esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Review of Studies Related to Sustainability in the Context of Multi-Modal Mobility
### Review of Studies
Measuring the MAG is an important issue in cities with multi-modal transportation networks. The study [108] measures the MAG in multi-modal transportation networks across the metropolitan area of Nanjing, China taking into account the factors of travel modes, traffic conditions, the location and attractiveness of the destination. The results indicate that there are substantial differences between public and private transport for a \"door-to-door\" trip in a multi-modal urban network environment. The accessibility of cars is always better than that of the transit and cycling modes. The smallest MAG between the transit mode and the car mode changes with traffic fluctuations and is distributed along metro and bus routes. MAG is influenced by conditions of road destiny, river obstacles, and the cross-river channel. The minimal MAG between the cycling mode and car mode is in central urban areas. 18. Question: How to assess the impact of home-to-work travel on sustainability? Results: Assessing the impact of home-to-work travel on sustainability is an interesting and important issue as it requires application of tools and methodologies for the analysis. In [89], the authors proposed a methodology for assessing the sustainability of home-to-work travel with shuttle service in the ENEA Casaccia Research Centre based on post-cost-benefit assessment. The findings show that operating the home-to-work shuttle service leads to reductions of 97% of volatile organic compounds, 72% of particulate matter, and 60% of carbon dioxide. Furthermore, the analysis shows that the benefits for users and the community are estimated to be EUR 1.35 million per year. 19. Results: How to reconstruct a damaged urban system following earthquake to implement a more sustainable efficient urban transport system? Results: Reconstructing a damaged urban system following earthquake relies on applying an appropriate method or principles. The research issue is not just to reconstruct the original urban but also to implement a more sustainable efficient urban transport system. An analysis of the influence of the earthquake on urban systems and mobility was carried out in [102]. An operating strategy integrating urban design with sustainable mobility strategies was proposed. The study shows that the post-quake reconstruction provides an opportunity to construct and implement a more sustainable efficient urban transport model through advanced technologies.
# Ordered Subspace Clustering for Complex Non-Rigid Motion by 3D Reconstruction
## 5 Experiments and Analysis
### Clustering on UMPM Motion Dataset  
The UMPM Benchmark consists of a set of human motion sequences collected in the real environment, which can be regarded as complex and various non-rigid motion due to several representative daily human actions and interactions of big range change of poses/shapes. Each motion sequences are performed by 1, 2, 3 or 4 persons, and acquired under four fixed viewpoints. The dataset includes the synchronized video recordings and 3D joints information, which were captured by motion capture device. This paper selected eight coherent motion sequences \(\{^{a}p1-table-2^{a}\), \({}^{a}p1-grab-3^{a}\), \({}^{a}p1-chair-2^{a}\), \({}^{a}p2-staticsyn-1^{a}\), \({}^{a}p4-free-11^{a}\), \({}^{a}p1-orthosyn-1^{a}\), \({}^{a}p3-ball-1^{a}\), \({}^{a}p3-meet-2^{a}\)} to evaluate our method. Here, the video named \({}^{a}p1-table-2^{a}\) represents a video recorded by one person performing two actions around the table. The sample images and markers of UMPM dataset [26] are shown in Figure 5.  
As each of the video was relatively large, about 5600 frames, we picked one frame every eight frames, therefore, in total 700 frames were used for testing. We used 15 virtual joint positions per subject as inputs, and then according to the given camera parameters, the corresponding 3D joint position may be reconstructed. In the following, our proposed method will report the ordered subspace clustering result via 3D reconstruction. Since the UMPM dataset contains the known 3D joint positions obtained directly from the motion capture markers. This paper conducts LRR on the 3D ground-truth,  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Actions**} & \multicolumn{4}{c}{**Normalized Mutual Information (NMI)**} \\ \cline{2-6}  & **CNRMS** & **Proposed** & **LRR** & **OSC** & **QOSC** & **SSC** \\ \hline
2 & 0.0293 & 0.6674 & 0.1023 & 0.2002 & 0.8157 & 0.0571 \\
3 & 0.0567 & 0.6425 & 0.1812 & 0.2954 & 0.7910 & 0.2236 \\
5 & 0.0919 & 0.6606 & 0.2706 & 0.4197 & 0.7044 & 0.3158 \\
8 & 0.1199 & 0.8348 & 0.3622 & 0.
