esa-sceva/satcom-chunk-collection huggingface dataset:
# Experimental Characterization of Thermal Conductivity with a New Compact Hot-Box Prototype
## 2 Materials and Methods
### Measurement and Data Acquisition  
Process monitoring was performed using surface temperature sensors and heat-flux thermopile sensors, which were fixed to the specimen surfaces. The sensors were connected to a LabJack T7-Pro data acquisition system, whose specifications are detailed in Table 3.  
To measure the surface temperature on the specimen in the hot chamber, five Type T surface thermocouples were used, distributed as follows:  
1. One thermocouple was placed at the center of the specimen.  
Four thermocouples were positioned 15 cm from the center, at the north, south, east, and west coordinates (Figure 3).  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Variables** & **Sensor** & **Range** & **Precision** & **Cost (USD)** \\ \hline Surface temperature & Type T & \((-30,\,250)^{\circ}\)C & \(\pm 0.5\) \({}^{\circ}\)C & 383 \\ Heat flow & Thermopile & \((-150,\,150)\) kW/m\({}^{2}\) & 7.7 mV/(W/cm\({}^{2}\)) & 420 \\ \hline \end{tabular}
\end{table}
Table 2: Characteristics of measuring instruments.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Equipment** & **Model** & **Characteristics** & **Cost (USD)** \\ \hline \multicolumn{4}{c}{14 analog inputs,} \\ Datalogger & LabJack T7-Pro & \begin{tabular}{c} Communication: USB, \\ Ethernet802.11b/ g WiFi \\ speed: 16 bits \\ PWM, 12 Vcc, 0.26 A \\ Voltage regulator \\ Thermal resistance \\ Energy meter \\ Hot-box architecture \\ \end{tabular} & \begin{tabular}{c} 735 \\ speed: 16 bits \\ PWM, 12 Vcc, 0.26 A \\ Kira dimmer AC \\ helical wire \\ DROK 200123 \\ Material + construction \\ \end{tabular} & \
\begin{tabular}{c} 22 \\ 110-125 W AC \\ 22 kW, 9999 kWh \\ 800 \\ \end{tabular} &
\begin{tabular}{c} 26 \\ 22 \\ 22 \\ 800 \\ \end{tabular} \\ \hline \end{tabular}
\end{table}
Table 3: Equipment used in the experimental cell.  
This arrangement allowed the uniformity of temperature distribution to be analyzed. The heat-flux density was measured using two PHFS-01e thermopile-type heat-flux sensors (FluxTeq LLC, Blacksburg, VA, USA), which were mounted on the specimen surface. The sensor distribution is illustrated in Figure 3:  
* One heat-flux sensor was placed at the center of the specimen.
* Another was located 15 cm south of the center.
* The specifications of these sensors are summarized in Table 2.
* On the cold chamber side, two Type T surface thermocouples were fixed on the specimen: one at the center and another 15 cm north of the center.  
To manage thermal load control and monitor and store measured variables, a custom interface was developed using Python version 3.11. Data acquisition was performed at a sampling rate of one (1) second, and each test generated a data file containing all measured variables. Data processing and analysis were conducted using MATLAB 2022b.
## 5 Conclusions  
In order to realize real time and accurate fault detection in complex electrical systems, one needs to obtain fault information of electric networks. In the process of power system operation, rich monitoring data includes the system's normal operation information. Once the fault of a system or equipment occurs, large amounts of fault feature information will be presented, such as operation sequence of protection and circuit breaker recorded by fault recorder, the switching action information, electrical quantities and measuring information provided by the Wide Area Measurement System. All of these have provided data guaranteed for accurate and reliable fault detection.  
In this paper, based on the fundamental of feature extraction about the fault coefficient, we have discussed the fault coefficient in complex electrical engineering. According to the research in this paper, the system failure is corresponding to the variable with the biggest coefficient in the first fault factor. For asymmetrical short circuit fault and symmetrical short circuit fault in IEEE 39-BUS New England power system, even if there is strong white Gaussian stochastic interference, the fault coefficient feature is still accurate and reliable. The feature extraction technology about fault coefficient proposed in this paper can extract fault characteristics with high efficiency, and it can satisfy the real-time and accuracy requirements of Wide Area Measurement System and Phasor Measurement Unit. The comparative analysis results of noise influence have also demonstrated the strong anti-interference ability and great redundancy of the fault coefficient feature in complex electrical engineering.
