esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Works  
### The Work of Predecessors  
In this field, many experts and scholars have carried out research for many years. [PERSON], from the Software Institute of the Chinese Academy of Sciences, proposed an on-demand partial topology routing algorithm in LEO satellite networks. The algorithm guarantees the minimum delay and better convergence time of the constructed route, so it is very suitable for those services requiring a higher delay in low orbit satellite networks. However, it is still a flooding algorithm in essence, and the cost of routing detection is still very large. The algorithm only needs to send data to the routing detection, and each node does not need the global topological information, so as to avoid a lot of link-state information exchange, minimize the overhead due to routing protocols, and smaller local topology protocol convergence time is the biggest advantage of this routing algorithm [9]. In 2001, [PERSON] designed a distributed routing algorithm to realize the minimum delay. [PERSON]'s algorithm is based on terrain factors and believes that a continuous local optimization strategy can make the final path tend to be globally optimal [10]. The datagram routing algorithm introduced by [PERSON] is applicable to polar satellite constellations. Satellite nodes are regarded as a network structure composed of virtual nodes, and data packets are transmitted in a distributed way in a fixed topology structure [11].  
[PERSON]'s algorithm can be regarded as a variant of the flooding algorithm, while [PERSON] and [PERSON]'s algorithms are improvements to the greedy algorithm. These algorithms also have the inherent defects of the flooding algorithm and greedy algorithm. Moreover, the above routing algorithm mainly relies on a one-star node to complete the calculation of each planned route. In the actual inter-satellite system, each star is often not a uniformly distributed workload. This will cause some nodes to bear a lot of computational pressure and consume a lot of energy. The principle of maximum redundancy would require each star to be fitted with a payload with more computing power and a larger capacity of solar panels, which would greatly increase the cost of satellite hardware. This is where we would like to further improve the existing inter-satellite routing algorithm. Therefore, we propose a balanced routing algorithm based on the partition routing idea in the original partition routing algorithm.
## 3 The Model Validation
### Load Sharing Ratio Contrast
#### 4.1.2 The Influence of Helical Angle on the Load Sharing Ratio  
As the helical angle is relatively small, the maximum value of the load sharing ratio equals one (as shown in Figure 15a). This indicates that there exists a situation where a single tooth bears the load alone. As the helical angle increases, the maximum value of the load sharing ratio decreases. Because two or more teeth will enter the engagement region simultaneously, the maximum value of the load sharing ratio will decrease, as shown in Figure 15b.
# Signal Preprocessing for Enhanced IoT Device Identification Using Support Vector Machine
## 1 Introduction
Section 4 provides a comprehensive analysis of the results, emphasizing the strengths and limitations of each signal preprocessing option. It explains the causes of misclassifications and evaluates the trade-off between improving accuracy and preserving computational efficiency, comparing the findings with other state-of-the-art works. Furthermore, this section highlights potential areas for improvement, such as increasing the model's robustness to noise and its ability to generalize effectively across different datasets. Finally, Section 5 summarizes the key findings, emphasizing the importance of RF signal preprocessing in improving the effectiveness of the RFF-based device identification. It discusses the broader implications for IoT security and suggests future research directions, including advanced feature extraction, real-world validation, and the exploration of alternative machine learning models to further improve classification performance.
## 3 Results and Discussion
### Characterization of BC-Curcumin Membrane  
#### 3.2.1 Surface and Surface and Cross-Sectional Morphologies  
Figure 1a illustrates the surface morphology of the air-dried BC film, revealing a well-organized network structure of microfibrils with diameters in the range of 0.05-0.1 \(\upmu\)m. The spaces between fibrils indicate a pore size of less than 0.1 \(\upmu\)m. The formation of H-bonds between the cellulose chains occurs during air drying and the resulting densely packed matrix was especially apparent when the films were observed in cross section [33] (Figure 2). Due to the hydrophilic nature of BC, the pore diameter of the BC film increased to 0.2-1.0 \(\upmu\)m after rehydration (Figure 1b). Water penetration caused relaxation of the polymer chain, which resulted in a loosening of the packed structure of the BC matrix. These results indicate that BC could be suitable for use as a releasing matrix of drugs or active components. After absorption of curcumin into BC at concentrations of 0, 0.2%, 0.4%, 0.6%, 0.8% and 1% (\(w/v\)), uniform distribution of curcumin aggregates was obvious on the surface of binary composites of BCC films. The formation of aggregates was not apparent between the fibril layers; except at the maximum curcumin concentration (BCC1.0), when some aggregates were seen between layered fibrils. Previously, we have reported similar observations from the preparation of films containing ethanolic extract of mangosteen peel [12].  
