esa-sceva/satcom-chunk-collection huggingface dataset:
# Coplanar Capillary Plasma Electrode Discharge Flat-Panel Lamps Based on Porous Anodic Alumina
## 4 Discussion  
The voltage in the gas gap of the DBD devices (Figure 1a) was determined using Equation (7).  
\[U_{g}=\frac{Ud_{g}}{d+\frac{d_{1}}{\epsilon_{1}}+\frac{d_{2}}{\epsilon_{2}}}, \tag{7}\]  
where \(d_{1}\), \(d_{2}\), and \(d_{g}\) are the thicknesses of dielectric 1, dielectric 2, and the gas gap, respectively, \(\epsilon_{1}\) and \(\epsilon_{2}\) are the dielectric constants of dielectric layer 1 and dielectric layer 2, respectively. The dielectric constant of the gas is assumed to be 1.00.  
Figure 12: Evolution of the electric field intensity in the coplanar CPED device. (**a**) 1/8 T, (**b**) 1/4 T, (**c**) 3/8 T, (**d**) 1/2 T, (**e**) 5/8 T, (**f**) 3/4 T, (**g**) 7/8 T, (**h**) 1 T.  
The capacitance of the dielectric layer is determined by Equation (8).  
\[C=\frac{\varepsilon_{0}\varepsilon_{r}S}{d}, \tag{8}\]  
where \(\varepsilon_{0}\) and \(\varepsilon_{r}\) represent the absolute and relative permittivities of the dielectric layers, respectively.  
In the PAA dielectric layer, the thickness of the pores varied, which led to a change in the voltage of the gas gap. The sharp change in the voltage in the gas gap causes a stronger electric field, as shown in Equation (9).  
\[E_{g}=-\frac{\partial U_{g}}{\partial l}, \tag{9}\]  
where \(E_{g}\) and \(U_{g}\) are the electric field intensity and potential in the gas gap, respectively. The electric field intensity varied with the geometry of the PAA, which helped decrease spark ignition.  
The results show that the PAA dielectric layer plays an important role in CPED devices. The electron density, electron temperature, and electric field intensity near the pores were higher than those in other parts. The electron distribution near the hole was uneven, similar to that of the plasma jets. The plasma jets facilitate the occurrence and stability of the coplanar CPED plasma.  
To investigate the influence of PAA on the plasma in CPED plasma flat-panel lamps, the properties were calculated using the software. Figure 13 shows the plasma properties 0.01 mm above four pores of PAA in the CPED, namely, (a) the electron density and (b) the electron temperature.  
As shown in Figure 13, the plasma concentration changed significantly above the pore zone. The electron density increased significantly, similar to that of the plasma jets. The plasma jets were small, which improved their uniformity. This uniformity assists in decreasing the electric power, which leads to an increase in luminous efficacy.
## 2 Materials and Methods
### Mechanical Properties Test
#### 2.2.2 Structural Crashworthiness Indicators  
To evaluate the crashworthiness of the bio-inspired structures, it is important to define appropriate indicators. In this study, several parameters were used to assess the energy-absorption performance of the proposed structures, including total energy absorption (\(EA\)), specific energy absorption (\(SEA\)), mean crush force (\(P_{m}\)), maximum crush force (\(P_{\max}\)), and crush load efficiency (\(CLE\)) [34; 35].  
\(EA\) represents the overall energy absorbed by the structure during impact deformation, indicating its capacity for absorbing energy. This value can be obtained by integrating the crush force-displacement curve using the following formula:  
\[EA=\int_{\Omega}E(\varepsilon)d\Omega \tag{1}\]  
where \(E(\varepsilon)\) represents the strain energy density of the structure, and \(\Omega\) represents the volume of the structure.  
Specific energy absorption (\(SEA\)) is used to quantify the energy absorbed by the structure per unit mass, which can be calculated as:  
\[SEA=\frac{EA}{M} \tag{2}\]  
where \(M\) is the total mass of the structure.  
The mean crush force \(P_{m}\) is defined as the average compression force resisted by the energy-absorber during the total plastic deformation process as expressed by:  
\[P_{m}=\frac{E(d)}{d} \tag{3}\]  
The energy absorbed at a given impact distance is denoted as \(E(d)\), with \(d\) representing the corresponding distance of impact.  
