esa-sceva/satcom-chunk-collection huggingface dataset:
# Deploying Secure Distributed Systems: Comparative Analysis of GNS3 and SEED Internet Emulator
## 6 Results and Evaluation
### Latency and Jitter
#### 6.2.1 GNS3 Network  
Table 4 presents the results based on the internal communication paths of the GNS3 platform. The paths chosen were to reflect and observe a variety of distances between the nodes in the network.  
The average latency results were around 20 ms for all variations of node communication, which can be observed in Table 5. In the study by [PERSON] et al. [51], the OSPF  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Nodes** & **Min Hops** & **Max** & **Min** & **Avg** & **StdDev** & **Median** & **Jitter** \\ \hline R1-R2 & 1 & 119.00 & 13.00 & 41.45 & 21.39 & 35.00 & 16.99 \\ R1-R3 & 2 & 183.00 & 26.00 & 70.39 & 32.79 & 66.00 & 24.97 \\ R3-R2 & 1 & 134.00 & 15.00 & 52.75 & 23.62 & 50.00 & 29.73 \\ R3-R6 & 2 & 132.00 & 21.00 & 59.55 & 24.65 & 54.50 & 19.41 \\ R1-R6 & 1 & 127.00 & 16.00 & 48.22 & 21.24 & 44.00 & 15.86 \\ R2-R5 & 2 & 138.00 & 18.00 & 55.97 & 23.54 & 48.50 & 17.94 \\ R4-R5 & 1 & 150.00 & 15.00 & 49.62 & 28.73 & 43.00 & 20.57 \\ R4-R6 & 2 & 147.00 & 9.00 & 50.17 & 27.62 & 42.00 & 20.65 \\ R6-R1 & 1 & 155.00 & 10.00 & 49.88 & 27.01 & 45.50 & 20.10 \\ \hline \hline \end{tabular}
\end{table}
Table 4: GNS3 Latency and Jitter (ms).  
Figure 4: Bandwidth and Throughput Comparison.  
Figure 5: Latency and Jitter Comparison (6 Hops).  
protocol produced the minimum value for packet loss in their emulated (GNS3) network compared to a variety of other routing protocols. The results in our emulated (GNS3) model were acceptable for network delay. In the study by [PERSON] et al. [52], similar experiments were performed in our paper, measuring against the same criteria. They found that the issues in communication based on the link state can be mitigated by using the OpenDaylight controller instead of OSPF to remove reliance on link state principles as the result of a link failure. Moreover, [PERSON] et al. [53] conducted performance evaluation tests in GNS3 similar to the one conveyed in this paper. Their results concluded that OSPF, compared to other interior gateway protocols such as the Routing Information Protocol (RIP), EIGRP, and iBGP, had the minimum amount of latency while having the maximum amount of latency; in the study, they used eight nodes--a similar quantity to our study. Different network protocols can produce different results in performance [54]. Compared to the RIP and OSPF, the EIGRP demonstrated the minimum delay time for the most-effective communication.
## 4 Verification and Testing
### Partial Shading  
Firstly, the partial shading conditions are set as shown in Figure 12a, where one part of the PV module is shaded whereas the other part is fully exposed to irradiation. Real-time working environment data for the PV modules with the angle of 30\({}^{\circ}\) were collected on a sunny day (on 15 June 2020). The average irradiance is 549 W/m\({}^{2}\). In the experiment, the freestanding cardboards are used to create shadows of different area on the surface of the PV modules. In condition 1, the same area of cardboards on the surface of modules M1 and M2 are used to shade the assembly from different directions which cover a substring horizontally and three substrings vertically. Due to the large shadow area, the shaded solar cells are bypassed and no longer work. It caused the substring where the shaded solar cells are located to be bypassed by the diode in the junction box. It was specially noted that the sensors in junction box operate on a voltage of 10-45 V. When the operating voltage of the shaded PV module is less than 10 V, the sensor delivers a voltage value of 0 V and a temperature of \(-\)273.15 \({}^{\circ}\)C. Therefore, the \(PI\_{\Delta V}\) is 1, whereas the \(PI\_{\Delta I}\) is higher than normal due to the temperature value of \(-\)273.15 \({}^{\circ}\)C. In condition 2, when the shading of module M1 was removed and the shading area of module M2 turns to be smaller. \(PI\_{\Delta I}\) of both modules returns to the normal value. However, \(PI\_{\Delta V}\) changes from 1 to 0.5 because the substring with the shaded solar cells is bypassed and the voltage of the entire PV module is reduced by one third. In the final condition 3, When M1 is re-shaded by the same shadow area of M2, the results of \(PI\_{\Delta I}\) and \(PI\_{\Delta V}\) are obtained to be the same as M2.  
