esa-sceva/satcom-chunk-collection huggingface dataset:
# RBF Neural Network Based Backstepping Control for an Electrohydraulic Elastic Manipulator
###### Abstract  
An electrohydraulic elastic manipulator (EEM) is a kind of variable stiffness system (VSS). The equilibrium position and stiffness controller are the two main problems which must be considered in the VSS. When the system stiffness is changed for a specific application, the system dynamics are significantly altered, which is a challenge in controlling equilibrium position. This paper presents adaptive robust control for controlling the equilibrium position of the EEM under the presence of the variable stiffness. The proposed control includes sliding mode controls (SMCs), radial basis function neural network (RBFNN), and backstepping technique. The RBFNN is employed to compensate for the uncertainties and the variant stiffness in mechanical dynamics and hydraulic dynamics. The Lyapunov approach and projection algorithm are used to derive the adaptive laws of the RBFNN and to prove the stability and robustness of the entire EEM. Finally, some experiments are implemented and compared with other controllers to prove the effectiveness of the proposed method with the variant stiffness.  
electrohydraulic system; sliding mode control; backstepping control; variable stiffness; projection algorithm; RBF neural network +
Footnote †: journal: Applied Sciences
###### Abstract  
Variability of sea surface temperature (SST), characterized by various spatiotemporal scales, is a proxy of climate change. A network analysis combined with empirical mode decomposition is newly presented for examining scale-dependent spatial patterns of SST variability. Our approach is applied to SST anomaly variability in the East/Japan Sea (EJS), consisting of satellite-derived daily datasets of 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) resolution from 1981 to 2023. Through the spatial distribution of instantaneous energy in intrinsic modes and features of intrinsic-mode networks, scale-dependent spatiotemporal features are found. The season-specific spatial pattern of energy density is observed only for weekly to semiannual modes, while a persistent high-energy distribution in the tongue-shaped region from East Korea Bay (EKB) to the Sub-Polar Front (SPF) is observed only for annual-to-decadal modes. The seasonality is apparent in the time evolution of energy only for weekly-to-annual modes, with a peak in summer and an increasing trend since the 2010s. Hubs of intrinsic-mode networks are observed in the whole southern area (some northern part) of EJS during the summer (winter), only for monthly to semiannual modes. Regional communities are observed only for weekly to seasonal modes, while there is an inter-basin community with annual-to-biennial modes, incorporating two pathways of East Sea Intermediate Water (ESIW).  
sea-surface-temperature anomaly; empirical mode decomposition; intrinsic mode; complex network theory +
Footnote †: journal: Applied  
1 Kyungpook Institute of Oceanography, Kyungpook National University, Daegu 41566, Republic of Korea; [EMAIL_ADDRESS]  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
## 2 Experimental Setup and Methodology
### Optimization of Imaging Performance Through Calibration and Scanning  
To enhance system performance, meticulous optical alignment and calibration were performed. Initial trials focused on refining the orientation and placement of the GDD within the established 8 \(\times\) 8 scanning matrix, strategically configured in the image plane to maximize both resolution and accuracy. The GDD detection circuit was mounted on motorized linear stages, facilitating precise vertical and horizontal raster scanning to ensure comprehensive coverage of the target area. This controlled scanning mechanism allowed the system to generate an 8 \(\times\) 8 grayscale image that accurately delineated the boundaries and internal structure of the metal square.  
Iterative adjustments to the positioning and scanning patterns were critical in improving image clarity, resulting in well-defined, high-quality millimeter-wave images. A notable challenge encountered involved maintaining the alignment of the reference signal, which needed to consistently direct at the GDD throughout the entire scanning process. The design necessitated the reference signal to correspond with each pixel value of the object-reflected signal; however, limitations in the alignment of the second mirror posed significant difficulties. To address this issue, a sequential part-by-part imaging approach was employed across various mirror positions to approximate full coverage of the image plane.  
