esa-sceva/satcom-chunk-collection huggingface dataset:
# Extraction and Detection of Surface Defects in Particleboards by Tracking Moving Targets
## 2 Algorithm Theory
### Sobel Edge Operator  
After the defect targets are captured by the tracking algorithm, their images will be extracted by edge detection. In this study, the defect targets were separated from the background by the Sobel edge operator.  
The Sobel edge operator has two \(3\times 3\) templates. Considering \(A\) as the original image, then image \(G_{x}\), which is detected vertically, and image \(G_{y}\), which is detected horizontally, can be expressed as follows:  
\[G_{x}=\left[\begin{array}{ccc}-1&0&+1\\ -2&0&+2\\ -1&0&+1\end{array}\right]\times A \tag{13}\]  
\[G_{y}=\left[\begin{array}{ccc}-1&-2&-1\\ 0&0&0\\ +1&+2&+1\end{array}\right]\times A \tag{14}\]  
Figure 1: The calculation diagram of forward–backward (FB) error.  
The value of gradient can be expressed as follows:  
\[G=\sqrt{G_{x}^{2}+G_{y}^{2}} \tag{15}\]  
The direction of gradient can be expressed as follows:  
\[\Theta=arc\tan(\frac{G_{y}}{G_{x}}) \tag{16}\]  
The Sobel edge operator can make a further weighted adjustment to the undesirable segmentation results according to the pixel position. This process can alleviate the edge blurring and improve the quality of the segmentation results.
# Line Matching Based on Viewpoint-Invariance for Stereo Wide-Baseline Aerial Images
###### Abstract  
Line matching is the foundation of three-dimensional (3D) outline reconstruction for city buildings in aerial photogrammetry. Many existing studies have good line matching effects when dealing with aerial images with short baselines and small viewing angles. However, when faced with wide-baseline and large viewing-angle images, the matching effect drops sharply or even fails altogether. This paper deals with an efficient and simple method to achieve better line matching performance by a pair of wide-baseline aerial images, which make use of viewpoint-in variance to conduct line matching in rectified image spaces. Firstly, the perspective transformation relationship between the image plane and the geoid plane can be established from a Positioning and Orientation System (POS). Then, according to perspective projection matrices, two original images are separately rectified to conformal images, whose perspective deformation of large viewing-angle can be eliminated. Finally, the rectified images are used to conduct line matching, and the matched line segments obtained are back-projected to the original images. Four pairs of urban oblique aerial images are used to demonstrate the validity and efficiency of this method. Compared with line matching on original images, the number and the correctness of the matched line segments are greatly improved. Moreover, there is no loss of time efficiency. The proposed method can also be applied to general UAV (Unmanned Aerial Vehicle) aerial photogrammetry and introduced into matching for other geometric features, such as points, circles, curves, etc.  
line matching; perspective invariance; wide-baseline; stereo aerial images +
Footnote †: journal: Applied  
Article
# Throughput/Area Optimized Architecture for Elliptic-Curve Diffie-Hellman Protocol
## 1 Introduction
### Novelty  
Although there are several ECDH designs provided in the literature [12, 16, 17, 18, 19], they mainly target a coprocessor implementation style to achieve flexibility which affects the performance in terms of latency and throughput. The automotive [3, 4], IoT [7, 8, 9, 10] and several other applications demand the exchange of sensitive information in a reasonable time. Therefore, to achieve an adequate throughput and to optimize or reduce the latency of the ECDH algorithm, we have utilized a dedicated crypto processor architecture instead of the use of a coprocessor. Furthermore, along with the throughput and latency parameters, the health-related applications [1] and embedded devices such as smart cards [5, 6] demand low hardware resources utilizations. Thus, no demonstration of an ECDH design exists before this work where throughput and area constraints are considered at the same time for implementation.
## 2 SRT Structure and Dynamics Model  
Figure 1 shows the basic structure of the SRT, with a total length of 35 m, a width of 2.55 m, and a floor height of 0.35 m. The SRT adopts a four-module marshalling, with the first and fourth modules being the same structure, equipped with a cab, and each with two rubber wheel running gears that can independently steer. The second and third modules have one steerable rubber wheel running gear. The SRT has six axles: the first and sixth  
axes are equipped with drive motors to provide torque, while the remaining axles are unpowered. Each module is connected through a hinge plate [34].  
When establishing the dynamics model, the following assumptions are made:  
Assuming that the vehicle runs on a flat surface, only the movement in the XOY plane and rotation around the Z-axis is considered, ignoring the rolling and vertical movements.  
