esa-sceva/satcom-chunk-collection huggingface dataset:
# Considerations of Curvature for a Near-Eye Holo-Video Display
## 2 Flat Screen
### Viewzone and Field of View  
For the purposes of this paper, we here consider the viewzone of the device to be the radial distance viewable by the user at any given point in image space. In contrast, the FOV will be the full angle of viewable area available to the user. This is illustrated in Figure 3.  
To determine the viewzone for a flat-screen device, we consider some point drawn by the active region of our device at some distance, \(d_{1}+d_{2}=d\). This point is created by some converging phase front created out of an aperture, a; this can be defined by the angle underneath the virtual point, which we will call \(2\theta\) (see Figure 4a). As the point is drawn along the radial distance chosen, the aperture must likewise move along the available active region space (while some addition deflection is possible while maintaining a fixed aperture location, it will always be of a lower quality than the symmetrical, normal case, so here we ignore this).  
When the virtual points are at their maximum distance, such that the eye can see both of them, the uppermost back-cast ray of one point and the lowest of the other will intersect at the eye, as seen in Figure 4b. The angle subtended by the virtual points and the eye will be the FOV for this device.  
Figure 3: (**a**) Viewzone is defined by a viewable radial length at some distance, d; field of view (FOV) is the angle of information accessible by the eye. (**b**) The goal of this paper is to improve the FOV by curving the device’s active region. This will allow the user to see a greater viewzone.  
It should be noted that, as the points are drawn closer to the eye, the maximum deflection angle will no longer be sufficient to converge to the chosen point; the closest drawable point that the display is capable of will be directly proportional to the aperture size chosen for the device, and the slope (as pictured above) will be \(m=\tan(\theta_{FOV}{}^{\circ}/2)\). Therefore, this limitation can be overcome by choosing a smaller aperture size. For the aperture size we will choose in the future, however, this point will occur closer to the eye than the eye is capable of resolving, so this can be ignored. In contrast, as the virtual points are drawn further from the eye, the angle, \(\theta\), will necessarily shrink. This conforms to standard optical methods.  
For a flat-screen device with \(\theta_{MAX}=2^{\circ}\), a FOV of \(4^{\circ}\), or \(2\cdot\theta_{MAX}\), is achievable. With an aperture size of approximately \(2a=17.5\) mm, the device can draw points up to the limit of normal adult human vision, around 25 cm from the eye [23].
## 2 Related Research Work  
To achieve locomotion in a cluttered and irregular terrain, a snake robot must be able to adapt its body motion to the environment. This requires that the robot can sense environment contact forces acting along its body [13]. To the best of our knowledge, the works in [13, 14, 15, 16, 17, 18] present snake robot designs featuring contact sensing capabilities. However, the vast majority of snake robots that have been designed thus far adopt traditional gear-motor-driven actuators. The fact that these robots employ rigid actuators requires a very high degree of awareness of their surroundings to achieve POAL. When adopting traditional gear-motor-driven actuators, this implies that a very precise mathematical model that includes the interaction between the snake robot and the surrounding operational environment is needed. Furthermore, when considering POAL, the high reflected inertia of rigidly actuated robots can cause possible collisions that may damage both the robot and the environment.  
To avoid the risk of rigid collisions, an alternative approach is inspired by the ability of biological mechanisms to accurately achieve compliance (passively and/or by precisely control torque). Based on this idea, series elastic actuators (SEA) were introduced in [19] as a means of achieving compliant motion and force control with traditional gear-motor-driven actuators. Thereafter, the design and control of SEA has been widely exploited in the fields of legged locomotion [20, 21], humanoid robots [22] and manipulators [23]. Regarding snake robots, different methods of achieving compliant motion by controlling the torques exerted by the joints of the robot were presented by the Robotics Institute at the Carnegie Mellon University [10, 24]. These control strategies are implemented on a snake robot that includes SEA and torque sensing at each joint, and demonstrate compliant locomotion that adapts naturally to the robot's surrounding terrain. This work is very pragmatic and has shown some success. However, the underlying idea is based on a relatively simplistic oscillation and adaptation of the torque to the surrounding obstacles. We hypothesise that exploiting full knowledge of the robot's configuration and surrounding environment can be more beneficial and can produce more reliable results with hopefully better performance. Moreover, the proposed robot design adopts financially demanding components and the software is not completely open-source.  
