esa-sceva/satcom-chunk-collection huggingface dataset:
# Cross-Domain Fusion Constellation Design of Communication, Navigation and Remote Sensing
## 5 Conclusions  
This paper proposes a CDFC design and optimization method for communication, navigation and remote sensing integration based on MDCRO. The CDFC designed by this method can reduce the number of satellites by 23.06% compared with the independent constellations and combined constellations in each domain, the highest can even be about 70%, and improve the coverage and GDOP of the constellation. Compared with the combined constellation, the system cost can be reduced by 18.31%. In this paper, the concept of CDFC proposed by us is verified, which has a good application prospect in the construction of space-based systems and constellation design. In the future research, the paper will combine the distribution of population on the ground, deeply model the needs of users, and design and optimize the CDFC in more detail.  
J.Y. and J.Q.; Methodology, X.G.; Software, X.L.; Validation, J.Q. and X.M.; Formal Analysis, J.Q.; Writing, J.Q.; Supervision, J.Y. and X.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data available on request due to restrictions.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} CDFC & cross-domain fusion constellation \\ MDCRO & multidisciplinary collaborative reverse optimization \\ MDO & multidisciplinary design optimization \\ GDOP & geometric dilution of precision \\ CO & collaborative optimization \\ LEO & low earth orbit \\ \end{tabular}  
Figure 7: Constellation cost.
# Optimised Tuning of a PID-Based Flight Controller for a Medium-Scale Rotorcraft
## 2 System Overview and Mathematical Modelling
### System Performance Specifications  
The goal of the present paper is focused on the development and investigation of an efficient controller for the rotorcraft. Five different controllers are developed, analysed and compared--that is, one manually tuned PID controller and four other PID controllers tuned using optimisation algorithms, as detailed in the next subsection. The manually tuned PID controller is used for benchmarking purposes. A successful controller must meet the following performance specifications [4]:  
1. The controller must exhibit general stability;
2. Overshoot should be kept at less than 5%;
3. Settling time should be less than 10 s;
4. Steady-state error should be within \(\pm 1\times 10^{-2}\) rad and \(\pm 1\times 10^{-1}\) m. In order to develop the best PID controller, the following objective function based on the integral of squared error (ISE) is used:  
\[J =\frac{1}{T}\int_{0}^{T}\biggl{[}\left(\frac{x_{d}-x}{x_{max}} \right)^{2}+\left(\frac{y_{d}-y}{y_{max}}\right)^{2}+\left(\frac{z_{d}-z}{z_{ max}}\right)^{2} \tag{25}\] \[+\left(\frac{\theta_{d}-\theta}{\theta_{max}}\right)^{2}+\left( \frac{\phi_{d}-\phi}{\phi_{max}}\right)^{2}+\left(\frac{\psi_{d}-\psi}{\phi_{ max}}\right)^{2}\] \[+\left(\frac{\delta_{col}}{\delta_{col_{max}}}\right)^{2}+\left( \frac{\delta_{lon}}{\delta_{lonmax}}\right)^{2}+\left(\frac{\delta_{lat}}{ \delta_{lat_{max}}}\right)^{2}+\left(\frac{\delta_{ped}}{\delta_{pol_{max}}} \right)^{2}\biggr{]}dt,\]  
where \(x_{d}\), \(y_{d}\) and \(z_{d}\) are the desired positions of the rotorcraft with respect to the Earth-fixed reference frame, \(\theta_{d}\), \(\phi_{d}\) and \(\psi_{d}\) are the desired Euler angles of the rotorcraft, \(\delta_{col}\), \(\delta_{lon}\)\(\delta_{lat}\) and \(\delta_{ped}\) are the collective, longitudinal cyclic, lateral cyclic and tail rotor collective inputs, respectively.
## 5 Conclusions  
In this study, an alumina melt material surface measuring system was constructed that utilized a vision system for auto seeding in a single crystal sapphire ingot growth furnace using the Ky method. Furthermore, the island position of the melt material was detected using the developed image processing algorithm, and its performance was evaluated.  
