esa-sceva/satcom-chunk-collection huggingface dataset:
# Multilevel Regularization Method for Building Outlines
## 2 Materials and Methods
### Detailed Regularization and Enhancement of Parallel and Perpendicular Relationships
#### 2.4.1 Detailed Regularization
Therefore, the parallel and perpendicular relationships in the building outline must be enhanced to make them more realistic. In this study, we took the long side of the MBR of the building outline as the main direction and performed parallel and perpendicular enhancements. The specific steps are as follows:  
1. Calculate the MBR of the building outline and take one of its long sides as vector **a**. 2. Calculate the angles \(\theta\) between vectors **b** (consists of two neighboring nodes) and **a** in a counterclockwise direction, as described by Equation (9): \[\theta=180\times\frac{arccos\left(\frac{\overrightarrow{a}\times \overrightarrow{b}}{|\overrightarrow{a}|\times|\overrightarrow{b}|}\right)}{ \pi}\hskip 28.452756 pt(0\leq\theta\leq 180).\] (9)
3. Set a threshold \(\gamma\) to \(15^{\circ}\). If \(\theta\in(90-\gamma,90+\gamma)\), then the line segment is approximately perpendicular to the main direction, and the method shown in Figure 13a is applied. A line is drawn through the midpoint \(P_{m}\) of line segment \(P_{i}P_{i+1}\), perpendicular to the main direction. This line intersects the extensions of the two adjacent line segments at points \(P_{i}^{\prime}\) and \(P_{i+1}^{\prime}\). Replace \(P_{i}\) with \(P_{i}^{\prime}\) and \(P_{i+1}\) with \(P_{i+1}^{\prime}\). If \(\theta\in(180-\gamma,180)\) or \(\theta\in(0,\gamma)\), then the line segment is parallel to the main direction, and the method shown in Figure 13b is applied. After that, a line is drawn through the midpoint \(P_{n}\) of line segment \(P_{j}P_{j+1}\), parallel to the main direction. This line intersects the extensions of the adjacent two line segments at points \(P_{j}^{\prime}\) and \(P_{j+1}^{\prime}\). Replace \(P_{j}\) with \(P_{j}^{\prime}\) and \(P_{j+1}\) with \(P_{j+1}^{\prime}\). If the line segment is not parallel or perpendicular to the main direction, no further action is taken, as shown in Figure 13c. Figure 12: Schematics of detailed regularization. (**a**) Before regularization; (**b**) During regularization; (**c**) Result of regularization.
# Assessment of GNSS Galileo Contribution to the Modernization of CROPOS's Services
## 2 Materials and Methods  
### Crepos  
CROPOS as a system was established in December of 2008. At that time, the network consisted of 30 stations, evenly distributed across the national territory at an average distance between stations of 70 km, and of a control center located in the headquarters of the State Geodetic Administration (SGA) in Zagreb. Later, the network on the national territory was enlarged by 3 stations, bringing the total number of CROPOS stations to 33. In order to improve the reliability of corrections in the areas near the border with neighboring countries, an additional 18 stations from Slovenia (7 stations), Bosnia and Herzegovina (5 stations), Hungary (4 stations), and Montenegro (2 stations) were included in the networked solution and correction parameters calculation, bringing the number of stations currently included in the networked solution to 51 [25]. The operation of the system relies on the VRS concept. The Trimble's GNSS infrastructure installed in 2008 was providing support for GPS and GLONASS systems. Since its establishment, CROPOS has been widely accepted by the surveying community in Croatia, offering three services: DSP, VPPS, and GPPS. DSP service is based on the networked solution of code observations providing 0.5 m accuracy level, and it is used mainly for GIS applications. The VPPS service (network RTK) is the most used service of CROPOS, providing 2 cm for 2D accuracy and 4 cm for 3D accuracy [26]. The Geodetic Precise Positioning Service (GPPS) provides observation data in different RINEX and Trimble proprietary formats for post-processing. The data are available at CROPOS GNSS REFERENCE STATION WEB SERVER [27] to the subscribed users for 51 CORS stations or arbitrary VRS stations with the following logging rates: 1, 2, 5, 10, 15, 20, 30, and 60 s. The modernization of CROPOS started in 2018, and it was finished by the end of August 2019. Within the modernization project, all existing installed GNSS receivers and antennas were replaced by the latest Trimble GNSS receiver Alloy and the accompanying GNSS antenna Zephyr Geodetic III [28]. The control center software was upgraded to Trimble Vivot Platform 4.1, enabling the correction determination and service delivery based on GPS, GLONASS (GLO), and Galileo (GAL) systems. Several mount points were added to the VPPS service (e.g., CROPOS\(\_\)VRS\(\_\)GGG\(\_\)RTCM32), thus providing support for the Galileo system in RTCM 3.2 MSM format (Radio Technical Commission for Maritime (RTCM) Multiple Signal Messages (MSM)) [29]. Since the modernization, the GPPS service has provided observation data for all GNSSs in various RINEX format versions (2.10, 2.11, 3.02, 3.03, 3.04) as well as in Trimble proprietary formats (T01, T02). According to the latest legislation (Law on Amendments to the Law on State Survey and Real Estate Cadastre), since April of 2022, the DSP and VPPS services are free of charge [30].
