esa-sceva/satcom-chunk-collection huggingface dataset:
# User-Information-Aware D2D Multicast File Distribution Mechanism
## 4 User's Demands Awareness  
The potential service requesters receiving the pushed video will consume the energy of the user's device, occupying the device's bandwidth and storage space. If the device's residual energy or storage space is insufficient, or the potential service requester is using the wireless network, the user may be unwilling to accept the pushed video. In addition, the user's subjective intention is also an important factor to affect the video push service. If the pushed video does not meet the user's interest, the push will lose its significance, and the user's experience quality will be seriously reduced. In order to accurately to predict user's service requests and improve the user's experience quality, the willingness of potential service requester to accept the pushed video is studied in this section, and then the user-demand-aware clustering algorithm is proposed.
# OneMap Drought Monitoring Analysis Based on Statistical Models
###### Abstract
Operating a well-organized response process, such as preliminary preparation and emergency measures, is necessary. Through reviewing previous studies, indices based on a single variable are insufficient to accurately assess drought conditions. Therefore, creating and adopting an integrated drought index based on multivariate analysis that can provide comprehensive, integrated drought information by maintaining its unique characteristics would be beneficial in assessing drought conditions and implementing appropriate measures. In addition, it is difficult to intuitively understand a drought situation, because various maps are provided depending on the division of ministry-specific business fields; technology is required to integrate the information available and assess the situation comprehensively. To this end, in this study, a OneMap drought index based on a multivariate statistical model was developed, and the ability of the drought index to reproduce drought based on ground and satellite data was evaluated.
## 2 Materials and Methods
### Methods  
#### 2.2.1 Fabrication of PCL/HA Composite Filaments  
The process of synthesizing PCL/HA composite flakes is displayed in Figure 1. First, separate solutions of PCL and HA dissolved in DMF were prepared, and stirred overnight at 100 \({}^{\circ}\)C. During the stirring process, the beakers containing both solutions were sealed with aluminum foil to prevent evaporation of the DMF solvent. Next, both solutions were mixed in the same container, then stirred for 60 min, before being ultrasonicated in a sonication bath for 30 min. Following this, the PCL/HA composite solution was divided into small containers. To evaporate the DMF from the solution, the container was heated to 100 \({}^{\circ}\)C and the solution was stirred until the DMF had completely evaporated. Once the PCL/HA composite solution had solidified, the container was sonicated to separate the solidified flakes from the beakers. Lastly, the PCL/HA composite was cut into small pieces and dried at room temperature.  
Using the synthesized PCL/HA composite flakes, 3D FDM filaments were fabricated using a Filabot EX2 extruder with a 1.75 mm extrusion nozzle, as shown in Figure 2. Instead of air cooling the extruded filaments, we used a water bath to rapidly cool them down, thus minimizing thermal deformation. The composite flakes loaded in the extruder were extruded as a PCL/HA composite filament, and the extruded filament was guided to a drive wheel, which was then wound at a constant speed. All the filaments of varying composition were extruded at 100 \({}^{\circ}\)C, and the dial speed of extrusion and spooler was adjusted until the diameter of the filaments became uniform.  
Figure 1: Schematic of the PCL/HA composite flake preparation steps. Photograph showing the PCL/HA composite flakes after evaporating the solvent from the composite solution.  
Figure 2: Photographs of Filabot EX2, consisting of spooler, water bath, and extruder (**top**). Fabricated filaments with various HA wt.% produced using the above filament extruder (**bottom**).  
The morphology of the extruded filaments was evaluated, using a scanning electron microscope (SEM) to identify whether filaments had been fabricated without voids, which can greatly affect the quality of the 3D printout. Before loading into the SEM, the filaments were Pt-sputtered and observed at 10 keV. Filaments of varying composition were cut into 8 cm pieces for tensile testing using a custom-built bending machine. The stress was recorded at steps of 0.5 mm.
## 5 Conclusions  
In this paper, the radial air-gap flux density of an eccentric rotor in a PMSM was analyzed and a dynamic model of a rotor bearing system was established when considering the gyroscopic effect, nonlinear bearing forces and UMP. The effects of static eccentricity, rotor offset and radial clearance on the system were analyzed in both the time domain and the frequency domain in detail. The main conclusions of this study can be summarized as follows:  
1. The static displacement eccentricity has a great effect on the system and the orbits of the rotor and bearings are center circles when the static displacement eccentricity is zero, while they become irregular and lager when the eccentricity exists. The bearing closer to the rotor can be affected more easily when the rotor is not in the middle of the shaft. The dynamic responses increase nonlinearly with the eccentricity and rotor offset due to the effects of UMP and bearing forces. When the radial clearance increases within a certain range, the dynamic responses of the rotor and the bearing farther away from the rotor decrease, while the dynamic responses of the bearing closer to the rotor increase. When the radial clearance reaches a certain value, the dynamic responses of the system will no longer be changed since the effects of the bearings disappear.
