esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Through the cooperation between spatial nodes in different layers, a Multi-Layer Space Communication Network (MLSCN) can massively transfer data with low latency. Especially in a MLSCN consisting of UAVs and HAPs, flexible UAVs can cope with the burst of massive data transmission when hot events happen, and a stable network can be built by almost stationary HAPs to ensure the reliability of data transmission. However, the communication environment between nodes varies from layer to layer, and the motions of nodes are also taken into account when establishing the inter-layer links, which further increase the difficulty of CPD. In this paper, we study the CPD in a MLSCN by introducing an intelligent computing method. We divide the CPD into intra-layer CPD and inter-layer CPD, and schedule the CPs in the delivery order of data. Specifically, a MLSCN model containing ground stations, UAVs, HAPs, and satellites, is presented first, and TEG is introduced to illustrate the difference between contact topology and CPs in MLSCN. Then, different CPD schemes are proposed for different inter-layer and intra-layer, respectively. For inter-layer contacts, a CI method named Multidirectional Particle Swarm Optimization (MPSO) is proposed to schedule conflicting contacts in an iterative manner. To ensure that the particles are able to search the solution domain as completely as possible during the initial stage of iterations, the gird-based initialization in MPSO maximizes the diversity of the CPs in the initial solution set. In addition, to avoid the particles' falling into local optimization trap, the quaternary optimization of MPSO can adjust the direction of searching particles based on the optimal position and the worst position. For intra-layer CPs, since the data in UAVs is transferred cooperatively through HAPs and satellites, a load balancing strategy is introduced in the UAV layer to deliver the data to the higher layers as soon as possible. The main concern of the HAP layer and the satellite layer is to relay the data from the lower layer and transfer it to ground stations. Therefore, we adopt the modified Dijkstra algorithm and Dynamic Virtual Topology Routing (DVTR) algorithm in the CPD of the HAP layer and the satellite layer. The simulation results show that our proposed CPD scheme can deal with the dynamic topology, and realize real-time, high-efficiency, and massive data transmission. The remainder of this paper is organized as follows. In Section 2, a MLSCN consisting of ground stations, UAVs, HAPs, and satellites is introduced, the data transfer process is characterized in a TEG manner, and a problem description is presented. Then, MPSO is proposed for the inter-layer CPD in Section 3, and optimized strategies for the intra-layer CPD of each network layer are introduced in Section 4. Finally, simulation results are presented and analyzed in Section 5 and conclusions are drawn in Section 6.
# Analysis and Synthesis of Architectures for Automotive Battery Management Systems
### Further Development of E/E Architectures and Challenges in Product Development  
The change from combustion engine driven vehicles to EVs lays the chance open to reduce the number of ECUs in vehicles. Not only OTA updates, but also the growing connectivity between different subsystems can only be realized by centralized E/E-architectures efficiently. Space, weight, energy consumption and costs are important parameters in the design process of vehicles. In particular, for electric vehicles, a reduction in physical ECUs makes sense, especially because software has an even greater share in these vehicles than in HEVs or vehicles powered by internal combustion engines. Together with the growing relevance of ADAS, many systems need to share information among each other. This will promote the centralization of the E/E-architecture and the combination of several subsystems into one system.  
As mentioned in Section 1, avionic E/E-architectures nowadays work with multi-core processing units. According to [20; 36; 37] multi-core operating systems are also promising future technologies for EV E/E-architectures. It enables the efficient use of a computing unit. High-performance applications such as x-by-wire and the BMS can be implemented more easily this way. Multi-core units are able to process several tasks parallel on separate cores. This results in an efficient use of physical hardware power and reduces the loss of energy at the same time. Nevertheless, the other architectures shown in Section 1 are also promising for EVs. Many manufacturers need to transform their current decentralized systems into more centralized ones, which can be enabled by an evolutionary product development process (compare Section 5).  