# Empowering Tourism Accessibility: A Digital Revolution in Pieria, Greece
## 2 Materials and Methods
### Data Collection Process  
The data collection process was carried out in two phases: route accessibility and point of interest (POI) accessibility. This dual approach ensured that both the general infrastructure for pedestrian movement and the specific accessibility features of individual sites were evaluated.  
In the case of route accessibility audits, the condition of pedestrian areas was the primary focus for route accessibility. This phase of data collection involved auditing sidewalks, crossings, ramps, and other relevant infrastructure that could impact a tourist's ability to navigate through the urban fabric. Trained auditors used the Seek & Go tool to map out routes, paying particular attention to obstacles such as broken tiles, steep inclines, and objects obstructing the path, like tables, chairs, or low-hanging trees. Detailed measurements were taken for sidewalk widths to ensure compliance with accessibility standards, as narrow sidewalks can significantly impede the movement of wheelchairs and other mobility devices.  
Figure 3: Definition of the study area using the Seek & Go auditing tool.  
Similarly, in the case of accessibility audits for POIs, comprehensive audits were realized to assess their accessibility features. Auditors collected data on horizontal routing elements (e.g., ramps and level entrances), as well as vertical routing elements (e.g., elevators). Additional data were gathered on accessible parking spots and signage to ensure that visitors could easily locate and access the studied POIs. Each point was meticulously evaluated using standardized forms to capture all relevant data, ensuring that users of the platform could depend on the information for their travel planning.  
The data collected during the audits were processed, validated, and integrated into the platform, allowing users to view the most accessible routes and POIs in the area under study. The platform provides users with an intuitive interface that includes cartographic data, enabling them to visualize routes and sites on a map. This visualization is enhanced by the ability to filter results based on user preferences, such as the need for wheelchair-accessible routes or POIs with specific accessible facilities.
# Shear Performance for Prestressed Concrete Hollow Core Slabs
## 3 Experimental Program  
### Materials  
To evaluate the shear performance of HCS, the concrete used for specimens had a specified compressive strength of 45 MPa, as shown in Table 1. The specified compressive strength of topping concrete was set at 24 MPa. Crushed gravel and crushed sand were used as coarse aggregates and fine aggregates in the concrete. The maximum size values of coarse aggregates for HCS and topping concrete were 19 mm and 25 mm, respectively, while that of fine aggregates was 5 mm.  
To examine the dynamic characteristics of concrete in relation to the concrete mix, a concrete cylinder with size of \(\phi\)100 \(\times\) 200 mm was fabricated. Curing was carried out under the same conditions for all specimens. The concrete compressive strength experiment was conducted according to days taken for specimen failure; the results are presented in Figure 2 and Table 2. The concrete compressive strength of HCS shown in Table 2 was obtained from 55 \(\times\) 55 mm cube samples extracted from specimens. The compressive strength values of HCS and of topping concrete averaged 48.2-48.7 MPa and 27.0-28.1 MPa respectively, which exceed the design strength. The compressive strength measured from the concrete cylinder of HCS averaged 46.8 MPa, which differs from that of the cube samples by 1.4 to 1.9 MPa.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Concrete**} & \multirow{2}{*}{\(f_{ck}\) (MPa)} & \multirow{2}{*}{**W/C**} & \multirow{2}{*}{**S/a (\%)**} & \multicolumn{6}{c}{**Unit Weight (kg/m\({}^{3}\))**} \\ \cline{5-8}  & & & & **W** & **C** & **S** & **G** & **AD** \\ \hline HCS & 45.0 & 0.32 & 43.8 & 120 & 380 & 856 & 1100 & 3.20 \\ Topping & 24.0 & 0.49 & 47.6 & 165 & 340 & 882 & 970 & 2.82 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Concrete mix proportions.  
To introduce prestress, the specimens were fabricated from strands (SWPC 7 BL). The strands had a yield strength of 1581 MPa and tension of 1860 MPa; those with diameters (\(\phi\)) of 12.7 mm and 9.5 mm were placed in the upper and lower parts to ensure the proper cross-sectional properties.
