esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Numerical and Simulation Results
### Multiple SWIPT Relaying Systems
#### 5.2.2 Outage Probability Comparison  
In Figures 8 and 9, the outage probability is compared with respect to the direct link SNR for varying values of \(R\), with the power-splitting ratio set to the optimal value, \(\rho_{r}=\rho_{\text{opt}}\), under Ch. Model\(=[1,1,X]\) and Ch. Model\(=[1,X,1]\), respectively. From Figures 8 and 9, it can be observed that the outage probability performance improves as \(R\) increases. It is verified that the analytical approximation denoted as 'Theory, AF-App' provides an upper bound on the outage probability for both the indirect and combined links. Moreover, as \(R\) increases, the performance gap between the indirect and the combined links becomes smaller. As \(R\) increases, the outage performance difference between indirect and combined links decreases. Furthermore, the analytical result labeled as 'Theory, Exact' based on (45) shows an excellent match with the simulation results across all SNR values of the direct link. Although the gap between the simulation results and the 'Theory, AF-App' results derived from (44) becomes more pronounced as \(R\) increases, the approximate analysis still accurately captures the overall trend of the outage probability performance with increasing \(R\).
# Guidelines towards Information-Driven Mobility Management
## 4 Mobility in ICN
### Consumer Mobility
#### 4.5.3 Consumer Mobility Discussion  
As the pull-based model relies on a per packet approach, even if a consumer already received some data chunks and then moves, transmission can be immediately re-established once the consumer (MN or CN) can send data to a neighbour. In our examples, this is synonymous with the consumer being in a state that allows it to forward Interest packets again. At a first glance, ICN supports consumer mobility well. Nevertheless, in large-scale networks and environments where consumers move frequently and quickly (e.g., vehicular networks and personal Internet of Things environments), data transmission may still be affected by frequent movement. Even though the in-network caching provided by ICN can counter-balance such situations, the performance of the data transmission is highly dependent on aspects such as the type of topology, type of movement, and speed of nodes.
### Motivation, Contribution, and Organization
The joint power control, spectrum allocation, and link matching is formulated as an integer programming problem, which can be decomposed into two parts: (1) a series of spectrum allocation and power control sub-problems, and (2) a weighted bipartite graph matching between potentially matched primary and secondary link pairs. Given the linear nature of WSP, these sub-problems can be easily proved convex and effectively solvedusing [PERSON]'s method. For the weighted bipartite matching problem, we employ the well-established Kuhn-Munkres (KM) algorithm to find the optimal solution. In our prior work [30], we have proposed a suboptimal resource allocation scheme with low computation time based on [PERSON]'s method and graphical method for the cooperative spectrum sharing in cognitive radio networks (i.e., the scenario where SUs serve as relays in exchange for the opportunity to access PUs' authorized spectrum). This work was also dedicated to minimizing system WSP. However, unlike the prior work, this paper focuses on a more common spectrum-sharing mode, i.e., overlay spectrum sharing. We derive an optimal spectrum allocation and power control scheme using [PERSON]'s method and the KM algorithm. The differences between [30] and this paper are listed in Table 1.  
The main contributions of our paper are summarized below:  
1. To the best of our knowledge, it is the first time that WSP has been taken as the objective function to handle resource allocation problems for overlay spectrum sharing. We also present the system model and frame structure associated with the proposed centralized scheme;  
2. Utilizing [PERSON]'s method, the optimal solutions for the spectrum allocation and power control sub-problems can be found with very short computational time;  
3. We also propose corresponding heuristic approaches to accelerate the convergence of [PERSON]'s method, which makes our scheme more suitable for practical real-time applications. Through simulation, the effectiveness and efficiency of our proposed centralized scheme and heuristic approaches are validated. The rest of this paper is organized as follows: In Section 2, we present the system model and formulate a joint problem of spectrum allocation, power control, and link-matching to minimize system WSP. Section 3 proposes a scheme based on the KM algorithm and [PERSON]'s method. In this section, we also discuss the initial value selection in [PERSON]'s method and weight adjustment. In Section 4, we present simulation results to evaluate the performance of the proposed scheme. Finally, we conclude this paper in Section 5.
