esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background
### 6 LoWPAN  
The 6 LoWPAN [10] working group of the IETF has defined an adaptation layer for sending IPv6 packets over IEEE 802.15.4. The goal of 6 LoWPAN is to reduce the sizes of IPv6 packets to make them fit in 127 byte IEEE 802.15.4 frames. The 6 LoWPAN proposal consists of a header compression scheme, a fragmentation scheme, and a method for framing IPv6 link local addresses into IEEE 802.15.4 networks. The proposal also specifies enhanced scalabilities and mobility of sensor networks. The challenge to 6 LoWPAN lies in the sizable differences between an IPv6 network and an IEEE 802.15.4 network. The IPv6 network defines a maximum transmission unit as 1,280 bytes, whereas the IEEE 802.15.4 frame size is 127 octets. Therefore, the adaptation layer between the IP layer and the MAC layer must transport IPv6 packets over IEEE 802.15.4 links. The adaptation layer is responsible for fragmentation, reassembly, header compression and decompression, mesh routing, and addressing for packet delivery under the mesh topology. The 6 LoWPAN protocol supports a scheme to compress the IPv6 header from 40 bytes to 2 bytes [11].
# Tutorial Review on Space Manipulators for Space Debris Mitigation
## 4 Space debris Mitigation
However, deployed drag devices introduce the potential for further collision in crossing multiple orbits with a wide area membrane while rocket apogee engines impose a prohibitive propellant and mass requirement. Nevertheless, the most plausible solution for de-orbiting is to either attach a dedicated propulsive stage to de-orbit the debris sacrificially or to employ a reusable, refuellable robotic system that acquires the debris and releases it in a disposal orbit. It has been determined that a single 2000 kg robotic spacecraft (of which 1400 kg is propellant) could remove 35 upper stage rocket bodies from 700-900 km polar orbit using solid rocket de-orbit kits over 7 years with 8 resupply missions [63]. This is similar to the ATLAS concept introduced later (Figure 1). Scheduling of consecutive debris removal operations is an NP-hard travelling salesman problem which has a branch-and-bound solution to minimise the propellant cost and manoeuvre time that is tractable for 5 removals but not for 10 [64]. A branch-and-prune strategy using low-thrust propulsion may be more efficient [65]. A multi-servicer approach invites ant colony optimisation routing and coordination through auction bidding [66]. In GEO orbit, the optimal schedule is to manoeuvre in an anti-orbit direction for minimum \(\Delta\)v [67]. Approximately, 400-500 m/s manoeuvres are required to acquire each target and 250 m/s is required for de-orbiting the upper stage rocket body. It appears that the robotic servicer concept with mounted manipulators is the most viable for active debris removal.
## 3 Performance Metrics
Accordingly, if the data producer sends a '1' (or '0') while the channel enforces a '1' (or '0'), and no detection is occurred by the detector, then a true positive would happen. In other words, CTP happens when the data producer sends a same value as the enforced value by the channel. This indicates a pure luck (i.e., 50% chance to end up as a logical '1' or '0') since if the data producer would have sent a '0' instead and the detector did not detect it, then it would have ended up as a false negative. Therefore, this category must be considered as dangerous as a false negative. Correspondingly, it is labeled in a shade of red. * Channel True Negative (CTN): The channel is in control and determines the output, and the received output is incorrect, even though the detector outcome is correct. This category is triggered by the same scenarios indicated for DTN. Furthermore, similar to DTN, the system receives warning which is desired. This category is labeled in a distinct shade of orange;
* Channel False Positive (CFP): The channel is in control and determines the output, and the received output is correct albeit the detector outcome is incorrect. This category is triggered by the same scenarios stated for DFP, but in these scenarios, the channel is in control. As a result, it reduces the safety of the system. Since the system receives a warning in these scenarios, this category is also labeled in a shade of orange. * Channel False Negative (CFN): The channel is in control and determines the output, the received output is incorrect, and the detector outcome is incorrect. This is a very dangerous scenario, since the channel turns the input data into other valid data, and RS Codes assume that all is right (i.e., the calculated syndrome is zero). In such a case, the system is unaware that the received data word is incorrect and, thus, no countermeasures can be taken. Consequently, this undetected category could result in critical failures. Accordingly, this category is considered detrimental to the overall system safety and is, therefore, labeled in a shade of red. Note that based upon the initial assumption, both data producer and consumer are protected from EMD or any internal hacking. Thus, all categories except DFN could happen within this paper [20]. Accordingly, an important focus of this paper is to study how RS Codes behave under single-frequency EMD, specifically when no warning is given (i.e., CFN), which could result in catastrophic failures, and when the output ends up being correct by an equal chance (i.e., CTP).
