esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 The Standard PTP
### PTP Issues  
The synchronization rule of the standard PTP is that the BC node prevents the loop of the messages inside the network by converting several ports of the node into passive-state ports based on the BMC algorithm, as shown in Figure 2. In this case, the node receives the timing information through a single slave port and it distributes the local clock timing information through multiple master ports toward the remaining networks. The main drawback of the standard PTP operation is that it does not provide a protection mechanism for the occurrence of link failure and/or MC failure. Consequently, the slave ports that have been separated from the synchronized network start listening for an Announce message from the MC for a specified duration called an Announce-Receipt-TimeOut; afterwards, the slave ports are converted into a master state port that represents the root of the synchronization hierarchy of the isolated network. Hence, the node distributes the local clock timing information toward the remaining connected networks.  
The timing accuracy of the isolated node's local clock is deteriorated by the link failure and the master failure occurrences in the network. Specifically, the fault occurrence causes the clock time drifting of the isolated nodes, which affects the synchronization of the network and reduces the reliability and the availability of PTP systems. This problem degrades the network performance and it may cause network delay. For this reason, we propose a TFR approach to solve the fault occurrence issue in PTP systems.
# A Parallelized Database Damage Assessment Approach after Cyberattack for Healthcare Systems
## 5 Experimental Results
### Experimental Setup  
All algorithms tested below were implemented using the Java programming language, specifically version 1.8.0_45. For connection to the database, the mysql.mysql-connector-java library (version 8.0.21) was used. For measuring the memory consumption of specific objects, the com.carrotsearch.java-sizeof library (version 0.0.5) was used. The code was packaged along with all dependencies using Apache Maven version 3.6.1 into a jar file, which was then run on the different algorithms and with different malicious transaction IDs.  
The environment of simulation had a Windows 10 operating system with an Intel(r)Core(tm) i7- 4700 MQ 2.40 GHz CPU with 4 cores and 16 GB of RAM. For the database, XAMPP was used to run a MySQL (version 15.1 distribution 10.4.13-MariaDB) DBMS on which the database was loaded before running each test. The different malicious transaction IDs tested were as follows: 1, 20, 50, 100, 150, 200, 400, 600, 800, and 1000. Since the time taken by the algorithm may have differed due to the load on the system, the response time of the database, and cores available, among other factors, all the algorithms ran 10 times for each malicious transaction ID. Among those runs, the best, worst, and average time were recorded. The memory required was generally not affected by other factors and hence had one reporting, which was the same for all runs.  
The number 10 was chosen to ensure that other factors mentioned above, such as other processes on the system, availability of cores, or database response time, did not greatly affect the reported results or provide a disadvantage to some algorithm. We understand that when measuring small units such as microseconds, the results may vary between runs, so we assume the average time reported to be the most accurate comparison. Going beyond 10 runs did not considerably change the reported results.
# Performance Analysis of Undifferenced NRTK Considering Time-Varying Characteristics of Atmosphere
## 2 Positioning Model of BDS Undifferenced NRTK
### Mathematical Model for Ambiguity Fixing of Reference Stations
Afterwards, the variance covariance matrix \(Q_{LL}\) of the DD observation values is obtained by transformation matrix \(T\), and the weight matrix \(P_{LL}\) of the observation equation can be expressed as:  
\[P_{LL}=\sigma_{0}^{2}/Q_{LL}= \begin{bmatrix}p_{11}&p_{12}&p_{13}&p_{14}\\ p_{21}&p_{22}&p_{23}&p_{24}\\ p_{31}&p_{32}&p_{33}&p_{34}\\ p_{41}&p_{42}&p_{43}&p_{44}\end{bmatrix}  \tag{28}\]  
Finally, the normal equation for integer ambiguity resolution can be formed by Equations (26) and (28) and is:  
\[\left\{B^{T}\cdot P_{LL}\cdot B\right\}\cdot X=B^{T}\cdot P_{LL}\cdot E\{L\} \tag{29}\]Expanding the normal equation by parameter type can be expressed as:  
\[N\cdot X=W\Rightarrow \begin{bmatrix}N_{\tau\tau}&N_{\tau I}&N_{\tau\tau}\\ N_{\tau I}&N_{II}&N_{Int}\\ N_{nT}&N_{nI}&N_{nm}\end{bmatrix} \cdot \begin{bmatrix}\
abla\Delta t\\ \Delta t^{s}_{r}\\ \Delta N\end{bmatrix} = \begin{bmatrix}W_{1}\\ W_{2}\\ W_{3}\end{bmatrix}  \tag{30}\]  
The \(N\) in the normal equation is completely independent of the observation, and is only related to the coefficient matrix of the observation, which is also called the design matrix, and is directly related to the geometric conditions of satellite distribution. A well-designed satellite constellation configuration will ensure the \(N\) matrix has good properties and improve the strength of the equation, while the \(W\) on the right side of the equation is closely related to the design matrix and the observation error, which is a comprehensive reflection of both. It can be seen from the normal equation that positioning accuracy depends on two aspects: the geometric distribution of satellites and the accuracy of observation. To improve the positioning accuracy, comprehensive consideration should be given to these two aspects.
