esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Conclusions and Future Issues  
As a means of sending information about the safety of victims (safety confirmation information) in a disaster, this paper has proposed delay/disruption tolerant networks (DTN) that uses a receiver-triggered handshake method, and has presented the detailed protocol of this method. The primary objective of this method is to reduce batter consumption of the mobile terminals of victims. The proposed protocol was implemented on a network simulator, and simulations were conducted for a disaster area that was modeled on an area around Shinjuku Station in Tokyo. Victims were randomly distributed in the area. The proposed method has been compared with _Epidemic Routing_ and _Spray and Wait_, which are representative routing methods for DTN. The simulation results showed that the probability at which safety confirmation information reaches a shelter is, more or less, the same for all the three methods, but that the proposed method is superior to the other existing methods in terms of battery consumption of victim terminals, storage usage of carrier terminals, and the number of bundles generated in the network. However, the proposed method takes a longer time for safety confirmation information to reach a shelter (delivery time) than the other methods.  
As the future issues, to determine the application area of the proposed protocol more precisely, it will be necessary to conduct simulation under more varied conditions. For example, a safety confirmation message can be larger if we consider the inclusion of images and videos in it. It is also necessary to  
Figure 15: Battery consumption rate of victim terminals and delivery time.  
consider a larger storage capacity for an information carrier terminal. Also, the proposed protocol has room for improvement in delivery time. We will study potential means of shortening delivery time, such as adjusting the number of copies made by victim terminals and revising the method of determining which of the two carrier terminals that begin to communicate with each other should receive safety confirmation information. Furthermore, in a major disaster, the number of information carriers will be far smaller than that of victims, making it difficult to collect safety confirmation information rapidly. A solution can be to enlist those victims who can walk to shelters as information carriers. To evaluate this solution, it will be necessary to add the relevant functions to the proposed system.
# Optimization of Effective Throughput in NOMA-Based Cognitive UAV Short-Packet Communication
## 3 Solutions of the Formulated Problems  
In this section, the problem of maximizing the effective throughput of the far secondary users is investigated. Firstly, the formulated problem is divided into three subproblems, which are solved by a successive optimization algorithm. Then, a joint optimization algorithm is proposed to obtain the optimal system parameters.
# State-of-the-Art DC-DC Converters for Satellite Applications: A Comprehensive Review
## 2 Electrical Subsystems in Satellites
### Electrical Propulsion Systems  
EP systems for satellite applications convert electrical potential energy to kinetic energy to accelerate a propellant. The transition can generally be done electrostatically, electrothermally, or electromagnetically based on the method used to accelerate the propellant [58; 59; 60; 25]. In contrast to chemical propulsion, EP relies on energy sources such as solar arrays, batteries, a Radioisotope Thermoelectric Generator (RTG), or a nuclear reactor and accounts for only about 10-50% of the overall mass of a satellite [61; 62]. The most popular and mature technology is solar EP. However, the scope of solar EP is limited by the available solar radiation in space, which decreases quadratically with the distance from the sun [63]. Nuclear EP uses energy from a fission reaction to ionize the propellant to generate the required thrust. It can provide higher power than solar EP and is especially beneficial for missions further from the sun, where the ability to harness solar power becomes impractical [64]. Nevertheless, several barriers need to be crossed before its actual implementation. A schematic showing various aspects of electric propulsion, such as the types of electrical thrusters along with their power levels, the scope of solar EP and nuclear EP, and a few past, present, and future solar EP missions along with their power levels, is shown in Figure 6[65].  
A PPU is the core component of the EP system, which offers power conditioning and control for the thrusters for the EP system. The PPU uses DC-DC converters to convert the low-voltage, high-current satellite power into high-voltage, low-current power required by the thruster while providing isolation. The voltage level requirement varies based on the thruster. For instance, while ion thrusters require high voltages in the range of kilovolts, electrothermal thrusters require moderate voltages only. Thus, the PPU must be designed to meet each thruster type's unique electrical and operational demands. Moreover, considering the limited power resources in space, the efficiency and reliability of PPUs are crucial. Thus, efficient power electronic designs are required to ensure that maximum energy is converted into proper thrust. Reliability is achieved through modular and robust designs using specially designed space-grade components [66].
