esa-sceva/satcom-chunk-collection huggingface dataset:
# A Quantum-Resistant FHE Framework for Privacy-Preserving Image Processing in the Cloud
## 6 Conclusions  
This paper effectively shows that high-performance, privacy-preserving computation and quantum-resistant security are no longer mutually exclusive. The proposed framework offers a practical framework for the upcoming generation of secure cloud services by cleverly combining CRYSTALS-Kyber for secure communication, an SIMD-optimized CKKS FHE scheme for computation, and crucial caching measures for efficiency. The outcome shows that our suggested work offers strong security against both classical and  
Figure 3: FHE trade-off: security vs. performance and data size.  
quantum adversaries while processing hundreds of pixels within milliseconds. Our thorough scalability analysis provides practitioners with measurable guidance, demonstrating that the framework's performance is practical for a wide range of image sizes. Based on specific threat models and operational constraints, well-informed decision-making is made possible by the clear connection between security criteria, resource requirements, and performance characteristics.  
Our framework provides post-quantum secure communication via CRYSTALS-Kyber-512 (IND-CCA2) combined with AES-GCM (AEAD), and ensures computational privacy through the CKKS FHE scheme under the Ring-LWE assumption (IND-CPA). It also offers side-channel resistance by relying on constant-time implementations and predictable memory access patterns. While operation types and timing patterns may still be visible to the server, future work will address these limitations through bootstrapping, dummy operations, and differential privacy techniques. The architecture remains crypto-agile, allowing Kyber to be replaced with other NIST-standardized post-quantum algorithms as they emerge.  
This work was supported by the personal research fund of Tokyo International University.  
The experimental data and implementation code supporting this research are available upon reasonable request from the corresponding author.  
The author declares no competing financial interest or personal relationships that could have influenced the work reported in this paper.
## 3 Numerical Application
### Configuration of Inspection  
The weld is inspected with a normal incidence \(\mathrm{OL0^{\circ}}\), where a probe is parallel to the flat and polished surface of the sample with a 20 mm water column height, as indicated in Figure 2. Two artificial Side-Drilled Holes (SDH) are vertically aligned in the middle of the weld at 10 mm (1) and 20 mm (2) depths and are of 1 mm diameter. The central axis of the array coincides with the alignment axis of the reflectors. The array operates around 5 MHz and is composed of 64 elements of 0.5 mm width with 0.6 mm pitch. Elements are excited with a Gaussian-type pulse with 80% bandwidth at \(-6\) dB and sampled at 100 MHz.  
The actual values of the 9 weld model parameters to be varied are indicated in Table 1. The base material is made of isotropic 316L stainless steel where longitudinal waves propagate with a phase velocity of \(5720\) m\(\cdot\)s\({}^{-1}\). Echoes are simulated in CIVA using the method of separation of variables [26], without accounting for attenuation.  
The TFM images are computed in a \(10\times 10\) mm\({}^{2}\) region composed \(51\times 101\) pixels around defect (1). The resolution in the imaging zone is approximati  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Elasticity** & **Values** & **Ogilvy’s Model** & **Values** \\ \hline \(C_{11}\) & 220 GPa & \(T_{1}=T_{2}\) & 1 A.U. \\ \(C_{13}\) & 150 GPa & \(D_{1}=D_{2}\) & 2 mm \\ \(C_{33}\) & 250 GPa & \(\alpha_{1}=\alpha_{2}\) & 20\({}^{\circ}\) \\ \(C_{55}\) & 105 GPa & \(\eta_{1}=\eta_{2}\) & 1 A.U. \\ \(\theta_{y}\) & \(-6^{\circ}\) & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Actual values of the 9 unknown parameters of the weld.  
Figure 2: Scheme of the numerical setup: immersion inspection using an array placed 20 mm above the surface; 316L stainless steel-based V-shape weld with two Side-Drilled Holes (SDH) of 1 mm diameter vertically aligned in the middle of the structure at depths 10 mm (1) and 20 mm (2) from the surface.  
axis and \(\lambda/10\) along the Z axis, where \(\lambda=1.14\) mm is the wavelength of a longitudinal wave emitted at 5 MHz and travelling at 5720 m\(\cdot\)s\({}^{-1}\).
