esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Literature Review and Conceptual Context
### Summary and Research Gap  
After performing the literature review, some research gaps were identified. Methodologies and heuristics have been proposed for traffic prediction and optimal vehicle routing. However, there is still a need to find an inclusive framework to develop a traffic prediction tailored for last-mile deliveries. DVRPs have been concentrating on optimizing a real-time online problem to satisfy responsiveness. Still, there is no implementation of a global methodology that can help improve it while implementing an accurate traffic prediction for urban areas with limited data available from local ITSs.  
Social media has been proposed in the literature to fill in the lack of traffic data in urban areas, but it requires constant queries to apply data mining to sparse tweets. All the social media applications for traffic prediction that have been analyzed have not included other factors. Furthermore, a social network analysis is a potential solution to eliminate constant queries and find influential accounts that drive changes in traffic conditions.  
A methodology that can implement a social network analysis and include that in traffic prediction with multiple factors tailored for a DVRP has yet to be developed. However, machine learning is an effective way to build this traffic prediction model, using deep learning techniques to handle complex structures.
# Application of Augmented Reality in Waterway Traffic Management Using Sparse Spatiotemporal Data
## 4 Methodology
### Multi-Source Data Fusion
#### 4.4.1 Camera View Partitioning  
To begin, the camera's visible range must be modeled as a set of regions. Its center is denoted as O, with the starting angle of the camera's field of view as \(\rm{\theta_{0}}\) and the maximum angular range as \(\rm{\theta_{max}}\). The camera's field of view is then uniformly divided into \(\rm{n}\) smaller regions, each spanning an angular range of \(\rm{[\theta_{k},\theta_{k+1}]}\), and each region is labeled as \(\rm{p_{k}}\). The specific formula is as follows:  
\[\rm{\Delta\  
partitions in the real camera's field of view. The baseline is set to V0, and each region is labeled as Vi. The specific calculation formula is as follows:  
\[\Delta\mathrm{V=}\frac{\mathrm{W}}{\mathrm{n}} \tag{30}\]  
\[\mathrm{V_{i}=[V_{i},V_{i}+\Delta v]=[V_{0}+(k-1)\cdot\Delta V,V_{0}+k\cdot \Delta V]} \tag{31}\]  
The starting boundary of the video frame is V0; \(\Delta V\) represents the pixel width of each region.
# Secure Speech Content Based on Scrambling and Adaptive Hiding
## 3 Proposed Scheme
### Recovery Module
#### 3.2.2 Bit to Sample Conversion  
Once all bits are extracted from the stego signal, the following step consists in converting them into samples. Firstly, the number of bits from the secret message in the host signal must be determined. This value is calculated by means of Equation (6).  
\[Nbits=ms*N \tag{6}\]  
where \(Nbits\) corresponds to the total number of bits from the secret message hidden in the host signal, ms is the number of samples of the hidden message, and \(N\) refers to the number of bits per sample. The value of ms is contained within the key sent by means of an alternative channel.  
The process that is carried out in this module is the following one:  
1. Calculating the value of \(Nbits\) by using Equation (6).
2. Taking the first \(Nbits\) from the binary sequence obtained in the \"adaptive LSB extraction\" block.
3. Dividing the previous result in groups of non-overlapped \(Nbits\).
4. Converting each group of Nbits into decimal values (thus obtaining a sample).
5. Normalisation is applied to each sample, in order for the dynamic range to be the same as the one from the secret message (e.g., \([-1\,1]\) V).  
The output of this block does not correspond to the recovered secret message yet, since the samples were saved in a scrambled way in the transmission module. In other words, only if the receptor has the scrambling key, he/she will be able to recover the secret message in a proper way. This process is performed in the following step.
## 5 Digital Image Frame Relay Transmission (DIFRT)  
In this section, the system architecture of DIFRT is presented. Typically, the function of each module is described in detail. Comparing with the previous AISRT approach, there are some additional steps in the image data processing before transmitting and after receiving using DIFRT method. These steps guarantee the transmission with high efficiency and low distortion.
