esa-sceva/satcom-chunk-collection huggingface dataset:
# Graphical and Analytical Quantitative Comparison
## 4 The Case Study of San Francesco di Paola
### Previous Calculation on the Case Study  
The Church of San Francesco di Paola in Naples is a majestic building that surprisingly has barely been studied, probably because of its architectural features, which resamble the type established by the Pantheon in Rome, despite it being a neoclassic building erected in the 19 th century. Thus, few documents are available in the literature on its more proper structural and constructive aspects. However, it arouses great interest due to its substantial and massive structure: its dome has an impressive 36 m span (the fourth largest dome in Italy).  
The geometry used for the calculation is done with an analysis by laser-scanner and a photogrammetric survey carried out in collaboration with Tecno IN Geosolutions [2].  
Recently [4], the stability assessment of the dome of San Francesco di Paola under vertical loads has been discussed using both the kinematic theorem and the safe theorem of limit analysis; by combining kinematic and static approaches, it was possible to comprehend the range of possible movements of the masonry structure and evaluate its relative safety. The most interesting aspect of this research concerns the idea that traditional masonry structures can be analyzed as rigid blocks whose collapse can occur, for example, due to variations in the applied load, long-term failures or accelerations of the ground. It has also been emphasized that the kinematic of historic masonry dome has an important role in assessing the stability of such structures. In fact, displacements are common in historic masonry structures due, for example, to the consolidation of materials, imperfections in construction or differential settlements in foundations [46; 47; 48]. For these traditional masonry buildings, it is more likely that collapse occurs due to excessive subsidence or accelerations of the ground, rather than to an applied load.  
The assessment of this dome under horizontal actions has been studied in [5; 7]. The horizontal force capacity of the dome-buttress system has been evaluated through a tilting test, adopting MEA and TLA as for the related evaluations. The work aimed to determine the limit value of the dome inclination for which the masonry is still entirely compressed and to assess the buttress stability. The results show that TLA is more conservative with respect to MEA for this kind of analysis, giving a lower limit rotation angle for TLA with respect to MEA.
# Fault Tolerant Spectral/Spatial Optical Code Division Multiple Access Passive Optical Network
## 7 Conclusions  
The proposed fault-tolerant 2D spectral-spatial OCDMA-based PON with time delay demonstrates a robust and efficient solution for next-generation communication systems, such as 5G, 6G, and beyond. By employing a ring topology at the FL, the network effectively mitigates the single point of failure issue inherent in tree-based PONs, thereby enhancing connection availability without compromising transmission capacity. Utilizing a pseudo-3D double-weight zero cross-correlation code, the system achieves high cardinality and capacity, supporting up to 128 users at 10 Gbps with minimal BER, outperforming conventional systems like 3D-DEU-DEU-MD and 3D PD-MD in terms of data rate and received power. Optisystem simulations reveal that the optimized architecture maintains performance under both normal and fault conditions, with acceptable BER and QF values and clear eye diagrams even at OF lengths of up to 16 km and a received power of approximately \(-19\) dBm, highlighting its improved power tolerance over competing systems. The network's resilience is further strengthened by its 99.999% connection availability for the optical fiber media at both the feeder and distribution levels, unlike any of the existing OCDMA systems with spectral-spatial and temporal encoding in the existing literature. Thus, the optimized architecture not only supports high data rates and extensive subscriber reach but also provides desirable connection availability and reliability through a robust infrastructure, making it a superior candidate for future optical access networks.  
Conceptualization, R.U., S.U., J.R. and W.A.I.; methodology, R.U. and W.A.I.; software, R.U., S.U., J.R. and W.A.I.; validation, R.U., S.U., J.R., Y.M., Z.Q., W.A.I. and F.W.; formal analysis, R.U., S.U., J.R., J.H. and F.K.; investigation, R.U., J.R., Y.M., Z.Q., J.H., F.K. and F.W.; writing--original draft, reviewing and editing, all authors; supervision, R.U., J.R., Y.M., Z.Q. and F.W.; project administration, R.U., S.U., J.R., Y.M., Z.Q. and F.W.; funding acquisition, R.U., J.R., Y.M., Z.Q., S.U. and F.W. All authors have read and agreed to the published version of the manuscript.  
