esa-sceva/satcom-chunk-collection huggingface dataset:
# CeRA-eSP: Code-Expanded Random Access to Enhance Success Probability of Massive MTC
## 1 Introduction
The proposed PUSCH allocation scheme can improve PUSCH resource utilization by using unused PUSCH resources at a lower access intensity. Finally, we validate the improvement of the proposed CeRA-eSP using a performance analysis simulation. The simulation results show that the proposed CeRA-eSP achieves the highest random-access success rate while maintaining the lowest access delay. In summary, the main contributions of this study are as follows:  
* We propose a CeRA-eSP scheme to improve the RA success rate and PUSCH resource utilization. The proposed CeRA-eSP scheme consists of two phases. One is the preamble codeword set selection phase that devices can select in each RAO. The other is the PUSCH resource allocation phase to the preamble codeword recognized by the BS. * We propose a preamble codeword set selection algorithm based on the number of active devices to maximize the RA success rate. The proposed preamble codeword set selection algorithm consists of three kinds of analytic models for the preamble transmission success rate, preamble codeword utilization rate, and PUSCH timeout rate. * We propose an improved PUSCH allocation scheme based on the PUSCH waiting message to improve the utilization of PUSCH resources. * We show the performance of the proposed CeRA-eSP scheme in terms of the access delay, preamble collision rate, and RA success rate. The proposed CeRA-eSP scheme has the lowest access delay among the benchmark schemes and shows the highest RA success rate. The remainder of this paper is organized as follows. Related studies on contention-based RA, CeRA, and PUSCH resource allocation are introduced in Section 2. The system model for the preamble codeword-based RA is introduced in Section 3. Analytical models for a successful preamble transmission rate, preamble ambiguity, PUSCH resource limitation, and preamble codeword set allocation scheme are introduced in Section 4. The experimental results and performance evaluation are presented in Section 5. Finally, Section 6 concludes the paper.
## 2 Materials and Methods
### Defining Repulsion Parameters \(a_{ij}\) between Dissimilar Beads  
The repulsion parameter for the dissimilar beads is chosen based on the affinity between the moieties these beads represent as [27]\(a_{ij}=a_{ii}+3.27\chi_{ij}\) for the chosen density, where \(\chi_{ij}\) is the Flory-Huggins interaction parameter. The values of \(\chi_{ij}\) can be estimated using the respective solubility parameters \(\delta_{i}\) and \(\delta_{j}\) as \(\chi_{ij}=V_{s}\big{(}\delta_{i}-\delta_{j}\big{)}^{2}/RT\), where \(V_{s}\) is the molar volume of solvent and \(R\) is the gas constant. Based on direct comparison with a number of experimental studies, a modified empirical expression for \(\chi_{ij}\) is often found to be more reliable for polymer solutions [54; 55]: \(\chi_{ij}=\beta+V_{s}\big{(}\delta_{i}-\delta_{j}\big{)}^{2}/RT\) The value of the empirical constant \(\beta\) is typically taken as [54; 55]\(\beta=0.34\), specifically in cases when calculated values of \(\chi_{ij}\) (without \(\beta\) correction) are below 0.3. The solubility parameters used in this study are taken from the literature where possible and are provided in Table S1 of Supplementary Materials. The solubility parameter of PHMS was estimated using the group molar attraction constants, \(F^{z}\), as [55; 56; 57]\(\delta=\rho\sum\limits_{z}F^{z}/M\), where \(\rho\) is the density, \(M\) is the molar weight of the repeat unit, and the summation is taken over all groups of the repeat unit. The relevant values of \(F^{z}\) are listed in Table S2 of Supplementary Materials. The same repulsion parameters are used for all the beads within each polymer chain, it is also assumed that changing a bead state from reactive to non-reactive does not affect the beads' affinity. Finally, the values of \(\chi_{ij}\) calculated based on the solubility coefficients and the respective repulsion coefficients \(a_{ij}\) are provided in Tables S3 and S4 of Supplementary Materials, respectively. We take the temperature \(T=298.15\) K at which the reference polymer system of interest in this study was crosslinked in the prior experiments [21]. Notably, with the estimated value of \(a_{\rm PDMS-PHMS}=79.12\), single beads of PHMS are miscible with PDMS, while polymer chains of PHMS and PDMS of the chosen length are immiscible. Hence this choice of the interaction parameter is consistent with experimental observations, showing both initial compatibility between the PDMS and PHMS molecules, and the phase separation between these moieties for sufficiently high molecular weight of PHMS [19; 58].
