esa-sceva/satcom-chunk-collection huggingface dataset:
# Improving Data Communication of Enhanced Loran Systems Using 128-_ary_ Polar Codes
## 2 Materials and Methods
### The Proposed 128-ary Polar Coding Scheme for eLoran
#### 2.2.2 Proposed Demodulation Method
Then, LLR \(L_{1,j}^{(1)}(\mathbf{y}_{i})\) is defined as follows:  
\[L_{1,j}^{(1)}(\mathbf{y}_{i})=ln\frac{W(\mathbf{y}_{i}|0)}{W(\mathbf{y}_{i}|j)}=\frac{y_{i} (j)}{2\sigma^{2}}-\frac{y_{i}(0)}{2\sigma^{2}}, \tag{15}\]  
where \(L_{1,j}^{(1)}(\mathbf{y}_{i})\) is the input of the SCL decoder, with \(L_{1,j}^{(1)}(\mathbf{y}_{i})=0\) if \(\mathbf{y}_{i}=\varnothing\). The Soft-Hard (SH) demodulation method is the simplified version of the SS demodulation method. And in Section 3, we use SH demodulation to work with the RS decoder to make a comparison with the proposed scheme and demonstrate the source of the performance gain. In the SH demodulation method, the first layer of soft demodulation is the same as that in the SS demodulation method. However, the second layer of SH demodulation for each symbol is given as hard decision \(\mathbf{z}(m)\):  
\[\mathbf{z}(m)=\underset{j\in[0,1,\ldots,q-1]}{argmin}\left(\widetilde{y}_{m}(j) \right), \tag{16}\]  
which is then used as the input for the RS decoder. The Hard-Hard (HH) demodulation method is a further simplified version of the SS demodulation method. HH demodulation is also used to work with the RS decoder to make a comparison in Section 3 with the proposed scheme. In the first layer of hard demodulation, let \(\hat{s}_{m,h}\) denote the decided modulation level of \(h\)-th \((h\in\{1,\,2,\ldots,6\})\) pulse. And \(\hat{s}_{m,h}\) is calculated as follows:  
\[\hat{s}_{m,h}=\underset{s\in[0,1,2]}{argmin}\left(\widetilde{y}_{m,h}^{s} \right), \tag{17}\]  
Then, in the second layer of the hard demodulation of HH, the hard decision \(\mathbf{z}(m)\) is obtained as follows:  
\[\mathbf{z}(m)=\underset{j\in[0,1,\ldots,q-1]}{argmin}\left(\sum_{h=1}^{H}\left( \hat{s}_{m,h}-S(h,j)\right)^{2}\right). \tag{18}\]  
which is the input of the RS decoder. In comparison to the HH demodulation method, the traditional eLoran system employs methods with even lower computational complexity, such as the EPD-MD method [8]. And in Section 3, we provide a comparison of the error performance of the 128-\(\it{ary}\) polar code with SS demodulation and the RS code with SH demodulation/HH demodulation/EPD-MD demodulation to explain the source of performance gain.
## 7 Limitations and Challenges
### Complexity in System Integration  
The integration of blockchain systems with existing legacy architectures, procedures, and devices presents significant challenges. At the enterprise level, organizations must either completely redesign their data management systems or develop new, complex interfaces, both of which require considerable investments of time, finances, and expertise.  
At the device level, devices such as those with embedded sensors or those serving as gateways in IoT networks are often not fully compatible with this new schema (seamlessly and constantly generating new records to be stored in blockchain). For instance, [PERSON] et al. highlighted limitations within the iOS architecture, where strict controls on background processes necessitate user intervention for data sharing [24].  
Integration with emerging technologies, such as digital twins, further complicates the landscape. [PERSON] et al. and [PERSON] identified the mandatory looping requirements for optimized event determination within digital twin frameworks, emphasizing the need for significant research and development to achieve seamless interoperability [25; 28].
# Design and Development of Hugging Mechanism for Capturing Chest and Back Auscultatory Sounds
## 1 Introduction
### Contributions  
The major limitation of previous studies is that the examination process is less efficient and more time-consuming than traditional human procedures due to the regulation of the velocity of the robot arm to ensure the patient's safety. To address this limitation, this study aimed to develop a novel robotic auscultation system capable of safely acquiring chest and back auscultatory sounds simultaneously without actuators. The proposed robotic system is equipped with a multi-acoustic sensor array that adapts to the patient's body shape, allowing each sensor to be positioned accurately at the chest and back auscultation points. In order to adapt to the body shape, this study developed a unique actuator-less hugging mechanism that can be transformed to wrap around the chest and back to fit the patient's body shape using only the patient's pushing force, thanks to an articulated arm with multi-layer gear coupling and a cam mechanism for patient power transmission. To the best of our knowledge, this is the first mechanism designed to capture chest and back auscultatory sounds concurrently corresponding to the patient's body shape without any actuators. The superiority of this actuator-less mechanism is that (1) the patient is not harmed by a sensor failure or uncertain control of the actuator and (2) efficient and personalized auscultation can be performed.  