# Energy-Efficient Controller Placement in Software-Defined Satellite-Terrestrial Integrated Network
## 5 Simulation Results
### Analysis of the Architecture  
The location of controllers determines the control mode of network, which also effects the efficiency of message processing. The controllers deployed on the ground network are often located at the pre-selected geographical location [43]. We compare the performance of the controller located on the LEO satellites with the satellite gateways on the ground.  
Figure 5 shows the effect of controller location on energy consumption and average latency. We compare the architecture deployed controllers on LEO satellite with controllers on satellite gateway. Since there are five satellite gateways deployed on the Belt and Road, the number of controllers is set from one to five for comparison. When the number of controllers is equivalent, the architecture which deploys controllers on LEO satellites consumes less energy and achieves lower latency than the controllers on the satellite gateway. In addition, when there are five controllers on LEO satellites, it saves nearly 30% on energy consumption and latency compared to controllers on the satellite gateway.  
The controllers on the satellite gateway are located on the Belt and Road and are close to each other in geography. The satellite gateway is prone to reaching its capacity with the increased number of controllers. The proposed software-defined STIN architecture considers the controllers on LEO satellites. We also adopt the MSAP algorithm to enumerate the optimal location of controllers. In this manner, it reduces energy consumption and average latency with the increased number of controllers.  
Figure 4: The snapshot of Iridium network at 1 January 2020 12 PM GMT (the satellite nodes are shown with blue circles, and the satellite gateways are denoted with orange).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline \(P_{out}^{\text{max}}\) (mJ) & 7.639 \\ \(P_{in}^{\text{max}}\) (mJ) & 1.944 \\ \(S_{ij}\) (Byte) & 160 \\ \(P_{in}^{j}\) (nJ/B) & 5.634 \\ \(P_{i}^{j}\) (nJ/B) & 8.406 \\ \(R\) (Mbps) & \(\{100,200,300,500\}\) \\ \(N_{j}\) (Byte) & 280 \\ \(T_{0}\) (\({}^{\circ}\)C) & 1 \\ \(T_{final}\) (\({}^{\circ}\)C) & 0.0001 \\ \(\alpha\) & 0.75 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Simulation parameters.
## 5 Ride Performance Analysis
### Result Analysis  
As stated in the introduction, many full or half tracked vehicle models have been developed for the systematic evaluation of suspension performance. Furthermore, a two-dimensional model of a tracked vehicle is found to be sufficient for detailed analyses of the suspension dynamics and associated shock and vibration environment of the vehicle [14]. Based on the verified single-cylinder model, the half-vehicle hydropneumatic suspension system is established by AMESim, as shown in Figure 10, which is composed of six hydropneumatic suspension units. Moreover, the MBD in-plane model of the vehicle is conducted based on the practical parameters in Table 4. The data exchange is carried out by the interface module between the two platforms. The aforementioned tension system in Figure 5 is taken as a spring force.  
While ensuring the mode switching time in the real scenarios, the pitch and heave vibrations of the tracked vehicle should also be taken into consideration at the same time [29]. The vehicle is designated to traverse two non-deformable specially designed road profile at a constant forward speed of 1 km/h to find a trade-off between the work efficiency and  
Figure 9: Exerted force (**a**) Force-displacement loop (**b**) Force-velocity loop.  
vehicle stability. The height of the obstacles refers to the size of the China Railway Track System (CRTS) as shown in Figure 10(a). The height of the trapezoidal barrier in Figure 10(b) is the same as the height of the rail track (176 mm). The height of the step barrier in Figure 10(c) is the same as the height of the rail board (200 mm). In the road modelling process, a little inclination to the original vertical road surface can speed up the calculation process and avoid errors reporting without affecting the accuracy of simulation results.  
