esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The precision and accuracy of the final geometry in micro-parts is crucial, particularly for high-value-added metallic products. Micro-extrusion is one of the most promising processes for delivering high-precision micro-parts. The curving tendency observed in micro-extrusion parts is a major concern, significantly affecting the final part geometry. The purpose of this paper was to investigate the driving mechanism behind the curvature in micro-extrusion at room temperature. A finite element (FE) simulation was carried out to observe the influential primary factors: (1) grain size, (2) grain boundary, (3) grain orientation, and (4) bearing length of a 6063 aluminum alloy. The Extrusion Curvature Index (_ECI_) was also established to indicate the level of curvature in micro-extruded parts. The results showed that the grain boundary at the high strain and die opening area was the dominant factor for single-grain conditions. The interactive effects of the grain boundary and grain orientation also affected the curvature under single-grain conditions. If the number of grains across the specimen increased up to 2.7 (poly-grains), the curvature effect was dramatically reduced (the pins were straightened). For all conditions, the curvature in micro-extrusion could be eliminated by extending the bearing length up to the exit diameter length.  
aluminum alloy; curvature; grain size; micro-extrusion; finite element analysis Article
# The Latest Advances in Wireless Communication in Aviation, Wind Turbines and Bridges
## 4 WSN Systems in Different Applications: Aerospace, Bridge Structures, and Wind Turbines
### WSN in Wind Turbines
#### 4.3.5 SCADA versus IoT (Internet of Things)  
It is worth emphasizing the fact that the implementation of SCADA system is not considered by most people as as Internet of Things (IoT) or machine-to-machine (M2M) communication.  
What primarily differentiates SCADA and the IoT is the fact that, with traditional wireline SCADA, the internet is not involved. The PLC (programmable logic controller) is where the decision is made. In IoT, the internet is the basis. Data have to be transferred to a cloud-based server via the internet before a decision is undertaken and the control signal flows back over the internet to the sensor. The IoT architecture is less robust compared to traditional SCADA due to the fact that the required internet is not trustworthy. (This explains why the IoT does not control nuclear power plants!) [92].  
Data management is crucial for the day-to-day operations of a wind farm. Operating conditions, such as air temperature, wind speed, and direction, are collected individually for each turbine. Additionally, the power generated by each turbine is stored. All of those variables are reported in time intervals of several minutes. Therefore, in order to keep some information about the instability of the phenomenon, more than one value is stored for every measured variable for each time period. Those can be, for instance, the mean value, maximum, minimum, and standard deviation.  
Thus, when all turbines on a wind farm are taken into account for a longer period of time, the amount of data is significant. The information is available online for the day-to-day operation, but it is also essential to be stored and easily accessed for further analysis. Big data analysis can also help transform the wind farm management from the traditional reactive to predictive and proactive. Moreover, the data are useful for research purposes, such as developing more sophisticated and accurate wind farm models.
## 3 Results and Discussion
### Preparation and Characterization of Coated Paper  
The coated paper containing different amounts of clove essential oil, eugenol, and cinnamon aldehyde was prepared by casting emulsions on paper. The coated paper sheets (see Figure 4) were characterized using FT-IR spectroscopy. The FT-IR spectra of pure essential oils (CL, EU, CI), paper, and coated paper (C-CL, C-EU, C-CI) are presented in Figure 5.  
