esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Design of ACM Controller
### RLS Adaptive Feedforward Control  
The RLS algorithm is a recursive least square algorithm [20], which implements an exact least square solution by recursive. The control block diagram is similar to Figure 3. Compared with LMS, RLS algorithm has poor tracking ability in non-stationary environment, complicated calculation and is difficult to implement, but it has the characteristic of fast convergence.  
In order to avoid the existence of instability problems, the error function minimized in RLS algorithm is generally defined as the exponential weighted sum of squared errors:  
\[\zeta_{k}=\sum_{i=1}^{k}\beta^{k-i}e_{i}^{2}=\sum_{i=  
let \(G_{k}=R_{k}^{-1}\), it can be expressed as:  
\[G_{k}=R_{k}^{-1}=\beta^{-1}R_{k-1}^{-1}-\beta^{-1}K_{k}x_{k}^{\mathrm{T}}R_{k-1} ^{-1} \tag{16}\]  
and we find there exist Equation (17) as below:  
\[G_{k}x_{k}=\beta^{-1}(R_{k-1}^{-1}x_{k}-K_{k}x_{k}^{\mathrm{T}}R_{k-1}^{-1}x_{ k})=K_{k} \tag{17}\]  
Apply the above formula, Equations (13), (16) and (17) are introduced into Equation (11). After algebraic processing, the weight coefficient update formula is obtained:  
\[\mathbf{w}_{k}=\mathbf{w}_{k-1}-\alpha_{k}K_{k}=\mathbf{w}_{k-1}-\alpha_{k}G_{k}x_{k} \tag{18}\]  
where \(\alpha_{k}=d_{k}+\mathbf{w}_{k-1}^{\mathrm{T}}x_{k}\).  
The above equations summarize this algorithm, when matrix \(\mathbf{R}_{k}^{-1}\) is initialized to \(\mathbf{R}_{0}^{-1}=\delta^{-1}\mathbf{I}\), where \(\delta^{-1}\) is a small positive constant, \(\mathbf{I}\) is an unit matrix, and the weight coefficients are simply initialized to zero.  
In MATLAB/Simulink, the DSP toolbox is used to build the simulation model of RLS algorithm. It can be seen in the oscilloscope that the RLS algorithm is in good convergence behaviour.
# Assessment of Affordable Real-Time PPP Solutions for Transportation Applications
## 3 Results
In addition, only the RTK solutions follow a normal distribution pattern, particularly the RTK-GE and RTK-GRE strategies. To further examine the performance of the multi-GNSS RT-PPP processing models applying various SSR corrections, a horizontal error box plot is illustrated in Figure 9 for each scenario. For the RT-BKG processing solution, the 2D position errors are widely distributed for RT-BKG-G; by contrast, they are narrowly distributed for RT-BKG-GR, with a medium to narrow distribution for both RT-BKG-GE and RT-BKG-GRE. To provide a robust estimate of the positioning differences and their central tendencies, the interquartile range (IQR) is computed for each processing solution; the IQR estimates are 0.255 m and  
Figure 8: Histogram of 2D positioning errors for the RT-PPP and RTK solutions. 0.043 m for the RT-BKG-G and RT-BKG-GR solutions, respectively, whereas they are 0.101 m and 0.063 m for the RT-BKG-GE and RT-BKG-GRE models, respectively. Therefore, it can be inferred that the real-time BKG GPS SSR corrections are less accurate than GLONASS and Galileo corrections, which is reflected in the resultant positioning accuracy. In terms of the RT-CNE solution, the RT-CNE-GR strategy demonstrates a large distribution of two-dimensional errors; in contrast, the other three processing strategies have somewhat equal two-dimensional positioning error distributions. The IQR estimates are 0.149 m, 0.269 m, 0.146 m, and 0.130 m for the RT-CNE-G, RT-CNE-GR, RT-CNE-GE, and RT-CNE-GRE processing strategies, respectively; as a result, it can be concluded that the RT-CNE-GR has the worst performance among the RT-CNE processing strategies. This can be attributed to the accuracy of the instantaneous GLONASS orbit and clock products provided by the CNE analysis center. The box plot indicates that RT-WHU-GE has a slightly wide horizontal positioning difference distribution compared with the other RT-WHU processing scenarios, while RT-WHU-GR has the narrowest error distribution. The IQR estimates are 0.133 m, 0.103 m, 0.166 m, and 0.088 m for RT-WHU-G, RT-WHU-GR, RT-WHU-GE, and RT-WHU-GRE, respectively. The horizontal positioning errors provided by the RT scenarios are significantly smaller than those provided by the RT-PPP solutions, with ultra-narrow error distributions and IQR values equal 0.007 m, 0.005 m, 0.004 m, and 0.004 m for RTK-G, RTK-GR, RTK-GE, and RTK-GRE, respectively. Figure 9: Box plots of 2D positioning error distributions for the RT-PPP and RTK solutions.
