esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Peer-to-Peer Energy Trading
### Smart Contracts in Energy Sector Applications
#### 3.4.2 Energy Sector Applications
With the increasing contribution of smaller assets to resilience, new challenges will arise, such as transmission coordination, DR delivery validation and contract settlement, while ensuring secure access to data. The authors used distributed ledger technology (DLT)/blockchain to securely track DR provisioning, emphasizing validation, data integrity, source, rapid logging and sharing within an authorized system across all necessary stakeholders (including TSOs, pools, etc. ), DSOs, BRPs and consumers. They designed and built the DR framework as a proof of concept on Hyperledger Fabric, using tangible assets in a lab environment to assess its applicability and performance. The lab is equipped with a 450 kW energy storage unit that provides DR services on demand from the system operator and is published on the blockchain. When there are fewer than 32 requests per second, the total execution time is less than 1 s. The memory usage of smart contracts did not exceed 1% for both active and passive nodes, while peer CPU usage remained below 5% across all simulations. The CPU consumption of smart contracts has remained below 1%. Scalable implementation results allow DLT to be deployed in the real world to facilitate the development of flexible markets using blockchain technology. In [106], the authors say government subsidies enable more families to install renewable energy sources, such as photovoltaic (PV) panels, to become grid-independent and save money. Consumers can sell excess electricity to the grid only at regulated prices in Romania. Allowing consumers to sell the surplus back into the local network can increase their number. Consumers will pay less for power that is not subject to grid fees, which leads to lower prices. Peer-to-peer contracts signed at the micro (G) level can facilitate this exchange. The authors introduced a new trading platform based on P2P smart contracts to trade surplus power to consumers in a micro-local network. Several trading scenarios are shown, which allow trading depending on the locations of the participants, instant active energy demand, maximum daily energy consumption and on a first come, first served basis in the blockchain-based trading ledger. The Small Grid, Low Voltage (LV) model is used to test the technology intended for real-world deployment. We compare the transferred amounts and financial rewards for different scenarios.
# A Survey of Algorithms and Systems for Evacuating People in Confined Spaces
## 3 Evacuation Wayfinding Algorithms
### Off-Line Evacuation Wayfinding Algorithms
#### 3.1.4 Lattice Gas Model-Based Algorithms  
Since a pedestrian flow is a many-body system [72] that is composed of strongly-interacting persons, lattice gas models that consider pedestrians as particles on the square lattices have attracted attention since the 1980s. The research in [51] utilised a lattice gas model to simulate the process of a pedestrian flow evacuating a hall; the hall was represented by square lattices, and evacuees were randomly distributed over the lattices; each evacuee could either hold still or move in four directions: forward, backward, left and right; evacuees moved in the preferential direction with no back step and could not overlap on lattices occupied by other evacuees; different dynamical patterns such as arching, flattening and pitting were observed in computer simulations; experimental results indicated that the dynamical phase transition from the choking flow to the decaying flow occurred at a critical time. The study in [52] employed a lattice gas model to study the evacuation time for a crowd to escape from a hall through a single exit; evacuees were modelled as biased random walkers and movedin preferential directions; the hall was represented by square lattices, and each square lattice could contain contain up to one evacuee at a time; the spatio-temporal distribution of evacuation time of evacuees was derived from simulations; the experimental results showed that the evacuation time of an evacuee depended highly on its initial position within the hall; the effects of the exit width, initial population density and urgency level were also investigated in the experiments.