# Understanding Balance Control in the Context of Riding a Personal Mobility Device
## 4 Discussion
### Performance and Pattern of the Targeted Weight Shifting
#### 4.1.3 Interaction Effects of Target Distance and Direction on the Weight-Shifting Performance  
Apart from the individual effects of distance and direction, there were interaction effects on the time and fluency of the COP movements. The MT\({}_{\text{PMS}}\) showed significant differences between the target distances in each target direction but there were patterns of non-significant differences between the values in the distances. The different patterns were classified into three groups: (1) N direction, (2) E and NE directions, and (3) W and NW directions. These different patterns by direction may be a result of the subject's footedness as most of their preferred foot was the right foot. As the preferred foot is commonly used to manipulate an object or mobilize an action while the non-preferred foot is used to support the action for postural stability [44, 45], the MT\({}_{\text{PMS}}\) can vary depending on which foot is used to mobilize or stabilize the whole-body movement. The foot on the side of the target location performs the stabilizing role of the movement while the opposite foot mobilizes the movement. When the target was located on the left side of a subject, the right foot, which was the mobilizing foot, was effective in moving the whole body quickly without a significant increase in the time, although the target distance increased from distance 2 to distance 3. However, when the target was located on the right side, the MT\({}_{\text{PMS}}\) significantly increased when the target distance increased as the former.  
In terms of fluency, the interaction effects revealed that the COP movement strategy can be varied by the target direction but there are also different ranges applied according to the direction. When comparing the d\({}_{\text{NMP}}\) of the target directions in each target distance, the differences between the values in the directions increased as the target distance increased. The lateral and diagonal COP movements did not show a significant difference in terms of the d\({}_{\text{NMP}}\) when the target was located at distance 1, but they did when the target was located farther at distance 3. With respect to the MD, there was also a similar pattern in that a significant difference between the lateral movement and the anterior movement was not found within target distance 2, but it was found at target distance 3. These results imply that the difference in the COP movement fluency between the target directions becomes greater when the target distance increases. It may imply the boundary that the weight-shifting performance is affected and may also be considered in the perspective of the functional stability region [27].
# A MAC Protocol to Support Monitoring of Underwater Spaces +
## 3 Description of the UWSO-TDMA Protocol
### Initialization Phase
#### 3.2.2 Slot Allocation
In this way, A and B should use different slots to prevent the collision in Node C.  
Figure 3: Slot allocation: Situation I. After several iterations, the allocation should converge to a stable solution, as there are more available slots than nodes to use them. The number of free slots in the sub-frame helps with the initialization process, but it introduces more latency in the network for data transmission. A sub-frame synchronized by node \(s_{i}\in S\) is notated \(SF_{ii}=\{t_{1},t_{2},\ldots,t_{sf_{ij}}\}\), where subindex \(j\) indicates the hop number and \(i\) the synchronizing node, and \(sf_{ji}\) indicates the amount of slots within the sub-frame. Figure 5 presents the algorithm for the slot selection process. At this point, we can assure that the exposed station problem is not present in this configuration, because nodes within the transmission range of each other are allocated to different slots. For the network shown in Figure 6, in [21], the authors show the way in which their template allocates the nodes to slots in a global optimum way. Figure 7 shows the assignment. As can be seen, with only four slots, all nodes are able to send their messages to the sink. With our distributed method, the SO-UWSN allocates the slots according to Figure 8. It requires some more slots, incrementing the  
Figure 4: Slot allocation: Situation II. Figure 5: Algorithm for slot allocation. latency. However, the method is distributed, and no previous knowledge of the nodes' deployment is necessary. As the protocol proposes also a periodic re-initialization of the network, dead nodes can be removed from the graph and eventually new ones incorporated.
