esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Recent developments in online marketing have enhanced the value of free space optics (FSO), purposing to improve the capacity and transmission accuracy of communication systems [1]. Low cost installation, improved security, and colossal bandwidth are the critical properties of FSO; therefore, communication system FSO based design is widely used in terrestrial and deep space applications [2]. The main structure of FSO is linked with the setup of an optical network; it takes inputs from laser based transmitters and is received at the photodiode based receiver [3]. Hence, the achievements of FSO can be further enhanced with the joint framework of optical networks. With the help of this structure, the issues in existing FSO models, such as radio frequency (RF) related matters, FSO pointing, and co-channel interference impairments, can be organized efficiently. In addition, the performance of 5G services can be improved by applying the composite structure of FSO and optical networks [4]. In this paper, the outage probability and commutative, distributive function (CDF) calculations are optimized for FSO and optical network based communication links.  
The simulation and analytical approach are estimated in terms of peak to average power ratio (PAPR) and bit error rate (BER).
## 6 Numerical Examples
### Numerical Example 3: Notched Plate with Hole (NPwH)
Furthermore, the analysis has been conducted using two different anisotropic strain energy splits widely used within the phase field literature (Figure 30):  
1. Spectral decomposition of strains proposed in [232]
2. Volumetric Deviatoric strain split proposed in [264]  
The crack path predicted via the spectral strain decomposition [232] appears closer to the experimentally observed crack than the volumetric-deviatoric strain split [264] (Figure 30a,b). These minor differences are also reflected to the equilibrium paths shown in Figure 30c. Since, contrary to the spectral strain decomposition split, the volumetric-deviatoric split only partially prohibits degradation due to purely compressive stresses, a higher amount of material is overall degraded in the latter case; hence the peak force is indeed expected to be lower. However, the spectral strain decomposition leads to a highly nonlinear formulation and therefore increased computational costs--see also [265] for a hybrid procedure to alleviate these. This highlights the significance of choosing the appropriate split and hence the level of expert judgment required when employing PFM for LEFM. Figure 23: NPwH geometry, material parameters, loading and boundary conditions. Figure 24: NPwH load-deflection curves. Figure 25: NPwH crack-paths obtained from SBFEM, XFEM and PFM-based crack propagation analysis. Figure 27: NPwH PFM force displacement response illustrating the dependence of peak fracture force on (**a**) \(\Delta u\) for Nstaggs = 1 (**b**) the number of staggered iterations. Figure 26: NPwH meshes for SBFEM (**top**) and XFEM (**bottom**), with focus on crack path region. The last crack propagation step prior to the cracks reaching the hole is depicted.
# Adaptive Impedance-Based Fault Location Algorithm for Active Distribution Networks
## 3 Adaptive Fault Location Algorithm for Active Distribution Systems
### Step 2: Processing of DER Information
#### 3.2.2 Using the Approximate Model of the Synchronous Machine for INIDER Model  
If the DER parameters are known, the approximate model of the synchronous machine is used. This model is suitable for INIDER, given that their main element is a synchronous generator.  
The main objective of this stage is to estimate the internal voltage of the synchronous generator model, using the prefault period substation voltage and current phasors (\(V_{Se}^{p}\) and \(I_{Se}^{p}\)). Therefore, considering Figure 5, a backward-sweep process from the substation to the DER node is implemented using Equations (16) and (17).  
\[\left[\begin{array}{c}\mathbf{V}_{k+1}^{p}\\ \mathbf{I}_{k+1}^{p}\end{array}\right]=\left[\begin{array}{cc}\mathbf{d}_{l}&-\mathbf{b} _{l}\\ -\mathbf{c}_{l}&\mathbf{a}_{l}\end{array}\right].\left[\begin{array}{c}\mathbf{V}_{k}^{p} \\ \mathbf{I}_{kk+1}^{p}\end{array}\right] \tag{16}\]  
\[\mathbf{I}_{k+1,k+2}^{p,f}=\mathbf{I}_{k+1}^{p}-\mathbf{I}_{L_{k+1}^{p}} \tag{17}\]  
In this process, the load is modeled as a constant impedance, which is appropriate in the subtransient fault period [31].  
