esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Fiber Effect on the Compressive Strength and Density of Geopolymer  
Figure 6 shows the PP fiber effect on the compressive strength of both 40% and 60% foamed geopolymer. It can be seen that the mechanical strength rises gently with the addition of PP fibers. An enhancement of PP fiber content was observed to give a significant effect at 7 days compressive strength. However, a minimal decrease of compressive was observed when 0.50% PP fiber contained in foamed geopolymer. At 7 days curing time, the strength of 40% foamed geopolymer show an increase at 205% times and 271% times when the PP fibers were at 0.25% and 0.50%, respectively, compared to without PP fibers. The strength of 60% foamed geopolymer shows the same trend, which tends to rise as the PP fiber content increases. However, at 28 days curing time, both 40% and 60% of foamed geopolymer contain PP fibers of 0.25% and 0.50% with a similar trend. First when 0.25% PP fiber were included in the foamed geopolymer the strength tended to rise, but this strength dropped slightly when PP fiber content was 0.5%.  
Figure 4: Thermal conductivity test (**a**) and the specimen (**b**).  
The rise in compressive strength of foamed geopolymer is caused by the bonding mechanism between the PP fibers and geopolymer matrix, where the PP fibers fill up the void from the air. The use of PP fibers beyond optimum dosages can also reduce the strength. According to [14], the PP fibers may have the properties of a hydrophobic material, which tends to retain water and create voids. Besides that, the higher dosage of PP fiber can obstruct the void and can cause weaknesses in the bonding between the matrix and the PP fibers.  
The strength reduction in 40% and 60% foamed geopolymer of PP fibers at 0.5% also corresponds with their dry density. A minimal increase in the density of foamed geopolymer was observed at 0.25% dosage of PP fiber, and the density slowly decreased when 0.50% amount of PP fiber was contained in geopolymer. As shown in Figure 7, the dry density of fiber reinforcement geopolymer decreased slightly around 5.3% and 4% compared to the dry density of foamed geopolymer without PP fibers, respectively. [PERSON] et al. [16] reported that the strength of fiber-reinforced geopolymer concrete was improved at 0% and 0.5% of PP fiber and decreased at the amount of 1.0% and 1.5%. Previous works also showed [15; 25; 26] that the increased amount of PP fibers decrease the  
Figure 5: Compressive strength of foamed geopolymer.  
Figure 6: The effect of PP fiber on the compressive strength of foamed geopolymers.  
rate of strength development. Even though the geopolymer matrix itself is strong locally, the interaction with PP fibers does not result in the same behavior.
# A Simple Experimental Stand for Studying the Network Security Level of Power Electronic Devices
## 8 Discussion  
### About the Proposed Experimental Stand  
From the obtained results, it was found out that both PDUs have almost the same vulnerabilities. Both devices have only one open port, port 80, which is used for access and control through a browser. Having only one open port is \"good news\" because no additional measures will be needed.  
For both devices the exchange of information is not secure. Data are exchanged either in plain text or through the use of simple coding techniques that are very easy to decode. For devices that are used by ISPs or service providers, the non-secure data exchange is a big problem because possible hacking of these PDUs could result in a network down or inability to deliver services.  
A difference between the two PDUs was found during the penetration tests when both devices were subjected to different DoS attacks. The EATON PDU was inaccessible during all attacks, which was an expected result. However, the Neomontana PDU was only inaccessible during the TCP SYN attack. During the other attacks, the device was accessed without problems. The penetration tests also confirmed the results of the vulnerability analysis carried out with Namp--the Neomontana PDU, according to Namp, may not be affected by some DoS attacks. That did occur. This means that the developed embedded web server is somehow designed to resist to some of DoS attacks.