The maximum crush force (\(P_{\max}\)) is an indicator of the highest crushing force that occurs during the effective compression stroke of thin-walled tubes in axial-impact situations. As it is an injury-based metric, larger \(P_{\max}\) values can result in greater deceleration and increase the risk of injury or damage to occupants. Therefore, it is imperative to minimize \(P_{\max}\) or at least ensure it remains within safe levels.  
\(CLE\) is used to measure load uniformity (i.e., the higher the \(CLE\), the more efficient the structure). \(CLE\) can be calculated as the ratio of \(P_{m}\) to \(P_{\max}\):  
\[CLE=\frac{P_{m}}{P_{\max}} \tag{4}\]
# A Phase Bias Compensation Method for Anti-Interference Antenna Arrays in RTK Positioning
###### Abstract  
To achieve high-precision positioning using the global navigation satellite system (GNSS), the onboard GNSS receiver integrates real-time kinematic (RTK) technology to enable centimeter-level positioning accuracy. Furthermore, array anti-interference technology is incorporated into the RTK receiver to enhance positioning reliability and mitigate interference in complex environments such as urban areas or regions with high electromagnetic activity. However, this approach can introduce signal distortion, which adversely affects the convergence of RTK positioning. To address the issue of bias introduced by interference suppression in RTK positioning, this paper focuses on error modeling and bias compensation through a phase bias compensation algorithm. A novel phase compensation algorithm is proposed, leveraging the anti-interference weighting coefficients of array elements and the anti-interference output signal. Compared to the conventional minimum variance distortionless response (MVDR) algorithm, the proposed method features a simpler architecture and achieves phase compensation at a lower computational cost using the power inverse (PI) algorithm. Simulation experiments demonstrate the effectiveness of the compensation method, achieving a mean phase bias of approximately 0.25 degrees and a variance of 4.62 degrees. This level of accuracy makes it highly suitable for UAVs operating in challenging environments where precision and reliability are paramount.  
Keywords:anti-interference; phase bias compensation; power inverse algorithm +
Footnote †: journal:
# Deploying Secure Distributed Systems: Comparative Analysis of GNS3 and SEED Internet Emulator
## 2 Background
### Network Performance Comparison  
[PERSON] et al. [32] compared the performance of network emulation using Mininet with physical networks in terms of bandwidth and jitter. The study found no significant difference in bandwidth between physical and emulated networks, both reaching a maximum value of 10 MB/s. However, the jitter results showed a significant improvement in the emulated Mininet model compared to the physical network, with maximum values of 0.028 ms for Mininet and 0.908 ms for the physical topology. [PERSON] et al. [33] compared two network emulators, GNS3 and Mininet, in a data center topology. Their analysis showed that Mininet provided a more-stable and higher bandwidth compared to the GNS3 network. Mininet also demonstrated better resource utilization, resulting in higher speed and service accessibility. [PERSON] et al. [34] compared the throughput, latency, and jitter capabilities of OpenFlow and Linux ProGFE. The results indicated that Linux ProGFE had enhanced throughput performance compared to OpenFlow, with similar latency, but lower jitter. The study also showed that a more-complex network with increased flexibility, functionality, and capability did not always result in performance degradation.
## 5 Experiment
### Data Processing and Statistical Analysis  
After each trial, the performance index \(W_{e}\) in (9) was calculated. Moreover, we averaged the performance indices for 5 repetitions from the data of each participant during straight-line walking. Walking speed was affected by the step length because of the walking constraint induced by the metronome, and so to cancel out the difference between individuals, the dimensionless walking speed \(V_{D}\) was obtained by scaling to the leg length \(L\) of each participant, as suggested in [36]: \(V_{D}=v/\sqrt{gL}\). Data processing and statistical analysis, including the Kruskal-Wallis test (nonparametric one-way analysis of variance (ANOVA)) and multiple comparison tests, were conducted in MATLAB, while nonparametric two-way ANOVA was performed with R based on the Aligned Rank Transform [37]. For the one-way ANOVA, the effect of the control method on the dimensional walking speed for each surface was investigated. For the two-way ANOVA on operational efficiency, the surfaces and control methods with/without the load were considered as factors to be examined. Multiple comparisons were performed if there was a statistically significant difference in a particular test. A \(p\)-value of less than 0.05 was considered statistically significant. Noise in the experimental data was removed through applying a zero-phase 10 th order low-pass filter with a cut-off frequency of 10 Hz.  