## 4 Experimental Results
### Cross-Validation
#### 4.3.1 K-Fold  
We split our dataset into five clusters using K-fold, each cluster giving a different accuracy. Table 5 and Figure 6 show the accuracy for each cluster and the mean using K-fold cross-validation. Figure 7 shows other performance metrics of the six classifiers using K-fold cross-validation.  
Figure 4: Cross-validation scores under different numbers.  
Figure 5: Correlation matrix heatmap for selected features.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Cluster 1** & **Cluster 2** & **Cluster 3** & **Cluster 4** & **Cluster 5** & **Average** \\  & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** \\ \hline MLP & 81.42 & 81.42 & 82.85 & 87.85 & 84.44 & 83.59 \\ SVM & 85.71 & 85.71 & 91.42 & 82.85 & 88.14 & 86.76 \\ RF & 84.28 & 94.28 & 95.71 & 97.14 & 89.62 & 92.20 \\ Bagging & 91.42 & 94.28 & 95.71 & 92.85 & 86.66 & 92.18 \\ AdaBoost & 90.00 & 94.28 & 94.28 & 91.42 & 89.62 & 91.92 \\ Gradient & 92.85 & 94.28 & 97.14 & 95.71 & 86.66 & 93.32 \\ Boosting & \multicolumn{1}{c}{} & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 5: K-fold Cross-Validation Accuracy Prediction For Six Classifiers.
## 4 Discussion
#### 4.1.1 Influence Mechanism of Confining Pressure  
The single-factor test of confining pressure showed that the permeability of all four subcategories of sandstone decreased with increasing confining pressure, which indicated that strain was generated in the sandstone under confining pressure (see Figure 15). In the low confining pressure range of 0-10 MPa, the permeability decreased rapidly, but the change in permeability decreased with increasing confining pressure. This is because when the confining pressure began to act on the sandstone, the particles in the sandstone skeleton underwent strain, resulting in the volume compression of pores and pore throats and the rapid reduction in sandstone permeability. However, when the pores and pore throats were compressed to a certain extent, the compression effect of stress on the pores and pore throats decreased, so the changes in the permeability of the sandstone samples decreased.  
Figure 14: Trend analysis of orthogonal test results for subcategory II\({}_{2}\) sandstone.
# Dynamic and Static Investigation of Ground Heat Exchangers Equipped with Internal and External Fins
## 5 Results and Discussions
### Short Timescale Response
By increasing the wave frequency (1/2400 Hz), the output wave amplitude decreases due to the reduction in the system response time compared to the first mode (1/4800 Hz). Figure 6: Fluid inlet and outlet temperatures with a frequency of 1/4800 Hz: (**a**) simple U-tube; (**b**) U-tube with outer fins; (**c**) U-tube with inner fins; (**d**) comparison of fluid outlet temperatures in three simple and finned U-tubes. According to Table 7, the difference between the average value of the input and output waves, with a frequency of 1/4800 Hz, in the simple pipe is 4.46 \({}^{\circ}\)C, in the pipe with external fins is 4.59 \({}^{\circ}\)C and in the internally finned pipe is 4.97 \({}^{\circ}\)C. The use of external fins increases temperature reduction in the fluid by 2.9% compared to a simple U-tube and the internal fins increase temperature reduction in the fluid by 11%. By doubling the frequency, the average value of the output wave has not changed compared to the first frequency, but the wave amplitude has decreased by 35% in the simple pipe, 39% in the pipe with the outer fins and 49% in the inner finned pipe. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{2}{c}{**Amplitude of Wave**} & \multicolumn{2}{c}{**Mean of Wave**} \\ \hline
**Inlet Temperature** & **8** & **28** \\ \hline \multirow{2}{*}{Outlet temperature (\({}^{\circ}\)C) with a frequency of 1/4800} & Simple U-tube with outer fins & 2.62 & 23.54 \\  & U-tube with outer fins & 2.40 & 23.41 \\  & U-tube with inner fins & 2.06 & 23.03 \\ \hline \multirow{2}{*}{Outlet temperature (\({}^{\circ}\)C) with a frequency of 1/2400} & Simple U-tube with outer fins & 1.69 & 23.54 \\  & U-tube with outer fins & 1.46 & 23.41 \\  & U-tube with inner fins & 1.04 & 23.03 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Input and output wave characteristics with different frequencies. Figure 7: Fluid inlet and outlet temperatures with a frequency of 1/2400 Hz: (**a**) simple U-tube; (**b**) U-tube with outer fins; (**c**) U-tube with inner fins; (**d**) comparison of fluid outlet temperatures in three simple and finned U-tubes. It was expected that finned GHEs have faster thermal responses than the smooth one. A comparison of the phase shift between the inlet and outlet temperature of the fluid in the three U-tubes shows that the thermal response of the three numerical models is almost simultaneous. The time shift of the outlet temperature of the simple and the externally finned pipes is 1200 s and in the internally finned pipe is 1320 s in a frequency of 1/4800 Hz. The time shift values at the second frequency of 1/2400 Hz for simple and externally finned pipes is 900 s and in pipes with internal fins is 1020 s.
