esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparison of Oil Spill Classifications Using Fully and Compact Polarimetric SAR Images
## 2 Methods
### Dimension Reduction  
Various features can be extracted from polarimetric SAR data. However, inevitably, they are correlated and suffer from noise. In this study, three typical algorithms, principle component analysis (PCA), local linear embedding (LLE) and ISOMAP, were comparatively employed to reduce the dimension of polarimetric SAR features.  
PCA reduces the number of features by replacing them with their linear combination. These new features are derived by the idea of maximizing their variance and making them uncorrelated. It comes from the theory of linear algebra; PCA has been abundantly used in many applications and has become a very popular method for its highly efficient, non-parametric characteristic.  
LLE is an unsupervised learning algorithm that computes low-dimensional, neighborhood-preserving embeddings of high-dimensional inputs. It maps its inputs into a single global coordinate system of lower dimensionality, and its optimizations do not involve local minima. LLE is capable of learning the global structure of nonlinear manifolds based on the exploration of the local symmetries of linear reconstructions [38].  
ISOMAP takes advantage of local metric information by measuring geodesic distances and learning the underlying global geometry of a dataset. Developed from multidimensional scaling (MDS), it is capable of discovering the nonlinear degrees of freedom that underlie complex natural observations, such as human handwriting or images of a face under different viewing conditions [39].
# An Intelligent Cluster-Based Routing Scheme in 5G Flying Ad Hoc Networks
### Fanet
The CCs are responsible for (a) managing network-wide traffic and changes in network topology due to node mobility and dead nodes as a result of battery drainage, and (b) making intelligent routing decisions based on network-wide policies. Network-wide policies deal with vertical routing (i.e., selecting the most favorable route across different network planes efficiently), whereas local policies deal with vertical clustering across different network planes.
## 2 Materials and Methods
### Fatigue Test  
The fatigue test was performed with an HSM-20 alternating bending fatigue machine (High-Tech Education, Hampshire, UK). According to the device manufacturer's specifications, fatigue RSW specimens with dimensions of 100, 10, and 1 mm were made using the best RSW parameters determined from each case's tensile shear test. In each case, the tensile strength of the RSW samples was utilised to determine the amount of load delivered as a stress (\(\sigma\)) due to deflection (\(\delta\)), and the objective of employing this device was to apply a precise oscillator on the specimens that were fixed on one side as a cantilever beam. The deflection (\(\delta\)) was calculated using Equation (5). For each case, the fatigue test used a stress range of 0.5%, 0.6%, 0.7%, 0.8%, and 0.9% of the tensile strength, and the number of cycles to failure of the RSW specimen was recorded. The fatigue experiments were carried out three times for each sample, and the average of the cycle numbers was calculated. Figure 3 shows the fatigue specimens for all cases. Equation (5) was derived as follows:  
For a cantilever beam, \(\delta\) is calculated based on [73]:  
\[\delta=\frac{F\cdot L^{3}}{3\ E.I} \tag{1}\]  
For cantilever beam, \(\sigma\) is calculated based on [73]:  
\[\sigma=\frac{M\cdot C}{I} \tag{2}\]  
\[I=\frac{b\cdot t^{3}}{12} \tag{3}\]  
Since M = F\(\cdot\)L, and C = t/2, and substituting Equation (3) into Equation (2), the following equation is derived:  
\[\sigma=\frac{F\cdot L\cdot\frac{t}{2}}{\frac{b\cdot t^{3}}{12}}=\frac{6F\cdot L }{b\cdot t^{2}}.\cdot\ \ F=\frac{\sigma\cdot b\cdot t^{2}}{6L} \tag{4}\]  
By substituting Equation (4) into Equation (1), Equation (5) is derived for calculating the deflection (\(\delta\)) in the bending fatigue test:  
\[\delta=\frac{L^{2}\cdot\sigma}{1.5t\cdot E} \tag{5}\]  
where:  
\(\delta\) deflection (mm),  
L cantilever length (mm),  
\(\sigma\) the applied stress used,  
t thickness (mm),  
[PERSON]'s modulus (MPa).
