esa-sceva/satcom-chunk-collection huggingface dataset:
# Real-Time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation +
## 5 Experiments and Results
### In-Depth Analysis
#### 5.3.5 rPPG in High HR Ranges  
To study how well the accuracy of the rPPG method spans over the range of heart rates, we can compare its performance for subjects in a rested state versus when they are in a post-workout state. This can be seen in Figure 11a. Furthermore, we can explicitly group the videos from all datasets based on their average ground truth heart rate/HRV and measure the rPPG performance on them separately. Figure 11b plots the relative error rate ratio (MAE) per group for each dataset w.r.t. the average error over the whole dataset. It can be noticed in Figure 11a that while the error rates in the post-workout condition does seem to be marginally higher than the baseline condition, the proposed method performs with sufficiently good accuracy in all conditions. On VicarPPG, closer examination revealed that the variable frame-rate of some videos often drops sharply. This affects the estimation of higher HRs more severely as the Nyquist sampling frequency requirement is also higher. More generally, heart rate estimation in higher HR ranges appears to produce higher errors more often, as seen in Figure 11b. A contributing factor for this could be the presence of higher frequency noise in the same frequency range as the higher heart rates. For HRV, no such trends could be observed in relation to the HRV ranges.  
Figure 9: rPPG performance (MAE; error bars represent standard deviation) with and without the rhythmic motion noise suppression, for different types of subject movements on VicarPPG 2 and MoLi-PPG. In both datasets, motion noise suppression results in lower errors, especially when the subject movement is large.
## 3 Dynamic Area Optimization Based on an NN Considering Intercell Relationships
### Communication Performance
Likewise, for the six-cell condition (Figure 12(b)), nearly 80% of the errors are less than 5\({}^{\circ}\), whereas the leftover errors range from 5\({}^{\circ}\) to 30\({}^{\circ}\). Two main reasons can be attributed to achieving the same total throughput as GA in our proposed method, despite the presence of errors. The one is that small errors have less impact on throughput when using large horizontal beamwidths, specifically around 40\({}^{\circ}\) for the three-cell condition and around 30\({}^{\circ}\) for the six-cell condition. The other is that depending on the user distribution, throughput remains relatively unaffected by errors in the beams in some scenarios.
# SESAM Mode-Locked Yb:Ca3 Gd2(BO3)4 Femtosecond Laser
## 2 Experimental Setup  
The experimental configuration of the Yb:GdCB laser is shown in Figure 1. A high-quality crystal was grown with the Czochralski method with a measured Yb\({}^{3+}\) concentration of 5 at.%.  
Yb:GdCB belongs to the orthorhombic class and its lattice constants are \(a\) = 7.1937 A, \(b\) = 15.5311 A and \(c\) = 8.6140 A. Here, we use the notations of the standard _Pnma_ crystallographic  
Figure 1: Schematic of the Yb:GdCB laser. LD: fiber-coupled laser diode; L\({}_{1}\): aspherical lens; L\({}_{2}\): achromatic doublet lens; M\({}_{1}\), M\({}_{2}\) and M\({}_{4}\): concave mirrors; M\({}_{3}\): flat rear mirror for CW operation; DM\({}_{1}\)–DM\({}_{6}\): dispersive mirrors; OC: output coupler; SESAM: SEemiconductor Saturable Absorber Mirror.  
