esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Meta-Regression and Heterogeneity
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline  & & **Effect** & **Lower Limit** & **Upper Limit** & **Z** & \(p\) & **Tau** & **Tau2 (SE)** & **I2** & **R2** & **df** & **Q** & \(p\) \\ \hline \multicolumn{2}{c}{Static} & & & & & & & & & & & & & & \\ Total warm-up & Constant & \(-0.9355\) & \(-2.728\) & \(0.857\) & \(-1.34\) & \(0.237\) & \(0.002\) & \(0.000\) & \(0\%\) & \(0.0\%\) & \(6\) & \(6.1\) & \(0.301\) \\  & Moderator & \(0.091\) & \(-0.059\) & \(0.177\) & \(1.29\) & \(0.254\) & & \((\text{SE}=0.0695)\) & & & & \\ \hline Time aerobic & Constant & \(-0.5098\) & \(-1.296\) & \(0.276\) & \(-1.5\) & \(0.173\) & \(0.045\) & \(0.002\) & \(2\%\) & \(0.0\%\) & \(9\) & \(9.6\) & \(0.298\) \\ warm-up & Moderator & \(0.055\) & \(-0.065\) & \(0.175\) & \(1.06\) & \(0.321\) & & \((\text{SE}=0.0514)\) & & & & \\ \hline \multicolumn{2}{c}{Set} & \multicolumn{6}{c}{not enough data} & & & & & & & & & & \\ \hline \multirow{2}{*}{Repetitions} & Constant & \(-0.143\) & \(-1.232\) & \(0.947\) & \(-0.30958\) & \(0.766\) & \(0.109\) & \(0.012\) & \(10\%\) & \(0.0\%\) & \(8\) & \(9.9\) & \(0.196\) \\  & Moderator & \(-6.84\times 10^{-4}\) & \(-0.46\) & \(0.459\) & \(-0.00352\) & \(0.997\) & & \((\text{SE}=0.0588)\) & & & & \\ \hline \multirow{2}{*}{Stretching time} & Constant & \(-0.4401\) & \(-1.156\) & \(0.276\) & \(-1.45\) & \(0.19\) & \(0.001\) & \(0.000\) & \(0\%\) & \(0.7927\) & \(8\) & \(8.5\) & \(0.293\) \\  & Moderator & \(0.0162\) & \(-0.019\) & \(0.052\) & \(1.08\) & \(0.317\) & & \((\text{SE}=0.0353)\) & & & & \\ \hline \multirow{2}{*}{Rest stretching} & Constant & \(0.0125\) & \(-1.22\) & \(1.245\) & \(0.0282\) & \(0.979\) & \(0.264\) & \(0.070\) & \(35\%\) & \(0\) & \(5\) & \(6.7\) & \(0.143\) \\  & Moderator & \(-0.0228\) & \(-0.129\) & \(0.083\) & \(-0.5968\) & \(0.583\) & & \((\text{SE}=0.1391)\) & & & & \\ \hline \multicolumn{2}{c}{Dynamic} & & & & & & & & & & & \\ \hline Total warm-up & Constant & \(0.6314\) & \(-1.977\) & \(3.239\) & \(0.672\) & \(0.538\) & \(0.167\) & \(0.028\) & \(21\%\) & \(0\) & \(5\) & \(5.8\) & \(0.214\) \\  & Moderator & \(-0.0315\) & \(-0.208\) & \(0.145\) & \(-0.495\) & \(0.647\) & & \((\text{SE}=0.0933)\) & & & & \\ \hline \multicolumn{2}{c}{Time aerobic} & Constant & & & & & & & & & & & \\ warm-up & Moderator & & & & & & & & & & & \\ \hline \multirow{2}{*}{Set} & Constant & \(-0.0292\) & \(-0.651\) & \(0.592\) & \(-0.106\) & \(0.918\) & \(0.002\) & \(0\%\) & \(0\) & \(10\) & \(10.091\) & \(0.343\) \\  & Moderator & \(0.1159\) & \(-0.35\) & \(0.582\) & \(0.563\) & \(0.587\) & & \((\text{SE}=0.0353)\) & & & & \\ \hline \multirow{2}{*}{Repetitions} & Constant & \(0.0518\) & \(-0.317\) & \(0.421\) & \(0.317\) & \(0.758\) & \(0.001\) & \(0\%\) & \(0\) & \(10\) & \(10.186\) & \(0.336\) \\  & Moderator & \(0.011\) & \(-0.041\) & \(0.063\) & \(0.48\) & \(0.643\) & & \((\text{SE}=0.0344)\) & & & \\ \hline \multirow{2}{*}{Stretching time} & Constant & & & & & & & & & & & \\  & Moderator & & & & & & & & & & & \\ \hline \end{tabular}
\end{table} 
Table 3: Effects of moderating variables.