Once \(\mathbf{V}_{\text{G}}^{p}\) and \(\mathbf{I}_{\text{G}}^{p}\) are known, the synchronous machine internal voltage is estimated by Equation (18).  
\[\mathbf{E}=\mathbf{V}_{\text{G}}^{p}-\mathbf{Z}_{\text{DER}}\mathbf{I}_{\text{G}}^{p} \tag{18}\]  
This process eliminates the use of a load flow, as it is proposed previously [16; 17; 32]. Knowledge of the internal voltage in the DER model allows determining its behavior in the fault period, which allows the estimation of its current contribution to the fault point. The last is done by application of circuit reduction theorems such as [PERSON]'s theorem, as it is presented in step 5 [16; 32].
# Communication Fault Maintenance Decision of Information System Based on Inverse Symmetry Algorithm
## 3 Experimental Analysis
### Failure Cause Node Analysis  
First, feature attribute items are extracted from the raw data of the fault records of all information communication systems  
The directed connection diagram of three module nodes \"information equipment\", \"communication equipment\", and \"platform software\" when an access failure occurs in a power information system is given, and 15 failure cause nodes corresponding to these three modules are established. The schematic diagram of the communication failure cause node is shown in Figure 4.  
Diagnose the communication failure of the information system based on Figure 4. The prior probability of an attribute is the number of times the attribute value appears in the existing fault diagnosis report divided by the sum of all attribute values.  
The probability value of each attribute is calculated by using the method of text information statistics. After applying rough set attribute reduction, the minimum attribute set can be obtained, thus the diagnosis rule of the minimum attribute set can be obtained. The minimum attribute set of fault reason reduction is shown in Figure 5.  
According to the statistical analysis of Figure 5, the probability of the minimum attribute set of each fault cause is obtained, and then the probability information of all connecting lines in the Bayesian network is calculated. According to the fault diagnosis model, the probability of the fault being caused by each system attribute is calculated. The attribute with high probability has a high probability of failure, so as to realize the rapid location of failure causes and improve the diagnosis efficiency.  
Figure 4: Schematic diagram of the fault cause node.  
Figure 5: Fault cause reduction minimum attribute set.
# An Energy-Efficient and Robust Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks
## 5 Performance Evaluation  
In this section, the proposed ERMR is evaluated via extensive computer simulation using NS-2.31 [26]. ERMR is compared to the conventional L2 ER because L2 ER is also an energy-efficient routing protocol for CRAHNs and exploits multiple routing metrics as in the proposed ERMR. In principle, L2 ER tends to find the best path by avoiding the tradeoff situation between the path with high residual energy but significant end-to-end delay and the path with minimal end-to-end delay but low residual energy. In the following subsections, the simulation environment, performance metrics, and simulation results are presented and discussed.
## 4 Decision Trees and Random Forests  
### Decision Trees  
Decision trees (DT) are a popular algorithm for classification or regression capable of providing reliable and easily interpretable results.  
Although there are a variety of DT algorithms, they all have a similar structure. To be concise, the algorithm consists of dividing the data set into successive subsets following  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Name** & **Formula** & **Units** & **Ref.** \\ \hline Penetration resistance & \(R_{p}=(t)_{dZ=0.2m}\) & s/0.2 m & [PERSON] et al., 2004 [33] \\ \hline Somerton index & \(S_{d}\approx P_{E}\left(\frac{V_{A}}{V_{A}}\right)^{\frac{1}{2}}\approx\frac{ P_{O}}{\sqrt{V_{A}}}\) & kPa & [PERSON] 1959 [34] \\ \hline Drilling specific energy & \(SDE=\frac{P_{O}}{\mathrm{S_{0}}}+\frac{2\pi}{\mathrm{S_{0}}}\frac{V_{A}\mathrm{ C_{R}}}{V_{A}}\) & kJ/m\({}^{3}\) & [PERSON] 1965 [35] \\ \hline Specific energy & \(E_{S}=C_{R}\cdot\frac{V_{A}}{V_{A}}\) & N-m/m & [PERSON] 1985 [36] \\ \hline Normalized energy & \(E_{N}=\frac{aP_{V}V_{A}+S_{0}c_{2}2 vV_{A}+\gamma P_{dif}}{V_{A}}\) & N-m/m & [PERSON] et al., 1998 [37] \\ \hline Alteration index & \(l_{a}=1+k_{0}\left(\frac{P_{O}}{P_{Omax}}-k_{1}\frac{V_{A}}{V_{max}}\right)\) & - & [PERSON] 1985 [36] \\ \hline Entropy of S & \(L(z)=\sum\limits_{Z}^{Z}\lvert S(z+dz)-S(z)\rvert\) & - & [PERSON] 1988 [38] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Most used compound parameters.  