# Energy-Efficient User Pairing for Downlink NOMA in Massive MIMO Networks
## 1 Introduction
### Contributions  
In this work, we solve the EE maximization problem for the downlink NOMA-based massive MIMO system; for short, it is named the NOMA-based scheme, through decoupling into the user pairing subproblem and fair power allocation subproblem to reduce complexity. Firstly, we study the energy efficient user pairing for zero forcing (ZF) beamforming. Then, we mathematically formulate the max-min EE into a non-convex fractional programming problem, which is transformed into a sequence of subtractive form, followed by the SCP approach to obtain the optimal solution. Different from [22], we study the performance of a massive MIMO system and its effect on power consumption calculations and power allocation solution. Additionally, we consider the max-min utility function for EE in the power allocation solution. Additionally, Ref. [23] introduced a matching-based framework to accomplish user association and subcarriers' assignment. The Gale-Shapley algorithm used in our work is a matching-based framework and is outperformed by the Hungarian algorithm, as is obvious from the results. The work in [24] gave two solutions for the fairness rate maximization problem. The first is based on relaxation and inner approximation and does not guarantee a globally optimal solution, whereas the second solution uses the channel correlation as the weights of edges on the bipartite graph for user pairing. Both of them are of high computational complexity, which leads to high power consumption. The main contributions in this paper are listed as follows:  
* We consider the evaluation of three different user-pairing approaches. Results are compared to obtain the optimal user pairing approach to maximize EE for downlink NOMA. We show how the pairing decisions affect the performance of the NOMA-based scheme.
* Propose a novel power allocation scheme based on the sequential convex programming (SCP) to iteratively update the power assignment vector that will eventually optimize EE.  
For comparison, the proposed algorithms are compared with the joint user-RB PA algorithm and NOMA-SCP-GA in terms of SE and EE. The remaining part of this paper is described as follows: In Section 2, the system model is described. In Section 3, the power consumption model for the downlink NOMA-based scheme is introduced. In Section 4, the different pairing approaches are discussed. Section 5 presents the proposed power allocation scheme. In Section 6, the complexity analysis is introduced. The simulation results are discussed in Section 7. Finally, the paper is concluded in Section 8.
## 3 Results and Discussion
### Penetration and Softening Point Test Results
ANOVA results that minimize the softening point after RTFOT using the \"smaller is better\" performance statistic are given in Table 11. At the 95% confidence level, the F values for all factors are greater than the F table value, which is 9.277 for (3.3). Furthermore, the model is statistically significant as all factors' \(p\)-values are below 0.05. The parameter that contributed the most to the softening point value of 77.082% was Cecabase ratio. This was followed by speed, time, and temperature, respectively. The optimum levels that minimize the softening point value after RTFOT were A3, B1, C4, and D2. The lowest softening point value in the experiment plan was 60.0 \({}^{\circ}\)C, representing a decrease of 1.397% compared to virgin bitumen. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Factors** & **DOF** & **Sums of Squares** & **Variance** & **F-Value** & **Pure Sum** & **Contribution** & \(p\)**-Value** \\ \hline Cecabase & 3 & 0.546 & 0.182 & 262.982 & 0.544 & 70.408\% & 0.0004 \\ Temperature & 3 & 0.120 & 0.040 & 57.982 & 0.118 & 15.523\% & 0.0037 \\ Time & 3 & 0.030 & 0.010 & 14.335 & 0.028 & 3.838\% & 0.0277 \\ Speed & 3 & 0.077 & 0.026 & 37.215 & 0.075 & 9.963\% & 0.0071 \\ \hline Error & 3 & 0.002 & 0.001 & & & 0.268\% & \\ \hline Total & 15 & 0.775 & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 10: ANOVA table for softening point before RTFOT. Figure 7: Performance statistics for softening point before RTFOT for all levels.
# Vibration-Based Fingerprint Algorithm for Structural Health Monitoring of Wind Turbine Blades
## 3 Algorithm
### Detection of Type 1 Vibrations  
As a first step, extracted peaks \(\hat{p}_{i,n}\) were analysed with regard to Type 1 vibrations, i.e., those peaks were identified, for which peak locations exhibited a low variation with the rotation frequency.  
