esa-sceva/satcom-chunk-collection huggingface dataset:
# Effects of Wind Barrier Porosity and Inclination on Wind Speed Reduction
## 2 Materials and Methods
### Wind Experimental Materials  
Previous studies have reported that a decrease in wind velocity can be indicated in the wind protection porosity function (e.g., [23; 28; 30]). This suggests that the influence of porosity on decreasing wind velocity could be much larger than that of the shape and material of the wind fence. The porosity (%) at this point was computed as follows:  
\[\Phi(\%)=\frac{A_{e}}{A_{a}}\times 100 \tag{1}\]  
where \(\Phi\) is the porosity, \(A_{e}\) is the projected area of the pores of the wind barrier, and \(A_{a}\) is the area of the perimeter of the wind barrier (i.e., height \(\times\) width).  
Different materials, such as metal, plastic, and wood, have been employed as wind barriers [36]. Among these windbreak materials, a wind barrier using a wood-based material is preferable because it is environment-friendly, light, simple, and inexpensive to  
Figure 1: (**a**) Structure of a small-scale simulation model installed at a 30 cm height from the ground with a wind barrier and (**b**) a sensor for wind velocity.  
build. In this study, we tested both the porosity and inclinations to examine their potential for decreasing wind velocity using wood-based materials (Figure 2a). In previous studies, wind barrier porosity was typically designed within a range of 0% to 50%, taking material costs into account [8; 18; 27; 29; 32]. Lower porosity tends to be more expensive in practical applications [18], whereas higher porosity permits increased air penetration, resulting in less wind speed reduction [9]. Regarding wind barrier inclination, preliminary tests were conducted on inclinations ranging from 90\({}^{\circ}\) to 70\({}^{\circ}\) prior to the wind tunnel experiment owing to the challenges of field construction. Thus, using these wood-based materials, our study was designed for three cases: (1) Case A: porosity of 0% with three inclinations (90\({}^{\circ}\), 80\({}^{\circ}\), and 70\({}^{\circ}\)), (2) Case B: porosity of 25% with three inclinations (90\({}^{\circ}\), 80\({}^{\circ}\), and 70\({}^{\circ}\)), and (3) Case C: porosity of 50% with three inclinations (90\({}^{\circ}\), 80\({}^{\circ}\), and 70\({}^{\circ}\)) (Figure 2b).  
Figure 2: (**a**) Schematic diagram of porous and non-porous wind barriers at different inclinations and (**b**) three case studies (A, B, and C) with different porosities (0%, 25%, and 50%) and inclinations (90\({}^{\circ}\), 80\({}^{\circ}\), and 70\({}^{\circ}\)).
# Independent System Calibration of Sentinel-1B
## 8 Polarimetric Characterization
### Cross-Talk  
The cross-talk is determined by relating the impulse response function of a corner reflector derived from both polarization channels. The results for all acquisitions with different modes using the DLR corner reflectors are shown in Figure 27. The overall cross-talk is below \(-35\) dB for all modes and confirms the very good quality of the isolation of the co- and cross-polarization channel in the receive path of the SAR instrument. However, focusing on the StripMap mode (blue symbols) with the highest spatial resolution, the real cross-talk of the SAR instrument is even better than \(-40\) dB. The lower spatial resolution of the IW and EW TOPS modes leads to a higher signal clutter for cross-polarized channels causing a higher variation. This limits the capability to verify such a low cross-talk of the instrument.
###### Abstract  
Background: Although many of the movements of skiers are asymmetric, little is presently known about how such asymmetry influences performance. Here, our aim was to examine whether asymmetries in technique and the ground reaction forces associated with left and right turns influence the asymmetries in the performance of elite slalom skiers. Methods: As nine elite skiers completed a 20-gate slalom course, their three-dimensional full-body kinematics and ground reaction forces (GRF) were monitored with a global navigation satellite and inertial motion capture systems, in combination with pressure insoles. For multivariable regression models, 26 predictor skiing techniques and GRF variables and 8 predicted skiing performance variables were assessed, all of them determining asymmetries in terms of symmetry and Jaccard indices. Results: Asymmetries in instantaneous and sectional performance were found to have the largest predictor coefficients associated with asymmetries in shank angle and hip flexion of the outside leg. Asymmetry for turn radius had the largest predictor coefficients associated with asymmetries in shank angle and GRF on the entire outside foot. Conclusions: Although slalom skiers were found to move their bodies in a quite symmetrical fashion, asymmetry in their skiing technique and GRF influenced variables related to asymmetries in performance.  