Figure 1: _Serpens_: A low-cost ROS-based snake robot with series elastic actuator (SEA), precision torque control and a screw-less assembly mechanism.  
To the best of our knowledge, a 3D-printable highly compliant multi-purpose modular robot that features SEA, precise torque control, open software/hardware and a screw-less assembly mechanism has not been released yet.
## 9 Conclusions  
Relying on the foundation pit project of Shenzhen karst formation station, this paper adopts the calculation method of coupling blasting near-field SPH and far-field FEM to accurately simulate the influence of karst cavities and filling media on the blasting effect of foundation pits. The main conclusions are as follows:  
1. The karst cavity will cause the blasting energy to dissipate along the interior of the cavity, which will change the blasting resistance line, making the resistance line between the cavity and the blasthole the direction of the minimum resistance line, and the energy of the explosive will be concentrated in the direction of the cavity, resulting in blast energy release.
2. When the cavity is fully filled with water medium and clay, the effect of blasting energy dissipation along the cavity is significantly improved, which is conducive to rock breaking in the area on the side of the air surface.
3. There are significant differences in rock-breaking effects under different grout stiffness conditions. As the cement mortar stiffness increases, the rock mass damage area inside the karst cavity first increases and then decreases. There is a cement mortar stiffness that makes the rock-breaking effect reach the maximum.
4. By fitting and analyzing the blasting stress of the karst cavity wall under different grouting stiffness under slightly weathered limestone, moderately weathered limestone and strongly weathered limestone, it is obtained that when the elastic modulus of cement mortar is 0.022 of that of slightly weathered limestone times, 0.0613 times the elastic modulus of moderately weathered limestone, and 0.270 times the elastic modulus of strongly weathered limestone, the rock breaking effect in the cavity is the best.  
Figure 18: Comparison of blasting effects before and after on-site grouting. (**a**) Rock-breaking effect before grouting; (**b**) rock-breaking effect after grouting.  
**Author Contributions:** Investigation, H.Z.; Writing--original draft, Y.D.; Writing--review & editing, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and X.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** Supported by the National Natural Science Foundation of China (51978671), Hunan Province Postgraduate Scientific Research Innovation Project (CX20200366), Central South University Postgraduate Innovation Project (1053320213141), China Railway Fifth Bureau Group Co., Ltd., Scientific Research Project (202112).  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 7 Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Authors** & **Method** & **Training and Testing (Data Selection)** & **Experiment Type** & **Accuracy (\%)** \\ \hline
**[PERSON]** & Time-frequency analysis & & S-Z & 100 \\
**e1. [54] (2007)** & and artificial neural network & 50\% training and 50\% testing & S-FNZO & 97.73 \\
**[PERSON]** & & & S-FN-ZO & 97.72 \\
**e1. [16] (2016)** & Key-point-based LBP and SVM & 10-fold cross-validation & S-FNZO & 99.31 \\
**e2. [55] (2016)** & Dual tree complex wavelet transform & & S-Z & 100 \\
**e3. [55] (2016)** & (DTCWT) and complex valued & 10-fold cross-validation & S-FNZO & 99.15 \\  & neural networks & & S-FN-ZO & 98.28 \\ \hline
**[PERSON] [56] (2014)** & DTCWT and Fourier features with nearest neighbor classifier & First half of the signals for training and the rest for testing & S-Z & 100 \\
**[PERSON] et al.** & K-means clustering and multilayer perceptron (MLP) & Randomly selected & S-FNZO & 99.60 \\
**[PERSON] et al.** & & S-FN-ZO & 95.60 \\
**[PERSON] et al.** & & S-FN-ZO & 99.80 \\
**[PERSON] et al.