Figure 6: Processing for an exemplary sensor with \(f_{s}=400\,\mathrm{Hz}\) and the rotation frequency \(f_{rot}\) selected as reference variable. **(Left)** Non-linear-scale spectrogram with \(L_{M}=1640\) single measurement campaigns. **(Middle)** Linear-scale spectrogram with linear grid of size \(L_{\mathrm{G}}=163\). **(Right)** Peak detection with \(N_{\hat{p},single}=15\) peaks per grid point, peak assignment to Type 1 vibrations (\(P_{v1}\)), noise (\(P_{noise}\)) and peaks used for detecting Type 2 vibrations (\(P_{v2}+P_{rem}\)) as discussed in the subsequent analysis. Colours of spectrograms corresponding to amplitudes on a logarithmic scale.
# Intelligent Recognition of Road Internal Void Using Ground-Penetrating Radar
###### Abstract  
Internal road voids can lead to decreased load-bearing capacity, which may result in sudden road collapse, posing threats to traffic safety. Three-dimensional ground-penetrating radar (3D GPR) detects internal road structures by transmitting high-frequency electromagnetic waves into the ground and receiving reflected waves. However, due to noise interference during detection, accurately identifying void areas based on GPR-collected images remains a significant challenge. Therefore, in order to more accurately detect and identify the void areas inside the road, this study proposes an intelligent recognition method for internal road voids based on 3D GPR. First, extensive data on internal road voids was collected using 3D GPR, and the GPR echo characteristics of void areas were analyzed. To address the issue of poor image quality in GPR images, a GPR image enhancement model integrating multi-frequency information was proposed by combining the Unet model, Multi-Head Cross Attention mechanism, and diffusion model. Finally, the intelligent recognition model and enhanced GPR images were used to achieve intelligent and accurate recognition of internal road voids, followed by engineering validation. The research results demonstrate that the proposed road internal void image enhancement model achieves significant improvements in both visual effects and quantitative evaluation metrics, while providing more effective void features for intelligent recognition models. This study offers technical support for precise decision making in road maintenance and ensuring safe road operations.  
ground-penetrating radar; void; Unet model; image enhancement; YOLO v8; intelligent recognition
## 6 Future Research Directions
### Automatic Target Detection under Scene-Tag-Supervision  
In many practical applications, it is not a simple task to label the accurate boundary of targets in the infrared imagery [106] or SAR imagery [107]. However, we can easily determine whether one image block (i.e., scene) contains the target of interest or not. Hence, training deep networks under scene-tag-supervision is a promising way to address many challenging target detection tasks (e.g., target detection from infrared imagery or SAR imagery).
###### Abstract  
Evaluation of the hydrophobic/hydrophilic interaction individually between the sorbent and target compounds in sample pretreatment is a big challenge. Herein, a smart titanium substrate with switchable surface wettability was fabricated and selected as the sorbent for the solution. The titanium wires and meshes were fabricated by simple hydrothermal etching and chemical modification so as to construct the superhydrophilic and superhydrophobic surfaces. The micro/nano hierarchical structures of the formed TiO\({}_{2}\) nanoparticles in situ on the surface of Ti substrates exhibited the switchable surface wettability. After UV irradiation for about 15.5 h, the superhydrophobic substrates became superhydrophilic. The morphologies and element composition of the wires were observed by SEM, EDS, and XRD, and their surface wetabilities were measured using the Ti mesh by contact angle goniometer. The pristine hydrophilic wire, the resulting superhydrophobic wire, and the UV-irradiated superhydrophilic wire were filled into a stainless tube as the sorbent instead of the sample loop of a six-port valve for on-line in-tube solid-phase microextraction. When employed in conjunction with HPLC, four kinds of wires were comparatively applied to extract six estrogens in water samples. The optimal conditions for the preconcentration and separation of target compounds were obtained with a sample volume of 60 mL, an injection rate of 2 mL/min, a desorption time of 2 min, and a mobile phase of acetonitrile/water (47/53, v/t). The results showed that both the superhydrophobic wire and UV-irradiated wire had the highest extraction efficiency for the polar compounds of estrogens with the enrichment factors in the range of 20-177, while the superhydrophobic wire exhibited the highest extraction efficiency for the non-polar compounds of five polycyclic aromatic hydrocarbons (PAHs). They demonstrated that extraction efficiency was mainly dependent on the surface wettability of the sorbent and the polarity of the target compounds, which was in accordance with the molecular theory of like dissolves like.  