Figure 1: SEM images of surface morphology of a dried BC film (**a**), a rehydrated BC film (**b**), and dried films of BCC0.2 (**c**), BCC0.4 (**d**), BCC0.6 (**e**), BCC0.8 (**f**), and BCC1.0 (**g**) at the magnification of 10,000\(\times\).
# Efficient Communication Model for a Smart Parking System with Multiple Data Consumers
## 6 Results Discussion  
When comparing the performances of the five different communication models, it is evident that the Mid1 and Mid4 models are showing good packet delivery ratio along with low overhead. Although the MidAgg model exhibits a low packet latency along with the lowest power consumption, the time taken for the occupancy data to reach the data collator is six times over the time taken for the Mid4 model or five times over the time taken for the Mid1 model. It requires a specific scheduling algorithm for packet transmission that can reduce the delay introduced by data aggregation at each hop. The Top1 model apparently demonstrates a lower data reliability and a high packet latency as the data packets need to traverse a higher number of hops than the other models. Between these Mid1 and Mid4 models, the Mid1's packet delivery ratio has an edge over Mid4. However, latency wise, the Mid4 model holds an edge. To understand the advantage of these two models, the experiments are repeated in a larger 15 \(\times\) 15 grid network.
# Realisation of a Novel Functionally Redundant Actuation System for a Railway Track-Switch
## 3 Development of Simulation Models
### The Actuator Models in Simulink
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Description** & **Value** & **Units** \\ \hline \(B_{c}\) & Cam frictional damping coefficient & 0.004 & Nm/(rad/s) \\ \(B_{g}\) & Gearhead frictional damping coefficient & \(1.91\times 10^{-5}\) & Nm/(rad/s) \\ \(B_{M}\) & Motor frictional damping coefficient & \(4.01\times 10^{-4}\) & Nm/(rad/s) \\ \(F_{vA}\) & Vertical force acting on the cam connected to switch & & N \\  & rail A & & N \\ \(F_{hA}\) & Horizontal force acting on the cam connected to & & A \\  & switch rail A & & N \\ \(i_{a}\) & Motor current & & A \\ \(J_{c}\) & Cam inertia & 0.003 & kgm\({}^{2}\) \\ \(J_{g}\) & Gearhead inertia & 2.16 & kgm\({}^{2}\) \\ \(J_{M}\) & Motor inertia & 6.28 & kgm\({}^{2}\) \\ \(K_{ght}\) & Rotational stiffness of the gearhead & 41250 & Nm/rad \\ \(K_{v}\) & Back emf constant of the motor & 0.441 & V/(rad/s) \\ \(K_{T}\) & Torque constant of the motor & 0.72 & Nm/A \\ \(L_{a}\) & Armature inductance & 2.7 & mH \\ \(m_{h}\) & Mass of the rail carrier & 25 & kg \\ \(n_{g}\) & Gear ratio & 20 & \\ \(m_{rail}\) & Mass of the rail on the rail carrier & & kg \\ \(P_{M}\) & Output mechanical power & & kW \\ \(R_{a}\) & Armature resistance & 0.54 & \(\Omega\) \\ \(R_{c}\) & Radius of the cam & 0.065 & m \\ \(T_{cpa}\) & Torque on the cam connected to straight Rail A & & Nm \\ \(T_{g\varphi}\) & Gearhead output torque & & Nm \\ \(T_{M}\) & Motor electrical torque & & Nm \\ \(V_{m}\) & Motor voltage & & V \\ \(\theta_{go}\) & Angular position of gearhead output shaft & & rad \\ \(\theta_{cA}\) & Angular position of the cam connected to switch & & rad \\  & rail A & & rad \\ \(\theta_{M}\) & Motor angular position & & rad/s \\ \(\omega_{gi}\) & Gearhead input angular velocity & & rad/s \\ \(\omega_{go}\) & Gearhead output angular velocity & & rad/s \\ \(\omega_{M}\) & Motor angular velocity & & rad/s \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Mathematical symbols used in the switch model and their values. \[J_{C}\;\theta_{CA}^{-}+B_{C}\dot{\theta}_{CA}=\left\{ \begin{array}{cc}T_{cpA}-R_{C} \{F_{pA}\cos\theta_{CA}-F_{hA}\sin\theta_{CA}\},&if\;2^{\prime}\leq\theta_{CA} \leq 178^{\prime}\\ T_{cpA},&if\;\theta_{CA}\leq 2^{\prime}\;\;\text{and}\;\theta_{CA}\geq 178^{ \prime}\end{array} \right. \tag{5}\]  
