esa-sceva/satcom-chunk-collection huggingface dataset:
# Design and Study of a New Wave Actuator for a Boat
Another system captures a yacht's wave-induced oscillations (heave, pitch, roll) using a linear generator, where a mass shifts with wave motion, moving a magnetic cursor through stator coils to induce current via electromagnetic induction [18]. Despite significant advancements, challenges remain for wave-powered boat technology. Existing fully wave-powered boats often achieve low speeds, and systems that convert wave energy into electricity typically rely on complex setups with limited efficiency, resulting in substantial energy losses. Additionally, while some designs show improved adaptability to varying flow conditions, they frequently depend on external power sources, limiting their practicality. To overcome these limitations, our study introduces a novel wave actuator that directly harnesses wave forces to generate thrust, distinguishing it from conventional designs. Unlike previous approaches, our proposed actuator integrates a flexible water tank, inlet and thrusting outlet nozzles, solenoid valves, and a revolving spring. As rising waves compress the tank, water is expelled through the thrusting outlet nozzle, propelling the boat forward. This direct conversion of wave energy into thrust eliminates intermediate steps, simplifies the system, and maximizes efficiency by minimizing energy losses. Our wave actuator represents a significant departure from existing designs, offering a simple, energy-efficient solution for wave-powered propulsion. By leveraging wave forces directly, it addresses the shortcomings of current technologies and provides a promising pathway for practical, sustainable maritime applications. The main contributions of the present manuscript are as follows:  
1. Introducing a novel wave actuator that utilizes hydrodynamic forces from waves to generate propulsion. 2. Developing a new hydrodynamic model based on second-order differential equations to analyze the performance of the wave actuator. 3. Demonstrating, through simulations, the superior actuating performance and energy conversion efficiency of the proposed system in various sea conditions. The remainder of this paper is organized as follows: Section 2 presents the mathematical modeling of the wave actuator, including the equations of boat motion under wave excitation. Section 3 details computer simulations evaluating the boat's thrusting performance with the proposed actuator. Section 4 offers conclusions and discusses future implications.
# A Versatile Resilience Packet Ring Protocol Model for Homogeneous Networks
###### Abstract
The intermediate driver generates a virtual protocol driver on the bottom and a virtual miniport driver on top. In this model, there is a concept of the mobile address and fixed address. A fixed address is assigned to the primary and secondary links in the first model, but a mobile address is only assigned to the primary link. In the case of failure, the mobile address is assigned to the secondary link. When the mobile address is shifted, there is no loss of connection, and the application runs smoothly. In the second model, there are two computing devices, and they used different subnets. When we talk about wired and wireless links at the same device, that means that, in the same computing or network device, there should be at least two NICs. Many vendors in the market are making such computing devices, mainly with the name \"Blade server\". One example is the Dell Power Edge Server which comes with a dual NIC and dual power supply. The solution mentioned above is purely for wired computing and network devices, but the same method is used for wireless and wired solutions. Here, we discuss the different methods of network availability in a wired and wireless environment. These methods are sometimes used for the best roaming purpose or sometimes for resilience purposes. Hence, two methods and their problems are discussed. After a deep study of their problems, we suggested our proposed model and modification to the existing network topology, such as mesh networks and sensor networks, due to their route discovery and maintenance nature. Recent advancement in research at the network layer comes up with ample routing protocols to reduce the overhead of message control and reduce the  
Figure 3: Network driver interface specification. Figure 2: Virtual miniport/virtual driver. end-to-end hop count and minimum energy consumption of wireless LAN networks. The term handover terminology is mainly used in cellular networks. This is a process of ongoing transfer of one voice or data session from one channel/backbone to another channel/backbone with the interruption of services. If handover occurs in the same type of network, then it is called homogeneous (horizontal). In this paper, we propose a Versatile Resilience Ring protocol (VRPR)-based network model and provide the detailed simulation results. Further, the paper is organized as follows: Section 2 discusses related work and the pros and cons of the existing wired and wireless networks. Section 3 briefly explains the proposed Enhanced VRPR protocol model and its working mechanism, such as the packet drop percentage. Section 4 presents the simulation results, and finally, Section 5 concludes this paper.
