esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Process  
### Experimental Device  
In this study, a ferrofluid was used as the heat transfer medium. It was a colloidal solution containing Fe\({}_{3}\)O\({}_{4}\) magnetic nanoparticles with a size of 5 to 15 nm in an oil-based base fluid called EFH-1. It was composed of iron oxide magnetite, oleic acid dispersant, hydrotreated light distillate. Surfactant treatment was applied to prevent agglomeration between particles. Table 1 shows the physical properties of EFH-1 [13]. It has a property of increasing thermal conductivity when an external magnetic field is applied, so heat transfer performance can be improved by using ferrofluid. The overall experimental setup is shown in Figure 1a. To contain the ferrofluid, a Pyrex glass tube with high heat resistance was used. The temperature deviation was set to compare the heat transfer performance inside the glass tube according to the arrangement of permanent magnets. A heating pad was placed to transfer high temperature heat to the lower portion of the glass tube. The heating pad was the principle of generating heat by the internal coil. This device can set the target temperature through the control box. Permanent magnets were placed around the glass tube to apply an external magnetic field. Neodymium permanent magnets (20 mm \(\times\) 15 mm \(\times\) 3 mm) were used, and they were arranged as shown in Figure 1c. The magnetic field strength was set to 0.325 T. When permanent magnets are fixed in one position without movement, magnetic nanoparticles aggregate only around the magnets, and the fluidity of the ferrofluid is limited. Therefore, linear motors were used to ensure the dispersion of the particles and to promote heat exchange by the fluid. Permanent magnets were placed on the front side of the motors; the magnets moved according to the reciprocating motion of motors. Through various arrangements of the permanent magnets, the behavior of the ferrofluid inside the glass tube could be diversified, thereby affecting the heat transfer performance. A T-type thermocouple TC wire was used to measure the temperature inside the glass tube in real time. The TC wires were placed at four points at regular height intervals, and the location was set at the center of the glass tube. The temperature data obtained from the TC wires was confirmed in real time through a data acquisition system DAQ (DAQ970A, of Keysight). Temperature data using the DAQ was measured and stored at 2 s cycle.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Properties** & **Value** \\ \hline Thermal conductivity & 0.19 W/(m\(\cdot\)K) \\ Thermal expansion coefficient & 0.00086 1/K \\ Relative permeability & 2.552 \\ Heat capacity at static pressure & 1840 1/(kg\(\cdot\)K) \\ Density (T = 298.15 K) & 1221 kg/m\({}^{3}\) \\ Dynamic viscosity & 0.00727 Pa\(\cdot\)s \\ \hline \hline \end{tabular}
\end{table}
Table 1: The properties of EFH-1 [13].
# Investigation into the Fire Hazards of Lithium-Ion Batteries under Overcharging
## 3 Results and Discussion
### Discussion  
The experimental results reveal that a battery overcharged beyond the cut-off voltage will exhibit higher fire hazard, and the hazard increases with the rise in voltage. To explain why overcharge greatly affects the thermal behaviors of LIB, the charging mechanism of LIB needs to be clarified. When an LIB is in a state of equilibrium, there will be a lithium ion concentration difference between the cathode and anode that is related to the open circuit voltage of battery. The cut-off voltage is the open circuit voltage when battery is fully charged and it is generally taken to be 4.2 V for 18650 LIB. During charging, a voltage applied across the electrodes forces lithium ions to be extracted from the cathode crystal and transferred to the graphite anode through electrolyte. This results in a decline in the lithium ion concentration in the cathode and growth in the anode. The process is demonstrated vividly in Figure 12. Overcharge beyond the cut-off voltage implies the excessive extraction of lithium ions from the cathode, which causes the collapse of the cathode crystal. The collapsed cathode will lose the ability to absorb lithium ions. Hence, the LIB is damaged irreparably. On the other hand, overcharge  
Figure 11: Heat flux curves of LIBs during tests: (**a**) NMC; (**b**) LFP.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**LIB Type** & **Voltage/V** & **Peak Heat Flux (kW/m\({}^{2}\))** & **Total Radiative Heat Flux (kJ/m\({}^{2}\))** & **Total Radiative Heat (kJ)** \\ \hline \multirow{4}{*}{NMC} & 4.2 & 1.81 & 25.9 & 27.5 \\  & 4.5 & 3.08 & 26.7 & 28.3 \\  & 4.8 & 6.51 & 41.4 & 43.9 \\  & 5.0 & 7.63 & 41.8 & 44.3 \\ \hline \multirow{4}{*}{LFP} & 4.2 & 1.98 & 26.7 & 28.3 \\  & 4.5 & 4.77 & 34.7 & 36.8 \\ \cline{1-1}  & 4.8 & 6.72 & 36.3 & 38.5 \\ \cline{1-1}  & 5.0 & 1.99 & 17.9 & 19.0 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Some detailed data on heat flux in tests.  
