esa-sceva/satcom-chunk-collection huggingface dataset:
# A Medical Image Segmentation Network with Multi-Scale and Dual-Branch Attention
## 3 Method
### Multi-Receptive Field Densely Connected Module  
The effective receptive field of many of the current traditional convolutional neural networks does not grow proportionately with an increase in the number of convolutional layers. Traditional Fully Convolutional Networks [22] (FCNs) rely on fixed receptive field sizes of convolutional and pooling layers for feature extraction. This approach limits the ability to simultaneously capture features of both large and small target regions, leading to detail loss and blurred boundaries during image segmentation. To address this issue, we introduce a novel module (MRD) in upsampling. Incorporating multi-receptive field extraction into the network allows it to capture features at various scales, enabling the detection of a broader context while simultaneously focusing on detailed information.  
This approach ensures a more accurate capture of features across different target sizes, preserving feature details and achieving clearer boundaries. MRD consists of three densely connected multi-scale dilated convolutions (MDC). Its structure is shown in Figure 2. The multi-scale dilation convolution module employs three parallel convolution branches with varying expansion rates to extract features across different receptive fields, thereby enhancing sensitivity to features of various sizes. The MDC module takes the input feature map \(X\) and feeds it into convolutional branches with dilation rates of 1, 3, and 4, respectively. Through feature concatenation and 1 \(\times\) 1 convolution, the outputs of the three parallel branches are fused to achieve feature integration across different scales. In the following formula, \(MDC()\) is the multi-scale dilated convolution function of input feature map \(X\)  
Figure 1: MSDA-Net network structure.  
and \(DConv_{msm}^{r}(X)\) represents an atrous convolution operation with a convolution kernel of \(m\times m\) and an atrous rate of r for input feature map \(X\).  
\[MDC(X)=Conv_{1\times 1}\Big{(}ConCat\Big{(}DConv_{3\times 3}^{1}(X),DConv_{3 \times 3}^{2}(X),DConv_{3\times 3}^{4}(X)\Big{)}\Big{)}\]  
Additionally, leveraging dense connectivity [42] enables the capture of richer and more detailed feature representations. As shown in Figure 1, the final output feature map, \(Y\), is generated by summing the outputs of the three densely connected MDC modules and the input feature map \(X\).  
\[Y_{1}=X+MDC(X) \tag{1}\]  
\[Y_{2}=Y_{1}+MDC(Y_{1}) \tag{2}\]  
\[Y_{3}=Y_{2}+MDC(Y_{3}) \tag{3}\]  
\[Y=Y_{3}+Conv_{1*1}(X) \tag{4}\]
## 4 Materials and Methods for Designing Tether-Deployed Constellations
### Conceptual Design
#### 4.1.2 Symmetric versus Asymmetric Release  
The system uses paired tethers for stability upon release, as symmetrical release simplifies the return to a non-spinning state after deployment. Symmetrical release in this context involves releasing two opposing tethered objects simultaneously, which, if needed, can allow for payloads and potential counterweights of different masses and geometries as long as the center of mass remains near the central axis of rotation. The term symmetric is used to describe the geometry of the overall system, with a deployer in the center and two identical tethered payloads on either side of the deployer. Asymmetrical release involves letting go of just one tethered payload rather than two, which introduces complex disturbances due to a rapid change in the system's center of mass on one side, necessitating corrections with attitude control systems, which can be non-ideal if needing to restabilize between multiple sequenced deployments. An asymmetrical release can also alter the deployer's orbit after releasing a payload, which could require propulsive corrections depending on the nature of the mission. Symmetrical release, however, preserves the deployer's position, as the releases of opposing masses cancel out orbit-changing forces, assuming the released payloads' masses and tether lengths are identical.  
With symmetrical releases, one aspect that must be considered is that releasing payloads into opposing directions means releasing payloads into different orbits. These two orbital planes of prograde and retrograde released payloads can be initially approximated as coplanar, but over significantly long periods, the effects of nodal precession can become visible due to the minute differences in altitude and velocities of the satellites in the two different planes. If these satellites include onboard propulsion for station-keeping; however, nodal precession effects can be easily mitigated.