Based on the current compact suspension design space, the size range of the cylinder-piston assembly is already minimal. Therefore, the virtual tests are conducted under the different initial gas volumes (\(V_{1}\)), varied diameters (\(d\)) and lengths (\(l\)) of the damping pipe.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Structure Parameters** & **Unit** & **Value** & **Structure Parameters** & **Unit** & **Value** \\ \hline Mass of half-vehicle & kg & 1250 & Sprocket tooth height & mm & 28 \\ Length of the chassis & mm & 3771 & Track width & mm & 350 \\ Height of the chassis & mm & 633 & Diameter of tension wheel & mm & 300 \\ Sprocket pitch & mm & 90 & Diameter of load wheel & mm & 420 \\ Sprocket teeth number & & 12 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Vehicle parameters.  
Figure 11: Road surface establishment (**a**) CRTSI railway (**b**) Trapezoidal barrier (**c**) Step Barrier.  
Figure 10: Hydraulic system model of the hydropneumatic suspension.  
The influences of the above parameters on the vehicle ride performance are investigated in the following.
## 3 Results
### Study of a Frame-Type Structure  
The optimization studies carried out focus on frame-type structures with square cross-sections, having as a goal the minimization of the maximum resultant displacement while considering mass constraints. Although in the present work only square cross-sections were considered, other geometrical configurations could be considered, either standard or customized ones, as the implementation considered allows us to deal with continuous or discrete design variables. In addition, other constraints could also be accommodated, for example, related to Eurocode design rules, manufacturability constraints, or cost sensitivity factors. However, considering the aim of this work, related to the evaluation of the mentioned dataflow, only stiffness and mass constraints were considered in the next case studies.  
The frame-type structures studied have the configuration and loading illustrated in Figure 4. The design variables are related to the members' cross-section dimensions.  
In the present study, a selective discretization approach was adopted, considering 10 quadratic beam elements in the member subject to distributed loading, and 5 elements in the remaining ones. This discretized model was selected after convergence tests.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Number**} & \multicolumn{5}{c}{**Number of Iterations**} \\ \cline{3-8}  & **of Foxes** & **50** & **100** & **150** & **200** & **500** & **1000** \\ \hline Mean & \multirow{2}{*}{10} & \(-12.7866\) & \(-13.5320\) & \(-13.5320\) & \(-13.0820\) & \(-13.5320\) & \(-13.5320\) \\ SD & & \(1.4910\) & \(1.0257\times 10^{-10}\) & \(2.4418\times 10^{-10}\) & \(1.3502\times 10^{-11}\) & \(2.3262\times 10^{-13}\) & \(9.3925\times 10^{-14}\) \\ \hline Mean & \multirow{2}{*}{20} & \(-12.7737\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) \\ SD & & \(1.5796\) & \(1.0581\times 10^{-11}\) & \(3.4485\times 10^{-12}\) & \(1.3143\times 10^{-11}\) & \(1.7249\times 10^{-13}\) & \(1.7764\times 10^{-15}\) \\ \hline Mean & \multirow{2}{*}{30} & \(-13.5319\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) \\ SD & & \(0.0003\) & \(2.8218\times 10^{-11}\) & \(1.4790\times 10^{-12}\) & \(1.9876\times 10^{-14}\) & \(6.4782\times 10^{-15}\) & \(3.2269\times 10^{-15}\) \\ \hline Mean & \multirow{2}{*}{40} & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) \\ SD & & \(5.7240\times 10^{-7}\) & \(1.7452\times 10^{-11}\) & \(6.8349\times 10^{-12}\) & \(4.3701\times 10^{-12}\) & \(9.3638\times 10^{-14}\) & \(1.6852\times 10^{-15}\) \\ \hline Mean & \multirow{2}{*}{50} & \(-13.1565\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) & \(-13.5320\) \\ SD & & \(1.1265\) & \(2.9396\times 10^{-11}\) & \(2.9753\times 10^{-13}\) & \(3.1482\times 10^{-14}\) & \(6.3553\times 10^{-15}\) & \(1.7764\times 10^{-15}\) \\ \hline \hline \end{tabular}
\end{table}
Table 8: Effect of the optimization parameters _tmax_ and \(N\) on the results obtained for the benchmark Jones function.