## 4 Matrix Converters in the Connection of Renewable Energies to the Grid
### Matrix Converter Applications for Integration of Photovoltaic (PV) Systems
#### 4.1.4 Experimental Indirect Matrix Converter (IMC) Application Results  
The SG integration of PV arrays using an IMC has been tested in the laboratory using the fast-prototyping software and hardware dSPACE 1103, with a specific attention to the switching vector transitions to avoid negative voltages on the 'DC link'. The grid line-to-ground voltage rms value is 110 V and the sample time 18 \(\upmu\)s.  
Results are shown in Figure 13a for the shunt compensation of a 250 W non-linear load low-order harmonics. The load currents present high 5 th and 7 th harmonics (THD of 33%) that are compensated for by the shunt converter to reduce the SG currents THD to 10.83% with Displacement Power Factor (DPF) of 0.997. In Figure 13b the series compensation is tested with a 15% sag. The voltage at the PCC \(v_{a}^{\prime}\) maintains a constant rms value during the sag in order to supply the sensitive loads and it is in phase with the grid voltages.
## 3 Results
### Muscle Activity (EMG)
#### 3.1.3 Interaction Effects between Working Height and Passive Exoskeleton on EMG
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Muscle**} & \multicolumn{4}{c}{**Working Height [Unit: \%MVC]**} & \multirow{2}{*}{\(p\)**-Value**} \\ \cline{2-2} \cline{4-4}  & **60 cm** & **85 cm** & **110 cm** & \\ \hline Upper trapezius (UT) & 11.8 (1.9) \({}^{\text{A}}\) & 6.7 (1.1) \({}^{\text{B}}\) & 10.1 (1.4) \({}^{\text{AB}}\) & 0.009 \({}^{*}\) \\ \hline Middle deltoid (MD) & 3.0 (0.3) & 3.3 (0.3) & 3.3 (0.4) & 0.710 \\ \hline Triceps brachii (TB) & 3.9 (1.2) & 4.4 (1.0) & 4.3 (0.8) & 0.930 \\ \hline Biceps brachii (BB) & 7.4 (0.9) \({}^{\text{B}}\) & 11.5 (1.2) \({}^{\text{A}}\) & 10.6 (1.2) \({}^{\text{AB}}\) & 0.016 \({}^{*}\) \\ \hline Erector spinae (ES) & 11.6 (1.2) & 14.0 (1.3) & 12.9 (0.8) & 0.212 \\ \hline Rectus femoris (RF) & 6.1 (1.4) & 4.3 (1.2) & 4.6 (1.0) & 0.390 \\ \hline Biceps femoris (BF) & 5.6 (0.7) \({}^{\text{B}}\) & 12.3 (2.0) \({}^{\text{A}}\) & 5.8 (1.0) \({}^{\text{B}}\) & \textless{0.001 \({}^{*}\)} \\ \hline Tibialis anterior (TA) & 7.8 (1.6) \({}^{\text{A}}\) & 3.2 (0.6) \({}^{\text{B}}\) & 2.4 (0.5) \({}^{\text{B}}\) & \textless{0.001 \({}^{*}\)} \\ \hline \hline \end{tabular} Asterisks indicate the statistical significance of the main effect (i.e., intervention) evaluated in generalized linear mixed models (\(p<0.05\)). Different letters indicate significant statistical differences among the three intervention conditions obtained from post-hoc follow up tests (\(p<0.05\), [PERSON]’s test).  
\end{table} 
Table 2: Mean (standard error) values of muscle activity according to working height. Figure 3: Interaction effect between working height and exoskeleton on upper-limb muscles. Different letters indicate significant statistical differences (\(p<0.05\), [PERSON]’s test).