# Communication System Based on Magnetic Coils for Underwater Vehicles
###### Abstract  
In this work, a wireless communication system based on magnetic coils for underwater vehicles is presented. Firstly, the mathematical model of magnetic field induction using magnetic coils is discussed. Then, a description of the proposed communication system is presented, including the main components of the transmitter and receiver module. The experimental results show that due to the properties of the magnetic field, the proposed communication system can work properly in different environments such as air or water with the same efficiency. Underwater tests were carried out in different water circumstances: varying the temperature in a range from 10 \({}^{\circ}\)C to 35 \({}^{\circ}\)C, varying concentrations of clay in a range from 0% to 10%, and varying the salinity concentration in a range from 1000 ppm ( parts per million) to 35,000 ppm. It was observed that these conditions do not affect the information transfer. Finally, the advantages of using the proposed system compared to existing submarine communication systems are discussed.  
wireless communication; magnetic field; underwater communication; magnetic coil; magnetic induction 20222222183
# Collecting Sensed Data with Opportunistic Networks: The Case of Contact Information Overhead
## 2 Problem Background
By maintaining and updating encounter history about other nodes in the network, these approaches can efficiently identify routing paths to destination nodes [36], thereby making them more suitable for sensed data collection. PRoPHET in particular inspired most of the encounter-based protocols and continue to inspire forthcoming ones, and has been incorporated into the reference implementation maintained by the Internet Research Task Force Delay Tolerant Networks Research Group. PRoPHET has also been trialed in real-world situations during the Sami Network Connectivity project [45] and is being further developed for the European Union's Seventh Framework Programme project (namely Networking for Communications Challenged Communities) [46]. Hence, irrespective of how the forwarding utility is computed, most encounter-based protocols apply PRoPHET's approach of exchanging and updating contact information. This section describes this approach and the problem of contact information overhead that arises. Existing solutions for addressing the problem and their shortcomings are also presented.
## 2 Materials and Methods
### Optimization of Fermentation Parameters  
Fermentation parameters were optimized according to the method described in [PERSON] and [PERSON] [29]. The parameters optimized included pH, temperature, and media of fermentation using a full-factorial design (7 \(\times\) 5 \(\times\) 4). Four different fermentation media were used to study the optimum medium including rice, wheat, wheat bran, and malt as described earlier [29], whereas rice was found to be the most optimal media, and thereby used in further experiments. A pH range of 3 to 12 was investigated to optimize the production of antioxidants. Antioxidant efficacy was estimated by the thiocyanate method [30]. Different pH values were used for organic solutions including citrate (at pH 3 and 5) with a concentration of 0.2 M, and phosphate (regulated at pH 7, 9, 10, 11, and 12) with a concentration of 0.2 M to study the effect of pH on the stability of the antioxidative activity of _A. flavus_. The obtained data was compared to the control sample (containing BHT and alphatocopherol) grown in the same pH. Different temperatures were used to optimize the production of antioxidants produced from rice koji inoculated with _A. flavus_. Five growth temperatures were explored; 20, 25, 30, 35, and 40 \({}^{\circ}\)C.
# Gearbox Fault Diagnosis Based on ICEEMDAN-MPE-AWT and SE-ResNeXt50 Transfer Learning Model
## 3 Gramian Angular Field  
Gramian angular field can transform a one-dimensional time series to two-dimensional image encoding. In Gramian angular field, the elements on the main diagonal correspond to different timestamp values. The article encoded time series into images by using GASF based on the polar coordinate matrix, so as to preserve the correlation between one-dimensional information and the time series. The process of transforming a one-dimensional time series into a two-dimensional image based on GASF is as follows.  
