esa-sceva/satcom-chunk-collection huggingface dataset:
# SVDC: Synchronous Update with the Division and Combination of SRv6 Policy
## 5 Performance Evaluation
### Result and Analysis
#### 5.2.4 Timeliness Cost of SUDC  
We define the timeliness cost of SUDC as the time that the router receiving the first policy distribution SID block must wait. In SUDC, some nodes need to wait for some time before updating their flow tables, even though these nodes have received all the policy distribution SID blocks that they should have received. That is the timeliness cost that certain nodes need to pay under the SUDC scheme. Under the definition of timeliness cost, the time that all routers need to wait is usually less than or equal to this metric. Table 6 and Figure 8 present the variation of timeliness cost for different test set sizes. It can be observed that the growth of timeliness cost slows down as the test set size grows.
# Use of SAR and Optical Time Series for Tropical Forest Disturbance Mapping
## 2 Material and Methods
### Main Processing
#### Evaluation Concept for FNF Mapping  
The evaluation of the FNF maps is based on systematic random sampling points [78] that were visually interpreted in VHR image chips (see Figure 5, example of Peru). The VHR image chips were ordered based on a pre-defined systematic sampling grid. Within each grid cell a random sampling was applied. We additionally derived inclusion probabilities and area estimates from the final forest/non-forest classifications since the VHR image chips do not cover the entire mapped area. Tables A1 and A2 provide the confusion matrices for Peru including all accuracy measures (overall, user, and producer accuracy; confidence levels).
# Evaluation of VoIP QoS Performance in Wireless Mesh Networks
## 4 Results and Analysis
### Platoon  
In this scenario, a platoon with 31 military personnel is considered in a line deployment in a terrain size of 400 \(\times\) 600 m, as shown in Figure 13. This main scenario is experimented under six sub-scenarios. The nodes are configured with waypoint mobility. This mobility model makes the nodes move in a particular direction in order to keep the platoon's formation intact, while the nodes are moving.  
Figure 12: Isolated village MOS values for VoIP initiators: (**a**) VoIP initiators; (**b**) VoIP receivers.  
Figure 13: Platoon scenario line deployment.  
The analysis of this scenario and its sub-scenarios shows that the best performing scenario is PL4 in which IEEE 802.11g, IEEE 802.11, G.729 codec, and AODV have been integrated, as compared to other sub-scenarios. The worst performing sub-scenario is PL6, in which IEEE 802.11n, IEEE 802.11e, G.729, and AODV have been integrated, as shown in Figure 14a for VoIP initiators and Figure 15b for receivers.  
The overall analysis of all sub-scenarios shows that IEEE 802.11g with AODV without the IEEE 802.11s integration results in better VoIP performance and IEEE 802.11n with AODV resulted in the worst VoIP performance.
## 4 Experiments and Results Discussion
### Target Gas Detection Experiment
The average signal-to-noise ratios (SNR) of the CO\({}_{2}\) absorbance spectra at different blackbody temperatures for the two filter channels are presented in Table 3.  
Due to the spectral region of the SMWIR-IFTS being 1.5\(\sim\) 5 \(\upmu\)m, which falls within the short- and medium-wavelength infrared band, the measurement process is susceptible to interference from environmental stray radiation. Additionally, factors such as the instability of the instrument's electronic components can also affect the collected spectral data. As shown in Figures 10 and 11, the lower the blackbody temperature, the poorer the spectral consistency, and the more severe the overlapping of absorbance spectra at different CO\({}_{2}\) concentrations. Table 3 further illustrates that as the blackbody temperature decreases, the average SNR of the spectra also decreases. At a blackbody temperature of 353 K, the average SNR of both filter channels falls below 5.2 dB. Moreover, due to the saturated absorption effect of the gas, as the concentration increases, the non-linear shift between the  
Figure 10: CO\({}_{2}\) absorbance spectra collected by 1 st filter channel at blackbody temperatures of (**a**) 353 K; (**b**) 373 K; and (**c**) 383 K.  
Figure 9: (**a**) Gas radiance spectra; (**b**) 90% CO\({}_{2}\) absorbance spectrum collected by the 2 nd filter channel at a blackbody temperature of 408 K.  
absorbance spectrum and concentration becomes more pronounced, making the accurate inversion of CO\({}_{2}\) concentration more challenging.