The steering angles of the left and right wheels of the same axle are equal.  
The vehicle is considered a multi-rigid body system.  
The vehicle dynamics model and CG generalized forces are briefed in [33], but the reconfigurable features were not included. First, a single-module dynamics model is established with the CG generalized and hinge forces as control inputs. The hinge is equivalent to the constraint between adjacent modules. A full-state dynamics model of the entire vehicle is obtained through matrix assembly. Then, the hinge constraint equations are combined to obtain the expression of the hinge force using the vehicle state and CG generalized forces. The dynamics model that can be directly used for model-based control algorithm design is obtained by preserving the DOFs related to path tracking. Finally, the vehicle CG generalized forces can be calculated from the tire force generated by the wheel control input. We newly defined the \"Boolean matrix\" to determine the availability of axles, namely the axles' quantity and their ability to provide torques of the wheels. This method can quickly expand and reconstruct the dynamics model for a different number of modules and different configurations of wheels per module.
###### Abstract  
Here, by harnessing a composite combination of wave retarders, we propose and experimentally demonstrate a first-order narrowband fiber comb filter capable of continuously tuning its wavelength, of which the filter structure is on the fundamental basis of a polarization-diversity loop structure. The demonstrated comb filter consists of a polarizing beam splitter (PBS), two high birefringence fiber (HBF) segments of the same length, an ordered wave retarder combination (WRC) of a quarter-wave retarder (QWR) and a half-wave retarder (HWR) before the first HBF segment, and an ordered WRC of an HWR and a QWR before the second HBF segment. The second HBF segment is butt-coupled to one port of the PBS so that its principal axis should be 22.5\({}^{\circ}\) away from the horizontal axis of the PBS. Taking the filter transmittance obtained by Jones calculus into consideration, we found the azimuth orientation angle (AOA) sets of the four wave retarders, which could allow extra phase shifts (\(\psi\)'s) ranging from 0\({}^{\circ}\) to 360\({}^{\circ}\) to be induced in the narrowband transmittance function. From filter transmission spectra calculated according to the AOA sets found above, it is confirmed that the first-order narrowband comb spectrum can be continuously tuned by properly controlling the AOA's, clearly indicating the continuous wavelength tunability based on a composite combination of ordered wave retarders. This theoretical prediction was verified by actually constructing the proposed filter. Then, it is concluded that our filter employing the composite combination of wave retarders can be continuously frequency-tuned by properly controlling the AOA's of the wave retarders.  
optical filter; comb filter; polarization interference; narrowband; continuous wavelength tuning 2020
## 2 Results and Discussion
### Identification of Gelatin from Sika Deer by Defined Marker Peptides  
The occurrence patterns of the selected marker peptides across various gelatin samples were compared using extracted ion chromatograms (XICs) of their precursor ions (Figure 3). All four marker peptides were detected in sika deer gelatin, whereas only specific marker peptides were detected in gelatin from other animals. Among the three kinds of sika deer gelatin (antler, hide, and bone), the peptide P11 consistently exhibited the highest intensity. The peak areas of R2, R3, and R4 varied depending on the gelatin source, showing distinct patterns: R4 > R3 > R2 for antler gelatin (Figure 3A), R4 > R3 = R2 for hide gelatin (Figure 3B), and R4 = R3 > R2 for bone gelatin (Figure 3C). In contrast, the peptide R4 was strongly detected in donkey hide and porcine gelatin (Figure 3D,F), while P11 was prominent in bovine gelatin (Figure 3E), and no marker peptides were detected in fish gelatin (Figure 3G). These findings demonstrate that combining multiple marker peptides effectively distinguishes sika deer gelatin from other animal-derived gelatins. Furthermore, the differences in the peak area values of the selected marker peptides suggest the potential to distinguish the anatomical origin of the gelatin within sika deer samples.  
Figure 3: Extracted ion chromatograms (XICs) of marker peptides in sika deer gelatin and commercially available gelatins. (**A**) Sika deer antler, (**B**) sika deer hide, (**C**) sika deer bone, (**D**) donkey hide, (**E**) bovine, (**F**) porcine, and (**G**) fish.
