esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Payload Characteristics and Thermal Control Requirements  
### The Overall Distribution of Payloads in CSS  
The initial plan for CSS included three sealed modules, the overall configuration is \"T\" shaped structure [20] and each module of CSS has a different number of payloads inside. Similar to the International Space Station (ISS), the payloads were mainly installed inside as standard-style racks; the number and spatial distribution of the racks in different modules of the space station are shown in Figure 1:  
Taking module 2 as an example, there are seven payload racks in the module, which are used for scientific experiments in multidisciplinary fields. The system support rack is mainly used for the integrated power distribution, numerical control and thermal control of the payloads in the module. In addition, a new kind of rack is arranged for the verification of the new technology on orbit. It also contains two empty racks for the installation of subsequent uplink loads for CSS [21; 22; 23; 24]. The total thermal power of the whole module is 5500 W, and the maximum power of a single rack is 2300 W. The space station platform provides the installation and heat exchange boundary for the experimental payload rack. The thermal environment and heat boundary inside the module are as shown in Figure 2, specific thermal boundary conditions are described as follows:  
1. Heat conduction installation boundary  
The heat source of the rack is installed in the module via hinged installation, and the installation point adopts the method of heat insulation as far as possible so as to reduce the heat transfer from the heat source of the rack to the module wall.
2. Air convection environment  
The natural convection heat transfer is obviously weakened in the micro-gravity environment of the payload rack in the module. The environmental control ventilation system in the module contacts the payload rack through the front surface for heat transfer.  
Figure 1: Distribution of the payloads in every module of CSS.  
Radiation background environment  
There is radiative heat exchange between the payload rack and the surroundings; the payload rack will radiate heat to the surrounding environment through surface and, at the same time, receive radiative heat from the surrounding equipment.  
The boundary of fluid heat dissipation  
The payload racks in the module have the characteristics of large heat consumption and long-term work; the convective ventilation and radiation cannot meet the demand of heat dissipation. Therefore, the active thermal control resources available in the space station platform are used as the interface for the thermal management of the payload system.
## 4 Performance Metric
### Bleu  
BLEU [46] is one of the most widely used metrics for evaluating the performance of machine translation and natural language generation models. It measures the similarity between a generated sentence and a reference sentence based on _n_-gram overlap. BLEU typically calculates precision from unigrams (1-g) to four-grams (4-g) and applies a brevity penalty (BP) to address the issue of shorter sentences receiving disproportionately high scores. The BLEU score is computed using the following formula:  
\[\text{BLEU}=BP\cdot\exp\left(\sum_{n=1}^{N}w_{n}\log p_{n}\right) \tag{1}\]  
where \(p_{n}\) represents the _n_-gram precision value, and \(w_{n}\) denotes the weight, which is typically set as \(w_{n}=\frac{1}{N}\). The brevity penalty (BP) is introduced to penalize excessively short generated sequences and can be formally defined by the following equation:  
\[BP=\begin{cases}1,&\text{if }c>r\\ e^{(1-r/c)},&\text{if }c\leq r\end{cases} \tag{2}\]  
where \(c\) represents the length of the generated sentence, while \(r\) denotes the length of the reference sentence.  
BLEU allows for quantitative performance comparison. However, it has limitations in capturing contextual meaning, as it does not account for synonyms or the flexibility of sentence structures.
# Stiffness Estimation and Equivalence of Boundary Conditions in FEM Models
## 2 Equivalence Method Based on a Series of Static Analyses
### Results and Discussion  
The equivalent stiffness coefficients calculated by the above procedure were used in the definition of the bushing connector in the equivalent FE model. Their values are given in Table 2. The assumption of the equivalence method is that the finite element model modified in this way retains the stiffness properties of the original model and can therefore be used in further static or dynamic analyses. In order to verify this assumption, both FE models, the complete reference model (Figure 1a) and the equivalent model (Figure 2b), were subjected to modal analysis to assess their modal properties. A Lanczos eigensolver  
Figure 2: (**a**) Removed part of the model used to obtain the stiffness coefficients; (**b**) the equivalent model with bushing connector.  
was used to calculate the natural frequencies and the modes shapes of the beam in the frequency range up to 5000 Hz.  
