esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Wind Speed Prediction Research Methodology  
### Forecasting Process  
In this study, a combined wind speed prediction model for wind farms with CEEMDAN-RIME-MHSA-BiLSTM was constructed, and the prediction steps are shown in Figure 1.  
1. First, wind speed data are collected, followed by data preprocessing and outlier detection to remove anomalies in a timely manner, improving the data's reliability and stability;
2. The dataset is split into training and validation sets. The training set is used to construct the wind speed prediction model by analyzing the historical wind speed data, while the validation set is used to evaluate the performance of the wind speed prediction model;
3. The CEEMDAN algorithm decomposes the time series wind speed data to generate multiple intrinsic modal functions (IMFs). The wind speed prediction model is constructed based on the decomposed IMFs;4. The BiLSTM model hyperparameters are automatically tuned via the RIME algorithm, which includes parameters such as the number of neurons in the hidden layer, the learning rate, and the number of training times. The RIME automatically searches the parameter space to quickly identify the optimal parameter combination for the BiLSTM model, which serves as the foundation for constructing prediction models for each component;
5. A multi-head self-attention mechanism is introduced based on the BiLSTM model to capture the complex relationship between different subsequence components. Each attention head learns the feature representation of different subspaces, and each subsequence component can be regarded as a different representation subspace;
6. The prediction of each modal component is performed using the trained model. By weighting and summing the predicted values of the modal components at different time scales, the overall wind speed prediction is finally obtained. Decomposition and then reconstruction allow the model to capture the trend of the wind speed changes more accurately.
System Design and Launch of a Hybrid Rocket with a Star-Fractal Swirl Fuel Grain Toward an Altitude of 15 km +
Footnote †: The 11 th International Multi-Conference on Engineering and Technology Innovation 2022 (IMETI2022).  
Because of the physical partition of fuel and oxidizer, hybrid rockets have high resistance to explosion hazards and can achieve safer and more reliable space transport system performance compared to conventional liquid and solid fuel rockets. Moreover, the safer character can realize low costs in ground manipulation of fuels and rockets, such as storage, production, and transportation. Thus, many studies on hybrid rockets were conducted.  
Because a plastic grain like acrylonitrile butadiene styrene (ABS) can be used for the fuel of hybrid rockets, many studies have been conducted using 3D-printed plastic grain. [PERSON] et al. developed powder fuel containing 3D-printed fuels to improve the regression rate of the grain [3]. [PERSON] and [PERSON] conducted a static combustion test of 3D-printed grain made from ABS, acrylonitrile styrene acrylate, polylactic acid (PLA), polypropylene, polyethylene terephthalate glycol, Nylon, and PLA with aluminum particles to investigate the regression rate of the grain [4]. [PERSON] et al. investigated the combustion performance of fuels comprising a paraffin-based fuel embedded on a 3D-printed nested helical ABS grain [5].  
Paraffins can also be used for the grain. [PERSON] et al. investigated the regression rate of five types of cylindrical port paraffin fuels with oxidizer swirl flow and concluded that the regression rate can be increased with oxidizer swirl flow [6]. [PERSON] et al. investigated mechanically modified paraffin-based grain in combustion tests to obtain an excellent paraffin-based grain with both good mechanical properties and good combustion performance [7]. In 2017, the authors developed a 3D-printed solid fuel grain with a star-fractal port to improve the regression rate and used it in a launch experiment. In 2018, the authors added a swirl shape to a star-fractal port. The vehicle used a star-fractal swirl port hybrid rocket engine that was launched in that year and reached an altitude of 6.2 km [8]. In 2019, a 50 kNs-class hybrid rocket engine was developed with the goal of reaching a maximum altitude of 15 km; however, an engine rupture occurred during the combustion test; hence, the launch was abandoned. In 2020, COVID-19 prevented sufficient experiments from being conducted to determine the cause of the rupture failure, and the launch was abandoned again. In March 2021, the cause of the rupture was identified. An engine equipped with countermeasures successfully completed five combustion tests from May to July 2021, and a rocket named \"Amanuma Maru\" was launched at 6:00 am on 19 September 2021 from Noshiro City, Akita Prefecture. Atmospheric pressure telemetry data indicated that it reached a maximum altitude of 10.1 km. This paper reports a summary of its development and launch test [9].
