esa-sceva/satcom-chunk-collection huggingface dataset:
# On Analyzing Routing Selection for Aerial Autonomous Vehicles Connected to Mobile Network
## 3 Motivation
### Description of the Solution  
In our solution, the UAV and the control station select the network operator based on short-term measurements performed in each one of the operator's networks. Therefore, we assume two different links and three different routing paths (three network operators). Figure 2 shows the connectivity scenario considered in our approach for \(N\) Network Operators.  
Each agent (UAV and control station) selects independently (i.e., without any information from the other agent) the Operator's network that assures highest quality of the transmission is the agent's link: From UAV to antenna or from control station to antenna. A posteriori, another external agent uses this information to select the best routing in the two paths subject to the use of the same operator's network.  
Each agent performs measurements of the network during the first minute of the connection. This time is relatively low in comparison to flight duration. During this time the measurements are stored and the throughput during the next 20 min (assumption  
Figure 1: Delay measurements in communication between drone and control station.  
Figure 2: Connectivity scenario of two links: Unmanned aerial vehicles (UAV) to antenna and antenna to Control station. \(N\) network operators.  
of flight average time) is estimated based on those measurements. Such an estimation is performed by using Machine Learning (ML) algorithm, which is trained by real data measurements performed in the network previously.  
Once, the system estimates the throughput in both links, then another ML algorithm decides which one of the routing options (which network operator) should be selected in both links (the same network operator). For this, the third ML receives information about the throughput in UAV and control station links (provided by the first two Machine Learning algorithms).  
The problem then, consists of solving multi-path routing in two independent links subject to some conditions imposed to the final routing.  
Let us remark that the solution provided is valid for any kind of scenario where routing is divided in several links that provide different and independent routing rules, but final routing selection is subject to some conditions that have impact in partial (links) routing. In the case of multiple Radio Access Technology (known as multi-RAT), which is taking increasing importance in 5G networks, the network and the end user are responsible of the selection of the technology and both of them may veto any technology because of, e.g., security reasons. Also in the case of multi-RAT, our solution based on two-step routing decision process is valid.
## 1 Introduction
### Measurement System Requirements  
The PANTHYR system was developed to fit the following user requirements:  
* Measurement of downwelling irradiance, as well as downward (sky) and upward (water) radiance just above the water surface, at flexible zenith and azimuth (relative to sun) angles for a spectral range covering at least 400-900 nm with full-width half-maximum (FWHM) spectral resolution of 10 nm or better and spectral sampling every 5 nm or better.
* Storage of all measurements and diagnostic logs and regular transmission to a land-based server.
* User interface with flexibility for scientists to easily program pointing and data acquisition scenarios.
* Reliable autonomous operation at remote sites, e.g., offshore platforms, with a typical maintenance frequency of once or twice per year without grid power.
* Resistance to harsh offshore environments, including large temperature ranges (measurement limited to between 2 \({}^{\circ}\)V and 40 \({}^{\circ}\)C, and survival between \(-\)20 \({}^{\circ}\)C and 60 \({}^{\circ}\)C ambient temperature), rain, salty sea spray, atmospheric deposition, and possible animals (birds, spiders, etc.).
* Modularity to adapt to sites with different possibilities for power (grid/solar/wind), data transmission channels (cabled internet, 3G/4G cellular networks), and mechanical mounting possibilities (rails, masts, etc.), and to cope with future evolution of system components.
* Moderate hardware purchase costs, e.g., typically \(<\)10,000 \(\epsilon\) commercial price excluding taxes for a full system excluding radiometers.  
* Pointing accuracy of at least 5\({}^{\circ}\) azimuth and 1\({}^{\circ}\) zenith.
# Analysis of a Novel Automatic Control Approach for the Free Forging Hammer
## 3 System Structure and Dynamic Performance Analysis
### Dynamic Performance Analysis  
In order to study the dynamic characteristics of the servo drive system with different servo cylinders, AMESim can be adopted to model and simulate the servo control system, and the dynamic response of the forging hammer under different servo drive systems can then be obtained, combined with the actual operation effect.  