## 3 Results
### Volatile Compounds
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Volatile** & **KI** & **T0** & **T1** & **T2** & **T3** \\ \hline
**Hydrocarbons** & & & & & \\
2-E-octene & 809 & ND & ND & 1545 \(\pm\) 145 & 1888 \(\pm\) 536 \\
2-Z-octene & 816 & ND & ND & 1228 \(\pm\) 147 & ND \\ _Total hydrocarbons_ (\(\Sigma\)) & & ND & ND & 2773 \(\pm\) 292 & 1888 \(\pm\) 536 \\
**Aldehydes** & & & & & \\ \hline (E)-2-Pentenal & 748 & 3975 \(\pm\) 250 d & 34,862 \(\pm\) 1209 c & 33,744 \(\pm\) 799 b  & 22,541 \(\pm\) 723 a  \\ Hexanal & 803 & 32,637 \(\pm\) 2008 a  & 46,946 \(\pm\) 868 b  & 54,638 \(\pm\) 2225 c  & 90,102 \(\pm\) 395 d  \\ (E)-2-Hexanal & 851 & ND & 4812 \(\pm\) 161 a  & 7289 \(\pm\) 406 b  & 11,901 \(\pm\) 409 c  \\ Heptanal & 901 & 1328 \(\pm\) 123 a  & 4654 \(\pm\) 403 b  & 5570 \(\pm\) 469 c  & 16,596 \(\pm\) 677 d  \\ (E,E)-2-A-Headenian & 908 & ND & 17,550 \(\pm\) 4010 a  & 25,314 \(\pm\) 1190 b  & 14,631 \(\pm\) 1445 a  \\ (E)-2-Heptpenal & 954 & 2166 \(\pm\) 318 a  & 95,008 \(\pm\) 738 b  & 56,474 \(\pm\) 2760 b  & 109,829 \(\pm\) 6641 c  \\ (E,E)-2-4-Heptdenian & 995 & 28,023 \(\pm\) 1536 a  & 281,746 \(\pm\) 9605 c  & 253,474 \(\pm\) 4111 b  & 338,112 \(\pm\) 13,035 d  \\ Octan & 1002 & 7425 \(\pm\) 965 a  & 38,155 \(\pm\) 3868 b  & 48,629 \(\pm\) 4496 c  & 108,931 \(\pm\) 8382 d  \\
2,4-Heptdenian & 1009 & 2024 \(\pm\) 208 a  & 123,654 \(\pm\) 4945 b  & 14,258 \(\pm\) 4930 c  & 406,889 \(\pm\) 12,144 d  \\ (E)-2-Octenal & 1056 & ND & 20,883 \(\pm\) 713 a  & 24,107 \(\pm\) 1092 b  & 42,758 \(\pm\) 1391 c  \\ Nonanal & 1103 & 1783 \(\pm\) 198 a  & 25,040 \(\pm\) 905 b  & 29,285 \(\pm\) 1501 b  & 203,362 \(\pm\) 9729 c  \\ Nonanal & 1158 & ND & ND & 11,815 \(\pm\) 1128 a  & 25,786 \(\pm\) 988 b  \\ \hline
**Alcohols** & & & & & \\ \hline
1-Pentanol & 762 & ND & 2255 \(\pm\) 607 a  & 2527 \(\pm\) 199 a  & 23,617 \(\pm\) 2435 b  \\
1-Hexanol & 870 & ND & 1748 \(\pm\) 2052 ab  & 454 \(\pm\) 88 a  & 2870 \(\pm\) 702 b  \\
1-Heptanol & 970 & ND & 914 \(\pm\) 633 a  & ND & 8945 \(\pm\) 2214 b  \\
1-octen-3-ol & 979 & ND & 1112 \(\pm\) 404 a  & ND & 16,833 \(\pm\) 857 b  \\
1-Octanol & 1072 & ND & ND & ND & 14,544 \(\pm\) 5097  & 14,544 \(\pm\) 5097  \\ _Total alcohols_ (\(\Sigma\)) & & ND & 6029 \(\pm\) 2217 a  & 2981 \(\pm\) 266 a  & 66,809 \(\pm\) 10,615 b  \\ \hline
**Other** & & & & \\ \hline
1,2,3-Propanotriol, triacetate & 1362 & 15,242 \(\pm\) 8033 a  & 17,477 \(\pm\) 4521 a  & 7572 \(\pm\) 3551 a  & 62,884 \(\pm\) 32,025 b  \\ \hline
**Furans** & & & & \\ \hline \begin{tabular}{c} Furam-2-Pentyl \\ _Total funms_ (\(\Sigma\)) \\ \end{tabular}  & 991 & ND & 13,307 \(\pm\) 8451 a  & 7694 \(\pm\) 2791 a  & 103,251 \(
# Experimental Demonstration of Beam Scanning of Dual-Metasurface Antenna
###### Abstract  
Beam-scanning antennas are employed in a wide range of applications, such as in satellite communications and 5G networks. Current commercial solutions rely mostly on electronically reconfigurable phased arrays, which require complex feeding networks and are affected by high losses, high costs, and are often power-hungry. In this paper, a novel beam scanning architecture employing a pair of planar metasurfaces, for use in thin reconfigurable antennas, is presented and experimentally demonstrated. The structure consisted of a radiative passive (non-reconfigurable) modulated metasurface, and a second metasurface that controls beam pointing, operating as a variable-impedance ground plane. Unlike other existing approaches, surface impedance variation was obtained by on-plane varactor diodes, no vias and a single voltage bias. This paper presents a design procedure based on an approximate theoretical model and simulation verification; a prototype of the designed antenna was fabricated for operation in X band, and a good agreement between measured results and simulations was observed. In the presented simple embodiment of the concept, the angular scanning range was limited to \(10^{\circ}\); this limitation is discussed in view of future applications.  
