esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Establishment of the Simulation Test System and Design of Testing Methods
### Design of the Simulation Testing Plan and Process Simulation  
Based on the simulation testing system previously established, different simulation testing schemes could be achieved by setting and adjusting the operating parameters, such as the support inclination angle and height: the initial states of driving parameters, such as the tamping angle, tamping path, and column path; as well as the target position of the tamping device motion.  
This study simulated the support, dumping, and tamping processes using the column, swing-angle cylinder, and tamping cylinder path as the driving parameters. Before the start of the support process, the initial value of the support height was 2980 mm, the target position was 3550 mm, and the simulation path was \(A_{1}\)-\(A_{2}\). Before starting the tamping process, the initial value of the tamping angle was 9\({}^{\circ}\) and the initial value of the tamping path was 600 mm. By setting the target position points of the tamping process to \(C_{2}\) and \(C_{5}\), the tamping device was controlled by the interface automatic-recognition and damping path automatic-planning algorithm modules, also known as the process action automatic-execution algorithm module, and the simulation path was \(C_{1}\)-\(C_{2}\)-\(C_{3}\)-\(C_{4}\)-\(C_{5}\). After the tamping process was completed, resetting the tamping device to the initial position before the dumping process started to prepare for the next dumping and tamping cycles was necessary. Before the dumping process started, the initial position of the tamping device was \(C_{5}\), the target position point of the tamping device in the dumping process was \(C_{8}\), and the simulation path was \(C_{5}\)-\(C_{6}\)-\(C_{7}\)-\(C_{8}\). The abovementioned simulation results are shown in Figure 15.  
Figure 14: Joint-simulation testing system of SolidWorks and MATLAB/Simulink.  
From Figure 15, it can be seen that the motion path of the tamping device does not reach the optimal path. During the movement process, there was a collision interference with the perforated bottom discharge scraper conveyor. For the \(C_{5}\)-\(C_{6}\) and \(C_{6}\)-\(C_{8}\) segments, the optimal action sequence should first reduce the tamping path and then increase the tamping angle to avoid collision interference. As shown in Figure 5, when the tamping angle reaches the maximum value, it needs to be further increased to trigger the tamping end process, which initiates the dumping interference-recognition part. This process might cause instability in the tamping device motion, leading to interference. Therefore, it was necessary to improve the process action automatic-execution algorithm module. The optimization of the algorithm is shown in the dashed box in Figure 5. The tamping device tamping angle and tamping path reaching the maximum value were used as discriminant markers for the end of the tamping, thus avoiding the abovementioned problems.
## 2 Data and Methods  
### Satellite Data  
In this study, the altimeter SWH data provided by Institut Francais de Recherche pour l'Exploitation de la Mer (IFREMER) from January 1992 to December 2016 (25 years) were utilized [42]. This database is composed of nine altimeters (European Remote Sensing-1 (ERS-1), Topography Experiment/Poseidon (TOPEX/Poseidon), European Remote Sensing-2 (ERS-2), Geosat Follow-On (GFO), Joint Altimetry Satellite Oceanography Network-1 (Jason-1), Environmental Satellite (Envisat), Joint Altimetry Satellite Oceanography Network-2 (Jason-2), Cryosat-2, and Satellite for Argos and Altika (SARAL)) data over the study period, as shown in Table 1. The altimeter SWH data used in this study were quality controlled with along-track data. In addition, to improve accuracy and consistency, corrections of each altimeter SWH data were also performed by [PERSON] and [PERSON] [42] by the comparison of satellite data with in situ measurements or an inter-comparison between altimeter data. In the Northwest Pacific, these altimeter SWH data were validated to be about 0.1 m in terms of bias and 0.3 m in terms of the root-mean-square error (RMSE) [36].  
To investigate if satellite SWH data could be measured near the typhoon center under a condition of severe sea states, we used 10.8 \(\upmu\)m channel infrared images of the Communication, Ocean, and Meteorological Satellite/Meteorological Imager (COMS/MI) for a period from 26 to 27 August 2012. During this period, serval satellite altimeter tracks passed over the typhoon Bolaven in the seas around the Korean Peninsula, and satellite SWHs could be obtained for the typhoon event.
