esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Section
### Microwave Measurements  
The microwave measurements were provided by scalar network analyzer R2-408R (ELMIKA, Vilnius, Lithuania) at room temperature and normal pressure. The system consists of the sweep generator, waveguide reflectometer, network analyzer and indicator unit (personal computer). Scalar Network Analyzer is designed for measurement of the transmission factor module (attenuation) and reflection factor module (VSWR) of waveguide devices and components in frequency range from 25.96 GHz to 37.5 GHz. Frequency sweep bandwidth range can vary from the full frequency range of the instrument to 1500 MHz. The set-up provides automatic frequency sweep over the full frequency range with sweep time of 0.08 \(\pm\) 0.016 s. Basic error limit of frequency setting does not exceed \(\pm\)0.2% in normal conditions. Design of the sweep generator is based on back wave oscillator characteristic to change the generated signal frequency in a wide range depending on voltage change on delay line structure, which is provided by the sweep generator control unit. In the panoramic measurement mode, the generator is operating in periodic frequency sweep from start frequency to end frequency of the sweep range. The output signal is modulated by 100 kHz square pulse modulation. Measurements are based on separation, by the directional couplers, of signals proportional to incident to device under test (DUT) and reflected from DUT mm-wave powers (in case of VSWR measurements) or proportional to incident and passed through DUT (in case of attenuation measurements) mm-waves. The IEC 62431:2008(E) standard specifying the measurement method for the reflectivity of EM materials for the normal incident is used. The EM response of samples as ratios of transmitted/input (S\({}_{21}\)) and reflected/input (S\({}_{11}\)) signals has been measured within 26-37 GHz frequency range (K\({}_{a}\)-band). The frequency stability of the oscillator was controlled by frequency meter and was as high as 10\({}^{-6}\). The power stabilization was provided on the level of 7.0 mW \(\pm\) 10 \(\upmu\)W. Measurement range of EM attenuation was from 0 dB to \(-\)40 dB. Basic measurement errors of EM attenuation over the range 0-25 dB were \(\delta|\)S\({}_{21}|\) = \(\pm\) (0.6 + 0.06\(|\)S\({}_{21}|\)). The substrate before PyC deposition was cut precisely to fit the waveguide cross-section 7.2 mm \(\times\) 3.4 mm. After standard procedure of the instrument calibration for transmission and reflection measurements, the S-parameters were measured by subsequent insertion of the specimen into the waveguide. The accuracy has been controlled by repetitive measurements.  
Reflectance (R), transmittance (T) and absorbance (A) are obtained from the measured S-parameters in the following way: \(R=S_{11}^{2},T=S_{21}^{2}\), \(A=1-R-T\). The scheme of waveguide measurements is presented in Figure 2.  
We performed measurements in both \"quartz + PyC\" (the EM wave incidents on the quartz substrate) and \"PyC + quartz\" (the EM wave incidents on the PyC film) geometries.
## 3 Case Study (Levels and Options of Factors (Step 1 in Figure 3))
### Factors on General Matters (1-5 of Step 1 in Figure 3)  
#### 3.2.1 Navigational Condition  
Detailed navigational conditions used in this case study, including weather, navigation area, traffic density and visibility, are shown in Table 2. Each option in the table was set based on scenarios that happen in the actual navigation area. It excludes the port area because the operators' task in this area is complicated. They sometimes navigate the ship with the help and advice of a pilot [35] in the pilot area. The main difference between Option 2 and 3 is visibility and average wave height, and the difference between Option 3 and 4 is the navigation area (density).
# A Review on the Deformation Behavior of Silver Nanowire Networks under Many Bending Cycles
###### Abstract  
Silver nanowire networks are attractive for flexible transparent electrodes due to their excellent optical transparency and electrical conductivity. Their mechanical reliability under bending is an important feature for the adoption of silver nanowire transparent electrodes for flexible electronics. Therefore, various studies have been conducted to understand the deformation behavior of silver nanowire networks, which are different from those of bulk silver or silver thin films. The focus of this review is to elucidate the deformation mechanism of silver nanowire networks under high cycles of bending and to present ways to improve the mechanical reliability of silver nanowire transparent electrodes.  
silver nanowire; transparent electrode; deformation; reliability; bending +
Footnote †: journal: Medical  
demonstrated that silver nanowire transparent electrodes show decreased resistance as the number of deformations increases [25]. In the work of [PERSON] et al., in situ tensile testing of silver nanowires provided the curvature criterion of the silver nanowire network on the polyimide substrate under a single cycle of tensile strain for up to 4% [27]. However, these studies did not involve in situ observations of changes in resistance and performed a limited number of deformation cycles, making them insufficient to secure the reliability of flexible electronic devices.  