beam steering; leaky-wave antenna; reconfigurable metasurface; varactors +
Footnote †: journal: Electronics Letters  
1
Footnote 1: email: {1,4,5,6,7,8,9,10,1  
One of the most recent uses of metasurfaces is as refracting or reflective intelligent surfaces [19; 20; 21], also beamformers [22] for satellite-terrestrial networks have been revamped.  
In this paper, a novel fixed-frequency beam scanning mechanism is introduced and demonstrated. The main goal of the present study was to investigate the potential of beam steering via distributed varactor diodes with a _single_ DC control, i.e., on-plane varactors and no vias: this can be realized with existing standard low-cost technologies (e.g., pick-and-place). Using the metasurface paradigm, varactors can act as variable (reactive) loads in a suitably designed texture, yielding a variable impedance surface, with a surface impedance value controlled by the DC bias.  
By combining a modulated upper metasurface (responsible for radiation) with a reconfigurable impedance plane (responsible for beam scanning), we effectively separated RF wave propagation from DC bias, while maintaining a very small form factor.  
In this paper, Section 2 illustrates the adopted design techniques and describes the geometry of the designed antenna, while simulation results and experimental measurements of the fabricated prototype are reported in Section 3. In Section 4, these results are discussed and future work is outlined. Finally, conclusions are drawn in Section 5.
## 5 Experiment
### Open-World Evaluation
#### 5.5.2 Results  
Figure 6 shows the results of WF attacks in the open-world scenario. Attackers may use high confidence thresholds to reduce false positives, resulting in higher precision but lower recall. It is also possible for the attacker to sacrifice precision to capture the user's access to the monitored websites as much as possible. Therefore, we use the \(F_{1}\)-score to balance these two metrics. Like the closed-world results, our bionic traffic is more effective than HDA. It significantly improves the detection ability of the Var-CNN model. To a certain extent, our method is more practical than TF. For example, its performance is more stable as the threshold changes in the 10/15/20-shot settings. Moreover, the model trained with the SRP-based cumulative feature performs the best when the threshold grows. This phenomenon indicates that our bionic traces and the SRP-based cumulative feature give more detailed information about monitored websites. It can help the model better understand the distinction between different websites.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **5-Shot** & **10-Shot** & **15-Shot** & **20-Shot** \\ \hline DF [24] & \(1.2\pm 0.3\) & \(8.9\pm 3.4\) & \(58.6\pm 6.5\) & \(85.2\pm 2.3\) \\ TF [11] & \(84.5\pm 0.4\) & \(86.2\pm 0.4\) & \(86.6\pm 0.3\) & \(87.0\pm 0.3\) \\ Var-CNN [10] & \(37.4\pm 2.8\) & \(69.4\pm 1.8\) & \(79.9\pm 3.5\) & \(88.1\pm 0.2\) \\ Var-CNN + HDA [14] & \(76.9\pm 2.4\) & \(87.1\pm 0.6\) & \(89.8\pm 0.4\) & \(90.6\pm 0.4\) \\ \hline Var-CNN + BionicT & \(78.8\pm 0.3\) & \(87.9\pm 0.7\) & \(90.2\pm 0.2\) & \(91.3\pm 0.1\) \\ Var-CNN + BionicT * & \(79.3\pm 0.3\) & \(88.1\pm 0.2\) & \(90.2\pm 0.3\) & \(91.0\pm 0.3\) \\ \hline \hline \end{tabular}  
* Using the proposed SRP-based cumulative feature.  
