esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Efficient Data-Balancing for CPS
### Optimal Distance Determination with Mid-Point Module  
Moreover, the arrangement of the actuators is vital and might influence the execution performance and coverage. Therefore, the actuators should cover the entire placed sensor nodes. As a result, a mid-point calculation is connected to adjust the correct position of the sensor nodes explained in Algorithm 1. Thus, the optimal number of actuators \(A_{opt}\) can be obtained as  
\[A_{opt}=\Bigg{\{}\sqrt{\frac{S_{n}}{2\pi}}\times\sqrt{\frac{FS_{e}}{MP_{e}}} \times\frac{A_{net}}{D_{avg}}\Bigg{\}}, \tag{6}\]  
where \(S_{n}\) is the number of the sensor nodes, \(FS_{e}\) is the amplifier energy of free space, \(MP_{e}\) is the multipath energy, \(A_{net}\) is the network area, and \(D_{avg}\) is the mean distance from actor to base station.  
```
0:\(r\) in Output:\(r_{\mathit{init}}\) out
1:Initialization:\(\{\gamma o\): Origin; \(\gamma e\): Each point; r: Distance; \(r_{\mathit{init}}\): Initial centroid distance; \(r_{s}\): Sorting distance\(\}\)
2:Determine\(r\) between \(\gamma o\) & \(\gamma e\)
3:Set\(r_{s}\) in ascending order
4:Separate the \(r\) into \(A_{\mathit{opt}}\) equal sets
5:if\(\mathit{midpoint}==r_{\mathit{init}}\)then
6:Set\(r_{\mathit{init}}\)
7:endif
```  
**Algorithm 1** Optimized distance determination from sensor node to actuator.  
Algorithm 1 separates the optimal number of actuators with respect to the clusters. Each cluster is headed by an actuator. The actuator broadcasts the packet to the sensors to form the cluster. The packet comprises the actuator's location and identity. On receipt of the packet, the sensor device acknowledges with its identity and residual energy. In existing approaches, when a sensor device receives a cluster formation message from more than one actuator, it chooses to join only the nearest actuator based on the location inserted in the packet. However, this cluster formation association increases the path length because it could be that the actuator is located far from the base station. Thus, avoiding back transmissions, an average midpoint of the optimal actuator algorithm is useful. If the sensors receive a higher received signal strength indicator (RSSI) from the base station compared to the actuator, then the sensor device should send data to the base station rather than the actuator.  
Similarly, the sensor can calculate the distance between itself and the base station, and then determine its midpoint. Based on the midpoint, the sensor decides to send the data either to the actuator or the base station, as depicted in Figure 3.  
The sensor node relates to Actuator-1 due to the receipt of a higher signal strength, but Actuator-1 is far from the base station compared to Actuator-2. As a result, additional energy is consumed, and the delay is extended. Thus, the proposed algorithm is applied to determine the midpoint to reduce the delay and improve the energy efficiency. Table 1 provides a description of used notations for the node selection and recruitment module.  
Figure 3: Average midpoint of the optimal actuator.
## 2 Guiding the Light
### Photonic Lanterns  
The concept of photonic lanterns emerged from the need to efficiently combine the light-capturing efficiency of MMFs and the light manipulation flexibility of SMFs [25]. A photonic lantern is essentiallya MMF adiabatically tapering into a set of SMFs, allowing a low-loss transition. For highest efficiency, the number of SMFs should be the same as number of modes supported in the MMF, but fewer SMFs could be used if the efficiency requirement is lower [26; 27]. The technology has since matured to lead to several variants. The key categories include: a) A MMF to a bundle of SMFs, with a demonstrated efficiency of \(\sim\)85-90% in the H-band [28; 29; 30]; b) a MMF to a multi-core fiber with an array of identical SMFs [29]; and c) an integrated photonic lantern, in which the transition from a multimode waveguide to many single-mode waveguides is inscribed in a glass block using ultra-fast laser inscription (ULI) [31; 32]. While initially produced in the J (1100-1300 nm) and H bands (1400-1700 nm), photonic lanterns are now being developed in the mid-infrared bands as well using femto-laser inscription [33].  
