esa-sceva/satcom-chunk-collection huggingface dataset:
# Recent Progress on Irradiation-Induced Defect Engineering of Two-Dimensional 2H-MoS2 Few Layers
## 4 Other Irradiation
### Hybrid Irradiation: UV-Ozone Treatments  
Ultraviolet-ozone cleaning technique is a dry-cleaning method to clean material surfaces by the decomposition of contaminants through ultraviolet irradiation and the chemical action of oxidation by ozone. During cleaning, surface organic compounds decompose to volatile substances by ultraviolet lights and by strong oxidation of ozone. The technique has been employed to irradiate 2D MoS\({}_{2}\) mono-layers [163; 164] and few-layers [165; 109; 166; 167].  
[PERSON] et al. [164] rapidly treated MoS\({}_{2}\) 1-3 layers that were mechanically exfoliated from crystals. These was no any change before and after the UV-ozone treatments. It was assumed that the irradiation effect was below detection because of the rapid treatment (30 s) and nitrogen protection that reduced high oxidation and mobility change. [PERSON] et al. [165] prepared MoS\({}_{2}\) nanosheets using a sonication exfoliation method and UV-ozone treated the MoS\({}_{2}\) multi-layers for 15-30 min. The MoS\({}_{2}\) layers were converted to MoO\({}_{x}\). [PERSON] et al. [167] treated liquid-exfoliated MoS\({}_{2}\) few-layers (15-16 layers) in UV-ozone atmosphere for 1.5 h. It was found that the Mo/S atomic ratio decreased, and atomic percentage of oxygen increased with the expose time. [PERSON] et al. [109] exposed the mechanically exfoliated MoS\({}_{2}\) layers under ultraviolet-ozone at room temperature. They found that oxygen-sulfur bonds were formed at the top sulfur layer while the sulfur-molybdenum bonds were kept besides removal of adsorbed carbon contamination from the MoS\({}_{2}\) surface.  
Figure 30: PL spectra of mono-layer MoS\({}_{2}\) for different annealing time [162]. The anneal temperature is 450 \({}^{\circ}\)C in a vacuum. Reprinted with permission from Reference [162]. Copyright © 2013 American Chemical Society.  
Figure 29: **(a)** AFM images of MoS\({}_{2}\) single-layer (1L), bi-layer (2L), tri-layer (3L), and four-layer (4L) on SiO\({}_{2}\) after oxidation at 320 \({}^{\circ}\)C for 3 h [161]. The inset shows an optical image of this flake before oxidation. **(b–e)** Close-up images of the areas surrounded by dashed lines on **(b)** 1L, **(c)** 2L, **(d)** 3L, and **(e)** 4L in the panel **(a)**[161]. The scale bars are 500 nm. **(f)** The average distance \(r\) from the center to the apex of triangular pits as a function of oxidation time [161]. The inset is an AFM image of a typical triangular pit formed on single-layer MoS\({}_{2}\) after oxidation for 4 h. The scale bar is 300 nm. Reprinted with permission from Reference [161]. Copyright © 2013 American Chemical Society.  
The ultraviolet-ozone technique was also used to mill MoS\({}_{2}\) few-layers to mono-layers [166]. Compared to mechanically exfoliated MoS\({}_{2}\) single-layers, the PL intensity of the UV-ozone milled MoS\({}_{2}\) mono-layers was enhanced by 20-30 times.
## 2 Background
### Process Mining
#### 2.1.2 Petri Net  
A Petri net is a formal language with graphical representation consisting of places, transitions, and a flow relation. It is defined as a tuple \(\mathcal{N}=(\mathcal{P},\mathcal{T},\mathcal{F})\)[24], where \(\mathcal{P}\) represents the set of places; \(\mathcal{T}\) represents the set of transitions; and \(\mathcal{F}\) represents the flow relation, which is a subset of \((\mathcal{P}\times\mathcal{T})\cup(\mathcal{T}\times\mathcal{P})\). A marked Petri net is denoted by \(\mathcal{N}_{m}=(\mathcal{N},M_{r})\), where \(\mathcal{N}=(\mathcal{P},\mathcal{T},\mathcal{F})\) and \(M_{r}:\mathcal{P}\rightarrow\mathbb{N}\) represents a marking. The marking, also referred to as a _state_, can be understood as a representation that encompasses a collection of places.