These developments can improve spectrum sharing and coexistence with fixed-satellite services (FSS-ES). It is important to note, however, that the specific interference impact of future 5G technologies and the applicability of proposed solutions will depend on their deployment strategies, implementation details, and regulatory frameworks. As these technologies continue to evolve and mature, it will be necessary to conduct additional research, analysis, and empirical studies in order to assess their interference effects and develop appropriate solutions. While the discussed analysis concentrates on the current state of 5G technology, it is essential to recognise the potential impact of future 5G technologies, such as 5G-NR, on the interference issue. As 5G technology evolves, it will be necessary to conduct ongoing research and implement solutions in order to address any potential new obstacles.
## 3 Antenna Characteristics
### Effect of the Fractal Indentation Ratio  
The indentation ratio of the Minkowski fractal plays a crucial role in enhancing both impedance matching and antenna gain. Figure 7 illustrates the results of simulating this phenomenon. It is noticeable that a substantial increase in the indentation ratio shifts the lower cut-off frequency far from the desired frequency. However, this shift is accompanied by improved impedance matching, resulting in the observation of two resonance frequencies at 4.22 GHz and 9.68 GHz. On the other hand, a very small indentation ratio creates a band notch between the C and X bands, covering the range from 7.53 GHz to 8.20 GHz. The trade-off involves deciding between moving the lower cut-off frequency away from the design frequency while maintaining good impedance or moving it to the design cut-off frequency while creating a band notch. Following numerous parametric optimizations, excellent impedance matching was achieved at an indentation ratio of 0.25 mm. This configuration offers significantly improved impedance matching and bandwidth, with a minimum return loss of \(-\)34.72 dB at 9.68 GHz and no band notch observed.  
Figure 6: Simulated reflection coefficient curve for different dimensions of the slotted arc on radiating patch.
# Selected Plants as Sources of Natural and Active Ingredients for Cosmetics of the Future
## 5 Plantago lanccolata L
### Biological Activity  
The active ingredients obtained from _P. lanceolata_ L. include flavonoids, which have anti-inflammatory, antihistamine, and anticancer properties. They neutralize free radicals and chelate metals. In addition, flavonoids protect the skin from harmful ultraviolet radiation, inhibit certain enzymes, and prevent the oxidation of lipid substances. Tannins have astringent properties on the skin. Another group of bioactive chemicals present in plant extract are iridoid glycosides, which are responsible for antibiotic, antihepatotoxic, anti-inflammatory, spasmolytic, antiviral, and anti-stress effects. Additionally, _P. lanceolata_ L. is known for its diuretic and antispasmodic properties. Propionic glycosides exhibit antibacterial, antioxidant, anti-inflammatory, and anticancer effects [80; 93].  
Phytosterols (such as sitosterol, stigmasterol, and campesterol) are responsible for anti-inflammatory effects. It has been observed that they reduce swelling and redness  
Figure 11: Chosen bioactive substances from _Plantago lanceolata_ L. [80].  
of the skin. Furthermore, they lower cholesterol levels in the blood and have antipyretic properties. In addition, they have been documented to inhibit the growth of tumors in colon, stomach, breast, and lung [93; 94].  
Acetoside ester, also known as verbascoside, is used as the main ingredient in syrup against cold [84]. Verbascoside is also applied in other pharmaceutical preparations used to treat neurodegenerative diseases and pain [89]. There have been some reports of the development of liquid crystals containing plantain extract. In this form, the bioactive ingredients, especially verbacoside, would be protected against hydrolysis [95].  
