esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Data Pre-Processing  
As Sentinel-2 Level 1C data is provided in top of atmosphere reflectance, we used the Sen2 Cor processor to derive surface reflectance data (BoA Bottom of Atmosphere). Sen2 Cor is a processor for Sentinel-2 Level 2A product generation and formatting; it performs the atmospheric-, terrain (optionally and not used for this study of flat terrain) and cirrus correction of the Top-Of-Atmosphere Level 1C input data [23].  
According to [PERSON] et al. [24], this is particularly important for vegetation analysis, as atmospheric interaction is stronger when the target surfaces consist of non-bright objects, as is the case for vegetation. Furthermore, in order to evaluate spectral properties of tree species, correction algorithms that lead to a material-dependent signature are highly important. The usage of non-atmospheric corrected images can increase the uncertainty up to 10% [24].  
In Figure 2 the corrected Sentinel-2 scene of the Ebersberger and Freisinger Forest is shown for 29 September 2016 as an example for the good data quality. The image is clear and we observe no effect of clouds. The other images have a similar quality after correction.
# Multi-Objective Optimization of Three-Stage Turbomachine
## 5 Simulation Results of Optimization Algorithms
### Consideration of Rotordynamic Behavior  
When a rotor spins, it undergoes gyroscopic separation into forward whirl and backward whirl at its natural frequency. The backward whirl frequency primarily excites damping-related structures, while the forward whirl frequency triggers unbalance-induced lateral modes. Therefore, it is desirable for the forward whirl frequency to remain outside the operating speed range. For the optimization study, the operating speed was set at 160 Hz. With a 25% margin, the forward whirl frequencies should ideally be 200 Hz (12,000 RPM) or higher. Indeed, as observed in Figure 7, the best results from all optimization algorithms exceed this margin. Although gyroscopic behaviors vary from model to model, all models meet the desired criteria. The key consideration is that rotors achieving this frequency with the lowest mass are more valuable, as a lightweight rotor corresponds to a significant cost parameter. For instance, although the critical speed of the model suggested by HHO meets the operating speed margin, it does so with a rotor that is 9 kg heavier than the one proposed by PS.  
The disks shifted toward the bearings as a result of the optimization. Considering \(F=m\cdot e\cdot\omega^{2}\), it is likely that the radial misalignment on the disk will be greater than that on the shaft. To minimize the deflection caused by this force and increase the stiffness, the disks approaching the bearings as much as possible align with Equation (30). Indeed, as the value of b in Equation (30) decreases, the deflection decreases and the shaft stiffness increases.  
\[\delta_{max}=\frac{Fb\big{(}3L^{2}-4b^{2}\big{)}}{48 EI} \tag{30}\]  
Here, \(\delta\) represents the maximum deflection of the beam, F denotes the unbalanced force, L is the total length of the beam, b is the distance to the load application point, E is the modulus of elasticity, and I is the area moment of inertia of the beam. To aid in the understanding of these expressions, a graph is provided in Figure 8.
## 1 Introduction
As for the performance analysis of the proposed DM-CVQKD system, we take into account the asymptotic case [17] where the secure key rate can be obtained via the covariance matrix approach. It is a theoretically calculated value without involving the finite-size effect. Unfortunately, the derived upper bound is difficult to obtain in practical implementations. Therefore, we have to consider the finite-size effects [26; 27]. Though the secure key rate is still pessimistic, it approaches to the practical implementation. Its security analysis is based on the finite-size effects; hence, we can achieve the upper bound of the maximal transmission distance. This paper is structured as follows. In Section 2, we propose the PC-based DM source for CVQKD, and then elaborate on the characteristics of the ZPC-based scheme for improving the DM-CVQKD system. In Section 3, we demonstrate the transmission distance improvement of the DM-CVQKD system via the ZPC-based source preparation scheme. Finally, we draw a conclusion in Section 4.