1. For a given original time series \(x=\{x_{1},x_{2},\ldots,x_{n}\}\), it can be normalized to between 0 and 1 through Equation (17): \[\widetilde{x}_{t}=\frac{x_{t}-x_{min}}{x_{max}-x_{min}},\] (17) where, \(\widetilde{x}_{t}\) is the scaled signal at time \(t\), and \(x_{min}\) and \(x_{max}\) are the minimum and maximum values in the sequence, respectively. Then, the normalized time series can be mapped to the polar coordinate system according to Equation (18): \[\left\{\begin{aligned} \phi_{i}=\arccos(\widetilde{x}_{i}),0\leq \widetilde{x}_{i}\leq 1\\ r_{i}=\frac{t_{i}}{N},t_{i}\in N\end{aligned},\right.\] (18) where \(\phi_{i}\) is the angular value of the polar coordinate corresponding to \(\widetilde{x}_{i}\), \(r_{i}\) is the polar coordinate radius corresponding to \(\widetilde{x}_{i}\), \(t_{i}\) is the timestamp corresponding to \(\widetilde{x}_{i}\), and \(N\) is the length of the time series.
2. After the one-dimensional signal is mapped to the polar coordinate system, the value of the angular and difference between each point is used to measure the time dependence of the different time intervals. Finally, the GASF can be obtained according to Equation (19): \[GASP=\begin{bmatrix}\cos(\phi_{1}+\phi_{1})&\cos(\phi_{1}+\phi_{2})& \cdots&\cos(\phi_{1}+\phi_{n})\\ \cos(\phi_{2}+\phi_{1})&\cos(\phi_{2}+\phi_{2})&\cdots&\cos(\phi_{2}+\phi_{n}) \\ \vdots&\vdots&\vdots&\vdots\\ \cos(\phi_{n}+\phi_{1})&\cos(\phi_{n}+\phi_{2})&\cdots&\cos(\phi_{n}+\phi_{n}) \end{bmatrix},\] (19)
## 3 Results
### Heavy Metal Contents
The Zn level in soil samples taken from organic and conventional farming areas was examined, and the highest Zn content was 133.80 ppm at station 6 in soil samples taken from organic farming areas and 74.66 ppm at station 1 in samples taken from conventional farming areas (Figure 3a). When soil samples taken from organic and conventional production areas were compared in terms of total Zn content, the Zn level was higher in soil samples taken from organic farming areas. Figure 2: Zn (**a**), Cu (**b**) and Pb (**c**) contents in water samples taken from different stations. Circular marks indicate statistically significant differences (_p_ < 0.05) between organic and conventional stations. The data obtained show that the highest Cu content was 74.26 ppm at station 1 in soil samples taken from regions with organic farming and 108.10 ppm at station 4 in samples taken from regions with conventional agriculture (Figure 3b). When soil samples taken from organic and conventional production areas were compared in terms of total Cu content, the Cu level was higher in soil samples taken from conventional farming areas. When the Pb level was examined in soil samples taken from organic and conventional farming regions, the highest Pb content was 10.58 ppm at station 1 in soil samples taken from organic farming areas and 35.69 ppm at station 10 in samples taken from conventional farming areas (Figure 3c). In terms of total Pb content, when soil samples taken from organic and conventional production regions were compared, the Pb level was higher in soil samples taken from conventional farming regions. The correlation between Zn and Cu contents in soil water samples taken from strawberry stations practicing conventional and organic growing methods and Zn and Cu contents taken from fruit samples is given in Figure 4.  
Figure 3: Zn (**a**), Cu (**b**) and Pb (**c**) contents in soil samples taken from different stations. Circular marks indicate statistically significant differences (_p_ < 0.05) between organic and conventional stations. In Figure 4, it is seen that there is a high correlation between the Zn content in irrigation water and the Zn content in strawberries. This is an expected situation. However, the same conditions could not be determined between the Zn content in the soil content and the content determined in the fruit. A similar situation is observed for Cu contents in soil, water and fruit. The relationship between the variables is a \"cause and effect\" relationship, and it may not always seem clear. Therefore, the fact that the variables change together does not always mean that there is a cause-effect relationship between them.