As can be seen in Figure 5a,b, the FT-IR spectra of CL and EU are uniform due to the composition of clove oil, which contains a substantial amount (40-90%) of eugenol [46]. The characteristic peaks (A) of EU at 1636, 1607, and 1512 cm\({}^{-1}\) were found to be attributed to the stretching C=C of the aromatic moiety [52]. Other peaks at 912, 816, and 795 cm\({}^{-1}\) were found from eugenol, which could be due to the presence of CH\({}_{2}\) deformation vibration, stretching vibration of the C-O bond, and bonding vibrations of C-H, respectively [53]. As can be seen in Figure 5c, the FT-IR spectra of CI showed a characteristic peak (B) at 1670 cm\({}^{-1}\), corresponding to the R-CHO stretching vibration. Furthermore, there were some peaks at 1450, 746, and 688 cm\({}^{-1}\), which can be attributed to the phenyl group of CI [53]. In the FT-IR spectra of the coated paper samples, the main characteristic peaks, A and B, can be attributed to CL, EU, and CI, respectively, which were also visible; however, these were at a lower intensity. In addition, the intensity of peaks was higher for the coatings with higher quantities of active substances. Meanwhile, the bands at 3290 and  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Microorganism**} & \multicolumn{2}{c}{**EM-CL-10**} & \multicolumn{2}{c}{**EM-EU-10**} & \multicolumn{2}{c}{**EM-CI-10**} \\ \cline{2-7}  & **MIC (mg/mL)** & **MBC (mg/mL)** & **MIC (mg/mL)** & **MBC (mg/mL)** & **MIC (mg/mL)** & **MBC (mg/mL)** \\ \hline _E. coli_ & 0.50 & 1.00 & 1.00 & 2.00 & 0.50 & 0.50 \\ _S. aureus_ & 0.50 & 4.00 & 0.125 & 2.00 & 0.25 & 0.50 \\ _L. monocytogenes_ & 0.50 & 2.00 & 1.00 & 2.00 & 0.25 & 0.50 \\ _B. cereus_ & 0.50 & - & 0.50 & - & 0.50 & 25.00 \\ _C. albicans_ & 1.00 & 2.00 & 0.50 & 1.00 & 0.125 & 0.25 \\ \hline \hline \end{tabular}
\end{table}
Table 4: MIC and MBC of emulsions containing 10% of CL, EU, or CI against different microorganisms.  
Figure 4: The coated paper sheets obtained using different emulsions.  
2895 cm\({}^{-1}\) in the spectra of the samples containing paper are assigned to the characteristic stretching vibrations of -OH and -CH\({}_{2}\) in cellulose, respectively.
## 3 Related Works
### OTP Mechanism
#### 3.2.3 Extraction Algorithm  
This is an algorithm that extracts three-byte or four-byte data from the encrypted bit string to use as the OTP. This can be divided into static algorithms and dynamic algorithms (RFC4226 [19], an OTP-related standard, only specifies dynamic algorithms; and the Telecommunication Technology Association (TTA) [17] specifies static, dynamic, and improved dynamic algorithms), and it uses an 'extraction index' to specify the extraction location. This algorithm uses the value at the extraction index as the 'extracted data'. The extraction index can use a value defined in a specific area of the ciphertext or an undefined value. After extracting three bytes, the hexadecimal value of the three bytes is converted to a decimal form for ease of human recognition. At this point, the range of the extracted 3-byte value is [0, 16,777,215] (i.e., [0, 2\({}^{24}-1\)]), but the upper two digits change little (\(10^{7}\): \(d_{7 th\ digit}\in\{0,1\}\), \(10^{6}\): \(d_{6 th\ digit}\in\{0,1,2,3,4,5,6\}\)), so they are discarded, and only the lower six digits are used. Therefore, the final range is [0, 999,999]. This process corresponds to the yellow part in Figure 1.  
The static algorithm extracts data by specifying in advance the extraction information (the offset of the cipher text) to be used. The dynamic algorithm extracts data by obtaining extraction information from the cipher text. The improved dynamic algorithm is used when generating OTP using a chip used as a smart card or USIM [17]. Figure 2 shows the extraction algorithms by type. It illustrates the operation of static, dynamic, and improved dynamic extraction algorithms in order, showing slight differences in their operations [1].
# Efficient Wireless Monitoring and Control of a Grid-Connected Photovoltaic System
###### Abstract  
The design, monitoring, and control of photovoltaic (PV) systems are complex tasks that are often handled together, and they are made even more difficult by introducing features such as real-time, sensor-based operation, wireless communication, and multiple sensor nodes. This paper proposes an integrated approach to handle these tasks, in order to achieve a system efficient in tracking the maximum power and injecting the energy from the PV modules to the grid in the correct way. Control is performed by means of an adaptive Lyapunov maximum power point tracking (MPPT) algorithm for the DC/DC converters and a proportional integral (PI) control for the inverters, which are applied to the system using low latency wireless technology. The system solution exploits a low-cost wireless multi-sensor architecture installed in each DC/DC converter and in each inverter and equipped with voltage, current, irradiance, and temperature sensors. A host node provides effective control, management, and coordination of two relatively independent wireless sensor systems. Experimental validation shows that the controllers ensure maximum power transfer to the grid, injecting low harmonic distortion current, thus guaranteeing the robustness and stability of the system. The results verified that the MPPT efficiency is over 99%, even under perturbations and using wireless communication. Moreover, the converters' efficiency remains high, i.e., for the DC/DC converter a mean value of 95.5% and for the inverter 93.3%.  