# Evaluation of Condition of Concrete Structures Using Ultrasonic Pulse Velocity Method
## 2 Literature Review  
Studies on nondestructive testing methods for concrete structures began in the 1930s and increased in the 1970s when flaws were detected in unhardened concrete. In England, BS 1881 part 4 and part 5, which were standards on concrete testing methods for strength and others, were published, and BS 1881 part 201, which provided guidelines on the use of nondestructive testing for hardened concrete, was published in the 1980s. In the 2000s, standards on core testing, rebound hardness, and ultrasonic pulse velocity measurement were announced. In the U.S., an ACI 228 strength evaluation report with 38 papers on the standards of nondestructive evaluation and measurement area was published in the 1980s [1]. Based on this report, many studies have been conducted on the application of nondestructive testing methods to the diagnosis of concrete structures [2; 3; 7; 8].  
The representative previous studies on nondestructive testing methods can be summarized beginning with the most recent as follows. In 2018, [PERSON] and [PERSON] (2018) conducted research on estimating the residual compressive strength of concrete after a fire using the concrete surface hardness [9]. [PERSON] et al. (2016) and [PERSON] and [PERSON] (2006) conducted research on estimating the thickness of concrete as well as the defect locations inside a slab for concrete structures using the ultrasonic pulse velocity method and impact echo method [10; 11]. In 2014, [PERSON], [PERSON] and [PERSON] (2014) conducted research on the benefits of combining the impact echo method and the method of ultrasonic surface waves [4]. In 2013, [PERSON] et al. (2013) identified the difference between lightweight aggregate and normal aggregate using the ultrasonic pulse velocity method and proposed an estimation equation for predicting the compressive strength of concrete [12], and [PERSON] (2013) describes a fundamental uncertainty analysis for a flowrate measurement in a pipe using an ultrasonic Doppler velocity profile method and an evaluation of the estimated uncertainty by an actual flow calibration [13]. In 2011, [PERSON] (2011) conducted research on estimating the corrosion of rebar in concrete walls using a self-potential survey method and infrared thermographic technique [14]. [PERSON] et al. (2005) conducted research on a method of estimating the rebar corrosion level using infrared thermography data [15]. There are many other studies ([PERSON] et al. (2017), [PERSON] and [PERSON] (2017), [PERSON] et al. (2016), [PERSON] et al. (2016) and [PERSON] et al. (2018)) but most of these studies were conducted for a concrete age of 28 days or more, and the studies on quality control related to the compressive strength of concrete at early ages are insufficient [5; 6; 7; 16; 17].
# Multi-Objective Pareto Optimization of Tensile Membrane Architecture for Energy Harvesting
## 2 Related Works
### TMA Optimization  
To design the TMA optimization simulation, the parameters for consideration were identified according to other TMA studies, and the optimization method was defined with reference to multi-objective building optimization methods. In TMA optimization, stability defined by deflection or stress was the main optimization target for maintaining the tension of the membrane without ponding or tearing. [PERSON] et al. [28] introduced an optimal frame-supported conic TMA that can maintain the initial prestress values even with uncertain wind loads. They optimized the TMA by using the nodal deformation as an objective and by using the strength-based probability of failure as a constraint in a random wind environment. [PERSON] and [PERSON] [29] designed TMAs whose shape and layout were optimized to minimize the strain energy in three methods--hanging models, soap films, and structural shape optimization--and investigated their differences and similarities. In both studies, the material or boundary properties were optimized for the structure to remain well stabilized. Additionally, the TMA was defined using elastic constants, boundary conditions, and form-finding properties [30]. In this study, to determine the stability and energy efficiency of the TMA according to the type of material (which was classified according to the stiffness), [PERSON]'s modulus was used to define an elastic constant used in the experiment. A study by [PERSON] and [PERSON] [30] indicated that in the warp direction, the elastic modulus is proportional to the fabric stress for all three types of TMAs. Therefore, the stability of the TMA can be enhanced by maximizing the elastic modulus. To maintain a stabilized state of the structure, the maximization of the material stiffness (also known as the elastic modulus or Young's modulus) was used as an objective.  