# An Adaptive Dempster-Shafer Theory of Evidence Based Trust Model in Multiagent Systems
## 4 Proposed Trust Model
### Indirect Reputation
#### 4.2.2 Credibility of Individual Witnesses  
In this subsection, a detailed analysis of the credibility of individual witnesses in MASs is carried out. For a group of witnesses \(w_{1},w_{2},\ldots,w_{k}\ldots w_{L}\), they provide testimony to the resource client \(c_{i}\) if \(c_{i}\) urges them to evaluate the trustworthiness of the resource provider \(s_{j}\). From the perspective of \(c_{i}\), to rely on the witness or not is a thought-provoking question. Thus, the agent's credibility is adopted to indicate how much the witness is reliable. In this paper, we force the witness credibility to be in the range \([0,1]\), and the value is initializedto 0.5 if no cooperation has occurred. As interactions go by, the credibility is updated according to the interactive feedback.  
It is necessary to explain how credibility is updated. Of the previous Dempster-Shafer theory based trust estimations models, the value of credibility decreases over interactions all the time if the witness is found lying in [63]. This model works under the assumption that all agents are acting in a constant way. In addition, never forgiving an agent and providing it a second chance also seems irrational. In the literature [29], credibility is learned mainly from two aspects, namely, positive feedback and negative feedback. That is to say, rewards are expressed to all agents when positive feedback is reached, whereas all agents are punished when negative feedback is collected. However, some witnesses may have opposing attitudes when positive feedback is raised, and so it is the same when negative feedback is received. Thus, the credibility of these witnesses needs to be updated separately. What is more, it is sometimes questionable to update the value only according to the current interactive feedback, especially in dynamic systems. Individual reliability has a great influence on indirect reputation. We consider the credibility \(Cred(c_{i},w_{k})\) of the witness \(w_{k}\) from the perspective of \(c_{i}\) when generating indirect reputation. More details about learning from the experience to renew personal credibility are discussed in Section 4.4.
## 6 Steady-State Map Results  
After simulating all the map operating points, the predicted results can be collected and represented by means of contour plots, indexed by engine speed and load, which are used to identify the engine working conditions. These contour plots can be addressed as the steady-state maps of the IC engine, each one detailing a particular property. This kind of representation offers a quick, graphical way to verify the satisfactory correspondence between simulation results and experimental data.  
As an example, Figure 10 shows a group of steady-state maps referring to the most important engine performance and emission characteristics: in particular, Figure 10a-f highlight the discrepancy between measured and calculated results in terms of percentage error, whereas Figure 10g,h directly show the measured and simulated (non-dimensional) cylinder-out NOx emissions.  
Figure 10: _Cont._  
Figure 9: (a) Fuel burnt mass fraction profile for the operating point at n = 800 rpm, BMEP = 12 bar. This is characterized by a double injection (a pilot and a main one), however the assumption of neglecting the pilot injection (for the fitting of the double-Wiebe function) is accurate; (b) Fuel burnt mass fraction profile for the operating point at n = 1700 rpm, BMEP = 8 bar (with single injection, in this case).  
The prediction of specific fuel consumption by means of the 0D/1D code is very accurate at low and medium engine speeds, as reported in Figure 10a, whereas a larger discrepancy can be found at high regimes. However, considering the typical applications  
Figure 10: Steady-state maps of the six-cylinder Diesel engine predicted by _Gasdyn_: (**a**) % error—BSFC; (**b**) % error—air mass flow rate; (**c**) % error—turbocharger Speed; (**d**) % error—turbine inlet temperature; (**e**) % error—turbine inlet pressure; (**f**) % error—cylinder peak pressure; (**g**) cylinder-out NOx concentration (non-dimensional); (**h**) cylinder-out experimental NOx concentration (non-dimensional).  
of the engine investigated, that part of the engine map is not frequently exploited, so that a reliable evaluation of fuel consumption is expected during an RDE test cycle.  
Considering further important engine parameters (Figure 10b-f), the percentage errors are very small and local distortions can be acceptable at the edge of the maps (typically due to interpolation issues). Finally, the calculated NOx emission map (Figure 10g) agrees with the corresponding measured trends and values (Figure 10h), represented in normalized form with respect to the maximum experimental value. The satisfactory comparison confirms the good set-up of the combustion model, being NOx formation dependent on the correct prediction of in-cylinder temperature and local air-to-fuel ratio. The most important result of this activity is that the engine model can be run across non-mapped conditions reflecting the behavior of the real engine. When the model runs in transient, interpolations are performed to set up the engine model exploiting the know values of the nearest mapped operating conditions parameters.
## 4 Results
### CTT Topic Precision Empirical Data  
The same algorithms were compared using real student data from the 2019 dataset (104 students) to measure their precision in selecting topics using classical test theory Figure 5. The figure presents the measured precision of suitable topic detection dependence on quiz length involving real students' results are presented as mean precision \(\pm\) standard error of the mean (SEM).  