biomechanics; kinematics; kinetics; global navigation satellite system; GPS; IMU; inertial motion capture; pressure insoles; ski racing Article
## 2 Materials and Methods
### Application at the Regional Scale  
The application of CVFZ at a regional scale involves the extraction of the LAI mean time series from different functional areas of the same vegetation, which requires superimposing it with other land cover products. In this paper, MCD12Q1 serves as an example, and the resulting image is referred to as MCD-CVFZ. The zoning rule for MCD-CVFZ is based on the reclassification of each pixel, where the single-digit number corresponds to the legend of the pixel in the CVFZ, which is represented by a number from 0 to 9, and the ten-digit aligns with the pixel value in the MCD12Q1 type 3 band. Specifically, 1 denotes grasslands, 2 denotes shrublands, 3 denotes broadleaf croplands, 4 denotes savannas, 5 denotes evergreen broadleaf forests, 6 denotes deciduous broadleaf forests, 7 denotes evergreen needleleaf forests, and 8 denotes deciduous needleleaf forests. Subregions comprising over 1000 pixels were retained for the analysis, while subregions in shrublands and deciduous needleleaf forests comprising over 20 pixels were retained due to their small areas. The discriminatory effect of CVFZ on vegetation function was studied from the perspectives of LAI mean and time series.  
We extracted the pixels' LAI value in MOD-2011 according to the MCD-CVFZ, and determined the LAI mean and LAI standard deviation averaging for time and region. To compute the LAI time series, we averaged the LAI value of each subregion pixel corresponding to 25 June 2000 to 25 June 2022. As the production of MCD-CVFZ is based on high-quality pixels from the main algorithm, no filtering method was employed.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Threshold** & **2.02** & **2.03** & **2.04** & **2.05** & **2.06** & **2.07** & **2.08** \\ \hline \(MR\) & 0.0769 & 0.0633 & 0.0477 & 0.0318 & 0.0205 & 0.0134 & 0.0087 \\ \(D_{1}\) & 0.2581 & 0.2577 & 0.2571 & 0.2567 & 0.2562 & 0.2557 & 0.2553 \\ \(D_{2}\) & 0.2068 & 0.2063 & 0.2057 & 0.2051 & 0.2046 & 0.2042 & 0.2039 \\ \(D_{3}\) & 0.0513 & 0.0514 & 0.0514 & 0.0516 & 0.0515 & 0.0515 & 0.0514 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The adjustment of the Threshold of CVFZ induces a shift in the evaluation metrics (missing rate (\(MR\)), interclass distance (\(D_{1}\)), in-class distance (\(D_{2}\)), and discrimination (\(D_{3}\))). The identification of the optimal Threshold is predominantly dependent on \(D_{3}\).
# Decentralized Public Transport Management System Based on Blockchain Technology +
## 3 System Design and Implementation
### Data Encoding and Packaging Method  
Satellite communication is a critical element for a model that collects vehicle data and transmits them to the blockchain for further analysis. It allows data transfer from vehicles in hard-to-reach regions and along highways, where it is impossible to use a traditional communication network, such as mobile or cable networks.  
With satellite communication, public transport vehicles operating in remote or hard-to-reach places will be able to transmit data about their technical condition, which could indicate potential malfunctions, delays in the schedule, and passenger safety concerns.  
However, satellite communication may face limitations in data transmission speed and cost. Here, the GDEPZ method aims to optimize the amount of data transmitted via satellite communications--a bottleneck regarding transmission speed and cost.  
Thus, satellite communication and optimized data transmission methods, such as GDEPZ, are necessary for successfully operating a model that collects vehicle data and transmits them to the blockchain for further analysis. It provides reliable communication with vehicles operating in hard-to-reach places and allows for the efficient use of satellite communication resources.  
