esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Solid Model
### Numerical Verification  
To verify the performance of the present model, the natural frequencies obtained were compared with those results reported in the literature. It must be noted that the numerical comparisons correspond to shells with uniform thickness. In addition, a comparison is included with results obtained by using linear solid elements (SOLID185). The latter allows us to verify the behavior of the present model for shells with thickness variation. In the following comparisons, the natural frequencies obtained by means of the present model are indicated by the label 7-PL. On the other hand, the label 3D represents the results obtained using solid elements in the commercial code ANSYS. Tables 1-3 present a comparison for conical, cylindrical, and parabolic shells, respectively. The natural frequencies obtained using the present formulation show very good agreement with the ones reported in the literature and the ones computed by means of solid elements in ANSYS. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & & & & & & & & & \\ \cline{3-10} \(n\) & **Model** & \(f_{1}\)**–\(f_{2}\)** & \(f_{3}\)**–\(f_{4}\)** & \(f_{5}\)**–\(f_{6}\)** & \(f_{7}\)**–\(f_{8}\)** & \(f_{9}\)**–\(f_{10}\)** & \(f_{11}\)**– & \(f_{13}\)**– & \(f_{15}\) \\ \hline  & 7-PL & 206.20 & 225.98 & 279.08 & 318.23 & 348.99 & 355.98 & 398.53 & 444.36 \\
0.6 & 3D * & 205.93 & 226.02 & 279.55 & 318.32 & 348.57 & 356.80 & 397.36 & 444.55 \\  & FSDT [22] & 205.96 & 225.52 & 277.93 & 318.18 & 349.48 & - & - & - \\ \hline  & 7-PL & 205.12 & 224.88 & 277.82 & 316.39 & 347.13 & 354.42 & 396.71 & 441.88 \\
1 & 3D * & 204.79 & 224.81 & 278.08 & 316.47 & 346.59 & 354.94 & 395.26 & 442.02 \\  & FSDT [22] & 204.91 & 224.44 & 276.66 & 316.32 & 347.66 & - & - & - \\ \hline  & 7-PL & 204.19 & 228.16 & 285.59 & 309.64 & 346.64 & 366.47 & 404.55 & 434.38 \\
5 & 3D * & 203.69 & 227.75 & 285.14 & 309.65 & 345.64 & 365.74 & 402.10 & 434.30 \\  & FSDT [22] & 203.93 & 227.67 & 284.26 & 309.57 & 347.08 & - & - & - \\ \hline \hline \end{tabular}  
* 1,188,000 SOLID185 elements.  
\end{table} 
Table 1: Comparison for a conical shell with UT and CF boundary conditions (FG-II). In addition, Table 4 shows a comparison of the vibration modes for a parabolic shell with uniform thickness and with a volume distribution of the type FG-I. A very good coincidence is observed in the depicted modes. Moreover, similar modes were reported in [23]. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{8}{c}{**Vibration Mode**} \\ \cline{2-9}  & \(f_{1}\)–\(f_{2}\) & \(f_{3}\)–\(f_{4}\) & \(f_{5}\)–\(f_{6}\) & \(f_{7}\) & \(f_{8}\)–\(f_{9}\) & \(f_{10}\)–\(f_{11}\) \\ \hline \multirow{4}{*}{7-PL} & 114.15 Hz & 157.94 Hz & 161.82 Hz & 186.26 Hz & 195.78 Hz & 202.13 Hz \\  & & & & & & & \\ \cline{1-1} \cline{2-9}  & 113.98 Hz & 157.87 Hz & 161.79 Hz & 186.15 Hz & 196.02 Hz & 201.99 Hz \\ \cline{1-1} \cline{2-9}
3D & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Vibration mode comparison for a parabolic shell with UT and SF boundary conditions, \(n=5\) (FG-I).
# Application of Machine Learning Tools for Long-Term Diagnostic Feature Data Segmentation
## 5 Simulated Data Analysis
### Signal Simulation for Gaussian and Non-Gaussian Noise  
The variance for Gaussian noise is time varying; its increase may be described as a linear or exponential function according to Equation (4). Simulation of degradation data in the presence of Gaussian noise is shown in Figure 5.  
Figure 5: Input simulated data for Gaussian noise. (**a**) deterministic component, (**b**) random component, (**c**) simulation of the signal  
For a non-Gaussian case, the symmetric \(\alpha\)-stable distribution is selected as an example of heavy-tailed, non-Gaussian distribution [41; 69; 70; 71; 72].  