To overcome these limitations, [PERSON] et al. and [PERSON] et al. investigated the in situ deformation behavior of silver nanowire transparent electrodes under repeated deformation, using a cyclic bending tester [28]. The cyclic bending tester was primarily designed to investigate the deformation behavior of metal thin films for flexible electronics under a high number of bending cycles and measured the change in the resistance of the electrode in situ while bending the sample 300 times per minute and bending the sample more than 1,000,000 times. Measuring changes in the resistance allows investigation of the electrode's reliability and the deformation mechanism that occurs within the electrode. In addition, using a cyclic bending tester and microstructure analysis, such as electron microscopy, makes it possible to unravel changes in the electrical properties, as the microstructure of the material deforms with multiple bending. This review introduces the fundamentals of a silver nanowire network's mechanical reliability and the deformation behavior under multiple bending cycles, using a cyclic bending tester.
# Spaceborne Sparse SAR Imaging Mode Design: From Theory to Implementation
## 3 Design and Performance Analysis of Sparse SAR Imaging Mode  
In this section, we will introduce the design scheme of the sparse SAR imaging mode including beam position design, parameter calculation, and system performance analysis in detail. Sparse SAR can obtain high-quality images from downsampled data. Thus, the sparse imaging mode has a lower requirement of PRF than the corresponding conventional one, and it can obtain wider swath coverage.
# Dynamic Data Filtering of Long-Range Doppler LiDAR Wind Speed Measurements
## 2 Methodology
### Static Standard Deviation Filter  
One way of filtering wind speed data, when there is no secondary information such as signal quality or process quality indication, is the application of a standard deviation filter. Looking at the radial speed, all data with a higher scattering around the average radial speed, \(\mu_{r}\), than defined by a standard deviation depending tolerance will be filtered out.  
\[\mu_{r}-n\cdot\sigma_{r}\leq u_{r}\leq n\cdot\sigma_{r}+\mu_{r} \tag{2}\]  
where \(u_{r}\) is the radial speed of a measurement point and \(n\) is a multiplier of the standard deviation \(\sigma_{r}\). In a data set, outliers can be eliminated with the right choice of \(n\). With the unsuspectingness of the measurement quality and existence of outliers, the \(n\)-sigma interval may lead to a detectable data loss. The influence of different averaging times of \(\mu_{r}\) is discussed in Section 4.
## 2 Materials and Methods
### Step I: Edge Detection  
Noise in the CBCT images is a little serious, leading to many incorrect or weak edges that are detected by some edge detectors. Figure 2a shows an axial CBCT image with mandible foramina. Figure 2b shows the enlarged portion of the mandible foramen that is enclosed by the yellow square in Figure 2a. The edges of the foramen are not clear. Figure 2c shows the enlarged portion that is enclosed by the red square in Figure 2a, which illustrates that background noises are serious, and the gray value distribution of background is not uniform. Thus, the Canny edge detector is used to detect edges [19]. This method uses two thresholds to detect strong and weak edges. The strong edges and the weak edges that are connected to strong edges are the detected results. The Canny edge detector is less likely to be fooled by noise than other detectors [20].  
The two thresholds that are used by the Canny detector are normalized to [0, 1] in this paper. After many experiments, the higher the threshold of the Canny edge detector is selected in range of 0.15-0.25, and the lower threshold is a classic threshold--0.4 times of the higher threshold. Figure 3a shows the Canny edges of Figure 2a with the higher threshold 0.2. The edges contain not only the mandible, the maxilla, and the spine, but also the trachea, artifacts, and the circular boundaries of CBCT field of view (FOV). The intensity values of the mandible, the maxilla, and the spine are at a high level in original CBCT images but the intensity values of the trachea, artifacts, and the circular boundaries of FOV are at a low level in original CBCT images. Therefore, an appropriate threshold T can remove or reduce these redundant edges. The T can be calculated by an automatic threshold method, such as the [PERSON]'s method [21]. There are four steps to obtain edges as follows:  
1. Detect edges in each axial image by the Canny edge detector and generate a volume that is composed of the edges;
2. Dilate the volume by a spherical structuring element with 3 pixels radius in three-dimensions to ensure that the edges between each axial image are connected in three-dimensions;
3. Calculate a threshold T by the [PERSON]'s method that is based on pixel values of whole original CBCT images so that the between-class variance achieves maximum;