2. The bearings have an effect on the system and the coupling effects of the bearing forces, unbalanced mass force and UMP are discovered in this study. The coupling effects exist when the bearing forces are formed, while the coupling effects disappear when the bearing forces are not formed. The dynamic angle responses are affected more obviously by the coupling effects than the displacement responses in the frequency domain.
3. The main frequencies of dynamic responses are the rotating frequency and the double rotating frequency when the static displacement eccentricity exists and the frequency components of the bearing are more complex, while the main frequency is the rotating frequency when the static eccentricity is zero. Moreover, high integer multiples of rotating frequency can be found with the increase of static displacement eccentricity. The combination of VC frequency and odd multiples  
Figure 14: The spectra of dynamic responses for different rotor offsets. (**a**) The spectra of \(x\); (**b**) The spectra of \(\theta_{x}\); (**c**) The spectra of \(x_{A}\).\(Cont\).  
of rotating frequency can be observed more obviously than other combined frequencies due to the coupling effects, and the coupling effects on the bearings are greater.  
This work was supported by the National Natural Science Foundation of China (Grant No. 51675091) and the Collaborative Innovation Center of Major Machine Manufacturing in Liaoning, the Major Scientific and Technological Innovation Project of Liaoning Province (Grant No. 201506003).  
[PERSON] and [PERSON] conceived and designed the study; [PERSON] and [PERSON] performed the simulation; [PERSON] wrote the manuscript. [PERSON] reviewed and edited the manuscript. All authors read and approved the manuscript.  
The authors declare no conflict of interest.
# Role of Multi-Scale Microstructure in the Degradation of AI Wire for Power Transmission
## 3 Results
### Microstructure Characterization
#### 3.3.1 Transmission Electron Microscopy (TEM) Observations  
As shown in Figure 3a-i, the grains in the radial section of the CPAWs and the AFWs are equiaxed. With the increase of annealing temperature, the radial grains of the CPAWs and the AFWs grew up gradually. Additionally, the evolution of precipitates in the AFWs was also observed (Figure 3g-i). The dispersive precipitated phases found in the cold-drawn AFW were identified to be Al\({}_{6}\)Fe in our previous paper [12]. As the annealing temperature increases to 200 and 250 \({}^{\circ}\)C, the coalescence of precipitates at grain boundaries occurs (Figure 3h,i).  
Moreover, the TEM images of cold-drawn CPAWs and cold-drawn AFWs (Figure 3a,d) demonstrated wider extinction contours near grain boundaries compared with those in the CPAWs and the AFWs annealed at 250 \({}^{\circ}\)C (Figure 3c,f). It is reported that the non-equilibrium grain boundaries usually have wider extinction contours [18]. Besides, the non-equilibrium grain boundaries are unstable at elevated temperature, which could revert to the stable equilibrium grain boundaries [19; 20]. As a result, the grain boundaries in the cold-drawn CPAWs and AFWs are non-equilibrium grain boundaries formed during the drawing process (Figure 3a,d). In contrast, the grain boundaries in the CPAWs and the AFWs annealed at 250 \({}^{\circ}\)C (Figure 3c,f) are in equilibrium state. Therefore, the transformation from non-equilibrium grain boundary to equilibrium grain boundary occurs for the cold-drawn Al wires annealed at high temperature.  
Figure 2: The yield strength and the electrical conductivity of the commercially pure Al wires (CPAWs) and the Al-Fe wires (AFWs).  
The axial TEM images of the CPAWs and the AFWs were exhibited in Figure 4. The grains in the cold-drawn CPAWs and AFWs are elongated along the drawing direction (Figure 4a,d). When annealed at relatively low temperature (Figure 4b,e), the grains of the CPAWs and the AFWs remain elongated. However, as the annealing temperature increases to 250 \({}^{\circ}\)C, the elongated grains for the CPAWs and the AFWs become wider and shorter.  