\end{table}
Table 4: Results of closed-world WF attack on [PERSON]\({}_{100}\). Metrics: accuracy.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **5-Shot** & **10-Shot** & **15-Shot** & **20-Shot** \\ \hline CUMUL [22] & \(72.2\pm 1.7\) & \(79.7\pm 1.4\) & \(83.3\pm 2.0\) & \(85.9\pm 0.6\) \\ k-FP [4] & \(79.3\pm 1.0\) & \(83.9\pm 1.0\) & \(85.9\pm 0.6\) & \(87.5\pm 0.8\) \\ \hline DF [24] & \(3.2\pm 0.6\) & \(66.4\pm 5.3\) & \(89.3\pm 1.3\) & \(90.3\pm 2.4\) \\ TF [11] & \(92.2\pm 0.6\) & \(93.9\pm 0.2\) & \(94.4\pm 0.3\) & \(94.5\pm 0.2\) \\ Var-CNN [10] & \(24.6\pm 3.0\) & \(61.9\pm 4.3\) & \(79.3\pm 2.6\) & \(87.9\pm 0.7\) \\ Var-CNN + HDA [14] & \(59.7\pm 1.5\) & \(74.7\pm 2.6\) & \(86.4\pm 1.3\) & \(90.7\pm 0.8\) \\ \hline Var-CNN + BionicT & \(76.3\pm 2.4\) & \(92.5\pm 0.3\) & \(95.1\pm 0.1\) & \(95.7\pm 0.2\) \\ Var-CNN + BionicT * & \(78.2\pm 0.6\) & \(93.1\pm 0.2\) & \(95.0\pm 0.2\) & \(96.1\pm 0.2\) \\ \hline \hline \end{tabular}  
* Using the proposed SRP-based cumulative feature.  
\end{table}
Table 3: Results of closed-world WF attack on AWF\({}_{100}\). Metrics: accuracy.
## 6 Experiments and Results
### Translating an Object along the Links  
The next experiment (Figure 17) demonstrates the robot's ability to convey the travelling object along the arm from the arm's base to the last link without bending the arm, unlike in conventional arms. The movement begins at step (A). At this point, the mobile actuator closes its gripper on a ball suspended above it. Once the gripper grasps the ball, the mobile actuator moves to the third joint. It rotates this joint by 26 degrees, as shown in step (B). Next, in step (C), the mobile actuator moves to the last link to drop the ball into the target bowl. After the ball has been successfully dropped, the mobile actuator resets the arm to its initial position (D), as shown in Video S1.