# Experimental Study on Shear Strengthening of RC Beams with an FRP Grid-PCM Reinforcement Layer
## 5 Conclusions  
1. CFRP grids close to the shear cracks show orthogonal failure and the corresponding PCM experiences debonding failure when the specimen is strengthened on the web to resist shear force. It can be deduced that the shear strengthening effect of the CFRP grid-PCM reinforcement layer is insufficient if the RC beam is only reinforced by a strengthening layer on the web.
2. Compared to the specimen with a reinforcement layer only in the web, better performances of specimens reinforced in both the web and haunch regions are obtained in terms of the second stiffness and the ultimate shear capacity, reconfirming that the CFRP grid-PCM layer used for the full sectional reinforcement of RC beams with an I-shaped profile is indispensable.
3. The shear capacity is improved by 30-40% in specimens strengthened by a CFRP grid-PCM reinforcement layer. Considering the limited contribution of the PCM layer alone, the conclusion is that the shear strengthening of RC beams with CFRP grid-PCM layer is obvious and is primarily provided by the FRP grid.
4. Better synergistic deformation of the CFRP grid is obtained when the corresponding reinforcement amount is reduced. On the other hand, delamination or debonding of the CFRP from the surrounding PCM can be excluded.
5. Local debonding failure usually occurs at the FRP grid-concrete interface prior to the rupture of the CFRP grid. In addition, using the effective strain of the FRP rod to predict the effective/actual strain for the CFRP grid can be considered to be secure, but is somewhat over-predictive.
6. A new evaluation method based on the CFRP grid's effective strain has been developed in this paper. According to a series of experimental results and collected data from other results, this novel evaluation method is validated and a more effective and reasonable approach for predicting the shear capacity of RC beams using a CFRP grid-PCM layer is obtained.  
Data curation, R.G. and S.H.; software, L.C.; visualization, L.C.; writing--original draft preparation, L.C.; writing--review and editing, R.G. and B.W.; supervision, R.G.; funding acquisition, R.G. This research was supported by the Fundamental Research Funds for the Central Universities (grant number: 2682018 CX06) and the Key Laboratory Opening Project of Southwest Jiaotong University (grant number: ZD201918018). The authors are grateful for the technical support from FRP Grid Method Association at Japan. They would also like to acknowledge the relevant staff of Kyushu University that make a huge contribution to all experimental tests. The authors declare no conflict of interest about the research and the publication of this paper.  
Figure 13: Comparison between the calculated and corresponding experimental values: (**a**) Comparison of shear capacity; (**b**) Comparison of CFRP grid strain.
## 3 Results
### Gaussian Process Modeling and Sampling Algorithm Verification
In addition to the comparison of the mean function, the estimated parameters in the Matern covariance function with respect to the number of sampling points are shown in Table 2. There are three parameters in the Matern covariance function, and the given values are denoted in the parentheses. In contrast to the deviations in the mean function, the estimated parameters do not significantly depend (within a 5% error) on the number of sampling points. It can be speculated that the sampled points from the variability-based sampling gives enough information to accurately estimate the hyperparameters in the covariance function even though it missed a few local variabilities in the mean function. Figure 3 shows the prior and the posterior PDFs of three unknown parameters in the Matern covariance function. Figure 2: Given and estimated stochastic processes: (**a**) 10 realizations from the given model; (**b**) Given mean function (solid line) and sampled points in 1 st (circle), 2 nd (triangle), and 3 rd (rectangle) runs after variability-based sampling algorithm; (**c**) root-mean-square error (RMSE) of the mean function from uniform and variability-based sampling algorithm; (**d**) 10 sampled realizations from the estimated Gaussian process model. function. The prior PDF from Equation (8) is displayed with a blue line at the displayed region and the blue histogram is from the posterior PDF obtained by histogram of the trace values from MCMC sampling. The red line is a fitted normal distribution to the histogram. Figure 3 clearly visualizes the updating process of Bayesian inference by incorporating the observed data. It is important to emphasize that since the estimated parameters are obtained as PDFs instead of single values, the Gaussian process described by the estimated parameters is a set of multiple Gaussian processes defined by hyperparameters realized from the posterior PDFs. This helps us to model a wide range of uncertainties in the observed data while keeping the practical advantages of Gaussian process.