AMESim uses ISO symbols to represent various components related to mathematical descriptions. Furthermore, AMESim provides users with optional libraries, such as the hydraulic component design library, the signal library, and the mechanical library, and users can select submodel and set parameters after building the appropriate sketch model. Figure 8 presents a flow chart of AMESim simulations. According to the flow chart, the physical simulation model of the servo control system can be established based on the hydraulic schematic diagram, as shown in Figure 9. Table 1 includes the main parameters of the simulation model.  
Figure 7: (a) Driving mechanism based on a single-acting servo cylinder; (b) Double-acting servo cylinder; (c) Double-rod servo cylinder.  
During a working cycle, the dynamic responses of the servo control system with different cylinder structures are shown in Figure 10. It can be seen from Figure 10 that the simulation results are basically consistent with the experimental results, verifying the effectiveness of the physical model built in AMESim. From the response curve, three servo cylinders can all meet the control requirements of the forging hammer. The double-rod cylinder is a symmetric cylinder with the best response characteristics, followed by the single-acting cylinder, and the worst is the double-acting cylinder. However, in terms of the actual assembly process, since the oil circuit and assembly structure of the single-acting cylinder is simpler than the double-rod cylinder and the dynamic response time between the single-acting cylinder and the double-rod cylinder exhibits little difference, the single-acting servo cylinder is the best choice for realizing automatic control for a free forging hammer. In addition, due to the vibrations of the displacement sensor when the hammerhead strikes, some volatility also exists in the measured response data, but the overall trend is consistent with the simulations.  
Figure 8: Flow chart of AMESim simulations.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **Values** & **Units** \\ \hline Duty cycle pressure & 14 & MPa \\ Piston rod diameter (Servo cylinder) & 45 & mm \\ Piston diameter (Servo cylinder) & 65 & mm \\ Main control valve diameter & 190 & mm \\ Main cylinder diameter & 140 & mm \\ Length of stoke & \(-\)30\(-\)+30 & mm \\ Accumulator Volume & 10 & m\({}^{3}\) \\ Gas pressure of Accumulator & 14 & MPa \\ Control signal & 0–40 & mA \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main parameters in simulation model.  
Figure 9: The physical simulation model of the main system.
## 7 Conclusions and Future Work
### Avoiding the Spatial Reuse of the Communication Resources and Improving Reliability  
In this paper, we assumed that the two hops reuse distance guarantees that concurrent transmissions in the same cell will not cause internal interference. In a realistic setting, however, the interference and transmission range of a node may not be equal. This may cause internal interference between those concurrent transmissions. To improve the reliability of D-MSR, we proposed a solution by considering the _virtual_ links that represent the interfering links. We intend to assess another potential solution in which the communication resources (timeslot-channel matrix) are divided into several timeslot-channel blocks and the authority of each block of resources is delegated to different two-hop neighborhoods in a distributed manner. We intend to add this capability to D-MSR to avoid the spatial reuse of communication resources in order to address the requirements of those applications for which improving reliability is more important than losing high throughput.
# Learning an Efficient Convolution Neural Network for Pansharpening
## 4 Experiment
### Experimental Settings
#### 4.1.2 Loss Function  
As mentioned in Section 3.3, an input-to-output skip connection was added to make up the lost details and perform residual learning; formally, the mapping function of our model is denoted as \(\mathcal{R}(\mathbf{\omega},\mathbf{b};\{\mathbf{y},\mathbf{p}\},\mathbf{x})=\mathbf{x}-\mathbf{y}\). Furthermore, the loss function is given as:  
\[\widetilde{\mathcal{L}}=arg\underset{\mathbf{\omega},\mathbf{b}}{min}\mathcal{L}(\mathbf{ \omega},\mathbf{b};\{\mathbf{y},\mathbf{p}\},\mathbf{x})+\frac{\lambda}{2}\Omega(\mathbf{\omega}) \tag{7}\]  
\[=arg\underset{\mathbf{\omega},\mathbf{b}}{min}\frac{1}{N}\sum_{l=1}^{N}\left(\frac{1} {2}\|\mathbf{x}^{l}-\mathcal{R}\Big{(}\mathbf{\omega},\mathbf{b};\Big{\{}\mathbf{y}^{l},\mathbf{p }^{l}\Big{\}},\mathbf{x}^{l}\Big{)}-\mathbf{y}^{l}\|_{2}^{2}\right)+\frac{\lambda}{2} \|\mathbf{\omega}\|_{2}^{2} \tag{8}\]  
where \(\mathcal{L}\) is a mean square error (MSE) term; \(\mathbf{\omega}\) and \(\mathbf{b}\) are weights and biases respectively; we let \(\mathbf{\theta}=\{\mathbf{\omega},\mathbf{b}\}\) represent all the trainable parameters in the model; \(N\) is the batch size of the training datasets; and \(\mathbf{x}^{l},\mathbf{y}^{l}\), and \(\mathbf{p}^{l}\) are the corresponding component of the \(l\)-th training sample in the batch. To further reduce the effect of overfitting, we employed a weight decay term (\(\Omega\)) to regularize the weights in the model, and \(\lambda\) is the trade-off parameter.  
