esa-sceva/satcom-chunk-collection huggingface dataset:
# Review of Structural Health Monitoring Techniques in Pipeline and Wind Turbine Industries
## 3 Health Monitoring in Corrosion
### Quasi-Distributed OFS for Corrosion  
It can be considered that sensors based on Fiber Bragg grating are equivalent to point sensors. For every FBG sensor, there is a shift in the Bragg wavelength owing to the changes in the environment such as changing temperature and strain. On the basis of this principle, it becomes possible for the FBG sensors to be able to monitor the changes in temperature and strain parameters which are closely related to the corrosion that happens in pipelines and wellbores (Figure 8).  
\[\lambda_{B}=2\;n_{\mathrm{eff}} \tag{29}\]  
The FBG-based pressure sensors that have been developed can be utilized in finding the point of leakage in the pipelines by using the method of negative pressure wave (NPW). When a leak in a pipeline initially happens, there is a pressure drop that is induced, and it travels in either direction from the point of leakage. The NPW reaches the FBG pressure sensors that are fixed on the pipe, which records the time taken for the wave to reach it,  
Figure 6: Change in intensity of light results in the detection of corrosion [85].  
Figure 7: Light spectrum data indicating presence of anomalies [71].  
and this information is utilized to evaluate the point of leakage [91; 92]. It has been found that the strain sensors based on FBG are attached directly to the pipeline surface in order to evaluate the strain of the refurbished pipes [93]. In field tests, the installation of sensors based on FBG are done over the risers for watching the riser stress during drilling-based operations such as subsea drilling (Figure 9b) [94; 95; 96]. When a coat of hygroscopic polymers is done over the FBG-based structures, these structures can then be utilized as an H sensor, since there is a mechanical expansion that happens inside the polymeric structure [97; 98; 99].
# Design of a 90 GHz SOI Fin Electro-Optic Modulator for High-Speed Applications
## 2 Modulator Structure and the Performance Parameters  
A cross section of the phase shifter is shown in Figure 1a. The shifter consists of a rectangular waveguide of silicon core and silicon dioxide cladding. The width of the core is \(W\) and its height is \(H\). Three rectangular pieces of aluminum are placed around the core to form the electrodes. The top and right pieces are electrically connected to the modulating voltage while the left is grounded. The silica layer between the core and the right or left electrodes has a thickness denoted by \(y_{o}\). A silica layer of thickness \(z_{o}\) separates the core from the top electrode.  
The proposed modulator employs the Mach-Zender interferometer (MZI) structure where light propagates through two arms, as shown in Figure 1b. Each arm possesses a phase-shifter as the one just described. When the applied modulating voltage, \(V\), is zero on both arms, the two modes in the MZI arms are in phase and the output power is high, \(P_{H}\). Applying a voltage difference to the arms, the output optical power is then low, \(P_{L}\). The extinction ratio, \(ER\), in \(dB\) is given by \(ER=10\log\frac{P_{H}}{P_{L}}\)[40]. If the input optical power is \(P_{o}\), then the insertion loss, \(IL\), in \(dB\) is given by \(IL=10\log\frac{P_{o}}{P_{H}}\). One goal in such designs is to maximize \(ER\) and minimize \(IL\). The voltage difference is applied to the arms in the form of positive voltage, \(V_{1}\), on one arm and negative voltage, \(V_{2}\), on the other. This technique is known as the push-pull technique [41] and is useful to decrease the voltage applied to an arm.  
See Figure 1b. The phase shifter length is denoted by \(L\). If this length is enough to produce a \(\pi\) phase-shift between the two arms, then the length is called the 'effective length', denoted by \(L_{\pi}\). This length is calculated from \(L_{\pi}=\frac{\lambda_{o}}{2\Delta n_{e}}\), where \(\lambda_{o}\) is the free-space wavelength of the light and \(\Delta n_{e}\) is the difference in the effective index, \(\Delta n_{e}\), between the propagating modes in the two arms. The required voltage difference to induce this phase shift is denoted by \(V_{\pi}\). In such a case, \(ER\) is at its absolute maximum since \(P_{L}\) is at its absolute minimum. The reason for why \(P_{L}\) cannot go down to zero is that the two arms do not possess the same optical loss, since the optical loss due to plasma dispersion is function of the applied voltage, which inherently is not the same for the two arms. Hence, \(ER\) cannot be infinity. Still, due to small differences in the optical loss values in the two arms and also due to the short arm length, very high \(ER\) values can be achieved as will be discussed later. A trade-off exists, on the other hand, between the aforementioned parameters. The device size can be reduced, to enable higher fabrication density, lower \(IL\), and lower \(C\) and hence higher \(f_{\rm 3 dB}\), at the expense of the phase shift between the arms, which results in a decrease in \(ER\).