## 3 Network Sliced Distributed Learning
### DL-as-a-Service for IoV Applications  
#### 3.2.1 Proposed Methods  
The IoV scenario considered is implemented through an integrated T/NTN equipped with edge computing platforms. Different networking nodes, such as Road Side Units (RSUs), Low-Altitude Platforms (LAPs), High-Altitude Platforms (HAPs), and Satellite nodes, are distributed throughout the service area. The system is able to take advantage of different DL methods to cope with the requirements of heterogeneous users. Since the scenario considered includes a massive amount of computation, communication, and storage resources distributed over the ground, air, and space networks, these resources can be utilized to create an intelligent VN through proper deployment of required DL methods, where each network device is able to host the virtual functions enabling the different DL execution. In such a system, a slice-based approach is considered, where each slice is a logical entity that enables the interconnection of different functions to build a specific DL method.  
Without loss of generality, in Figure 1, four DL methods implemented in the form of slices are represented. The first slice aims to deliver an FL service performed on different layers of edge devices. In particular, end devices have their datasets to perform the learning process. For this, the DAF, DPrF, and DLF functions are deployed on a VU layer to enable the learning process. The learned parameters are then transmitted to nearby edge nodes (i.e., RSUs) through DPsF, limiting communication costs. The RSU node then collects the data from the VUs and performs the aggregation operations, for which DCF and GMUF are placed over it. The GMUF results are then transferred to the upper layer, where appropriate functions are present. The second slice aims to deliver DL with collaborative learning frameworks. The learning part is performed collaboratively over the user devices, and appropriate learning functions are placed over the VUs cloud. The upper layers are used to create a generalized global model by aggregating the local models. The third slice is for the case of split learning, where a data parallelization technique is adapted to split the learning process over the device and edge layers. Thus, learning functions are implemented both on the device and on the edge layer. Additionally, the HAP layer is used to create a global model. For latency-critical applications, a transfer learning-based DL slice can be considered, where past learning experiences are integrated into current learning cycles to limit the learning process costs. The learning process is distributed over different edge layers.  
Figure 2 shows a more detailed view of the DLaaS concept, where the virtual learning functions of a single slice are reported. A multi-layer FL is considered representative, involving data collection and learning at the VU nodes, local/intermediate model updates collections and processing, i.e., averaging at the intermediate layers of RSUs, LAPs, HAPs, satellites, and model inference operation at VUs.
# A Large Area Pixelated Silicon Array Detector for Independent Transit In Vivo Dosimetry
## 4 Discussion  
The MP987 has shown to be suitable for performing a wide variety of phantom dosimetry measurements. The results not only demonstrate the dosimetric characteristics of the detector but the capability of the custom DAQ to perform real-time readout on a pulse-by-pulse basis for close to 1000 channels. Measurements carried out in phantom proved that most of the limitations from the previous generation of diodes adopted in the \"Magic Plate\" detector, associated with dose per pulse dependence and stability with radiation damage, are negligible in the new MP987 diodes. The reduction in these effects brings the technology closer towards a correction free in vivo dosimetry solution. Additionally, it has been demonstrated that MP987 is uniquely suited to the intended application of transit dosimetry. When a homogeneous phantom is used as the target, measured and predicted dose at the EPID level for field sizes between 3 \(\times\) 3 and 10 \(\times\) 10 cm\({}^{2}\) agreed within error. While correction factors may be required for larger field sizes, the discrepancy remains within 3% for field sizes up to 20 \(\times\) 20 cm\({}^{2}\). In the first pre-clinical test pass rates for absolute dose gamma analysis of the four segments of a step and shoot IMRT plan showed between 94.2% and 97.4% pass fractions with a 5%/5 mm criteria. While this collapsed IMRT study is not a comprehensive assessment of multiple patient plans on a truly anthropomorphic phantom, it is still considered by the authors to be a significant result that will motive future in vivo dosimetry studies with the MP987.  
The spatial resolution of MP987 may be too sparse for beamlets with their penumbra falling in the peripheral area of the detector. The high sensitivity of the diodes and the real-time multichannel electrometer performing pulse by pulse acquisition makes the detector uniquely suited to perform analysis at each control point of the delivery. Future developments of the MP987 include the mechanical setup to secure the system above the EPID without triggering the collision sensor and allowing the rotation of the linac's gantry and allow delivery in clinical settings.  