\[T_{cpA}=K_{gh}\{\theta_{go}-\theta_{CA}\} \tag{6}\]  
The effect of the dead-zone or backlash at either end of the cam rotation is significant is included in the model (via Equation (5)). The mass of the rail carrier is shared equally between the two cams, cam-A and cam-B, so is included in the cam inertial term, \(J_{C}\). The vertical (\(F_{pA}\)) and horizontal (\(F_{hA}\)) forces in Equation (5) are passed to the Simulink model from the SimPack model.
## 4 Hybrid Trust-Based Congestion-Aware Cluster Routing (HTCCR)
### CH Selection Phase  
During CH selection, a cost function based on energy, distance, trust, and load level is employed. These values are considered as fitness values for computing the cost function and they are given as the input to the hybrid KHM and GSA. A node with an 'NDL' greater than 0.8 is considered to be an attacker. In such a case, the attacker will not be allowed to take part in the process of CH selection.  
\[\text{Overall fitness}=T_{\text{dist}}\times\delta+CI_{k^{\prime}}\times\varepsilon +WT\times\vartheta+\big{(}(\text{Trust}\times\gamma)+N_{\text{RE}}\times\tau \big{)} \tag{13}\]  
Figure 2: Overall flow of proposed work.  
where \(\delta\), \(\varepsilon\), \(\psi\), \(\gamma\), \(\theta\), and \(\tau\) are the adjustment parameters that lie between 0 to 1.  
The overall fitness of the energy level recommends that nodes with increased distances include a higher value of overall fitness. In this scenario, those nodes with a higher value of 'overall fitness' have the lowest possibility of becoming CHs. Conversely, the nodes that have a large number of neighbors and the nodes with increased energy will have a lower value of 'overall fitness.' The nodes with a lower value of 'overall fitness' will have a greater possibility of becoming CHs. Further, they aggregate the data to reduce redundancy. The aggregation of data conserves energy within the network since unnecessary data are not transmitted to the BS (sink). Once data are collected and a CH is chosen, every node with a specific energy level sets its 'overall fitness' to a particular value. A node with a lower 'overall fitness' value involves less energy consumption and has the possibility of becoming a CH. The chosen CH forwards data packets to other nodes within its radius.
## 3 Results  
### UV-Visible Spectroscopy: Anthocyanin Content and AgNP Surface Plasmon Resonance  
The anthocyanin content in freeze-dried Peruvian purple potatoes was quantified using the differential pH method, employing UV-Visible spectroscopy in buffer solutions at pH 1 and pH 4.5 (Figure 1a). The analysis revealed an anthocyanin concentration of 153.03 mg/100 g, which is significantly higher than the 75.71 mg/100 g reported in a previous study where fresh potatoes were used under the same extraction conditions [17]. This substantial difference highlights the effectiveness of freeze-drying in preserving anthocyanins, in contrast to the grating process, which causes greater degradation due to enzymatic oxidation and exposure to environmental factors.  
