esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion  
The conducted research highlights that investigations using laser scanners allow for the large-scale determination of the state of surface strength through reflectivity values (_I_), which are correlated to the Schmidt hammer rebound values (_r_). From the overall analysis of the results, it can be noted that the average values of measurements obtained with the laser scanner are well correlated with those obtained with the Schmidt hammer. This has allowed for the derivation of linear relationships correlating these two types of measurements (direct and indirect), thereby enabling the estimation of rebound values even for surfaces where direct measurement was not possible but indirect measurement can be carried out through the more convenient and effective laser scanning system. It is, however, worth noting that such linear correlations are obtainable for each individual rock mass (i.e., each lithotype) as reflectivity is closely dependent on the type of material composing the surface under survey. Through the linear correlation, any value of reflectivity measured in the comprehensive laser scanner survey can be associated with a rebound value. As a result, from these rebound values, it was possible to derive the Joint Coefficient of Strength (_JCS_), essential for determining shear strength using Barton's equation.  
The results suggest that the laser scanner technique could be a useful tool for quantifying the state of alteration and, consequently, the strength of rock materials in a rapid and non-destructive manner, even over large areas. This method presents higher sensitivity than that achievable with the Schmidt hammer, not only because reflectivity measurement is carried out continuously over the entire investigated surface but also over extremely small areas, practically pixel-sized compared to the impact area of the Schmidt hammer piston. Additionally, the rebound value of the Schmidt hammer is influenced by the possible detachment of small portions of material around the impact surface. Through the geometric processing of coordinates acquired at a large number (\(10^{6}\)) of points on the surface of the discontinuity, it is possible to obtain roughness profiles in any direction and for the entire extent of the discontinuity. This allows for the reconstruction of textural anisotropy, particularly in directions of kinematically possible sliding or, more generally, on surfaces of project interest. This surpasses the limitations of JRC evaluation through a profilometer. An additional advantage provided by the use of the laser scanner is the ability to acquire a large number of coordinates, allowing for statistical analysis of the inclinations of asperities as the base amplitude varies. This, in turn, enables measurements in the direction of kinematically admissible sliding.  
However, it is worth noting that the parameters of the correlation curve depend on the wavelength of the emitted beam from the instrument and, consequently, on the model of the instrument used. To make these correlations directly applicable, the research should include tracking the spectral signature of the specific rock mass under examination.
## 3 Results and Discussion
Time series MODIS NDVI (patterned curve) and EVI (solid curve) data of 2000 to 2007 for natural terrestrial ecosystems in Turkey. The recurrent seasonal order between years on X-axis is Winter, Spring, Summer, and Autumn, respectively; The error bars indicate \(\pm\) one standard deviation (SD) around each mean (patterned and solid lines for NDVI and EVI, respectively, or dashed line when mean NDVI and EVI are the same); (a) (Sub)nival snow/ice; (b) Alpine barren/sparsely vegetated; (c) Boreal barren/sparsely vegetated; (d) Boreal forest; (e) Cool Temperate barren/sparsely vegetated; (f) Cool Temperate grassland; (g) Cool Temperate shrubland/woodland; (h) Cool Temperate forest; (i) Warm Temperate barren/sparsely vegetated; (j) Warm Temperate grassland; (k) Warm Temperate shrubland/woodland; (l) Warm Temperate forest; (m) Mediterranean barren/sparsely vegetated; (n) Mediterranean grassland; (o) Mediterranean shrubland/woodland; and (p) Mediterranean forest. Figure 2: cont. Each wave is characterized by amplitude and phase values, where the amplitude value is defined as half the height of a wave, and the phase value as range between the origin and the peak of a wave. High amplitude values for a given period show a high periodicity of, and thus, a high level of variation in the seasonal VI values. Phase values indicate the length of the time in a given year during which the VI value reaches a peak. In most VI plots where strongly periodic patterns of the seasonal VI (an indication of the presence of high amplitudes) are exhibited, there existed little or no interannual changes in annual phase values (Figures 2 to 4). The amplitudes of the seasonal NDVI data maintained higher values for all the NTE types than those of the EVI data, thus revealing a relatively wide range of the seasonal NDVI values (Figures 2 to 4). Figure 2: cont. The NTEs of (sub)nival snow/ice, and warm temperate and Mediterranean barren/sparsely vegetated lands and grasslands had similar amplitude values (Figures 2 to 4). A tendency was detected for NDVI and EVI to behave more distinctly in terms of the amplitude and phase values for alpine and boreal barren/sparsely vegetated lands, and boreal and Mediterranean forests during senescence (December to March) than the remaining NTEs during greenup (March to May). Alpine and boreal barren/sparsely vegetated lands, and boreal forest had a biomodal temporal EVI pattern that peaked in summer and winter (Figures 2 to 4). Mediterranean forest had less periodic (more chaotic) unimodal EVI and NDVI profiles that peaked in spring and winter, respectively, than the rest of the VI profiles (Figures 2 to 4).
