esa-sceva/satcom-chunk-collection huggingface dataset:
# Performance of Numerically Optimized Tuned Mass Damper with Inerter (TMDI)
## 1 Introduction
The conventional topology is given by the parallel arrangement of inerter, spring and viscous damper, aiming at increasing the inertial force of the TMDI mass, as in Figure 1b. The benchmark for this TMDI configuration is the classical TMD with the same mass ratio (Figure 1c). The other considered TMDI topology is the serial arrangement of spring, inerter and viscous damper together with the main spring of the TMDI mass, as proposed in [25] (Figure 1d). This topology aims to produce an additional degree of freedom of the inerter. The performance of the resulting three-degrees-of-freedom system is compared to the performance of the primary structure with two half TMDs, both with half mass ratio and different natural frequencies and damping ratios, leading to a three-degrees-of-freedom system as well (Figure 1e). The comparative study is performed for both harmonic and random excitations. The performances of the simulated TMDs and TMDIs are assessed by the primary structure displacement response and the damper relative motion response. The structure of the paper is as follows. Section 2 describes the modelling of the considered TMDI concepts and the associated TMDI benchmarks. To make the modelling closer to reality, an inerter model based on a fly wheel mechanism is considered as well. Section 3 describes the simulation procedure concerning the optimizations of the considered TMDI and TMD systems and their performance assessments. Section 4 shows the numerical results of the considered TMDI configurations and the benchmark TMD with the same mass ratio. The comparison is made in a systematic way. First, the conventional TMDI with the commonly used inertance ratio of 1% and with parameters according to those described in the literature is compared to the TMD with Den Hartog parameters that minimize the primary structure displacement response, assuming zero structural inherent damping [1]. Then, the conventional TMDI and TMD with numerically optimized parameters are compared and the very small inertance ratio of 0.02% is considered as well. For the serial TMDI, the parameters are numerically optimized for inertance ratios of 1% and 0.02% due to the lack of analytical optimum parameter solutions. For the TMDI with an inertance ratio of 1%, the frequency response function is characterized by two peaks. Therefore, the classical TMD is used here as a benchmark. For the TMDI with an inertance ratio of 0.02%, the frequency response function shows three peaks due to the additional degree of freedom induced by the serial inerter with the low inertance ratio of 0.02%. Consequently, the benchmark is given here by two half TMDs with different natural frequencies and damping ratios. Discussions of these comparative studies are included in Section 4. The article ends with a short summary and conclusions in Section 5.
# Free Vibrations and Flutter Analysis of Composite Plates Reinforced with Carbon Nanotubes
## 2 Materials and Methods
### Micromechanical Modeling
In the equations presented below (1a-1e), the isotropic plane (2-3) is perpendicular to the axial direction of the perfectly aligned carbon nanotubes  
\[E_{11}\approx V_{t}E_{t}+V_{m}E_{m}+\frac{8(\
u_{t}+\
u_{m})^{2}V_{t}V_{m}G_{ m}}{1+V_{m}+V_{t}\delta_{m}+V_{m}(\delta_{t}-1)\frac{G_{m}}{G_{t}}}, \tag{1a}\] \[G_{12}=G_{13}\approx G_{m}\frac{1+V_{t}+V_{m}\frac{G_{m}}{G_{t}}}{V_{m}+(1+V_{t}) \frac{G_{m}}{G_{t}}},\] (1b) \[\
u_{21}=\
u_{31}\approx\
u_{m}-\frac{V_{t}(\delta_{m}+1)(V_{t}-V_{m})}{1+V_{m} +V_{t}\delta_{m}+V_{m}(\delta_{t}-1)\frac{G_{m}}{G_{t}}},\] (1c) \[\frac{1}{E_{22}}=\frac{1}{E_{33}}\approx\frac{\
u_{21}^{2}}{E_{11}}+\frac{1}{8G _{m}}\Bigg{[}\frac{2V_{m}(\delta_{m}-1)+(\delta_{t}-1)(\delta_{m}+V_{t}-V_{m} )\frac{G_{m}}{G_{t}}}{1+V_{m}+V_{t}\delta_{m}+V_{m}(\delta_{t}-1)\frac{G_{m}}{ G_{t}}}+\frac{2G_{m}}{G_{23}}\Bigg{]},\] (1d) \[\frac{\
u_{23}}{E_{22}}=-\frac{\
u_{21}^{2}}{E_{11}}+\frac{1}{8G_{m}}\Bigg{[} \frac{2G_{m}}{G_{23}}-\frac{2V_{m}(\delta_{m}-1)+(\delta_{t}-1)(\delta_{m}+V_{ t}-V_{m})\frac{G_{m}}{G_{t}}}{1+V_{m}+V_{t}\delta_{m}+V_{m}(\delta_{t}-1) \frac{G_{m}}{G_{t}}}\Bigg{]}, \tag{1e}\]  
where \(\delta_{i}=3-4\