# Hybrid Dual-Link Data Transmission Based on Internet of Vessels
## 2 Related Work
[38] addressed the stable matching problem by using reputation to measure workers' reliability, employing multi-criteria trust and reputation factors derived from a Mamdani fuzzy inference system to allocate each spatial task. In this study, we propose a Bayesian reputation-based spatial crowdsourcing allocation algorithm, which effectively assigns task information to the most suitable vessels, selecting the best vessels as relay nodes to ensure link stability.
# SRv6-Based Edge Service Continuity in 5G Mobile Networks +
## 6 Testbed and Performance Evaluation
### Implementation and Testbed Deployment
#### 6.1.2 Edge Service Migration  
Edge services run as Docker containers. For what concerns their migration, we leveraged CRIU [48] and rsync [49] tools. CRIU, which stands for Checkpoint/Restore in Userspace, deals with the checkpoint of the container's status on its original host and its restoration on the target host. We exploited CRIU's --tcp-established option to guarantee TCP connection persistence after migration [50]. This allows CRIU to obtain the support of Linux Kernel to retrieve and restore the TCP connection status, i.e., it saves the socket state and restores it at the destination. In addition, before the connection is restored on the target host, the original container's IP address must be available. To guarantee the latter requirement, the same network namespace must be created on the target host. The rsync tool is used to transfer the container and connection checkpoints to the target host.
# Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring
## 3 Sensor Operating Modes and Energy Consumption Measurements
### Consumption Profiles in Active and Idle Mode
#### 3.3.5 BLE Advertising Event  
During one BLE advertising event, the BLE radio transmits the advertising packet on three consecutive advertising channels and listens for a short period on each channel for possible requests for connection from a scanner device (initiator), which searches for the available ECG sensors. We averaged the current consumption profiles for 10 advertising events to suppress the effects of slight deviations between them. The energy consumption of a BLE advertising event \(e_{adv}\), can be calculated in the same way as for the ECG sampling event--as a sum of all current consumption samples \(i_{t}\) multiplied by a sample time \(\Delta t\) and battery voltage \(V_{batt}=4.13\) V (Equation (2)). The average measured advertising energy consumption is 120.65 \(\upmu\)J with 2.43 \(\upmu\)J standard deviation. The resulting power consumption profile is presented in Figure 8. The power (current) consumption profile begins with a radio wake-up event ranging from 0.0 ms to approximately 1.8 ms, and the following pattern from approximately 1.8 ms to approximately 3.7 ms represents three consecutive RX and TX events on three different advertising channels. The last part of the BLE advertising event represents the BLE stack processing and the transition to the radio sleep state.  
\[e_{adv}=V_{batt}\sum_{t=0}^{T}i_{t}\times\Delta t \tag{2}\]
# Dual-Indicator Micro-Electro-Mechanical System Monitoring Method for Rock Instability Early Warning
## 2 Fundamental Theory and Methodology
### Dynamic Interdependence: NF Versus Safety Factor
Under the condition that other parameters of the rock mass remain constant, a decrease in the NF induces a monotonic decline in the safety factor. A critical NF necessarily exists at which the safety factor equals 1. Consequently, the real-time monitoring of NF variations enables instability early warning for rock masses, leveraging this deterministic frequency-safety correlation. The quantitative relationship between the NF of unstable rock mass and the safety factor can be calibrated through laboratory experiments or finite elements simulation, and the safety factor of unstable rock mass can be determined by the NF value of the field measurable index and the multi-stage early-warning threshold of unstable rock mass can be set.