The \(\alpha\)-stable distribution is defined by its characteristic function, and it is characterized by four parameters: \(\alpha\) (stability), \(\beta\) (skewness), \(\sigma\) (scale) and \(\mu\) (location). However, for the symmetric case, it is assumed \(\beta=\mu=0\), and the corresponding characteristic function takes the form  
\[E[\varepsilon^{iIX}]=\exp\{-\sigma^{\alpha}|t|^{\alpha}\}. \tag{5}\]  
The \(\alpha\) is known as the stability index and takes values in the interval \((0,2]\). It should be noted that the \(\alpha\)-stable distribution reduces to the Gaussian distribution when \(\alpha=2\). In the case of decreasing \(\alpha\) value, the distribution is significantly different from the Gaussian distribution [73]. In the presented simulation study, we assume the stability index is equal to 1.8.  
Exemplary simulated data with non-Gaussian distributed noise are shown in Figure 6.
# Monitoring of [PERSON]'s Disease Based on Wireless Sensing Technology
## 3 Principle of Wireless Sensing Technology
### Msp  
The MSP independently developed in this paper works in C-band (4.8 GHz). It is a highly customizable platform that can adapt to different application scenarios. MSP consists of omnidirectional antenna, industrial personal computer, absorbing material, frequency converter, and other related facilities. The use of absorbing materials is mainly to shield the surrounding environment from interference. The main function of MSP is to obtain the CSI of the wireless channel. By analyzing the CSI data, the behavior of patients can be monitored.  
MSP uses OFDM technology. Its essence is an OFDM transceiver system, and its functional block diagram for obtaining CSI is shown in Figure 2.  
In Figure 2, \(d(k)\) is converted to N parallel data \(\{x_{0},\)\(x_{1}\),..., \(x_{N-1}\}\) through serial-parallel conversion. These data can be regarded as N data in the frequency domain. A set of time domain data  
Figure 2: Block diagram of microwave sensing platform (MSP) to obtain channel state information (CSI) data.  
\(\{s_{0}\), \(s_{1}\),..., \(s_{N-1}\}\) obtained after the inverse discrete Fourier transform (IDFT) is an OFDM symbol. After adding a cyclic prefix to an OFDM symbol, the OFDM symbols are transmitted on the wireless multipath channel after parallel-serial conversion and digital-analog conversion. At the receiving end, the reverse work is performed: analog-digital conversion, parallel-serial conversion, removing cyclic prefix, and fast Fourier transform (FFT). The training sequence after FFT is used to perform channel estimation according to Equation (5), and CSI data can be obtained.
# Performance Evaluation of Machine Learning Methods for Anomaly Detection in CubeSat Solar Panels
## 2 Materials
### Dataset Overview  
The dataset contains solar panel data of Tsuru satellite (from March 2021 to November 2021). It includes 16,704 temperature, current, and voltage data points from the satellite panels. Additionally, the dataset consists of 8439 samples from Nepalisat, Raavana, and Uguisu Satellites (from June 2019 to October 2020). Please refer to TSURU.xlsx, NEPAL-ISAT.xlsx, RAAVANA.xlsx and UGUISU.xlsx in Supplementary Materials section. The satellites use the sensors described in Table 1.  
Figure 3: EPS block diagram with power distribution.  
Figure 2: Solar panel with two cells connected in series.  
The BIRDS team operators periodically execute the High Sampling Sensors Data Collection Mission (HSSC) to obtain the data during one orbit. Subsequently, the team downloads housekeeping data to the ground station. The sampling rate is 10 s for the Tsuru satellite and 5 s for Nepalisat, Raavana, and Uguisu Satellites.
# An Investigation of Parameter Dimension Reduction Optimization of PMA-Synrm
## 4 Experimental Verification  
Based on the above optimization results, a prototype of a 7.5 kW, 1500 rpm permanent magnet-assisted synchronous reluctance motor was fabricated. The prototype structure is shown in Figure 18.  