setting. The laser crystal was cut along the \(\mathbf{a}\)-axis with an aperture of 4 mm \(\times\) 4 mm and a thickness of 3 mm. The input and output faces were polished to laser quality and left uncoated. The crystal was mounted on a copper holder without active cooling and placed between two dichroic folding mirrors M\({}_{1}\) and M\({}_{2}\) (radius of curvature (RoC) = \(-\)100 mm) with the Brewster angle minimum loss condition fulfilled for both the laser and the pump beams. CW and ML laser operation of the Yb:GdCB crystal were evaluated with an X-folded astigmatically compensated linear cavity. The crystal orientation determined the laser polarization \(E\parallel\mathbf{c}\) (due to its higher gain compared to \(E\parallel\mathbf{b}\)). The pump source was a non-polarized fiber-coupled laser diode emitting a nearly diffraction-limited beam with a propagation factor (M\({}^{2}\)) of -1.02. The laser diode had a fiber Bragg grating (FBG) for wavelength-locking at 976 nm over the entire operation range with an emission bandwidth (full width at half-maximum (FWHM)) of 0.2 nm, which matched the bandwidth of the zero-phonon-line in the absorption spectrum of the Yb:GdCB crystal well. Given the transmissions of the pump reimaging lenses and the pump mirror M\({}_{1}\), the maximum incident pump power on the laser crystal was 1.29 W. The use of the single-transverse mode laser diode with a nearly diffraction-limited beam led to higher gain per watt of absorbed pump power due to the improved mode-matching and the lowest thermal stress in the laser crystal (as compared to pumping by fiber-coupled diodes with a \"top-hat\" beam profile). This allowed us to optimize the Yb laser for low-threshold and high-efficiency operation in the CW regime, and also for femtosecond pulse generation in the ML regime. The pump beam was collimated by an aspherical lens L\({}_{1}\) (\(f\) = 26 mm) and focused into the laser crystal through the M\({}_{1}\) mirror using an achromatic doublet lens L\({}_{2}\) (\(f\) = 100 mm), resulting in a beam waist radius of 18.7 and 36.9 \(\upmu\)m in the sagittal and tangential planes, respectively.
# Wireless and Fiber-Based Post-Quantum-Cryptography-Secured IPsec Tunnel
###### Abstract  
In the near future, commercially accessible quantum computers are anticipated to revolutionize the world as we know it. These advanced machines are predicted to render traditional cryptographic security measures, deeply ingrained in contemporary communication, obsolete. While symmetric cryptography methods like AES can withstand quantum assaults if key sizes are doubled compared to current standards, asymmetric cryptographic techniques, such as RSA, are vulnerable to compromise. Consequently, there is a pressing need to transition towards post-quantum cryptography (PQC) principles in order to safeguard our privacy effectively. A challenge is to include PQC into existing protocols and thus into the existing communication structure. In this work, we report on the first experimental IPsec tunnel secured by the PQC algorithms Falcon, Dilithium, and Kyber. We deploy our IPsec tunnel in two scenarios. The first scenario represents a high-performance data center environment where many machines are interconnected via high-speed networks. We achieve an IPsec tunnel with an AES-256 GCM encrypted east-west throughput of 100 Gbit/s line rate. The second scenario shows an IPsec tunnel between a wireless NVIDIA Jetson and the cloud that achieves a 0.486 Gbit/s AES-256 GCM encrypted north-south throughput. This case represents a mobile device that communicates securely with applications running in the cloud.  
post-quantum cryptography; falcon; dilithium; kyber; data processing unit; data center; IPsec E16080300
# Spoken Language Identification System Using Convolutional Recurrent Neural Network
## 5 Experiments
### Performance Evaluation
#### 5.1.4 F-Measure (F1)  
As shown in Equation (4), a weighted average of recall and precision is known as the F-measure.  
\[F1=2\times\frac{P\times R}{P+R} \tag{4}\]  
The variables \(P\) and \(R\) represent precision and recall in this equation.
