esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 RT or TMA Coupling a Beam Splitter  
If there is a need to spectrally separate the incoming beam into spectral channels, in either an RT or a TMA optical system, then a beam splitter is inserted between the tertiary mirror and the focal plane, provided that the back focal length is long enough. However, a non-parallel beam (i.e., an optical beam that has a field angle), passing through a plane parallel plate, introduces some lower-order Seidel aberrations, including lateral color [5; 6; 7; 8; 9; 10].  
We (YW) invented a dichroic beam splitter optical element [28] to mitigate the aberrations created by the newly inserted beam splitter. Its position within the optical system is illustrated in Figure 9. The beam splitter in the invention has one plane surface and a phase plate on the second surface. The plane surface, facing the incoming beam, has the required coating to spectrally separate the two spectral bands and reflects half of the incoming beam faithfully, without changing the image quality, into one channel. The phase plate, without the beam-splitting coating, with the basic antireflection coating, features a small wedge and power. Furthermore, some high-order aspheric coefficients are added on top. During the alignment phase, the technician slightly tilts and decenters the beam splitter to remove  
Figure 8: An excellent TMA optical layout is found in Ref. [23] (European Patent EP 0019447). The optical stop is located at element 1 (Item 12); the intermediate focal point (Item 18) also hosts a field stop; and the Lyot stop is Item 22.  
the newly added lower-order aberrations in the transmitting beam. Additionally, some higher-term aberration terms inherited from the parent RT are also reduced. In other words, the image quality of the transmitting channel is slightly better than that of the reflected one.  
A version of an RT, developed for demonstration purposes, is shown in Figure 9. Item 109 is a flat plane mirror, which is used to fold the remaining portion of the optical train along the y-direction, avoiding extra intrusion into the x-direction. Item 111 is the new dichroic beam splitter; Item 121B is the reflected channel (carrying the RT original wavefront error), and Item 121A is the transmitted channel. Its beam quality features reduced wavefront error. By beam splitter design, the transmitted beam quality is better than that in the reflected channel.
## 4 Results and Discussion
### Simulation of the Effects of Rainfall Intensity on Slope Stability
#### 4.5.4 Simulation of Pore Pressure Variation Analysis in Case of Soil Slope  
Exploring the effect of pore water pressure on the stability of the soil slope is one of the critical aspects to assess. Nevertheless, numerical simulation on variation in pore water pressure relative to slope stability with a change in the water table has been simulated. Considering that the previous section focused more on FoS, it is equally important to have a close look at the variation of pore water pressure with change in the water table, as this factor also contributes largely to the generated FoS.  
With reference to Figures 35-38, the simulation has denoted that pore water pressure contour plots were gradual increasing with the increase with water table while the FoS decreases on the other hand. This brings us to talk about the effect of pore water pressure on stress interacting among soil particles as well as reducing the connection between soil particles. In short, the presents and increase in pore water in the pores (or voids) of soil, the pore water pressure generally pushes the soil particles apart and reduces the stress between the particles resulting in soil slope failure. It is well-known that pore water pressure reduces engineering material ( soils) strength by reducing their cohesion and frictional resistance. [PERSON] [40] has evidence the above-mentioned behavior of water pore pressure toward engineering material, the previous documented that the maximum deviator stress decreases as the pore water pressure increases.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Factor of Safety (FoS)**} & \multirow{2}{*}{**Volume of Rainfall (m\({}^{3}\))**} & \multicolumn{2}{c}{**Slope Max Shear Strain**} \\  & & **(Displacement in Shear)** & \\ \cline{3-4}  & & **Minimum Shear Strain** & **Maximum Shear Strain** \\ \hline
1.89 & 1000 & \(2.500\times 10^{-08}\) & \(4.989\times 10^{-07}\) \\
1.72 & 1500 & \(1.0\times 10^{-08}\) & \(2.833\times 10^{-07}\) \\
1.51 & 2000 & \(2.500\times 10^{-08}\) & \(7.418\times 10^{-07}\) \\
1.25 & 2500 & \(2.00\times 10^{-08}\) & \(2.273\times 10^{-07}\) \\ \hline \hline \end{tabular}
\end{table}
Table 7: General results of FLACSlope simulations in clay soil slope.  
Figure 35: Simulated water pore pressure of the soil slope using FLACSlope in sunny conditions with a water table with 1000 m\({}^{3}\) volume of water.  