will result in strong Li metal plating on the surface of the anode [7; 28; 29]. Li metals are sticky and will puncture the separator between the cathode and anode, resulting in the short circuiting of the battery. The overcharged LIB is in an unstable state. Finally, overcharge beyond the cut-off voltage will bring a high \(SOC\) to the battery. However, \(SOC\) has a great influence on the thermal stability of electroactive materials, where highly delithiated electroactive materials become more reactive [30; 31]. This induces more intense reactions in the processing of thermal runaway, including SEI decomposition, the polymer separator shrinking, reaction between electrode materials, reaction between the electrode material and electrolyte, etc. [32; 33]. The whole scheme of a battery catching fire is shown in Figure 13.
## 3 Results and Discussion
### Optimization of HS-SPME
#### 3.2.3 The Effect of Salt Contents on the Extraction  
The salinity of the sample solution also affects the efficiency of SPME. It was reported that the salt effect improves the ionic strength of the solution, reduces the solubility of the target compound in the solution and promotes the volatilization of malodorous substances [30]. In the present work, the salt effect was studied by adding a series of 0-1.8 g NaCl to 6.0 mL of sample solution. As can be seen from Figure 5a, the addition of NaCl significantly increased TN and TA in comparison to that of the control group. These results suggest that a certain amount of salt is helpful to drive volatiles from the sample matrix to the fiber coating. The increase in the total number of volatile compounds and their peak area can be attributed to the fact that the addition of NaCl can enhance the ionic strength of water samples [31], thereby reducing the solubility of organic compounds by the so-called saltsing out effect. With the increase of salt concentration, however, the extraction efficiency for SA increases at first and then decreases gradually. It was found when the concentration of NaCl reached 20%, the peak area of the SA tended to be stable. Thus, this concentration was selected for the subsequent experiment.
# Hardware Design for Cascade-Structure, Dual-Stage, Current-Limiting, Solid-State DC Circuit Breaker
## 4 Hardware Design of the Circuit Breaker Prototype
### Power Supply System Design  
The physical diagram of the capacitor power supply is shown in Figure 4a. For flexible application in the circuit breaker prototype, four integrated capacitor power supplies with different capacities are used. The capacities from left to right in the physical setup are 680 \(\mu\)F, 1000 \(\mu\)F, 2200 \(\mu\)F, and 4700 \(\mu\)F, respectively. Each capacitor is connected in series with a mechanical switch to achieve hard open and close for charging and discharging. During the charging process of the capacitors, a current-limiting resistor needs to be connected; in this design, the current-limiting resistor is a 100 \(\Omega\) plug-in resistor. The soft switch circuit of the capacitor power supply is illustrated in Figure 4b. The left side connects to the output of the capacitor power supply, and the right side connects to the power supply interface of the circuit breaker mainboard. The STM32 microcontroller drives the MOSFET through an optocoupler and MOSFET driver circuit (to be detailed later) to achieve soft open and close of the capacitor power supply, effectively preventing premature discharge of the power capacitors during circuit breaker startup, which could cause the circuit breaker to fail to start.