Figure 3: The radial microstructures observed by TEM of (**a**) the cold-drawn CPAW, (**b**) the CPAW annealed at 90 \({}^{\circ}\)C for 8 h, (**c**) the CPAW annealed at 250 \({}^{\circ}\)C for 8 h, (**d**,**g**) the cold-drawn AFW, (**e**,**h**) the AFW annealed at 200 \({}^{\circ}\)C for 8 h, (**f**,**i**) the AFW annealed at 250 \({}^{\circ}\)C for 8 h.
# Improving Low-Frequency Panel Absorbers with Two-Dimensional Acoustic Black Hole
## 3 Simulation Results
### Residual Thickness  
The manufacturing process of the two-dimensional Acoustic Black Hole (ABH) geometry on a thin panel with its parabolic shape is a non-trivial task. To achieve an exact result, Computerized Numerical Control (CNC) machining is required. However, even with an accurate machine, an endlessly thin structure is not achievable. Therefore, the thickest but still efficient design must be selected. Figure 11 depicts the normalized mean surface velocity \(\overline{v}_{x,y}(f)\) for the same ABH configuration, with radius \(a=0.1\,\mathrm{m}\) and power-law exponent \(m=4\) placed on the center position \(\mathrm{P11}\). The residual thickness \(h_{\mathrm{ABH}}\in\{0.1;\,0.3;\,0.6\}\) mm is varied to evaluate its effect on the vibration characteristics of the panel. Position \(\mathrm{P11}\) was chosen for this analysis to suppress the positive effects of asymmetrical placement shown in the previous Section 3.1.  
The suppression of the even modes results in the outstanding first mode \(f_{1,1}\approx 85\) Hz in all three curves, as shown in Figure 11. The resonant peaks for the higher frequencies are therefore attributable to the circular mode \(f_{\mathrm{ABH}}\) of the ABH. The curve for \(h_{\mathrm{ABH}}=0.1\) mm shows a peak at the first mode of the ABH geometry around \(f_{\mathrm{ABH},0.1\,\,\mathrm{mm}}\approx 120\) Hz. The curve for \(h_{\mathrm{ABH}}=0.3\) mm shows the same ABH mode but at a higher frequency \(f_{\mathrm{ABH},0.3\,\,\mathrm{mm}}\approx 195\) Hz. For the curve of the \(h_{\mathrm{ABH}}=0.6\) mm, the frequency of the first ABH mode is found at even higher frequencies, hence, it is not visible in the figure. This makes \(h_{\mathrm{ABH}}=0.6\) mm not suitable for improving the DMA panel in the target frequency range.  
Figure 11: Comparison of the normalized mean surface velocity \(\overline{v}_{x,y}(f)\) of three different residual heights at position \(\mathrm{P11}\).  
Figure 10: First four mode shapes for the panel ABH (\(a=0.1\) m and \(h_{\mathrm{ABH}}=0.1\) mm) at position \(\mathrm{P22}\).  
The results of this section indicate that the thinner the structure gets in the middle, the more suitable it becomes in terms of evenly distributed modes within the targeted frequency range. But on the other hand, with a thicker ABH, easier manufacturing and more stability are reached. The practical solution is to select the compromise and move on with a residual thickness of \(h_{\text{ABH}}=0.3\) mm.
###### Abstract  
A good understanding of historical change rates is a key requirement for effective coastal zone management and reliable predictions of shoreline evolution. Historical shoreline erosion for the coast of Guardamar del Segura (Alicante, Spain) is analyzed based on aerial photographs dating from 1930 to 2022 using the Digital Shoreline Analysis System (DSAS). This area is of special interest because the construction of a breakwater in the 1990s, which channels the mouth of the Segura River, has caused a change in coastal behavior. The prediction of future shorelines is conducted up to the year 2040 using two models based on data analysis techniques: the extrapolation of historical data (including the uncertainty of the historical measurements) and the Brunn-type model (considering the effect of sea level rises). The extrapolation of the natural erosion of the area up to 1989 is also compared with the reality, already affected by anthropic actions, in the years 2005 and 2022. The construction of the breakwater has accelerated the erosion along the coast downstream of this infrastructure by about 260%, endangering several houses that are located on the beach itself. The estimation models predict transects with erosions ranging from centimeters (\(\pm\)70 cm) to tens of meters (\(\pm\)30 m). However, both models are often overlapping, which gives a band where the shoreline may be thought to be in the future. The extrapolation of erosion up to 1989, and its subsequent comparison, shows that in most of the study areas, anthropic actions have increased erosion, reaching values of more than 35 m of shoreline loss. The effect of anthropic actions on the coast is also analyzed on the housing on the beach of Babilonia, which has lost around 17% of its built-up area in 40 years. This work demonstrates the importance of historical analysis and predictions before making any significant changes in coastal areas to develop sustainable plans for coastal area management.  