## 3 Impact of external errors
### Impact of environmental effects
#### 3.2.1 Ionosphere  
The ionospheric delay is mainly dependent of the Total Electronic Content (TEC) and the radar signal frequency. The nadir altimeter, which now commonly operates at two frequencies, has thus the ability to determine the TEC along its path and in the mean time the ionospheric delay. However, this measurement only applies in the nadir direction, and not in the off-nadir direction. Therefore, there is an error in applying the nadir ionospheric delay to the interferometer master antenna range.  
The ionosphere is known to have variability with spatial wavelengths of the order of one thousand kilometers. However, in order to get an accurate error budget, the maximum amplitude of TEC variations over about 100 km (FR) must be determined (worst cases consideration). Dual-frequency ionospheric data have already been computed along nadir altimeter paths (see [4]). They only enable us to determine these ionospheric delays along one direction. However, delays must also be known along the crosstalk direction and even along all directions because of the yaw steering. GIM (Global Ionospheric Model) maps resulting from GPS (Global Positioning Satellites) worldwide data are available daily and have been intensively validated (see [21, 22]). They constitute the best dataset to derive global statistics of the worst cases.  
Figure 12 shows an example of the errors for April 2000, plus a summary of the results for the years 2001 and 2002.  
Statistics show that ionospheric errors (difference between the nadir and off-nadir delays) above 0.7 cm in the Middle Range (MR) and 1 cm in the Far Range (FR) are common, especially in the tropics. Then, the use of worldwide GPS data in the ground processing segment can be an appropriate solution to solve such an issue.
## 2 Related Works
### Disconnected Vehicular Network  
Previous studies have extensively delved into the communication challenges within Disconnected VANETs. They focused on identifying reasons for disconnections, such as insufficient deployment of RSUs and the unpredictability of RSUs potentially failing. These investigations also examined the consequences of these disconnections, including message delays and inadequate message propagation. To tackle these issues, various advanced algorithms were proposed. It is critical to note, however, that none of these studies have specifically addressed the enhancement of communication reliability in the absence of RSUs. One notable study [13] concentrated on determining the mean length of clusters by exclusively relying on V2V communication. Additional research [14; 15; 16; 17] investigated network connectivity using a generic radio channel model. Despite achieving full connectivity during high-vehicle-density periods, configurations with sparser vehicles led to inefficient message propagation, resulting in significant delays [18; 19]. While specific investigations [20; 21] scrutinize overall delay and frame the placement of RSUs as an integer linear programming problem, there is a significant void in the literature regarding the assessment of the speed at which alert messages propagate. This gap is particularly pronounced in scenarios where vehicles communicate directly with each other in the absence of RSUs.
## 4 Discussion  
Metamaterials with ring and split-ring structures have been extensively studied for broadband absorption applications, yielding significant results [39; 40; 41; 42; 43; 44]. However, the achievement of broadband absorption in previous studies often required the use of external electrical components, multilayer structures, or specialized materials. For instance, in  
Figure 8: Measured absorption of the plasmonic metasurface at various incident angles for the (**a**) TE and (**b**) TM modes. Ref. [39], [PERSON] et al. obtained an absorption exceeding 90% at incident angles from 0 to 30\({}^{\circ}\) within a frequency range of 7.93 to 17.18 GHz using a double octagonal ring structure. However, this design necessitated the integration of four resistors into each unit cell, where the resistors functioned as energy absorption points, contributing to the broadband absorption performance of the structure. Similarly, in Ref. [40], the proposed absorber prototype demonstrated an absorption exceeding 80% across a frequency range of 5.46 to 14.75 GHz, with an incident angle tolerance up to 30\({}^{\circ}\). To achieve this result, the metamaterial absorber was fabricated as a multilayer structure, incorporating two layers of double split-serration rings (DSSRs) sandwiched between three layers of modified epoxy with varying thicknesses. Additionally, several other structures have been proposed for broadband absorption. However, these designs typically required the use of four resistors per unit cell [41; 42] or even eight ones per unit cell [43]. In cases where resistors are not employed, the proposed structures tended to rely on multilayer configurations and specialized materials, such as indium tin oxide combined with air gaps [44]. In other studies [45; 46] that did not employ external electrical components or specialized materials, achieving broadband absorption still remained challenging. Instead, these studies often resulted in multi-peak absorption [45]. Occasionally, broadband absorption was achieved; however, the absorption bandwidth was typically less than 1 GHz [46]. In contrast, our proposed plasmonic design features a simple configuration based on a metal--dielectric-metal structure. The top copper layer was fabricated by using the standard PCB technology, which was highly straightforward and ensured high reproducibility. No resistors or external components are required in this plasmonic metasurface. Consequently, our proposed design achieved a broadband absorption within a range of 12.30 to 14.80 GHz. When compared to the previous results that used lumped elements/multilayer, our reported relative absorption bandwidth of 18.45% is indeed narrow. However, when compared to the publications without the use of lumped elements/multilayer, the 18.45% bandwidth is significantly larger, since the previous publications have reported values of 1.18%, 2.46%, and 6.46%, respectively (see Table 2). This approach offers significant advantages in terms of compactness, ease of fabrication, and cost-effectiveness. A detailed comparison of the performance of this work with previous studies is presented in Table 2.
