esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Researches
### FIS (Fuzzy Inference System)  
Fuzzy inference systems take inputs and process them based on the predefined rules to produce crisp outputs. Both the inputs and outputs are practical values, whereas the internal processing is based on fuzzy rules and fuzzy operation [32; 33; 34; 35; 36; 37].  
The processing of the FIS consists of the steps as follows:  
1. A fuzzification supports the application of numerous fuzzification methods and converts the crisp input into fuzzy input.
2. A knowledge-based rules and database are formed upon the conversion of crisp input into fuzzy input.
3. The defuzzification fuzzy input is finally converted into crisp output.  
The FIS process is shown in Figure 4.  
Mamdani-style fuzzy inference requires one to find the centroid of a two-dimensional shape by integrating across a continuously varying function. In general, this process is not computationally efficient. For computational efficiency, a fuzzy singleton is used as a set with a membership function that is unity at a single point on the universe of discourse and zero everywhere else. This Sugeno-style fuzzy inference is very similar to the Mamdani method. However, [PERSON] changed only a rule consequently. Instead of a fuzzy set, he used a mathematical function of the input variable [38; 39; 40; 41; 42; 43; 44; 45; 46; 47].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**\(T\)(n)** & \(\frac{E_{\text{Format}}}{T_{\text{new}}}\) & \(T\)(\(n\))\({}_{new}\) \\ \hline \multirow{3}{*}{0.7888} & 1 & 0.7888 \\  & 0.5 & 0.3944 \\ \cline{1-1}  & 0 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Change in the selection probability for being CH due to residual energy.  
Figure 3: One round of flow-chart of LEACH.  
In this paper, we have chosen the Mamdani FIS method because it is widely accepted and is the most commonly used method in FIS, which has the advantage of being intuitive and easy to understand.
## 1 Introduction and Motivation
### Graph-Based Algorithms  
The motion-planning problem can also be solved using a graph-based algorithm. This method uses three different layers [5]:  
1. Prediction of the motion of the surrounding vehicles.
2. Determination of the collision-free trajectories.
3. Computation of the feasible trajectories for the overtaking maneuver.  
First, a spatial prediction horizon is defined in such a way to cover the whole area of the overtaking maneuver. This spatial horizon is discretized in both longitudinal and lateral directions, creating a finite number of prediction points using equidistant segments. Then, the predictions of the participating vehicle are performed using a similar algorithm to the method presented in the previous subsection. In [6], the authors used a multilayer perceptron approach to predict the motion of the vehicles. The uncertainty is taken into account by Gaussian propagation [7]. The main difference is that the prediction is extended with the probability of the collision in the lateral direction, which requires the computation of the lateral motion of the vehicle. The density function of the lateral motion can be easily computed. The feasibility of the possible trajectories can be determined by considering the maximum lateral acceleration of the trajectories. Firstly, the probabilities of collisions are computed for each discrete point of the prediction horizon. Secondly, a graph is created, in which nodes are assigned to the previously-computed discrete sets. The probability values are computed to every set and these can be assigned to the nodes. The nodes are connected with edges. Each edge has a weight, which reflects on the probability of the collision. This leads to one directed, weighted graph. Using a greedy search method like [PERSON]'s algorithm [8] the shortest path can be found, which means in this case, the path with the sum of lowest probability values. The greedy search algorithm results in a set of discrete points. However, these discrete points do not provide a continuous trajectory, therefore it may not be tracked by the vehicle. Furthermore, an online trajectory planning method is also applied to ensure the feasibility of the vehicle. The final trajectory is computed by a Model Predictive Control (MPC) algorithm using the result of the greedy algorithm.
# Parallel Complex Quadrature Spatial Modulation
## 2 System Model and Related Works  
We consider the downlink communication between a base station and mobile station in a massive MIMO wireless communication system. A number of transmit antennas \(N_{t}\) and receive antennas \(N_{r}\) are installed on the base station and the mobile station, respectively. The signal symbols are drawn from a modulation set of size \(M\). The channel matrix \(\mathbf{H}\) of size \(N_{r}\times N_{t}\) and the \(N_{r}\times 1\) noise vector \(\mathbf{n}\) have i.i.d elements of circularly symmetric complex Gaussian variable with zero mean variances of one and \(\sigma^{2}\), respectively. The channel state information is assumed to be known at the receiver side.