# Numerical Study on Tree Belt Impact on Wind Shear on Agricultural Land
## 2 Methods  
### Experimental Setup  
A 60 m meteorological mast with specialized instrumentation was used to evaluate the wind speed profile change with height. This mast was equipped with 3 calibrated anemometers that continuously measured the wind velocity and 2 wind vanes for wind direction. In addition, temperature and barometric pressure sensors were installed. They were fixed to heights of 40 m, 50 m, and 60 m, respectively [80] (Figure 1a). Ten-minute readings for the wind parameters were collected for more than one year, as the data were checked for consistency. To meet the wind potential measurement criteria, calibrated equipment was used [81]. The location of a measurement mast located immediately downstream southwards from belt 3 is presented in Figure 1b. A summary of the technical specifications of the measuring equipment used during the experiment is presented in Table 1.  
Figure 1: (**a**) Mast and sensor diagram, (**b**) satellite image of the surveyed area with location, distance, and elevation of the three belts, and (**c**) field photo of belt 3.  
Based on the processed field data, the wind shear was reconstructed by fitting it to known mathematical relationships for the atmospheric wind profile. The mast was located downstream of a belt (Figure 1c), which can possibly disturb the profile near the ground. Since this disturbance is likely to be smaller at higher heights (as was confirmed by the results of the study), it was accepted that the measurement data from the mast, sampled at heights of 40-60 m, would not be affected significantly, so these data could be used to construct the atmospheric boundary layer profile. However, to acknowledge the fact that this profile will be disturbed near the ground if it is close behind a belt, the boundary condition was moved sufficiently downstream of the mast and a classical atmospheric boundary layer profile was assigned to it. The domain inlet was thus positioned around 1100 m downstream of the third belt and 176 m upstream of the fourth belt.  
Studying the airflow above such a large area is a challenging task and can only be effectively accomplished numerically. Increasing numbers of field and model studies of the velocity and turbulence characteristics of the flow above land areas were performed recently [17]. In particular, the number of numerical studies has increased, among which RANS and Large-Eddy Simulations (LES) are the most popular choices. The present study was motivated by the need to define the value of the drag coefficient, respectively the momentum sink, within the tree belt region, as well as the value of turbulent viscosity, which largely determines the shape of the velocity profiles with height.
## 4 Case Study
### Synthesis of Expected Solutions  
The search for task rotation schedules boils down to the answer to the following question (see the synthesis problem formulation): Is there a task rotation schedule that guarantees both the \(EP\) project portfolio and the execution of additional \(EX\) orders while maintaining the required degree level of competence structure \(SG^{*}\geq 35\)?  
As in the previous case, the problem under consideration was formulated as \(CS\) (12) and solved in the IBM ILOG environment. An example of an acceptable solution is shown in Figure 9. The considered EP project portfolio is executed on time, as well as the additionally accepted \(EX\) order within \(HE_{3}=17\) while maintaining the expected level of competence structure: \(SG^{17}=36\). The result obtained is a consequence of the task rotation used. For example, already at the first moment (\(t=5\)) of the project implementation, the assignment \(X^{5}\) changed in relation to the assignment from Figure 8--the employee was \(P_{3}\) assigned to the new task \(Z_{3}\) (previously \(Z_{2}\)). This type of rotation (carried out cyclically) allows for maintaining the required level of competence structure.  
Figure 8: Solution to the analysis problem in which the portfolio \(EP\) was executed according to the sequence of assignments \(X^{1}\), \(X^{2}\),..., \(X^{17}\) without task rotation but, however, with an additional \(EX\) order.