In addition to conveniently allowing single-mode functionality with the astronomical light, photonic lanterns also make it possible to reformat the beam in many ways by rearranging the output single-mode fibers (e.g., in a slit form or closed packing [27] ) for the next instruments in the pipeline (e.g., a diffraction-limited spectrograph or an interferometer) [34; 35; 36].
## 1 Introduction
### Major Contributions  
The major contributions of this paper are listed below.  
1. Transmission distances of up to 500 km have been used in this work and the corresponding nonlinear effects have been investigated.
2. The proposed system is analyzed through an analytical and simulation model. The characterization is presented through a mathematical model and an optimal design is proposed using frequency domain-multiple in multiple out (FD-MIMO) equalizer and microstrip medyshev low pass filter.
3. The parameters used for simulation analysis include channel spacing, nonlinear refractive index, fiber length, input power, and nonlinear dispersion, to ensure a comprehensive analysis.
4. The performance of the proposed model is quantified in terms of BER and OSNR, where these two parameters are achieved below \(10^{-9}\) and above 25, respectively.
5. FWM, XPM and SPM are reduced successfully till 500 km covered distance for channel spacing as low as 25 GHz and number of channels as much as 32.  
The OptiSystem software package, used in this work for simulation investigations, provides a library of multiple optical components that enables users to plan, test, and simulate different types of OTSs. The modeling of end-to-end downlink transmission system in this paper has been performed by the characterization of each component, careful investigation of interdependencies among different components, modeling of noise for active components in the system and other considerations to realize a practical OTN. The varying refractive index response and intrinsic group velocity delay for SMF, and DSP block are modeled in MATLAB and integrated with the optisystem.  
The remainder of this work is arranged as follows. Section 2 presents the proposed system model layout, followed by the description of analytical model in Section 3. Section 4 summarizes results and discussion of the presented system. Finally, the conclusion is presented in Section 5.
# Security Protection of 3D Models of Oblique Photography by Digital Watermarking and Data Encryption
## 5 Experimental Results and Analysis
### Analysis of Imperceptibility
#### 5.2.5 Comparison of Similar Algorithms  
As shown in Figure 8, the amplitude range of noise attacks is 0-1%. The algorithm of [PERSON] et al. [34] selects the distance from the point in the model to the center of the model as the embedding feature, so the image affected by noise attacks is larger. [PERSON] et al. [28] select the ratio between the triangular network lines approximately perpendicular to the ground as the watermark embedding feature. [PERSON] et al. [35] embed watermarks in 3D point cloud data based on redundant discrete wavelet transform and singular value decomposition of the matrix, which is robust to noise attacks. The algorithm of this paper selects the distance from the texture coordinate to the origin of the texture coordinate as the embedding feature for the texture coordinate watermark and performs hash mapping. The vertex coordinate watermark performs clustering on the point cloud before embedding, and extracts feature points from the clustered clusters. Therefore, its robustness against noise attacks is better than other algorithms. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{6}{c}{**Cropping Ratio**} \\ \cline{2-7}  & & **30\%** & **40\%** & **50\%** & **60\%** & **70\%** \\ \hline \multirow{3}{*}{M-1} & Vertex coordinates & 0.973275 & 0.973275 & 0.973275 & 0.978778 & 0.972987 \\ \cline{2-7}  & Texture coordinates & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-2} & - & 0.956968 & 0.951453 & 0.940324 & 0.894427 & 0.389943 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-3} & - & 1.0 & 1.0 & 1.0 & 0.994778 & 0.994778 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-4} & - & 0.9895285 & 0.989528 & 0.978945 & 0.978945 & 0.9574271 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-5} & - & 0.881917 & 0.881917 & 0.843274 & 0.843274 & 0.809663 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-6} & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-7} & - & 0.984140 & 0.984140 & 0.99477 & 0.962513 & 0.945905 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-8} & - & 0.827743 & 0.801314 & 0.801314 & 0.801314 & 0.801314 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-9} & - & 0.957947 & 0.946484 & 0.946484 & 0.935414 & 0.935414 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{M-10} & - & 1.0 & 0.973610 & 0.973610 & 0.973610 & 0.940965 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \multirow{3}{*}{Average} & - & 0.957151 & 0.9501721 & 0.945199 & 0.934644 & 0.876500 \\ \cline{2-7}  & - & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Normalized correlation coefficient after the clipping attack (ten sets of data).