photovoltaic monitoring; smart grids; MPPT; low latency; wireless communication +
Footnote †: journal: Applied Sciences
## 2 Materials and Methods
### Governing Equations  
The governing equations are solved using the finite volume method within ANSYS Fluent 2024 R2. The volume of fluid (VOF) model is coupled with the energy equation and the Lee model to simulate interfacial evaporation-condensation. The pressure-based solver is employed with the PISO algorithm for transient simulations.  
The volume of fluid (VOF) model is applicable to the case where the sum of the volume fractions of all components is one in each computational cell. By defining the volume fraction of each phase, the movement of each phase can be tracked, and the interface between each phase can be determined; the VOF method is widely used to model two or more immiscible phases. It is also the preferred method in the literature for tracking the vapor-liquid interface.  
Continuity equation:  
\[\frac{\partial}{\partial t}(\alpha_{v}\rho_{v})+\
abla\cdot(\alpha_{v}\rho_{v} \mathbf{u}_{v})=S_{m} \tag{1}\]  
\[\frac{\partial}{\partial t}(\alpha_{l}\rho_{l})+\
abla\cdot(\alpha_{l}\rho_{l} \mathbf{u}_{l})=-S_{m} \tag{2}\]  
where \(\rho\) is the fluid density, \(\alpha\) is the volume fraction of the phase that satisfies \(\alpha_{v}+\alpha_{l}=1\), and the subscript \(v\) and \(l\) are the vapor and liquid, respectively. \(\mathbf{u}\) is the velocity vector. \(S_{m}\) is the source term of mass transfer between vapor and liquid phases.  
Momentum equation:  
\[\frac{\partial\Big{(}\rho\overset{\rightarrow}{u}\Big{)}}{\partial t}+\
abla \cdot\Big{(}\rho\overset{\rightarrow}{u}\overset{\rightarrow}{u}\Big{)}=- \
abla p+\rho g+\
abla\cdot\left[\mu\left(\
abla\overset{\rightarrow}{u}+ \
abla\overset{\rightarrow}{u}^{T}\right)\right]+\overset{\rightarrow}{F}_{CSF }+\overset{\rightarrow}{F}_{vol} \tag{3}\]  
\(\overset{\rightarrow}{F}_{CSF}\) is calculated by the continuum surface force (CSF) model:  
\[\overset{\rightarrow}{F}_{CSF}=2\sigma\frac{\alpha_{l}\rho_{l}C_{v}\
abla \alpha_{v}+\alpha_{v}\rho_{v}C_{l}\
abla\alpha_{l}}{\rho_{l}+\rho_{v}} \tag{4}\]  
where the surface tension coefficient is represented by the letter \(\sigma\), and the surface curvature is represented by the letters \(C_{v}\) and \(C_{l}\), respectively. \(\overset{\rightarrow}{F}_{vol}\) is the volume force because of sloshing.  
Energy equation:  
\[\frac{\partial(\rho E)}{\partial t}+\
abla\cdot\left(\rho\overset{\rightarrow }{u}E\right)=\
abla\cdot(\lambda\
abla T)+\text{S}_{h} \tag{5}\]  
\[E=\frac{\sum_{q=1}^{n}\alpha_{q}\rho_{q}E_{q}}{\sum_{q=1}^{n}\alpha_{q}\rho_{q}} \tag{6}\]  
\(E\) and \(T\) are the internal energy and temperature, respectively.  
\(\lambda\) is the thermal conductivity; \(\text{S}_{h}\) is the energy source term.