To periodically acquire images of the alumina melt material surface during sapphire growth, an experimental system was constructed with a vision module unit that contained a CCD camera, a shutter module unit to protect the camera, a motion module unit for the seeding process, and the PC control unit for total system control. The images were stably acquired through this system.  
The stream lines and background regions on the alumina melt material surface were detected separately using an image-processing algorithm, and the island center coordinates were calculated using the intersections of the stream lines.  
When the observed coordinates of the island center were compared with the coordinates detected from the image processing algorithm, there was an average error rate of 1.87 mm (based on 1024 \(\times\) 768 pixels). The reason for this was that the accuracy level dropped for observed coordinates compared to algorithmically detected coordinates when some stream lines intersected in a vortex shape and when the detection of stream lines was limited due to the outline of rod and seed shapes in the visual field. However, since the maximum error was about 3 mm when converted to actual distance, this error did not cause a significant problem in judging the stable condition of the internal convection of the melt material during the actual growth furnace process.  
Considering the above results, the vision system and algorithm could be applied to the heater type growth method of axial symmetry in a circular cylindrical crucible using the Cz method as well as the Ky method. When applied to an actual system, these results can provide objective indicators for the seeding preparation process during sapphire growth. If the problems discovered in this study are addressed, such as the limited field of view and the error occurring in the curved parts of stream lines, automated techniques for the seeding process as well as the entire process of single crystal sapphire growth will be possible.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON], [PERSON] and [PERSON] analyzed the data; [PERSON] wrote the paper.  
The authors declare no conflict of interest.  
Figure 15: Distance from the center of the crucible in the growth furnace to the island center point.
## 7 Sizing Constraint
### Space Constraint  
Sometimes, customers give specific area to mount PV modules. In past years, several researchers included area as a constraint in their sizing. There are two types of area sizing for PV system, which are roof space's area constraint and land space area constraint. As referred in [108], optimization process for grid connected PV system on the rooftop of federal office building. In the study, array size and tilt angle are optimized, and the objectives for the model are to maximize array output energy as well as minimize electricity sold to grid.  
Meanwhile, in [2; 4], detailed sizing on top of roof was done based on PV module orientation. As shown in Figure 3, the roof space was used by choosing between two arrangements that can maximize panel's quantity on top of the roof, where \(L\) is roof length, \(W\) is roof width, \(l\) is panel length, and \(w\) is panel width.  
Moreover, authors in [2] also proposed to consider PV system layout as shown in Figure 4, to allow PV panel mounted at optimum tilt angle on flat roof. Calculation was done to minimize shading losses while area was exploited at the same time, where \(L\) is roof length, \(W\) is panel width, and \(\beta\) is module tilt angle.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Year** & **Authors** & **Technique** & **System Cost Analysis** & **Reference** \\ \hline
2005 & [PERSON], et al. & Numerical & Others & [108] \\
2006 & [PERSON], et al. & Evolutionary Programming & NPC & [109] \\
2009 & [PERSON], et al. & GA & NPC & [22] \\
2010 & [PERSON] & PSO & NPC & [111] \\
2010 & [PERSON] [PERSON], et al. & Multi-Objective & NPC & [112] \\
2011 & [PERSON] [PERSON], et al. & GA & & [25] \\
2011 & [PERSON], et al. & GA & LCOE & [110] \\
2012 & [PERSON], et al. & GA & LCOE & [112] \\
2012 & [PERSON], et al. & Evolutionary Programming & NPC & [4] \\
2013 & N\(\ddot{\text{a}}\)[PERSON] & Numerical & LCOE & [2] \\
2014 & [PERSON], et al. & GA & Others & [3] \\ \hline \hline \end{tabular}
\end{table}
Table 3: Summary of GCPV optimal sizing methods.  
Figure 3: PV system layout options based on roof space constraint in system sizing [2].  