## 9 Conclusions  
This study has reviewed and summarised, from a comparative perspective, the main calculation methods in the analysis of stiffened and unstiffened liners located in pressure tunnels at hydroelectric power plants. It has also examined the calculation and current design codes that were derived from the 1960s onwards.  
The main parameters that determine the critical pressure that liners may withstand are the relationship between the thickness and diameter, quality of steel, inertia of stiffeners and their spacing (should this apply), initial gap, and geometric imperfections. In addition, it is recommended that the beneficial effect of the encasing concrete and rockfill be neglected when analysing a liner submitted to interior pressure, unless it can be assured that there is no gap between the liner and its grouting.  
The analytical methods available (Amstutz and Jacobsen) for calculating the instability of stiffened liners only consider that failure is caused by plastic instability. Indeed, the scope of the Amstutz approach is rather limited. Instead, it is paramount to determine the failure mode, whether by geometric instability or yielding.  
In the case of unstiffened liners, the Jacobsen values agree with the FEM results for common values of the \(D/t\) relationship, though it should be noted that for slender thin-walled liners, the Jacobsen approach does not consider failure due to geometric instability but by yielding.  
The FEM serves as a valuable tool not only for determining the critical pressure of steel liners but also in addressing a given problem. Such an approach may be implemented for assessing the critical pressure when failure occurs by local instability (shell buckling), by overall buckling of the pipeline wall along with stiffeners or through inelastic instability.  
The selection of the steel-liner type should be performed after examination of practical and financial criteria, which involve the choice of either stiffened or unstiffened liners, quality of steel, as well as spacing between stiffeners.
# NDVI or PPI: A (Quick) Comparison for Vegetation Dynamics Monitoring in Mountainous Area
## 2 Materials and Methods  
### Study Area  
The study area is delimited through the borders of the carton of Valais in Switzerland (Figure 1). The lowest point is at 372 m at Geneva Lake, and the highest is at 4634 m at the Dufourspitze. The surface of the area of interest is about 5224.35 km\({}^{2}\). The Valais encompasses several valleys, with the Rhone Valley being the central one. This mountainous region is situated in the northwestern European Alps, with several peaks rising above 4000 m. This mountain range shelters the inner Rhone Valley from moist oceanic air masses, resulting in a steep precipitation gradient from the west (around 1000 mm/year) to the east (around 600 mm/year) [43; 44; 45]. The eastern Rhone Valley is considered one of the driest and most continental inner alpine valleys and hosts a rich xerothermic flora [44]. Cloud cover is generally low, while solar radiation is high [45]. As in other mountainous regions, the Valais is therefore characterized by a high diversity of vegetation types and ecosystems due to its diverse geographical features [7].  
Figure 1: Localization of the carton of Valais (CH) and altitudinal range (projection: CH1903+/LV95).
## 4 Results
### Evaluation of Conditioning Factors
#### 4.2.1 Application of Conventional Algorithms
\begin{table}
\begin{tabular}{c c c c c} \hline