## 4 Conclusions  
The results of this study revealed correlations between the topological features expressed by surface roughness and the wettability properties expressed by the contact angle of a liquid droplet placed on the surface of nanocomposite metal oxide films for a wide range of compositions. A direct relationship between the surface roughness and the value of the contact angle was found in nanocomposite films containing \(In\), \(Ga\), \(Mg\), \(Zn\), and \(Al\), such as (In\({}_{1-x}\)Ga\({}_{x}\))\({}_{2}\)O\({}_{3}\), (In\({}_{2}\)O\({}_{3}\))\({}_{1-x}\)(MgO)\({}_{x}\), Zn\({}_{1-x}\)Mg\({}_{x}\)O, and (Ga\({}_{1-x}\)Al\({}_{x}\))\({}_{2}\)O\({}_{3}\), for which both the surface roughness and the contact angle increase with the increasing \(\Omega\)\(x\)-value. An inverse relationship was found to be characteristic for films containing \(Sn\), such as ITO and (Ga\({}_{2}\)O\({}_{3}\))\({}_{1-x}\)(SnO\({}_{2}\))\({}_{k}\) films, in which the contact angle increases with the increasing \(Sn\) content, while their roughness decreases. An explanation was proposed for this behavior in terms of a combined effect of the surface roughness and the nature of chemical bonds, which is determined by the electronegativity of the metals contained in the films. These data are supposed to be relevant for a range of practical applications, specifically for microfluidic applications. A combination of wide bandgap with controlled topology and wettability of metal oxide films would extend their areas of application even further.  
Conceptualization, V.M., E.V.M. and V.V.U.; methodology, V.M., E.V.R. and E.V.M.; software, E.I.M. and V.V.U.; validation, E.V.M. and V.V.U.; formal analysis, E.V.R. and V.V.U.; investigation, V.M. and E.I.M.; resources, V.M. and E.V.M.; data curation, V.V.U. and E.V.M.; writing--original draft preparation, V.M., V.V.U. and E.V.M.; writing--review and editing, V.V.U., V.M. and E.V.M.; visualization, E.V.R. and V.V.U.; supervision, V.V.U.; project administration, E.V.R. and E.V.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Ministry of Education and Research from the Republic of Moldova, institutional subprogram #02.02.01 \"Nanostructures and advanced materials for applications in spintronics, thermoelectricity and optoelectronics\" and #02.04.02 \"Development of technologies and investigation of the properties of layered semiconductor compounds, hybrid nanostructures and laser sources\". Institutional financing contract no. 4/FI of 22 February 2024.  
Not applicable[PERSON]  
The data presented in this study are available on request from the corresponding author.  