** [58] (2015)** & Rational discrete STFT and MLP classifier & Randomly selected & S-N & 99.30 \\
**e1. [58] (2015)** & Rational discrete STFT and MLP classifier & 50\% data for training & S-N & 98.50 \\  & & S-FN-ZO & 94.90 \\
**[PERSON] and** & Amplitude and frequency modulation & 10-fold cross-validation & S-FNZO & 99.50-100 \\
**[PERSON] [3] (2012)** & bandwidths of IMPs and least-squares SVM (LS-SVM) & 10-fold cross-validation & S-Z & 99.6 \\
**[PERSON]** & Line length feature and & Randomly selected & S-Z & 99.6 \\
**e1. [59] (2010)** & artificial neural networks & 50\% data for training & S-FNZO & 97.77 \\ \hline
**Kaya** & 1D LBP and functional tree & & S-Z & 99.50 \\
**e1. [54] (2014)** & 1D LBP and BayesNet & 10-fold cross-validation & S-F & 95.50 \\
**e2. [54] (2009)** & RQA features, SVM classifier & 3-fold cross-validation & S-FN-ZO & 95.6 \\
**e3. [54]** & ApEn, SEn, phase entropy features, & & & \\
**e4. [60] (2012)** & and fuzzy classifier & 3-fold cross-validation & S-FN-ZO & 98.1 \\ \hline
**Yuan** & ApEn, Hurst exponent, scaling exponents of EEG, & & & \\
**e1. [61] (2011)** & and extreme learning machine (ELM) algorithm & 50\% data for training & S-F & 96.5 \\ \hline
**Ghayab** & Simple random sampling, & & & \\
**e1. [62] (2016)** & sequential feature selection and LS-SVM & Not specified & S-Z & 99.9 \\ \hline
**Our work** & TQWT-based multi-scale K-NN entropy & 10-fold cross-validation & S-Z & 100 \\  & & & S-N & 99.50 \\  & & & S-FNZO & 99 \\  & & & S-FN-ZO & 98.60 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of the proposed method with the existing methods studied using the same EEG dataset. used to record the EEG signals. The proposed multi-scale K-NN entropy can be applied for diagnostic application of diseases using electrocardiogram (ECG), electromyogram (EMG) and respiratory signals. The proposed framework in this paper can be used for automated diagnosis of abnormalities using biomedical signals.
# A Review of Seatbelt Technologies and Their Role in Vehicle Safety
## 6 Conclusions  
Seatbeltls remain a fundamental component of vehicle safety, with immense potential to save lives, and continued advances in technology are essential, especially with the development of autonomous vehicles.  
Innovations in seatbelt technology, such as advanced retractors, pretensioners (including active and reversible ones), and load limiters, have significantly improved occupant protection in various collision scenarios. These systems work together to provide optimal restraint and reduce the risk of specific injuries.  
The integration of active systems such as AEB, lane departure warning, with passive systems, seatbeltls, and airbags, is a trend in modern automotive safety design, allowing for a more effective response to hazards and preparing occupants for an imminent impact.  
In the context of autonomous vehicles, where occupants can adopt more relaxed positions, a reassessment and adaptation of conventional restraint systems is necessary to prevent risks such as submerging and to ensure effective protection in the event of a collision.  
The effectiveness of seatbeltls and the need for technology adaptation vary significantly depending on the category of passengers, including children, who require special systems, pregnant women, where correct positioning is vital, the elderly, who are more susceptible to certain types of injuries, and even people with disabilities.  
Correct use of seatbeltls is essential to maximize their safety benefits, and factors such as age, socioeconomic status, and risky behaviors can influence the frequency of use. Reminder systems and other strategies can be effective in increasing seatbelt use.  
The insights from this review are valuable for a wide array of stakeholders, including automotive manufacturers in designing advanced and adaptable restraint systems for all occupants and autonomous vehicles, regulatory bodies in shaping future safety standards, safety advocates in promoting proper usage, researchers in furthering innovation, technology developers in creating next-generation safety solutions, healthcare professionals in injury prevention, and ultimately, consumers in understanding and maximizing their safety on the road.  
Despite significant advancements, further research is important in understanding the optimal adaptation of restraint systems for non-conventional seating positions in autonomous vehicles and in developing personalized and adaptive seatbelt technologies that effectively cater to the diverse needs and vulnerabilities of all passenger categories, including children, pregnant women, and the elderly.  
Conceptualization, A.S. and C.G.; methodology, A.S.; validation, A.S. and C.G.; investigation, C.G. and A.S.; resources, A.S.; data curation, A.S. and C.G.; writing--original draft preparation, C.G. and A.S.; writing--review and editing, C.G. and A.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflicts of interest.