Section 2 introduces the final concept of our robot-assisted auscultation system and the detailed design and implementation of the proposed hugging mechanism. Section 3 represents the experimental results of the performance of the hugging mechanism corresponding to various body shapes, and Section 4 discusses the experimental results and future research directions.
## 3 Results and Discussion
### Assessment of a Modelling Approach with a Quasi-3D Description of the Junction
#### 3.3.1 Time Domain Assessment  
In Figure 15 the results obtained with the quasi-3D description of the junction (labeled MDT Q3D) are compared with those previously shown in Figure 7 corresponding to the MDT with 0D description of the junction. Again the plots on top represent the raw results, whereas the bottom plots show the differences with respect to the experimental values. It can be seen that, in all the cases, a certain improvement is achieved when using the quasi-3D junction, improvement which is more apparent when the junction is excited at port 3, this is, at the side branch, which is intuitively reasonable.  
Again, the mean quadratic errors were computed, as shown in Table 3.  
These results indicate that, while the reflection coefficients exhibit a similar mean error, there is a substantial improvement in the transmission coefficients, thus confirming the previous analysis.  
However, the improvement achieved is not sufficient to produce results comparable to those shown in Figure 8 for the conventional model in the case of the reflection coefficient, and the differences  
Figure 14: Meshes used in the staggered-grid method: (**a**) a 0D description of the junction; (**b**) a quasi-3D description.  
Figure 15: Influence of the description of the junction in the time domain, MDT method: raw data (top) and differences with measurement (bottom). (**a**) Excitation at port 1; (**b**) excitation at port 3. Ports are denoted as in Figure 1.  
in the transmission coefficients are clearly significant only when the junction is excited at the side branch. Therefore, while it appears that further refinement of the mesh at the junction should improve further the quality of the results, this might produce in turn an unacceptable increase in the computation time.
# Signal Enhancement of Helicopter Rotor Aerodynamic Noise Based on Cyclic Wiener Filtering
## 2 Theory  
The operation of rotating machines determines that any type of rotating machine can be modeled with cyclostationary. [PERSON] summarized the research on the cyclostationary mechanism of various rotating machines [14; 15; 16; 17]. Given the periodic motion of the rotor when the helicopter is flying and hovering, the aerodynamic noise of the rotor presents cyclostationarity. However, ambient noise can be filtered out by the cyclic Wiener filter since it is not cyclostationary.
# Magnetocaloric Properties and Critical Behaviour of the Sm\({}_{2}\)Ni\({}_{17}\) Compound
## 3 Results and Discussion
### Critical Phenomenon and Spin Interaction
#### 3.4.2 Kouvel-Fisher Plot
The magnetic equation of state is stated under the scaling assumption in the asymptotic critical area as follows:  
\[M(H,\epsilon)=\epsilon^{\beta}f_{\pm}(H/\epsilon^{\beta+\gamma}) \tag{9}\]  
where \(f_{-}\) for \(T<T_{\rm C}\) and \(f_{+}\) for \(T>T_{\rm C}\) are regular analytic functions. By utilizing the \(\beta\) and \(\gamma\) obtained through the KF method, we plotted the scaled quantity \(M/|\epsilon|^{\beta}\) as a function of \(\mu_{0}H/|\epsilon|^{\beta+\gamma}\), as shown in Figure 13. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Composition** & **Technique** & \(<T_{\rm C}>(K)\) & \(\beta\) & \(\gamma\) & \(\delta\) & **Ref.** \\ \hline Sm\({}_{2}\)Ni\({}_{17}\) & MAP & 160.6(1) & 0.26(1) & 1.38(9) & 6.36(6) & Our Work \\  & KF & 160.5(2) & 0.25(1) & 1.39(6) & 6.50(4) & \\  & CI & 160 & & & 6.64(2) & \\ \hline Mean-field & Theory & - & 0.5 & 1 & 3 & [71] \\
3D Heisenberg & Theory & - & 0.37(1) & 1.39(1) & 4.80(4) & [71] \\
3D Ising & Theory & - & 0.33(1) & 1.24(1) & 4.82(2) & [71] \\