established rules. This process can be represented graphically in structures that resemble a tree (Figure 2).  
The success of DTs is explained by several factors that make them quite useful in practice [39]:  
* DTs are non-parametric. They do not assume the way in which the variables are related, and they are able to model complex interactions.
* They handle heterogeneous data (numbers, categories, or a mix of both).
* In their own operation, DTs implement the choice of the most important variables, making them robust (up to a point) against irrelevant variables.
* They are equally robust against outliers and sorting errors.
* They are easy to interpret, even for users without previous knowledge of statistics.  
Building a decision tree consists of three parts: division rules, stop criteria and assignment rules.
# Transmission Reduction for UV and IR Radiation with Dyed Lyocell Knitted Textiles
## 3 Results  
### Transmission Measurement of Aqueous Dye Solutions  
A huge number of dyes are commercially available, from this one yellow/orange dye and one red/purple dye each were selected from the dye classes of direct dyes and reactive dyes. Before starting the application of the dyes to textile fabrics, their optical transmission is determined at aqueous dye solutions. Figure 2 shows transmission spectra for the aqueous solutions of the dyes Sirius Orange and Solophenyl Bordeaux (Figure 2a) and for the dyes Drimaren Yellow and Remazol Red (Figure 2b) for two different dye concentrations.  
Figure 2: Transmission spectra of dyes in aqueous solution, (**a**) Sirius Orange and Solophenyl Bordeaux, (**b**) Drimaren Yellow and Remazol Red.  
For all investigated dyes, it can be seen that a higher dye concentration in the solution leads to lower transmission. Sirius Orange has a high red content. The transmission spectra of the dyes Sirius Orange and Remazol Red are very similar: the transmission of both dyes increases very steeply in the spectral range around 550 nm and runs almost horizontally from 730 nm to 1200 nm.  
The transmission spectra of Drimaren Yellow and Solophenyl Bordeaux differ significantly from this. In the case of the Drimaren Yellow HF-CD, the transmission rises strongly at around 595 nm and has a rather linear rise to 700 nm. Due to this, the transmission is reduced in the spectral range of 700 nm to 850 nm. From 870 nm onwards, a slightly rising, horizontal curve follows. The overall transmission is significantly lower. Solophenyl Bordeaux 3 BLE is a dark red dye with very high blue content. The transmission increases linearly only at 680 nm, up to around 1000 nm. Thus, this dye shows a reduction of transmission for near-infrared light in the spectral range up to 1000 nm.  
All dyes reduce the transmission in the UV range completely. Furthermore, in the NIR range, all dyes exhibit a low to medium potential for transmission reduction. Because the dyes Drimaren Yellow and Solophenyl Bordeaux have the best capability to reduce transmission for near-infrared light, these dyestuffs were chosen in the current investigation to dye the knitted Lyocell fabrics.