Several past studies [3; 22; 109; 110; 111; 112] designed more complicated sizing in land space area, where PV modules tilt angle, maximum land space area, and shading effect was considered in order to find optimal arrangement of PV modules in the available installation area. The system layout is as shown in Figure 5 below, where \(D\) is space between collector rows, \(L_{c}\) is collector length, \(H\) is collector height, \(E_{max}\) is limit of collector's height from ground, W is land width, \(\beta\) is module tilt angle, \(K\) is rows number, \(L_{m}\) is module length, and \(H_{m}\) is module width. However, this technique has limitation, where the researchers can only use the calculation and layout for land in south direction only.
## 4 Discussion
### Ablation Studies
#### 4.1.2 Bidirectional Cross Fusion  
The BCF module significantly enhances spatiotemporal fusion by simultaneously addressing both the time and scale directions. To evaluate the effectiveness of this Bidirectional Cross Fusion module, two ablation experiments were conducted by removing the fusion modules for the temporal and scale directions. Specifically, the model without  
Figure 10: Fusion results and error maps for the subregions on 18 October 2015, generated by different models on the Wuhan dataset. (**a**) Ground truth. (**b**) STARFM. (**c**) FSDAF. (**d**) Fit-FC. (**e**) EDCSTFN. (**f**) GAN-STFM. (**g**) MLFF-GAN. (**h**) STF-Trans. (**i**) CTSTFM. (**j**) Proposed.  
temporal fusion was designated BCSR-STF-NT (No Time direction), and the model without scale fusion was designated BCSR-STF-NS (No Scale direction).  
For BCSR-STF-NT, we removed the cross-temporal feature fusion in the time direction and only performed spatiotemporal fusion in the scale direction, with other settings unchanged. Similarly, BCSR-STF-NS removed the cross-scale feature fusion in the scale direction and only performed spatiotemporal fusion in the time direction. The results of the ablation experiments, shown in Figure 12, demonstrate that BCSR-STF outperforms both BCSR-STF-NT and BCSR-STF-NS. This improvement can be attributed to the design of the Bidirectional Cross Fusion module. The fusion in the time direction helps capture temporal variation features, while the fusion in the scale direction enhances the detailed information between different resolutions. By simultaneously utilizing both directions of fusion, BCSR-STF can better handle spatiotemporal differences, providing more comprehensive and detailed spatiotemporal features.
## 2 Proposed Methodology  
As illustrated in Figure 1a, the PDED-ConvLSTM model consists of two key components: The first is known as the Pyramid Convolution (PC) module, designed for multi-scaleextraction of spatially significant features. This is achieved through a set of convolutional layers with varying kernel sizes. The second module, termed Pyramid Dilated ED-ConvLSTM (DED-ConvLSTM), enhances the ED-ConvLSTM module by utilizing varied dilation rates of the convolutional kernels, enabling the learning of more profound spatial information. The DED-ConvLSTM module takes the spatial features learned from the PC module as input and outputs enhanced spatiotemporal saliency features, which are then utilized for the final prediction of the sea ice concentration sequence. Detailed information about each component will be provided in the following sections.
# A Medical Image Encryption Scheme for Secure Fingerprint-Based Authenticated Transmission
## 3 Materials and Methods
### Comparation Analysis  
The proposed scheme is compared to other schemes of visually secure image encryption introduced in [48; 49; 50; 51; 52]. The quality of the reconstructed image is the main requirement in a medical image encryption scheme. The averages of PSNR and MSSIM obtained between the embedded image (medical image) and the image reconstructed by the proposed scheme have been compared with the other schemes to evaluate the quality of the reconstructed image. Table 3 shows the comparison results. On the other hand, the visual security of the visually meaningful encrypted image is another essential requirement. The PSNR achieved between the reference images and the visually meaningful encrypted image has been compared to evaluate the visual security of the proposed system, and the results have been shown in Table 4. The same images used as carrier images in the other approaches have been used as reference images in the comparison analysis to provide a fair comparison. N/A in Tables 3 and 4 refers to information not available in the comparison schemes.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Reference Image** & **Embedded Medical Image** &
\begin{tabular}{c} **Distance of Histogram** \\ **Intersection** \\ \end{tabular} \\ \hline Barbara & lungs & 0.968 \\ Lena & pelvic & 0.989 \\ airplane & head & 0.992 \\ pepper & skin & 0.992 \\ baboon & breast & 0.987 \\ girl & kidney & 0.980 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The distances of histogram intersection between the reference image and the visually meaningful encrypted image.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & [48] & [50] & [51] & [52] & [53] & [54] & **Proposed Scheme** \\ \hline PSNR & 49.137 & 35.107 & 33.4204 & 32.4235 & 51.6860 & 31.62 & **54.947** \\ MSSIM & 0.92339 & 0.95564 & N/A & 0.8855 & N/A & 0.9887 & **0.9963** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of the average PSNR and MSSIM values of reconstructed images (the best results are shown in bold).  
