esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Real-Word Examination and Evaluation  
### Evaluation Platform  
To validate the feasibility and effectiveness of the RPAM system, we utilized a Geely Geometry E model [20], which is an automatic transmission vehicle, for testing. The Geely Geometry E is a compact A-class car, which is frequently employed in China's driver's license examinations due to its small and lightweight nature, implying relatively lower driving skill requirements. Subsequently, we conducted testing in real-world vehicle examination segments within the Beijing Changping District Northern Driver Examination Center.  
We made hardware modifications to the Geely Geometry E vehicle as the base model lacks an in-cabin driver monitoring camera and external LiDAR perception equipment. To address this, we custom-fitted a Robosense 80-line LiDAR unit on top of the vehicle via a specialized mounting bracket. Simultaneously, we installed a driver monitoring camera on the interior control side. In order to obtain real-time vehicle positioning for high-precision map matching, we incorporated two GPS signal receivers and an inertial navigation system. The post-modification appearance and interior of the vehicle are depicted in Figure 6.  
For the computational platform of the RPAM system used in this test, we opted for a compact domain controller based on the NVIDIA Orin chipset. The domain controller was strategically positioned at the front of the vehicle to facilitate harness management and program debugging, taking into account cost-effectiveness and spatial constraints. To facilitate testing and debugging, a portable screen with a microphone speaker was placed behind the front passenger seat within the vehicle. This setup not only provided convenience for program debuggers but also alerted the driver to the testing program's operational status through voice announcements.  
In order to monitor the real-time location and performance status of the test driver within the scenarios, including the effectiveness of their observation actions, we developed a front-end user interface for the program. The interface is divided into sections for map display, examination system status indications, and driver information, as illustrated in the  
Figure 5: The performance of LiDAR detection.  
following Figure 7. The blue vehicle model on the map represents the position of the test vehicle, with the model displaying both the location and vehicle orientation.
## 6 Case Study: Application of the Method on LoA 4 Valet Parking with V2X  
In this section, we present a case study (automated valet parking) on the alignment the V2X capabilities with the SAE levels of autonomy, considering the features offered by various protocols. According to the proposed method, the investigated areas of interest can be mapped to the function to the extent of the function's level of automation according to SAE, carried our from the automated driving point of view. AVP is categorized as an LoA 4 function, as the ODD is limited to the parking lot or garage, however, the driver is not needed for the operation of the vehicle. AVP is also a special case of LoA 4 driving, as the physical presence of the driver in the vehicle is not required. The mapping of the function's requirements, components and challenges is done for the 6 areas of interest as follows.  
Figure 2: Volkswagen’s integration of Car2X technology, utilizing the IEEE 802.11p WiFi standard, claims to enable secure and privacy-preserving communication between vehicles within an 800-m radius, marking an important milestone in local V2 Vcommunication. _Image credit: DALL-E_.
# Application of RFID to Soil-Erosion Research
## 4 Analysis and Discussion  
### Experiment 1  
The recovery rate of particles (81.7%) is lower than that for a previous laboratory experiment (97%), but comparable to that for field experiment (84.5%) reported by Reference [7]. In all probability the loss is a function of total rainfall. For the present experiment, total rainfall was 103 mm, whereas for the previous laboratory and field experiments it was 15 mm and 106 mm, respectively. The need to physically locate the tagged particles in order to identify them and record their travel distance is a weakness of this use of RFID for measuring soil erosion, and limits its practical application to (i) the understanding of processes, (ii) studies of factors controlling rates of erosion conducted in the laboratory or controlled field experiments, and (iii) providing parametrisation for models of soil erosion. Nonetheless, these are important elements towards better practical predictions of soil erosion. The distribution of travel distances of individual particles is well fitted by a Burr 4-parameter distribution which Reference [10] fitted to the distribution of particles splashed by an individual raindrop. Inasmuch as the travel distances of these particles are short and most likely represent a combination of detachment by raindrops and transport by flow (see Reference [11]), this result lends  
Figure 7: Difference between RFID nominal locations and those obtained from the multiple observations by the remote reader.  
support to the use of the Burr 4-parameter distribution for modelling travel distances of particles eroded by water.
