esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology
### Validation  
The developed CFD models incorporated the UDF codes and were validated against a published experimental measurement. The CFD modeling of conventional heat sinks was validated with the experimental study of [PERSON] et al. [39]. For validation purposes, the numerical investigations were conducted under a range of vibrational frequencies with the amplitude, supplied power, and air velocity of 0.005 m, 17 W, and 0.6 m/s, respectively. compared with the experimental measurements of [PERSON] et al. [39], the validation results show good agreement, as depicted in Figure 4a, with a maximum deviation of 3%.  
[PERSON] et al. [41] experimentally investigated the heat-transfer augmentation of flapping thin plate fins due to the sinusoidal excitation of the base under natural convection phenomena. Therefore, the CFD modeling of thin plate-fin heat sink was validated using the experimental measurements of [PERSON] et al. [41]. Numerical computations were performed using a thin plate fin with the dimension of 0.1 \(\times\) 0.025 \(\times\) 0.0004 m. In simulations, the vibration amplitude was varied, while the frequency and supplied temperature were kept constant at 59 Hz and 328.15 K, respectively. Figure 4b shows a strong agreement between  
Figure 4: Validation of the current study. (**a**) validation of conventional heat sink model at an amplitude of 0.005 m with [PERSON] et al. [39] (**b**) validation of thin plate-fin heat sink model at a vibrational frequency of 59 Hz. withPark et al. [41].  
Figure 3: Time independence test results. (**a**) conventional heat sink model (**b**) thin plate-fin heat sink model.  
numerical and experimental data, with a maximum percentage error of 2.6%. Thus, it can be concluded that the CFD modelings used in the present study can be confidently employed to numerically analyze the vibration-assisted thermal performance of conventional and thin plate-fin heat sinks.
# Energy Ratio Variation-Based Structural Damage Detection Using Convolutional Neural Network
## 5 Experimental Validation  
### Experimental Model  
In order to verify the feasibility of numerical simulation, the experimental platform is set up as Figure 11. The size, material parameters, and physical parameters of the experimental model are the same as those of the finite element model. The simple supported steel-beam used in this paper is 1 m in length, 0.1 m in height, 0.068 m in width, and 0.0045 m in waist thickness. The two sides of the beam are fixed by the masonry cement bearing with good stiffness to limit the horizontal displacement of the structure. The acceleration sensor is arranged on the beam to simulate the damage scenarios of single damage scenario S2 and multiple damage scenario S7.  
The notch damage simulation is made at the second unit, the second unit and eighth unit, respectively, as shown in Figure 12. The notch length is 0.05 m, the width is 0.068 m, the height is 0.026 m, and the damage area of the unit is 0.0047 m\({}^{2}\).
## 8 Technical Challenges for 6G Development
### Challenges in Achieving Tactile Internet  
A key obstacle in developing the tactile internet is the smooth fusion of communication, control, and computing into a single framework. Utilizing the mobile communication system as a core wireless network, together with its software and virtual network components, aids in merging them into a bidirectional real-time control loop, combining immediate control with efficient computing capabilities. Although still in preliminary phases, the tactile Internet encounters numerous unresolved research issues. Beyond tackling basic layer issues such as choosing waveforms and developing sturdy modulation techniques, smart strategies for separating and coordinating the control and user planes are essential to reduce signaling clutter and delays in the air interface. For diminishing end-to-end latency, it is crucial to delve into highly flexible network coding techniques and expandable routing protocols. Moreover, securing tactile Internet applications is critical, requiring robust mechanisms to bolster defenses against harmful activities. The guiding principle for the design of wireless tactile networks ought to enable human empowerment through authorization, rather than replacing human roles in innovation or service provision autonomously [1; 272; 32].
