esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on the Settlement Patterns of Tunnel-Surrounding Rock Under Groundwater Conditions
## 4 Results and Discussion
### Settlement Simulation Analysis  
#### 4.2.1 Displacement Cloud Images Analysis  
Using the FLAC3D software, Z-directional displacement cloud map slices with and without groundwater were generated and then analyzed through comparison.  
The surrounding rock's Z-directional displacement cloud image with groundwater influence is clearly presented in the upper section of Figure 8. The maximum vault settlements within Y = 40\(-\)60 m are 2.55 cm, 2.58 cm, 2.583 cm, 2.591 cm, and 2.596 cm. The maximum difference in vault settlements among cross-sections is 0.64 mm. The maximum ground surface settlements within Y = 40\(-\)60 m are 9.73 mm, 10.87 mm, 11.94 mm, 1.29 cm, and 1.38 cm. The maximum difference in ground surface settlements among cross-sections is 4.07 mm. The surrounding rock's Z-directional displacement cloud image without groundwater influence is clearly presented in the lower section of Figure 8. This figure effectively illustrates the displacement pattern of the rock in the absence of groundwater action. Within the range Y = 40\(-\)60 m, the maximum vault settlements are 7.67 mm, 7.68 mm, 7.79 mm, 7.85 mm, and 7.91 mm. The maximum difference in vault settlements among monitoring cross-sections is 0.24 mm. Similarly, the maximum ground surface settlements within the same range are 5.77 mm, 5.78 mm, 5.89 mm, 5.95 mm, and 6.01 mm, with a maximum difference of 0.24 mm among cross-sections.  
By comparing settlement data under groundwater influence and without groundwater influence, it is observed that the maximum vault settlements under groundwater influence are 3.28 times greater than those without groundwater influence, while the maximum ground surface settlements are 1.8 times greater. When groundwater is the primary influencing factor, both tunnel vault and ground surface settlements show a significant upward trend due to the softening of strata lithology upon water contact. The results indicate that groundwater can amplify tunnel-surrounding rock deformation by modifying soil mechanical parameters (e.g., cohesion and internal friction angle) and seepage pressure. This effect is particularly pronounced in weaker geological formations, significantly influencing settlement development.
## 2 Numerical Methods
### Rotating Blade (Body Force Propeller) Model
#### 2.3.3 Blade Element Theory at 1/4 Chord Position  
Once the RANS grid point is identified inside one blade, the propeller computation is conducted on the corresponding foil section/blade element at that propeller radius. The total velocities are obtained for the 25% chord position \(\big{(}x_{q},y_{q},z_{q}\big{)}\), which is the usual location of the aerodynamic center for a foil section.  
\(\big{(}x_{q},y_{q},z_{q}\big{)}\) can be generated by Equations (3) and (4) using \(k^{\prime}\) = 0.5. The cell search algorithm in Section 2.3.1 is performed again to locate the RANS grid points surrounding the point \(\big{(}x_{q},y_{q},z_{q}\big{)}\), such as for points A, B, C, and D as shown in Figure 2. Accordingly, the total velocities \(\big{(}u_{q},v_{q},w_{q}\big{)}\) at \(\big{(}x_{q},y_{q},z_{q}\big{)}\) are obtained by the inverse distance weighting interpolation from the velocities on point A, B, C, and D:  
\[u_{q}=\sum_{i=1}^{4}(W_{i}\cdot u_{i})/\sum_{i=1}^{4}W_{i}, \tag{24}\]  
\[v_{q}=\sum_{i=1}^{4}(W_{i}\cdot v_{i})/\sum_{i=1}^{4}W_{i}, \tag{25}\]  
\[w_{q}=\sum_{i=1}^{4}(W_{i}\cdot w_{i})/\sum_{i=1}^{4}W_{i}, \tag{26}\]  
\[W_{i}=(1/r_{i})^{p}, \tag{27}\]  
where \(r_{i}\) is the distance between \(\big{(}x_{q},y_{q},z_{q}\big{)}\) and grid point. The grid point A, B, C, and D are assigned to \(i\) = 1, 2, 3, 4, respectively. The power parameter \(p\) is a positive real number, and is set as 1.51294159474 which is a common value used in CFD-SHIPIOWA V4.5.  
