esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methodology
### Experimental Details  
In our experiments, we investigated signal recovery from FL model updates with and without differential privacy. For our attacks, we used a deep neural network transformer model. This setup simulates a GIA threat, where a server-side adversary can observe raw model updates and attempt to reconstruct private input data. A recent study [55] has shown that transformers can be successfully used to process time-series signals. For example, for classifying time-series using positional encoding and attention over time [56] or combining trend/seasonality decomposition with attention using auto-correlation attention mechanism [57], or using patch-based encoding, inspired by the Vision Transformer on multivariate time-series forecasting benchmarks. Transformer-based methods are increasingly applied to time-series data due to their ability to capture long-range dependencies and interactions, which is particularly beneficial for tasks such as prediction, anomaly detection and classification.  
As a data set, we used the data set on the ageing of lithium-ion batteries [58], which is described in more detail in the next subsection. All tasks are implemented using the Python 3.10.16 programming language and the PyTorch 2.5.1 machine learning library. Differential privacy is implemented using the OPACUS Privacy Engine Toolbox.  
In our experiments, we first trained transformer-based battery RUL estimation models (with 6 transformer-encoder blocks) under different DP levels. The experiments were performed with a learning rate of 0.0001 and the Adam optimiser. This process generated gradients/model updates and simulated an FL use case. We then applied GradInv methods to recover the input signals responsible for the model updates. The results are presented in more detail in the next section.  
The input signal is composed of the current I[n] and the voltage U[n], which are concatenated to form a tensor of the shape (B, 30, 128), where B represents the batch size. The output consists of the time-series of the discharge capacitance \(\Delta C\) with a shape of (B, 1920). In addition, the outputs of the transformer layer can be connected to layers that are responsible for estimating the battery's remaining useful life (RUL), such as linear classification layers (LC). The structure of the model used is shown in Figure 3.  
When considering time series data, special aspects must be taken into account, such as temporal dependencies, possible periodicity and sensitivity to timing. In FL, for example, each client could have time series data from different time periods or from different sensors. The model updates would encapsulate patterns in these sequences.
## 3 Results
### Competitiveness Evaluation Results of French-Speaking African Countries
In contrast, adaptive LASSO uses differentiated weight penalties to ultimately screen out 8 variables, including 3 core factors and 5 secondary factors, which not only avoids the redundant retention of traditional LASSO but also overcomes the problem of missing core factors of random forests. From the perspective of model fitting indicators, the BIC value of adaptive LASSO (126.8) is lower than that of traditional LASSO (142.3) and random forest (138.5), indicating that it maintains a better fitting effect while streamlining variables. The consistency analysis of core factors shows that the proportion of variables overlapping between adaptive LASSO and other methods reaches 75%, and the only newly added \"R&D expenditure ratio\" has been confirmed to be a key driving factor of competitiveness in economic theory, further confirming the scientific nature of its screening results. \begin{table}
\begin{tabular}{l l l l l} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{2}{l}{**Number of**} & \multicolumn{1}{l}{**Core Factor**} & \multirow{2}{*}{**BIC Value**} & \multirow{2}{*}{**Key Flaws**} \\  & **Filter** & & & \\  & **Variables** & & & \\ \hline Adaptive-LASSO & 8 & 75\% & 126.8 & - \\ Traditional LASSO & 12 & 62.5\% & 142.3 & Keep redundant variables \\ Ridge regression & 30 & 50\% & 189.5 & Unable to remove variables \\ Random forest & 8 & 62.5\% & 138.5 & Missing the key factor “R\&D expenditure” \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison results of adaptive LASSO and alternative methods.
## 6 Methodology of Sample Implementation
### Implementation of VR Conferencing
#### 6.1.5 Result  
In the VR conference room solution given above, the basic functions of the conference were achieved. Users could switch perspectives horizontally, make speeches, and communicate with other participants. In terms of listening feeling, users heard the voices of different participants from different directions and experienced the effect of room reverberation. The NetCode latency and VoIP latency in the LAN were acceptable. Character animation and scenes could be optimized by referring to 3D games, and more applicable interactive functions could be further explored.