## 4 Dynamic Splitting Test of Sandstone after Corrosion by Strong Alkali Solution
### Specim Energy Analysis  
In order to better understand the influence of corrosion time on the process of sandstone deformation damage from the perspective of energy evolution, the variation law of transmitted energy of sandstone in dynamic impact deformation damage with corrosion time is studied. Since the incident shock air pressure is kept constant, the incident energy and dissipation energy are not further explored, where the incident wave energy \(\mathrm{E_{I}}\) reflects the wave energy \(\mathrm{E_{R}}\) and transmits the wave energy \(\mathrm{E_{T}}\) of the rock specimen, as shown in the relationship in Equation (9).  
\[\begin{array}{l}\mathrm{E_{I}}\mathrm{=A_{0}C_{0}E_{0}\int_{0}^{\tau} \varepsilon_{\mathrm{I}}^{2}(t)dt}\\ \mathrm{E_{R}}\mathrm{=A_{0}C_{0}E_{0}\int_{0}^{\tau}\varepsilon_{\mathrm{I}}^ {2}(t)dt}\\ \mathrm{E_{T}}\mathrm{=A_{0}C_{0}E_{0}\int_{0}^{\tau}\varepsilon_{\mathrm{I}}^ {2}(t)dt}\end{array} \tag{9}\]  
where \(\mathrm{A_{0}}\) is the cross-sectional area of the compression bar; \(\mathrm{E_{0}}\), \(\mathrm{C_{0}}\) are the moduli of elasticity of the compression bar material and the longitudinal wave velocity; \(\varepsilon_{\mathrm{I}}(t)\), \(\varepsilon_{\mathrm{R}}(t)\), \(\varepsilon_{\mathrm{T}}(t)\) are the incident, reflected and transmitted stress waves at time \(t\), respectively, and the compressive stress is taken as the positive direction; \(t\) is the duration of the stress wave.  
The variation curve of the ratio of transmitted energy to incident energy with corrosion time is shown in Figure 15.  
It can be seen that, in the corrosion at 1 d-14 d, the ratio of \(\mathrm{E_{T}}\) to incident energy of the specimen decreased from 1.39% to 1.23%, the ratio of transmitted energy corresponding to the uncorroded specimen decreased by 10.98%, and the change in this stage is more obvious; meanwhile, in the corrosion at 14 d-28 d, the ratio of transmitted energy decreased from 1.23% to 1.20%, corresponding to the uncorroded specimen decreasing by 13.48%, the change being relatively flat. The preliminary analysis of the reason is that with the prolongation of corrosion time, the specimen within the micro-cracks continues to sprout and expand, and the macroscopic performance of resistance to deformation deterioration and the transmitted wave intuitively reflects the dynamic stress changes in the specimen. In Section 4.1, it can be deduced from the specimen that the dynamic tensile strength with the prolongation of corrosion time is significantly reduced, so with the prolongation of corrosion time, the transmitted energy ratio decreases, and at 14 d-28 d, the transmitted energy ratio decreases smoothly, and the dynamic tensile strength decreases correspondingly with the law. At the same time, this is corroborated in Section 4.2, where the extent of sandstone damage increases with corrosion time.  
Figure 15: Transmitted energy percentage change curve with the corrosion time.
# Dual-View Integral Imaging 3D Display Based on Multiplexed Lens-Array Holographic Optical Element
## 3 Experiments and Results
### Experiments for Displaying Images on the Proposed Dual-View 3D Display
The reconstructed 3D image II has obvious horizontal and vertical parallaxes. Visualizations 2 and 3 clearly show the horizontal and vertical parallaxes between the \"A\", \"B\" and the real object. The resolution of reconstructed 3D image II is also almost the same as the conventional integral imaging 3D display. The resolution of 3D image II is also the same as the number of the image element \(70\times 70\) in EIA II. The 3D images I and II have the same resolution, according to the parameters of the micro-lens array, the resolution of the conventional integral imaging is \(70\times 70\). Therefore, the resolution in the dual viewing zones are the same as the conventional one. Figure 10: (a) EIA I and (b) EIA II. Figure 9: Experiment setup for the dual-view 3D display. It was observed that there is slight image crosstalk in the 3D image reconstructed in the left and right viewing zone. When projection beam I is projected onto the MHOE, the light produces diffuse reflection on the glass substrate of the MHOE, and the diffuse light can produce slight crosstalk with reconstructed 3D image II in the right viewing zone. Reconstructed 3D image I in the left viewing zone has slight crosstalk, which is caused by the same reason as in the right viewing zone.