Figure 2: Cell search algorithm.  
The main part of propeller computation is the same as in the average model in Section 2.2. The only difference in this case is the body force distribution. In the rotating blade model, the linear body force distribution is specified along the chord length \(C\) with the maximal value at leading edge, and a value of zero at the trailing edge. If \((x_{q},y_{q},z_{q})\) is at \(x^{\prime}\)/C portion of the chord length \(C\), the body forces are distributed axially and tangentially as below:  
\[fb_{x}=\frac{2 dT}{\Delta x\cdot C}\left(\frac{x^{\prime}}{C}+\frac{3}{4} \right), \tag{28}\]  
\[fb_{\theta}=\frac{2 dQ}{\Delta x\cdot C\cdot r}\left(\frac{x^{\prime}}{C}+\frac {3}{4}\right). \tag{29}\]  
Figure 3 illustrates the linear distribution of the axial and tangential body force.
# Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Parana State, Brazil
## 2 Material and Methods  
### Study Region  
The study area is the state of Parana in the south region of Brazil (Figure 1). Parana occupies an area of 199,315 km\({}^{2}\) and covers 399 municipalities [34]. According to the Koppen classification, carried out by [35], the state is in the transition from tropical and subtropical climates where the humid subtropical Cfa (hot summer) and Cfb (warm summer) predominate across 61.7% and 37.0% of the state, respectively. Because of its extensive area, there is a great diversity in terms of climate, soil types, vegetation, and agricultural use. The main biomes that constitute the state are the Atlantic Forest and the Cerrado. The predominant crops are maize, soy, and sugar cane. Most of Parana's relief is found at altitudes above 600 m (Figure 1), subdivided into four Morpho-sculptural Units [36].  
Figure 1: Study area and gauges used to validate the Integrated Multi-satellite Retrievals for GPM (IMERG) estimates of precipitation at daily and monthly time-steps.  
Precipitation in Parana varies spatially, with an annual average between 1300-2200 mm. Summer is the season with the highest rainfall in South America, including the subtropical region [37; 38]. The geographic mesoregions of Parana, demarcated by the Brazilian Institute of Geography and Statistics (IBGE) and shown in Figure 2, were considered for the regional analysis of the performance of the IMERG products over the study area.
## 4 Results and Discussion
### Numerical Results for Isoparametric Elements  
The SBFEM performance in terms of computing time and accuracy is strongly related to the discretization of the cross-section. In the absence of a criterion for optimum discretization, calculations are performed using six to twelve nodes per wavelength (8) for isoparametric elements and different interpolation orders for spectral elements. The results are used to estimate the number of nodes required to ensure the efficiency and convergence of the SBFEM. The accuracy for the mode of interest with the highest frequencies (\(\lambda\)min) according to Equation (41) will be considered,  
\[l_{\text{min}}=\frac{C_{T}}{\left(\text{\emph{nodes per unit of }}\lambda\right)\,f_{ \text{max}}}=\frac{\lambda_{\text{min}}}{\delta}. \tag{41}\]  
Numerical results with different numbers of nodes were obtained and compared with the analytical solution. In Figure 5, the phase velocity versus frequency for the S and A modes are plotted. In Figure 5, red is used for the isoparametric elements, black for the analytical ones, and green for the spectral elements. A good agreement is observed for the given frequency range for both the curves calculated with isoparametric and spectral elements as shown in Table 3.  
Small deviations are observed for the \(S\) and \(A\) modes at high frequencies, \(f>900\) kHz. This is to be expected, since the higher the frequency of the mode, the shorter its wavelength, requiring a greater number of nodes to capture the dynamics of the system.  
Figure 6 shows the group velocity dispersion curves of the modes that can propagate in the steel plate. Using the SBFEM with six nodes per wavelength (8) for isoparametric and only one element of order six for spectral elements has been done for the discretization of the cross-section. The results obtained from both approaches are in excellent agreement with the analytical solution.  