## 6 Conclusions  
This paper proposes a MRCFM approach to suppress the DPWM-induced sideband harmonic and vibro-acoustic components. The multi-physical field co-simulation prediction model is developed to numerically forecast the spectral distribution and amplitude characteristics of the sideband vibro-acoustic response with different PWM strategies. According to the research results, the conclusions are as follows:  
(1) The proposed MRCFM can effectively optimize the performance of random numbers, further optimizing the sideband current harmonics and vibro-acoustic response, and the distribution of the sideband spectrum shows better uniformity. The optimal noise suppression effect can reach 11 dBA.  
(2) The co-simulation model constructed based on multi-physics fields can accurately predict the sideband vibro-acoustic response of each DPWM scheme. The error between the simulation results and the measured results is within 8%, which verifies the accuracy of the co-simulation prediction model with multi-physics fields.  
(3) The proposed PSO optimization algorithm can effectively optimize the random gain \(R\) and the transition probability \(P\), and the analysis method proposed in this paper can be applied to the prediction and analysis of sideband acoustic vibration of PMSM under various PWM strategies, which can provide a new idea for the identification and optimization of sideband acoustic vibration characteristics of PMSM.  
Data curation, Y.C., B.Y., L.Z. and X.J.; software, Y.C., B.Y. and L.Z.; writing--original draft preparation, Y.C. and B.Y.; writing--review and editing, Y.C. and K.Y.; project administration, Y.C. and K.Y. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the Guangxi Science and Technology Major Program (2023 AA09006).  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
Author [PERSON] was employed by the company Wuhan Fareo Automotive Parts Co., Ltd. Author [PERSON] was employed by the company Dongfeng Liuzhou motor Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  
Figure 22: Comparison of simulated and measured peak sideband acoustic response for different modulation strategies.
# Force Performance Analysis and Numerical Simulation of Assembled Ribbed-Slab Abutments
## 2 Static Load Test of Assembled Ribbed-Slab Abutment Model
### Bending Test of Assembled Ribbed-Abutment
#### 2.2.2 Experimental Results  
By summarizing and comparing the main performance indices of the two ARBA models with different joint configurations and the cast-in-place abutment model, appropriate joint configurations of the ARBA were explored through comparative analyses.  
(1) Crack load  
The results obtained from the tests were used to determine the cracking loads of each abutment model, and the comparison results are listed in Table 2. The data reveal that the cracking load of the NT2 abutment model was only 58% of that of the XJ1 abutment model. The cracking load of the FLP3 abutment model was 67% of that of the XJ1 abutment model. These findings indicate that, in terms of cracking resistance, the ARBA with a flanged joint configuration exhibited a superior performance.  
Figure 4: Comparison of load–deflection curves of test models.  
Local ultimate load  
Based on the measured results obtained from the tests, Table 2 lists the ultimate bearing capacity of each abutment model and comparison results. According to the data in the table, the ultimate load-carrying capacity of the NT2 bridge pier model was only 60% that of the XJ1 bridge pier model. Conversely, the ultimate load-carrying capacity of the FLP3 abutment model was 100% or equal to that of the XJ1 abutment model. This suggests that, in terms of bearing capacity, the ARBA model with a flanged joint structure can achieve a performance level \"equivalent to cast-in-place\".  
(3) Local limit displacement  
While testing the NT2 and FLP3 models, the structural joint position was damaged when the structure reached the ultimate state, which manifested as a transient state. In contrast, for the XJ1 model, once it reached the ultimate load, the load remained unchanged, and the displacement continued to increase as the loading proceeded. The displacement of the structural state at the time of reaching the ultimate load was used as basis for comparison data in this study. Table 2 lists the ultimate displacements of each bridge abutment model and the comparison results. Evidently, the ultimate displacements of the two ARBA models with different configurations were smaller than those of the cast-in-place abutment model (XJ1 abutment model). The ultimate displacement of the NT2 abutment model reached 84% of that of the XJ1 abutment model, while the ultimate displacement of the FLP3 abutment model reached 80%. Therefore, the deformation capacities of the two ARBA models were not significantly different and were weaker than those of the cast-in-place abutment model.