The prototype is tested experimentally, and the data of no-load and load of the motor are shown in Figure 19. It can be seen from Figure 19a that when the motor is running at the rated load, the measured load current is 13.5 A, and the simulated load current is 13.2 A. Figure 19b shows the curve of no-load back EMF. When the prototype is running at no-load, the measured no-load back EMF is 76.1 V, which is 1.27 V lower than the simulated value. In addition, the optimized prediction value, finite element calculation results, and prototype test results are summarized in Table 9. It can be seen that the three results are not much different. It can be further proved that the parameter dimension reduction optimization method proposed in this paper can ensure the accuracy of the optimization results while reducing the optimization parameters and improving the optimization efficiency.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter Name** & **Initial Value** & **Predicted Value** & **Simulative Value** & **Error** \\ \hline Current (A) & 13.6 & 13.3 & 13.4 & +0.1 \\ Output torque (Nm) & 50.2 & 50.1 & 49.7 & \(-\)0.4 \\ Torque ripple (\%) & 15.6 & 4.6 & 4.8 & +0.2 \\ No-load back EMF (V) & 85 & 77.52 & 77.37 & \(-\)0.15 \\ Core loss & 147.6 & 130.4 & 134.2 & +3.8 \\ Power factor & 0.925 & 0.914 & 0.910 & \(-\)0.004 \\ Efficiency (\%) & 93.5 & 94.15 & 94.1 & \(-\)0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 8: The optimization results of permanent magnet-assisted synchronous reluctance motor are compared with finite element results.  
Figure 19: Prototype test data and calculation data curve. (**a**) No-load back EMF curve. (**b**) Rated-load current curve.  
Figure 18: Permanent magnet-assisted synchronous reluctance motor rotor structure diagram.
# Advanced Cooperative Formation Control in Variable-Sweep Wing UAVs via the MADDPG-VSC Algorithm
## 3 Cooperative Control of Variable-Sweep Wing UAV via MADDPG
### Optimization of the MADDPG-VSC Algorithm for Control Design
#### 3.2.4 Adaptive Sweep Angle Control Strategy  
The MADDPG-VSC algorithm employs an adaptive sweep angle control strategy, dynamically adjusting the sweep angle in response to real-time flight parameters. This strategy is critical for optimizing UAV formation control, as it allows for adjustments that enhance aerodynamic efficiency and overall mission success. By dynamically responding to changes in velocity, altitude, and other flight conditions, the algorithm ensures that UAV formations maintain optimal configurations throughout various flight states.  
This adaptive approach not only improves trajectory planning and obstacle avoidance but also significantly enhances overall UAV performance in diverse and challenging task scenarios. By integrating these techniques, the MADDPG-VSC algorithm provides a robust and flexible solution for cooperative UAV formation control in complex environments.
# An Overview of Privacy Dimensions on the Industrial Internet of Things (IIoT)
###### Abstract  
The rapid advancements in technology have given rise to groundbreaking solutions and practical applications in the field of the Industrial Internet of Things (IIoT). These advancements have had a profound impact on the structures of numerous industrial organizations. The IIoT, a seamless integration of the physical and digital realms with minimal human intervention, has ushered in radical changes in the economy and modern business practices. At the heart of the IIoT lies its ability to gather and analyze vast volumes of data, which is then harnessed by artificial intelligence systems to perform intelligent tasks such as optimizing networked units' performance, identifying and correcting errors, and implementing proactive maintenance measures. However, implementing IIoT systems is fraught with difficulties, notably in terms of security and privacy. IIoT implementations are susceptible to sophisticated security attacks at various levels of networking and communication architecture. The complex and often heterogeneous nature of these systems makes it difficult to ensure availability, confidentiality, and integrity, raising concerns about mistrust in network operations, privacy breaches, and potential loss of critical, personal, and sensitive information of the network's end-users. To address these issues, this study aims to investigate the privacy requirements of an IIoT ecosystem as outlined by industry standards. It provides a comprehensive overview of the IIoT, its advantages, disadvantages, challenges, and the imperative need for industrial privacy. The research methodology encompasses a thorough literature review to gather existing knowledge and insights on the subject. Additionally, it explores how the IIoT is transforming the manufacturing industry and enhancing industrial processes, incorporating case studies and real-world examples to illustrate its practical applications and impact. Also, the research endeavors to offer actionable recommendations on implementing privacy-enhancing measures and establishing a secure IIoT ecosystem.  