This sequential imaging technique enabled data capture in segmented areas, ensuring that reference alignment was preserved, which provided continuous range data across the entire image. Although this method introduced additional complexity to the data acquisition process, it ultimately allowed for complete depth capture by cycling the reference alignment across all pixels.
# Computationally Efficient Channel Estimation in 5G Massive Multiple-Input Multiple-output Systems
## 3 Low Complexity Signal Detection
### Gauss-Seidel Algorithm  
In the Neumann series expansion algorithm, when the number of expansion terms \(i\geq 3\), the computational complexity is still \(O\left(K^{3}\right)\), which is equal to or even exceeds the complexity of the exact inverse calculation of the MMSE filter matrix. Unlike the Neumann series expansion, which approximates \(W\), the GS algorithm [19] can solve N-dimensional linear equations of the form \(Ax=b\) without inverting the matrix, where matrix \(A\) is an \(N\times N\) dimensional symmetric positive definite matrix, \(x\) is the \(N\times 1\) dimensional solution vector, and \(b\) is the \(N\times 1\) dimensional measurement vector. Decomposing matrix \(A\) into a diagonal element matrix, \(D_{A}\), a strict lower triangular element matrix, \(L_{A}\), and a strict upper triangular element matrix, \(L_{A}^{H}\), the GS algorithm can estimate \(x\) by the following iterative method:  
\[\hat{x}^{\ (i)}=\left(D_{A}+L_{A}\right)^{-1}\left(b-L_{A}^{H}\hat{x}^{(i-1)}\right) \tag{12}\]  
where \(i=1,\ 2,\dots\) represents the number of iterations of the GS algorithm. In a massive MIMO system, as the number of base station antennas increases substantially, when it is much larger than the number of single-antenna users (\(N\gg K\)), the individual column vectors of the uplink channel matrix \(H\) are progressively orthogonal [20], and \(W=G+\sigma^{2}I_{2K}\) is a symmetric positive definite matrix. Similarly, \(W\) can be decomposed into:  
\[W=\left(D+L+L^{H}\right) \tag{13}\]  
Among those terms, \(D\), \(L\), and \(L^{H}\), respectively, is the diagonal element matrix of \(W\), the strict lower triangular element matrix, and the strict upper triangular matrix. The GS algorithm can be used to avoid inverting the high-dimensional matrix, which directly estimates the transmitted signal vector \(\hat{s}\):  
\[\hat{s}^{(i)}=\left(D+L\right)^{-1}\left(\hat{y}-L^{H}\hat{s}^{(i-1)}\right) \tag{14}\]  
where \(\hat{s}^{(0)}\) represents the initial solution and is usually set to a zero vector.
# Research Needs for Realization of Zero-Carbon Power Grids with Selected Case Studies
## 4 Additional Research
### Energy and Capacity Adequacy
#### 4.1.2 Metrics and Calculation Methodologies  
In a 100% renewable electricity system, the bulk of investment is a capital expense, primarily driven by energy requirements and the adequacy of capacity [85, 86]. VRE sources contribute to both of these. However, their contribution decreases as the VRE proportion increases, as for most types of energy. The decreases are marked mainly because the characteristics of VRE sources are inherently correlated but can thus be mitigated via the diversification and creation of large geographical footprints. In other words, grid operators should invest in diverse and less-correlated VRE sources [87], and in energy storage and demand-side participation, thus ensuring the adequate energy and capacity without overinvestment. Note that demand-side participation does affect the adequacy, although in a rather unidirectional manner; electricity is transformed into another form of energy that is not re-transformed back to electricity. Consequently, as the VRE proportion rises to 100%, grid operators must re-examine their classical adequacy metrics (e.g., the loss of load and the expected unserved energy) and update adequacy calculation methodologies; metrics and methods that consider wind and solar PV are rather well developed but not widely applied in practice.  