Figure 11: Performance indicators of faultless operation: (**a**) performance indicator in current; (**b**) performance indicator in voltage.
## 3 Survey Results
### Deployment State and Attributes
Therefore, it is important to support fast prototyping and effective debugging mechanisms for these phases. Despite theoretical assumptions about huge networks consisting of thousands of nodes, only a few deployments contain more than 100 nodes. Eighty percent of listed deployments contain 50 or less nodes, 34%: less than 10 nodes (Figure 1). It seems that the most active period of large-scale WSN deployment has been experienced in the years 2004-2006, with networks consisting of 100 and more nodes (Figure 2). Another theoretical assumption, which is only partially true, is a heterogeneous network. The majority of deployments are built on homogenous networks with equal nodes: 70% of deployments. However, significant amount of deployments contain heterogeneous nodes, and that must be taken into account in remote reprogramming design. Remote reprogramming is essential, as it is very time-intensive and difficult to program even more than five nodes. Additionally, often, nodes need many reprogramming iterations after initial setup at the deployment site. Users must be able to select subsets of network nodes to reprogram. Different node hardware must be supported in a single network. Figure 1: **Distribution function of note count in surveyed deployments—Eighty percent of deployments contain less than 50 motes; 50%: less than 20 motes; and 34%: ten or less. **  
Although remote reprogramming is a low-level function, it can be considered as a debug phase feature, and external tools, such as QDiff [57], can be used to offload this responsibility from the operating system. Almost all (95%) networks have a sink node or base station, collecting the data. A significant part of deployments use multiple sinks. _Design rule 2_:  
Sink-oriented protocols must be provided and, optionally, multiple sink support. Almost half of deployments use a regular more connected to a PC (usually a laptop) as a base station hardware solution. _Design rule 3_:  
The OS toolset must include a default solution for base station application, which is easily extensible to user specific needs.
## 3 More Recent Technology: Non-Thermal Plasma
### Applications of Plasma Purification  
There are several different techniques used to generate plasma. Popular techniques include gliding (glow) arc plasma (GAP), dielectric barrier discharge (DBD) and pulsed corona discharge (PCD). In a DBD, the electrical discharge is facilitated by the presence of two electrodes with one covered by a thin dielectric material and the application of a high voltage [36]. In the gas phase, the carrier gas will be broken down to generate active species and highly oxidative/reactive agents after further reactions, which are all useful in the degradation of contaminants. In the GAP, the plasma discharge is produced at a high working voltage by two or more diverging metallic electrodes placed in the gas flow direction [37]. In a PCD, the discharge is generated when high voltage pulsed power is applied on sharp-pointed electrode tips (the high voltage electrode) and a working gas introduced in the electric field of the sharp electrode tips, generating a group of active species. The chemical characteristics of the oxidative species produced in each of the plasma discharges are dependent on the gas type (or composition), because sometimes a mixture of gasses is applied rather than a single gas type.  
Due to the variety of plasma technologies, intensive research is being performed to determine the advantages that each type holds over the other. At present, DBD is one of the more energy-efficient plasma reactors [38]. [PERSON] et al. [39] recounted the application of plasma technology to degrade different types of pollutants including dyes, organic compounds such as phenol, pesticides, emerging contaminants and pathogenic microorganisms. The authors further discussed the synergistic effect from the plasma with complementally processes such as catalysis, achieved through the increase in the production of reactive species, resulting in enhanced process performance.  