# Overview of Blockchain Oracle Research
## 4 Results
### Number of Publications Per Year  
The first academic papers considering blockchain oracles appeared in 2016 and were equally distributed among the categories \"oracle theory (OT)\" and \"oracle applied (OA)\" [60; 61]. As Figure 3 shows, interest in the topic remained low until 2018. Until 2019, the number of papers concerning OT were slightly more than those discussing OA. The increase and the shift in the trend can be observable from 2019, with 2020 having four times more publications than in 2018 and 2021 having more than double the number of publications of 2019. Moreover, the number of papers regarding OA started to exceed that of OT by 2021. Although the 2022 sample concerns only the first two months, the imbalance in the number of publications appears to be confirmed. These data reveal that the topic has gained more impact and attention among academics, probably because of the higher developments of blockchain-related platforms.  
Figure 3: Publications per year.  
However, in absolute terms, the overall numbers remain low, with a peak of 62 publications in 2021 and only 162 publications in all six years of academic production. These numbers show that this is still a niche subject.
## 5 Results and Discussion
### RQ1: What State-of-the-Art Methods Exist for Optimizing LoRaWAN Energy Efficiency?
#### 5.1.2 State-of-the-Art Supervised and Unsupervised Learning Techniques  
The reviewed studies have used various supervised learning techniques to address the challenges of LoRaWAN networks. Methods such as k-means clustering, LSTM neural networks, DTs [25; 31] SVR [31], and DNN [43] are used to predict IoT packet timing as well as to optimize network parameters and enhance battery life. Techniques also include advanced models such as ARIMA [44], ANN, and SVM for improving measurement accuracy and managing network configurations effectively. Table 5 presents a summary of the supervised learning techniques adopted by the authors.
# Embedded Deep Learning for Ship Detection and Recognition
## 4 Architecture Design of ESDR-DL  
In order to reduce network traffic caused by video streaming from surveillance cameras, and resolve the limitation of low transmission bandwidth, we design an embedded architecture for deep learning, which connects surveillance cameras and performs image processing at the front end, as shown in Figure 6. In this ESDR-DL, the video stream is connected to a nearby TX2 through a LAN. To ensure real-time performance of video surveillance, each TX2 receives only one or two video streams. When the system is running, a Video Stream Receiver in TX2 is responsible for receiving the video stream accessed by the current device, decoding the video stream through a Video Stream Decoder, and inputting the decoded images to an Image Processor for detection. In the Image Processor, the DCNet model is used to detect and identify key parts of a ship (the bow, the cabin, and the stern), and classify the ship's identity based on these key parts, and output three prediction results. These prediction results are then used in a Voter for the decision of the ship's identity.  
We use NVIDIA Jetson TX2 as it is an industry-leading embedded computing device. Table 2 lists the main properties of TX2 related to our work in this paper.  
Figure 4: DCNet Training.  
Figure 5: Labels of bow, cabin and stern.
## 2 Methodology
The BOD was calculated by the following formula:  
\[\textbf{BOD5}=\textbf{Initial dissolved oxygen - Final dissolved oxygen (after 5 days)}\]  
**Determination of COD:** The COD value of effluent gives information about the oxygen required to oxidize total organic material. Determination of COD involves the oxidation of organic material in the effluent with a strong oxidizing solution/digestion solution (K\({}_{2}\)Cr\({}_{2}\)O\({}_{7}\), HgSO\({}_{4}\) and (98%) H\({}_{2}\)SO\({}_{4}\)). A catalyst solution was used to enhance the oxidation process, which comprised of 10 g of Ag\({}_{2}\)SO\({}_{4}\) in 500 mL of H\({}_{2}\)SO\({}_{4}\). To determine the value of COD in effluents, 1.5 mL of digestion mixture was placed in a closed vial along with 3.5 mL of catalyst solution and 2.5 mL of effluent at 150 \({}^{\circ}\)C in an oven for 2 h. The values of COD were estimated by taking the absorbance at 600 nm. The blank consisted of all solutions except effluents, while Potassium hydrogen phthalate (KHP) was used as the standard. The standard solution of 425 ppm concentration gave a 500 mg O\({}_{2}\)/L COD value. It was calculated by the procedure described by [20]. The COD was calculated by following formula:  
\[\textbf{COD}=\textbf{Standard factor}\times\textbf{Absorbance at 600 nm}\]  
where:  
\[\textbf{Standard factor}=\textbf{Concentration of standard/ absorbance of standard}\]  
**HPLC analysis of the industrial effluent:** HPLC analysis of the untreated and treated effluents was performed to monitor the products during the biodegradation of textile industrial effluents. The treated samples with maximum biodegradation at the most suitable conditions were selected for the HLPC analysis. The HPLC was performed on the model SHIMAZDU LC-20 AT with a C-18 column having a length of 25 mm and a 4.6 mm diameter. It was performed in the isocratic mode with a 1 mL/minute flow and a reverse phase mode. Acetonitrile to water (H\({}_{2}\)O) with a ratio of (60:40) was used as solvent system, while 20 \(\upmu\)L of the sample was injected for the analysis of each sample with a detection wavelength set at 254 nm [21; 22]. Retention time (\(t_{\text{R}}\)) was used to identify the compounds in the sample by comparing with the retention time of the standards. The stock solutions of the standards were prepared having a concentration of 0.1 mg/mL and injected volume of 20 \(\upmu\)L.