The optimal allocation of \(\mathbf{\theta}\) is updated iteratively with stochastic gradient descent (SGD) by calculating the gradients of \(\widetilde{\mathcal{L}}\) to \(\mathbf{\omega}\) and \(\mathbf{b}\):  
\[\left\{\begin{array}{l}\
abla_{\mathbf{\omega}}\widetilde{\mathcal{L}}=\
abla_{ \mathbf{\omega}}\mathcal{L}+\lambda\mathbf{\omega}\\ \
abla_{\mathbf{b}}\widetilde{\mathcal{L}}=\
abla_{\mathbf{b}}\mathcal{L}\end{array}\right. \tag{9}\]  
As the gradients obtained, we set a threshold as \(\delta\), and clipped the gradients as [29]:  
\[\Big{(}\
abla_{\mathbf{\theta}}\widetilde{\mathcal{L}}\Big{)}_{clipped}=\frac{ \
abla_{\mathbf{\theta}}\widetilde{\mathcal{L}}\delta}{\max\Big{(}\delta,\|\
abla _{\mathbf{\theta}}\widetilde{\mathcal{L}}\|_{2}^{2}\Big{)}} \tag{10}\]  
By clipping the gradients, the effect of gradient explosion can be removed.  
To speed up the training procedure, we also adopted a classic momentum (CM) algorithm [30]. With the momentum and learning rate set as \(\mu\) and \(\varepsilon\), the updating of \(\mathbf{\theta}\) is formed using:  
\[\begin{split}\Delta\mathbf{\theta}\leftarrow\mu\cdot\Delta\mathbf{ \theta}-\varepsilon\cdot\Big{(}\
abla_{\mathbf{\theta}}\widetilde{\mathcal{L}} \Big{)}_{clipped}\\ \mathbf{\theta}\leftarrow\mathbf{\theta}+\Delta\mathbf{\theta}\end{split} \tag{11}\]
# Three-Dimensional Imaging of Metallic Grain by Stacking the Microscopic Images
## 5 Conclusions  
Three-dimensional imaging of metallic grain by stacking the microscopic images was successfully applied to obtain 3D grain volume from processed 2D images. This method can be applied as a useful tool for the characterization of metal grains. It is ready to be used in industrial steel applications. It has been pointed out that the method presented here allows quick and easy use. Furthermore, it does not require many experimental resources.  
An efficient technique to avoid positional errors in image piling has been established. Owing to the size of a wide number of nodes, an alternate method was adopted and presented without jeopardizing the precision of the results.  
The research finding confirmed that the 3D imaging technique would be suitable for the mechanical properties and also very interesting and promising for studying the visualization of 3D magnetic domains, which is the next step of this research.  
Algorithms and experimental techniques are constantly being refined to further improve and enhance the reliability and efficiency of the desired 3D microstructures.  
Conceptualization, J.L.; methodology, J.L., A.B. and Y.-H.H.; software, A.B., J.L. and D.W.; validation, A.B. and J.L.; formal analysis, A.B., J.L. and Y.-H.H.; investigation, J.L. and A.B.; resources, J.L. and D.W.; data curation, J.L., A.B. and D.W.; writing--original draft preparation, [PERSON] and [PERSON]; writing--review and editing, [PERSON] and [PERSON]; visualization, [PERSON] and [PERSON]; supervision, [PERSON]; project administration, [PERSON]; funding acquisition, J.L. This paper was prepared with the contributions of all authors. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.NRF-2019R1A2C2006064).