The natural frequencies of both models are compared in Table 3. Some corresponding mode shapes are shown in Figure 3. The results obtained show very good agreement. The natural frequency values of the equivalent model differ from the reference values in the range from \(-0.06\%\) to \(4.21\%\). The average percentage change is \(1.33\%\). Negligible differences were also found for the mode shapes, which means that the equivalent model response corresponds to the response of the original complete model. In addition to maintaining dynamic behavior, the model was significantly simplified. The number of elements decreased from 59,747 to 15,148. Based on these findings, it can be concluded that the equivalence method works correctly.  
\begin{table}
\begin{tabular}{c c c} \hline
**The Equivalent Translational Stiffness in x-, y-, z- Direction** \\ \hline \(k_{x}=3.97\times 10^{5}\) N/mm & \(k_{y}=1.01\times 10^{5}\) N/mm & \(k_{z}=9.8\times 10^{3}\) N/mm \\ \hline \multicolumn{3}{c}{**The Equivalent Rotational Stiffness about x-, y-, z- Axis**} \\ \hline \(k_{qx}=1.547\times 10^{6}\) N.mm/rad & \(k_{qy}=9.72\times 10^{5}\) N.mm/rad & \(k_{qz}=4.5455\times 10^{7}\) N.mm/rad \\ \hline \end{tabular}
\end{table}
Table 2: Bushing stiffness coefficients obtained by FEM.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Mode** & \begin{tabular}{c} **Reference Model** \\ **(Hz)** \\ \end{tabular} & \
\begin{tabular}{c} **Equivalent Model** \\ **(Hz)** \\ \end{tabular} &
\begin{tabular}{c} **Percentage Change** \\ **(\%)** \\ \end{tabular} \\ \hline
1. & 37.6 & 37.7 & 0.27 \\
2. & 235.5 & 239.7 & 1.78 \\
3. & 332.6 & 339.4 & 2.05 \\
4. & 511.2 & 505.4 & \(-1.14\) \\
5. & 658.7 & 676.6 & 2.72 \\
6. & 1289.7 & 1329.7 & 3.10 \\
7. & 1547.5 & 1533.3 & \(-0.92\) \\
8. & 1975.4 & 2058.6 & 4.21 \\
9. & 2129.2 & 2194.7 & 3.08 \\
10. & 2624.3 & 2610.5 & \(-0.53\) \\
11. & 3173.7 & 3256.5 & 2.61 \\
12. & 3765.5 & 3763.1 & \(-0.06\) \\
13. & 4111.3 & 4107.4 & \(-0.09\) \\
14. & 4424.3 & 4494.1 & 1.58 \\ \hline \end{tabular}
\end{table}
Table 3: Natural frequencies of compared FE models.
# Calibration of a Rotating or Revolving Platform with a LiDAR Sensor
###### Abstract  
Perceiving its environment in 3D is an important ability for a modern robot. Today, this is often done using LiDARs which come with a strongly limited field of view (FOV), however. To extend their FOV, the sensors are mounted on driving vehicles in several different ways. This allows 3D perception even with 2D LiDARs if a corresponding localization system or technique is available. Another popular way to gain most information of the scanners is to mount them on a rotating carrier platform. In this way, their measurements in different directions can be collected and transformed into a common frame, in order to achieve a nearly full spherical perception. However, this is only possible if the kinetic chains of the platforms are known exactly, that is, if the LiDAR pose w.r.t. to its rotation center is well known. The manual measurement of these chains is often very cumbersome or sometimes even impossible to do with the necessary precision. Our paper proposes a method to calibrate the extrinsic LiDAR parameters by decoupling the rotation from the full six degrees of freedom transform and optimizing both separately. Thus, one error measure for the orientation and one for the translation with known orientation are minimized subsequently with a combination of a consecutive grid search and a gradient descent. Both error measures are inferred from spherical calibration targets. Our experiments with the method suggest that the main influences on the calibration results come from the the distance to the calibration targets, the accuracy of their center point estimation and the search grid resolution. However, our proposed calibration method improves the extrinsic parameters even with unfavourable configurations and from inaccurate initial pose guesses.  
LiDAR; LRF; extrinsic parameter; calibration Article
## 3 Results
### Seismogram Conversion--R\({}_{Q}\)-Envelope
#### 3.2.4 Measures of R/R\({}_{\rm Q}\)-Envelope Variability  
In converting seismograms into an R\({}_{\rm Q}\)-envelope or bigraph, the transformation takes place and maps objects from the domain of raw seismograms into the domain of their representations, i.e., images, which are usually simpler than the originals and have less variability. In such cases, it is necessary to define a distance between images to accomplish grouping (clustering) more effectively.  