## 3 Results and Discussion
### PTFE Thermal Expansion
Figure 6 demonstrates how the annealing process releases manufacturing residual stresses so that the length of PTFE and the antenna efficacy will not change during ablation. Another observation is that the annealed antennas exhibit notably lower standard deviation than the non-annealed antennas during the heating cycles. The decrease in variability suggests improved dimensional stability owing to reduced non-linear expansion under ablation conditions. This is especially important, given that the applicator is disposed of after the ablation process. Greater standard deviation during the cooling cycle and minor shrinkage of PTFE were also noted in the annealed antennas, probably due to extended heating and subsequent uncontrolled natural cooling. This indicates that the parameters of the annealing process, especially the cooling rate, need further refinement. Future studies could benefit from incorporating a slower, more controlled cooling phase to increase the polymer's entropy state, which may help alleviate residual stresses and minimise dimensional instability.
## 3 Results and Discussion
### Discrimination Models for South Korean and Chinese Rice Using Pre-Treatments
However, the discrimination accuracies of these pre-treatment methods are very high (over 95%). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Pretreatment**} & \multirow{2}{*}{**None**} & \multirow{2}{*}{**SNV**} & \multirow{2}{*}{**Baseline**} & \multirow{2}{*}{**MSC**} & \multicolumn{4}{c}{**Normalization**} & \multirow{2}{*}{**Smoothing**} & \multirow{2}{*}{**1D [FOOTNOTE:]Footnote : 1D: first-order derivatives with a gap of 43.2 nm, 2D: second-order derivatives with a gap of 52.8 nm, 2D: second-order derivatives with a gap of 52. The geographical discrimination models that included baseline pre-treatment, maximum normalization, smoothing pre-treatment, and Savizky-Golay first-order and second-order derivatives yielded a total accuracy of 98.89% (Figure 6). Among these pre-treatment methods, when the Savizky-Golay first-order and second-order derivative were applied together, the discrimination model yielded a low optimal factor and high R\({}_{\text{v}}\)2. Therefore, it is apparently the most efficient pre-treatment method in this model (Table 5). According to a previous study [1], the discrimination accuracies of a rice geographical origin model developed using one year of data (2016) were all above 99.99% for the South Korean rice samples. The discrimination accuracies of the PLS models developed in this study, which applied three years of data, were relatively low compared to those previous results [1]. This may be because rice samples harvested for three years included more cultivation environment differences, such as cultivation temperature, climate, and soil conditions, than the samples harvested for one year. Considering these differences, the results show that the proposed models with pre-treatment provide excellent performance for geographical origin discrimination. Furthermore, the discrimination accuracies of these models are outstanding compared to those of another previous study [37], which showed 93.5% rice geographical origin discrimination accuracy by using an electronic nose combined with ICP-MS by PCA and linear discriminant analysis (LDA).
# Impact of Direction Parameter in Performance of Modified AODV in VANET
###### Abstract  
A vehicular ad hoc network (VANET) is a technology in which moving cars are used as routers (nodes) to establish a reliable mobile communication network among the vehicles. Some of the drawbacks of the routing protocol, Ad hoc On-Demand Distance Vector (AODV), associated with VANETs are the end-to-end delay and packet loss. We modified the AODV routing protocols to reduce the number of route request (RREQ) and route reply (RREP) messages by adding direction parameters and two-step filtering. The two-step filtering process reduces the number of RREQ and RREP packets, reduces the packet overhead, and helps to select the stable route. In this study, we show the impact of the direction parameter in reducing the end-to-end delay and the packet loss in AODV. The simulation results show a 1.4% reduction in packet loss, an 11% reduction in the end-to-end delay, and an increase in throughput.  
AODV; end-to-end delay; packet loss ratio; throughput; VANET Article Impact of Direction Parameter in Performance of Modified AODV in VANET
# Improvement of Fast Simplified Successive-Cancellation Decoder for Polar Codes
## 3 Proposed Method  
By taking advantage of the special positions of the frozen bits, the Rep and SPC nodes are identified from the R-other nodes of the SSC pruned tree. Because the frozen leaf bits have no particular location, there is no corresponding low-complexity decoding algorithm for the remaining R-other nodes, which causes additional latency. To further reduce the decoding latency and adapt to the different rates and different channel conditions, we propose an approach that combines the stability of the recognition-based method and the dynamics of the check-based method, as described in this section.  