V.M. and E.V.M. acknowledge support from the Alexander von Humboldt Foundation (Bonn, Germany).  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 2 Numerical Model
Dynamic mesh techniques are widely employed in fluid dynamic analyses of moving objects such as ships, aircraft, and cars, particularly in cases involving complex motions like rotation, translation, and deformation. In this paper, a combination of overset meshing and grid deformation methods was utilized to simulate the inclined and yaw motions of the submarine. The overset meshing approach was applied to handle the translational motion of the submarine, while grid deformation was used to address its rotational motion. Due to the high computational cost associated with dynamic meshing, only the initial stages of the submarine's motion were considered for the study, precluding simulations of the full-motion states [40; 41; 42; 43]. Numerical computations are based on Fluent software, where numerical simulations using the RNG \(k\)-\(\epsilon\) model have shown better agreement with experimental results in submarine motion. Therefore, in subsequent research, fluid numerical solutions are obtained by solving the Reynolds-averaged Navier-Stokes (RANS) equations closed with the RNG \(k\)-\(\epsilon\) turbulent model. Dynamic grid technology is applied during submarine yaw and heading movements, treating the entire hull as a rigid body controlled by a Six Degrees of Freedom (6 DOF) model for motion. Grid iteration updates are implemented using layering techniques. In numerical simulations, the water boundaries are set as Walls. It is assumed that the submersible moves within a very large enclosed water tank, with both the submersible itself and the boundaries of the water tank using no-slip boundary conditions. The entire study involves incompressible fluid flow assumptions. The wall function is the standard wall function. The calculation adopts the coupled algorithm based on the pressure solver. For the gradient discretization, a least squares cell-based approach is used; second-order discretization is applied for pressure, a second-order upwind condition is used for momentum, and a first-order implicit approach is used for transient formulation. The numerical calculations were performed using Fluent 16.0 software on a server with the following specifications: Dual Intel Platinum 8373C CPUs, operating at 2.6 GHz base frequency, with Turbo Boost up to 3.5 GHz, featuring 2 \(\times\) 36 cores and 2 \(\times\) 72 threads.
## 5 Results and Discussion
### Numerical Studies  
The modified MC simulations (Section 3.1) were executed for two-layered numerical media for the desired optical parameters and SRR was extracted from the locations which mimic the positions of detection fibers of the probe. The synthetic SRR data was then contaminated with 5% Gaussian noise. The data thus procured, mimics the experimental SRR measurement collected by the fabricated probe.
# Evolutionary Optimization for Robust Epipolar-Geometry Estimation and Outlier Detection
## 6 Conclusions  
In this study, we proposed an integer-coded genetic algorithm for the problem of accurate epipolar-geometry estimation from putative matches, followed by an adaptive thresholding algorithm for inlier classification. The proposed algorithm can be considered as a solution to resolve some of the drawbacks involved in conventional robust estimators, specifically RANSAC-like methods. Based on the experiments, the proposed approach showed robustness to high percentages of outliers, planar degeneracy and image noise. On a general note, the success of the proposed algorithm is due to a combination of elements: (i) the evolutionary behaviour of the search for outlier-free sample sets; (ii) the definition of the objective function to not depend on the maximum number of the inliers, but their minimum number; (iii) the integration of guided sampling and (iv) the uncertainty analysis in the final inlier classification scheme. It should be noted that, except for the first element, other ones could be easily integrated with different iterative robust estimation algorithms, as well. In the future, the proposed sampling and classification techniques will be integrated with the variants of RANSAC, and their improvement will be assessed. In general, the algorithm was able to detect the inliers by more than 85% accuracy, which is a remarkable success for large datasets containing over 80% outliers. Furthermore, the computational expenses of the algorithm were not increasing with either the ratio of outliers or the magnitude of image noise. The efficiency of the proposed algorithm regarding speed was greater than other methods for datasets with a high ratio of outliers (with more than 50% outliers). In the future, the algorithm could also become more robust to degeneracy by extending the proposed two-dimensional guided sampling to three dimensions by finding the probable three-dimensional structures. **Acknowledgments:** The authors gratefully acknowledge the substantive contributions of [PERSON] from Bonn University in reviewing and editing this manuscript and providing the authors with constructive comments. This study is supported in part by grants from the: Centre de Geomatique du Quebec (www.cgq.qc.ca), Fonds de Recherche Quebecois sur la Nature et les Technologies (www.frqnt.gouv.qc.ca) and Natural Sciences and Engineering Research Council of Canada (www.nserc-crsng.gc.ca). The authors would also like to acknowledge the provision of the datasets (the 12 th pair in Table 3) by ISPRS and EuroSDR, released in conjunction with the ISPRS scientific initiative 2014 and 2015, led by ISPRS ICWGKI/Vb, as well as the provision of the Downtown Toronto datasets (the 3D point cloud used to simulate the Urban dataset in Table 3 and the 11 th pair in Table 3) by Optech Inc., First Base Solutions Inc., GeoICTLab at York University and ISPRS WGIII/4.