For the case of R-envelope, the distance can be defined as:  
\[\Delta_{ij}=\int\limits_{\tau_{1}}^{\tau_{2}}\left|\frac{1}{\mathrm{R}_{i}( \tau)\big{|}_{\rm max}}\mathrm{R}_{i}(\tau)-\frac{1}{\mathrm{R}_{j}(\tau) \big{|}_{\rm max}}\mathrm{R}_{j}(\tau)\right|\cdot w(\tau)\,d\tau, \tag{17}\]  
which is, actually, the difference between two normalized R-envelopes, where the limits \(\tau_{1}\) and \(\tau_{2}\) are defined by R(\(\tau\))\({}_{\rm max}\) and by weighting function \(w(\tau)\) (see Figure 14).  
A similar equation can be written for R\({}_{\rm Q}(n)\) as well.  
According to the previous interpretation, which is that the polygonal line defining the shape of R(\(\tau\)) or of R\({}_{\rm Q}(n)\) is essentially not the line but the string of numbers, the distance (17) can be rewritten as:  
\[D_{ij}=\sum_{k=1}^{K}\left|\frac{1}{A_{\rm max}^{(i)}}\,A_{k}^{(i)}-\frac{1}{ A_{\rm max}^{(j)}}A_{k}^{(j)}\right|\cdot w(k), \tag{18}\]  
In both cases, one sees the importance of normalization since seismograms can significantly vary in maximum amplitude, while the waveform carries the most significant information and is the main factor in which seismograms differ from each other.  
As a general remark, it should be stressed that the convention of the ordering direction of SFs, increasing maximum amplitudes from left to right adopted in this paper, is chosen quite by chance, with no objective reason. This means that the decreasing convention, from left to right, would be equivalent.  
The pronounced difference in the shape of the head and the tail in the R\({}_{\rm Q}\)-envelope inspired the idea to separately measure the distance for both of them.
## 2 Optically Transparent Antennas
### Transparent Antennas Using Thin Films
This design reduces the conduction losses during the operation of reflect array, producing 272\({}^{\circ}\) of phase change through a subwavelength rectangular patch. The authors also suggested several  
Figure 3:1 Transparent wideband antenna with radiation patch using AgHT-8 [26]. Figure 3:2 Branch line coupler based on micro metal (MM) conductive film [21]. techniques that can reduce the loss in the reflect array antenna design. A 26 GHz design frequency was chosen, resulting in a peak gain of 22.2 dBi; moreover, good efficiency and better reflect array performance were observed in this design. ITO is the most widely used material for antenna transparency. Due to the shortage of this material along with high prices, this material was replaced by zinc oxide heavily doped with gallium (GZO), as proposed by authors in [27]. Material conductivity can be compared to that of ITO as they are produced in the form of thin films. A planner dipole was fabricated to investigate the efficiency of this system at 2.4 GHz frequency. In [29], authors presented the dual-band CPW (coplanar waveguide) optical transparent antenna working at 2.45 GHz and 5.8 GHz with AghT-8 material. The antenna had a size of 36 mm \(\times\) 39 mm \(\times\) 0.175 mm printed on 2 mm thick glass, as shown in Figure 3:3 This material has above 80% transmittance with \(\sigma\) = 1.25 \(\times\) 10\({}^{5}\) S/m, of electrical conductivity, which is high compared to other TCOs or nanowires. The results show return loss of less than \(-\)10 dB along with good antenna performance. An alternate representation of ITO as indium zinc tin oxide was proposed in [31; 80] to overcome ITO weakness, operating at 2.45 GHz (Wi-Fi frequency band). The sheet resistance was kept around 2.52 \(\Omega\)/sq, having 80% optical transmittance. Acrylic substrate with 100 nm thickness was used in the design. The efficiency of this antenna was 7.7% with a peak gain of around \(-\)4.3 dBi.
