esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
The two identical Samsung XCover 4s models which were tested, on average, used almost the same number of active satellites for the fixed position (Figures 3 and 6b) but differed slightly in the distribution of satellite frequency (Figure 5) and in the positional accuracy (CEP: 6.02 m vs. 7.22 m; DRMS: 7.73 m vs. 7.98 m). The differences between the two tested Samsung XCover 4s cannot be explained, as they are identical in construction, were bought together, and were treated absolutely the same in terms of software. The two Xiaomi smartphones (Mi 8 and Mi 8 pro) should have accessed the same satellites and acquired the same position data, as they have the same GNSS chip (Broadcom BCM47755) installed. The similarity between the two smartphones is that they are the only smartphones with a two-top distribution of satellites in use (Figure 5). The positional accuracy was significantly different (CEP: 4.08 m vs. 5.77 m; DRMS: 7.20 m vs. 8.55 m)  
However, the differences that occurred confirmed the practitioners' statements that more significant deviations can occur with absolutely identical phones. A more detailed explanation for this cannot be derived from these studies. These potential differences and the associated fluctuations in position determination must be considered when using and testing these smartphones and should be investigated more closely in the future. Therefore, if possible, two identical smartphones should be constantly tested. In principle, it should be assumed that newer smartphones with improved hardware and software also achieve higher positioning accuracy. However, the results of this study do not allow a generalised statement to be made (Figures 6a and 9a). Newer hardware and software do not necessarily imply higher accuracy. In [97], it was found that, under open sky conditions, the Samsung S4 and Samsung S5 achieved a higher accuracy than their predecessors, the Samsung S6 and Samsung S7. Other studies found that the Xiaomi Mi 8 had a higher accuracy in GPS- and multi-GNSS solutions than its successor, the Xiaomi Mi 9 [87]. The present study comes to similar conclusions, especially when comparing the Huawei P20 with its successor, the Huawei P40. In the case of the manufacturer Xiaomi, the Xiaomi Mi 10 light, the latest tested mobile phone, is also the one in the current study with the best positioning accuracy under the forest canopy. The results for the Xiaomi Mi 10 light, in particular, show a more advanced determination of the position could be observed, resulting in higher accuracy. Therefore, the combination of hardware, the version of the operating system, and the application must be considered when determining GNSS measurement accuracy [89]. This leads to the assumption that each hardware and software generation must be checked individually for positioning accuracy both in open sky and under complex conditions such as the forest. For this reason, an international, standardised test method and the regular testing of new smartphones and software variants are advisable.
## 3 Reliability Analysis  
### Formulation of the RBTO  
Reliability analysis and design optimization are effective methods to ensure structural safety, as demonstrated by [27; 28; 29]. For the mathematical model of RBTO, it is sufficient to transform the stress constraint in Equation (6) as follows:  
\[\begin{split}\text{Minimize}& V\big{(}x_{i},\mathbf{X}_{j},\mathbf{u}\big{)}=\sum_{i=1}^{NE}x_{i}V_{i}\big{(}x_{i},\mathbf{X}_{j}, \mathbf{u}\big{)}\\ \text{subject to}& P_{f}=\text{P}\big{[}G\big{(}x_{i},\mathbf{X}_{j}\big{)}\leq 0 \big{]}=\int\ldots\int_{G(x_{i},\;X)\leq 0}f_{X}(\mathbf{X})dx\\ &\text{K}\big{(}x_{i},\mathbf{X}_{j},\mathbf{u}\big{)}\text{U}\big{(}x_{i},\mathbf{X}_{j},u\big{)}=\text{F}\big{(}\mathbf{X}_{j},\mathbf{u}\big{)}\\ &\beta(\mathbf{u})=\beta_{t}\\ & x_{i}=1\;\;\;or\;x_{i}=10^{-9}\;\text{with}\;\;i=1,\;\ldots,\; NE\;\;and\;\;j=1,\;\ldots,\;m\end{split} \tag{6}\]  
with \(x_{i}\) being the finite element, \(\mathbf{X}_{j}\) is the j-th random variable, \(\text{V}\) is the volume of the total structure, \(P_{f}\) is the probability of failure, G is the limit state function, and NE is the number of variables and m the number of uncertain variables. To control the topologies obtainedby the RBTO model, the reliability index \(\beta(\mathbf{u})\), see [30], is introduced with a normalized vector \(\mathbf{u}\).  
