esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Experimental Results
### Network Performance Analysis  
In the previous sections it has been demonstrated that the embedded query-respond is the most efficient communication architecture for control and monitoring of smart microgrids, as well as the latency network requirements are fulfilled. In this section, the network usage and the bandwidth requirements are evaluated. With this goal, periodic query-response queries tests have been carried out, where information is transmitted from each peer at a frequency of 1 Hz and 100% of TCP load.  
Figures 16 and 17 show the network usage generated by peers in the network and the bandwidth utilization (per peer), respectively. The total traffic generated by 25 peers in Figure 16 is around 400 kBps. The traffic is much lower than the bandwidth provided by the Ethernet installation (Ethernet's 100 BaseT twisted pair cable (UTP)), which would possibility the execution of a large number of nodes. Otherwise, the average bandwidth per peer (Figure 17) is around 1200 bytes/s inbound and 1600 bytes/s outbound. These results show that both network usage and average bandwidth meets the distributed control microgrid requirements (Table 1).
## 5 Results and Analysis
### Component Analysis  
#### 5.2.1 Bent Bolt  
The stress contour and deformation of the bent bolts of the unreinforced specimen are shown in Figure 9a. The internal surface began to yield (the Mises stress exceeded 400 MPa) when the moment increased to 113 kN\(\cdot\)m, and the deformation grew quickly after yielding. When the moment reached 193 kN\(\cdot\)m, most of the bent bolt entered the plastic stage, but only a limited region (the mid-span internal surface) reached the ultimate stress (500 MPa).  
As shown in Figure 9b, with the SSCP sharing the load, the stress and deformation of the bent bolt were relatively low under the same moment (M = 87 kN\(\cdot\)m). Moreover, the ultimate moment was obviously increased (464 kN\(\cdot\)m) and the stress in the ultimate stage was higher. Nearly the whole bolt yielded and the midrange reached the ultimate  
Figure 9: Mises stress (Pa) and deformation results (mm) of bent bolts at different stages of (**a**) unreinforced specimen and (**b**) reinforced specimen.  
stress, resulting in considerably larger deformation (543 mm) than that of the unreinforced specimen (516 mm).
# A Survey of Wi-Fi 6: Technologies, Advances, and Challenges
## 4 OFDMA in Wi-Fi 6
### Advances on the PHY Layer
#### 4.1.2 RUs in Wi-Fi 6  
To support fine-bandwidth granularities, Wi-Fi 6 uses a subcarrier spacing four times narrower than Wi-Fi 5 (78.125 kHz vs. 312.5 kHz), which is visualized in Figure 2(b). Narrower RUs compared with legacy Wi-Fi help to increase the robustness of multipath but they are also more sensitive to noise. The number of available RUs within a channel depends on its bandwidth and the RU. For instance, an 80 MHz channel bandwidth may contain a single 996-tone RU or 16 orthogonal 52-tone RUs. Table 6 lists all possible RU sizes and the maximum number of RUs according to the channel width.  
Figure 7 depicts the various RU sizes supported in a 20 MHz channel. We have:  
**data subcarriers:** these subcarriers transport data;  
**guard subcarriers:** these subcarriers comprise 11 tones in total in a 20 MHz channel and are located at the beginning and end of the channel;  
**null subcarriers:** these subcarriers separate different subcarriers; with guard subcarriers, they help to relieve interference from adjacent channels and sub-channels;  
**DC (direct conversion) subcarriers:** these subcarriers indicate the center of the channel; their sizes may differ depending on the RU sizes.
## 3 Case Study  
### Container Ship  
The initial version of the container ship (\(V_{0}\)) under investigation, modeled and studied with Rhinoceros(r) and Maksurf(r), is equivalent to Laura Maersk, Maersk's first green methanol ship delivered in 2023 [29], and has 43 bays counted from the bow, organized in nine cargo holds, separated from each other by transverse bulkheads, in the cylindrical body forward of the superstructure and two more container bays aft of the superstructure (Figure 3).  
Table 1 shows the main particulars of the container ship in the initial version (\(V_{0}\)).  