## 2 Materials and Methods
### Rayleigh Diffraction Limit  
For comparison, we introduce the Rayleigh criterion used to estimate the diffraction limit of an array imaging system for two ideal point sources [40]:  
\[\theta_{R}=1.22\lambda/D \tag{16}\]  
In this formula, \(\theta_{R}\) denotes the minimum resolution angle determined by the Rayleigh criterion, \(\lambda\) is the wavelength, and \(D\) is the numerical aperture of the imaging system. According to the numerical simulations and experimental calculations in this chapter, \(D\) = 200 mm. The SLDV-measured out-of-plane guided wave signal predominantly corresponds to the \(A_{0}\) mode, with a guided wave wavelength of 7.6 mm at a center frequency of 250 kHz, resulting in \(\theta_{R}\) = 0.0464. Considering the distance L = 100 mm from the array to the damage imaging location, the resolution limit based on the Rayleigh criterion can be estimated:  
\[d_{R}=4.64\;\mathrm{mm}=0.61\lambda \tag{17}\]
# Analysis and Experimental Test of Electrical Characteristics on Bonding Wire
## 4 Bonding Wire Design and Measurement Experiment
### Port Extension
The S parameters of the final bonding wire are shown in the Table 9 after calculation. The data of 5 fixed frequency points are calculated by extending the port, and the calculated data were compared with the result and original test data without error elimination using HFSS three-dimensional electromagnetic field simulation. The comparison graph of the three cases above is shown in Figure 25.  
From the experimental data, system error can be eliminated to some extent by the port extension method making the measurement result more accurate. From the comparison between the simulation and the experimental data, the trends of S11 and S21 parameters were consistent. There was a deviation in some specific values, and the S parameter error contrast value was extracted in Table 10 among the five fixed points. Due to limited experimental method and inability to establish the precise and accurate bonding wire loop model of experiment wire, even after port extension method and data processing, there was still some deviation between the simulation and measurement values. However, the experimental results have confirmed the results of S parameters simulation for the bonding wire and design rules. The error is also within the reasonable range. Therefore, the correctness of the simulation is proved. Figure 24: Port extension outward and signal flow graph. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Frequency/GHz** & \(|S_{11}|\) & \(\theta_{11}\) & \(|S_{21}|\) & \(\theta_{21}\) \\ \hline
2.5 & \(6.67\times 10^{-1}\) & \(-2.51\times 10\) & \(5.51\times 10^{-2}\) & \(3.27\times 10\) \\
3.0 & \(6.94\times 10^{-1}\) & \(5.87\times 10\) & \(5.03\times 10^{-2}\) & \(-4.62\times 10\) \\
3.5 & \(7.03\times 10^{-1}\) & \(2.60\times 10^{2}\) & \(4.16\times 10^{-2}\) & \(-8.54\times 10\) \\
4.0 & \(7.10\times 10^{-1}\) & \(-4.21\times 10\) & \(4.21\times 10^{-2}\) & \(-1.08\times 10\) \\
4.5 & \(7.71\times 10^{-1}\) & \(8.59\times 10\) & \(4.05\times 10^{-2}\) & \(1.85\times 10^{2}\) \\ \hline
**Frequency/GHz** & \(|S_{12}|\) & \(\theta_{12}\) & \(|S_{22}|\) & \(\theta_{22}\) \\ \hline
2.5 & \(4.65\times 10^{-2}\) & \(3.24\times 10\) & \(6.89\times 10^{-1}\) & \(-2.69\times 10\) \\
3.0 & \(4.47\times 10^{-2}\) & \(-2.89\times 10\) & \(7.23\times 10^{-1}\) & \(4.17\times 10\) \\
3.5 & \(4.32\times 10^{-2}\) & \(-5.69\times 10\) & \(7.42\times 10^{-1}\) & \(3.28\times 10^{2}\) \\
4.0 & \(4.02\times 10^{-2}\) & \(-6.78\times 10^{2}\) & \(7.38\times 10^{-1}\) & \(-8.26\times 10\) \\
4.5 & \(3.65\times 10^{-2}\) & \(1.95\times 10^{2}\) & \(7.94\times 10^{-1}\) & \(1.22\times 10\) \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Bonding wire S parameter results file DUT_WireBond.TXT.
