esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experiments on a Reduced-Scale Laboratory Bench
### Results
#### 2.4.1 Influence of the Current Intensity  
In a previous study carried out by the SNCF under railway conditions (i.e., at scale one), it was observed that the highest track circuit current intensities caused an irreversible modification of the electrical behaviour of the wheel-rail interface (for the usual frequency of 2300 Hz). We therefore sought to reproduce this effect on the bench. In order to achieve this goal, for the same frequency of 2300 Hz, we first imposed current intensities of 1.25, 3.7, and 5.2 A before applying a maximum intensity of 6.3 A; finally, the initial intensities were applied again. The corresponding characteristics are presented in Figure 3. The curve relating to the maximum current is plotted with black symbols, while the curves relating to the other currents are plotted with coloured symbols--blue before the maximum current is imposed, and red after. We can see first that all of the curves are nonlinear, which was also observed during tests at scale one as soon as the current was higher than 1 A. But we can see above all that, whatever the current applied, the curves obtained after the maximum current intensity sequence are superimposed on the characteristic relating to the latter. This attests to an irreversible modification of the interface by the highest current intensity.  
Figure 2: Principle of the electrical contact resistance measurement the by four-probe method; on the (**left side**), intentionally rusted surfaces; on the (**right side**), “clean” reference surfaces. Black arrows represent copper brushes for measurements of current feeding (**bottom**) and contact voltages (U\({}_{1}\) and U\({}_{2}\)).
## 2 Numerical Simulation
### Monitoring Point Setup  
In order to analyze the pattern of pressure pulsation changes, monitoring points Y1 and Y2 are arranged in the secondary impeller runners near the central position of the inlet and outlet area, and monitoring points Y3 and Y4 are arranged in the secondary space guide runners near the central position of the inlet and outlet area, as shown in Figure 4.  
To make the calculation more practical and general, the dimensionless pressure pulsation coefficient \(C_{P}\) is introduced and calculated as follows:  
\[C_{P}=\frac{p-\overline{p}}{\frac{1}{2}\rho u_{2}} \tag{12}\]  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Program Number** &
\begin{tabular}{c} **Number of Full** \\ **Runner Grids (pc)** \\ \end{tabular} & **Relative Head** & **Relative Efficiency** \\ \hline
1 & 1,103,596 & 1.0152 & 1.0123 \\
2 & 2,563,487 & 1.0000 & 1.0000 \\
3 & 4,016,349 & 0.9956 & 0.9963 \\
4 & 5,538,964 & 0.9931 & 0.9946 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Grid independence analysis.  
Figure 4: Layout of monitoring points. (**a**) Impeller; (**b**) space guide leaf.  
where \(p\) indicates the pressure value at the position of the monitoring point at a certain moment, \(\overline{p}\) indicates the average value of the pressure at the monitoring point during a cycle, \(\rho\) indicates the density of the medium conveyed by the pump, and \(u_{2}\) indicates the impeller outlet circumferential velocity.
## 3 Maintenance and Lifespan Management
### Advanced Decision-Making Systems
#### 3.3.1 Power System Infrastructure  
AI has been used continuously for a great amount of time, as reported by [PERSON] and [PERSON] (2007). Therefore, and following with [PERSON] et al. (2008), expert systems can serve for maintenance and decision making, since they can learn from the alarms received. In this sense, [PERSON] (2009) uses expert systems to detect vulnerabilities in automated systems, which allows a more efficient and controlled system.  
It is possible to detect variations in the network from the data received using symbolic aggregate approximation (SAX) and pattern recognition, as defined by [PERSON] et al. (2010). [PERSON] et al. (2011) implement an S-transform algorithm for the detection and monitoring of overvoltage.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{\begin{tabular}{c} **Summary of Maintenance Based** \\ **on Asset Lifecycle Management** \\ \end{tabular} } & \multicolumn{2}{c}{**Maintenance and Lifespan Management: Maintenance**} \\ \cline{2-3}  & **Based on Asset Lifecycle Management** \\ \cline{2-3}  & **Artificial Intelligence** & **Other Techniques** \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} **Asset Management and** \\ **Monitoring** \\ \end{tabular} } & [193; 194; 195] & [196; 197] \\ \hline \multirow{2}{*}{
\begin{tabular}{c} **Maintenance and Risk** \\ **Management** \\ \end{tabular} } & [199; 200; 206] & [198; 201; 205] \\ \hline \hline \end{tabular}
\end{table}
Table 8: Summary of Maintenance based on Asset Lifecycle Management.