# Optimization of Pin Type Single Screw Mixer for Fabrication of Functionally Graded Materials
## 3 Results and Discussion
### Numerical Validation
Figure 10: Response curve of three types screw mixer for changes in material A at the outlet. **(a)** is the curve of change in volume fraction of material A at the outlet, and **(b)** is the probability density function of residence time distribution. Moreover, the degree of chaotic mixing was quantified through the utilization of Equation (6), which calculates the Lyapunov exponent. A larger positive Lyapunov exponent signifies a more pronounced level of chaotic mixing. During the Lyapunov exponent calculation process, particles with close initial distances were selected as clusters, utilizing the spatial coordinates of the five randomly tracked particles over time, as previously described. The sampling frequency was set at 1 Hz, with a mixing period of 100 s. Each screw type yielded five sets of Lyapunov exponents, which were averaged to characterize the final degree of chaotic mixing, as presented in Table 6. The results clearly demonstrate that the optimized mixer generates over three times the level of chaotic mixing compared to the other two screw types. Figure 13 illustrates the Poincare map representing the behavior of two isolated particles influenced by the presence of three screws over flow durations of 100 s and 200 s. The x and y coordinates on the Poincare map represent the specific positions of these particles. The findings demonstrate that a screw devoid of pins and a screw equipped with symmetrically shaped pins yield similar cross-sectional flow trajectories for the two separated particles. This similarity has a detrimental effect on radial mixing. A comparison between Figure 13c,f shows that the optimized pin shape mixer allows the two separated particles more uniformly distributed in the radial direction of the mixing chamber after 100 s of mixing. Moreover, it is observed that the trajectories of these particles exhibit increased chaotic behavior in the cross-section of the optimized pinned screw. This results in a higher number of cross-foldings and, thus, enhances homogeneity in the extrusion process. Thus, it is verified that the optimization-induced asymmetry in the pin shape allows the mixing fluid to continuously overlap and merge after passing through the upper and lower surfaces of the pin. This phenomenon enhances chaotic convection in the mixing chamber, thereby enhancing radial mixing and reducing axial mixing. Finally, this leads to a reduction in the transition delay time. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Screw without Pins**} & \multicolumn{2}{c}{**Screw with**} & \multirow{2}{*}{**Screw with**} \\  & & **Cylindrical Pins** & \\ \hline Lyapunov exponents & 0.007833 & 0.00965 & 0.03402 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Lyapunov exponents of each screw mixer. Figure 12: Path line of five random particles in the mixing chamber.
# A Multi-Gateway Behaviour Study for Traffic-Oriented LoRaWAN Deployment
## 4 Simulations and Results Analysis  
To study multi-gateway behaviour and its correlation with the parameters, we conducted several simulations using the NS-3 simulator. Our simulation took into consideration five parameters, which are the number of EDs deployed in the network, the payload length, the generation packet period, the number of deployed gateways, and whether or not the traffic required an ACK. Table 3 summarises the used simulation parameters. We note that we used the LoRaWAN implementation available in [25]. In addition, we used the Simulation Execution Manager (SEM) for NS-3 [26] to manage all the discussed parameters. We also note that the obtained results were the average of ten simulations for each parameter combination. The network formed a star topology architecture composed of several nodes ranging from 100 to 1000, deployed randomly over a radius of 7.5 km. The number of GWs varied from 1 to 5 with a predefined fixed position. The first GW was placed at the centre of the network. The simulation time was 60 min, where each node sent a data packet with a frequency varying from one packet per minute to one packet every 17 min. The data payload varied from 10 to 100 bytes.