# Experimental Comparison of Editor Types for Domain-Specific Languages
###### Abstract  
The editor type can influence the user experience for a domain-specific language, but empirical evaluation of this factor is still quite limited. In this paper, we present the results of our empirical study, in which we compare the productivity of users with different kinds of editors for the same domain-specific language. We chose the domain of quiz definitions and used three editors: a text editor with syntax highlighting and code completion developed with the Xtext framework, a projectional editor created using JetBrains MPS, and an existing form-based editor--Google Forms. The study was performed on 37 graduate students of computer science. The measured time was lower for the text editor than for the form-based editor, and the form-based editor's time was lower than the projectional one's; however, the results were statistically insignificant. The experiment was also complemented with a survey providing insight into the perception of different editor types by users.  
domain-specific languages; text editor; projectional editor; form-based editing; experiment 202220220220220220220220220220222022202220  
There are some recommendations on the use of different language notations, and some of their trade-offs are known (e.g., [6]). Another, different aspect of DSLs is the language implementation approach: implementing a language from scratch or using language workbenches that simplify language definition, either with classical parsing technologies (e.g., Xtext or Spoofax) or with projectional and graphical editing (e.g., JetBrains MPS, or MetaEdit+). A discussion of the advantages and shortcomings of such approaches for language designers already exists [7]. However, we are not aware of any human-based empirical study comparing different editor kinds from the DSL user's point of view.  
The main goal and the contribution of the presented work is, therefore, an experimental evaluation of different types of editors for domain-specific languages. We have conducted experiments where we compared three editors for the same DSL:  
1. _A text editor_ with syntax highlighting and code completion based on Eclipse IDE (Xtext);
2. _A projectional editor_ based on JetBrains MPS;
3. _A form-based web editor_.  
Our hypothesis for the experiment was that the choice of the editor type would have a significant impact on the language users' productivity.  
While the scope of the experiment was quite limited and does not allow us to make definitive conclusions, it provides useful insights into the efficiency of using different kinds of editors for DSLs.
# Numerical Validation of the Radiative Model for the Solar Cadaster Developed for Greater Geneva
## 2 Materials and Methods  
### Modeling Approaches for Radiative Transfers  
Two main methods are commonly used for the evaluation of radiative transfers: ray-tracing-based models or radiosity methods. Their principles, as well as their advantages and drawbacks, are described in the following.
# Satellite-Aided Consensus Protocol for Scalable Blockchains
## 6 Evaluation  
In this section, we evaluate the proposed satellite-aided consensus protocol from throughput and security aspects. We establish a satellite-aided blockchain simulation system according to the proposed protocol. (Please see github.com/xtling/SatelliteChain for the source code.) In our setting, terrestrial miners form a peer-to-peer network with the same winning probability and the same transmission outage from space. In Figures 4-6, simulation results are shown by markers, whereas analytical curves are illustrated by dashed lines. We require \(k=6\) blocks to confirm a block, and normalize the throughput by the mining network capacity \(C\).  
In Figure 4, we illustrate the throughput and security of the proposed protocol in the presence of one adversary. One can see that the simulation results (markers) match our analytical throughput and security results (dashed lines). As shown in Figure 4, both space and terrestrial safety levels (\(\beta_{s}\) and \(\beta_{t}\)) compromise the security of the whole blockchain. However, to manipulate the blockchain, an adversary must control a vast number of resources \(\beta=\beta_{s}+\beta_{t}-\beta_{t}\beta_{s}>\frac{1}{2}\) in the mining network.  