National Key Research and Development Program of China (2023 YFB2804901); National Natural Science Foundation of China (62171227, U22B2009, 62205151, 62275127); Jiangsu Provincial Key Research and Development Program (BE2022079, BE2022055-2).  
Not applicable.
# Survivability Prediction of Open Source Software with Polynomial Regression
## 4 Results and Analysis
### Threats to Validity  
We proposed a method to predict the development process and trends of OSS using polynomial regression analysis based on GitHub data. We identified and addressed several potential threats to the validity of our findings. These threats are divided into two categories: external threats and internal threats, and each category has associated mitigation strategies.  
**External threats**: Each OSS project may exhibit unique development patterns, influenced by factors such as the size and complexity of the project and the dynamics of the contributing community. Some OSS projects may follow a well-defined and predictable development pattern, making them good candidates for regression analysis to predict stability using the proposed method. However, some OSS projects may have a highly irregular development pattern, characterized by unpredictable changes, inconsistent bug-fixing activity, or other nonlinear trends. In these cases, traditional regression models may struggle to identify meaningful patterns, limiting the effectiveness of reliability prediction methods. To address these external threats, we used cross-validation to train the model on different subsets of the training data and evaluate the model's performance. Furthermore, extracting only bug issues can be challenging if issue labeling is not performed. Therefore, we excluded those OSS from our study. However, if measuring survivability including them is necessary, methods used by [PERSON] et al. or [PERSON] et al. might be more suitable [8; 10].  
**Internal threats**: The size of the dataset used to train and test a model can affect its performance. A small sample size can limit representativeness and reduce predictive accuracy. To address this insider threat, only open sources with sufficient data should be used. Therefore, we ran our predictions on open sources with at least five data points.
# Analytical-Numerical Model for Temperature Prediction of a Serpentine Belt Drive System
## 4 Results and Discussion
### Model Verification  
The thermal model is validated by comparing the temperatures of the belt-side and pulley-side at the belt-pulley surface temperature with the experimental values. These values are critical to determine the thermal failures of materials, because belt-side contact surface temperature is the belt uniformed temperature and pulley-side temperature is the highest temperature in the pulley. The thermal model calculates the heat flux on each component and the temperatures on the contact surfaces, and it can provide the changes in the temperature distribution of the contact surfaces from 2000 RPM to 6000 RPM in intervals of 2000 RPM. Figure 16a,b shows the comparison of the measured and calculated temperatures for a two-belt drive system under various conditions. The model predicts the upward trends of the temperatures when the rotation speed of the belt drive system increases. The diagrams show that the calculated results are in good agreement with the experimental data. The maximum difference is less than 20% of total temperature rise, which is acceptable for industrial use or the subsequent thermal fatigue analysis.
## 2 Characterization of FBG
### FBG Temperature Compensation  
A fiber grating wavelength change is mainly affected by its strain and temperature; this law of change has been tested and is was found that there is a relationship between the wavelength and the two covariates [29; 30; 31; 32; 33]:  
\[\frac{\Delta\lambda_{B}}{\lambda_{B}}=K_{e}\epsilon+K_{T}\Delta T \tag{16}\]  
Due to the strain-temperature cross-sensitivity issue inherent in Fiber Bragg Gratings (FBGs), when investigating the impact of strain on the grating, it is imperative to eliminate the temperature effect. A prevalent approach to accomplish this is by employing temperature compensation techniques. This is crucial as the simultaneous influence of strain and temperature on FBGs can lead to inaccurate measurements. Temperature compensation techniques are designed to decouple these two effects, ensuring that the strain-related changes in the grating are accurately detected and isolated from the confounding temperature-induced variations. By implementing such techniques, the reliability and precision of FBG-based sensing systems, such as those used in the context of hydraulic support attitude monitoring, can be significantly enhanced.  