The GDEPZ method aims to optimize the amount of data transmitted over a satellite communication line, which is a bottleneck in terms of speed and cost, as shown in Figure 3.
# Content Adaptation and Depth Perception
## 3 System Description  
### Hardware  
SliceView does not contain moving parts and is a down-to-up projection-based auto-stereoscopic display that consists of two main components: a regular computer monitor acting as the light-source and a multi-planar optical element composed of tilted translucent sheets placed at different depths. A scene is sliced by our software into layers, then they are transformed and mirrored, and each slice is projected into a translucent sheet. The light from the monitor below is reflected on each sheet and directed towards the user's eyes, which perceives the accumulated images. A diagram of a SliceView is shown in Figure 1. It must be noted that the image on the first slice is reflected directly into the user, but light reflected on the other sheets refracts on the slices in front of it until reaching the user.  
We use a Lenovo L2251p Wide TFT 22\" monitor screen and three 297 \(\times\) 210 \(\times\) 2 mm acrylic-polyethylene transparent sheets. Sheets should be ideally placed at 45\(\circ\) degrees to maximize projection area and maintain image proportions. However, they can be used at wider angles with more layers stacked to provide more depth levels in the displayed graphics, with the downside of reducing resolution along one of the planar axis. This reduction occurs because the image of the projecting monitor needs to be split into different slices, i.e., if the original monitor has a resolution of  
Figure 1: (**a**) Ray diagram on SliceView: the image emitted from a part of the monitor is reflected on the slice above it, then it refracts on the slices in front of it until it reaches the user. Primary refractions, secondary reflections and residuals are lost and reduce the final intensity. (**b**) Schematic diagram of a SliceView rendering a layered videogame (SNES Super Mario WorldTM).  
1920 \(\times\) 1200 and is divided into three slices, the resolution for each slice would be 640 \(\times\) 1200. Pre-rendering transformations are needed to maintain proportions and avoid distortions in the perceived graphics; they are detailed later and shown in Section 3.2.  
A regular PC (i5 with 8 GB of RAM) is used to render the 3D scenes, and a mouse and keyboard are situated in front of SliceView when user interaction is required. Alternative USB-powered interaction devices like a graphic tablet or a gaming controller are used for some applications.  
All the applications are rendered in real time at 60 Hz. With the hardware used, no rendering speed differences were perceived between the original content and the automatically adapted content. Furthermore, the required image transformation operations were achievable within this 60 Hz.
###### Abstract  
Catalytic hybrid rocket motors using hydrogen peroxide (HP) are easy and efficient to achieve multiple starts and stops, and hydroxyl-terminated polybutadiene (HTPB) grains are commonly used due to their excellent mechanical properties. The low regression rate of HTPB grains limits the application of hybrid rocket motors. Furthermore, the addition of solid aluminum particles can effectively improve the regression rate and performance of hybrid rocket motors. However, the experimental results of a high mass fraction of aluminum and hydrogen peroxide available at present are not sufficient. In this research, the impact of a high mass fraction of aluminum on the motor performance and ablation rate of nozzles is studied experimentally. A solution of 95% hydrogen peroxide and HTPB with an aluminum additive are adopted as propellants. The variation in the axial regression rate of the grains is obtained by computed tomography (CT) scans and pre-test parameter measurements. The instantaneous regression rate method is adopted to obtain the real-time regression rate of the motor. The surface appearance and composition of the front and the end of the grains after the tests are analyzed by electron microscopy. Carbon ceramic and tungsten-bronze nozzles are used to explore the effect of a high mass fraction of aluminum on nozzle ablation. The experimental results show that the addition of aluminum raises the specific impulse and decreases the optimal oxygen-to-fuel ratio of the propellant combination. The high mass fraction of the aluminum particles has a severe ablative effect on carbon ceramic nozzles, while the effect on tungsten-bronze nozzles is minimal for a hot test lasting four to five seconds. Our results can provide experimental guidance for the application of a high mass fraction of aluminum and hydrogen peroxide hybrid rocket motor.  