## 3 Experiment and Analysis
### Ablation Experiments
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & **Intact/F1** & **Slightly** & **Severely** & **Collapsed/F1** & **Mean/F1** & **Mean/P** & **Mean/R** & **Mean/IOU** \\  & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** \\ \hline U-Net & 81.93 & 50.05 & 51.51 & 56.48 & 57.78 & 56.82 & 58.67 & 40.53 \\ ResNet-50 & 84.91 & 52.77 & 49.82 & 57.66 & 58.16 & 59.26 & 57.05 & 40.91 \\ Deeplabv3+ & 81.13 & 51.02 & 53.01 & 48.97 & 56.13 & 55.27 & 57.17 & 39.06 \\ Our method & 83.62 & 53.31 & 56.63 & 70.95 & 64.35 & 64.36 & 63.73 & 47.15 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of results among semantic segmentation networks.
# Road Obstacle Detection Method Based on Improved YOLOv5
## 3 Methods  
### Effective Multi-Scale Feature Fusion Module  
#### 3.1.1 Efficient Multi-Scale Attention  
Efficient Multi-Scale Attention (EMA) [39] is an advanced mechanism rooted in Channel Attention (CA) [40]. Traditional methods of reducing channel dimensions often result in the loss of critical depth information, a challenge that the EMA module aims to overcome. The fundamental principle of EMA is to mitigate information loss during dimensionality reduction by grouping channels, thereby enhancing feature extraction capabilities.  
The EMA mechanism integrates triple parallel subnetworks that synergistically generate attention weights through cross-scale feature grouping. This architecture combines dual \(1\times 1\) convolutional branches with a \(3\times 3\) convolutional branch, enabling hierarchical feature abstraction while preserving the 98.3% computational efficiency of the baseline model. By implementing cross-dimensional interaction pathways, EMA achieves amplified multi-scale fusion through coordinated multi-receptive field analysis.  
The mechanism demonstrates dual enhancement: enriched feature abstraction through hierarchical attention propagation and expanded perceptual scope with only a 0.5% parameter increment, establishing optimal scale-aware feature representation. Its operational schematic appears in Figure 2.
# Reaction Forces and Apparent Thrust in Dual Oscillating Control Moment Gyroscopes
###### Abstract  
This paper investigates a controversial phenomenon: the supposed generation of thrust from a symmetric system consisting of two contra-rotating gyroscopes whose spin axes form equal and opposite polar angles with respect to the axis connecting their supports. An elementary mechanical model demonstrates that, for this configuration of gyroscopes, an internal moment arises within the system. This torque, although internally generated, is well known for playing a significant role in satellite attitude control using control moment gyroscopes (CMGs). The mechanical analysis considers the system of gyroscopes mounted on a platform or cart, which is supported at its front and rear ends. In this context, it was found that the resulting dynamic interaction causes unequal reaction forces at the support points, which do not obey the length-ratio rule predicted by static analysis. Such behavior can lead to misinterpretation of the net external thrust, despite the system being closed and momentum-conserving. In this context, the present paper clearly shows that no net force is allowed to develop.  
control moment gyroscope; reaction force; thrust; inertial propulsion Article
## 3 Results and Discussion
### CFD Simulations
#### 3.2.3 Simulation of the 16-Bar J-Ring Test  
The 16-bar J-ring test was also simulated through CFD tools by considering the parameters of the Bingham equation obtained from the results of the slump-flow test (Figure 14), as shown in Figure 18. The error rates for the different results of the tests are listed in Table 6.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Mix** & **Slump Flow** & \(t_{\text{500 Time}}\) & **Blocking Ratio** \\ \hline \(RW\) & 5.1 & 10.5 & 55.2 \\ W1.5 & 12.7 & 14.5 & 72.1 \\ W3.0 & 22.8 & 32.7 & 62.1 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Error rates (%) of the CFD simulation of the 16-bar J-ring test.  
Figure 16: Example of the simulation of the 3-bar L-box test in the \(W1.5\) mix.  
Figure 17: Linear simple regression between plastic viscosity and 3-bar L-box test.  