# Compressive Ghost Imaging of the Moving Object Using the Low-Order Moments
## 3 Experimental Results
Further more, there is a positive regularization parameter \(\tau\) controlling the sparsity constraint in CS, which may affect the performance of the image reconstruction or the estimation accuracy of the object location or rotation of our proposed method. To evaluated the sensitivity of \(\tau\) on the reconstructed image quality and estimation accuracy, experiments with respect to the various \(\tau\), in the case of object translation and rotation are conducted. In our experiments, three groups of data with measurement number \(m=100\), \(200\), \(300\) are chosen to compare the different effect of \(\tau\) on imaging and tracking the translational object. The location estimation accuracy evaluated by the RMSE, and the reconstructed image quality evaluated by SSIM is presented in Figure 6a,b, respectively. Likewise, the performance comparison on the case of rotational object is presented in Figure 6c,d. Overall, there exists an optimal \(\tau\) that achieves the best performance on the tasks of image reconstruction and the translation or rotation estimation, but the optimal value varies under different conditions. Different from the suggested value in Ref. [21; 23], the optimal \(\tau\) would change with the measurement number \(m\), and the trend is that the smaller the measurement number \(m\), the larger the optimal \(\tau\). The reason can be interpreted from Equation (4), in which the first term fits the measured data to reconstruct the image vector \(T\), and the second term controls the sparsity of \(T\). Generally speaking, the \(\tau\) should be set in accordance with the noise level, i.e., a larger \(\tau\) put more emphasis on the sparsity of object, thus the unsparse image noise could be suppressed more effectively, and a small \(\tau\) is the reverse [24]. Therefore, in each image period, when the measurement number \(m\) is small, the first term of Equation (4) cannot find a good solution of \(T\), and it requires a larger \(\tau\) to suppressed the random statistical noise for a faithful image reconstruction. On the other hand, when the \(m\) is enough for the first term of Equation (4) to fit the \(T\) well, it is suggested to reduce the \(\tau\) to preserve more fine details of the object. Figure 5: Comparing the performance of different methods on (**a**) the RMSE of the estimated rotation angle against the measurement number \(m\) per image period; (**b**) SSIM of the reconstructed images against the total measurement number \(M\).
# MQC-MB: Multiphoton Quantum Communication Using Multiple-Beam Concept in Free Space Optical Channel
## 8 Conclusions  
This paper presented the mathematical model to evaluate the effects of geometrical losses and atmospheric attenuation on the performance of multiphoton quantum cryptography over FSO. The parametric analysis for calculating the channel loss was also presented to analyze the impact on key generation performance and maximum achievable distances for the photons. Determining a suitable number of transmitters and receivers for quantum communication over the FSO is considered a critical issue because it directly impacts the overall performance of secret key transmission. The single beam is vulnerable to geometrical loss since a limited number of beams are used. This research contributes to the performance enhancement of quantum cryptography by implementing the multiple beam on FSO links to transmit multiphoton. The performance evaluation considered both atmospheric and geometrical effects. Extensive mathematical analysis was conducted to evaluate the performance of the multiple beam for the multiphoton protocol. From the analysis, it was proven that the multiphoton protocol using the multiple-beam FSO quantum cryptography system provides significant improvements in terms of distance, total loss, QBER, and secret key rate generation compared to single-beam implementation. Hence, it can be concluded that the multiple beam can always improve quantum communication over the static channel and fluctuating channel loss. This theoretical analysis was validated with simulation results and the proposed work could be practically implemented in the future.  
Investigation, N.Z.H.; Methodology, N.Z.H.; Supervision, Z.A.Z., Z.M.H. and I.A.; Validation, Z.A.Z., Z.M.H., I.A. and M.F.K.; Writing--original draft, N.Z.H.; Writing--review & editing, Z.A.Z., Z.M.H. and I.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Loss (dB)**} & \multicolumn{3}{c}{**SExect Key Rate (K/vs)**} & \multirow{2}{*}{**Multiple-Beam**} \\  & \(\sigma\)=0.3 & \(\sigma\)=0.6 & \(\sigma\)=0.9 & \(\sigma\)=0.3 & \(\sigma\)=0.6 & \(\sigma\)=0.9 \\ \hline
5 & \(-1.953\) & \(-2.265\) & \(-2.464\) & \(-1.216\) & \(-1.526\) & \(-1.726\) \\
10 & \(-4.712\) & \(-2.807\) & \(-2.597\) & \(-3.872\) & \(-2.00\) & \(-1.808\) \\
15 & \(-14.108\) & \(-5.109\) & \(-3.585\) & \(-13.163\) & \(-4.164\) & \(-2.640\) \\
20 & \(-30.247\) & - & - & \(-28.497\) & \(-7.891\) & \(-4.218\) \\
25 & - & - & - & \(-51.985\) & \(-13.941\) & \(-7.038\) \\
30 & - & - & - & - & - & - \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of SKR with the single beam and multiple beam over channel loss and fluctuating channel loss.