**Conditioning Factors** & **Zone** & **Ni/N** & **Si/S** & **IV** \\ \hline \multirow{8}{*}{Distance to streams (km)} & \(<\)1 & 47.58\% & 14.51\% & 1.187 \\  & 1–3 & 19.35\% & 25.62\% & \(-\)0.280 \\  & 3–5 & 7.06\% & 19.97\% & \(-\)1.040 \\  & 5–7 & 6.65\% & 14.66\% & \(-\)0.790 \\  & 7–9 & 9.07\% & 11.07\% & \(-\)0.199 \\  & 9–11 & 5.44\% & 7.00\% & \(-\)0.252 \\  & 11–13 & 3.63\% & 4.38\% & \(-\)0.189 \\  & \(>\)13 & 1.61\% & 2.78\% & \(-\)0.544 \\ \hline \multirow{8}{*}{Distance to roads (km)} & \(<\)3 & 57.66\% & 32.20\% & 0.583 \\  & 3–6 & 11.69\% & 25.23\% & \(-\)0.769 \\  & 6–9 & 14.11\% & 18.23\% & \(-\)0.256 \\  & 9–12 & 6.20\% & 9.08\% & \(-\)0.374 \\  & 12–15 & 5.44\% & 6.37\% & \(-\)0.158 \\  & 15–18 & 1.41\% & 4.46\% & \(-\)1.151 \\  & 18–21 & 2.62\% & 2.07\% & 0.237 \\  & \(>\)21 & 0.81\% & 2.35\% & \(-\)1.070 \\ \hline \multirow{8}{*}{Average annual precipitation (mm)} & \(<\)480 & 32.26\% & 50.99\% & \(-\)0.458 \\  & 480–580 & 29.44\% & 24.55\% & 0.182 \\  & 580–680 & 24.60\% & 11.55\% & 0.756 \\  & 680–780 & 3.02\% & 9.38\% & \(-\)1.132 \\  & \(>\)780 & 10.69\% & 3.53\% & 1.107 \\ \hline \multirow{8}{*}{NDVI} & \(<\)0.15 & 16.53\% & 12.68\% & 0.265 \\  & 0.15–0.3 & 25.20\% & 36.62\% & \(-\)0.374 \\ \cline{1-1}  & 0.3–0.45 & 15.12\% & 19.74\% & \(-\)0.266 \\ \cline{1-1}  & 0.45–0.6 & 15.93\% & 17.94\% & \(-\)0.119 \\ \cline{1-1}  & 0.6–0.75 & 22.18\% & 9.93\% & 0.804 \\ \cline{1-1}  & \(>\)0.75 & 5.04\% & 3.09\% & 0.490 \\ \hline \end{tabular}
\end{table} 
Table 4: _Cont._
## 6 Human-Aerial Robot Interaction
### Aerial Co-Worker for Fast Tool Delivery  
One application in which the use of aerial manipulators can be particularly useful for the operators working on the power lines is the delivery of tools, such as screwdrivers and pliers, or devices, such as clip-type bird diverters. This is motivated by taking into account the time and effort required to climb to the power lines, and the possibility to lose accidentally part of the equipment during operations. As occurs with other human-robot collaborative tasks [49; 50], the close interaction of the aerial robot with the human operator must be safe, especially taking into account the risk due to the high altitude and the difficulty in standing upright in this kind of workspace. Since the proximity of the propellers to the worker will result in an uncomfortable feeling and a sense of danger [51], it is preferable that the handover operation [8; 52] is carried out in such a way that the manipulator is separated from the aerial platform. Thus, the proposed solution consists of employing an aerial manipulator in long-reach [8; 27] or cable-suspended configurations [14; 15], using a cable (around 1.5 m in length) to attach the manipulator to the multirotor base. Figure 12 illustrates the use of a dual-arm aerial manipulator in a long-reach configuration for the delivery of tools (a screwdriver and some pliers) to a human operator working on a line.  
Four reference frames are considered in the definition of the operation: the Earth fixed frame \(\{\mathbf{E}\}\) (inertial), the multirotor body frame \(\{\mathbf{E}\}\), the manipulator frame \(\{\mathbf{0}\}\), and the operators head/helmet frame \(\{\mathbf{H}\}\). These are illustrated in Figure 12. In the navigation phase, the aerial robot takes of from the supply point and navigates to the proximity of the power line employing GNSS (Global Navigation Satellite System) sensors, such as GPS, to estimate the position relative to the Earth fixed frame. In the approaching phase, the aerial robot is positioned relative to the operators helmet, using, for example, visual markers on it for its detection and localization [53]. Two constraints should be imposed in the realization of the handover operation: (1) keep a minimum separation distance between the multirotor base and the operator's helmet for safety, and (2) keep the end effector of the  
Figure 11: Augmented human–machine interface.  
manipulator within the reach of the operator's hand to ensure a comfortable interaction with the aerial robot.