## 3 Results and Discussions
### Ndvi  
ArcGIS 10.4.1 was used to calculate the NDVI values for the three satellite images of the southern Iraqi Marshes for 1977 and 2017, Figure 4. The NDVI values of Landsat 2 images in 1977 were large. The areas of green color in the landscape were wide and extended on a large area within the marshes and on their borders. They represent the natural and agricultural vegetation, and their value ranges from 0 to +1. While the blue color represents the water bodies of the marshes at that time, and their values are less than 0. The 10 m resolution of Sentinel 2 was more accurate in showing vegetation and water for NDVI values than in Landsat 8 in 2017, although the two images were captured at about the same time. The reason was the range of NDVI in Sentinel 2 image ranges between (\(-\)1 to 0.84). This allows for slight changes in the difference between R and IR bands, and showing vegetation areas, shallow and deep-water levels in it, compared to Landsat-8 image, in which the value of NDVI ranged from (\(-\)0.27 to 0.57). When comparing the NDVI values between 1977 and 2017, observe the deterioration of the vegetation cover and water bodies in the marshes. Large areas of natural vegetation and agricultural land have disappeared, and have been replaced by dry arid lands.  
Figure 4: _Cont._  
Figure 3: Digital elevation model (DEM) for marshes of southern Iraq.  
Figure 4: Normalized difference vegetation index (NDVI) values for images of (a) Landsat 2 in 1977, (b) Landsat 8 in 2017 and (c) Sentinel 2 in 2017 for southern Iraqi Marshes sowing the differences between the years 1977 and 2017.
## 5 The Construction of Timbre Space
### The Construction of the 3D Timbre Space Using MDS  
The reliability and validity processing method applied to the experimental data was the same as in experiment B. The processed data were averaged and the mean score for all subjects on each evaluation term was calculated for each sample. These data were then used to calculate the timbre dissimilarity, expressed in the form of a distance matrix. The MDS algorithm was adopted in this paper [77], which considers individual differences between subjects and assigns a corresponding weight to each score. This approach considers terms in every dimension and more fully utilizes the experimental data. Multidimensional scaling is based on dissimilarity analysis for two samples in a timbre attribute space, which can be expressed using a distance matrix as follows:  
\[d^{i}_{jk}=\sqrt{\sum_{r=1}^{R}w_{ir}\cdot\left(x_{ir}-x_{kr}\right)^{2}}, \tag{8}\]  
where \(d^{i}_{jk}\) represents the dissimilarity evaluation score for subject \(i\) assessing sounds \(j\) and \(k\), \(w_{ir}\) represents the weight of subject \(i\) in the \(r\)th dimension, and \(x_{kr}\) represents the coordinates of sample \(k\) in the \(r\)th dimension.  
Equation (8) was used to calculate the distance for 37 timbre feature vectors and the dissimilarity distance matrix for 37 samples. This matrix was used as input into the MDS algorithm. The number of timbre space dimensions was determined by referring to previous research results [51; 52]. The timbre space dimension was determined in three dimensions using Kruskal's stress function [78]. The coordinates of each sound sample in 3D timbre space were acquired by using MDS to reduce the dimensionality of the dissimilarity distance matrix (Figure 6).  