The Elo-bandit has virtually the same performance as the UCB based algorithm in this application. Even though it breaches the 95% precision mark sooner, it lags in reaching 70% accuracy. Both of these algorithms offer about a 50% reduction in quiz length  
Figure 4: Formative assessment precision selecting items as a function of quiz length for synthetic students. Simulated data from 10 groups, taking 10 different quizzes, 120 students in each group.  
compared to classical testing methods when searching for the weakest topics. Enumerate and random algorithms perform similarly, enumerate having a better performance in medium quiz lengths.  
A more detailed look at the precision distribution for UCB and Elo-bandit algorithms for the 2019 dataset CCT model is presented in Figure 6.  
Both algorithms display very similar behavior. The Elo-bandit shows slightly fewer students with wildly incorrect, less than one percent precision, estimates at quiz lengths shorter than 30 questions. This is because UCB uses the average score to measure topic knowledge. This estimate overshoots real value with a low sample size, while Elo rating estimation approaches the final estimate more smoothly. However, UCB demonstrates fewer students in the 50-99% category past 30 question mark, because it uses the same mean score as the benchmark ground truth CCT measure. Therefore, given full information, it will always reach full agreement with the benchmark.
# Protecting Hybrid ITS Networks: A Comprehensive Security Approach
## 4 Experimental Evaluation and Results Analysis
### Network Latency  
Latency is an important performance indicator in communication. For this reason, this section assesses the latency of the developed hybrid network. To perform these tests, the round-trip time (RTT) was utilised. Figure 17 describes the adopted methodology.  
Figure 16: Performance impact of security protocols (DLAPP and MFSPV). The computation times are relative ratios to the respective ‘No Security’ task.  
Figure 17: Methodology for calculating the RTT in communications involving the cellular network.  
This methodology was used to calculate the communications latencies involving the cellular network segment. The timestamps (\(rtt\_ts_{start}\) and \(rtt\_ts_{end}\)) are used to calculate the transmission latency, as given by Equation (8).  
\[cl=\frac{RF-RI}{2} \tag{8}\]  
where:  
_cl_ -- latency measurement of a cellular network segment;  
_RI_ -- initial timestamp;  
_RF_ -- final timestamp.  
The above methodology was used in the calculation of latency of the following communication flows: (i) X \(\rightarrow\) Smartphone Y, (ii) Smartphone X \(\rightarrow\) RSU, (iii) M_RSU \(\rightarrow\) Smartphone X. A slightly different strategy was adopted to calculate the communication latency in G5 (between the P_RSU and OBU). Figure 18 illustrates the methodology used, while Equation (9) shows the latency calculation.  
\[gl=\frac{RF~{}-~{}RI}{2}~{}-~{}wl \tag{9}\]  
where:  
_gl_ -- latency measurement of G5 network segment;  
_RI_ -- initial timestamp;  
_RF_ -- final timestamp;  
_wl_ -- latency measurement of WSS communication (between the M_RSU and the P_RSU).  
The M_RSU was used to help extract G5 latency measurements. By eliminating the latency linked to WSS communication, the G5 transmission latency is calculated. In all conducted tests, \(\sim\)2000 latency samples were extracted, with a message transmitted once per second. Due to the occurrence of outliers, as illustrated in Figure 19, the median values are reported.  
Figure 18: Methodology for calculating latency in G5 communications.
# Image Mosaicing Applied on UAVs Survey
## 2 Panorama Generation
Optimal means that the parameter estimates are found by minimizing some cost function that quantifies the model fitting error and jointly that the solution is simultaneously optimal concerning both structure and camera variations [54]. This optimization problem is usually formulated as a nonlinear least squares problem, where the error is the squared \(L_{2}\) norm of the difference between the observed feature location and the projection of the corresponding 3D point on the image plane of the camera [55]. The image composition is the last stage, where, when the illumination and brightness of the images stitched may not be continuous, different algorithms can be applied to postprocess the image and blend the mosaic images as one. A method based on the use of gain compensation and multiband blending is proposed in [33]. Gain compensation adjusts the intensity of the mosaic by computing the local mean brightness of the image. Nevertheless, simply adjusting the gain to give all regions the same medium intensity will tend to reduce the intensity in regions with high brightness and increase the dark or low-intensity regions [56]. Multiband image blending  
Figure 2: Image acquisition: (**a**) multiple-camera translational and rotational acquisition; (**b**) single-camera rotational acquisition. is proposed in [57], and it is one of the most popular applications for image fusion due to its easy implementation and its advantage of being insensitive to misalignment. The basic idea of this process is to decompose the original image into a pyramidal representation and blend the images at each level [58; 59]. Another approach is presented in [60], with a variant of Gaussian function as the weighting function, and it proposes improved implementation and improvement of the weighted mean method to eliminate the edges.