## 4 Resource Management in Heterogeneous Network (RM HetNet)
### Spectrum Allocation (SA)
#### 4.4.4 Open Issues and Proposed Solutions  
To meet the stringent requirements of modulating THz signals, novel schemes that can provide spectral efficiency of at least 14 bits/s/Hz are essential. However, this is not possible with current modulation techniques, though research into this area is recommended. The development of THz transceivers and power amplifiers for frequencies between 500 and 750 GHz presents a significant challenge for the industry. However, redesigning antennas to accommodate increasingly dense arrays is necessary because of the shortness of these radio waves. A system that operates at mmWave or THz frequencies is more efficient than in the sub-6 GHz networks, which makes it a perfect field for the EE of future 6G networks. The consumption factor theory provides a power trade-off metric for communication systems. This spectrum method is necessary to avoid interference between new THz-operating systems and established satellite communication systems. Finally, the cooperation between different bands (tradition band, mmWave, and THz) has to be modeled in the best scenario to mitigate the interference and increase the SE.
## 2 Methodology of the Study
### Model Training and Performance Evaluation  
In the model training stage, the ML models were trained with the database by tuning the model parameters to minimize the specific cost function. Regression-based models such as LR, SLR, RR, DT, RF, SVM, GPR, and NN were implemented to identify the seismic response of the URM building. The performance of the models was evaluated through the coefficient of determination (\(R^{2}\)) and root mean square error (RMSE), and an optimum demand model was identified. Classification-based ML models such as NB, DA, KNN, DR, RF, AB, SVM, and NN were trained to classify the building damage states. The performance of the classification models was evaluated through metrics such as accuracy, precision, recall, and F1 score, along with the confusion matrix.
## 4 Practical Implications  
Based on the growing advancements and interest in WDED, several practical implications can be mentioned for industry-involved applications. First and foremost, industries such as those in the aerospace, automotive and biomedical sectors can use this method to fabricate parts with stainless steel, titanium, aluminum, and copper-based alloys to optimize their WDED processes. By carefully choosing materials and setting processing parameters, companies can achieve desired mechanical and microstructural properties, enhancing the performance and reliability of their components. Next, since AM-fabricated parts mostly require post-processing, this study underscores the importance of post-processing techniques such as machining, heat treatment and surface finishing to enhance the quality of WDED samples. Companies must integrate these methods into their production workflow to meet industrial standards for mechanical and microstructural properties. Afterwards, to invest in R&D and collaboration, companies can find collaborators from countries that are accentuating their resources for WDED. This approach ameliorates technological development and aids industries in staying at the forefront of cutting-edge technology. Finally, as WDED is growing, companies can develop new alloys and composites. This could widen their horizons for an innovative approach, allowing for the creation of components with better mechanical properties that could not be achieved via traditional manufacturing methods.  
WDED offers practical applications in various industries, such as those in the aerospace, automotive, and biomedical fields. In the aerospace industry, WDED is a useful method for manufacturing complex, high-performance parts such as structural components and turbine blades from titanium and Inconel alloys. These are widely known for their strength-to-weight ratio, which is a vital characteristic in aerospace industries. Also, WDED's ability to fabricate near-net shapes reduces material waste. Likewise, in the automotive field, WDED can be utilized to fabricate lightweight, high-strength components such as aluminum cylinder heads and heat exchangers. These parts can take advantage of WDED's multi-material capabilities, which enable the deposition of wear-resistant coatings that automotive standards for performance and durability require. In the biomedical sector, WDED aids in fabricating custom implants and prosthetics using biocompatible materials. The ability to fine-tune the mechanical and microstructural properties through careful selection of processing parameters and post-processing techniques ensures that implants meet the functional requirements. Moreover, industries can use WDED to gain the flexibility to develop new alloys and composites that offer enhanced mechanical properties that cannot be obtained via traditional manufacturing methods.
# Design and Analysis of High-Capacity MIMO System in Line-of-Sight Communication
## 1 Introduction
### Motivation and Contributions  
The existing research primarily focuses on the theoretical study of small-scale LoS MIMO systems; however, there are a few studies that can be employed in a variety of practical LoS MIMO applications, such as coupling train communication and satellite communication. In these application scenarios, the antenna configuration often results in poor channel characteristics. Therefore, this paper derives the precise expression between channel phase and capacity of the n-order MIMO system in LoS communication. Since there exists a small amplitude difference in channel matrix elements, the phase of the channel matrix is regarded as the most critical component for the channel capacity and the optimal antenna configurations. The theoretical premise is a channel without scattering and multipath, which is mainly used in short-range LoS communication and non-scattering environment communication, such as coupling train communication and inter-satellite communication. Moreover, the optimal placement and parameters of 2 \(\times\) 2 and 3 \(\times\) 3 transceiver antennas are provided based on the maximum channel capacity in coupling train communication and inter-satellite communication, which lays a basic foundation for the MIMO layout.