The results obtained in this test were modeled with varying accuracy by means of CFD tools. Thus, two different groups could be distinguished depending on the fitting quality:  
* On the one hand, there are slump flow and \(t_{500}\) time. The error rate for these results was higher with the RCWTB content. For example, the error rate of the 16-bar J-ring slump flow was 5.1% of the _RW_ mixture and 10.5% for its \(t_{500}\) time, while these values for the \(W\)3.0 mix were 22.8% and 32.7%, respectively. Nevertheless, these values were always within adequate limits according to the indications of other studies available in the scientific literature [63; 64], thus validating the adjustment of the Bingham equation conducted and the CFD model developed through the results of the slump-flow test. As for the slump-flow test (Figure 15), a more precise relationship of the plastic viscosity with the slump flow (Figure 19a) than with the \(t_{500}\) time (Figure 19b) was found. The plastic viscosity thus enabled us to explain and successfully simulate the free flow of SCC containing RCWTB in the long term regardless of the presence of obstacles simulating concrete reinforcements, which is in line with the trends found in other studies [46].
* On the other hand, the error rates obtained for the blocking ratio were high, in all cases greater than 55%. No clear trend with the RCWTB amount was found, nor a precise relationship with the plastic viscosity (Figure 19c). This property did not depend on the Bingham parameters, and the GFRP fibers may have a much more noticeable influence that could be further explored by other simulation approaches [48] or by considering meshes of lower size [46].  
Figure 19: Relationship (linear simple regression) between plastic viscosity and 16-bar J-ring tests: (a) slump flow; (b) \(t_{500}\) time; (c) blocking ratio.  
Figure 18: Example of the simulation of the J-ring test in the _W3.0_ mix.
# Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications
## 5 Graph-Based RA in D2D Networks
### Miscellaneous Methods
Increasing \(T_{RB}\) yields slightly better fairness that remains stable. A multiple small-cell scenario with a fixed number of channels and variable number of CUEs and DUEs is used as a base for the proposed distributed RA in [69]. A small cell serves different CUEs and DUEs, with the algorithm aiming to provide the necessary resources and minimize the interference between the cells and among the nodes associated with each one. The network is described as a graph with the small cells being its vertices, two of which are connected with an edge, if their mutual interference is greater than a predefined threshold. Then, channel allocation is performed via the Hungarian algorithm, subjected to maximizing the CUE satisfaction parameter (dependent on the user's throughput). Afterwards, channel selection for the small cells is performed via a potential game, while a coalition game is used for channels sharing between the CUEs and DUEs in each cell. Nearly exponential growth of \(R_{T}\) with the increase in \(N_{DUE}\) has been reported. The authors of [70] proposed a new graph-based clustering solution that achieves what they term \"pure D2D\", which describes channel allocation for DUEs without the involvement of the CUEs, in order to avoid mutual interference between the users, especially at the cell's edge. In addition, some RBs are only allocated to DUEs, multiple DUEs may utilize the same RB, and the RBs of the CUEs are orthogonal. The scenario includes a fixed number of CUEs and channels, and a variable number of DUEs. The network is modeled as a graph, with the CUEs and DUEs being the vertices, and edges existing between every two nodes that can potentially interfere with each other. Then, all nodes are grouped in clusters so that there are no shared RBs within a cluster. After the clusters' formation, they are refined so that nodes with better channel conditions may be chosen within each, through appropriate power allocations to meet their SINR requirements. This cluster reformulation is modeled as a tree that includes all potential nodes which should either be added to a cluster or not, depending on whether the SINR constraint is satisfied. As seen from the simulation results, the algorithm achieves a linear increase in the number of supported links, with the number of DUEs, while both the average throughput per user \(\bar{R}_{u}\), and the fairness \(\beta\) remain stable.
# Development of Simultaneous Dual-Resolution Digital Holography System
## 1 Introduction
However, the Sagnac interferometer is relatively complicated in optics; furthermore, the system reported is not very practical due to the phenomenon of spectrum aliasing. In this paper, we will present a novel dual-spatial-resolution holographic system to measure deformation, which has a relatively simple optical setup and can easily separate the spectra from two channels. By changing the combined focus length, the two holographic setups can observe different fields of view, i.e., one has a large and the other has a small field of view. To realize a simultaneous measurement, the polarization technique is used to avoid cross-interference between the two optical layouts [26]. Finally, based on the spatial carrier frequency technique [27], the reference beam is adjusted to introduce a different carrier frequency to obtain the spatial carrier fringes with different orientations in one speckle pattern image captured from the two holographic setups. The different oriented spatial carrier fringes enable the spectra of the two interferograms to be easily separated after a FT (Fourier transform), thus overcoming the main deficiency of spectrum aliasing reported in the dual-spatial-resolution shearographic system. The phase distributions of the two interferograms can be extracted and separated by windowing the spectrum to perform an IFT (inverse Fourier transform). The phase distributions can then be used to analyze and calculate the deformations. Different applications will be presented, and the practicability of this method is verified by the obtained experimental results.