###### Abstract  
This article characterizes and presents Global Navigation Satellite Systems in relation to rail transportation applications. Due to the review character of this article, a synthesis of the literature discussing issues related to the possibility of implementing satellite positioning systems in the framework of their use in the management and control of railway traffic was made. On the basis of the literature review, the area of potential implementation of Global Navigation Satellite Systems was identified, as well as assumptions regarding the architecture of such systems being defined, along with the definition of criteria for assessing the impact of the use of satellite systems on rail traffic safety. The purpose of the above is to direct the development of rail guidance and control systems to systems that enable precise localization of rail vehicles, thereby optimizing the use of rail infrastructure through the implementation of efficient and cost-effective localization systems. This article goes on to characterize existing Global Navigation Satellite Systems and future directions related to the use of new satellite constellations. The basis of this review is the last twenty years of scientific publications on the subject of research issues related to the use of satellite positioning in railway systems. Based on the review of the state of the art and the results of the analysis, it was determined that the most frequently mentioned area of use of satellite positioning systems is the European Train Control System, the functionality of which enables the implementation of the transportation process based on so-called moving block spacing. The results of this review of the current state of knowledge will direct those responsible for the development and implementation of modern systems in the direction and control of railway traffic.  
GNSS; ETCS; positioning; rail transportation; signaling; architecture; safety criteria; applications +
Footnote †: journal: Applied Sciences  
1
## 3 Overview of the Selected Techniques
### SOGI-Type Adaptive Observer
#### 3.3.1 Quadrature Signal-Based Dynamic Model Development  
For model development purposes, let us consider that the states are:\[\xi_{1}=U_{a}^{\perp}=-A^{+}\cos\bigl{(}\omega t+\phi^{+}\bigr{)}-A^{-}\cos \bigl{(}\omega t+\phi^{-}\bigr{)}-A^{0}\cos\Bigl{(}\omega t+\phi^{0}\Bigr{)},\] \[\xi_{2}=U_{a}=A^{+}\sin\bigl{(}\omega t+\phi^{+}\bigr{)}+A^{-}\sin \bigl{(}\omega t+\phi^{-}\bigr{)}+A^{0}\sin\Bigl{(}\omega t+\phi^{0}\Bigr{)}.\]  
Then, the following can be obtained:  
\[\dot{\xi}_{1}=\xi_{2}\omega,\] \[\dot{\xi}_{2}=-\xi_{1}\omega.\]  
By considering the state vector, \(\xi=\bigl{[}\begin{array}{cc}\xi_{1}&\xi_{2}\end{array}\bigr{]}^{T}\), the dynamic model for the grid phase voltage \(U_{a}\) is given by:  
\[\dot{\xi}=\mathcal{A}\xi, \tag{29}\] \[U_{a}=\mathcal{C}\xi, \tag{30}\]  
where  
\[\mathcal{A}=\biggl{[}\begin{array}{cc}0&\omega\\ -\omega&0\end{array}\biggr{]},\mathcal{C}=\bigl{[}\begin{array}{cc}0&1\end{array} \bigr{]}.\]  
Observability matrix of system (29) and (30) is given by:  
\[\mathcal{O}=\biggl{[}\begin{array}{c}\mathcal{C}\\ \mathcal{C}\mathcal{A}\end{array}\biggr{]}=\biggl{[}\begin{array}{cc}0&1\\ -\omega&0\end{array}\biggr{]}. \tag{31}\]  
Since the observability matrix \(\mathcal{O}\) is of rank 2 which is the same as the rank of the state matrix \(\mathcal{A}\), the system (29) and (30) is observable. Observer design for this system is described in the following section.
# Study on Flow Characteristics of Venturi Accelerated Vortex Drainage Tool in Horizontal Gas Well
## 4 Results and Discussion
### The Liquid-Carrying Capacity with Different Liquid Flow Rates  
To further investigate the impact of different liquid flow rates on the drainage performance of the tools, liquid-carrying experiments with the gas flow rate of 300 m\({}^{3}\)/h and the liquid flow rates of 1, 3, 5, 10, and 15 L/min were conducted. Photographs of the spiral flow patterns in the horizontal tube with three tools are depicted in Figure 11.  