# Development of a Novel Concrete Curing Method Using Induction Heating System
## 1 Introduction
Most importantly, it has the advantage of being capable of heating the metallic form according to a desirable heating scenario since it is possible to control the surface temperature of the form by regulating the current intensity applied to the induction heating coil. The heat produced is affected by the structure and number of turns of the coils, working frequency, and material of the heated object. It is noted that although certain parameters that affect the performance of induction heat curing of concrete were initially investigated by the authors [13; 14], highly limited data are available. Therefore, to provide a comprehensive understanding of the concrete heat curing method using induction heating, a finite element method (FEM)-based thermal analysis was initially carried out in this study. The analysis provided certain information on the appropriate materials for metallic forms for induction heat curing and the number of coil turns for better distribution of the generated heats in the form. Concrete curing tests were also carried out to verify the efficiency of the use of induction heat curing for early strength development of concrete and to identify appropriate procedures for curing using an induction heating system.
# Regular Wave Effects on the Hydrodynamic Performance of Fine-Mesh Nettings in Sampling Nets
## 1 Introduction
Numerical simulation methods are particularly favored for their cost-effectiveness and high precision [34; 35; 36]. In these simulations, netting models are often constructed based on various simplifying assumptions. For example, some models represent netting as a series of lumped masses points interconnected by massless springs [25; 37], while others treat netting as porous media to explore the hydrodynamic behavior under wave conditions [33; 38; 39]. Furthermore, fluid-structure interaction models have been employed to integrate these approaches, enabling more comprehensive analyses. The establishment of a numerical wave tank is critical for examining wave forces on netting. Such wave tanks typically consist of three primary regions: the wave maker, the computational domain, and the wave absorber. The design precision of these components directly influences the accuracy of the simulation results [37; 38]. Analytical and experimental studies have explored wave reflection and transmission by vertical netting to assess wave attenuation both upstream and downstream of the netting. For instance, [PERSON] et al. found that netting with a higher solidity ratio leadsto greater wave energy dissipation, particularly for longer waves [23]. [PERSON] et al. observed that the transmission coefficient remained constant with an increasing wave height but increased with longer wavelengths [38]. [PERSON] et al. examined the damping effect of net cages on wave propagation across varying wave periods, revealing that the transmission coefficient inside a net cage was higher than that downstream of it [27]. Moreover, as the number of net cages increased, the wave transmission coefficient gradually decreased. Despite these contributions, the attenuation of waves downstream of fine-mesh netting remains poorly understood. Further research is necessary to fully comprehend the complex flow field around fine-mesh netting under wave conditions. In this study, we examine the hydrodynamic performance of fine-mesh netting under various linear wave conditions by combining wave hydrodynamic experiments and numerical simulations. A porous media fluid model is employed to simulate fine-mesh netting in waves and the numerical results are validated against experimental data. The relationships between the drag and inertial coefficients and the Reynolds number and Keulegan-Carpenter number are systematically investigated. Additionally, a numerical analysis of wave elevation upstream and downstream of the netting is conducted, with the transmission coefficient utilized to evaluate wave attenuation downstream. The water particle velocity field distribution around the netting is analyzed using numerical simulations and particle image velocimetry (PIV) technology.
# Defining Feasible Joint and Geometric Workspaces Through Boundary Functions
Structural synthesis methods [14] have also been introduced to systematically refine parallel robot architectures for improved workspace feasibility. Another challenge in workspace determination involves identifying singularity curves and assembly configurations [8]. The characterization of singular configurations is essential for ensuring continuous, collision-free motion within the workspace, a concept that aligns with prior findings [3] where singular points were employed to construct precise workspace boundaries. Several studies have emphasized the role of Jacobian-based analysis in detecting singularities, particularly in complex parallel mechanisms, as demonstrated in [15], where a post-processing strategy was developed to improve control performance near singularities. Further studies on parasitic motion analysis [16] have provided insights into workspace constraints by leveraging constraint-embedded Jacobian formulations. Furthermore, numerical ray-based methods, such as the one introduced by [PERSON] et al. [7], offer an alternative approach for defining workspace limits in kinematically redundant manipulators. However, as noted by [PERSON] [10], algebraic formulations provide more efficient methods for workspace evaluation and design. In summary, the primary contribution of this work is the introduction of a rigorous mathematical framework for defining feasible, collision-free workspaces via the formulation of boundary functions that integrate kinematic, collision avoidance, and geometric constraints. Unlike traditional numerical methods--which rely on extensive iterative sampling and often yield fragmented boundaries--the proposed approach yields continuous and analytically tractable workspace boundaries. This study provides a clear and structured alternative to existing methods, thereby enhancing both the theoretical understanding and the practical efficiency of workspace determination. To clarify the structure of the proposed methodology, a step-by-step process is followed throughout the manuscript. First, a standardized convention is established to define reference frames and spatial relationships in robotic manipulators. Then, a general model is developed to identify the conditions under which two parts of a robot may come into contact. Based on this, a set of constraints is formulated to determine whether a given robot configuration is valid and free of collisions. These constraints are categorized and evaluated to identify the limits of safe operation. A geometric region of feasible configurations is then constructed and adjusted to ensure safety margins and avoid singularities. Finally, the method is applied to a planar robot example, where different motion alternatives are analyzed and compared.