## 4 Results and Analysis
### Calculation of the Size of Each Type of Defect  
This paper further investigates the \(M_{33}\) element as an example as it can detect and classify various types of defects on the surface of the element, due to the relations \(M_{12}=M_{21}\), \(M_{33}=M_{44}\), and \(M_{34}=-M_{43}\). In particular, the authors analyze relationship between \(M_{33}\) spectral values and increasing roughness \(\sigma\) and the depth of the digs [29], as shown in Figure 15a,b. For further verification, setting \(\lambda=633\) nm, the \(M_{33}\) values show a monotonic increase with dirty particle size above the surface of the optical element, and a monotonic decrease with particle size as SSBDs increase, as shown in Figure 16, i.e., there is a one-to-one correspondence between the \(M_{33}\) values and the particle size dimensions. Therefore, after determining the RMMS of various types of defects, the sizes of defects with different roughness on the surface of the optical element, different depths of surface digs, and particle defects of different sizes can be calculated from the Muller matrix elements according to such relationships. This provides a theoretical basis for the measurement of defect sizes.  
Figure 14: The polar plot of the reflection Mueller matrix for dirt particles above the surface of the optical test plate at \(\theta_{i}=\theta_{s}=70^{\circ}\) (the radial coordinate represents the wavelength, and the angular coordinate represents the azimuth angle).
###### Abstract
As noted by [PERSON] (2008) [20], invasive transducer deployment can pose health and safety risks to customers (due to potential water contamination in potable water), in addition to the potential costs of creating access points within the pipe. Rather than using the internal fluid medium, [21] investigated the pipe wall as an acoustic communication channel by designing an ultrasonic-based digital communication system using time reversal pulse position (TR-PPM) modulation. Although acoustic communication along the pipe wall was reported by the authors, the reliable digital communication distances along the exposed pipes was limited to less than 2 m. Furthermore, the findings from [21] showed the influence of acoustic signal dispersion (due to multiple acoustic propagation modes excited at these ultrasonic frequencies) in increasing the bit error rate (BER), thus rendering digital communication unreliable along the pipe. One option for minimizing acoustic signal dispersion along the pipe is using low-frequency (<1 kHz) acoustic excitation where only a few acoustic propagation modes occur along the pipe. Acoustic dispersion studies by [22] along a buried ductile iron pipe showed the possibility of generating a fundamental longitudinal acoustic wave along the pipe wall, using non-invasive acoustic excitation, which can propagate distances approaching 10 m. These studies, however, focused on pipe condition assessment and not on using longitudinal acoustic wave propagation, especially along a buried non-metallic pipe, for possible digital communication. To address this gap, this paper demonstrates the successful use of low-frequency acoustic signal propagation along exposed and buried medium-density polyethylene (MDPE) pipes for non-invasive digital communication, which ultimately can be used to communicate sensed data information. Analytical and numerical modelling alongside laboratory and field experiments are used to evaluate the attenuation of an acoustic wave and then to predict the potential distances at which reliable acoustic communication can be achieved. It highlights how this system can overcome some of the limitations of radio frequency (RF) signal transmission.
## 5 Sensitivity Analysis of Thermal Conductivity
### Effects of Coarse Aggregate with Different Thermal Conductivity  
The thermal conductivity of coarse aggregates varies by kind. In order to analyze the effect of various coarse aggregate types on the effective thermal conductivity of asphalt concrete, the combined prediction method was used to calculate. Some typical aggregates were considered in this section. Eight groups of asphalt concrete three-dimensional meso-structure models were generated, and the effective thermal conductivity was calculated, as demonstrated in Figure 11.  
Asphalt concrete and coarse aggregate have a nearly linearly positive correlation in terms of effective thermal conductivity. Higher effective thermal conductivity can be achieved by mixing asphalt concrete with marble or granite aggregates. However, the addition of limestone can decrease the effective thermal conductivity. Generally, aggregate thermal properties had a significant impact on the thermal properties of asphalt concrete, which was in accordance with existing literature [14; 25].