# Creep Characteristics of Soil in the Sliding Zone of Huangtupo Landslide
## 4 Shear Creep Model and Verification
### The Comparison of Fitted Curves and Experimental Curves  
The Burgers model was used to fit the creep process of the sliding zone soil under different consolidation paths. The results are shown in Figure 13. Table 2 shows the fitting results of the constructed creep model parameters, and it can be seen that the Burgers model fits the experimental data to a high degree and can represent the creep characteristics of the sliding zone soil.  
The comparative analysis showed that the Burgers model had a high degree of fitting to the curve, and R\({}^{2}\) was concentrated between 0.88 and 0.99. The Burgers model was composed of elements with mechanical properties. The parameters in the equation reflect the mechanical meaning of the elements in the model, and changes in the parameters can reflect the variation of the internal mechanical properties of the specimen during the test. Therefore, this model is more accurate and applicable to the creep description of sliding zone soil, and research using this method is more meaningful.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Sample Number** & \(\tau\) **(kPa)** & \(G_{1}\) **(kPa)** & \(G_{2}\) **(kPa)** & \(\eta_{1}\) **(kPa h)** & \(\eta_{2}\) **(kPa h)** & \(\mathbf{R^{2}}\) \\ \hline \multirow{8}{*}{HD-1} & 17.85 & 1358 & 3198 & \(2.07\times 10^{4}\) & 468 & 0.885 \\  & 40.47 & 759 & 1501 & \(5.18\times 10^{4}\) & 1960 & 0.964 \\  & 59.51 & 293.4 & 807.4 & \(6.67\times 10^{4}\) & 501.2 & 0.94 \\  & 79.74 & 160.9 & 198.8 & \(5.21\times 10^{4}\) & 28.8 & 0.91 \\  & 101.17 & 23.29 & 50.6 & \(3.74\times 10^{4}\) & 6.78 & 0.88 \\  & 22.15 & 1567 & 3215 & \(2.20\times 10^{4}\) & 394 & 0.896 \\  & 50.21 & 803.6 & 1824 & \(8.50\times 10^{4}\) & 1820 & 0.895 \\ HD-2 & 73.85 & 318.6 & 1158 & \(7.23\times 10^{4}\) & 1982 & 0.967 \\  & 98.95 & 175.4 & 423.9 & \(5.84\times 10^{4}\) & 269.7 & 0.905 \\  & 125.54 & 30.56 & 60.8 & \(3.42\times 10^{4}\) & 10.21 & 0.971 \\  & 26.46 & 1711 & 4054 & \(2.18\times 10^{4}\) & 714 & 0.919 \\  & 59.97 & 903.2 & 3982 & \(9.50\times 10^{4}\) & 1750 & 0.956 \\ HD-3 & 88.19 & 600.2 & 2169 & \(9.20\times 10^{4}\) & 3605 & 0.966 \\  & 118.17 & 301.3 & 709.7 & \(8.60\times 10^{4}\) & 348.8 & 0.926 \\  & 149.91 & 3.84 & 39.6 & \(3.84\times 10^{4}\) & 6.31 & 0.971 \\  & 30.76 & 2048 & 5312 & \(2.10\times 10^{4}\) & 783 & 0.901 \\  & 69.71 & 1699 & 4839.9 & \(1.02\times 10^{5}\) & 2239 & 0.9522 \\ HD-4 & 102.52 & 749.3 & 3158.4 & \(1.40\times 10^{5}\) & 6172 & 0.9646 \\  & 137.38 & 474.4 & 1273.9 & \(1.20\times 10^{5}\) & 1573 & 0.9454 \\  & 174.28 & 300.2 & 131.24 & \(4.20\times 10^{4}\) & 53.26 & 0.987 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Burgers constitutive model parameters.  