In Figure 5, we compare the proposed satellite-aided consensus protocol with PoW as a benchmark. The throughput and security properties of PoW have been presented in [11; 41], respectively. The proposed consensus protocol can achieve much higher throughput than PoW with comparable safety property as PoW. Moreover, one can see that the throughput of the satellite-aided blockchain depends heavily on the quality of satellite multicast channels, which is consistent with the remarks in Section 5.1.  
Figure 4: Analytical and simulation results of throughput and safety property of the proposed protocol.  
In Figure 6, we demonstrate the impact of network propagation factor \(i_{\Delta}\) on blockchain throughput. The analytical results (lines) based on the Markov model is closely matched by simulations (markers). As shown in Figure 6, the network propagation delay leads to more orphaned blocks and degrades the network throughput by a factor \(1/\left(1+\left(1-i_{\Delta}\right)h\right)\) shown in Equation (9). As a guideline for practical design, for a given network with \(i(t)\), we must systematically optimize the block size \(B\) and round slot \(\Delta\) to obtain a proper \(i(\Delta)\) for higher throughput.
## 4 Numerical Experimental Simulation and Analysis
### Algorithm Performance Analysis
#### 4.3.4 Comparison of the Convergence Performance in the Matrix Solving Process  
Due to the prevalence of sparse matrices in practical applications, which significantly affect the stability of the matrix solving process, oscillations often occur during iterative solving. Specifically, the residual values during iteration do not maintain a monotonically decreasing trend and may exhibit occasional spikes or inverse biases. The presence of such oscillations indicates poor disturbance resistance in the linear system, leading to larger responses to potential perturbations, thereby impacting the efficiency and stability of the linear system.  
Optimizing the matrix condition number and structure using preconditioning can mitigate these oscillations during the iterative process. Both the convergence performance and stability during the solution process are illustrated in Figure 7 for numerical experiments involving four matrices. It is important to note that for a better comparison during the iteration process, the shown solution iteration processes do not necessarily correspond to those with the fastest solving times and thus may not directly reflect the solving times discussed in the previous section.  
Without preconditioning, the residuals in the matrix iteration process frequently exhibit abnormal fluctuations, resulting in extremely large values--an indication of oscillation. This makes the matrix iteration convergence process less stable. The root cause of this oscillation is the high condition number of the matrix, i.e., the matrix is \"ill-conditioned\", making it highly sensitive to small perturbations in input data, which amplifies numerical errors during the solving process, affecting both efficiency and convergence performance.  
After applying G-Pre and ILU preconditioning, the matrix condition numbers were reduced, and the iteration process became more stable, leading to an improved convergence performance. As shown in the condition number comparisons, G-Pre further reduced the number of iterations by factors of 2.4 and 5.2, respectively. Additionally, when combined with the solving time comparisons, it was evident that G-Pre did not show a significant advantage in Matrices 1 and 2. However, the reduction in the number of iterations also led to a decrease in solving time. It should be noted that the speedup ratio in terms of the number of iterations did not directly translate to the speedup ratio in solving time. This is because the number of iterations in the solving process is not linearly related to time; fewer iterations merely indicate a better convergence performance.  
Figure 6: Comparison of the distribution of matrix plots before/after G-Pre preconditioning. (**a–d**) Matrices 1-4. The left side is the distribution of matrix plots before G-Pre preconditioning, and the right side is the distribution of matrix plots after G-Pre preconditioning.
## 2 Materials and Methods
### Optimized LC-Q-TOF-MS Conditions  
LC-Q-TOF-MS was performed using an Agilent 1290 Infinity II LC system (Agilent Technologies, Santa Clara, CA, USA) coupled with an Agilent 6545 XT Q-TOF-MS system (Agilent Technologies, Santa Clara, CA, USA) to examine analyte fragmentation. The mobile phase consisted of (A) 10 mM ammonium formate in water containing 0.1% formic acid and (B) ACN-MeOH (80:20, \(\it{v}\)/\(\it{v}\)). The gradient was as follows: 0-4 min (B: 5-40%), 4-6 min (B: 40-70%), 6-8 min (B: 70-95%), 8-10 min (B: 95%), 10-12 min (B: 95-5%), and 12-15 min (B: 5%). The injection volume and flow rate equaled 1 \(\upmu\)L and 0.3 mL/min, respectively. The other MS parameters were as follows: ion source = ESI, capillary voltage = 3500 V, gas temperature = 300 \({}^{\circ}\)C, nebulizer = 45 psi, drying gas (N\({}_{2}\)) = 10 L/min, fragmentor = 175 V, and skimmer = 65 V.
