esa-sceva/satcom-chunk-collection huggingface dataset:
## 9 Theoretical Approaches and Cases of Legislation  
The current Civil Act in Korea sets the scope of land ownership \"within the scope, where a justifiable profit exists\". Therefore, whether the right to develop and use underground space and groundwater also belongs to the owner of the land above the underground space will be determined by the concept of \"justifiable profit\" in the same act, based on what standards exist and to what extent the scope can be acknowledged. Conventional theories, views, and cases of legislation focusing on such discussions are as follows.  
First, the theory of unlimited land ownership is considered. According to this view, there is no limit to the scope of land ownership above and below the surface of land, and that the right of thelandowner reaches the root of heaven above the Earth's surface and to the nucleus of the Earth below its surface. By extremely expanding the Roman law stating that the ownership of land reaches both above and below the land through the interpretation of Glossatoren, this theory is derived [22]. The German uniform law, French civil code, and Austrian law are typical cases of legislation that take this stance [23].  
Second, the theory of limited land ownership is considered. According to this view, the scope in which land ownership has effect is limited to the \"scope where a profit exists\", as defined in the Korean Civil Act. This theory is divided into slightly different views in terms of specific standards and arguments or legal relations according to the scope of the limitation. However, they ultimately share the common view that the spatial scope of land ownership above and below the surface of land is not acknowledged to an unlimited extent, but is limited to a certain scope [5]. The civil laws in Korea, Japan, Germany, and Switzerland take this stance.
# A High Capacity Watermarking Technique for the Printed Document
## 2 Related Theory
### Print-Scan Invariant  
In [25], the print-scan process is studied, and the transformation process of the print-scan is obtained as shown in Equation (1), where \(F\) is the character image before the print-scan process, \(F_{ps}\) is the character image after the print-scan process. \(\varphi\) is a kernel function, which is only related to the print-scan process. \(x\) represents the image pixel; \(*\) represents the convolution operation.  
\[F_{ps}(x)=\varphi*F(x) \tag{1}\]  
In [21], the invariant of the print-scan process is obtained by mathematically inferring Equation (1). That is, the ratio of black pixels contained in each character to the average of the black pixels of all characters is an invariant before and after the print-scan process. Then the invariant can be used to embed the watermark. The invariant is defined as shown in Equation (2), where the denominators \(M_{ps}\) and M are the average black pixels of all the characters after print-scan and before print-scan. The numerator is the integral operation for the pixel points of each character on the entire text image.  
\[\frac{\int F_{ps}(x)dx}{M_{ps}}=\frac{\int F(x)dx}{M} \tag{2}\]  
It is worth mentioning that literature [21] also has shortcomings. When watermark embedding is conducted based on the invariant, it is necessary to keep the average value of the pixels of the entire document unchanged, so the text is divided into the embedding part and the adjusting part, and the ratio is 3:1. Therefore the maximum watermark capacity is 75% of the number of characters. In this paper, we find that \(M_{ps}\) and M can be the average of a certain reference line in the text, so that the adjustment part of the literature [21] is not needed to ensure that the average black pixels of the whole document is unchanged. Figure 1 shows the original text image and the scanned text image, and Figure 2 shows the improved print-scan invariant obtained with the first line as a benchmark. As can be observed in Figure 2, the improved print-scan invariant is consistent before and after the print-scan process, and the error here does not exceed 0.015.  
Figure 1: The print-scan process; (**a**) the original binary image; (**b**) the scanned text image.
## 3 Analytical Solution for Anchor Load Transfer
### Debonding State Solution  
As the pull-out load surpasses the plastic limit load (\(P_{sk}\)), the pulling end of the anchored section initiates the debonding stage. In this phase, the plastic and elastic components persist in the deeper regions. As illustrated in Figure 2, near the pulling end of the anchored section, the interfacial shear stress in the debonding part is represented by the residual stress (\(\tau_{2}\)). The elastic and plastic elements in the deeper section can further adhere to Equations (7)-(9) and Equations (16)-(18). Subsequently, the expression for the debonding part can be derived through the following solving process.  