Figure 13: Comparison between the fitting curve and the experimental data.
## 4 Results
### Discontinuity Identification Results  
In the discontinuity identification algorithm, the configuration of numerical parameters plays a decisive role in detection accuracy, noise robustness, and computational efficiency. According to the characteristics of complex lighting conditions and high vegetation coverage in the study area, firstly, the image size of the study area is unified, and the  
\begin{table}
\begin{tabular}{l c} \hline \hline
**UAV Platform Parameters** & \\ \hline Positioning accuracy & 1.5 cm + 1 ppm (vertical), 1 cm + 1 ppm (horizontal) \\ Maximum speed & 14 m/s \\ Operation temperature & 0 \({}^{\circ}\)C to 40 \({}^{\circ}\)C \\ Flight duration & 30 min \\ \hline
**Camera Parameters** & \\ \hline Lens & DJI DL 24 mm F2.8 LS ASPH, FOV 84\({}^{\circ}\) \\ Image dimensions & 8192 \(\times\) 5460 with 45 MP effective pixels \\ Sensor size & 35.9 \(\times\) 24 mm \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters of the DJI PHANTOM 4 RTK and DJI Zenmuse P1.  
Figure 4: The 3D point cloud model of the slope.  
threshold interval of strong edge and weak edge is defined. Then, the image denoised by PCA is filtered by a Gaussian filter with a kernel of 9 \(\times\) 9. The setting of this parameter can effectively suppress the vegetation texture interference and sensor noise while maintaining the macro continuity of the discontinuity edge. Through repeated experiments, we found that the effect of selecting a low threshold of 150 and a high threshold of 350 to identify the discontinuity on the slope in the study area is better. We identified discontinuities within the entire model of the slope, ultimately obtaining 1401 discontinuity surfaces, as detailed in Figure 5.
On the other hand, the limitation of photon number of a high harmonic source no longer exists, which is quite important for many potential applications. Based on a home-made 200-TW/1-Hz Ti: Sapphire laser facility [16], significant progress on LWFA has been achieved in Shanghai Institute of Optics and Fine Mechanics (SIOM) [17]. The progress on LWFA has also opened a new opportunity for the development of compact XFEL. Researches on full-coherent HHG-seeding XFEL are now carrying out at SIOM. However, producing XFEL requires at least multi-hundred-TW laser systems. To decrease the timing jitter between LWFA and HHG, it is better for them to come from the same laser source. However, the beam quality, and the shot-to-shot energy fluctuation of the hundred-TW-level laser are not comparable to a few TW laser system, and they are still problems for HHG. Thus, it is a promising work to optimize HHG driven by multi-hundred TW laser systems. In this work, we used a 200-TW/1-Hz Ti: Sapphire laser amplifier system based on a chirped pulse amplification [16]. This laser system consists of four-stage Ti: Sapphire amplifiers, which can produce an output energy of 8 J at a central wavelength of 800 nm with a pulse duration of 30 fs (FWHM). In order to achieve the full-coherent XFEL, the laser was separated into two beams. The main laser beam, which has a peak power of nearly 200 TW, was used to produce the high-performance electron beam by LWFA. The other laser beam, which has a peak power of 1.3 TW, was used to produce soft X-rays in the HHG experiment. By using generally adopted loosely focusing method and optimizing the phase-matching conditions, we have obtained bright high-order harmonics around 30 nm. Output energy of the 29 th harmonic (27.6 nm) reached as high as 100 nJ per pulse, and the harmonic beam divergence was estimated to be 0.3 mrad (FWHM). In this experiment, bright stable HHG has been achieved, which is an important step in the production of highly stabilized ultrashort XFEL.