## 1 Introduction
When a magnetic field is applied to a metal, it influences the process of electrode kinetics, mass transfer, and the formation of a hydroxide/oxide layer by different external forces, such as Lorentz force, paramagnetic gradient force, and gradient magnetic force [26; 27; 28; 29; 30]. However, contradictory observations have been made by researchers for different metals under different conditions. [PERSON] et al., studied the effect of a magnetic field on the dissolution of SS304 and observed that, in an FeCl\({}_{3}\) system, the corrosion rate increased under a permanent magnetic field [31]. However, for [PERSON] et al., the results were contradictory as they observed that, for AISI 303 stainless steel in an FeCl\({}_{3}\) solution, the corrosion rate decreased along with the number of pits [32]. For the case of copper and titanium alloys in a NaCl solution, the corrosion rate was accelerated, but, for copper and zinc alloys in a HNO\({}_{3}\) solution, the corrosion rate was decreased [21; 33]. [PERSON] et al. studied the effect of a magnetic field on the corrosion performance of different Al-Mg alloys and observed that the Al-Mg alloy with Fe showed a higher corrosion rate and more pits compared to alloys of only aluminum and magnesium, which showed inhibition characteristics under the magnetic field [34]. Hence, it is important to contemplate in detail how a magnetic field can impact pipeline corrosion as there is relatively very little research in this area. In our study, to address the effect of magnetism on the corrosion of steel pipelines, a flow loop was designed and built. The corrosion rates were evaluated using electrochemical methods and a three-electrode corrosion setup in the flow loop. Our previous study investigated the corrosion rate and its relationship with the temperature, NaCl concentration, flow velocity, and pH in carbon steel [35]. A magnetic-based fiber optic sensor [36; 37] was also developed to detect the internal corrosion of pipelines using magnetism and the optical strain sensing technology. The work investigated the effects of magnet size, the magnetic permeability of the pipe material, and the magnetic flux density of the magnet. In the later work [38], a new internal corrosion detection sensor based on the magnetic interaction between a rare-earth permanent magnet and the ferromagnetic nature of steel was developed with a suitable design that can be easily installed on pipelines and storage tanks. Hence, the aim of this research is to study the impact of a DC magnetic field on a steel specimen in a flow loop system. It examines a specific correlation between the applied permanent magnetic field at different orientations to various flow velocities produced in the flow loop system. This would yield a greater understanding of hydrodynamics and the magnetohydrodynamic effects, which are insufficiently researched but are of great importance considering real-life scenarios. A flow loop was designed for conducting the electrochemical testing under a permanent magnetic field, which is explained in the following sections.
# Coverage Analysis and Efficient Placement of Drone-BSs in 5G Networks +
## 5 Simulation Results  
The simulation and numerical results for the downlink coverage probability and optimal drone-BSs placement are presented in this section. 200 users and 10 drone-BSs are randomly distributed within a \(2\times 2\) km\({}^{2}\) area. The simulation parameters are illustrated in Table 1. Our goal is to serve the maximum number of users based on a reduced number of drone-BSs using a mmWave carrier frequency.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline \(f_{c}\) & 28 GHz \\ \(h_{min}\leq h\leq h_{max}\) & \(1000\leq h\leq 3000\) m \\ \(M\) (number of drone-BSs) & 10 \\ \(N\) (number of users) & 200 \\ \(p_{t}\) & 30 dBm \\ \(SINR_{thr}\) & 5 dBm \\ \(B\) & 20 MHz \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters adopted for our work.  