However, many such studies have been conducted at laboratory scale involving small volumes of water and pollutant concentrations in more controlled environments.  
The wide-scale implementation of plasma water purifiers has yet to be achieved. In our pragmatic line of thought and reality, the industrial scale plasma systems developed employ less complicated plasma degradation processes. The manufacturers are building small-scale reactors that display the benefits of this nascent technology [8].
## 4 Application of HSI and AI in the Food Industry  
Food in the industry exists in solid and liquid phases. These different phases have specific characteristics with each phase having its own problems in relation to the assessment of quality and safety. Solid foods often undergo spoilage through physical, chemical, and microbiological processes, necessitating rigorous quality management practices such as proper storage and handling to mitigate deterioration. On the other hand, liquid foods are more susceptible to microbial contamination, requiring proper evaluation of their quality parameters to prevent them from spoilage [149]. With the development of HSI integrated with AI, a more accurate and comprehensive analysis is enabled across these phases. HSI detects spatial and chemical properties of solid products, such as grains, fruits, meat, and liquid products, like juices and oils, and boosts AI models in the enhancement of classification and identification of defects. In addition, this supports the lacunars for the real-time monitoring not only of chemical composition but also of contaminant detection, making it a suitable fit through which real-time quality control could be effective for all states of food.
## 4 Communication Architecture
### Modeling of Intra-Level Communication Architecture
#### 4.1.3 Level 2 Sensor  
The second level of our architecture consists of multimedia sensors. They are in charge of collecting multimedia data (camera, sound, video) throughout the intelligent city, but they also serve as gateways for the transfer of data from level 1. To minimize delay and respond to alerts, the radio component of these sensors must remain on standby for wake-up messages. During the monitoring phase, the Level 2 sensors can determine the type of data to be transferred. To do this we suggest that they analyze the _msg_ messages received from the CHs in order to decide whether to activate the camera's sensor card, collect environmental data or relay only level 1 data. From an energy point of view, it does not seem desirable at this stage to permanently activate the camera's sensor card. Figure 7 summarizes the modeling of the behavior of level 2 sensors (case of sending an _msg_ message if a person is detected).  
Figure 6: Diagram of activity sequences of clusters at the first level of the architectureThe activity of sensors 2 turns around the multi-stream transfer of data to level 3 (transfer of single data and/or multimedia content). When a message is received from a CH, the level 2 sensor switches to state 2 and checks the detection of movements in its field of vision (recognition by a presence sensor integrated in the _Imote2_). If data from level 1 is received, the level 2 sensor switches to state 3 and adds its own information (merged with the data received from the CH) and transmits it (e.g., takes a picture) to the sink. If no data is received after a defined delay, it returns to state 1. One of the advantages of the layer 2 network is that the sensors provide auxiliary (safety) routes to reach the sink.
## 3 Test Results and Analysis
### Shear Characteristics Analysis
#### 3.1.3 The Influence of Different Undulating Heights  
As can be seen from Figure 5c, the shear stress-shear displacement curve under the influence of different undulating heights can also be divided into four stages. 1 The initial linear stage (OA): In this stage, the shear stress increases linearly with the increase of shear displacement, the slope of the curve is fixed, and the shear stiffness is constant. It shows that the shear stiffness has nothing to do with the height of the jagged teeth. 2 Pre-peak nonlinear stage (AB): This stage starts from the end point of the initial linear stage to the peak point of the curve. At this stage, with the increase of shear displacement, the shear stress increases slowly, the slope of the curve becomes smaller, and the shear stiffness becomes smaller. Furthermore, the shear stiffness is related to the height of relief. The larger the height of the relief is, the larger the shear stiffness is. 3 Post-peak softening stage: Currently, the shear stress reaches its peak, and with the continuous increase of shear displacement, the shear stress begins to decline. Obvious brittle failure is found on the rock discontinuity, and most of this failure first occurs at the root of the near force end of the sawtooth on both sides and is rapidly transmitted to the rest of the sawtooth, accompanied by an obvious brittle sound, which shows the softening of shear stress on the curve. 4 Residual strength stage (CD): With sawtooth failure and shear stress fall, the rock discontinuity still bears a certain shear stress, and the shear stress is mainly provided by the broken sawtooth friction.