A potential additional application of the MP987 system is in high dose rate (HDR) brachytherapy source tracking. The compact mechanical setup, the large area and the high sensitivity make it uniquely suitable for this application. Therefore, both a fully integrated dual detector for in vivo dosimetry in external beam radiotherapy and HDR brachytherapy source tracking will be the subject of future work with the MP987.
# Minimizing the Number of Distrustful Nodes on the Path of IP Packet Transmission
## 3 Results and Discussion
### Scenario B, with Several Distrustful Nodes in a Small Network  
Let two more nodes (D and F) in the network of Figure 2 be replaced by distrustful ones. The network now looks as is shown in Figure 6 and there are no paths from node A to nodes G, H, and I through trust nodes only.  
Figure 5: Fragments of routing tables: on the left for the classic Dijkstra algorithm, on the right for the modified one, the changed paths are circled in red.  
Figure 6: Network topology with several distrustful nodes.  
Figure 7 illustrates the shortest path tree for node A of this network, built on the classic Dijkstra algorithm.  
This tree has two branches--one uses one transit distrustful node, E, but the other includes two such nodes, D and F, which are on the way to node G.  
For comparison, we will build the shortest path tree according to the modified algorithm. The path to each node should contain the smallest amount of distrustful transit nodes and, at the same time, have a minimum possible weight. The result of the program is shown in Figure 8.  
As we can see, in the tree built according to the modified algorithm, there is a path to any node through no more than one distrustful transit node. This is node E on the way to nodes G, H, and I, and node D on the way to F. So, in this way, we demonstrated the achievement of minimizing the number of transit distrustful nodes on the way to the addressees.  
After the appearance of distrustful nodes D, E, and F in the network (Figure 9), let us examine how the routing table for Node A has changed.  
Figure 8: The shortest path tree for the network with multiple distrustful nodes, according to the modified Dijkstra algorithm.  
Figure 7: The shortest path tree for the network with multiple distrustful nodes, according to the classical Dijkstra algorithm.  
As can be seen from Figure 9, the gateway for router G has been changed from C to B. As a result, the metric and path have become longer. This change occurred because there were two distrustful nodes (D and F) on the way to node G and, after the change, there was only one distrustful node, which is E.  
So, the comparison of the shortest path trees and routing tables constructed using the classical and modified algorithms illustrates the effectiveness of the modified algorithm, according to the criterion of minimizing the number of distrustful transit nodes.  
To more clearly demonstrate the advantages of the proposed approach, three more examples of network topologies with an increased number of nodes are given below.
## 3 Results and Discussion
### Lipid and Protein Oxidation  
Lipid oxidation was measured by thiobarbituric acid-reactive substances (TBARs) analysis, which determines the content of secondary lipid oxidation products responsible of the meat off-flavors. TBARs values increased over the storage time in all burger types (Table 3).  
Figure 2: Total phenol content (Folin index) and radical scavenging activity determined by DPPH and ABTS methods of deer burgers after 12 days of chilled storage. C: sodium ascorbate control; Lva: 2.5% “verdejo” lees; Lvb: 5% “verdejo” lees; Lpa: 2.5% “palomino” lees; Lpb: 5% “palomino” lees; DM: dry matter. Different lowercase letters appearing in the same method for determining antioxidant activity (a–d) and Folin index (z–x) indicate significant differences (\(p<0.05\)) between samples.  
This rise was also observed in other studies with pork and beef burgers [13; 30], and it reveals the instability of minced products even though they are stored in MAP conditions. Control samples presented the greater increase, reaching the highest values at days 8 and 12. Therefore, the wine lees prevented lipid oxidation, mainly after four days of storage, being more effective than sodium ascorbate. This property could be due to their high phenolic content and scavenging activity (Figure 2), which was also observed by other authors in ice creams [12]. TBARs values in control samples after eight days of storage (7.39 mg MDA/kg) exceeded 5 mg MDA/kg, concentration established as acceptability limit from a sensorial point of view [31]. However, samples with lees did not reach this limit concentration during storage, showing a maximum value of 4.06 mg MDA/kg (Lpa).  
