esa-sceva/satcom-chunk-collection huggingface dataset:
# GNSS Spoofing Detection Based on Wavelets and Machine Learning
## 4 Results and Discussion
\begin{table}
\begin{tabular}{l l l l l l l} \hline
**Dataset and** & **ML** & **Mean** & **F1** & **Recall** & **Precision** & **Elapsed** \\
**Coefficient Type** & **Method** & **Acc. (\%)** & **Score** & & & **Time (s)** \\ \hline db8 & SVM & 99.78 & 0.9978 & 0.9985 & 0.997 & 4.9 \\ \multirow{3}{*}{(clean + os2) approx.} & KNN & 99.98 & 0.9998 & 0.9996 & 1 & 2.8 \\  & RF-100 & 100 & 1 & 1 & 1 & 4.87 \\  & RF-200 & 100 & 1 & 1 & 1 & 7.8 \\ \hline \multirow{3}{*}{(clean + os4) approx.} & SVM & 99.70 & 0.997 & 0.9981 & 0.9959 & 5.3 \\  & KNN & 99.85 & 0.9985 & 0.9996 & 0.9974 & 3.7 \\ \cline{1-1}  & RF-100 & 99.98 & 0.9998 & 1 & 0.9996 & 5.87 \\ \cline{1-1}  & RF-200 & 100 & 1 & 1 & 1 & 7.85 \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{l l l l l l l} \hline
**Dataset and** & **ML** & **Mean** & **F1** & **Recall** & **Precision** & **Elapsed** \\
**Coefficient Type** & **Method** & **Acc. (\%)** & **Score** & & & **Time (s)** \\ \hline db4 & & & & & & \\ \multirow{3}{*}{(clean + os10) approx.} & SVM & 93.94 & 0.9346 & 0.9322 & 0.937 & 684 \\  & KNN & 86.63 & 0.8657 & 0.8693 & 0.8622 & 722 \\  & RF-100 & 89.46 & 0.895 & 0.8922 & 0.8978 & 569 \\  & RF-200 & 90.35 & 0.9039 & 0.9001 & 0.9078 & 604 \\ \hline \multirow{3}{*}{(clean + os12) approx.} & SVM & 75 & 0.7512 & 0.7483 & 0.7541 & 522 \\  & KNN & 74.72 & 0.762 & 0.7199 & 0.8093 & 510 \\ \cline{1-1}  & RF-100 & 74.70 & 0.7481 & 0.745 & 0.7511 & 548 \\ \cline{1-1}  & RF-200 & 73.94 & 0.738 & 0.742 & 0.7341 & 533 \\ \cline{1-1}  & SVM & 97 & 0.9701 & 1.9785 & 0.9619 & 8.7 \\ \cline{1-1}  & KNN & 92.74 & 0.9272 & 0.9308 & 0.9241 & 1.3 \\ \cline{1-1}  & RF-100 & 95.63 & 0.9563 & 0.9563 & 0.9563 & 6.5 \\ \cline{1-1}  & RF-200 & 95.55 & 0.9556 & 0.9552 & 0.9559 & 116 \\ \cline{1-1} \cline{2-6}  & SVM & 76.43 & 0.7612 & 0.7712 & 0.7515 & 3.6 \\ \cline{1-1}  & KNN & 44.38 & 0.7483 & 0.7431 & 0.7444 & 2.2 \\ \cline{1-1}  & RF-100 & 72.29 & 0.7718 & 0.7758 & 0.7678 & 7.45 \\ \cline{1-1}  & RF-200 & 72.27 & 0.777 & 0.7799 & 0.7741 & 3.14 \\ \hline \end{tabular}
\end{table} 
Table 3: Performance metrics for ML signal-type classification for the Galileo dataset using db4 and db8 wavelets calculated for different input data: (a) images (blue), (b) extracted image features (orange), (c) statistical and spectral features (green).