# A Review of PCI Express Protocol-Based Systems in Response to 5G Application Demand
## 4 Technical Strategy Using PCI Express, CXL, USB, NVMe, and Security
### Technical Strategy Using USB  
Thunderbolt 3 was included in USB and became USB 4.0. Thunderbolt 3 with PCIe and DP is included in USB 4.0, which extends the USB pin device and protocols for some combined features through the USB connector. Based on the Type-C cable with different pin definitions, Thunderbolt enables more protocols: USB, Display Port, PCIe, and Thunderbolt. Power delivery methods were also enhanced [24; 35].
## 3 Influence Metrics
### Quality of Service Metrics Analysis  
Latency, overhead, or hop count are QoS metrics that allow us to assess the performance and efficiency of the network. By quantifying the latency, we can determine how quickly data or messages are transmitted from the source to the destination. An overhead calculation helps assess the additional resources or data required to support the communication process. By quantifying overhead, we can identify potential inefficiencies or resource-intensive aspects of the network. This information is valuable for optimizing network performance and ensuring efficient resource utilization.  
On the other hand, a hop count calculation helps evaluate the number of network devices or \"hops\" required for data to travel from the source to the destination. Lower hop counts generally imply a more direct and efficient routing path, resulting in reduced latency and improved overall network performance.  
Overall, accurate calculation and analysis of latency, overhead, and hop count are crucial for performance evaluation, resource optimization, reliability assessment, routing efficiency analysis, identifying areas for improvement, and making informed decisions regarding network design and configuration.  
In summary, precise calculations and analyses of latency, overhead, and hop count are pivotal for performance evaluation, resource optimization, reliability assessment, and routing efficiency analysis. To fulfill these requirements, we have implemented a set of algorithms to evaluate these QoS metrics and incorporate our proposals into The ONE--an opportunistic network simulator that is well-suited for simulating and studying such networks, as mentioned earlier.
## 2 Pattern-Matching Algorithms Review
### Hashing-Based Technique  
Hashing-based algorithms [12; 13] compare the hash values instead of comparing the packet payload and the pattern character by character. In the study numbered [14], the matching performance of the hashing-based Rabin-Karp (RK) [12] algorithm on IDSs is evaluated. There are also DPI applications in which the matching performance of the parallel application of this algorithm on the GPU is assessed [15; 16]. Each thread carries out the algorithm procedure for all patterns, starting from the position corresponding to the thread index in the multi-pattern-matching version of the RK algorithm performed on the GPU. An increase in the number of patterns to be examined requires additional hash calculations for the RK algorithm, and the matching speed decreases in large pattern datasets. Thus, RK is not an efficient algorithm for multi-pattern matching [16].
# Wintertime Local Wind Dynamics from Scanning Doppler Lidar and Air Quality in the Arve River Valley
## 2 Passy-2015 Field Experiment
### Instrumentation and Measurement Strategy  
Figure 1 and Table 2 present the instruments used in this study and the three corresponding sites deployed within the Passy basin. A complete description of the large set of instruments deployed is available in [29]. Situated in the valley centre, Site 1 was the most instrumented. Its elevation is taken as the valley level reference and used to define elevation in metres Above Valley Level (m AVL). Site 1 was dedicated to the vertical description of the atmosphere from the ground up to a few kilometres AVL. A profiler Doppler wind lidar (DWL) the WLS8-5 was used in this study. It provided profiles of wind speed and direction every 3 s from 40 m up to 500 m AVL with a 20 m vertical resolution. More technical details of the WLS8-5 specifications are given in Table 3. During IOPs, radiosoundings were launched every 3 h using a technique of reusable radiosondes developed by [PERSON] et al. [38]. Radiosoundings provided profiles of wind, temperature and humidity, with a 10 m vertical resolution up to 2000 m AVL. Fog episodes were detected using data from a Present Weather Detector (PWD22) and a Ceilometer (CT25K). The CNR1 net radiometer measuring radiative fluxes was used to derived the surface albedo. The bare ground has an albedo of 0.2 and a threshold of 0.5 was used to identify the days with snow cover (black dots in Figure 2).  