# MIMO Self-Heterodyne OFDM Using Band Selection Technique
## 2 The FSTBC MIMO Self-Het OFDM System
To apply the ZF equalizer, let \(\mathbf{H}_{\text{eq}}^{\dagger}\) be the pseudo-inverse of \(\mathbf{H}_{\text{eq}}\) which is calculated and defined as follows:  
\[\mathbf{H}_{\text{eq}}^{\dagger}\ \triangleq\ \left(\mathbf{H}_{\text{eq}}\ \mathbf{H}_{\text{eq}}^{ \dagger}\right)^{-1}\mathbf{H}_{\text{eq}}^{\text{H}}=\frac{1}{\text{C}_{ \text{i}}}\ \mathbf{H}_{\text{eq}}^{\text{H}}, \tag{12}\]  
where i = 1, 2 and the constants C\({}_{1}\) and C\({}_{2}\) are defined as:  
\[\text{C}_{1}=|\alpha_{c}|^{2}\Bigg{(}\sum_{a=1}^{2}\lvert\text{H}_{1a}|^{2} \ \Bigg{)}+|\beta_{c}|\ ^{2}\Bigg{(}\sum_{a=1}^{2}\lvert\text{H}_{2a}|^{2}\ \Bigg{)}, \tag{13}\]  
\[\text{C}_{2}=|\alpha_{c}|^{2}\Bigg{(}\sum_{a=3}^{4}\lvert\text{H}_{1a}|^{2} \ \Bigg{)}+|\beta_{c}|\ ^{2}\Bigg{(}\sum_{a=3}^{4}\lvert\text{H}_{2a}|^{2}\ \Bigg{)}, \tag{14}\]  
where \(a\) is \(a\)th transmit antenna and \(\mathbf{H}_{\text{eq}}^{\text{H}}\) is the hermition of \(\mathbf{H}_{\text{eq}}\) which can be represented in a matrix form as:  
\[H_{\text{eq}}^{H}\ \triangleq\ \left[\begin{array}{cccc}\alpha_{c}H_{11}^{*}& \beta_{c}H_{21}^{*}&\alpha_{c}^{*}H_{12}&\beta_{c}^{*}H_{22}\\ \alpha_{c}H_{12}^{*}&\beta_{c}H_{22}^{*}&-\alpha_{c}^{*}H_{11}&-\beta_{c}^{*}H_ {21}\\ \alpha_{c}H_{13}^{*}&\beta_{c}H_{23}^{*}&\alpha_{c}^{*}H_{14}&\beta_{c}^{*}H_ {24}\\ \alpha_{c}H_{14}^{*}&\beta_{c}H_{24}^{*}&-\alpha_{c}^{*}H_{13}&-  
Figure 3: STBC MIMO self-het OFDM transmitter when the data is transmitted in the lower band. Figure 2: STBC MIMO self-het OFDM transmitter when the data is transmitted in the upper band. A pilot bit = 1 is added to indicate the band which the data symbol will be sent on. At the receiver, if the bit = 1, the data symbols are sent on the upper band and if the bit \(\
eq\) 1, the data symbols are sent on the lower band.
## 1 Introduction
The advantages of \"component minimum amplitude phase shift (CAP) with M-order quadrature amplitude modulation (M-QAM)\", including good spectrum effectiveness and a low peak-to-average ratio, are frequently cited. Yet, linear and nonlinear impairments are unavoidable in a true high-speed UVLC system, significantly lowering the possible transmission rate and system efficiency. These limitations are mostly the outcome of defects in optical components, including lighting, electrical amplifying systems, photosensitive elements, and the complicated underwater environment that results in dispersion, diffraction, and turbulence. Post-equalizers have been created for UVLC systems to address these shortcomings successfully. The least mean square (LMS) and Volterra series approaches are common equalizer methods. Volterra is frequently used for nonlinear normalization, while LMS concentrates on linear compensation [7]. Neural networks (NN) have gained significant interest, especially in optical communication [8]. NNs have been demonstrated to be highly effective in approximating complex functions by learning from large datasets. Due to their capability, NNs are a promising option for mitigating nonlinear distortion [9; 10]. Greater nonlinear distortion is observed in the UVLC system for higher power messages compared to lower power signals. In previous research, random sequential data was handled using long short-term memory (LSTM) networks that depend on machine learning approaches. A total of 13.5 Gbps of data speed and a 2-m connection distance, these networks have been utilized to demonstrate a high-speed VLC connection. The collected M-QAM signals show various distortion levels at various symbol strengths, mainly when applying high-order modulation. The usual configuration shows that symbols in the outer part of the constellations are more prone to nonlinear impairments than those in the inner portion. The UVLC system is most affected by distortions, which increases its complexity and effectiveness. We suggest the idea of an adaptive fuzzy logic deep-learning equalizer to address this problem and reduce these drawbacks. The structure of essay is as follows: Section 2 indicates a literature review concerning the proposed work; Section 3 provides a detailed study of the suggested novel HC framework; Section 4 analyzes the comparative and experimental results of the proposed work; and lastly, Section 5 indicates the study and describes future work.