# Vulnerability Analysis of a Multilayer Logistics Network against Cascading Failure
## 2 Methodology and Data
### Attack Strategies
#### 2.2.2 Load Redistribution Algorithm  
The iteration rule against cascading failure with the following algorithm. After a given node \(i\), with the highest load, or the lowest is attacked, the load will be assigned to its neighboring nodes with certain rules, resulting in an update of \(L_{ji}\)  
\[L_{ji}\to L_{ji}{}^{\prime}=L_{j}+\Delta L_{ji} \tag{5}\]  
After node \(i\) fails, the load obtained by the adjacent node is defined as  
\[\Delta L_{ji}=L_{i}\cdot\frac{C_{j}}{\sum\limits_{m\in\Gamma_{i}}C_{m}} \tag{6}\]  
where \(\Gamma_{i}\) represents the set of all the neighboring nodes of node \(i\), \(m\) represents any node in the set, and \(C_{j}\) and \(C_{m}\) represent the capacity. If \(L_{j}+\Delta L_{ji}>C_{j}\), then node \(j\) will also fail. The rest of the load will be distributed by the above rules until the failure node no longer appears. Assigning the load to the neighboring nodes is a partial redistribution mode because the neighbor of the failed node may continue to load. The transfer between intact nodes in the network, that is, the distribution of the nodes, is a global behavior.
# Sample-Efficient Deep Learning Techniques for Burn Severity Assessment with Limited Data Conditions
## 1 Introduction
In the evaluation, we deliberately assumed limited dataset conditions and utilized only a small number of training samples (i.e., no more than tens or hundreds of burn images). Our experimental setting was intended to assess the feasibility of sample-efficient deep learning techniques in the context of medical image analysis with data limitations. For this purpose, we used the task of burn severity assessment as the subject of our empirical study. Specifically, we compared the performance of sample-efficient deep learning models to that of a CNN model learned on the entire dataset (i.e., our sample-sufficient baseline model), to determine whether or not sample-efficient models trained with a small part of the dataset could achieve comparable performance to the sample-sufficient baseline. For example, our SSL-based method utilized a pretrained SSL model (i.e., simCLR [10]), obtaining high accuracy comparable to the sample-sufficient baseline, even when only 16% of the entire dataset was used; the method achieved high sample-efficiency, showing comparable accuracy to a baseline model learned on a dataset six-times larger. To the best of our knowledge, our work has been the first to implement and evaluate sample-efficient deep learning techniques with real-world burn injury data. The main contributions of this paper are as follows. * We present sample-efficient deep learning models for burn severity assessment using various techniques. Through extensive experiments, we demonstrate the feasibility of these sample-efficient models with limited training data. * We build a large dataset containing 13,715 burn images with professionally annotated information, on which not only the high-accuracy burn severity assessment model is trained but also various limited data conditions can be emulated to evaluate the sample-efficient models. * We discuss the dataset conditions under which sample-efficient deep learning techniques can be productively applied. The remainder of this paper is organized as follows: The details of the burn severity assessment task, including its datasets and baseline models, are described in Section 2. Several deep learning techniques for limited training data conditions are explained in Section 3. The experimental results for these sample-efficient techniques using burn injury datasets are provided in Section 4. Finally, the study conclusions are presented in Section 5.