climate change; beach erosion; dune cliff; land management; data analysis 2023
## 3 Data and Strategies
### Experimental Design  
After introducing the data processing strategy, this section elaborates on the experimental design. In order to investigate the influence of the a priori orbit on the ISL/SLR combined orbit determination, as well as the impact of introducing the SLR into the ISL orbit determination, we designed four sets of experiments, as shown in Table 4. Specifically, the BDS-3 broadcast ephemeris and precise ephemeris generated by the Wuhan University Analysis Center, one of the International GNSS Service (IGS) analysis centers, are utilized as the prior orbits.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Categories** & **Item** & **Description** \\ \hline \multirow{4}{*}{Data and Configuration} & Data length & 30 days \\  & Observation accuracy & ISL: 30 cm; SLR: 3 mm \\  & Elevation angle & \(7^{\circ}\) for SLR \\  & Satellite antenna model & isg14.at [31] \\  & Arc length & 24 h \\ \hline \multirow{4}{*}{SLR Error Model} & Eccentricity correct & ecc\_xyz.snx \\  & Tidal displacement & IERS Conventions (2010) \\  & Atmospheric refraction & Mendes–Pavils model \\  & General relativity & Corrected with model \\  & Satellite eccentricity & ecc\_une.snx \\ \hline \multirow{4}{*}{Dynamic Model} & Solar radiation pressure & Box-wing + 7-parameter ECOM-2 [32] \\  & Earthshine pressure & Model correction [31] \\  & Earth’s rotation parameters & Fixed to IERS-C04-14 [33] \\  & Satellite attitude & Perturbation + orientation model [34] \\  & Solid earth tide, Polar tide, Ocean tide & IERS Conventions (2010) [35; 36] \\ \hline \multirow{4}{*}{Estimated parameters} & Position and velocity of satellites & 6 parameters \\  & Dynamic parameter & 9 parameters \\ \cline{1-1}  & ISL antenna phase center offset & 3 parameters \\ \cline{1-1}  & ISL hardware delay & 1 parameter \\ \hline \hline \end{tabular}
\end{table}
Table 3: ISL/SLR POD data processing strategy.
# Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
## 2 System Model
### Achievable Rates  
Suppose the MMSE detector is adopted by the LEO satellite to recover the information from both primary and secondary transmissions. For the primary transmission, let \(\mathbf{w}_{u}\) be the MMSE vector used to detect the \(u\)-th element of \(\mathbf{c}_{1}\), we can get  
\[\mathbf{w}_{u}^{H}\mathbf{y}=\mathbf{w}_{u}^{H}\mathbf{s}_{u}h_{u}a_{u}+ \mathbf{w}_{u}^{H}(\sum_{i=1,j\
eq u}^{U}\mathbf{s}_{i}h_{i}a_{i}+\sum_{k=1}^{K }f_{k}b_{k}\mathbf{t}_{k}+\mathbf{z}). \tag{6}\]  
Thus, the SINR of the legacy satellite user \(u\) can be calculated as  
\[\gamma_{u,p}=\frac{|\mathbf{w}_{u}^{H}\mathbf{s}_{u}h_{u}|^{2}}{\mathbf{w}_{u }^{H}(\sum_{i=1,j\
eq u}^{U}|h_{i}|^{2}\mathbf{s}_{i}\mathbf{s}_{i}^{H}+\sum_{ k=1}^{K}|f_{k}|^{2}\mathbf{t}_{k}\mathbf{t}_{k}^{H}+\sigma^{2}\mathbf{I}_{N}) \mathbf{w}_{u}}.\]  
The MMSE vector \(\mathbf{w}_{u}\) is designed by minimizing the mean-square error (MSE) between the processed signal and the transmitted symbols. Define the MSE function for the legacy satellite user \(u\) as  
\[J(\mathbf{w}_{u})=\mathbb{E}[|a_{u}-\mathbf{w}_{u}^{H}\mathbf{y}|^{2}]. \tag{7}\]  
Then the MMSE vector \(\mathbf{w}_{u}\), which minimizes the MSE function \(J(\mathbf{w}_{u})\), is represented as  
\[\mathbf{w}_{u}=(\sum_{i=1}^{U}|h_{i}|^{2}\mathbf{s}_{i}\mathbf{s}_{i}^{H}+ \sum_{k=1}^{K}|f_{k}|^{2}\mathbf{t}_{k}\mathbf{t}_{k}^{H}+\sigma^{2}\mathbf{I} _{N})^{-1}\mathbf{s}_{u}h_{u}. \tag{8}\]  
Based on the analysis in [42], the SINR of legacy satellite user \(u\) can be evaluated as  
\[\gamma_{u,p}=|h_{u}|^{2}\mathbf{s}_{u}^{H}(\sum_{i=1,j\
eq u}^{U}|h_{i}|^{2} \mathbf{s}_{i}\mathbf{s}_{i}^{H}+\sum_{k=1}^{K}|f_{k}|^{2}\mathbf{t}_{k} \mathbf{t}_{k}^{H}+\sigma^{2}\mathbf{I}_{N})^{-1}\mathbf{s}_{u}. \tag{9}\]  