## 3 Result and Discussion
### Drifting Snow Susceptibility Judgment  
As we can see in Figure 13, along the railway, the places with higher probability of drifting snow occurrence are located in Kangding County and Litang County, and there is a long railway line passing through the drifting snow susceptible areas in Litang, Batang, and Baiyu counties, with a total length of about 321 km that may experience drifting snow along the line. The entire area of Ya'an City has almost zero probability of drifting snow occurrence; about 12 km of railway in the adjacent area of Luding County and Tianquan County may experience drifting snow, with a probability of 15%; in Kangding County, there are two sections of railway that may experience drifting snow phenomenon, located at 101.9\({}^{\circ}\) E-102\({}^{\circ}\) E and 101.6\({}^{\circ}\) E-101.8\({}^{\circ}\) E, respectively, with lengths of 20 km and 23 km, respectively, and probabilities of 12% and 8%, respectively; about 22 km of railway in Yajiang County at 101.2\({}^{\circ}\) E-101.4\({}^{\circ}\) E may experience drifting snow, with a probability of about 4%; about 50 km of railway in Litang County at 99.8\({}^{\circ}\) E-100.2\({}^{\circ}\) E has a probability of 8%; about 87 km of railway passing through Batang County and Baiyu County at 99.15\({}^{\circ}\) E-99.7\({}^{\circ}\) E has a probability of 4% for drifting snow phenomenon; about 24 km of railway in Jomda County at 98.25\({}^{\circ}\) E-98.45\({}^{\circ}\) E has a probability of 6%; about 71 km of railway passing through Qamdo County and Chaya County at 97.50\({}^{\circ}\) E-97.90\({}^{\circ}\) E has a probability of 5%; about 12 km of railway in Chaya County and Basu County at 97.35\({}^{\circ}\) E-97.40\({}^{\circ}\) E has a probability of 6%. The railway located in Kangding County has a slightly higher probability of drifting snow phenomenon than other areas, and the length of the railway affected is larger, so the railway in this section needs to strengthen its protection against drifting snow.
###### Abstract  
Visible light communication (VLC) has recently gained significant academic and industrial attention. VLC has great potential to supplement the functioning of the upcoming radio-frequency (RF)-based 5G networks. It is best suited for home, office, and commercial indoor environments as it provides a high bandwidth and high data rate, and the visible light spectrum is free to use. This paper proposes a multi-user full-duplex VLC system using red-green-blue (RGB), and white emitting diodes (LEDs) for smart home technologies. It utilizes red, green, and blue LEDs for downlink transmission and a simple phosphor white LED for uplink transmission. The red and green color bands are used for user data and smart devices, respectively, while the blue color band is used with the white LED for uplink transmission. The simulation was carried out to verify the performance of the proposed multi-user full-duplex VLC system. In addition to the performance evaluation, a cost-power consumption analysis was performed by comparing the power consumption and the resulting cost of the proposed VLC system to the power consumed and resulting cost of traditional Wi-Fi based systems and hybrid systems that utilized both VLC and Wi-Fi. Our findings showed that the proposed system improved the data rate and bit-error rate performance, while minimizing the power consumption and the associated costs. These results have demonstrated that a full-duplex VLC system is a feasible solution suitable for indoor environments as it provides greater cost savings and energy efficiency when compared to traditional Wi-Fi-based systems and hybrid systems that utilize both VLC and Wi-Fi.  
full-duplex; smart home; visible light communication; energy consumption Article
###### Abstract
Multiple iterations, utilizing both original and virtual pilots, allow for the accurate estimation of all reference frame data pixels. Simulation results demonstrate a significant increase in achievable data rate, nearly doubling the performance of the 2D-DFC communication scheme while maintaining display unobtrusiveness. The work in [7] focuses on designing a wide spectrum zoom system for in vivo fluorescence imaging devices operating in the visible light spectrum to NIR-II spectrum. The system achieves desirable performances in terms of the modulation transfer function (MTF), distortion, and aberration correction, meeting the requirements for each optical element. Reference [8] presents a cost-effective visible light positioning (VLP) system for indoor positioning, combining LED flat panel lights and barcodes. The proposed \"pseudo-two-light positioning\" algorithm, assisted by angle sensors, achieves centimeter-level positioning accuracy. Finally, ref. [9] addresses thermal deformation challenges in a laser communication satellite by reducing optical axis angle fluctuations via optimization design and adaptable isolation. The work enhances the stability and efficiency of laser communication systems. Conceptualization, S.-Y.J. ; methodology, P.S. ; software, S.-Y.J. and P.S. ; validation, S.-Y.J. and P.S. ; formal analysis, P.S. ; investigation, P.S. ; resources, S.-Y.J. ; data curation, P.S. ; writing--original draft preparation, P.S. ; writing--review and editing, S.-Y.J. and P.S. ; visualization, S.-Y.J. and P.S. ; supervision, S.-Y.J. ; project administration, S.-Y.J. ; funding acquisition, S.-Y.J. and P.S. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Research Foundation of Korea (NRF) through the grant NRF-2022R1G1A1004799. The Guest Editor would like to thank all authors who submitted their valuable and insightful contributions to this Special Issue, addressing key challenges with respect to optical camera communication as well as its applications. The Guest Editor would also like to thank the reviewers whose thorough and timely reviews were crucial for the success of this SI. The author declares no conflict of interest.