## 4 Conclusions
### Nomenclature  
ABS absorber TIP turbine inlet pressure BOI boiler TUR turbine CO condenser WW power (kW) DEP dephlepmator X ammonia concentration DHE domestic heat exchanger EVA evaporator **Subscripts and abbreviations**  
\(\rm e_{ch}^{0}\) standard chemical exergy 0 ambient EX expansion valve CD cooling demand E exergy rate ch chemical DE Specific exergy D destruction GEN generator BB specific enthalpy HD heating demand Molar weight L loss PD pressure PD  
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline  & **TSF** & **TWF** & **SWX** & **SSX** & **SSX** \\ \hline \(T_{ambient}\) (\({}^{\circ}\)C) & 13.81 & & 15.42 & & 15.67 & & 17.24 \\ \(\hat{Q}_{heating}\) (MW) & 4.79 & & 5.69 & & 2.99 & & 2.9 \\ \(\hat{Q}_{cooling}\) (MW) & 1.78 & & 1.9 & & 2.58 & & 2.5 \\ \hline \multicolumn{1}{c}{(a)} & (b) & (a) & (b) & (a) & (b) & (a) & (b) \\ \hline \multicolumn{1}{c}{**Decision operational variable**} & & & & & & & \\ \hline \multicolumn{1}{c}{TIP (bar)} & 20 & 21.7 & 19.5 & 25.2 & 20 & 26.06 & 20.2 & 29.6 \\ \(T_{\rm gen}\) (\({}^{\circ}\)C) & 67.62 & 67.62 & 61.02 & 64.7 & 58.96 & 65 & 60.81 & 66.85 \\ \(\delta T_{\rm ABS}\) (\({}^{\circ}\)C) & 12.11 & 7.81 & 12.71 & 7.69 & 11.61 & 11.51 & 12.01 & 7.55 \\ \(\delta T_{\rm CON1}\) (\({}^{\circ}\)C) & 14.2 & 14.2 & 7.02 & 10.12 & 4.99 & 10.12 & 5 & 10.12 \\ \hline \multicolumn{1}{c}{\(\overline{S}T_{\rm CON2}\) (\({}^{\circ}\)C)} & 5 & 5 & 5 & 5 & 5 & 5 & 5 \\ \hline \multicolumn{1}{c}{**Calculated parameters in the off-design conditions**} & & & & & & & \\ \hline \(n_{\rm start}\) (\%) & 71 & 60 & 079 & 66 & 80 & 71 & 79 & 56 \\ \(S_{\rm TP}\) (\({}^{\circ}\)C) & 25.47 & 26.01 & 14.65 & 15.14 & 14.22 & 12.46 & 14.84 & 11.78 \\ \(T_{\rm ex}\) (\({}^{\circ}\)C) & 10.58 & 10.14 & 9.7 & 7.1 & 11.57 & 6.522 & 14.89 & 15.5 \\ \(\delta T_{\rm ex,abs}=T_{\rm EQ}-T_{\rm EQ}\) (\({}^{\circ}\)C) & 13.64 & 9.29 & 12.76 & 7.7 & 10.74 & 4.07 & 11.38 & 7.13 \\ \(\delta T_{\rm ex,CON1}=T_{\rm EQ}-T_{\rm EQ}\) (\({}^{\circ}\)C) & 14.13 & 14.13 & 6.55 & 9.37 & 3.83 & 7.79 & 3.9 & 8.11 \\ \(\delta T_{\rm ex,CON2}=T_{\rm EQ}-T_{\rm EQ}\) (\({}^{\circ}\)C) & 7.215 & 8.9 & 3.3 & 5.23 & 2.5 & 3.71 & 2.7 & 13.11 \\ \(\delta T_{\rm ex,REC}=T_{\rm EQ}-T_{\rm EQ}\) (\({}^{\circ}\)C) & 4.311 & 4.5 & 3.1 & 3.22 & 2.45 & 2.43 & 2.4 & 2.42 \\ \hline \end{tabular}
\end{table}
Table 2: Detailed parameters of the optimization calculation (a) maximum exergy efficiency (b) minimum exergy destruction rate.
# An Experimental Study of the Performance of a Crossed Rib Diffuser in Room Acoustic Control
## 3 The Experiment Using a Small Meeting Room
### Comparisons of Room Acoustic Parameters
#### 3.2.3 Definition \(D_{50}\)  
Figure 12a,b presents comparisons of spatial averaged \(D_{50}\)s measured in each case and increases in \(D_{50}\) relative to case 0 normalized with JND (5 % [29]) for each case. The \(D_{50}\) values increased more than 1 JND in comparison with case 0 in the following conditions: case 2 at 500 Hz and 4 kHz; case 3 at 500 Hz and higher; case 4 at 4 kHz; case 5 at 500 Hz and higher; and case 6 at 250 Hz and higher. Case 6 using CRD-A on two surfaces mostly improved \(D_{50}\) in all cases, augmenting \(D_{50}\) more than 3 JND compared with case 0 at 500 Hz and higher. Additionally, for identical installed area, the CRD enhanced speech clarity in a wider frequency band than the 1D periodic diffuser.