Table 2 shows the stowage and arrangement of containers on deck (\(OD\)) and below deck (\(BD\)) in the initial version (\(V_{0}\)).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Description** & **Value (m)** \\ \hline Length overall, \(L_{OA}\) & 187.84 \\ Length between perpendiculars, \(L_{tp}\) & 173.74 \\ Moulded breadth, \(B\) & 28.56 \\ Scantling draught, \(T\) & 9.99 \\ Depth to main deck, \(D\) & 15.6 \\ Prismatic coefficient, \(C_{P}\) & 0.59 \\ Midship coefficient, \(C_{M}\) & 0.95 \\ Block coefficient, \(C_{B}\) & 0.56 \\ Waterplane coefficient, \(C_{W}\) & 0.8 \\ Service speed, \(V\) & 19.5 \\ Froude number, \(Fn\) & 0.234 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main particulars (\(V_{0}\)).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Bay** & \(BD\) & \(OD\) & **Total** \\ \hline
1 & 2 & 18 & 20 \\
3 & 8 & 32 & 40 \\
5 & 16 & 32 & 48 \\
7 & 24 & 40 & 64 \\
9 & 30 & 40 & 70 \\
11 & 40 & 40 & 80 \\
13 & 46 & 40 & 86 \\
15 & 52 & 50 & 102 \\
17 & 52 & 50 & 102 \\
19 & 58 & 50 & 108 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Container stowage in version \(V_{0}\).  
Figure 3: Three-dimensional view and general arrangement. (**a**) Container arrangement, (**b**) Subdivision of bulkheads and holds.  
Figure 4 shows the scantling of the midship section in its initial version. In Figure 4, inside the yellow squares, the plate element number is shown and below it is the thickness (in mm) of each plate element, while in Figure 4, the dimension (in mm) of the longitudinal stiffeners with a bulb-type cross-section is shown.  
Table 3 depicts the geometric properties of the midship section in the initial version.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Bay** & **BD** & **OD** & **Total** \\ \hline
21 & 58 & 50 & 108 \\
23 & 58 & 60 & 118 \\
25 & 58 & 60 & 118 \\
27 & 58 & 60 & 118 \\
29 & 58 & 60 & 118 \\
31 & 58 & 60 & 118 \\
33 & 56 & 60 & 116 \\
35 & 50 & 70 & 120 \\
37 & 48 & 70 & 118 \\
39 & 0 & 76 & 76 \\
41 & 0 & 76 & 76 \\
43 & 0 & 76 & 76 \\ Total & 830 & 1152 & 2000 \\ \hline \end{tabular}
\end{table}
Table 2: _Cont._  
Figure 4: Midship section in the initial version \(V_{0}\). (**a**) Plates (**b**) ordinary stiffeners.  
Figure 5 shows the sectional area curve for the \(V_{0}\) version.
###### Abstract  
In this paper, we propose a novel design of a photonic crystal fiber (PCF) with tellurite-cladding, three rings of air-holes and elliptical concentration of As\({}_{2}\)S\({}_{3}\) in the fiber core. The combined effect of tight mode confinement (an effective mode area of nearly 0.6 \(\upmu\)m\({}^{2}\)), large non-linear refractive index of As\({}_{2}\)S\({}_{3}\) and significant variation between the effective modal index values of the two orthogonal states of the fundamental guided mode leads to extreme non-linear coefficient and birefringence values, all achieved at the zero dispersion wavelength (ZDW) of 1550 nm. The corresponding birefringence and non-linear coefficient (7 \(\times 10^{-3}\) and 28 W\({}^{-1}\) m\({}^{-1}\), respectively) are more than three orders of magnitude larger than that of the regular silica-based highly non-linear PCFs. In addition, we numerically demonstrate that by modifying the core and air-hole dimensions one can easily control the dispersion curve and tune the ZDW of the proposed fiber to any excitation wavelength ranging from near-infrared to short-wave-infrared, including optical telecommunication windows close to 1550 nm. The superior characteristics of the proposed elliptical-core composite PCF including extreme non-linearity, nearly-zero confinement loss (2.47 \(\times\) 10\({}^{-12}\) dB/cm), the ability to maintain polarization of light, and tunable ZDW can open the door to new possibilities in non-linear optics, optical telecommunications, optical signal processing, and sensing devices.  