u_{i}\), \(i=t\) or \(m\) denotes nanotube and matrix, respectively; \(V_{t}\) and \(V_{m}\) denote volume fractions; \(G_{t}\) and \(G_{m}\) denote shear moduli; \(E_{t}\) and \(E_{m}\) denote [PERSON]'s moduli; \(\
u_{t}\) and \(\
u_{m}\) denote [PERSON]'s ratios; \(E_{11}\), \(E_{22}\), and \(E_{33}\) denote nanocomposite [PERSON]'s moduli; \(\
u_{21}\), \(\
u_{31}\), and \(\
u_{23}\) denote nanocomposite Poisson's ratios; and \(G_{12}\), \(G_{13}\), and \(G_{23}\) denote nanocomposite shear moduli. Additionally, a nanocomposite density is computed from the rule of mixture (ROM) as  
\[\rho=\rho_{t}V_{t}+\rho_{m}(1-V_{t}), \tag{2}\]  
The volume fractions of nanoreinforcement are typically very low. At higher volume fractions of carbon nanotubes, it has been observed that the mechanical properties of nanocomposites deteriorate due to the formation of CNT agglomerates, which act as stress concentrators. Therefore, the assumed volume fractions of nanotubes are 1%, 3%, and 5%. The calculated effective properties of CNT/nanocomposites for selected volume fractions are listed in Table 2. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Material**} & **Young’s Modulus (GPa)** & **Poisson’s Ratio** & **Density (kg/m3)** \\ \hline Carbon nanotubes & 1000 & 0.175 & 1400 \\ Epoxy matrix & 2.945 & 0.35 & 1200 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Properties of nanocomposite constituents.
applied sciences  
**Key Laboratory for Ecological Metallurgy of Multimetallic Mineral (Ministry of Education), Northeastern University, Shenyang 110819, China**  
**School of Metallurgy, Northeastern University, Shenyang 110819, China; [EMAIL_ADDRESS] (T.Q.); [EMAIL_ADDRESS] (Y.Z.)**  
* **Correspondence: [EMAIL_ADDRESS]**  
Theoretical, the vertical sinter sensible heat recovery process can significantly improve the recovery rate of sinter sensible heat. However, the segregated distribution of the sinter and uneven gas-solid flow in vertical cooling furnaces result in insufficient contact and heat exchange between the high-temperature sinter and the cooling gas, thereby limiting the improvement in the sinter sensible heat recovery rate. A Venturi vertical cooling furnace can improve the contact heat transfer between gases and solids and the uniformity of the sinter and the cooling gas temperature. However, this leads to a significant increase in the gas pressure drop and affects the integrity of the downward movement of the sinter. To control the increase in the gas pressure drop while increasing the sensible heat recovery and maintaining the integral flow of the sinter, this study takes a Meishan Steel vertical cooling furnace as the research object and uses the DEM-CFD coupling model to optimize the structural parameters of the Venturi-type vertical cooling furnace. Firstly, a scaling method was designed to reduce the computational cost. Secondly, based on the on-site conditions, the selection range of structural parameters for the Venturi furnace was determined. Finally, an orthogonal experiment was designed. Taking the sensible heat recovery of the sinter and the pressure drop of the cooling gas as the main index, the integrity of the sinter flow was taken as the secondary index to study the Venturi structure parameters suitable for the Meishan Steel vertical cooling furnace, including the width of the vertical part \(w\), the length of the vertical part \(l\), the contraction angle of the contraction part \(\beta\), and the expansion angle of the expansion part \(\alpha\). The results showed that the order of structural parameters affecting the sensible heat recovery was \(w\), \(\beta\), \(\alpha\), and \(l\), and the order of parameters affecting the gas pressure drop was \(w\), \(\beta\), \(l\), and \(\alpha\). The appropriate structural parameters of the Venturi furnace type, obtained by considering the sensible heat recovery and gas pressure drop, were \(w=1.1\) m, \(\beta=16^{\circ}\), \(\alpha=13^{\circ}\), and \(l=0.5\) m. In addition, in order to improve the integrity of the sinter flow, it was also necessary to increase the wall friction of the particles in the central area of the vertical section by adding steel plates. The results can provide theoretical guidance for improvements to the Meishan Steel vertical cooling furnace. The operation parameters corresponding to the Venturi furnace type can be studied later.  