# Network Performance Optimization for Low-Voltage Power Line Communications
## 4 Network Performance Optimization Based on Dynamic Game Theory
### Improved Performance Optimization Model Based on HMM Algorithm  
Saturation bandwidth utilization and access delays are sensitive to access probabilities. Access probabilities are relevant to the number of active competitive stations. The stations cannot directly obtain the number of competitive stations. They only rely on themselves to judge channel states, dynamically sense the channel decision results of competitive stations, and obtain the number of competitive stations. This study uses HMM to dynamically sense the number of competitive stations in the game process.
## 3 Results
### Comparison of the Model with Other Models
#### 3.3.1 Comparison with SVM and PLS  
SVM and PLS-DA are two commonly used traditional machine learning methods widely applied in spectral analysis. SVM is a popular supervised learning model used for classification and regression analysis, with the core idea of finding a hyperplane that maximizes the margin between classes. PLS_DA is a classification method that combines partial least squares regression with linear discriminant analysis, particularly suitable for high-dimensional data.  
In this section, we compared the deep learning model SpectraViT with SVM and PLS_DA to verify the superiority of our model over traditional methods. SVM and PLS_DA are commonly used traditional machine learning methods in spectral analysis. To implement these two classification algorithms, we first standardized the data. For the SVM model, we used a linear kernel function with parameters C = 1 and \(\gamma\) = auto, applying the One-vs-One strategy for classifying the four types of UV spectra. For the PLS-DA model, we selected 100 principal components for feature extraction. All of the models were implemented using Python and its Scikit-learn library.  
As shown in Table 4, the SpectraViT model demonstrated outstanding performance in accuracy, recall, precision, and F1 score, achieving 99.24%, 99.25%, 99.06%, and 99.23%, respectively. In comparison, the performance of SVM and PLS_DA is lower. These results indicate that SpectraViT offers performance advantages in spectral analysis tasks over traditional machine learning methods, particularly in providing a higher classification accuracy and better model generalization when handling complex datasets.
# Characterization of Inter-System Biases in GPS + BDS Precise Point Positioning
## 4 Characterization of ISB
### ISB Characterization Affected by the Antenna Type  
This experiment aimed to find out whether the ISB characterization was related to antenna type or not. See Table 4, we select stations YARR and YAR3 equipped with the SEPT PLOARX5 receivers. Station YARR was connected to LEIAT504 antenna, while was YAR3 connected to LEIAR25 antenna. Similar as before, the distance between YARR and YAR3 was less than 30 m, the external temperature of these two stations could be considered very similar.  
Figure 5 shows, the ISBs from different antennas were inconsistent when using WUM and CODE products, due to the smaller scales, the differences of ISB estimated with CODE precise products were more significant. This indicate that the ISB was related to antenna type and it may be caused by antenna and cable induced delay [32], thus making the ISB antenna-specific. However, the ISBs based  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Station** & **Receiver Type** & **Antenna Type** \\ \hline YARR & SEPT POLARX5 & LEIAT504 \\ YAR3 & SEPT POLARX5 & LEIAR25 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Stations selected for the investigation of ISB characterization affected by the antenna type.  
Figure 4: GPS/BDS ISB series of MAT1/MATE and MATZ estimated using WHU, CODE and GFZ precise products on DOY 253, 255, 257, 2018.  
on GFZ products were consistent, this was because the ISB variation caused by the change of satellite clock datum were much larger than the variation caused by the antenna code bias.  
Based on the analysis of ISB characterizations, we carried out the GPS/BDS PPP with modeling the ISB as, constant (CT), random walk (RW) process and white noise (WN) [33], respectively. Data from twelve ICS stations on DOY 252-281, 2018 were used to analyze the performances of GPS/BDS float dynamic PPP using different ISB modeling strategies. Taking station PNGM as an example randomly, the GPS/BDS float dynamic PPP solutions were carried out with modeling ISB as constant, random walk and white noise process. As for the equipped receivers and antennas, refer to Table 2.  
