esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Simulation Results and Discussion
### Simulation of Flight Cruising in a Real Wind Field
#### 4.2.2 Comparison of Energy Generation
\begin{tabular}{l l} \(I_{th}\) & scattered radiation intensity, W/m\({}^{2}\) \\ \(I_{m,ij}\) & output current of PV module, A \\ \(I_{mp}\) & maximum power point current, A \\ \(I_{ph,ij}\) & photoelectric current of PV module, A \\ \(I_{ref}\) & short-circuit current under standard irradiance, A \\ \(I_{sc}\) & short circuit current, A \\ \(K_{air}\) & atmosphere thermal conductivity \\ \(m\) & number of cell units in the circumferential direction \\ \(n\) & number of cell units in the axial direction \\ \(\stackrel{{\rightarrow}}{{n}}_{ij}\) & unit normal vector of PV module \\ \(N_{r}\) & correction term of day number \\ \(\stackrel{{\rightarrow}}{{n}}_{s}\) & unit vector of solar direct radiation \\ \(Nu_{air}\) & free convection Nusselt number \\ \(p_{0}\) & atmospheric pressure and sea level, Pa \\ \(p_{h}\) & atmospheric pressure at the cruising altitude, Pa \\ \(P_{\rm mis}\) & mismatch loss power, kW \\ \(P_{PV,ij}\) & output power of PV module, W \\ \(q\) & electric charge, C \\ \(Q_{con,ij}\) & convective heat transfer energy, J \\ \(Q_{sun,ij}\) & total irradiance power of PV module, W \\ \(Q_{ir,ij}\) & infrared radiation energy, J \\ \(R\) & transformation from the airship coordinate system to the inertial coordinate system \\ \(r_{0}\) & radius of Earth \\ \(\mathrm{Re}_{air}\) & Reynolds number \\ \(R_{s}\) & series resistance of PV module \\ \(R_{sh}\) & parallel resistance of PV module \\ \(T_{air}\) & atmospheric temperature, K \\ \(T_{ref}\) & reference temperature, K \\ \(T_{ij}\) & operating temperature of PV module, K \\ \(V_{mp}\) & maximum power point voltage, V \\ \(V_{PV}\) & voltage of PV array, V \\ \(V_{\alpha c}\) & open circuit voltage, V \\ \(x\) & \(x\) coordinate in airship body reference system, m \\ \(y\) & \(y\) coordinate in airship body reference system, m \\ \(z\) & \(z\) coordinate in airship body reference system, m \\ \(\alpha_{ij}\) & angle between PV module and horizontal plane \\ \(\varepsilon_{e}\) & external emissivity of infrared radiation \\ \(\theta_{axi}\) & azimuth angle \\ \(\theta_{day}\) & solar day angle \\ \(\theta_{dec}\) & solar declination angle \\ \(\theta_{DIP}\) & angle of view \\ \(\theta_{de}\) & solar elevation angle \\ \(\theta_{hour}\) & solar hour angle \\ \(\psi\) & yaw angle \\ \(\varphi\) & pitch angle \\ \(\phi\) & roll angle \\ \(\Phi\) & local latitude \\ \(\eta_{t}\) & atmospheric transmissivity \\ \(\lambda_{e}\) & true anomaly \\ \(\delta\) & power temperature coefficient of PV module \\ \(\rho_{p}\) & areal density PV module, kg/m\({}^{2}\) \\ \(\sigma\) & Stefan-Boltzmann constant, J/K \\
**Abbreviation** & \\ BL & bridge-link \\ FF & fill factor \\ HC & honey-comb \\ HTCT & horizontal total-cross-tied \\ KCL & Kirchhoff's current law \\ \end{tabular}
## 4 System Performance Analysis and Discussions
As \(K\) also contributes to PIIN variance, a large \(K\) results in a large system BER. This effect is especially noticeable when the interference cancellations are executed at the initial stages, as the received signal contains many interference users. High-power noise induces a large probability that the value of the interference bit is misjudged, so the interference signals cannot be reconstructed correctly or eliminated. In the next RIC stage, these residual signals generating a relatively large amount of noise power still degrade the receiver performance. Based on Equation (11), effective user number \(K_{\text{eff}}\) is increased with \(K\), leading to the increased BER of the target signal. To keep the same BER for a large \(K\), reducing the signal data-rate or increasing the receiver stage number is required.
