esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Conclusions  
In this paper, we have investigated both the SU and MU-network MIMO based on FFR-based ICIC, together with their power management methods. Two considered FFR-based ICIC are regular and rearranged frequency partitions, which are associated with SU and MU-network MIMO, respectively. With regular partition, the SU-network MIMO can avoid the multi-user interference, but it just has a hard CEU capacity. As for rearrange partition, MU-network MIMO needs joint preprocessing among cooperative BSs to deal with the serious multi-user interference. However, it can provide soft capacity for CEUs. To this end, we have derived three joint preprocessing schemes, including two superposition-coding schemes (MU-JZF and MU_JMMSE) and an orthogonal one (MU-JTDMA).  
Uniform capacity makes sure that users can acquire uniform data rate regardless of their position. To achieve uniform data rate for SU-network MIMO, we can adjust either  
Figure 16: Capacity comparison between different values of center-edge area ratio for SU-network MIMO.  
Figure 15: Capacity comparison between different values of center-edge area ratio for MU-network MIMO with TDMA orthogonal joint preprocessing.  
the power coefficient \(\alpha\) or power ratio \(K_{\max}\). For MU-network MIMO with unit power coefficient, because of the excellent preprocessing gain, the superposition-coding schemes yield much better CEU capacity and slightly better CCU capacity as compared with the SU-network MIMO. As a result, the MU-network MIMO can allocate very small power to CEUs by greatly reducing the value of power coefficient to achieve a uniform data rate.  
Conceptualization, J.-S.S.; methodology, J.-S.S. and K.-M.H.; software, J.-S.S. and K.-M.H.; validation, J.-S.S. and K.-M.H.; formal analysis, J.-S.S.; investigation, J.-S.S.; resources, J.-S.S. and K.-M.H.; data curation, [PERSON]-S.S. and K.-M.H.; writing--original draft preparation, [PERSON]-S.S. and K.-M.H.; writing--review and editing, [PERSON]-S.S.; visualization, [PERSON]-S.S. and K.-M.H.; supervision, [PERSON]-S.S.; project administration, [PERSON]-S.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The source codes of this studies are available at the following link: [[https://drive.google.com/drive/folders/1](https://drive.google.com/drive/folders/1) LvBDXByQDKKVKEInCJDBH8x9t2 aXitf]([https://drive.google.com/drive/folders/1](https://drive.google.com/drive/folders/1) LvBDXByQDKKVKEInCJDBH8x9t2 aXitf)]?usp=sharing (accessed on 31 October 2021).  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Description of Numerical Study  
#### 2.2.1 Single Layer Membrane Sample  
A 3D Finite Element Analysis (FEA) model that includes acoustic-structure interaction was created in the commercial software COMSOL Multiphysics to simulate the surface mobility of a membrane mounted in an impedance tube. Based on the simulation data, the \(nTL\), \(\alpha\) and \(\tau\) were determined using the theory that was presented in the previous chapter. To resemble the real case, the situation of a membrane being mounted in an impedance tube, the FEM model of impedance tube with inner diameter of the cylinder shape tube was \(d=0.1\) m created (\(d<0.586^{\circ}c/f_{upper~{}frequency~{}limit}\), which corresponds to the upper frequency limit, or the cut-off frequency of 2 kHz). The distance between microphones (receiving datapoints) was set to \(s=0.075\) m (\(s<<c/(25f_{upper~{}frequency~{}limit})\)).  
The upstream and downstream impedance tube is a cylindrical tube with acoustically hard wall boundary conditions. The model allows for a variation of the surface impedance of the tube termination (backing wall), with the impedance \(Z=(1+r)/(1-r)\times(\rho\cdot c_{0})\), where \(r\) is the desired reflection coefficient of the backing wall. As the testing specimen, a 0.5 mm thin membrane with material properties of PTFE (Polytetrafluoroethylene) foil was chosen. PTFE is widely used in modern architecture to cover open spaces. It is also used as a facade-coating material.  