## 4 Simulation System Design
### State Estimator Design  
The designed simulation system uses the robot_localization package for motion state estimation. The robot_localization is an open-source package in ROS2 designed for state estimation of moving agents in 3D space. It utilizes two non-linear filtering algorithms--the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF)--to fuse multi-sensor data (e.g., GNSS, IMU, odometry). In this design, the package processes GNSS and IMU measurements of the USV's motion states using the EKF algorithm to estimate its 3D pose and velocity. Notably, when GNSS signals degrade or are lost, the navigation mode switches to a pure inertial navigation mode based solely on IMU data to ensure continuous output. Upon GNSS signal recovery, the system transitions to a hybrid mode combining GNSS and IMU inputs.
## 6 Limitations and Future Work  
### Limitations  
1. All case studies are confined to 2D plane-strain conditions. Extending to 3D would require redefining rigid-body degrees of freedom (e.g., six-DOF motion) and implementing hexahedral interface elements, which would significantly increase computational complexity. Additionally, the framework focuses on static equilibrium, excluding dynamic loads (e.g., seismic effects).
2. The method assumes isotropic rock properties, neglecting directional anisotropy (e.g., bedding or joint effects). Furthermore, the displacement compatibility equations for interface elements are derived under small-deformation theory, which may fail to capture geometric nonlinearities in large-displacement scenarios.
3. The numerical robustness of the PRE-IE-FE method is supported by its inheritance of mesh-stable characteristics from the original PRE-IE framework [15], where validation cases (e.g., symmetric wedge models) showed consistent results across mesh refinements, indicating minimal sensitivity to volumetric discretization. However, a dedicated mesh-dependency analysis for soil-rock binary slopes was not performed. Additionally, the small-deformation assumption for interface compatibility limits its applicability to large-displacement scenarios, necessitating future integration of adaptive remeshing or finite deformation theory.
###### Abstract
[39] took a high-speed catamaran as an example, conducted impact modeling of the catamaran ship type and fluid model based on the finite element method, proposed an impact resistance analysis method for high-speed catamaran ship types and discussed related influencing parameters, and finally compared the simulation results with empirical data for analysis. [PERSON] et al. [40] proposed a universal method for analyzing the dynamic response of underwater impact loads on ship equipment without the need for 'coupled calculations'. Based on the calculation of transfer functions of fluid, structure, and structure coupling, the impact resistance performance of the ship's hull and equipment was analyzed. [PERSON] et al. [41; 42] studied a system composed of a fluid-filled underwater cylindrical shell and a rigid cylinder, where the fluid dynamic field was affected by an external shock wave, analyzed various phenomena of shock wave propagation and reflection, and the impact of the mass size of the core on the interaction between fluid and structure. From the current state of research, it is evident that the impact resistance calculations for marine propulsion shafting systems primarily focus on calculations from the propeller to the thrust bearing, with almost no attention given to impact calculations for shafting systems containing high-elasticity couplings. Additionally, current research on high-elasticity couplings mainly revolves around the simulation and experimental computation of the couplings' performance parameters, including radial stiffness and torsional stiffness. There is a notable lack of research and calculations on the impact characteristics simulation models of high-elasticity couplings. This paper aims to address the existing issues in the impact calculation and analysis of propulsion shafting systems containing high-elasticity couplings, thereby further perfecting the modeling methods for impact calculations, analysis of influencing factors, and other related theoretical issues. The arrangement of the research content of this paper is as follows: Section 2 will conduct a model study on the electric propulsion shafting system and high-elasticity coupling, providing a detailed description of the mechanical properties of the rubber material of the high-elasticity coupling, and performing static and modal analysis based on the established model of the electric propulsion shafting system; Section 3 will calculate the design impact acceleration based on the Dynamic Design Analysis Method (DDAM), and then analyze the impact response of the shafting system shaft segments and critical cross-sections under the action of impact loads; Section 4 will use the time-history method to calculate the impact spectrum, focusing on the analysis of the impact displacement response at the cross-section; Finally, in Section 5, the conclusions will be drawn based on the aforementioned analyses.