## 6 Discussion  
Taking the tunnel of Chengdu Guiyang railway crossing the huge karst cave section as project example, this study took the underground river in the karst cave as the research object, used the finite element software FLAC3D and the measured data to explore the adverse impact of underground river level increases on tunnel construction and selected the best parameters for backfill material for practical engineering. The main findings of this study are as follows:  
1. In this study, the commonly used parameters, including density, elastic modulus, cohesion, internal friction angle, porosity and parameter reduction coefficient in backfill, were selected as the main variables. The six data of layered settlement, tunnel crown settlement, convergence on both sides and internal force and bending moment of initial lining obtained by the finite element software FLAC3D were used as evaluation indexes. The average value and standard deviation of the mechanical response results for the surrounding rock and lining structure in multiple sections were transformed into the ECULID distance from the origin on the two-dimensional plane as the evaluation index. The parameter influence analysis was carried out based on the orthogonal test. It was found that the bulk elastic modulus of backfill and the reduction coefficient of water on materials have the greatest influence on structural mechanics.  
Figure 14: Crown settlement of sections. (**a**) Crown settlement of the d3k279 + 875–895 section. (**b**) The final vault settlement of each section during open excavation and concealed excavation.  
According to the field measured data of 10 different sections, the layered settlement of the backfill body presented three different stages of slow increase, rapid increase and slow increase in the backfilling period, open excavation period and concealed excavation period. The growth range of each section was different but the trend was basically the same.
3. According to the measured data of tunnel crown settlement in different sections, in the open excavation period, the crown settlement increased in step with the advance of the construction steps, and the tunnel crown settlement fluctuated continuously in the concealed excavation period. However, due to the different nature of the surrounding rock, the support method and grouting amount, the settlement of each section at the end of the open excavation period and the concealed excavation period varied greatly, but they were all within a controllable range, and the impact of groundwater on tunnel construction was basically eliminated. In general, the tunnel crossing the giant cavity was well controlled.
# Image Segmentation Framework for Detecting Adversarial Attacks for Autonomous Driving Cars
## 2 Background and Related Works
### Defense Mechanisms Against Adversarial Attacks
#### 2.2.5 Feature Squeezing  
[PERSON] et al. [25] proposed a defense method called feature squeezing, which reduces the bit-depth of images to limit the effects of the perturbation noise of adversarial examples. This method is computationally efficient and applicable to any DNN. It enhances the model's robustness against adversarial images. Also, a joint detection method is introduced to calculate the \(L_{0}\) distance between the output vector (the Logit layer) of the original input and its filtered versions using a median smoothing filter and a non-local means filter [40]. It then compares the distance with a certain threshold to detect adversarial examples. However, the detection rates for non-targeted attacks like FGSM and BIM are low.
# A Survey of Visible-Light-Communication-Based Indoor Positioning Systems
## 4 Techniques of VLC-Based Indoor Positioning Systems
### Positioning Techniques
#### 4.2.6 Image-Sensor-Based Schemes  
Many systems use photodetectors or photodiodes as receivers. However, there are also systems that use image sensors or cameras. Algorithms using image sensors need to deal with the transformation of the two coordinate systems: the real world and the -reception plane of the image sensor. The positions of the image sensor and LEDs should be known for setting up the transformation equations and their geometric relationships. The LEDs' coordinates can be transmitted by broadcast through VLC and the reception plane coordinates can be derived from image processing. In [79], the algorithm proposes to use the co-linearity condition as well as least squares method to determine the transformation equations. Generally, the accuracy of the scheme can be improved when the number of pixels increases. Note that the cost of image-sensor-based schemes is usually higher due to the cost of image sensors. In addition, a compromise should be made between the accuracy and the running time of the image processing. In practice, one can also use a fish-eye camera [80] to have a larger field of view and to improve coverage.  
In [81], the system contains two identical image sensors and four LED arrays while each pixel at the image sensors acts as an individual photo sensor. Similarly, the coordinate information of the LEDs is broadcast via VLC. According to the knowledge of the focal length of the image sensor lens, the locations of the image sensors, and the geometric relationship between the distance and the position difference of the LED images on the two image sensors, the coordinates of each image sensor can be calculated. Note that the algorithm does not require any angular measurement, such as AOA, but the separation of the image sensors has to be known with high accuracy for good performance.