# Formation Control and Distributed Goal Assignment for Multi-Agent Non-Holonomic Systems
## 3 Stability of the System
From the Equation (28) it is clear that \(\dot{e}_{ix}\) and \(\frac{\partial V_{aij}}{\partial e_{ix}}\) have different signs and as a result \(\frac{\partial V_{aij}}{\partial e_{ix}}\dot{e}_{ix}<0\). To fulfil the condition that \(\dot{V}_{aij}=\frac{\partial V_{aij}}{\partial e_{ix}}\dot{e}_{ix}+\frac{ \partial V_{aij}}{\partial e_{iy}}\dot{e}_{iy}\) is less than zero the second term on the right hand side must be less than the first one taking their absolute values. This can be obtained by reducing \(k_{3}\) parameter (refer to Equation (16)). The property \(\dot{V}_{aij}\leq 0\) guarantees boundedness of both \(V_{aij}\) and \(\frac{\partial V_{aij}}{\partial e_{ix}}\). Finally one can state that the collision avoidance block that is input to the system shown in Figure 4 also has bounded output and both error components \(e_{ix}\) and \(e_{iy}\) in \(\Sigma_{1}\) are bounded. The above is true if the robot is not located close to the boundary of more than one robot at a time. This situation is unlikely because it leads to high controls that increase the distance between the robots quickly and therefore this will not be considered further. As shown in [7] collision avoidance is guaranteed if \(\dot{V}_{aij}\leq 0\) and \(\lim_{||[x_{i}\;y_{i}]^{\top}-[x_{j}\;y_{j}]^{\top}||\to r^{+}}V_{aij}=+ \infty\), \(i\
eq j\). Each robot needs information about positions of other robots in its neighbourhood to avoid collision (their orientations are not needed). It can be obtained using on-board sensors with the range equal to or greater than \(R\). In addition, robots need to know their position and orientation errors to calculate the tracking component of the control. This requirement imposes the use of a system allowing localization with respect to the global coordinate frame, because usually, the motion task is defined with respect to it. The author plans to conduct experiments on real robots in the near future. The OptiTrack motion capture system will be used to obtain coordinates of robots (positions and orientations) which is enough for control purposes.
# Review on Active and Passive Remote Sensing Techniques for Road Extraction
## 2 Overview of the Existing Data Acquisition Techniques for Road Extraction
### SAR Imaging Technology
#### 2.3.2 Typical Sensors  
A list of typical SAR satellite systems was recently presented in [152]. With the spotlight imaging mode, less than 1 m spatial resolutions can be achieved (e.g., RCM, Cosmo-Skymed, Terrasar-X, ICEYE). However, the area covered by the image is limited. In general, the swath width varies from 5 to 500 km, and for a wide swath, the resolution is of the order of tens of meters. Spaceborne systems use the X-, C-, S-, L- or P-band sensors. X-band sensors provide the highest resolution; however, their penetration into the vegetation canopy is limited [153]. Furthermore, the polarimetric capabilities of satellites vary significantly; for example, Alos-2, Radarsat-2 and Terrasar-X are fully polarimetric, providing HH, VV, VH and HV data (where HH is horizontal transmit, horizontal receive; VV is vertical transmit, vertical receive; VH is vertical transmit, horizontal receive and HV is horizontal transmit, vertical receive); Cosmo-Skymed and Sentinel-1 provide dual polarimetric HH and VV data and ICEYE provides single polarisation (VV) data. The incidence angle in most satellites can be adjusted between 10\({}^{\circ}\) and 60\({}^{\circ}\).  