## 4 Convergence Analysis of the Revised CIM-PNMCC
### Mean Square Convergence (MSC)
 \tag{45}\]  
In Equation (45), \(\varphi\left(n\right)\), \(\mathrm{E}\left[\tilde{\mathbf{w}}\left(n\right)\right]\), and \(\mathrm{B}\left(n\right)\) are all bounded. Thus, \(\mathrm{E}\left[\tilde{\mathbf{w}}\left(n\right)\mathrm{B}^{T}\left(n\right)\right]\) is converged. Then, the CIM-PNMCC is stable when  
\[\left|1-\frac{2\chi_{1}tr\left[\mathbf{G}\left(n\right)\right]\mathrm{E} \left[f\left(e\left(n\right)\right)\right]\varphi_{x}^{2}}{N\sigma_{x}^{2}+ \epsilon_{\mathrm{CM}}}+\left(N+2\right)\frac{\chi_{1}^{2}tr\left[\mathbf{G} ^{2}\left(n\right)\right]\mathrm{E}\left[f^{2}\left(e\left(n\right)\right) \right]\sigma_{x}^{4}}{\left(N\sigma_{x}^{2}+\epsilon_{\mathrm{CM}}\right)^{2 }}\right|<1. \tag{46}\]  
By solving the Equation (46), we can get the range of \(\chi_{1}\)  
\[0<\chi_{1}<\frac{2\left(N\sigma_{x}^{2}+\epsilon_{\mathrm{CM}}\right)tr\left[ \mathbf{G}\left(n\right)\right]\mathrm{E}\left[f\left(e\left(n\right)\right) \right]}{\left(N+2\right)tr\left[\mathbf{G}^{2}\left(n\right)\right]\mathrm{ E}\left[f^{2}\left(e\left(n\right)\right)\right]\sigma_{x}^{2}}. \tag{47}\]
# Pido: Predictive Delay Optimization for Intertidal Wireless Sensor Networks
## 4 Design of Pido
### Performance Evaluation of Pido
#### 4.4.4 Delay Evaluation
The reason is when the disconnection time is 240 cycles, nodes are more likely to suffer two tidal periods during the transmission process, and the waiting time increases up to double disconnection time (240 \(\times\) 2), which is even longer than 300 and 360 cycles. In general, Pido reveals robustness in variant system conditions, which indicates Pido can be utilized in intertidal areas with variant tidal periods for data collection. **Energy consumption:** Though Pido decreases the system latency efficiently, inevitable consequence is higher energy consumption than other energy efficient routing protocols. As discussed above, energy consumption during the sleep mode is same with different routing protocols. We set the retransmission limit as 10 for all three algorithms and the energy consumption during the under-water period is also the same. Here, we compare the energy consumption of these three routing protocols by counting the average transmission times of packets during the above-water period in the simulation, and the result is shown in Figure 9. We test energy consumption in variant network sizes from 49 to 225 with a tidal period of 360 cycles. In Figure 9, the energy consumption of Pido and ORW are similar, and are higher than CTP, which is consistent with the analytical results in Section 4.4.1. The additional energy consumption increases with an average of 15.47% when comparing Pido with CTP (10.73% with a network size of 49 and 21.77% with a network size of 225). Recall that, in Figure 8b, when system tidal period is 360 cycles, Pido can save up to 73% average delay when the network size is 225. Based on this, we consider the additional energy consumed by Pido is acceptable in a delay-priority system.