# Finite Element Analysis of a Novel Approach for Knee and Ankle Protection during Landing
## 3 Results
### Ankle Protection  
Figure 3 shows the peak von Mises stress of the inferior articular surface of tibia with and without the protective double-joint brace at 0.4 m, 0.8 m, and 1.2 m. Without the brace, the maximum von Mises stress increased from 5.787 MPa to 34.32 MPa when the jumping height increased from 0.4 m to 1.2 m, while it increased from 4.316 MPa to 25.27 MPa with the brace. Obviously, the stresses when wearing our brace were always lower than when not wearing it. After wearing the protective brace, the maximum stress on the inferior articular surface of tibia decreased by 25.4%, 21.8%, and 19.4%, respectively, at the heights of 0.4 m, 0.8 m, and 1.2 m.  
The stress distribution on the inferior articular surface of the tibia is presented in Figure 4. At the heights of 0.8 m and 1.2 m, stress concentrations were found to occur in similar locations, i.e., on the medial malleolus, while the stress on the posterior aspect of the articular surface was greater at 0.4 m. At the three heights, wearing the protective brace mainly reduced the stress peak at the stress concentration, but the pattern of stress distribution did not change obviously.  
Figure 3: Maximum von Mises stress of the inferior articular surface of the tibia with and without the brace, and the percentage decline in peak value at the three different heights.  
Figure 2: Validation of finite element model via comparison to existing studies. The bottom axis, left axis, and histogram show the comparison with [PERSON]’s results to validate the biomechanical property of the ankle, while the top axis, right axis, and line chart present the comparison with [PERSON]’s results to validate the biomechanical property of the knee.  
The average horizontal forces on the talus are shown in Table 1. Before wearing the brace, the average horizontal forces were 210.77 N, 270.91 N, and 347.45 N with increasing jump height. After wearing the brace, the average horizontal forces corresponding to the three heights decreased by 32%, 27.4%, and 27.5%, respectively, to 143.24 N, 196.82 N, and 251.87 N.
## 2 Experimental
### Adsorption Experiments
#### 2.2.2 4-MBC Adsorption on Microplastics  
The investigation focused on the kinetics and isotherms of adsorption in a synthetic water matrix containing three salts: CaCl\({}_{2}\), NaHCO\({}_{3}\), and MgSO\({}_{4}\cdot\)7H\({}_{2}\)O. This synthetic water matrix was designed to closely simulate the inorganic content found in natural aquatic environments. The characteristics of the synthetic water matrix are provided in Table 1.  
The investigated adsorbents, weighing 20 mg, were added to the synthetic matrix. Methanol (J.T. Baker, for organic residue analysis) was utilized to prepare a stock solution of 4-MBC at a concentration of 1000 \(\upmu\)g/mL, ensuring the purity and consistency of the organic compound. In the experiments, the initial concentration of 4-MBC was set at 100 \(\upmu\)g/L. The vials were sealed and placed on a digital shaker (IKA\({}^{\oplus}\) (Staufen im Breisgau, Germany) Orbital shaker KS 501 Digital) at a speed of 150 rpm. Each experiment was replicated three times, ensuring reliability in the data.  
Specified time intervals (2, 4, 6, 12, 24, 48, 72, and 96 h) were used to collect samples, which were then filtered through a 0.45 \(\upmu\)m membrane filter. Subsequently, the samples were prepared for gas chromatographic analysis. To evaluate the adsorption kinetics, three models were employed: pseudo-first-order, pseudo-second-order, and Weber-Morris models, allowing for a comprehensive understanding of the adsorption mechanism.  
The range of 4-MBC concentrations for the adsorption isotherm experiments was 0-100 \(\upmu\)g/L (1, 25, 50, 75, 100 \(\upmu\)g/L). The equilibrium concentrations of 4-MBC in the aqueous phase were quantified by collecting samples after 48 h of continuous agitation. The adsorption isotherm data were fitted using the Freundlich and Langmuir adsorption  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline pH & 7.23 \(\pm\) 0.06 \\ Electro conductivity 25 \({}^{\circ}\)C (\(\upmu\)S/cm) & 226 \(\pm\) 23 \\ Dissolved organic carbon (mg/L) & \textless{}0.5 \\ Chloride concentration (mg/L) & 52.1 \(\pm\) 3.59 \\ Sulphate concentration (mg/L) & 21.2 \(\pm\) 4.89 \\ Hydrogen carbonate concentration (mg/L) & 134 \(\pm\) 6 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characteristics of synthetic water matrix.  
models, as described by [PERSON] et al. [43], providing insights into the adsorption capacity and nature of the interactions involved.