# Durability of Mortars with Partial Cement Replacement by Recycled Brick Powder
## 3 Results
### Electrical Resistivity  
Resistivity is also an indirect indicator of durability. It gives information about pore connectivity and resistance to electric transfer, essential in electrochemical processes such as rebar corrosion [93]. The results obtained from resistivity monitoring are presented in the graphs in Figure 11. This figure also presents the thresholds established by other authors for classifying the material's durability based on its electrical resistivity [86; 87].  
Figure 10: Apparent chloride diffusion coefficient results measured by migration test.  
The results exhibit a similar trend to those obtained in the previously described tests. The addition of RBP as a partial substitute for OPC significantly increased the resistivity of the mortar, reaching values eight and nine times higher than those of the reference mortar (C00) in mixes C45 and C40, respectively, indicating high durability [86; 87]. The C30 and C35 mixes exhibited resistivities between four and five times higher than those of C00, while the C15, C20, and C25 mixes showed resistivities between two and three times higher than C00, reaching values typical of concrete with medium to high durability. In contrast, the C05 and C10 mixes showed little to no difference compared to the reference mortar (C00), indicating low or even very low durability [86; 87].  
As described in the analysis of RBP's pozzolanic activity and according to [PERSON] et al., the use of pozzolanic materials promotes the reaction of the pozzolan with calcium hydroxide in the presence of water. This reaction, which occurs after cement hydration, leads to the formation of C-S-H gels [94]. This secondary reaction generates more solid substances that block the capillary pore network, and this obstructs the flow of the electric current, producing a higher resistivity [95; 96]. Furthermore, the filler effect densifies the matrix and accelerates hydration reactions, resulting in pore refinement and a more tortuous pore network [96]. Mortars and concretes including these characteristics have shown reduced permeability and higher chloride ion penetration resistance [97], which  
Figure 11: Resistivity evolution.  
reduce the risk of the corrosion of the reinforcement, which is in accordance with the results described in Sections 3.2 and 3.3.
# Effect of an Organic Rectorite on the Properties of a Waste Engine Oil-Modified Asphalt
## 2 Experimental Section
### Testing Methods  
The chemical structure of the modified agent and asphalt samples was determined using a Nicolet 6700 Fourier transform infrared spectrometer (FTIR) with a testing range of 4000-650 cm\({}^{-1}\) and a resolution of 4 cm\({}^{-1}\). The storage stability of the composite-modified asphalt was measured according to the \"Test Methods of Highway Engineering Asphalt and Asphalt Mixture\" (JTG E20-2011 [37]) using the polymer-modified asphalt exudation test method. Three replicates were used in this test. The high-temperature performance of the asphalt samples was assessed using a TA dynamic shear rheometer (DSR) with a temperature scanning mode at 58 \({}^{\circ}\)C, 64 \({}^{\circ}\)C, 70 \({}^{\circ}\)C, and 76 \({}^{\circ}\)C, and a scanning frequency of 10 rad/s. Meanwhile, the low-temperature performance of the asphalt samples was measured using a Cannon bending beam rheometer (BBR) at \(-18\) \({}^{\circ}\)C. The \"Fatigue-Intermittent-Fatigue\" test for the asphalt samples was conducted using the same DSR instrument with a time scanning mode at 25 \({}^{\circ}\)C and 10 Hz loading frequency. The loading was controlled at 12% strain with an intermittent time of 300 s. It is generally believed that fatigue damage occurs in asphalt when the complex shear modulus decreased by 50-60%, so the loading was stopped when the complex shear modulus decreased by 50% and 60%, respectively. The self-healing property of the asphalt samples was evaluated using the healing index (HI) formula (as shown in Equation (1)), which provided a quantitative assessment of the material's ability to self-repair. The comprehensive testing methods applied in this research allowed for a thorough analysis of the modified asphalt's performance under various conditions, contributing to a better understanding of its potential application in sustainable road engineering.  
\[HI=\frac{G_{h}}{G_{0}}\times\frac{t_{2}}{t_{1}} \tag{1}\]  
In the equation, \(G_{0}\) represents the initial complex shear modulus, \(G_{h}\) represents the initial complex shear modulus after the healing (intermittent) period, \(t_{1}\) represents the time required for the initial complex shear modulus to decrease by 50% (or 60%) before the healing period, and \(t_{2}\) represents the time required for the initial complex shear modulus to decrease by 50% (or 60%) after the healing period.