The unstressed grating method is stable, reliable and simple to operate; so, it is suitable for further promotion. However, now, only the influence of the temperature compensation method is said to be the case, which can be obtained from the theory above:  
\[\frac{\Delta\lambda_{B1}}{\lambda_{B1}}=K_{e1}\epsilon+K_{T1}\Delta T \tag{17}\]  
where \(\lambda_{B1}\) is the wavelength at crossover and \(K_{T1}\) is the corresponding sensitivity factor.  
\[\frac{\Delta\lambda_{B2}}{\lambda_{B2}}=K_{T2}\Delta T \tag{18}\]  
where \(\lambda_{B2}\) is the unstressed grating wavelength and \(K_{T2}\) is the corresponding sensitivity factor.  
Make \(\gamma=K_{\rm T1}/K_{\rm T2}\); therefore:  
\[\varepsilon=(\Delta\lambda_{B1}/\lambda_{B1}-\gamma\Delta\lambda_{B2}/\lambda_{B2 })/K_{\rm e1} \tag{19}\]  
If the specification parameters of the two gratings that make the experiment are the same, pasted on a substrate with \(\gamma=1\), the wavelength change \(\Delta\lambda_{\varepsilon}\) due to strain is only [34]:  
\[\Delta\lambda_{\varepsilon}=\Delta\lambda_{B1}-\Delta\lambda_{B2}\cdot\frac{ \lambda_{B1}}{\lambda_{B2}} \tag{20}\]  
From the analysis, it is concluded that \(\Delta\lambda_{B}\) depends on \(n_{eff}\) and \(\Lambda\). Stress-strain and temperature can directly and significantly change \(\lambda_{B}\). The relationship between grating wavelength and stress and temperature is analyzed from FBG sensing characteristics, and it is concluded that the wavelength is linear with both. When using FBG to make functional sensors, researchers must pay attention to the temperature and strain cross-sensitivity problem; if there is only a need to monitor stress-strain, Temperature effects can be isolated by compensation techniques.
# Geometric Spherical Surfaces Emulating the Geostationary Orbit at Any Latitude with Zenith Links
###### Abstract  
According to altitude, the orbits of satellites constellations can be divided into geostationary Earth orbit (GEO), medium Earth orbit (MEO), and low Earth orbit (LEO) constellations. We propose to use a Walker star constellation with polar orbits, at any altitude, to emulate the geostationary orbit with zenith paths at any latitude. Any transmitter/receiver will be linked to a satellite as if the site were at the equator and the satellite at the local zenith. This constellation design can have most of the advantages of the current GEO, MEO, and LEO constellations, without having most of their drawbacks. Doppler phenomena are largely minimized because the connected satellite is always seen almost at the local zenith. The extra free-space loss, due to the fixed pointing of all antennas, is at most 6 dBs when the satellite enters or leaves the service area. The connections among satellites are easy because the positions in the orbital plane and in adjacent planes are constant, although with variable distances. No steering antennas are required. The tropospheric propagation fading and scintillations are minimized. Our aim is to put forth the theoretical ideas about this design, to which we refer to as the geostationary surface (GeoSurf) constellation.  
satellite constellations; walker star; GeoSurf; zenith paths +
Footnote †: journal: Future Internet
# Assessment of Six Machine Learning Methods for Predicting Gross Primary Productivity in Grassland
## 2 Study Area and Data
### GPP Data  
In this study, we chose two kinds of GPP data: remote sensing data and flux observation data. Among them, remote sensing data is used for machine learning model training and result evaluation. Due to the small amount of measured data, it is only used for the evaluation of results.  
At the positions of non-flux stations (points a-h in Figure 1), this study uses remote sensing data as reference data. They come from the MOD17A2H dataset ([[https://lpdaac.usgs.gov/products/mod17a2](https://lpdaac.usgs.gov/products/mod17a2) hv006/]([https://lpdaac.usgs.gov/products/mod17a2](https://lpdaac.usgs.gov/products/mod17a2) hv006/), accessed on 15 April 2023) with a spatial resolution of 500 m and a temporal resolution of 8 d. As long series, spatialized, medium to high-resolution raster data, the remote sensing data are the main part of the GPP input and verification in this study. In the positions of non-flux stations (point i in Figure 1), this study uses the flux observation data as the reference data for the evaluation of results. The flux observation data are the key part of controlling the quality of GPP prediction and strict accuracy assessment. They come from the Chinese FLUX Observation and Research Network (ChinaFLUX, [[http://www.chinaflux.org/](http://www.chinaflux.org/)]([http://www.chinaflux.org/](http://www.chinaflux.org/)), accessed on 15 April 2023), including daily carbon flux data from 2004-2010 of the Xilingol Temperate Typical Grassland Flux Station. To meet the research needs, we eliminated the outliers in the data and calculated the GPP using Formula (4) [49]. Then, through time series aggregation, the temporal resolution was unified to 8 d.  