The proposed scheme achieves the highest PSNR and MSSIM values of reconstructed images compared to other approaches, as shown in Table 3. Therefore, the proposed scheme is appropriate for medical image protection, where accurate image reconstruction is the most crucial requirement. Table 4 shows that the PSNR values of the visually meaningful encrypted images are not the highest compared to other approaches. However, the visual security of the encrypted image is, in any case, ensured, as shown in Tables 1 and 2.
# DDTMS: Dirichlet-Distribution-Based Trust Management Scheme in Internet of Things
## 4 Simulations and Analysis
### Node Interaction Based on Dirichlet Distribution
In summary, the trust management scheme based on the Dirichlet distribution is superior to the trust management schemes based on the Beta distribution and the Gaussian distribution in theoretical and related simulation experiments. The trust values distribution of each node (including normal nodes and malicious nodes) in the cluster is also in line with the functional expectation of detecting malicious nodes.
## 2 Literature Review
[8] improved PSO with a comprehensive learning strategy for multimodal optimization. Ref. [29] proposed a hierarchical PSO with time-varying coefficients for better exploration. Ref. [9] developed an adaptive PSO for dynamic environments. Recent works like [30] combined PSO with simulated annealing for UAV path planning, improving solution quality, while [31] introduced a multi-swarm PSO for scalable task allocation. Other metaheuristics include Differential Evolution (DE) by [32] for trajectory optimization, Artificial Bee Colony (ABC) by [33] for task allocation, Ant Colony Optimization (ACO)by [34] for dynamic path planning, and Genetic Algorithms (GA) by [35] for real-time task allocation. Additional challenges like communication constraints and collision avoidance are also significant. Ref. [36] studied task allocation under communication limits, while ref. [37] proposed decentralized methods for communication-delayed UAVs. Ref. [38] developed collision avoidance algorithms, and Ref. [39] applied reinforcement learning for real-time avoidance. Real-time data processing, vital for dynamic planning, was addressed by [40, 41], focusing on efficient algorithms and edge computing. Despite these advances, critical gaps remain. Few studies integrate task allocation, path planning, and energy management holistically in dynamic settings [17, 42]. Rolling horizon applications with energy constraints are limited [16]. PSO methods often lack adaptive perturbation and local search for multi-objective dynamic problems [30, 31]. Many assume idealized conditions like instantaneous recharging [24], impractical in reality. This paper addresses these gaps with a unified framework integrating dynamic task allocation, path planning, and energy management, using an enhanced PSO with adaptive perturbation and simulated annealing within a rolling horizon structure, ensuring adaptability and energy efficiency. Furthermore, although machine learning methods can model the environment in a data-driven manner and have attracted attention from some scholars, they heavily rely on task-specific data and exhibit limited generalization capability, making performance tuning across different settings challenging. Moreover, these algorithms require extensive training data and complex environment setups, resulting in high training and deployment costs.
# Setonix: Blockchain-Based Hierarchy Domain Name System for Web3
## 8 Conclusions  
This paper raised the issue that blockchain-based decentralized Web3 services are using the centralized Web2 server-client model for service access. Due to this, the advantages of decentralized systems are lost, and vulnerabilities arise in the service because of the SPoF issue inherent in the centralized structure of the access path. To resolve this, it was necessary to introduce a decentralized access path, leading to the proposal of Setonix, which combines a decentralized DNS with a proxy-based interface for its use.  