The proposed method is called Fast-ISSC. First, the different constituent codes are identified on the decoding tree offline. During decoding, the current node can be decoded directly if it is a special constituent code; otherwise, the FC is performed at the R-other nodes, reducing the decoding latency of those nodes. Simultaneously, the problem of high latency for the check method in the case of a high code rate and low SNR can be solved. The overall procedure of the Fast-ISSC decoder is described in Algorithms 1-4. First, the main function is summarized in Algorithm 1. The receiver calculates an LLRs vector \(\boldsymbol{L}=(l_{1},...,l_{N})^{\text{T}}\) with \(l_{i}=\ln(W(y_{i}|1)/W(y_{i}|0))\), and feeds it into the Fast-ISSC decoder. Then, the node state initialization is outlined in Algorithm 2. The FC and \(\beta_{v}\) procedures are summarized in Algorithms 3 and 4, respectively.
## 4 Experiments
### The Performance of Similar User Recommendation
#### 4.2.4 Effects of Autoencoder for Dimension Reduction  
To verify the effectiveness of using an autoencoder in finding similar users, we took the features produced by either early fusion or late fusion as inputs to a single-layer neural network for dimension reduction. The performance comparison of autoencoders in different dimensions is shown in Figure 11.  
Figure 11: The performance of autoencoders with different dimensionality.  
Figure 9: The performance comparison of early and late fusions.  
From the experimental results in Figure 11, the best performance could be obtained with the average top-k accuracy of 0.462, when the feature dimension was reduced to 1500 if we used the feature map as the features. This was not as good as the best performance after either early or late fusion. However, the number of dimensions could be greatly reduced from 4096 to 1500. This can help reduce the storage needed for the redundant features. It would be useful to keep the more important features for more efficient computations in practice.
## 2 Friction Coefficient Estimation
### Calculation of the Tire Side-Slip Angles and Slip Ratios  
The speed and direction of each wheel can be calculated as follows [33; 34; 35; 36; 37]:  
\[\left\{\begin{array}{l}v_{xfl}=(v_{x}-\omega_{r}l_{s})\cos\delta_{f}+\left( v_{y}+\omega_{r}l_{f}\right)\sin\delta_{f}\\ v_{xfr}=(v_{x}+\omega_{r}l_{s})\cos\delta_{f}+\left(v_{y}+\omega_{r}l_{f} \right)\sin\delta_{f}\\ v_{xrl}=(v_{x}-\omega_{r}l_{s})\cos\delta_{r}+\left(v_{y}-\omega_{r}l_{r} \right)\sin\delta_{r}\\ v_{xrr}=(v_{x}+\omega_{r}l_{s})\cos\delta_{r}+\left(v_{y}-\omega_{r}l_{r} \right)\sin\delta_{r}\\ \end{array}\right. \tag{5}\]  
and:  
\[\left\{\begin{array}{l}\theta_{fl}=\arctan\left(\frac{v_{y}+\omega_{r}l_{f} }{v_{x}-\omega_{r}l_{s}}\right)\\ \theta_{fr}=\arctan\left(\frac{v_{y}+\omega_{r}l_{f}}{v_{x}-\omega_{r}l_{s}} \right)\\ \theta_{rl}=\arctan\left(\frac{v_{y}-\omega_{r}l_{r}}{v_{x}+\omega_{r}l_{s}} \right)\\ \theta_{rr}=\arctan\left(\frac{v_{y}-\omega_{r}l_{r}}{v_{x}+\omega_{r}l_{s}} \right)\\ \end{array}\right., \tag{6}\]  
where \(v_{xi}\) and \(\theta_{i}\) (\(i=fl\), \(fr\), \(rl\), and \(rr\)) are the speed and direction, respectively, of each wheel. The longitudinal speed, lateral speed, and yaw rate can be obtained by means of integrated GPS/INS sensors [30]. The front and rear steering angles can be obtained from angle sensors in the steering system.  
