esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Shear Strength \(q_{max}\)  
To further investigate the effect of remolding water content \(w\), the \(q_{\text{max}}\) value of each curve was extracted and plotted against remolding water content \(w\) in Figure 8. Note that the shear strength \(q_{\text{max}}\) was determined as the peak shear stress observed in the stress-strain curve (see Figure 5). The peak shear stress represented the maximum resistance of the soil to shearing deformation under a given confining pressure, and was therefore commonly regarded as the shear strength in laboratory testing. This method was well-established and has been extensively used in many studies ([PERSON] et al., 2018; [PERSON] et al., 2020)([PERSON] et al., 2018; [PERSON] et al., 2020). As could be observed, for each \(\sigma_{3}\) value, the variation of \(q_{\text{max}}\) with \(w\) exhibited a bi-linear pattern characterized by two distinct slopes, the transition between which occurred at \(w\) = 27.5%. In addition, the slope of \(w\) = 27.5-35% was obviously larger than that of \(w\) = 19-27.5%. Specifically, at \(\sigma_{3}\) = 200 kPa, the slope for \(w\) = 27.5-35% was \(k_{1}\) = 1.07 and for \(w\) = 19-27.5% it was \(k_{2}\) = 0.54. At \(\sigma_{3}\) = 700 kPa, the slope for \(w\) = 27.5-35% was \(k_{1}\) = 0.89 and for \(w\) = 19-27.5% it was \(k_{2}\) = 0.46. At \(\sigma_{3}\) = 1200 kPa, the slope for \(w\) = 27.5-35% was \(k_{1}\) = 0.80 and for \(w\) = 19-27.5% it was \(k_{2}\) = 0.38. Note that \(k_{1}\) and \(k_{2}\) refer to the slopes of the fitting lines corresponding to two different remolding water content ranges (\(w\)\(\leq\) 27.5% and \(w\) > 27.5%). These values were derived from the angle between the trend line and the horizontal axis. The purpose of calculating these slopes was to qualitatively compare the variation trends of a given mechanical parameter with respect to \(w\) within the same coordinate system, under two distinct moisture regimes. Given that the comparison was limited to one single parameter and conducted within the same coordinate system, it was believed that this method was appropriate. The calculated results are summarized in Table 2.  
In addition, it could be observed that the increasing rate of \(q_{\max}\), which reflected the sensitivity of mechanical behavior to \(w\), decreased as \(\sigma_{3}\) increased. Specially, at \(w\leq 27.5\%\), the slope decreased from 0.54 at \(\sigma_{3}\) = 200 kPa to 0.46 at \(\sigma_{3}\) = 700 kPa and further to 0.38 at \(\sigma_{3}\) = 1200 kPa. Similarly, for \(w>27.5\%\), the slope declined from 1.07 to 0.89 and then to 0.80 with increasing \(\sigma_{3}\). This trend could be attributed to the relative contributions of cohesion and internal friction to the overall shear strength \(q_{\max}\). Under low \(\sigma_{3}\) level, \(q_{\max}\) tended to be more sensitive to \(w\) variation because cohesion (primarily attributed to ice cementation between particles) contributed more significantly to the overall \(q_{\max}\). In contrast, at higher \(\sigma_{3}\) level, the contribution of internal friction increased, thereby reducing the relative influence of water-induced cohesion on \(q_{\max}\).
# Robust Optimization of Transport Organization for China Railway Express
## 3 Optimizing China-Europe Freight Train Logistics Amidst Uncertain Transportation Demand  
### Assumptions  
The main assumptions of this article are as follows:  
* Freight trains are differentiated into two categories: domestic section transport trains, which operate exclusively within the domestic leg from the origin freight node to the cargo assembly transit center, and transnational section transport trains, which operate either from the origin freight node to the foreign freight terminal or from the cargo assembly transit center to the foreign freight terminal.
* Each freight train is allowed only a single assembly for transit. This entails adopting either a \"point-to-point\" direct transportation mode or a transfer scenario, where cargo moves from the freight node to the assembly transit center and then to the freight terminal.
* The model assumes a single transport section between any two nodes, with only one mode of transport being used for each section. This simplification aims to focus on the key logistical elements without the complexity of multiple transport modes or sections.
* The model does not differentiate specific sources of demand fluctuations and their impact on each node. This simplification is to streamline the focus on the overall functionality and efficiency of the freight transportation network, avoiding the complexities associated with analyzing individual demand influences at each node.