Figure 6 shows that, for the PNGM station, the positioning errors in east, north and up were almost the same with different modeling strategies of ISB using WUM and CODE precise products, while the solution using GFZ precise products, the performance with constant ISB modeling strategies were much worse than random walk and white noise ISB modeling strategies. Taken altogether, as Tables 5 and 6, similar to the positioning performance, the convergence performances were almost uniform with different modeling strategies of ISB, the performances of GPS/BDS PPP based on CODE and WUM products were comparable. In these three cases, the CT process performs best, the RW process follows, and the WN process presents
# Manufacturing Scheduling Using Colored Petri Nets and Reinforcement Learning
## 4 The Case Study
### The Order-Picking Scheduling
#### 4.2.1 Order Batching  
Order batching is calculated based on the following two-step heuristic [44]. The agent's goal, in this stage is a balanced workload among robots.  
Step 1: The first incoming order to the system goes to the first batch. The second order goes to the second batch, until each batch has one order. The next order goes to the batch with the least workload. All the remaining orders are assigned following this rule.  
Step 2: The average workload per pick zone is calculated. Next, for each batch, orders are assigned to pick zones 1 through 4, so that the workload per pick zone does not exceed the average workload, starting from pick zone 1.
## 1 Introduction
This adaptability bolsters the model's resilience to complex data distributions. Additionally, an automatic relevance determination (ARD) network was employed to facilitate the identification of critical factors within sensor data, thereby enhancing the model's interpretability. The contributions of this study are summarized as follows:  
1. A novel interpretable recurrent variational state-space model (IRVSSM) is proposed for diagnosis of complex systems. Recurrent neural networks (RNNs) are utilized to capture long-term dependencies in sensor data, while the state-space model (SSM) captures dynamic changes in complex sensor data. The incorporation of nonlinear emission and transition matrices enables the model to flexibly adapt to various data distributions. Additionally, integrating a variational autoencoder (VAE) within the state-space framework not only enhances the model's generalization capability but also helps alleviate overfitting issues. 2. To extract crucial information from sensor data, an automatic relevance determination (ARD) network is designed. By comparing sensor weights with actual fault information and conducting detailed analyses of the model's decisions, the ARD network furnishes compelling explanations for engine fault classification. 3. Experiments were carried out on simulated and actual liquid rocket engine test data. The results demonstrate the fault diagnosis performance of the proposed methodology outperforms baseline models.
# Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications
## 4 Graph-Based RA in Cellular Homogeneous and Het-Nets
### RA Methods in OFDMA Systems
A scenario in which middle-mile Long Term Evolution (LTE) networks operate in unused TV broadcast frequencies is the basis for the channel allocation problem solved in [20]. A conflict interference graph connects all BSs (vertices) which interfere with each other. The algorithm aims to avoid the allocation of the same channels (provided that they are available for sharing, i.e., unused by the TV broadcast network) to neighboring BSs, subject to a pre-defined value of the fairness index \(\beta\) (dependent on \(R_{T}\)). The proposed solution provides significantly higher throughput gains; \(R_{T}\) declines with the increase in the number of BSs due to the higher interference levels, but the fairness index remains nearly constant. The authors of [21] study RA for an OFDMA small-cell network with prioritization of the users' data streams. The considered system model includes a varying number of indoor small cells and users served by them, on a variable number of channels. An interference conflict graph is constructed from the UEs as vertices, which are connected with edges if they are associated with an interfering small cell (one that is closer than a certain distance to a user's serving cell). Furthermore, users are divided into a high- and low-priority sets, which--together with whether a user is associated with a small cell--are also taken into consideration by the channel allocation problem. To reduce the computational complexity, the graph is transformed into a cordial one (if a group of vertices form a closed cycle, then there is at least one chord that connects two vertices on the opposing ends). Then, a heuristic admission control algorithm is employed to associate the UEs with the most appropriate cells, in accordance with the users' RB demands. Finally, the RBs are allocated. In addition, the authors describe the necessary procedures for the implementation of the proposed scenario in an LTE network. The algorithm's performance is evaluated through the ratio of guaranteed users \(\alpha_{u}\) (sum of satisfied users divided by by their overall number), the throughput satisfaction rate \(\theta_{u}\) (ratio of the achievable and required throughputs), and \(\beta\) (which describes how fairly the RBs are distributed). The results show that \(\alpha_{u}\) is significantly improved compared to other methods, and remains nearly unchanged as the number of small cells increases. In addition, its complexity is many orders of magnitude smaller. Both \(\theta_{u}\) and the fairness index are relatively stable if the number of available RBs is sufficient.