Figure 6: A 3D timbre space for 37 Chinese instruments.
## 5 Conclusions  
In this article, concerning a geographical area struck with high disaster, we simulate and demonstrate the UABS's capabilities to maintain and restore mission-critical communications in the event of any damage to the public safety infrastructure. Through Monte Carlo simulations, we maximized the coverage probability and 5 pSE gains of the overall AG-HetNet, while mitigating intercell interference and optimizing the ICIC parameters. Furthermore, we compare and analyze the 5 pSE and coverage probability of the AG-HetNet for different GUEs' distribution when UABSs are deployed on a fixed hexagonal grid and different numbers of UABS are deployed. The result outlines that the AG-HetNets with reduced power subframes (FeICIC) yield better 5 pSE than almost blank subframes (eICIC).  
**Funding:** This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.  
**Data Availability Statement:** Data are contained within the article.  
**Conflicts of Interest:** The author declares no conflict of interest. Author [PERSON] was employed by the company Motorola Solutions, Inc.  
**Abbreviations**  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l}
3 DBF & Three-dimension beam forming \\
5 pSE & Fifth-percentile spectral efficiency \\ ABS & Almost blank subframes \\ AG-HetNet & Air-ground heterogeneous cellular network \\ CRE & Cell range expansion \\ CSF & Coordinated radio-subframes \\ eICIC & Enhanced intercell interference coordination \\ FeICIC & Further-enhanced intercell interference coordination \\ GUE & Ground user equipment \\ HetNet & Heterogeneous network \\ ICIC & Intercell interference coordination \\ LOS & Line of sight \\ LTE & Long term evolution \\ MBS & Macro base-stations \\ MCP & Matérn cluster process \\ MOI & MBS cell-of-interest \\ MUE & MBS GUE \\ NIM & No interference management \\ \end{tabular}
# Scale-Adaptive Simulation of Unsteady Cavitation Around a Naca66 Hydrofoil
## 5 Conclusions and Future Works  
Numerical simulations of unsteady turbulent cavitation flows around a NACA66 hydrofoil were carried out using OpenFOAM version 4, and the main remarks are:  
* The unsteady behavior of the cavitation phenomenon was reproduced using the \(k-\omega\) SST SAS and ILES turbulence models. Comparisons among results show that SAS reproduces fairly well the unsteady behavior of the cavitation phenomenon with a cycle frequency of 4.01 Hz, which matches experimental results. The growth of the leading edge cavity was regular, and it was performed with RANS conditions using SAS without showing any detached cavity process at the beginning of the cycle, which is an improvement in comparison to LES results. Therefore, the proposed use of SAS to reproduce unsteady cavitating flows, has been validated as a reliable hybrid turbulence model to be applied in studies of the unsteady cavitation around hydrofoils.
* The Zwart-Gerber-Belamri cavitation model was updated and implemented in OpenFOAM version 4 to simulate liquid-vapor phase changes, and it showed good accuracy against experimental results from [PERSON] at Naval Academy Research Institute.
* The main contribution of this work was to explore a new turbulence model based on RANS for the study of unsteady cavitation, which presents potential applications for hydraulic machinery design due to low computational demand and high phenomenon reproducibility. Future work will be focused on the implementation of the aforementioned model on optimization routines for hydraulic turbine runners.  
Conceptualization, V.H.; methodology, V.H., X.L. and X.E.; software, V.H., J.E. and D.P.; validation, V.H., X.P. and X.E.; formal analysis, V.H., X.E., X.L., X.P. and E.V.; investigation, V.H., X.L. and X.E.; writing--original draft preparation, V.H., X.E., E.V., X.L. and J.E.; writing--review and editing, V.H., E.V., J.E. and D.P.; visualization, V.H.; supervision, V.H.; project administration, V.H.; funding acquisition, V.H. and E.V.  