Figure 10: Experimental environment: slope of 8 degrees and the same material as the tile surface.
## 3 Results
### Frequency-Domain Performance  
As shown in Figure 16, we obtained the S\({}_{\text{dd21}}\) measurement from DC to 12.35 GHz within the \(-3\) dB definition. In addition, the CM noise stopband is shown as the S\({}_{\text{cc21}}\) measurement. The frequency range was from 2.9 GHz to 16.2 GHz using a \(-10\) dB definition.
# Improvement of the Cross-Scale Multi-Feature Stereo Matching Algorithm
## 2 Algorithm Description
### Cost Computation
The traditional SAD and improved census joint matching cost function can be expressed as:  
\[C_{AD}(p_{i},d)=\frac{1}{3}\sum_{e\in[r,g,b]}\mathrm{I}_{I}^{C}(\omega_{i})- \mathrm{I}_{r}^{C}(\omega_{i}) \tag{3}\]  
Figure 4: Improved census transform. Figure 3: Census transform under central pixel mutation. Figure 2: Census transform. \[\mathrm{I}(\omega_{1})=\frac{1}{N}\sum_{j\omega_{i}}p_{j} \tag{4}\]  
\[\mathrm{C}(p_{i},d)=\alpha(C_{encus}(p_{i},d),\lambda_{encus})+(1-\alpha)(C_{AD}( p_{i},d),\lambda_{AD}) \tag{5}\]  
where \(\alpha\) is the weighting coefficient. In this formulation, \(C_{AD}(p_{i},d)\) represents the sum of absolute differences (SAD) cost, \(C_{encus}(p_{i},d)\) represents the improved cost of census, and \(C(p_{i},d)\) represents the cost after fusion. The fused cost is normalized via the natural exponential function, yielding the final composite cost-computation function as:  
Figure 2.0  
In the matching computation, the enhanced census transform cost exhibits superior performance over its conventional counterpart in weakly textured regions, while the SAD cost ensures higher matching accuracy in areas with repetitive patterns compared to the census-based approach. Through the fusion of these complementary cost modalities, the proposed method achieves an enhanced matching capability for weakly textured surfaces and significantly improves the algorithm's robustness. To validate the effectiveness of the proposed algorithm, we conducted experiments on weakly textured images selected from the Middlebury benchmark dataset. Figure 5 compares the disparity maps generated by three methods: AD-Census, Gradient-Census, and our algorithm. While the AD-Census cost partially reduces mismatch rates in weakly textured regions compared to conventional approaches, it still exhibits significantly higher mismatch errors than our method in these areas. Furthermore, the Gradient-Census method fails to effectively handle large-scale weakly textured surfaces due to its limited texture discrimination capability.
## 4 Conclusions  
The modern consumer is interested in the origin, composition and preservation methods used by food companies. Health-conscious eating and the consumption of food made from the most natural ingredients and in the most natural way possible have been given a prominent role. For this reason, minimal processing such as HHP and natural preservatives and bioactive substances such as spicy marinades and piperine are gaining ground. The study provided comprehensive insights into the effects of various marinades, HHP treatments and storage times on the texture, color, pH and microbiological properties of marinated meat (short loin slices).  
This study demonstrated the significant effect of HHP treatment and piperine enrichment on the texture, color, pH and microbiological properties of marinated meat. HHP treatment notably increased the hardness and altered the color of the samples, with higher pressures leading to more pronounced changes due to protein coagulation. Piperine enrichment slightly enhanced the redness of the meat and influenced the pH, albeit to a lesser extent than HHP. Importantly, HHP treatment significantly improved the microbiological safety of the samples, with pressures of 450 MPa and 600 MPa effectively reducing microbial counts while maintaining acceptable organoleptic properties. The presence of piperine further reduced the growth of microorganisms in the products. However, the piperine enrichment and storage time did not have strong effects on techno-functional properties, which is beneficial for consumers. Overall, the combination of HHP treatment and piperine bioactive component enrichment offers a promising approach to improving both the safety and quality of marinated meats.  