Freeze-drying is a more effective method for preserving bioactive compounds such as anthocyanins, as it minimizes degradation by reducing exposure to heat and oxygen, both of which contribute to the breakdown of these sensitive compounds [21]. Additionally, the freeze-drying process removes water at low temperatures, helping to maintain the integrity and concentration of anthocyanins in Peruvian purple potatoes. Consequently, freeze-drying not only preserves these compounds more effectively but also enhances their concentration.  
Figure 1b displays the UV-visible spectrum of the biosynthesized silver nanoparticles, featuring the characteristic surface-plasmon-resonance (SPR) absorption maximum at 403 nm. This band corresponds to AgNPs with an average diameter of approximately 21.6 nm, as detailed in our previous work ([PERSON] et al., 2024) [22].
## Appendix A Impact of Different Battery Levels of Relays on Throughput in Low Node Density Network  
This section presents additional analysis comparing average throughput of our proposed MRS-ST-BL and MRS-SD-BL schemes with various relay selection schemes, when network width is 1000 m. We analyzed average throughput of each schemes, where search radius ranges from 5 m upto 700 m. The simulation data are recorded at an interval of 25 m.  
Figure 11-14 show the throughput comparison at different social trust scenarios for a low node density network.  
Figure 11 depicts a very weak social trust scenario (Shape = 1.001, Scale = 0.001) among users in a network with low node density. The change in throughput with the increase in radius  
node density. The trend of change in throughput of all the schemes analyzed are similar to those in Figure 14.  
Figure 15 depicts average throughput comparison of different schemes for a strong social trust scenario (Shape = 2, Scale = 0.5) among users in a network with low node density. The change in throughput with the increase in search radius for all the schemes analyzed are not different to those in Figure 6.  
In summary, our proposed schemes MRS-ST-BL and MRS-SD-BL provide higher throughput compared to existing art-of-the-state schemes in a low node density network having devices with varying battery levels.
## 3 Experiments and Results
### Experimental Results
#### 3.3.1 Ablation Experiments  
To explore the impact of each proposed component, we performed an ablation study by incrementally adding modules to a baseline network. The configurations include combinations of CADCN, LKF, CATM, and their fusions. We compared model parameters, FLOPs, and IoU, as shown in Table 2.  
The baseline model (MobileNetV2) achieved an IoU of 86.19%, with a computational cost of 136.06 GFLOPs and 6.644 M parameters. After integrating the LKF module, the IoU increased significantly to 88.86%, while the computation only slightly rose to 136.088 GFLOPs, indicating that the LKF module is both lightweight and effective in stabilizing feature representations. To reduce computational cost, we replaced the deep encoder with a shallow CADCN, resulting in a lightweight model with 0.10 M parameters and 72.91 GFLOPs. However, the IoU dropped to 81.62%, suggesting a loss of feature representation capacity under aggressive compression. To address this, we introduced the CATM module in the decoder. This addition slightly increased the parameter count to 0.22 M, reduced the computational load to 71.38 GFLOPs, and improved the IoU to 82.55%. These results demonstrate that the CATM module effectively compensates for the performance degradation caused by model compression.