# A Spatial Compounding Method for Non-Delayed Sequential Beamforming
## 2 Materials and Methods  
### Non-Delayed Sequential Beamforming  
Non-delayed sequential beamforming introduced in [13] proposes a new dual-stage beamformer. A low-resolution image (LRI) is produced by the direct summation of channel data at the first stage. A second beamformer then reconstructs a high-resolution image (HRI) using the LRI. The time-of-flight (TOF) for the NDSB is shown in Figure 1, which is given as  
\[t_{TOF\_NDSB}=\frac{1}{c}\Big{(}\Big{|}\overrightarrow{r_{VS}}-\overrightarrow{r_{e }}\Big{|}+\Big{|}\overrightarrow{r_{VS}}-\overrightarrow{r_{ip}}\Big{|}+ \Big{|}\overrightarrow{r_{r}}-\overrightarrow{r_{ip}}\Big{|}\Big{)}. \tag{1}\]  
In the equations, \(\overrightarrow{r_{VS}}\), \(\overrightarrow{r_{r}}\), \(\overrightarrow{r_{e}}\), and \(\overrightarrow{r_{ip}}\) denote the positions of the virtual source, the receive element, the transmit origin, and the imaging point, respectively. \(c\) is the speed of sound. To reconstruct \((x,\,z)\) in the HRI, a time-delay \(\Delta t\) is applied to the LRI data at the lateral position \(x_{f}\):  
\[\Delta t=\frac{(\sqrt{(z-z_{f})^{2}+(x-x_{f})^{2}}-|z-z_{f}|)}{c}, \tag{2}\]  
Figure 1: Wave propagation path for NDSB. \(\overrightarrow{r_{VS}}\), \(\overrightarrow{r_{r}}\), \(\overrightarrow{r_{e}}\), and \(\overrightarrow{r_{ip}}\) denote the positions of the virtual source, the receive element, the transmit origin, and the imaging point, respectively. The blue arrows indicate the transmit path, and the red arrows indicate the receive path. The active elements are indicated as black.  
where \(z_{f}\) is the focus depth. The high-resolution image can be written as  
\[HRI_{NDSB}(x,z)=\sum_{x_{f}}\!\!W(x,z,x_{f},z_{f})LRI(t-\Delta t(x,z,x_{f},z_{f})), \tag{3}\]  
where \(HRI_{NDSB}\) denotes the high-resolution image for NDSB, \(W\) is the apodization function, and \(LRI\) denotes the low-resolution image.
# Structural Behaviour of Concrete Deep Beams Reinforced with Aluminium Alloy Bars
## 3 Results and Discussion
### Parametric Study
#### 3.2.3 Size Effect  
The size effect in RC structures refers to the tendency for the shear strength (V/(bw * d)) to decrease as effective depth increases [46]. Because brittle shear failures are more prone to occur in deep and large-scale beams, the size effect becomes especially important for these elements [46; 47; 48; 49]. Three beams--small, medium, and large scale--were considered to examine this effect (see Figure 11). The beams had widths of 120, 172, and 240 mm and effective depths of 175, 250, and 350 mm. All dimensions of the small-scale beam were multiplied by about 1.43 and 2. The reinforcement ratios of tension, compression, and shear were kept constant for all beams. All other parameters, such as material properties (e.g., a concrete strength of 20 MPa) and the a/d ratio, were also kept constant.  
Figure 11: Size effect.  
Figure 10: Effect of tension reinforcement ratio.  