## 3 Results and Discussion
### Statistical Analysis  
#### 3.2.1 Pareto Effects  
Table 4 shows the turbidity removal efficiency and coagulation ability observed in each run. The best result for the removal of turbidity, and coagulation ability from the synthetic kaolin water was obtained in run 6, where a dosage of 50 mg/L of deshelled _Cara papaya_ seeds at pH 3 was used for initial turbidity of 500 NTU. In this condition, the removal efficiency of turbidity, and coagulation activity were 97.2 and 73.1%, respectively.  
The Pareto charts (Figure 3) indicate the variables that are significant in the removal process of turbidity, and coagulation activity from the synthetic kaolin water. Based in the charts (Figure 3), the statistical importance of each factor on the turbidity removal, and coagulation activity from the synthetic kaolin can be compared. The interaction between all three factors viz. bio-coagulant dosage, pH and initial turbidity is the most important factor that influenced the turbidity removal and coagulation activity of the synthetic kaolin  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Run** & **Dosage** & **pH** & **Initial Turbidity** & **Turbidity** & **Coagulation** \\  & **(mg/L)** & **(NTU)** & **Removal (\%)** & **Activity (\%)** \\ \hline
1 & 50 & 3 & 500 & 97.2 & 72.8 \\
2 & 200 & 7 & 100 & 2.9 & 1.0 \\
3 & 50 & 3 & 100 & 3.7 & 2.4 \\
4 & 50 & 3 & 100 & 0.0 & 2.3 \\
5 & 200 & 7 & 500 & 10.6 & 14.5 \\
6 & 50 & 3 & 500 & 97.2 & 73.1 \\
7 & 200 & 3 & 100 & 2.1 & 2.2 \\
8 & 200 & 7 & 500 & 15.1 & 17.3 \\
9 & 50 & 7 & 100 & 2.7 & 6.1 \\
10 & 200 & 7 & 100 & 2.0 & 6.0 \\
11 & 50 & 7 & 100 & 6.1 & 4.9 \\
12 & 200 & 3 & 500 & 75.5 & 30.5 \\
13 & 50 & 7 & 500 & 4.8 & 8.6 \\
14 & 200 & 3 & 100 & 11.8 & 7.6 \\
15 & 200 & 3 & 500 & 72.7 & 57.1 \\
16 & 50 & 7 & 500 & 1.2 & 1.4 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Turbidity removal efficiency and coagulation activity from synthetic kaolin water using deshelled _Cara papaya_ seeds.  
Figure 2: FESEM microphotograph of deshelled _Cara papaya_ seeds at 500\(\times\) magnification.  
water. As for coagulation activity alone, pH is the most significant influence factor. The increment of pH decreases the coagulation activity of deshelled _Caraic papaya_ seeds towards synthetic kaolin water.  
The effect of increasing the deshelled _Caraic papaya_ seeds dosage to the treatment process was shown to be negative for turbidity removal and coagulation activity. In case of turbidity removal, the individual effect from dosage was insignificant unless it is interacted with other operational factors. Meanwhile, for the coagulation activity, even though the dosage was found significant, its effect had small relevance when compared to the pH and initial turbidity effect (Figure 3b). This suggests that a low dosage of deshelled _Caraic papaya_ seeds is required for the treatment of turbid water. Excessive bio-coagulant dosage can reverse the surface charge of colloidal particles, which causes dispersion and subsequently decreases the coagulant efficiency if it is not optimized well with other interacting factors [38; 39].