Keywords:photonic crystal fiber; chalcogenide glass; nonlinear optics +
Footnote †: journal: Applied Physics Letters
###### Abstract  
A hybrid immersed boundary-lattice Boltzmann and finite difference method for fluid-structure interaction and heat transfer in non-Newtonian flow is presented. The present numerical method includes four parts: fluid solver, heat transfer solver, structural solver, and immersed boundary method for fluid-structure interaction and heat transfer. Specifically, the multi-relaxation time lattice Boltzmann method is adopted for the dynamics of non-Newtonian flow, with a geometry-adaptive technique to enhance the computational efficiency and immersed boundary method to achieve no-slip boundary conditions. The heat transfer equation is spatially discretized by a second-order up-wind scheme for the convection term, a central difference scheme for the diffusion term, and a second-order difference scheme for the temporal term. The structural dynamics is numerically solved using a finite difference method. The major contribution of this work is the integration of spatial adaptivity, thermal finite difference method, and fluid flow immersed boundary-lattice Boltzmann method. Several benchmark problems including the developing flow of non-Newtonian fluid in a channel, non-Newtonian fluid flow and heat transfer around a stationary cylinder and flow around a stationary cylinder with a detached filament are used to validate the present method and developed solver. The good agreements achieved by the present method with the published data show that the present extension is an efficient way for fluid-structure interaction and heat transfer involving non-Newtonian fluid. The heat transfer around an oscillating cylinder in non-Newtonian fluid flow at Reynolds number of 100 is also numerically studied using the present solver, considering the effects of the oscillating frequency and amplitude. The results may be used to expand the currently limited database of fluid-structure interaction and heat transfer benchmark studies.  
Keywords: immersed boundary method; lattice Boltzmann method; heat transfer; non-Newtonian fluid
## 3 Test Results and Analysis
### Analysis of Influencing Factors and Failure Characteristics of Shear Strength
#### 3.2.2 Effect of Undulating Angle on Shear Strength  
As can be seen from Figure 7, under the condition that the normal stress is 3 MPa, both the shear peak and residual strength of the rock discontinuity decrease with the increase of the undulating angle. The shear peaks of the rock discontinuity at 40\({}^{\circ}\), 50\({}^{\circ}\), and 60\({}^{\circ}\) are 6.42 MPa, 4.7 MPa, and 3.77 MPa, respectively, and the shear peaks are the largest when the undulating angle is 40\({}^{\circ}\). When the undulating angle increases from 40\({}^{\circ}\) to 60\({}^{\circ}\), the residual strength of the rock discontinuity decreases from 2.48 MPa to 1.84 MPa. At the same time, it can be seen from Figure 7 that the peak shear displacement of the rock discontinuity decreases approximately linearly with the increase of the undulating angle. When the undulating angle increases from 40\({}^{\circ}\) to 60\({}^{\circ}\), the peak shear displacement decreases from 0.789 mm to 0.457 mm.
# A Reconfigurable Radio-Frequency Converter IC in 0.18 \(\upmu\)m CMOS
## 4 System Implementation and Validation
### Frequency Synthesizer  
The test VCO is the one that generates the higher frequencies for the synthesizer, which has been chosen to optimize the area and test its operation under the most stringent conditions. Its active area occupies 800 \(\upmu\)m \(\times\) 350 \(\upmu\)m, of which 350 \(\upmu\)m \(\times\) 350 \(\upmu\)m and 260 \(\upmu\)m \(\times\) 200 \(\upmu\)m are used, respectively, by the inductor and the switched capacitor bank. The VCO for the lower frequencies occupies a  
Figure 6: Circuit diagram of the mixers.  