Bringing Equation (5) into Equation (4) gives the differential equation for the debonding part as  
\[\frac{d^{2}s_{h}}{dx^{2}}-\frac{U}{EA}\tau_{2}=0 \tag{20}\]  
The generalized solution of the differential Equation (20) is  
\[s_{h}(x)=\frac{1}{2}Zx^{2}+C_{3}x+C_{4} \tag{21}\]  
where \(C_{3}\) and \(C_{4}\) are coefficients to be determined, and \(Z=\frac{U}{EA}\tau_{2}\). Bringing Equation (21) into Equation (3) yields the axial force distribution in the debonding part of the anchoring section as  
\[p_{h}(x)=-EA(Zx+C_{3}) \tag{22}\]  
From Figure 3c, the boundary condition for the slip stage is \(p_{h}(x)|_{x=0}=P\), \(s_{h}(x)|_{x=L_{2}}=S_{2}\), where \(L_{2}\) is the length of the debonding section. The coefficients to be determined for the corresponding slip sections \(C_{3}\), \(C_{4}\) can be solved as follows:  
\[\left\{\begin{array}{l}C_{3}=-\frac{P}{EA}\\ C_{4}=S_{2}-\frac{1}{2}ZL_{2}^{2}+\frac{PL_{2}}{EA}\end{array}\right. \tag{23}\]  
From the continuity condition of displacement and axial force at any cross-section of the anchor, we can see that \(p_{h}(x)|_{x=L_{2}}=p_{s}(x)|_{x=L_{2}}=P_{sk}\). Bringing in Equation (23) gives  
\[P-U\tau_{2}L_{2}=P_{sk} \tag{24}\]  
Using Equation (24), the length (\(L_{h}\)) of the debonding section under any pullout load (\(P\)) in the debonding stage can be computed, specifically as \(L_{h}=L_{2}\). Similarly, knowing the maximum allowable length (\(L_{h}\)) of the debonding part allows the back-calculation of the maximum ultimate load capacity of the anchor, denoted as \(P_{umax}=P\). The calculation method for the entire process of the anchoring system under the pull-out load at each stage is illustrated in Figure 5.
## 5 Simulation Results
### Single-Entry Interference from Starlink to MSS  
In this scenario, the interfering Starlink satellite was in close proximity to the MSS system, which was actively receiving a transmission from user equipment. This scenario lasted approximately 200 s, aligning with the MSS uplink access duration while considering the necessary carrier-to-noise values. The average distance between the victim MSS receiver and the Starlink transmitter was 1600 km. Figure 8 displays the CDFs of single-entry interference from the Starlink satellite operating in the 1990-1995 MHz frequency band to the typical MSS system.  
The results indicate that in the case of single-entry interference, specifically in a scenario involving the proximity of a Starlink satellite to an MSS system, the end-to-end link performance of the MSS system can experience an Eb/No degradation from 1 to 3 dB. For the most part, the overall BER levels are within acceptable limits. However, it is noteworthy that there can be a significant surge in BER levels under certain conditions. Considering that our MSS link simulation assumed close to ideal conditions, it is reasonable to speculate that in practical scenarios with this type of interference, BER levels could exceed acceptable thresholds for a substantial portion of the time.  
Figure 7: Simulation of the interference from a Starlink satellite to the NTN satellite receiver: (**a**) single-entry interference; (**b**) aggregate interference.
