esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Application of Marine Accident Occurrence Prediction Model and Results
### Reduction in MTSA-Related Accidents upon Implementation of MTSA
#### 5.5.3 MTSA-Related Accident Reduction Rate Calculation  
In this study, the MTSA-related accident occurrence predictive model was employed to learn the probability of MTSA-related accident occurrences using the SMOTE dataset U. Subsequently, the number of cases of accidents before the application of MTSA (BNA) was derived by applying this probability to Data R in 2022. In addition, the annual average number of MTSA-related accidents from 2017 to 2022 near the sites where MTSA was implemented was defined as the expected number of MTSA-related accidents after the implementation of MTSA (ANA), and it was then calculated. These values were then used to calculate the ARR defined in Section 3.5 according to Equation (1), and the findings are presented in Table 13.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**BNA** & **ANA** & **Calculation Result (\%)** \\ \hline
2.01 & 1.66 & 17.41\% \\ \hline \hline \end{tabular}
\end{table}
Table 13: Calculation result of the MTSA-related accident reduction rate.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number (i)** & **Predicted Values (P)** & **Correction Factor (C)** & **BNi** \\ \hline
1 & 0 & & \\ \hline
2 & 0.01 & & \\ \hline
51 & 0.04 & & \\ \hline
101 & 0.16 & & \\ \hline Total & 2.51 & 0.80 & 2.01 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Predicted number of accident cases.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**2017** & **2018** & **2019** & **2020** & **2021** & **2022** & **Mean** \\ \hline Number of accidents & 4 & 1 & 1 & 2 & 1 & 1.66 \\ \hline \hline \end{tabular}
\end{table}
Table 12: Annual number of cases of MTSA-related accidents after application of MTSA (ANA).
## 3 Simulation and Experimental Results
### Effect of the Filter Optical Characteristics on the Combining Efficiency  
The deduced equations (Equations (16)-(18)) show that the spectra of the incident channels and the reflectance curve of the edge filter play a dominant role in achieving the combining efficiency. According to the above discussion and analysis, the reflectance curve is affected by the surface roughness, the thickness error, and the angle of incidence, and thus, a further discussion and analysis was included, to introduce the impacts of these factors on the combining efficiency. Figure 7a shows the measured normalized spectrum from a 1070 nm laser and a 1090 nm laser at full power. The broad linewidth of each channel (The full width at half maximum is over 4 nm) influences the steepness of the reflectance curve, and the rising edge of the filter must be within the range of 1080 nm-1085 nm, in order to achieve a high efficiency of combination. The simulation results of the combining efficiency as a function of the surface roughness are shown in Figure 7b. As expected, a greater surface roughness results in an increase of the scattering, and this subsequently leads to a decline in the combining efficiency. Apart from the aspect of scattering, the enhancement of the surface roughness also causes a shift in the position of the reflectance curve, and the rising edge tends to be gentler, which further aggravates the decline in the combining efficiency. Therefore, the combining efficiency shows a significant negative correlation with the surface roughness, especially when the surface roughness is more than 1 nm. In  
Figure 5: The reflectance curves of the edge filter with various random errors on each layer of the stack: (a) 0.1%-0.3%; (b) 0.4%-0.6%.  
Figure 6: The simulation and experimental results of the reflectance curves under different incident angles: (a) \(s\) polarization; (b) \(p\) polarization.  
general, the combining efficiency of a valid beam combination system should exceed 94%, and in this case, the surface roughness of an edge filter, when used in a 10-kW-class FSBC system, should be within 1.2 nm.  
Figure 8a shows the relationship between the combining efficiency and the thickness error. When the thickness error lies in the range of 0-0.25 nm, the combining efficiency is almost constant, and the maximum value is 97%. In other cases, the combining efficiency shows a significant negative correlation with the thickness error, especially when the error is greater than 0.25 nm. For the case of the incident angle, an obvious decrease in the combining efficiency could be observed with the increasing incident angle (shown in Figure 8b). Hence, to achieve a high combining efficiency, the thickness error of such an edge filter should be limited to within 0.25 nm, and a small incident angle is necessary. We have conducted a spectral beam-combining experiment with an incident angle of 2.5\({}^{\circ}\), and the measured combining efficiency at full power is 95.8%, which is consistent with the simulation result.