# Adapting the GACT-X Aligner to Accelerate Minimap2 in an FPGA Cloud Instance
## 2 Materials and Methods  
### Research Approach  
This paper proposes an approach to accelerate the Minimap2 algorithm with an FPGA hardware design, targeting its extending step because it has been shown in previous works [26,28] to be one of Minimap2's bottlenecks that has not been successfully accelerated in the literature. The approach substitutes Minimap2's SK-based extending step [24] with the GACT-X algorithm [30] and implements the hybrid system in an FPGA cloud platform. Analyses and discussion are provided for the results obtained from this setting. FPGA cloud platforms bring advantages in terms of maintenance, cost, development speed, and replicability. Currently, there are several available FPGA cloud platforms; in this research, the Amazon Web Services platform was opted for since GACT-X was developed and can be mirrored on it. Figure 2 illustrates Minimap2's software pipeline and the GACT-X switch in dashed arrows.  
Regarding the input data for the _ksw_ function, which performs the SK algorithm, or for GACT-X, Minimap2 uses the seed-and-extend strategy presented in Figure 1. Indexing is performed with a hash table, where unique sequences are associated to unique index numbers, which in turn are used to store all positions of those sequences in the reference and in the read. In seeding, the positions in the read and the reference are matched in a process called anchoring (from the figure, it can be noticed that a seed in the read may be anchored in different parts of the reference). Parallel-positioned anchors between the read and the reference are considered candidates for forming a chain, and the best scoring chain is selected to indicate the read's mapping position in the reference. In the original Minimap2 program, aimed at software implementation, read alignment is performed incrementally by sets of anchor-separated sub-sequences, e.g., fragments from both read- and reference-separated anchors are aligned separately in the _ksw_ function and their outputs are then stitched back together.  
In order to improve the performance of Minimap2 with GACT-X implementation, some optimizations have been necessary, as will be presented in later sections. They refer to the transfer of data sub-sequences and to GACT-X's tiling strategy.
###### Abstract  
The estimation of the Instantaneous Angular Speed (IAS) has in recent years attracted a growing interest in the diagnostics of rotating machines. Measurement of the IAS can be used as a source of information of the machine condition per se, or for performing angular resampling through Computed Order Tracking, a practice which is essential to highlight the machine spectral signature in case of non-stationary operational conditions. In these regards, the SURVISHNO 2019 international conference held at INSA Lyon on 8-10 July 2019 proposed a challenge about the estimation of the instantaneous non-stationary speed of a fan from a video taken by a smartphone, a pocket, low-cost device which can nowadays be found in everyone's pocket. This work originated by the author to produce an offline motion-tracking of the fan (actually, of the head of its locking-screw) and obtaining then a reliable estimate of the IAS. The here proposed algorithm is an update of the established Template Matching (TM) technique (i.e., in the Signal Processing community, a two-dimensional matched filter), which is here integrated into a Genetic Algorithm (GA) search. Using a template reconstructed from a simplified parametric mathematical model of the features of interest (i.e., the known geometry of the edges of the screw head), the GA can be used to adapt the template to match the search image, leading to a hybridization of template-based and feature-based approaches which allows to overcome the well-known issues of the traditional TM related to scaling and rotations of the search image with respect to the template. Furthermore, it is able to resolve the position of the center of the screw head at a resolution that goes beyond the limit of the pixel grid. By repeating the analysis frame after frame and focusing on the angular position of the screw head over time, the proposed algorithm can be used as an effective offline video-tachometer able to estimate the IAS from the video, avoiding the need for expensive high-resolution encoders or tachometers.  