The membrane was clamped at the perimeter. The tension was applied as initial stress in the radial and tangential directions of the membrane as \(T_{0}=10\) kN/m\({}^{2}\). The [PERSON]'s modulus, Poison's ratio, and density of the PTFE membrane were \(4.8125\times 10^{9}\) Pa, \(0.33\) and \(2175\) kg/m\({}^{3}\), respectively. The structural loss factor was defined as \(\eta_{s}=0.02(\cdot)\) (for objective reasons related to the use of linear solvers, it was necessary to enter at least minimal damping into the model). The membrane was surrounded by air (\(\rho_{0}=1.29\) kg/m\({}^{3}\); \(c_{0}=343\) m/s) at both sides of the membrane and was excited in by a 1 Pa plane wave radiated from the upstream end of the tube. Six absorption properties of termination were simulated (\(\alpha_{1}=1.0\); \(\alpha_{2}=0.9\); \(\alpha_{3}=0.7\); \(\alpha_{4}=0.5\); \(\alpha_{5}=0.2\); \(\alpha_{6}=0.1\)), to investigate the impact of the termination on the resulting \(nTL\), \(\tau\) and \(\alpha\), respectively. The generated mesh resulted into 34,547 degrees of freedom (DOF) with a maximum element size (\(c_{0}/f_{upper~{}frequency~{}limit}/5\)) \(\cong 0.034\) m (Figure 3a).  
Figure 3: View of 3D FEM model meshing. (**a**) Single membrane; (**b**) rectangular shape membrane, where \(l_{1}\), \(l_{2}\), \(h\), \(w\), \(d\) are length of downstream and upstream part of impedance tube, height, width and diameter of the tube cross section, respectively.
# Joint Timekeeping of Navigation Satellite Constellation with Inter-Satellite Links
## 4 Performance Evaluation of ISLT
### Frequency Stability Analysis
Figure 7: The frequency stability of the ISLTs kept by different clock ensembles.
# Applying Neural Networks with Time-Frequency Features for the Detection of Mental Fatigue
## 4 Discussion
As such, the development of deep learning approaches for mental fatigue detection using EEG signals could be enhanced by including larger datasets (containing a variety of population and settings, subsequently increasing diversity/reducing population biases), cognitive load measures and behavioral observations, and optimization in the DL architecture. These, paired with explainability methods, are likely to yield valuable insights and improvements in the ability to detect and comprehensively investigate the underlying neural substrates that govern mental fatigue.
# On Blockchain-Enhanced Secure Data Storage and Sharing in Vehicular Edge Computing Networks
## 4 Security Analysis and Performance Evaluation
### Performance Evaluation  
#### 4.2.1 System Setup  
We design a highway traffic scenario using the simulation of urban mobility (SUMO) supported by the OSMWebWizard package to prototype and evaluate our proposed model's performance. We use NS-3 as a discrete-event network simulator to analyze a vehicle mobility trace file to validate the result. The wireless access for the vehicular environments (WAVE) protocol defines the network according to the IEEE 802.11p @ 5.9 GHz standard compatible with DSRC communication among vehicles and RSU. We consider utilizing an optimized link-state routing protocol (OLSR) due to its efficiency based on delay, mobility, and speed in packet delivery, compared to other protocols [34]. Furthermore, we utilize Hyperledger Sawtooth [35], the new member of the Hyperledger family, to implement consortium blockchain in our scenario. We use Docker containers to run validators, transaction processors, and Sawtooth REST server, which in our case acts as the RSUs, smart contracts, and blockchain application interface, respectively.  
Our scenario simulates the region of Daeyon-Busan in South Korea with 10 RSUs and 26 left-hand driving vehicles for 100 s with no pause time. Each vehicle transmits a 512 byte block header ten times/second to the RSUs at a rate of 6 Mbps. Here, RSUs acting as miners are placed 50 m apart to collects the data broadcasted and uploaded by vehicles. All numerical results were carried out using a computer desktop with Ubuntu OS version 16.04 that was installed on a virtual machine, Oracle VM VirtualBox. The computer has the following specifications: CPU Intel(R) Core(TM) i5-4690 CPU @ 3.50 GHz with 16.00 GB RAM. The simulation parameters are listed in Table 3, and the results are given in Figures 5-13.  
Figure 5: Effect of batch size on throughput.  
Figure 8: MAC/PHY overhead.  
Figure 6: Routing traffic receiving rate.  
Figure 7: Application packets receiving rate.  
Figure 11: Packet delivery ratio over RSUs comparison.  
Figure 10: MAC/PHY overhead comparison.  
Figure 9: Packet delivery ratio over RSUs.  
Figure 12: MAC/PHY overhead with compromised RSUs.  