4. Remove voxels of the dilated volume whose intensity values of the original CBCT images are less than the threshold T.  
Figure 2: (**a**) An axial CBCT image, (**b**) the enlarged yellow square portion of (**a**), and (**c**) the enlarged red square portion of (**a**).  
It is important to emphasize that pixels that are outside the FOV are removed before calculating T. Figure 3b indicates the result of Figure 2a that was processed by this step.
## 3 Methodology
### Quality Assessment  
The quality of the HJ composites were evaluated by inter-comparison with existing well validated Landsat WELD and MODIS products. Two kinds of comparison were considered. One comparison was that HJ composites were directly compared with WELD to evaluate the radiometric consistency under the same spatial and temporal resolution. The other was that HJ composites were indirectly compared with MODIS products under the same temporal but different spatial resolution. This scheme was performed by evaluating the visual consistency with the 500-m 8-day MODIS reflectance product (MOD09A1) and the NDVI consistency with 500-m 16-day MODIS NDVI product (MOD13A1).
## 4 System Development
### Frontend of the System
#### 4.1.2 Navigation Function Using AR  
Figure 5 shows the screen for the navigation function using AR. When users search for a sightseeing spot and a tourism-related facility using the spots and facilities search function, navigation to that destination is made available using AR. While the route to the destination is being displayed, users can select the AR button on the screen to enable the function. By selecting the AR button, an image of the spot or facility set as the destination, as well as an image of the route to the destination, will be displayed on the AR screen. In the image showing the route, numbers are applied to each part, enabling users to proceed in the order of those numbers to their destinations.  
Figure 4: Screen for the search function of spots and facilities.  
1.3 Submitting Function of the Information Concerning Sightseeing Spots and Tourism-Related Facilities  
Figure 6 shows the screen for the submission function of information concerning sightseeing spots and tourism-related facilities. Users select a relevant location on the digital map of Web-GIS when submitting the information concerning a sightseeing spot or a tourism-related facility. They can submit information by entering the name and longitude and latitude of the sightseeing spot or tourism-related facility they wish to submit, as well as select the applicable category. The submitted information is immediately reflected in the database and displayed on the digital map, as well as in the list on the screen for the search function of spots and facilities. The submitting function enables users to not only register new information that has not yet been accumulated in the database of the system, but also share their favorite sightseeing spots and tourism-related facilities with other users.  
Figure 5: Screen for the navigation function using AR.
## 4 Time-Varying Environmental Influences
### Stratified Oceans
[33], who have applied [PERSON]'s single-parameter model based on Chl-\(a\) concentrations [56] for the derivation of attenuation subcomponents along the stratified column. This may be a more appropriate approach for estimating IOPs for practical situations, where georeferenced satellite information of surface Chl-\(a\) content could help to define the properties of the given water column. However, in this article, we have instead evaluated Chl-\(a\) concentrations using (5)-(7) and Table 1 from [PERSON] et al. [34] before applying [PERSON]'s equations. For the re-parameterized coefficients, we refer the reader to Appendix A. \begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Class** & \(\mathbf{C_{b}}\) & **s** & \(\mathbf{C_{max}}\) & \(\mathbf{\zeta_{max}}\) & \(\mathbf{\Delta\zeta}\) & \(\overline{Chl\text{-}a_{Z_{eu}}}\) & \(\mathbf{Z_{eu}}\) \\ \hline S1 & 0.471 & 0.135 & 1.572 & 0.969 & 0.393 & 0.0910 & 119.1 \\ S2 & 0.533 & 0.172 & 1.194 & 0.921 & 0.435 & 0.151 & 99.9 \\ S3 & 0.428 & 0.138 & 1.015 & 0.905 & 0.630 & 0.185 & 91.0 \\ S4 & 0.57 & 0.173 & 0.766 & 0.814 & 0.586 & 0.250 & 80.2 \\ S5 & 0.611 & 0.214 & 0.676 & 0.663 & 0.539 & 0.338 & 70.3 \\ S6 & 0.390 & 0.109 & 0.788 & 0.521 & 0.681 & 0.410 & 63.4 \\ S7 & 0.569 & 0.183 & 0.608 & 0.452 & 0.744 & 0.578 & 54.4 \\ S8 & 0.835 & 0.298 & 0.382 & 0.512 & 0.625 & 1.206 & 39.8 \\ S9 & 0.188 & 0 & 0.885 & 0.378 & 1.081 & 2.950 & 26.1 \\ \hline \end{tabular}
\end{table} 
Table 2: Dimensionless normalized coefficients for vertical Chl-\(a\) concentration distribution [34]. Figure 5: Reconstructed depth distribution of Chl-\(a\) concentration profiles for S1–S9.