\[GPP=NEE-Re \tag{4}\]  
Among them, \(NEE\) and \(Re\) are net ecosystem exchange and ecosystem respiration, respectively, measured by flux observation stations.  
Considering the available years of all the factor and GPP data, we decided to use the 2005-2010 data to train the models, input the 2004 factor data into the trained model, and use the GPP data from that year for accuracy verification.
## 4 Scenario Analysis
### Study Solution and Result Analysis
#### 4.2.1 Solution Analysis  
In this paper, an Intel i5 1.9 GHz central processing unit (CPU) computer with 4 GB RAM was used to solve mathematical programming (7)-(21) through CPLEX v12.6.1, and 3156 consecutive Numbers, 1987 binary variables and 4156 constraints were obtained. In an urban distribution, different requirements are put forward for logistics companies due to different properties of goods and different needs of customers. For example, more attention is paid to minimize costs in large-scale distribution, while more attention is paid to timeliness in drug distribution. Therefore, in order to make this study more suitable for the actual needs, four different objective functions were designed, including the shortest distance objective function, the shortest time objective function, the minimum fuel consumption objective function and the minimum cost objective function, as shown in Formulas (22) and (23).  
Figure 2: The distribution map of Jingdong (JD) distribution center and customer nodes.  
In order to obtain the travel solution with the shortest distance, the following function was designed in this paper:  
\[\textit{Minmize}\sum_{(i,j)\in A}\sum_{p\in P}d_{ij}^{p}X_{ij}^{p} \tag{22}\]  
In order to obtain the travel solution with the shortest time, the following function was designed in this paper:  
\[\textit{Minmize}\sum_{(i,j)\in A}\sum_{p\in P}\bigg{(}d_{ij}^{p}/s_{ij}^{p} \bigg{)}X_{ij}^{p} \tag{23}\]  
In order to obtain the travel solution with the least fuel consumption and the minimum cost, we employed Equations (6) and (7) as the objective functions. Different models use the same constraint conditions, i.e., Constraints (18)-(21). Table 2 clearly illustrates the differences among the various models.  
Through the analysis above, it can be seen that the variables covered by different models were significantly different. Therefore, Constraints (8)-(21) were attached to the four different objective functions, and then CPLEX and MATLAB were invoked by Java to solve the problem. The following results were obtained, as shown in Table 3.  
From the analysis in Table 3, it can be seen that vehicles had different path choices in different objective functions. By assigning the same Constraints (11)-(24) to the objective functions (25), (26), (6), and (7)-(10), we obtained the routing formulation of the optimal time, distance, fuel consumption, and cost, respectively. At the same time, four main performance indicators under a different routing formulation were obtained by MATLAB. It was found that there were significant differences among the four indicators under a different route formulation, and the indicators that were consistent with the objective function gave the best results.
## 4 Study on the Blast Resistance of Ultra-Wide Concrete Twin-Edge Box Girders Coated with Polyurea
### Parametric Analysis
#### 4.2.1 Analysis of the Impact of Different Scaled Blast Distances
The temporal evolution curves depicting the vertical shift of the baseplate directly beneath the blast center at varied scaled blast distances are depicted in Figure 27. As shown in the figure, under the impact of the blast shockwave, the vertical shift of the box girder rapidly reaches its highest point over a short duration before transitioning into a decay phase. The highest displacements observed in the baseplate under the blast zone for specimen PG under blast scenarios 1 to 5 are 6.99 mm, 8.82 mm, 12.41 mm, 17.92 mm, and 24.61 mm, respectively, while for Specim PPCG, the corresponding maximum displacements are 5.63 mm, 8.53 mm, 11.53 mm, 14.61 mm, and 19.45 mm. These results indicate that the vertical shift of the girder grows progressively with increasing blast charge. Additionally, the proportional blast distance significantly affects both the damage and dynamic response of specimens PG and PPCG. Under blast scenario 4, specimen PPCG demonstrated superior protective performance coated with polyurea, reducing the peak displacement by 35.66% compared to specimen PG. This suggests that the application of polyurea coatings has a notable suppressive effect on reducing the vertical displacement of box girder structures under blast impact. Figure 26: Temporal evolution curves of concrete stress at the top-plate center of box chamber 1 under varying scaled blast distances.