## 4 Application  
### Dataset  
In this study, comprehensive experiments are conducted on the [68 Ga]Ga-Pentixafor PET/CT images of glioma patients [41], which includes data from 24 treatment-naive adult patients diagnosed with high-grade glioma. Each patient received an intravenous injection of a radiolabeled CXCR4-targeting tracer, followed by PET/CT imaging approximately 60 min post-injection. Scanning was performed with a dedicated PET/CT system, acquiring images at 10 min per bed position. The data were reconstructed using a 3D-OSEM algorithm incorporating point spread function (PSF) resolution recovery (TrueX, Syngo(r) software (VB80A), Siemens Medical Solutions), with 3 iterations, 21 subsets, and a 3 mm Gaussian post-smoothing filter. For analysis, the middle 128 slices were selected from each patient's  
Figure 11: Parameter sensitivity in relation to ACC for the parameter \(\alpha\) (\(\lambda=0.01\), \(\beta=1,\text{m}=5\)).  
scan, each representing a region of interest (ROI) within the glioma tumor. For the glioma dataset, the selected features are evaluated using K-means clustering to assess their ability to distinguish between different tumor regions, such as active tumor tissue and necrotic areas. The experimental results demonstrate that the selected features contribute to effective clustering and hold potential value for tumor characterization.
# Analysis of the Odor Purification Mechanism and Smoke Release of Warm-Mixed Rubber Asphalt
## 3 Results and Discussion
### Analysis of High-Temperature Rheological Properties of Asphal  
The analysis of Figure 2 reveals significant insights into the high-temperature performance of different asphalt types, particularly those modified with warm-mix agents and deodorants.  
Figure 1: Analysis of rutting factors.  
Figure 2: High temperature failure temperature analysis.  
Firstly, it is evident that the addition of warm-mix agents significantly enhances the high-temperature resistance of asphalt. The high-temperature failure temperatures of asphalt modified with these agents are notably higher than those of other asphalt types. This suggests that the warm-mix agents effectively improve the asphalt's ability to withstand high temperatures, potentially due to changes in its chemical structure and physical properties.  
At elevated temperatures, asphalt materials undergo chemical and structural transformations that can affect their mechanical properties and durability. The warm-mix agents likely interact with the asphalt in a way that stabilizes its molecular structure and chemical bonds, thereby delaying the onset of high-temperature failure.  
Interestingly, the data also indicate that increasing the content of the deodorant has minimal impact on the high-temperature failure temperature of asphalt. This suggests that the chemical composition and reactions associated with the deodorant do not significantly alter the asphalt's high-temperature performance. This finding could be influenced by various factors, including the asphalt's initial composition, viscosity, and wax content, which can affect its natural resistance to high temperatures.  
From a practical perspective, understanding the high-temperature failure temperatures of different asphalt materials is crucial for road construction and maintenance. In regions with high ambient temperatures, selecting asphalt materials with superior high-temperature resistance can significantly enhance road stability and durability. This, in turn, reduces the likelihood of common road issues such as rutting, oil leakage, and cracking, ultimately extending the lifespan of the roadway and improving overall road safety.
# Investigation of Titanium Alloy Cutting Dynamics in Thin-Layer Machining
## 2 Methods and Materials
### Measurement of Cutting Forces  
Cutting force components were measured throughout the experiments with the use of a three-component piezoelectric dynamometer (Kistler 9272) mounted in the lathe's turret head using a VDI 30 tool holder. The dynamometer was connected to a Kistler 5019 charge amplifier, which interfaced with a KPCI 3108 data acquisition card. Force signals were recorded using LabView software.  
Prior to machining, the measurement system was fully prepared, including the installation of the dynamometer, connection of all components, and sensor calibration. Cutting operations were carried out at various feed rates and depths of cut. Force signals were continuously recorded during each cutting pass, with data acquisition initiated just before and terminated immediately after each segment using LabView. All recorded data were stored on a PC for subsequent analysis. The methodologies of free orthogonal cutting and constrained oblique cutting were similar. The research was conducted for free orthogonal cutting with a cut layer width of 0.3 mm and variable cutting depths of 0.025, 0.035, 0.05, 0.07, and 0.1 mm for titanium alloys Ti Grade 2 and Ti Grade 5. The constrained oblique cutting was extended to include cross-sections of cut layers close to the minimum values. Hence, the feed rate varied in the range from 3 \(\upmu\)m/rev to 100 \(\upmu\)m/rev.  
The experimental setup for constrained oblique cutting is shown in Figure 1, which also illustrates the data flow algorithm for the acquisition and analysis of cutting force components. Cutting forces were measured using a piezoelectric dynamometer mounted on a CNC lathe. The force signals were acquired at a sampling rate of 250 Hz, then filtered and converted into force values using calibration coefficients obtained from static load tests. A region of interest (ROI) was defined within the steady-state cutting zone to ensure consistent conditions for analysis. Frequency-domain analysis was employed to identify the dynamic characteristics of the system, and appropriate filtering techniques were applied to isolate cutting-related force components from background noise and machine-induced vibrations.
## 3 Method
### The Overall Framework of the Proposed Method  
The method proposed in this paper first constructs a spatial proximity graph using the convex hull Voronoi diagram of area objects. Secondly, it systematically analyzes the physical meanings of nodes and edges in the spatial proximity graph, as well as the relationship between these physical meanings and spatial distribution information. Four characteristic indicators, including the geometric information content of nodes, node degree, adjacency strength, and adjacency distance, are selected to comprehensively represent the spatial information of area maps. Finally, considering the regular arrangement characteristics of artificial buildings in practical applications, the limited growth theory of visual repetition in cognitive psychology is introduced to eliminate and weaken the redundant information caused by regular arrangement, resulting in a more objective and accurate quantitative expression of spatial information content for area maps. The main research approach is illustrated in Figure 1:
# FL-LoRaMAC: A Novel Framework for Enabling On-Device Learning for LoRa-Based IoT Applications
## 4 Proposed Framework: FL-LoRaMAC
### Optimizing Communication Bandwidth
#### 4.4.2 QoS-Based Assignment of SF for Differential Priorities
If 36% of \(p>d_{10}\), then \(d_{10}\) number of devices will be configured on SF-10 and the remaining \(p-d_{10}\) devices will be configured on SF-9, given that \(p-d_{10}<d_{9}\). All other devices will be distributed between SF-7 and SF-8 according to the 64:36 ratio. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Spreading Factor** & **Physical bit Rate** & **Transmission Range** \\ **(UL for 125 KHz)** & **(bits/s)** & **(Depends on Terrain)** \\ \hline SF7 & 5470 & 2 km \\ \hline SF8 & 3125 & 4 km \\ \hline SF9 & 1760 & 6 km \\ \hline SF10 & 980 & 8 km \\ \hline \hline \end{tabular}
\end{table} 
Table 1: LoRa spreading factors. 3. If \(p>d_{9}+d_{10}\) but \(p<d_{8}+d_{9}+d_{10}\), then all the low-priority devices will be configured on SF7 and high-priority devices will be configured on SF-8, SF-9, and SF-10. 4. If \(p>d_{8}+d_{9}+d_{10}\), the required PDR \(x\) will decrease for HP devices and the values of \(d_{8}\), \(d_{9}\), and \(d_{10}\) for this new \(x\) will be found. 5. All \(p\) devices will be configured on SF-8, SF-9, and SF-10 in optimum fraction. The thresholds \(d_{8}\), \(d_{9}\) and \(d_{10}\) must be maintained at all times. There can be other ambient devices in the network running some other applications, transmitting packets with higher priorities selected based on some criteria. Using the network configuration, the maximum number of devices that can be supported by each spreading factor can be found and the spreading factors can be allocated to different packets according to the top-down approach [13].
## 2 Materials and Methods
### Remote Sensing Data  
The remote sensing data used in this study are from MODIS and Sentinel-2. The MODIS datasets were the primary dataset, while the Sentinel-2 data were used for validation purposes. The subsection below describes the reasons for the selection of these datasets and the pre-processing and processing steps conducted on the image datasets.
## 4 Case Study
### The Method Employed in this Study Is Illustrated in Figure 7
#### 4.1.2 Phases 2 and 3: Do and Check
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Process Data:** & & & & **Overall Capability** & \\ \hline \multirow{2}{*}{**Short-Side Armature**} & **Long-Side** & & **Short-Side** & **Long-Side** \\  & **Armature** & & **Armature** & **Armature** \\ \hline LSL & 58.8399 & 58.8399 & PPL & 1.06 & 0.67 \\ \hline Sample & 291.441 & 105.186 & Ppk & 1.06 & 0.67 \\ mean & 27 & 27 & Potential (within) capability & \\ \hline Overall & 73.2918 & 23.1488 & CPL & 1.26 & 0.65 \\ \hline StDev & 61.6931 & 23.741 & Cpk & 1.26 & 0.65 \\ (within) & & & & & \\ \hline \multicolumn{5}{l}{Performance:} \\ \hline \multicolumn{5}{c}{Observed} & \multicolumn{2}{c}{Expected Overall} & \multicolumn{2}{c}{Expected Within} \\ \hline \multirow{3}{*}{PPM \(<\) LSL} & Short-Side & Long-Side & Short-Side & Long-Side & Short-Side & Armature & Long-Side \\  & **Armature** & **Armature** & **Armature** & **Armature** & **Armature** \\ \hline PPM \(<\) LSL & 0 & 0 & 752.74 & 22,637.33 & 81.53 & 25,460.03 \\ \hline Total PPM & 0 & 0 & 752.74 & 22,637.33 & 81.53 & 25,460.03 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Detachment force capability response to epoxy coating thickness increase. Figure 23: Histograms of detachment force capability response to inverting the lamination: (**a**) short-side armature; (**b**) long-side armature. To ensure proper performance and adhesion, the percentage of epoxy curing needs to be precisely measured. This is calculated using the following equation:  
\[\%\text{Curing}=(1-\Delta\text{H})/\Delta\text{H}_{0}\times 100 \tag{2}\]  
Enthalpy represents the total energy content of a system at constant pressure. In the context of epoxy curing, \(\Delta\text{H}_{0}\) denotes the energy change when the uncured epoxy fully cures, while \(\Delta\text{H}\) represents the energy change during partial curing stages. Comparing these values allows us to accurately assess the extent of epoxy curing throughout the process. This information is crucial for ensuring the final product meets the desired quality and performance standards. Understanding the enthalpy changes helps in monitoring and controlling the curing process to achieve consistent and reliable epoxy properties. To determine the optimal voltage setting to maximize the epoxy curing percentage, experiments were conducted, varying the curing process voltage from 2.8 to 3.3 kV. The epoxy layer thickness was maintained at 150-200 microns, while the degreasing voltage remained at 2.6 kV. Analysis of data from both the short side (Figure 26) and long side (Figure 27) revealed that 2.9 kV achieved the highest curing percentage on both sides. This finding shed light on the potential reasons for the poor breaking force results observed when increasing the voltage in the curing process, as discussed in Section Adjusting the Voltage at the Epoxy Coating Curing Station to Optimize Curing Conditions. Figure 24: DSC test on a virgin sample (without curing treatment). Figure 25: DSC test on a cured sample.