# An Assessment of Agent-Based Modelling Tools for Community-Based Adaptation to Climate Change
## 2 Methodology Adopted
### Tool Assessment Criteria  
The comprehensive assessment of the selected tools hinges on overarching criteria, namely general characteristics, modelling, simulation, and exchange, as listed in Table 4. Modelling criteria cover parameters related to the modelling process, while application criteria delve into agent types and application domains. Simulation criteria encompass considerations such as speed, parallelization, and the feasibility of applying optimisation methods. Exchange criteria focus on data exchange possibilities with other file formats and programmes [27]. For a thorough comparison of tools suitable for CBA, it is essential to assess them based on their ability to incorporate the key aspects of the CBA approach. This ensures that the tools can comprehensively capture the complexity of community dynamics and enhance decision-making processes in the face of environmental and socio-economic challenges. A review of the relevant literature on CBA projects has identified six criteria under seven broader criteria, as compiled in Table 5. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Criteria** & **Subcategory** & **Description** \\ \hline \multirow{3}{*}{General Characteristics} & Licence, Release Date, Coding Language, & Open source or proprietary? Latest version release date. \\  & Operating System, Community Support & Programming languages supported. \\  & & Compatibility with various OS; presence and activity of user community. \\ \hline \multirow{3}{*}{Modelling} & Agent Definition & Flexibility in defining agent attributes and behaviours. \\  & Behaviour Specification & Ease of specifying agent behaviours and interactions. \\  & Model Validation & Tools for validating the model. \\  & Sensitivity Analysis & Capability for sensitivity analyses. \\  & Scalability & Handling large-scale simulations. \\ \hline \multirow{3}{*}{Simulation} & Time Step Control & Control over simulation time steps. \\  & Visualisation, Parallel Processing, & Tools for visualising model output. \\  & Experiment Design, Output Analysis & Utilisation of parallel processing. \\  & & Experiment Design, Output Analysis \\ \hline \multirow{3}{*}{Exchange} & Data Formats & Supported data input/output formats. \\  & External Data Integration & Ability to incorporate external data sources. \\ \cline{1-1}  & Export Options & Ease of exporting simulation results. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Generic assessment criteria for ABM tools. In developing the six criteria for assessing tools in CBA projects, a literature review was conducted. This review aimed to collect all referenced criteria of CBA from the scientific literature without excluding any and to document them in their entirety. This review began by linking key aspects of CBA in the literature and its requirements for modelling, including
## 4 Conclusions  
According to the study presented in this manuscript, regarding the use of PEX as a partial substitute of aggregates and a binder modifier in asphalt mixtures, a series of conclusions can be drawn, as follows:  
Cross-linked polyethylene (PEX) waste can be partially melted into hot bitumen, modifying the final properties of the resulting binder.  
When incorporated into asphalt mixtures as an aggregate partial substitute, PEX reduces the density of the mixtures by about 5%, which may be an advantage in specific circumstances, namely, during transport and in the application over structural elements, like bridges.  
Regarding the water sensitivity test results, the introduction of PEX was not able to improve the performance of the mixture, unless an increased binder content (0.5% higher) was used. Similar results were observed in the fatigue cracking resistance tests because polyethylene based polymers are not able to improve the flexibility of asphalt mixtures in the same way as the elastomeric polymers that were used in the PMB 45/80-60 mixtures.  
Permanent deformation results of the mixtures with PEX were clearly better than those of the mixtures without PEX, even when higher binder contents were used. This is a result of the lower susceptibility to temperature variation of those mixtures, which can also be observed from their higher stiffness modulus and lower phase angle values. These properties are related to each other and can be seen as the main performance related improvements of incorporating PEX in asphalt mixtures.  
The inclusion of PEX in asphalt mixtures is a viable solution that can assure adequate performance of a road pavement, especially when high service temperatures are expected. This technology also contributes to give new life to cross-linked polyethylene plastic waste. Nevertheless, further research should be carried out regarding low temperature and in situ performance, in order to validate this technology with a broader range of application, loading and climatic conditions.  
The authors gratefully acknowledge the funding provided by the Portuguese Government (Portuguese Foundation for Science and Technology) and by the Competitiveness Factors Operational Programme (EU/ERDF funds), through the FCT project PLASTIROADS (PTDC/ECM/119179/2010).  
[PERSON] was in charge of the whole research, which is part or her PhD work. Nevertheless, all authors were involved in the conception and design of the experimental work. [PERSON] performed the experiments. Finally, all authors analyzed the data and contributed to the completion of the manuscript.  
The authors declare no conflict of interest.