Keywords:experimental study; high-performance hybrid rocket motors; performance evaluation; nozzle ablation +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Dynamic Changes during Processing Analyzed via GC-MS  
#### 3.3.1 Analysis of Volatile Compounds in SFABT across All the Processing Steps  
A comprehensive analysis of volatile components during SFABT processing was performed by GC-MS. A total of 106 volatile compounds were identified, which comprised 11 categories (Table S3). Notably, the four component types accounting for the greatest relative proportion included alcohols (17%), alkenes (17%), aldehydes (15%), and esters (15%), as illustrated in Figure 4A. These volatile compounds exhibited significant variations across various processing stages (Figure 4B).  
Figure 4: The volatiles identified throughout the entirety of the manufacturing process for SFABT via GC-MS. **(A)** Comparative proportions of volatiles across distinct categories. **(B)** Dynamic alterations of various volatile classifications throughout the complete manufacturing process.  
In terms of aldehydes, the highest content was observed during withering (1517.23 \(\upmu\)g/L), followed by fresh leaves (841.45 \(\upmu\)g/L), shaking (636.05 \(\upmu\)g/L), fermentation (430.44 \(\upmu\)g/L), first drying (402.30 \(\upmu\)g/L), rolling (361.29 \(\upmu\)g/L), and final firing (306.74 \(\upmu\)g/L). The levels of alkenes, alcohols, ketones, heterocyclic compounds, and aromatic hydrocarbons exhibited analogous alterations. The content of esters exhibited an ascending trajectory from fresh leaves (194.64 \(\upmu\)g/L) up to shaking (378.28 \(\upmu\)g/L), and then showed a downward trend. The change trend of organic acids was the same as that of esters. The content of alkanes displayed a precipitous decrease from fresh leaves (58.02 \(\upmu\)g/L) to rolling (8.44 \(\upmu\)g/L), remaining constant in the subsequent stages. Sulfur compounds demonstrated an impressive augmentation by 8.5-fold (from 1.56 \(\upmu\)g/L in fresh leaves to 13.26 \(\upmu\)g/L in withering stage), which remained steady throughout the shaking stage. As the processing progressed, the level of sulfur compound drastically declined during the rolling stage (down to 5.37 \(\upmu\)g/L), but subsequently, the content remained stable. We noted that the contents of amines displayed little variation throughout the entire process. Volatile constituents in the different categories showed different trends of change, potentially attributed to the release of volatiles arising from glycoside hydrolysis, carotenoid or lipid degradation, and the Maillard reaction during the manufacturing process [6,30].
## 7 Conclusions  
To deal with the ever increasing traffic through the cellular users, D2D communications has been considered as one of the promising technique. We studied the problem of non-orthogonal resource sharing between cellular users and D2D pairs in an uplink network to enable traffic offloading from eNB. In the paper, two-pairs of D2D users simultaneously shared the same uplink cellular resource. This introduced severe interference between the cellular users and D2D users. In order to minimize the resource reuse interference, a resource allocation and power control scheme using FFR method with FRF of 2 was proposed. Outage probability has become an imperative topic in cellular networks as it determines the capacity of the network. Based on the distances, the outage probability was calculated by ensuring SINR requirements of cellular users and D2D pairs. Moreover, the proposed scheme analyzed channel coefficient relationship based on the distances. We evaluated D2D throughput and overall system throughput mathematically and simulated using Monte Carlo simulation. Moreover, we analyzed the fair allocation of cellular resource among two D2D pairs by using [PERSON]'s fairness index. Precisely it is showed that the proposed scheme leverages higher system throughput by minimizing system outage value. Our analytical and simulation results showed a promising solution for accommodating demands for high data rate services. In future research, we will extend our work into the D2D communication scenario with large reuse factor.  
D.D.N. organized and developed the proposal of the study, carried out the mathematical analysis, and performed simulations using Monte Carlo. S.S. provided guidance, key suggestions, and finalized the paper.  
This research is partly supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education with Grant No. NRF-2015R1D1A1A01059962 and a part of the project titled 'Development of Automatic Identification Monitoring System for Fishing Gears', funded by the Ministry of Oceans and Fisheries, Korea with Grant No. 20170388.  