## 4 Discussion
Further analyses should be performed to find a direct causation between the rainfall event duration and the landslide area change. However, the freely available CWB data are limited to those hours when the typhoon passed Taiwan, and hence a complete historical rainfall database cannot be analyzed together with these extreme events. Several parameters could be computed from such a database, as indicated by [PERSON] et al. [81], which could lead to a more robust evaluation of the relationship between rain events and landslide evolution. Better knowledge about the reactivation of large landslides and the recurring impact on downstream areas is of high importance for disaster mitigation. Even if our results did not indicate a direct relationship between the extension of the Butangbunasi landslide and the strength of thetyphoon event, it became evident that also comparatively small typhoons or tropical storms could cause landslide reactivation. This is, for example, of high relevance for implementing early warning measures. The repeated sediment delivery after rainfall events frequently impacts the rivers system, which can result in the formation of landslide-dammed lakes and debris flows, and eventually poses a risk for people, settlements and infrastructure downstream. Major efforts are taken to maintain the transportation infrastructure in the study area and to avoid the repeated damming of the river (Figure 8). In particular, the Southern Cross-Island Highway, which is a popular tourist route that crosses the CMR and that provides a connection to the remote Yushan National Park, was severely affected by typhoon Morakot and following events, and the associated debris and sediment from the Butangbunasi landslide [29; 30]. Information about the evolution of the Butangbunasi landslide is thus also important for planning and implementing maintenance and reconstruction activities of roads and bridges. In this study, we focused on one large landslide. By studying larger areas and relating spatio-temporal landslide hotspots to rainfall events brought by typhoons or tropical storms, more robust correlations between landslide extensions and triggering events might be found. Further research should also emphasize on the combination of OBIA and machine learning approaches for automated landslide time series analysis.
## 4 The Improved Self-Collision Detection Technology
### Determine the Position of Each Approximation Object
#### 4.2.2 Determine the Position of the Link and the Tool  
For the link or the tool of the manipulator subsystem, we can directly describe their positioning by two adjacent joint coordinate systems, such as the second link in Figure 5a. The lower-key point is \(p_{1}=[x_{1},y_{1},z_{1}]^{T}\), the upper-key point is \(p_{2}=[x_{2},y_{2},z_{2}]^{T}\), the radius of the corresponding link is \(R_{L2}\), and the height is \(H_{L_{2}}\), so the unit vector of the straight line regarded as the corresponding link at any time can be expressed as  
\[e_{p_{1}p_{2}}=\frac{[x_{2},y_{2},z_{2}]^{T}-[x_{1},y_{1},z_{1}]^{T}}{\|\;[x_{ 2},y_{2},z_{2}]^{T}-[x_{1},y_{1},z_{1}]^{T}\|} \tag{12}\]  
where \(e_{p_{1}p_{2}}\) represents the unit vector of the straight line for the corresponding link.  
We determined the center of each spherical object. Due to analysis of the basic structural parameters of the connecting link, the radius of the corresponding multiple spheres is determined as \(\frac{l}{s}(i)\). For the surrounding outer boundary of the connecting link and the motors with multiple spheres, the small spherical objects envelop the connecting link from the center to the two ends, and the large sphere envelops the motors at both ends of the link. Thus, the center position of multiple spherical objects can be expressed as  
\[\begin{cases}C_{i}^{L}=\frac{[x_{2}+x_{1},y_{2}+y_{1},z_{2}+z_{1}]^{T}}{2}-k \cdot e_{p_{1}p_{2}}\\ k=-\frac{i}{2}:1:\frac{i}{2};\\ i=\frac{H_{L_{i}}}{\sqrt{2}R_{s}^{L}(i)};\end{cases} \tag{13}\]  
where \(C_{i}^{L}\) represents the position of the center of the corresponding approximation for the link, and \(H_{L_{i}}\) represents the length of the corresponding link.  
We determined the location of the surface point. After determining the center and the radius of each sphere based on the basic structure of the corresponding component and Formula (13), the location of the surface point can be acquired via the surface expression of each sphere, which can be denoted as  
\[\begin{cases}p_{xi}^{L}=C_{x}^{L}(i)+R_{s}^{L}(i)\cdot cos(m^{L});\\ p_{yi}^{L}=C_{y}^{L}(i)+R_{s}^{L}(i)\cdot sin(m^{L})\cdot cos(n^{L});\\ p_{zi}^{L}=C_{z}^{L}(i)+R_{s}^{L}(i)\cdot sin(m^{L})\cdot sin(n^{L});\end{cases} \tag{14}\]  
where \(p_{xi^{l}}^{l},p_{yi}^{l},p_{zi}^{l}\) represent the positioning result of the corresponding approximation of the corresponding link; \(C_{x}^{L}(i),C_{y}^{L}(i),{}^{L}\,C_{z}(i)\) represent the center of the spherical object approximated the corresponding link; and \(m^{L},n^{L}\) represent the minimum divided distance of the corresponding spherical object. The value range is \([0,2\pi],[0,\pi]\).