Figure 12 represents the inverse correlation between shear strength (MPa) and effective depth (mm) for numerically tested beams described above. The inverse relationship was indicated by the decreased shear strength as the effective depth increases. The shear strengths for beams with effective depths of 175, 250, and 350 mm were 2.95, 2.47, and 2.1 MPa, respectively. The shear strength decreased from 2.95 MPa to 2.1 MPa as the effective depth increased from 175 mm to 350 mm. This is consistent with the well-known shear behaviour of RC beams, where large-scale cross-sections tend to carry lower shear stresses [46; 47; 48; 49; 50]. For example, one study [51], which included RC deep beams reinforced with steel bars, showed that shear strength loss was 26% with doubling beam dimensions. In this study, the shear stress decreased by about 28.8% when the beam size doubled. This can show the size effect in AA RC beams that can be comparable to steel-RC beams. When the corrosion resistance of AA bars is considered, AA RC beams are superior to RC beams reinforced with steel bars.
###### Abstract  
This paper proposes an analytical expression set to determine the maximum values of currents and voltages in the Class-E Power Amplifier (PA) with Finite DC-Feed Inductance (FDI) under the following assumptions--ideal components (e.g., inductors and capacitors with infinite quality factor), a switch with zero rise and fall commutation times, zero on-resistance, and infinite off-resistance, and an infinite loaded quality factor of the output resonant circuit. The developed expressions are the average supply current, the RMS (Root Mean Square) current through the DC-feed inductance, the peak voltage and current in the switch, the RMS current through the switch, the peak voltages of the output resonant circuit, and the peak voltage and current in the PA load. These equations were obtained from the circuit analysis of this ideal amplifier and curve-fitting tools. Furthermore, the proposed expressions are a useful tool to estimate the maximum ratings of the amplifier components. The accuracy of the expressions was analyzed by the circuit simulation of twelve ideal amplifiers, which were designed to meet a wide spectrum of application scenarios. The resulting Mean Absolute Percentage Error (MAPE) of the maximum-rating constraints estimation was 2.64%.  
Class-E; curve fitting; mathematical model; power amplifier +
Footnote †: journal: Applied Sciences
###### Abstract  
The aft-body mounted inlet of a hypersonic vehicle has garnered attention for its potential to shorten the propulsion system. This study aims to explore the influence of compression direction on the performance of the hypersonic inlet attached to the vehicle's aft body. To achieve this objective, a simplified, integrated model of the body and two-dimensional inlet was developed and evaluated using numerical simulation techniques. The study conducted a comparative analysis of the overall and starting performance between inverted and normal inlet layouts while ensuring uniformity in inlet configuration and installation location. The results indicated that the inverted layout surpassed the normal layout in terms of airflow capture capabilities, with an 8.24% higher mass flow rate. However, the inverted inlet layout exhibited an 11.46% reduction in total pressure recovery performance compared to the normal layout. Additionally, the study found that the inverted inlet layout demonstrated a self-starting Mach number 1.62 lower than that of the normal inlet layout. This difference stemmed primarily from the pressure gradient on the body surface induced by the incident shock wave of the inverted inlet, which enhanced starting performance by eliminating low-energy flow near the wall.  
inlet layout; boundary layer; shock boundary layer interference; aerodynamic design Article The Effects of Compression Direction on the Performance of a Two-Dimensional Inlet Mounted on the Aft Body  
[PERSON], [PERSON] and [PERSON]
# Exploring the Potential of Event Camera Imaging for Advancing Remote Pupil-Tracking Techniques
## 1 Introduction
By integrating event camera data with our previous frame-based methods [4; 11], we emphasize the promise of event-camera-based tracking. Through this research, we explore the benefits, challenges, and limits of using event camera imaging for remote pupil tracking.