## 2 Results and Discussion
### Catalytic Performance of Nb/HMS and Nb/MCS Catalysts
#### 2.2.3 Catalyst Reusability  
Hydrothermal stability of catalytic materials is of great importance for successful development of heterogeneously catalyzed conversion of biomass-derived carbohydrates to value-added chemical products in aqueous solution. Herein, we verified the stability of 10-Nb/MCS as the suitable catalyst in the HMF synthesis from glucose via a reusability study. After thoroughly washing with deionized water and THF, the spent 10-Nb/MCS was calcined at 550 \({}^{\circ}\)C for 5 h under Ar flow prior to reuse in the glucose conversion. The reaction was operated under the suitable conditions as described in the previous sections. The reusability of this catalyst is shown in Figure 8. It can be seen that no significant loss of glucose conversion, and the HMF yield of \(>\)57% retained in five repetitive uses. Moreover, the humins yield was insignificantly changed. Nb\({}_{2}\)O\({}_{5}\) is an acidic oxide with excellent hydrothermal stability in the aqueous-phase reaction systems [11; 12; 13]. The carbon moieties dispersed in the MCS nanocomposites offered hydrophobic properties [23], and so retarded the adsorption of H\({}_{2}\)O on the catalyst surface. The overall results indicated that 10-Nb/MCS not only had good catalytic activity, but also high hydrothermal stability, in the selective synthesis of HMF from an aqueous glucose solution.
# Caching Placement Optimization Strategy Based on Comprehensive Utility in Edge Computing
## 4 The Cache Placement Optimization Algorithm Based on Improved Tabu Search in Edge Computing  
To solve the comprehensive-utility-based cache placement problem, the initial allocation scheme of data blocks was first obtained with the replacement-rate-based cache placement strategy. Subsequently, an optimization approach for cache placement based on an improved tabu search algorithm was implemented to further refine the initial solution.  
The Cache Placement Strategy Based on the Replacement Rate to Find the Initial Solution of the Placement  
The initial cache placement solution was determined using a strategy based on the replacement rate. The specific solution procedure is as follows:  
1. The set of data blocks for caching is \(F(n)=\left\{f_{i}|i=1,2,\ldots,n\right\}\) and the collection of edge servers is \(E(m)=\left\{e_{j}|j=1,2,\ldots,m\right\}\).
2. The data block value \(Pop_{i}*re_{i}\) is calculated and then sequenced, \(Epospet\); the server replacement rate \(Rep_{j}\) is calculated and arranged in the composition \(Repset\).
3. Each data block is accessed sequentially, starting with the data block where no server is placed, and representing this set as: \(F(n)\).
4. The span of a data block is determined by considering its current prevalence and the remaining validity ratio, which is expressed as follows: \[span=\frac{Pop_{i}*re_{i}-\minPop_{i}*re_{i}}{\maxPop_{i}*re_{i}-\min Pop_{i}*re_{ i}}\] (23)
5. The span of the data block obtained in step 4 is used to calculate the server replacement rate for that data block placement, which can be shown as: \[rep=span*\left(\maxRep_{j}-\minRep_{j}\right)+\minRep_{j}\] (24)
6. The resulting server replacement rate \(rep\) is compared to the replacement rate set \(Repset\) to place the data blocks into the appropriate servers.  
The correspondence can be defined as \(P:f(\left(f_{1},f_{2},\ldots,f_{n}\right))=\left(e_{i},e_{j},\ldots,e_{k}\right)\). Among them, \(\left(f_{1},f_{2},\ldots,f_{n}\right)\) denotes the data block to be cached and \(\left(e_{i},e_{j},\ldots,e_{k}\right)\) represents the corresponding server where the data block is placed.
# An Efficient Multi-Lane SpaceFibre Core for Spacecraft Data-Handling Networks
###### Abstract  
As one of the key technologies in spacecraft data-handling networks mounting high-resolution payloads, the multi-lane native SpaceFibre standard is designed to meet the demands for the high-speed and reliable interconnections between satellite payloads. A few studies are about the implementations of a multi-lane SpaceFibre core. Even though they exhibit good performance, several limitations still, more or less, exist. We detail an efficient multi-lane SpaceFibre (E-ML-SpFi) core for high-rate and fault-tolerant data communication. The E-ML-SpFi core exploits a hierarchical method to decouple the complex control logic of the retransmission mechanism. The core employs a modified word re-ordering block to map an extended set of words on a real-time variable number of data-ending lanes. Meanwhile, the core introduces the architecture of a fast alignment subsystem to accelerate the alignment process. A hardware implementation on XC7Z100 FPGA shows that the E-ML-SpFi core has complete functionality stipulated by the standard and requires limited resources, with 6290 (2.26%) LUTs and 8252 (1.49%) FFs. The maximum operating frequency of the core is 200 MHz. Moreover, the recovery time is reduced up to 30.9% compared with previous work. Therefore, the core provides a valid solution for future interconnection networks onboard spacecraft.  