# NaYF4 Microstructure, beyond Their Well-Shaped Morphology
## 4 Conclusions  
Many works have reported the synthesis, optical properties and application of Na(Gd)YF\({}_{4}\):Yb, Er nanoparticles. The large interest for this systems comes both from their highly appealing emission properties, and the ability to synthesis particles with different size and shapes. In particular, very nice facetted nanorods can be obtained with adjustable aspect ratio playing on the particles composition such as some Gd\({}^{3+}\) ions in substitution to Y\({}^{3+}\). Nevertheless, characterizations of polarized emission from single nanorods evidence that the particles are not monocrystals, which motivated this study to  
Figure 7: (**a–c**) HRTEM of NPs with below the FFT of the indicate area (**a**) NR09 with a typical FFT orthogonal to the c-axis (**b**) NR13 with a typical FFT parallel to the c-axis (**c**) NR11 with a FFT characteristic from an hexagonal phase trough the c-axis but observed orthogonally to the c-axis. (**d**) HRTEM of a NR06 with various defects below same image filtered with false color.  
get a deeper insight in the particles microstructure. This work has been done using TEM and XRD analysis on a set of 13 samples obtained under various conditions. We could show that in a given batch of synthesis, and focusing on particles with the \(\beta\)-NaYF\({}_{4}\) structure, different populations of particles may coexist with different size and shape, but also with strong deviations from the nominal composition. XRPD analysis using the Halder-Wagner approach, combined with HRTEM point out an anisotropic polycrystalline structure of the nanorods with important local variations of the crystallites orientations. This is clearly at the origin of the polarization spectra, which is very sensitive to crystallites orientation.  
As NaYF\({}_{4}\) NPs are now widely used for their interesting optical properties, these observations show that an exhaustive structural and chemical analysis is compulsory in the aim to understand and optimize this system for the targeted applications.  
Conceptualization, Data curation, Formal analysis, G.L. and S.T.-N.; Funding acquisition, T.G.; Investigation and Methodology, G.L. and S.T.-N.; Resources, G.L., S.T.-N., M.T., P.-E.C., K.L., E.L. and T.G.; Software, S.T.-N.; Validation, G.L., S.T.-N. and T.G.; Visualization, G.L.; Writing--original draft, G.L. and S.T.-N.; Writing--review & editing, G.L., S.T.-N. and T.G.  
Funding: Funding for this project was provided by the French National Research Agency in the frame-work of the FiPlaNT project (ANR-12-BS10-012). This work was supported by the French ANR research programm \"Investissements d'avenir\" (ANR-10-EQPX-50).  
We acknowledge the European Synchrotron Radiation Facility for provision of synchrotron radiation facilities and we would like to thank [PERSON], [PERSON] and [PERSON] for the help during the experiment.  
The authors declare no conflict of interest.
## 3 Results
### Characterization of the Surface Wettability  
Figure 6 gives the average contact angle results of the investigated samples. According to the optical subsystem measurement, it was found that the average contact angles of the control, HDPA-SAM/TiO, NDPA-SAM/TiO, PUA-SAM/TiO, and PHA-SAM/TiO samples were \(81.7\pm 0.9^{\circ}\), \(83.3\pm 0.9^{\circ}\), \(90.3\pm 0.4^{\circ}\), \(68.8\pm 0.7^{\circ}\), and \(78.9\pm 1.2^{\circ}\), respectively (\({}^{\star}p<0.05\)). Evidently, it indicated that the NDPA-SAM/TiO sample exhibited surface hydrophobicity since its contact angle was slightly larger than \(90^{\circ}\). Hydrophobic surfaces are usually defined as having water contact angles greater than or equal to \(90^{\circ}\). Contrarily, the water contact angle of a hydrophilic surface is typically less than \(90^{\circ}\). Thus, the control, HDPA-SAM/TiO, PUA-SAM/TiO, and PHA-SAM/TiO samples possessed hydrophilic surfaces. However, the PUA-SAM/TiO sample had the best hydrophilic surface as compared to the other investigated samples.