\[G\big{(}x_{i},X_{j}\big{)}=R-S=\sigma^{*}-\sigma_{e}^{vm}\big{(}x_{i},X_{j}\big{)} \tag{7}\]  
where \(R\) denotes the structural strength and S denotes the load variable. In this paper, we consider the possibility that random variables may cause the von Mises stress to exceed the yield strength limit of the material, thus causing the failure of the structure. Here, R indicates the allowable stress for the material \((\sigma^{*})\) and S indicates the von Mises stress of the element \(\sigma_{e}^{vm}\big{(}x_{i},X_{j}\big{)}\). Thus, if \(G>0\), the structure is reliable, if \(G<0\), the structure fails, and if \(G=0\), the structure is in the limit state.
## 2 Unit Cell Design  
Figure 1 depicts the complete structure of the unit cell and evaluation process. The proposed unit cell for the polarization converter is composed of a PTFE substrate, with a thickness of h = 1.6 mm, \(\epsilon_{r}=2.1\), and tan \(\delta\)(tangent loss) = 0.0002. The top pattern and metallic ground plane are composed of copper, which has a thickness of 35 \(\upmu\)m and an electric conductivity of 5.8 \(\times\) 10\({}^{7}\) S/m.  
Figure 1 depicts the two evaluation processes for the meta-atom. In the evolution stage of the meta-atom, the semicircle patch structure (type I) is depicted in Figure 1a. In step 2, the slotted rectangular patch (type II) is shown in Figure 1b. Finally, the proposed meta-atom is constituted by combining a slotted rectangular patch with a semicircle, as shown in Figure 1c. The schematic figure of the proposed meta-atom is illustrated in Figure 1d. The equivalent LC circuit of the slotted rectangular patch combined with a semicircle is shown in Figure 2. The red dotted box shows the equivalent circuit of the slotted rectangular patch and the blue dotted box indicates the equivalent circuit of the semicircle. The optimized dimensions of the proposed meta-atom are tabulated in Table 1.
## 3 Method Development
### Modes and Fundamental Frequencies Computation  
Coefficient vectors \(\mathbf{c}_{i}\) of each beam segment \(e_{i}\in\{e_{1},e_{2},...,e_{n}\}\) depend on the boundary conditions of the complete structure. In detail, the set of all boundary conditions, as described in the previous section, can be rewritten as a set of coupled linear equations of the form  
\[F(\omega)\left[\begin{array}{c}\mathbf{c}_{1}\\ \mathbf{c}_{2}\\ \vdots\\ \mathbf{c}_{n}\end{array}\right]=\mathbf{0} \tag{19}\]  
where \(F(\omega)\) is a \(4n\times 4n\) matrix that depends on \(\omega\). For this, it is required to substitute variables \(\beta_{1},\beta_{2},...,\beta_{n}\) in the boundary conditions by their equivalent expressions on \(\omega\), accordingly with (6), i.e.,  
\[\beta_{i}=\left(\frac{\rho_{i}A_{i}}{E_{i}I_{i}}\right)^{1/4}\omega^{1/2}\]  
Equation (19) has always a trivial solution, in which all the coefficients are null. Nevertheless, the solutions of interest appear when the coefficients are not null. For this, matrix \(F(\omega)\) must lose rank, which occurs for the fundamental frequencies \(\omega^{k}\). These values \(\omega^{k}\) can be obtained numerically, by using roots-finding methods such as [PERSON]'s or bisection. Next, for each of such value \(\omega^{k}\), the corresponding values \(\{\beta_{1}^{k},\beta_{2}^{k},...,\beta_{n}^{k}\}\) can be computed as in (6). Moreover, coefficients vectors \([(\mathbf{c}_{1}^{k})^{T},(\mathbf{c}_{2}^{k})^{T},...,(\mathbf{c}_{n}^{k})^ {T}]^{T}\) can be computed fulfilling (19).