Figure 2 depicts the downlink coverage probability considering different altitudes for the drone-BSs. We observe that the coverage probability increases when the altitude of the drone-BSs also increases. However, as mentioned above, a very high altitude can influence the energy performance of the drone. Figure 3 shows the optimal drone-BSs placement and the minimum required number of drone-BSs to ensure that all users are covered. The results indicate that in order to satisfy 0.76 of downlink coverage probability, it is necessary to deploy five drone-BSs. On the other hand, a coverage probability can be improved by increasing the number of drones, although this would lead to a decrease in the distance between the drones and consequently the interference at user level would be higher.  
Furthermore, the number of users served by the deployed drone-BSs are illustrated in Figure 4. We observe a decrease in the number of users covered by the network when the number of drone-BSs is reduced. Moreover, the results obtained indicate that the drone-BSs are separated in distance, leaving uncovered areas. Besides, the optimal altitude selected for the drone-BSs can be improved to increase the coverage radius and get more users covered, but with reduced energy performance.  
Figure 3: Drone-BSs placement at the end of the GWO iteration.  
Figure 2: Coverage probability versus SINR threshold, at different altitudes.
# A Redactable Blockchain Scheme Supporting Quantum-Resistance and Trapdoor Updates
## 5 Experiments and Results Analysis
### Performance of HIBCH-RS
#### 5.1.1 Evaluation Time and Size of the Hierarchical Model  
From the parameter analysis in Section 3.3.1, we selected four sets of parameters for the experiment in Table 3.  
In the first experiment, we tested the time and secret key size of the runs of the hierarchical algorithm in the HIBCH-RS model, respectively.  
From Figure 4, we can see that the trapdoor delegation algorithm consumes more time and produces larger trapdoor matrix elements as the parameters change. This is because in the algorithm we have used _nk_ times the _SampleD_ Gaussian sampling algorithm and the _SampleD_ algorithm performs a complex Gaussian sampling that causes the size of the delegated trapdoor to be linear with the dimensions of the delegated public key [36]. In future experiments, we will look to establish more efficient and stable Gaussian sampling algorithms for improvement. On the other hand, as can be seen in Figure 4, we added the _Slavekey_ algorithm, which runs in much less time than the _Setup_ algorithm. Therefore, the addition of this algorithm does not put too much burden on the system. For the storage expense shown in Figure 4b,c, among the public key of the public parameter PP, master key, and delegated public key, and delegated trapdoor, the trapdoor storage expense is higher because the trapdoor is generated by the _DelTrap_ algorithm, which runs _nk_ times the _SampleD_ algorithm.  
Next, we observe that some schemes for hierarchical identity encryption are related to the number of layers of delegation, such as schemes with a hierarchical identity-based puncturable encryption model (HIBPE) in [38], and the efficient quantum-safe hierarchical identity-based cryptosystem with traceable identities (AHIBET) in [39].  
In Table 4, we list the delegated key sizes for both schemes and HIBCH-RS.  
Figure 4: Comparison of running times and size. (**a**) The run time of HIBCH-RS with update algorithm; (**b**) the public key size; (**c**) the private or trapdoor size.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Parameter Group** & **n** & **m** & **w** \\ \hline Group 1 & 20 & 920 & 460 \\ Group 2 & 40 & 2080 & 1040 \\ Group 3 & 60 & 3480 & 1740 \\ Group 4 & 80 & 5120 & 2560 \\ \hline \end{tabular}
\end{table}
Table 3: The selected parameter groups.  
From the experimental results shown in Table 4, the key size of the HIBPE and AHIBET models increases linearly with increasing levels. In our model, due to the introduction of the slave key algorithm, the size of the delegated key can be fixed in a certain dimension.