## 3 Computer Simulation of PV Cell and Panel  
### Purpose of Computer Simulations  
As seen in Figure 1, the \(I\)-\(V\) and \(P\)-\(V\) curves show the potential output current and power of a PV cell under STC (\(\lambda\) = 1000 W/m\({}^{2}\), \(T_{c}\) = 25 \({}^{\circ}\)C and AM1.5). However, as the environmental conditions outdoors vary, so do the output current and power of PV cells. Hence, simulations are helpful in calculating the output performance under different ambient conditions than the STC.  
With the help of computer simulations, commonly carried out in MATLAB/Simulink or other mathematical programs, we are able to obtain information on how much PV energy we can produce with PV cells that are integrated into the surfaces of electric vehicles. Moreover, simulations can provide estimates on how much we can charge high-voltage batteries in parking conditions and prolong the ERE in driving conditions.  
As seen in Figure 1, a single PV cell provides only a certain level of output voltage (\(V_{out}\)) and output current (\(I_{out}\)). Hence, two PV cells are connected either in series to double the \(V_{out}\) or in parallel to double the \(I_{out}\). In this way, PV cells are connected with each other to form a PV panel. Commonly, in PV simulation models, series and parallel connections are considered by the factor \(N_{s}\) (number of PV cells in series) and \(N_{p}\) (number of PV cells in parallel). For a single PV cell, Ns and Np are equal to 1. Different interconnections do not change the shape of the \(I\)-\(V\) curve, but the scale of the \(x\)-axis (series connection) or \(y\)-axis (parallel connection).  
However, this assumption can only be made for a flat PV panel in which all PV cells, despite their type of interconnection, are aligned under the same angle towards the sun. Figures 2 and 3 show the curved shape of the roof of a Toyota Prius. The length of the roof area is about 168 cm, and the width is about 108 cm. If standard 156 mm \(\times\) 156 mm silicon-based PV cells are used, about 45 cells (nine rows with five cells in each row) can be integrated on the roof.  
It is worth noting that the rows of PV cells, from the hood to the rear of the vehicle, will be oriented towards the sun under different angles. Table 1 summarizes the longitudinal angles for rows 1-9. If the vehicle is parked in such a way that the windscreen faces the sun, then the PV cells in rows 1-5 will be oriented towards the sun, while in the rear of the  
Figure 2: Curved shape of the roof of a Toyota Prius.  
vehicle, the cells in rows 7-9 will face away from the sun. If the vehicle is turned around 180\({}^{\circ}\), then the rear of the vehicle will be oriented towards the sun, resulting in the opposite situation.
# Harmonic Detection Method Based on Parameter Optimization VMD-IWT Combined Noise Reduction
## 2 VMD Parameter Optimization and Wavelet Noise Reduction
### Optimize VMD Based on RIME
#### 2.2.4 Greedy Choice  
To enhance population diversity in the RIME algorithm, a greedy selection mechanism is designed to actively engage in population renewal. This mechanism compares the updated individual fitness value of rime with its value before the update. If the updated fitness value improves upon the previous value, the solutions of two rime individuals are replaced simultaneously. This process ensures that the population evolves in a better direction with each iteration.
# A Miniaturized Circularly-Polarized Antenna for In-Body Wireless Communications
## 5 Conclusions  
This article has numerically designed and experimentally studied a novel miniaturized single-fed circularly-polarized microstrip patch antenna at the ISM band of 2.40-2.48 GHz. By introducing reactive loading to form slow wave effect on the radiator and etching V-shaped slots on the main patch to lengthen the current flow path, a miniaturized antenna with the dimensions of 9.2 mm \(\times\) 9.2 mm \(\times\) 1.27 mm can be obtained. The radiations of the proposed antenna show a left-handed circular polarization when we adjust the sizes of geometrical structure. The prototype of the proposed implantable antenna has been implemented. The agreements between the simulated results and ex vivo measured ones have been reached.  