Site 2 was installed in the southeastern part of the valley, 2.6 km away from Site 1 and about 40 m higher. The main purpose of this site was to describe the spatial variability of the lower levels of the atmosphere. Its panoramic view permitted scanning of the atmosphere with horizontal and vertical cross-sections. A scanning DWL was deployed and will be described in the following section. The pollutant monitoring was performed at Site 3 by an automatic TEOM-FDMS station of the local air quality agency Atmo Auvergne-Rhone-Alpes. It provided hourly-averaged PM10 concentrations. TEOM-FDMS stations are also routinely-operated at Sallanches, Marnaz and Chamonix (blue stars in Figure 1). Finally, some of the 20 Meteo-France automatic weather stations located in the area of interest were also used in this study (Annecy, Sallanches and Mont-Arbois, yellow squares in Figure 1).
###### Abstract  
This paper proposes a stereo-vision-based method that detects and registers the positions and postures of muti-type, randomly placed miniature circuit breaker (MCB) components within scene point clouds acquired by a 3D stereo camera. The method is designed to be utilized in the flexible assembly of MCBs to improve the precision of gripping small-sized and complex-structured components. The proposed method contains the following stages: First, the 3D computer-aided design (CAD) models of the components are converted to surface point cloud models by voxel down-sampling to form matching templates. Second, the scene point cloud is filtered, clustered, and segmented to obtain candidate-matching regions. Third, point cloud features are extracted by Intrinsic Shape Signatures (ISSs) from the templates and the candidate-matching regions and described by Fast Point Feature Histogram (FFFH). We apply Sample Consensus Initial Alignment (SAC-IA) to the extracted features to obtain a rough matching. Fourth, fine registration is performed by employing Iterative Closest Points (ICPs) with a K-dimensional Tree (KD-tree) between the templates and the roughly matched targets. Meanwhile, Random Sample Consensus (RANSAC), which effectively solves the local optimal problem in the classic ICP algorithm, is employed to remove the incorrectly matching point pairs for further precision improvement. The experimental results show that the proposed method achieves spatial positioning errors smaller than 0.2 mm and postural estimation errors smaller than 0.5\({}^{\circ}\). The precision and efficiency meet the requirements of the robotic flexible assembly for MCBs.  
stereo vision; flexible assembly; spatial positioning; postural estimation; sequential strategy +
Footnote †: journal: Applied  
Applied Sciences
# VANET Clustering Based Routing Protocol Suitable for Deserts
## 4 Clustering and Cluster Management
### Cluster Head Election Principles
#### 4.1.3 Vehicle Velocity Priority  
We assume: \(v_{1}\), \(v_{2}\), \(v_{3}\)... \(v_{n}\) are the instantaneous velocities of the vehicles and \(v_{\mu}\) is the mean velocity at time instant \(t\). Calculate \(P_{v}\) for each vehicle as follows:  
\[P_{v}=\frac{1}{n}\left(v(i)-v_{\mu}\right)\quad\forall i\in\phi_{n} \tag{13}\]  
For one cluster, the velocity priority of the vehicles can be obtained by:  
\[P_{v_{I}}=\left[\begin{array}{cccc}P_{v_{1}}&P_{v_{2}}&P_{v_{3}}&...&P_{v_{ N_{c}}}\end{array}\right] \tag{14}\]  
These values can be normalized by scaling them between zero and one as:  
\[P_{v_{norm}}=\frac{P_{v}(i)-min(P_{v_{I}})}{max(P_{v_{I}})-min(P_{v_{I}})} \quad\forall i\in\phi_{n} \tag{15}\]  
A vehicle with the lowest \(P_{v_{norm}}\) has the highest velocity priority.
# Localization of Radio Sources Using High Altitude Platform Station (HAPS)
## 3 Results  
This section describes the localization simulations performed in this study. The simulations were performed for cases where a single stationary radio source and multiple stationary radio sources exist. Additionally, the number of sources was assumed to be unknown, and localization was carried out using the MUSIC (Multiple Signal Classification) method.
# Design of Indoor Visible Light Communication PAM4 System
## 5 Results and Analysis  
### Simulation  
After completing the overall design of the FPGA, the software simulation of the system is carried out, and the code is written in Verilog language. After the compilation is passed smoothly, the testbench test script is written, and then the simulation result is shown in Figure 17, which is converted into a waveform, as shown in Figure 18. The clk is the system clock signal, nrz_data_1 and nrz_data_2 are the original two NRZ signals, pam4_level is the encoded PAM4 signal, and the output signal is delayed compared with the input signal, which is a normal phenomenon. According to the principle of the PAM4 signal, different input signals output four different amplitude information, corresponding to four symbols. It can be seen from Figure 17 that the output four amplitudes \"0\", \"1\", \"3\", \"2\" correspond to symbols \"00\", \"01\", \"11\", \"10\" respectively, which conforms to the criterion of gray coding, that is, only one adjacent symbol is different.  