## 3 Image-Motion Compensation Technique of the Secondary Mirror Motion
### Aberration Field Constant Technique  
The catadioptric optical system typically consists of a two-mirror telescope system and a correction lens. In this optical system, the two-mirror telescope system adopts a Cassegrain structure, and the correction lens adopts a combination of single lenses and a double-glued lens. Considering the universality and applicability of modeling, this paper takes the Cassegrain optical system with aperture stop on the primary mirror as the research object of the secondary mirror for image-motion compensation. During the process of compensating for image motion, the secondary mirror is inevitably eccentric and tilted, resulting in the secondary mirror being off-axis. Once the secondary mirror is off-axis, the optical system loses the original symmetry of the optical system, so the traditional aberration model is no longer applicable and the vector aberration theory must be introduced [12; 13].
## 3 AI Techniques and Their Applications
### Deep Learning Techniques
#### 3.2.2 Semantic and Instance Segmentation  
For a more granular interpretation of GPR data, semantic segmentation models have emerged as powerful tools by which to classify each pixel or voxel within a GPR image. Unlike traditional classification or object detection approaches that provide coarse results, semantic segmentation offers fine-grained spatial understanding by assigning a class label to every element of the input data. Several deep learning architectures have been widely adopted for this task. U-Net and its residual variant ResU-Net are among the most popular choices for both 2D and 3D GPR data segmentation, thanks to their encoder-decoder structure and skip connections that preserve spatial detail. DeepLabv3+ enhances segmentation performance further by incorporating atrous convolutions and spatial pyramid pooling, enabling multi-scale context aggregation, which is particularly useful for capturing subtle variations in subsurface features. Another notable architecture is SegNet, which also employs an encoder-decoder structure but is optimized for edge-aware boundary detection, making it suitable for applications that require the precise delineation of object boundaries.  
These semantic segmentation models have demonstrated strong performance in mapping complex subsurface structures across a variety of domains. For instance, in civil engineering, they are used for tunnel lining assessment and defect localization by accurately identifying anomalies such as cracks or voids. In environmental studies, such models enable the detailed mapping of tree root systems, which is crucial for understanding soil-vegetation interactions and preventing infrastructure damage. Archeological investigationsbenefit from the ability of these models to distinguish layered interfaces and buried artifacts with high precision. Additionally, in geotechnical applications, semantic segmentation contributes to subsurface stratigraphy modeling, where detecting and interpreting layers of soil or rock is essential for construction planning and hazard assessment. Overall, the integration of semantic segmentation into GPR interpretation workflows enhances both the accuracy and interpretability of subsurface imaging, making it a valuable advancement for both research and practical applications [45,46].