# A Review of Photothermal Detection Techniques for Gas Sensing Applications
## Fabry-Perot-Based PTS Gas Sensors
### Balanced Detection Fabry-Perot PT Gas Sensor  
The work presented in Reference [59] was quickly followed by a second publication by the same Authors. In Reference [60], [PERSON] et al. addressed the main issues of their previous sensor and proposed a similar configuration, but enriched with balanced detection of the PT-induced intensity modulation of the beam leaking from the FP cavity. The modified sensor layout is presented in Figure 14.  
Compared to the previous configuration, in this improved version of the FP-based PT gas sensor, the _probe_ beam is split into a reference beam and probing beam before entering the interferometer cavity (both beams travel through the same mirrors). The beam separation was 10 mm. Here, only one of the beams was intersected with the _pump_ beam injected into the cavity perpendicularly to the _probe_ beams. Both beams are detected by separate photodiodes after exiting the FP cavity, and the signals are subtracted using a differential amplifier. Both _probe_ beams experience common noise and therefore can be easily cancelled out. In FP interferometers, the registered noise is enhanced proportionally to the finesse of the cavity. Balanced detection significantly limited the registered noise; therefore, this simple improvement allowed the authors to use higher reflectivity mirrors to achieve higher finesse of the cavity and increase the overall sensitivity of the sensor. In this experiment, mirrors with reflectivity R = 0.985 were used, forming a cavity with a finesse of \(\sim\)89. The _pump_ laser and the  
Figure 13: Schematic of the Fabry-Perot interferometer-based photothermal gas sensor. Reprinted with permission from [59] C The Optical Society.  
signal processing part of the sensor was identical to the previously reported, and was based on WMS detection technique via modulating the QCL laser with sinusoidal waveform in the vicinity of SO\({}_{2}\) absorption line (1390.93 cm\({}^{-1}\)) and a LIA-based signal retrieval. This improved version of the sensor reached an NEC of 5 ppbv at an acquisition time of 1 s. This result is 240 times better than reported in the previous version of the sensor.
# An Algorithm for Rescheduling of Trains under Planned Track Closures
## 2 Related Work
### Joint Approaches
As an example, in Reference [56], the authors consider a two-stage algorithm as a means of problem decomposition which speeds-up the algorithm execution time. The algorithm is tested on a network of 66 stations in case of a single, full blockade of a selected connection. This approach is further explored in Reference [57], where online, closed-loop rescheduling is done with the use of model model predictive control. Further integration of traffic control and train operation is considered in Reference [58], where train speeds are considered. The authors formulate a nonlinear integer programming problem which they then simplify by approximating the nonlinearities with piecewise linear functions. To solve the many formulated sub-problems, the authors use a solver, a genetic algorithm and a custom procedure. The method is tested on a railway network of 40 nodes. In Reference [59], the authors consider two control loops: inner, which is responsible for managing immediate train operation and outer, where traffic control is done. The authors focus on Automated Train Operation subsystem of the Automatic Train Control system, and they provide an extensive review on the subject. In our paper, we propose a joint approach that focuses on specifics of the Polish Railways. This leads to a new decision-making problem, which is formulated with a unique combination of constraints, such as limits in total travel time extension and total distance extension, that might arise during rescheduling. This problem is, by nature, highly nonlinear, mainly due to to existence of a large number of binary variables, and it cannot be solved quickly to optimality (or, in fact, to feasibility), in the general case. We prove that property by showing that the problem is NP-hard. Our quality criterion consists of three types of sub-criteria: number of accepted train runs, number of accepted closures, and the total deviation of the new schedule from the original schedule. To solve such a problem, we propose a four level solution algorithm that attempts to iteratively include train runs and closures and optimizes the total deviation. This iterative character, if left unchecked, leads to long execution times. We reduce those times by providing a Track Grouping Algorithm that divides the railway network into smaller sub-networks which are easier to optimize.