## 3 Results and Discussion
### Corrosion Resistance Properties
Although the majority of the surface area retains the film after 168 h of salt spray corrosion, it can be seen that there are obvious bubbling on the surface. Although numerous studies have shown that superhydrophobic coatings can improve the corrosion resistance of metals [33; 34], the durability of corrosion resistance  
Figure 9: Polarization curve of AZ31B Mg alloy surface: (**a**) pre–treated magnesium alloy, (**b**) the PVDF/PROTES-SiO\({}_{2}\) super-hydrophobic surface on Mg alloy. during actual use is closely related to the adhesion between the superhydrophobic coating and the substrate [35]. SEM was used to characterize the sample at the micro-scale after observing the surface of the sample after the salt spray experiment at the macro level. The results are shown in Figure 12. After salt spray corrosion, the surface of bare AZ31B is composed of flakes that resemble petals, which is due to the contact between the corrosive medium and the magnesium alloy substrate to form a film containing MgO and Mg(OH)\({}_{2}\)[11]. However, as shown in Figure 12d, the superhydrophobic coating surface morphology barely changed before and after corrosion, indicating that salt spray corrosion did not affect the structure of the superhydrophobic composite coating. The contact angle of the sample surface was measured after the salt spray experiment. Due to the composite coating maintains its surface integrity after 144 h of salt spray corrosion, the contact angle is still greater than  
Figure 11: The optical surface photo after salt spray experiment: (**a**) bare AZ31B Mg alloy, (**b**) superhydrophobic coatings. The dimensions for all samples were \(70\times 50\times 5\) mm). Figure 10: The Nyquist plots obtained from (**a**) pretreated magnesium alloy, (**b**) the PVDF/PFOTES-SiO\({}_{2}\) super-hydrophobic surface on Mg alloy after immersion in 3.5 wt % NaCl aqueous solution for 30 min. 150\({}^{\circ}\), as shown in Figure 13, which corresponds to the appearance of the sample in the digital photo of Figure 11.  
The long-term corrosion performance of the samples after salt spray corrosion was studied through the dynamic polarization curve [14; 15], and the curves are recorded in Figure 14. Parameters of the potentiodynamic polarization were listed in Table 1. The parameters clearly showed that with the extension of salt spray corrosion time, the \(I_{\text{corr}}\) gradually decreases. The \(I_{\text{corr}}\) changed from (6.18 \(\pm\) 2.34) \(\times\) 10\({}^{-9}\) A/cm\({}^{2}\) to (5.58 \(\pm\) 2.35) \(\times\) 10\({}^{-7}\) A/cm\({}^{2}\) after salt spray for 168 h, but it is still an order of magnitude lower than \(I_{\text{corr}}\) of brae AZ31B Mg alloy, indicating that durability of the as prepared superhydrophobic. Figure 12: The surface morphology before and after the salt spray experiment (**a**) bare AZ31B Mg alloy—0 h, (**b**) bare AZ31B Mg alloy—168 h, (**c**) PVDF/SiO\({}_{2}\) coating—0 h, (**d**) PVDF/PFOTES-SiO\({}_{2}\) coating—168 h.  
Figure 11.0 The contact angle after salt spray experiment of superhydrophobic coating.
# Multi-Stage Dynamic Transmission Network Expansion Planning Using LSHADE-SPACMA
###### Abstract
The performance of LSHADE-SPACMA to solve the TNEP problem was compared to other well-established meta-heuristic methods such as IBPSO, MVO, and the HM. Three testing systems: the Garver 6-bus test system, Egyptian WDN, and 93-bus Colombian system were used to validate the proposed algorithm's capability to solve the TNEP problem. A comparison of two planning scenarios presented for WDN expansion was also conducted. The following sections are organized as follows: Section 2 presents mathematical formulations of models adopted in this study; long-term load forecasting using ANFIS and LSHADE-SPACMA algorithms are introduced in Sections 3 and 4, respectively; the characteristics of the testing systems and results are discussed in Section 5; and conclusions are presented in Section 6.
## 2 Materials and Methods
### Evaluation of Knee Cartilage Thickness Using MRI  
At the first and second follow-ups, cartilage thickness was measured in both knees (study and control group) using MRI, which was performed using a 0.32T O-Scan device designed for knee examination. FSE T2, STIR and 3D-Sharc sequences were obtained (1.9 mm slices). Measurements were performed on the images of the 3D-Sharc sequences. The articular cartilage thickness of each patient was measured in the knee after ACL-R (study group) and in the healthy knee joint (control group). The plane of measurements for femoral and tibial condyles was determined based on a bone reference point at the level of the tendon incision of the popliteus muscle of the lateral femoral condyle and at three reference points in the frontal view: (1) center of the condyle; (2) 5.7 mm medial from the midline; and (3) 5.7 mm lateral to the midline of the condyle (Figures 2 and 3). Cartilage thickness was defined as the shortest distance between the articular surface and the subchondral bone surface of the cartilage.  