# BIMO: Bootstrap Inter-Intra Modality at Once Unsupervised Learning for Multivariate Time Series
## 3 Results and Discussion
### Univariate Time Series
In contrast, the main network was trained with the intra-auxiliary network in a higher ratio than that used for the inter-auxiliary network at first; gradually, the ratio of the inter-auxiliary network was increased (_Intra_\(\mapsto\)_Inter_), which is the training method of BIMO. As shown in Table 3, the _Intra_\(\mapsto\)_Inter_ method obtained the best rank score. We confirmed that the initial training trained the intra-modality representations sufficiently, which are the relatively low-level features, and then the inter modality representations, which are the relatively high-level features. The proposed dynamic training method made the main network evenly learn both modality representations. **Representation Metric Space:** We also validated the performance of representation learning for some UCR datasets using embedding visualization with dimensionality reduction. The results are shown in Figure 3. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Dataset**} & \multicolumn{2}{c}{**Single**} & \multicolumn{2}{c}{**Plural**} \\ \cline{2-6}  & _Inter_ & _Intra_ & _Inter and Intra_ & _Inter_\(\mapsto\)_Intra_ & _Intra_\(\mapsto\)_Inter_ \\  & _Inter_ & _Intra_ & _Inter and Intra_ & _Inter_\(\mapsto\)_Intra_ & _(BIMO)_ \\ \hline SyntheticControl & 0.873 & 0.850 & 0.863 & 0.873 & **0.900** \\ ToeSeg1 & **0.917** & **0.917** & **0.917** & 0.886 & **0.917** \\ ToeSeg2 & 0.883 & 0.883 & 0.883 & 0.883 & **0.891** \\ Trace & **1.000** & **1.000** & **1.000** & **1.000** & **1.000** \\ TwoLeadECG & **0.996** & **0.996** & 0.995 & **0.996** & **0.996** \\ TwoPatterns & **1.000** & 0.997 & **1.000** & 0.996 & **1.000** \\ UWavGesLibAll & 0.954 & 0.956 & 0.951 & **0.962** & 0.742 \\ UWavGesLibX & 0.804 & 0.799 & 0.811 & 0.802 & **0.958** \\ UWavGesLibY & 0.726 & 0.686 & 0.717 & 0.690 & **0.802** \\ UWavGesLibZ & 0.735 & 0.719 & **0.748** & 0.734 & 0.712 \\ Wafer & **0.996** & 0.991 & 0.995 & 0.991 & **0.996** \\ Wine & **0.827** & 0.731 & 0.750 & 0.731 & 0.808 \\ WordSynonyms & 0.682 & 0.690 & 0.700 & 0.662 & **0.701** \\ Worms & 0.671 & 0.618 & 0.658 & 0.592 & **0.684** \\ WormsTwoClass & 0.803 & 0.724 & 0.763 & 0.711 & **0.842** \\ Yoga & 0.807 & **0.810** & 0.796 & 0.797 & 0.807 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._  
Figure 3: Visualization of embedded vectors of ECG500 and UWaveGestureLibrary UCR test datasets with dimensionality reduction. Each class marked with different shapes and colors is well differentiable.
# A Review on Vibration Control Using Piezoelectric Shunt Circuits
## 3 Experimental Studies
[PERSON] et al. [124] introduced a technique for the online adaptation of multimode resonant shunts. By minimizing the relative phase difference between a vibration reference signal and the shunt current, circuit component values can be optimally tuned online. Experiments on a cantilever beam validate the proposed technique and demonstrate the simplicity of implementation. The adaptive law converges quickly and maintains optimal performance in the presence of environmental uncertainties. [PERSON] et al. [125] presented an energy-recycling method is studied that enables effective semi-active vibration suppression with piezoelectric transducers embedded or bonded to a structure. A simple electric circuit and a control law for multiple-degree-of freedom systems with multiple piezoelectric transducers are proposed for this method based on energy recycling. Numerical simulation of vibration suppression of a truss structure shows that this method is more effective in suppressing vibration than both a semi-active method without energy recycling and one based on the use of an optimally tuned passive system. A preliminary experiment with a truss structure also shows that this method can effectively suppress vibration in an actual structure. However, there was some discrepancy in the experimental results compared to the results of the numerical simulation performed assuming ideal linear characteristics of the piezoelectric transducers estimated from a static test.