The extract from this plant has also been studied as a wound healing agent. The results of studies conducted on rats and mice showed that the kinetics of wound healing increased. A reduction in scar formation was also observed. The wound healing activity of _P. lancolata_ L. extracts is associated with modulation of all processes involved in that process (proliferation, migration, differentiation, and induction of fibroblasts to myofibroblasts transition, and extracellular matrix formation/organization) [96; 97]. The presence of iridoid glycosides makes it possible to use _P. lancolata_ L. extract as an insecticide [80]. The _P. lancolata_ L. plant is also characterized by high anti-aging effectiveness [87]. Its water infusions and stabilized juices are used as an active ingredient in cream and mask formulas. The presence of salicylic acid in leaf extracts also shows antibacterial and anti-inflammatory activity, resulting in cleansing and protective properties of skin care products [80].
# Collecting Sensed Data with Opportunistic Networks: The Case of Contact Information Overhead
## 4 An Algorithm for Reducing Contact Information Overhead  
Message forwarding in high node population and dynamicity requires a means of minimizing contact information overhead without throughput degradations. We already learned from a previous study [47] that it may not be necessary to maintain the history of every encounter in order to realize  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**No. of Encounters**} & \multirow{2}{*}{**Energy Utilized (Joules)**} & \multicolumn{1}{c}{**\% of Allocated Energy**} & \multicolumn{1}{c}{**\% of Allocated Energy**} \\  & & **Utilized** & **Remaining** \\ \hline
300 & 317.2 & 23.1\% & 76.9\% \\
400 & 423.0 & 30.8\% & 69.2\% \\
500 & 528.7 & 38.5\% & 61.5\% \\
600 & 634.5 & 46.2\% & 53.8\% \\
700 & 740.2 & 53.9\% & 46.1\% \\
800 & 846.0 & 61.7\% & 38.3\% \\
1295 & 1369.5 & 99.8\% & 0.2\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: The percentage of energy allocated to the OppNet that is utilized in exchanging contact information alone for a different number of encounters within 24 h (battery energy = 45,738 Joules; and allocated energy = 1372.14 Joules).  
comparable throughput. The modification of PRoPHET to maintain encounter history for only nodes from the same home-region traded only 11% throughput for about 84% average reduction in contact information maintained at each node. Hence, the challenge in optimizing the trade-off between contact information overhead and throughput lies in: determining which encounters to consider in terms of maintaining encounter history, and which ones to forego; and a forwarding approach that can utilize the available information to carry messages close enough to the destination or to nodes that have recorded their encounter history with the destination. Without a proper understanding of the relationship between node movement and encounter opportunities, important encounters may be neglected and the resulting insufficiency in knowledge may cause throughput degradation. In this section, we present PoiFord, and tackle the following points in the process:  
* A means of minimizing routing information without significant throughput degradations, more specifically, addressing the challenge of determining the most relevant encounters for which to maintain encounter history; and
* A forwarding approach that can utilize the available information to carry messages close enough to the destination or to nodes that have encounter history with the destination.  
By addressing these points, PoiFord is able to achieve the features shown in Table 3.
## 4 Discussion
### Obstacle Avoidance and Power Limitations  
The obstacle avoidance system, utilizing infrared time-of-flight sensors, effectively detected and prevented collisions by identifying obstacles within 0.35 m and retreating 0.2 m. This mechanism ensured continuous flight in cluttered environments, where multiple directions were sometimes obstructed simultaneously. While the system performed reliably, occasional issues occurred due to the drone's battery size, which led to rapid power depletion after only a few flights. This constraint not only restricted the duration of each test session but also introduced risks during extended flight operations, such as mid-flight shutdowns or degraded sensor performance. Power limitations affecting drone performance have been discussed in previous research, suggesting that optimizing power management strategies or using energy-efficient algorithms could enhance flight duration [34]. Furthermore, improving obstacle detection through sensor fusion with LiDAR or ultrasonic sensors has been proposed as a way to increase reliability in within different environments [35]. While the obstacle avoidance mechanism performed well in the given test setup, the experimental conditions were limited to short-range, single-obstacle scenarios. This system could be explored further to enhance its operation in more complex environments by incorporating real-time path planning and adaptive behavior to maintain safe navigation amid multiple obstacles or irregular layouts.