# Quadrupedal Robots Whole-Body Motion Control Based on Centroidal Momentum Dynamics
## 2 Methods
### Application to Quadrupedal Robot Dynamic Motion
#### 2.3.2 Desired Centroidal Momentum for Motion Control  
The motion of the robot is determined by the desired linear and angular momentum rate change. For angular momentum, we employ the PD feedback control policy to regulate the CoM orientation. When the robot is walking in a straight line, \(q_{d,b}\) is set to zero.  
\[\dot{k}_{G,d}=\bar{I}_{G}\left[-K_{P,k}\left(q_{b}-q_{d,b}\right)-K_{D,k}\dot{q }_{b}\right] \tag{23}\]  
To encode a whole-body rotation given the desired motion plan, \(\bar{I}_{G}\) can be found from the mass matrix by computing the centroidal composite-rigid-body inertia of the system \(I_{G}\) about the CoM.  
\[\begin{split} I_{G}&={}^{1}X_{G}^{T}\left[\sum_{i= RF}^{RH}H_{i}^{11}(\theta_{i})\right]{}^{1}X_{G}\\ &=\begin{bmatrix}M&0\\ 0&\bar{I}_{G}\end{bmatrix}\end{split} \tag{24}\]  
For linear momentum, a commanded \(l_{G,d}\) is formed from the PD control on the desired CoM  
\[l_{G,d}=M\left[-K_{D,l}^{x}\left(\dot{r}_{b}^{x}-\dot{r}_{b,d}^{x}\right),-K_{ D,l}^{y}\left(\dot{r}_{b}^{y}-\dot{r}_{b,d}^{y}\right),-K_{P,l}^{z}\left(\dot{r}_{ b}^{z}-\dot{r}_{b,d}^{z}\right)-K_{D,l}\dot{r}_{b}^{z}\right]^{T} \tag{25}\]  
The desired velocity of the CoM \(\dot{r}_{b,d}^{x}\) and \(\dot{r}_{b,d}^{y}\) is the output of the walking pattern, which is described in Section 2.3.1. The CoM height \(\dot{r}_{b,d}^{z}\) is often assumed to be constant.