sinter; vertical cooling furnace; Venturi furnace type; gas-solid heat transfer; orthogonal experiments
# Semantics-Preserving RDB2 RDF Data Transformation Using Hierarchical Direct Mapping
## 3 Preliminaries
### Semantics Preservation of Direct Mapping  
Further research has been conducted on the improvement of direct mapping to reduce information loss and ensure semantics preservation. Semantics preservation is an important feature of direct mapping as the quality of direct mapping is heavily depends on the semantics preservation. [PERSON] et al. [7] provided a theoretical definition of semantics preservation. In addition to the definition, this research provides a stricter definition to quantify semantics preservation and evaluate  
Figure 4: An example input relational data of the direct mapping.  
Figure 5: An example result of the direct mapping.  
the accuracy of the mapping methods. This paper defines the semantics preservation of mapping methods as follows:  
Semantics preservation: Suppose X is a set of relational data, F is a RDB to RDF mapping function, and G is an RDF to RDB inverse-mapping function of F, if \(|\)X\(|\) = \(|\)G(F(X))\(|\) and \(|\)G(F(X)) \(-\)X\(|\) = 0, then F is an ideal function that satisfies semantics preserving mappings (Figure 6).
# Empirical Study of Fully Homomorphic Encryption Using Microsoft SEAL
## 5 Conclusions  
While FHE is a promising solution to keeping the balance between data privacy and data use for innumerable applications, its applicability is still a challenge. This study's investigation into FHE using the Microsoft SEAL library underscores the technical challenges and considerations necessary for applying FHE across different computational environments, including traditional PCs and edge devices like the Jetson Nano. Our research demonstrates that while FHE offers a pathway to secure and privacy-preserving computation by enabling operations on encrypted data, its practical deployment is hindered by significant computational overhead and memory requirements. These limitations are particularly pronounced in environments such as edge computing, which are increasingly prevalent in IoT ecosystems. If FHE is to be applied in both high-resource and resource-constrained environments, such as data lakes, further works on optimizing these algorithms should be addressed.  
Conceptualization, P.M.-L. and M.-D.C.; methodology, P.M.-L. and M.-D.C.; software, F.-J.-V.-R.; validation, F.-J.V.-R., P.M.-L. and M.-D.C.; investigation, F.-J.V.-R., P.M.-L. and M.-D.C.; writing--original draft preparation, F.-J.-V.-R. and P.M.-L.; writing--review and editing, M.-D.C.; visualization, F.-J.-V.-R., P.M.-L. and M.-D.C.; supervision, P.M.-L. and M.-D.C.; project administration, M.-D.C.; funding acquisition, M.-D.C. All authors have read and agreed to the published version of the manuscript.  
This research was carried out within the framework of the Recovery, Transformation and Resilience Plan funds, financed by the European Union (Next Generation).  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.