[PERSON] et al. [31] proposed a three-dimensional (3D) building facade optimization method that optimizes two parameters: the daylight performance and electricity generation. The optimization was conducted using three design components: a transparent window that allows sunlight to enter the interior, an opaque wall that blocks the sun, and building-integrated photovoltaics, which block the sun but produce electricity. The 3D building facade optimization results were presented via a Pareto-optimal graph, analysis of 50 Pareto-optimal solutions, and visualized alternatives with maximized daylight performance, maximized electricity generation, and intermediate performance. Pareto-optimal graphs and analysis of selected Pareto-front solutions were used to describe the optimized TMAs. Additionally, because the results corresponded to a total of 18 Pareto optimizations, comparisons were made between Pareto-front solutions obtained under different conditions.
## 4 Experimental Results
As concerns the trend versus the EGR rate, it is worth noting that the measurements are performed keeping constant the overall engine load; hence, the single cylinder IMEPs are almost constant at varying the exhaust-gas recirculation. In Figure 5, the EGR-related trend of the engine ISFC is presented for the measured operating points. As expected, a reduced ISFC is observed at low and medium/high IMEPs by increasing the EGR content. At low loads, the ISFC benefits are ascribed to the EGR-induced reduction in the pumping losses promoted by the engine de-throttling; at medium/high loads, the ISFC advantages are obtained thanks to the EGR capability in reducing the knock tendency [18]. Figure 3: Relative air-fuel ratio (\(\lambda\)) in Cyl #1, Cyl #2 and overall engine at different operating points as a function of EGR rate. Figures 6 and 7 show the characteristic angle of MFB 10% and the combustion core duration (MFB 10-50%) for both cylinders at different operating conditions. Looking at the early stage of combustion, at each operating condition, a slight delay in MFB 10% (Figure 6) of Cyl #1 compared to Cyl #2 is evident: the richer mixture in Cyl #2 provides a higher flame speed, advancing the MFB 10%. As shown in Figure 6, this gap increases at higher EGR rates; as is well-known, the charge dilution slows down the combustion rate, enhancing the effect of the equivalence ratio on the flame speed. The cylinder-to-cylinder variation in MFB 10% does not provide significant differences in the core combustion duration as reported in Figure 7. Even though the combustion duration in Cyl #1 results always prolonged compared to Cyl #2, the maximum difference in MFB 10-50% is less than 1.5 CAD at 1800@10 with 14.4% of external EGR. Regarding the effect of charge dilution on the combustion duration, the EGR prolongs the MFB 10-50% at each operating condition. This trend is more evident at higher engine speed, due to the reduction in cycle length,  
Figure 4: Indicated load in Cyl #1 and Cyl #2 at different engine operating points as a function of EGR rate. Figure 5: Engine Indicated Specific Fuel Consumption at different operating points as a function of EGR rate. leaving a shorter period available to complete the combustion process. Further increase in combustion duration against the EGR is found at lower engine load, because of the greater impact of internal EGR which contributes to increase the overall in-cylinder residual content at decreasing the load.
# Automatic Detection of Online Recruitment Frauds: Characteristics, Methods, and a Public Dataset
## 3 The Problem of Online Recruitment Fraud
### The ORF Facets  
The methods followed by scam practitioners can be classified into two main groups of increasing severity. The first category comprises of rogue job advertisements that aim at harvesting contact information. By luring the user into filling application forms corresponding to non-existing positions, an ill-motivated individual is able to build a database usually containing the full name, phone number, address and ZIP code of that user. More sophisticated scammers may also elicit the educational and working experience profile of their victims and end up aggregating this information with other contextual socioeconomic data. Comprehensive databases and statistical results can then be re-sold to third parties such as cold-callers, aggressive marketeers, communicators for political campaigns or even to website administrators who plan to send out targeted bulk email messages containing links to generate page views and inbound traffic. In other cases, the collected email addresses can be used to forward spam emails.  