Figure 13: Packet delivery ratio with compromised RSUs.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline simulators & NS-3, SUMO, OSMWebWizard \\ \hline simulation time & 100 s \\ \hline MAC type & IEEE 802.11p \\ \hline WAVE ITS band & 5.9 GHz \\ \hline routing protocol & OLSR \\ \hline physical mode & OFDM (6 Mbps rate) \\ \hline fading model & Nakagami fading \\ \hline propagation loss model & Two-ray ground \\ \hline vehicle speed & 20 m/s \\ \hline number of RSUs & 10 \\ \hline distance between RSUs & 50:500 m \\ \hline \hline \end{tabular}
\end{table}
Table 3: Simulation parameters.
## 4 Global Analysis
### LA and LBA  
To determine the linear elastic stress field of a reference loading state, a linear analysis (LA) was performed, presuming linear elastic material behavior as well as small deformation theory. The resulting membrane stresses in the meridian and circumferential direction, as well as bending and shear stresses, are shown in Figures 6 and 7.  
Figure 6: (**a**) Meridional membrane stress; (**b**) radial membrane stresses in the middle panel.  
Figure 7: (**a**) Shear stress; (**b**) bending stresses in the middle panel.  
As noted in [34], so-called buckling-relevant membrane stresses must be defined for the stressed-based design. An additional linear buckling analysis (LBA) might be performed to gain knowledge of the buckling modes. The first, third, fifth, and seventh eigenmodes are shown in Figures 8 and 9. As can be deduced from these figures, the first eigenmode shows short waves in a meridional direction starting some distance away from the bulkheads. Consequently, stress peaks in the region of the bulkheads were neglected in the stress-based design approach.
## 2 Theoretical Background
### Fractal Dimension
#### 2.3.1 Higuchi's Fractal Dimension (\(Hfd\))  
The process of calculating \(HFD\) consists of four steps [33]:  
1. The signal \(X\) in the time domain, with \(N\) samples, gets decomposed into new series or sequences, \(x_{k}{}^{m}\), using Equation (20), with \(m\) as the initial time and \(k\) as the time interval. \[x_{k}^{m}=x_{m},\ x_{m+k},x_{m+2k},\ldots,x_{m+\lfloor\frac{N-m}{k}\rfloor k} \qquad(m=1,2,\ldots,k)\] (20)
2. The average normalized length, \(L_{m}\), of each \(x_{k}{}^{m}\) is calculated with Equation (21). \[L_{m}(k)=\frac{(N-1)}{k\Big{[}\frac{N-m}{k}\Big{]}}\sum_{i}^{\lfloor\frac{N-m }{k}\rfloor}\Big{|}x_{m+ik}-x_{m+(i-1)k}\Big{|}\] (21)
3. The total length, \(L(k)\), is calculated for every \(k\) using Equation (22). \[L(k)=\sum_{m=1}^{k}L_{m}(k)\] (22)
4. The value \(k\) is updated with \(k=k+1\). Steps 1 to 3 are repeated while \(k<k_{max}\), with \(k_{max}\) being a selected value at which the slope of the best-fit line of the plotted diagram in the plane (\(ln[L(k)]\) versus \(ln[1/k]\)) is constant, with the slope being the value of \(HFD\).
## 4 Conclusions  
In this paper, the characteristics of droplet breakup in symmetrical Y-junction microchannels were studied under the flow rate range of \(q_{\rm d}\) = 2-18 mL/h for the discrete phase and the flow rate range of \(q_{\rm c}\) = 2-22 mL/h for the continuous phase. Among them, the liquid-liquid two-phase uses silicone oil as the dispersed phase and distilled water with 0.5% SDS as the continuous phase. The main conclusions are as follows:  
1. At the two-phase flow ranges covered in this paper, three modes of breakup were observed: breakup with permanent obstruction, breakup with gaps, and no breakup. Three stages in the droplet breakup process were found: the entry stage, the deformation stage, and the breakup stage. The change of neck width during droplet breakup has two stages: rapid breakup stage and thread breakup stage;
2. The breakup behavior of droplets has a significant impact on the flow pattern. Before breakup, most flow patterns are slug flow. After breakup, no parallel flow can be observed in the microchannel and a new flow pattern, droplet flow, appears. Moreover, the area occupied by the slug flow in the flow pattern becomes smaller after breakup;
3. Two-phase flow parameters affect the length of the sub-droplets after breakup. The droplet length has a positive correlation with the discrete-phase flow \(q_{\rm d}\) and a negative correlation with the continuous-phase flow \(q_{\rm c}\); the dimensionless droplet length \(L_{\rm d}/W\) has a positive correlation with the two-phase flow ratio \(q\) and a negative correlation with the capillary number. According to this rule, the correlation formula of sub-droplet length is proposed and the prediction effect is good.  