In conclusion, Setonix provides a decentralized access path option for Web3 services, enabling ownership verification without the involvement of central authorities through smart contracts. This results in a DNS that allows services to be uniquely and freely expressed. In addition, through the proxy-based interface, which efficiently categorizes domain names and enhances user experience, users can freely use both Web2- and Web3-based domains without needing any manual conversion after a one-time setup.  
However, as it is implemented as a smart contract using Solidity, it has a clear limitation in that it can only operate in blockchain environments equipped with an EVM. Conducting future research to enhance its general applicability to typical blockchain networks would provide substantial value in supporting Web3. Additionally, future research will focus on exploring methods for directly connecting to nodes of services operating on blockchain p2p networks, including addressing deficiencies in security settings. In particular, incorporating DNSSEC extensions currently used in DNSs into blockchain systems or utilizing Decentralized Identifiers (DIDs) to enhance the security of blockchain-based DNSs could serve as valuable research topics.  
In terms of scalability, further research is expected to overcome the current limitation of operating only on EVM-based systems, enabling functionality across various blockchain platforms. Such advancements could lead to a more versatile system, playing a significant role in positively promoting Web3 and other blockchain-based services.  
Conceptualization, J.J. and S.P.; Methodology, J.J.; Software, J.J.; Validation, J.J.; Investigation, J.J.; Resources, S.P.; Writing--original draft, J.J.; Writing--review & editing, J.J.; Visualization, J.J.; Supervision, S.P.; Project administration, S.P.; Funding acquisition, S.P. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Bisa Research Grant of Keimyung University in 2023 (Project No: 20230222).  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
# Influence of Solvent Selection in the Electrospraying Process of Polycaprolactone
## 3 Selection of Solvent Systems Used in PCL Electrospraying
### Solution Properties for Cone-Jet in PCL Electrospraying
#### 3.2.1 Electrical Conductivity  
During electrospraying, due to the electrostatic force generated from the applied electric field, the solution is stretched and accelerated into a jet from the tip of the nozzle to the collector. The formation of the Taylor cone occurs at the tip of the nozzle, when a balance among six forces, including gravity, electrostatic force, Coulomb repulsions, viscoelastic and frictional forces, and surface tension, is achieved (Figure 1). The strength of the electrostatic force and Coulomb repulsion acting on electrospray droplets mainly depend on the amount of polarization charge in droplets and the strength of the applied electric field. The amount of polarized charges on the surface of the droplets is closely related to the range of the electrical conductivity of working solution in the electric field. The surface tension and viscoelastic forces are counteracted by the electrostatic attraction under the electric field, leading to the formation of the Taylor cone. If the electrical conductivity of the working solution is too high, the Coulomb repulsions among charged droplets increase, as well as the breakup of charged droplets. All these phenomena contribute to modify the balance among the six forces, and the stable cone-jet change to an unstable jet. On the other hand, an excessively low electrical conductivity leads to insufficient electrostatic attractions on the droplets to match with the surface tension and viscoelastic forces of the working solution. Thus, the Taylor cone at the tip of the nozzle is not achieved, nor is the formation of particles. According to [PERSON] and [PERSON] et al. [124; 125], the electrohydrodynamic process is carried out under cone-jet mode when the electrical conductivity of working liquids are in the range of \(10^{-11}\) to \(10^{-1}\) S/m. Nevertheless, for PCL it ranges from 8.0 \(\times\)\(10^{-10}\) to 3.2 \(\times\)\(10^{-2}\) S/m, and more specifically from \(10^{-4}\) to \(10^{-8}\) S/m (Table 3). It can also be noticed that it increases with the increase of surface tension and the viscosity of working solutions. Furthermore, a high PCL concentration requires high electrical conductivity of solvent systems. In some cases, if the surface tension and viscosity of the working liquids are too high, an electrical conductivity of working liquids, exceeding the mentioned range, is needed to balance the surface tension and viscoelastic forces in order to achieve the cone-jet mode.