# Research on Environmental Vibration Induced by High-Speed Maglev Transportation
## 5 Vibration Propagation and Distribution Laws
### Vibration Attenuation through Surrounding Ground  
While a high-speed maglev train is running, the vibration propagated to the surrounding ground has complex distribution laws in different directions. The vibration magnitude does not monotonically decrease with increasing distance, and the maximum acceleration does not appear at the cross-sectional plane of the column. The traveling wave effects in the maglev environmental vibration problem act as the superposition and interfere with different frequency components, generating several vibration-amplifying zones in the plane. As the complex laws of vibration propagation and attenuation cannot be easily summarized using simple formulas, in this part, a visualization procedure was proposed to make it clearer.  
The 1s RMS value was chosen as the evaluation of each ground test point, and the calculated results are shown in Table 3.  
To visualize the propagation and attenuation laws, a three-dimensional graph of the acceleration distribution across the whole plane is given in Figure 14. The labeled dots are the measured results, and the curved surface is the biharmonic spline interpolation (through the MATLAB(r) 4 grid data algorithm), which makes the surface smooth and continuous, thus making it more realistic.  
The 3D graph above shows the distribution of the whole plane around the maglev line. It is clear that the maximum acceleration occurs at about one-third of the distance away from the guideway column, under the maglev guideway girder, and the minimum acceleration occurs near the middle zone of the plane, where the vibration magnitude does not exceed the human perception threshold. As the distance to the maglev line increases, there is an obvious vibration-amplifying zone caused by the wave superposition, and the vibration magnitude rises with the increase in the distance. If researchers or designers estimate the ground vibration as monotone decreasing in this amplifying zone, they may underestimate the vibration level, and vibration serviceability problems may occur in structures constructed in this zone.  
Figure 13: Empirical formula of vibration propagation in the vertical direction.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Position**} & \multicolumn{1}{c}{\(\mathbf{0}^{\circ}\)} & \multirow{2}{*}{**45\({}^{\circ}\)**} & \multirow{2}{*}{**60\({}^{\circ}\)**} & \multicolumn{1}{c}{\(\mathbf{90}^{\circ}\) (Perpendicular**} \\  & **(Along the Line)** & & & & **to the Line)** \\ \hline
0 m & 45.01 & 45.01 & 61.92 & 45.01 & 45.01 \\
7.5 m & 61.41 & 8.11 & 8.58 & 6.73 & 9.41 \\
10 m & 68.78 & 4.31 & - & 4.77 & 5.71 \\
12.5 m & 50.05 & 4.82 & 14.04 & 9.10 & - \\
15 m & - & 4.87 & - & - & - \\ \hline \end{tabular}
\end{table}
Table 3: One-second RMS value of each test point (mm/s\({}^{2}\)).
## 4 Analysis Results and Discussion of Coupled Multi-Body Dynamics
### Influence of Thermo-Solid Coupling on the Vibration Characteristics of Brake Disc  
The friction contact state of disc brakes is directly impacted by the uneven distribution of temperature and stress, which causes varying degrees of warpage and deformation at different locations. This leads to incomplete contact between the brake disc and brake pad  
Figure 10: Deformation distribution of the brake disc friction surface.  
Figure 9: Deformation distribution of brake disc surface at different braking moments: (**a**) \(t=0.5\) s; (**b**) \(t=30.0\) s; (**c**) \(t=56.6\) s.  
during braking, which causes brake vibration. To further analyze the effect of thermoset coupling on the vibration characteristics of the disc braking system, this paper compares the vibration acceleration signals of the brake model with/without thermoset coupling. Figure 11 shows the axial vibration acceleration of the brake discs obtained from the two different models, and the trends of both were approximately the same.  