3D XY & Theory & - & 0.35 & 1.32 & 4.81 & [71] \\ Tricritical mean-field & Theory & - & 0.25 & 1 & 5 & [71] \\ \hline Pr\({}_{2}\)Fe\({}_{16}\)Al & MAP & 357.5 & 0.37(1) & 1.34(1) & 4.62(3) & [72] \\  & KF & 358.1 & 0.37(1) & 1.35(1) & 4.67(1) & \\  & CI & 358 & & & 4.72(2) & \\ \hline SmNi\({}_{2.2}\)Fe\({}_{0.8}\) & MAP & 239.5 & 0.38(1) & 1.30(1) & 4.45(4) & [73] \\  & KF & 239.8 & 0.38(1) & 1.30(1) & 4.43(8) & \\  & CI & 239 & & & 4.63(3) & \\ \hline CeCo\({}_{12}\)B\({}_{6}\) & MAP & 128 & 0.39(1) & 1.39(1) & 4.60 & [74] \\  & KF & 128 & 0.37(1) & 1.38(1) & 4.77 & \\ \hline \end{tabular}
\end{table} 
Table 2: The obtained critical exponents of Sm\({}_{2}\)Ni\({}_{17}\) (our work) compared to those obtained for comparable materials and those corresponding to the main universality classes. Figure 12: The critical isothermal magnetization curve against the applied magnetic field. The inset shows the same plot in In–ln scale. The resulting graph shows the collapse of all data into two distinct strands below and above the critical temperature \(T_{C}\). This observation is compelling evidence of our research findings' reliability and robustness. The critical coefficients of our compound obtained in this work together with the theoretical models are compared in Table 2. It can be seen that the experimentally generated coefficients cannot be listed in any of the conventional universality class. The exponent \(\beta\) converges towards the value predicted by the tricritical MFM, while \(\gamma\) exhibits proximity to the value anticipated by the 3D Heisenberg model.
# Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring
## 4 Power Consumption Models  
The proposed power consumption models describe two main operating modes of the sensor: the idle mode and the active mode. In the idle mode, the sensor sends advertisement packets at regular intervals to be discoverable by the PDAs for data acquisition. Active mode, on the other hand, acts as a data collection mode where the MCU collects ECG samples and forwards them to the BLE radio for transmission to the connected PDA. The models are based on the parameters identified in the previous section, i.e, measured during the events that constitute a certain mode, idle or active. The events are, however, standard from the perspective of BLE specification. Different hardware and software  
Figure 8: Current consumption profile of an advertising event.  
implementations of BLE transceivers can have different event power profiles, but the events are equal from the protocol perspective. The only requirement for another BLE sensor platform to use the proposed energy consumption model is to measure the energy consumption for the identified events previously.
# Design of a Compact Planar Magnetic Levitation System with Wrench-Current Decoupling Enhancement
## 4 Control System
### Lookup Table  
Since the wrench-current transformation matrix is a function of the mover pose, the real-time solution of this matrix must be computed for every control sampling. However, numerically computing the Lorentz forces and torque cannot be implemented in real time. Hence, in this work, the wrench-current transformation matrices within a specific range of motion were precomputed and stored in a lookup table.  
To keep the size of the lookup table reasonable while providing sufficient information for the operational space, a 5-D table with a 1 mm grid on both \(x\) and \(y\) axes from \(-10\) mm to 10 mm, 1 mm grid on \(z\) axis from 18 mm to 26 mm, and a 5-degree grid on both \(\psi\) and \(\theta\) axes from \(-10\) degrees to 10 degrees was created. The matrix with corresponding mover  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**DOF**} & \multicolumn{5}{c}{**PID Controller**} \\ \cline{2-6}  & \multicolumn{2}{c}{**P Gain**} & \multicolumn{2}{c}{**I Gain**} & \multicolumn{2}{c}{**D Gain**} \\ \hline \(x\) & 1500 & N/m & 6500 & N/m s & 55 & N s/m \\ \(y\) & 600 & N/m & 3000 & N/m s & 36 & N s/m \\ \(z\) & 900 & N/m & 5000 & N/m s & 40 & N s/m \\ \(\psi\) & 1 & N m & 3.33 & N m & 0.06 & N m \\  & \multicolumn{2}{c}{rad} & \multicolumn{2}{c}{rad s} & \multicolumn{2}{c}{rad/s} \\ \(\theta\) & 1.5 & \multicolumn{2}{c}{N m} & \multicolumn{2}{c}{N m} & \multicolumn{2}{c}{0.09} & N m \\  & \multicolumn{2}{c}{rad} & \multicolumn{2}{c}{rad s} & \multicolumn{2}{c}{rad/s} \\ \hline \hline \end{tabular}
\end{table}
Table 5: Five-DOF PID controller gains.  