# Temperature Stable, High-Quality Factor Li2 TiO3-Li4 NbO4F Microwave Dielectric Ceramics
## 4 Conclusions  
In this work, the structural evolution, microstructure, surface analysis, and microwave dielectric properties of (1-x)Li2 TiO3-xLi4 NbO4F (x = 0.05, 0.10, 0.15, 0.20) ceramics have been investigated. Continuous solid solutions between Li2 TiO3 and Li4 NbO4F were formed across the entire compositional range, with the phase structure transforming from the monoclinic phase to cubic phase. With the increase of Li4 NbO4F, the \(\tau_{\rm f}\) value of Li2 TiO3-based ceramics was close to zero, and the sintering temperature of the ceramics was reduced. The Q\(f\) value of the Li2 TiO3-xLi4 NbO4F ceramics was conspicuously enhanced compared with that of the Li2 TiO3-Li3 NbO4 ceramics doped with B2O3. Excellent microwave dielectric properties of \(\varepsilon_{\rm r}\) = 18.7, Q\(f\) = 61,388 GHz, and \(\tau_{\rm f}\) = 0.9 ppm/\({}^{\circ}\)C were obtained for the 0.90 Li2 TiO3-0.10 Li4 NbO4F ceramics sintered at 1050 \({}^{\circ}\)C. The samples with a near-zero \(\tau_{\rm f}\) and high Q\(f\) were suitable for practical applications in the field of satellite communications and global positioning system antennas.  
Analysis and writing, S.X.; Review and editing, J.J. and D.W.; Methodology, S.S. and X.C.; Date curation, Z.C.; Project administration, T.Z. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Science Foundation of China (Grant Nos. 11774083 and 51902093) and China Scholarship Council (Grant No. 201808420353). The authors declare no conflict and interest.
# A Simhash-Based Integrative Features Extraction Algorithm for Malware Detection
## 4 Experiments and Results
### Experimental Design
#### 4.2.2 Obfuscated-Detection Evaluation  
Obfuscated-detection refers to the ability that can obfuscate samples. First, we randomly select 500 obfuscated samples from the dataset and extract their features. Then, the 500 obfuscated samples and 500 normal samples are used as the verification set, and the three feature-trained detection models are used to detect the set.  
As shown in Figure 5, the CC value of the static features is higher than the other two types of features, the CC value of the dynamic features is relatively low, and the CC value of the integrative features is centered. The reason for this may be that the static information is rich and that there are more static features. Therefore, the generalization ability of the training model of the static feature is relatively high, and the CC value is increased. Some samples, e.g., samples in the.dll file format, do not have behavior information, so there are fewer dynamic features than static features and the CC values of the dynamic features is lower. The integrative features integrate the above two types of features. Although the number of features trained is large enough, the simhash algorithm is affected by the missing dynamic information during the integrative process, so that the classification effect is between the other two types of features.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Feature Type**} & \multicolumn{5}{c}{**Random Trees**} \\ \cline{2-7}  & **CC** & **TP** & **TN** & **FP** & **FN** & **T** \\ \hline Static feature & 0.954179 & 0.975 & 0.793 & 0.217 & 0.025 & 2.01s \\ Dynamic feature & 0.914794 & 0.951 & 0.689 & 0.311 & 0.049 & 1.41s \\ Integrative features & 0.941315 & 0.968 & 0.814 & 0.196 & 0.032 & 1.73s \\ \hline \hline \end{tabular}
\end{table}
Table 7: The results of the random trees algorithm. CC (Correctly Classified rate, CC), TP (True Positive rate, TP), TN (True Negative, TN), FP (False Positive, FP), FN (False Negative, FN), T (training Time, T).  
Figure 4: The ROC (Receiver Operating Characteristic curve, ROC) curve of the algorithms. TP (True Positive rate, TP), FP (False Positive, FP), NB (Naive Bayes, NB), SGD (Stochastic Gradient Descent, SGD), SVM (Support Vector Machine, SVM), Ada (Adaboost, Ada) and RT (Random Trees, RT).  
As shown in Figure 6, the model trained by the SGD algorithm has the highest CC value, followed by the RT, the SVM and Ada algorithms. The model trained by the dynamic features using the Ada algorithm has the lowest CC value. From the perspective of training time, although the SGD algorithm has the highest CC value, the training model takes a relatively long time, especially in the experiment using K-fold cross validation (i.e., approximately 40 min for 5000 samples detection), thus the algorithm is not suitable for actual detection. In summary, using the RT algorithm to train the integration integrative features is comparatively better.