As shown in Figure 11, it can be observed that when the gas flow rate is 300 m\({}^{3}\)/h and the liquid flow rate varies from 1 L/min to 5 L/min, the fluid pattern changes from laminar flow to unstable annular flow for the tube drainage. Moreover, the fluid flows according to spiral laminar flow for the vortex tools. The venturi accelerated vortex tool can make this flow more stable than the vortex alone. When the liquid flow rate reaches 10-15 L/min, the kinetic energy of the gas flow is not enough to drive the liquid for the tube drainage. At this point, the vortex tool has a critical role. Although the stable flow characterized by the coupling of the spiral and turbulent flows was formed for the vortex tool, the liquid can be carried relatively well to flow out of the horizontal tube.  
To analyze the flow patterns of the spiral flow at different liquid flow rates, when the gas flow rate was 600 m\({}^{3}\)/h, spiral flow experiments with different liquid flow rates of 1-15 L/min for the venturi accelerated vortex tool were conducted, as shown in Figure 12.  
Figure 11: _Cont._  
Figure 11: Spiral flow patterns of different tools with various liquid flow rates (1, 3, 5, 10, 15 L/min) and the gas flow rate of 300 m\({}^{3}\)/h.  
Figure 12: Photographs of spiral flow for the venturi and vortex tool with various liquid flow rates (1, 3, 5, 10, 15 L/min) and the gas flow rate of 600 m\({}^{3}\)/h.  
As can be observed, as the liquid flow rate increased from 1 L/min to 10 L/min, the length of the spiral flow gradually decreased, and the pitch gradually increased. The flow transitions from spiral laminar flow to unstable flow coupling the spiral and turbulent flow. When the liquid flow rate reached 15 L/min, the typical spiral flow could not be observed, and as a result, it reached the critical liquid flow rate for the tool.
## 2 Deformation Monitoring of Inverted Arch Uplifts of Soft Rock Tunnels
### Plane Fitting of Inverted Arch of Soft Rock Tunnel  
The plane fitting of soft rock tunnel inversions is carried out based on the reconstructed 3D point cloud data of soft rock tunnel invert splicing using the overall least square method, which provides data support for the subsequent monitoring of soft rock tunnel invert uplift deformations [22]. The plane fitting equation of the inverted arches of soft rock tunnels is:  
\[\hat{a}x\ +\ \hat{b}y\ +\ z\hat{c}=0 \tag{15}\]  
Here, \(\hat{a}\), \(\hat{b}\), and \(\hat{c}\) are the ground parameters.  
Assume that the plane of an inverted arch of a soft rock tunnel is scanned in three dimensions with \(\eta\) scan point coordinates, \(\{(x_{i^{\prime}},y_{i^{\prime}},z_{i^{\prime}}),i^{\prime}=1,2,\cdots,\eta\}\). Considering the 3D point cloud data of soft rock tunnel inversions in \(x\), \(y\), \(z\), if there are errors in all three directions [23], the equation is changed to:  
\[\hat{a}\big{(}x_{i^{\prime}}\ +\ \xi_{x_{i^{\prime}}}\big{)}\ +\ \hat{b}\big{(}y_{i^{ \prime}}\ +\ \xi_{y_{i^{\prime}}}\big{)}\ +\ \hat{c}\big{(}z_{i^{\prime}}\ +\ \xi_{z_{i^{\prime}}}\big{)}=0 \tag{16}\]  
where \(\xi_{x_{i^{\prime}}}\), \(\xi_{y_{i^{\prime}}}\), and \(\xi_{z_{i^{\prime}}}\) are \(x\), \(y\), and \(z\) of the error correction number in three directions.  
The ground parameters \(\hat{a}\), \(\hat{b}\), \(\hat{c}\) can be considered as the result of the orthogonal overall least square plane fitting of the tunnel inverted arch uplift surface. Now, assuming that the datum plane passes through the origin of the three-dimensional coordinate system, the datum plane formula can be obtained as follows:  
\[\hat{a}\big{(}x_{i^{\prime}}\ +\ \xi_{x_{i^{\prime}}}\big{)}\ +\ \hat{b}\big{(}y_{i^{ \prime}}\ +\ \xi_{y_{i^{\prime}}}\big{)}\ +\ \hat{c}\big{(}z_{i^{\prime}}\ +\ \xi_{z_{i^{\prime}}}\big{)}=0 \tag{17}\]  
Here, \(\hat{a}\), \(\hat{b}\), \(\hat{c}\) are the datum parameters.  