It is therefore arguable that the entire simulations agree with the visual and laboratory analysis, most especially the factor that low FoS factors with extreme displacement have been simulated with an increase in the water table or during extreme rainfalls. This correlation can therefore validate and solidify the confusion which has been not well understood within the study area. It is also crucial to indicate that extreme rainfalls are not the only factors that influence the soil slope instability in the study area, but the scope of this study is only limited to extreme rainfalls.
## 3 Results
### Liquid Hydrocarbons
#### 3.3.4 Analysis of Gas-Phase Combustion Products  
Figure 14 presents the results of the analysis of gas-phase compounds (CO, CO\({}_{2}\), NOx, and SO\({}_{2}\)) formed during the combustion of liquid hydrocarbon droplets at different air temperatures (\(\mathrm{T_{g}}=500\)-\(700\)\({}^{\circ}\mathrm{C}\)).  
As the air temperature increased from 500 to 700 \({}^{\circ}\mathrm{C}\), the intensity of the CO release present in the gas-phase products of liquid hydrocarbon combustion is observed to decrease. This is due to the change in the combustion kinetics (Figure 12) and the oxidation of carbon monoxide to CO\({}_{2}\). For carbon dioxide (the main product of hydrocarbon combustion), an inverse relationship is expressed by an increased value of the maximum concentration of CO\({}_{2}\) released at an increased \(\mathrm{T_{g}}\). It should be noted that additional CO oxidation can be associated with microexplosions (Figure 13), the frequency of which increases as \(\mathrm{T_{g}}\) increases. In particular, this is due to the fact that when liquid fuel is heated, water in microdroplets evaporates first, since it is more volatile than liquid hydrocarbons, which leads to further microexplosions. This occurs at temperatures much higher than the boiling point of water. The dispersion of fuel droplets is favorable for mixing the fuel with the air to intensify the air-fuel interaction. Thus, it enhances the secondary spraying of the fuel during combustion and causes the formation of flammable gases such as CO and \(\mathrm{H_{2}}\).  
It should be noted that the total time virtually does not change for almost all the recorded compounds at increased temperatures \(\mathrm{T_{g}}\). This is likely due to the constancy of the time interval of the flame combustion in the test liquid hydrocarbon sample (Figure 12).  
An increased concentration maximum of NOx released at higher temperatures of the air can be associated with the additional involvement of molecular nitrogen from the air. In this case, the pattern of the profiles that describe SO\({}_{2}\) release at increased \(\mathrm{T_{g}}\) does not change significantly.
# A Multi-Bandwidth Reconfigurable Patch Antenna for Devices in WLAN and UWB Technology Applications
## 2 Materials and Methods  
### Proposed Design  
The antenna design (Figure 1) consists of a rectangular monopole of size \(W\times L=30\times 34\) mm\({}^{2}\) that is constructed on an FR4 substrate with a relative permittivity of \(\epsilon_{r}=4.4\) and a thickness of \(h=0.8\) mm. This monopole acts as the primary radiator for the antenna. A rounded rectangular patch (main patch (MP)) is placed on this rectangular monopole. The MP is the result of the intersection of a circle of radius \(R\) and a rectangle centered on the circle, with sides \(l_{1}=12\) mm and \(l_{1}=11.542\) mm. The main patch (MP) is fed with a microstrip line with length \(l_{p}=16.5\) mm and width \(w_{p}=1.529\) mm, and is connected to two other smaller patches through two rectangular slots where PIN diodes have been placed: a semicircular patch (SCP) and a rectangular patch (RP). A summary of the dimensions of the antenna is shown in Table 1. The arrangement and shapes of the patches have been designed to produce the necessary resonance frequency, radiation pattern, input impedance, and bandwidth. The patch antenna includes a hybrid-shaped slot in the ground plane. The shape of the slot is equal to the envelope of the projection of the MP, the SCP, and the RP on the ground plane. The addition of this slot provides the antenna with a large bandwidth and allows for the control of the radiation characteristics of the antenna.