## 3 Proposed Methodology
### Multi-Preference Search Mode Based on Evolutionary Demand
#### 3.2.1 Search Mode 1: Angle-Based Convergence Model for Feasible Domains  
In Mode 1, the main population \(P\) is responsible for exploring the feasible domain, and the auxiliary population \(A\) is used to store the feasible solutions of \(P\). A sampling strategy based on the direction of convergence is designed to enhance the convergence of \(P\) and feasible selection pressure. In the decision space, based on the solution \(x_{1}\), two convergence directions are formed by the lower bounds \(L\) and \(x_{1}\) and the upper bound \(U\) and \(x_{1}\).  
\[v^{(L,x_{1})} =x_{1}-L \tag{9}\] \[v^{(u,x_{1})} =x_{1}-U \tag{10}\]  
Afterwards, the solution is generated by sampling at different step sizes in the direction of convergence:  
\[X_{j}^{(l,X_{1})} =L+s_{j}^{l}\cdot\frac{v^{(l,X_{1})}}{\|v^{(l,X_{1})}\|} \tag{11}\] \[X_{k}^{(u,X_{1})} =U+s_{k}^{u}\cdot\frac{v^{(u,X_{1})}}{\|v^{(u,X_{1})}\|} \tag{12}\]  
where \(s_{j}^{l}\) and \(s_{k}^{u}\in[0,\|U-L\|]\) denote the step size, \(j\) and \(k\) denote the first \(j\) times and the \(k\) times sampling, and \(\|\cdot\|\) denotes the Euclidean distance.
## 4 Software/Hardware Overview  
### Open-Source Software  
In line with the overall low-cost approach of _Serpens_, an open-source software framework is designed for the low-level control. To design the software architecture, there are different robotic frameworks and middleware available in recent years [29]. However, the Robot Operating System (ROS) [12] has emerged as a de facto standard for robot software architecture in the research community. ROS is designed as a meta-operating system for robotic applications. The primary goal of ROS is to provide a common platform to make the design of capable robotic applications quicker and easier. Some of the features it provides include hardware abstraction, device drivers, message-passing and package management. In conjunction with ROS, Gazebo 3D simulator [30] can be adopted to accurately and efficiently simulate robots in complex indoor and outdoor environments. Gazebo also provides a robust physics engine, high-quality graphics, and convenient programmatic and graphical interfaces. In this perspective, ROS serves as the interface for the robot model of _Serpens_, while Gazebo is used to simulate both the robot and its operational environment. In addition to ROS and Gazebo, the RViz (ROS visualisation) [31] tool can be adopted to visualise and monitor sensor information retrieved in real-time from both the simulated scenario as well as from the real world. Another benefit for developers are the ROS community-driven support and the stable release-cycle of distributions (a new version is released every year, while a new long-term support (LTS) version is released every second year). Moreover, ROS offers an excellent interface to hardware components such as different micro-controllers and other peripheral hardware, i.e., actuators and sensors. The choice of ROS for the design of the control architecture makes it possible to extend the modular concept to both the hardware as well as the software of _Serpens_.
## 3 Results
### Run-to-Failure Bearing Experiments  
#### 3.2.1 Experimental Set-Up  
To illustrate the effectiveness of the method proposed in this paper, the vibration data of a run-to-failure experiment of a rolling element bearing were collected by a test bench, as shown in Figure 8.  
The test bearing is a single-row deep groove ball bearing (ERK16) whose main geometric parameters are shown in Table 4. According to different working conditions of the bearing, experiments were carried out under both constant speed and variable speed. This paper mainly discussed the RUL prediction of the rolling bearing under variable rotational  
Figure 8: Accelerated life test bench of the rolling bearing.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Dataset** & **RVM** & **PF** & **EKF** & **PHPA** & **This Model** \\ \hline Bearing1\_1 & 0.5741 & 0.6107 & 0.6209 & 0.9047 & 0.9186 \\ Bearing1\_2 & 0.1815 & 0.7256 & 0.3500 & 0.8546 & 0.8992 \\ Bearing1\_3 & 0.6245 & 0.4850 & 0.8010 & 0.8482 & 0.8663 \\ Bearing1\_4 & 0.3722 & 0.2305 & 0.6839 & 0.7240 & 0.7976 \\ Bearing1\_5 & 0.6122 & 0.4311 & 0.5042 & 0.7878 & 0.8293 \\ \hline \hline \end{tabular}
\end{table}
Table 3: CRA comparisons between five methods.  
speed. Hence, the test conditions are as follows: radial load 8500 N rotational speed fluctuation range [1450, 1550] r/min, sampling frequency 12,800 Hz, sampling interval 5 min, and sampling duration 4 s.