titanium wire; superhydrophobic; in-tube solid-phase microextraction; high-performance liquid chromatography +
Footnote †: journal: _m molecules_  
Article
# Study on Drone Handover Methods Suitable for Multipath Interference Due to Obstacles
## 4 Proposal Method According to the Issue  
In this section, we propose two methods to solve these problems and demonstrate their effectiveness through simulation evaluation.  
**Proposed method #1:**: In the conventional method, a handover to a better-conditioned base station cannot be performed unless a beacon failure occurs. In proposed method #1, the handover decision is based on a SINR threshold instead of beacon reception. The proposed method solves this problem by actively performing handovers from an AP with a low transmission rate to another AP with good conditions.
**Proposed method #2:**: Since proposed method #1 performs handover aggressively, if a connection is attempted with a base station whose reception power is momentarily high due to the influence of buildings, etc., the reception power drops immediately and handover is performed again immediately, which increases the number of handover attempts. To solve this problem, the number of handover attempts can be reduced by eliminating base stations with instantaneously high received power from handover candidates by acquiring a moving average with reference to the past received power.
## 3 Results and Discussion  
Figure 4 details the fabricated resonator and its characterization. Figure 4 reports an optical microscope top-view of the fabricated device. The resonator structure is analyzed through its SEM cross-section (Figure 4b), illustrating the successful release of the membrane without affecting the other materials of the stack. The measured layer thicknesses are 185 nm for the interlayer, 226 nm for the molybdenum, 1.4 um for the aluminum nitride, and 190 nm for the aluminum. According to the Monte Carlo assumptions, these values fall within the acceptable error range (the maximum error equals 5%, while the experimental error is 3%). The device has two ports corresponding to the top and bottom electrodes. It is characterized using Vector Network Analyzer (VNA, Anristu MS46122B, Morgan Hill, CA, USA) and Ground Signal Ground (GSG) probes (Form Factor, Z-Probe-Coaxial, Livermore, CA, USA). Figure 4c shows the modulus and the phase of the impedance of the resonator. As it can be noted, the operating frequency is equal to 2.545 GHz; indeed, it is within the confidence interval estimated by the Monte Carlo simulation in Section 3.  
Figure 3: Fabrication protocol of the FBAR on the flexible membrane using an organic LOR sacrificial layer. (**a**) Patterning of the sacrificial layer, (**b**) covering with the protection layer, (**c**) patterning of the bottom electrode, (**d**) patterning of the piezoelectric layer, (**e**) patterning of the top-electrode, and (**f**) etching of the protection layer and releasing of the structure.  
Table 2 compares the design tool with the method already present in the literature. In addition, it reports a comparison of the proposed resonator to the state-of-the-art Quality factor (\(Q\)), Electromechanical coupling factor (\(k_{eff}^{2}\)), and Figure of Merit (_F.O.M_) parameters.  
It can be noted that with this approach, the computational costs can be drastically contained without affecting the relative error. Indeed, unlike other design processes based on FEM models, the use of calibration curves ensures faster and more lightweight simulation processes despite a contained relative error. The use of this approach makes the method highly scalable as new information can be easily added in the form of curves. In addition to the state-of-the-art, the very low computational cost allows the inclusion of fabrication tolerances exploiting Monte Carlo Simulations. Finally, thanks to the proposed fabrication protocol, the FBARs can be obtained with a very fast and straightforward process with the highest product between Q-factor and \(k_{eff}^{2}\).