Figure 5: Phase velocity dispersion curves were calculated by SBFEM with isoparametric and spectral elements for a 3 mm-thick isotropic plate. Symmetric Sn and antisymmetric An (\(n=0,\,1,\,2,\ldots\)) modes.
# Data Security-Based Routing in MANETs Using Key Management Mechanism
## 5 Experimental Results and Comparative Analysis
### Future Scope  
Further improvements of the proposed model can be achieved by using deep-learning models [41; 42; 43] to predict the CK and DK nodes efficiently. The effect of hyper-parameter tuning [44; 45; 46] is also ignored. Therefore, in the future, the hyper parameters of the proposed model will be optimized using various optimization approaches, such as genetic algorithms [47]. Additionally, in the future, the proposed model can be used for other kinds of wireless networks, such as Vehicular Ad Hoc Networks (VANETs).
# How 5G Wireless (and Concomitant Technologies) Will Revolutionize Healthcare?
## 4 5G and Healthcare Opportunities
### Internet of Medical Skills  
The exhilarating breakthrough in technology focuses on connecting societies and professionals with a great responsiveness and reach. This will create an Internet of medical skills to transfer or share your experience and expertise over a long distance using robotics and haptic feedback. 5G will not only spread connectivity, but it will also enhance the opportunity for remote training with visual and tactile communication. Doctors will become teachers, and students in remote areas can follow and experience surgical procedures. Robots will be controlled by the use of haptic glove, and they will transfer tactile data back to operating doctor over a distance. This exciting glimpse of the future is only possible with the ultra-low latency of under ten milliseconds.
# A Monopole UWB Antenna for WIFI 7/Bluetooth and Satellite Communication
## 5 Measurement and Discussion
### Far-Field Characteristics  
The antenna was tested for its radiation patterns in an anechoic chamber, as shown in Figure 9a-e, which shows the simulated and measured xoz and yoz planes of the antenna at 2.4 GHz, 5.1 GHz, 6 GHz, 10 GHz, and 13.2 GHz. From Figure 9a-c, the antenna on the yoz surface is basically in omnidirectional radiation state for 4G/5G, Bluetooth, and WiFi 7. In addition, it can be seen from Figure 9d that the energy is mainly concentrated between 15\({}^{\circ}\)-60\({}^{\circ}\), 120\({}^{\circ}\)-240\({}^{\circ}\) and 300\({}^{\circ}\)-350\({}^{\circ}\) of the yoz plane, while Figure 9e illustrates that the energy is mainly concentrated between 60\({}^{\circ}\)-110\({}^{\circ}\) and 240\({}^{\circ}\)-300\({}^{\circ}\) of the yoz plane, which is suitable for satellite directional communication. On the xoz surface, it can be seen from Figure 9a,b that the pattern of the antenna is \"8\", and the two-way radiation effect is obvious; for Figure 9c-e, the pattern of the antenna is basically in full radiation mode.  
Moreover, as shown in Figure 10, the antenna gain is between 2 and 6 dBi, with a maximum peak gain of 5.43 dBi at 13.2 GHz and a lower peak gain at 5.5-5.7 GHz. Due to the existence of the test environment and actual errors, the measured gain is lower than the simulated value. Although some of the range gain is unstable, the gain is relatively stable over the frequency band in which it operates, which can be suitable for wireless applications.  
The comparison of this work in terms of size, bandwidth, and application with the designs reported in references is provided in Table 2. Although the size of the monopole UWB antenna proposed in this paper is moderate among the reported antennas, it has certain advantages in terms of band coverage and gain and will be valuable in wireless communication networks. UWB has the characteristics of high data rate, strong anti-multipath effect, and low power consumption, and it can be applied to several applications in communication. In addition, the proposed design covers all WiFi bands and can achieve omnidirectional radiation with higher gain compared to other references, which can also be applied for 4G/5G communication. Meanwhile, the last ultra-wideband can be used  
Figure 9: Simulated and measured far-field patterns on XOZ and YOZ planes at: (**a**) 2.4 GHz, (**b**) 5.1 GHz, (**c**) 6 GHz, (**d**) 10 GHz, (**e**) 13.2 GHz.
# Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node
## 2 Literature Review
### Comparative Analysis  
Table 1 shows the comparative analysis of existing handoff techniques in VANET. The authors in [1] have proposed approach named vehicle link expiration time (VLET) metric. In this approach packet loss rate cannot decrease but handoff delay reduces. RFID Tags proposed by [PERSON], [PERSON], et al. (2016) [12]. Packet loss rate decreases in the proposed scheme and handoff latency reduces. In another attempt, the work presented in [13] gives the multichannel functions method. The authors have maintained the handoff process in vehicular network based on IEEE 802.11p network standard. Wi-Fi was also utilized to interface every one of the hosts with MRs and WI-MAX is utilized to associate MRs to the web. In NEMO clusters of vehicles are considered as transports. The primary vehicle in the gathering is considered as front MR, while the last vehicle is assigned to be as back MR, which is the proposed mobile edge-node. Pre-handoff performance for last MR is the requirement of front MR.  
This approach reduces the handoff delay and support real-time services. [PERSON], [PERSON], et al. (2014) [14] proposed schemes called turned detection scheme and AP selection scheme. They worked on handoff delay by using location-based handoff approach specifically build for vehicular communication system. According to movement route and positions of vehicle information and nearby APs information, the proposed protocol guesses many APs that the vehicle may be visit in future and allocates these APs different priority levels.  
[PERSON], [PERSON], et al. (2018) [15] proposed a new optimal handover decision model. Packet loss rate decreases in this approach but handoff delay cannot reduce. [PERSON], [PERSON], et al. (2016) [16] proposed efficient proxy mobile IPv6 (E-PMIPv6).  
E-PMIPv6 allows mobile nodes to get continuous internet connectivity from static roadside units or mobile routers and enhance cache usage at the local movement fixed by binding the cache data of the mobile users. In the handoff procedure E-PMIPv6 focuses on multiple handoff circumstances in the urban vehicular surroundings and gives mobility support to individual mobile users or group of users in an identical network without disturbing continuous sessions. [PERSON], [PERSON], and [PERSON]. (2013) [17] provides a scheme named the vertical handoff scheme. Packet loss rate decreases and also handoff delay reduces in this scheme. In this approach vertical handoff evaluation of vehicular users in VANET environment comprise of different mobile systems and wireless networks. Simulation is performed in network simulator 2.  
This work details the investigation of the handoff challenges in cluster-based handoff using proposed DEBCK. The outcomes are contrasted with NEMO and cluster-based Technologies. The result portrays that coherence in communication during handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.
# Multimodal AutoML via Representation Evolution
## 5 Results
### Quantitative Results
\begin{table}
\begin{tabular}{l c c c c c c c c c c c c c c c} \hline \hline