The data recorded by Sentinel-1 of the European Copernicus system are openly and freely accessible. The Sentinel-1 data is similar to those of the previous European Envisat SAR; however, the data availability has increased because of the use of multiple satellites.  
When satellites fly in a constellation, short revisit times are possible. Cosmo-Skymed (four satellites) and SAR-Lupe (five satellites) constellations were designed to provide intelligence information. New commercial microsatellite constellations such as ICEYE (10/18 satellites launched), Spacety (18/56 launched) and Capella XSAR (18/36 launched), can provide good temporal coverage. A particular constellation is also formed by TerraSAR-X and Tandem-X, allowing single-pass interferometry. Based on the data collected by these satellite constellations, a global digital elevation model (DEM) has been developed [154].  
Airborne SAR systems that enable data acquisition at different wavelengths, higher resolutions and single-pass interferometry are more versatile than the spaceborne systems. Most of these airborne systems are used for research purposes; for instance, the German Aerospace Centre (DLR) has an F-SAR [155] system operating on a Dornier 228 aircraft, providing fully polarimetric data in the X-, C-, S-, L- and P-bands (maximum four bands simultaneously); this system enables single-pass interferometry in the X- and S-bands. In addition, several UAV SAR sensors are also available in the market; for example, SAR Aero offers 1.8 kg SAR sensors in the X-or L-band with 0.3 to 3 m for a range of up to 10 km.
# Defending against FakeBob Adversarial Attacks in Speaker Verification Systems with Noise-Adding +
## 6 Performance Evaluation
### Effect of Different Noise Types for Noise-Adding Defense  
In the previous experiments, we applied Gaussian noise for the noise-adding defense method. In this section, we evaluate the effect of different noise types for noise-adding defense. Besides the normal distribution [16] (i.e., Gaussian noise), we consider the following continuous probability distribution functions for generating noise with a mean of 0: uniform [17], logistic [18], and Laplace [19]. Moreover, we study noise with a discrete probability distribution that is a variation of the Rademacher distribution [20]:  
\[\Pr(K=k)=\left\{\begin{array}{ll}0.5,&\text{if }k=\sigma,\\ 0.5,&\text{if }k=-\sigma.\end{array}\right. \tag{16}\]  
Note that \(E[K]=0\) and \(Var[K]=\sigma^{2}\).  
Figures 8 and 9 show how the noise-adding defense with different noise types can affect the EER of GMM SV systems for the normal operations and the ASR of FakeBob  
Figure 7: Performance of the adaptive FakeBob attacks with \(\epsilon=0.002\) in GMM SV systems with noise-adding.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**a** & 0 & 10\% & 20\% & 30\% \\ \hline
**ASR (\%)** & 90.24 & 88.34 & 86.00 & 84.03 \\ \hline
**Total running time** & 31 h 3 min & 35 h 32 min & 40 h 17 min & 44 h 47 min \\ \hline \hline \end{tabular}
\end{table}
Table 5: Performance evaluation of adaptive FakeBob attacks with \(\epsilon=0.002\) in generating adversarial audios in GMM SV systems without noise-adding.  
adversarial audios (with \(\epsilon=0.002\)) for the defense. Here, FakeBob adversarial audios were generated by bypassing the plugin function as described in Section 5.1 and then applied to GMM SV systems with noise-adding defense to measure ASR. It can be observed that the noise-adding defense with the different noise types behaves in a similar way for both EER and ASR. Therefore, the choice of the noise type is not a major consideration for the noise-adding defense method. Moreover, Figure 9 uses an error bar to indicate the standard deviation of ASR when the Gaussian noise is applied. It can be observed that the standard deviation of ASR is relatively small, comparing with the average of ASR.
## 6 Results and Discussion
### Comparison with the State of the Art Approaches  
In the second part of the experimental study, the proposed binary bWSO-log method was compared with algorithms widely used in the literature.