# Flow-Induced Noise Characteristics Analysis of a Pipeline Structure in a Cabin Rigid Corner
## 3 The Acoustic Radiation Equation of the Pipeline Structure in a Rigid Corner
### Acoustic Boundary Condition Influence Analysis  
According to Figure 2, the pipeline structure has four different locations; namely, the distance between the cylindrical shell and three kinds of acoustic boundary conditions were selected to compare the influence of location factor. Figure 3 shows the location position of the pipeline structure. Here, \(l=s=0\) m is defined as the free-space field.  
Four different locations were selected for comparison, namely, the distance between the centers of the cylindrical shell to the rigid acoustic boundary. The influence of flow velocity, frequency, and location on acoustic radiation power were compared, as shown in Figure 8.  
There is a clear distance influence of the center of pipeline to the rigid wall, and the maximum values of the difference were approximately 10 dB in low-frequency scenarios;  
Figure 8: Comparison of acoustic radiation power. (In (a), the flow velocity is 2 m/s; and in (b), the flow velocity is 5 m/s. In Figure 8, \(l=0\) and \(s=0\) represent the pipeline structure location in free space; \(l=0.25\) and \(s=0.25\), \(l=0.25\) and \(s=1\), \(l=1\) and \(s=1\) represent the distance between the center of the pipeline structure to the rigid wall).  
Figure 7: Comparison of acoustic radiation power. (The red line represents the flow velocity 2 m/s and the black line represents the flow velocity 5 m/s).  
when the frequency increased, the influence of the location factor gradually decreased, and the maximum value was approximately 2 dB; in addition, the localization factor on the acoustic radiation power also decreased.  
The total level of acoustic radiation power corresponding to the different positions of the pipeline structure are shown in Table 1.  
As shown in Table 1 and Figure 8, when comparing the frequency and location parameter effects on the acoustic radiation power of the cylindrical shell subject to turbulent fluctuating pressure, the following conclusions can be drawn: (1) In the low-frequency band, the distance parameter of the pipeline structure has a slight influence on the acoustic radiation power parameter. (2) In the low-frequency range, the existence of two rigid surface acoustic boundaries has a significant influence on the acoustic radiation power parameter, and the influence is more obvious at the peak value of the acoustic radiation power parameter; (3) The influence of the acoustic boundary condition decreases if the distance between the cylindrical shell and the acoustic boundary increases. In general, the acoustic boundary characteristics have a significant influence on the acoustic radiation power, especially in the low frequency band.
# On the Quality of Deep Representations for Kepler Light Curves Using Variational Auto-Encoders
## 3 Experimental Setup and Results
### Results
#### 3.3.1 Is the Time Needed?  
Table 1 shows the results on the behavior of the model when using the time information. The first thing to mention is that the learning models, on average, manage to reconstruct the data without the time channel. However, including the delta time channel as input to both sub-architectures (encoder and decoder) helps the methods to regularize the reconstruction. This phenomenon can be seen by the RMSE and MAE metrics since they report an increase when using time, while the Spectral-H indicates that the models leave more noise in the residual reconstructing non-uniform patterns of the original time series. In that sense, the denoising results report that the consecutive values of the reconstructed time series are more auto-correlated and with smoother transitions. All this indicates that the model does not focus on exactly imitating each measurement but generates smoother light curves with more residual noise. This effect is stronger on the \(\text{RAE}_{t}\) model, since the variational loss on \(\text{VRAE}_{t}\) already forces some regularizations.
# A Survey of Visual SLAM Based on RGB-D Images Using Deep Learning and Comparative Study for VOE
## 5 Comparative Study for VOE
### Fine-Tuning VOE Model Based on DL  
Recently, there have been many Visual SLAM and VOE construction models based on the DL method. In this paper, we exploited an MLF-VO framework [35] to fine-tune the VOE model on the TQU-SLAM benchmark dataset. The MLF-VO framework was proposed by [35] with a combination of different fusion strategies to estimate ego-motion from RGB images and depth images obtained from depth sensors. In particular, the MLF-VO framework includes two main tasks with two stages: The first stage is to use the baseline framework to estimate ego-motion using two independent CNN models for depth prediction and pose estimation.At this stage, the MLF-VO framework uses the fully conv. U-Net to obtain architectural depths at four scales.  