Carbonyls are one of the main products of oxidized proteins and they have been widely used as indicators of protein oxidation in food and biological systems [32]. Table 3 shows the results of protein oxidation in deer burgers. All samples showed a significant increase of hydrazones over time, mainly between days 4 and 8. The use of wine lees significantly decreased the carbonyl content only at the beginning of storage. Other authors also reported a significant reduction of protein oxidation employing oenological by-products such as wine pomace in different meat products [23; 33]. This protective effect was in agreement with TBARs values, showing the link between lipid and protein oxidation [34].  
No effect was observed due to the concentration or type of lees used, despite the higher content of phenolic compounds in \"palomino\" lees (Table 1).
# A Reliable Scheme for Synchronizing Multimedia Data Streams under Multicasting Environment
## 3 Problem Statement
### Use Case 1  
The first use case is if a user would like to play audio and video on different devices, e.g., audio in headset and video on the TV. Both audio and video should be played-out synchronously regardless of the fact that they are being played out on different devices. The scenario is shown below in Figure 3a.
## 3 Result and Discussion
### Quantitative Analysis of Methanol in Gasoline
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \multirow{2}{*}{**Model**} & **Variable** & **Number of** & \multirow{2}{*}{**LVS**} & \multicolumn{2}{c}{**Calibration Set**} & \multicolumn{2}{c}{**Prediction Set**} \\ \cline{4-9}  & **Selection** & & & \(\mathbf{R^{2}}_{\mathbf{c}}\) & **RMSEC** & \(\mathbf{R^{2}}_{\mathbf{p}}\) & **RMSEP** & **RPD** & **ABS** \\ \hline PLSR & / & 1762 & 15 & 0.998 & 0.405 & 0.968 & 1.658 & 6.124 & 1.253 \\ LS-SVM & / & 1762 & / & 0.998 & 0.395 & 0.968 & 1.661 & 5.886 & 1.266 \\ PLSR & CARS & 48 & 11 & 0.97 & 0.426 & 0.969 & 1.597 & 6.563 & 1.171 \\ LS-SVM & CARS & 48 & / & 0.998 & 0.404 & 0.968 & 1.636 & 6.373 & 1.232 \\ PLSR & UVE & 479 & 10 & 0.994 & 0.699 & 0.972 & 1.545 & 6.420 & 0.847 \\ LS-SVM & UVE & 479 & / & 0.998 & 0.395 & 0.964 & 1.742 & 5.555 & 1.347 \\ \hline \end{tabular} Note: PLSR: partial least squared regression; LS-SVM: least square-support vector machine; CARS: competitive adaptive reweighted sampling; UVE: uninformative variable elimination; IVS: latent variables; R\({}^{2}\): determination coefficient; RMSE: root mean squared errors; RPD: residual predictive deviation; ABS: the absolute difference between RMSEC and RMSEP.  
\end{table} 
Table 1: Quantitative analysis results of methanol content in gasoline based on multivariate model. Figure 4: Scatter plot of actual values versus predicted values in the prediction set by successive projections algorithm- partial least square (UVE-PLS) model.
## 2 Materials and Methods
### Physicochemical and Sensory Quality Determination  
The physicochemical quality analyses were carried out on each sampling day. Bell peppers were weighed (g) using a FH-2000 scale (GRAM, Barcelona, Spain). Weight losses (%) were calculated by using the next formula: ((Initial Weight\(-\)Final Weight)/Initial Weight) \(\times\) 100. Thickness and longitudinal and equatorial calibre were initially measured using a digital calliper (Mitutoyo, Neuss, Germany), expressing the results in mm. Colour was determined using a Konica Minolta CR-400 colorimeter (Tokyo, Kanto, Japan). Measurements were recorded using the CIELab system (L*, a*, and b* coordinates). Total colour differences (\(\Delta\)E) throughout the shelf life were compared to their respective initial values according to equations previously described by [PERSON] et al. (2017). A texturometer (Brookfield, CT3-4500, Toronto, ON, Canada) was used to test firmness at room temperature (RT) with a cylinder of 8 mm diameter and a surface area of 2.01 cm\({}^{2}\) and compressing the fruit by 5 mm at a contact speed of 2 mm s\({}^{-1}\), expressing these results in newtons (N).  