Figure 7: (a) Micro-photograph of the fabricated RFID-II prototype (dimensions are 2.5 mm \(\times\) 2.5 mm) and (b) photograph of the PCB designed and assembled for its experimental characterization.  
slightly larger area to incorporate a bigger inductor and capacitors, measuring \(900\,\mathrm{\SIUnitSymbolMicro m}\times 450\,\mathrm{\SIUnitSymbolMicro m}\), with \(450\,\mathrm{\SIUnitSymbolMicro m}\times 450\,\mathrm{\SIUnitSymbolMicro m}\) for the inductor and \(300\,\mathrm{\SIUnitSymbolMicro m}\times 250\,\mathrm{\SIUnitSymbolMicro m}\) for the switched capacitor bank.  
Also, to facilitate testing, only 3 PADs for the VCO coarse control have been enabled to be controlled externally, which along with the fine-tuning PAD, allow the use of a 4-bit DC-probe for frequency control. These 3 PADs have been distributed to that one of them controls the least significant bit of the coarse control, and the other two fix the remaining coarse control bits in groups of 3. In this way, then, the coarse states that can be chosen in the test VCO are given by \(SW_{2}SW_{2}SW_{2}SW_{1}SW_{1}SW_{1}SW_{0}\) and their 8 possible values are '000000', '0000001', '0001110', '0001111', '111000', '1110001', '1111110' and '111111', which allows testing of the highest and lowest frequencies, as well as the coarse frequency step.  
Figure 8 shows the measured results of the oscillating frequency of the VCO in its 8 available bands as described in the previous paragraph. It achieves a frequency range from 2.06 GHz to 2.73 GHz with a coarse frequency step of 2 MHz and 46 MHz at its lowest and highest frequencies, respectively. The phase noise of the VCO is \(-117\,\mathrm{d}\mathrm{B}\mathrm{C}\mathrm{/}\mathrm{H}\mathrm{z}\) at a 1 MHz from the carrier at the maximum oscillation frequency. This is a value that suits all modulation modes of both DVB-T (QPSK, 16 QAM, and 64 QAM) and DVB-T2 (the former and 256 QAM), since one feature of the proposed architecture is that it is suitable to feed directly the TV set, without the need to cascade receivers. Finally, the synthesizer consumes a power of \(25\,\mathrm{m}\mathrm{W}\).
## 3 Proposed Scheme
### Preliminaries  
Following is the brief description of the notations that have been used in our proposed forwarder selection scheme.  
* _Neighbors of node \(i\), (\(\xi_{i}\)):_ All the nodes that are in \(T_{r}^{i}\) form which \(i\). \[\xi_{i}=|\ \{j\in\mathcal{N}\ |\ D_{j}^{i}\leq T_{r}^{i}\}\ |\] (1)  
Figure 1: Holding Time and PFZ scenario.  
Figure 2: Relationship between holding time difference and broadcast suppression in the underwater networks.  
where \(\mathcal{N}\) is the set of nodes in the network and \(D_{j}^{i}\) is the euclidean distance between \(i\) and \(j\) in three-dimensional euclidean space: \[D_{j}^{i}=\sqrt{\left(x_{i}-x_{j}\right)^{2}+\left(y_{i}-y_{j}\right)^{2}+\left( z_{i}-z_{j}\right)^{2}}\] (2)
* _Potential Forwarding Zone (PFZ)_: PFZ is the region of between node \(S(x_{S},y_{S},z_{S})\) (that currently forwarded the packet \(p\)) and Sink \(D(x_{D},y_{D},z_{D})\). PFZ is the subregion of \(T_{r}^{S}\) of node \(S\) and the nodes in the region are called potential forwarder nodes (PFNs), which are preferable to further relay \(p\). Any point in 3D euclidean space \(f(x_{f},y_{f},z_{f})\) is considered to be in the PFZ of \(S\), if it satisfies the following conditions: \[D_{D}^{f} <D_{D}^{S},\] \[D_{S}^{f} <T_{r}^{S},\text{ and }\] \[z_{f} \leq z_{S}.\] Neighbors of node \(i\) that are in PFZ of \(S\): \[\chi_{i}=\left\{n_{i}\in\xi_{i}\mid D_{n_{i}}^{i}\leq T_{r}^{i}\wedge D_{S}^{ n_{i}}\leq T_{r}^{S}\wedge z_{n_{i}}\leq z_{S}\right\}\] (3)
## 3 Results and Discussion
### Cr(VI) Adsorption Experiments
#### 3.1.5 Influence of the Adsorbent Dosage  
The effect of the adsorbent dosage on the Cr(VI) adsorption process was also evaluated. Figure 6 shows the obtained results from the different experiments carried out. As expected, metal removal increased with the increase of the adsorbent dosage and for a fixed metal concentration because the number of binding sites available for ions adsorption increased [38]. It should be noted that, for an extremely low adsorbent dose (i.e., 2.5-10\({}^{-3}\) g/L), an adsorption percentage exceeding 30% was found. In addition, for 0.5 g/L adsorbent, the Cr(VI) adsorption was almost quantitative.  