## 2 Materials and Methods
### Computational Fluid Dynamics Model  
The physical domain was discretized in 3.305 \(\times\) 10\({}^{6}\) tetrahedral elements using ICEM CFD v.18 (ANSYS Inc., Canonsburg, PA, USA). The smallest element size was chosen according to previous mesh independence studies on stented coronary artery models [10; 11] and was approximately one seventh of the strut thickness, which enabled a good description of the blood flow at the scaffolded segment. The hemodynamic field was computed by solving the governing equations of the unsteady, incompressible fluid motion with the commercial finite volume based software Fluent v.18 (ANSYS Inc.). A typical human LAD flow waveform [12] (mean flow-rate of 90.17 mL min\({}^{-1}\)) was applied at the inlet. The mean flow-rate was estimated from patient's angiography using a frame count method, which accounts for the number of cine frames with the radio-opaque liquid flowing in a coronary artery segment [13]. A flow-split 44.2%:9.5%:6.4% for the distal main branch and side branches, respectively, was imposed at the outlets [14]. No slip-condition was applied to the arterial and scaffold walls, which were defined as rigid. The blood was described as an incompressible, non-Newtonian fluid, implementing a Bird-Carreau constitutive law with \(\mu_{\infty}\) = 0.0035 kg m\({}^{-1}\) s\({}^{-1}\), \(\mu_{0}\) = 0.25 kg m\({}^{-1}\) s\({}^{-1}\), \(\lambda\) = 25 s, n = 0.25, and a density of 1060 kg m\({}^{-3}\)[15]. The solver settings are reported in [10].  
The local hemodynamics of the patient-specific case was analyzed in terms of WSS descriptors. In particular, given the definition of WSS:  
\[\overset{\rightarrow}{\tau}_{w}=\overset{\rightarrow}{n}\overset{ \rightarrow}{\tau}_{ij} \tag{1}\]  
where \(\overset{\rightarrow}{n}\) is the normal vector to the arterial wall surface and \(\overset{\rightarrow}{\tau}_{ij}\) is the fluid viscous stress tensor, the time-averaged WSS (TAWSS) was calculated as [16]:  
\[TAWSS=\frac{1}{T}\int\limits_{0}^{T}|\overset{\rightarrow}{\tau}_{w}|dt \tag{2}\]  
where \(T\) is the duration of cardiac cycle. Therefore, the TAWSS enables to analyze the overall effects of the temporal variation of the WSS over the cardiac cycle along the coronary artery lumen.
## 6 Sixth-Generation (6G) Testbeds and Platforms  
As 6G strides towards reality, testbeds emerge as crucial proving grounds. These simulated environments bridge the gap between theoretical concepts and practical implementations, allowing us to prototype cutting-edge technologies, assess their performance, foster collaboration, and uncover challenges before they hinder real-world deployment. This section dives into the diverse landscape of 6G testbeds, illuminating their essentialelements, deployments, and future directions, ultimately paving the path for a robust and insightful journey into the hyperconnected 6G era.  
In this section, we explore the creation of testbeds intended for comprehending channel characteristics and confirming key technologies. Two primary types of testbeds are highlighted: those specifically crafted for 6G channels and those focused on 6G key technologies.
## 4 Engineering Example
### Accuracy Analysis of the Algorithms  
The initial exploration values, exploration step size, and termination step size for the improved modular vector method are presented in Table 5[38; 39]. For the genetic algorithm, the parameter ranges are displayed in Table 6, with a population size of 100, 200 generations, a cross-over probability of 0.95, and a mutation probability of 0.005 [40; 41]. Regarding the particle swarm algorithm, the parameter ranges and maximum flight speed are specified in Table 7, with a population size of 100, a maximum of 200 iterations, an inertia weight of 0.90, a particle position update constraint factor of 1, and weight coefficients of 2 for tracking individual optimal positions and group optimal positions [42; 43]. The simulated annealing algorithm is initialized with a temperature of 700, which is consistent with the initial parameters of the improved modular vector method. The coefficient of temperature drop is set to 0.95, and the self-adaptive coefficient is also 0.95 [44; 45]. To ensure the reliability of the experimental results, 20 experiments are conducted for each of the mentioned algorithms, and the outcomes with the smallest root mean square error are selected for comparison, as depicted in Figure 8.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Category** & \(q\) & \(tg\beta\) & \(\theta(^{c})\) & \(S_{1}\)/m & \(S_{2}\)/m & \(S_{3}\)/m & \(S_{4}\)/m \\ \hline Lower limit of value & 0.50 & 1.00 & 60 & 0 & 0 & 0 \\ Upper limit of value & 1.00 & 3.00 & 90 & 40 & 40 & 40 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Parameter values of the genetic algorithm.  