## 8 Discussion
### Sensor Comparison
The pronounced peaks at the lower end of the intensity spectrum are characteristic of the dark background typical in starfield images. Moreover, the increased count of lower intensity values in subpayload 1's histogram compared to that of subpayload 2 conclusively shows subpayload 1's superior sensitivity to subtle light features. Subpayload 1 is equipped with a more refined detection capability for capturing faint astronomical phenomena, as expected. In terms of RSO detection, the PCO camera appeared to be far superior to the IDS camera. As per the results in Table 5, the PCO camera was able to capture over 20 times as many unique RSOs, while yielding more than 40 times as many RSO detections. This was despite the fact that the PCO camera had a narrower FOV and almost half as many images. However, this is expected, given that the PCO camera was selected for its low-light sensitivity and low-noise, and is an order of magnitude outlier than the IDS camera. It is important to note, however, that the RSOs detected by the IDS camera were determined by the onboard algorithm, rather than a comprehensive visual review of the original images, which is to be accomplished. Therefore, it can be expected that the IDS camera may have captured more RSOs but was limited by the algorithm's performance.
# Experimental Study on Shear Strengthening of RC Beams with an FRP Grid-PCM Reinforcement Layer
## 2 Experimental Study on Reinforcement Range
### Test Results and Discussion  
The crack patterns of beam specimens on ultimate states and the load-deflection (_P_-\(\delta\)) responses are indicated in Figures 6 and 7, respectively. Moreover, the PCM material was stripped off as completely as possible after the specimens were damaged to observe the failure modes of the CFRP grid. In Figure 6, the pictures on the right correspond to the marked areas on the specimens, showing the grid. The typical shear-compression failure, regarded as the main failure mode, appeared in strengthened beams.  
Figure 5: Schematic of specimens in Series A (Unit: mm): (**a**) Side view for strengthened beams (left side for RWC5, right side for RHWC5); (**b**) Front view for the reinforcement cage and the longitudinal section of the beam; (**c**) Front view for FRP grid area (left side for RWC5, right side for RHWC5).  
Figure 6: Crack patterns of strengthened beams: (**a**) RWC5; (**b**) RHWC5. The pictures on the right correspond to the marked areas (blue dashed rectangle) on the specimens, showing the grid.  
Figure 7: Load–deflection (_P_–\(\delta\)) responses.  
According to Figure 7, specimen RHWC5 is obviously better than the others in this series tests, no matter in ultimate capacity, second stiffness, or even displacement of peak load level. In detail, when compared to the specimen without reinforcement (i.e., N0), the ultimate load of specimens with reinforcement, i.e., the specimen RWC5 and RHWC5, are improved by approximately 17% and 33%, respectively. It can be concluded that the CFRP grid-PCM reinforcement layer proposed for the strengthening of concave concrete is effective. Moreover, for specimen RHWC5, the slope of the \(P\)-\(\delta\) relationship increases slightly and the ultimate load is increased by approximately 14% when the loading force is beyond 500 kN, in comparison with specimen RWC5. Therefore, better performance in both the second stiffness occurred and the ultimate load if an RC beam with an I-shaped profile is strengthened by CFRP grid-PCM layer along the web and haunch. On the other hand, the orthogonality failure of partial grids (red dashed rectangular pointed by an arrow) close to the critical shear cracks and the corresponding local debonding failure of PCM are shown in specimen RWC5, reconfirming that the strengthening approach for RC beam, which is externally bonded by the CFRP grid-PCM reinforcement layer along the web only, is not sufficient, in comparison with the web and haunch strengthening layer. It should be noted that the casting number of each type of beam was only one in this series; as a result, the disadvantages (e.g., the influence of a scatter range, the determination of the failure modes) caused by testing each configuration once are inevitable to some extent, but they are unlikely to deny the effectiveness of the results obtained with these beam specimens.