# A Cross-Chain Solution to Connect Multiple DNS Blockchains in Consensus Roots System
## 4 Construction of Our System
### Atomic Deal
#### 4.4.1 Negotiation Phase  
At the start of the negotiation phase, chainA (the initiator) sends a transaction packet, \(tx\), to the relay platform. The packet has chainA's identifier (\(A.ID\)), chainB's identifier (\(B.ID\)), and the domain name data (domain.info). The relay platform checks the validity of domain.info to find chainB as the recipient. It forwards the packet to chainB using relay.forward.tx (\(tx,target.ID\)).  
The establishment of this preliminary phase augments the security infrastructure while offering flexibility, thereby contributing to the holistic trustworthiness of the cross-chain interaction.
## 5 Experimental Results  
In this subsection, experiments are designed to verify the effectiveness of the proposed control method in a real scenario. Figure 7 shows the task environment in which the manipulator of the UR5 moves close to the target. Specifically, the manipulator acquires the visual features \(S\) of the target in real-time through the end-mounted Realsensed 435i camera and feeds them back to the located PC, which further sends the IBVS control commands to the UR5 manipulator controller. The camera captures video at a resolution of 640 \(\times\) 480 pixels and feeds the acquired image data into the Visp image processing library program in Visual Studio 2017. The program extracts the feature center coordinates at a sampling interval of 0.01 s and sends them to the IBVS controller, implemented in MATLAB R2016b on the PC side, for processing. In the practical experiments, we established the DQN-based uncalibrated visual servoing framework. Within the established framework, the Q-networks were trained as expected; as described in Section 3.4, the task is to control the manipulator from an arbitrary initial pose to the desired pose by using the proposed uncalibrated IBVS system with closed-loop feedback of image features. The manipulator takes the features of the QR code target's four corner points on the platform as input, which are labeled A, B, C, and D in the experiment. The current feature is obtained as \(S=[s_{1},s_{2},s_{3},s_{4}]\in R^{8\times 1},s_{i}=(u_{i},v_{i}),i=1,2,3,4\), and the manipulator control variable is \(\theta\in R^{6\times 1}\). The Q-network parameters in the DQN feature-constrained control module are the same as the training parameters in 3-4. Note that in the DQN feature constraint section, the actual input state is \(s_{i}\).  
Figure 6: Multidimensional feature screening.  
Figure 7: UR5 manipulator experimental platform.
## 3 Materials and Methods
### Methodology
#### 3.5.1 Detection  
In almost all optical satellite image-based applications, most of the images showing a total background are labeled as negative examples. Before dealing with the ships in the positive samples, eliminating the negative examples ensures suitable inputs for further stages of DLRI. At this point, HieD's detection stage accomplishes this task by classifying images as positives (with ship(s)) or negatives (without ship), without regard for the location of the ship(s). For this binary classification, well known deep learning classifier networks like Alexnet [54], ResNet 18/50/101 [55], DenseNet 201 [56], GoogLeNet [57], EfficientNet [58], and Xception [59] were implemented, and the highest overall accuracy was achieved with the Xception architecture.  