identity privacy; location privacy; footprint privacy; multidimensional privacy; privacy; privacy threats; privacy principles +
Footnote †: journal: _Algorithms_
# Impacts of Lightning-Induced Overvoltage on a Hybrid Solar PV-Battery Energy Storage System
###### Abstract  
With increased electrical energy demands projected in the future, the development of a hybrid solar photovoltaic (PV)-battery energy storage system is considered a good option. However, since such systems are normally installed outdoors and in open areas, they are vulnerable to lightning strikes and may suffer from malfunctions or significant damage to sensitive components, which may result in a major breakdown and loss of revenue due to equipment replacement costs and inefficient operation. Thus, the objective of this paper is to investigate the effect of lightning-induced overvoltage on a hybrid solar PV-battery energy storage system, considering indirect lightning strikes nearby the system. The presented hybrid solar PV-battery energy storage system and lightning-induced overvoltage are modeled in Electro-Magnetic Transient Program-Restructured Version (EMTP-RV) software. The lightning-induced overvoltage is simulated based on a lightning waveshape of 10/350 \(\upmu\)s using the Heidler expression, whilst the Rusck model is used to simulate the lightning-induced overvoltage. Different lightning current amplitudes (3, 19, and 169 kA), lightning strike locations (20, 50, and 100 m), and cable lengths (5, 10, and 20 m) are used to investigate the induced effects on the system and on the impulse withstand voltage of 6 kV, as stated in MS IEC 60664-1 for solar PV-battery systems and inverters at the DC side. The results indicate that as the lightning strike distance increases from 20 to 100 m, the percentage of strikes exceeding the impulse withstand voltage reduces from 67% to 54% at 19 kA. At 169 kA, the impulse withstand voltage is exceeded by more than 100%, regardless of the strike distance (from 20 to 100 m). Furthermore, differences in cable length do not have much impact on the lightning-induced overvoltage due to the small voltage drop across the short cable length. This study provides useful information for PV systems owners and will be useful in assigning appropriate lightning protection schemes for PV farms.  
hybrid solar PV; battery energy storage; indirect lightning effect; lightning-induced overvoltage; EMP-RV
# First-Principles Study for Gas Sensing of Defective SnSe\({}_{2}\) Monolayers
## 5 Conclusions  
In summary, the adsorption of NO\({}_{2}\) and NH\({}_{3}\) on the Se-vacancy, O-doped and N-doped SnSe\({}_{2}\) monolayer are investigated and compared to the pristine SnSe\({}_{2}\) monolayer. Due to the high adsorption energy and large charge transfer of gas adsorption on the Se-vacancy SnSe\({}_{2}\) monolayer, the Se-vacancy SnSe\({}_{2}\) monolayer shows a better sensitivity only to NO\({}_{2}\). However, the sensitivity of NH\({}_{3}\) adsorbed on the Se-vacancy SnSe\({}_{2}\) monolayer has higher adsorption energy but lower charge transfer amount than the pristine SnSe\({}_{2}\) monolayer. Furthermore, the O-doped SnSe\({}_{2}\) monolayer has similar interaction with NO\({}_{2}\) with the pristine SnSe\({}_{2}\) monolayer, but weaker interaction with NH\({}_{3}\) than the pristine SnSe\({}_{2}\) monolayer. This indicates that the O-doped SnSe\({}_{2}\) monolayer has similar sensitivity to the pristine SnSe\({}_{2}\) monolayer and better selectivity than the pristine SnSe\({}_{2}\) monolayer. The N-doped SnSe\({}_{2}\) strongly interacts both with NO\({}_{2}\) and NH\({}_{3}\) and shows obvious sensing enhancement for those two gases. In brief, the vacancy and doped SnSe\({}_{2}\) monolayers can enhance the selectivity and sensitivity of gas sensing for NO\({}_{2}\) and NH\({}_{3}\) molecules. This work demonstrates the potential of the SnSe\({}_{2}\)-based gas sensors by introducing defects and dopants in the SnSe\({}_{2}\) monolayer.  
The following are available online at [[http://www.mdpi.com/2076-3417/10/5/1623/s1](http://www.mdpi.com/2076-3417/10/5/1623/s1)]([http://www.mdpi.com/2076-3417/10/5/1623/s1](http://www.mdpi.com/2076-3417/10/5/1623/s1)): Figure S1: The initial configurations of the defective SnSe\({}_{2}\) monolayers adsorbing NO\({}_{2}\) molecule with N-top and N-bottom orientations, Figure S2: The initial configurations of the defective SnSe\({}_{2}\) monolayers adsorbing NH\({}_{3}\) molecule with N-top and N-bottom orientations.  