**Metric** & \multicolumn{3}{c}{**Macro F1**} & \multicolumn{3}{c}{**Accuracy**} & \multicolumn{3}{c}{**Precision**} & \multicolumn{3}{c}{**Recall**} \\
**Approach/Data Set** & **Recipes** & **Faux** & **Fake** & **Birds** & **Recipes** & **Faux** & **Fake** & **Birds** & **Recipes** & **Faux** & **Fake** & **Birds** & **Recipes** & **Faux** & **Fake** & **Birds** \\ \hline Majority classifier & 0.002 & 0.354 & 0.378 & 0.0 & 0.03 & 0.547 & 0.608 & 0.002 & 0.001 & 0.274 & 0.304 & 0.0 & 0.042 & 0.5 & 0.5 & 0.005 \\ (I) MobileNet + SVM & 0.623 & 0.683 & 0.712 & 0.699 & 0.671 & 0.685 & 0.726 & 0.702 & 0.667 & 0.684 & 0.713 & 0.708 & 0.646 & 0.684 & 0.713 & 0.707 \\ (I) MobileNet + NN & 0.423 & 0.745 & 0.742 & 0.692 & 0.476 & 0.748 & 0.754 & 0.694 & 0.471 & 0.747 & 0.742 & 0.707 & 0.473 & 0.745 & 0.742 & 0.7 \\ (I) Fine-tuned MobileNet & 0.512 & 0.354 & 0.378 & 0.192 & 0.568 & 0.547 & 0.608 & 0.199 & 0.567 & 0.274 & 0.304 & 0.23 & 0.554 & 0.5 & 0.5 & 0.202 \\ (T) N-grams + SVM & 0.852 & 0.801 & 0.753 & 0.602 & 0.875 & 0.805 & 0.768 & 0.618 & 0.872 & 0.807 & 0.758 & 0.611 & 0.889 & 0.799 & 0.75 & 0.624 \\ (T) Fine-tuned BERT & 0.777 & 0.813 & 0.829 & 0.593 & 0.804 & 0.818 & 0.886 & 0.595 & 0.814 & 0.825 & 0.828 & 0.613 & 0.819 & 0.811 & 0.839 & 0.597 \\ (I) TPOT & 0.861 & 0.791 & 0.732 & 0.612 & 0.889 & 0.803 & 0.75 & 0.617 & 0.877 & 0.882 & 0.739 & 0.632 & 0.889 & 0.788 & 0.729 & 0.622 \\ (I+T) Late fusion (sum) & 0.79 & 0.76 & 0.773 & 0.781 & 0.822 & 0.764 & 0.786 & 0.782 & 0.813 & 0.765 & 0.777 & 0.789 & 0.818 & 0.758 & 0.771 & 0.787 \\ (I+T) Late fusion (max) & 0.73 & 0.76 & 0.773 & 0.762 & 0.771 & 0.764 & 0.786 & 0.764 & 0.761 & 0.765 & 0.777 & 0.771 & 0.763 & 0.758 & 0.771 & 0.769 \\ (I+T) Late fusion (stacking) & 0.711 & 0.72 & 0.781 & 0.768 & 0.756 & 0.722 & 0.792 & 0.768 & 0.751 & 0.72 & 0.783 & 0.779 & 0.72 & 0.78 & 0.773 \\ (I+T) Early fusion + NN & 0.5 & 0.796 & 0.82 & 0.694 & 0.568 & 0.801 & 0.828 & 0.697 & 0.534 & 0.806 & 0.82 & 0.704 & 0.568 & 0.794 & 0.821 & 0.701 \\ (I+T) Early fusion + SVM & 0.746 & 0.784 & 0.816 & 0.721 & 0.808 & 0.788 & 0.824 & 0.726 & 0.782 & 0.789 & 0.816 & 0.728 & 0.773 & 0.783 & 0.817 & 0.732 \\ \hline (I+T) MuRE-1h & 0.913 & 0.812 & 0.766 & 0.911 & 0.952 & 0.817 & 0.776 & 0.948 & 0.911 & 0.824 & 0.773 & 0.911 & 0.923 & 0.813 & 0.773 & 0.919 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Classification results—10 fold cross validation, same seed for all methods (420). Green cells denote either first or second rank for a given dataset (I = images, T = texts). Figure 2: Visualization of the projection of multimodal latent space (I+T) for the _tasty_ dataset.
# Object-Tracking Algorithm Combining Motion Direction and Time Series
## 4 Experimental Results and Analysis
### Comparison of Results
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Tracker** & **Published** & **AO (\%)** & **SR0.5 (\%)** & **SR0.75 (\%)** \\ \hline ATOM [45] & 2019 & 55.6 & 63.4 & 40.2 \\ TR-Siam [46] & 2022 & 58.2 & 68.3 & 45.7 \\ SiamFC++ [15] & 2020 & 59.5 & 69.5 & 47.9 \\ DiMP50 [39] & 2019 & 61.1 & 71.7 & 49.2 \\ Ocean [47] & 2020 & 61.1 & 72.1 & 47.3 \\ SiamRDT [43] & 2022 & 61.3 & 72.5 & 49.2 \\ PrDiMP50 [44] & 2020 & 63.4 & 73.8 & 54.3 \\ SiamRCNN [19] & 2020 & 64.9 & 72.8 & 59.7 \\ TransT [21] & 2021 & 67.1 & 76.8 & 60.9 \\ STARK-ST50 [25] & 2021 & 68.0 & _77.7_ & 62.3 \\ Ours & - & **69.7** & **79.4** & **63.9** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Evaluation on the GOT-10K test set. Bold indicates best result.