###### Abstract
[31] integrated TEM with the sampling approximation method (SAM) [32], demonstrating that the combined approach achieves higher numerical simulation precision in a small wavenumber range compared to SAM alone. Similarly, [PERSON] et al. [33] merged TEM with the minimax approximation method (MAM), showing that this integration enhances numerical accuracy in small wavenumber scenarios, outperforming MAM alone. In light of the superior accuracy of TEM in the small wavenumber range, various scholars have explored the integration of TEM with other numerical methods to compensate for the inherent limitations of original techniques in this specific range. [PERSON] et al. [31] combined TEM with the sampling approximation method (SAM) [32], with findings indicating that this hybrid method surpasses the numerical simulation accuracy of SAM when used alone in the small wavenumber spectrum. Similarly, [PERSON] et al. [33] integrated TEM with the minimax approximation method (MAM). Results from this collaboration reveal that the combined approach offers greater numerical accuracy than MAM alone within the same wavenumber range. However, these studies did not extend their comparisons to include the original TEM across different wavenumber ranges, leaving a gap in comprehensive evaluation. Given the high numerical precision of the least squares method (LSM) in the larger wavenumber ranges and its computational simplicity, this research proposes a novel integration of LSM with TEM to enhance the numerical accuracy of LSM in the small wavenumber range. Furthermore, as TEM is traditionally confined to a small wavenumber range, this integrated approach is also anticipated to bolster the capability to mitigate numerical artifacts across a larger wavenumber range. This paper is structured as follows: Initially, we outline the fundamental principles of the staggered grid finite difference method as applied to the acoustic wave equation. Subsequently, we detail the process of calculating FD coefficients using both TEM and LSM and describe the derivation of FD coefficients for the integrated method. We then present a comparative analysis of the numerical accuracy, frequency dispersion, and stability of the combined method against standalone TEM and LSM across small, medium, and large wavenumber ranges. Finally, we corroborate the effectiveness of the proposed method through both uniform and complex modeling tests, demonstrating its potential to improve the fidelity of acoustic wave simulations.
# Effect of Process Parameters on Mode Conversion in Submicron Tapered Silicon Ridge Waveguides
## 4 Conclusions  
In summary, the effect of ridge height, sidewall angle, and asymmetric cladding on mode conversion in a tapered submicron 500 nm SOI ridge waveguide is analyzed. The waveguide is highly asymmetrical in the vertical direction irrespective of top cladding (\(\rm{SiO_{2}}\) or air). Therefore, if the taper end widths lie in between the mode hybridization regions, then mode conversion between TM fundamental mode and higher-order TE modes can occur. This mode conversion in the submicron ridge waveguide is strongly dependent on the ridge height. The SOI ridge tapered waveguide with reduced etching depth has efficient mode conversion compared with deeply etched ones. Angled sidewalls and asymmetric cladding can further strengthen the mode hybridization and mode conversion. We demonstrate an 84.7% reduction in length for an efficient mode conversion with a low  
Figure 10: The mode conversion efficiency with (**a**) thickness variation due to fabrication (\(\rm{\theta=8^{0}}\)) (**b**) Sidewall angle (h = 200 nm) The and simulations are done at 1550 nm wavelength with \(\rm{n_{cl}}=1\) and \(\rm{L_{tp}=277\ \mu m}\).  
etched waveguide (\(8^{0}\) sidewalls) with air-top cladding. Such efficient mode conversion enables applications like compact polarization rotators/splitters. For general TM-type PICs, such mode conversions are not usually desired because it introduces excess loss and cross talk. It has also been shown that for such applications, PICs should be implemented using ultra-short non-adiabatic tapers designed with deep-etched ridge waveguides. This will ensure TM fundamental mode is maintained in the circuit. This work also shows that 97% efficient TM preserving taper can be designed with a deep-etched ridge waveguide.  
Conceptualization, Z.M.; methodology, Z.M.; software, Z.M. and B.P.; validation, Z.M., B.P. and M.R.; formal analysis, Z.M.; investigation, Z.M.; resources, M.R.; data curation, Z.M. and B.P.; writing--original draft preparation, Z.M.; writing--review and editing, Z.M., B.P. and M.R.; visualization, Z.M.; supervision, M.R.; project administration, M.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not Applicable.  
The authors declare no conflict of interest.