###### Abstract
In addition to the higher power levels permitted in the 433 MHz ISM band, the free space path loss in the 433 MHz frequency is 11.22 dB less, as presented in Figure 1, while the penetration through walls is higher than at 1575.42 MHz (GPS frequency) or 2.4 GHz (Wi-Fi frequency). Therefore, in terms of coverage and compatibility with existing rules on the use of repeaters, the proposed system could outperform the existing indoor positioning systems that are operating at frequencies higher than 433 MHz. The system we propose in this paper differs from the existing systems with its following properties. The down- and up-conversion schemes have previously been proposed in [43; 44; 45] for indoor positioning applications with GPS signals. While in [43; 44], a down-converting repeater is proposed, neither indoor positioning nor GPS signal down-conversion is demonstrated. In [45], only the down-converting repeater and up-converting receiver circuits are presented, to show that GPS signal fidelity is preserved. However, in [45], it is not shown how the proposed circuits perform in an indoor environment for positioning. In [46], the indoor positioning of an up-converting receiver at a point on a line between two down-converting repeaters (1-dimensional (1D) positioning) is proposed;  
Figure 1: Free space path loss at 2.4 GHz, 1575.42 MHz, and 433 MHz. however, non-line-of-sight conditions and two-dimensional (2D) positioning of the receiver are not addressed. In [47], we refer to the patent application of a system that can be used with different positioning systems (i.e., BeiDou, Galileo, GLONASS) by changing the register sets in the down- and up-converters to work in the 433 MHz frequency band or even in other ISM bands. In the latter case, the indoor antennas should also be changed to the selected frequency band. Upon review of readily available publications and to the best of the authors' knowledge, this paper is the first experimental study that demonstrates that 2D indoor positioning can be achieved by transmitting GPS signals, at 433 MHz, from three repeaters in an indoor environment, where the position of the receiver can be estimated by calculating the distance between each repeater and the receiver, on the plane that is formed by the deployed repeaters. The indoor positioning concept that is proposed in this paper is described visually in Figure 2.  
In this particular paper, we present two experiments for 2D indoor positioning in the 433 MHz ISM band: one experiment is under line-of-sight conditions, and another is under non-line-of-sight conditions. Note that adding a 4 th repeater will allow us to achieve 3D indoor positioning. The rest of the paper is organized as follows: Section 2 introduces the proposed indoor positioning system and describes its hardware, software and algorithms. Section 3 describes the experimental framework and the real-life environment where we tested our system. Section 4 analyzes and discusses the results we achieved when the proposed system and technique are used for 2D indoor positioning. Finally, Section 5 concludes this paper.
## 2 Literature Review
### Solution Approaches and Model Extensions
In [40], the authors propose a GLSP-based model for a pulp and paper mill planning problem and solve the problem with a two-step approach with a MIP-based construction heuristic followed by a MIP-based improvement heuristic. The authors of [41] extend this model to the multi-stage scenario and include additional constraints with the objective to maximize the steam output used to generate electrical energy. To solve the problem, the authors develop a hybrid approach that combines the general variable neighborhood search heuristic, a specific heuristic called speeds constraint heuristic and an exact solver. In [42], the authors also extend the model of [40] to the case of parallel non-identical paper machines and solve the problem by a hybrid solution method composed of an exact method embedded in a genetic algorithm. The authors of [43] present a model formulation for a production environment with wear and tear of resources and maintenance activities based on a combination of the PLSP and the GLSP where exogenous macro-periods with given length and demand are combined with endogenous micro-periods of flexible length. The authors propose a fix-and-optimize type decomposition heuristic to solve this problem. The authors of [44] present a GLSP formulation with multiple machines in a job shop environment and solve the problem with two MIP-based algorithms based on the rolling horizon iterative procedure. A multi-stage GLSP formulation for a flexible job-shop problem is presented by [45] and solved with a metaheuristic method that combines a GA with particle swarm optimization (PSO) and a local search heuristic. Deterioration and perishability for the GLSP are considered by [46]. The authors propose a model formulation that includes products that deteriorate after a maximum lifetime while being stored in an inventory. In this paper, we regard a model formulation based on this GLSP version, which was first presented by [1] and combines lifetime constraints for defective items with the ideas of an imperfect production process and rework, called GLSP-RP. Reference [47] study a robust optimization and a scenario-based two-stage stochastic programming model for the General Lot-Sizing and Scheduling Problem (GLSP) under demand uncertainty. The authors propose an extensive simulation experiment based on Monte Carlo to evaluate different characteristics of the solutions, such as average costs, worst-case costs, and standard deviation. The authors of [48] focus on a general lot-sizing and scheduling problem, including perishable food products, and apply two mixed-integer programming based heuristics to the problem. The authors use relax-and-fix approaches as a constructive heuristic to find an initial feasible solution and afterward apply a fix-and-optimize heuristic to improve the obtained initial solution.