# A Hybrid Encryption Scheme for Quantum Secure Video Conferencing Combined with Blockchain
###### Abstract
A networking scheme for seamlessly connecting QKD equipment to the video conferencing system is established to realize the effective combination of the quantum key and classical applications. 2. According to the characteristic that the quantum key generation rate is lower than the quantum key consumption rate, a hybrid encryption scheme is designed. Based on the security level of the video conference data, two sets of encryption algorithms of \"one-time pad + AES\" quantum key encryption and \"AES\" classical key encryption are adopted. 3. Since the QKD is affected by factors such as the channel, environment, and eavesdropping, the real-time monitoring function of the QKD network is designed to detect the key generation, so as to ensure the continuous and stable operation of the video conference system. 4. Using blockchain technology to share meeting minutes. After the meeting, miners write the encrypted meeting minutes into the blockchain. A cache-efficient query method based on B+ tree is designed, and an adaptive space method is used to solve the problem of index address conflict. On the basis of not revealing the plaintext of meeting minutes, previous meeting information can be searched, decrypted, and viewed. The other parts of this paper are arranged as follows. Section 2 explains the basic knowledge of the Quantum Key Distribution, Blockchain and B+ tree. Section 3 describes the system model. Section 4 gives the specific design of the scheme. Section 5 analyzes the security and stability of the model. Section 6 provides the system operation analysis. Section 7 summarizes the full text. Appendix A describes two algorithms.
# Soil Erosion Estimates in Arid Region: A Case Study of the Koutine Catchment, Southeastern Tunisia
## 4 Results and Discussion
### Practice Support Factor (\(P\))  
Different water and soil conservation (WSC) practices were essentially implemented in the study site, such as Jessour, Tabias, Check dams and Contour benches. The efficiency of these practices varies according to the slope value (Table 3, Figure 7f). The WSC practices are entirely useless on slopes higher than 26% (\(p\) = 1), representing only 3.5% of the Koutine catchment. They become less efficient as the slope declines.
## 4 Simulation of Use Cases
### Design of the Simulation Models Based on Various Industry 4.0 Use Cases  
For the fourth industrial revolution the same examples are simulated. Each of them refers to one of the clusters of the GUVEI-Model starting from an initial situation.  
* Initial situation: the model starts with a supply chain system that has delivery problems. Therefore, there is a capability need, i.e., the production system is not able to supply the needed demand to the market. Causes are unknown and could be multiple, such as low availability level of machines, lack of training of employees, long lead times for procurement of spare parts, lack of supplies on-time, etc.
* Cluster 1 simulation model: from the basis of the initial situation, the use case of the first cluster consists of the implementation of sensors for equipment monitoring. As a result, it is possible to know the bottleneck resources, as well as to incur less reaction times for maintenance activities, as breakdowns would be known in real time.
* Cluster 2 simulation model: this steps consists of the utilization of data provided from sensors about availability, performance and quality to adjust the production planning to develop into reliable planning that can enhance service levels to customer and capacity utilization levels thanks to better forecasting and capacity planning.
* Cluster 3 simulation model: later, with the help of virtual reality, the training and qualification of employees can improve significantly, and problems can be detected earlier. Therefore, this use case will enable a better-quality rate, and a reduction of production times leading, as a result, to higher capacities.
* Cluster 4 simulation model: it consists of the implementation of CPS with mobile devices as well as intelligent AGV (automated guided vehicles) that will improve the availability and reaction times for manufacturing spare parts, as well as for production supplies as agents are interconnected and without delays in communication and decisions.
* Cluster 5 simulation model: finally, the last step consists of applying additive manufacturing to reduce production lead times, procurement lead times for raw materials,as well as for spare parts, enabling improvement of the capacity level of the plant and the reaction times.  
Table 1 shows a review of the described use cases classified according to the technology applied, and, as can be seen, the element of the global production system is improved: