esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimizing Foreign Language Learning in Virtual Reality:
## 3 Theoretical Foundations
### Educational Psychology Theories Relevant to VR  
Pedagogical psychology unfurls a tapestry of discernments into the modalities through which individuals assimilate knowledge, particularly within tech-augmented milieus like virtual reality (VR). As VR burgeons into an influential instrument within the educational sphere, grasping the psychological tenets bolstering efficacious edification within this domain ascends in significance. This segment ventures into salient pedagogical psychology postulates inextricably linked to VR environments. These postulates elucidate not merely the cerebral and affective oscillations of scholars within VR, but also chart the blueprint of VR odysses to optimize edificatory outcomes. By amalgamating these theoretical vantages, we can adeply leverage the distinctive boons of VR, forging engrossing educative sojourns that resonate both in allure and scholarly merit.  
A comparative chart highlighting the differences in learner motivation and engagement between traditional and VR learning is presented in Figure 4.  
In conducting a questionnaire survey to analyze learner engagement and motivation, a sample size of 200 university students from Kunsan National University in South Korea was selected. The survey consisted of a series of questions designed to measure and compare the efficacy of traditional learning methods versus virtual reality (VR) environments in educational settings.  
The questionnaire results, as summarized in Figure 4, indicate a significant difference in the impact of VR and traditional learning on students. Notably, engagement levels were higher in the VR group, with a reported 85% engagement rate compared to 65% in the traditional group. This suggests that VR's immersive nature may be more effective in capturing and maintaining student attention.  
The retention rate of learned material was 75% for the students who utilized VR, which was 25% higher than for those who engaged in traditional learning methods. This could be attributed to the interactive elements and realistic simulations provided by VR, which are known to enhance memory retention.  
The cognitive load was reported to be lower in VR at 50%, as opposed to 70% in traditional learning scenarios. This might be due to the intuitive and experiential learning environments created by VR, which can simplify complex concepts and reduce cognitive overload.  
The motivation to continue learning was markedly higher in VR, with an 80% positive response, underscoring VR's potential to sustain student interest over time. Finally, real-world application was perceived to be more effective in VR at 70%, indicating that VR provides a more practical learning experience that students find relevant to real-life situations.  
The survey conducted at Kunsan National University National University provides compelling evidence that VR can significantly improve learner engagement, retention rates, and motivation, while potentially decreasing cognitive load and enhancing the applicability of learned concepts to real-world contexts.
## 4 Experimental Results and Discussion
### Experimental Results
In the second trial of the last test, as shown in Figure 13, the inefficient paths were chosen again, as observed from the information obtained at MP3 and MP4. Similar results were observed for the MP1, MP2 and MP3 but worse paths were selected at MP compared to the previous trial. MP4 communicates with MP2 through MP3, and MP3 communicates through MP1. These two paths are obviously not the best paths because they require travelling a longer distance and an additional hop, compared to the direct path.
## 3 Results
### Estimation of Innovative Codends' Drag  
The economic aspects of trawling with innovative codons were not the main part of this research, and thorough analysis of drag, fuel consumption, energy efficiency, and the optimisation of resultant emissions should be further undertaken in future studies. Nevertheless, a potential increased resistance of trawls with innovative codons has been assessed by drag measurements of T90, UC + JD + JK, and UC + DD + DK trawl sets while towing with speeds in the range of 1 to 1.9 m/s (see Figure 15).  
It can be noticed that for a towing speed of 1.5 m/s (approximately 3 kts) used in cod bottom trawling, the drag of a trawl set with an empty T90 codend was about 22.5 kN, the drag of a trawl set with a UC + JD + JK codend was about 22.7 kN, and the drag of a trawl set with a UC + DD + DK coded was about 23 kN. The difference between the extreme drag values is less than 2.2%. These values are consistent with [1], as the drag of the codend itself is relatively small and amounts to approximately 2-3% of the total drag of the whole stern trawl gear, depending on whether it is empty or full. Also, because the drag of the T90 codend is up to 3% greater in comparison to the ultracross Bacoma type (which was measured in [1]), the drag of the innovative codons constructed of ultracross net was only insignificantly higher than T90's one. The innovative devices reducing the speed of water flow contributed to the growth of the resistance value while simultaneously the net of ultracross mesh contributed to its decline in comparison to T90. And it is worth noting that on the scale of actual measurements of the entire trawl set, the differences in drag are within the limits of measurement accuracy.
# mmS-TCP: Scalable TCP for Improving Throughput and Fairness in 5G mmWave Networks
## 2 Related Work
### Congestion Control in MmWave Network  
Network fairness must be considered when designing transport layer protocols. A good TCP CCA provides the best throughput and ensures fairness between TCP flows. However, traditional TCP CCAs do not fully utilize the wide bandwidth of mmWave links and cause excessive latency problems due to the frequent changes in channel state.  
Figure 1: End-to-end TCP connection over 5G mmWave link.  
Therefore, TCP congestion control studies to improve TCP performance in the mmWave environment have been carried out [22; 23]. If the TCP sender accurately identifies the state of the mmWave link and adjusts the cwnd, utilization of the link and end-to-end performance improve.  
MillProxy [24], a TCP proxy for mmWave cellular networks, divides end-to-end connection into two segments and uses different strategies for wired and wireless communication. It induces throughput improvement by sending data to a larger maximum segment size (MSS) over the mmWave link. MillProxy applies the cross-layer technique to quickly adapt to changes in link state while reducing latency and improving throughput. However, it is very difficult to apply the proxy function to the mmWave base station, and there is the problem that overhead may occur due to the classification operation that divides the end-to-end connection into two segments.  
X-TCP [25], a cross-layer CCA that performs congestion control using the parameters of the link layer, finds the optimal cwnd value using the resource information allocated by the base station to the UE and the SINR. X-TCP minimizes latency and quickly adapts to changes in link state without reducing throughput. However, there is the limitation when competes with existing TCP CCAs that the fairness problem may occur, and X-TCP is a cross-layer-based congestion control that is applied only to uplinks.  
The design and deployment of new CCAs that are focused solely on improving the performance of mmWave networks can cause fairness issues for existing TCP protocols. For example, [26] showed that RTT fairness issues may arise with changes in channel quality if there is a difference in RTT between TCP flows passing through the mmWave links. Even if multi-path TCP is applied to improve end-to-end throughput and connection robustness, TCP fairness problems may occur [27], so it is necessary to develop a protocol that achieves excellent performance and that maintains fairness in the mmWave environment.
## 2 Fundamentals of Ion-Imprinted Polymers
### Synthesis  
The general process for the synthesis of IIP can be summarized in three steps according to [PERSON] and coworkers [34]. First, the metal ion (template or analyte) is complexed using a vinylated ligand (functional monomer). Then, the vinyl complex is polymerized in the presence of a crosslinking agent and the radical initiator, where the polymeric skeleton is formed on the template and, consequently, remains incorporated into the polymeric network. Finally, after obtaining the polymer, the metal ion is removed by using dilute mineral acids, leaving three-dimensional recognition spaces or cavities within the polymeric network, which have a high affinity for the metal ion [35].  
A schematic representation of the general process of synthesis of an IIP is illustrated in Figure 1.  
Figure 1: Schematic representation of the synthesis process of an Ion-imprinted polymer (IIP).
# Urban Free-Space Optical Network Optimization
## 4 Results
### Simulation Framework
#### 4.1.1 Generating a Random Visibility Graph  
The first part of the simulation implements a generator for random red-blue visibility graphs. This generator randomly creates graphs while controlling statistical attributes. The importance of such a graph generator is its ability to produce large numbers of graphs while controlling essential parameters, such as edge density and average graph sizes. These graphs were the basis for a variety of experiments.  
The random graphs we generated vary in two primary parameters:  
* Graph size (number of vertices).
* Graph density (derived from the maximal range capabilities of the FSO links).  
The graph size is a key parameter for evaluating the scalability of the algorithm. The number of edges in a graph is also an important parameter to consider, as it significantly affects the algorithm's performance; thus, we also consider the graph density, which is defined by the following formula,  
\[density(G)=\frac{2m}{n(n-1)} \tag{2}\]  
where \(m\) is the number of edges and \(n\) is the number of vertices in graph \(G\).  
Figure 13 shows example random red-blue visibility graphs. Those examples represent a red-blue graph with different densities, sizes, and red-blue node ratios.  
In addition to creating random red-blue visibility graphs, we modeled a city terrain in this simulator. The city model has objects representing buildings, building attributes (such as height, location, and shape), and city terrain. On top of this model, we implemented the LOS function (presented in Section 2) and created an LOS geometric-based visibility graph.
## Results and Discussion
### Cell Compatibility and Ability to Support Cell Viability of pDMYO- and pDSIS-Gels  
Neonatal rat cardiomyocytes (NRCMs) and human umbilical vein endothelial cells (HUVECs) were seeded and cultured on three different hydrogels. COL1-gel was taken as reference to investigate cell compatibility and viability on pDMYO- and pDSIS-gel. The three-day survival rate of the NRCMs was greater than 85% on the three hydrogels, and no significant difference was observed (Figure 2A,B). For the HUVECs, the three-day survival rate was greater than 98% for on all three gels, exceeding that of the NRCMs (Figure 2C,D).  
NRCMs viability and cytotoxicity on the three hydrogels was tested using a CCK-8 assay. At one, three, and seven days, NRCMs survival was significantly higher on pDMYO-gel than on pDSIS- or COL1-gels (Figure 2E). In contrast, HUVECs viability was maintained for three days on the three hydrogels, and was the highest on pDSIS-gel (Figure 2F), which indicates pDSIS-gel can promote the proliferation of HUVECs better than other hydrogels.
###### Abstract  
Generators with high-temperature superconducting armatures have an advantage in the fact that they can carry high currents. However, the AC loss of high-temperature superconducting (HTS) armatures is difficult to calculate precisely because HTS coils exist in a complex and time-varying electromagnetic environment. In addition, when the HTS coil is carrying a short circuit fault overcurrent, an electromagnetic-thermal simulation study of this process is required to ensure that the HTS coil is not damaged. In this paper, first, a fully coupled T-A formulation model is used to calculate the AC loss of HTS armatures. Then, the current and temperature distributions are simulated, considering the intrinsic characteristic of superconducting coated conductors, when the generator suffers the worst short circuit fault accidently. It is found that the turn with the lowest critical current quenches after 0.01 s, but the temperature rise cannot damage the coil if the circuit breaker can clear the fault quickly. The effects of the copper stabilizer thickness on the thermal stability of the HTS coil during the worst short circuit fault are also investigated. A thicker copper stabilizer improves the thermal stability of the HTS coil in the event of a short circuit fault, but the use of a simulation model is needed to make trade-offs between the engineering current density and the thermal stability of the HTS tapes. The work in this paper is necessary and can provide an important reference for manufacturing superconducting generators.  
AC loss; short circuit faults; T-A formulation; HTS generator +
Footnote †: journal: Applied Sciences
# Underwater SLAM Meets Deep Learning: Challenges, Multi-Sensor Integration, and Future Directions
## 5 Sensors Driving Underwater SLAM
### Vision-Based SLAM  
Underwater environments pose serious challenges for SLAM techniques due to limited visibility, varying illumination, and dynamic conditions caused by moving marine life and shifting currents. Vision-based approaches have emerged as a crucial solution, particularly in clear water conditions where visual features can be reliably detected. Their ability to record textures and features makes them ideal for tasks like habitat mapping, underwater archaeology, and marine biology research, where detailed imagery is crucial for understanding the environment [50]. This section examines these methods through three key perspectives: monocular systems, stereo vision approaches, and advanced image enhancement techniques.
# Random Access for Underwater Acoustic Cellular Systems
## 5 Experimental Results
As shown in Figure 17a, four distinct peaks occur at the value of \(\beta_{c}\) (0.5, 1.5, 2.5 and 3.7 kHz) where the received waveforms are matched with the local counterparts. The four peak values decrease owing to pathloss. The four peaks are well-separated, thus facilitating a successful detection of each RAP. In Figure 17b, the normalized versions of CAF in Figure 17a are compared with the analytical results. As shown in Figure 17b, the analytical result also produces four distinct peaks at the same position. However, the analytical results are sharper and have lower cross-correlation levels than the experimental results because the channels and noise are ignored in analytical results. In summary, the AF and CAF analytically obtained in Section 3 are shown to be similar to those obtained from experimental data, except for a small difference in magnitude owing to the effect of channels and noise. Therefore, the upper bound of CAF and the number of RAPs derived in this paper can be effectively used to select the parameters of RAP 2. In this experiment, the following parameters are selected:  
Figure 16: AF comparison (experiment vs. analytical). (**a**) Experiment; (**b**) Analytical. \(\beta_{c}=\{0.5,\,1.5,\,2.5\}\) kHz, \(\beta_{d}=\{1.5,\,2.5,\,3.7\}\) kHz, and \(\Delta\beta=\{-1,\,-1,\,-1.2\}\) kHz. In this case, the upper bound of CAF, given in (19), is \(\{5.46,\,5.46,\,4.98\}\%\). The numbers of RAPs, given in (20), are 9 and 7 when the upper bound values are \(5.46\%\) and \(4.98\%\), respectively. Six additional RAPs are generated using different frequency shifting parameters (\(|f_{c}|\in\{0.5,\,1,\,1.5\}\) kHz).
# Security Audit of a Blockchain-Based Industrial Application Platform
## 3 Attacker Goals, Resources, and Capabilities
### Attack Classification
#### 3.3.2 Communication Channel Attacks  
This section describes attacks on communication channels between the blockchain and external systems such as state monitoring, machines, networks, and sensors.  
* _Routing_: these are direct attacks in which the attacker forges or modifies routing information and causes problems through activities such as creating routing loops, sending error messages, and more [42]. Attackers can eavesdrop and disrupt the transmission channels. Even if the signals are encrypted, the attackers are able to analyze the signal streams and derive private information, such as the locations of sources or destinations. The attackers can also disrupt and even jam the wireless channels by sending noisy signals [43].
* _Replay_: an attacker can intercept a signed packet and send the packet back to the destination multiple times. This packet keeps the network busy, resulting in a DoS attack [44]. Advanced replay attacks hide the manipulated behavior of devices by sending old sensor data [45].
* _Selective forwarding_: in this attack, a malicious node selectively modifies messages, discards them, or forwards them to other nodes. Therefore, the information that reaches the destination is incomplete [46].
# Metamaterial Based Design of Compact UWB/MIMO Monopoles Antenna with Characteristic Mode Analysis
## 6 Conclusions  
This paper presents a UWB-MIMO antenna with the isolation of \(-20\) dB. The UWB response is achieved by designing a slotted shaped circular antenna. Simultaneously, the isolation is improved by using metamaterial structure on the upper plane and perturbed stub in the ground plane. Characteristic mode analysis is introduced to gain physical insight into antenna operating principles. The simulated design is fabricated, and performance parameters are calculated and measured. The simulated and measured results are in good agreement. The ECC, DG, TARC, CCL and MEG are 0.01, 9.99 dBi less than 0 dB, less than 0.35 bps/Hz, and less than \(-3\) dB, respectively.  
Conceptualization: A.H.J. and A.G.; methodology, A.H.J., and A.G.; software, A.H.J., A.G., A.A., M.A and S.S.; validation, A.H.J., M.A and X.J.L.; investigation, A.G., A.A., and S.S.; resources, M.A., F.F, and E.L.; writing--original draft preparation, A.H.J., A.G., and S.S.; writing--review and editing, X.J.L., A.A., M.A., F.F, and E.L.; supervision, X.J.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Figure 32: Mean effective gain (MEG) of the MIMO system.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Ref.**} & **Size** & **Publ** & **Spacing** & **Freq** & **Isolation** & **ECC** & **Gain** & **Efficiency** \\  & **(mm\({}^{2}\))** & **Year** & **(mm)** & **(GHz)** & **(dB)** & **ECC** & **(dBi)** & **(\%)** \\ \hline
[3] & \(24\times 42\) & 2020 & NG * & 3.5 & NG * & NG * & 4.9 & 86.4 \\
[5] & \(33\times 48\) & 2020 & 3 & 2-137 & 20 & 0.15 & 4.3 & NG * \\
[20] & \(39\times 44\) & 2018 & 7 & NG * & 24.5 & 0.1 & 4 & NG * \\
[31] & \(32\times 64\) & 2020 & NG * & 2.7-10.5 & 22.5 & 0.025 & 8.4 & 50 \\
[32] & \(55\times 55\) & 2019 & NG * & 5–6 & 32 & 0.0001 & 5.3 & 84 \\
[33] & \(23\times 29\) & 2016 & NG * & 3–12 & 15 & 0.15 & 4.7 & 82 \\
[40] & \(70\times 150\) & 2019 & NG * & 2.5-3.6 & 15 & 0.02 & NG * & NG * \\
[41] & \(37\times 44\) & 2020 & 5.8 & NG * & 23 & 0.1 & 4.25 & 82.4 \\
[45] & \(26\times 26\) & 2020 & NG * & NG * & 25 & 0.02 & 2.4 & 77 \\
[46] & \(40\times 40\) & 2020 & NG * & 2.4-2.48 & 25 & 0.21 & 2.36 & NG * \\ This Work & \(30\times 30\) & 2021 & 10 & 2.6–12 & 20 & 0.01 & 5.5 & 89 \\ \hline \hline \end{tabular} NG * = Not Given.  
\end{table}
Table 3: Performance comparison with other antennas presented in the literature.
# Practical Application of Sustainable Road Structure: Mechanical and Environmental Approach
## 4 Mechanical Analysis
### Loading Testing on Test Sections
The volumetric properties of the sub-base were based on the results of the verification tests carried out during the construction of the sections. The obtained results of the elastic moduli are also characterized by quite large dispersions, so their statistical variability was taken into account in the mechanistic analysis. The calculation of the condition of strains in the road pavement structure in a probabilistic approach is a complex issue. The NOAH software uses the Rosenbluth method [26]. It consists of an approximation of the continuous distribution of probability by a discrete (three-point) distribution characterized by statistical moments such as, for example, the average, variance, etc. The result is a continuous beta distribution of the strain values of the structure. For the analysis, layer strains were used for the 95% probability level, which is typically used in calculations for the pavement structure designs. The results of the calculations are presented in Table 2. Differences in strain values based on FWD measurements in 2017 and 2018 are a consequence of the different elastic modulus values. The fatigue life of the reference structure is generally higher in all cases than the APSE structure. In the case of APSE structure, fatigue life is determined by the sub-grade criterion. The results obtained on the basis of tests in 2017 are much lower than in 2018, which is due to the previously discussed extremely unfavourable conditions in that period. Nevertheless, they are suitable for the traffic load category KR3 on this road. The results of measurements in 2018 allow classifying the load capacity of the structure in the higher traffic class KR4, which means the range of the number of axes of 100 kN over a period of 20 years from 2.5 to 7.3 million. It is also worth noting that the APSE structure is 2 cm thinner than the standard structure for the KR4 class according to the Polish catalogue for the design of asphalt pavements [25]. When assessing the APSE structure, it should be objectively stated that, on the one hand, the fatigue life of this structure is lower than that of the reference structure, but at the same time it successfully meets the requirement for desired traffic category. \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**Strain, μm/m**} & \multicolumn{4}{c}{**Pavement Structure and Year**} \\ \cline{2-5}  & **Reference** **2017** & **Reference** **2018** & **Experimental** **2017** & **Experimental** **2018** \\ \hline \(\varepsilon_{a}\) & 118.0 & 103.7 & 156.6 & 116.2 \\ \hline \(\varepsilon_{g}\) & 385.0 & 333.5 & 484.2 & 376.3 \\ \hline Life criteria & & & Design life, mln of 100 kN Esals & \\ \hline \(N_{a}\) & 3.2 & 4.6 & 1.8 & 3.9 \\ \hline \(N_{g}\) & 2.7 & 5.2 & 1.0 & 3.0 \\ \hline \(N_{min}\) & 2.7 & 4.6 & 1.0 & 3.0 \\ \hline \end{tabular}
\end{table} 
Table 2: Strains and calculated life criteria for reference and experimental pavements.
# Autonomous Mobile Station for Artificial Intelligence Monitoring of Mining Equipment and Risks
## 3 Materials and Methods
### Incorporation of the Communication System
#### 3.3.2 High Bandwidth (5 GHz) Wi-Fi Link  
Video and telemetry data are transmitted over the IEEE 802.11 ad standard in the 5.180-5.825 GHz range, which supports transfer rates of up to 433 Mbps. The key parameters are:  
* Channel width: 80 MHz
* Latency: \(<\)50 ms
* Security protocol: WPA2-PSK with 128-bit AES encryption
* Range: 500-800 m (LoS)
* Antennas: 5 dBi dual-band Omni, with low interference shielding  
Both systems operate simultaneously and independently, ensuring redundancy and enabling full interoperability with cloud platforms, centralized mining dashboards, or SCADA systems. Local edge processing is performed on board the station through an integrated GPU-enabled unit running a YOLO11 deep learning model, enabling mining asset detection and classification without external computational dependencies.