# Cost-Effective Design Modification of a Sleeve Bearing with Large Bearing Clearance
###### Abstract
However, the authors concluded that the three-lobe bearings demonstrated no stability advantages over the plain cylindrical bearing regarding the whirl frequency ratio (WFR). The aim of the current study is to examine the dynamics of the vertical hydropower machine exhibiting extensive vibrations, which were attributed to a large bearing clearance at the lower generator guide bearing (LGB). Due to this, the LGB exhibited reduced stiffness and was unable to generate sufficient bearing forces, prompting the machine to rely on the support from the other two bearings. To resolve this problem, the LGB, originally a sleeve bearing, was modified to a four-lobe bearing by offsetting the two halves of the bearing twice in two axes (Figure 1). Hence, the diametric bearing clearance (\(C_{b}\)) was reduced from 1.6 mm to 0.45 mm, which increased the bearing stiffness and enabled the LGB to carry a sufficient load. The design modification is cost-effective, as it allows for a redesign process with reduced financial costs. Replacing the bearing with a new design requires the disassembly of the original and installation of the new bearing, which would have incurred significant costs and an extended maintenance duration. Roughly speaking, the maintenance might take up to three months and interrupt the electricity production, which could potentially lead to a loss of approximately USD 5 million. In contrast, the design modification implemented in this study was executed on-site without the need to dismantle the original bearing, substantially reducing the downtime losses by a factor of ten. Numerical simulations and experimentations were conducted to investigate if this modification improved the dynamics of the hydropower machine. Numerical simulations were performed for two cases, i.e., operation at nominal speed and over-speeding condition, and the dynamics of the two setups were compared. In the first case, the normal operation of the hydropower unit running at its nominal speed was investigated. The effect of the unbalanced magnetic pull (UMP) produced by the generator and exciter was considered in the model. For the second case, however, the dynamics of the system were examined when the machine encountered a sudden power loss and disconnected from the grid, leading to zero electromagnetic torque and an increase in rotor speed to runaway speed. In this case, the UMP was not considered. Experiments, on the other hand, were conducted on-site for operation at nominal rotor speed, and the vibrations were measured at three bearing locations before and after the design modification.
# A Multicast Routing Scheme for the Internet: Simulation and Experimentation in Large-Scale Networks
## 3 The Greedy Compact Multicast Routing (GCMR) Scheme
### Summary  
The GCMR scheme is (i) leaf-initiated, (ii) name-independent, (iii) dynamic, (iv) adaptive, (v) distributed, (vi) protocol-independent, and (vii) QoS-aware. It is leaf-initiated since join/leave requests are initiated by the leaf nodes. It is name-independent as it does not use additional labels or headers containing (partial) information for computing the routing paths like BIER. It is dynamic as nodes can join and leave the MDT during operation without interrupting the service. It is adaptive as it can adapt the MDT to keep it both as optimal as possible and connected in case of a node/link failure. It is distributed since any node can process the incoming messages and independently derive the least cost branching path to the MDT without requiring any centralised or specialised nodes. It is protocol-independent as it is not dependent on any underlying topology constructed by the unicast routing scheme. Finally, it is QoS-aware as different metrics can be consulted to determine the least cost branching path during the search process.  