Conceptualization, G.J. and Z.F.; methodology, G.J. and Z.F.; validation, A.V. and K.L.H., formal analysis, G.J. and Z.F.; investigation, Z.F.; resources, A.V. and G.J.; data curation, Z.F. and T.C., writing--original draft preparation, Z.F. and T.C.; writing--review and editing, G.J. and I.D.; visualization, T.C.; supervision, L.F.F.; project administration, Z.F.; funding acquisition, F.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
This work was supported by the Flagship Research Groups Programme of the Hungarian University of Agriculture and Life Sciences. The authors are grateful to the Department of Livestock Products and Food Preservation Technology.  
The authors declare no conflicts of interest.
## 3 Result and Discussion
### Ultrasonic Pulse Velocity  
Ultrasonic pulse uses solid or liquid as its travel medium. According to its transfer characteristics, when an ultrasonic pulse was transferred from the transmitter to the receiver, specimens with more pores or cracks exhibited longer transmission paths and times. Therefore, the principle of ultrasonic pulse velocity can be used to assess the internal uniformity and density of the BJPA-GGBFS composite geopolymer. The results are shown in Figure 7A-F.  
Figure 7: _Cont._  
At an L/S of 0.3, 0.4 and 0.5, the ultrasonic pulse velocity increased by 37.3-50.7% (3 days), 36.1-54.2% (7 days), 35.5-49.6% (28 days) and 36.4-51.4% (56 days). This was mainly because the ratio of the alkali activator in the overall volume was lower at an L/S of 0.3.  
The latter phenomenon resulted from the BJPA not being fully involved in the polymerization process, resulting in larger pores within the specimen and a decrease in the density of the specimen, which reduced the ultrasonic pulse velocity and compressive strength.
## 3 Analyses and Results
### Forest Distribution of Northeast China Derived from HJ-1 Images
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Class**} & \multicolumn{4}{c}{**GT Samples**} & \multirow{2}{*}{**WI**} & \multirow{2}{*}{**UA**} & \multirow{2}{*}{**PA**} \\ \cline{2-2} \cline{6-9}  & **ENF** & **DNF** & **DBF** & & & & \\ \hline ENF & 84 & 5 & 12 & 3 & 1 & 0.03 & 0.80 \(\pm\) 0.03 & 0.76 \(\pm\) 0.005 \\ DNF & 8 & 100 & 10 & 6 & 4 & 0.20 & 0.78 \(\pm\) 0.04 & 0.75 \(\pm\) 0.005 \\ DBF & 12 & 10 & 213 & 10 & 8 & 0.68 & 0.84 \(\pm\) 0.02 & 0.84 \(\pm\) 0.004 \\ MF & 5 & 13 & 16 & 82 & 6 & 0.07 & 0.70 \(\pm\) 0.02 & 0.69 \(\pm\) 0.008 \\ SRF & 1 & 5 & 3 & 17 & 31 & 0.02 & 0.54 \(\pm\) 0.03 & 0.62 \(\pm\) 0.007 \\ \hline \hline \end{tabular} Note: GT: Ground Truth; WI: proportion of area mapped; UA: User’s Accuracy; PA: Producer’s Accuracy; ENF: Evergreen needleleaf forest; DNF: deciduous needleleaf forest; DBF: deciduous broadleaf forest; MF: Mixed forest; SRF: Strubland.  
\end{table} 
Table 5: Confusion matrix of the forest subcategories from HJ-1-based map with a 95% confidence interval. forest area: Daxing'an Mountains > Changbai Mountains > Xiaoxing'an Mountains > Songliao Plain > Sanjiang Plain > Hulun Buir region. In each sub-region, deciduous broadleaf forest accounted for the largest proportion among all types of forest, and deciduous needleleaf forest comprised the second largest area. Shrubland and evergreen needleleaf forest made up a relatively smaller proportion of all forested areas in each sub-region. Figure 5: Spatial distribution of forest area from three datasets in Northeast China: **(a)** HJ-1-based forest 2010, **(b)** GlobCover 2009, and **(c)** MCD12Q1 2009.
## 5 Evaluation
### Network Model  
The nodes in our network model have unique IDs and have location coordinates namely \(x\) and \(y\) deployed using a uniform random distribution. Initially, all the nodes have same amount of energy. Two nodes are called neighbors if they are within the transmission range of each other. All the results have been averaged on 100 different runs for varying distribution of nodes.  