# 3D Stress Analysis of Multilayered Functionally Graded Plates and Shells under Moisture Conditions
## 4 Results
### New Benchmarks
Figure 8: Third benchmark: cylindrical sandwich shell panel featuring an FGM (\(p=0.5\)) core with an imposed moisture content on the top and bottom surfaces. The results are calculated for a thick (\(R_{a}/h=4\)) structure via the 3D(\(\mathcal{M}_{c},3D\)) model. (**a**) Amplitude of \(u\) displacement component. (**b**) Amplitude of \(v\) displacement component. (**c**) Amplitude of \(w\) displacement component. (**d**) Amplitude of \(\sigma_{zz}\) stress component. (**e**) Amplitude of \(\sigma_{\beta\beta}\) stress component. (**f**) Amplitude of \(\gamma_{xz}\) strain component. The fourth and last benchmark proposes a sandwich spherical shell panel, which embeds an FGM core and features simply supported edges. The lamination scheme is analogous to that discussed in the third benchmark: the bottom skin is metallic, and the top ceramic. Then, the volume fraction of the ceramic phase evolves inside the core through the thickness direction following an exponential law with \(p=0.5\) as chosen coefficients. The hygrometric and elastic properties of the sandwich skin are the same proposed in the previous benchmark and assessments for the metallic and ceramic phases, respectively; those of the core follow the volume fraction law. The exponential trend of the volume fraction \(V_{c}\) vs. the non-dimensional thickness coordinate \(\tilde{z}/h\) can be seen in Figure 9a; for completeness, the evolution of the moisture expansion coefficient \(\eta\) through the thickness direction is also given in Figure 10. The spherical shell panel is the only structure among those studied in which both the radii of curvature are non-infinite; furthermore, they take the same value, which equals \(R_{\alpha}=R_{\beta}=10\) m. Furthermore, the dimensions of the reference mid-surface are the same in \(\alpha\), and \(\beta\) directions as both are a function of the radii of curvature; it holds \(a=\frac{\pi}{3}R_{\alpha}\) and \(b=\frac{\pi}{3}R_{\beta}\). Those dimensions are fixed; however, a wide range of thinner/thicker shells is considered by choosing different thickness ratios: \(R_{\alpha}/h\) ranges from 2 to 100. The amplitude of the moisture content is imposed on the top and the bottom surfaces; it equals \(\mathcal{M}_{t}=1.0\%\) and \(\mathcal{M}_{b}=0.0\%\), respectively. As discussed, the external fields are required to have a harmonic form in order for the problem to be exactly solved; \(m=2\) and \(n=2\) are the half-wave numbers considered in this last case study. Table 8 and Figures 9 and 10 summarize an extract of the main results. This fourth benchmark also reports three different sets of results: the elastic model is the same (prefix 3D), but the moisture content profile follows the different approaches. This analysis highlights the distinctions between the three methods. The 3D one is the only model in which no assumptions are made concerning the three-dimensionality of
## 4 Numerical Analysis of the Thermal Performance
### Temperature Comparison  
According to the established model in Section 3, the dynamic temperature series of the tool--chip interface of the ascent stage is calculated and is shown in Figure 15. In Figure 15, the horizontal coordinate indicates the time with a unit of second; the vertical coordinate indicates the measure point with a unit of degree Celsius. As can be seen in this figure, the temperature of the interface increased to the highest temperature of 450 \({}^{\circ}\)C in 30 s and almost kept unchanged.  
Tool-chip interface parameters are extremely difficult to estimate because of the high contact pressure, high temperature, and intense friction applied to the tool-chip interface during the machining process [29; 30]. In this experiment, a thermal imager is employed to acquire the temperature. The measured temperature during the indirect cooling experiment is presented in Figure 16. Figure 16a is the captured tool-chip interface infrared image when the cutting temperature stays at the steady state. There is a reasonable error existing between the value of the actual maximal temperature (433.5 \({}^{\circ}\)C) and that of the predicted temperature (450 \({}^{\circ}\)C). As can be seen in Figure 16b, the temperature decreased dramatically with the insert leaving the workpiece, from 433.5 to 258.5 \({}^{\circ}\)C. Compared with Figure 15, the analytic results show a good consistence that indicates the rationality of established model.  