# LoRaWAN Communication Protocols: A Comprehensive Survey under an Energy Efficiency Perspective
## 3 Communication Protocols
### Routing Protocols
#### 3.3.2 Non-Clustering Approaches (NCA)
Otherwise, if the timeout of the window expires, the node goes into sleep mode to save energy and schedules a wake- up. The drawback of this approach is that it does not support downlink transmissions. Flooding Topology: In [76], the authors uses the concurrent transmissions (CT) protocol to LoRaWAN nodes. CT is a flooding approach in which only one node is the source of data and all other nodes that receive a packet must retransmit it. In order to avoid collisions, the protocol accommodates synchronized packet collisions resulting from on-the-fly retransmissions by multiple relays. Due to the absence of a CA mechanism, the packets move very quickly through the network through the RNs. The TDMA protocol is used by the GW to synchronize the nodes by assigning each a dedicated timing slot to enable it to transmit data. Nodes can act as an initiator or transmitter at specific timing slots, while at other times they act as relays. For proving the flooding technique, instead of immediate re-transmission, the authors used a small timing offset during the re-transmission time, and the results have demonstrated improved receiving performances. Finally, the authors deployed nodes in different buildings to perform field tests as well as simulations. In [77], the authors presented an IoT protocol for LoRaWAN transceivers named LoRaBlink. This protocol supports communication over multiple hops, to minimize energy consumption, to achieve low-latency communication and to enable high message delivery probability. The protocol uses a single sink and synchronization time using beacons among nodes to define slotted channel access. A beacon message contains the hop distance to the sink and upon receiving a beacon, a node will transmit its own beacon according to its distance to the sink. The GW, which is connected to the network server, initiates the network operation by sending a beacon. Then, the nodes nearest to the GW receive the beacon and transmit concurrently their beacons. The next nodes perform the exact same process and increment the hop count by one. Note that, when a node receives a beacon, it checks if its hop count to the GW is less than the hop count included in the beacon message. Only nodes with a lower hop count relay the message and send an ACK to the source node. Otherwise, the message is discarded. Finally, when the GW receives the message after several hops, it replies with an ACK. Messages from the sink to the nodes are distributed using flooding and on the other hand, messages from nodes to the sink use a directed flooding approach. However, this approach in not efficient in large-scale networks due to collisions that may occur.
## 7 Conclusions and Future Outlook  
In conclusion, relative to the investigation on the analyzed compositions, it can be deduced that:  
1. From the compression tests and foam property measurements, sample 2, containing SiC = 2.8%, TiH\({}_{2}\) = 0.4% and Al = 96.8%, has the highest energy absorption.
2. Sample 4, containing SiC = 6%, TiH\({}_{2}\) = 0.2% and Al = 93.8%, exhibited good morphological properties overall.
3. Higher TiH\({}_{2}\) content involves greater areas of the pores and consequently average diameter, but, at the same time, a greater dispersion of the porosity has been evidenced.
4. Higher SiC content involves an effect of stabilization on the porosity and consequently on the circularity and the equivalent diameter.
5. Specific energy absorption is strictly correlated to the morphology of the stress-strain curve and the contribution of both. The combination of higher stress and lower strain as well lower stress and higher strain is the reason for the smaller specific absorbed energy while average values of stress and strain allow the highest specific absorbed energy to be obtained.
6. In general, the combined use of mechanical characterization and image analysis can aid in the development of a new kind of closed cell aluminum foam materials with tailored microstructures to meet specific application requirements. Image analysis also enables researchers to study the behavior of closed cell aluminum foams under different loading conditions, such as compression and impact, which can provide valuable insights for designing safer and more durable products or materials with customized deformation properties and energy absorption.
7. Low weight and energy absorption capability but also thermal properties in heat dissipation can be exploited in further possible applications.  
In the future, further developments may regard a systematic investigation with a greater amount of blowing agent and stabilizing agent, different base metals, and alloys in order to extend relevant results to other materials and the morphology of porosity.  
**Author Contributions:** Conceptualization, G.C. and M.E.T.; methodology, M.B., G.C. and M.E.T.; software, M.B.; formal analysis, M.B.; investigation, M.B., G.C. and M.E.T.; resources, M.B., G.C. and M.E.T.; data curation, M.B., G.C. and M.E.T.; writing--original draft preparation, M.B.; writing--review and editing, M.B., G.C. and M.E.T.; visualization, M.B., G.C. and M.E.T.; supervision, M.B., G.C. and M.E.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
No new data were created.  
Authors are grateful to [PERSON] and [PERSON] for the technical support in the experimental tests.  
The authors declare no conflict of interest.