The receiver is simulated and verified. First, the clock signal is recovered from the PAM4 signal, and then the frame synchronization and decoding are performed based on the clock signal. Since a PAM4 data frame designed in this paper contains a frame header and multiple sets of PAM4 data, after detecting the frame header, when the output frame synchronization signal is at a low level (the frame synchronization signal is valid at a high level), the data segment of the PAM4 data frame is PAM4 decoded. The decoding simulation result is shown in Figure 19. The clk is the recovered bit synchronization signal, which acts as the clock signal of the receiving end. The pam4_level is the PAM4 signal to be decoded; the output signal is also delayed compared to the input signal. The recovered two NRZ signals and the original nrz_data_1, nrz_data_2 comparison can be seen by calculating the algorithm in the case where the bit synchronization clock as a reference clock can successfully recover two NRZ signals, verifying that the decoding scheme is feasible.
# Predictive Control for Current Distortion Mitigation in Mining Power Grids
## 1 Introduction
The authors of [28] use the CPT to share imbalances and harmonics in four-wires droop-based MGs. The CPT is used to decompose currents and powers in the balanced, unbalanced and distorted components. Then, virtual impedance loops are implemented. Similar approaches for imbalance sharing are proposed in [29; 30; 31]. Nevertheless, these approaches are based on PI controllers and use virtual impedance loops computed via power theories. It has been validated that virtual impedance loops do not guarantee the sharing of single-phase powers. In [32], current harmonics components are detected by using fast Fourier transform and used as initial conditions for a discrete-time model of the converter's output filter. In this case, a continuous control set MPC is used for minimizing the overall system distortion in a marine vessel power grid, and, thus, Kirchhoff laws are used to solve the power flow. By using current as the optimization variable, capacity constraints are included to avoid overpassing maximum values, notably present in the presented simulation results. Another application of continuous control set MPC for power quality is shown in [33], where independent synchronous reference frames are used to estimate phase voltage vectors in order to compensate imbalances in a microgrid. This approach uses consensus of reactive power, among distributed generators, to satisfy phase voltage unbalance rate constraints in a cooperative way. Based on this context, this paper proposes a novel MPC scheme for current distortion mitigation by including power harmonics compensation and total current distortion as optimization constraints. This MPC-based solution is justified because of the optimal distribution of the control effort along the prediction horizon, and the bounding of the solution space through equality and inequality constraints. The contributions of this work are stated as follow:  
* A frequency harmonics decomposition of real power is proposed, enabling control of their magnitudes by an MPC and of their angle phases by a traditional PI controller. * A reformulation of the MPC optimization problem is performed, in order to control two current harmonics components by manipulating one power harmonic component and satisfying current distortion requirements imposed by IEEE std 1547. * As a result of previous contributions, the proposed scheme was validated in a Hardware-In-the-Loop (HIL) system, validating its capability to be synthesized in real-time applications and embedded devices. The rest of this paper is organized as follows. In Section 2 preliminary concepts and the mathematical formulation of power bounds to current harmonics control are derived. In Section 3, the optimization problem used by the MPC scheme is stated, whereas a real-time simulation setup and the results of this proposal are presented in Section 4. Finally, conclusions are drawn in Section 5.
# To What Extent Are the Effects of UV Radiation on Grapes Conserved in the Resulting Wines?
## 2 Results
### Comparing the Effects of UV Radiation on Grapes and Wines  
A total of 51 variables related to phenolic composition and VOCs could be compared between grapes [9] and the resulting wines (Table 3). Only five of them showed a similar effect of the radiation regimes used on both grapes and wines: total flavonoids, four individual flavonoids (kaempferol-glucoside and three quercetin-glycosides), and one fatty acid (nonanoic acid). In all these cases, samples exposed to a combination of UV-A and UV-B radiation (either PAB or PAB\(\uparrow\) samples, or both), showed higher concentrations of those compounds than samples exposed to only PAR, or to a combination of PAR and either UV-A or UV-B (P, PA, and PB samples). In the remaining 46 variables, grapes and the respective resulting wines showed different responses (or no response) to the radiation regimes.