## 5 Experimental Results and Analysis
### Results and Discussion  
The optimal \(K\) and \(\sigma\) values for each dataset are shown in Tables 5 and 6. The optimal K value on the NSL-KDD (KDDTest+), NSL-KDD (KDDTest-21), and UNSW-NB15 datasets is 2. A value of 2 for \(K\) implies that MDPCA can divide the original data into normal and attack records. The training dataset is divided into two subsets, which reduces the imbalance of the training dataset and improves the detection accuracy of the intrusion detection system. MDPCA-DBN has the same training set on the NSL-KDD (KDDTest+) and NSL-KDD (KDDTest-21) datasets, but the detection accuracy of the latter is lower than that of  
As shown in Table 10, the proposed MDPCA-DBN has the best overall accuracy, recall, precision, F1-score and FPR on the NSL-KDD (KDDTest+) dataset. In addition, our proposed model also achieved the best detection rate in the Normal and U2R classes. ANN has a slightly better detection rate in the DoS class compared to MDPCA-DBN (2.42% more). Moreover, MultinomialNB has 8.67% and 4.97% higher detection rates in Probe and R2L classes than MDPCA-DBN, respectively, but MDPCA-DBN has the best overall detection rate. Table 11 shows that MDPCA-DBN achieved the best overall performance, except for RF (slightly more 1.44% on the overall FPR). In addition, the detection rate of RF in the Normal class is 1.44% higher than that of the MDPCA-DBN, and the detection rate of DBN in the DoS class is 2.97% higher than that of MDPCA-DBN, but they are poor in other performances. MDPCA-DBN has the best detection rates on classes U2R and R2L. Tables 10 and 11 show that MultinomialNB achieved the highest detection rate on the Probe class, which implies that the Probe attacks conform to the multinomial distribution. As shown in Tables 10 and 11, all classifiers have very low detection rates on both U2R and R2L classes. Unlike DoS and Probe attacks, U2R has very few records (with only 11 records) in the NSL-KDD training dataset, which results in the classifier not being adequately trained; however, some of the attacks included in R2L class, such as snmpgetattack and snmpguess, exhibit highly similar features to those of normal records, which can cause the classifier to misclassify them as normal records. Table 12 shows that MDPCA-DBN achieved the best overall performance compared to the other six well-known models, except for the overall recall rate (ANN slightly higher, 2.9%). MDPCA-DBN reaches the highest detection rate on the Normal, Generic, Reconnaissance, and Worms classes, but the detection rates are slightly worse on other classes. MultinomialNB achieves a highest detection rate of 73.84% in the DoS class, which implies that the DoS attack features are suitable for the multinomial distribution. RF reaches the highest detection rates on the Analysis, Backdoor, and Shellcode classes, but it is worse than the MDPCA-DBN on the overall F1-Score. In addition, we can see that all
## 2 Wellbore Attitude Measurement Method and Error Analysis
### Wellbore Attitude Calculating Method
#### 2.1.3 Gyroscope-Based Attitude Tracking  
The MEMS gyroscopes are typically utilized to track the attitude variations with measured rotational angular velocities \(\mathbf{\omega}^{D}=\begin{bmatrix}\omega_{x}&\omega_{y}&\omega_{z}\end{bmatrix}^{T}\) of the \(D\) frame. The quadratic differential equation (QDE) expressed by Equation (8) is the commonly used continuous attitude calculating method [17].  
\[d\mathbf{q}/dt=0.5\mathbf{\bullet}\mathbf{q}\otimes\mathbf{\omega}^{D} \tag{8}\]  
Here, \(\mathbf{q}=\begin{bmatrix}q_{0}&q_{1}&q_{2}&q_{3}\end{bmatrix}\) and \(\mathbf{\omega}^{D}\) is the rotational angular velocities measured by the gyroscopes. The detailed expression is written as Equation (9).  
\[\left[\begin{array}{c}\dot{q}_{0}\\ \dot{q}_{1}\\ \dot{q}_{2}\\ \dot{q}_{3}\end{array}\right]=\frac{1}{2}\left[\begin{array}{cccc}0&- \omega_{x}&-\omega_{y}&-\omega_{z}\\ \omega_{x}&0&\omega_{z}&-\omega_{y}\\ \omega_{y}&-\omega_{z}&0&\omega_{x}\\ \omega_{z}&\omega_{y}&-\omega_{x}&0\end{array}\right]\left[\begin{array}{c} q_{0}\\ q_{1}\\ q_{2}\\ q_{3}\end{array}\right] \tag{9}\]  
The transformation rule between quaternions and an attitude matrix is expressed as Equation (10).  