The side-slip angle and slip ratio of each tire can be expressed as follows:  
\[\alpha_{i}=-\delta_{i}+\theta_{i} \tag{7}\]  
and:  
\[s_{i}=\frac{v_{xi}-\omega_{i}\hat{R}_{wi}}{\max\left(v_{xi},\omega_{i}\hat{R} _{wi}\right)}, \tag{8}\]  
where \(i=fl\), \(fr\), \(rl\), and \(rr\) and \(\omega_{i}\) is the rolling speed of the corresponding wheel, which can be obtained from an angular speed sensor on that wheel.
## 5 Discussion and Future Research Directions
### Decentralized Networks  
This survey focused basically on the centralized networks where the controller has the full information about the network, devices, and architecture. The centralized framework maintains efficient resource management and allocation. Table 4 illustrates the benefits and the limitations of this architecture.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Benefits** & **Limitations** \\ \hline Low complexity & Abrupt failure \\ \hline Efficient resource management & Security issues \\ \hline Economical & Bottlenecks problem and latency \\ \hline Easy control and Quick updates & Single point of failure \\ \hline \hline \end{tabular}
\end{table}
Table 4: Centralized architecture: Benefits vs. limitations.  
The need to apply a distributed architecture is increased due to the emergent applications such as the 5G networks and beyond. The new generations of mobile networks become more and more distributed by paving gradually its way into modern technologies since the resources can be managed and shared among individual nodes, and each player can be the consumer as well as the provider. This distributed architecture must be able to capably run applications such as device-to-device, machine-to machine, and internet of things at reduced latency. Therefore, game theory attracts a lot of attention as an efficient and suitable solution to solve the optimization problem in the decentralized architecture such as reducing latency and maximizing bandwidth between nodes. In [68, 69], the authors introduced game models to the device-to-device communications to solve the interference and routing problems. Thus, using game theory for the optimization problems in the centralized and decentralized network virtualization remains a hot research topic for many researchers.
## 5 Conclusions  
This research introduced a medical imaging method, the minimum variance spatial smoothing (MVSS) beamforming imaging method, for near-surface seismic detection to achieve rapid and accurate imaging. To increase the robustness of the algorithm, the DL method was employed to add spatial white noise to the recorded wavefield and to adjust the weight calculation in the proposed method. The CF method was used to improve the image quality by amplifying the amplitudes of points with a strong focusing effect and depressing those with a weak focusing effect. We observed that reducing the delay time by one-half of a wavelet cycle provided the best image focusing effect when the wavelet length was not short enough for the imaging area in a near-surface situation. The method was tested on multiple synthetic near-surface geological models and compared with DAS beamforming, Kirchhoff migration, and reverse time migration. The results indicate that the MVSS beamforming method has a high computational efficiency while maintaining a high imaging quality, a high imaging resolution and a high contrast. The MVSS beamforming method provides the superior suppression of artifacts caused by surface waves as well  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Kirchhoff Migration** & **DAS Beamforming** & **MVSS Beamforming** \\ \hline Calculation Time (s) & 520.1 & 3.9 & 201.1 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Calculation time of each method.  
Figure 27: Results when the CF matrix was applied into Kirchhoff migration and DAS beamforming. Kirchhoff migration (**a**) without and (**b**) with CF matrix applied. DAS beamforming (**c**) without and (**d**) with CF matrix applied.  
as other imaging artifacts or interferences caused by S-waves, surface waves, and white noise. Meanwhile, we suggest that future works should focus on adapting inhomogeneous velocity models into beamforming imaging.  
Conceptualization, C.L.; Formal analysis, D.W.; Funding acquisition, Z.S.; Methodology, D.W.; Project administration, M.P. and Z.S.; Resources, M.P., L.L., C.L., Z.S. and F.M.; Software, L.L. and J.S.; Writing--original draft, D.W.; Writing--review and editing, M.P., D.W. and L.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant numbers 42172296, 42071010 and 42061160480, and the Shanghai Natural Science Foundation, grant number 20 ZR1461300.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.