# Behavior of Circular CFST Columns Subjected to Different Lateral Impact Energy
## 1 Introduction
The effects of design variables on the residual axial bearing capacity were investigated by an extensive parametric study with 12 columns, which showed that axial load ratio had a significant effect on the residual axial bearing capacity with a low transverse reinforcement ratio. [PERSON] et al. [31] developed a theoretical model to evaluate the lateral strain, confining stress and axial stress in a CFST with a fiber reinforced polymer (FRP) jacket at various stages of load. [PERSON] et al. [32] developed the finite element model of CFST columns strengthened by carbon fiber reinforced polymer (CFRP) and investigated the effect of a CFRP-bound length on strength under transverse impact load. The test results showed that CFRP with an effective bound length improved the strength of the CFST column and the column strengthened by CFRP could successfully avoid buckling failure. [PERSON] et al. [33] investigated the dynamic response of steel tube columns filled with normal or recycled aggregate concrete under lateral projectile impact. They also studied the influences of CFRP jackets on the structural behavior of those columns. The results indicated that normal and recycled aggregate concrete filled steel tube (NACFST and RACFST) specimens had a similar displacement shape. The results also indicated that the confinement of the CFRP reduced the global displacement of both the RACFST and NACFST specimens. [PERSON] et al. [34] investigated blast resistance and the residual strength of CFST columns with the damage of close-range blast loads. The results indicated that CFST columns still had a large portion of axial load capacity even after close-range blast events. Given the research mentioned above, the mechanical behavior of columns under lateral impact load has been investigated with many numerical and test researches [35; 36]. A conclusion can be draw that CFST columns have great capacity of the lateral impact resistance. Nevertheless, there is little theoretical research and few calculation formulae about the residual ultimate axial capacity of the circular CFST columns after the lateral impact damage. This paper mainly investigates the effects of concrete compressive strength, impact location and impact energy on the residual ultimate axial capacity of the circular CFST columns. According to the experimental results, a calculation formula is proposed to predict the residual ultimate axial capacity of the specimens after the lateral impact load, which has been verified to be accurate.
## 2 Numerical Model and Method
### Design of Computation Domain  
In order to save computation resources and time while keeping a high simulation accuracy, the computation domain of the parallel foils is divided into several parts. The region close to the parallel foils is the inner zone, and the region outside the inner zone is the outer zone, as shown in Figure 2. Along the parallel foils' surface, the no-slip boundary condition is adopted. The interface between the inner and outer zone is set as the interface which connects the structured mesh and unstructured mesh. The velocity inlet is defined as \(U_{\infty}=1\) m/s and the pressure outlet is set. Based on the C programming language, the plunging and pitching motion characteristics in all simulations are controlled by the user-defined function (UDF) in Fluent. The dynamic mesh technique is applied to realize the reasonable transformation and reconstruction in the inner zone during the oscillation process, the quality of grids around the parallel foils is kept at a proper accuracy.  
As displayed in Figure 3, large transformation due to the oscillation of foils occurs in the inner zone grid. Thus, the unstructured mesh is selected for the inner zone, which is denser and where it is easier to improve the grid quality. The structured mesh is adopted at the foil surface to ensure the computation accuracy of the boundary layer near the foil surface. For the outer zone, there is a much smaller transformation during oscillation, so the sparse structured mesh is used here to save the computation time. The mesh contains \(7.5\times 10^{4}\) cells, the height of the first cell in the boundary layer is set as \(10^{-5}c\) to satisfy the computation accuracy.  
Figure 1: The structure and oscillation process of parallel foils: (**a**) \(t/T=0\)–\(0.5\); (**b**) \(t/T=0.5\)–\(1\).
# Kalman-Filter-Based Tension Control Design for Industrial Roll-to-Roll System
## 5 Experimental Verification
### Experimental Results  
In order to evaluate the tension tracking performance of the proposed control scheme, experiments were carried out under the following conditions. The web was transported at a constant speed by the feeder motor and the tension command had a section varying from 0 N to 100 N. Figure 10 shows the experimental results for verifying the performance of the KF. As shown in Figure 10b, the tracking error could be reduced and the bandwidth could be increased when signal processing was performed with the proposed KF relative to the LPF, which is a conventional signal processing method in R2R systems.  
Figure 11 shows the results of applying the proposed control scheme in the case of signal processing with KF. Particularly, the tracking performance of the FF controller was powerful in the transient section where the tension changes. Moreover, the experimental results demonstrate that the DOB is effective in compensating for disturbance and model uncertainty.  
Figure 11: Tracking error for three different control cases.  
Figure 10: Experimental results to verify the effectiveness of KF: (**a**) Reference and measured tension; (**b**) Tracking errors.