## 3 Algorithm for Multi-Station Satellite Orbit Optimization in Common-View
### The Implementation of Optimal Satellite Orbit Algorithm in Common View
#### 3.2.2 Constraints  
In order to optimize the optimal satellite orbit design between multi-stations in the common view, the following constraints should be satisfied:  
1. Provide the exact moment in time: A four-dimensional space vector is required for the satellite's instantaneous Earth coordinate system coordinates, which includes the precise UTC time used to calculate the satellite coordinates at that specific point in time. Therefore, the instant time is denoted as \(time_{instant}=[Y,M,D,H,Min,S]\).
2. Boundaries of \(i_{com}\) and \(\Omega_{com}\): The shape of a satellite's orbit is determined by its orbital inclination and the right ascension of the ascending node. Therefore, it is necessary to establish reasonable ranges for the upper and lower boundaries of these parameters. Specifically, the orbital inclination and right ascension of the ascending node should be framed within the ranges \(i_{com}=[0,\ 180]\) and \(\Omega_{com}=[0,\ 360]\).
3. Angular velocity constraint: If we assume that the satellite orbit is a closed circular one, then it operates at an angular rate that satisfies [PERSON]'s third law, which is \(\omega_{AR}=\sqrt{\frac{GM}{P^{3}}}\).
4. Ground laser station coordinates: Different observable time periods correspond to distinct ground laser station coordinates, that is \(L_{station}=\begin{bmatrix}X_{L1}&Y_{L1}&Z_{L1}\\ X_{L2}&Y_{L2}&Z_{L2}\\ &\vdots\end{bmatrix}\).  
Observation elevation angle constraint: The design of the satellite orbit must ensure that during observation at different stations, the elevation angle of observation is larger than the station's lowest observation elevation angle, or \(\theta_{i}\geq\theta_{min}\).
6. Common-view time constraint: The satellite's orbit must be designed in order to fulfill the requirement that, upon passing through several orbital planes, the satellite is visible to ground stations for the greatest possible amount of time. This is indicated by the following equation: \(max:Time_{com}=\sum_{i=1}^{n}f(i_{com},\Omega_{com})\).
# Decoupling the Impacts of Climate Change and Human Activities on Terrestrial Vegetation Carbon Sink
## 3 Results
### Correlation Between NEP and Meteorological Factors  
From the results of the partial correlation analysis, as shown in Figures 6 and 7, we can observe that the partial correlation coefficients between temperature and NEP range from \(-0.83\) to \(0.93\), with a positive correlation area percentage of 82.6%. Among them, the proportion of significantly positively correlated areas is 16.22%, mainly concentrated in Shandong Province. The insignificant positive correlated areas account for 66.38%, widely distributed in CCZ. The negative correlation area percentage is 17.4%, with a significantly negative correlation area percentage of 0.79%. The insignificant negative correlated areas account for 16.61%, and they are mainly found in Taiwan, Hainan, and Guangxi.  
Figure 4: Hotspot cluster map of average NEP in CCZ.  
There is a north-south difference in the partial correlation coefficients between precipitation and NEP. Moreover, the range of the partial correlation coefficient between precipitation and NEP is \(-0.94\) to \(0.86\), with a positive correlation area percentage of \(58.25\%\). Among them, the proportion of significantly positively correlated areas is \(20.67\%\), mainly observed in the Beijing-Tianjin-Hebei region and the western parts of Liaoning Province. The insignificant positive correlated areas occupy \(37.58\%\) of the total area, observed primarily in eastern Liaoning and parts of Shandong, Jiangsu, and Guangxi. The negative correlation area percentage is \(41.75\%\), with a significantly negative correlation area percentage of \(11.5\%\), predominantly distributed in the Fujian Province and parts of the Pacific  
Guangdong, Hainan, and Taiwan. The region of insignificant negative correlation has similar distribution characteristics as the region of significant negative correlation at the provincial scale. Combining the results of the trend analysis (Figure 5), we can summarize that temperature mainly affects the magnitude of NEP in CCZ, while precipitation mainly dominates the spatial heterogeneity of NEP.