# The eIDAS Regulation: A Survey of Technological Trends for European Electronic Identity Schemes
## 3 RQ1: Authentication Mechanisms Based on LoA
### Authentication Mechanisms: LoA Low  
The authentication mechanisms at this level ensure that the subject controls an authenticator registered to the service, requiring single-factor authentication. Based on our analysis (see Table 2, column 2), 12 out of 40 notified eID means under analysis support the LoA Low, and all of them use \"Login with Password\" as the authentication method (i.e., based on what you know and consisting of a combination of a valid and unique identifier (username) and a secret pass-phrase (password)). Some of them (4 eID means) offer the \"Login with QR code\" (that will be discussed in the LoA substantial section) as an alternative to password-based authentication. Figure 3 represents this alternative option for the Poste ItalianeID mean. The main reason behind this implementation choice is to provide additional security and, more importantly, usability. Indeed, first of all, it removes the demand to remember the username and password. Secondly, it provides a smoother user experience that demands scanning a QR code using the citizen's pre-registered device and providing a PIN or using biometrics (e.g., touch ID or face ID).  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**MS**} & \multirow{2}{*}{**ID**} & \multicolumn{2}{c}{**LoA**} & \multicolumn{4}{c}{LoA S} & \multicolumn{4}{c}{LoA H} & \multicolumn{4}{c}{**Auth Standard**} & \multicolumn{4}{c}{**Mobile Apps**} \\  & & & \multicolumn{4}{c}{**Authentication**} & \multicolumn{4}{c}{**Mechanisms**} & \multicolumn{4}{c}{**Crypto-Auth**} & \multicolumn{4}{c}{**SSO**} & \multicolumn{4}{c}{**Fed.**} & \multicolumn{4}{c}{**Prot.**} & \multicolumn{4}{c}{**Storage**} \\  &
# Sulfur-Doped Carbon Nanohorn Bifunctional Electrocatalyst for Water Splitting
###### Abstract  
Sulfur-doped carbon nanohorns (S-CNHs) were prepared by an easy one-pot solvothermal process and were employed as efficient electrocatalysts towards water splitting. Initially, oxidation of CNHs followed by thermal treatment with the Lawesson's reagent resulted in the formation of S-CNHs with the sulfur content determined as high as 3%. The S-CNHs were thoroughly characterized by spectroscopic, thermal and electron microscopy imaging means and then electrocatalystycell screened. Specifically, S-CNHs showed excellent activity and durability for both O\({}_{2}\) and H\({}_{2}\) evolution reactions, by showing low overpotential at 1.63 and \(-\)0.2 V vs. RHE for oxygen and hydrogen evolution reaction, respectively. Additionally, S-CNHs showed significantly lower Tafel slope value and lower current resistance compared to oxidized and pristine CNHs for both electrocatalytic reactions. The outstanding electrocatalytic properties and high conductivity, along with the high S-doping level, render S-CNHs a promising bifunctional electrocatalyst for water splitting.  
c 2020; 10.3390/nano10122416
# Accelerated Simulation of Discrete Event Dynamic Systems via a Multi-Fidelity Modeling Framework +
## 5 Applications
### UTV Simulation
#### 5.2.3 Simulation Results  
In this case study, the parameters of the UTV simulation model were set based on real map data and a domestic report to increase the reliability of the simulation results. According to the various number of vehicles, Figure 19 represents the average waiting time of passengers, the average utilization rate of vehicles, and the execution time of the UTV simulation models with different fidelities. The meanings of the high-, low-, and multi-fidelity models are the same as those in the previous case study. The results in Figure 19 demonstrate the effectiveness of the proposed multi-fidelity framework. The execution time of the multi-fidelity model is lower than that of the high-fidelity model while the average waiting time and the average utilization rate are almost the same as those of the high-fidelity model.  