Conceptualization, L.L. and J.Z.; methodology, Y.Z.; validation, L.L., J.A. and Y.Z.; formal analysis, B.Z.; investigation, L.L. and Y.Z.; resources, J.Z.; data curation, Y.Z.; writing--original draft preparation, Y.Z. and L.L.; writing--review and editing, L.L.; supervision, L.L.; project administration, L.L. and J.Z.; funding acquisition, J.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Guangdong Basic and Applied Basic Research Foundation (2019A1515111116), Shandong Province Natural Science Foundation (No. ZR2021 ME080), Shandong Provincial Postdoctoral Innovation Project (No. 201902002), Foundation of Shandong University for Young Scholar's Future Plans, and Double First-Class Foundation for the Talents of Shandong University (31380089963090).  
Not applicable.  
We thank the Guangdong Basic and Applied Basic Research Foundation, the Shandong Province Natural Science Foundation, and Shandong University for the fundings.  
The authors declare no conflict of interest.
## 3 Results
### Temporal Changes in ESV
#### 3.1.2 Changes in Individual ESVs
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**ESV (CNY 100 Million)**} & \multicolumn{2}{c}{**1991–2006**} & \multicolumn{2}{c}{**2006–2021**} \\ \cline{2-7}
**Ecosystem Services** & **1991** & **2006** & **2021** & **Change (CNY 100 Million)** & **Change Rate (\%)** & **Change (CNY 100 Million)** & **Change Rate (\%)** \\ \hline Food production & \(606.93\) & \(564.96\) & \(528.82\) & \(-41.97\) & \(-6.92\) & \(-36.14\) & \(-6.40\) \\ Raw material production & \(386.40\) & \(362.87\) & \(342.19\) & \(-23.54\) & \(-6.09\) & \(-20.68\) & \(-5.70\) \\ Water resources supply & \(179.99\) & \(236.66\) & \(217.84\) & \(56.66\) & \(31.48\) & \(-18.82\) & \(-7.95\) \\ Gas regulation & \(741.03\) & \(710.90\) & \(674.09\) & \(-30.12\) & \(-4.06\) & \(-36.81\) & \(-5.18\) \\ Climate regulation & \(1117.24\) & \(1109.87\) & \(1067.96\) & \(-7.37\) & \(-0.66\) & \(-41.91\) & \(-3.78\) \\ Environmental purification & \(523.99\) & \(551.87\) & \(520.94\) & \(27.88\) & \(5.32\) & \(-30.93\) & \(-5.60\) \\ Hydrological regulation & \(4137.24\) & \(4618.83\) & \(4278.13\) & \(481.59\) & \(11.64\) & \(-340.70\) & \(-7.38\) \\ Soil conservation & \(940.63\) & \(900.48\) & \(853.39\) & \(-40.15\) & \(-4.27\) & \(-47.09\) & \(-5.23\) \\ Nutrient cycling maintenance & \(107.09\) & \(101.01\) & \(95.28\) & \(-6.07\) & \(-5.67\) & \(-5.73\) & \(-5.68\) \\ Biodiversity maintenance & \(634.87\) & \(665.31\) & \(629.05\) & \(30.45\) & \(4.80\) & \(-36.26\) & \(-5.45\) \\ Aesthetic landscape provision & \(332.32\) & \(354.12\) & \(333.20\) & \(21.80\) & \(6.56\) & \(-20.93\) & \(-5.91\) \\ Total value & \(9707.72\) & \(10{,}176.88\) & \(9540.88\) & \(469.16\) & \(4.83\) & \(-636.00\) & \(-6.25\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Values and changes in individual ecosystem services along the Grand Canal from 1991 to 2021. Through an in-depth analysis of the ESVs along the Beijing-Hangzhou Grand Canal, the proportion and ranking of each individual service value were obtained (Figure 2). Hydrological regulation ranks first, followed by temperature regulation, soil conservation, gas regulation, biodiversity, food production, environmental purification, raw material production, aesthetic landscape, water resource supply, and nutrient maintenance. From 1991 to 2021, hydrological regulation contributed most significantly to the total ESV in the study area, accounting for more than 40% of the total ESV. This highlights its central role in maintaining regional ecological balance. Additionally, the four ecosystem services of gas regulation, temperature regulation, soil conservation, and biodiversity also had significant impacts on the total ESV in the study area, demonstrating high levels of contribution. In contrast, nutrient maintenance, water resource supply, and aesthetic landscape contributed relatively limitedly.