## 1 Introduction  
A micro holographic storage system (MHSS) is one of the best candidates for next-generation high density optical memories [1,2]. Data bits are represented by microscopic-size holograms formed by the interference of two tightly focused counter-propagating beams, with each bit consuming a small amount of the entire volume [3,4]. The main advantage of the micro holographic data storage (MHDS), compared with conventional optical storage technologies, originates from use of the entire volume of the storage medium and multi-layer/wavelength multiplexing methods [5,6]. Each recorded hologram bit size should be reduced for high density recording. To satisfy this requirement, the optical system is required to short wavelength and high numerical aperture (NA) lenses. The micrograting created in a photopolymer is commonly analyzed by two counter-propagating beams using scalar diffraction theory [1,7,8]. However, the scalar diffraction theory is not considered polarization illumination and transmission and reflection of the propagating beam. Moreover, as the NA increases, the full width at half maximum (FWHM) size in the recording layer is changed; its value is dependent on the analysis method used [9]. Inaccuracies in the analysis method result in spherical aberration (SA), reduction of beam quality, and cross-talk between the recording layers. The finite element method (FEM) and finite different time domain (FDTD) method have been used to better resolve the FWHM; however, heavy computation loads can be time-consuming [10,11]. In the field of MHSSs, it is difficult to achieve superposition of two counter-propagating beams in the same location. The increment of micrograting size, reduction of beam quality, and SA are caused by misalignment of the \(z\)-axis.  
In this paper, we propose a method to determine the optimal focal position using vector diffraction theory for MHSS;the method provides exact solutions when the NA exceeds 0.6. In Section 2, we describe the refractive index grating created by the interference of two counter-propagating Gaussian beams in the photopolymer using vector diffraction theory. To obtain maximum diffraction efficiency, we determined the optimal focal position for minimum hologram size and SA. In this section, we also present an analysis of the micrograting size as a function of NA and wavelength, based on vector diffraction theory; the results from this analysis were compared with the micrograting size defined by \(\lambda/(2\)NA)and in scalar diffraction theory. In Section 3, we demonstrate our precise optical alignment method using a Twyman-Green interferometer (TGI); good agreement was achieved between the analysis results and experimental results. The proposed method was then applied to determine the reflected power and diffraction efficiency of recorded microgratings. Section 4 provides concluding remarks.
## 5 Conclusions  
1. To further improve the path-tracking quality of automatic navigation in agricultural machinery with a 4 WIS-4 WID structure, a pure pursuit model based on a variable look-ahead distance was adopted. A fuzzy controller was designed, with lateral deviation and heading deviation as the input and look-ahead distance as the output, to obtain dynamic variable look-ahead distances. A real vehicle path-tracking test was implemented in a real agricultural environment to validate the effectiveness of the algorithm in path tracking.
2. The dynamic adjustment of the variable look-ahead distance according to the deviation of the vehicle matches the driving habits of experienced drivers. The non-uniform membership function quantization method can guarantee the accuracy of path tracking and consider the speed and stability of the path tracking. Compared with the fixed look-ahead distance method, the method presented in this paper improved the performance of average deviation, average steady-state deviation, average steady-state distance, average maximal deviation, and the average stability time by 19.6%, 24.4%, 33.7%, 2.9% and 20.3%, respectively, according to the comparison test of the test prototype. The path-tracking accuracy, convergence rapidity, and stability were significantly improved compared to those of the traditional fixed look-ahead distance method. The path-tracking method can be applied to multi-input, nonlinear and time-varying system control.
3. The quantitative scale design of fuzzy control rules can be further refined. In follow-up research, more fine fuzzy control rules can be used, and the input and output variables can be quantified into more fuzzy subsets to determine a variety of deviation states with more accurate look-ahead distances, further improving the path-tracking accuracy of automatic navigation technology for agricultural machinery.  
Conceptualization, Y.Y. and F.F.; methodology, Y.Y., F.F. and L.Y., data curation, B.Y.; software, Y.Y., F.F. and Q.C.; writing--review and editing, Y.Y., L.X. and L.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Key R&D Program of Zhejiang, grant number 2022C02042.  