This research was financially supported by Escuela Politecnica Nacional (Project No. PIJ 17-13).  
The authors gratefully acknowledge the financial support provided by Escuela Politecnica Nacional for the development of the project PIJ 17-13. They also thank the support given by the State Key Laboratory of Hydroscience and Engineering, Tsinghua University.  
The authors declare no conflict of interest.
# Online Measurement of Internal Parameters in a Quasi-CW Diode-Pumped Nd:YAG Laser
###### Abstract  
We present a simple and practical online measurement method to estimate internal parameters (small-signal gain coefficient, internal optical losses, the saturation parameter, and transmittance of the coupling output mirror) in an neodymium doped yttrium aluminum garnet Nd:YAG laser system. A measurement cell, placed in the optical cavity of a laser, consists of a polarizer and a rotatable polarization analyzer. Internal parameters are measured conveniently by introducing variable polarization reflective loss. Online measurements of the internal parameters in a quasi-continuous-wave (CW) diode-pumped Nd:YAG laser are performed and the measured results, which are discussed and analyzed, indicate good measurement accuracy. Experiments to investigate validity are conducted and further verify the applicability of the measurement method. A measurement cell with a small volume that is easy to access has potential to be used in the online measurement, optimized design, and maintenance of a laser.  
online measurement; internal parameters; Nd:YAG laser; small-signal gain; optical losses +
Footnote †: journal: Applied Physics Letters  
_Article_  
Online measurement of internal parameters in a Quasi-CW Diode-Pumped Nd:YAG Laser
# An Embedded System Based on Raspberry Pi for Effective Electrocardiogram Monitoring
### Our Contribution  
In this work, we are presenting the development of an embedded system based on raspberry pi that can be used to successfully measure the electrocardiogram signals at different heart rates. The measured signal includes all the important peaks that can be used as an indicator for the health condition by comparing the signal from healthy cases with that from patients who have heart diseases. The contributions of this work can be summarized as follows:  
Integration of Raspberry Pi for ECG Monitoring: While it is true that previous research has explored the use of Raspberry Pi in ECG devices, our work presents a comprehensive and practical implementation of an embedded system using Raspberry Pi for effective ECG monitoring. We have focused on optimizing the system's performance, ensuring real-time monitoring, and developing a portable, cost-effective, and user-friendly solution.  
Complete System Design: Although prior studies have discussed aspects of ECG device development, our paper provides a detailed account of the entire system design, encompassing analog and digital components. We describe the electronic circuit, including signal conditioning, amplification, noise filtering, and power management, as well as the incorporation of an analog-to-digital converter and a graphical liquid-crystal display for signal measurement and visualization. The comprehensive integration of these components is a noteworthy contribution to our work.  
Health Condition Analysis: Our paper emphasizes the importance of analyzing the ECG signals to assess health conditions. We propose a method for detecting abnormal heart functionality in real time by comparing signals obtained from healthy individuals with those exhibiting heart arrhythmia. This aspect of our work contributes to the field by providing a practical approach to diagnosing and monitoring cardiac abnormalities using Raspberry Pi.  
While we acknowledge that previous research has explored related topics, our work distinguishes itself by providing a holistic and practical solution for ECG monitoring, incorporating Raspberry Pi as a key component, and focusing on real-time detection and health condition analysis.  
We have covered the details of our work in the next sections including the simulation of the ECG system circuit on Proteus software; the connection on the bread board and testing using both the commercial ECG simulator and the human body signals; and finally we have included the PCB design of our complete system connected to the raspberry pi and graphical LCD, and the results of testing the final device using both commercial ECG simulator and human body signals.