\[\mathbf{C}_{G}^{D}=\begin{bmatrix}q_{0}^{2}+q_{1}^{2}-q_{2}^{2}-q_{3}^{2}&2(q_{1}q _{2}-q_{0}q_{3})&2(q_{1}q_{3}+q_{0}q_{2})\\ 2(q_{1}q_{2}+q_{0}q_{3})&q_{0}^{2}-q_{1}^{2}+q_{2}^{2}-q_{3}^{2}&2(q_{2}q_{3}- q_{0}q_{1})\\ 2(q_{1}q_{3}-q_{0}q_{2})&2(q_{2}q_{3}+q_{0}q_{1})&q_{0}^{2}-q_{1}^{2}-q_{2}^{2}+q_{ 3}^{2}\end{bmatrix} \tag{10}\]  
The general attitude measurement schematic block diagram is shown in Figure 3. The MEMS gyroscope with low accuracy is not sensitive to the angular velocity of the Earth. Therefore, the initial attitudes are measured by the tri-axial magnetometers and the tri-axial accelerometers. The rotational angle of the carrier is identified by the quaternionic attitude tracking method combined with the tri-axial gyroscopes. If the wellbore attitude measurement tool is stationary, the magnetometer will be utilized to calculate the azimuth angle to calibrate the accumulated attitude errors from the gyroscope.
## 4 Simulations and Experimental Test  
To verify the performance of the proposed control scheme, numerical simulations are carried out on a tilt tri-rotor UAV with the aircraft structure shown in Figure 1. All the simulations are completed by using MATLAB/SIMULINK software. In the simulations, the performance of the proposed control method is examined in the hover mode for its ability to reject low-frequency disturbances, and the robustness against system parameter variations is also tested. Besides, in order to validate the performance improvement obtained with the proposed control scheme, the proposed SMC-AD control approach is compared with the two other control methods.  
The model parameters using in the simulations are obtained by experiments. The oscillation method is used to measure the moments of inertia and the center of gravity [36]. The relationships between the force, moment, and rotation speed of the rotors are also tested by an intelligent ergometer. Based on the experimental results, \(k_{f}\) and \(k_{d}\) is obtained by the least square method [37]. The physical parameters of the tilt tri-rotor UAV are shown in Table 1.
# SPD-Safe: Secure Administration of Railway Intelligent Transportation Systems
## 4 Network Layer Security
### Cryptographic Service--_u TESLA_s  
TELSA is a building-block for the Sensor Protocols for Information via Negotiation (SPIN) [81]. Loose time synchronization is required between the receiver and sender, with TESLA utilizing broadcast messages and symmetric cryptography to implement the aforementioned core cryptographic properties. The security functionality of asymmetric cryptography is achieved by utilizing keyed Message Authentication Code (MAC) operations. In brief, the sender includes a keyed MAC on every transmitted packet, where this key is initially known only to this entity. Receivers maintain the received packets without authenticating the sender at this point. Shortly after, the key is revealed by the sender and then the receiver authenticates the packet and proceeds to further processing. Otherwise, the receiver discards the unauthenticated packets after a time-slot.  
The protocol TESLA is efficient and exhibits low computational and communicational overheads. It also tolerates packet loss and scales well for large networks. We use the Ultra-Lightweight Cryptographic Library (ULCL) [61] in order to develop the cryptographic functionality of TESLA, adopting the Secure Hash Algorithm (SHA) with 256-bits message digest (SHA-256) for the MAC computations and the Advanced Encryption Standard (AES) with 256-bits cryptographic keys (AES-256) for the encryption/decryption.
## 5 Comparison Analysis
### Compared with Previous Research  
Reference [25] introduced NAP into the field of fault diagnosis for the first time and achieved good classification results, eliminating the interference caused by different speeds, loads, channels and noises when classifying. However, the steps of the proposed method are complex, and the structure is not simple enough. Compared with Reference [25], CNN-NAP has the following advantages (similar conclusions are presented in Figure 8):  
1. CNN-NAP cancels the steps of extracting features manually and embeds the step of calculating projection matrix P directly into the training of neural network.
2. The original method to get the projection matrix is to transform the optimization problem into the problem of finding the eigenvalues and eigenvectors. However, the CNN-NAP method directly gets the optimization problem through the neural network training, and does not need to get the projection matrix separately.
3. CNN-NAP extended NAP to multiple fault cases, and the obtained projection matrix P could eliminate the nuisance attributes under each fault at the same time. In Reference [25], the corresponding number of projection matrixes P are needed for different fault types.  
Figure 7: C9 layer tSNE visualization: (**a**) before multiplying by P and (**b**) after multiplying by P.  