The brake disc vibrated continuously when the brake model did not consider the thermo-solid coupling effect. In contrast, the axial vibration acceleration range was reduced from 601 m/s\({}^{2}\) to 497 m/s\({}^{2}\) when the model considered the thermos-solid coupling effect. The variation of the axial vibration amplitude of the brake disc was significantly less than that without considering the frictional heat effect.  
The above results show that the thermo-solid coupling effect had a great influence on the vibration characteristics of the brake disc. This was mainly because, when the thermo-solid coupling was not considered, the work done by the frictional force impeding the movement of the brake disc mainly converted the energy of the disc into the unstable vibration of the brake. However, when the thermo-solid coupling was considered in the model, the work done by the frictional force was not only converted into the unstable vibration of the brake but also converted into heat energy and continuously exchanges heat with the air. The energy released by the brake disc through vibration was reduced. As a result, the axial vibration intensity of the brake disc was reduced. In summary, when researching and analyzing the vibration characteristics of disc brakes, it is necessary to consider the influence of thermo-solid coupling, so as to accurately reflect the vibration characteristics of the brake.
# Multi-Objective Parameter Optimization of Flexible Support System of Optical Mirror
## 4 Experimental Analysis
### Pressure Test of FSS  
The RD determines the pressure resistance of the FSS. When the size parameters of the RD are determined, its hardness plays a decisive role in the rated working pressure of the FSS. In the experiment, install the RDs of different hardness values in the FSS. Then, gradually apply pressure to the upper and lower chambers of the FSS until the RD is damaged by pressure. The highest pressure is then recorded (i.e., the pressure attained when the RD is damaged). The ultimate pressure of the RD at each hardness value collected through repeated tests is shown in Figure 15.  
It can be observed from Figure 15 that when the RD hardness is at least 40 Shore, the ultimate pressure that it can withstand satisfies the requirement of the rated pressure of the FSS (1 MPa). The simulation results of the RD reveal that when the RD hardness is smaller under identical structural parameters, the deformation resistance is smaller. A 45 Shore RD is selected for use in the FSS to minimize the deformation resistance of the RD while  
Figure 14: Experimental prototype of the Flexible support system.  
Figure 15: Relationship between RD hardness and limit working pressure.  
increasing its life. It can be observed from Figures 12 and 13 that, when the deformation of the RD with a hardness of 45 Shore is 1 mm, the deformation resistance of the large and small RDs is 0.5 N and 0.35 N, respectively. At this time, the ultimate pressure that the FSS can withstand is 1.18 MPa.
# A High-Resolution, Wide-Swath SAR Imaging System Based on Tandem SAR Satellites
## 2 Imaging System Based on Tandem SAR Satellites
### Working Mode of the Second Satellite  
The second satellite, which is noted as Sat-2, adopts a new scanning method. It randomly assigns each pulse to one of the subswaths on the ground and receives the reflected echo, as shown in Figure 2.  
Since spaceborne SAR platforms usually work at an altitude of more than 100 km [19], the reflected echoes of transmitted pulses return to the receiver after several pulse intervals (PIs). Because all subswaths share one receiver, the waiting PI number for different subswaths must be the same to avoid overlapping of the received echoes. Assuming that the waiting PI number is \(N_{PI}\), as shown in Figure 3, the reflected echoes of all the subswaths should return to the receiver during the \(N_{PI}+1\)th PI after transmission. To that end, we set the farthest subswath work in broadside mode and the other subswaths in squint mode. The squint angle increases as the distance of subswath to nadir decreases, as shown in Figure 2.  
In the trans-receive view, the time interval of the two transmitted pulses is fixed to \(1/PRF\), while the time interval of the two received pulses of any subswath is not certain, and the average sampling rate is lower than the Nyquist rate. Therefore, the received echoes are downsampled.