# Technical Performance of an Inflatable Solar Dryer for Drying Amaranth Leaves in Kenya
## 3 Results and Discussion
### Simulation of Airflow Distribution in the ISD  
Visualization of simulated airflow distribution and direction in the ISD (isometric and side view) and throughflow on the trays, i.e., exclusively vertical direction (top view), is presented in Figure 4. Air velocity inside the ISD varied between 0.5 and 1.5 m/s. High turbulence was visible in the preheating area. After the air deflector, air with high velocity passed across tray 1 to 5. It could be seen that the stands allowed both through- and overflow of the air, particularly on those trays. The contact of the leaves with the air was intense, and the air velocity was high, with values between 0.5 and 0.7 m/s. This indicates that the leaves on those trays might have had a faster drying rate compared to the other trays. The following trays 6 to 20 showed mainly overflow at a relatively uniform air velocity of around 0.15 m/s. Close to the outlet, particularly tray 21, turbulence was high again.  
Figure 3: State-of-charge (SOC) and voltage of battery and air mass flow of an inflatable solar dryer (ISD) with two 100 W\({}_{\text{P}}\) PV modules and a 912 Wh battery, estimated for solar radiation data of Nairobi, together with measured data for air mass flow (data points), Kenya, on 8–11 December 2016.  
Due to the spatial differences in intensity of the vertical component of the air flow and the increasing relative humidity of the dryer, the drying rate decreased along the dryer. Figure 5 presents the momentary moisture content of the amaranth leaves after 68 h of drying along the dryer. An increasing pattern of moisture content of the leaves as they got closer to the outlet was observed. The highest moisture content of leaves of 55.2% was detected on tray 21.  
Figure 4: Visualization of airflow distribution and direction in the ISD (isometric and side view) and vertical flow through the 21 trays (top view).  
Figure 5: Momentary moisture content of leaves along the dryer (trays 1–21) in the ISD after 68 h of drying.
## 2 Materials and Methods
### Expert Fitting  
For the participants' cochlear implants, all configurations, including the primary map utilized by the participants, were exported from their personal processors and transferred to the Advanced Bionics Naida(tm) CI M processor used in this study. This approach ensured that the hearing experience closely resembled their everyday perception. Participants were asked whether the new program sounded familiar, and adjustments were made if they were not satisfied. This final setting represented the expert fitting for the patients' CIs. For the hearing aids, if a participant privately used a Phonak Naida(tm) Link M, their data were transferred to the study device, with only minor adjustments made, if requested. If a different hearing aid was used, the settings from the private device were not exported. Instead, a new expert setting was created using the Target CI 1.5 fitting software for the study device. This fitting was performed using data from the AudiogramDirect functionality and the Adaptive Phonak Digital Bimodal (APDB) formula. The APDB formula was specifically tailored for bimodal CI users, especially those with limited hearing on the HA side, where the CI often plays a dominant role in speech understanding [15]. Cochlear implants are good at encoding higher frequencies (1-8 kHz) but can only deliver limited temporal fine structure in the lower-frequency range. The APDB fitting formula enhances the audibility of low-frequency information through the HA, complementing the CI by providing temporal cues that aid speech understanding in noisy environments [9; 16]. Additionally, the volume boost and automatic gain control (AGC) functions were synchronized between the CI processor and the HA [9; 16]. To achieve the best bimodal benefit, the loudness of the new HA fitting was matched to the loudness of the CI side. This loudness adjustment was performed informally through conversation with the participant, without further measurements, and in consultation with subject. Subsequent fine-tuning was performed if necessary. These expert settings for both the CI and HA also served as the baseline from which participants made adjustments using the smartphone application.
# MEMS-Based Vibration Acquisition for Modal Parameter Identification of Substation Frame
## 4 Modal Analysis of the Substation Frame
### Mode Shapes  
Figure 10(a) shows the first-order torsional mode shape at 2.14 Hz. In this torsional mode, all measurement points, except point 3, vibrate towards the left in the parallel truss direction, while in the vertical truss direction, measurement point 1 vibrates in the opposite direction to the other points. Figure 10(b) presents the first-order mode shape at 2.81 Hz in the vertical truss direction. It can be seen that, except for measurement point 4 at the center of the second-level busbar truss, which vibrates towards the rear of the substation frame, all other points vibrate towards the front, exhibiting a unidirectional tilt mode shape at the top of the substation frame.  