# A Reconfigurable Single-/Dual-Bandstop Filter with Controllable Equal-Ripple Performance
## 2 Design and Analysis of the Proposed Reconfigurable BSF
### State II: D-Bsf  
As shown in Figure 1, when the PIN diodes are switched to ON state, the proposed reconfigurable BSF exhibits the D-BSF performance.
# Experimental Analysis of a Novel GFRP Stiffened Pipe
## 4 Results and Discussion
### Deformation Analysis  
#### 4.2.1 Plain Pipes Compared with the Outer Stiffened Pipes  
The typical strain-time curves for each type of pipe with the same internal diameter of 400 mm and same materials are given in Figures 10 and 11, respectively. It can be seen that the strains increased with the increased compressive load throughout the loading  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Diameter (mm)** & **Type** & **No.** & **Deflection (m)** & **Load (N)** & \(\mathbf{D_{m}}\) **(m)** & \(\mathbf{s_{0}}\) **(Pa)** \\ \hline \multirow{4}{*}{400} & \multirow{4}{*}{Plain} & P1 & 0.012 & 3465.2 & 0.40844 & 18,571.23 \\  & & P2 & 0.012 & 3654.1 & 0.40844 & 19,583.61 \\  & & P3 & 0.012 & 3636.0 & 0.40844 & 19,486.61 \\ \cline{2-6}  & \multirow{4}{*}{Stiffened} & OS1 & 0.012 & 4550.9 & 0.40844 & 24,065.52 \\  & & OS2 & 0.012 & 5200.1 & 0.40844 & 27,498.54 \\  & & OS3 & 0.012 & 5373.2 & 0.40844 & 28,413.91 \\ \hline \multirow{4}{*}{500} & \multirow{4}{*}{Plain} & P1 & 0.015 & 2152.8 & 0.50897 & 9430.38 \\  & & P2 & 0.015 & 2480.7 & 0.50897 & 10,620.09 \\  & & P3 & 0.015 & 2388.2 & 0.50897 & 10,095.66 \\ \cline{2-6}  & \multirow{4}{*}{Stiffened} & IS1 & 0.015 & 2712.5 & 0.50897 & 11,574.31 \\ \cline{1-1}  & & IS2 & 0.015 & 3001.1 & 0.50897 & 12,805.77 \\ \cline{1-1}  & & IS3 & 0.015 & 2537.2 & 0.50897 & 10,826.30 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of pipe ring stiffness results under different structural designs at 3% \(D_{m}\) displacement point.  
process, and the mechanical behaviors for both pipes exhibited a linear trend before the final structure failure. The results also show that there was a certain level of consistency between the strain responses in each pipe group. For instance, the strains measured at different points along the axis of the pipe were small, which is mainly attributed to the loading carried out along the radial direction of the pipe. The strains increased most quickly at the \(0^{\circ}\) oblique point and \(90^{\circ}\) hoop point, especially at the point of the \(90^{\circ}\) hoop in Figure 10, which resulted in the first local fractures of the outer web at that place (as shown in Figure 14). The applied compressive load acted on the specimen and deformed the cross-section from the original circular shape into an oval shape. With compressive loads applied continuously, the minor axis of the oxidized cross-section became shorter and its major axis grew longer. Then, the point at \(90^{\circ}\) was farthest from the major axis, and the inner wall was under pressure. Correspondingly, the deformation at the \(45^{\circ}\) point was relatively small, so the strain levels in the three directions at this point were low. The deformations at points of \(0^{\circ}\) and \(180^{\circ}\) were similar, and were the farthest points from the minor axis of the oval, where the inner wall was under tension, and the hoop strain increased with the increase of the load.  
Figure 10: A typical strain-time curve for the outer stiffened type of DN400.