# Structural Information Reconstruction of Distorted Underwater Images Using Image Registration
## 1 Introduction
In the first stage, a gaussian blur is added to sequence frames to improve the registration effect, and in the second stage, a rank minimization is used to dislodge sparse noise. In our previous research [21], an iterative robust registration algorithm was employed to overcome the structural turbulence of the waves by registering each frame to a reference frame. The high-quality reference frame is reconstructed by the patches selected from the sequence frames and a blind deconvolution algorithm is performed to improve the reference frame. [PERSON] et al. [22] proposed a registration approach using pixel shift maps, where registers image sequence against the sharpest frame to obtain pixel shift maps. Motivated by deep learning technology, [PERSON] et al. [23] introduced the trained convolution neural network to dewarp dynamic refraction, which has a larger requirement of training samples and training cycles. Recently, [PERSON] et al. [24] assumed that water fluctuation possesses spatiotemporal smoothness and periodicity. Based on this hypothesis, compressive sensing technology was combined with local polynomial image representation. Later, based on the periodicity, a Fourier based pre-processing was proposed to correct the apparent distortion [25]. Most of the above studies were performed to restore the whole image from an underwater sequence. However, some structural information of the image is expected to be obtained in some cases, such as underwater cable number observing. In this paper, a new image restoration approach for underwater image sequences using an image registration algorithm is proposed. In our approach, the lucky patches fusion was employed to discard the patches with severer warping, then a guided filter algorithm was used to enhance object boundary in the fused image. An iterative registration algorithm was applied to remove most of the distortions in the frames, which registers frames against the enhanced image. After the registration process, the unstructured sparse noises were eliminated by principal component analysis (PCA) and patches fusion technology to produce undistorted image sequences and frames. Experiments present that the proposed method has better performance on structural information reconstruction [20; 21]. The remaining part of this paper proceeds as follows: Section 2 presents an overview of the proposed method and introduces it in detail, Section 3 shows the results of the experiment, Section 4 analyzes and discusses the experimental results, and Section 5 concludes the paper.
# Research on Nonlinear Vibration Characteristics of Internal Beveloid Gear Transmission System
###### Abstract  
The internal beveloid gear has good scientific research value and a broad application field. However, there is a lack of research on the nonlinear vibration characteristics of internal beveloid gears. The present study establishes a nonlinear vibration model that takes into account axial vibration, gear torsional vibration, and radial support vibration. The effects of various excitation parameters on the vibration characteristics of the gear transmission system are analyzed and computed using the Runge-Kutta method. After analyzing the dynamic model of the gear pair using numerical methods, the harmonic balance method is employed to obtain the theoretical analytical solution for a single\(-\)stage gear. The obtained results are compared with the velocity and acceleration time\(-\)domain response curves obtained from the numerical method, and they show excellent agreement.  
beveloid gears; Runge-Kutta method; nonlinear vibration; harmonic balance method +
Footnote †: journal: Applied Sciences
###### Abstract  
We demonstrate full-field optical coherence microscopy (OCM) using an ultrathin forward-imaging short multimode fiber (SMMF) probe with a core diameter of 50 \(\upmu\)m, outer diameter of 125 \(\upmu\)m, and length of 7.4 mm, which is a typical graded-index multimode fiber used for optical communications. The axial and lateral resolutions were measured to be 2.14 \(\upmu\)m and 2.3 \(\upmu\)m, respectively. By inserting the SMMF 4 mm into the cortex of an in vivo rat brain, scanning was performed to a depth of 147 \(\upmu\)m from the SMMF facet with a field of view of 47 \(\upmu\)m. Three-dimensional (3D) OCM images were obtained at depths ranging from approximately 20 \(\upmu\)m to 90 \(\upmu\)m. Based on the morphological information of the resliced 3D images and the dependence of the integration of the OCM image signal on the insertion length, the obtained 3D information of nerve fibers has been presented.  
full-field optical coherence microscopy; endoscopic imaging; medical optics instrumentation; fiber optics imaging +
Footnote †: journal: Applied Sciences
# Deep Learning-Based ECG Arrhythmia Classification: A Systematic Review
## 3 Results
### DL Methodology
#### 3.3.3 Classification Categories  
Out of 368 selected studies, 118 (32%) studies categorized ECG signals into five classes. The large proportion stems from the fact that most studies utilize MITDB as their ECG databases, where ECG signals have been categorized into five essential groups (N: Normal beat; S: Supraventricular ectopic beat; V: Ventricular ectopic beat; F: Fusion beat; Q: unknown beat) following the American Association of Medical Instrumentation (AAMI) standards [77]. Some studies [68;78] follow the AAMI standards but calculate the classification performance of categories of N, S, V, and F, which account for major categories in the ECG dataset. Binary classification (19%, 73 out of 368) is mostly used to identify one certain arrhythmia type, such as AF [79] and left ventricular dysfunction [80]. The conclusions from many studies suggest that accurate multi-class arrhythmia classification is more challenging [19;20].