Figure 17 shows the measured temperature in the conventional dry cutting condition of the three measure points. Compared with Figure 14 which measured in the proposed indirect cooling system, the first measure point maximum temperature is decreased from 80.66 \({}^{\circ}\)C (dry cutting) to 58.47 \({}^{\circ}\)C (ICS), the second measure point maximum temperature was decreased from 69.94 \({}^{\circ}\)C (dry cutting) to 48.56 \({}^{\circ}\)C (ICS), and the third measure point maximum temperature was decreased from 59.23 \({}^{\circ}\)C (dry cutting) to 35.3 \({}^{\circ}\)C (ICS). These decreases indicate the feasibility and heat dissipation productiveness.  
Figure 16: Captured infrared image of the tool-chip interface. (**a**) Steady machining state; (**b**) cutter-shaft backstroking process.  
Figure 15: Predicted temperature on the tool–chip interface.  
Figure 18 shows the temperature comparison between the experimental results (dotted dashed lines) and the numerical results (solid lines) of the placed three measure points the ascent stage. The comparisons show a good agreement which further support the validity of the proposed predicted models.
# An Investigation of Optically Very Thin Ice Clouds from Ground-Based ARM Raman Lidars
## 5 Discussion
For reference, the median absolute uncertainty for all ice cloudy transparent profiles (Figure 3) is 0.029 (0.030) and 0.18 (0.10) for the RL and CALIPSO SGP (TWP), respectively. The median relative uncertainty for all ice cloudy transparent profiles (Figure 3) is 30.3% (33.7%) and 66.8% (72.2%) for the RL and CALIPSO over SGP (TWP), respectively. Analyzing profiles nearby to the optically very thin ice clouds indicates that optically thicker ice clouds are directly adjacent, categorized as cloud edge or in-between clouds. This provides confidence that the optically very thin ice clouds are real atmospheric phenomena and not artifacts of noise. The optically very thin ice clouds detected by the RL indicate the great value in the RL to observe clouds; in particular, those that prove challenging for remote sensing. The temporal structure of optically very thin ice clouds observed by the RL reveals a clear sky-cloud continuum that has also been shown for aerosols and low marine clouds [46; 47]. The clear sky-cloud continuum drifts away from the binary cloud mask approach as a spectrum exists between clear and cloudy sky. The optically very thin ice clouds detected by the RL can aid in estimating a global cloud fraction. Leveraging the strengths of the RL and CALIPSO suggests that the cloud fraction could be around 0.13 larger than the CALIPSO global cloud fraction of 0.66 based on the average difference between the RL and CALIPSO at SGP and TWP. This study is also informative of the ice cloud fraction for transparent profiles. For transparent profiles, the ice cloud fraction could be around 0.17 larger than the CALIPSO global ice cloud fraction of 0.36. The possible underestimation is largely related to the optically very thin ice clouds that can go undetected by CALIPSO. Optically thin ice clouds have recently been discovered to be vitally important for understanding ice cloud climatic impacts. [PERSON] and [PERSON] [11] showed that the median ice water path was more important than the mean ice water path (as previously thought) for determining the cloud radiative forcing of ice clouds due to the abundance of optically thin ice clouds which were largely missed by earlier remote sensing efforts. In this study, we have not quantified the possible radiative effects related to the optically very thin ice clouds, although we expect the overall effect to be small. Other recent studies have calculated cloud radiative forcings of ice clouds for varying locations and altitudes [13; 14; 15; 16]. This necessitates comprehensive ice cloud detection and ice cloud optical depth distributions and highlights the importance for understanding optically very thin ice clouds as presented in this study.