* The model does not account for the border process, including changes in railway gauge. This exclusion is to maintain focus on the broader aspects of transportation logistics and to simplify the model's scope.
## 4 Results and Discussions  
### Data Acquisition  
Before starting the measurement, checking the sensor array is strongly recommended, which usually includes the connection between the probes and the mounting frame, the measuring range, and the installed attitude of the sensors. Following the flow diagram of the measuring process (see Figure 10), put the sensor array at the calibration platform  
Figure 11: The formal measurement in the test platform. to obtain the distances between sensors at each group. All data would then be stored. Secondly, move the measuring device to the test platform carefully, avoiding bumps, because any change, especially on the sensors, will possibly alter the measurement results during calibration. Finally, start the formal measuring until all the results are acquired and saved. Several tests are carried out and the data are averaged, which helps in reducing unnecessary errors. The platform, which can be seen in Figure 11, is also designed and assembled with a gap of 260 mm. The calibration and measuring results of the sensor groups are settled and given in Table 3. It took about 5 s to get each measured result during the measuring process, showing increased speed compared to the traditional manual measuring technique. Since the two opposite sensors are set as a group, take the z-axis as the vertical direction for both the upper and lower surfaces, then the direction of the x-axis and y-axis coordinates of the measuring points are the same. The z-axis coordinate values of each measuring point are calculated. The three-dimensional coordinate values are shown in Table 4. Substitute the data into the equations introduced before, and the flatness of the upper and lower metal surfaces could be calculated as 0.1621 mm and 0.155 mm, respectively, in which the process has been omitted since it was just calculated. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & \begin{tabular}{c} **x** \\ **Coordinate/mm** \\ \end{tabular} & \begin{tabular}{c} **y** \\ **Coordinate/mm** \\ \end{tabular} & \
\begin{tabular}{c} **z Coordinate** \\ **(Top)/mm** \\ \end{tabular} &
\begin{tabular}{c} **z Coordinate** \\ **(Down)/ mm** \\ \end{tabular} \\ \hline
1 & 0 & 245 & 259.994 & 0.003 \\
2 & \(-240\) & 90 & 260.096 & 0.091 \\
3 & \(-80\) & 120 & 260.003 & \(-0.01\) \\
4 & 80 & 120 & 259.896 & \(-0.107\) \\
5 & 240 & 90 & 260.004 & \(-0.008\) \\
6 & 0 & 0 & 259.988 & \(-0.033\) \\
7 & \(-240\) & \(-90\) & 259.992 & \(-0.003\) \\
8 & \(-80\) & \(-120\) & 260.007 & \(-0.001\) \\
9 & 80 & \(-120\) & 259.992 & \(-0.021\) \\
10 & 240 & \(-90\) & 260.003 & \(-0.002\) \\
11 & 0 & \(-245\) & 260.024 & 0.031 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The coordinates for measuring points.
## 5 Parametric Study
Even achieving a minor improvement becomes extremely challenging at this point. This is because the factors affecting the axial ratio, such as the antenna's geometric structure, the feeding network, and the interactions between different modes are highly sensitive and interrelated. A slight change in one parameter can have a complex and unpredictable impact on the overall axial ratio performance. 3. Optimization of coupling slot radius r  
In the process of achieving the most effective coupling, the inner radius \(r_{1}\) and outer radius \(r_{2}\) of the ring slot are a pair of key parameters. They can be initially calculated using the following formula [29]:  
\[f\approx\frac{c}{\pi(r_{1}+r_{2})\sqrt{\varepsilon_{\text{eff}}}} \tag{4}\]  
\(f\) is the designed central resonance frequency, and \(\varepsilon_{\text{eff}}\) is the effective relative permittivity of the dielectric substrates on both sides of the slot. It can be seen from Figure 6 that the maximum current values of the most central patch are distributed at the edges of the patch. Therefore, the inner radius of the ring slot must be smaller than the side length of the most central patch to ensure that the coupling range of the ring slot can cover the edges of the most central patch. With the inner radius of the ring slot \(r_{1}\) determined to be 3.3 mm, a parametric study on the outer radius of the ring slot \(r_{2}\) is conducted to analyze its impact on the IBW and ARBW. As shown in Figure 10, it presents the axial ratio values of the CP antenna under different \(r_{2}\). As expected, when \(r_{2}\) starts to increase from 4.3 mm, the ARBW of the antenna gradually widens. However, a larger \(r_{2}\) is not always better. After \(r_{2}\) exceeds 5.3 mm, the axial ratio of the antenna increases, and the ARBW narrows. Therefore, setting \(r_{2}\) to 5.3 mm is the optimal choice.