Figure 19: Simulation results for the UTV simulation: (**a**) average waiting time of passengers according to the number of vehicles; (**b**) average utilization rate of vehicles according to the number of vehicles; (**c**) simulation execution time according to the number of vehicles; (**d**) frequency of fidelity exchange in the multi-fidelity UTV model.  
Figure 18: Simulation results to decide the fidelity change point of “_Distance_”: (**a**) Simulation accuracy against the change point; (**b**) simulation execution time against the change point.  
Based on the simulation speedup defined in Section 4.4, applying the proposed framework increases the speed about 1.21 times. Meanwhile, the speedup is lower than in the previous case study because the fidelity change frequency is high in the multi-fidelity UTV model, as shown in Figure 19d (in the UUV simulation, the fidelity change occurs only once). As mentioned previously in Section 4.4, this high frequency increases the overhead for exchanging models and decreases the effectiveness of the framework. Nevertheless, this case study demonstrates that the framework can increase the simulation speed without a significant loss in accuracy and without modifying the simulation engine and other existing models.
## 3 Background and Related Work
### Identity Management  
Within an effective identity security framework, the three activities of identification, authentication, and authorization work together to keep the resources secure. The identification mainly takes place during the provisioning, i.e., the second phase of the identity lifecycle. The identity lifecycle [9] can be adapted from the Deming Cycle [10]. Authentication and authorization, short AuthNZ, provide the user with access to the requested services if the permissions are good enough. The relevant element of the user account lifecycle is the user resp., the digital identity, as shown in Figure 1. The lifecycle includes the following phases:  
**Request:**: The user requests an account at an organization.
**Provisioning:**: The account is provisioned (attributes, roles, and permissions) and assigned to an entity after identification.
**Permissions:**: The permissions are set for the account.  
Figure 1: User account lifecycle based on [9].  
**Authentication and Authorization:**: For accessing resources, such as services or data, the user must first be authenticated, using their identifier and the pre-defined authentication method(s). Then, the service checks the authorization of the user.
**Self-Service and Core Account Management:**: The user can access a self-service to change information, such as MFA methods. At the same time, the user makes use of identity management.
**De-Provisioning:**: In the end, the user account is de-provisioned.  
In the following, we describe the main processes during the usage of an identity, i.e., identification, authentication, and authorization.
# Structural-Missing Tensor Completion for Robust DOA Estimation with Sensor Failure +
## 5 Simulation
### Performance of Source Identifiability  
The source identifiability of using the 4D covariance tensor \(\mathbf{\mathcal{R}}\in\mathbb{C}^{M\times N\times M\times N}\) corresponding to the \(M\times N\) URA \(\mathbb{U}\) can be measured by the Kruskal's condition. Generally speaking, for the 4D tensor \(\mathbf{\mathcal{A}}\in\mathbb{C}^{I_{1}\times I_{2}\times I_{3}\times I_{4}}\) with rank \(R\), its CPD is essentially unique if  
\[R\leq I_{4},\ \ R(R-1)\leq I_{1}I_{2}I_{3}(3I_{1}I_{2}I_{3}-I_{1}I_{2}-I_{2}I_{3}-I _{1}I_{3}-I_{1}-I_{2}-I_{3}+3)/4. \tag{31}\]  
As for the 4D covariance tensor \(\mathbf{\mathcal{R}}\), the maximum of \(R\) can be calculated as 7. This means that a 7 \(\times\) 7 URA can identify up to \(K=7\) sources.  
Based on the above analysis, we validate the source identifiability of the proposed algorithm in Figure 7, where the azimuth and elevation angles of 7 sources are uniformly distributed within \([-50^{\circ},70^{\circ}]\). The SNRs of sources are set to 15 dB and the number of snapshots is fixed at \(T=200\). The proposed algorithm can locate all these sources with high accuracy. Such a finding verifies the source identifiability of the proposed algorithm.  
In addition, we test the performance of the proposed algorithm for 8 sources in Figure 8 with the same simulation settings. Although the analytical result presented in (31) offers the theoretical bound on the maximum number of distinguishable sources, the proposed algorithm is still capable of estimating more sources with slightly lower accuracy, which further highlights its robustness in practical usage.
# Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation
## 2 CO2 Observation, Datasets, Global Related Research
### Ground-Based Observation
#### 2.1.1 TCCON (Total Column Carbon Observation Network)  
The Total Carbon Column Observation Network (TCCON) was established in 2004 as a ground-based network of Fourier Transform Spectrometers (FTS). These instruments record solar spectra to invert and monitor precision greenhouse gas data with the content of atmospheric molecules about CH4, HF, CO2, NO2, etc. Since TCCON can provide accurate measurements (better than 0.25%) and inversion errors within 0.25% [16], the XCO2 data measured by TCCON has been widely used to assess the accuracy of satellite retrievals, providing an essential data validation resource for GHG remote sensing satellites such as OCO-2 and GOSAT.  
TCCON ground-based stations are strategically located around the world to provide long-term monitoring of atmospheric gases. The global distribution of these stations is depicted in Figure 4. In the figure, red dots denote active TCCON stations that measure atmospheric CO2 column concentrations, grey dots indicate stations that have ceased operation, and bright blue dots represent proposed future sites. While these stations offer continuous time series data on atmospheric CO2 concentrations, their sparse distribution limits the data to the regions surrounding each station, leaving gaps in the global and regional time series of CO2 changes.  
Figure 3: The structure of this paper.
## 2 Method
### Experimental Design  
The galvo scanning system of the UV laser device included a two-axis XY scanner (Raylase AG model SS-15) with a Nd:YVO\({}_{4}\) solid-state Q-switched UV laser source (AVIA 355-14; Coherent Inc., Santa Clara, CA, USA) that emits a 355 nm wavelength and whose focal length is 110 mm. The laser parameters of interest in the experiments were laser power output, frequency, and scanning speed. The working distance was 150 mm, which used a defocused laser beam. The scanning speeds were 100 mm/s, 125 mm/s, and 150 mm/s. Laser power output of 1 W, 1.5 W, 2 W, 2.5 W, and 3 W were used for prior experiments, which were done for selecting the range of laser power output with 100 mm/s and 90 k Hz. The results showed the 3 W power output was too powerful and thus impaired the integrity of the printed NiO thin films. The cracks and flakes on the surface caused an open circuit (see Figure 4b). On the contrary, the 1 W laser output had an inefficient effect on sintering NiO nanoparticles in a laser scanning speed 100 mm/s (Figure 4a); thus, thin films remained insulated. The characteristic of these thin films was similar to the electrical property of the furnace-curried NiO thin films at ambient temperature, where the resistances were too high to be measured [21]. Therefore, the laser power outputs were determined to be 1.5 W, 2 W, and 2.5 W. The laser settings are summarized in Table 2, and each setting was executed three times for experimental replications and statistical difference (\(p\) value). The rest of the parameters of the laser system remained the same.  
In order to define the optimal parameters setting from the experiments, the optimized condition was determined as the lowest resistance with the lowest error bar since the short error bar represents low deviation in the same laser parameters setting. Besides electrical analysis, the other characterization analyses of sintered NiO thin films were studied, including the morphology form SEM and confocal microscopy, the XRD pattern  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Laser Parameters** & **Setting** \\ \hline Distance (lens-thin film) & Out of focus (150 mm) \\ \hline Laser power output & 1.5 W, 2 W, and 2.5 W \\ \hline Frequency (kHz) & 90, 105, and 120 \\ \hline Scanning speed & 100 mm/s, 125 mm/s, and 150 mm/s \\ \hline Laser trajectory spacing & 5 \(\upmu\)m \\ \hline \hline \end{tabular}
\end{table}
Table 2: Laser parameters experiments setting.  
Figure 4: (**a**) Microscope photography of 1 W sintered thin film with 100 mm/s laser scanning speed (scale bar 50 \(\upmu\)m). (**b**) microscope photography of 3 W sintered thin film with 100 mm/s laser scanning speed (scale bar 50 \(\upmu\)m).  
for sintering states and defect analyses, these analyses are introduced and further illustrated in the next section.