After that, bell peppers were cut and blended using a Robot Coupe J80 Ultra (Vincentes, Ile-de-France, France). The total soluble solids content (TSS), pH, and titratable acidity (TA) of the obtained pepper juice were determined. TSS were measured by a digital handheld refracometer (Atago N1; Tokyo, Kanto, Japan) and expressed as %. A pH meter (GLP21, Crison; Allella, Cataluria, Spain) was used to determine the pH while TA was determined by titration of 5 mL of pepper juice plus 45 mL of distilled water with 0.1 M NaOH to pH 8.1 (T50, Metter Toledo; Milan, Lombardia, Italy) and expressed as mg citric acid 100 mL\({}^{-1}\).  
Each sample was analysed in quintplicate on each sampling day per treatment, and 5 bell peppers formed a replicate (\(n=25\)). After the physicochemical analyses were performed, three replicates of 5 juiced peppers each per treatment were frozen in liquid nitrogen for every sampling time and stored at \(-80\)\({}^{\circ}\)C. Frozen samples were ground to fine powder prior to analyses using liquid N\({}_{2}\) with a mincer (IKA, A 11 basic, Berlin, Germany) at 12,700 g for 10 s.  
The characterization was completed with a sensory evaluation each sampling day. The tasting room was air-conditioned and free of disturbing factors. Bell peppers were cut into 1 \(\times\) 5 mm pieces. Ten panellists were trained following the ISO guide ([PERSON], 2018). Samples were coded with three random digits and were presented individually to the panellists. Mineral water was provided for mouth rinsing between samples. The attributes measured for the colour, odour, and taste characteristics were 'Dehydration', 'Visual appearance', 'Colour (green/mature)', 'Odour', 'Firmness (touch, when slightly compressing with the fingers)'. 'Firmness (mouth, when eating)', and 'Flavour'. Overall acceptability was measured by a panel of 30 consumers. A hedonic scale in intensity from 1 to 5 was used, being 1 'Extremely bad', 2 'Bad'; 3 'Limit of commercialization', 4 'Good', and 5 'Excellent'.
# Radiation Hardened Read-Stability and Speed Enhanced SRAM for Space Applications
## 2 Proposed RHRSE-20T SRAM
### Single Node Upset Recovery Analysis
#### 2.5.4 Single Event Transient Occurs at Node S1  
S1 changes from '1' to '0'. This deactivates transistor N1 and activates P5 but does not affect the values stored in the other nodes. Transistor N2 is activated by node S3, and P2 is activated by node S2 while N3 is deactivated. Consequently, S1 recovers from '0' to '1'. Through this process, all nodes are restored to their original states.
###### Abstract  
The goal of this study was to develop an impact-echo device that can conduct automatic oscillation tests, process signals rapidly, and apply it to concrete object anomaly analysis. The system presented in this study comprises three parts, namely the impact device, the oscillator circuit, and signal processing software. The design concept of the impact-echo device was inspired by a pendulum clock, and its implementation used a nondestructive wooden hammer instead of a conventional manual steel hammer. In this study, we used a pulse generator in the adjustable oscillator circuit to produce delayed changes. The delayed changes would activate the wooden hammer that struck the surface of the object. To process the signal, our lab used a built-in sound card in the computer to transfer the reflection soundwave from striking the wall to MATLAB software to analyze the energy of the frequency spectrum. This was conducted to evaluate whether the object contained anomalies and, if so, to determine the location of the anomalies to serve as a reference for real-life implementation.  
Keywords:nondestructive; impact-echo device; concrete object; adjustable automatic oscillator; signal acquisition +
Footnote †: journal: Applied Sciences
## 3 Results
### Influence of the Atmospheric Stability on Wind Speed Gradients
#### 3.7.1 \"Undisturbed\" Horizontal Wind Speed Gradients
The major difference is found for the stable cases with maximum values of about 80% and 40%, respectively. One can also see that the stability of the stable cases is in fact slightly higher for the easterly wind directions. The wind speeds near the land in stable conditions are about 40% lower for easterly winds and the sea surface roughness, therefore smaller in the initial phase of sea-state development. Furthermore, the drag coefficient relating wind speed at 10 m height to friction velocity decreases with stability [55]. The fact that the drag coefficient is lower for stable conditions also indicates that the observed larger increase for easterly winds in neutral conditions is not an artefact of the SAR wind measurements, because one would expect a bias towards lower wind speeds in those conditions [56].