## 4 Experimental Setup
### Research Questions  
To evaluate our method, we ask the following research questions:  
RQ1. Does our proposed method of using sentence significance factors yield higher summary quality (i.e., F1-score) than that of BugSum?  
There are two related research questions that we investigate to understand the aspects that affect summary quality:  
RQ2. How do sentence significance factor assessments and feature preservation influence summary quality?  
RQ3. How does summary quality change as the length of a summary changes?  
As a consequence of its generality, our method has a wider applicability than BugSum, which relies on just believability. The following research question compares our method and BugSum in this respect.  
RQ4. Is the application scope of our proposed method wider than that of the state-of-the-art method BugSum?
# Accurate Tracking Algorithm for Cluster Targets in Multispectral Infrared Images
## 3 Methods  
### Establishment of an Infrared Image Subspace  
An infrared image subspace is a complete linear aggregation of weak targets, and each feature node represents an image information parameter to be extracted. Considering the rigidity of infrared image extraction in complex environments, the larger the actual range of the subspace, the larger the total amount of matching information.  
Assuming that the maximum range of variation of a weak target never exceeds the parameter \(\lambda\) in an infrared image subspace and that the maximum information quantity condition of the extracted image is \(r\), the infrared image subspace of the weak target can be defined as:  
\[A=\int\limits_{r=1}^{n}\frac{\lambda}{r(\delta_{1}+\delta_{2})}dr \tag{3}\]  
where \(\lambda\) represents the number of weak target limits, \(r=1\) represents the minimum extraction matching condition of the weak target feature node, \(r=n\) represents the maximum extraction matching condition of the weak target feature node, and \(\delta_{1}\) and \(\delta_{2}\) represent two different infrared image information parameter values.
## 3 System Design and Implementation
### Hardware Design
#### 3.2.1 STM32 Minimum System Schematic  
The system adopts the STM32F103C8T6 microcontroller as the core of the gateway, and its minimum system schematic is shown in Figure 5. The system operates at 3.3 V and adopts a dual clock design: the 8 MHz main crystal provides the system clock reference, and the 32.768 kHz low-speed crystal drives the real-time clock (RTC). Both oscillator circuits are stabilized using matched capacitors to optimize performance. A push-button reset circuit ensures reliable reboot, and serial communication is realized through a USART interface, which is connected to a TTL-to-RS485 module for signal conversion. A standard JTAG debugging interface compatible with the J-Link debugger and the Keil MDK development environment is integrated for firmware programming, real-time monitoring, and debugging.  
The W5500 Ethernet controller communicates with the STM32 microcontroller via SPI. As shown in Figure 6, the STM32F103C8T6's PB12 (SCS), PB13 (SCLK), PB14 (MISO), and PB15 (MOSI) pins are directly connected to the corresponding SPI pins of the W5500, enabling seamless data exchange.  
Figure 5: STM32 minimum system.  
Figure 6: SPI communication.
## 5 Discussion
### Point Cloud Registration at Ship Turning  
For point cloud registration, the larger the overlapping part of the point cloud, the better the registration result, and the smaller the overlapping part usually leads to registration failure. In Figures 4 and 7, we can find that there is a large positioning error and state estimation error at the turning point. The reason for this phenomenon is that the ship's heading angular velocity is large at the turning point, which will lead to a low overlap rate of the two adjacent frame point clouds, resulting in large registration errors and poor positioning accuracy. This is also one of the main reasons for the low positioning accuracy of scan-matching technology.