Figure 7: Inversion flow of four intelligent algorithms.  
Figure 8 reveals that the fitting root mean square error of the improved modular vector method is 64.31 mm, surpassing the fitting results of the genetic algorithm (70.47 mm), particle swarm optimization algorithm (72.82 mm), and simulated annealing algorithm (75.45 mm). Notably, the fitting root mean square error of the improved modular vector method accounts for only 1.79% of the maximum measured subsidence value (3598 mm). This outcome substantiates the accuracy of the fitting results achieved by the improved modular vector method.  
The inversion results of the improved modular vector method are detailed in Table 8, showcasing relative errors in the inversion outcomes \(q\), \(tg\beta\), and \(\theta\), which do not exceed 10%. This evidence supports the alignment of the initial exploration values--as determined by the pattern recognition of mining subsidence--with the inversion results, to a certain extent.
# Highlight Removal Emphasizing Detail Restoration
## 4 Results
### Detail Analysis  
Information hidden in image details is often crucial, and bright image details are essential for practical applications such as object detection and tracking. Therefore, an excellent highlight removal algorithm should have the ability to enhance image details. This paper compared the detail information of the images after highlight processing, as shown in Figure 7. The detail information after restoration was compared between the algorithm from references [10,32], which performed well in the comparison mentioned above, and the algorithm proposed in this paper.  
As shown in Figure 9, it was observed that the highlight removal method proposed in this paper excelled in detail restoration compared to the existing methods. This is particularly evident in the weld seam images. Additionally, in various other environments, the highlight removal approach presented in this paper outperformed the existing methods in terms of detail.  
Therefore, the application scenarios of this method can be welding or industrial production scenarios. Among them, welding plays a vital role in industrial production, and weld quality is key to ensuring structural integrity. Detecting a weld can effectively reduce the potential risk and ensure the safety of the connection point. The timely identification and repair of welding defects can prevent product failures during use, thereby reducing the cost of later maintenance and replacement. By using effective inspection methods, quality problems can be eliminated before the product leaves the factory and production efficiency can be improved. In the automated welding process, timely and accurate detection helps to quickly eliminate nonconforming products and ensure the continuity and stability of the production workflow.
# Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites  
[PERSON]  
1 Center for Global Discovery and Conservation Science (GDCS), Arizona State University, Tempe, AZ 85281, USA; [EMAIL_ADDRESS] (J.L.); [EMAIL_ADDRESS] (D.E.K.)1 Center for Global Discovery and Conservation Science (GDCS), Arizona State University, Tempe, AZ 85281, USA; [EMAIL_ADDRESS] (J.L.); [EMAIL_ADDRESS] (D.  
mid-spatial resolution satellite images (e.g., Landsat-8, Sentinel-2) or high-resolution images with low temporal frequency (e.g., IKONOS, Worldview) [3; 4; 10; 11; 12; 13]. Coral reef mapping could benefit from high temporal frequency satellite sensors (e.g., Planet Dove).  
Mapping benthic composition in shallow coastal environments requires multiple inputs, including sea surface reflectance, bottom (or benthic) reflectance, and bathymetry to identify different habitats using either an object- or a pixel-based approach [2; 14]. In particular, bathymetry information is central to identifying different benthic surfaces within distinct coastal geomorphic zones. Moreover, bottom reflectance retrieved from satellite images follows the removal of water column attenuation effects using radiative transfer modeling techniques [15]. Here, we developed a comprehensive object-based mapping approach that provides bathymetry estimation, bottom reflectance retrieval, and object-based classification, all using Planet Dove satellite images. We applied and verified our approach in three coastal sites located in the southeastern Dominican Republic using GPS-referenced underwater video and transducer bathymetry field data. We then performed an accuracy assessment analyzing different benthic habitat types and bathymetric ranges. As part of this research, we also investigated the effects that benthic habitat reflectance, bathymetry, and water column attenuation have on Dove-derived coral reef habitat products.