SpaceFibre; multi-lane; fault-tolerant control; hardware architecture; system on chip; FPGAs; data-handling network +
Footnote †: journal: Electronics
## 2 Materials and Methods
### Determination of the Actual Phytoextraction Rate  
Every year (2015 to 2018), the amount of each element extracted by willlow and poplar plants was determined following a standard protocol. Firstly, at the end of each growing season, we assessed the total fresh weights of stem and leaves on five randomly selected plants per plot. Subsamples of each plant were oven dried (to constant weight) at 80 \({}^{\circ}\)C and the dry biomass used to determine the water content. The yield was adjusted considering the initial and actual planting density. The biomass yield was expressed as (oven dried) Mg ha\({}^{-1}\) year\({}^{-1}\). Five 0.5 g samples of oven-dried ground biomass per plot were mineralized in a Teflon beaker with 10 mL of HNO\({}_{3}\) and 3 mL of H\({}_{2}\)O\({}_{2}\) in a Mars6 Xpress microwave system (CEM(r) Matthews, NC, USA) using the following settings: power level of 1600 W applied at 100%; ramp of 15:00 min to reach 200 \({}^{\circ}\)C; held at 200 \({}^{\circ}\)C for 15:00 min. The final solution volume of 25 mL was obtained by adding ultrapure demineralized water (resistivity \(\leq\) 18 M\(\Omega\) cm\({}^{-1}\)), and the diluted extracts were analyzed for TE (i.e., Cd, Cu, Ni, Pb, Zn) concentrations by means of inductively coupled plasma-optical emission spectrometry (ICP-OES) (Thermo Scientific(tm) iCAP(tm) 7400). We used a certified reference material (CRM) of ryegrass (ERM(r)--CD281 RYE GRASS, European Commission, Joint Research Centre, Institute for Reference Materials and Measurements, Belgium) for method validation and assurance purposes. The phytoextraction rates for each metal were calculated as follows:  
\[\text{TE}_{\text{x}}\;\text{photoextraction}\;\text{(g}\;\text{ha}^{-1}\;\text{yr}^{ -1})=\text{[TE}_{\text{x}}\;\text{]}\;\text{(mg}\;\text{kg}^{-1})\cdot\text{ Biomass yield}\;\text{(Mg}\;\text{ha}^{-1}\;\text{yr}^{-1}) \tag{1}\]  
where [TE\({}_{\text{x}}\)] is the concentration of the element (x) in the plant biomass and Biomass yield is the oven-dried annual aboveground plant biomass.
## 3 Experiment Results and Discussion
### Autofocus Results  
The image sources are the NVG images introduced in the description of the tested images section. According to the process introduced in the autofocus using sparse matrix section, an experiment was performed and Equation (9) was carried out for computing. The statistical result was as shown in in Figure 19a. The lowest point was the frame with the best sharpness. In the example, the 96 th frame was the sharpest frame. The image in this frame is Figure 19c. In order to compare the accuracy of the sharpness in this study, Figure 19b was the same source image. The normalized gray-level variance sharpness method proved that the autofocusing application of NVG was effective. According to the calculation result using the normalized gray-level variance sharpness method, the 96 th frame was also the one with the best sharpness. Figure 19d is the image in the vicinity of the sharpest point. Compared to Figure 19c, the 90 th frame showed obvious differences, proving the robustness of the method in this study and the normalized gray-level variance sharpness method. The method in this study featured the advantages of simple and easy-to-understand computing. In Equation (9), only the sum of the sparse matrices corresponding to the respective images needed to be computed, and the least value was sought as the best sharpness point. This part also validated the concept that \"the corresponding frame information in the sparse matrix serves as a reference for sharpness\" proposed in the autofocus using sparse matrix section.  
Figure 18: The fusion result of the NVG image (63 and 96 degrees).