Most images have spatial (x and y) plus channel dimensions, which are handled as a whole by the CNNs, generating a high computational load for the network. [PERSON] proposes applying spatial convolution to each channel separately [59]. Additionally, \(1\times 1\) convolution kernels are used to build the cross-channel correlations to implement the depth-wise separable convolution. Xception is a follow-up of Inception versions 1, 2, and 3 [60]. It performs the convolution kernels first and then applies channel-wise spatial convolution. There is no intermediate ReLU non-linearity layer in the Xception network. The parameters to tune Xception in HieD are given in Table 5. In brief, the binary classification is applied to the input images, and only the images labeled as \"including ship(s)\" pass through the next stage, localization.  
\begin{table}
\begin{tabular}{c c} \hline \hline  & **Software Parameters** \\ \hline Software Name & MATLAB 2021a Academic Version \\  & Google Colaboratory \\  & MATLAB Computer Vision Toolbox 10.0 \\  & MATLAB GPU Coder Support Package \\  & MATLAB Parallel Computing Toolbox 7.4 \\  & MATLAB Deep Learning Toolbox 14.2 \\  & MATLAB Embedded Coder 7.6 \\  & MATLAB Coded 5.2 \\  & MATLAB Image Processing Toolbox 11.3 \\  & CUDA 10.1 \\  & cuDNN 9.0 \\ \hline \hline \end{tabular}
\end{table}
Table 4: _Cont._Figure 1: The flowchart of the proposed HieD approach.
## 5 Experimental Analysis
### Comparison with Previous Works
It can be observed that BengaliNet has a fewer number of parameters than previous transfer learning  
Figure 10: Illustration of performance comparison for all 8 datasets among previous noteworthy approaches and our proposed architecture in terms of overall accuracy. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Method/Approach** & **Dataset-1** & **Dataset-2** & **Dataset-3** & **Dataset-4** & **Dataset-5** & **Dataset-6** & **Dataset-7** & **Dataset-8** \\ \hline GhostNet & 87.13\% & 83.33\% & 79.48\% & 77.22\% & 80.12\% & 75.80\% & 80.42\% & 76.04\% \\ InceptionV4 & 97.05\% & 96.07\% & 97.04\% & 95.51\% & 94.99\% & 95.89\% & 97.57\% & 95.41\% \\ Xception & 97.45\% & 97.13\% & 97.18\% & 94.96\% & 95.34\% & 96.86\% & 97.32\% & 95.05\% \\ MobileNetV1 & 96.04\% & 94.07\% & 95.11\% & 93.02\% & 93.25\% & 92.99\% & 95.07\% & 93.52\% \\ MobileNetV2 & 96.52\% & 94.20\% & 95.09\% & 93.00\% & 93.39\% & 93.72\% & 95.27\% & 94.48\% \\ MobileNetV3 Small & 96.60\% & 94.70\% & 95.38\% & 93.39\% & 94.08\% & 93.96\% & 95.38\% & 94.87\% \\ MobileNetV1 Large & 96.68\% & 94.63\% & 96.77\% & 94.37\% & 94.47\% & 94.69\% & 96.15\% & 94.86\% \\ BengaliNet & **99.01\%** & **98.97\%** & **98.35\%** & **96.07\%** & **95.89\%** & **97.79\%** & **97.82\%** & **95.71\%** \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Comparison among results obtained by our proposed BengaliNet and popular CNN architectures. methods which denotes that BengaliNet needs less recognition time. Moreover, in terms of overall accuracy, BengaliNet outperforms all these studies as well. It can be noticed that BengaliNet achieved decent accuracy for Ekush, BanglaLekha, and NumtaDB datasets also as the last achieved highest accuracy for these datasets are 97.73% [46], 93.45% [58], and 98.40% [59] respectively.
# Ocean Surface Topography Altimetry by Large Baseline Cross-Interferometry from Satellite Formation
## 5 Methodology for Altimetric Accuracy Analysis
### Multi-Looking  
The total coherence which ultimately determines the phase noise level of LB-IRA can be expressed as:  
\[\gamma=\gamma_{uB}\gamma_{thermal}\gamma_{uve}\gamma_{time}\gamma_{others} \tag{15}\]  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Altitude & 891 km \\ Carrier frequency of Sat1 & 13.5 GHz \\ Carrier frequency of Sat2 & 13.5–13.6 GHz \\ CFS & 30–60 MHz \\ Bandwidth & 30–60 MHz \\ Radar look angle & 12–15 \\ Peak transmit power & 3000 W \\ Pulse length & 5 μs \\ Pulse repeat frequency & 4000 \\ Antenna length & 5 m \\ Antenna width & 0.4 m \\ Cross-track baseline length & 629–1000 m \\ Along-track baseline length & 0–40 m \\ \hline \hline \end{tabular}
\end{table}
Table 1: System parameters.  