## 2 Related Works
### Four-Directional Total Variation  
In 2011, [PERSON] et al. proposed an extension of TV referred to as TV4 [31] in which both diagonal and back diagonal directional components are included in the typical TV model. TV4 can be defined as  
\[\text{TV4}(\mathbf{F})=\sum_{i,j}(|\mathbf{F}_{i+1,j}-\mathbf{F}_{i,j}|+|\mathbf{F}_{i,j+1}- \mathbf{F}_{i,j}|+|\mathbf{F}_{i+1,j+1}-\mathbf{F}_{i,j}|+|\mathbf{F}_{i+1,j}-\mathbf{F}_{i,j+1}|). \tag{3}\]  
Further, based on TV4, [PERSON] et al. improved the boundary conditions and provided a complete mathematical proof for both anisotropic and isotropic cases [32]:  
\[\text{TV4}_{\text{A}}(\mathbf{F}^{\prime})=\sum_{i,j}(|\mathbf{F}_{i+1,j}^{\prime}- \mathbf{F}_{i,j}^{\prime}|+|\mathbf{F}_{i,j+1}^{\prime}-\mathbf{F}_{i,j}^{\prime}|+|\mathbf{F }_{i+1,j+1}^{\prime}-\mathbf{F}_{i,j}^{\prime}|+|\mathbf{F}_{i+1,j}^{\prime}-\mathbf{F}_{i,j+1}^{\prime}|), \tag{4}\]  
\[\text{TV4}_{\text{I}}(\mathbf{F}^{\prime})=\sum_{i,j}[(\mathbf{F}_{i+1,j}^{\prime}- \mathbf{F}_{i,j}^{\prime})^{2}+(\mathbf{F}_{i,j+1}^{\prime}-\mathbf{F}_{i,j}^{\prime})^{2 }+(\mathbf{F}_{i+1,j+1}^{\prime}-\mathbf{F}_{i,j}^{\prime})^{2}+(\mathbf{F}_{i+1,j}^{\prime }-\mathbf{F}_{i,j+1}^{\prime})^{2}]^{\frac{1}{2}}, \tag{5}\]  
where \(\mathbf{F}^{\prime}\in R^{(m+2)\times(n+2)}\), and \(\text{TV4}_{\text{A}}(\mathbf{F}^{\prime})\) and \(\text{TV4}_{\text{I}}(\mathbf{F}^{\prime})\) represent the anisotropic TV4 and isotropic TV4, respectively.  
Compared with the typical TV, TV4 involves four-dimensional components of the spatial domain; these components consider the entire neighborhood information of every pixel, and thus, contain more structural information of the image.
## 7 Conclusions  
This study took a multi-energy microgrid as its research target, sorted out the energy efficiency and economical models of the key equipment in the microgrid system, presented a double-layer model with optimal configuration, operation, and reliability consideration for the multi-energy microgrid planning, and determined the optimal capacity configuration and energy management scheme via an optimization algorithm. Compared with traditional, independently supplied and operated energy supply methods, joint planning and design considering multi-energy coupling and complement significantly improved the economic performance of the microgrid system. The energy storage device in the microgrid system mitigated fluctuations in the output of distributed power and further enhanced the energy supply reliability of the microgrid.  
In the meantime, this study also proposed a calculation method for energy supply reliability under multi-energy circumstances and perfected the planning model in terms of the economic loss caused by reliability evaluations. The study properly calculated the significance of reliability in planning and compensated for drawbacks in the traditional planning model (which only considers economical factors under normal operation). The optimized design model with the noted reliability consideration can help decision-makers determine the optimal equipment capacity and quantity to satisfy the load demands in actual multi-energy microgrids. The proposed model was designed to not only improve energy supply reliability, but also minimize cost. On this basis, the paper further studied the function of reliability in the maintenance of key units. Based on the proposed reliability assessment techniques, the paper made a comprehensive analysis on the planning, operation, and maintenance of a multi-energy microgrid, providing certain guidance for the future construction of integrated energy systems.  
For future research, regarding reliability evaluation, the impact of the system structure such as lines, pipelines on reliability, as well as the time-delay difference of different energy transmission will be further considered. Moreover, the impact of different operation modes of a microgrid system on reliability will be analyzed as well. In the research on planning methods, energy efficiency, pollutant emissions, and other factors will be further considered to improve the planning model from different perspectives.  