# Machine Learning-Based Methods for Enhancement of UAV-NOMA and D2D Cooperative Networks
## 4 ANN-Based Placement Scheme Selection
### ANN Model Selection
Among the evaluated ANNs, the neural network with two hidden layers ANN\({}_{8-32-31-2}\) achieves the best prediction result. The specific model yields a mean precision of 94.12%, a mean recall of 93.14%, and an average F1-score of 93.63%. Hence this level of accuracy in a balanced data set implies that the model has recognized and formed strong correlations between features and class and has avoided overfitting issues. Moreover, this success is related to the two-layered neural network's ability to effectively approximate nonlinear functions and reliably predict the PSS class value. Hence the ANN with two hidden layer is chosen to solve the PSS classification problem.
# Distributed Bragg Reflectors for GaN-Based Vertical-Cavity Surface-Emitting Lasers
## 4 Non-Epitaxial DBRs for GaN VCSELs
### Dielectric DBRs through Substrate Removal  
Nichia [20], Panasonic [83], and University of California, Santa Barbara (UCSB) [84], have demonstrated GaN VCSELs using a flip-chip method. In the flip-chip and substrate removal process, a dielectric DBR is firstly deposited on the as-grown surface side (or p-type side), followed by wafer bonding to a handling wafer. Substrate removal can be accomplished by laser-induced liftoff (LLO) [20], photoelectrochemical (PEC) etching of a sacrificial layer [84], wet/dry etching [85], or chemo-mechanical polishing (CMP) [86]. LLO was developed in 1999 [87] to separate GaN LEDs from a sapphire substrate  
Figure 7: (a) \(2\times 2\)\(\upmu\)m\({}^{2}\) atomic force microscope (AFM) image of a 45-pair n-type conducting AlInN/GaN DBR. (b) Measured and simulated reflectance spectra of the AlInN/GaN DBR. Reprinted from Ref [78; 79].  
with the back-side irradiation of an excimer laser. This method, however, does not work with GaN or Si substrates due to their opacity to the excimer laser, which is a serious limitation for VCSEL devices grown on bulk GaN substrates. Generally, substrate removal requires a follow-up polishing step to smoothen the surface and fine-tune the cavity thickness after layer separation. Achieving precise control of cavity thickness through polishing, with good uniformity across the entire wafer can be a challenging task. The use of a PEC approach has an advantage of precisely controlling the thickness of the microcavity through a bandgap-selective etching process [84]. A schematic drawing of an all-dielectric VCSEL device using the PEC method is shown in Figure 8. The dielectric DBRs could impede heat dissipation, and UCSB reported a very sophisticated method of heat sinking [88].
## 4 Security Analysis of the MAPP Protocol
### Security Requirement Analysis
#### 4.1.5 Unlinkability  
The proposed methods use pseudo-identity change to make it hard for an attacker to link the new pseudo-identity with the old one, which preserves both the identity and the location privacy. The previous V2X standards suffer from position tracking problems. Our methods, however, never disclose the vehicle's real identity, as the real identity is stored securely in the CA. Each pseudo-identity is composed of two parts--the first dynamic part is \(pid_{1}=h(Ri)\) with a random number \(Ri\) that changes with every transmitted message The second part is \(pid_{2}\) where a fixed value \(pid_{init}\) allows the CA to track the malicious vehicle, while the full pseudo-identity \(pid_{i}\) makes it hard to link two pseudo-identities.
# Phase Balancing and Reactive Power Support Services for Microgrids
## 2 Microgrid Architecture
### Energy Generation  
An important aspect for granting full autonomy to the MG during islanding conditions is the inclusion of DERs into the system. These can be separated into conventional and renewable generation units. The former includes a 100 kVA diesel generator (DG) which is located in Block J. Note that the DG is utilized here for accommodating the intermittent nature of the renewables and for re-synchronization purposes. The latter represents the existence of PVs on the top of each building with a total rated power of 63 kW peak (21 kW in each building).
# Practical Performance Assessment of Water Vapor Monitoring Using BDS PPP-B2b Service
## 3 Methodology  
This section detailly describes the methods used for the evaluation experiments, including the GNSS data processing and the following performance evaluation process. A general flow chart of this experiment is presented in Figure 2 as follows.