## 1 Introduction
The corresponding measured output spectra for each scheme are plotted as insets on the left side. FF: feeder fiber, DF: distribution fiber. The question is, then, if there is a colorless transmitter that is more economical than an externally seeded RSOA scheme and still offers a better performance over the ASE spectrum-sliced source. We believe this question is answered with what is called the self-seeded RSOA-FCL transmitter shown in Figure 1b [3,17,18,19,20]. In contrast to the externally seeded scheme, the RSOA-FCL does not need extra laser sources. As the name indicates, the seeding light is the ASE emitted by the RSOA itself. A simple mirror at the RN reflects part of the emitted ASE back to the RSOA. This cuts the cost significantly. The RSOA at the ONU and a mirror at the RN form the resonant cavity that is imbedded in the distribution fiber trunk of the PON. The emission wavelength of the laser is automatically tuned by the port of the WGR to which the ONU is connected. The laser characteristics lead to a narrower spectrum, lower RIN, and a higher power compared to the ASE spectrum-sliced scheme, thus improving the transmission performance. In this paper, we compare the self-seeded RSOA-FCL with the ASE spectrum-sliced and the externally seeded RSOA schemes, as shown in Figure 1. Both simulation and experimental results show that the RSOA-FCL outperforms the ASE spectrum-sliced scheme. With a simple architecture and low cost, the RSOA-FCL offers more power, lower RIN, narrower spectrum and a \(\sim\)5 dB more signal-to-noise ratio (SNR). The externally seeded scheme delivers an additional \(\sim\)5 dB SNR over the RSOA-FCL. However, this is paid for through the expensive extra lasers needed. Finally, we perform 5 and 10 Gbit/s transmission experiments using these schemes. The results show that the RSOA-FCL is a cost-efficient solution with a performance in between of the ASE spectrum-sliced and the externally seeded sources. Thus, the RSOA-FCL is a practical colorless source for short-reach WDM-PONs with transmissions up to 10 Gbit/s. The paper is organized as follows. First, we use a mathematical model [21] to describe and compare the ASE spectrum-sliced and RSOA-FCL schemes. Next, we experimentally characterize the three schemes by measuring output power, spectrum and RIN. Finally, the performances of the three are compared by measuring their SNR and data transmission up to 10 Gbit/s.
## 3 Results and Discussion
### Effect of Surfactants on the Properties of Matrices  
#### 3.2.1 Rheology of Fresh Matrices  
Surfactants are often used to reduce the amount of water, thus the L/S ratio, given that they reduce the viscosity. They might also have an influence on the wetting of fibers in composites. The effect of two surfactants is discussed here. The effect of 2-methyl 2,4 pentanediol (\"m\") and PEG (\"p\") on the rheology of the fresh matrices K, 80K20 MKm and 80K20 MKp was compared each time with the selected matrix 80K20 MK (Figure 7; see Table 3 for matrices).  
The substitution of 20 wt.% copper slag by metakaolinite has a special effect on the viscosity (Figure 7a). At low shear rates, a decrease in the thixotropy is observed due to the addition of metakaolinite. This is interesting for the flow of the paste at almost steady conditions, for instance, when a textile is pulled through a bath of matrix. Under those conditions, the thixotropy of the pure Koranel-based matrix hinders a uniform deposition of the matrix on the textile. However, at intermediate shear rates there is no substantial difference between both pastes up to a rate of about 2/s, when the viscosity of the mixture with MK becomes slightly higher than the one without MK. The shear thinning observed at intermediate shear stresses can be related to the alignment of particles. The addition of 2 wt.% 2-methyl 2,4 pentanediol to 80K20 MK reduced the viscosity and shear stress slightly up to 1/s (Figure 7b), opposite to polyethylene glycol, for which there is a slight increase in almost the complete studied range of shear rates (Figure 7c).  
In our system, MK thus lowers the thixotropy; the surfactants did not change the rheology to a large extent. Only 2 wt.% 2-methyl 2,4 pentanediol lowered the viscosity in the intermediate range, with maximum a factor of 10. PEG slightly increased the viscosity in the studied composition range.