Coming from a decentralized architecture, a domain oriented architecture already opens up advantages such as OTA updates and the combination of related sub-ECUs into one domain. In terms of a domain-oriented E/E-architecture, there are several domains found: The powertrain or vehicle control domain, which handles functions considering the movement and energy flow in EVs, the ADAS domain for autonomous driving functions, a body and comfort domain for the interior functions, a connectivity domain that handles communication between the car and further several devices and sometimes also an  
Figure 4: Exemplary BMS-architecture with a powertrain-domain integrated master unit and a daisy-chain communication.  
infotainment domain [6; 38]. A powertrain or vehicle control domain unit is indispensable in EVs due to the required connectivity between the single electric components needed for driving.
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Advantages** & **Explanation** \\ \hline
**Multiwavelength LEDs**[29] & & \\ \hline \multirow{6}{*}{Enhanced precision} & Using LEDs with different wavelengths allows for improved precision in distance estimation. Different wavelengths allow the system to account for variations in the environment, such as potential obstructions or reflections, providing a more accurate representation of the actual distance between the transmitter and the receiver. & \\ \cline{1-1}  & Mitigation of interference & The use of multiple wavelengths reduces the likelihood of interference with other light sources or electronic equipment in the hospital. This is especially crucial in healthcare settings, where the coexistence of various technologies is common. & \\ \hline
**RSS Method**[30] & & \\ \hline \hline \multirow{6}{*}{Accuracy in dynamic environments} & The RSS method excels in providing accurate distance estimates even in complex and dynamic hospital environments. Its reliance on signal strength allows for real-time adjustments, accommodating changes in the surroundings or potential obstacles, which is particularly vital in areas where equipment or the movement of medical personnel is frequent. & \\ \cline{1-1}  & Reduced environmental interference & Unlike some other methods that can be affected by environmental noise, the RSS method is less susceptible to interference, contributing to a more reliable and stable localization process. & \\ \hline
**PSO Scheme**[33] & & \\ \hline \multirow{6}{*}{Optimized trilateration} & Integrating the PSO scheme into the trilateration algorithm optimizes the localization process. PSO enhances the convergence speed of the algorithm, ensuring a faster and more accurate determination of the target location. This is especially advantageous in time-sensitive medical scenarios. & \\ \cline{1-1}  & PSO aids in overcoming the challenges posed by NLOS scenarios, common in indoor environments. It allows the algorithm to adapt and converge even when the direct line-of-sight (LOS) is obstructed, contributing to the overall robustness of the system. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: System components and advantages. Regarding the organization of the article, the following details are provided. Section 2 describes the implemented VLC system along with its main features. Section 3 describes the PSO algorithm implemented for trilateration. Section 4 provides a detailed description of the procedure, presents the parameters used in the simulation of the system, and discusses the results obtained. Finally, Section 5 concludes the article by summarizing the key findings and drawing conclusions from the work carried out.
## Appendix A Proof of Theorem 1  
The derivation method of SOP for \(U_{1}\) and \(U_{2}\) is the same, and we present the SOP calculation steps for \(U_{2}\) and \(U_{3}\) here.  