Figure 4: Cr(VI) adsorption at different temperatures. Aqueous phase: 0.01 g/L Cr(VI) at pH 3. Carbon dosage: 0.5 g/L. Time: 5 h. Stirring speed: 1000 min\({}^{-1}\).
# Exploring the Effectiveness of the Phase Features on Double Compressed AMR Speech Detection
## 6 Experimental Setup
### Feature Extraction and Classifier Setup  
The proposed LSTM-based systems in the experiments utilize magnitude spectrum (spectrogram) and phase spectrum representations of the speech signals as input. These feature representations are computed using STFT analysis of the signal. To achieve this, speech signals are segmented into short frames lasting 25 ms each (containing 200 and 400 speech samples for narrowband and wideband signals, respectively) with a frame shift of 10 ms, resulting in a frame rate of 100 frames per second. Each frame is then multiplied by a Hamming window, and a 512-point DFT of each windowed frame is computed to obtain complex-valued Fourier transforms. Subsequently, the spectrogram is computed by taking the logarithm of the magnitude of the STFT spectrum of the signal. The phase spectrum representation is obtained by computing the angle of the STFT spectrum and then applying phase unwrapping to avoid discontinuities. The resulting spectrogram and phase spectrum representations are of dimensions \(257\times 100\), where each dimension corresponds to the DFT bin and frame index, respectively.  
The features (spectrogram or phase spectrum features) of the SC and DC speech signals from the training set are then fed into the LSTM-based DC detection systems as described in Section 5. All models (LSTM and parallel LSTM networks) are trained using the Adam optimizer [40]. The networks undergo training for 100 epochs, with an initial learning rate set to 0.001. If the validation loss increases compared to the previous epoch, the learning rate is reduced by a factor of 0.95. To prevent overfitting, an early stopping approach is employed during model training.
# Farm Monitoring System with Drones and Optical Camera Communication
## 5 Experimental Results  
This section presents the experimental results of the proposed scheme. The feasibility of the proposed system and the accuracy of data transmission in the real environment were confirmed using a drone and an implemented sensor node.
# Comparative Real-Time Study of Three Enhanced Control Strategies Applied to Dynamic Process Systems
## 1 Introduction
By incorporating fractional-order calculus, the FO-APIDSMC controller gains enhanced flexibility and precision, enabling it to more effectively manage long-term system behaviours and nonlinearities. The adaptive PID component continuously adjusts the control parameters in real-time, ensuring that the controller remains robust in the face of system changes. Meanwhile, the sliding mode control component guarantees that the system remains stable and resilient against disturbances while also mitigating the chattering effect that typically plagues traditional SMC approaches [41]. As far as we know from a detailed literature survey, no study has been found in which the FO-APIDSMC controller is applied to a dual tank level system, which is a process system, in real-time. Taking this gap in the literature into account, the FO-APIDSMC method based on the system model has been created and applied to a process system in real-time within the scope of this article. In a real-time comparison of the FF-PI and CNPIR controllers, FO-APIDSMC presents significant improvements in control accuracy, external disturbance resistance, and robustness. The fractional order calculus allows for smoother control actions and better handling of nonlinearities, while the adaptive PID component ensures real-time responsiveness to changing system conditions. The sliding mode control provides the necessary robustness to external disturbances, making FO-APIDSMC the ideal solution for complex industrial systems like liquid level control. In the next section, firstly, the system modelling is performed; then, the mathematical equations of FF-PI, CNPIR, and FO-APIDSMC control laws are created based on the system model. In the experimental results section, real-time results are reported. A list of topics that require further research concludes this study.