# Visual Navigation Systems for Maritime Smart Ships: A Survey
## 4 Future Trends  
### Trends in Intelligence and Automation  
The relevant data for our study can be found in [4; 14; 16; 115] as well as Rolls-Royce data, which provide us with a solid foundation for the study of smart ship navigation technology. In particular, the Rolls-Royce data provide valuable references for our research by providing information about the composition of ship cargo costs, which provides us with the advantages brought about by the development of smart ships. Through these data, we were able to gain an in-depth understanding of the pulse of the development of smart ship navigation technologies, as well as the performance and potential of each technology in practical applications. The accumulation of these research results adds persuasive power to our thesis and provides clear guidelines for our future research direction. By comprehensively reviewing the development history of smart ships, industry guidelines and current navigation technologies, this paper provides a clear perspective on the future direction of visual navigation technology for smart ships. Future ship visual navigation systems will realize the integrated processing of AIS, radar, infrared and visual data through the fusion of multi-modal perception technologies, thus improving the robustness and adaptability of the systems. The development of smart ships will benefit from the convergence of cross-domain technologies, especially the Internet of Things, big data analytics and cloud computing. The integration of these technologies will provide smart ships with powerful data processing and analysis capabilities, enabling real-time remote monitoring and decision support.  
With the rapid development of artificial intelligence technology, the intelligent transformation of the future shipping industry has become an irreversible trend. The core of smart ship technology lies in the intelligence and automation of the ship's visual navigation system. The future direction of this system will rely on the in-depth application of deep learning and machine learning algorithms to achieve accurate identification and analysis of dynamic changes in the marine environment. Through these advanced algorithms, the system will be able to provide comprehensive information support to the crew, enhance their understanding of the surrounding environment and improve their ability to anticipate potential risks, thereby significantly improving their situation awareness.
## 4 Experimental Platform and Result Analysis
### Static Test Analysis  
In this test, after energizing the MHD ARS for 30 min, static data were recorded with a sampling frequency of 100 Hz for 1 h. In CEEMDAN, we set the noise factor of the added gaussian white noise to 0.1. To ensure the denoising effect and save on computational costs, we set the times of adding noise to 100 and the maximum number of iterations to 300. Considering the output of the MHD ARS in the experiment is in the millivolt range and the mode mixing, \(\beta_{1}\) and \(\beta_{2}\) were both chosen as 0.0005. The mother wavelet function was sym6, and the decomposition scale was 5 layers. We set \(a\) to 1000 and \(b\) to 0.001. To remove as much noise as possible, \(\alpha\) was 0.1. The IMFs are shown in Figure 6.  
Considering that conventional CEEMDAN-WTD have been applied to signal denoising [20; 21; 22; 23], we used the CEEMDAN, CEEMDAN-hard thresholding, and CEEMDAN-soft thresholding algorithms to compare the effects of the improved method. Figure 7 shows the \(R_{RMS}\) of the IMFs. Figure 8 shows the effects of several methods for denoising, the proposed method significantly reduces the base drift.  
Figure 5: MHD ARS measurement system experimental platform.  
Figure 6: IMFs of MHD ARS signal in static condition.  
The Allan variance can be quantified and analyzed as, for example, the quantization noise (Q), angle random walk (N), bias instability (B), rate random walk (K), rate ramp (R) and other noise sources [35]. We performed the Allan variance analysis on the MHD ARS denoised signal under the static condition. As shown in Figure 9, in the curve of the noise signal, the slope of the oblique part is close to \(-1/2\), and the slope of the straight part is close to zero. Is indicates that the main noise of the measurement system is the angle random walk and bias instability. The proposed method has the lowest curve.  
Figure 8: Denoising results of MHD ARS signal in static condition.  
Figure 7: \(R_{RMS}\) of the IMFs.  
The Allan variance results for random noise are listed in Table 1. As can be seen, the quantization noise is reduced by 10 times as compared to the noisy signal, the angle random walk is reduced by 30 times, and the bias instability is reduced by 1.75 times. The method proposed in this paper has advantages over conventional methods in the static test.