\[\begin{split} P_{U_{2}\_{\_}{\text{sop}}}(R_{2}^{s})& =\text{Pr}\big{[}C_{\_}{\_}{\text{s}_{2}}\leq R_{2}^{s}\big{]}\\ &=\text{Pr}\big{[}\text{log}_{2}\big{(}1+\gamma_{\_}{\gamma_{\_}{U _{2}}}\big{)}-\text{log}_{2}\big{(}1+\gamma_{\_}{\gamma_{\_}{U_{2}}}\big{)} \leq R_{2}^{s}\big{]}\\ &=\int_{\omega}^{\frac{\alpha_{2}}{\alpha_{3}}}f_{\_}{\gamma_{\_}{ U_{2}}}(x)dx+\int_{0}^{\omega}F_{\_}{\gamma_{\_}{U_{2}}}(\theta_{\_}{2}x+\theta_{ \_}{2}-1)f_{\_}{\gamma_{\_}{U_{2}}}(x)dx\\ &=\sum_{k=0}^{M}{(-1)^{k}\left(\begin{array}{c}M\\ k\end{array}\right)}\frac{\lambda_{\_}{U_{2}}}{\lambda_{\_}{E}k\theta_{\_}{2}+ \lambda_{\_}{U_{2}}}\Big{(}1-e^{-\frac{Q}{\lambda_{\_}{PD}D^{s}}}\Big{)}e^{- \frac{\text{b}^{2}\big{(}\theta_{\_}{2}-1\big{)}}{\lambda_{\_}{U_{2}}\alpha_{ \_}{3}R_{2}^{s}}}\end{split} \tag{2}\]  
Using Gaussian-Chebyshev quadrature, (1) can be approximated as follows:  
\[\begin{split} P_{U_{2}\_}{\text{sop}}(R_{2}^{s})& =1-\sum_{\_}{n=1}^{N}\frac{\sigma^{2}\alpha_{\_}{2}\omega\pi\sqrt{1- \tau_{\_}{n}{}^{2}}}{\left(\alpha_{\_}{2}-\alpha_{\_}{3}v_{\_}n\right)^{2} \lambda_{\_}{E}P_{\_}{s}2N}e^{-\left(\frac{\sigma^{2}\upsilon_{\_}{\text{sop} }}{\lambda_{\_}{E}P_{\_}{s}(\alpha_{\_}{2}-\alpha_{\_}{3}v_{\_}n)}+\frac{ \sigma^{2}\left(\theta_{\_}{2}v_{\_}{\text{sop}}+\theta_{\_}{2}-1\right)}{ \lambda_{\_}{U_{2}}P_{\_}{s}(\theta_{\_}{2}-\alpha_{\_}{3}(\theta_{\_}{2}v_{ \_}{\text{sop}}+\theta_{\_}{2}-1)\right)}}\end{split} \tag{3}\]  
\[\begin{split} P_{U_{3}\_}{\text{sop}}(R_{3}^{s})& =\text{Pr}\big{[}C_{\_}{\text{s}_{3}}\leq R_{3}^{s}\big{]}\\ &=\text{Pr}\Big{[}\text{log}_{2}\big{(}1+\gamma_{\_}{\gamma_{\_}{U _{3}}}\big{)}-\text{log}_{2}\big{(}1+\gamma_{\_}{\gamma_{\_}{U_{3}}}\big{)} \leq R_{3}^{s}\big{]}\\ &=\int_{\omega}^{\frac{\alpha_{2}}{\alpha_{3}}}f_{\_}{\gamma_{\_}{ U_{2}}}(x)dx+\int_{0}^{\omega}F_{\_}{\gamma_{\_}{U_{3}}}(\theta_{\_}{3}x+\theta_{ \_}{3}-1)f_{\_}{\gamma_{\_}{U_{2}}}(x)dx\\ &=\sum_{\_}{k=0}^{M}{(-1)^{k}\left(\begin{array}{c}M\\ k\end{array}\right)}\frac{\lambda_{\_}{U_{3}}}{\lambda_{\_}{E}k\theta_{\_}{3}+ \lambda_{\_}{U_{3}}}\Big{(}1-e^{-\frac{Q}{\lambda_{\_}{PD}D^{s}}}\Big{)}e^{- \frac{\text{b}^{2}\big{(}\theta_{\_}{3}-1\big{)}}{\lambda_{\_}{U_{3}}\alpha_{ \_}{3}R_{3}^{s}}}\end{split} \tag{4}\]  
According to BS transmit power \(P_{\_}{\_}{\text{s}}=\min\Big{(}P_{\_}{\text{s}},\text{Q}/\left|h_{\_}{PD} \right|^{2}\Big{)}\), the SOP of \(U_{1}\), \(U_{2}\) and \(U_{3}\) in Formulas (19) and (20) can be obtained after calculating the statistical average of the interfering channel gain variable \(\left|h_{\_}{PD}\right|^{2}\) in Formula (17).