## 4 Simulation Results
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Scheme** & **Number of Sub-Time Slots** & **SDoF** \\ \hline time division multiple address (TDMA) & 3 & 4/3 \\ Alternate [2] & 3 & 5/3 \\ Extended methods e.g., & & \\ zero-forcing (ZF), methods in [5; 6; 10] & 3 & 2 \\ TPIA (proposed) & 2 & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Achievable SDoF comparison of different schemes. The Average rate of TPIA versus SNR under different amplification factors is shown in Figure 4. It is based on the assumption that the location of each user is invariable (i.e., in Table 1) and the channel is static during each transmission period. As can be seen from the figure, the achievable rate decreases with the increase in amplification factor. That is because the average rate increment at CEU is lower than the decrement at CCU, although both of the desired signal and interference (inter-cell and intra-cell interference) are enhanced by the relay. Figure 3: Average rate comparison under TPIA between cell-center user (CCU) and cell-edge user (CEU). Figure 2: Achievable sum-rate versus signal to noise ratio (SNR) comparison of different schemes.
## 3 Verification with Simulated Results
Figure 8: Waveforms of the output voltage with output voltage regulation capabilities for output frequency requirement: (**a**) one-half; (**b**) one-third; and (**c**) one-fourth. Figure 7: Harmonic factors of output voltage and input current for various output frequencies with respect to magnitude scaling factor (_k_): (**a**) one-half; (**b**) one-third; and (**c**) one-fourth. The 50% voltage amplitude adjustment in the selected half cycles of the output voltage deviates the sinusoidal characteristics of the input currents. The peak amplitude of all half cycles of the input currents, as shown in Figure 10, is unequal. Once there is a low peak output voltage, it results in low peaks in the output and input currents. This change in the peak values of the input currents generates low-frequency harmonics shown in the FFT spectral plots of Figure 11.  
There are two prominent harmonics in the spectrum of these currents. The harmonics present at 25 Hz and 75 Hz frequencies have their amplitude at approximately 30% and 18% of the fundamental component (50 Hz). They are responsible for their harmonic factor of 35%. In summary, it is concluded that a 15% to 20% improvement in the harmonic factor of the output voltage results in an increase of 30% to 35% in the harmonic factor of the input current. There is no way to improve the power quality of the output voltage through the pulse voltage adjustment approach for the output frequency, which is one-half the input frequency. The plot of the output voltage without pulse adjustment approach for previously addressed three output frequencies and their corresponding FFT plots are illustrated in Figures 12 and 13, respectively. Figure 9: FFT spectrum of the output voltage with output voltage regulation capabilities for output frequency requirement: (**a**) one-half; (**b**) one-third; and (**c**) one-fourth. Figure 11: FFT spectrum of the input current with output voltage regulation capabilities for output frequency requirement: (**a**) one-half; (**b**) one-third; and (**c**) one-fourth. Figure 10: Waveforms of the input current with output voltage regulation capabilities for output frequency requirement: (**a**) one-half; (**b**) one-third; and (**c**) one-fourth. Figure 12: Waveforms of the output voltage without output voltage regulation capabilities for output frequency requirement: (**a**) one-half; (**b**) one-third; and (**c**) one-fourth. Figure 13: FFT spectrum of the output voltage without output voltage regulation capabilities for output frequency requirement: (**a**) one-half; (**b**) one-third; (**c**) one-fourth. The investigation of these FFT results shows that although there is a slight increase in the harmonic factor of the output voltage, this approach helps retain the sinusoidal characteristics in the input currents (as described in Figure 14).