# Multifrequency Impedance Method Based on Neural Network for Root Canal Length Measurement
## 4 Conclusions  
The method proposed in this paper combined the multifrequency impedance ratio method and neural networks. To increase the accuracy of the model, the impedance ratio data were augmented with different combinations of currents at various frequencies generated by the designed circuit system. The pre-verification of impedance was performed to provide theoretical support for training the neural network. Impedance, tooth type, and file type were selected as features in the model. Leave-one-out cross-validation was used during the training process due to the limited tooth samples. An optimal neural network was determined according to the performances of neural network models with different structures. Compared with the dual-frequency impedance ratio method, the proposed approach can reduce the influence of measuring factors on the measurement results, increase the measurement accuracy, and enhance the robustness.  
Conceptualization, X.Q., Z.Z., and X.C.; methodology, Z.Z. and X.C.; software, Z.Z.; validation, Z.Z.; formal analysis, X.Q. and Z.Z.; investigation, X.Q.; resources, X.C.; data curation, X.Q.; writing--original draft preparation, Z.Z.; writing--review and editing, X.Q.; supervision, X.C.; project administration, X.C.; funding acquisition, X.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key Research and Development Program of China (No. 2019 YFF0216401) and the Major projects of Science and Technology Commission of Shanghai (No. 17 JC1400800).  
The authors declare no conflict of interest.
# Design of a New Non-Coherent Cross-QAM-Based \(M\)-ary DCSK Communication System
## 3 Performance Analysis  
In this section, the BER expression of the proposed XQAM-MDCSK system over multipath Rayleigh fading channel is analyzed. The average symbol energy can be calculated as \(E_{s}=E_{p}+E_{p}\frac{1}{M}\sum_{i=1}^{M}(a_{i}^{2}+b_{i}^{2})=[\frac{(31M-32)d^ {2}+48}{48}]E_{p}\), where \(d\) stands for the minimum distance of the XQAM-MDCSK constellation. According to [14; 16], the mean and variance of the decision vector \(\widetilde{z}\) are \(E(\hat{z}_{a})=a_{i}\), \(E(\hat{z}_{b})=b_{i}\) and \(Var[\hat{z}_{a}]=Var[\hat{z}_{b}]=\frac{hE_{s}h_{0}/2+\beta N_{0}^{2}/4}{h^{2 }E_{p}^{2}}=\sigma^{2}\), respectively, where \(E(\cdot)\) and \(Var(\cdot)\) denote the expectation and variance operators, respectively. For convenience, \(L\)-path Rayleigh fading channels are used and their channel gains are equal. The probability density function (PDF) of the instantaneous symbol  
Figure 2: Constellations and decision boundaries of (**a**) XQAM-32 DCSK and (**b**) XQAM-8 DCSK. It should be noted that the slash is used to distinguish the I and Q signals for the XQAM-32 DCSK constellation. In the XQAM-8 DCSK constellation, the first bit and the third bit are I signals, while the second bit is Q signal.  
signal-to-noise rate (SNR) \(\gamma_{s}=hE_{s}/N_{0}\) is obtained as \(f(\gamma_{s})=\frac{\gamma_{s}^{l-1}}{(L-1)!\overline{\gamma_{c}}}\exp\left(- \frac{\gamma_{s}}{\gamma_{c}}\right)\), where \(\sum_{l=1}^{L}E\left(a_{l}^{2}\right)=1\) and \(\tilde{\gamma}_{c}=(E_{s}/N_{0})E\left(a_{j}^{2}\right)\), \(j=l,\ldots,L\). Hence, the BER expression of the proposed XQAM-MDCSK system can be written as  
\[P_{b}=\int\limits_{0}^{+\infty}P_{b}(\gamma_{s})f(\gamma_{s})d\gamma_{s}, \tag{3}\]  
where \(P_{b}(\gamma_{s})\) is the conditional BER and \(\gamma_{s}=\log_{2}(M)E_{b}/N_{0}\).  