## 3 Experimental Plan and Setup
### Material Properties  
Concrete with a compressive strength of 28 MPa was used for the preparation of reinforced concrete beam specimens. The average compressive strength of concrete was determined by the procedure mentioned in ASTM C-39 [35] and was found equal to \(f_{c}^{\prime}=28\) MPa. The modulus of elasticity and shear modulus of concrete were 24,870 MPa and 10,360 MPa, respectively. The modulus of elasticity of concrete was calculated using the ACI 318-08 [34] and shear modulus of elasticity was computed using poison ratio of 0.2. For quality control, the ready-mix concrete was delivered by a local supplier from a plant located in Saudi Arabia. For internal reinforcement, the yield strength of \(f_{y}=420\) MPa was selected for deformed rebar. The steel reinforcement has a tensile rupture strength of 620 MPa with elastic and shear modulus values of 200,000 MPa and 76,920 MPa, respectively.  
Concrete beam specimens were cast and cured as per ASTM-C31 [36]. On completion of curing time, the external surfaces of the beam specimens were cleaned with a wet cloth and acetone. Epoxy (Sikadur 330) of uniform thickness was used to attach external CFRP strips to the concrete surface. After the application of CFRP strips on the surface of the concrete, the beams specimens were cured  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sr. No.**} & \multirow{2}{*}{\begin{tabular}{c} **Specimen** \\ **Designation** \\ **Ratio (\% Age)** \\ \end{tabular} } & \begin{tabular}{c} **External CFRP** \\ **Shear** \\ **Reinforcement** \\ **Ratio (\% Age)** \\ \end{tabular} & \begin{tabular}{c} **Total CFRP** \\ **Reinforcement** \\ **Ratio** \\ \end{tabular} & \
\begin{tabular}{c} **Number of** \\ **CFRP Shear** \\ **Ratio** \\ \end{tabular} &
\begin{tabular}{c} **Width of** \\ **CFRP Shear** \\ **Ratio** \\ \end{tabular} \\ \hline
1 & Control-C1 & N/A & N/A & N/A & N/A \\
2 & CFRP-B1 & 0.38 & 0.25 & 0.63 & 8 & 50 \\
3 & CFRP-B2 & 0.38 & 0.31 & 0.69 & 10 & 50 \\
4 & CFRP-B3 & 0.38 & 0.37 & 0.75 & 12 & 50 \\
5 & CFRP-B4 & 0.38 & 0.56 & 0.94 & 18 & 50 \\
6 & CFRP-B5 & 0.75 & 0.00 & 0.75 & N/A & 100 \\
7 & CFRP-B6 & 0.75 & 0.38 & 1.13 & 12 & 100 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Testing specimen details.  
Figure 3: Test setup (**a**) and test layout for Beam CFRP-B1 (**b**).  
for three days by using a wet layup method. Figures 1 and 2 show the layout of beam specimens along with their external and internal reinforcement details. The CFRP has a tensile strength of 1600 MPa with the ultimate tensile elongation value of 1.8%. The tensile modulus of elasticity of CFRP was 120,000 MPa. The epoxy has tensile bond and compressive bond strength values of 9.6 MPa and 21 MPa, respectively. The aforementioned material properties of CFRP and epoxy were provided by their respective suppliers.
# Precision Agriculture: A Remote Sensing Monitoring System Architecture +
## 4 The Network Layer
### The Middleware Layer
* The ONEM2M [32] technical specification standards are an upcoming solution for device and asset management in precision agriculture. ONEM2M is a middleware IoT platform that provides functions and APIs for different service domains dealing with interoperability challenges. There are commercial and open-source implementations of this technology. * A popular queuing protocol for enabling server connection in IoT is the AMQP (Advanced Message Queuing Protocol). This open standard protocol can facilitate message orientation, queuing, routing, reliability and security in precision agriculture applications. * Last but not least, the DDS (Data-Distribution Service) [33] is the first open international M2M standard directly addressing publish-subscribe communications for real-time and embedded systems. This protocol has the advantage of providing fast data, event, and command exchange among the IoT sensor nodes in a precision agriculture monitoring system.