The authors declare no conflict of interest.
# Challenges of Using Synthetic Data Generation Methods for Tabular Microdata
## 3 Results
The Copula model (green) consistently demonstrates very low \(\varepsilon\)-Identifiability across all datasets, making it a strong candidate for privacy preservation. However, it tends to have lower utility compared to other models, except in the Breast Cancer (BC) dataset, where it maintains relatively high utility. CopulaGAN (blue) exhibits moderate to high \(\varepsilon\)-Identifiability, which is especially noticeable in the AP dataset, with generally high utility except in the MB dataset. Lower batch sizes (60) and more epochs increase both \(\varepsilon\)-Identifiability and utility, indicating a strong privacy-utility trade-off. CTGAN (blue) shows a pattern similar to CopulaGAN but with slightly lower \(\varepsilon\)-Identifiability values and comparable utility, suggesting a better privacy-utility trade-off. TVAE (purple) generates high \(\varepsilon\)-Identifiability and utility values, with these metrics being less dependent on epoch and batch sizes. This model is best suited for scenarios where high utility is crucial, and some level of privacy risk is acceptable. It is notably the only method that provides acceptable utility for high-dimensional data despite the increased risk known as the curse of dimensionality in anonymization [23; 24]. These insights underscore the complexities involved in balancing privacy and utility in SDG. Figure 1: Comparison of \(\varepsilon\)-Identifiability and RF-utility across batch size, model types, and epochs on the UCI Machine Learning datasets.
## 3 Signal Model
### CCU Point-to-Point and SU-Network MIMO Signal Models  
We have presented the signal model for CEUs in MU-network MIMO. In this subsection, we first present the CCU point-to-point signal model. For CCU \(u\), the DFT signal at subcarrier \(k\) received from the serving BS \(b\) by its receiver antenna \(v\) is  
\[\begin{split}\Upsilon_{k}^{(u,v)}=\sum_{q=0}^{N_{T}-1}\lambda_{ k}^{(b,u,q,\pi)}X_{k}^{(b,u,q)}+W_{k}^{(u,v)},\ k\in\Im^{(u)}_{A}.\end{split} \tag{15}\]  
There is no intra-cell interference because each CCU is assigned a different sub-channel from the inner band \(f_{A}\). Here, the index set \(\Im^{(u)}_{A}\) of subcarriers is associated with a particular sub-channel selected from the inner band \(f_{A}\).  
As for the CEUs in SU-network MIMO, consider a 3-cell coordinated network MIMO as shown in Figure 1a, where each CEU is together served by 3 cooperative BSs using a different sub-channel from an outer sub-band. For instance, a CEU located at cell-edge region of sector 0(a) would be collectively served by the 3 cooperative BSs using a sub-channel selected from outer sub-band \(f_{B1}\). Thus, after DFT, the signal reception at subcarrier \(k\) by receiver antenna \(v\) of CEU \(u\) can be expressed as  
\[\begin{split}\Upsilon_{k}^{(u,v)}=\sum_{b=0}^{2}\sum_{q=0}^{N_{T }-1}\lambda_{k}^{(b,u,q,\pi)}X_{k}^{(b,u,q)}+W_{k}^{(u,v)},\ k\in\Im^{(u)}_{ Bi},\end{split} \tag{16}\]  
where the index set \(\Im^{(u)}_{Bi}\) of subcarriers is associated with a particular sub-channel selected from an outer band \(f_{Bi}\).
## 2 Materials and Methods
### Explainable AI (XAI)
#### 2.8.1 Shapley Additive Explanations (SHAP)  
SHAP is a methodology based on cooperative game theory that assigns a unique value to each feature, known as the SHAP value [42]. This value represents the contribution of that feature to the model's prediction for a specific instance. SHAP is versatile, offering both global explanations, which provide insights into the overall behavior of the model across the entire dataset, and local explanations that clarify how individual features influence specific predictions. SHAP values are consistent, ensuring that the sum of contributions from all features matches the difference between the model's output for a given sample and the average output. While SHAP offers a comprehensive understanding of feature importance and interactions, it can be computationally intensive, particularly for complex models and large datasets.