## 2 Materials and Methods
### Study Site Description
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline
**Study Site** & **State, County** & **Physiographic Province** & **Lat. / Long.** & **Sol Series** & \begin{tabular}{} **Precipitation** \\ **(mm year** & **1**)** \\ \end{tabular} & \begin{tabular}{} **Temperature** \\ **max/min** \\ \end{tabular} & \
\begin{tabular}{} **Density** \\ **(stems ha\({}^{-1}\))** \\ \end{tabular} &
\begin{tabular}{} **Plantation** \\ **Year** \\ \end{tabular} \\ \hline
180101 & South Carolina, Kershaw & Piedmont & 34.45/-80.50 & Lakeland & 1208.5 & 32.6/-0.5 & 1445 & 1997 \\
180301 & Georgia, Oglethorpe & Piedmont & 33.89/-82.91 & Mecklenburg & 1237.3 & 32.9/-0.6 & 1640 & 1993 \\
180601 & Virginia, Brunswick & Piedmont & 36.68/-77.99 & Cecil & 1165.6 & 31.7/-3.0 & 1677 & 1993 \\
180801 & North Carolina, Craven & LCP & 35.23/-76.97 & Leaf & 1235.9 & 32/0.9 & 1317 & 1992 \\
181101 & South Carolina, Berkeley & LCP & 33.19/-80.19 & Lynchburg & 1289.5 & 33.4/1.3 & 1622 & 1994 \\
181201 & Alabama, Coosa & Piedmont & 32.91/-86.38 & Louisa & 1412.6 & 32.6/0.3 & 1457 & 1996 \\
181502 & Georgia, Floyd & Valley \& Ridge & 34.15/-85.83 & Townley & 1371.8 & 32.1/-1.0 & 1655 & 1998 \\
181503 & Texas, Angelina & WGCP & 31.13/-94.46 & Kurth & 1331.3 & 34.1/2.5 & 1267 & 2000 \\
182201 & Georgia, Wilkes & Piedmont & 33.81/-82.96 & Appling & 1240.6 & 32.9/-0.3 & 1815 & 1997 \\
183101 & Louisiana, Sabine & WGCP & 31.72/-93.56 & Sacul & 1370.6 & 33.8/1.2 & 2141 & 1993 \\
183102 & Louisiana, Vernon & WGCP & 31.47/-93.18 & Sacul & 1489.8 & 33.8/2.1 & 1756 & 1994 \\
183601 & Mississippi, Kemper & EGCP & 32.70/-88.58 & Smithdale & 1451.4 & 33.3/0.6 & 1632 & 1996 \\
183901 & Alabama, Marengo & EGCP & 32.37/-87.84 & Savannah & 1431.5 & 33.3/1.2 & 1413 & 1998 \\
184201 & Georgia, Bramtley & LCP & 31.34/-81.82 & Leon & 1310.3 & 32.4/3.4 & 1781 & 1994 \\
184202 & Georgia, Bramtley & LCP & 31.34/-81.83 & Leon & 1308.2 & 32.4/3.4 & 1781 & 1995 \\
184301 & Georgia, Marion & UCP & 32.17/-84.63 & Troup & 1275.9 & 33.1/2.0 & 1862 & 1996 \\
184401 & Arkansas, Bradley & WGCP & 33.49/-92.13 & Savannah & 1402.1 & 33.5/0.8 & 1247 & 1996 \\
184501 & Alabama, Marengo & EGCP & 32.58/-87.55 & Bramtley & 1418.5 & 33.3/1.4 & 1415 & 1996 \\
184801 & Texas, Newton & WGCP & 30.48/-93.78 & Evadale & 1496.8 & 33.7/3.7 & 1264 & 1999 \\
185201 & North Carolina, Montgomery & Piedmont & 35.28/-79.94 & Herndon & 1212.7 & 32.5/-1.0 & 1215 & 1999 \\
185301 & Mississippi, Montgomery & EGCP & 32.55/ -89.64 & Shubuta & 1491.2 & 33.2 / 0.7 & 1326 & 1997 \\ \hline \end{tabular}
\end{table} 
Table 1: Location (State, County), physiographic regions, latitude / longitude (decimal degrees), soil series, average annual precipitation, average maximum and minimum temperature (\({}^{\circ}\)C), planting density (stems ha\({}^{-1}\)), and plantation year for study sites used to determine relationship between site index and FR in 3-PG.