# Effects of an Inclined Blade on the Performance of a Sirocco Fan
## 1 Introduction
[14] performed a numerical study to investigate the influence of the design parameters of the diffuser in a small high-speed centrifugal fan, and the optimized model was derived based on the results. The main reason for the decrease in performance was the increasing pressure loss due to the reduced cross-sectional area between the vanes and the vortex flow in the center of the trailing edge in the vanes. [PERSON] et al. [15] investigated the performance of a centrifugal fan based on a flap-adjustment approach, compared with that based on leading-adjustment. [PERSON] et al. [16] studied the complex phenomenon of the interaction and instability caused by the motion of the rotating blades relative to the volute and their effect on the aeroacoustics behavior of the fan, based on the computational fluid dynamics (CFD) technique coupled with experimental investigation. [PERSON] [17] described the flow field of a centrifugal fan based on these assumptions, including the impeller rotating at a constant angular speed and the flow field in the impeller considered incompressible and inviscid. [PERSON] et al. [18] performed a numerical simulation of the generation of entropy; the results showed that reduction of entropy generation which improves the performance is caused by the reduced secondary flow vortex, wake jet, and angle of attack. [PERSON] et al. [19] performed a quantitative analysis on the influence of the inlet angle and the gap between the impeller and inlet on the performance of the fan. The results showed that the blade inlet angle and impeller clearance have an important impact on the performance of the fan. [PERSON] et al. [20] studied the slotting technology of a centrifugal fan blade with lateral suction side along blade pressure; the modification can effectively reduce blade surface resistance and increase lift force under suitable parameters, and control the stall of the flow passage of the centrifugal fan. The fluid flow in a centrifugal or Sirocco fan was also studied in a number of works [21; 22; 23; 24]. From the above review, it is concluded that the flow separation and complex vortex interaction in the impeller passage are the main sources affecting the aerodynamic performance of a fan. In this work, a numerical investigation is performed to modify the inclination angle of the blade to study the effect on the aerodynamic performance of a Sirocco fan. The reduction of flow separation the in impellers and the vortices evolved from the relatively low speed of the forward-curved blades are investigated. The paper is formulated in the following sections. Section 2 briefly describes the numerical simulation scheme and numerical simulation method. In Section 3, the numerical results for the performance of the fan are presented and discussed. Some conclusions are addressed in Section 4.
## 4 Conclusions  
The geopolymer mortar specimens with different amounts of PVA fibers in the presence of nanosilica particles at ambient temperature were developed. The main conclusions are as follows:  
* The fracture toughness K\({}_{\text{lc}}\) and CMOD values increased with the increasing amount of PVA fibers. The higher toughness value of 0.46 MPa m\({}^{1/2}\) was observed for the GP7 specimen. The higher strength is due to the bridging effect of fibers with the matrix.
* The compressive strength increased considerably in all the geopolymer mortar specimens with the addition of PVA fibers.
* The cyclic uniaxial compression response of the GP5 specimen showed better results for both single unloading/reloading and three unloading/reloading cycles. The 78.1% increase in peak load was noticed in relation to the GP0 specimen for the three unloading/reloading cycles scheme.
* The compressive strength degradation was observed in the geopolymer specimens when subjected to extreme temperatures. The greater the temperature, the greater the reduction in strength. Although at 800 \({}^{\circ}\)C, strength reduction in geopolymer specimens GP3, GP5, and GP7 was almost the same, but much lower than in GP0. For the freeze-thaw effect at a lower temperature (\(-25\)\({}^{\circ}\)C) the GP5 and GP7 specimens dropped strength by 4.18% and 5.1%, respectively.
* Bond strength increased with the increase of PVA fiber contents. Higher values of bond strength, i.e., 1.92 MPa and 3.03 MPa, were noted in the GP5 and GP7 specimens, respectively.  
Figure 17: Microstructural study: (**A**) FTIR spectra; (**B**) XRD.  
* Microstructural analysis showed that the PVA fibers and nanosilica synergistically improved the dense and compact matrix structure.  
Conceptualization, M.A.M., S.X., and Q.L.; formal analysis, M.A.M. and M.S.; investigation, M.A.M. and M.S.; methodology, M.A.M.; resources, S.X. and Q.L.; supervision, S.X. and Q.L.; writing--original draft, M.A.M.; writing--review & editing, M.A.M. and M.S.  
The authors gratefully acknowledge the financial supports provided by the Zhejiang Provincial Natural Science Foundation of China (No. LR16E080001) and the National Natural Science Foundation of China (No. 51878601). The authors thank the Zhejiang University for providing the facilities to carry out this work.  
The authors declare that they have no conflict of interest.
# Embedded Deep Learning for Ship Detection and Recognition
## 5 Experiment Results  
We use the recall-R and precision-P as the evaluation standard, defined as  
\[\text{R}=\text{TP}/(\text{TP}+\text{FN})\,,\text{P}=\text{TP}/(\text{TP}+\text{ FP}).\]  
TP refers to true positive, FN indicates false negative, and FP means false positive.