###### Abstract  
The performance of a free-space optical (FSO) communications link suffers from the deleterious effects of weather conditions and atmospheric turbulence. In order to better estimate the reliability and availability of an FSO link, a suitable distribution needs to be employed. The accuracy of this model depends strongly on the atmospheric turbulence strength which causes the scintillation effect. To this end, a variety of probability density functions were utilized to model the optical channel according to the strength of the refractive index structure parameter. Although many theoretical models have shown satisfactory performance, in reality they can significantly differ. This work employs an information theoretic method, namely the so-called Jensen-Shannon divergence, a symmetrization of the Kullback-Leibler divergence, to measure the similarity between different probability distributions. In doing so, a large experimental dataset of received signal strength measurements from a real FSO link is utilized. Additionally, the Pearson family of continuous probability distributions is also employed to determine the best fit according to the mean, standard deviation, skewness and kurtosis of the modeled data.  
J 2021 9 26 2021 9  
Kullback-Leibler divergence; Pearson distribution; RSSI; optical wireless communications
# An Integrated DQN and RF Packet Routing Framework for the V2X Network
## 3 Design of the IDRF System
### Real-Time Phase
#### 3.2.4 Integration of DQN and RF Using the Real-Time Decision Unit
\begin{table}
\begin{tabular}{c c} \hline \hline
**Intersection** & **Intersection Transfer Probability** \\ \hline \(I_{24}\) & 0.24 \\ \hline \(I_{54}\) & 0.68 \\ \hline \(I_{70}\) & 0.90 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The intersection transfer probability \(R_{w}\) for Hop 3. \begin{table}
\begin{tabular}{c c} \hline \hline
**Link for Hop 3** & **IDRF Delay Weight of Hop 3** \\ \hline \(V_{6}\to V_{9}\) & 0.4270 \(\times\) 0.24 = 0.102480 \\ \hline \(V_{7}\to V_{11}\) & 0.1723 \(\times\) 0.68 = 0.117164 \\ \hline \(V_{7}\to V_{12}\) & 0.3516 \(\times\) 0.90 = 0.316440 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The new delay weight \(H_{w}\) for Hop 3. Figure 27: (**a**) The DQN-decided packet forwarding path from the source to the destination; (**b**) IDRF real-time vehicle decision that integrates DQN and RF (S and D denote the source and destination vehicles, the arrow indicates the intersection transfer probability of Hop3, and the dotted line are possible paths between the source and the destination). \begin{table}
\begin{tabular}{c c} \hline \hline
**End-to-End Forwarding Path** & **Total Delay Weights** \\ \hline Path 1 & \(S\to V_{3}\to V_{6}\to V_{9}\to D\) & 0.5789 + 0.1450 + 0.4270 + 0.1420 = 1.2929 \\ \hline Path 2 & \(S\to V_{4}\to V_{7}\to V_{11}\to D\) & 0.1046 + 0.0944 + 0.1723 + 0.4806 = 0.8519 \\ \hline Path 3 & \(S\to V_{4}\to V_{7}\to V_{12}\to D\) & 0.1046 + 0.0944 + 0.3516 + 0.4615 = 1.0121 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Total delay weights of three packet forwarding paths without considering the intersection transfer probabilities.