To make the expression more concise, we can define the following expression as  
\[q(i)=Q\left(\frac{id}{\sigma}\right), \tag{4}\]  
where \(Q(x)\) is a \(Q\)-function.  
According to [20], we also define the following expression as  
\[q(i,j;\rho) = \frac{2}{\pi}\int\limits_{0}^{\Phi_{1}}\exp\left(-\left(\frac{id }{\sqrt{2}\sin\theta\sigma}\right)^{2}\right)d\theta \tag{5}\] \[+ \frac{2}{\pi}\int\limits_{0}^{\Phi_{2}}\exp\left(-\left(\frac{id }{\sqrt{2}\sin\theta\sigma}\right)^{2}\right)d\theta\ \ (i\geqslant 0,j \geqslant 0),\]  
where \(\Phi_{1}=\tan^{-1}\left(\frac{i\sqrt{1-\rho^{2}}}{j-\rho i}\right)+\frac{\pi }{2}(1-\text{sgn}((j-\rho i)/j))\), \(\Phi_{2}=\tan^{-1}\left(\frac{j\sqrt{1-\rho^{2}}}{i-\rho j}\right)+\frac{\pi }{2}(1-\text{sgn}((i-\rho j)/i))\) and \(\rho=-\frac{1}{\sqrt{2}}\). In addition, one has \(q(-i,j;\rho)=2q(j)-q(i,j;-\rho)\), \(q(i,-j;\rho)=2q(i)-q(i,j;-\rho)\) and \(q(-i,-j;\rho)=4-2q(i)-2q(j)+q(i,j;\rho)\).
## 3 Results  
### Spatial Distribution of Average NPP  
From the spatial perspective (Figure 3), NPP exhibits distinct regional characteristics, with higher values in the southern and eastern parts compared to the northern and western regions. The multi-year average NPP is 543.95 gC/(m\({}^{2}\cdot a\)). Areas with an average NPP ranging from 0 to 400 gC/(m\({}^{2}\cdot a\)) account for 22.56% of the entire watershed, primarily distributed in the northwestern parts of the Jinsha River and Mintuo River watersheds. Regions with NPP ranging from 400 to 600 gC/(m\({}^{2}\cdot a\)) cover approximately 35.72% of the area and are found in the Sichuan Basin, Jianghan River Basin, middle and lower reaches of the YRB, Taihu Lake, and Poyang Lake areas to the north. Areas with NPP ranging from 600 to 800 gC/(m\({}^{2}\cdot a\)) account for about 30.20% and are predominantly distributed in the vicinity of the Sichuan Basin, Dongting Lake watershed, and the southern part of the Poyang Lake watershed. Regions with NPP ranging from 800 to 1000 gC/(m\({}^{2}\cdot a\)) make up approximately 10.82% of the area, predominantly situated in the southern part of the Jinsha River watershed. NPP values ranging from 1000 to 1945.2 gC/(m\({}^{2}\cdot a\)) account for only 0.26% of the entire study area. The Sichuan Basin features a closed topography, a higher latitude resulting in relatively higher temperatures, and abundant precipitation, but lower solar radiation compared to other latitudes. In summary, these unique climatic factors contribute to slightly lower NPP values in this region compared to the surrounding areas.
## 6 Conclusions  
Basically, the modified delay and Doppler profiler (mDDP), which estimates not only attenuation, relative delay, and the Doppler shift, but also the sampling clock shift of each multipath component, combined with an ICI canceling multitap equalizer reduces inter-carrier interference between OFDM subcarriers. With the one-step mDDP, the BER reduction was limited by the degradation of the estimation accuracy of those parameters, but with the iterative two-step mDDP, dramatic ICI cancellation can be achieved.  