It is known that the uplift surface of tunnel inversions is perpendicular to the datum plane, so it can be obtained by combining Formulas (16) and (17) that:  
\[\hat{a}\hat{\hat{a}}\ +\ \hat{b}\hat{\hat{b}}\ +\ \hat{c}\hat{\hat{c}}=0 \tag{18}\]  
Therefore,  
\[\hat{a}=-\frac{\hat{b}}{\hat{a}}\hat{b}-\frac{\hat{c}}{\hat{a}}\hat{c} \tag{19}\]  
Formula (19) is the basic relationship of the datum plane parameters.
## 6 Open Challenges, Future Prospects and Research Directions
### ML-Driven Predictive Adaptation
#### 6.4.3 Aperture Averaging  
As FSO communication systems advance, exploring new developments in aperture averaging offers several promising directions that can significantly enhance system performance. Aperture averaging, which mitigates the impact of AT by averaging the received optical signal over a larger aperture, is critical for improving signal quality and reliability in FSO systems. Future research in this area can explore several innovative approaches to optimize and advance aperture averaging techniques.
# Performance of Fuzzy Inference System for Adaptive Resource Allocation in C-V2X Networks
## 1 Introduction
In this paper, we propose an FIS approach with multiple input variables to strengthen the dynamic \(P_{rk}\) value determination mechanism. Previous work was conducted in [26] to investigate the feasibility of FIS on V2V communications. In general, the main contributions of this work can be described as follows:  
We conducted several simulations and found that the use of static \(P_{rk}\) values had not achieved optimal performance. To explore the optimal solution to dynamically determine the \(P_{rk}\) value, we carried out an initial design approach using a matching IF-statement table. We used the vehicle distance and the Channel State Information (CSI) variable as a decision-making consideration. The results of the initial design of the IF-statement matching table were then refined by applying FIS. Performance measurement was carried out by comparing the PDR results for each scenario of fixed \(P_{rk}\) value, matching table, and FIS. The remainder of the paper is structured as follows: Section 2 describes the technology. Section 3 describes the proposed FIS. Section 4 describes the simulation configuration and simulation results. Section 5 provides the conclusion of this work.
# A Privacy-Preserving Protocol for Utility-Based Routing in DTNs
## 5 Performance Evaluation
### Performance Comparison
#### 5.2.2 Influence of TTL  
The impact of TTL on delivery ratio is shown in Figure 6. It can be seen that the delivery ratio increases as the TTL increases for all protocols; this is because the messages with larger TTL can stay longer in the buffer and have more chance to be delivered. The delivery ratios of PPUR1, PPUR2, PPUR3, and FaceChange are smaller than that of PROPHET, but the PPUR4 protocol has a similar delivery ratio to PROPHET because nodes can update the routing utility value only when encountering the TA.  
Figure 4: Delivery delay for varying buffer size.  
Figure 5: Overhead ratio for varying buffer size.  
Figure 7 shows the influence of TTL on delay. It can be seen that delivery delay increases as TTL increases for all protocols. This is because as the TTL increases, nodes can store and deliver more messages with longer delay. The delivery delay of PPUR4 is similar to that of PROPHET, and delays of PPUR1, PPUR2, PPUR3, and FaceChange are smaller than that of PROPHET.  
Figure 8 shows the impact of TTL on overhead ratio. For all the routing protocols, because more messages are successfully delivered as TTL increases, the overhead ratio will decrease. PPUR1, PPUR2, and PPUR3 have smaller overhead ratio than PROPHET. PPUR4 protocol has a similar overhead ratio to PROPHET and FaceChange.  
Figure 6: Delivery ratio for varying TTL.  
Figure 7: Delivery delay for varying TTL.
# Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization
## 4 Results
### Comparison with Baseline  
The previous section proved the usefulness of the time-varying concept in terms of reducing the transient time of one of the second-order sections. For the whole design to be useful, one needs to focus on the performance of the final (full) filter design. Figure 6 presents the comparison of the complete static solution with the novel approach to improving one of the SOS parts.  