## 5 State-of-the-Art Comparison  
This section highlights the most prominent contributions of the proposed antenna design in comparison to the current state-of-the-art of the multi-band shared-aperture MIMO antenna. Table 1 summarizes the comparison as follows:  
* The proposed antenna is designed based on a new hybrid design technique; it is based on a dual-mode composite antenna and higher-order modes of sub-mode-SIW-cavities for the first time. This is different from current techniques of shared-aperture antennas in the open literature, which are designed based on the dual-mode composite and higher-order modes of full-mode cavity antennas [30; 31; 32; 33; 34; 35], while self-multiplexing antennas are based on sub-mode cavity antennas alone, without the dual-mode concept [20; 21; 22; 23; 24; 25; 26; 27; 28; 29].
* In terms of frequency ratio, most current design techniques have low frequency ratios, as they are only able to operate in a few close frequencies in either Mw [25; 26; 31; 32; 34] or MMw [21; 24; 30; 33], or both [37; 38; 40]. The proposed design has a high frequency ratio (about 23), as it operates in Mw, MMw, and sub-THz frequency applications. Although the proposed design in [37] has a higher frequency ratio than this work, the current work has a very small footprint area (0.018\(\lambda_{0}^{2}\)) compared to [37].
* Regarding the electrical size, and for fair comparison with reported works, the calculation of footprint area was made at the longest wavelength of each reported work. Consequently, the proposed antenna has the lowest footprint area compared to all previous works in the table. The footprint area is calculated based on the electrical lengths; it is about 0.018\(\lambda_{0}^{2}\), where \(\lambda_{0}\) represents the free space wavelength at 5.5 GHz frequency.
* The proposed design represents the first shared-aperture design with four-port MIMO operation at MMw and sub-THz frequencies.
* In terms of the reuse aperture utilization (RAU) efficiency as described in (4), the presented design technique is very efficient, as it has a large RAU (about 92%). \[RAU=\frac{S_{r}}{S}\] (7) where, \(S\) is the occupied footprint area of the larger antenna (the open-loop antenna, which is fed by Port 5), while \(S_{r}\) is the occupied area of the smaller antennas, the QMSIW antennas.  
Figure 21: Simulated and measured results of MEG and branch power ratio: (**a**) MEG, Simulated and measured results at the 28 GHz and 38 GHz bands. (**b**) MEG, Co-simulation results at the 0.13 THz band. (**c**) Branch power ratio results at the 28 GHz and 38 GHz bands. (**d**) Branch power ratio results at the 0.13 THz band.
## 7 Conclusions  
Viewing significant challenges encountered in extending greedy routing from 2D to 3D space, we have investigated decentralized solutions to achieve greedy routing in 3D sensor networks. Our proposed approach is based on a unit tetrahedron cell (UTC) mesh structure. We have proposed a distributed algorithm to realize volumetric harmonic mapping of the UTC mesh under the spherical boundary condition. It is a one-to-one map that yields virtual coordinates for each node in the network. Since a boundary has been mapped to a sphere, node-based greedy routing is always successful thereon. At the same time, we have exploited the UTC mesh to develop a face-based greedy routing algorithm and proved its success at internal nodes. To route a data packet to its destination, face-based and node-based greedy routing algorithms are employed alternately at internal and boundary UTCs, respectively. For general networks with multiple internal holes, a segmentation and _tunnel_-based routing strategy is proposed on top of VHM to support global end-to-end routing. To our best knowledge, this is the first work that realizes truly deterministic routing with constant-bounded storage and computation in general 3D wireless sensor networks.