machine vision; machine diagnostics; instantaneous angular speed; SURVISHNO 2019 challenge; video tachometer; motion tracking; edge detection; parametric template modeling; adaptive template matching; genetic algorithm +
Footnote †: journal:  
Article
# Effect of Lateral End Plates on Flow Crossing a Yawed Circular Cylinder
## 3 Results and Discussion
### Streamlines  
To discover the mechanism of the axial vortex separated from the rear wall of a cylinder, streamlines are depicted for both types of boundary condition on the two lateral endplate walls. The pattern of streamlines around a cylinder for the nonslip boundary condition is shown in Figure 8a-c respectively for yaw angles of \(15^{\circ},30^{\circ}\), and \(45^{\circ}\). As uniform streamlines approach the frontal wall of a cylinder, they begin to deflect tangentially towards the tip end of the cylinder. Then, they swerve to align normal to the cylinder and smoothly pass the frontal half of the cylinder wall. In the wake, the streamlines at the base side are pushed towards the tip side at the adjacent region to the cylinder, forming an axial flow attached to the rear surface of the cylinder along the cylinder axis. Up to the tip side, they are separated away from the cylinder at a certain point, the location of which is dependent on the yaw angle of the cylinder. The separated point is extended further towards the tip end with the increase of the yaw angle of the cylinder. Eventually, they return into the incoming direction before the cylinder. Finally, the flow pattern in the far region of the wake is transformed as follows: the streamlines on the tip side are becoming denser while the streamlines on the base side are becoming sparser. Thus, a strong shear flow including high vorticity is engendered between them.  
Figure 8: \(Cont\).  
Figure 7: Comparisons of normal and axial vortices.  
Furthermore, at a large yaw angle such as 30\({}^{\circ}\) and 45\({}^{\circ}\), a secondary wall-attached axial flow, besides the incoming streamlines, is originated around the trailing edge from the base end. It more tightly attaches to the wall of the cylinder. Finally, it is also separated from the wall and coalesces with the incoming flow.  
Under the periodic boundary condition on the two lateral endplate walls, the streamline development crossing a cylinder is more regular than the above nonslip condition, as shown in Figure 9a-c. The incoming streamlines are deflected to align normal to the cylinder when approaching the cylinder wall. Moreover, when passing the upright ridge, they are deflected to the tip end under the advection of the primary axial velocity component, the trend of which is aggravated with the increase of yaw angle. At a yaw angle of 45\({}^{\circ}\), they almost evolve into axial flow along the cylinder wall.  
Figure 8: Streamline development for three yaw angles under nonslip boundary condition.  
Figure 9: _Cont._
# Optimal Insertion Torque for Orthodontic Anchoring Screw Placement: A Comprehensive Review
## 4 Discussion
### Placement Location  
#### 4.3.1 Buccal Alveolar Area  
The buccal alveolar area is a frequent site for OAS placement in orthodontic practice because of the simplicity of the procedure and advantageous anchorage. [PERSON] et al. [7] recommended ITs of 5-10 Ncm to improve the success rate of \(\varphi\)1.6 mm OASs. As diameters of 1.3-1.7 mm were used in this area [1; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15], a reference IT range for various conditions would be desirable. The present review aimed to determine the optimal IT using the outcomes of previous studies [1; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15].  
Based on these studies, \(\varphi\)1.5-1.7 mm OASs were commonly used in this area, and ITs of 5-8 Ncm and 6-12 Ncm were optimal for cylindrical OASs in the upper and lower buccal alveolar areas, respectively. For tapered OASs, ITs of 6-12 Ncm and 8-15 Ncm were most suitable (Tables 2 and 3, Figures 2 and 3).  
However, an in vitro study by [PERSON] et al. [26] reported fracture torques of 20.1 \(\pm\) 3.8 Ncm to 28.7 \(\pm\) 2.4 Ncm for \(\varphi\)1.5-1.7 mm OASs. [PERSON] et al. [27] also reported that the yield torque to fracture (i.e., the boundary torque between the elastic region without permanent deformation and the plasticity region with that deformation on tightening the OASs) for \(\varphi\)1.5-1.7 mm OASs ranged from 16.3 \(\pm\) 1.6 Ncm to 25.2 \(\pm\) 2.8 Ncm. Therefore, the authors would like to recommend that ITs of 5-14 Ncm may be suitable for \(\varphi\)1.5-1.7 mm OASs in the buccal alveolar area, and the reported fracture and yield torques must be considered during placement.