# A New Approach to Border Irregularity Assessment with Application in Skin Pathology
## 1 Introduction
The application of our algorithm is not limited to the field of skin pathology, it can easily be adjusted and used in pathological diagnostics of organs covered with the mucous membrane (e.g., gallbladder, intestine), in dermatoscopy (to assess border irregularity of melanocytic lesions [13]--a jagged lesion border is the hallmark of melanoma), as well as in cardiology (e.g., intravascular ultrasound (IVUS) contour detection for the diagnosis of coronary atherosclerosis [14], optical coherence tomography (OCT) image analysis for edge restenosis after stent implantation [15; 16], lumen segmentation method for intracoronary OCT [17; 18]). To the best of our knowledge it is the first method to measure morphometric parameters of individual border projections as well as the first one to show its application to analyze the epidermal morphometry in skin histopathological images. The main contributions of this paper are as follows:  
* we propose a new border irregularity assessment method which can be used in different applications, and
* we present an accurate algorithm for the detection of individual projections and for measuring their morphometry.
# Bearing Fault Identification Using Machine Learning and Adaptive Cascade Fault Observer
## 4 Adaptive Cascade Observer with Machine Learning for Fault Identification
### Adaptive Cascade Observer for Signal Estimation
Next, the residual signal is generated, and the energy features are extracted from residual signals for fault identification using machine learning.
## 2 Current Studies and Technologies for V2X Services  
This section relates the evolution of vehicles equipped either with IEEE 802.11 p or C-V2X wireless communication technologies for deploying V2X services. This section describes the V2X and C-V2X communications modes. A comparative study of existing architectures and a system model of LTE-V2X communication in the implementation of V2X services are detailed.
# Essential Features in a Theory of Context for Enabling Artificial General Intelligence
## 3 Research in Context-Rich Artificial Intelligence
### Explainable AI  
Explainable AI has witnessed a resurgence in the last 5-7 years [74; 75], both due to interest from the community and well-funded programs such as the Explainable AI (XAI) program that was instituted by the United States Defense Advanced Research Projects Agency (DARPA) in 2016 [76]. According to the program's website, its central goal is to 'produce more explainable models, while maintaining a high level of learning performance.' The definition of explainable AI is more straightforward and less controversial than commonsense reasoning, where agreement on a single definition and set of tasks has been lacking, although there has been convergence over the last two years.  
While the direct connection between explainable AI, and some of the other research areas such as knowledge graphs, representation learning and commonsense reasoning, is not fully evident, the argument is that any AI system that exhibits the kind of robustness that would be expected of human intelligence should have the capacity to explain itself [77]. For example, an explanation-capability ought to be a defining feature of a commonsense reasoner that is asked to provide a justification for an answer or action. Current language models that have achieved state-of-the-art performance in commonsense QA tasks do not seem to have this capability (at least in their current state), although recent work has made  
Figure 1: An example knowledge graph (KG) fragment from the Books domain.  
progress on this issue [78]. An advantage of an explanation-capability is that it makes the AI more trustworthy to non-developers and domain scientists who can probe the AI for the reasoning behind its decisions. Such a capability would be obviously critical in an HMI system deployed in the real world. The DARPA XAI program mentioned above also mentions as its the goal the development of a suite of machine learning techniques that 'enable human users to understand, appropriately trust, and effectively manage the emerging generation of artificially intelligent partners.'  
At least in part, an explainable AI can generate convincing explanations by leveraging its task-context and background knowledge, and by activating the elements in its background knowledge that are relevant in the context of the task. For example, when answering a question such as _why will not an elephant fit through my kitchen door_? the salient element that must be activated in the context of the question is _size_ since an elephant is too big to fit through the kitchen door. However, along with possessing such an activation capability, the AI must also have the requisite background knowledge about the _typical_ sizes of kitchen doors and elephants.