The second class of job scamming is sleazier as it aims towards complete identity theft that can later be used as part of economic chicaneries such as money-laundering and reshipping fraud [22]. In this case, scammers assume the role of a legitimate or fictional employer and use the ATS as a medium to disseminate content about fake job positions. These posts re-direct the users to external methods of communication (i.e., site, email address or telephone number). From that point on, they may engage into a series of actions such as dissemination of fake skills test, scheduling of phony interviews, transmission of congratulatory emails for successful onboarding, etc. The ulterior purpose is to convince the victim to hand out extremely sensitive documents such as Social Security Numbers, identity cards, and passports or unwittingly become a \"money mule\" and use their bank accounts to help criminals launder money [23]. Alternatively, scammers may even trick candidates into filling out an inquiry that looks like a direct deposit form, aiming to steal their bank information and routing numbers or drive them to a direct wire transfer usually under the guise of working visa and travel expenses [24].
## 2 Data Acquisition and Processing
### Sensor Data Acquisition and Processing  
Real-time data related to ships are acquired through various sensors. The real-time fuel consumption data of the ship's main engine, auxiliary engine, and boiler are obtained using mass flowmeters. Sensor data also provide information on the ship's main engine speed and trim. The original units for heavy and light oil data (kg/h) are converted to kg based on each data time interval. Missing values in the fuel consumption data are addressed using linear interpolation, interpolating fuel consumption, speed, and trim data with a one-hour interval.
# Probabilistic Condition Monitoring of Azimuth Thrusters Based on Acceleration Measurements
## 2 Materials and Methods
### Condition Monitoring Algorithm
#### 2.2.2 Feature Extraction
4-8 and the features for gear monitoring are shown as features no. 9-11. Figure 4 shows amplitude spectra from a case with no reported damage and a case with inner race defect in the bearing in thruster 1. The 1-10 BPFI harmonics and the closest sidebands are marked there separately. The median (feature no. 4) and upper quartile of the amplitudes of BPFI harmonics are marked there as well. These graphs illustrate that the feature values increased in the case of damage. The change is seen the most clearly in the fifth and higher harmonics of BPFI and sideband components in this case. Similarly, Figure 5 shows amplitude spectra from the cases with no reported damage and wear on the gear surfaces in thruster 2. The 1-4 GMF harmonics and sidebands are marked together with the median (feature no. 9) and upper quartile computed from their amplitudes. The graphs indicate that the amplitudes of GMF harmonics and sidebands increased in the case of damage. In automated condition monitoring, an individual frequency component may have small significance, because the fault symptoms become manifested differently when the operational state of the machine changes. Therefore, the features computed based on several frequency components could contain more diagnostic information than separate components individually. Finally, the presented features may not be optimal for the studied data sets and their optimization goes beyond the scope of this study.