## 3 Results
### Trial n.2--Effect of Tempering  
From the above-reported results on martempering and austempering routes, the contribution of a final tempering treatment was investigated. Figure 8 displays a comparison of the HRC evolutions along the ring's height after tempering performed at 230 \({}^{\circ}\)C for 120 min. Considering the martempering route, no remarkable changes in HRC values were detected from the surface to the center after tempering. The final tempering led to quite a uniform reduction of about 4 HRC in hardness values along the ring's height points with respect to the untempered conditions. By contrast, the final tempering performed on the austempered rings enhanced the contribution of the salt bath temperature, as indicated by the HRC  
Figure 7: SEI-SEM micrographs of the heat-treated EN 100 CrMo7 rings—Trial n.1: (**a,b**) austenitizing at 880 \({}^{\circ}\)C for 150 min, martempering at 180 \({}^{\circ}\)C for 30 min, and cooling to room temperature in calm air for the upper surface and central region, respectively; (**c,d**) austenitizing at 880 \({}^{\circ}\)C for 150 min, austempering at 240 \({}^{\circ}\)C for 300 min, and cooling to room temperature in calm air for the upper surface and central region, respectively; (**e,f**) austenitizing at 880 \({}^{\circ}\)C for 150 min, austempering at 220 \({}^{\circ}\)C for 300 min, and cooling to room temperature in calm air for the upper surface and central region, respectively.  
evolution along the ring's height. As seen, the austempering and tempering treatments pointed out a slight hardness reduction in the center of the ring that, for the highest salt bath temperature, reached up to about 3 HRC points. The higher the temperature of the salt bath, the lower the obtained HRC values.  
Figure 9 displays the BSE-SEM micrographs of the tempered rings. Concerning the martempering and tempering condition (Figure 9a,b), a complete microstructural transformation of the matrix can be observed; due to tempering, the martensitic matrix is less tetragonal, even if it maintains a latthy morphology and if a higher density of spheorodized small carbides can be detected. Conversely, for the same investigated region, and regardless of the austempering temperature, no remarkable microstructural effects were observed in the tempered microstructure of the rings for the upper surfaces (Figure 9c,e). This experimental finding agrees with [12]; it is well-known that the tempering of bainitic microstructures mainly reduces internal stresses. By contrast, in the central region, the microstructure was mainly composed of lower bainite; nevertheless, some regions of upper bainite (see red arrows in Figure 9d,f) were detected.
# COMA: Propagating Complementary Multi-Level Aggregation Network for Polyp Segmentation
## 4 Discussion
### Analysis of Loss Functions  
#### 4.4.1 Comparison of Loss Functions  
To investigate the effectiveness of each loss function in the proposed hybrid loss function, a comparative experiment was performed between the hybrid loss function and other single loss functions in Table 9. First, we compared the BCE, IoU, and L1 loss functions and observed that IoU loss performed better than BCE loss on mean dice and mean IoU, whereas BCE loss performed better than IoU loss on \(S_{m}\) and \(E_{m}\); however, L1 loss outperformed in most evaluation metrics. Second, to verify the effectiveness of the weighted loss function, BCE and weighted BCE were comapred along with IoU and weighted IoU. The weighted loss functions significantly improved the overall performance. This suggests that the weighted loss function allows the network to focus on the boundary information, leading to improved performance. Third, we compared the weighted BCE and the weighted IoU loss functions and found similar trends to the comparison of the BCE and IoU loss functions. Based on the results of this experiment, we concluded that the weighted IoU affected mDice and mIOU more than weighted BCE and L1, whereas weighted BCE affected \(S_{m}\) and \(E_{m}\) more. In addition, L1 loss, which exhibited the best MAE, helped the model to make pixel-by-pixel predictions with high confidence. Although some single loss functions outperformed the hybrid loss function on certain metrics, the proposed hybrid loss function significantly outperformed the alternatives on most evaluation metrics.  