In the non-reflective pool experiment of a two-wave multipath environment where the receiving transducer moves at a speed of 0.25 m/s and is subject to the backward Doppler shift, increasing NumCOL, the number of taps in the multitap equalizer that removes ICI, the BER of 0.0526661 at NumCOL = 1 was reduced by a sequential ICI-canceling mDDP, the BER at NumCOL = 51 was significantly reduced by about a factor of 45 to 0.0011655.  
Although the simulations in this paper were performed assuming a two-wave multipath Doppler-shift environment, DDP and mDDP have achievements in analyses for multipaths that are larger than the current assumed environment by setting the number of detected paths Np, to a large value, such as 16. The marine experiment is also planned at the end of 2024.  
Conceptualization, T.W.; methodology, T.W.; software, S.O.; validation, S.K., S.O., R.S. and T.W.; formal analysis, S.K.; investigation, S.K. and T.W.; resources, S.K., R.S. and T.W.; data curation, S.K. and S.O.; writing--original draft preparation, S.K.; writing--review and editing, R.S. and T.W.; visualization, S.O. and R.S.; supervision, T.W.; project administration, T.W.; funding acquisition, T.W. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 16: BER comparison of non-reflective pool experiment.
Based on these parameters, the worst-case end-to-end delay (WCD) bounds are determined for a targeted TT queue, providing a complete view of WCD performance under every expected OR. Thus, the critical contributions of the paper are summarized as follows:  
* We propose a flexible window-overlapping scheduling (FWOS) algorithm that allows TT windows to overlap each other and considers the relative positional relationships between window offsets for consecutive nodes. The network calculus (NC) approach is used to formulate the worst-case latency bounds. The FWOS algorithm is evaluated under a realistic vehicle use case considering three overlapping metrics: the priority of overlapping, the position of overlapping, and the overlapping ratio (OR). A critical discussion is introduced based on GCL design parameters. * Based on the latency performance evaluation under flexible overlapping scenarios, we create an additional TSN scheduling constraint, leading to more relaxed GCL implementations. For each particular latency deadline, the FWOS algorithm defines the maximum allowable OR that maximizes the solution space for unscheduled traffic, while guaranteeing TT latency requirements at the same time. Additionally, the FWOS algorithm presents an improvement in WCD boundaries, even in a complete isolation scenario among TT windows compared with the latest related works. The remainder of the paper is organized as follows. Section 2 describes related works, and Section 3 introduces a general background about the basic structure of the TSN system and a brief overview of the IEEE 802.1 Qbv protocol. Our system model and the basics of the network calculus approach are described in Sections 4 and 5, respectively. Section 6 presents the worst-case latency analysis for the FWOS algorithm. Then, we evaluate the performance of the FWOS model, with a relevant discussion in Section 7. Finally, the paper is concluded in Section 7.
## 5 Simulation Results
On the other hand, the numerators for the rest of the \(h\) values are odd and will have \(2p\) phase states, which is, relatively, a much higher number, making the Viterbi decoder complex. To compare the performance of the proposed system with that of a traditional OFDM system, we plot coded CPM-OFDM alongside PSK-OFDM for four typical \(h\) values in Figure 6. In all these plots, for each value of \(h\), BER is plotted against the channel distance. Each plot shows the performance of four scenarios as follows:  
1. Uncoded PSK-OFDM
2. BCH-encoded PSK-OFDM
3. Uncoded CPM-OFDM
4. BCH-encoded CPM-OFDM  
Figure 5: BER performance of coded CPM-OFDM for 23 values of \(h\) over seven transmitter–receiver distances. The superiority of the proposed system is clearly visible. Moreover, it is observed that the difference in performance for the four \(h\) values is barely noticeable. This gives an added advantage to the designer selecting such a value of \(h\) that would optimize the implementation of the proposed system, especially on the receiver side. Furthermore, for these \(h\) values, there is a significant difference in performance between the uncoded and BCH-encoded systems. It is also observed that for channel distances of 100 and 250 m there is no need for equalization as the transmission is error-free. At other distances, equalization will be required for acceptable error performance. Figure 7 compares the BER performance of the proposed system with four different types of BCH codes, viz. a viz., BCH(63,10), BCH(63,16), BCH(31,11), and BCH(31,6). It is observed that except for BCH(31,11), all the other BCH codes achieve zero-error performance for distances of 250 and 100 m.  