Not applicable.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 4 Classification Results and Discussion
### Effects of Downscaling Algorithms  
For Sentinel-2, first, the effect of image sharpening on classification accuracy improvement is negligible. As shown in Table 5, based solely on spectral bands, HPF achieved the best accuracy than other pansharpening algorithms with an OA of 90.54% and Kappa of 0.88. Nevertheless, it is almost the same with the benchmark image downscaled by nearest neighbor resampling, which achieved an overall accuracy of 90.33% and Kappa of 0.87. This result is inconsistent with that obtained from MODIS and ASTER [27], because the classification accuracy is not only affected by the different spectral fidelity of these pansharpening algorithms, but also influenced by the classification system and the characteristics of the Sentinel-2 data, and they can be illustrated by the global feature importance, as shown in Figure 5[68]. The most important features contain bands 2, 3, 4, 11, and 12, where only two of them were sharpened. As feature importance represents its contribution to distinguish the different classes, it demonstrates that for our classification system that only contains major land cover and land use types, the original four 10-m bands can already well discriminate these classes. Compared to MODIS and ASTER, the more fine resolution bands of Sentinel-2 makes it of great convenience and potential in regional LULC mapping.  
Second, because of the sensor dependence in spectral fidelity and spatial enhancement of different pansharpening algorithms, their effects on classification accuracy for Sentinel-2 imagery is distinct from that for other data. For example, the accuracies of NNDiffusion and PANSHARP are almost the same as GS, which illustrates that, for Sentinel-2, the statistics-based pansharpening algorithms have the same effect on classification accuracy as the one based on CS. It is inconsistent with the conclusion which has been proved on WordView-2, GeoEye-1, Landsat 7(ETM+), IKONOS, and QuickBird [23; 53]. That is because the spectral preservation capability of statistics-based algorithms is greatly limited by the spectral overlaps between the MS image and the PAN band. For Sentinel-2, only two of six bands at a 20-m GSD (bands 7 and 8a) have a spectral overlap with the PAN-like band (band8), resulting in a poor performance compared to the images with a PAN band. In addition, the MRA-based pansharpening algorithms can achieve a better spectral and spatial quality than those based on CS. This finding is consistent with other studies that used other sensor's data [69].  
In addition to the promotion to overall accuracy, image sharpening can also benefit some specific LULC classes. Figure 6 illustrates the accuracy of each class obtained by different downscaling methods. We can easily observe that image sharpening has advantages in class road with the classification accuracy increased by 3.8% with HPF and WTF and that the HPF also has a slight superiority in water. In contrast, image sharpening also has an obvious disadvantage in the shrub, bare land, and built-up areas.
# A Review of the Evolution Characteristics and Argillization of Clay Interbeds in Rockslides
## 3 Parameter Changes during the Argillization Process
### Clay Minerals in the Process of Argillization
#### 3.5.2 Changes in Clay Minerals during the Argillization Process
The higher the ratio of kaolinite to montmorillonite, the muddier the degree of gangue would be [54]. The variation in specific ion concentrations could indicate the level of hydration, reflecting changes in the degree of argillization [55]. Based on the siltstones found in the Gezhouba hydropower project, it is evident that the clay-enriched substrate junction contained a higher concentration of montmorillonite and adsorptive Na\({}^{+}\). It was prone to hydration-dispersion softening and disintegration. This process and the disintegration caused by the micro-fissure adsorption effect in siltstone could occur simultaneously. Figure 8: The sequence of shear zone alteration (modified from [PERSON] [47]). Furthermore, they would promote each other, accelerating the softening, disintegration and argillization of the soft rock. The immersion of brine on the clay interbed also had effects on clay minerals [56]. The main mechanism for softening under brine immersion is the dissolution of particles contained in the intercalation in water. The particles would cause the clay mineral to swell and soften when exposed to water. The lower the concentration of brine (referring mainly to the salt content, specifically the content of Na\({}^{+}\)), the more pronounced the impact on the clay interbed would be. The higher the concentration of brine, the smaller and slower its effect would be.