# Response of Corroded Steel Pipeline Without and with CFRP Reinforcement to Reverse Fault Movement
## 2 Finite Element Model
### Simulation of Fault Displacement and Pipe-Soil Interaction  
The frictional contact model, face-to-face discretization, penalty function, and hard contact are used to simulate fault displacement [26]. The friction coefficient at soil interfaces is set to 0.7, while the coefficient at the pipe-soil interface is set to 0.3 [27]. The pipeline mesh is refined within 10 m near the fault plane, while the mesh of the farther part is relatively coarse.  
The loading is applied in two stages. First stage: the soil domain and bottom surface are fixed, and the gravity load is applied to the whole model to simulate the initial geostatic stress conditions and the deformation of the whole model. Second stage: the footwall is fixed, and the hanging wall represents the displacement applied by the moving block \(60^{\circ}\) along the fault direction to simulate the reverse fault movement, and both are fixed in the normal direction. The fault displacement caused by an earthquake is predicted based on an empirical statistical equation [28], i.e.,:  
\[\begin{array}{ll}\log_{10}d_{max}=\text{M}&-2.247\log_{10}\left(\frac{k}{L_ {R}}\right)+0.6489M+0.0581s-0.3407v-2.985\\ &-0.1369M^{2}-0.0306S_{L}+0.2302S_{L}^{2}+0.5792S_{L}^{3}\\ &+[-0.3898R-0.2749(1-R)]R/100,\end{array} \tag{3}\]  
where M is earthquake magnitude, R is epicentral distance (km), H is depth of seismic source, and LR is rupture length.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(\mathbf{E_{1}}\)/MPa & \(\mathbf{E_{2}}\)/MPa & \(\mathbf{N_{u}}\) & \(\mathbf{G_{12}}\)/MPa & \(\mathbf{G_{13}}\)/MPa & \(\mathbf{G_{23}}\)/MPa & \(\mathbf{t_{CFR}}\)/mm \\ \hline
230,000 & 1900 & 0.3 & 3387 & 3387 & 3387 & 0.18 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Mechanical properties of CFRP material.  
Figure 2: The Ramberg–Osgood constitutive model of X65 steel.
## 2 Study Area
### Step 1: Measuring PSI Indicators at the Census Block Level
#### 3.3.2 Multilevel Modeling  
As we are explicitly interested in variation within and between neighborhoods, the random intercepts and slopes were specified to covary in the multilevel modeling [73]. The individual-level citizens' perceptions were treated as dependent variables, and the PSI contextual value of each neighborhood unit was treated as the independent variable. The multilevel model was carried out by using the lme4 library in R. It is expressed by the formula [82]:  
\[Y_{ij}=\beta_{0}+\beta_{10}PSI_{ij}+u_{0j}+u_{1j}PSI_{ij}+e_{ij} \tag{1}\]  
where \(Y_{ij}\) is the perception (self-perceived health status/neighborhood cohesion/neighborhood safety) of individual \(i\) in cluster \(j\), \(PSI_{ij}\) is the PSI index representing the contextual information of cluster \(j\), \(\beta_{0}\) is the overall mean across the whole clustering layers, \(u_{0j}\), \(u_{1j}\) represents the effects of cluster \(j\) on \(Y_{ij}\), and \(e_{ij}\) is an individual-level residual.  
The variance partition coefficient (VPC) and the log-likelihood value (LR) were used to explore the multiscale variances of the neighborhood PSI contextual characteristics in relation to citizens' perception of place. The VPC can be expressed as:  
\[VPC=\frac{\delta_{\mu}^{2}}{\delta_{e}^{2}+\delta_{\mu}^{2}} \tag{2}\]  
where \(\delta_{u}^{2}\) is the external variance between groups and \(\delta_{e}^{2}\) is the internal variance within groups. The VPC measures the percentage of the variance in \(Y_{ij}\) that can be attributed to differences between clusters. The higher the VPC, the higher the external variance of \(Y_{ij}\) and the lower the internal variances of \(Y_{ij}\), which means more homogeneity of citizens' perceptions within a neighborhood.  