In addition, the GCMR does not need any additional or supporting protocol. Figure 4(a) shows the different protocols currently involved in the construction and maintenance of an MDT, meaning a multicast protocol like PIM or BIER, a unicast protocol like MP-BGP (Multiprotocol extension Border Gateway Protocol) [35] for addresses discovery, and IGMP for multicast membership subscription between hosts and local routers. In contrast, Figure 4(b) highlights GCMR as a real end-to-end multicast protocol over the internet: routers run a full featured GCMR while hosts use a lighter version which can initiate or terminate an instance but they cannot forward messages.  
Figure 4: Example of the MDT adaptability: (**a**) a failure in link \(l\) disconnects leaves \(D_{1}\), \(D_{2}\), and \(D_{3}\); (**b**) upstream node 2 starts looking for the downstream leaves using a type-A\({}_{2}\) message; (**c**) disconnected leaves join the new least cost branching paths to the upstream node 2; (**d**) leaves are now re-connected and can release previous edges.
## 4 Proposed RSII Model
### The Review Semantics Learning Module  
In this subsection, we describe the structure and workflow of the review semantics learning module in detail. Due to the fact that the review semantic learning module does not include the target review in its input, the learned predictive features are difficult to effectively reflect the target user's opinion on the target item. Therefore, we urgently needed to generate the semantics of the target review in order to understand the target user's opinion on the target item. Combining the teacher and review semantic learning modules can achieve the above functions.  
The review semantics learning module consisted of two CNNs and a generator. Firstly, \(C_{i}^{I}\) and \(C_{i}^{j}\) were quantified by word embeddings to get \(\hat{C}_{i}^{I}\) and \(\hat{C}_{I}^{j}\). Then, \(\bar{C}_{i}^{J}\) and \(\bar{C}_{I}^{j}\) were obtained by their respective CNNs. The formulation is as follows:  
\[\hat{C}_{i}^{I}=G\left(C_{i}^{I}\right) \tag{13}\]  
\[\hat{C}_{I}^{j}=G\left(C_{I}^{j}\right) \tag{14}\]  
\[\bar{C}_{i}^{J}=CNN\left(\hat{C}_{i}^{J}\right) \tag{15}\]  
\[\bar{C}_{I}^{j}=CNN\left(\hat{C}_{I}^{j}\right) \tag{16}\]  
In order to better learn the feature representation, this paper concatenates \(\bar{C}_{i}\) and \(\bar{C}^{j}\) to form \(\hat{c}_{i,j}\) through vector stitching. The formulation is as follows:  
\[\hat{c}_{i,j}=\bar{C}_{i}^{J}\oplus\bar{C}_{I}^{j} \tag{17}\]  
where \(\oplus\) denotes concatenate.  
Then, \(\hat{c}_{i,j}\) goes through the generator to get the generated semantic features of reviews \(\hat{c}_{i,j}\). The formulation is as follows:  
\[h_{0}=Tanh\left(W_{0}\hat{c}_{i,j}+b\right) \tag{18}\]  
\[\hat{c}_{i,j}=Tanh\left(W_{1}h_{0}+b\right) \tag{19}\]where \(W_{0}\) and \(W_{1}\) separately denote the weight matrix of the first fully connected layer and the second fully connected layer, \(b\) denotes the bias vector of the fully connected layer, \(Tanh\) denotes the \(\tanh\) activation function. We set the input size of the first layer to be \(2d\) and the output size to be \(d\). We set the input size of the second layer to be \(d\) and the output size to be \(d\).  
In this paper, the teacher module was used to supervise the learning of the review semantics learning module. The error between \(\hat{c}_{i,j}\) and \(c_{i,j}^{2}\) was minimized in this paper. The formulation is as follows:  
\[L_{1}=\sum\left(\hat{c}_{i,j}-c_{i,j}^{2}\right)^{2} \tag{20}\]
## 3 Results and Discussion
### Analysis of CRI and Aging Coefficient
Figure 13: Aging coefficient versus test temperature for AC-13 under different degrees of aging. In conclusion, SMA-13 is superior to AC-13 regarding the cracking resistance when considering different aging degrees and test temperatures. However, in practical engineering, economic cost is a necessary factor to be considered, so a brief cost analysis is given in Table 11. Table 11 shows that the annual expenses are 16.5 RMB-m\({}^{-2}\) for AC-13 pavement; however, they are 11.4 RMB-m\({}^{-2}\) on SMA-13. Apparently, the application of SMA-13 can save costs by 44% when compared with AC-13.