## 1 Introduction
The traditional 3 \(\times\) 3 and 1 \(\times\) 1 convolution blocks in the U-Net encoder are replaced with residual (Res) modules. This deepens the network structure, alleviates the vanishing gradient problem, and effectively transfers features from one layer to the next, enabling the extraction of deeper semantic information. 2. The direct skip connections are replaced with an Edge Enhancement Attention Module (EEAM). This module enhances the extraction of contour and edge information of buildings by calculating the difference between positional features and original features, thus improving segmentation accuracy. 3. A hybrid loss function combining edge consistency loss and binary cross-entropy loss is proposed, tailored to the characteristics of building segmentation in remote sensing images. This function helps the model capture building contours of varying sizes and shapes, distinguish buildings from the environment and background, and enhance the performance of the segmentation network.
## 3 Experimental Setup
### Plasma System under Study  
The aim of this work is to spectroscopically characterize a pulsed, low-current direct discharge operated at atmospheric pressure. There are several commercially available systems on the market utilizing a more or less similar working principle [3; 10; 16; 61]. In this  
Figure 1: Rotational structure of a band sequence of the \((0,0)\)-transition of the \(B^{2}\Sigma_{u}^{+}\to X^{2}\Sigma_{g}^{+}\) system of \(N_{2}^{+}\) measured experimentally at peak current for the discharge operated at 60 kHz. Based on the calculated fit, a heavy particle temperature of 6300 K was estimated.  
work, the Plasmbrush(r) system consisting of a PG31 plasma generator and a PS2000 OEM power supply is used. This generator can be used for surface activation, decontamination or deposition of different materials [9; 10; 11; 15; 25].  
The PG31 generator has a conventional construction with a positively biased, finger-shaped non-refractory inner electrode and a copper alloy nozzle acting as cathode. A conical shaped nozzle of type A450 with an exit diameter of 4 mm is used exclusively for the experiments. Furthermore, pure nitrogen as well as a mixture of nitrogen and hydrogen of 99/1 vol. %, both at a flow rate of 35 L/min, are used as plasma carrier gases in the following, regulated externally by a mass flow controller of type 8626 produced by Burkert GmbH & Co. KG, Ingelfingen, Germany. The admixture of 1 vol. % of hydrogen is sufficient to achieve evaluable line intensities, but has no significant effect on the discharge. The discharge is driven by unipolar, triangular current pulses with an variable amplitude of maximal 1 A generated at the output of the PS2000 power supply. The power supply utilizes a single-phase full-bridge push-pull converter design with the rise and fall times of the triangular pulses fixed at 5 \(\upmu\)s, regardless of the selected pulse frequency. The power supply can be controlled via a PC software, which allows an adjustment of the output power between 70-100%, which corresponds to a current amplitude of 0.7-1.0 A at the exit, whereas the pulse frequency can be varied between 40 kHz and 65 kHz in 1 kHz steps.  
The generator is connected to the power supply by a 9 m long triaxial cable (similar to a coaxial cable, but with an additional conductive sheath), which serves as an additional high voltage capacitor by utilizing the properties of such a cable. The total cable length between PG31 and PS2000 is 10 m. For the experiments, the output power of the source was set to 100% and pulse frequency to 60 kHz. The typical voltage and current traces for these parameters are shown in Figure 2 and were measured as close to the discharge as possible, i.e. in the connection point between the high-voltage cable and the plasma generator. The energy delivered by the power supply during one discharge pulse averaged 11.1 \(\pm\) 0.9 mJ, resulting in an average power of 665 \(\pm\) 50 mJ.
## 10 Conclusions  
In this paper, we presented an improved version of the GN-AK key agreement protocol. The improvement was based on a new scalar multiplication algorithm using double-base chains and point halving in binary fields. The security level is the same as the original GN-AK, but the new protocol requires less computation and, therefore, is more efficient for constrained devices.  
The experimental evaluation conducted on an 8-bit AVR and a 32-bit Cortex-M4 platform shows that the improved GN-AK requires less computation than the original protocol because it replaces a point doubling with a point halving. The improvements in scalar multiplication are visible in execution time and energy consumption. However, we can further optimize the new scalar multiplication to support hardware implementations better.  