## 4 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Algorithms**} & \multicolumn{2}{c}{**Before Bayesian Optimization**} & \multicolumn{2}{c}{**After Bayesian Optimization**} \\ \cline{2-5}  & **Hyperparameter** & **Values** & **Hyperparameter** & **Values** \\ \hline \multirow{8}{*}{LSTM} & Units 1–4 & 16, 32, 64, 128 & Units 1–4 & 550, 715, 146, 216 \\  & return\_sequences & True & return\_sequences & True \\  & Dropout 1–4 & 0.2 & Dropout 1–4 & 0.2, 0.6, 0.4, 0.4 \\  & Optimizer & Rmsprop & Optimizer & Rmsprop \\  & Loss & Categorical\_crossentropy & Loss & Categorical\_crossentropy \\  & Batch size & 80 & Batch size & 80 \\  & LeakyReLU & 0.2 & LeakyReLU & 0.2, 0.8, 0.01, 0.01 \\ \hline \multirow{8}{*}{1D-CNN} & Filters & 32, 64, 128, 256, 512 & Filters & 670, 347, 948, 268 \\  & Kernel size & 3 & Kernel size & 3 \\  & Padding & same & Padding & same \\  & LeakyReLU & 0.001 & LeakyReLU & 0.002, 0.001, 0.001, \\  & Pool size & 3 & Pool size & 3 \\  & Strides & 2 & Strides & 2 \\  & Dropout & 0.2 & Dropout & 0.3, 0.7 \\  & Loss & Categorical\_crossentropy & Loss & Categorical\_crossentropy \\  & Batch size & 80 & Batch size & 80 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Parameters of Hyper parameter tuning of LSTM and 1D-CNN.
## 3 The Proposed SP-IoUAV Model
### Intrusion Detection System (IDS)  
As part of our proposed model for detecting and preventing intrusions in the Internet of UAVs ecosystem, the IDS is a critical component. Within the UAV network, it efficiently identifies threats and abnormalities.
###### Abstract  
The traditional source uses a square wave with a fixed fundamental frequency to excite transient electromagnetic (TEM) fields, with harmonic energy primarily concentrated in the low-frequency range, limiting the detection resolution of the TEM. The differential pulse, composed of two square waves with identical pulse widths but opposite polarities, concentrates harmonic energy more effectively. By adjusting the pulse width of the differential pulse, the concentration frequency band of harmonic energy can be changed, enabling multi-resolution detection of geological structures at different depths. In this study, TEM fields are excited using differential pulses of varying pulse widths during power supply. A preconditioned precise integration time-sweeping wavefield reverse transformation method is applied to interpret the virtual wavefield from the diffusion field, effectively improving the numerical accuracy and noise resistance of the virtual wavefield. Then, the finite-difference migration imaging method is used to obtain imaging profiles for differential pulses of different pulse widths, and stacking techniques are applied to acquire high-resolution characteristics of electrical interfaces at various depths. Finally, the feasibility of the method is verified through a complex geological model. By comparing the relative anomalies of square waves and differential pulses with different pulse widths, the results show that the electromagnetic anomalies for differential pulses are increased by 53.7%. Therefore, using differential pulses as the excitation source leads to higher-resolution electromagnetic responses, which in turn result in high-resolution imaging.  
t +
Footnote †: journal: applied sciences  
e1 State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering, China University of Mining and Technology, Xizhou 221116, China; [EMAIL_ADDRESS]
# Dual-Band MIMO Antenna for n79 and sub-7 GHz Smartphone Applications
## 3 Results and Discussion
### Radiation Pattern  
In order to have detailed information on the radiation behavior of the antenna, the far-field radiation patterns at 4.7 GHz and 6.7 GHz for the E-plane and H-plane are illustrated in Figure 7. When measuring these parameters and also when simulating the system, one of the ports is excited with 50 \(\Omega\) impedance. The proposed antenna has near-stable radiation patterns of the omnidirectional kind in the H-plane at 4.7 GHz and 6.7 GHz. Consequently, the E-plane radiation pattern at GHz is bidirectional, and, therefore, a distinct and coherent pattern is easily displayed. But when the resonance is achieved at 4.7 GHz, the E-plane radiation patterns seem distorted. The deformation in the structure does not have any severe effects in terms of the overall radiation performance of the antenna. These observations suggest that the antenna can function with a favorable level of radiation across the examined frequency bands, as required for practical use. The steady H-plane patterns prove the usefulness of the antenna for applications that demand omnidirectional coverage, and the E-plane characteristics at various frequencies help in understanding the directional pattern of the antenna and behavior at the higher frequency. The 3D radiation pattern is presented in Figure 8.  
Figure 6: Transmission coefficient of proposed ten-port MIMO antennas.  
Figure 7: Simulated and measured E- and H-planes.