14 & 1.77 & 1.58 & 2.82 \\ Ethyl hexadecanoate & 12.19 & 13.62 & 16.05 & 9.10 & 8.22 & 11.00 & 2.36 \\ Ethyl hexanoate & 7.23 & 12.89 & 5.07 & 6.90 & 7.47 & 4.33 & 2.72 \\ Ethyl isovalerate & 11.84 & 120.99 & 33.97 & 14.43 & 15.00 & 0.00 & 10.79 \\ Ethyl octanoate & 0.56 & 0.26 & 1.59 & 0.59 & 0.32 & 0.64 & 0.55 \\ Isoamyl acetate & 9.36 & 5.84 & 3.21 & 2.92 & 3.10 & 1.27 & 0.99 \\ Isobutyl acetate & 152.96 & 59.59 & 24.70 & 40.69 & 26.57 & 6.75 & 9.93 \\ Isobutyl butanoate & 209.13 & 167.38 & 29.44 & 88.87 & 52.26 & 10.77 & 13.62 \\
2-Phenylethyl acetate & 5.88 & 4.07 & 2.70 & 2.68 & 2.90 & 0.44 & 0.91 \\ methyl thioacetate & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.21 & 0.00 \\
2-Methyl propanoate & 0.89 & 0,00 & 1,16 & 1,13 & 0.46 & 0.00 & 0.44 \\ \hline \hline \end{tabular} The values reported represent the relative abundances of the specific subset of metabolites compared to the layer yeast strain (G10).  
\end{table} 
Table 4: Strains with higher aroma ester production than the _Wehnerstphan_ layer yeast strain.
## 6 Discussion  
The construction of the deep surrounding rock temperature field cloud monitoring system is based on the high-precision temperature monitoring systems installed at the 930 m and 945 m levels in the Xishan mining area of the Sanshandao Gold Mine. By using underground optical cables, fiber optic transceivers, routers, and 5G modules, the system achieves long-term unmanned monitoring of the temperature field, effectively reducing labor costs. The real-time feedback of temperature data to the cloud enhances the convenience and practicality of monitoring. Furthermore, the application of this monitoring system in the mine is not limited to monitoring the deep surrounding rock temperature field. It can adapt to various complex underground environments and be used for real-time monitoring of underground water inflow temperature, surrounding rock surface temperature, and underground air temperature. This system provides a significant reference value for studying heat release from mining electromechanical equipment, ore transportation heat dissipation, underground hot water heat release, and human heat release.  
During the monitoring process, it was found that the actual measured temperatures exceeded the simulated temperatures during periods of intensive mining production tasks. This discrepancy is due to the increased use of underground mining electromechanical equipment and ore transportation equipment, which are not fully accounted for in the numerical simulations. The simulations are based on numerous assumptions and thus differ significantly from actual field conditions. By calibrating the model using temperature monitoring data from depths of the \(-930\) m and \(-945\) m measurement points, it was determined that the rock temperature stabilizes at a depth of 28.11 m. The original rock temperature at the \(-930\) m measurement point is 33.05 \({}^{\circ}\)C, and at the \(-945\) m measurement point, it is 36.55 \({}^{\circ}\)C. Therefore, for future monitoring of the rock temperature field in this area, the temperature monitoring boreholes need to be at least 30 m deep to verify the model's accuracy with actual measured temperatures.
###### Abstract  
Solar irradiance is a critical factor influencing the reliability of optical inter-satellite links (O-ISLs). Despite its significance, limited research has focused on addressing this challenge. This work investigates the impact of solar irradiation on the optimal path configuration. A multi-directional field-of-view (FoV) model is used to practically accommodate the solar irradiance imposed on each optical transceiver module in a single satellite. The effectiveness of the optimal path configurations is evaluated through detour mitigation strategies, comparing inter-plane and inter-shell link alternatives in intercontinental scenarios within the northern hemisphere. In the scenarios, it is found that there is a tradeoff between the FoV and the level of the signal-to-noise ratio (SNR) required to overcome the effects of solar irradiance. Also, seasonal alterations in the sun's incident direction significantly influence the link availability, with unusable link rates nearly doubling in summer compared to spring because of orbital inclinations tending to be aligned more closely with the solar direction toward Earth. The proposed inter-shell-based path optimization reduces the total link distance by up to 2500 km compared to those of the inter-plane configurations, demonstrating superior performance in mitigating impairment due to solar irradiance.  
optical inter-satellite links; O-ISLs; laser inter-satellite links; low-Earth orbit; free space optics; optical wireless communications; solar irradiation; inter-plane link; inter-shell link; Starlink; optical antenna; RIS; beam-steering Article