The security of the improved GN-AK relies on the hardness of the elliptic curve discrete logarithm problem (ECDLP), as the original GN-AK protocol does, and the changes do not alter the core cryptographic assumptions. While a complete formal verification and comprehensive side-channel analysis remain outside the scope of this work, the protocol design incorporates constant-time operations and avoids data-dependent branching, aiming to mitigate leakage vectors and enhance implementation-level resilience.  
In conclusion, this work is aligned with the current trends in lightweight cryptography, focusing on developing and optimizing cryptographic protocols for constrained devices. The practical applicability of the improved GN-AK protocol for secure key exchange is illustrated for some use cases, including IoT nodes, embedded control units, and mobile devices, highlighting its relevance and potential impact. Future work in this area may include expanding the support for different curves and further optimizing the new scalar multiplication for hardware implementations.  
[PERSON] investigated the ideas, formal analysis and provided a review; [PERSON] implemented the method and wrote the original draft of manuscript; I.D.H. provided the conceptualization, validation of the method, resources and funding support; [PERSON] and [PERSON] revised the draft of the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Lucian Blaga University of Sibiu through the research grant LBUS-IRG-2023.  
Not Applicable.  
The original contributions presented in the study are included in the article.  
The authors declare no conflicts of interest.
###### Abstract  
In this paper, we have proposed a filter-assisted self-coherent detection (FASCD) scheme that reconstructs the optical field of a dual-polarization complex-valued double-sideband (DP-CV-DSB) signal. At the receiver, the carrier is extracted using an optical bandpass filter (OBPF), and a pair of orthogonal carriers is constructed to achieve polarization-division multiplexing (PDM) by a Faraday rotator mirror (FRM). To address the issue of polarization crosstalk, channel estimation is performed using the least squares (LS) method, and the estimation results are further optimized through the intra-symbol frequency-domain averaging (ISFA) method. We demonstrate the system architecture and algorithms by simulation on a 224 Gbit/s 16-ary quadrature amplitude modulation DSB-PDM-OFDM system. The system performance is improved by 1 dB using the ISFA method.  
polarization-division multiplexing; digital signal processing; self-coherence detection; double-sideband (DSB) +
Footnote †: journal: _photonics_
# Compact Ultra-Wideband Series-Feed Microstrip Antenna Arrays for IoT Communications
## 2 Materials and Methods  
In this section the design of the antenna array is explained. Microstrip technology consists of a dielectric material covered in both surfaces by a conductive layer, normally of copper. In one side, typically fully covered, working as a ground plane, while in the other, only partially filled, where the transmission lines and other structures are designed. Microstrip structures were used in this work, because of their low cost of manufacturing and high versatility, and because the antennas built in such technology are compact, lightweight, and highly compatible with simple printed circuit boards [30].  
The substrate used was the Rogers RO4350B, with a dielectric constant \(\varepsilon_{\text{r}}\) of 3.48, loss tangent of tan \(\delta\) = 0.0026 and thickness of \(h\) = 0.762 mm.
# An RSSI-Based Localization, Path Planning and Computer Vision-Based Decision Making Robotic System
###### Abstract  
A robotic navigation system operates flawlessly under an adequate GPS signal range, whereas indoor navigation systems use the simultaneous localization and mapping system or other vision-based localization systems. The sensor used in indoor navigation systems is not suitable for low power and small scale robotic systems. The wireless area network transmitting devices have fixed transmission power, and the receivers get the different values of signal strength based on their surrounding environments. In the proposed method, the received signal strength index (RSSI) values of three fixed transmitter units are measured every 1.6 m in mesh format and analyzed by the classifiers, and robot position can be mapped in the indoor area. After navigation, the robot analyzes objects and detects and recognize human faces with the help of object recognition and facial recognition-based classification methods respectively. This robot detects the intruder with the current position in an indoor environment.  