The second stage is relative pose estimation based on the MLF-VO framework with the combination of a multi-layer fusion strategy according to several features appearing in intermediate layers of the encoder. To encode features from color and depth images, the MLF-VO framework includes two structural streams. The Channel Exchange (CE) strategy is used to swap the positions of components and their importance for combining features at multiple levels. In both streams, Resnet18, Resnet34, Resnet52, Resnet101, and Resnet152 [234] are used as the encoder. To build an end-to-end automatic learning DL network, the MLF-VO has built a self-learning mechanism with a loss function combined with the process of depth prediction and relative pose estimation.In this paper, we were only interested in fine-tuning the VOE model and fine-tuning using backbones like Resnet18, Resnet34, Resnet52, Resnet101, and Resnet152.
# Dose Calculation Algorithms for External Radiation Therapy: An Overview for Practitioners
## 2 Dose Calculation Algorithm for Photon Beams
### Linear Boltzmann Transport Equations  
The need for a fast and reliable method for absorbed dose calculation resulted in the exploration of deterministic solutions to the coupled linear Boltzmann transport equations (LBTEs) for photons and secondary species (electrons and positrons). LBTEs define for each type of particle the behavior of their distribution function in the phase space under the action of a variety of mutual interaction processes. Once the relevant physics, defining the species interactions that occur in the radiation beam, is properly accounted for, the LBTEs result in a set of kinetic partial integro-differential equations, the numerical solution of which requires the discretization of the phase space in spatial, angular and energy domains [33; 34]. Once the LBTEs are solved for the fluence of the particles, the dose can be calculated by integrating over the fluence direction the electron stopping power via Moller scattering (the only process actually depositing energy in the medium). The advantage of the LBTE solution method over MC methods relies on the fact that deterministic calculations can typically run faster than MC simulations, providing detailed information on the radiation field distribution with no issues related to statistical uncertainty [35].
## 4 Systematic Review of the Research Pillars
### Digital Twins in the Built Environment
#### 4.1.5 AI-Driven Heritage Building Maintenance  
By integrating cutting-edge technologies and data analytics, AI-driven digital twins can significantly optimize the preservation of heritage structures while maintaining their historical integrity. These digital representations make informed decision-making, predictive maintenance, and real-time monitoring possible, guaranteeing that interventions preserve the building's cultural significance. Data Integration for Maintenance, Building Information Modeling (BIM), and Heritage BIM (HBIM) are used in digital twins to generate dynamic models that mimic building behavior, enabling efficient maintenance schedules [61]. IoT devices gather data on structural health and environmental conditions in real-time, allowing for rapid interventions and ongoing monitoring [62; 63]. A socio-technical approach enables an in-depth understanding of heritage structures by integrating social dynamics with building data, forming a framework for adaptive management [64]. According to [PERSON] et al. [64], adaptive management is supported by the iterative system dynamics approach, which guarantees sustainability and resilience throughout time.
## 3 Results  
### Printability of Aluminum Parts in GIS Products  
* According to the proposed decision charts (Table 2), the green area indicates the parameters with a good match to AM as a production method. During this study, and with an evaluation of more than 1500 aluminum parts, it is observed that there are multiple challenges through the path of productization with AM. First, significant numbers of aluminum parts are large and bulky without the remarkable possibility of re-design because of the surrounding elements. Consolidation of multiple parts was also limited because of the multiple material printing requirements. Second, there are costly and time-consuming tests that need to be performed for printed parts before installing them in customer sites except for some aluminum parts used as joints and connections. Another challenge of implementing AM in this industry is the additional required processes such as threading or post-processing for sealing areas. The additional required processes factor is crucial as it will increase the supply chain management risks and cost of the final part. Finally, the required electrical and mechanical properties are significantly high and need additional heat treatment or special powder. Table 4 shows some of the evaluated parts and their limitations. It is clear that most parts are in the range of simple to medium complexity; however, because of their maturity and availability, PBF methods are one of the options for printing.  
The evaluated parts shown in Table 4 are some examples of the analyzed parts and indicate the available AM methods and solutions for most aluminum parts in GIS products. However, more than 90% of the components need additional processes after printing, threading, surface roughness improvements, or heat treatment to increase electrical conductivity or mechanical properties. Therefore, supply chain management will be more complicated, and the benefits of AM resulting from one-step production with a short lead time will be ignored. In addition to printability, the testing and validation of all required standards is an essential step. The high-voltage power industry faces restricted standards and certification for the majority of parts. Pilot testing and going through the certification process is a challenging and costly process, so AM currently can be used for parts with less strict standards.
# Influence of Alternating Temperature on the Effectiveness of EICP in Consolidating Aeolian Sand
## 5 Conclusions  
Based on the mixing method and EICP to consolidate aeolian sand, the differences in calcium carbonate content, calcium carbonate precipitation rate, permeability coefficients,and shear wave velocity of the three alternating temperature experimental groups (T1, T2, and T3) at different maintenance periods were tested and analyzed. Meanwhile, the mineralized external cementation state was observed by SEM. The following conclusions can be drawn.  