# Optimization of Bit Allocation for Spatial Multiplexing in MIMO VLC System with Smartphones
## 2 System Model
### Detection of Physical Channels  
The MIMO VLC communication system is constructed with two mobile devices for transmitters and receivers. For each pair of transmitter and receiver, the signals would be represented as grayscale values. The real channel in the MIMO VLC system needs to be detected with varying defects in the optical components and medium. In particular, the configuration of the camera may dominate the design of the receiver in the system. Therefore, the powers of signals used in this system are calculated with statistical tests in real cases. Firstly, the original signal in the transmitter is defined as an image block where each pixel has the same grayscale value according to the modulation level in each channel. Secondly, the area of interest block in the image captured by the digital camera (as receivers) is shrunk to half of the range located with the corner detection [23]. In the third step, all grayscale values in the same area are averaged as the received signal in the channel. In the practical MIMO VLC system, the analysis of each channel can provide the gain \(\mathbf{H}\), seen in (5), to perform the incoming bit allocation to improve the transmission efficiency.  
Figure 4: Geometric scenario (transmitters in yellow and receivers in purple) used to detect the channel response.
# Chaotic Image Encryption: State-of-the-Art, Ecosystem, and Future Roadmap
## 4 Ecosystem
### Application Areas
#### 4.2.3 Satellite Systems  
Transmission of image data over satellite connection poses a unique problem of a non-negligible time delay between the involved parties. A novel solution to this issue was proposed by [PERSON] et al. [176], where Lyapunov stability theory was applied to achieve time synchronization in finite time.  
Another algorithm dealing with satellite transmission was proposed by [PERSON] et al. [177], where a new Cascade Modular Tent Logistic Map (CMTLM) was used. Simulation results demonstrated high effectiveness for the algorithm to perform in the satellite cryptosystem.
# Radar-Assisted Multiple Base Station Cooperative mmWave Beam Tracking
## 5 Conclusions  
In this paper, we have proposed a radar-assisted predictive beam tracking design for the V2I network by exploiting ISAC and multi-RSU cooperation. Firstly, on top of the linear mobility scenario, we derive the kinematic parameters evolution model and radar measurement model of the curvilinear mobility scenario which can be used in the EKF for angle prediction and thus beam tracking. Then we designed wideband eSV channel modeling in the communication process, which is more compatible with the existing OFDM system, and we use the more general path loss model given by the protocol. Moreover, aiming for improving sensing accuracy and RSU coverage in ISAC systems, we proposed a multi-RSU cooperation technique based on the prediction accuracy of each RSU which takes full advantage of distributed sensing. Since we considered multiple RSUs, we proposed three different RSU switching methods with an analysis of their respective performance. The proposed schemes have been validated with numerical results, which show that whether the vehicle is moving in a straight line or a curve, multi-RSU collaboration can  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Scheme** & **Computational Complexity** \\ \hline beam traversal search & \(\mathrm{O}(N_{t}MLKN)\) \\ EKF-based and multi-RSU cooperation & \(\mathrm{O}(N(LKn^{2}+3 LK+K))\) \\ EKF-based and non-cooperation & \(\mathrm{O}(NLKn^{2})\) \\ DNN prediction & \(\mathrm{O}((N_{train}+N)(n_{1}n_{2}+n_{2}n_{3}+n_{3}n_{4}+n_{4}))\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Computational Complexity.  
improve the angular tracking accuracy, which in turn improves the beam quality and obtains higher spectral efficiency. In addition, different RSU switching methods have also been proven to be highly effective.  
Conceptualization, K.C.; methodology, K.C. and Z.Z.; software, K.C.; validation, K.C.; investigation, K.C.; data curation, K.C.; writing--original draft, K.C.; writing--review and editing, D.L. and Z.Z.; Supervision, D.L. All authors have read and agreed to the published version of the manuscript.  
This work is supported in part by National Natural Science Foundation of China: No. 61971069, and 62271065, Beijing Natural Science Foundation: No. L202003, Project of China Railway Corporation: No. N2022G048, The Open Research Project of the State Key Laboratory of Media Convergence and Communication, Communication University of China: No. SKLMCC2021 KF009, and The Fundamental Research Project of Science and Technology on Complex Electronic System Simulation Laboratory: DXZT-JC-ZZ-2020-011.  