## 2 Utilization of Various Nano-Modified Coatings for Corrosion Mitigation
### Carbon Allotrope-Based Nanoc coatings
It is significant to observe that by injecting and discharging the CIs' MBT, GAS NMs offered extra proactive corrosion prevention for epoxy coating. In affected regions, GAS-Coat had accomplished self-healing and continued to have higher corrosion resistance over prolonged exposure. GAS-Coat offers a significant deal of possibility for useful anticorrosion operations because it performs both active and passive corrosive protection. In order to create a proactive (inhibitive)/passive (barrier) anti-corrosion covering solution, [PERSON] et al. [62] created a sustainable MOF centered on cerium (Ce-MOF) on GO nanosheets (GO@Ce-MOF). The 1,3,5-benzene tricarboxylic acid used in the construction of the Ce-MOF NPs produced a dense configuration resembling a straw sheaf. The Ce-MOF NPs were then housed in the GO as a nanocontainer, and the resulting NPs were then introduced to the epoxy matrices. Raman spectroscopy and transmission electron microscopy (TEM) were used to validate the effective production of NPs. TGA and BET techniques were used to measure the NPs' surface region and thermal behaviors. Utilizing the EIS approach and a salt spray experiment, the produced nanostructures' passive and active anti-corrosion abilities were examined in epoxy matrices. GO@Ce-MOF/corrosion EP's resistance was improved by about 500% over Blank/EP according to the EIS data from the damaged coverings after 48 h. Additionally, following 7 weeks of exposure to corrosive solutions, the GO@Ce-MOF/EP covering demonstrated better protective qualities, exhibiting low-frequency coefficients greater than 1010 \(\Omega\)cm\({}^{2}\). Similarly, unique N and S co-doped CDs (N, S-CD) with a significant S and N concentration of 19% and 17%, correspondingly, were created by [PERSON] et al. [92]. The Tafel data demonstrate that N, S-CDs are a highly effective mixed inhibitor, and the g ratio rises as N, S-CD levels increased. Since the polarization assessment and the EIS findings are in agreement, it could be concluded that a persistent N, S-CD adsorption coating could be created on the copper (Cu) substrate to substantially prevent Cu corrosion. The anti-corrosion capabilities of N, S-CDs were investigated in relation to temperature using the polarization curve. Though the corrosion procedure was accelerated by the temperature increase, Cu in a 0.5 M H\({}_{2}\)SO\({}_{4}\) medium at 298-318 K was well protected by N, S-CDs. The novel NMs exhibit outstanding efficiency for Cu (99.88%) at a dose of 50 mg in 0.5 M H\({}_{2}\)SO\({}_{4}\) medium; this research may offer a fresh perspective on the exploration of highly potent CIs for metal preservation that is also environmentally acceptable.
# Low Temperature Resistance Increase for Bitumen by Compounding with Tar
## 2 Materials and Methods
### Compounding  
The compounding of virgin bitumen with penetration grade 100-130 and the tar has been performed in the laboratory of the Kazakhstan Highway Research Institute by means of an electric mixer (rotation rate is equal to 450-500 revolutions per minute) with an electric hot plate.  
The technology for preparation of the compounded bitumen has been performed as follows:  
1. A sample of the virgin bitumen with penetration grade 100-130 has been selected in the required volume and prepared for compounding;
2. The virgin bitumen was gradually heated up to the temperature of 120 \({}^{\circ}\)C;
3. A previously prepared portion of the tar has been added at the mixing of the sample of the virgin bitumen with the rate of 450-500 revolutions per minute;
4. The virgin bitumen and the tar were mixed at a steady pace with the rate of 450-500 rotations per minute at the constant temperature of 120 \({}^{\circ}\)C for 30-40 min;
5. The prepared portion of the compounded bitumen cooled down to room temperature.  
The compounded bitumens have been prepared with the content of the tar at 5, 10, 15, 20, 25, 27 and 30% of bitumen weight.