# An Improved Monte Carlo Reliability Analysis Method Based on BP Neural Network
## 4 Examples Verification
### Reliability Problem of Series System
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & \(\mathbf{N_{FEM}}\) & \(\mathbf{N_{call}}\) & \(\mathbf{P_{f}}\) & \(\mathbf{COV_{P_{f}}}\) & \(\mathbf{\varepsilon}\) \\ \hline MCS & \(10^{6}\) & \(10^{6}\) & \(2.233\times 10^{-3}\) & 0.0211 & — \\ Kriging [30] & 600 & \(10^{6}\) & \(2.450\times 10^{-3}\) & 0.0202 & 9.72\% \\ AK-MCS-U [15] & 96 & \(10^{6}\) & \(2.233\times 10^{-3}\) & 0.0211 & 0.00\% \\ AK-MCS-EFF [15] & 101 & \(10^{6}\) & \(2.232\times 10^{-3}\) & 0.0211 & 0.04\% \\ AK-MCS-IRS [28] & 21 & \(10^{6}\) & \(2.23\times 10^{-3}\) & 0.0212 & 0.13\% \\ DRL [27] & 2597 & \(5\times 10^{5}\) & \(2.314\times 10^{-3}\) & 0.0208 & 3.63\% \\ Direct BP-MCS & 88 & \(10^{6}\) & \(2.262\times 10^{-3}\) & 0.021 & 1.30\% \\ Improved BP-MCS & 88 & \(15\),714 & \(2.243\times 10^{-3}\) & 0.0211 & 0.45\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Reliability calculation results of series system. stable. When \(k\) is 1.1, the method proposed in this paper has high precision, and the relative error is only 0.45%, so the amplification coefficient \(k\) of subsequent examples is 1.1. The weight adopted by the algorithm is \(\omega_{1}=0.00228\), then the critical value of the weight is \(\omega_{0}=0.00251\), and the critical region is shown as the circle in Figure 5. When the weight of the sample point \(\omega_{i}>\omega_{0}\), the sample point is in the circular region, and the sample point is reliable. When \(\omega_{i}<\omega_{0}\), meaning the sample point is outside the circular region, it needs to be substituted into the BP model to determine whether it is failed.
## 4 Discussion
### Variation of ANPP on Elevation Gradient
When precipitation surpasses the vegetation growth demands, the photosynthesis of vegetation reacts adversely to the reduced radiation and increased relative humidity. Hence, from low to high altitude areas, as precipitation values approach the vegetation growth needs, the adverse reactions induced by radiation and relative humidity decrease, causing an increment in the ANPP values. However, the influencing factors for ANPP in high altitude areas are not limited to precipitation; studies demonstrate that temperature remains the dominant factor for ANPP in these regions [84; 85]. In this study, the ANPP in high altitude areas predominantly showed a positive correlation with temperature. Consequently, despite the reduction in precipitation with increased altitude causing some increase in the ANPP, the overall trend of ANPP was significantly downward due to the dominant effect of temperature. Within elevation intervals divided into 100 m units, different factors dictated the changes in ANPP at various altitudes. The variation in ANPP along the elevation gradient illustrated the influence of several meteorological elements, such as precipitation, temperature, and solar radiation, coupled with human activities, on the altitudinal distribution of ANPP.
## 2 Materials and Methods  
We developed a structured framework to categorize the literature into three main areas: (1) remote sensing of SM (including satellites and UAVs), (2) modeling techniques, auxiliary data as covariates and algorithms for SM modeling, and (3) ground-based SM measurements. This framework includes specific technologies such as UAVs and satellites, machine learning data analysis methods, and various spectral and vegetation indices used in SM modeling.  
A comprehensive literature review of published, peer-reviewed scientific articles was conducted for the period from 2014 to May 2024 using Harzing's Publish or Perish software version 8.12. This approach ensured a focus on the most recent methods and advances in SM measurement and monitoring. In addition, Google Scholar was used to search for peer-reviewed articles with keywords like \"Soil Moisture\", \"Remote Sensing\", \"UAV\", and \"Semi-arid\". The initial search yielded 896 articles cited more than 34,000 times. After refining the search to eliminate papers not pertinent to the designated ecoregions, algorithms, or remote sensing applications, we identified relevant papers. These selected articles were deemed highly relevant due to their alignment with the core topics and their significant contributions to the state of the art in SM monitoring and modeling. In addition, in some cases, we include gray literature such as technical reports, government documents, and databases from national and global sources to ensure a comprehensive understanding of the topic. We also utilized literature prior to 2014 when contextualizing a relevant subject was necessary.  
Each core topic was thoroughly reviewed to assess its current relevance and application, ensuring the review reflects the latest knowledge and practices. The analysis highlighted gaps in current methodologies and technologies and suggested strategies for advancing SM monitoring and measurement in semi-arid regions. Figure 1 illustrates the framework, the topics, and the principal criteria applied in this review.  
Figure 1: Methodology: (**A**) review framework, (**B**) keyword cloud infographic derived from the analysis of relevant papers included in the literature review, illustrating the primary themes and topics discussed.