# A Self-Supervised One-Shot Learning Approach for Seismic Noise Reduction
###### Abstract  
Neural networks have been used in various computer vision applications, including noise removal. However, removing seismic noise via deep learning approaches faces a specific issue: the scarcity of labeled data. To address this difficulty, this work introduces an adaptation of the Noise2 Self algorithm featuring a one-shot learning approach tailored for the seismic context. Essentially, the method leverages a single noisy image for training, utilizing a context-centered masking system and convolutional neural network (CNN) architectures, thus eliminating the dependence on previously labeled data. In tests with Gaussian noise, the method was competitive with established approaches such as Noise2 Noise. Under real noise conditions, it demonstrated effective noise suppression removal for a smaller architecture. Therefore, our proposed method is a robust alternative for noise removal that is especially valuable in scenarios lacking sufficient data and labels. With a new approach to processing seismic images, particularly in terms of denoising, our method contributes to the ongoing evolution and enhancement of techniques in this field.  
seismic denoising; self-supervised; Noise2 Self; deep learning Article
## 2 Materials and Methods
### Data Collection  
Some sources report LSWI to sandstones/carbonates saturated with oil with a viscosity higher than 150 cp. These data are collected and shown in Table 4. The recovery factor indicated in the table is the incremental recovery for low salinity water/engineered water injection. The main criteria for data selection were the temperature of the test (to be less than 60 \({}^{\circ}\)C) and the oil viscosity (to be more than 150 cp at room temperature). All these data are measured by core flooding tests. Injection at the secondary stage resulted in high recovery due to the high initial oil saturation. In most reported core flooding at the tertiary stage, the recovery is low and less than 10%.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Source**} & \multirow{2}{*}{**Rock type**} & \multirow{2}{*}{**Viscosity, cp**} & \multirow{2}{*}{**Acid Number**} & \multirow{2}{*}{**Injection Mode**} & \multirow{2}{*}{\begin{tabular}{c} **Recovery** \\ **Factor by** \\ **LSW1, \%** \\ \end{tabular} } \\ \cline{5-6}  & & & & & 8.70\% \\ \hline \multirow{3}{*}{[PERSON] et al. [29]} & \multirow{3}{*}{ sandstone} & \multirow{3}{*}{202 @21 \({}^{\circ}\)C} & \multirow{3}{*}{Not reported} & \multirow{3}{*}{\begin{tabular}{c} **Tertiary** \\ **3\%** \\ \end{tabular} } \\ \cline{5-6}  & & & & & 5.60\% \\ \cline{5-6}  & & & & Secondary & 49.40\% \\ \hline \multirow{3}{*}{[PERSON] et al. [32]} & \multirow{3}{*}{ sandstone} & \multirow{3}{*}{2000 @54 \({}^{\circ}\)C} & \multirow{3}{*}{2.36} & \multirow{3}{*}{Secondary} & \multirow{3}{*}{\begin{tabular}{c} 24\% \\ **28\%** \\ \end{tabular} } \\ \cline{5-6}  & & & & & 14.7\% \\ \hline \multirow{3}{*}{[PERSON]. Et al [33]} & \multirow{3}{*}{ sandstone} & \multirow{3}{*}{61,637 @22.5 \({}^{\circ}\)C} & \multirow{3}{*}{Not reported} & \multirow{3}{*}{Secondary} & \multirow{3}{*}{\
\begin{tabular}{c} 26\% \\ **14.7\%** \\ \end{tabular} } \\ \cline{5-6}  & & & & & 26\% \\ \hline \multirow{3}{*}{[PERSON] et.al [31]} & \multirow{3}{*}{ sandstone} & \multirow{3}{*}{600} & \multirow{3}{*}{1.1} & \multirow{3}{*}{Tertiary} & \multirow{3}{*}{
\begin{tabular}{c} 4.45\% \\ **5.80\%** \\ \end{tabular} } \\ \cline{5-6}  & & & & & 7.80\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: Data reported in the literature for the LSWI to heavy oil formations.