## 6 Future Research Direction and Discussion  
We recommended the wavelet Bi-LSTM (W-Bi-LSTM) approach [85] to predict the groundwater level. There are two strategies, one is wavelet data decomposition [104; 105; 106; 107] and the second is bi-directional long short-term memory (Bi-LSTM). Satellite-based techniques [108] can be used for groundwater monitoring by measuring changes in the Earth's gravity field and surface deformation caused by water movement underground. Point-to-point satellite-based techniques, such as interferometric synthetic aperture radar (InSAR) and global navigation satellite system (GNSS), can be used to detect changes in ground elevation and surface displacement, which can be used to infer changes in the amount of groundwater. These techniques provide valuable information for managing groundwater resources and mitigating the impacts of groundwater depletion.
###### Abstract  
The decrease of strength after saturation of rocks is known as moisture-induced softening. To date, there are numerous studies on the mechanism of moisture-induced softening of different rocks. However, due to a lack of effective observational methods, the microcosmic mechanism of moisture-induced softening still needs to be understood. We collected and processed acoustic emission (AE) signals during the uniaxial compression test of marble specimens. The results of spectral and statistical analysis show that two dominant frequency bands of AE waveforms exist regardless of the specimen's water content. Additionally, for the AE signals from the saturated specimens, the ranges of the low and high frequency bands are wider than dried rock samples. Besides, since the tensile and shear failures in the rock release low and high dominant frequency AE signals, respectively, the test results of this paper show that micro-shear and micro-tensile failures dominate the final failure of dried and saturated rocks, respectively.  
m arble; moisture-induced softening; acoustic emission; spectrum analysis; microcosmic failure; energy +
Footnote †: journal: Applied Sciences
## 3 Design of Maritime Data Security Management Platform
### Information Service Layer
Ship dynamic information service module;  
The ship dynamic information service module includes the ship information service and the traffic flow analysis service. This module realizes the real-time display of the ship's current position, ship's name, current speed, course and other information in the electronic navigation chart, and different sources of ships are shown with different symbols and different types of ships with different colors. This module also realizes intelligent ship supervision. After binding the corresponding ship, it can automatically display static data, dynamic data and associated data of the ship, such as the type of ship, real-time position, historical track, etc. 3. Maritime security information service module;  
The navigation support information service module realizes the timely release and inquiry of information regarding navigation beacon businesses, surveying and mapping businesses, navigation businesses, navigation books, port information, maritime security-related laws and regulations, international conventions, etc. The system has internal control of the release policy, and the release of all contents can only be granted through the process of approval. The specific process can be customized according to users' business needs, which supports both a simple one-step workflow and a complex approval process. 4. System management module. The system management module implements the permission management of the above three modules. Each service module needs permission to obtain information content. The administrator with management permissions can conduct the configuration management for each published service.
# Study on Band Gap and Sound Insulation Characteristics of an Adjustable Helmholtz Resonator
## 4 Discussion
### Influence of the Spacing of Cells on Band Gap  
The influence of the spacing of cells on low-frequency band gaps was analyzed. In the simulation experiment, the lattice constant \(a\) was increased from 62 mm to 70 mm, and the other structural parameters (\(b\) = 25 mm, \(l\) = 60 mm, \(s\) = 0.35 mm, \(l_{1}\) = 254.8 mm and \(h\) = 24.5 mm) remained unchanged. The effect of the lattice constant \(a\) on band structure was obtained.  
As shown in Figure 12, as the lattice constant \(a\) keeps increasing and the spacing of cells keeps increasing, the upper limits of the first band gap and the second band gap gradually decrease, but the lower limits are basically unaffected. Moreover, the width of the first and the second band gap both gradually decreases. This is because with the increase of the spacing of cells, the volume of the outer cavity keeps increasing, resulting in the decrease of the equivalent stiffness of the air spring of the outer cavity. The lower limits of the band gaps have nothing to do with the air in the outer cavity, so the lower limits are basically unaffected. The result shows that keeping the spacing of cells small is an effective way to increase the width of the band gap.  
Figure 11: The impact of the partition location on band gap.  
Figure 12: The impact of the lattice constant \(a\) on band gap.