As illustrated in Table 3, the performance of the proposed antenna is not perfect. Whereas, a trade-off has been reached. Compared with [5], although the dimensions of the proposed antenna are bigger, its AR bandwidth is broadened. The proposed antenna has less efficiency than the work in [21], but it has smaller dimensions and bigger AR bandwidth; compared with the art [23], the proposed antenna has compact dimensions with higher AR bandwidth; compared with [27], the proposed antenna has much compact dimensions with high efficiency. Hence, based on the slow wave effect, this novel implantable CP antenna is designed and miniaturized with the advantages of great size reduction and high polarization purity. The merit performance of the proposed implantable antenna shows the great potential in the application of biomedical telemetry, such as subcutaneous real-time glucose monitoring.  
**Author Contributions:** [PERSON] and [PERSON] conceived the initial project; [PERSON] performed the design and experiment; [PERSON] verified the results; [PERSON] and [PERSON] prepared the original draft; [PERSON] answered the comments and modified the manuscript; [PERSON] reviewed the manuscript; [PERSON] supervised the project; all authors read and approved the final manuscript.  
**Funding:** This work was funded by the National Natural Science Foundation of China (No. 61372008), the Science and Technology Planning Project of Guangdong Province (Nos. 2014A010103014 and 2015B010101006), and the China Scholarship Council (No. 201706155018).  
**Acknowledgments:** The authors would also like to thank the anonymous reviewers for their valuable comments and suggestions in improving the quality of this paper.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Designing Dual-Function Nanostructures for Water Purification in Sunlight
## 4 Conclusions  
The current study has used the nanolayers of Zn-Al LDHs and the sheets of graphene oxide to produce well-designed nanostructures for improving the efficiency of water purification through a dual process. These nanostructures decreased the band gap energy of Zn-Al LDHs from 5.5 eV to become 2.5 eV by adding 1.3% of graphene oxide. However, the other percentages of graphene oxide have a minor effect on their composites. This narrowing of the band gap energy led to converting Zn-Al LDHs to be optical active material in sun light. Therefore, complete decolorization and mineralization of green dyes happened in short time by these nanostructures under solar energy. In addition, the kinetic study indicated that the reaction rate of photocatalytic degradation of green dyes was seven times higher than that of the pure Zn-Al LDHs. In the same time, these nanostructures showed another positive effect. The growth of the nanolayers of Zn-Al LDHs on the sheets of graphene oxide created micro- and meso-porous structures and increased their surface area from 5.6 to 60.3 m\({}^{2}\)/g. Therefore, these nanostructures improved the adsorption process of green dyes from 35% to 48%.  
According to our results, we concluded that not all LDHs based on graphene oxide are useful for water purification and active in sun light. It means that there are special requirements for these nanostructures to be useful for removal and solar degradation of industrial pollutants. They must have a limited and controlled percentage of graphene oxide to get three advantages; the first one is easy penetration of solar radiation inside the nanostructures, the second advantage is narrowing the band gap energy to act in visible region, and the third advantage is creating micro-and meso-porous  
Figure 15: Kinetic study of photocatalytic degradation of acid green 1 in presence of: (**a**) Zn-Al-GO1, (**b**) Zn-Al-GO2, (**c**) Zn-Al LDH and (**d**) Zn-Al-GO3.  
structures. In addition, the high conductivity of graphene oxide is considered an assistant factor for accelerating photocatalytic degradation of pollutants.  
Conceptualization, O.S.; methodology, O.S.; software, O.S.; validation, H.M.K. and O.S.; formal analysis, O.S. and H.M.K; investigation, O.S.; resources, O.S.; data curation, O.S.; writing--original draft preparation, O.S.; writing--review and editing, O.S.; visualization, O.S.; supervision, O.S.; project administration, O.S.; funding acquisition, O.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Deanship of Scientific Research in King Faisal University (Saudi Arabia), grant number 180079 and the APC was funded by the same grant number 180079.  
The authors acknowledge the Deanship of Scientific Research at King Faisal University for the financial support under the annual research project (Grant NO. 180079).  
The authors declare no conflict of interest.