The LR statistic was used to test the significance of the effects of the cluster or neighborhoods on \(Y_{ij}\). If LR is larger than 3.84, it means that there are significant neighborhood effects on citizens' perceptions. The LR statistic is calculated as follows:  
\[LR=-2\log L_{1}-(-2\log L_{2}) \tag{3}\]where \(L_{1}\) is the likelihood value of the multilevel model, and \(L_{2}\) is the likelihood value of a null single-level model.
# Data-Driven Health Assessment in Flight Control System
## 4 Health Assessment Method
### Fuzzy Comprehensive Evaluation
(7) Calculating the health index of the channel: As the evaluation vector for channel \(X_{i}\) is obtained, the evaluation vector \(b_{i}\) is weighted summed and normalized to obtain the health index of the channel \(SCHI_{i}\), which can be shown as:  
\[SCHI_{i}\ =\ \frac{\sum\limits_{k\ =\ 1}^{m}b_{i}^{k}(\mathrm{m}-k+1)}{m\sum \limits_{k\ =\ 1}^{m}b_{i}^{k}}, \tag{7}\]  
where m is the interval number of health state interval sets, \(k\) is the sequence number of elements in \(b_{i}\), \(k\ =\ 1,2\cdots m\)
# Object/Scene Recognition Based on a Directional Pixel Voting Descriptor
## 4 Results
We have demonstrated that our method outperforms previous approaches, particularly in scenarios with variations in rotation, scale, and texture. Despite the increased computational complexity of our method compared to traditional point-based approaches, our algorithms achieve promising performance, laying down the basis for future improvements and applications in real-world applications. Additionally, while our implementation in MATLAB provides a solid implementation, future optimizations and hardware accelerations are expected \begin{table}
\begin{tabular}{c c} \hline \hline
**Method** & **Processing Time (fps)** \\ \hline SIFT [7] & 1.0044 \\ SURF [36] & 3.6597 \\ FAST [37] & 3.9117 \\ ORB [9] & 0.3820 \\ This work & 0.5726 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Processing speed for the proposed algorithm compared with previous approaches in the literature. Input image resolution 2160 \(\times\) 1080 (Full HD). Figure 14: Original SIFT [7]. Results for scene recognition showed a lot of mismatches were generated, and in this case, it could be difficult to determine if the scene was recognized or not. Accuracy = 57%. \begin{table}
\begin{tabular}{c c} \hline \hline
**Method** & **Processing Time (fps)** \\ \hline SIFT [7] & 3.3245 \\ SURF [36] & 11.4322 \\ FAST [37] & 11.4230 \\ ORB [9] & 1.0328 \\ This work & 2.0012 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Processing speed for the proposed algorithm compared with previous approaches in the literature. Input image resolution 1080 \(\times\) 540 (HD). to further improve processing speed and efficiency. We believe that our work allows for improvements such as additional constraints for the descriptor previously laid down, non-maximal suppression methods (to avoid multiple matches for some features in the template and query), and so on.
# A Compact Dual-Band Microstrip Patch Antenna for C- and X- and Ku-Band Applications +
###### Abstract  
The paper presents a compact dual-band pentagonal-shaped patch antenna, with resonating frequencies 7.6 GHz and 12 GHz, that is used for satellite communication, 5G application, and high-speed applications. The proposed antenna is designed on an FR4 substrate with an overall dimension of 16 \(\times\) 16 mm where the height of the substrate is 0.8 mm. The proposed antenna contains a pentagonal-shaped patch with four circles at each corner of the patch that is used for the dual-band; in addition, the circular slot with the combination of the cross-shaped slot achieves better results. The proposed antenna has a partial ground configuration for better bandwidth and gain. The peak gain of the antenna is 8.07 dB at 12 GHz and has a 7.13 dB gain at 7.6 GHz. With its compact size and wide bandwidth capabilities, the antenna proves to be an ideal solution for mobile communication systems, satellite ground stations, and remote sensing applications across C-, X-, and Ku-bands. The proposed antenna also covers Ku used for satellite and high-speed communication.  