## 5 Construction Execution Activities Management (CEAM).
The digital twin technology can help in tracking resource management and linking between the construction project site and the office through secure data transmission, keeping track of the financial items according to the financial plan prepared and stored in the BIM [26]. This will help in calculating the expenditure for each budget item, for example, worker salaries, raw materials, fixed and overhead costs etc., and can also be useful during the active life of the building [27]. The necessary functions could include a comparison with the tables entered in the system, calculating costs and allocations, monitoring financial flows, as well as operational requests [28] per the project requirements at each stage through a live data flow that also monitors the status of the work. The tracking of the expenses, schedules and supplies helps to understand the progress of the project activities [29]. DTCP also assists decision makers in making estimates about resource availability and calculating the time to completion, which helps in time and deadline management, in addition to recording the inputs and outputs of resources and managing logistics [15; 30]. Additionally, it is possible to expand the scope of DTCP with blockchain technology, which can aid in establishing cybersecurity measures and in achieving compliance management and environmental management tasks [31]. The process of implementing construction projects is a complex one that requires constant follow-up and control in terms of tracking the activity versus the prepared plans, and the digital twin can perform these tasks faster than its human counterparts [2], while also increasing productivity, as results are achieved by collecting the data from the work site and then using it in accomplishing tasks without anomalies. These beneficial aspects are limited by the current intricacies of self-developed systems that combine various technologies and the lack of standardization in data collection and processing [32]. Ensuring the achievement of project objectives, avoiding potential risks and assisting decision makers are critical features for digital twins to be implemented in this sector. The digital replica collects data through sensors and other devices and then compares them to the stored data, including its own history, within a dynamic and interlocking process, providing the possibility for future predictions by use of the proper analytics and algorithms [33]. However, the further development of DTCP towards artificial intelligence solutions compatible with human team members requires considerable efforts in both technical capabilities and project organization [34].
# Performance Evaluation of Multi-UAV Network Applied to Scanning Rocket Impact Area +
## 4 Proposed System
### Communication Subsystem
#### 4.1.2 XBee Pro 900 HP S3B Modules  
According to the adopted scanning strategy and the communication flight requirements, module ZigBee IEEE 802.15.4 developed by ZigBee Alliance associated with IEEE protocol was chosen for communication and data routing. This technology has the appropriate characteristics to provide a wireless sensor network with low power consumption [47].  
This component allows setting the network in star, mesh and tree topologies. The nodes in a ZigBee network are classified according to their logical functions: coordinator, router and end device. A coordinator is the initial network node, which is always in active mode to perform the network control. The router node is used in the mesh and cluster (tree) topologies to increase the network robustness. The router employs routing tables that allow determining the shortest path for a packet to reach its destination, providing the network with the auto-regeneration features if there is a drop in the functionality of other router nodes. End devices are located at the edges of the cluster and star topologies.  
An XBee module is capable of determining reliable routes using an algorithm based on a reactive method derived from an ad-hoc on-demand distance vector (AODV). An associative routing table is used to map a destination node address with its next hop. By sending a message to the next hop address, either the message will reach its destination or be forwarded to an intermediate node, which will route the message on to its destination. If the source node does not have a route to the requested destination, the packet is queued to await a route discovery process. This process is also used when a route fails, which occurs when the source node reaches the maximum number of retries without receiving an ACK [46].
# Fusion of Bilateral 2 DPCA Information for Image Reconstruction and Recognition
## 4 Experiments
### The Effect of Reordering Pixels in Images  
All faces, handwritten characters and palmprint images carry semantic information for humans but not for machines. When analyzed by statistical algorithms, an image is essentially a stack of data. Since 2D algorithms treat an image as a whole without transforming it into a long vector, it is natural to ask whether the image structure information affects the classification performances of the above algorithms. To this end, we reorder the pixels in all images of a database by the same rule and then perform classification as described above.  
Figure 3 shows sample images from the Extended Yale B face database and six variants generated by reordering the pixels in the original images. For clarity, the original image and its six variants are called variants 0 to 6, respectively. The variants 1 to 4 are generated by rotating the original images by 180 degrees clockwise, flipping the original images upside down, flipping the original images in the left/right direction and exchanging the upper half and lower half of the original images. The remaining two variants are generated by randomly reordering pixels of the original images. These reordering rules are representative. Note that when a reordering rule is chosen, it is applied to the whole database to keep the image structure consistent across all images. Then, we conduct image classification tasks on the reordered databases in order to examine the effect of reordering pixels in images.