Figure 10(c) shows the second-order torsional mode shape at 3.05 Hz. In the parallel truss direction, measurement point 2 vibrates out of phase with the other points, while in the vertical truss direction, all points vibrate in the same direction. Figure 10(d) presents the first-order mode shape at 4.78 Hz in the parallel truss direction, where all measurement points are observed to vibrate in the same direction.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Mode**} & \multirow{2}{*}{**Direction**} & \multicolumn{3}{c}{**Frequency (Hz)**} & \multicolumn{3}{c}{**Damping Ratio (\%)**} \\ \cline{3-8}  & & **MSMS** & **941b** & **Discrepancy** & **MEMS** & **941b** & **Discrepancy** \\ \hline
1 & 1 st Torsional & 2.14 & 2.15 & 0.01 & 0.31 & 0.23 & 0.08 \\
2 & 1 st Vertical & 2.81 & 2.79 & 0.02 & 1.29 & 1.17 & 0.12 \\
3 & 2 nd Torsional & 3.05 & 3.06 & 0.01 & 0.46 & 0.33 & 0.13 \\
4 & 1 st Parallel & 4.78 & 4.79 & 0.01 & 0.15 & 0.12 & 0.03 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The identified results of frequencies and damping ratios.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Mode**} & \multirow{2}{*}{**Direction**} & \multicolumn{3}{c}{**Frequency (Hz)**} & \multicolumn{3}{c}{**Damping Ratio (\%)**} \\ \cline{3-8}  & & **SSI** & **FDD** & **Discrepancy** & **SSI** & **FDD** & **Discrepancy** \\ \hline
1 & 1 st Torsional & 2.14 & 2.15 & 0.01 & 0.31 & 0.43 & 0.12 \\
2 & 1 st Vertical & 2.81 & 2.79 & 0.02 & 1.29 & 0.88 & 0.41 \\
3 & 2 nd Torsional & 3.05 & 3.05 & 0 & 0.46 & 0.27 & 0.19 \\
4 & 1 st Parallel & 4.78 & 4.79 & 0.01 & 0.15 & 0.23 & 0.08 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of modal identification results from different method.  
It should be noted that mode shape decomposition is based on the theory of modal superposition, meaning that under actual service conditions, the structure's mode shapes represent a coupling of multiple modes. However, mode shape decomposition is beneficial for designers seeking to verify construction quality, understand the service state of the structure, and accumulate data and experience for the design of new structures.
## 3 Design of a Digital Satellite-Borne Base Station for Quick Functional Reconfiguration
### Network Model
#### 4.2.1 Optimization Problem  
This section develops a multi-objective optimization problem to lower the overhead of VNF migration and the number of VNF migrations in NFV networks and to increase system stability. To lower the overhead of real-time computation during VNF migration in the system, a method of migration precomputation in collaboration with real-time computation is proposed.
# Evolution of Hybrid LiFi-WiFi Networks: A Survey
## 2 Framework for HWLNet
### Backhaul Devices  
These devices form the backbone of HWLNets, and their main goal is to accommodate a relatively large number of APs and differences in network (LiFi and WiFi users) demand for high network capacity, such as one LiFi AP providing data rates in Gbps. There is a vast number of technologies that are being researched to find an optimal backhaul solution. All of these can be classified as wireless or wired backhaul.  
Wired backhaul such as power line communication (PLC) can provide stabile connection at low cost using existing electrical wires proposed in [18]. The latest developments [19] show that the hybrid PLC-VLC structure can handle multiple users with backhaul data rates up to 1 Gbps. Another wired backhaul use is provided by the power over Ethernet (POE) devices. Moreover, dual-hop relay transmission with a series of alternating POE and VLC devices can achieve backhaul data rates of 1 Gbps [20]. Finally, plastic optic fibre (POF) can be used for backhauling [21] with frequency division multiplexing to transmit signals to LiFi APs with backhaul data rates up to 15.7 Gbps [22]. Figure 7 presents the maximum user throughput at given distances of 0 m, 2.5 m, and 5 m from a LiFi AP for different backhaul technologies. The achieved throughput differs from the data rates of backhaul solutions due to physical differences in the LED transmitters used in the studies and due to different modulation schemes.  
Wireless solutions are more complex and have higher costs but offer more flexibility in installation. Recent developments [23] have exhibited backhaul devices on the base of a millimetre wave (mmWave) with point-to-point connection. Another study [24] uses VLC-base as a backhaul device with in-band full-duplex for both access and backhaul. Finally, VLC and infrared can be used for backhaul as well [25] with a distinction of inter network between the backhaul devices and APs.  
The authors of this paper believe that the allocation of LiFi-WiFi resources can be best used if they share the same backbone. For now, wired backhaul devices have shown greater reliability with lower costs compared to their wireless counterparts. Therefore, future HWLNets should use POF technology for intra-networking of backhaul devices accompanied with POE devices to form a more reliable and flexible backhaul. The use of wireless backhaul technology should be investigated further as it is the future of indoor networking.  
Figure 7: User’s achieved data rates in different backhaul configurations.