Published: 20 September 2023  
Department of Telecommunication Engineering, University of Engineering and Technology Taxila,  
Taxila 47050, Punjab, Pakistan, [EMAIL_ADDRESS] (M.M.T.); [EMAIL_ADDRESS] (Y.A.)  
* Correspondence: [EMAIL_ADDRESS]  
* Presented at the 8 th International Electrical Engineering Conference, Karachi, Pakistan, 25-26 August 2023.
_applied sciences_  
_Article Modeling and Testing of ESD Protective Textiles_  
**[PERSON] \({}^{1,\star}\)\({}^{\text{\textcircled{\char 31}}}\)**, \({}^{\text{\textcircled{\char 31}}}\), [PERSON] \({}^{2}\)\({}^{\text{\textcircled{\char 31}}}\) and [PERSON] \({}^{1}\)\({}^{\text{\textcircled{\char 31}}}\)**  
**Featured Application: Protection against electrostatic discharge (ESD) is crucial in many industries and everyday life. The results described in this paper have the potential to be helpful for the design process of ESD textiles. The described modeling process, along with the simulator settings leading to convergent results and the provided plots and illustrations, allow for an understanding of the charge decay phenomenon occurring in textiles.**  
This article discusses the important issue of designing textiles for electrostatic discharge (ESD) protection. ESD protective textiles are used to prevent the failure of electronic circuits. They also safeguard human health and life in explosive environments. The textiles are usually made of woven, knitted, or nonwoven fabrics incorporating a grid or strips of conductive fibers within a base material made of cotton, polyester, or blends of these materials. Various testing standards have been developed to evaluate the suitability of textiles for ESD protection. One of the most widely used is the EN 1149-3 standard, which outlines procedures for recording charge decay plots. The procedure can be used to evaluate all types of textiles. This paper discusses models corresponding to the standard developed in the general-purpose COMSOL Multiphysics software. Using the advanced numerical methods of the software, it is possible to graphically present the phenomena occurring during the application of the standard procedure and to determine the influence of the grid and material parameters on the shape of the charge decay plots. Furthermore, this article compares charge decay plots and shielding effectiveness measured in an accredited laboratory with simulation results.  
**Keywords:** anstatic materials; computer-aided design; electrostatic discharge protection; induction decay method; modeling; shielding effectiveness
# Revolution or Evolution? Technical Requirements and Considerations towards 6G Mobile Communications
## 6 Enablers for 6G and Relevant Technical Preparation and Implementation
### Cell-Free mMIMO (CF-mMIMO) Technology  
mMIMO is starting to be deployed in some markets worldwide, but it is still a relatively immature technology that is expected to mature and provide more applications and use cases in 6G. One of the current challenges of broadband connectivity is providing stable/reliable service quality in a coverage area. The utilization of cell-free (distributed) mMIMO is considered one of the potential solutions to improve coverage for the future. In cell-free structures, all distributed mMIMO should appear as one physical co-located mMIMO to form an ultra mMIMO.  
Figure 6: Holographic beamforming.  
CF-mMIMO (Figure 7) is considered a spectral and energy-efficient system that is capable of simultaneously serving numerous users over the same radio resource. At the same time, it can effectively reduce radiation power consumption and mitigate interference between adjacent user terminals. However, along with numerous advantages of mMIMO, its performance is limited by challenging problems, such as complex precoding procedure, time synchronization in time division duplex (TDD) [68], and large CSI feedback overhead.  
As discussed in Section 4, one of the main limitations of 5G is the issue of time synchronization. In a real-time scenario, multiple objects are going to collaborate with each other in a physical or in a virtual world; therefore, in CF-mMIMO the importance of time synchronization in addition to the CSI overhead and resource allocation will be vital.