## 4 Environment Perception, Mapping, and Representation for Locomotion
### Sensor Technologies for Environment Perception for Navigation in Robotics
A clear distinction can be made between methods that perform a temporal coding (which require a sequence of patters that are successively projected onto the scene) versus spatial coding methods which concentrate all the coding scheme in a unique pattern. Following some rather extended nomenclature, we denote temporal coding methods just by _structured light_, and spatial methods by _light coding_[79]. Light coding methods have been popularized in the last years by the introduction of low-cost devices in the consumer market, such as the Microsoft Kinect. Those devices are also often referred to as RGB-D cameras. Despite the name, most commercially available time-of-flight cameras (_To camera_) [80] operate by measuring the phase shift of the modulated infrared signal bounced back. The main difference with respect to LiDAR systems is that in ToF cameras the whole scene is captured with each pulse, as opposed to one-point measurements in the case of LiDARs. ToF cameras can provide 3D measurements at high rates, but at the cost of low resolutions and accuracies in the range of a few centimetres. Referring to passive 3D imaging techniques, _stereovision_[81] consists of two calibrated cameras that acquire images of a scene from two different viewpoints. Calibration involves both the optical characteristics of the cameras, but also the relative position and orientation between them. Points in the scene need to be recognized or matched across the images from the two cameras, and then their position is triangulated to calculate the depth. Stereovision methods can be classified as sparse or dense, according to the nature of the point cloud generated: sparse methods select certain interest points from the images to be triangulated, while dense methods operate on a per-pixel basis. A single camera can also be used to recover the 3D structure of an environment: structure from motion (_SfM_) [82] or visual SLAM (_vSLAM_) [83] methods use different images from a moving camera (or images taken from  
Figure 6: A taxonomy of sensors for environment perception for navigation in robotics. different viewpoints) to simultaneously estimate the positions from where the images were taken and the 3D structure of the environment.
# Improving the Quality of Laser-Welded Butt Joints of Metal-Polymer Sandwich Composites
###### Abstract  
Sandwich panels are promising composite materials, although the possibilities for their thermal joining are limited due to the degradation of the polymer core at elevated temperatures. The purpose of this study is to improve the quality of the but joints in metal-polymer sandwich composites performed by laser welding. A pulsed Nd:YAG Rofin StarWeld Performance laser was used to perform the two-sided welding of the metal-polymer three-layer composite material. On each of the two sides of the material, a welded joint was made with partial penetration of the covering steel sheets, which was considered a prerequisite for preventing the degradation of the core polymer layer. The energy density of the laser irradiation was redistributed by increasing the diameter of the laser spot. The structure of the welded joints was examined using a polarized optical microscope and a scanning electron microscope. It was determined that the laser treatment resulted in a partial penetration weld on each of the two covering metal sheets of the material, reaching a depth of more than 50% of the sheet's thickness without damaging the polymer. The welding area consisted of two zones, one being the weld metal and the other the heat-affected zone. As a result of relatively rapid heating and cooling cycles, fine-dispersed structures were formed in the heat-affected and remelted zones. The performed tensile tests showed that the strength of the welded area was about 80% of that of the base material.  
metal-polymer; sandwich composites; laser welding; butt joint; partial penetration; microstructure +
Footnote †: journal:  
0000-0001-999-2270][PERSON] 1  
1 TU Wien, Karlsplatz 13, 1040 Vienna, Austria; [EMAIL_ADDRESS]  
3 Institute of Metallurgy (IMET), Clauthasl University of Technology, 38678 Clauthasl-Zellerfeld, Germany 3
# Convolutional Neural Network Architecture for Recovering Watermark Synchronization
###### Abstract  
In this paper, we propose a convolutional neural network-based template architecture that compensates for the disadvantages of existing watermarking techniques that are vulnerable to geometric distortion. The proposed template consists of a template generation network, a template extraction network, and a template matching network. The template generation network generates a template in the form of noise and the template is inserted into certain pre-defined spatial locations of the image. The extraction network detects spatial locations where the template is inserted in the image. Finally, the template matching network estimates the parameters of the geometric distortion by comparing the shape of spatial locations where the template was inserted with the locations where the template was detected. It is possible to recover an image in its original geometrical form using the estimated parameters, and as a result, watermarks applied using existing watermarking techniques that are vulnerable to geometric distortion can be decoded normally.  
Keywords:digital watermark; depth-image-based rendering; copyright protection; template watermark; deep neural network +
Footnote †: journal: Accepted: 17 September 2020; Published: 22 September 2020