Accordingly, the achievable rate for the \(u\)-th legacy satellite user can be written as  
\[R_{u,p}=\frac{1}{N}\log(1+\gamma_{u,p}). \tag{10}\]  
Similarly, we use the MMER detector to recover the transmitted signal by the IoT users. Based on the above analysis, we can obtain the SINR of the IoT users. Specifically, the SINR of the \(k\)-th IoT user is given by  
\[\gamma_{\text{k,s}}=|f_{k}|^{2}\mathbf{t}_{k}^{H}(\sum_{i=1,j\
eq k}^{K}|f_{i }|^{2}\mathbf{t}_{i}\mathbf{t}_{i}^{H}+\sum_{u=1}^{U}|h_{u}|^{2}\mathbf{s}_{u }\mathbf{s}_{u}^{H}+\sigma^{2}\mathbf{I}_{N})^{-1}\mathbf{t}_{k}. \tag{11}\]  
Then, the achievable rate for the \(k\)-th IoT user can be written as  
\[R_{k,s}=\frac{1}{N}\log(1+\gamma_{k,s}). \tag{12}\]  
From (9) and (11), we can find that the legacy satellite user's SINR depends on the spreading codes of the primary system as well as those of the secondary system. Because of the randomness of spreading codes, it is difficult to exactly calculate the SINR of the legacy satellite user and allocate resources for these two systems. Thus, in Section 3, we will analyze the asymptotic SINRs for both primary and secondary transmissions.
# Lower-Latency Screen Updates over QUIC with Forward Error Correction
###### Abstract
In our previous work, we showed that integrating FEC for high-priority resources could even further reduce resource download completion time [8]. Figure 1: Dependency graph (based on Figure 1 in [4]). Figure 2: Total vs. partial delivery (based on Figure 2 in [4]). Some network workloads with partial ordering requirements can take advantage of running over QUIC if there are appropriate mechanisms and semantics. For example, remote desktop applications and online video games have periodic screen updates in which different parts or rectangles of the screen can be updated in any order as long as each screen update is finished before starting the next one. Over QUIC, different updates can be sent over different QUIC streams, but QUIC does not have any mechanism to make sure that we finish delivering all of the parts of one screen update before starting to deliver the next one. In this paper, we extend and combine two of our previous contributions [4, 8] to implement a partial ordering approach over QUIC with FEC to reduce the latency and blocking time for pixel-based screen sharing protocols such as Virtual Network Computing (VNC). VNC runs over TCP and suffers from the unnecessary added latency forced by total order delivery of TCP. We also include the OpenFEC library [9] in our implementation to have access to its FEC methods codes such as Reed-Solomon, although our focus is not on evaluating any particular FEC code. In Section 2, we review some of the previous works related to supporting partial ordering and explain the background regarding our previous work on CFs and QUIC. In Section 3, we explain VNC, the FrameBuffer protocol, and the two synthetic workloads that we used for our evaluation. Section 4 includes the details of our implementation to add FEC and the partial ordering needed for our workloads over QUIC, while Section 5 explains our Emulab testbed setup used for our results in Section 6. As discussed, our empirical results are based on synthetic workloads evaluated on the Emulab testbed. There are no widely accepted benchmarks for screen sharing, so we started with simpler tests that helped us isolate low-level effects (e.g., the different impacts of partial ordering and FEC on different congestion control algorithms). We speculated that real-world scenarios have more dynamic interactions due to contention between concurrent data streams, resulting in complicated packet-loss patterns. However, our empirical evaluation established a baseline for the benefit of integrating partial ordering and FEC, and future work will explore other workloads.