For the energy analysis, we consider communication on Rayleigh fading channel. We take optimum constellation sizes for MIMO and SISO communication, same as suggested by [4]. All other values are assumed as mentioned in Table 1, otherwise stated. All nodes generate packets independently. We have used poisson distribution (\(\lambda\)) for packets generation per 10 seconds.  
We assume sink node to be located outside the square field (sensor nodes deployment) unless stated otherwise. The CCS is equipped with multiple antennas. Multi-hop operation based on an energy-efficient routing is used for intercluster communications. We assume signal to noise ratio (SNR) required to achieve a BER of \(10^{-3}\) based on [3]: 24.4 dB for SISO, 10.6 dB for SIMO, 14.1 dB for MISO, and 6.9 dB for MIMO. For performance analysis we implement and compare our scheme with CMIMO [3] and traditional multihop SISO approach.
# Dual Attention Fusion Enhancement Network for Lightweight Remote-Sensing Image Super-Resolution
## 4 Results
### Results of Real Remote-Sensing Images  
To further demonstrate the stability of the model, the reconstruction results of two real remote-sensing satellite images are shown in Figure 8. We use four different methods to upscale real satellite remote-sensing images by a factor of four for visual perception comparison. It can be observed that our model provides better visual perception in terms of both overall texture and detailed textures compared with other methods. This validates that our approach performs well on images captured by real remote-sensing satellites.
# Urban Traffic Signal Control under Mixed Traffic Flows: Literature Review
###### Abstract
Moreover, CVs or CAVs have advantages over existing traffic sensor technology because they are not limited by the line of sight like cameras and, as mentioned, collect large amounts of data at the microscopic level, which is convenient for studying traffic. Such large amounts of data will be generated by future mixed traffic flows containing classic vehicles and CVs or CAVs. The share of the latter will rise, decreasing the need for classic traffic sensors (inductive loops, cameras, radars, etc.). Although CVs can provide data on the microscopic level, those data must be pre-processed before they can be used as input for various TCS systems. Hence, having a lot of data requires data processing to be fast and efficient. Therefore, the question of how to process large quantities of data quickly and efficiently using the potential of CVs and CAVs as mobile sensors and actuators arise. CAV-based multi-agent based traffic control systems are a possible solution as a single agent can process a small piece of information acting on it, and more agents together can handle very complex processes, including a network of intersections [9]. Thus, another question is the applicability of the CVs or CAVs in the multi-agent system since both can also receive information about the traffic state ahead. Based on the received information, CVs or CAVs can also act accordingly, creating a closed-loop control system assuming the driver will use the received information like a CAV would. The presented topic overview leads us to the motivation for this review paper as similar reviews like [10; 11; 12] do not explicitly address the problem of mixed traffic intersection control. Thus, the contributions of this paper are as follows:* Overview of relevant research papers on the topic of urban TSC and mixed traffic flows with a systematic overview of conventional TSC strategies, and intersection state estimation methods. * Analyzed the impact of mixed vehicle traffic flows on TSC. * Suggestions for further research steps on the topic TSC of mixed traffic flows in urban environments. The rest of the paper is organized as follows. Section 2 describes the research methodology. In Section 3, the technological background is given. Conventional TSC strategies are described in Section 4. Intersection state estimation methods are presented in the following Section 5. Section 6 describes the impact of mixed traffic flows on TSC. The concept of the connected and autonomous vehicle-based TSC is described in Section 7. The discussion with open questions is given in Section 8, and Section 9 concludes the paper.
# Solar-Supplied Satellite Internet Access Point for the Internet of Things in Remote Areas
## 5 Discussions
### Modular Design to Cater to other Communication Modules  
The proposed satellite access point consists of three modules: solar, satellite, and the Wi-Fi hotspot, as shown in Figure 1. Instead of Wi-Fi, to provide communication to IoT, the proposed system can be extended to support other communication technologies, such as LoRaWAN [22] or Sigfox [23]. In the solar module, a solar controller is used to convert the voltage generated by the solar panel to DC output. The DC output can be used to power other communication modules. For example, if a LoRaWAN module is used, the solar-supplied satellite terminal become the Internet gateway for the LoRaWAN networks. The LoRaWAN clients (e.g., IoT equipped with a LoRaWAN interface) can then connect to the LoRaWAN module and access the remote IoT server (through the solar-supplied satellite terminal).