Classical metrics are inappropriate when energy storage systems are adequate and the loads are both flexible and responsive. Given more flexible resources and more demand-side participation in a zero-carbon power grid, the adequacy metrics need to be updated to reflect the needs regarding critical loads, consumer types, and network sizes, for example [88]. The LOLP and LOLE are rather arbitrarily employed without consideration of the requirements, and the expected unserved energy (EUE) may be more meaningful if energy limitations become more dominant than capacity limitations. The LOLP and EUE are useful if a large proportion of demand is totally inflexible--i.e., demand must be served. If enough demand is flexible and responsive, the classical metrics recede and should be replaced by new metrics. There is also a need for more rigorous methods of adequacy calculation; adequacy should be ensured at a minimal cost and rewarded in a market setting (or otherwise) without overinvestment. The classical adequacy problem is then replaced by a cost minimization problem, wherein the grid investment cost is balanced with the cost of energy storage system installation and reductions (or shifts) in consumer load demands.
## 4 Security Proofs
### Unlinkability
For \((m,\delta,\sigma,\gamma,s)\in\{(m_{0},\,\delta_{0},\,\sigma_{0},\,\gamma_{0}, \,s_{0}),\,(m_{1},\,\delta_{1},\,\sigma_{1},\,\gamma_{1},s_{1})\}\) and \((\alpha_{i},\,\beta_{i},\,t_{i})\), \(i\in\{0,1\}\), there always exists a pair \((r^{\prime}_{i},b^{\prime}_{i})\) such that \(H\) can compute \(r^{\prime}_{i}=(\alpha_{i}F^{2}_{1}(m)^{-1})^{d_{H}}\) mod \(n_{H}\) via (1) and \(b^{\prime}_{i}=(\beta_{i}F_{2}(\delta,\sigma,\gamma)^{-1})^{d_{H}}\) mod \(n_{H}\) via (2). Thus, (3) is satisfied owing to \(t_{i}=(\alpha_{i}\beta_{i})^{d_{H}}\) mod \(n_{H}\) and \(s\equiv(F^{2}_{1}(m)F_{2}(\delta,\sigma,\gamma))^{d_{H}}\pmod{n_{H}}\). From the above, given any \((m,\,\delta,\,\sigma,\,\gamma,s)\in\{(m_{0},\,\delta_{0},\,\sigma_{0},\,\gamma _{0},\,s_{0}),\,(m_{1},\,\delta_{1},\,\sigma_{1},\,\gamma_{1},s_{1})\}\) and \((\alpha_{i},\,\beta_{i},\,t_{i})\), \(i\in\{0,1\}\), there always exists a corresponding pair \((r^{\prime}_{i},b^{\prime}_{i})\) such that Equations (1)-(3) are satisfied. Hence, considering Step 6 of the game, \(H\) successes in determining \(b\) with probability \(\frac{1}{2}\). We have that \(P[b^{\prime}=b]=\frac{1}{2}\) and \(Adv^{Linkability}_{H}(k)=0\). Therefore, the proposed scheme satisfies the unlinkability property.
# Improving the Solving of Optimization Problems:
## 3 Quantum-Compliant Problem Formulations  
### Ising  
The Ising formulation [20] is a physical-mathematical model used in statistical mechanics to describe phase transitions in ferromagnetic systems. It represents magnetic dipoles as binary variables, \(+1\) (spin-up) and \(-1\) (spin-down), arranged in a lattice structure with interactions. Initially proposed for a one-dimensional chain, it was extended to two dimensions by [PERSON] in 1944.  
Its energy function, known as Hamiltonian, includes the following:  
* An external field term \(h\), whose sign determines the preferred spin orientation and the magnitude reflects the strength of the spin's contribution to the total energy.
* An interaction term between neighboring spins \(J\), due to the influence of the magnetic field generated by each magnetic dipole on its neighbors, which can be either aligned or counter-aligned, with the strength depending on its magnitude.  