# New and Efficient Algorithms for Producing Frequent Itemsets with the Map-Reduce Framework
## Mining Closed Frequent Itemsets with Map-Reduce
### Reduce Step  
The reduce task gets a key as input, a collection of values and the minimum support. The key is the generator \(g\) (which is an itemset), a collection \((t_{1},s_{1}),\ldots,(t_{n},s_{n})\) of \(n\) tuples, composed of a set of items \(t_{i}\) (an intersection of transactions from the combiner), all containing \(g\) and a number \(s_{i}\) indicating the support of the tuple. In addition, it gets, as a parameter, the user-given minimum support, _minSup_. The reducer is depicted in Algorithm 4.  
At first, the frequency property is checked: \(sup(g)=\sum\limits_{i=1}^{n}s_{i}\geq minSup*|\mathcal{D}|\). If so, then an intersection of \(t_{1},\ldots,t_{n}\) is performed and a closure, denoted \(c\), is produced. If the item that was added in the map step is lexicographically greater than the first item in \(c\backslash g\), then \(c\) is a duplication and can be discarded. Otherwise, a new closed frequent itemset is discovered and is added to \(C_{i}\).  
In other words, if the test in line 7 passes, then it is guaranteed that the same closure \(c\) is found (and kept) in another reduce task--the one that will get \(c\) from its first minimal generator in the lexicographical order (as is proven later).  
The pseudo-code of the reduce function is presented below.  
In line 5 in the algorithm, we apply the \(f\) function, which is actually an intersection of all the transactions in \(T\). Notice that we do not need to read all of \(T\) and store in the RAM. \(T\) can be treated as a stream, reading transactions one at a time and performing the intersection.  
```
Input: Key: \(g\), a generator  Values: \((t_{1},s_{1}),...,(t_{n},s_{n})\): a collection of \(n\) tuples such that \(t_{i}\) is a set of items (intersection of transactions) and \(s_{i}\) is its support \(minSup\): The user-given minimum support Output: A closed frequent itemset, if found
1\(supp\leftarrow\sum_{i=1}^{n}s_{i}\) ;
2 if\(supp<minSup\)then
3 return;
4
5 end if /* Applying the \(f\) function on \(t_{1},...,t_{n}\), i.e. intersecting \(t_{1},...,t_{n}\): */
6\(c\gets f(t_{1},...,t_{n})\);
7\(c.generator\gets g\); /* Duplication elimination: */
8 if\(g.item>(c\setminus g)\)then
9 return;
10
11 end if
12
13 emit(c);
```  
**Algorithm 4**Reducer.
# Space-Borne System-in-Package Based on High Reliability Microwave Interconnections
## 2 Analysis of Traditional Interconnections in Space-Borne Microwave Systems
### Directly Soldering Structure  
When the inner core of the seal is directly soldered with the substrate, 3D electromagnetic simulation is carried out for its electrical performance to analyze its microwave transmission performance, and the matching results are evaluated with reflection loss (S11). For the reasonable parameters in the structure, the maximum stress at the soldering point reaches 436 MPa, which is far greater than the solder joint stress requirements, and the reliability is poor. Therefore, the solder joint cracking fault as shown in Figure 2 will occur.  
To solve this reliability problem, the coaxial seal and the substrate are usually connected by flexible structures such as wires and strips [13; 14]. The interconnection modes mainly include core wire winding soldering [15], gold-ribbon lap bonding [16] and gold-ribbon wrap bonding [17].