# Adaptive Age Estimation towards Imbalanced Datasets
## 4 Experiments
### Ablation Experiments  
To validate the effectiveness of three parts of the proposed method, ASL (adaptive soft label) and DDS (Data Density Smoothing), we compare different combinations of two parts with the baseline. We can see from Table 3 that SQINV, a loss reweighting method of classification imbalance, is ineffective and may even drag down model age-estimation accuracy. The results show that using DDS before the reweighting loss fuction (SQINV + DDS) is better than only using SQINV, which reduces the error by 24% for the Few shot region and continuously improve the performance of all regions. We can conclude that DDS provides comprehensive and fair treatment for all target values, and the imbalanced age estimation problem is significantly improved.  
It can also be observed from the experimental results that adding ASL to the baseline can reduce MAE from 2.88 to 2.75, which indicates that the adaptive soft label (ASL) is very  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metrics** & \multicolumn{4}{c}{**MAE \(\downarrow\)**} & \multicolumn{4}{c}{**GM \(\downarrow\)**} \\ \hline
**Shot** & **All** & **Many** & **Med.** & **Few** & **All** & **Many** & **Med.** & **Few** \\ \hline Baseline & 8.08 & 7.24 & 15.49 & 24.96 & 4.56 & 4.14 & 11.21 & 20.60 \\ SMOTER [45] & 8.14 & 7.42 & 14.15 & 25.28 & 4.64 & 4.30 & 9.05 & 19.46 \\ SMOSA [46] & 8.03 & 7.30 & 14.02 & 25.93 & 4.63 & 4.30 & 8.74 & 20.12 \\ RRT [18] & 7.81 & 7.07 & 14.06 & 25.13 & 4.35 & 4.03 & 8.91 & 16.96 \\ BMC [44] & 8.08 & 7.52 & 12.47 & 23.29 & - & - & - & - \\ GAI [44] & 8.12 & 7.58 & 12.27 & 23.05 & - & - & - & - \\ DIAAR & 7.79 & 7.20 & 12.78 & 23.38 & 4.30 & 4.14 & 7.35 & 13.35 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison experiment on IMDB-WIKI-DIR.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metrics** & \multicolumn{4}{c}{**MAE \(\downarrow\)**} & \multicolumn{4}{c}{**GM \(\downarrow\)**} \\ \hline
**Shot** & **All** & **Many** & **Med.** & **Few** & **All** & **Many** & **Med.** & **Few** \\ \hline ResNet50 [47] & 2.88 & 2.76 & 4.38 & 8.43 & 1.78 & 1.72 & 2.96 & 5.69 \\ ResNet50 + OURS & 2.66 & 2.51 & 4.34 & 7.40 & 1.62 & 1.54 & 3.04 & 5.12 \\ C3 AE [35] & 3.36 & 3.21 & 5.25 & 9.76 & 2.16 & 2.09 & 3.34 & 7.71 \\ C3 AE + OURS & 3.10 & 2.86 & 6.24 & 11.18 & 1.92 & 1.80 & 5.15 & 10.26 \\ SqueezeNet [48] & 3.32 & 3.14 & 5.87 & 10.36 & 2.08 & 1.99 & 4.43 & 9.28 \\ SqueezeNet + OURS & 3.09 & 2.86 & 5.90 & 11.06 & 1.92 & 1.82 & 4.39 & 10.07 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison experiment on Morph II-DIR.  
effective. Even if used alone, ASL is competitive among many methods of arrangement and combination, as shown in Table 3.  
Finally, it is shown in Table 3 that the combination of the two key operations proposed in this paper (SQINV + DDS + ASL) can achieve the best test error of 2.72 MAE. Overall, DIAAR has advantages in imbalanced age estimation.
# Recent Progress on Irradiation-Induced Defect Engineering of Two-Dimensional 2H-MoS2 Few Layers
## 2 Charged Particle Irradiation
### Swift-Heavy Ion Irradiation
#### 2.1.5 Manganese Ion Irradiation  
[PERSON] et al. [103] mechanically exfoliated natural bulk MoS\({}_{2}\) and deposited it on Si substrates covered with SiO\({}_{2}\). The exfoliated MoS\({}_{2}\) mono-layers were bombarded with Mn\({}^{+}\) (kinetic energy of 25 keV) with different ion doses (10\({}^{12}\)-10\({}^{14}\) ions/cm\({}^{2}\)) in a UHV. The resulting average inter-defect distance ranged from 1 nm to 10 nm. The generated defects activated new Raman modes around 227 cm\({}^{-1}\), broadened Raman peaks, and shifted Raman modes.