###### Abstract  
In a multi-node spacecraft or unmanned aerial vehicle (UAV) group, a multifunctional signal containing measurement, navigation, and communication functions is required to simplify the receiver structure, and to increase spectrum utilization. The paper proposes a multifunctional signal based on a binary offset carrier (BOC) and binary phase shift keying (BPSK) modulation. The signals which carry different functions are orthogonal in the frequency domain, which causes the data transmission signal to not be affected by BOC signal. In addition, in the high carrier to noise ratio (\(C/N_{0}\)), the spreading gain of the BOC signal ensures that the communication signal has a slight influence on navigation signals. Moreover, the multifunctional signal can achieve communication and measurement functions at the same frequency point and fast switching in multinodes. These advantages can simplify the receiver design and improve the frequency band utilization. Finally, in this study we completed the design and verification of the hardware system.  
multifunctional signal; BOC and BPSK composite signal; multi-node communication; inter-satellite links 2022141653[[https://doi.org/10.3390/rs14071653](https://doi.org/10.3390/rs14071653)]([https://doi.org/10.3390/rs14071653](https://doi.org/10.3390/rs14071653)) +
Footnote †: journal: Remote Sens.  
2022141653[[https://doi.org/10.3390/rs14071653](https://doi.org/10.3390/rs14071653)]([https://doi.org/10.3390/rs14071653](https://doi.org/10.3390/rs14071653))
## 3 Influence Analysis of Stiffeners on Lamb Wave Propagation Law
### Effect of Stiffeners on S0 Mode Lamb Wave  
According to the simulation results, the time when the A0 mode Lamb wave reaches the receiving points at 230 mm from the origin is about 70.3 \(\upmu\)s, and the S0 mode Lamb wave before 70.3 \(\upmu\)s is selected as the research object.  
The energy factor curves from point 1 to point 7 at 230 mm from the origin are shown in Figure 8. It can be seen from the figure that the stiffeners have a comb filter effect on the Lamb wave, that is, the Lamb wave energy fluctuates with the change of the frequency. When the number of stiffeners is 2, the comb filter has a clear pass band in the 70 kHz-170 kHz, and the pass band bandwidth is narrow in the 50-100 kHz. The maximum energy factors are in the range of 40-55. As the frequency increases below 300 kHz, the energy factor changes sharply. When the frequency is more than 350 kHz, the energy  
Figure 6: Three-dimensional finite element simulation model: (**a**) stiffened panel; (**b**) flat panel.  
Figure 7: Displacement in the z-axis of each receiving point.  
factors fluctuate only within 0-3. The Lamb wave energy is generally attenuated after passing through the stiffener, but the energy of S0 mode is very small relative to that of A0 mode. When passing through the stiffener, part of A0 mode energy will transfer to S0 mode, which results in that the energy of S0 mode in stiffened panel is much higher than that of S0 mode in panel, so there will be a large energy factor in some frequency bands. When the number of stiffeners is 3, the overall change of the energy factor is gentle. In the 50-250 kHz band, the comb filter has smaller passband and wider bandwidth. The energy factor is also extremely small when the frequency is more than 350 kHz.  
Combining the energy factor curves, it can be seen that the energy of S0 mode varies greatly in the frequency band of 50-100 kHz after different number of stiffeners, there is instability. At the same time, the frequency of this band is relatively low and the resolution is not high in the time domain. In practice, the impact signal is a broadband Lamb wave, and the path from the impact source to each sensor is uncertain. The frequency components of Lamb wave received by different sensors are usually quite different. There is a risk of intercepting signals of different frequency bands and different phases at the arrival time of signals obtained by threshold method. At this time, a large error may occur when the locating calculation is performed using the same wave velocity. Based on the above factors, the S0 mode signal characteristics in the 100-200 kHz band meet the locating requirements.  
Figure 8: Cont.