## 3 Experimental Results
Table 3 provides a comparison between the presented work with the previous literature and the proposed antenna design. The proposed antennas provide a wider tilted angle than [24,25,31,32,33], enhancing energy harvesting efficiency across a wider spatial range. Although the peak gains of the proposed beam-tilted antennas may not reach the levels achieved by the crank-line array in [32], the proposed designs have simple structures with compact sizes, streamlined structures, and more compact dimensions, rendering them advantageous for applications with spatial limitations like UAV. Furthermore, the proposed antennas provide CP compared with linear polarization (LP) works [21,24,25,31], with immunity to the polarization mismatch in diverse orientations. Refs. [22,26] were applied to WPT, with dual LP used to mitigate the decrease in transmission efficiency caused by polarization mismatches. However, this approach necessitates the use of two ports, and in the circuitry, a hybrid coupler [22] and two rectifiers [26] is employed for integration. In contrast to the array in [24], which offers a wider tilted angle, but at the expense of a larger and taller structure, proposed antennas achieve a balance between size and functionality, accommodating more radiating elements within a reduced antenna dimension. Hence, the \begin{table}
\begin{tabular}{c c c c c c} \hline  & **Impedance** & **AR Bandwidth** & **Gain at a Tilted** & **HPBW in \(\phi\) = 90\({}^{\circ}\)** & **AR 3-dB BW in \(\phi\)** \\  & **Bandwidth [GHz]** & **[GHz]** & **Angle [dBic]** & **Plane [deg]** & **= 90\({}^{\circ}\) Plane [deg]** \\ \hline \multirow{2}{*}{Broadside antenna} & 4.79\(\sim\)6.29 & 5.8\(\sim\)5.84 & \multirow{2}{*}{14.59} & \multirow{2}{*}{8.9} & \multirow{2}{*}{14.2} \\  & (27.1\%) & (1.03\%) & & & \\ \hline \(\theta\) = 15\({}^{\circ}\) beam-tilted & 5.62\(\sim\)6.28 & 5.78\(\sim\)5.84 & \multirow{2}{*}{13.09} & \multirow{2}{*}{11.2} & \multirow{2}{*}{24.3} \\ antenna & (11.1\%) & (1.03\%) & & & \\ \hline \(\theta\) = 30\({}^{\circ}\) beam-tilted & 5.59\(\sim\)6.05 & 5.78\(\sim\)5.83 & \multirow{2}{*}{12.07} & \multirow{2}{*}{13.3} & \multirow{2}{*}{18.5} \\ antenna & (7.9\%) & (0.86\%) & & & \\ \hline \(\theta\) = 45\({}^{\circ}\) beam-tilted & 5.52\(\sim\)5.88 & 5.79\(\sim\)5.84 & \multirow{2}{*}{10.71} & \multirow{2}{*}{16.5} & \multirow{2}{*}{15.9} \\ antenna & (6.3\%) & (0.86\%) & & & \\ \hline \end{tabular}
\end{table} 
Table 2: The measured impedance bandwidth, AR bandwidth, RHCP realized gain, HPBW, and AR 3-dB beamwidth of the proposed antennas at 5.84 GHz. Figure 18: Simulated and measured RHCP gains at each tilted angle and radiation efficiencies of the proposed antennas: (**a**) broadside antenna, (**b**) \(\theta\) = 15\({}^{\circ}\) beam-tilted antenna, (**c**) \(\theta\) = 30\({}^{\circ}\) beam-tilted antenna, and (**d**) \(\theta\) = 45\({}^{\circ}\) beam-tilted antenna. proposed antennas are a good candidate for designing linear arrays with reduced size, CP, moderate tilted-beam angle, and low profile.
###### Abstract  
Real-world datasets are heavily skewed where some classes are significantly outnumbered by the other classes. In these situations, machine learning algorithms fail to achieve substantial efficacy while predicting these underrepresented instances. To solve this problem, many variations of synthetic minority oversampling methods (SMOTE) have been proposed to balance datasets which deal with continuous features. However, for datasets with both nominal and continuous features, SMOTE-NC is the only SMOTE-based oversampling technique to balance the data. In this paper, we present a novel minority oversampling method, SMOTE-ENC (SMOTE--Encoded Nominal and Continuous), in which nominal features are encoded as numeric values and the difference between two such numeric values reflects the amount of change of association with the minority class. Our experiments show that classification models using the SMOTE-ENC method offer better prediction than models using SMOTE-NC when the dataset has a substantial number of nominal features and also when there is some association between the categorical features and the target class. Additionally, our proposed method addressed one of the major limitations of the SMOTE-NC algorithm. SMOTE-NC can be applied only on mixed datasets that have features consisting of both continuous and nominal features and cannot function if all the features of the dataset are nominal. Our novel method has been generalized to be applied to both mixed datasets and nominal-only datasets.  
SMOTE; nominal feature; continuous feature; class imbalance; precision; recall; area under receiver operating characteristic curve (ROC-AUC); area under precision-recall curve (PR-AUC)