**Funding:** This research was funded by National Natural Science Foundation of China, grant number 51777133.  
**Acknowledgments:** This work was supported by the National Key R&D Plan of China (2017 YFB0903400).  
**Conflicts of Interest:** The author's team has confirmed that there is no conflict of interest in this paper.
# Survey on 5G Physical Layer Security Threats and Countermeasures
## 3 Possible Attack Types on Physical and MAC Layer
### Jamming and Spoofing Mitigation Techniques  
Several techniques have been proposed to mitigate the effects of spoofing attacks to the 4G/5G PHY layer, such as:  
* PSS spoofing can be mitigated using a timer and a blacklist. After a certain time when the SSS is not received, the PSS is blacklisted for a specific time and the second strongest PSS at the channel can be chosen.
* PSS/SSS spoofing can be mitigated by the UE's proactive measures. The UE can generate a comprehensive list of all the cells present within a specific frequency channel. This list should also include the received power levels of each cell, as described in [78]. Then, PBCH can be decoded for the strongest cell and timer applied for decoding MIB. After timer expiration, the second strongest cell can be decoded.
* Spoofing and sniffing can be mitigated by the reduction of information broadcast by MIB and SIB frames, which contain essential information to establish a radio link [79]. Both UEs and base stations implicitly trust all messages before authentication and encryption, potentially leading to security exploits. It is essential to develop methods for UEs to verify a base station's legitimacy before acting on unauthenticated RRC and NAS messages, despite current specifications not requiring this.
## 3 Application to a Case Study
### Analysis of the Factors Affecting the Health of an Offshore Platform Structure
#### 3.5.2 Corrosion  
With increasing service life, the diameter the of steel structure will decrease and pitting corrosion will occur under the action of seawater. This will affect its structural stiffness and natural frequency. Generally speaking, defining an accurate corrosion model is very complex; as such, we use a simple linear model here to describe the corrosion [40]:  
\[r(t)=r_{i}(t-t_{0}), \tag{10}\]  
where \(r(t)\) is the material corrosion thickness at time \(t\), \(r_{i}\) is the annual corrosion rate, and \(t_{0}\) is the time at which corrosion began.  
Corrosion is realized by reducing the component wall thickness with increasing service time. Considering that the corrosion rates of surfaces in air and under the sea are different, it is assumed that the wall thickness of the platform components under the sea surface is reduced by 0.2 mm every year, while that of components exposed to air is reduced by 0.05 mm every year [40].  
The diagram of time-varying effect on frequency under corrosion is shown in Figure 12. It denotes that the platform frequency generally decreases with the increasing of service time. Within the service life, the effects of corrosion on the frequency are 1-10%, so corrosion also has a greater impact on the lower-order modes.
# Intrinsic Interference Cancellation Scheme for FBMC-OQAM Systems Based on Power Multiplexing
## 3 Description of the Proposed Scheme
### Power Multiplexing and Intrinsic Interference Cancellation in Transmitter
Note that data symbol \(a_{1}\) was sacrificed in the transmitter for intrinsic interference cancellation, but fortunately, we recovered \(\hat{a}_{1}\) in (20) with the help of power multiplexing coding in the transmitter and successive interference cancellation in the receiver, contributing to an increase in spectral efficiency compared with previous methods.
### Vehicular Communication Standards Currently in Use  
Vehicle communication standards were established primarily for safety applications in high-mobility contexts. This can help drivers stay safe and inform other road users if a problem arises. The IEEE 802.11 P standard, commonly known as DSRC, is used for vehicle-to-vehicle communication. It facilitates multi-hop communication and works in high-dynamic settings. It does, however, allow for a lot of movement. Due to its limited coverage, it can only converse across a 1000-m range [1].
## 2 Materials and Methods
### Impact Load Test  
#### 2.2.1 Testing Apparatus  
The test model box (dimension of 0.3 m \(\times\) 0.3 m \(\times\) 0.5 m) was made of iron plates (thickness of 3 mm). The boundary reflection seriously affects the test results, especially in the case of a small size and rigid boundary. To reduce this boundary reflection, XPS plates (thickness of 3 cm) were placed at the bottom and surrounding the model box. The small rigidity and high porosity of XPS could effectively reduce the boundary reflection.  
The piezoelectric acceleration sensor DH311E and the acquisition instrument DH5922 used in this study was made by Donghua Co. Ltd. (Jingjiang, China). To avoid being affected by moisture and soil when obtaining data, the acceleration sensor should be wrapped with waterproof plastic bags.