Figure 6: Comparison of BER performance of the proposed system with traditional one. A comparison of OOB radiation appears in Figure 8. It is observed that, by and large, CPM-OFDM has a better OOB performance than the traditional PSK-OFDM, especially for the uncoded systems. For the BCH-encoded system, the performance of both the systems is pretty much the same.
# Experimental Demonstration of 3 \(\times\) 3 MIMO LED-to-LED Communication Using RGB Colors
###### Abstract  
Optical wireless communication (OWC) is one of the promising candidates for beyond fifth-generation communication (B5G). Depending on the type of transmitters, receivers, and information carriers applied in the system, OWC can be categorized into visible light communication, light fidelity, free-space optical communication, optical camera communication, etc. In addition to these OWC subcategories, this paper proposes light-emitting diode (LED)-to-LED communication as another subcategory of OWC technique. Furthermore, we show an experimental demonstration of the multiple-input multiple-output (MIMO) LED-to-LED communication system using red, green, and blue colored LEDs. We believe that LED-to-LED communication is an effective solution to resolve the communication burden arising from massive connectivity in B5G internet of things. Along with the measurement results of the transmitter LED, receiver LED, and the channel properties, it is shown that the MIMO LED-to-LED system is able to successfully recover the transmitted signal with low inter-channel interferences due to the receiver LED's unique characteristics. Finally, the bit error rate (BER) performance of the MIMO LED-to-LED system is shown in comparison with the BER performance of the single-input single-output (SISO) LED-to-LED system. We successfully implemented the 3 \(\times\) 3 MIMO LED-to-LED communication system using RGB colors at a data rate of 30.62 kbps over a 10 cm transmission distance along with direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) modulation and zero-forcing (ZF) equalizer.  
LED-to-LED; Li-Fi; light-emitting diodes; optical wireless communication; visible light communication +
Footnote †: journal: Sensors  
**Citation**: [PERSON]; [PERSON].  
Experimental Demonstration of 3 \(\times\) 3 MIMO LED-to-LED Communication Using RGB Colors. _Sensors_**2021**, 21, #921. [[https://doi.org/10.3390/g21144921](https://doi.org/10.3390/g21144921)]([https://doi.org/10.3390/g21144921](https://doi.org/10.3390/g21144921))  
Academic Editor: [PERSON] Received: 26 May 2021  
Accepted: 18 July 2021  
Published: 20 July 2021  
**Published**: **Note**: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.  
**Copyright**: **C 2021 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/40/](https://creativecommons.org/licenses/by/40/)]([https://creativecommons.org/licenses/by/40/](https://creativecommons.org/licenses/by/40/))).
## 3 Test Data Analysis
### Frequency Domain Analysis
#### 3.2.1 FFT Analysis
According to Figure 15, the peaks of the acceleration amplitude spectrum of the tunnel wall in the tunnel wall at the steel-spring-floating slab track segment are significantly smaller than those in the ordinary monolithic track segment, especially the frequency band below 2500 Hz is greatly weakened. In Figure 15a, the maximum peak values of the tunnel wall acceleration amplitudes of the ordinary monolithic track and the steel-spring-floating slab track are located at 442.86 Hz and 1541.73 Hz, respectively, and their amplitudes are 8.57 \(\times\) 10\({}^{-4}\) g and 1.44 \(\times\) 10\({}^{-4}\) g, respectively. In Figure 15b, the maximum peak values of the tunnel-wall acceleration amplitudes of the ordinary monolithic track and the steel-spring-floating slab track are located at 1213.73 Hz and 1888.33 Hz, respectively, and their amplitudes are 1.7 \(\times\) 10\({}^{-3}\) g and 3.21 \(\times\) 10\({}^{-4}\) g, respectively. It can be seen that the vibration isolator of the steel-spring-floating slab track can effectively isolate and filter the frequency band below 2500 Hz, and its built-in damping structure can greatly consume the vibration energy, thereby reducing the vibration wave transmitted to the tunnel wall.