# A Filter Pruning Method of CNN Models Based on Feature Maps Clustering
## 4 Filter Pruning Based on Feature Maps Clustering  
The filter is essentially a matrix of size \(\mathrm{M}\times\mathrm{N}\). It is used to detect specific features in images. Different filters have different parameters. When the image is processed in the computer, it is in the form of \(\mathrm{M}\times\mathrm{N}\times 3\) size. Suppose we only consider the grayscale of the image regardless of RGB, then the size of the image is \(\mathrm{M}\times\mathrm{N}\). The filter processes the image by sliding through all the regions of the image from left to right, from top to bottom, and then dot-multiplying with all the same size areas in the image. After the sum of the products, a new filtered image, i.e., the feature map, is obtained.  
When the filter processes the image, it dot-multiplies with each equal area in the image. If a certain area of the image is similar to the feature detected by the filter, the filter will be activated and get a high dot multiplication result when passing through the area. Conversely, if an area of the image is very dissimilar to the features detected by the filter, the filter will not be activated or the value obtained by dot multiplication will be very small.  
It can be concluded that when the filter slides through the whole image, the higher the value obtained from an area of the image, the higher the correlation between the area and the undetermined features detected by the filter. The neural network can obtain sufficient features of the image through a large number of filters so that it can detect and locate the image.  
The feature map is extracted by the filter and passed as input to the next convolutional layer. [PERSON] et al. [5] used a de-convolution method to project the activated feature matrix back into the input pixel space and found that filters in different layers can extract featuresof different levels. [PERSON] et al. [29] demonstrated that different filters in the same layer can also extract features from different aspects. Therefore, the feature map can represent filters in some respects [30]. Inspired by these, the work hypothesizes that the redundant filters in convolutional neural networks may extract similar feature maps to that from other filters in the same layer when processing the same input.  
Based on this assumption, we can determine how many similar feature maps are extracted by each convolutional layer using the clustering method, and then we can determine how many necessary features of the input image need to be extracted. Finally, we can select the filters to be pruned. The image clustering method used in this paper will be introduced below.
# Nano-Interaction Mechanism Between Crumb Rubber and Asphal Components: A Molecular Dynamic Study
## 3 Results and Discussion
### Effect on Density
#### 3.1.2 CR Effect on Asphalt Density  
The time course curves of density change at 298 K for base asphalt, CRMA with 10%, 20%, and 30% dosage are shown in Figure 12.  
The time curve showed that the density was stable at 200 ps when the configurations of the components were stable. After that, the density showed a slight stable increase, indicating that the internal structure of the components was still optimized and reconstructed. At 700 ps, the density time curve shows a stable trend. The average value of the latter stabilization stage (after 100 ps) was taken as the representative value. The analysis is as follows:  
The simulation showed that, with the increase in CR dosage, the density of CRMA showed a trend of increasing and then decreasing. However, the decrease is slight. The order of density compared to base asphalt is 10% CRMA (0.974 g/cm\({}^{3}\)) > base asphalt (0.972 g/cm\({}^{3}\)) > 20% CRMA (0.971 g/cm\({}^{3}\)) > 30% CRMA (0.969 g/cm\({}^{3}\)). The density reduction of 30% CRMA asphalt was 0.003 g/cm\({}^{3}\) compared to the base asphalt. The reduction was 0.3%. Under a small dosage (10%), the asphalt density increased, indicating that CR could realize the effective filling of asphalt. When the dosage continued to increase, the \"solubility\" of asphalt to CR was limited and saturated. Due to the CR (this paper used SBR) density being smaller than the base asphalt, the excess of CR mixed reduced the density of the asphalt system.  
The above pattern of change in the density of CRMA and base asphalt and the actual situation in the laboratory have some differences. Generally, CRMA has a bigger density than base asphalt [18], mainly because the MD analysis did not consider the CR in the asphalt for a long time in the swelling and dissolution reaction. Therefore, if we need to use molecular dynamics to simulate the density of CRMA accurately, we should consider the influence of CR and asphalt swelling and dissolution reactions in future studies [37].  
Figure 11: Density time course curve of asphalt’s four components.  
Figure 12: Comparison of density time course curves of CRMA and base asphalt.