W.-Y.C.: Data curation, Data analysis, writing - original draft & review & editing; H.-R.F.: Conceptualization, writing - review & editing; C.-R.C.: Supervision, Writing - review & editing. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Ministry of Science and Technology of R. O. C. under grant No. MOST 107-2112-M-002-013-MY3.  
[PERSON] thanks for supports from Ministry of Science and Technology of R. O. C. under grant No. MOST 107-2112-M-002-013-MY3. [PERSON] thanks for supports from Ministry of Science and Technology of R. O. C. under grant No. MOST 107-2112-M-155-001-MY3. [PERSON] and [PERSON] thanks the computer and information networking center in National Taiwan University, Taiwan for the computational support.  
The authors declare no conflict of interest.
## 3 Background
### Optimization Variable
#### 3.3.1 Scheduler Policy  
Inside the Linux kernel, there are five scheduler policies currently defined: NORMAL(CFS), FIFO, RR, BATCH, and IDLE [16]. STUN can change these policies using schedtool, a tool provided by Linux, without having to reboot the server.  
* **SCHED_NORMAL (CFS)** This is the default scheduler policy of the Linux kernel. The purpose of CFS is maximizing the overall CPU utilization and providing fair CPU resources for all tasks. CFS is based on each CPU run queue, the tasks of which run in order of the virtual runtime and are kept sorted by red-black trees.
* **SCHED_FIFO** As a fixed-priority scheduling policy, each task is executed with a priority value of 1 to 99, and it is a policy that preempts and executes CPUs in the order of high priority.
* **SCHED_RR** This is basically the same operation as SCHED_FIFO, although each task has a time quantum value, which is the maximum time of execution, and when the time quantum is expired, the task is switched to the next task in a round robin manner.
* **SCHED_BATCH** This policy is suitable for batch jobs. By avoiding preemption by other tasks, we can run a task longer and leverage the hardware cache better than other policies; however, this works poorly for interactive tasks.  
* **SCHED_IDLE** This policy operates in a non-interactive manner, similarly to SCHED_BATCH. However, differing from SCHED_BATCH, SCHED_IDLE can be performed when other processes are idle.
# Wearable Inertial Devices in Duchenne Muscular Dystrophy: A Scoping Review
## 2 Methodology
### Search Schemes  
Starting from the main questions, four different fields were identified for the formulation of suitable keywords according to the PICOS framework: (1) Population; (2) Intervention; (3) Comparison; and (4) Outcome. The search focused on patients affected by Duchenne muscular dystrophy and articles dealing with pediatric populations were included in the review without any cultural, gender, race, or age restrictions. Due to the principal question on the use of wearable inertial sensors for the identification of meaningful outcomes, the intervention was identified in the experimental application of IMUs for the monitoring and evaluation of patients' motor performance, without any limits on the environment. Studies dealing with the comparison of results with a control group and those focusing on the comparison with other neuromuscular diseases were included in the analysis. No restrictions were imposed on the objective outcomes obtained with the sensors. Moreover, clinical functional scales were not included in the keywords to avoid too many strict restrictions. The following keywords were defined:  
* Duchenne muscular dystrophy, neuromuscular disease;
* Wearable, inertial systems, IMU, accelerometer, gyroscope, magnetometer;
* Outcome measures.  
The following search string was formulated: \"((duchenne OR duchenne muscular dystrophy OR neuromuscular disease)) AND ((wearable) OR (inertial) OR (imu) OR (accelerometer) OR (gyroscope) OR (magnetometer)) AND ((outcome))\".  
For the article selection, the Scopus, Web of Science, and PubMed electronic databases were explored. The search strategy and search string used for all three databases were the same. The three lists of articles were uploaded on Mendeley and all duplicates were automatically eliminated.
## 2 Materials and Methods
### Data Acquisition and Processing
#### 2.2.4 Precipitation and Temperature Data  
Precipitation and temperature data were obtained from TerraClimate [49], a global land surface monthly climate and climate water balance dataset with a spatial resolution of 4638.3 m and a monthly temporal resolution. In this study, precipitation and temperature data for May-August 2019 in Tianjin were downloaded from Google Earth Engine (GEE). The data resampling and clipping pre-processing based on the bilinear interpolation method were performed in QGIS 3.22.1 software. Finally, the raster data of accumulated precipitation and average temperature of each month with a spatial resolution of 10 m were obtained.