Figure 3: Visualization of complementary masking and explicit boundary generation.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Loss Function**} & \multicolumn{6}{c}{**Kvasir**} & \multicolumn{6}{c}{**ColonDB**} \\ \cline{2-11}  & **mDice** & **mIoU** & \(S_{m}\) & \(E_{m}\) & **MAE** & **mDice** & **mIoU** & \(S_{m}\) & \(E_{m}\) & **MAE** \\ \hline BCE & 0.868 & 0.805 & 0.913 & 0.948 & 0.036 & 0.703 & 0.632 & 0.841 & 0.862 & 0.042 \\ IoU & 0.886 & 0.838 & 0.902 & 0.937 & 0.038 & 0.729 & 0.664 & 0.829 & 0.848 & 0.045 \\ L1 & 0.886 & 0.835 & 0.903 & 0.941 & 0.032 & 0.751 & 0.681 & 0.843 & 0.869 & 0.038 \\ wBCE & 0.876 & 0.815 & 0.915 & 0.945 & 0.033 & 0.731 & 0.658 & **0.852** & 0.878 & 0.042 \\ wIoU & 0.892 & 0.842 & 0.905 & 0.940 & 0.037 & **0.762** & **0.699** & 0.845 & 0.870 & 0.041 \\ \hline Hybrid (wBCE + wIoU + L1) & **0.901** & **0.852** & **0.919** & **0.951** & **0.027** & 0.754 & 0.689 & 0.849 & **0.897** & **0.037** \\ \hline \hline \end{tabular}
\end{table}
Table 9: Comparison of the hybrid loss function and single loss functions.
# A Bayesian Modeling Approach to Situated Design of Personalized Soundscaping Algorithms
## 3 Experimental Validation
### Experimental Overview  
Two different experiments were conducted in this research to validate our proposed framework for the models from Section 2.2. In both experiments, the source model for the speech signal was pretrained offline, as speech signals are inherently complex to model and a short fragment will not be enough to capture all characteristics of speech. The noise model is trained on three seconds of the noise signal, which should be recorded in-the-field by the user. During the source separation stage in both experiments 10 s of the mixture signal, consisting of a speech and noise signal, is processed. In both experiments the signal-to-noise ratio (SNR) of the input signal is varied for a constant number of mixture components for the speech and noise model. The number of mixture components of the speech model has been set to 25. In the first and second experiment the number of noise clusters is set to 1 and 2, respectively.
[14] showed that it could be used as a dissipative element in ductility class medium structures. However, this joint design required a complex set of stirrups in the connection zone because the stirrups had to go through the steel beam. Figure 1: Two types of beam–column joint. To overcome this inconvenience, a novel RCS beam-column joint, in which an H steel profile covered by two supplementary plates embedded inside an RC column is directly welded to the steel beam, was proposed (Figure 2). The two supplementary plates are included in this design to avoid the stirrups resisting the shear in the connection region. A numerical study based on 3D finite element (FE) modeling recently performed by [PERSON] et al. [15] indicated that the static behavior of this novel joint depended strongly on the length of the encased steel profiles. It has been observed that the presence of supplementary plates in joint regions allowed for the removal of the stirrups in this region. Furthermore, the parametric study performed with various lengths of supplementary plates pointed out that supplementary plates were useful only at the beam-column connection. However, the cyclic behavior of this type of connection has not been studied yet. This paper describes an experimental study on the seismic performance of the above-mentioned novel joint. Two full-scale composite joints with and without supplementary plates were tested under reversed-cyclic loading. The seismic performance in terms of load-bearing capacity, story drift  
Figure 2: Description of the test specimens. capacity, ductility, energy dissipation, and stiffness was monitored and evaluated, and the results are presented herein.