## 3 Comparison among Different AC Signal Analysis Methods
### Influence of Spectral Leakage on the Accuracy of the Amplitude and Phase  
In this section, we also consider the general sinewave response signal \(x[k]=A\cdot sin(2\pi ft+\varphi)\) with a length of \(N\) as an example for the theoretical part. An exemplary signal of 11 kHz with amplitude \(A=1V\) and phase \(\varphi=\frac{\pi}{6}\), sampled at a rate of \(F_{s}=500\) kHz, is used as a test scenario. The number of samples is 2048, the spectral leakage is 11.2%, and the distance to the nearest frequency bin \(k=45\), corresponding to \(f_{bin}[45]=10\),986.328 Hz, is \(\delta m=0.05\). In the first part, we study the accuracy and precision of the amplitude values, while in the second part, we consider the accuracy and precision of the phase values. We note that DFT in this section represents both FFT and Goertzel.
# Enhancing Real-Time Video Streaming Quality via MPT-GRE Multipath Network
## 8 Evaluation of Video Streaming Performance
Additionally, the MPT-GRE tunnel benefits from multiple paths, which aggregate throughput, reduce congestion, and handle packet loss more effectively than a single path. Distributing packets over several paths helps sustain higher throughput, directly contributing to better video quality. Higher throughput minimizes interruptions, reduces jitter, and ensures a consistent data flow, preventing the quality degradation often observed with a single path.
## 2 Methods
### Processing Radar Data by Combining BP and RPCA  
RPCA can be used to decompose a matrix into low-rank and sparse components. Low-rank matrices generally contain little information, and they are indicative of regular structures. Sparse matrices, on the other hand, only contain a few non-zero elements, and they are indicative of prominent points or structures. Therefore, RPCA can be used to distinguish sparse anomalies in migration imaging that can be distinguished from low-rank background noise, ghost images and regular bedding anomalies in GPR data.  
In this paper, we combined the BP algorithm with the RPCA algorithm to restore the responses of lining defects and extract the imaging results related to the lining defects. Specifically, the implementation steps of the integrated approach are as follows (see Figure 2):  
1. Preprocessing the detection data, including direct wave removal, signal gain, bandpass filtering and moving average. Note that to eliminate the random disturbance of the characteristics of the white Gaussian noise that affects BP imaging and RPCA, a Gaussian smooth filtering is also required for the detected data.
2. Performing BP imaging on the pre-processed data and Gaussian smooth filtering on the imaging results.
3. Decomposing the migration imaging results with RPCA. The interference of multipath ghosts in BP imaging results is because of low-rank characteristics, and most of the information is contained in a low-rank matrix A. The imaging results of lining defects are usually sparse, and most of the information is included in the sparse matrix E.  
Figure 2: The implementation steps of the integrated approach.
# Building Scalable and Secure Multicast Delivery Infrastructure in a Local Area Network
## 4 Core Based Multicast Tree
### Security Analysis  
In this subsection, we analyse how robust our algorithm is in terms of security requirements.
# Collision Risk Evaluation and Verification of GNSS-Based Train Integrity Detection
## 6 Conclusions  
This paper proposed methods of formal and Monte Carlo simulation-based collision risk evaluation and verification of GNSS-based Train integrity Monitoring Systems. When GNSS in applied in TIMS, the positioning error is the uncertain factor in train integrity detection. Based on the positioning errors and protection level from the filtering, the collision risk evaluation method is proposed by using PFH to quantity the SIL. To verify the collision risk of GNSS-based TIMS, an experiment-based Monte Carlo simulation procedure is presented. In the simulation, GNSS localization statistics are found from the field test in the High Tatra Mountain railway line. The CPN is employed to simulate the positioning errors based on the testing scenarios and states, then the protection level is computed in MATLAB, and the PFH is derived. The simulation results show that the GNSS-based TIMS satisfies the safety requirements in the system design phase for railway applications.  
Future research will concentrate on the more complex scenarios of both GNSS localization and TIMS operation for simulation. In the next phase of system development, more real system operation data should be collected and analyzed to further evaluate the train integrity detection performance.  
Collision Risk Evaluation, K.J.; train integrity, L.C.; colored Petri Net, S.L.; safety verification, X.L.; simulation procedure, X.P. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Key Research and Development Program of China (2018 YFB1600600), National Natural Science Foundation of China (61903024), S&T Program of Hebei(20310801D), Beijing Natural Science Foundation (L191013).  
Not applicable.  
The authors declare no conflict of interest.