Figure 14: Flowchart of the methodology for parameters selection.  
where \(\gamma_{uB}\) is the baseline decorrelation in cross-interferometry mode, \(\gamma_{thermal}\) is the thermal decorrelation, \(\gamma_{wave}\) is the wave volume decorrelation, and \(\gamma_{time}\) is the time decorrelation. In addition to the above decorrelation factors, quantization, ambiguities, and processing, etc., all may lead to signal decorrelation, however, they can be considered minor comparing to those major ones. The total coherence is shown in Figure 15, along with all major decorrelation factors as well, and the parameters used for numerical analysis are from Table 1. Figure 15a,b corresponds to the results of 629 and 1000 m of cross-track baseline length, respectively. The total coherence of 629 m is above 0.5, and as the cross-track baseline length increases to 1000 m, the total coherence decreases due to more severe wave volume decorrelation, however, it is still above 0.4 throughout most of the swath.  
The phase noise due to coherence loss can be considered as white noise, hence spatial averaging, or, in other words, multi-looking, can be utilized to suppress phase noise in order to increase the altimetric accuracy [6; 16]. Different from terrain topography, OST varies extremely mildly, therefore, large numbers of independent pixels of intrinsic resolution can be multi-looked. The phase noise standard deviation after multi-looking is [23]:  
\[\sigma_{\phi}=\sqrt{\frac{1-\gamma^{2}}{2N_{azi}N_{rg}\gamma^{2}}} \tag{16}\]  
where \(\gamma\) is the total coherence before multi-looking, \(N_{rg}=\frac{\rho_{grid}}{\rho_{rg}}\), \(N_{azi}=\frac{\rho_{grid}}{\rho_{zi}}\) are the number of independent resolution cells along the range and azimuth direction respectively, \(\rho_{azi}\) and \(\rho_{rg}\) are the intrinsic resolution along range and azimuth direction respectively, and \(\rho_{grid}\) is the grid resolution after multi-looking.
## 2 State-of-Practice for the Design and Fabrication of Tie-Wired Rebar Cages  
The studies completed by [PERSON] et al. [1] resulted in a set of guidelines that are included in California Department of Transportation (Caltrans) Standard Specifications Section 52 [5] for the design and fabrication of tie-wired circular rebar cages with diameters  
Figure 1: (**a**) Schematic view of a U-bolt connection; (**b**) an assembled U-bolt connector for a cross-bar connection in a rebar cage.  
equal to or larger than 1.2 m. Based on these guidelines, the following recommendations are proposed to improve the stability of rebar cages during construction.
* At least four longitudinal rebars forming a square at the rebar cage's cross-section shall be tied at every intersection with transverse rebars. These rebars are responsible for carrying the weight of the cage during the pickup process; hence, they are referred to as pick-up bars.
* At a maximum of 2.4 m spacing, lateral hoops shall be tied at every intersection to the longitudinal rebars. These hoops are referred to as template hoops.
* For large rebar cages, it may be necessary to provide diagonal brace bars [1, 6], also referred to as internal stiffening elements or internal braces. Caltrans Standard Specifications Section 52 specifies that, at a maximum of 3 m increments, internal braces with minimum of #8 (equivalent to 25 in metric) reinforcing bars and interlocking hoops at the ends shall be provided and connected to the longitudinal bars by wrap-and-saddle or stronger tie-wire connections.  
Internal stiffening elements can increase the overall bending stiffness of a tie-wired rebar cage. However, they often need to be removed before casting concrete because of seismic detailing requirements or other construction limitations. The process is usually cumbersome and requires careful consideration to avoid failure in the rebar cage. Therefore, a solution that can eliminate the need for internal stiffening elements in large rebar cages would considerably facilitate the construction progress. As will be shown, using mechanical connectors can provide a solution to this objective.
## 4 Results of Mission Analysis
### Payload Coverage  
The payload coverage analysis was conducted to verify the coverage area above the UAE. The coverage analysis shown in Figure 15 was done based on the constraint that the sensors will only cover the area from 8 am to 5 pm. The grid area for the coverage in STK was set according to the ground sampling distance that the payload is capable of capturing i.e., 1.5 km \(\times\) 1.5 km. The analysis showed that 46% of the total area of the UAE was covered by the spectrometer over the three-year mission period, given only nadir pointing satellite attitude.  
Figure 14: Lifetime analysis of MeznSat [1].  
Average contact time for the satellite with the GS is approximately 10.40 min per passes for the SSO orbit with an altitude of 550 km and inclination 97 degrees.