# Induction Heating-Assisted Compaction in Porous Asphalt Pavements: A Computational Study
## 1 Introduction
### Development of Porous Asphalt  
A lot of effort has been spent worldwide and in the Netherlands on developing new materials and design specifications for durable PA pavement layers [4; 5]. PA concrete mixes are mainly used as surface courses [6; 7], and it is well known that these mixes have been developed as a material solution to increase skid resistance as well as to reduce splash during a rainstorm. Typically, an asphalt surface layer is placed, which has high air void contents, to absorb tire-pavement noise and provide good riding smoothness to reduce vehicle vibration-related noise. Factors such as aggregate characteristics, mix design, construction variables, and environment play crucial roles in the performance of PAs.  
The compaction process of PAs differs from those of the conventional dense-graded mixes, which involve both static steel wheel rollers and pneumatic-tired rollers [8]. PAs are typically compacted only by a static steel roller with a few passes over the surface [9; 10]. However, a serious problem in the compaction process of PAs is the aggregate segregation during laying down and the quick reduction of laying temperature when the continuity of material supply to the construction site is irregular [11]. The aggregate segregation causes unevenness in asphalt pavement surface and texture, whereas the rapid temperature reduction mainly causes inadequate compaction. All the before-mentioned leads to poor PA performance.
# Survey on 5G Physical Layer Security Threats and Countermeasures
## 4 mmWave and MIMO-Specific Attacks
### Pilot Contamination  
Another type of vulnerability could be pilot contamination. The term pilot contamination refers to the interference that occurs in the channel estimation process when the same pilot sequences are reused in adjacent cells or by injection by the attacker. This is a significant challenge in massive-MIMO (mMIMO) systems because the size of the coherence interval is constrained, limiting the length of the pilot sequence. In [83], the authors modify the precoder employed by the legitimate transmitter in a controlled way to strengthen signal reception at the eavesdropper during data transmission. Additionally, they explore the transmission efficiency of an advanced full-duplex eavesdropper to ensure effective eavesdropping and impair the detection capabilities of the legitimate receiver simultaneously.
# Multi-UAV Area Coverage Track Planning Based on the Voronoi Graph and Attention Mechanism
## 5 Conclusions  
This paper aims to address the multi-UAV trajectory optimization problem. First, it used the regional decomposition method based on the Voronoi diagram to transform it into a single-UAV trajectory optimization problem. Then, it improved the basic ResNet50 model and integrated CSAM and reinforcement learning strategies to reduce the average path length by 10%, significantly improving the performance. A regional decomposition method based on the Voronoi diagram was designed to transform the multi-center regional decomposition problem into a single-center regional decomposition problem so that the deep learning method can be used for single-target trajectory classification optimization and the complexity of the problem is reduced. Then, a deep learning model integrating the channel and spatial attention mechanism (CSAM) was designed, and the reinforcement learning training strategy was used to significantly improve the model's performance. Finally, the problem of UAV and UAV regional coverage was analyzed and studied from the perspective of policies and regulations, and policy recommendations were provided.  
Figure 9: Visual results of trajectory optimization algorithm integrating CSAM.  
The method in this paper has achieved excellent performance in multi-UAV path coverage tasks and has broad application prospects. However, the method in this paper is divided into two stages: region segmentation and path optimization. These stages do not achieve a unified and complete network structure, but it is a direction worthy of further research and improvement.  
Conceptualization, methodology, validation, R.W.; formal analysis, investigation, resources, data curation, writing, J.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Tianjin Applied Basic Research Multi-input Fund, grant number 21 JCQNJC00790 and National Natural Science Foundation of China (No. 72301278), the Nature Foundation Matching Program (No. 3122024 PT29).  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to commercial use.  
I would like to express my gratitude to all those who helped me during the process of researching and writing my thesis. Thanks to Tianjin Applied Basic Research Multi-input Fund (21 JCQNJC00790) for their help in funding and materials.  
The authors declare no conflicts of interest.