# Mixed Reality Enhanced User Interactive Path Planning for Omnidirectional Mobile Robot
## 1 Introduction
However, the above studies only control the real environment after virtualization, or merely control the virtual robot, and there is no interaction between real robot motion and virtual objects. This paper proposes a novel path planning interactive system based on MR. With more and more practical applications of VR, mobile robots sometimes need to avoid some virtual objects, such as virtual meetings that need to avoid projecting participants or factories that need to avoid certain locations. The system is proposed for these scenarios. The work of this paper has two main points. Firstly, an MR interaction system was developed to control the mobile robot. Additionally, virtual obstacles can be added to the map of the robot's movement based on specific needs, and path planning can be actively modified. Secondly, the original VFH* algorithm was modified in terms of the threshold setting, the candidate direction selection, and the cost function, making the generated path more suitable for the scene in this paper and more safe and smooth. The remainder of this paper is organized as follows: In Section 2, the system structure of this paper is described. Section 3 introduces the knowledge regarding mixed reality. The dynamics of the omnidirectional mobile robot used in this paper are discussed in Section 4. Section 5 introduces the basic process of the VFH* algorithm and describes the improvement of the algorithm in detail. Section 6 describes the development process of the virtual reality interactive system and the experimental results and effects of path planning. The conclusion of this paper is presented in Section 7.
## 2 Related Works
### Routing Based on Network Coding  
It is clear that the transmission reliability could be improved when a network coding technique is used. Some existing researches show that applying network coding techniques to DTN environments can improve the performance in terms of the message loss rate. In [10], an efficient network coding scheme for DTN has been proposed to analyze the redundancy of the coded messages which has significant advantages in enhancing the message delivery ratio and reducing the transmission overhead. In [11], based on the fact that there are some mobile nodes, denoted as HUBs, which have frequent contacts with other mobile nodes, a new mechanism, Message Forwarding using Hub-based Network (HUBCODE), has been proposed to use the random linear network coding scheme to address the routing issue, which can obtain 20% improvement.
## 1 Introduction
Although GABNI shows good performance for large-scale networks, it employs a limited representation model of regulatory functions. In this regard, a novel genetic algorithm combined with a neural network for the Boolean network inference was proposed in [9], where a neural network was used to represent the regulatory function instead of the incomplete Boolean truth table used in the GABNI. In brief, although the inferred results were reliable with acceptable accuracy, Boolean network methods often show poor performance due to the simplicity (information loss) of the Boolean representation of the data. To extend the limited representation of the Boolean network for the network reconstruction problem, we propose a novel algorithm called mutual information based on multiple-level discretization network inference from gene expression profiles (MIDNI). The algorithm first discretizes gene expression data with multiple levels (two or three) according to the distribution of the expression values of a gene. Through analysis based on the validity index [10; 11] over massive data, we observe that two-level discretization performs best on certain genes. However, three-level discretization is shown to be effective for a considerably larger number of genes. On the other hand, using a value of \(k\) larger than three increases system complexity and computational cost. Subsequently, the discretized expression data are fed to the mutual information-based feature selection (MISF) method [7]. We used MIFS to estimate the mutual information between a target gene and a set of candidate regulatory genes to reduce the computational cost. The loss of information increases as the number of regulatory genes considered in MIFS increases, which can eventually cause a significant decrease in inference accuracy. To overcome this problem with MIFS, we used a SWAP subroutine, which is a greedy algorithm wherein a gene in the set of regulatory genes selected by MIFS is iteratively swapped with another gene in the set of unselected genes. MIFS and SWAP were presented in the MIBNI algorithm [7]. However, MIFS and SWAP in MIBNI were implemented to process only Boolean expression data. Thus, we carry out appropriate modifications to these subroutines. We validate the performance of our method on both artificial and real gene expression datasets in comparison with three well-known methods, namely, new dynamic Bayesian network (DBN) [12], maximal information coefficient with conditional relative average entropy and time series mutual information (MICRAT) [13], and the aforementioned MIBNI [7]. Our experimental result show that our method outperforms all three in terms of dynamic accuracy. Furthermore, MIDNI is able to infer a network against noisy datasets. This indicates that MIDNI is a notable method for inferring regulatory networks from gene expression datasets.