The Ising Hamiltonian is expressed as follows:  
\[H(\mathbf{s})=\sum_{i=1}^{N}h_{i}s_{i}+\frac{1}{2}\sum_{i=1}^{N}\sum_{j=1,j \
eq i}^{N}J_{ij}s_{j}\,, \tag{1}\]  
where \(N\) is the total number of spins, \(s_{i}\) is \(i\)th spin, \(h_{i}\) is the external field coefficient of the \(i\)th spin, and \(J_{ij}\) is the interaction coefficient between the \(i\)th and \(j\)th spins.  
Minimizing this Hamiltonian is generally NP-hard, except for special cases, such as planar 2D graphs without external fields [21].  
The Ising model, extensively studied with computational methods like Monte Carlo simulations, is widely used for solving CO problems, where the ground state represents the optimal solution. Any CO problem can be recast into the Ising framework, as any binary-variable objective function can be reduced to a second-order polynomial, matching the Ising Hamiltonian, at the expense of introducing auxiliary variables.
# Design and Evaluation of Flexible Support Based on Space Mirror
## 4 Analysis and Evaluation
### Modal Analysis  
Modal analysis is also critical to theoretically evaluate the design rationality, and the analysis results can objectively reveal the mechanical characteristics of the structure and assess the vibration response of such structure under mechanical load.  
Modal analysis theory is a recognized technique to determine the vibration characteristics of a structure, by which mass frequencies, vibration, and mode-participation coefficients can be determined. Performing a modal analysis at the primary stage of the design allows the structure to avoid resonating or vibrating at a specific frequency, allows the designer to find out how the structure responds to different types of dynamic loads, and helps to estimate the control parameters in other dynamic analyses.  
Obtaining the fundamental frequency of the structure before the component is machined, and optimizing the design, ensuring that it avoids forced vibrations during launch and transportation, enables avoidance of structure damage caused by the occurrence of resonance phenomena.  
By simulation, the first four order modes of the overall mirror components are shown in Table 4 with analysis results demonstrated in Table 5. Based on the stimulation result, the first-order modal of the mirror components reached 179.6 Hz, which has a higher stiffness compared with the mirror components among a similar size.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{3}{c}{First order of vibration modes} & Second order of vibration modes \\ \hline \hline \multicolumn{3}{c}{Third order of vibration modes} & Fourth order of vibration modes \\ \hline \hline \multicolumn{3}{c}{} \\ \hline \hline \end{tabular}
\end{table}
Table 4: Four vibration modes of the mirror component.  
Figure 7: Finite element model of mirror component.
###### Abstract  
The aim of this work is to investigate the main dominant terms of lunisolar perturbations that affect the orbital eccentricity of a Molniya satellite in the long term. From a practical point of view, these variations are important in the context of space situational awareness--for instance, to model the long-term evolution of artificial debris in a highly elliptical orbit or to design a reentry end-of-life strategy for a satellite in a highly elliptical orbit. The study assumes a doubly averaged model including the Earth's oblateness effect and the lunisolar perturbations up to the third-order expansion. The work presents three important novelties with respect to the literature. First, the perturbing terms are ranked according to their _amplitudes_ and _periods_. Second, the perturbing bodies are not assumed to move on circular orbits. Third, the lunisolar effect on the precession of the argument of pericenter is analyzed and discussed. As an example of theoretical a application, we depict the phase space description associated with each dominant term, taken as isolated, and we show which terms can apply to the relevant dynamics in the same region.  