Figure 2: The plane and points of measurements for femoral and tibial condyles include three reference points in frontal view: center of the condyle (green line); 5.7 mm medial from the midline (orange line); and 5.7 mm lateral to the midline of the condyle (blue line).
## 3 Results and Discussion
### Compressive Strength  
CLSM is mainly used in the application of trench backfilling, and it must have self-filling, excavation and low subsidence requirements. As specified in ASTM D4832, the uniaxial compressive strength on Day 28 should not exceed 8.4 MPa. The compressive strength values of CLSMs in the current study are shown in Figure 4. Compressive strength increased with age for all mixture proportions. The compressive strength was 3.02-2.71 MPa on Day 3, 4.59-4.34 MPa on Day 7, and 6.25-5.87 MPa on Day 28. These values conformed to the strength requirement of excavatability. After the cement hydration was completed through the gradual aging of the CLSM, the increase in the later-stage compressive strength gradually plateaued.  
When the replacement of the MSWI bottom ash was increased, the compressive strength decreased, which was possibly attributed to the porous structure and water absorption characteristics of MSWI bottom ash, this result is the same as the compressive strength of the application of pulp ash to CLSM by [PERSON] et al. (2016), the use of materials with high water absorption reduces the compressive strength. In addition, the FM of MSWI bottom ash is lower than that of fine aggregates. Thus, when an identical water-binder ratio is used, an increase in the replacement of MSWI bottom ash increased the FM of the fine aggregate, reducing the compressive strength of the CLSM.
# A New Technical Ear Training Game and Its Effect on Critical Listening Skills
## 2 Design and Development of a New Technical Ear Training Game
### Technical Details of Game Development  
The user interface of the game that players interact with is implemented using Unity version 2017.3.1f1. Unity provides the following: a framework to develop the auditory training game into a 2D platform implementation; a scripting framework to program the game's logic using C#; and the ability to build the game for multiple platforms without modification to the original codebase. Unity seemed to be a great way to implement the game once and be able to target it to many platforms such as Android, iOS, Linux, and Universal Windows Platform (UWP) for the greatest amount of future-proofing. Vufforia Engine version 6.2.9 was heavily utilized to integrate an Augmented Reality SDK into the Unity framework for development. The targeted platform (and main test platform) for the game was UWP so that it could be loaded onto a Microsoft Surface tablet. The Surface tablet was an easily accessible platform with the capability for Augmented Reality given it had a back-facing camera. The unity application was set to build for UWP where a final build distribution could be side loaded to a Surface tablet or hosted on a private Windows Store to be downloaded/updated from.  
Motivation for storing user data outside of the local game was needed to gather research data on auditory training progression across all users. A separate server was used to host a database where user data and progression in the game would be tracked. A Raspberry Pi 3 Model B (running Raspberry Pi OS for its operating system) would be used as a cost-effective server hosting a MySQL database responsible for handling requests from the game client to insert and update game data. For players to track their game completion data and for new users to create their own accounts to be stored in the database, there needed to be a way for the game client to communicate with the external database. This communication was implemented by having a PHP web server on the Raspberry Pi server receive web form data from the game client and send back response data. The PHP scripts would then handle the connection with the database and perform the appropriate database insert/query and return any information associated with the operation back to the game client.  
Figure 2: Main screen of the new ear-training game. A player needs to complete four training modules, the first two basic skills (spectral identification (S) and auditory localization (L)) and two following challenges to prove that one can judge consistently (C) and memorize (M) the given mix balance. The current player in this figure has completed the basic skills (S) and (L), and is going to challenge the consistency (C) evaluation in level 2.