1. T2 had the highest calcium carbonate content and the greatest alteration on the permeability coefficient and shear wave velocity, followed by T3 and, finally, T1. The different alternating temperatures would affect the urease survival time, and T2 showed the longest reaction time as the urease stayed active for the longest time;
2. At a high urease activity, vaterites could be clearly observed in the form of spherical or spherical aggregates. Moreover, sand particles could be used as nucleation sites to separate calcium carbonate from solutions, but this adsorption is not strong;
3. T2 reflected the process from sunset to sunrise in a natural desert environment. Utilizing the alternating temperature process, the construction step of mixing the cementing solution into the aeolian sand can be scheduled at sunset to obtain better on-site cementation effectiveness.  
[PERSON], [PERSON], [PERSON] and [PERSON] conceived of the study, designed this study, and carried out the field investigation. [PERSON] and [PERSON] carried out the lab work and analyzed data. [PERSON] and [PERSON] wrote the original manuscript. [PERSON] critically revised the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Major Projects of the Financial Science and Technology Plan of Xinjiang Production and Construction Corps, grant number 2020 AA002.  
Not Application.  
**Data Availability Statement:** Some or all data that support the findings of this study are available from the corresponding authors upon reasonable request.  
The authors declare no competing interests.
# Enhancing Autonomous Vehicle Navigation with a Clothoid-Based Lateral Controller
## 6 Results and Discussion
### Tracking of 8-Shaped Figure  
The figure-8 trajectory shown in Figure 11a combines tight turns with straightaways, requiring the vehicle to constantly adjust its steering angle and lateral acceleration. This tests its ability to handle a wide range of curvature demands. The continuous changes in curvature expose potential weaknesses in the control algorithms, revealing any instability or overcorrections in the steering system.  
Figures 11 and 12 show the lateral control results obtained for an 8-shaped figure. Figure 11b represents the variation of cross-track error throughout the entire simulation run. The maximum cross-track error (CTE) observed throughout the entire simulation  
Figure 11: (**a**) Tracked trajectory of an 8-shaped figure. (**b**) CTE vs. time plot.  
remained below 0.4 m, even during sharp turns. Examining the CTE data in more detail, it becomes apparent that the maximum CTE coincides with segments of the 8-shaped figure where the curvature rate \(\left(\frac{\mathrm{d}\mathrm{x}}{\mathrm{d}s}\right)\) is at its peak. This correlation emphasizes the importance of considering local road geometry and curvature when determining the lookahead distance. The adaptive Frechet distance-based mechanism effectively adjusts the lookahead distance, allowing the controller to anticipate and respond to varying curvature rates, thus minimizing the CTE.  
To understand the controller's behavior during the 8-shaped figure traversal, the steering wheel angle (control input to TruckSim(r)) versus time plot (Figure 12b) provides valuable insights. The lateral controller demonstrated a well-balanced response, keeping both curvature changes and resultant lateral acceleration within reasonable limits throughout the simulation. Figure 12a indicates the change in speed throughout the entire simulation. It can be noted that the vehicle negotiated the curves with a maximum curvature change (\(\mathrm{d}\mathrm{x}/\mathrm{d}s\)) at around 17 mph, a notable speed for such tight turning curves. This is further seen in the steering wheel angle vs. time plot Figure 12b which shows a maximum attained value of around 300 degrees at the points with maximum curvature changes, indicating the controller's ability to track highly demanding winding curves with a low cross-track error solidifying its tracking capabilities.
# Optimal Placement of Vibration Sensors for Industrial Robots Based on Bayesian Theory
## 1 Introduction  
### Background and Significance of the Study  
As more and more robots are introduced into space, industry, and private homes, fault monitoring is becoming a more critical problem. In the past 30 years, fault monitoring and diagnosis methods for various nonlinear systems and robotic systems have been studied. Model-based analytical redundancy methods have been used for fault detection and isolation of nonlinear and robot systems [1, 2, 3].  
The purpose of fault detection technology is to generate fault-sensitive diagnostic signals. In existing automatically controlled systems, faults can occur in both the mechanical and electrical parts of the plant. Fault isolation allows fault-related inputs to be located from all other system inputs and generates specific residual signals for each fault. For example, in an electromechanical system, such as a robot, a single fault may occur in a specific driver, a specific sensor, or a system on a specific component [4, 5].  
For multi-joint robots, dynamics [6], kinematics [7], joint clearance [8], and friction models [9] have been studied. The results show that the mechanical transmission system is an essential part of multi-joint robots to transmit motion and force [10].  
When the transmission accuracy of the robot is reduced, the working efficiency and output product quality decrease, and the positioning accuracy of the robot is also affected by various factors. Therefore, when the sensors are arranged, the motion state information of the joints should be captured as efficiently as possible. In theory, how to define the validity of sensor distribution is the core of solving this problem.