pose closest to the current mover pose was returned while searching the lookup table at runtime. This lookup table approach helped reduce the computation cost by sacrificing the controller memory. Only a finite number of mover poses were stored. Therefore, it was inevitable to use lookup results when the operation location was not in the lookup data. By applying a multidimensional linear interpolation approach, the transformation matrix could be estimated for the desired pose instead of using the nearest data.
# A Transfer Reinforcement Learning Approach for Capacity Sharing in Beyond 5G Networks
## 5 Implementation Considerations
The proposed TRL approach for capacity sharing in this paper is included in the _ML model training_ in Figure 8. Once the InP decides to deploy new cells in the RAN, it can  
Figure 8: O-RAN-based system model for capacity sharing and deployment at the edge. activate the TRL capacity sharing training functionality, specifying the value of \(\Delta N\). This functionality will use the knowledge gained from a previously learned policy \(\pi\), which can be obtained from the _ML model repository_, to learn the new policy \(\pi^{\prime}\). When the training of \(\pi^{\prime}\) is completed, this policy can be deployed in the _rApp_ through the R1 interface, replacing the old policy \(\pi\). The disaggregated nature of the O-RAN architecture offers the flexibility to deploy the O-RAN functionalities at different network locations, including far edge nodes (i.e., edge nodes co-located with cells and closer to users), aggregation edge nodes (i.e., edge nodes at an aggregation point of multiple far edge nodes), or the cloud, as described in [34]. The choice of deployment location depends on the requirements of the functionalities in terms of their operating times and geographical scope (i.e., the area where they exert influence or need to gather data). It may also consider the minimization of network data transfer among the transport network, core network, or the cloud to reduce bandwidth requirements and associated costs. Figure 8 also indicates a proposal for the placement of the different components among far edge nodes and aggregation edge nodes, colored in yellow and purple, respectively. Regarding cell-related O-RAN functionalities, the O-DU is deployed in a far edge node, while the O-CU-UP and O-CU-CP can be deployed both at far edge and aggregation edge nodes. Considering that the inference of the _rApp_ containing the DQN-MARL capacity sharing policy does not have stringent real-time requirements, it can be deployed at an aggregation edge node that is close to the different cells managed by the solution and has access to them. The _ML model training_, _ML model repository_, and _ML model monitoring_ functionalities can be located at the same node if it has enough computing power to support them.
# A Review on Vibration Control Using Piezoelectric Shunt Circuits
## 4 Modeling of Dynamical Systems with Piezoelectric Shunt Circuits
### Distributed Parameter Systems
The coupled \((N+1)\) governing equations are expressed as follows:  
\[ \begin{array}{c}\ddot{q}_{n}+2\zeta_{n}\omega_{n}\dot{q}_{n}+\omega_{n}^{2}q_ {n}+\frac{k_{n}}{C^{\epsilon}}\left(\frac{N}{i}k_{i}q_{i}+Q\right)+\sum\limits _{i,j,k}^{N}b_{ijkn}q_{i}q_{j}q_{k}\\ =f_{n}\text{sin}(\Omega t),\;n=1,2,\ldots,\;N\end{array}  \tag{26}\]  
\[\ddot{Q}+2\zeta_{e}\omega_{e}\dot{Q}+\omega_{e}^{2}Q+\frac{1}{LC^{\epsilon}} \frac{N}{i}k_{i}q_{i}=0 \tag{27}\]  
where the electrical natural frequency and damping ratio are defined as follows:  
\[\omega_{e}=\frac{1}{\sqrt{LC^{\epsilon}}},\;\zeta_{e}=\frac{1}{2}R\sqrt{\frac {C^{\epsilon}}{L}} \tag{28}\]  
By applying a frequency sweep, a frequency response plot around the first two modes is obtained as shown in Figure 8. The location of the PZT patch on the beam's root, middle, or tip was found to be significant, as shown in Figure 8. Multiple modes are controlled by using current-blocking circuits [130]. Some comments about the model's assumptions, limitations, and possible future work are summarized below. It is worth noting that the model lacks the real-time analysis of the long-term degradation of piezo materials that can lead to an incorrect assessment of the reliability and efficiency of devices. It is advisable to integrate such effects into models through age functions of material parameters or the introduction of degradation models that depend on time, load, and temperature. Moreover, the effectiveness of piezoelectric shunts is likely to be significantly affected by the geometry of the piezo plates, so it is possible that generalizations without analyzing geometric variability may lead to incorrect conclusions, especially when scaling up systems. Therefore, it is important to integrate this geometry dependence into the model. The above is an opportunity for the future development of mathematical models. The current model accounts for the piezo plate'sgeometry, namely, the plates' length, width, and thickness, as per Equations (24) and (25) that determine the shunt capacitance and the electromechanical coupling coefficient as functions of the geometry, the material of the piezoelectric patch, and the concerned mode of vibration. The question is to what extent does variability in the geometry of piezo plates affect generalized conclusions about their efficiency, especially when scaling up systems? This remains an open research question for future developments.