Not applicable.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Pharmacological Research of the Extracts
#### 2.5.1 Anti-Inflammatory Activity  
The study of the extracts' anti-inflammatory activity was conducted using the method developed by [PERSON] [27], employing male white rats weighing 130-240 g. The animals were divided into six experimental groups, each consisting of six individuals. Experimental procedures and data analysis were performed in comparison with two reference anti-inflammatory agents: the non-steroidal drug diclofenac sodium (administered at 8 mg/kg) and quercetin (administered at 5 mg/kg) [28; 29]. To evaluate the effects of \(M\). _memorosum_ extracts on the exudative phase of inflammation, the rat paw oedema model was used. In this model, 0.1 mL of a 2% aqueous formalin solution was injected subplantarly under the aponeurosis of the hind paw. Rats in groups I and II received oral administration of the respective extracts MN40 and MN70 at a dose of 100 mg/kg body weight, 2 h before and immediately after the injection of the phlogogenic agent. Group III received di clofenac sodium at 8 mg/kg (using the injectable solution \"Diclofenac-Darnitsa (CP120622)\" 25 mg/mL, 3 mL ampoules, manufactured by PrJSC \"Darnitsa\", Kyiv, Ukraine). Group IV was treated with quercetin at 5 mg/kg (granules \"Quercetin (0500924)\", manufactured by PJSC \"Borshchahivskiy Chemical-Pharmaceutical Plant\", Kyiv, Ukraine). Group V (control) received only 0.1 mL of 2% formalin without any treatment. Group VI consisted of intact animals that were not subjected to any intervention. The volume of the rat hind paw was measured using an onometric method before the experiment and at 1, 3, and 5 h after formalin injection, corresponding to the peak phase of oedema.  
The anti-inflammatory efficacy of the _M. memoosum_ extracts was assessed by the degree of inhibition of formalin-induced oedema compared to the untreated control group. The inflammation inhibition index was calculated using the following formula:  
\[A=\frac{\left(V_{k}\ -\ V_{d}\right)\ \times\ 100}{V_{d}},\]  
where \(A\) is the percentage of anti-inflammatory activity; _V\({}_{k}\)_ is the increase in paw volume in the control group (arbitrary units); and _V\({}_{d}\)_ is the increase in paw volume in the experimental group (arbitrary units).
## 2 Experimental Program
### Mix Proportioning and Details of Tested Beams  
The experimental program included seven simply supported RC beams. All the beams had an equal section of 200 mm depth, 150 mm width, and 1500 mm length. The reinforcement bars, dimensions, and geometry information of the tested beams are illustrated in Figure 4. The main bottom reinforcement was two bars of 12 mm diameter with a design yield stress of 410 MPa, and the top reinforcement bars were two bars of 10 mm diameter with the same yield strength. Vertical stirrups were constructed using 125 mm-spaced, 8 mm-diameter bars with a yield strength of 240 Mpa to ensure that all tested beams failed in the flexural mode according to ACI-19 [52].  
Figure 2: Pull out static test.  
The proportioning of the concrete mix of the tested beams is given in Table 2. Table 3 provides a summary of the information and the tested beams' designation. The beams' designation is arranged as follows: the beam number, numbers 0, 0.6, and 1.2 referring to the SGF ratio, and GPP and EP referring to the geopolymer and Sikadur(r)-330 epoxy paste of Sika Egypt, respectively. Three groups of beams were used. The first group included the beam B0-control, which referred to the control beam without strengthening. The second group included three tested beams, which were marked as B1-0-GPP, B2-0-6-GPP, and B3-1.2-GPP, and had bonding material GPP with SGF by the percentages of 0%, 0.6%, and 1.2%, respectively. The third group included three beams, which were marked as B4-0-EP, B5-0.6-EP, and B6-1.2-EP, and had EP with SGF percentages of 0%, 0.6%, and 1.2%, respectively.  
Figure 4: GFRP externally strengthened RC beam under two-point loads.  
Figure 3: The interface bond shear stress between the GFRP laminate and concrete surface experimentally.