# Route Availability as a Communication Quality Metric of a Mobile Ad Hoc Network
## 5 Evaluation of the RA Calculation Method and Verification of Usefulness of RA
### Observability of the Route Feature Values
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Emulation** & **Number of** & **Total Connected** & **Total Disconnected** & **RA (\%)** \\
**Time (s)** & **Nodes** & **Time** & **Time** & \\ \hline \multirow{4}{*}{90} & 3 & _69_ & 21 & 77 \\  & 4 & _67_ & 22 & 76 \\ \cline{1-1}  & 5 & 74 & 15 & 83 \\ \cline{1-1}  & 6 & 74 & 16 & 82 \\ \cline{1-1}  & 7 & _69_ & 20 & 78 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: How the route feature values and RA changed when the emulation time and the number of nodes were changed. Figure 9: Example of communication pattern consisting of connections and disconnections and the number of hops (emulation time: 90 s; number of relay nodes: 5; “number of hops = \(-1\)” means that the route is disconnected). (**a**) Pattern for a case where the emulation time is from 0 to 45 s; (**b**) Pattern for a case where the emulation time is from 45 s to 90 s.
# Selective Laser-Melted Alloy 625: Optimization of Stress-Relieving and Aging Treatments
## 3 Results and Discussion
### Single- and Double-Aging Treatments
Some residual porosity is visible, but no corrosion damage characterizes the surface. The corresponding corrosion rate is in fact very low (0.5 mm/year). Pictures c and d are instead related to specimens aged at 621 \({}^{\circ}\)C for 130 h. Unlike the as-built condition, the surface clearly shows the effects of the corroding solution. The corrosion attack follows the laser tracks' borders preferentially, even if the damage includes the inner zones as well. Accordingly, the corrosion rate (5.7 mm/year) was much higher than of the as-built one. The effect of the standard stress-relieving temperature (850 \({}^{\circ}\)C) on corrosion resistance is clearly detrimental, as shown in Figure 11e,f. Similarly to the aged condition, the corrosion damage proceeds along the laser track direction and removes material both from the border and the inner part of the track. Also, in this case, the corrosion rate is quite high (5.7 mm/year). Finally, the new heat treatment at 980 \({}^{\circ}\)C resulted in a corrosion rate (0.6 mm/year) very similar to the as-built one. The corrosion pits reported in Figure 11g,h were in fact very small on all the corroded surface. Figure 6.1 Performance map relating the tensile and corrosion properties of the conditions tested in this work for the selective laser-melted material and in our previously published papers [43; 44] for conventional forged alloy 625. The green shaded area corresponds to the acceptability region with respect to the minimum standard requirements for the tensile properties (ASTM B446 [12]). The data labels report the corrosion rate in mm/year according to the ASTM G28—Method A standard [38] (green label: acceptable; red label: not acceptable). The standard deviation values range from 2 to 14 MPa for YS and from 1 to 2% for A%.
# Trepenes and Trepenoids in Plants: Interactions with Environment and Insects
## 1 Plant Trepenes in Abiotic Stress
### Effects of Plant Terpenes on Abiotic Stress
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Plant Species** & **Terpenes** & **Abiotic Stress** & **References** \\ \hline \multirow{2}{*}{_Nicotianaattetunata_} & \multirow{2}{*}{sesquietrepenes: (\(E\))-\(\beta\)-Famesene; (\(E\))-\(\alpha\)-Bergamotene} & \multirow{2}{*}{Tropospheric ozone, ROS} & \multirow{2}{*}{[50; 51; 52]} \\  & & & ROS \\ \hline \multirow{2}{*}{_Oryza-asativa_} & \multirow{2}{*}{monoterpenes: limonee; sabinene, myrcene; H2O2, and Y rays} & \multirow{2}{*}{[53]} \\  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \hline _Vitis vinifenfex_. **Chardonay** & \multirow{2}{*}{monoterpenes} & Thermal stress & \multirow{2}{*}{[54]} \\ \cline{1-1} \cline{3-4}  & & & \\ \hline _Pseudotusquenzeisti_ (**Douglas fir**) & \multirow{2}{*}{monoterpenes: \(\beta\)-pinene; a-pinene; \(\beta\)-citronello; \(3\)-carene; camphene} & \multirow{2}{*}{[55]} \\ \cline{1-1} \cline{3-4}  & & & \\ \hline _Zea mays_ & \multirow{2}{*}{Sesquietrependiol: zealesi; ditempendio: kaualexins} & \multirow{2}{*}{Drought- and salt-induced stress} & \multirow{2}{*}{[56]} \\  & & & \\ \hline _Salviaofficialnis_, _Salvia fruticose_, & \multirow{2}{*}{ditrepene: carnosic acid} & \multirow{2}{*}{[57]} \\  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Abiotic stress-associated terpenenes and terpenoids.