RSSI navigation; random forest regression; object detection; facial detection Article
## 5 Experiments and Discussion  
A prototype of the designed structure was built and tested. A servomotor is applied to drive the spindle, and a photoelectric sensor was used to indicate the initial position. A six-axis motion controller (Model SMC-48, ADHON Tech Co., Ltd., Ningbo, Zhejiang, China) was applied to provide pulse signals to drive the spindle and the adjusting roller, and to actuate the electromagnetic valves. The initial position was adjusted using a cross-line laser level meter. The spools used for experiments were white spools with 20 kg wire-containing capacity, eight rib plates, and 300 mm outer diameter. The mechanical system was tested for its capability to adjust the spool position, and to load and clamp the spool. The camera employed was a common commercial camera with \(1280\times 720\) resolution. Illumination was obtained using an LED lamp fixed on top of the spindle box. The machine-vision-based method was validated on a computer with an Intel(R) Core (TM) i7-8700 CPU @ 3.20 GHz (Intel Corporation, Santa Clara, CA, USA), 16 GB RAM and Windows 10 64-bit OS (Version 1909, Microsoft Corporation, Redmond, WA, USA). Algorithms were coded and run on Matlab 2019a (Version 9.6, The MathWorks, Inc., Natick, MA, USA).
# Testing the Galileo High Accuracy Service User Terminal (HAUT) in Static Scenarios +
## 7 Informative Convergence Assessment by Galileo HAS User Terminal Using Galileo HAS Corrections  
A key matter for high-accuracy applications is convergence time. In this study, we have defined the convergence time as the time from warm start until the Galileo HAS User Terminal provides the first solution with the required instantaneous positioning accuracy below the specified threshold.  
A warm start assumes that the whole set of input broadcast data is already available at the receiver and in this way, the time to demodulate navigation data from SIS is excluded from the computation.  
To consider the converged position, a horizontal and vertical threshold must be defined. In this study, we have chosen two sets, the first being 15 cm and 20 cm, respectively. The second set is double these values, so 30 cm horizontal and 40 cm vertical.  
The set-up for the first campaign was repeated, but the Galileo HAS User Terminal was configured to execute 1 h automatic warm restarts. One-hour restarts allowed us to evaluate 24 restarts every day. The User Terminal convergence time using HAS Initial Service corrections was evaluated for a period of 30 days from 29 March to 27 April 2023. The overall statistics for convergence time are presented in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Date** & \begin{tabular}{c} **Vertical** \\ **Accuracy 68\% (cm)** \\ \end{tabular} & \begin{tabular}{c} **Horizontal** \\ **Accuracy 68\% (cm)** \\ \end{tabular} & \begin{tabular}{c} **Date** \\ **Accuracy 68\% (cm)** \\ \end{tabular} & \
\begin{tabular}{c} **Vertical** \\ **Accuracy 68\% (cm)** \\ \end{tabular} &
\begin{tabular}{c} **Horizontal** \\ **Accuracy 68\% (cm)** \\ \end{tabular} \\ \hline
02.25 & 2 & 2 & 03.13 & 2 & 3 \\ \hline
02.26 & 2 & 2 & 03.14 & 1 & 3 \\ \hline
02.27 & 2 & 1 & 03.15 & 1 & 3 \\ \hline
02.28 & 4 & 1 & 03.16 & 1 & 3 \\ \hline
03.01 & 6 & 2 & 03.17 & 1 & 3 \\ \hline
03.02 & 4 & 2 & 03.18 & 1 & 2 \\ \hline
03.03 & 3 & 2 & 03.19 & 1 & 2 \\ \hline
03.04 & 3 & 2 & 03.20 & 1 & 2 \\ \hline
03.05 & 2 & 2 & 03.21 & 1 & 2 \\ \hline
03.06 & 2 & 2 & 03.22 & 1 & 2 \\ \hline
03.07 & 2 & 1 & 03.23 & 1 & 2 \\ \hline
03.09 & 3 & 3 & 03.24 & 1 & 2 \\ \hline
03.10 & 5 & 4 & 03.25 & 1 & 2 \\ \hline
03.11 & 3 & 4 & 03.26 & 1 & 2 \\ \hline
03.12 & 2 & 3 & 03.27 & 1 & 2 \\ \hline \end{tabular}
\end{table}
Table 1: Real time Galileo HAS User Terminal horizontal and vertical HAS positioning accuracy (68%) over 24 h periods using Galileo E1-E5a, GPS L1-L2C and Galileo HAS Initial Service corrections over E6-B.