## 2 Comparison of Long-Term Features
This discrepancy can be justified by a series of factors, among which are the following: overestimation of the slip rate adopted in the seismogenic model (for the CNAFS, it was obtained by the average of a range of values reported by the DISS database); missing the fraction of seismic moment released by earthquakes having a magnitude smaller than 6.5; uncertainty in the magnitude estimate of old earthquakes; lack of large magnitude earthquakes during the first seven centuries over a total period of ten centuries. The same kind of test carried out on the NMTFS exhibits a much better agreement between the synthetic and observed seismic moment, with a difference of the order of 40%, partly justifiable by the omission of events having a magnitude smaller than 7.9. Our results for the NMTFS can be compared with [PERSON] (2023) [28], who used a 3 Dmodel of the Nankai fault system to simulate a 1250-year earthquake sequence, including over 700 Mw 5.5-8.5 events and periods of quiescence followed by aftershocks. Despite differences in the methodology, such as [PERSON]'s use of the G-R law versus our physics-based approach, we found remarkable similarities in the periodicity and timing of strong events in both studies. To analyze the effect of smaller magnitude events on the total seismic moment released by the CNAFS, we have computed the seismic moment after 1000 A.D. for all the 36 earthquakes of magnitude M \(\geq\) 6.0 reported by CPTI ([PERSON] et al., 2022 [19]), 14 of which occurred before 1700 A.D. In this case, we obtained a total of 1.42 10\({}^{20}\) Nm, nearly three times larger than the value obtained for M \(\geq\) 6.5 only. We applied a stacking procedure for analyzing the temporal pattern of seismicity before and after earthquakes of magnitude equal to or greater than a target magnitude M\({}_{\rm pivot}\) (hereafter called pivot event). For each event of M \(\geq\) M\({}_{\rm pivot}\), the catalog was scanned for a time T\({}_{\rm dur}\) preceding and the same time T\({}_{\rm dur}\) following such an event, dividing these two periods in bins of T\({}_{\rm bin}\) length. The events that occurred in the same time bin were considered if their epicenters were within a distance R\({}_{\rm dist}\) from the epicenter of the target earthquake and their magnitudes exceeded a threshold M\({}_{\rm min}\). The procedure was repeated for all M \(\geq\) M\({}_{\rm pivot}\) earthquakes, and all the events found in each bin were analyzed together (see Table 3). Our analysis concerned the following:  
1. The average stress computed on the cells containing the epicenters of all the earthquakes selected in every time bin at their respective origin time;
2. The number of earthquakes selected in every time bin;
3. The b-value of the earthquakes selected in every time bin.
###### Abstract  
The knowledge of the solar irradiation components is required by most solar applications. When only the global horizontal irradiance is measured, this one is typically broken down into its fundamental components, beam and diffuse, by applying an empirical separation model. This study proposes a semi-analytical model for diffuse fraction, defined as the ratio of diffuse to global solar irradiance. Starting from basic knowledge, a general equation for diffuse fraction is derived. Clearness index, relative sunshine, and the clear-sky atmospheric transmittance are highlighted as robust predictors. Thus, the model equation implicitly provides hints for developing accurate empirical separation models. The proposed equation is quasi-universal, allowing for temporal (from 1-min to 1-day) and spatial (site specificity) customization. As a proof of theory, the separation quality is discussed in detail on the basis of radiometric data retrieved from Baseline Surface Radiation Network (BSRN), station Magurele, Romania. For temperate continental climate, overall results show for the diffuse fraction estimation a maximum possible accuracy around 7%, measured in terms of normalized root mean square error. One of the many options of implementing the semi-analytical model is illustrated in a case study.  
solar energy; diffuse fraction; atmospheric transmittance; sunshine duration; clearness index