## 3 Point Cloud Reconstruction
### Conversions of Coordinates
#### 3.2.4 The World Coordinate  
The POS outputs position and posture data, both located in the real world, or rather, in the WGS-84 coordinate system.  
We define \(\alpha,\beta\), and \(\gamma\) as the POS angles, which expresses the real POS posture to the ground plane of reference. These angles are formulated as the rotation matrix \(R(\alpha,\beta,\gamma)\).  
We use \(L_{0},B_{0}\), and \(H_{0}\) to indicate the longitude, latitude, and altitude of the POS, respectively. \(L_{0}\) and \(B_{0}\) continue to rotate the POS axes using the following matrix:  
\[R_{e}(L,B)=\begin{bmatrix}-\sin L&-\sin B\,\cos L&\cos B\,\cos L\\ \cos L&-\sin B\,\sin L&\cos L\,\sin L\\ 0&\cos B&\sin B\end{bmatrix}. \tag{10}\]  
To combine with the POS coordinate, longitude and latitude should be converted from angle to length variables using the following conversion:  
\[\begin{bmatrix}x\\ y\\ z\end{bmatrix}=f_{T}\begin{pmatrix}L\\ B\\ H\end{pmatrix}=\begin{bmatrix}(N+H\,\cos B\,\cos L)\\ (N+H)\,\cos B\,\sin L\\ \begin{bmatrix}N\big{(}1-e^{2}\big{)}+H\big{]}\sin L\end{bmatrix},N=\frac{a}{ \sqrt{1-e^{2}\sin^{2}B}}. \tag{11}\]  
The function \(f_{T}\) converts the positions \((L,B,H)\) from the WGS-84 system to an ECEF (Earth-centered, Earth-fixed point \((x,y,z)\), where a is the Earth radius, and e is the first eccentricity in the Earth model.  
With the same coordinate format, the point \(\big{(}x_{p},y_{p},z_{p}\big{)}\) is converted to the position on Earth by  
\[\begin{bmatrix}x_{e}\\ y_{e}\\ z_{e}\end{bmatrix}=R_{e}(L_{0},B_{0})\times R(\alpha,\beta,\gamma)\times \begin{bmatrix}x_{p}\\ y_{p}\\ z_{p}\end{bmatrix}+f_{T}\begin{pmatrix}L_{0}\\ B_{0}\\ H_{0}\end{pmatrix}. \tag{12}\]  
Finally, we convert the ECEF coordinate back to the WGS-84 system using the iterative process \(f_{W}(x,y,z)\) shown in (13) [35], which is the standard conversion relationship between ECEF and WGS-84 systems.  
\[f_{W}(x,y,z)\,\sim\,\left\{\begin{array}{l}L=\tan^{-1}\frac{y}{x}\\ B=\tan^{-1}\frac{z+N\rho^{2}\sin B}{\sqrt{x^{2}+y^{2}+z^{2}}}\\ H=\frac{\sqrt{x^{2}+y^{2}}}{\cos B}-N\\ N=\frac{\sqrt{1-e^{2}\sin^{2}B}}{\cos B}\end{array}\right. \tag{13}\]The end condition is that the difference between the old and new value is less than \(1\times 10^{-9\circ}\). The error in length due to a difference of \(1^{\circ}\) in latitude and longitude is not greater than 111 km, so this process results in an error of less than 1 mm.