# Energy-Aware 3D Path Planning by Autonomous Ground Vehicle in Wireless Sensor Networks
## 4 Proposed Energy-Aware Path Planning (EAPP) Approaches
### Genetic Algorithm (GA)-Based Approach  
In order to address the EAPP problem, which we address as a TSP, we present a solution that is based on the genetic algorithm and is a three-dimensional path planning solution [46; 47]. The primary concept behind genetic algorithms is to attempt to solve tough optimization problems by modelling their behaviour after that of biological evolution. This is carried out in an effort to solve optimal problems. In order to address TSP difficulties, the process of using a genetic algorithm begins with the identification of the people that comprise the TSP solution and the initialization of the population. These are the beginning steps of the process. In the process of selecting individuals for various genetic processes like selection, crossover, and mutation in the population, each individual can be evaluated based on a fitness function. Individuals who are thought to be the most fit are selected. The maximum number of iterations that have been selected is the final criterion that will help determine whether or not the GA will be terminated. Regarding this study, the individual fitness is defined by the total route size or the total energy consumption of the AGV. Both of these factors are taken into consideration.
## 3 Results and Discussion
### Thermal Conductivity  
In terms of thermal performance, after exposure to 250 \({}^{\circ}\)C, all mortars suffered a thermal conductivity reduction (Figure 7 and Table 7). This variation should be associated with possible changes in the internal structure of the mortars, namely the increasing porosity and micro-cracking. This reduction was more pronounced in sand mortars (mainly in mortar D\({}^{\text{ref}}\)), indicating a greater micro-cracking of these mortars. These results are in line with those previously discussed, where the properties of these mortars were reported to present a greater variation due to a higher aggregate / paste incompatibility under thermal expansion caused by temperature increase.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Compressive Strength [MPa] (standard deviation)**} \\ \hline
**Mortar** & \multicolumn{2}{c}{**A**} & **B** & **C** & **D** & **E** \\ \hline \multirow{4}{*}{Temperature [\({}^{\circ}\)C]} & 20 & 3.99 (0.19) & 0.89 (0.06) & 0.99 (0.03) & 8.83 (0.31) & 6.32 (0.24) \\ \cline{2-6}  & 100 & 3.27 (0.09) & 1.16 (0.10) & 0.93 (0.01) & 8.26 (0.36) & 6.40 (0.49) \\ \cline{2-6}  & 150 & 3.09 (0.14) & 1.07 (0.09) & 1.00 (0.02) & 8.02 (0.26) & 5.18 (0.27) \\ \cline{2-6}  & 200 & 3.59 (0.05) & 1.06 (0.04) & 0.78 (0.03) & 8.58 (0.22) & 5.15 (0.14) \\ \cline{2-6}  & 250 & 3.98 (0.18) & 0.97 (0.06) & 0.76 (0.02) & 7.77 (0.06) & 3.96 (0.31) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Compressive strength average vs. exposure temperature.  
The lightweight aggregates, with better compatibility with the cement paste under expansion phenomena, enable the mortar to maintain thermal insulation properties with acceptable thermal conductivity values. This is quite clear in mortars B\({}^{\text{GEC}}\) and C\({}^{\text{AERO}}\), for which the thermal conductivity variation is 0.027 and 0.014 W/(m.K), respectively.  
After exposure to 250 \({}^{\circ}\)C, the mortars with thermal insulating aggregates (silica aerogel and granular expanded cork (GEC)) presented a thermal conductivity coefficient between 0.06 W/(m.K) and 0.075 W/(m.K); therefore, since their thermal conductivity coefficient is below 0.1 W/(m.K), they comply with thermal class \"T1\" for thermal mortars according to standard EN998-1 [7], even after being exposed to high temperatures.