Figure 6 compares the step responses of a time-invariant, SOS-based digital filter (blue dashed line) with a time-varying, SOS-based design (red solid line). The baseline refers to a standard sixth-order elliptic filter, implemented using three fixed second-order sections. All coefficients remain constant over time, and no transient optimization is applied. In the proposed LTV design, the same sixth-order elliptic filter structure is used, but only one SOS (#2) has its coefficients varied across five samples based on the SQP-optimized trajectory. The other two SOSs remain identical to those in the baseline. Notably, the time-varying filter converges more rapidly to the steady-state level, displaying less overshot and fewer oscillations during the early samples. This outcome underscores the advantage of selectively adjusting SOS coefficients to reduce unwanted oscillations and accelerate the settling process, reducing the transient time of the filtering structure. Table 6 summarizes the overall improvement in the reduction in the transient time of the complete design when compared to the classical time-invariant structure.  
As one can notice, the reduction in the transient time has reached up to 80% for the 5% threshold, which should be considered a major improvement.  
Figure 6: Comparison of full classical time-invariant filter with the novel design with one time-varying SOS.  
\begin{table}
\begin{tabular}{c c c} \hline
**Transient Time Threshold** & **Sample Index** & **Time** \\ \hline
1\% & 3 & 0.02 s \\ \hline
2\% & 3 & 0.02 s \\ \hline
5\% & 3 & 0.02 s \\ \hline \end{tabular}
\end{table}
Table 5: Transient time data for time-varying SOS.
# A Review of Methods and Applications for a Heart Rate Variability Analysis
## 6 Classification Techniques
### _Support Vector Machine_  
One standard supervised learning method, a support vector machine (SVM), may be used to address categorization and regression issues simultaneously. Its purpose is to find the ideal contour (called the hyperplane) for categorizing n-dimensional space into categories. The features in the dataset determine the dimension of the hyperplane. The SVM can be linear or non-linear based on the nature of the dataset. Data that can be split into two groups in a linear fashion are said to be differentiable, and the SVM classifier used in such cases is known as a linear SVM. A non-linear support vector machine can be employed if a linear classification scheme fails to work on a given dataset. A simple graphical representation of both the linear and non-linear SVM is presented in Figure 9 below.
_applied_  
_sciences_  
_Article_  
Assessing Ground Motion Intensity Measures and Structural Damage Measures in Underground Structures: A Finite Element Analysis of the Daikai Subway Station  
**[PERSON] 1, [PERSON] 2, [PERSON] 2,* and [PERSON] 3\({}^{\copyright}\)**  
Footnote 1: School of Management, Shenyang Jianzhu University, Shenyang 110168, China; [EMAIL_ADDRESS]  
Footnote 2: School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110168, China; [EMAIL_ADDRESS]  
Footnote 3: State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China; [EMAIL_ADDRESS]  
Footnote 4: Correspondence: [EMAIL_ADDRESS]; Tel.: +86-(0)24-2469-1868  
**Abstract: Research on the characterization of ground motion intensity and damage of underground structures is limited, while reasonable selection of ground motion intensity measures and structural damage measures is a crucial prerequisite for structural seismic performance evaluation. In this study, a two-dimensional finite element model of soil and structures was established based on the Daikai subway station in Japan. Through incremental dynamic analysis, 32 ground motion intensity measures and seven structural damage measures were comprehensively evaluated from seven properties, including efficiency, practicality, proficiency, scaling robustness, relativity, hazard computability, and sufficiency. According to the analysis results, the purpose and significance of each property during measure optimization were hierarchically sorted out. The results show that peak ground acceleration, acceleration spectrum intensity, and sustained maximum acceleration are recommended as ground motion intensity measures, while maximum inter-story drift ratio, column end displacement angle, and two-parameter measures are recommended as the structural damage measures for seismic performance evaluation of the shallow-buried subway station. Furthermore, measure optimization approaches are proposed as follows: the basic selection of IMs should satisfy scaling robustness, hazard computability, and sufficiency to site condition; the optimal selection of IMs is suggested to be evaluated mainly through efficiency, practicality and proficiency, and verified through relativity and relative sufficiency between IMs. The optimal selection of DM is suggested to be evaluated through four properties, including efficiency, practicality, proficiency, and relativity.**  
**Keywords: subway station structure; ground motion intensity measure; structural damage measure; incremental dynamic analysis; measure optimization approach**