These three improvements greatly simplify the structure of the method and make the CNN-NAP much clearer. In addition, by training and testing the datasets in chapter 3 with the method mentioned in the Reference [25], the classification accuracy is 99.7%, which is almost the same as the CNN-NAP. Therefore, compared with the method in the Reference [25], CNN-NAP has a broader application prospect and a wider range of applications.  
Furthermore, it has been proved in Reference [25] that NAP is applicable to eliminate the interference properties including rotational speed, load, channel and so on. Limited by the experimental conditions, this paper did not discuss the elimination effect of interference attributes such as load and channel. However, according to Reference [25], it can be inferred that CNN-NAP is equally effective.
## 4 WFDB Window-Based Evaluation  
The MIT-BIH arrhythmia database is a publicly available database from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) comprising ECG recordings with supervised expert annotations. This dataset consists of 48 dual-channeled recordings, each 30 min long, sampled at 360 Hz with variables like artifacts, wave shapes, morphologically altered beat types, and extreme noises. Each recording is accompanied by a reference annotation (attr) file created by cardiovascular experts and used as the gold standard to evaluate R-peak detectors. The annotation consists of two key aspects for each ECG signal: the precise marking of the R-peak location and the labeling of any related arrhythmic anomalies, such as left or right bundle branch block beats, atrial premature beats, premature ventricular contractions, ventricular escape beats, and others. These anomalies are labeled according to the categories established by the ANSI/AAMI [4]. Each label consists of a single letter, such as \"L\" for left bundle branch block beat, \"R\" for right bundle branch block beat, \"A\" for atrial premature beat, \"V\" for premature ventricular  
Figure 2: Process Flow of the bxb Annotation Comparator.  
contraction, and \"e\" for ventricular escape beat. These labels or beat types can then be used for classification purposes after detection, as they help in classifying key events and particular shapes and features associated with different cardiovascular conditions in the physiological signals.  
The primary purpose of R-peak detectors is to predict R-peak time location. The window concept is essential for evaluating time location and is considered the foundation of all WFDB tools. It plays a critical role in validating the robustness of every R-peak detection methodology. It allows for the comparison of WRANN-generated annotations (based on predicted peaks) with manually edited reference annotations marked by a cardiologist, using the benchmark window size of 0.15 s [81]. This helps distinguish false peaks from true R-peaks. Using this standard, two R-waves are considered matching if their labels are, at most, 0.15 s apart [82]. This precise comparison ensures not only the accurate diagnosis of arrhythmia but also can be used for applications like heart rate variability (HRV) [16], fetal heart rate monitoring (fMRI) [83], and biometric recognition [84].
## 1 Introduction
### Optical Interferences Associated Issues and Solutions
Although the authors are mainly focused on the indoor use case, the resilience to noise and the data rate of this VLC system is higher than the one of any existing outdoor VLC system. Nevertheless, the simulation results further show that as the distance increases from 1 to 3 m, the data rates are reduced to half of the initial values, pointing out that the sunlight effect is highly disruptive. To improve these results, the authors propose the usage of a narrow band spectrum for the link, associated to the usage of narrow band optical filters. Even if this solution improves the link performances, its usage in automotive applications seems rather inappropriate. Unlike in indoor applications which use the blue component of the white light for high speed communications [26], in automotive applications this solution would require multiple VLC sensors, each with its narrow band optical filter (i.e., red, green, and orange band for the reception of signals coming from traffic lights, blue band for the reception of signals coming from a vehicle headlamp or from the street lighting system). Thus, although it has the potential to improve the SNR and the associated system performance, the complexity and the cost of the system are increased by at least four times. Moreover, when the transition from simulations to experimental evaluation is made, the communication distance in strong lighting conditions (i.e., 50,350 lux) is significantly reduced to 0.14 m, pointing again to the importance of real-life experimental testing in concept evaluation and validation in this area. To reduce the effect of ambient noise and to improve the SNR, the authors of [39] propose the usage of an average voltage detector along with a voltage subtractor that eliminates part of the generated noise. The SNR improvement is confirmed experimentally in an indoor scenario. Although the solution is effective in terms of SNR and Bit Error Rate (BER) improvement, again, its usage in an outdoor scenario can be effective only if the transimpedance circuit is not saturated by the sun. Another interesting and promising solution to improve the performances of VLC systems in strong sunlight conditions is proposed in [40] and is based on the concept of optical interference suppression based on LCD filtering. Unlike the previous solutions, this one has the potential to contribute to the mitigation of the photosensitive element saturation possibility but this solution proposes a new concept of active filtering rather than a new VLC receiver.