M +
Footnote †: journal: _Journal of the Royal Society Interface_  
doi:10.3390/universe7120482
## 2 Materials and Methods  
### The Fabrication of Flexible Pressure Sensor Materials  
The fabrication process of the flexible sensors mainly refers to reference [54], with the material and equipment information detailed in Table S2 in the supplementary document. Figure 1 illustrates the main fabrication workflow of preparing flexible pressure sensor materials. In the production of polyester (120.32 g/m\({}^{2}\), twill weave), chemical lubricants are often added to enhance the fiber's spinnability, necessitating the washing of the polyester fibers. Initially, a 2 g/L solution of detergent 209 is prepared, followed by ultrasonic washing for 30 min at a bath ratio of 1:50, and then rinsed with deionized water. After washing, the sample is dried in an oven at 80 \({}^{\circ}\)C. Next, a precise amount of polydimethylsiloxane (PDMS) is dissolved in anhydrous ethanol and accurately weighed on an electronic balance. The solution undergoes 10 min of ultrasonic stirring to ensure thorough mixing. The cleaned fabric is then cut to the specified dimensions, immersed in the PDMS solution, and subjected to ultrasonic impregnation for 10 min at 30 \({}^{\circ}\)C. This process is repeated three times, followed by drying at 60 \({}^{\circ}\)C. The sample prepared using this method is designated PET-d-PDMS. Subsequently, plasma is conducted using a plasma device with an RF power source set at 13.56 MHz, employing capacitively coupled plasma (CCP) discharge. Argon gas is utilized, with adjustments made to the gas pressure (30 Pa), discharge power (100 W), and discharge time (20 s). The sample obtained from this step is labeled PET-g-PDMS. Next, 2 g of multi-walled carbon nanotubes (MWCNTs) is added to 100 mL of anhydrous ethanol, and probe ultrasonication is performed at 20 kHz for 2 h. The resulting dispersion is gently centrifuged at 2000 rpm for 20 min to remove any free MWCNTs.  
The pretreated PET fabric is then immersed in the CNT dispersion for 30 min, dried in an oven at 60 \({}^{\circ}\)C, and subsequently cured by applying an alternating current (AC) electric field (ctp2000 k) between two electrode plates until the anhydrous ethanol completely evaporates. Finally, the fabric is cured and dried again at 60 \({}^{\circ}\)C. Now, the material preparation for the flexible pressure sensor is complete. The assembly and structure of the flexible pressure sensor will be introduced in Section 2.2.
# An Effective and Efficient Adaptive Probability Data Dissemination Protocol in VANET
## 5 Concluding Remarks and Future Work  
In this work, an accurate hybrid based dissemination protocol was designed called EEAPD. The goal is to minimize the so-called \"broadcast storm problem\". The EEAPD protocol is designed to be more effective and efficient only for safety applications. For this circumstance, EEAPD is considered as beaconless scheme and takes into account the number of road segments in determined which node is suitable for rebroadcasting the message. By using the \"redundancy ratio\" metric, each node is able to identify the surrounding neighboring vehicles' density. With the proposed protocol, simulation results show the proposed protocol performed better than SEAD, AddP, delay-based and S1 PD considered some performance metrics in which EEAPD provides a high packet delivery ratio with low end-to-end delay since it reduces the number of forward nodes (reduce broadcast messages) hence \"link load\" by default reduced and increase network capacity. The findings show that the proposed protocol configuration setting is practically achieved in realistic vehicular environment architecture (V2V) within a fixed number of road segments. In a realistic environment when the road segments increase, more network topology is connected hence the reliability of data dissemination operates simultaneously in the safety application. The simulation was performed to prove the effectiveness and efficiency of the proposed protocol in a realistic environment. Future work includes the EEAPD protocol in a scattered network since there is frequently a vehicle connectivity problem and the use of mathematical models to address the EEAPD parameterization.  
Conceptualization, J.S.; formal analysis, S.H. and T.T.; funding acquisition, T.T.; methodology, J.S.; project administration, D.W.; software, J.S.; supervision, D.W.; validation, S.H.; writing--original draft, J.S.; writing--review and editing, J.S.  
This work is supported by the National Natural Science Foundation of China (61370201), Open Research Found from the Key Laboratory for Computer Network and Information Integration (Southeast University, Ministry of Education, China).  
I would like to take this opportunity to thank all anonymous reviewers and editor for their useful comments/suggestions and contributions of this paper. I also thankful to my friends who help me a lot in the completion of this paper.  
The authors declare no conflict of interest.