## 4 Conclusions
This research was funded by EC through JOP Black Sea Basin 2014-2020, project code BSB27-MONITOX (2018-2021). **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Data supporting reported results are available from the corresponding author upon request. **Acknowledgments:** We acknowledge the support given by NIPNE team for technical support during PIGE analyses. **Conflicts of Interest:** The authors declare no conflicts of interest. Figure 12: SEM-EDX spectra and elemental maps for selected vegetal compartments. (**a**) SEM-EDX spectrum of _Triticium vulgare Vill._ caryopsis and the elemental map distribution (large starch particle (g1), medium starch particle (g2), small starch particle (g3), protein matrix (mp), plasma membrane (pc)); (**b**) SEM-EDX spectrum of a _Zea mays_ L. caryopsis and the elemental map distribution (small starch granule (g3), protein matrix (mp)); (**c**) SEM-EDX spectrum of cross-sectioned achenes of _Helianthus anusus_ L. and the elemental map distribution (lipid spherosomes (sl), cell membrane (mc), cell wall (pc)) [1]. \begin{table}
\begin{tabular}{c c c c} \hline  & _Tritcium vulgar_ & _Zea mays_ & _Helianthus annuus_ \\
**Elements** & _Vill._ & **L.** & **L.** \\ \hline \multicolumn{4}{c}{**Average Concentration (wt\%)**} \\ \hline C & 59.76 & 65.65 & 74.61 \\ N & 3.50 & 2.60 & * \\ O & 24.80 & 23.18 & 18.49 \\ Na & 0.10 & 0.08 & 0.16 \\ Mg & 0.20 & 0.22 & * \\ AI & 0.20 & 0.27 & 0.06 \\ Si & 0.10 & 0.07 & * \\ P & 0.60 & 0.48 & * \\ S & 0.40 & 0.33 & * \\ CI & 0.10 & 0.03 & * \\ K & * & 0.04 & 0.15 \\ Ca & 0.40 & 0.21 & 1.93 \\ Ti & * & 0.04 & 1.46 \\ V & * & 0.03 & * \\ Cr & 0.10 & 0.03 & 0.16 \\ Mn & 0.10 & 0.14 & * \\ Fe & 0.20 & 0.27 & * \\ Co & 0.30 & 0.18 & * \\ Ni & 0.30 & 0.60 & 0.19 \\ Cu & 0.90 & 1.18 & 0.17 \\ Zn & 0.80 & 0.66 & 0.09 \\ Pb & 6.18 & 3.71 & 2.57 \\ Hg & 1.24 & * & * \\ \hline \end{tabular}
* Not detected.  
\end{table} 
Table 10: Semi-quantitative EDX results of agricultural soil from TUL and SEN (GL) and VAD (BR) [1].
## 3 Material and Methods  
### Plant Materials and N-Deficient Treatments  
Cucumber (_Cucumis sativus_) cv. Lines 9930 were grown on 15 March 2015 and harvested on 23 April. The other six inbred lines (A23, A37, A38, A62, A74 and A91, cultivars of northern China) were grown 25 October and harvested on 10 December. Seeds were surface sterilized with 5% (\(w/v\)) NaClIO for 15 min and germinated on wet filter paper in the dark. Cucumber plants were then moved into a sponge floating and cultivated in a hydroponic system containing modified Hoagland solution (11 mM NO\({}_{3}\)\({}^{-}\), 1 mM NH\({}_{4}\)\({}^{+}\), pH 6.0) in a green house. The solutions were renewed every three or four days. After three true leaves reached, cucumber seedlings were moved into an N-free nutrient solution as N-deficiency treatment (0 mM NO\({}_{3}\)\({}^{-}\), 0 mM NH\({}_{4}\)\({}^{+}\); Ca(NO\({}_{3}\))\({}_{2}\) was replaced with CaCl\({}_{2}\); other ions were same as N-sufficient conditions except for chlorid ion (Table S4)), and plants cultivated in N-sufficient conditions as controls. The second fully expanded apical leaves were harvested and immediately frozen in liquid nitrogen and stored at \(-80\)\({}^{\circ}\)C until analysis. Plant samples were taken with three biological replicates.