# Development of A Loss Minimization Based Operation Strategy for Embedded BTB VSC HVDC
## 3 Determination of Embedded HVDC Operation Point
### System Total-Loss Minimization (STLM) Control
#### 3.1.2 Voltage Criteria  
The active/reactive power control of the BTB VSC HVDC can have a significant effect on the voltage of the near buses. Generally, embedded HVDC operates in \(AC\) voltage control mode. However, in this paper, we decided on the proper operating point in the reactive power setpoint control mode to maximize loss reduction and operate in \(AC\) voltage control mode to maintain the operating point.  
\[\underline{V_{i}}\leq V_{i}\leq\overline{V_{i}} \tag{4}\]  
in which  
\(\underline{V_{i}}\), \(\overline{V_{i}}\) is the minimum/maximum voltage at bus \(i\); and  
\(V_{i}\) is voltage at bus \(i\).
## 3 Results and Discussion
### Further Application Potential for Airborne Systems  
Through the above experiments and results, the suitable medium flow rate can be selected according to the heat flux of the actual electronic equipment in the airborne spray cooling equipment, and the flow rate can be adjusted appropriately when the heat flux is small, which can save energy consumption and achieve a better cooling effect. Due to the limited space on board and the trend towards integration and miniaturization of electronic equipment, the distance between the nozzle and the heating surface is very restricted. Using the conclusion that the optimal heat transfer performance is obtained when the heating surface is not completely covered, in practical application, the distance between the nozzle and the heating surface can be appropriately reduced according to the heating capacity of different equipment, and the droplet surface coverage can be adjusted near the optimal value, which not only improves the cooling efficiency, but also saves the equipment space. In addition, without changing the system structure, a certain concentration of additives can be added appropriately, which can significantly improve the heat transfer capacity.
## 3 Results and Discussion
### Influence of Aliphatic Amines on the Surface Tension Data  
Surface tension data at different temperatures were interpreted to comprehend the possible molecular interactions between aqueous taurine with D-glucose, as depicted inFigure 3a. However, an introduction of D-glucose generally increases the surface tension of water with cavity formation. The stabilization of taurine with D-glucose in aqueous media causes cavity formations, which in turn affects the surface interactions and surface energy [39]. The surface energy of cavity formation can be deduced, hereby, from the obtained surface tension numerical values of the solution's interface. As the glucose concentration increases in aqueous media, the added taurine molecules lead to a decrease in the numerical surface tension (\(\gamma\)) values at the various temperatures (298.15-318.15 K). Meanwhile, with the rising temperature, the adsorption process takes place with an expanse of dehydrated hydrophilic groups, which results in the surface energy slackening. Moreover, the small amount of surface energy indicates that the adsorption at the air/liquid interface is more favorable as compared to the bulk phase. Thus, the observed decreasing trend of the surface tension suggests that in aqueous taurine, a strong intermolecular force (IMF), including hydrogen bonding, was developed between N\({}^{8+}\) of taurine amino acid and O\({}^{8-}\) of water molecules in its aggregates [40; 41]. Further, the addition of glucose molecules as a solute results in the replacement of the taurine that was interacting with water, causing the weakening of IMF and hence, leading to a decrease in \(\gamma\) values. A linear decrease in the surface tension values was observed with the temperature rise (as shown in Figure 3b). With increasing temperatures, the molecules of D-glucose are directly interacting with the taurine molecules by possible hydrogen bonds between the -OH of D-glucose and (S-OH) groups of taurine molecules. We proposed these preferential interactions due to the decrease in surface tension and the comparatively strong binding of molecules as aggregates in bulk and then as free molecules at the interface. The surface tension on the interface depends on the temperature, which is attributed to the rise of the cohesive force between the taurine and water molecule, which in turn, increases the thermal activity and adhesive action [42; 43].