## 7 Conclusions  
Based on a series of data analyses, the evolution characteristics of the strength and dilation parameters of gas hydrate-bearing sediments are systematically studied, and a nonlinearly fitted model is proposed considering the evolution of the mechanical parameters. This model is verified by comparing the numerical and laboratory testing results, and thereafter, it is introduced into the stability analysis of the slope. The main conclusions are as follows:  
1. With increasing plastic shear strain, cohesion (_c_) increases quickly to a peak value and then decreases gradually to a residual value for the samples with different hydrate saturations. The samples with higher hydrate saturations have higher initial values, peak values, and residual values of cohesion (_c_). The internal friction angle (\(\varphi\)) increases quickly with increasing plastic shear strain and then becomes stable at a residual value for all the samples with different hydrate saturations.
2. The dilation angle increases from negative to positive values with increasing plastic shear strain and then becomes stable at a residual value. This shows that compaction occurs at the early stage of compression before expansion happens due to dilation.
3. A non-linearly fitted model is proposed considering the evolution of the mechanical parameters. The parameters in this proposed model have clear physical meanings.
4. The proposed model can simulate the stress-strain behaviors of the GHBS samples well. This model can be applied to different GHBS samples. This model can also be adopted in the stability analysis on the submarine slopes containing hydrate reservoirs. The analytical approach is developed accompanied by the strength reduction method.  
This study can be used for analyzing the stability of hydrate reservoirs. However, this research has not considered the process of hydrate decomposition. This will be studied further in future research.  
Conceptualization, C.C.; methodology, C.C.; software, J.Y. (jincai Yu); validation, C.C. and J.Y. (jincai Yu); formal analysis, C.C. and J.Y. (jincai Yu); investigation, C.C., J.Y. (jincai Yu), and J.Y. (jincai Yang); resources, C.C. and J.Y. (jincai Yu); data curation, J.Y. (jincai Yu) and J.Y. (jintao Yang); writing--original draft preparation, J.Y. (jincai Yu); writing--review and editing, C.C.; supervision, C.C.; funding acquisition, C.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (No. 51991362).  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
[PERSON], [PERSON], [PERSON], and [PERSON] are appreciated here for their help in data processing.  
The authors declare no conflicts of interest.  
\begin{table}
\begin{tabular}{c c} \hline \(\mathbf{S_{h}}\) & \(\mathbf{F}\) \\ \hline
0\% & 1.92 \\
27\(-\)34\% & 2.15 \\
41\(-\)45\% & 2.32 \\ \hline \end{tabular}
\end{table}
Table 9: The safety factors of the slope under each gas hydrate saturation.
# Smart System to Detect Painting Defects in Shipyards: Vision AI and a Deep-Learning Approach
## 2 Related Methods
### Defect Detection Methods  
#### 2.2.1 Handcrafted-Feature Method  
Detection systems based on image processing have been developed and used to overcome the limitations of visual inspection. A representative example is a handcrafted-feature method that uses machine learning to define, beforehand, the feature points of defective images. It was applied to various industrial processes, such as those involving automobiles and semiconductors. This method is highly accurate when the input data are relatively standardized. However, when various types of input data or new patterns occur, its detection capabilities are limited [4].
# Construction and Application of an Ecological Quality Evaluation System Based on a PIE-Engine +
## 2 Materials
### Construction of the Remote Sensing Index of Ecological Quality  
Ecosystem quality reflects the condition of the whole or part of the ecosystem within a certain time and space, which is reflected in the ecosystem function, ecosystem stability, external disturbances, and impacts on human survival and sustainable socioeconomic development. The ecological quality index constructed in this paper consists of three main components: the Ecological Function Index (EFI), which reflects the status of regional ecological function; the Ecological Stability Index (ESI), which reflects the changes in ecosystem; and the Ecological Threat Index (ETI), which indicates the pressure caused by human activities and serves as an early warning indicator.
## 3 Experimental Setup
### Assessment Parameters
#### 3.8.2 Thermal Efficiency  
The influence of the longitudinal tilt angle of the secondary system is determined by the thermal efficiency (\(\eta_{th}\)) of the cooling system defined as the ratio between the useful heat and the power not converted into electricity by the photovoltaic cells.  
\[\eta_{th}=\frac{Q_{u}}{Q_{th}} \tag{14}\]  
where \(Q_{u}\) is the useful heat (W) and \(Q_{th}\) is the power not converted into electricity by the \(PV\) system (W).