## Appendix D Description of General Purpose Mechanisms
### Dependability-Rank-Based Consensus [322]  
Dependability-Rank-based consensus constitutes a reputation-based consensus mechanism for permissioned networks. In this algorithm, 'bookkeepers' (participants who qualify as miners) are selected for mining subsequent blocks with a probability that aligns with their dependability rank. The mechanism is intended to be used in permissioned networks and does not offer Sybil attack resistance.
## 3 Review of Studies Related to MaaS in the Context of Multi-
### Review of Studies
Results: One approach to assessing the potential for MaaS to reduce the use of private cars in cities is to study the competitiveness of MaaS with respect to private car usage? The study [86] analyzes the competitiveness of MaaS versus private car usage for the commuting problem in a one-origin-one-destination network based on consideration of fixed cost for travel and the inconvenience cost of multi-modal trips. The analysis indicates that mode choice is affected by fixed and inconvenience cost and depends on demand. The entry fee to adopt different modes is set by fixed costs. The transportation resources utilization is influenced by inconvenience costs. The results suggest employing pricing and capacity strategies to maintain a balanced mode share. * Question: How to determine the route choices of different transport modes that can jointly form a complete path for transporting the user from origin to destination? Results: As a user provides his/her transportation request with given origin and destination to the MaaS decision support system, the system must determine the route choices of different transport modes that can jointly form a complete path consisting of multiple route choices for transporting the user from origin to destination. However, there still lacked a study on this problem. This problem was addressed in [68] as the generalized path overlapping problem described by a multi-modal logit kernel model to take into account the correlations of unobserved utilities of combined routes. The stochastic equilibrium on multi-modal transport networks was formulated as a fixed-point problem base on this model. It was found that the proposed solution method significantly affects both the route choice predictions and traffic flows at equilibrium. The numerical studies of this study were performed based on a novel network.
# Prospects for the Development of High Energy Density Dielectric Capacitors
## 7 Review of Electrochemical Capacitor Research Using Carbon/Graphene and Polymers  
As discussed in previous sections of the paper, the approach taken to increase the dielectric of the composite polymer is to embed nm size spherical particles or nano-sheets/platelets of carbon in the host polymer. Some of the research on using carbons in electrochemical supercapacitors is related to their use in developing polymer composites.  
There has been research done to generate spherical carbon particles for use in electrodes for supercapacitors. Since the objective of the supercapacitor research is to prepare carbons with high specific capacitance (F/g), the pore size distribution in the carbon and not the geometric size of particles was of prime interest. As shown in Figures 10-12, the particles appear to be nicely spherical, but their diameter is 100-500 nm in most cases [56; 57; 58]. The smallest diameter carbon spheres found in the literature was 50 nm, which is much larger than needed for the dielectric capacitors. Further work is needed to determine how spherical carbon particles having a diameter of 3-4 nm can be generated.  
Over the years, much research has been done to use various forms of carbon to increase the energy density of electric double-layer capacitors (EDLCs). The use of graphene and its derivatives in various forms can significantly increase the specific capacitance of electrode materials [59; 60; 61; 62; 63; 64]. Nanoscale graphene (particles and atomic scale layers) also enhance electron and thermal conductivity of the electrode, which improves the power capability and capacitance. Skeleton Technology [59] has developed large EDLC devices (3200 F)  
Figure 10: Spherical carbon particles.  
Figure 9: A spiral wound film capacitor tested at 1000 V [55].  
with an energy density of 8.9 Wh/kg using graphene combined with activated carbon in the electrodes. If used properly, graphene can improve the specific capacitance of carbon electrodes as its theoretical specific capacitance is 550 F/g. [PERSON] et al. [60; 61] demonstrated cells with very high energy density while maintaining high power density by laser reduction of graphene oxide. Electrochemical capacitor devices with graphene-based electrodes show excellent cycle stability (all-solid-state LSG-EC: >97% after 10000 cycles) in addition to very high energy density and power density. The laser scribed graphene-electrochemical capacitors have high potentiality for commercial applications due to their superior electrode structure. Supercapacitor research [63; 64] has also included combining conducting polymers with the nano-carbon to improve the specific capacitance (F/g) of the electrodes. In most cases, the conducting polymers have been used to coat carbon particles, nanotubes, or nanoplatelets.