## 3 Results
### Results of S1 Set: Range and Speed of Motion Patterns
Those values refer to the worst scenario, whereas, in the average ROM/speed combination, the angular dispersion is lower than 0.6 deg for configurations A and B, 0.8 deg for configuration C, and 3.5 deg for configuration D. The largest dispersion values are always obtained when a constant weighting factor is selected. The use of the other different weighting factors definitely reduces the angular dispersion of the IHA sets; however, it also has a negative impact on the estimation of the MHA location, as signaled by the increased rms distance. This effect is observed in most of the ROM/speed combinations selected; however, it is far more evident in A and C configurations. Compared to the helical axis method, the SARA algorithm shows far more stable results for most of the ROM/speed combinations selected, as expected. This result is particularly evident in A, B, and C configurations, both by considering the linear and angular dispersion values. The linear dispersion reaches 0.04 mm for the A and C configurations, both of which consider a stationary AoR along the \(u\) and \(w\) axes of the shank LCS, whereas it increases up to 0.52 mm and 2.54 mm for B and D configurations, respectively. Similar results are obtained as far as the angular dispersion is concerned, achieving values lower than 0.3 deg for all the ROM/speed combinations and motion configurations tested. However, the most significant improvement shown by the SARA methodology is related to the estimation accuracy of the AoR, as signaled by the low rms distance. For most of the ROM/speed combinations, the rms distance \(\Delta\) measured between the SARA-estimated and the exact AoRs is lower than the one calculated by considering the MHA. This result is particularly evident for A (see Figure 5) and C configurations (\(\Delta\) lower than 0.04 mm); however, it is confirmed for most of the trials performed by choosing the B configuration. Interestingly, the results obtained for the tri-planar motion configuration (D, see Figure 6)  
Figure 6: AoRs calculated with MHA, by choosing different weighting factors, and SARA, for motion configuration D. The axes are represented in two views: (**a**) transverse (horizontal) plane; (**b**) frontal plane. Each row and column correspond to a particular range of motion (ROM) and speed (V) selected, using the same nomenclature detailed in Section 2.3.2. The exact AoR imposed by joint kinematics setup is highlighted in dashed black line. All axes units are in mm. are comparable with the ones yielded by the helical axis methodology, with the latter performing even better in a few ROM/speed combinations. In particular, the IHA algorithm shows a limited improvement in the AoR estimation accuracy for the narrowest and average ROMs, regardless of the speed selected.
## 3 Results and Discussion
### Test Results
#### 3.3.3 Test 3 Results  
The evolution of the flight is represented in Figures 14 and 15.  
When the distance threshold set for the activation of the ASACAS collision avoidance function was reached, the DAA system indicated the predicted collision condition to the remote pilot and automatically started executing a suitable collision avoidance maneuver that allowed the ownship to avoid the collision. The remote pilot monitored the collision avoidance maneuver executed by the system, and they had the ability to abort it and take the control of the RPAS if desired.  
The collision avoidance maneuver for this head-on encounter geometry led to a 3D variation of the ownship's trajectory (the colliding intruder continued its straight-levelled flight undisturbed) that resulted in it being tangent to the collision volume centered in the intruder and whose size was increased with respect to the nominal one based on the closure rate between vehicles at the moment where the collision avoidance maneuver was elaborated by the ASACAS. As already indicated, the collision avoidance maneuver could be automatically updated by the DAA system during its execution if needed based on the current traffic picture. The updates of the maneuver are indicated by  
Figure 14: Test 3: automatic collision avoidance maneuver showing the 3D trajectory of the ownship and colliding intruder.  
Figure 15: Test 3: automatic collision avoidance maneuver and parameters of interest.  
the signal \"collision detection\" rising to 1 in Figure 15, whereas the implementation of the maneuver is indicated by the \"CA maneuver\" signal being maintained at level 1 in the same figure.  
An analysis of Figure 15 allows one to observe that in this real-time simulation test, the collision condition was detected by the DAA system at about 465 s, and, at the same time, the collision avoidance maneuver started to be automatically executed by the system (after the proper, very small elaboration time) through the automatic transmission of the maneuver reference commands to the aircraft autopilot.  
The minimum distance between vehicles (i.e., the distance at the CPA) was about 460 m, consistent with the set dimension of the collision volume; thus, the ownship's trajectory was tangent to the collision volume. The collision avoidance maneuver was completed at about 515 s, when the range rate between vehicles became positive (the vehicles started diverging). As in the previous tests, the indicated range and range rate were only calculated during the collision avoidance functionality execution, so the null values indicated outside this time interval have no meaning in the figure.  
The collision avoidance functionality of the ASACAS, therefore, was shown to perform as expected in the real-time simulation test described here.